WO2018112437A1 - Procédé et système pour caractériser des affections liées à une allergie et associées à des micro-organismes - Google Patents

Procédé et système pour caractériser des affections liées à une allergie et associées à des micro-organismes Download PDF

Info

Publication number
WO2018112437A1
WO2018112437A1 PCT/US2017/066866 US2017066866W WO2018112437A1 WO 2018112437 A1 WO2018112437 A1 WO 2018112437A1 US 2017066866 W US2017066866 W US 2017066866W WO 2018112437 A1 WO2018112437 A1 WO 2018112437A1
Authority
WO
WIPO (PCT)
Prior art keywords
species
kegg3
genus
family
gut site
Prior art date
Application number
PCT/US2017/066866
Other languages
English (en)
Inventor
Zachary APTE
Jessica RICHMAN
Daniel Almonacid
Catalina Valdivia
Rodrigo Ortiz
Inti PEDROSA
Victoria Dumas
Paz Tapia
Eduardo Morales
Original Assignee
uBiome, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US15/606,743 external-priority patent/US10803991B2/en
Application filed by uBiome, Inc. filed Critical uBiome, Inc.
Priority to EP17881032.1A priority Critical patent/EP3775257A4/fr
Publication of WO2018112437A1 publication Critical patent/WO2018112437A1/fr

Links

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids
    • G16B30/10—Sequence alignment; Homology search
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G16B20/40—Population genetics; Linkage disequilibrium
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/20—Supervised data analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/30—Unsupervised data analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics
    • G16B50/30—Data warehousing; Computing architectures
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/40—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/70—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mental therapies, e.g. psychological therapy or autogenous training
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/63—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Definitions

  • This invention relates generally to the field of microbiology and more specifically to a new and useful method and system for characterizing and/or treating allergy-related conditions associated with microorganisms.
  • a microbiome is an ecological community of commensal, symbiotic, and pathogenic microorganisms that are associated with an organism.
  • the human microbiome includes over 10 times more microbial cells than human cells, but characterization of the human microbiome is still in nascent stages due to limitations in sample processing techniques, genetic analysis techniques, and resources for processing large amounts of data. Nonetheless, the microbiome is suspected to play at least a partial role in a number of health/disease-related states (e.g., preparation for childbirth, diabetes, auto-immune disorders, gastrointestinal disorders, rheumatoid disorders, neurological disorders, etc.).
  • FIGURES lA-iB are flowchart representations of variations of an embodiment of a method
  • FIGURE 2 depicts embodiments of a method and system
  • FIGURE 3 depicts a variation of a process for generation of a characterization model in an embodiment of a method
  • FIGURE 4 depicts variations of mechanisms by which probiotic-based therapies operate in an embodiment of a method
  • FIGURE 5 depicts variations of sample processing in an embodiment of a method
  • FIGURE 6 depicts examples of notification provision
  • FIGURE 7 depicts a schematic representation of variations of an embodiment of the method
  • FIGURES 8A-8B depicts variations of performing characterization processes with models allergy- related models.
  • FIGURE 9 depicts promoting a therapy in an embodiment of a method.
  • embodiments of a method 100 for characterizing one or more allergy-related conditions associated with microorganisms can include: generating a microbiome dataset (e.g., microorganism sequence dataset, microbiome composition diversity dataset, microbiome functional diversity dataset, etc.) for each of an aggregate set of biological samples associated with a population of subjects, based on sample processing of the biological samples S110; processing a supplementary dataset associated with (e.g., informative of; describing; indicative of; etc.) one or more allergy-related conditions for the set of users S120; and performing a characterization process for the one or more allergy-related conditions, based on the supplementary dataset and microbiome features (e.g., microbiome composition diversity features; microbiome functional diversity features; etc.) extracted from the microbiome dataset S130.
  • microbiome dataset e.g., microorganism sequence dataset, microbiome composition diversity dataset, microbiome functional diversity dataset, etc.
  • Embodiments of the method 100 can additionally or alternatively include one or more of: determining a therapy model for determining therapies for preventing, ameliorating, and/or otherwise modifying one or more allergy-related conditions S140; processing one or more biological samples associated with a user (e.g., subject, human, animal, patient, etc.) S150; determining, with the characterization process, an allergy- related characterization for the user based upon processing a microbiome dataset (e.g., user microorganism sequence dataset, microbiome composition dataset, microbiome functional diversity dataset, etc.) derived from the biological sample of the user S160; promoting a therapy for the allergy-related condition to the user (e.g., based upon the allergy-related characterization and/ or a therapy model) S170; monitoring effectiveness of the therapy for the user, based upon processing biological samples, to assess microbiome composition and/or functional features associated with the therapy for the user over time S180; and/ or any other suitable operations.
  • a therapy model for determining therapies for preventing
  • Embodiments of the method 100 and/or system 200 can function to characterize (e.g., assess, evaluate, diagnose, etc.) and/or treat users in relation to one or more allergy- related conditions, based on at least one of user microbiome composition, microbiome function, and/ or other suitable microbiome-related aspects. Additionally or alternatively, embodiments can function to determine allergy-related characterizations and/or promote associated therapies in relation to specific physiological sites (e.g., gut, healthy gut, skin, nose, mouth, genitals, other suitable physiological sites, other sample collection sites, etc.).
  • specific physiological sites e.g., gut, healthy gut, skin, nose, mouth, genitals, other suitable physiological sites, other sample collection sites, etc.
  • embodiments can function to generate models (e.g., allergy- related characterization models; therapy models; etc.) that can be used to characterize and/or diagnose subjects according to at least one of their microbiome composition and functional features (e.g., as a clinical diagnostic, as a companion diagnostic, etc.), and/or provide therapeutic measures (e.g., probiotic-based therapeutic measures, phage-based therapeutic measures, small-molecule-based therapeutic measures, clinical measures, etc.) to subjects in relation to one or more allergy-related conditions.
  • therapeutic measures e.g., probiotic-based therapeutic measures, phage-based therapeutic measures, small-molecule-based therapeutic measures, clinical measures, etc.
  • embodiments can perform any suitable functionality described herein.
  • data from a population of subjects can be used to characterize subjects according to their microbiome composition and/or functional features, indicate states of health and areas of improvement based upon the characterization(s), and promote one or more therapies that can modulate the composition of a subject's microbiome toward one or more of a set of desired equilibrium states (e.g., correlated with improved health states associated with one or more allergy-related conditions; etc.).
  • a set of desired equilibrium states e.g., correlated with improved health states associated with one or more allergy-related conditions; etc.
  • Variations of the method 100 can further facilitate monitoring and/or adjusting of therapies provided to a subject, for instance, through reception, processing, and analysis of additional samples from a subject over time (e.g., throughout the course of a therapy regimen, through the extent of a user's experiences with allergy-relation conditions; etc.), which can facilitate therapy efficacy monitoring and/or therapy adjustment, microbiome characterization and/or related therapies over time, and/or performance of any suitable portion of the method 100 (e.g., over time, etc.).
  • therapies provided to a subject, for instance, through reception, processing, and analysis of additional samples from a subject over time (e.g., throughout the course of a therapy regimen, through the extent of a user's experiences with allergy-relation conditions; etc.), which can facilitate therapy efficacy monitoring and/or therapy adjustment, microbiome characterization and/or related therapies over time, and/or performance of any suitable portion of the method 100 (e.g., over time, etc.).
  • Embodiments of the method 100 and/or system 200 can preferably generate and/or promote (e.g., provide) characterizations and/or therapies for one or more allergy-related conditions, which can include one or more of allergy-related: symptoms, causes (e.g., triggers, etc.), diseases, disorders, associated risk, associated severity, and/or any other suitable aspects associated with allergy-related conditions.
  • allergy-related conditions can include one or more of allergy-related: symptoms, causes (e.g., triggers, etc.), diseases, disorders, associated risk, associated severity, and/or any other suitable aspects associated with allergy-related conditions.
  • Allergy-related conditions preferably include one or more food-related allergy conditions, which can include any one or more: a wheat allergy, a treenut allergy (e.g., allergies associated with almonds, cashews, chestnuts, pecans, pistachios, pine nuts, walnuts, macadamia nuts, etc.), a shellfish allergy, a soy allergy, a peanut allergy, an egg allergy, a fruit allergy, a milk allergy, a garlic allergy, a corn allergy, an alpha-gal allergy, a fish allergy, a meat allergy, a spices-related allergy, chemical additive-related allergy, food coloring-related allergy, food protein-induced enterocolitis syndrome (FPIES), and/or any other suitable allergies related to food items (e.g., ingredients, natural food items, combinations of food items such as meals, etc.).
  • a wheat allergy e.g., allergies associated with almonds, cashews, chestnuts, pecans, pistachios, pine nuts, walnuts, mac
  • allergy-related conditions can include any one or more of: a drug-related allergy (e.g., antibiotic medication-related allergies; etc.), a latex allergy, a seasonal allergy, an animal allergy (e.g., pet allergy, insect -related allergy such as a insect venom allergy, etc.), a mold allergy, a dust allergy, a skin allergy, a genetic-related allergy, a stress-related allergy, a hygiene-related allergy, respiratory allergies, and/or any other suitable types of allergies.
  • Allergy-related conditions can include symptoms including one or more of: dizziness, nausea, vomiting, swelling (e.g., of tongue, throat, lips, etc.), hives, sneezing, runny nose, stuffy nose, itchiness (e.g., eye itchiness, etc.), rash, cramps (e.g., stomach cramps), diarrhea, breathing-related symptoms (e.g., difficulty breathing), throat symptoms (e.g., scratchy throat, sore throat
  • Embodiments of the method 100 and/or system 200 can be implemented for a single user for whom microbiome characterization and/or microbiome modulation with therapeutics is of interest, and/or can additionally or alternatively be implemented for a population of users (e.g., including the subject, excluding the subject), where the population of user can include other users dissimilar to and/or similar to the user (e.g., in health condition, in dietary needs, in demographic features, in behavior, in microbiome composition and/or function, etc.); for a subgroup of users (e.g., sharing characteristics, such as characteristics affecting microbiome characterization and/or therapy determination; etc.).
  • a population of users e.g., including the subject, excluding the subject
  • the population of user can include other users dissimilar to and/or similar to the user (e.g., in health condition, in dietary needs, in demographic features, in behavior, in microbiome composition and/or function, etc.); for a subgroup of users (e.g., sharing characteristics
  • information derived from a set of users can be used to provide additional insight into connections between behaviors of a subject and effects on the subject's microbiome, due to aggregation of data from the set of users.
  • an aggregate set of biological samples is preferably received from a wide variety of users, collectively including users of one or more of: different demographics (e.g., genders, ages, marital statuses, ethnicities, nationalities, socioeconomic statuses, sexual orientations, etc.), different health conditions (e.g., health and disease states; different allergy-related conditions; different genetic dispositions; etc.), different living situations (e.g., living alone, living with pets, living with a significant other, living with children, etc.), different dietary habits (e.g., omnivorous, vegetarian, vegan, sugar consumption, acid consumption, caffeine consumption, etc.), different behavioral tendencies (e.g., levels of physical activity, drug use, alcohol use, etc.), different levels of mobility (e.g., related to distance traveled within a given time period), and/or any other suitable trait associated with (e.g., has an effect on, etc.) microbiome composition and/or functional features.
  • different demographics e.g., genders, ages, marital
  • the predictive power of processes implemented in portions of the method 100 can increase, such as in relation to characterizing a variety of users based upon their microbiomes.
  • the method 100 can involve generation of characterization and therapies derived from biological sample data from any other suitable group of users.
  • Data described herein can be associated with any suitable temporal indicators (e.g., seconds, minutes, hours, days, weeks, etc.) including one or more: temporal indicators indicating when the data was collected (e.g., temporal indicators indicating when a sample was collected; etc.), determined, transmitted, received, and/or otherwise processed; temporal indicators providing context to content described by the data (e.g., temporal indicators associated with allergy-related characterizations, such as where the allergy-related characterization describes the allergy-related conditions and/or user microbiome status at a particular time; etc.); changes in temporal indicators (e.g., changes in allergy-related characterizations over time, such as in response to receiving a therapy; latency between sample collection, sample analysis, provision of an allergy-related characterization or therapy to a user, and/or other suitable portions of the method 100; etc.); and/ or any other suitable temporal indicators (e.g., seconds, minutes, hours, days, weeks, etc.) including one or more: temporal indicators indicating when the data was collected
  • parameters, metrics, inputs, outputs, and/or other suitable data can be associated with value types including: scores (e.g., microbiome diversity scores; risk scores for allergy-related conditions; severity scores for allergy- related conditions; microbiome composition diversity scores; microbiome functional diversity scores; etc.), binary values (e.g., presence or absence of a microbiome feature; presence or absence of an allergy-related condition; etc.), classifications (e.g., allergy- related condition classifications for different types of allergies; behavioral classifications; demographic classifications; etc.), confidence levels (e.g., associated with microorganism sequence datasets; with microbiome diversity scores; with other allergy-related characterizations; etc.), values along a spectrum, and/ or any other suitable types of values.
  • scores e.g., microbiome diversity scores; risk scores for allergy-related conditions; severity scores for allergy- related conditions; microbiome composition diversity scores; microbiome functional diversity scores; etc.
  • binary values e.g., presence or absence of a microbiome feature;
  • Any suitable types of data described herein can be used as inputs (e.g., for different models described herein), generated as outputs (e.g., of different models), and/or manipulated in any suitable manner for any suitable components associated with the method 100 and/or system 200.
  • One or more instances and/or portions of the method 100 and/or processes described herein can be performed asynchronously (e.g., sequentially), concurrently (e.g., multiplex sample processing, such as multiplex amplification of microorganism nucleic acid fragments corresponding to target sequences associated with allergy-related conditions; performing sample processing and analysis for substantially concurrently evaluating a panel of allergy-related conditions; computationally determining microbiome datasets, microbiome features, and/ or allergy-related conditions in parallel for a plurality of users, such as concurrently on different threads for parallel computing to improve system processing ability; etc.), in temporal relation (e.g., substantially concurrently with, in response to, serially, prior to, subsequent to, etc.) to a trigger event (e.g., performance of a portion of the method 100), and/ or in any other suitable order at any suitable time and frequency by and/or using one or more instances of the system 200, components, and/or entities described herein.
  • multiplex sample processing such as multiplex amplification
  • the method 100 can include generating a microorganism sequence dataset based on processing microorganism nucleic acids of a biological sample with a bridge amplification substrate of a next generation sequencing platform of a sample handling system, and determining microbiome composition diversity features and microbiome functional diversity features at computing devices operable to communicate with the next generation sequencing platform.
  • embodiments of the system 200 can include any one or more of: a handling system (e.g., a sample handling system, etc.) operable to collect biological samples (e.g., collected by users and included in containers including preprocessing reagents; etc.) from one or more users (e.g., a human subject, patient, animal subject, environmental ecosystem, care provider, etc.), the handling system including a sequencing platform (e.g., next-generation sequencing platform) operable to determine a microorganism sequence dataset for the one or more users from the biological samples; an allergy-related characterization system operable to: determine user microbiome features (e.g., microbiome composition features; microbiome functional features; diversity features; relative abundance ranges; etc.) based on the microorganism sequence dataset (and/or other suitable data described herein), and determine allergy-related characterizations based on the user microbiome features; and/or a treatment system operable to promote a therapy for one or more allergy-related conditions
  • a handling system e.g
  • Microbiome analysis can enable accurate and/or efficient characterization and/or therapy provision (e.g., according to portions of the method 100, etc.) for allergy-related conditions caused by and/or otherwise associated with microorganisms.
  • the technology can overcome several challenges faced by conventional approaches in characterizing a user condition and/or promoting associated therapies.
  • conventional approaches can require patients to visit one or more care providers to receive a characterization and/or a therapy recommendation for an allergy-related condition (e.g., through diagnostic medical procedures such as skin prick testing; etc.), which can amount to inefficiencies and/or health-risks associated with the amount of time elapsed before diagnosis and/or treatment, with inconsistency in healthcare quality, and/or with other aspects of care provider visitation.
  • conventional genetic sequencing and analysis technologies for human genome sequencing can be incompatible and/or inefficient when applied to the microbiome (e.g., where the human microbiome can include over 10 times more microbial cells than human cells; where optimal sample processing techniques can differ, such as for reducing amplification bias; where different approaches to allergy-related characterizations can be employed; where the types of conditions and correlations can differ; where sequence reference databases can differ; where the microbiome can vary across different body regions of the user; etc.).
  • sequencing technologies e.g., next-generation sequencing
  • technological issues e.g., data processing and analysis issues for the plethora of generated sequence data; issues with processing a plurality of biological samples in a multiplex manner; information display issues; therapy prediction issues, therapy provision issues, etc.
  • Specific examples of the method 100 and/or system 200 can confer technologically-rooted solutions to at least the challenges described above.
  • the technology can transform entities (e.g., users, biological samples, treatment systems including medical devices, etc.) into different states or things.
  • the technology can transform a biological sample into components able to be sequenced and analyzed for characterizing users in relation to allergy-related conditions (e.g., using next-generation sequencing systems; multiplex amplification operations; etc.).
  • the technology can identify therapies (e.g., personalized therapies based on a microbiome characterization; etc.) to promote to a user to modify a microbiome composition (e.g., composition diversity), microbiome function (e.g., functional diversity) and/or other microbiome-related aspects to prevent and/or ameliorate one or more allergy-related conditions, thereby transforming the microbiome and/or health of the patient (e.g., improving a health state associated with an allergy-related condition; etc.).
  • the technology can transform microbiome composition and/ or function at different physiological sites of a user, such as targeting and/ or transforming a gut, nose, skin, mouth, and/or gentials microbiome.
  • the technology can control treatment-related systems (e.g., automated medication dispensers; allergen detection systems; etc.) to promote therapies (e.g., by generating control instructions for the treatment system to execute; etc.)), thereby transforming the treatment system.
  • the technology can confer improvements in computer-related technology (e.g., modeling associated with characterizing and/or promoting therapies for allergy- related conditions; improving computational efficiency in storing, retrieving, and/or processing microorganism-related data for allergy-related conditions; computational processing associated with biological sample processing; etc.) by facilitating computer performance of functions not previously performable.
  • the technology can computationally generate allergy-related characterizations and/ or recommended therapies associated with microbiome analysis based on techniques (e.g., leveraging microorganism taxonomic databases, etc.) that are recently viable due to advances in sample processing techniques and/ or sequencing technology.
  • techniques e.g., leveraging microorganism taxonomic databases, etc.
  • the technology can confer improvements in processing speed, allergy-related characterization accuracy, microbiome-related therapy determination and promotion, and/or other suitable aspects in relation to allergy-related conditions.
  • the technology can generate and apply feature-selection rules (e.g., microbiome diversity feature-selection rules for composition, function, etc.) to select an optimized subset of features (e.g., microbiome composition diversity features such as reference relative abundance features indicative of healthy ranges of taxonomic groups associated with allergy-related conditions; user relative abundance features that can be compared to reference relative abundance features correlated with allergy-related conditions and/or therapy responses; etc.) out of a vast potential pool of features (e.g., extractable from the plethora of microbiome data such as sequence data) for generating and/or applying characterization models and/or therapy models.
  • feature-selection rules e.g., microbiome diversity feature-selection rules for composition, function, etc.
  • microbiomes e.g., human microbiomes, animal microbiomes, etc.
  • the potential size of microbiomes can translate into a plethora of data, giving rise to questions of how to process and analyze the vast array of data to generate actionable microbiome insights in relation to allergy-related conditions.
  • the feature-selection rules and/or other suitable computer-implementable rules can enable one or more of: shorter generation and execution times (e.g., for generating and/or applying models; for determining allergy-related characterizations and/or associated therapies; etc.); optimized sample processing techniques (e.g., improving transformation of microorganism nucleic acids from biological samples through using primer types, other biomolecules, and/or other sample processing components identified through computational analysis of taxonomic groups, sequences, and/or other suitable data associated with allergy-related conditions, such as while optimizing for improving specificity, reducing amplification bias, and/or other suitable parameters; etc.); model simplification facilitating efficient interpretation of results; reduction in overfitting; network effects associated with generating, storing, and applying microbiome characterizations for a plurality of users over time in relation to allergy-related conditions (e.g., through collecting and processing an increasing amount of microbiome-related data associated with an increasing number of users to improve predictive power of the allergy- related characterizations and/or therapy determinations
  • the technology can amount to an inventive distribution of functionality across a network including a sample handling system, an allergy-related characterization system, and a plurality of users, where the sample handling system can handle substantially concurrent processing of biological samples (e.g., in a multiplex manner) from the plurality of users, which can be leveraged by the allergy-related characterization system in generating personalized characterizations and/or therapies (e.g., customized to the user's microbiome such as in relation to the user's dietary behavior, probiotics- associated behavior, medical history, demographics, other behaviors, preferences, etc.) for allergy-related conditions.
  • personalized characterizations and/or therapies e.g., customized to the user's microbiome such as in relation to the user's dietary behavior, probiotics- associated behavior, medical history, demographics, other behaviors, preferences, etc.
  • the technology can improve the technical fields of at least microbiome-related digital medicine, digital medicine generally, genetic sequencing, modeling (e.g., of allergy- related conditions associated with microbiomes; etc.) and/or other relevant fields.
  • the technology can leverage specialized computing devices (e.g., devices associated with the sample handling system, such as next -generation sequencing platforms; allergy-related characterization systems; treatment systems; etc.) in determining and processing microbiome datasets in relation to allergy-related characterization and/or therapy provision.
  • the technology can, however, provide any other suitable benefit(s) in the context of using non-generalized computer systems for allergy-related characterization, microbiome modulation, and/or for performing other suitable portions of the method 100.
  • 3.1 Generating a microbiome dataset e.g., a microbiome dataset.
  • Block Siio recites: generating a microbiome dataset (e.g., microorganism sequence dataset, microbiome composition diversity dataset, microbiome functional diversity dataset, etc.) for each of an aggregate set of biological samples associated with a population of users (e.g., subjects), based on sample processing of the biological samples.
  • Block Siio functions to process each of an aggregate set of biological samples (e.g., associated with a population of subjects, a subpopulation of subjects, a subgroup of subjects sharing a demographic characteristic and/or other suitable characteristics, etc.), in order to determine compositional, functional, pharmacogenomics, and/or other suitable aspects associated with the microbiomes of the users, such as in relation to one or more allergy- related conditions.
  • Compositional and/or functional aspects can include one or more of aspects at the microorganism level, including parameters related to distribution of microorganisms across different groups of kingdoms, phyla, classes, orders, families, genera, species, subspecies, strains, and/or any other suitable infraspecies taxon (e.g., as measured in total abundance of each group, relative abundance of each group, total number of groups represented, etc.).
  • Compositional and/or functional aspects can also be represented in terms of operational taxonomic units (OTUs).
  • compositional and/or functional aspects can additionally or alternatively include compositional aspects at the genetic level (e.g., regions determined by multilocus sequence typing, i6S sequences, i8S sequences, ITS sequences, other genetic markers, other phylogenetic markers, etc.).
  • compositional and functional aspects can include the presence or absence or the quantity of genes associated with specific functions (e.g. enzyme activities, transport functions, immune activities, etc.).
  • Outputs of Block Siio can thus be used to provide features of interest for the characterization process of Block S130 and/or other suitable portions of the method 100 (e.g., where Block S110 can lead to outputs of microbiome composition datasets, microbiome functional datasets, and/or other suitable microbiome datasets from which microbiome features can be extracted, etc.), where the features can be microorganism-based (e.g., presence of a genus of bacteria), genetic-based (e.g., based upon representation of specific genetic regions and/or sequences) and/or functional -based (e.g., presence of a specific catalytic activity).
  • microorganism-based e.g., presence of a genus of bacteria
  • genetic-based e.g., based upon representation of specific genetic regions and/or sequences
  • functional -based e.g., presence of a specific catalytic activity
  • Block Sno can include assessment and/ or processing based upon phylogenetic markers derived from bacteria and/or archaea in relation to gene families associated with one or more of: ribosomal protein S2, ribosomal protein S3, ribosomal protein S5, ribosomal protein S7, ribosomal protein S8, ribosomal protein S9, ribosomal protein S10, ribosomal protein S11, ribosomal protein S12/S23, ribosomal protein S13, ribosomal protein Si5P/Si3e, ribosomal protein S17, ribosomal protein S19, ribosomal protein Li, ribosomal protein L2, ribosomal protein L3, ribosomal protein L4/Lie, ribosomal protein L5, ribosomal protein L6, ribosomal protein L10, ribosomal protein L11, ribosomal protein Li4b/L23e,
  • markers can include target sequences (e.g., sequences associated with a microorganism taxonomic group; sequences associated with functional aspects; sequences correlated with allergy-related conditions; sequences indicative of user responsiveness to different therapies; sequences that are invariant across a population and/or any suitable set of subjects, such as to facilitate multiplex amplification using a primer type sharing a primer sequence; conserved sequences; sequences including mutations, polymorphisms; nucleotide sequences; amino acid sequences; etc.), proteins (e.g., serum proteins, antibodies, etc.), peptides, carbohydrates, lipids, other nucleic acids, whole cells, metabolites, natural products, genetic predisposition biomarkers, diagnostic biomarkers, prognostic biomarkers, predictive biomarkers, other molecular biomarkers, gene expression markers, imaging biomarkers, and/or other suitable markers.
  • markers can include any other suitable marker(s) associated with microbiome composition, microbiome functionality, and/or allergy
  • Characterizing the microbiome composition and/or functional aspects for each of the aggregate set of biological samples thus preferably includes a combination of sample processing techniques (e.g., wet laboratory techniques), including, but not limited to, amplicon sequencing (e.g., 16S, 18S, ITS), unique molecule identifiers (UMIs), 3 step PCR, CRISPR, metagenomic approaches, metatranscriptomics, use of random primers, and computational techniques (e.g., utilizing tools of bioinformatics) to quantitatively and/or qualitatively characterize the microbiome and functional aspects associated with each biological sample from a subject or population of subjects.
  • sample processing techniques e.g., wet laboratory techniques
  • amplicon sequencing e.g., 16S, 18S, ITS
  • UMIs unique molecule identifiers
  • 3 step PCR e.g., CRISPR, metagenomic approaches, metatranscriptomics, use of random primers
  • computational techniques e.g., utilizing tools of bioinformatic
  • sample processing in Block Sno can include any one or more of: lysing a biological sample, disrupting membranes in cells of a biological sample, separation of undesired elements (e.g., RNA, proteins) from the biological sample, purification of nucleic acids (e.g., DNA) in a biological sample, amplification of nucleic acids from the biological sample, further purification of amplified nucleic acids of the biological sample, and sequencing of amplified nucleic acids of the biological sample.
  • undesired elements e.g., RNA, proteins
  • Block Sno can include: collecting biological samples from a set of users (e.g., biological samples collected by the user with a sampling kit including a sample container, etc.), where the biological samples include microorganism nucleic acids associated with the allergy-related condition (e.g., microorganism nucleic acids including target sequences correlated with an allergy-related condition; etc.).
  • Block Sno can include providing a set of sampling kits to a set of users, each sampling kit of the set of sampling kits including a sample container (e.g., including pre-processing reagents, such as lysing reagents; etc.) operable to receive a biological sample from a user of the set of users.
  • lysing a biological sample and/or disrupting membranes in cells of a biological sample preferably includes physical methods (e.g., bead beating, nitrogen decompression, homogenization, sonication), which omit certain reagents that produce bias in representation of certain bacterial groups upon sequencing.
  • lysing or disrupting in Block Sno can involve chemical methods (e.g., using a detergent, using a solvent, using a surfactant, etc.).
  • lysing or disrupting in Block Sno can involve biological methods.
  • separation of undesired elements can include removal of RNA using RNases and/ or removal of proteins using proteases.
  • purification of nucleic acids can include one or more of: precipitation of nucleic acids from the biological samples (e.g., using alcohol-based precipitation methods), liquid-liquid based purification techniques (e.g., phenol- chloroform extraction), chromatography-based purification techniques (e.g., column adsorption), purification techniques involving use of binding moiety-bound particles (e.g., magnetic beads, buoyant beads, beads with size distributions, ultrasonically responsive beads, etc.) configured to bind nucleic acids and configured to release nucleic acids in the presence of an elution environment (e.g., having an elution solution, providing a pH shift, providing a temperature shift, etc.), and any other suitable purification techniques.
  • solvent-based precipitation methods e.g., liquid-liquid based purification techniques (e.g., phenol- chloroform extraction), chromatography-based purification techniques (e.g., column adsorption), purification techniques involving use of binding moiety-bound particles
  • amplification of purified nucleic acids can include one or more of: polymerase chain reaction (PCR)-based techniques (e.g., solid-phase PCR, RT-PCR, qPCR, multiplex PCR, touchdown PCR, nanoPCR, nested PCR, hot start PCR, etc.), helicase- dependent amplification (HDA), loop mediated isothermal amplification (LAMP), self- sustained sequence replication (3SR), nucleic acid sequence based amplification (NASBA), strand displacement amplification (SDA), rolling circle amplification (RCA), ligase chain reaction (LCR), and any other suitable amplification technique.
  • PCR polymerase chain reaction
  • HDA helicase- dependent amplification
  • LAMP loop mediated isothermal amplification
  • NASBA nucleic acid sequence based amplification
  • SDA strand displacement amplification
  • RCA rolling circle amplification
  • LCR ligase chain reaction
  • the primers used are preferably selected to prevent or minimize amplification bias, as well as configured to amplify nucleic acid regions/sequences (e.g., of the 16S region, the 18S region, the ITS region, etc.) that are informative taxonomically, phylogenetically, for diagnostics, for formulations (e.g., for probiotic formulations), and/or for any other suitable purpose.
  • amplification bias e.g., a F27-R338 primer set for 16S RNA, a F515-R806 primer set for 16S RNA, etc.
  • Block S110 can additionally or alternatively include adaptor regions configured to cooperate with sequencing techniques involving complementary adaptors (e.g., Illumina Sequencing). Additionally or alternatively, Block S110 can implement any other step configured to facilitate processing (e.g., using a Nextera kit).
  • performing amplification and/or sample processing operations can be in a multiplex manner (e.g., for a single biological sample, for a plurality of biological samples across multiple users; etc.).
  • performing amplification can include normalization steps to balance libraries and detect all amplicons in a mixture independent of the amount of starting material, such as 3 step PCR, bead based normalization, etc.
  • sequencing of purified nucleic acids can include methods involving targeted amplicon sequencing, metatranscriptomic sequencing and/or metagenomic sequencing, implementing techniques including one or more of: sequencing -by-synthesis techniques (e.g., Illumina sequencing), capillary sequencing techniques (e.g., Sanger sequencing), pyrosequencing techniques, and nanopore sequencing techniques (e.g., using an Oxford Nanopore technique).
  • sequencing -by-synthesis techniques e.g., Illumina sequencing
  • capillary sequencing techniques e.g., Sanger sequencing
  • pyrosequencing techniques e.g., using an Oxford Nanopore technique
  • amplification and sequencing of nucleic acids from biological samples of the set of biological samples includes: solid-phase PCR involving bridge amplification of DNA fragments of the biological samples on a substrate with oligo adapters, where amplification involves primers having a forward index sequence (e.g., corresponding to an Illumina forward index for MiSeq/NextSeq/HiSeq platforms), a forward barcode sequence, a transposase sequence (e.g., corresponding to a transposase binding site for MiSeq/NextSeq/HiSeq platforms), a linker (e.g., a zero, one, or two-base fragment configured to reduce homogeneity and improve sequence results), an additional random base, UMIs, a sequence for targeting a specific target region (e.g., i6S region, i8S region, ITS region), a reverse index sequence (e.g., corresponding to an Illumina reverse index for MiSeq/HiSeq platforms), a forward index
  • sequencing can include Illumina sequencing (e.g., with a HiSeq platform, with a MiSeq platform, with a NextSeq platform, etc.) using a sequencing -by-synthesis technique.
  • the method 100 can include identifying a primer type compatible with a genetic target associated with an allergy-related condition; fragmenting microorganism nucleic acids from a biological sample; performing multiplex amplification with the fragmented microorganism nucleic acids based on the fragmented microorganism nucleic acids and the identified primer type; and/or generating the microorganism sequence dataset based on the amplified microorganism nucleic acids.
  • primers used in Block Sno and/or other suitable portions of the method 100 can include primers associated with protein genes (e.g., coding for conserved protein gene sequences across a plurality of taxa, such as to enable multiplex amplification for a plurality of targets and/or taxa; etc.).
  • Primers can additionally or alternatively be associated with allergy- related conditions (e.g., primers compatible with genetic targets including microorganism sequence biomarkers for microorganisms correlated with allergy-related conditions; etc.), microbiome composition features (e.g., identified primers compatible with a genetic target corresponding to microbiome composition features associated with a group of taxa correlated with an allergy-related condition; genetic sequences from which relative abundance features are derived etc.), functional diversity features, supplementary features, and/or other suitable features and/or data.
  • Primers and/or other suitable molecules, markers, and/or biological material described herein
  • can possess any suitable size e.g., sequence length, number of base pairs, conserved sequence length, variable region length, etc.).
  • any suitable number of primers can be used in sample processing for performing characterizations (e.g., allergy-related characterizations; etc.), improving sample processing (e.g., through reducing amplification bias, etc.), and/or for any suitable purposes.
  • the primers can be associated with any suitable number of targets, sequences, taxa, conditions, and/or other suitable aspects.
  • Primers used in Block Sno and/or other suitable portions of the method 100 can be selected through processes described in Block Sno (e.g., primer selection based on parameters used in generating the taxonomic database) and/or any other suitable portions of the method 100.
  • Block Sno can include: identifying a primer type for a microorganism nucleic acid sequence associated with the allergy-related condition (e.g., a primer type for a primer operable to amplify microorganism nucleic acid sequences correlated with an allergy- related condition; etc.); and generating the microorganism sequence dataset based on the primer type and the microorganism nucleic acids (e.g., using primers of the primer type for amplification of microorganism nucleic acids; and sequencing the amplified nucleic acids to generate the microorganism sequence dataset; etc.).
  • a primer type for a microorganism nucleic acid sequence associated with the allergy-related condition e.g., a primer type for a primer operable to amplify microorganism nucleic acid sequences correlated with an allergy- related condition; etc.
  • generating the microorganism sequence dataset based on the primer type and the microorganism nucleic acids (e.g., using primers of the
  • Block Sno can include: fragmenting the microorganism nucleic acids; and performing multiplex amplification with the fragmented microorganism nucleic acids based on the fragmented microorganism nucleic acids and the identified primer type associated with the allergy- related condition.
  • primers and/or processes associated with primers
  • primers can include and/or be analogous to that described in U.S. App. No. 14/919,614, filed 21-OCT-2015, which is herein incorporated in its entirety by this reference.
  • identification and/or usage of primers can be configured in any suitable manner.
  • sample processing can include further purification of amplified nucleic acids (e.g., PCR products) prior to sequencing, which functions to remove excess amplification elements (e.g., primers, dNTPs, enzymes, salts, etc.).
  • additional purification can be facilitated using any one or more of: purification kits, buffers, alcohols, pH indicators, chaotropic salts, nucleic acid binding filters, centrifugation, and/or any other suitable purification technique.
  • computational processing in Block Sno can include any one or more of: identification of microbiome-derived sequences (e.g., as opposed to subject sequences and contaminants), alignment and mapping of microbiome-derived sequences (e.g., alignment of fragmented sequences using one or more of single-ended alignment, ungapped alignment, gapped alignment, pairing), and generating features derived from compositional and/or functional aspects of the microbiome associated with a biological sample.
  • Identification of microbiome-derived sequences can include mapping of sequence data from sample processing to a subject reference genome (e.g., provided by the Genome Reference Consortium), in order to remove subject genome-derived sequences. Unidentified sequences remaining after mapping of sequence data to the subject reference genome can then be further clustered into operational taxonomic units (OTUs) based upon sequence similarity and/or reference-based approaches (e.g., using VAMPS, using MG- RAST, using QIIME databases), aligned (e.g., using a genome hashing approach, using a Needleman-Wunsch algorithm, using a Smith-Waterman algorithm), and mapped to reference bacterial genomes (e.g., provided by the National Center for Biotechnology Information), using an alignment algorithm (e.g., Basic Local Alignment Search Tool, FPGA accelerated alignment tool, BWT-indexing with BWA, BWT-indexing with SOAP, BWT-indexing with Bowtie, etc.).
  • OTUs operational taxono
  • Mapping of unidentified sequences can additionally or alternatively include mapping to reference archaeal genomes, viral genomes and/or eukaryotic genomes. Furthermore, mapping of taxons can be performed in relation to existing databases, and/or in relation to custom-generated databases.
  • generating features derived from compositional and functional aspects of the microbiome associated with a biological sample can be performed.
  • generating features can include generating features based upon multilocus sequence typing (MSLT), in order to identify markers useful for characterization in subsequent blocks of the method 100.
  • generated features can include generating features that describe the presence or absence of certain taxonomic groups of microorganisms, and/or ratios between exhibited taxonomic groups of microorganisms.
  • generating features can include generating features describing one or more of: quantities of represented taxonomic groups, networks of represented taxonomic groups, correlations in representation of different taxonomic groups, interactions between different taxonomic groups, products produced by different taxonomic groups, interactions between products produced by different taxonomic groups, ratios between dead and alive microorganisms (e.g., for different represented taxonomic groups, based upon analysis of RNAs), phylogenetic distance (e.g., in terms of Kantorovich- Rubinstein distances, Wasserstein distances etc.), any other suitable taxonomic group-related feature(s), any other suitable genetic or functional aspect(s).
  • generating the allergy-related characterization can be baesd on a set of user microbiome features associated with at least one of: presence of a microbiome feature from a set of microbiome features, absence of a microbiome feature from a set of microbiome features, relative abundance of different taxonomic groups associated with the allergy-related condition, a ratio between at least two microbiome features associated with the different taxonomic groups, interactions between the different taxonomic groups, and phylogenetic distance between the different taxonomic groups.
  • generating features can include generating features describing relative abundance of different microorganism groups, for instance, using a sparCC approach, using Genome Relative Abundance and Average size (GAAS) approach and/or using a Genome Relative Abundance using Mixture Model theory (GRAMMy) approach that uses sequence-similarity data to perform a maximum likelihood estimation of the relative abundance of one or more groups of microorganisms.
  • generating features can include generating statistical measures of taxonomic variation, as derived from abundance metrics.
  • generating features can include generating features derived from relative abundance factors (e.g., in relation to changes in abundance of a taxon, which affects abundance of other taxons).
  • generating features can include generation of qualitative features describing presence of one or more taxonomic groups, in isolation and/or in combination. Additionally or alternatively, generating features can include generation of features related to genetic markers (e.g., representative 16S, 18S, and/or ITS sequences) characterizing microorganisms of the microbiome associated with a biological sample. Additionally or alternatively, generating features can include generation of features related to functional associations of specific genes and/or organisms having the specific genes. Additionally or alternatively, generating features can include generation of features related to pathogenicity of a taxon and/or products attributed to a taxon. Block S120 can, however, include generation of any other suitable feature(s) derived from sequencing and mapping of nucleic acids of a biological sample.
  • genetic markers e.g., representative 16S, 18S, and/or ITS sequences
  • the feature(s) can be combinatory (e.g. involving pairs, triplets), correlative (e.g., related to correlations between different features), and/or related to changes in features (e.g., temporal changes, changes across sample sites, etc., spatial changes, etc.).
  • processing biological samples, generating a microbiome dataset, and/ or other aspects associated with Block S110 can be performed in any suitable manner.
  • Block S120 recites: processing (e.g., receiving, collecting, transforming, etc.) a supplementary dataset associated with (e.g., informative of; describing; indicative of; etc.) one or more allergy-related conditions for the set of users.
  • Block S120 can function to acquire data associated with one or more subjects of the set of subjects, which can be used to train, validate, apply, and/or otherwise inform the allergy-related characterization process (e.g., in Block S130).
  • the supplementary dataset preferably includes survey-derived data, but can additionally or alternatively include any one or more of: contextual data derived from sensors, medical data (e.g., current and historical medical data; medical device-derived data; data associated with medical tests; etc.), and any other suitable type of data.
  • the survey-derived data preferably provides physiological, demographic, and behavioral information in association with a subject.
  • Physiological information can include information related to physiological features (e.g., height, weight, body mass index, body fat percent, body hair level, etc.).
  • Demographic information can include information related to demographic features (e.g., gender, age, ethnicity, marital status, number of siblings, socioeconomic status, sexual orientation, etc.).
  • Behavioral information can include information related to one or more of: health conditions (e.g., health and disease states), living situations (e.g., living alone, living with pets, living with a significant other, living with children, etc.), dietary habits (e.g., omnivorous, vegetarian, vegan, sugar consumption, acid consumption, consumption of wheat, egg, soy, treenut, peanut, shellfish, and/or other suitable allergy-related foods, etc.), behavioral tendencies (e.g., levels of physical activity, drug use, alcohol use, etc.), different levels of mobility (e.g., related to distance traveled within a given time period), different levels of sexual activity (e.g., related to numbers of partners and sexual orientation), and any other suitable behavioral information.
  • Survey-derived data can include quantitative data and/or qualitative data that can be converted to quantitative data (e.g., using scales of severity, mapping of qualitative responses to quantified scores, etc.).
  • Block S130 can include providing one or more surveys to a subject of the population of subjects, or to an entity associated with a subject of the population of subjects.
  • Surveys can be provided in person (e.g., in coordination with sample provision and reception from a subject), electronically (e.g., during account setup by a subject, at an application executing at an electronic device of a subject, at a web application accessible through an internet connection, etc.), and/or in any other suitable manner.
  • Block S130 can include receiving one or more of: physical activity- or physical action-related data (e.g., accelerometer and gyroscope data from a mobile device or wearable electronic device of a subject), environmental data (e.g., temperature data, elevation data, climate data, light parameter data, etc.), patient nutrition or diet-related data (e.g., data from food establishment check-ins, data from spectrophotometric analysis, user-inputted data, nutrition data associated with probiotic and/or prebiotic food items, types of food consumed, amount of food consumed, diets, etc.), biometric data (e.g., data recorded through sensors within the patient's mobile computing device, data recorded through a wearable or other peripheral device in communication with the patient's mobile computing device), location data (e.g.
  • physical activity- or physical action-related data e.g., accelerometer and gyroscope data from a mobile device or wearable electronic device of a subject
  • environmental data e.g., temperature data, elevation data, climate data
  • sensor data can include data sampled at one or more: optical sensors (e.g., image sensors, light sensors, etc.), audio sensors, temperature sensors, volatile compound sensors, weight sensors, humidity sensors, depth sensors, location sensors (GPS receivers; etc.), inertial sensors (e.g., accelerators, gyroscope, magnetometer, etc.), biometric sensors (e.g., heart rate sensors, fingerprint sensors, bio-impedance sensors, etc.), pressure sensors, flow sensors, power sensors (e.g., Hall effect sensors), and/or or any other suitable sensor.
  • optical sensors e.g., image sensors, light sensors, etc.
  • audio sensors e.g., image sensors, light sensors, etc.
  • temperature sensors e.g., volatile compound sensors
  • weight sensors e.g., weight sensors, humidity sensors, depth sensors, location sensors (GPS receivers; etc.
  • inertial sensors e.g., accelerators, gyroscope, magnetometer, etc.
  • biometric sensors e.g.,
  • portions of the supplementary dataset can be derived from medical record data and/or clinical data of the subject(s).
  • portions of the supplementary dataset can be derived from one or more electronic health records (EHRs) of the subject(s).
  • EHRs electronic health records
  • the supplementary dataset of Block S120 can include any other suitable diagnostic information (e.g., clinical diagnosis information), which can be combined with analyses derived from features to support characterization of subjects in subsequent blocks of the method 100.
  • diagnostic information e.g., clinical diagnosis information
  • information derived from a colonoscopy, biopsy, blood test, diagnostic imaging, survey-related information, and any other suitable test can be used to supplement.
  • the supplementary dataset can include therapy-related data including one or more of: therapy regimens, types of therapies, recommended therapies, therapies used by the user, therapy adherence, etc.
  • the supplementary dataset can include user adherence (e.g., medication adherence, probiotic adherence, physical exercise adherence, dietary adherence, etc.) to a recommended therapy.
  • user adherence e.g., medication adherence, probiotic adherence, physical exercise adherence, dietary adherence, etc.
  • processing supplementary datasets can be performed in any suitable manner.
  • Block S130 recites: performing a characterization process for the one or more allergy-related conditions, based on the supplementary dataset and/or microbiome features (e.g., microbiome composition diversity features; microbiome functional diversity features; etc.) extracted from the microbiome dataset.
  • Block S130 can function to identify, extract, and/or otherwise process features and/or feature combinations that can be used to characterize subjects or groups based upon their microbiome composition features, functional features, and/or other suitable microbiome features (e.g., such as through the generation and application of a characterization model for determining allergy-related characterizations, etc.).
  • the characterization process can be used as a diagnostic tool that can characterize a subject (e.g., in terms of behavioral traits, in terms of medical conditions, in terms of demographic traits, etc.) based upon their microbiome composition and/ or functional features, in relation to one or more of their health condition states (e.g., allergy-related condition states), behavioral traits, medical conditions, demographic traits, and/or any other suitable traits. Such characterization can then be used to suggest or provide personalized therapies by way of the therapy model of Block S140.
  • a subject e.g., in terms of behavioral traits, in terms of medical conditions, in terms of demographic traits, etc.
  • health condition states e.g., allergy-related condition states
  • behavioral traits e.g., medical conditions, demographic traits, and/or any other suitable traits.
  • Block S130 can use computational methods (e.g., statistical methods, machine learning methods, artificial intelligence methods, bioinformatics methods, etc.) to characterize a subject as exhibiting features characteristic of a group of subjects with a health condition.
  • computational methods e.g., statistical methods, machine learning methods, artificial intelligence methods, bioinformatics methods, etc.
  • characterization can be based upon features derived from a statistical analysis (e.g., an analysis of probability distributions) of similarities and/or differences between a first group of subjects exhibiting a target state (e.g., a health condition state) and a second group of subjects not exhibiting the target state (e.g., a "normal" state).
  • a target state e.g., a health condition state
  • a second group of subjects not exhibiting the target state e.g., a "normal” state.
  • KS Kolmogorov-Smirnov
  • permutation test e.g., a permutation test
  • Cramer-von Mises test e.g., t- test, z-test, chi-squared test, test associated with distributions, etc.
  • one or more such statistical hypothesis tests can be used to assess a set of features having varying degrees of abundance in a first group of subjects exhibiting a target state (e.g., a sick state) and a second group of subjects not exhibiting the target state (e.g., having a normal state).
  • the set of features assessed can be constrained based upon percent abundance and/ or any other suitable parameter pertaining to diversity in association with the first group of subjects and the second group of subjects, in order to increase or decrease confidence in the characterization.
  • a feature can be derived from a taxon of bacteria that is abundant in a certain percentage of subjects of the first group and subjects of the second group, where a relative abundance of the taxon between the first group of subjects and the second group of subjects can be determined from the KS test, with an indication of significance (e.g., in terms of p-value).
  • an output of Block S130 can include a normalized relative abundance value (e.g., 25% greater abundance of a taxon in subjects with an allergy-related condition vs. subjects without the allergy-related condition; in sick subjects vs. healthy subjects) with an indication of significance (e.g., a p-value of 0.0013).
  • Variations of feature generation can additionally or alternatively implement or be derived from functional features or metadata features (e.g., non-bacterial markers). Additionally or alternatively, any suitable microbiome features can be derived based on statistical analyses (e.g., applied to a microorganism sequence dataset and/or other suitable microbiome dataset, etc.) including any one or more of: a prediction analysis, multi hypothesis testing, a random forest test, and principal component analysis.
  • Block S130 can additionally or alternatively transform input data from at least one of the microbiome composition diversity dataset and microbiome functional diversity dataset into feature vectors that can be tested for efficacy in predicting characterizations of the population of subjects.
  • Data from the supplementary dataset can be used to provide indication of one or more characterizations of a set of characterizations, where the characterization process is trained with a training dataset of candidate features and candidate classifications to identify features and/ or feature combinations that have high degrees (or low degrees) of predictive power in accurately predicting a classification.
  • refinement of the characterization process with the training dataset identifies feature sets (e.g., of subject features, of combinations of features) having high correlation with specific classifications of subjects.
  • feature vectors (and/or any suitable set of features) effective in predicting classifications of the characterization process can include features related to one or more of: microbiome diversity metrics (e.g., in relation to distribution across taxonomic groups, in relation to distribution across archaeal, bacterial, viral, and/or eukaryotic groups), presence of taxonomic groups in one's microbiome, representation of specific genetic sequences (e.g., 16S sequences) in one's microbiome, relative abundance of taxonomic groups in one's microbiome, microbiome resilience metrics (e.g., in response to a perturbation determined from the supplementary dataset), abundance of genes that encode proteins or RNAs with given functions (enzymes, transporters, proteins from the immune system, hormones, interference RNAs, etc.) and any other suitable features derived from the microbiome diversity dataset and/or the supplementary dataset.
  • microbiome diversity metrics e.g., in relation to distribution across taxonomic groups, in relation to distribution across archae
  • microbiome features can be associated with (e.g., include, correspond to, typify, etc.) at least one of: presence of a microbiome feature from the microbiome features, absence of the microbiome features from the microbiome features, relative abundance of different taxonomic groups associated with the allergy-related condition; a ratio between at least two microbiome features associated with the different taxonomic groups, interactions between the different taxonomic groups, and phylogenetic distance between the different taxonomic groups.
  • microbiome features can include one or more relative abundance characteristics associated with at least one of the microbiome composition diversity features (e.g., relative abundance associated with different taxa, etc.) and the microbiome functional diversity features (e.g., relative abundance of sequences corresponding to different functional features; etc.).
  • Relative abundance characteristics and/or other suitable microbiome features can be extracted and/or otherwise determined based on: a normalization, a feature vector derived from at least one of linear latent variable analysis and non-linear latent variable analysis, linear regression, non-linear regression, a kernel method, a feature embedding method, a machine learning method, and a statistical inference method.
  • combinations of features can be used in a feature vector, where features can be grouped and/ or weighted in providing a combined feature as part of a feature set.
  • one feature or feature set can include a weighted composite of the number of represented classes of bacteria in one's microbiome, presence of a specific genus of bacteria in one's microbiome, representation of a specific 16S sequence in one's microbiome, and relative abundance of a first phylum over a second phylum of bacteria.
  • the feature vectors can additionally or alternatively be determined in any other suitable manner.
  • the characterization process can be generated and trained according to a random forest predictor (RFP) algorithm that combines bagging (e.g., bootstrap aggregation) and selection of random sets of features from a training dataset to construct a set of decision trees, T, associated with the random sets of features.
  • RFP random forest predictor
  • N cases from the set of decision trees are sampled at random with replacement to create a subset of decision trees, and for each node, m prediction features are selected from all of the prediction features for assessment.
  • the prediction feature that provides the best split at the node (e.g., according to an objective function) is used to perform the split (e.g., as a bifurcation at the node, as a trifurcation at the node).
  • the strength of the characterization process, in identifying features that are strong in predicting classifications can be increased substantially.
  • measures to prevent bias e.g., sampling bias
  • account for an amount of bias can be included during processing to increase robustness of the model.
  • Block S130 e.g., extracting microbiome features; generating characterization models for allergy-related conditions; etc.
  • other suitable portions of the method 100 can employ data processing approaches including any one or more of: performing pattern recognition on data (e.g., identifying correlations between allergy-related conditions and microbiome features; etc.), fusing data from multiple sources (e.g., generating characterization models based on microbiome data and/ or supplementary data from a plurality of users associated with one or more allergy- related conditions; etc.), combination of values (e.g., averaging values, etc.), compression, conversion (e.g., digital-to-analog conversion, analog-to-digital conversion), performing statistical estimation on data (e.g.
  • Block S130 and/or other portions of the method 100 can include applying computer-implemented rules (e.g., models, feature selection rules, etc.) to process population-level data, but can additionally or alternatively include applying computer- implemented rules to process microbiome-related data on a demographic-specific basis (e.g., subgroups sharing a demographic feature such as allergy-relation conditions therapy regiments, dietary regiments, physical activity regiments, ethnicity, age, gender, weight, sleeping behaviors, etc.), condition-specific basis (e.g., subgroups exhibiting a specific allergy-related condition, a combination of allergy-related conditions, triggers for the allergy-related conditions, associated symptoms, etc.), a sample type-specific basis (e.g., applying different computer-implemented rules to process microbiome data derived from different collection sites; etc.), a user basis (e.g., different computer-implemented rules for different users; etc.) and/or any other suitable basis.
  • a demographic-specific basis e.g., sub
  • Block S132 can include assigning users from the population of users to one or more subgroups; and applying different computer-implemented rules for determining features (e.g., the set of feature types used; the types of characterization models generated from the features; etc.) for the different subgroups.
  • features e.g., the set of feature types used; the types of characterization models generated from the features; etc.
  • applying computer-implemented rules can be performed in any suitable manner.
  • Block S130 can include processing (e.g., generating, training, updating, executing, storing, etc.) one or more characterization models (e.g., allergy- related condition characterization models, etc.) for one or more allergy-related conditions.
  • characterization models e.g., allergy- related condition characterization models, etc.
  • the characterization models preferably leverage microbiome features as inputs, and preferably output allergy-related characterizations and/or any suitable components thereof; but characterization models can use and suitable inputs to generate any suitable outputs.
  • Block S130 can include transforming the supplementary data, the microbiome composition diversity features, and the microbiome functional diversity features into a characterization model (e.g., training an allergy-related characterization model based on the supplementary data and microbiome features; etc.) for the allergy- related condition.
  • a characterization model e.g., training an allergy-related characterization model based on the supplementary data and microbiome features; etc.
  • the method 100 can include: determining a population microorganism sequence dataset (e.g., including microorganism sequence outputs for different users of the population; etc.) for a population of users associated with one or more allergy-related conditions, based on a set of samples from the population of users (e.g., and/or based on one or more primer types associated with the allergy-related condition; etc.); collecting a supplementary dataset associated with diagnosis of the one or more allergy-related conditions for the population of subjects; and generating the allergy- related condition characterization model based on the population microorganism sequence dataset and the supplementary dataset.
  • a population microorganism sequence dataset e.g., including microorganism sequence outputs for different users of the population; etc.
  • different allergy-related characterization models and/or other suitable models can be generated for different demographic groups (e.g., a first characterization model for users on a dietary regimen including food items associated with the allergy-related condition, and a second characterization model for users on a dietary regimen not including the food items; different models based on physical activity level; different models based on age, gender, weight, height, ethnicity; etc.), different physiological sites (e.g., a gut site model, a nose site model, a skin site model, a mouth site model, a genitals site model, etc.) allergy-related conditions (e.g., different characterization models for users with different allergy-related conditions; etc.), individual users, supplementary data (e.g., models incorporating features
  • determining allergy-related characterizations and/or any other suitable characterizations for conditions associated with microorganisms can include determining allergy-related characterizations in relation to specific physiological sites (e.g., gut, healthy gut, skin, nose, mouth, genitals, other suitable physiological sites, other sample collection sites, etc.), such as through any one or more of: determining an allergy- related characterization based on an allergy-related characterization model derived based on site-specific data (e.g., defining correlations between an allergy-related condition and microbiome features associated with one or more physiological sites); determining an allergy-related characterization based on a user biological sample collected at one or more physiological sites, and/or any other suitable site-related processes.
  • specific physiological sites e.g., gut, healthy gut, skin, nose, mouth, genitals, other suitable physiological sites, other sample collection sites, etc.
  • site-specific data e.g., defining correlations between an allergy-related condition and microbiome features associated with one or more physiological sites
  • machine learning approaches e.g., classifiers, deep learning algorithms
  • statistical tests e.g., dimension reduction approaches, and/or other suitable approaches (e.g., described herein) can be applied in determining site-related (e.g., physiological site-related, etc.) characterizations, other suitable characterizations, therapies, and/or any other suitable outputs.
  • the method 100 can include determining any suitable site-related (e.g., site-specific) outputs, and/or performing any suitable portions of the method 100 (e.g., collecting samples, processing samples, determining therapies) with site-specificity and/or other site-relatedness in any suitable manner.
  • Characterization of the subject(s) can additionally or alternatively implement use of a high false positive test and/or a high false negative test to further analyze sensitivity of the characterization process in supporting analyses generated according to embodiments of the method 100.
  • performing a characterization process S130 can be performed in any suitable manner.
  • Block S130 can include performing a wheat allergy condition characterization process (e.g., determining and/or applying a wheat allergy characterization model; etc.) for one or more users.
  • a characterization process e.g., of Block S130; based upon statistical analyses and/or other suitable approaches described herein; etc.
  • can identify a set of microbiome features e.g., microbiome composition features, microbiome function features, etc.
  • correlations e.g., positive correlations, negative correlations, correlations of greatest magnitude, etc.
  • performing a wheat allergy condition characterization process can facilitate identifications of one or more therapies operable to have a positive effect on the wheat allergy condition (e.g., based upon a random forest predictor algorithm trained with a training dataset derived from a subset of the population of subjects, and validated with a validation dataset derived from a subset of the population of subjects).
  • a wheat allergy condition can include an immune disorder of the subject characterized by an abnormal reaction of the immune system of the subject to any suitable proteins present in wheat, and where the wheat allergy condition can be associated with diagnosis through laboratory analysis (e.g., skin-prick test, blood-samples tests, IgE tests, etc.) and/ or other suitable diagnostic procedures.
  • Performing a wheat allergy condition characterization process can be based on microbiome features (e.g., microbiome composition features) associated with (e.g., derived from, informative of, correlated with, etc.) one or more (e.g.
  • Blautia luti (species), Collinsella aerofaciens (species), Flavonifractor plautii (species), Faecalibacterium prausnitzii (species), Dorea formicigenerans (species), Subdoligranulum variabile (species), Barnesiella intestinihominis (species), Bacteroides thetaiotaomicron (species), Roseburia inulinivorans (species), Parasutterella excrementihominis (species), Bifidobacterium longum (species), Erysipelatoclostridium ramosum (species), Bacteroides fragilis (species), Bacteroides vulgatus (species), Bacteroides caccae (species), Blautia sp.
  • YHC-4 (species), Alistipes putredinis (species), Bifidobacterium (genus), Subdoligranulum (genus), Collinsella (genus), Dorea (genus), Sarcina (genus), Moryella (genus), Intestinibacter (genus), Faecalibacterium (genus), Oscillospira (genus), Terrisporobacter (genus), Bacteroides (genus), Anaerotruncus (genus), Marvinbryantia (genus), Barnesiella (genus), Eggerthella (genus), Parabacteroides (genus), Dialister (genus), Roseburia (genus), Akkermansia (genus), Sutterella (genus), Bifidobacteriaceae (family), Ruminococcaceae (family), Coriobacteriaceae (family), Oscillospiraceae (family), Clostridiaceae (family), Bacteroidaceae (family), P
  • microbiome features can be associated with one or more of the following taxons in relation to a sample site (e.g., wheat allergy condition correlations with microorganisms observed at a particular sample site Abiotrophia (genus) (e.g., nose site); Abiotrophia defectiva (species) (e.g., nose site); Acetanaerobacterium (genus) (e.g., gut site); Acetitomaculum (genus) (e.g., gut site); Acetobacteraceae (family) (e.g., skin site); Acholeplasmatales (order) (e.g., gut site); Acidaminococcaceae (family) (e.g., gut site); Acidaminococcus (genus) (e.g., gut site); Acidaminococcus intestini (species) (e.g., gut site); Acidaminococcus sp.
  • Abiotrophia e.g., nose site
  • Abiotrophia defectiva
  • D21 (species) (e.g., gut site); Acidobacteria (phylum) (e.g., nose site); Acidobacteria (phylum) (e.g., skin site); Acidobacteriia (class) (e.g., nose site); Acidobacteriia (class) (e.g., skin site); Acinetobacter (genus) (e.g., nose site); Actinobacillus (genus) (e.g., gut site); Actinobacillus porcinus (species) (e.g., gut site); Actinobacteria (class) (e.g., gut site); Actinobacteria (phylum) (e.g., gut site); Actinomyces (genus) (e.g., nose site); Actinomyces (genus) (e.g., genital site); Actinomyces europaeus (species) (e.g., genital site); Actinomyces neuii (spec
  • ICM41 (species) (e.g., mouth site); Actinomyces sp. ZSY-i (species) (e.g., mouth site); Actinomycetaceae (family) (e.g., nose site); Actinomycetales (order) (e.g., gut site); Adlercreutzia (genus) (e.g., gut site); Adlercreutzia equolifaciens (species) (e.g., gut site); Aerococcaceae (family) (e.g., nose site); Aerococcaceae (family) (e.g., skin site); Aerococcus (genus) (e.g., gut site); Aerococcus christensenii (species) (e.g., gut site); Aggregatibacter (genus) (e.g., nose site); Aggregatibacter aphrophilus (species) (e.g., nose site); Akkermansia (genus) (e.
  • EBA6-25CI2 (species) (e.g., gut site); Alistipes sp. HGB5 (species) (e.g., gut site); Alistipes sp. RMA 9912 (species) (e.g., gut site); Alloprevotella (genus) (e.g., mouth site); Alloprevotella (genus) (e.g., skin site); Alphaproteobacteria (class) (e.g., nose site); Alphaproteobacteria (class) (e.g., gut site); Anaerobacter (genus) (e.g., gut site); Anaerococcus (genus) (e.g., gut site); Anaerococcus (genus) (e.g., mouth site); Anaerococcus sp.
  • 8404299 (species) (e.g., gut site); Anaerococcus sp. 9402080 (species) (e.g., gut site); Anaerofilum (genus) (e.g., gut site); Anaerosporobacter (genus) (e.g., gut site); Anaerosporobacter mobilis (species) (e.g., gut site); Anaerostipes (genus) (e.g., nose site); Anaerostipes hadrus (species) (e.g., gut site); Anaerostipes sp. 3_2_56FAA (species) (e.g., gut site); Anaerostipes sp.
  • NML 070203 (species) (e.g., gut site); Anaerovorax (genus) (e.g., gut site); Asaccharospora (genus) (e.g., gut site); Asaccharospora irregularis (species) (e.g., gut site); Atopobium (genus) (e.g., genital site); Bacillaceae (family) (e.g., gut site); Bacillaceae (family) (e.g., nose site); Bacillales (order) (e.g., gut site); Bacillus (genus) (e.g., gut site); Bacillus (genus) (e.g., nose site); Bacteroidaceae (family) (e.g., gut site); Bacteroidaceae (family) (e.g., genital site); Bacteroidales (order) (e.g., gut site); Bacteroidales (order) (e.g., skin site); Bactero
  • AR20 (species) (e.g., gut site); Bacteroides sp. AR20 (species) (e.g., genital site); Bacteroides sp. AR29 (species) (e.g., gut site); Bacteroides sp. D22 (species) (e.g., gut site); Bacteroides sp. DJF_Bo97 (species) (e.g., gut site); Bacteroides sp. EBA5-17 (species) (e.g., gut site); Bacteroides sp. S-17 (species) (e.g., gut site); Bacteroides sp.
  • SLCi-38 (species) (e.g., gut site); Bacteroides sp. XB12B (species) (e.g., gut site); Bacteroides stercoris (species) (e.g., gut site); Bacteroides thetaiotaomicron (species) (e.g., gut site); Bacteroides uniformis (species) (e.g., gut site); Bacteroides vulgatus (species) (e.g., nose site); Bacteroides vulgatus (species) (e.g., genital site); Bacteroides vulgatus (species) (e.g., gut site); Bacteroidetes (phylum) (e.g., gut site); Bacteroidia (class) (e.g., gut site); Bacteroidia (class) (e.g., skin site); Barnesiella (genus) (e.g., gut site); Barnesiella intestinihominis (species
  • kits (species) (e.g., gut site); Bifidobacterium stercoris (species) (e.g., gut site); Bilophila (genus) (e.g., gut site); Bilophila sp. 4_i_30 (species) (e.g., gut site); Blautia (genus) (e.g., nose site); Blautia (genus) (e.g., gut site); Blautia glucerasea (species) (e.g., gut site); Blautia hydrogenotrophica (species) (e.g., gut site); Blautia luti (species) (e.g., gut site); Blautia producta (species) (e.g., gut site); Blautia sp.
  • Ser5 (species) (e.g., gut site); Blautia sp. Ser8 (species) (e.g., gut site); Blautia sp. YHC-4 (species) (e.g., gut site); Blautia stercoris (species) (e.g., gut site); Blautia wexlerae (species) (e.g., gut site); Brevundimonas (genus) (e.g., nose site); Burkholderiaceae (family) (e.g., nose site); Burkholderiales (order) (e.g., genital site); Burkholderiales (order) (e.g., gut site); Butyricimonas (genus) (e.g., gut site); Butyrivibrio crossotus (species) (e.g., gut site); Caldicoprobacteraceae (family) (e.g., gut site); Candidatus Soleaferrea (gen
  • CM59 (species) (e.g., nose site); Capnocytophaga sp. oral taxon 329 (species) (e.g., nose site); Capnocytophaga spumblea (species) (e.g., nose site); Cardiobacteriaceae (family) (e.g., mouth site); Cardiobacterium (genus) (e.g., mouth site); Cardiobacterium hominis (species) (e.g., mouth site); Carnobacteriaceae (family) (e.g., gut site); Carnobacteriaceae (family) (e.g., mouth site); Carnobacteriaceae (family) (e.g., skin site); Catabacter (genus) (e.g., gut site); Catabacteriaceae (family) (e.g., gut site); Catenibacterium mitsuokai (species) (e.g., gut site); Caulobacteraceae (family) (e.g
  • Incertae Sedis family (e.g., gut site); Clostridiales (family) XIII. Incertae Sedis (family) (e.g., gut site); Collinsella (genus) (e.g., gut site); Collinsella aerofaciens (species) (e.g., gut site); Collinsella intestinalis (species) (e.g., gut site); Comamonadaceae (family) (e.g., gut site); Comamonas (genus) (e.g., mouth site); Coprobacillus (genus) (e.g., gut site); Coprobacillus sp.
  • D6 (species) (e.g., gut site); Coriobacteriaceae (family) (e.g., gut site); Coriobacteriales (order) (e.g., gut site); Corynebacteriaceae (family) (e.g., gut site); Corynebacterium (genus) (e.g., gut site); Corynebacterium canis (species) (e.g., gut site); Corynebacterium epidermidicanis (species) (e.g., gut site); Corynebacterium grisburgense (species) (e.g., gut site); Corynebacterium glucuronolyticum (species) (e.g., gut site); Corynebacterium glucuronolyticum (species) (e.g., genital site); Corynebacterium mastitidis (species) (e.g., genital site); Corynebacterium sp.
  • Family
  • NML 97-0186 (species) (e.g., nose site); Corynebacterium spheniscorum (species) (e.g., gut site); Corynebacterium ulcerans (species) (e.g., gut site); Corynebacterium ulcerans (species) (e.g., genital site); Corynebacterium ulcerans (species) (e.g., skin site); Cronobacter (genus) (e.g., gut site); Cyanobacteria (phylum) (e.g., nose site); Cyanobacteria (phylum) (e.g., gut site); Deinococci (class) (e.g., nose site); Delftia (genus) (e.g., skin site); Delftia sp.
  • genera e.g., nose site
  • Corynebacterium spheniscorum e.g., gut site
  • Corynebacterium ulcerans e.g
  • BN-SKY3 (species) (e.g., skin site); Deltaproteobacteria (class) (e.g., gut site); Dermabacteraceae (family) (e.g., nose site); Dermabacteraceae (family) (e.g., gut site); Desulfovibrio piger (species) (e.g., gut site); Desulfovibrio sp.
  • mice site e.g., gut site
  • Desulfovibrionaceae (family) e.g., gut site
  • Desulfovibrionales order
  • gut site Dialister (genus) (e.g., gut site); Dialister (genus) (e.g., skin site); Dialister invisus (species) (e.g., gut site); Dialister propionicifaciens (species) (e.g., gut site); Dielma (genus) (e.g., gut site); Dielma fastidiosa (species) (e.g., gut site); Dorea (genus) (e.g., gut site); Dorea formicigenerans (species) (e.g., gut site); Dorea longicatena (species) (e.g., gut site); Eggerthella (genus) (e.g., gut site); Eggerthella sinensis (species) (e.g., gut),
  • HGAi (species) (e.g., gut site); Eisenbergiella (genus) (e.g., gut site); Eisenbergiella tayi (species) (e.g., gut site); Enterobacter (genus) (e.g., gut site); Enterobacter sp.
  • BS2-1 (species) (e.g., gut site); Enterobacteriaceae (family) (e.g., gut site); Enterobacteriales (order) (e.g., gut site); Enterococcaceae (family) (e.g., gut site); Enterococcus (genus) (e.g., gut site); Enterococcus faecalis (species) (e.g., gut site); Enterococcus raffinosus (species) (e.g., gut site); Enterococcus sp. C6I11 (species) (e.g., gut site); Enterococcus sp.
  • SI-4 (species) (e.g., gut site); Erysipelatoclostridium (genus) (e.g., gut site); Erysipelatoclostridium ramosum (species) (e.g., gut site); Erysipelotrichaceae (family) (e.g., gut site); Erysipelotrichales (order) (e.g., gut site); Erysipelotrichia (class) (e.g., gut site); Eubacteriaceae (family) (e.g., gut site); Eubacterium (genus) (e.g., gut site); Eubacterium callanderi (species) (e.g., gut site); Eubacterium sp.
  • SA11 (species) (e.g., gut site); Euryarchaeota (phylum) (e.g., gut site); Faecalibacterium (genus) (e.g., gut site); Faecalibacterium (genus) (e.g., mouth site); Faecalibacterium prausnitzii (species) (e.g., gut site); Faecalibacterium sp.
  • canine oral taxon 147 canine oral taxon 147 (species) (e.g., gut site); Fibrobacter (genus) (e.g., gut site); Fibrobacteraceae (family) (e.g., gut site); Fibrobacterales (order) (e.g., gut site); Fibrobacteres (phylum) (e.g., gut site); Fibrobacteria (class) (e.g., gut site); Finegoldia (genus) (e.g., gut site); Finegoldia (genus) (e.g., genital site); Finegoldia (genus) (e.g., mouth site); Finegoldia (genus) (e.g., skin site); Finegoldia sp.
  • S8 F7 (species) (e.g., gut site); Finegoldia sp. S8 F7 (species) (e.g., genital site); Finegoldia sp. S9 AA1-5 (species) (e.g., gut site); Finegoldia sp. S9 AA1-5 (species) (e.g., mouth site); Finegoldia sp.
  • S9 AA1-5 (species) (e.g., skin site); Firmicutes (phylum) (e.g., gut site); Flavobacteriaceae (family) (e.g., gut site); Flavobacteriales (order) (e.g., skin site); Flavobacteriales (order) (e.g., gut site); Flavobacteriia (class) (e.g., gut site); Flavobacterium (genus) (e.g., nose site); Flavonifractor (genus) (e.g., gut site); Flavonifractor plautii (species) (e.g., gut site); Fusicatenibacter (genus) (e.g., gut site); Fusicatenibacter saccharivorans (species) (e.g., gut site); Fusobacteriaceae (family) (e.g., nose site); Fusobacterium (genus) (e.g., nose site); Fusobacteriace
  • CM21 (species) (e.g., nose site); Gammaproteobacteria (class) (e.g., gut site); Gammaproteobacteria (class) (e.g., genital site); Gelria (genus) (e.g., gut site); Gemella (genus) (e.g., mouth site); Gemella (genus) (e.g., gut site); Gemella (genus) (e.g., skin site); Gemella sanguinis (species) (e.g., mouth site); Gemella sp. 933-88 (species) (e.g., gut site); Gemella sp.
  • SOR89 (species) (e.g., gut site); Kluyvera (genus) (e.g., gut site); Kluyvera (genus) (e.g., mouth site); Kluyvera georgiana (species) (e.g., gut site); Kluyvera georgiana (species) (e.g., mouth site); Kocuria (genus) (e.g., nose site); Lachnospira (genus) (e.g., skin site); Lachnospira (genus) (e.g., gut site); Lachnospira pectinoschiza (species) (e.g., gut site); Lachnospiraceae (family) (e.g., nose site); Lachnospiraceae (family) (e.g., genital site); Lactobacillaceae (family) (e.g., gut site); Lactobacillaceae (family) (e.g., genital site); Lactobacillales (order
  • 7_i_47FAA (species) (e.g., skin site); Lactobacillus sp. 7_i_47FAA (species) (e.g., gut site); Lactobacillus sp. 7_i_47FAA (species) (e.g., nose site); Lactobacillus sp. Akhmroi (species) (e.g., gut site); Lactobacillus sp. TAB-26 (species) (e.g., gut site); Lactobacillus sp.
  • TAB-30 (species) (e.g., gut site); Lactonifactor (genus) (e.g., gut site); Lactonifactor longoviformis (species) (e.g., gut site); Lautropia (genus) (e.g., nose site); Lautropia sp.
  • TeTO TeTO (species) (e.g., nose site); Leptotrichia hongkongensis (species) (e.g., mouth site); Leuconostocaceae (family) (e.g., gut site); Marvinbryantia (genus) (e.g., gut site); Megasphaera (genus) (e.g., gut site); Methanobacteria (class) (e.g., gut site); Methanobacteriaceae (family) (e.g., gut site); Methanobacteriales (order) (e.g., gut site); Methanobrevibacter (genus) (e.g., gut site); Methanobrevibacter smithii (species) (e.g., gut site); Methylobacteriaceae (family) (e.g., nose site); Methylobacterium (genus) (e.g., nose site); Microbacteriaceae (family) (e.g., gut site);
  • WB18-01 (species) (e.g., nose site); Mollicutes (class) (e.g., gut site); Moraxella (genus) (e.g., nose site); Moraxella sp. WB19-16 (species) (e.g., nose site); Moraxellaceae (family) (e.g., skin site); Moryella (genus) (e.g., gut site); Murdochiella (genus) (e.g., gut site); Murdochiella asaccharolytica (species) (e.g., gut site); Mycobacteriaceae (family) (e.g., mouth site); Mycobacterium (genus) (e.g., nose site); Negativicutes (class) (e.g., gut site); Neisseria (genus) (e.g., skin site); Neisseria (genus) (e.g., gut site); Neisseria elongata (species) (e.g., nose
  • MFCi (species) (e.g., gut site); Peptoclostridium (genus) (e.g., gut site); Peptococcaceae (family) (e.g., gut site); Peptococcus (genus) (e.g., gut site); Peptoniphilus (genus) (e.g., gut site); Peptoniphilus (genus) (e.g., skin site); Peptoniphilus lacrimalis (species) (e.g., gut site); Peptoniphilus sp. 2002-2300004 (species) (e.g., skin site); Peptoniphilus sp. 7-2 (species) (e.g., gut site); Peptoniphilus sp.
  • DNF00840 (species) (e.g., gut site); Peptoniphilus sp. gpacoi8A (species) (e.g., gut site); Peptoniphilus sp. oral taxon 836 (species) (e.g., gut site); Peptostreptococcaceae (family) (e.g., gut site); Peptostreptococcaceae (family) (e.g., skin site); Peptostreptococcus (genus) (e.g., mouth site); Phascolarctobacterium (genus) (e.g., gut site); Phascolarctobacterium faecium (species) (e.g., gut site); Porphyromonadaceae (family) (e.g., gut site); Porphyromonas (genus) (e.g., nose site); Porphyromonas bennonis (species) (e.g., genital site); Porphyrom
  • WAL 2039G (species) (e.g., nose site); Prevotellaceae (family) (e.g., gut site); Propionibacteriaceae (family) (e.g., mouth site); Propionibacteriaceae (family) (e.g., genital site); Propionibacterium (genus) (e.g., mouth site); Propionibacterium acnes (species) (e.g., nose site); Propionibacterium sp.
  • MSP09A (species) (e.g., genital site); Proteobacteria (phylum) (e.g., gut site); Proteus (genus) (e.g., gut site); Pseudobutyrivibrio (genus) (e.g., nose site); Pseudoclavibacter (genus) (e.g., gut site); Pseudoflavonifractor (genus) (e.g., gut site); Pseudoflavonifractor capillosus (species) (e.g., gut site); Pseudomonadaceae (family) (e.g., nose site); Pseudomonadales (order) (e.g., skin site); Pseudomonadales (order) (e.g., genital site); Pseudomonadales (order) (e.g., gut site); Pseudomonas (genus)
  • 11SE39 (species) (e.g., gut site); Roseburia sp. 499 (species) (e.g., gut site); Rothia (genus) (e.g., gut site); Rothia dentocariosa (species) (e.g., nose site); Rothia mucilaginosa (species) (e.g., gut site); Ruminococcaceae (family) (e.g., gut site); Sarcina (genus) (e.g., nose site); Sarcina (genus) (e.g., gut site); Selenomonadales (order) (e.g., gut site); Senegalimassilia (genus) (e.g., gut site); Shinella (genus) (e.g., skin site); Shinella sp.
  • DR33 (species) (e.g., skin site); Shuttleworthia (genus) (e.g., gut site); Slackia piriformis (species) (e.g., gut site); Slackia sp. NATTS (species) (e.g., gut site); Solanales (order) (e.g., nose site); Solanales (order) (e.g., gut site); Sphingomonadaceae (family) (e.g., nose site); Sphingomonadales (order) (e.g., nose site); Sphingomonas (genus) (e.g., nose site); Staphylococcus sp.
  • C-D-MA2 (species) (e.g., skin site); Staphylococcus sp. C9I2 (species) (e.g., genital site); Stenotrophomonas sp. C-S-TSA3 (species) (e.g., skin site); Streptococcaceae (family) (e.g., mouth site); Streptococcaceae (family) (e.g., gut site); Streptococcus (genus) (e.g., mouth site); Streptococcus (genus) (e.g., gut site); Streptococcus gordonii (species) (e.g., nose site); Streptococcus mitis (species) (e.g., mouth site); Streptococcus pasteurianus (species) (e.g., gut site); Streptococcus peroris (species) (e.g., gut site); Streptococcus s
  • BS35a (species) (e.g., mouth site); Streptococcus sp. oral taxon G59 (species) (e.g., gut site); Streptococcus sp. oral taxon G63 (species) (e.g., mouth site); Streptococcus thermophilus (species) (e.g., gut site); Streptococcus thermophilus (species) (e.g., skin site); Streptophyta (phylum) (e.g., gut site); Subdoligranulum (genus) (e.g., gut site); Subdoligranulum variabile (species) (e.g., gut site); Sutterella (genus) (e.g., gut site); Sutterella sp.
  • YIT 12072 (species) (e.g., gut site); Sutterella wadsworthensis (species) (e.g., gut site); Sutterellaceae (family) (e.g., nose site); Sutterellaceae (family) (e.g., gut site); Synergistaceae (family) (e.g., gut site); Synergistales (order) (e.g., gut site); Synergistetes (phylum) (e.g., gut site); Synergistia (class) (e.g., gut site); Tenericutes (phylum) (e.g., gut site); Terrisporobacter (genus) (e.g., gut site); Tessaracoccus (genus) (e.g., mouth site); Tessaracoccus sp.
  • IPBSL-7 (species) (e.g., mouth site); Thalassospira (genus) (e.g., gut site); Thermoanaerobacteraceae (family) (e.g., gut site); Thermoanaerobacterales (order) (e.g., gut site); Varibaculum sp. CCUG 45114 (species) (e.g., gut site); Veillonella (genus) (e.g., mouth site); Veillonella (genus) (e.g., gut site); Veillonella rogosae (species) (e.g., gut site); Veillonella sp. CM60 (species) (e.g., mouth site); Veillonella sp.
  • CM60 (species) (e.g., gut site); Veillonella sp. FFA-2014 (species) (e.g., gut site); Veillonella sp. MSA12 (species) (e.g., gut site); Veillonellaceae (family) (e.g., gut site); Verrucomicrobia (phylum) (e.g., gut site); Verrucomicrobiaceae (family) (e.g., gut site); Verrucomicrobiae (class) (e.g., gut site); Verrucomicrobiales (order) (e.g., gut site); Weissella (genus) (e.g., gut site); Weissella hellenica (species) (e.g., gut site); Xanthomonadaceae (family) (e.g., gut site); Xanthomonadales (order) (e.g., gut site); Xanthomonadales (order) (e.g., genital site).
  • performing a wheat allergy condition characterization process can be based on microbiome features (e.g., microbiome function features) associated with one or more of (e.g., such as in relation to a corresponding sample site): Metabolism (KEGG2), Carbohydrate Metabolism (KEGG2), Translation (KEGG2), Transport and Catabolism (KEGG2), Enzyme Families (KEGG2), Biosynthesis of Other Secondary Metabolites (KEGG2), Cellular Processes and Signaling (KEGG2), Nucleotide Metabolism (KEGG2), Replication and Repair (KEGG2), Glycan Biosynthesis and Metabolism (KEGG2), Genetic Information Processing (KEGG2), Lipid Metabolism (KEGG2), Signal Transduction (KEGG2), Neurodegenerative Diseases (KEGG2), Metabolism of Other Amino Acids (KEGG2), Metabolism of Cofactors and Vitamins (KEGG2), Signaling Molecules and Interaction (KEGG2), Environmental
  • microbiome features e.
  • KEGG_Pathways_Level_3) e.g., gut site
  • Immune System Diseases KEGG_Pathways_Level_2
  • Infectious Diseases KEGG_Pathways_Level_2)
  • Inorganic ion transport and metabolism KEGG_Pathways_Level_3)
  • Inositol phosphate metabolism KEGG_Pathways_Level_3)
  • Ion channels KEGG_Pathways_Level_3) (e.g., gut site
  • Isoquinoline alkaloid biosynthesis KEGG_Pathways_Level_3)
  • Limonene and pinene degradation KEGG_Pathways_Level_3) (e.g., gut site)
  • Linoleic acid metabolism KEGG_Pathways_Level_3) (e.g., gut site); Lipid biosynthesis proteins (KEGG_Pathways_Level_3) (e.g., gut site); Lipid biosynthesis proteins (KEGG_P
  • Nervous System (KEGG_ .Pathways. .Level. -3) (e.g., mouth site); Nervous System
  • KEGG_ .Pathways. .Level. _2 e.g., gut site
  • KEGG_ .Pathways. .Level. .3) e.g., gut site
  • Others KEGG_Pathways_Level_3) (e.g., gut site); Oxidative phosphorylation (KEGG_Pathways_Level_3) (e.g., gut site); p53 signaling pathway (KEGG_Pathways_Level_3) (e.g., gut site); Penicillin and cephalosporin biosynthesis (KEGG_Pathways_Level_3) (e.g., genital site); Penicillin and cephalosporin biosynthesis (KEGG_Pathways_Level_3) (e.g., gut site); Pentose and glucuronate interconversions (KEGG_Pathways_Level_3) (e.g., gut site); Pentose phosphate pathway (KEGG_Pathways_Level_3) (e.g., gut site); Peptidoglycan biosynthesis (KEGG_Pathways_Level_3)
  • Determining an allergy-related characterization of a user can include diagnosing a user with a wheat allergy condition based upon one or more of the above microbiome features and/or other suitable features described herein, such as in an additional or alterative manner to typical methods of diagnosis.
  • features used in the wheat allergy characterization process can include any other suitable features (e.g., features useful for diagnostics), and performing the wheat allergy characterization process can be performed in any suitable manner.
  • 3.3.B Treenut allergy condition characterization process can include any other suitable features (e.g., features useful for diagnostics), and performing the wheat allergy characterization process can be performed in any suitable manner.
  • Block S130 can include performing a treenut allergy condition characterization process (e.g., determining and/or applying a treenut allergy characterization model; etc.) for one or more users.
  • a characterization process e.g., of Block S130; based upon statistical analyses and/or other suitable approaches described herein; etc.
  • can identify a set of microbiome features e.g., microbiome composition features, microbiome function features, etc.
  • correlations e.g., positive correlations, negative correlations, correlations of greatest magnitude, etc.
  • performing a treenut allergy condition characterization process can facilitate identifications of one or more therapies operable to have a positive effect on the treenut allergy condition (e.g., based upon a random forest predictor algorithm trained with a training dataset derived from a subset of the population of subjects, and validated with a validation dataset derived from a subset of the population of subjects).
  • a treenut allergy condition can include an immune disorder of the subject characterized by hypersensitivity to dietary substances from treenut and/or edible tree seeds causing an overreaction of the immune system, which may lead to severe physical symptoms, where diagnosis can be associated to laboratory analysis (e.g., skin-prick test, blood-samples analysis, IgE tests, etc.) and/or other suitable diagnostic procedures.
  • Performing a treenut allergy condition characterization process can be based on microbiome features (e.g., microbiome composition features) associated with (e.g., derived from, informative of, correlated with, etc.) one or more: Blautia luti (Species), Collinsella aerofaciens (Species), Parabacteroides distasonis (Species), Flavonifr actor plautii (Species), Bacteroides fragilis (Species), Dorea formicigenerans (Species), Roseburia inulinivorans (Species), Clostridium (Genus), Marvinbryantia (Genus), Dorea (Genus), Eggerthella (Genus), Terrisporobacter (Genus), Sarcina (Genus), Bacteroides (Genus), Barnesiella (Genus), Oscillospiraceae (Family), Clostridiaceae (Family), Bacteroidaceae (Family),
  • microbiome features e.g., microbio
  • microbiome features can be associated with one or more of the following taxons in relation to a sample site (e.g., treenut allergy condition correlations with microorganisms observed at a particular sample site): Acetitomaculum (genus) (e.g., gut site); Acidaminococcaceae (family) (e.g., gut site); Actinomyces (genus) (e.g., nose site); Actinomyces (genus) (e.g., gut site); Actinomyces sp.
  • Acetitomaculum e.g., gut site
  • Acidaminococcaceae family
  • Actinomyces e.g., nose site
  • Actinomyces e.g., gut site
  • Actinomyces sp Actinomyces sp.
  • ICM54 (species) (e.g., nose site); Actinomycetaceae (family) (e.g., nose site); Actinomycetaceae (family) (e.g., gut site); Adlercreutzia (genus) (e.g., gut site); Adlercreutzia equolifaciens (species) (e.g., gut site); Aerococcaceae (family) (e.g., nose site); Akkermansia (genus) (e.g., gut site); Akkermansia muciniphila (species) (e.g., gut site); Alistipes putredinis (species) (e.g., gut site); Alistipes sp.
  • RMA 9912 (species) (e.g., gut site); Alphaproteobacteria (class) (e.g., mouth site); Alphaproteobacteria (class) (e.g., gut site); Anaerostipes (genus) (e.g., gut site); Anaerostipes sp. 3_2_56FAA (species) (e.g., gut site); Anaerostipes sp.
  • 5_i_63FAA (species) (e.g., gut site); Anaerotruncus colihominis (species) (e.g., gut site); Bacteroidaceae (family) (e.g., gut site); Bacteroidales (order) (e.g., gut site); Bacteroides (genus) (e.g., gut site); Bacteroides clarus (species) (e.g., gut site); Bacteroides fragilis (species) (e.g., gut site); Bacteroides massiliensis (species) (e.g., gut site); Bacteroides sp. AR20 (species) (e.g., gut site); Bacteroides sp.
  • AR29 (species) (e.g., gut site); Bacteroides sp. D22 (species) (e.g., gut site); Bacteroides sp. SLCi-38 (species) (e.g., gut site); Bacteroides thetaiotaomicron (species) (e.g., gut site); Bacteroidetes (phylum) (e.g., gut site); Bacteroidia (class) (e.g., gut site); Barnesiella (genus) (e.g., gut site); Barnesiella intestinihominis (species) (e.g., gut site); Bifidobacterium choerinum (species) (e.g., gut site); Bilophila (genus) (e.g., gut site); Bilophila sp.
  • Bacteroides sp. D22 e.g., gut site
  • Bacteroides sp. SLCi-38 (species) (e.g.
  • 4_i_30 (species) (e.g., gut site); Blautia (genus) (e.g., gut site); Blautia luti (species) (e.g., gut site); Blautia sp. Ser8 (species) (e.g., gut site); Blautia sp.
  • YHC-4 (species) (e.g., gut site); Blautia wexlerae (species) (e.g., gut site); Butyricicoccus (genus) (e.g., gut site); Campylobacter (genus) (e.g., gut site); Campylobacteraceae (family) (e.g., gut site); Campylobacterales (order) (e.g., gut site); Cardiobacteriaceae (family) (e.g., nose site); Cardiobacteriales (order) (e.g., nose site); Cardiobacterium (genus) (e.g., nose site); Clostridia (class) (e.g., gut site); Clostridiaceae (family) (e.g., gut site); Clostridiales (order) (e.g., gut site); Clostridium (genus) (e.g., gut site); Collinsella (genus) (e.g., gut site); Collinsella aero
  • HGAi (species) (e.g., gut site); Eisenbergiella (genus) (e.g., gut site); Eisenbergiella tayi (species) (e.g., gut site); Enterobacter (genus) (e.g., gut site); Enterobacter sp.
  • BS2-1 (species) (e.g., gut site); Enterococcus raffinosus (species) (e.g., gut site); Epsilonproteobacteria (class) (e.g., gut site); Erysipelatoclostridium ramosum (species) (e.g., gut site); Erysipelotrichales (order) (e.g., gut site); Faecalibacterium (genus) (e.g., gut site); Faecalibacterium prausnitzii (species) (e.g., gut site); Finegoldia (genus) (e.g., skin site); Finegoldia sp.
  • S9 AA1-5 (species) (e.g., skin site); Firmicutes (phylum) (e.g., gut site); Flavobacteriaceae (family) (e.g., gut site); Flavobacteriales (order) (e.g., gut site); Flavobacteriia (class) (e.g., gut site); Flavobacterium (genus) (e.g., gut site); Flavonifractor plautii (species) (e.g., gut site); Fusicatenibacter (genus) (e.g., gut site); Fusicatenibacter saccharivorans (species) (e.g., gut site); Fusobacteria (phylum) (e.g., nose site); Fusobacteria (phylum) (e.g., gut site); Fusobacteriaceae (family) (e.g., nose site); Fusobacteriales (order) (e.g., nose site); Fusobacterial
  • 377 (species) (e.g., gut site); Prevotella maculosa (species) (e.g., mouth site); Rhodospirillaceae (family) (e.g., gut site); Rhodospirillales (order) (e.g., skin site); Rhodospirillales (order) (e.g., gut site); Robinsoniella (genus) (e.g., gut site); Roseburia (genus) (e.g., gut site); Roseburia inulinivorans (species) (e.g., gut site); Roseburia sp.
  • 11SE39 (species) (e.g., gut site); Rothia (genus) (e.g., nose site); Rothia dentocariosa (species) (e.g., nose site); Ruminococcaceae (family) (e.g., gut site); Sarcina (genus) (e.g., gut site); Selenomonadales (order) (e.g., gut site); Streptococcus sp.
  • oral taxon G59 (species) (e.g., nose site); Subdoligranulum (genus) (e.g., gut site); Subdoligranulum variabile (species) (e.g., gut site); Terrisporobacter (genus) (e.g., gut site); Thalassospira (genus) (e.g., gut site); Veillonella (genus) (e.g., nose site); Verrucomicrobia (phylum) (e.g., gut site); Verrucomicrobiaceae (family) (e.g., gut site); Verrucomicrobiae (class) (e.g., gut site); Verrucomicrobiales (order) (e.g., gut site).
  • performing a treenut allergy condition characterization process can be based on microbiome features (e.g., microbiome function features) associated with one or more of (e.g., such as in relation to a corresponding sample site): Transport and Catabolism (KEGG2), Glycan Biosynthesis and Metabolism (KEGG2), Biosynthesis of Other Secondary Metabolites (KEGG2), Glycosaminoglycan degradation (KEGG3), Lipoic acid metabolism (KEGG3), Lysosome (KEGG3), Inorganic ion transport and metabolism (KEGG3), Cell motility and secretion (KEGG3), Glycosphingolipid biosynthesis - ganglio series (KEGG3), Glycosphingolipid biosynthesis - globo series (KEGG3), Lipopolysaccharide biosynthesis proteins (KEGG3), Ribosome Biogenesis (KEGG3), Other glycan degradation (KEGG3), Phosphatidylinositol
  • microbiome features e
  • microbiome features can be associated with one or more of the following in relation to a sample site (e.g., treenut allergy condition correlations with microorganism-related function observed at a particular sample site): Metabolism (KEGG_Pathways_Level_2) (e.g., gut site); Signaling Molecules and Interaction (KEGG_Pathways_Level_2) (e.g., gut site); Glycan Biosynthesis and Metabolism (KEGG_Pathways_Level_2) (e.g., gut site); Translation (KEGG_Pathways_Level_2) (e.g., gut site); Transport and Catabolism (KEGG_Pathways_Level_2) (e.g., gut site); Cellular Processes and Signaling (KEGG_Pathways_Level_2) (e.g., gut site); Peptidoglycan biosynthesis (KEGG_Pathways_Level_3) (e.g.,
  • KEGG_Pathways_Level_3) e.g., gut site
  • RNA degradation e.g., gut site
  • Glycosyltransferases e.g., gut site
  • Others e.g., gut site
  • Phosphatidylinositol signaling system e.g., gut site
  • Pores ion channels e.g., gut site
  • Biosynthesis and biodegradation of secondary metabolites KEGG_Pathways_Level_3) (e.g., gut site); Phosphonate and phosphinate metabolism (KEGG_Pathways_Level_3) (e.g., gut site); Dioxin degradation (KEGG_Pathways_Level_3) (e.g., gut site); Benzoate
  • microbiome features can be associated with one or more of the following in relation to a healthy gut sample site (and/or other suitable sites and/or healthiness levels): Biosynthesis of Other Secondary Metabolites (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Excretory System (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Membrane Transport (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Infectious Diseases (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Cell Motility (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Metabolism (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Signaling Molecules
  • KEGG_Pathways_Level_2) (e.g., gut site); Metabolism of Other Amino Acids (e.g. KEGG_Pathways_Level_2) (e.g., gut site); Poorly Characterized (e.g. KEGG_Pathways_Level_2) (e.g., gut site); Lipid Metabolism (e.g. KEGG_Pathways_Level_2) (e.g., gut site); Transport and Catabolism (e.g.
  • KEGG_Pathways_Level_2) (e.g., gut site); Metabolism of Terpenoids and Polyketides (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Cellular Processes and Signaling (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Carbohydrate Metabolism (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Environmental Adaptation (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Bacterial chemotaxis (e.g., KEGG_Pathways_Level_3) (e.g., gut site); Membrane and intracellular structural molecules (e.g., KEGG_Pathways_Level_3) (e.g., gut site); Pentose and glucuronate interconversions (e.g., KEGG_
  • KEGG_Pathways_Level _3) (e.g., gut site); N-Glycan biosynthesis (e.g. KEGG_Pathways_Level_3) (e.g., gut site); Sulfur metabolism (e.g. KEGG_Pathways_Level _3) (e.g., gut site); Peptidoglycan biosynthesis (e.g. KEGG_Pathways_Level _3) (e.g., gut site); Xylene degradation (e.g. KEGG_Pathways_Level_3) (e.g., gut site); Aminoacyl-tRNA biosynthesis (e.g.
  • KEGG_Pathways_Level_3) (e.g., gut site); Huntingtons disease (e.g. KEGG_Pathways_Level _3) (e.g., gut site); RNA degradation (e.g. KEGG_Pathways_Level _3) (e.g., gut site); Glycosyltransferases (e.g. KEGG_Pathways_Level_3) (e.g., gut site); Others (e.g., KEGG_Pathways_Level_3) (e.g. gut site); Lipopolysaccharide biosynthesis proteins (e.g., KEGG_Pathways_Level_3) (e.g.
  • KEGG_Pathways_Level_3 Phosphatidylinositol signaling system
  • Pores ion channels e.g., KEGG_Pathways_Level_3) (e.g., gut site); Biosynthesis and biodegradation of secondary metabolites (e.g., KEGG_Pathways_Level_3) (e.g., gut site); Phosphonate and phosphinate metabolism (e.g., KEGG_Pathways_Level_3) (e.g., gut site); Dioxin degradation (e.g., KEGG_Pathways_Level_3) (e.g., gut site); Ribosome Biogenesis (e.g., KEGG_Pathways_Level_3) (e.g., gut site); Benzoate degradation (e.g., KEGG_Pathways_Level_3) (e.g., gut site); Translation proteins
  • Determining an allergy-related characterization of a user can include diagnosing a user with a treenut allergy condition based upon one or more of the above microbiome features and/or other suitable features described herein, such as in an additional or alterative manner to typical methods of diagnosis.
  • features used in the treenut allergy characterization process can include any other suitable features (e.g., features useful for diagnostics), and performing the treenut allergy characterization process can be performed in any suitable manner.
  • Block S130 can include performing a shellfish allergy condition characterization process (e.g., determining and/or applying a shellfish allergy characterization model; etc.) for one or more users.
  • a characterization process e.g., of Block S130; based upon statistical analyses and/or other suitable approaches described herein; etc.
  • can identify a set of microbiome features e.g., microbiome composition features, microbiome function features, etc.
  • correlations e.g., positive correlations, negative correlations, correlations of greatest magnitude, etc.
  • performing a shellfish allergy condition characterization process can facilitate identifications of one or more therapies operable to have a positive effect on the shellfish allergy condition (e.g., based upon a random forest predictor algorithm trained with a training dataset derived from a subset of the population of subjects, and validated with a validation dataset derived from a subset of the population of subjects).
  • a shellfish allergy condition can include an immune disorder characterized by an abnormal response by the immune system of the subject to proteins in certain marine animals, where diagnosis can be associated with laboratory analysis (e.g., blood-samples analysis, IgE tests, etc.) and/or other suitable diagnostic procedures.
  • Performing a shellfish allergy condition characterization process can be based on microbiome features (e.g., microbiome composition features) associated with (e.g., derived from, informative of, correlated with, etc.) one or more (e.g. in any suitable combination) of the following taxons: Parabacteroides distasonis (Species) and/ or other suitable taxa.
  • microbiome features e.g., microbiome composition features
  • microbiome features can be associated with one or more of the following taxons in relation to a sample site (e.g., shellfish allergy condition correlations with microorganisms observed at a particular sample site): Parabacteroides distasonis (species) (e.g., gut site).
  • a sample site e.g., shellfish allergy condition correlations with microorganisms observed at a particular sample site
  • Parabacteroides distasonis e.g., gut site
  • microbiome features can be associated with one or more of the following taxons in relation to a healthy gut sample site (and/ or other suitable sites and/or healthiness levels): Oscillospiraceae (family) (e.g., gut site); Acidaminococcaceae (family) (e.g., gut site); Clostridium (genus) (e.g., gut site); Phascolarctobacterium (genus) (e.g., gut site); Bilophila (genus) (e.g., gut site); Odoribacter (genus) (e.g., gut site); Oscillibacter (genus) (e.g., gut site); Parabacteroides distasonis (species) (e.g., gut site); Alistipes putredinis (species) (e.g., gut site); Odoribacter splanchnicus (species) (e.g., gut site); Phascolarctobacterium fae
  • 4_i_30 (species) (e.g., gut site); Butyricimonas sp. JCM 18677 (species) (e.g., gut site); Alistipes sp. EBA6-25CI2 (species) (e.g., gut site); Oscillibacter (genus) (e.g., gut site); Intestinimonas (genus) (e.g., gut site).
  • performing a shellfish allergy condition characterization process can be based on microbiome features (e.g., microbiome function features) associated with one or more of (e.g., such as in relation to a corresponding sample site): Signal Transduction (KEGG2), Cell Growth and Death (KEGG2), Energy Metabolism (KEGG2), Replication and Repair (KEGG2), Selenocompound metabolism (KEGG3), Cell cycle - Caulobacter (KEGG3), Two-component system (KEGG3), Inorganic ion transport and metabolism (KEGG3), Protein kinases (KEGG3), Fatty acid biosynthesis (KEGG3), Amino acid related enzymes (KEGG3), Translation factors (KEGG3), Mismatch repair (KEGG3), Glycerophospholipid metabolism (KEGG3), and/or other suitable function-related aspects.
  • microbiome features e.g., microbiome function features
  • KEGG3 Signal Transduction
  • KEGG2 Cell Growth and Death
  • Energy Metabolism KEGG2
  • microbiome features can be associated with one or more of the following in relation to a sample site (e.g., shellfish allergy condition correlations with microorganism-related function observed at a particular sample site): Infectious Diseases (KEGG_Pathways_Level_2) (e.g., nose site); Metabolism of Cofactors and Vitamins (KEGG_Pathways_Level_2) (e.g., nose site); Poorly Characterized (KEGG_Pathways_Level_2) (e.g., nose site); Glyoxylate and dicarboxylate metabolism (KEGG_Pathways_Level_3) (e.g., nose site); General function prediction only (KEGG_Pathways_Level_3) (e.g., nose site); Polyketide sugar unit biosynthesis (KEGG_Pathways_Level_3) (e.g., nose site); beta-Lactam resistance (KEGG_Pathways_Level_
  • microbiome features can be associated with one or more of the following in relation to a healthy gut sample site (and/or other suitable sites and/or healthiness levels): Cell Growth and Death (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Cell Motility (e.g.,
  • KEGG_ .Pathways, .Level. _2) (e.g., gut site); Signal Transduction (e.g.,
  • KEGG_ .Pathways, .Level. _2) (e.g., gut site); Energy Metabolism (e.g.,
  • KEGG_ .Pathways, .Level. _2) (e.g., gut site); Bacterial chemotaxis (e.g.,
  • KEGG_ .Pathways, .Level. _3) (e.g., gut site); Cell cycle - Caulobacter (e.g.,
  • KEGG_ .Pathways, .Level. _3) (e.g., gut site); Basal transcription factors (e.g.,
  • KEGG_ .Pathways, .Level. .3) (e.g., gut site); Oxidative phosphorylation (e.g.,
  • KEGG_ .Pathways, .Level. _3) e.g., gut site
  • Inorganic ion transport and metabolism e.g.,
  • KEGG_ .Pathways, .Level. _3) (e.g. gut site); Secretion system (e.g.,
  • KEGG_ .Pathways, .Level. _3) (e.g., gut site); Fatty acid biosynthesis (e.g.,
  • KEGG_ .Pathways, .Level. _3) (e.g., gut site); Selenocompound metabolism (e.g.,
  • KEGG_ .Pathways, .Level. .3) (e.g., gut site); Amino acid related enzymes (e.g.,
  • KEGG_ .Pathways, .Level. .3) (e.g., gut site);
  • Two-component system (e.g.,
  • KEGG_ .Pathways, .Level. .3) (e.g. , gut site); Protein kinases (e.g.,
  • KEGG_ .Pathways, .Level. .3) (e.g., gut site); Function unknown (e.g.,
  • KEGG_ .Pathways, .Level. .3) (e.g., gut site); Bacterial motility proteins (e.g.,
  • KEGG_ .Pathways, .Level. _3) (e.g., gut site); Flagellar assembly (e.g.,
  • KEGG_ .Pathways, .Level. _3) (e.g., gut site).
  • Determining an allergy-related characterization of a user can include diagnosing a user with a shellfish allergy condition based upon one or more of the above microbiome features and/or other suitable features described herein, such as in an additional or alterative manner to typical methods of diagnosis.
  • features used in the shellfish allergy characterization process can include any other suitable features (e.g., features useful for diagnostics), and performing the shellfish allergy characterization process can be performed in any suitable manner.
  • Block S130 can include performing a soy allergy condition characterization process (e.g., determining and/or applying a soy allergy characterization model; etc.) for one or more users.
  • a characterization process e.g., of Block S130; based upon statistical analyses and/or other suitable approaches described herein; etc.
  • can identify a set of microbiome features e.g., microbiome composition features, microbiome function features, etc.
  • correlations e.g., positive correlations, negative correlations, correlations of greatest magnitude, etc.
  • performing a soy allergy condition characterization process can facilitate identifications of one or more therapies operable to have a positive effect on the soy allergy condition (e.g., based upon a random forest predictor algorithm trained with a training dataset derived from a subset of the population of subjects, and validated with a validation dataset derived from a subset of the population of subjects).
  • a soy allergy condition can include an immune disorder characterized by by an abnormal reaction of the immune system of the subject to any of the proteins present in a soy bean or derivatives and food that contain soy components or derivatives; where diagnosis can be associated with laboratory analysis (e.g., skin-prick test, blood-samples analysis, IgE tests, etc.) and/ or other suitable diagnostic procedures.
  • Performing a soy allergy condition characterization process can be based on microbiome features (e.g., microbiome composition features) associated with (e.g., derived from, informative of, correlated with, etc.) one or more (e.g.
  • YHC-4 Bacteroides caccae (Species), Erysipelatoclostridium ramosum (Species), Bacteroides thetaiotaomicron (Species), Odoribacter splanchnicus (Species), Bacteroides fragilis (Species), Parabacteroides distasonis (Species), Collinsella (Genus), Sarcina (Genus), Faecalibacterium (Genus), Dorea (Genus), Eggerthella (Genus), Subdoligranulum (Genus), Moryella (Genus), Marvinbryantia (Genus), Barnesiella (Genus), Terrisporobacter (Genus), Bacteroides (Genus), Anaerotruncus (Genus), Clostridium (Genus), Bifidobacterium (Genus), Roseburia (Genus), Akkermansia (Genus), Ruminococcaceae (Family), Flavobacteriaceae (Family), Coriobacteriacea
  • microbiome features can be associated with one or more of the following taxons in relation to a sample site (e.g., soy allergy condition correlations with microorganisms observed at a particular sample site): Acetitomaculum (genus) (e.g., gut site); Acidaminococcaceae (family) (e.g., gut site); Actinobacteria (class) (e.g., gut site); Actinobacteria (phylum) (e.g., gut site); Actinomyces (genus) (e.g., gut site); Actinomyces sp.
  • oral taxon 175 (species) (e.g., nose site); Actinomycetaceae (family) (e.g., gut site); Actinomycetales (order) (e.g., gut site); Adlercreutzia (genus) (e.g., gut site); Adlercreutzia equolifaciens (species) (e.g., gut site); Aerococcaceae (family) (e.g., nose site); Aggregatibacter (genus) (e.g., gut site); Aggregatibacter aphrophilus (species) (e.g., nose site); Akkermansia (genus) (e.g., gut site); Akkermansia muciniphila (species) (e.g., gut site); Alistipes (genus) (e.g., gut site); Alistipes putredinis (species) (e.g., gut site); Alistipes sp.
  • EBA6-25CI2 (species) (e.g., gut site); Alistipes sp. RMA 9912 (species) (e.g., gut site); Alphaproteobacteria (class) (e.g., gut site); Anaerobacter (genus) (e.g., gut site); Anaerofilum (genus) (e.g., gut site); Anaerofustis (genus) (e.g., gut site); Anaerofustis stercorihominis (species) (e.g., gut site); Anaeroplasmataceae (family) (e.g., gut site); Anaerosporobacter (genus) (e.g., gut site); Anaerostipes sp.
  • Family e.g., gut site
  • Anaerosporobacter e.g., gut site
  • 3_2_56FAA (species) (e.g., gut site); Anaerostipes sp. 5_i_63FAA (species) (e.g., gut site); Bacillales (order) (e.g., gut site); Bacteroidaceae (family) (e.g., gut site); Bacteroidales (order) (e.g., gut site); Bacteroides (genus) (e.g., gut site); Bacteroides clarus (species) (e.g., gut site); Bacteroides finegoldii (species) (e.g., gut site); Bacteroides fragilis (species) (e.g., gut site); Bacteroides massiliensis (species) (e.g., gut site); Bacteroides nordii (species) (e.g., gut site); Bacteroides ovatus (species) (e.g., gut site); Bacteroides plebeius (species) (e.
  • AR20 (species) (e.g., gut site); Bacteroides sp. AR29 (species) (e.g., gut site); Bacteroides sp. D22 (species) (e.g., gut site); Bacteroides sp. DJF_Bo97 (species) (e.g., gut site); Bacteroides sp. EBA5-17 (species) (e.g., gut site); Bacteroides sp. SLCi-38 (species) (e.g., gut site); Bacteroides sp.
  • XB12B (species) (e.g., gut site); Bacteroides thetaiotaomicron (species) (e.g., gut site); Bacteroides uniformis (species) (e.g., gut site); Bacteroides vulgatus (species) (e.g., gut site); Bacteroides vulgatus (species) (e.g., genital site); Bacteroidetes (phylum) (e.g., gut site); Bacteroidia (class) (e.g., gut site); Barnesiella (genus) (e.g., gut site); Barnesiella intestinihominis (species) (e.g., gut site); Barnesiella sp.
  • Betaproteobacteria (e.g., gut site); Bifidobacteriaceae (family) (e.g., gut site); Bifidobacteriales (order) (e.g., gut site); Bifidobacterium (genus) (e.g., gut site); Bifidobacterium biavatii (species) (e.g., gut site); Bifidobacterium kashiwanohense (species) (e.g., gut site); Bifidobacterium sp.
  • MSX5B (species) (e.g., gut site); Bifidobacterium stercoris (species) (e.g., gut site); Bilophila (genus) (e.g., gut site); Bilophila sp. 4_i_30 (species) (e.g., gut site); Blautia faecis (species) (e.g., gut site); Blautia glucerasea (species) (e.g., gut site); Blautia luti (species) (e.g., gut site); Blautia producta (species) (e.g., gut site); Blautia sp.
  • Ser8 (species) (e.g., gut site); Blautia sp. YHC-4 (species) (e.g., gut site); Blautia wexlerae (species) (e.g., gut site); Bradyrhizobiaceae (family) (e.g., nose site); Bradyrhizobiaceae (family) (e.g., genital site); Bradyrhizobium (genus) (e.g., nose site); Bradyrhizobium sp.
  • 68A4SAPT serum (e.g., nose site); Burkholderiales (order) (e.g., gut site); Butyricicoccus (genus) (e.g., gut site); Butyricicoccus pullicaecorum (species) (e.g., gut site); Butyricimonas (genus) (e.g., gut site); Butyricimonas sp.
  • JCM 18677 (species) (e.g., gut site); Butyricimonas virosa (species) (e.g., gut site); Butyrivibrio crossotus (species) (e.g., gut site); Campylobacter ureolyticus (species) (e.g., gut site); Campylobacteraceae (family) (e.g., gut site); Campylobacterales (order) (e.g., gut site); Candidatus Soleaferrea (genus) (e.g., gut site); Candidatus Stoquefichus (genus) (e.g., gut site); Capnocytophaga sp.
  • CM59 (species) (e.g., nose site); Carnobacteriaceae (family) (e.g., gut site); Carnobacteriaceae (family) (e.g., skin site); Centipeda (genus) (e.g., nose site); Citrobacter (genus) (e.g., gut site); Citrobacter amalonaticus (species) (e.g., gut site); Clostridia (class) (e.g., gut site); Clostridiaceae (family) (e.g., gut site); Clostridiales (order) (e.g., gut site); Clostridium (genus) (e.g., gut site); Collinsella (genus) (e.g., gut site); Collinsella aerofaciens (species) (e.g., gut site); Collinsella intestinalis (species) (e.g., gut site); Coriobacteriaceae (family) (e.g., gut
  • BN-SKY3 (species) (e.g., nose site); Deltaproteobacteria (class) (e.g., gut site); Desulfovibrio piger (species) (e.g., gut site); Desulfovibrionaceae (family) (e.g., gut site); Desulfovibrionales (order) (e.g., gut site); Dialister (genus) (e.g., gut site); Dialister micraerophilus (species) (e.g., gut site); Dielma (genus) (e.g., gut site); Dielma fastidiosa (species) (e.g., gut site); Dorea (genus) (e.g., gut site); Dorea formicigenerans (species) (e.g., gut site); Dorea longicatena (species) (e.g., gut site); Eggerthella (genus) (e.g., gut site); Eggerthella sp.
  • HGAi (species) (e.g., gut site); Eisenbergiella (genus) (e.g., gut site); Eisenbergiella tayi (species) (e.g., gut site); Enterobacter (genus) (e.g., gut site); Enterobacter sp.
  • BS2-1 (species) (e.g., gut site); Enterobacteriaceae (family) (e.g., genital site); Enterobacteriales (order) (e.g., genital site); Enterococcaceae (family) (e.g., gut site); Enterococcus (genus) (e.g., gut site); Enterococcus raffinosus (species) (e.g., gut site); Enterococcus sp.
  • Family e.g., genital site
  • Enterobacteriales order
  • Enterococcaceae family
  • Enterococcus genus
  • Enterococcus raffinosus (species) (e.g., gut site); Enterococcus sp.
  • C6I11 (species) (e.g., gut site); Enterorhabdus (genus) (e.g., gut site); Epsilonproteobacteria (class) (e.g., gut site); Erysipelatoclostridium ramosum (species) (e.g., gut site); Erysipelotrichaceae (family) (e.g., gut site); Erysipelotrichales (order) (e.g., gut site); Erysipelotrichia (class) (e.g., gut site); Eubacteriaceae (family) (e.g., gut site); Eubacterium (genus) (e.g., gut site); Eubacterium callanderi (species) (e.g., gut site); Faecalibacterium (genus) (e.g., gut site); Faecalibacterium prausnitzii (species) (e.g., gut site); Firmicutes (phylum) (e.g
  • TeTO (species) (e.g., nose site); Marvinbryantia (genus) (e.g., gut site); Megasphaera (genus) (e.g., gut site); Megasphaera genomosp. Ci (species) (e.g., gut site); Mollicutes (class) (e.g., gut site); Moryella (genus) (e.g., gut site); Mycobacteriaceae (family) (e.g., nose site); Mycobacteriaceae (family) (e.g., mouth site); Mycobacterium (genus) (e.g., nose site); Negativicutes (class) (e.g., gut site); Neisseria elongata (species) (e.g., nose site); Neisseria mucosa (species) (e.g., nose site); Odoribacter (genus) (e.g., gut site); Odoribacter splanchnicus (species) (e.
  • DNF00840 (species) (e.g., genital site); Peptoniphilus sp. oral taxon 375 (species) (e.g., gut site); Phascolarctobacterium (genus) (e.g., gut site); Phascolarctobacterium faecium (species) (e.g., gut site); Phyllobacteriaceae (family) (e.g., gut site); Phyllobacterium (genus) (e.g., gut site); Porphyromonadaceae (family) (e.g., gut site); Prevotellaceae (family) (e.g., gut site); Pseudoflavonifractor (genus) (e.g., gut site); Pseudoflavonifractor capillosus (species) (e.g., gut site); Pseudomonadales (order) (e.g., gut site); Rhizobiaceae (family)
  • 11SE39 (species) (e.g., gut site); Roseburia sp. 499 (species) (e.g., gut site); Ruminococcaceae (family) (e.g., gut site); Ruminococcaceae (family) (e.g., genital site); Sarcina (genus) (e.g., gut site); Selenomonadales (order) (e.g., gut site); Shinella (genus) (e.g., nose site); Shinella sp.
  • DR33 (species) (e.g., nose site); Shuttleworthia (genus) (e.g., gut site); Slackia piriformis (species) (e.g., gut site); Sphingomonas (genus) (e.g., skin site); Streptococcaceae (family) (e.g., gut site); Streptococcus sp. BS35a (species) (e.g., gut site); Streptococcus sp.
  • BS35a (species) (e.g., mouth site); Subdoligranulum (genus) (e.g., gut site); Subdoligranulum variabile (species) (e.g., gut site); Sutterella stercoricanis (species) (e.g., gut site); Sutterella wadsworthensis (species) (e.g., gut site); Sutterellaceae (family) (e.g., gut site); Tenericutes (phylum) (e.g., gut site); Terrisporobacter (genus) (e.g., gut site); Thalassospira (genus) (e.g., gut site); Veillonella (genus) (e.g., gut site); Verrucomicrobia (phylum) (e.g., gut site); Verrucomicrobiaceae (family) (e.g., gut site); Verrucomicrobiae (class) (e.g., gut site); Verrucomicrobiales (order)
  • performing a soy allergy condition characterization process can be based on microbiome features (e.g., microbiome function features) associated with one or more of (e.g., such as in relation to a corresponding sample site): Metabolism (KEGG2), Translation (KEGG2), Carbohydrate Metabolism (KEGG2), Replication and Repair (KEGG2), Cellular Processes and Signaling (KEGG2), Nucleotide Metabolism (KEGG2), Enzyme Families (KEGG2), Cell Growth and Death (KEGG2), Poorly Characterized (KEGG2), Environmental Adaptation (KEGG2), Glycan Biosynthesis and Metabolism (KEGG2), Signal Transduction (KEGG2), Metabolism of Cofactors and Vitamins (KEGG2), Signaling Molecules and Interaction (KEGG2), Transport and Catabolism (KEGG2), Xenobiotics Biodegradation and Metabolism (KEGG2), Ribosome Biogenesis (KEGG3),
  • microbiome features e
  • KEGG_Pathways_Level_3) e.g., gut site
  • MAPK signaling pathway - yeast KEGG_Pathways_Level_3) (e.g., gut site); Inositol phosphate metabolism (KEGG_Pathways_Level_3) (e.g., gut site); Amino acid metabolism (KEGG_Pathways_Level_3) (e.g., gut site); Others (KEGG_Pathways_Level_3) (e.g., gut site); Pores ion channels (KEGG_Pathways_Level_3) (e.g., gut site); Biosynthesis and biodegradation of secondary metabolites (KEGG_Pathways_Level_3) (e.g., gut site); Phosphonate and phosphinate metabolism (KEGG_Pathways_Level_3) (e.g., gut site); Caprolactam degradation (KEGG_Pathways_Level_3) (e.g., gut site); Ribosome Biogenesis
  • KEGG_Pathways_Level_3) e.g., gut site
  • Lipopolysaccharide biosynthesis proteins KEGG_Pathways_Level_3) (e.g., gut site); Phosphatidylinositol signaling system (KEGG_Pathways_Level_3) (e.g., gut site); Cell motility and secretion (KEGG_Pathways_Level_3) (e.g., gut site); Protein folding and associated processing (KEGG_Pathways_Level_3) (e.g., gut site); Photosynthesis (KEGG_Pathways_Level_3) (e.g., gut site); D-Alanine metabolism (KEGG_Pathways_Level_3) (e.g., gut site); Glycosphingolipid biosynthesis - globo series (KEGG_Pathways_Level_3) (e.g., gut site); Circadian rhythm - plant (KEGG_Pathways_Level_3) (e.g
  • KEGG_Pathways_Level_3) e.g., gut site
  • African trypanosomiasis KEGG_Pathways_Level_3
  • Fatty acid elongation in mitochondria KEGG_Pathways_Level_3) (e.g., gut site); Germination (KEGG_Pathways_Level_3) (e.g., gut site); Type I diabetes mellitus (KEGG_Pathways_Level_3) (e.g., gut site); Secondary bile acid biosynthesis (KEGG_Pathways_Level_3) (e.g., gut site); Penicillin and cephalosporin biosynthesis (KEGG_Pathways_Level_3) (e.g., gut site); Carbohydrate metabolism (KEGG_Pathways_Level_3) (e.g., gut site); Lysine biosynthesis (KEGG_Pathways_Level_3) (e.g., gut site); Mismatch repair (KEGG_Pathways_Level
  • microbiome features can be associated with one or more of the following in relation to a sample site (e.g., soy allergy condition correlations with microorganism-related function observed at a particular sample site): Benzoate degradation (e.g., KEGG_Pathways_Level_3) (e.g., genital site); Excretory System (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Enzyme Families (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Metabolism (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Signaling Molecules and Interaction (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Translation (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Translation (e.g., KEGG_P
  • microbiome features can be associated with one or more of the following in relation to a healthy gut sample site (and/or other suitable sites and/or healthiness levels): Biosynthesis of Other Secondary Metabolites (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Excretory System (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Neurodegenerative Diseases (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Metabolism (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Signaling Molecules and Interaction (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Glycan Biosynthesis and Metabolism (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Glycan Biosynthesis and Metabolism (e.g.,
  • KEGG_Pathways_Level_3) (e.g., gut site); Biosynthesis of unsaturated fatty acids (e.g. KEGG_Pathways_Level_3) (e.g., gut site); Sulfur metabolism (e.g. KEGG_Pathways_Level_3) (e.g., gut site); Biotin metabolism (e.g. KEGG_Pathways_Level_3) (e.g., gut site); Peptidoglycan biosynthesis (e.g. KEGG_Pathways_Level_3) (e.g., gut site); Aminoacyl-tRNA biosynthesis (e.g.
  • KEGG_Pathways_Level_3) e.g., gut site
  • Ascorbate and aldarate metabolism e.g. KEGG_Pathways_Level_3) (e.g., gut site); Huntingtons disease (e.g. KEGG_Pathways_Level_3) (e.g., gut site); MAPK signaling pathway - yeast (e.g. KEGG_Pathways_Level_3) (e.g., gut site); Inositol phosphate metabolism (e.g. KEGG_Pathways_Level_3) (e.g., gut site); Amino acid metabolism (e.g.
  • KEGG_Pathways_Level_3) e.g., gut site
  • Others e.g., KEGG_Pathways_Level_3
  • Lipopolysaccharide biosynthesis proteins e.g., KEGG_Pathways_Level_3
  • KEGG_Pathways_Level_3 Phosphatidylinositol signaling system
  • Pores ion channels e.g., KEGG_Pathways_Level_3) (e.g., gut site); Biosynthesis and biodegradation of secondary metabolites (e.g., KEGG_Pathways_Level_3) (e.g., gut site); Phosphonate and phosphinate metabolism (e.g., KEGG_Pathways_Level_3) (e.g., gut site); Caprolactam degradation (e.g., KEGG_Pathways_Level_3) (e.g., gut site); Ribosome Biogenesis (e.g., KEGG_Pathways_Level_3) (e.g., gut site); Translation proteins (e.g., KEGG_Pathways_Level_3) (e.g., gut site); Cell motility and
  • Determining an allergy-related characterization of a user can include diagnosing a user with a soy allergy condition based upon one or more of the above microbiome features and/or other suitable features described herein, such as in an additional or alterative manner to typical methods of diagnosis.
  • features used in the soy allergy characterization process can include any other suitable features (e.g., features useful for diagnostics), and performing the soy allergy characterization process can be performed in any suitable manner.
  • Block S130 can include performing a peanut allergy condition characterization process (e.g., determining and/or applying a peanut allergy characterization model; etc.) for one or more users.
  • a characterization process e.g., of Block S130; based upon statistical analyses and/or other suitable approaches described herein; etc.
  • can identify a set of microbiome features e.g., microbiome composition features, microbiome function features, etc.
  • correlations e.g., positive correlations, negative correlations, correlations of greatest magnitude, etc.
  • performing a peanut allergy condition characterization process can facilitate identifications of one or more therapies operable to have a positive effect on the peanut allergy condition (e.g., based upon a random forest predictor algorithm trained with a training dataset derived from a subset of the population of subjects, and validated with a validation dataset derived from a subset of the population of subjects).
  • a peanut allergy condition can include an immune disorder of the subject characterized by hypersensitivity to dietary substances from peanut, causing an overreaction of the immune system which may lead to severe physical symptoms and where diagnosis can be associated to laboratory analysis (e.g., skin-prick test, blood- samples analysis, IgE tests, etc.) and/or other suitable diagnostic procedures.
  • Performing a peanut allergy condition characterization process can be based on microbiome features (e.g., microbiome composition features) associated with (e.g., derived from, informative of, correlated with, etc.) one or more (e.g.
  • Flavonifractor plautii (Species), Blautia luti (Species), Collinsella aerofaciens (Species), Dorea formicigenerans (Species), Barnesiella intestinihominis (Species), Bacteroides (Genus), Eggerthella (Genus), Sarcina (Genus), Marvinbryantia (Genus), Barnesiella (Genus), Thalassospira (Genus), Dorea (Genus), Oscillospiraceae (Family), Clostridiaceae (Family), Bacteroidaceae (Family), Flavobacteriaceae (Family), Rhodospirillaceae (Family), Flavobacteriales (Order), Bacteroidales (Order), Clostridiales (Order), Rhodospirillales (Order), Flavobacteriia (Class), Clostridia (Class), Bacteroidia (Class), Bac
  • microbiome features can be associated with one or more of the following taxons in relation to a sample site (e.g., peanut allergy condition correlations with microorganisms observed at a particular sample site): Acetitomaculum (genus) (e.g., gut site); Acidaminococcaceae (family) (e.g., gut site); Actinomyces (genus) (e.g., gut site); Actinomyces sp. ICM54 (species) (e.g., gut site); Actinomyces sp.
  • Acetitomaculum e.g., gut site
  • Acidaminococcaceae family
  • Actinomyces genus
  • Actinomyces sp. ICM54 species
  • oral strain Hal-1065 (species) (e.g., mouth site); Actinomycetaceae (family) (e.g., gut site); Adlercreutzia (genus) (e.g., gut site); Adlercreutzia equolifaciens (species) (e.g., gut site); Akkermansia (genus) (e.g., gut site); Alistipes (genus) (e.g., gut site); Alistipes sp. EBA6- 25CI2 (species) (e.g., gut site); Alistipes sp. NML05A004 (species) (e.g., gut site); Alistipes sp.
  • RMA 9912 (species) (e.g., gut site); Alphaproteobacteria (class) (e.g., gut site); Anaerobacter (genus) (e.g., gut site); Anaerofilum (genus) (e.g., gut site); Anaeroplasmataceae (family) (e.g., gut site); Anaeroplasmatales (order) (e.g., gut site); Anaerosporobacter (genus) (e.g., gut site); Anaerostipes sp. 3_2_56FAA (species) (e.g., gut site); Anaerostipes sp.
  • 5_i_63FAA (species) (e.g., gut site); Anaerotruncus colihominis (species) (e.g., gut site); Bacteroidaceae (family) (e.g., gut site); Bacteroidales (order) (e.g., gut site); Bacteroides (genus) (e.g., gut site); Bacteroides clarus (species) (e.g., gut site); Bacteroides fragilis (species) (e.g., gut site); Bacteroides massiliensis (species) (e.g., gut site); Bacteroides ovatus (species) (e.g., gut site); Bacteroides sp.
  • D22 (species) (e.g., gut site); Bacteroides thetaiotaomicron (species) (e.g., gut site); Bacteroides vulgatus (species) (e.g., gut site); Bacteroidetes (phylum) (e.g., gut site); Bacteroidia (class) (e.g., gut site); Barnesiella (genus) (e.g., gut site); Barnesiella intestinihominis (species) (e.g., gut site); Bilophila (genus) (e.g., gut site); Bilophila sp.
  • 4_i_30 (species) (e.g., gut site); Blautia glucerasea (species) (e.g., gut site); Blautia luti (species) (e.g., gut site); Blautia sp. Ser8 (species) (e.g., gut site); Blautia sp.
  • YHC-4 (species) (e.g., gut site); Blautia wexlerae (species) (e.g., gut site); Butyricimonas (genus) (e.g., gut site); Campylobacterales (order) (e.g., gut site); Candidatus Soleaferrea (genus) (e.g., gut site); Carnobacteriaceae (family) (e.g., gut site); Clostridia (class) (e.g., gut site); Clostridiaceae (family) (e.g., gut site); Clostridiales (order) (e.g., gut site); Clostridiales (family) XI.
  • Incertae Sedis (e.g., nose site); Clostridium (genus) (e.g., gut site); Collinsella (genus) (e.g., gut site); Collinsella aerofaciens (species) (e.g., gut site); Deltaproteobacteria (class) (e.g., gut site); Desulfovibrionaceae (family) (e.g., gut site); Desulfovibrionales (order) (e.g., gut site); Dielma (genus) (e.g., gut site); Dielma fastidiosa (species) (e.g., gut site); Dorea (genus) (e.g., gut site); Dorea formicigenerans (species) (e.g., gut site); Dorea longicatena (species) (e.g., gut site); Eggerthella (genus) (e.g., gut site); Eggerthella sp.
  • HGAi (species) (e.g., gut site); Eisenbergiella (genus) (e.g., gut site); Eisenbergiella tayi (species) (e.g., gut site); Enterobacteriaceae (family) (e.g., gut site); Enterobacteriales (order) (e.g., gut site); Epsilonproteobacteria (class) (e.g., gut site); Erysipelatoclostridium ramosum (species) (e.g., gut site); Erysipelotrichaceae (family) (e.g., gut site); Erysipelotrichales (order) (e.g., gut site); Erysipelotrichia (class) (e.g., gut site); Eubacterium (genus) (e.g., gut site); Eubacterium callanderi (species) (e.g., gut site); Faecalibacterium (genus) (e.g.,
  • BL302 (species) (e.g., gut site); Lactonifactor (genus) (e.g., gut site); Lactonifactor longoviformis (species) (e.g., gut site); Marvinbryantia (genus) (e.g., gut site); Megasphaera (genus) (e.g., gut site); Micrococcaceae (family) (e.g., gut site); Mollicutes (class) (e.g., gut site); Moraxella (genus) (e.g., nose site); Moryella (genus) (e.g., gut site); Negativicutes (class) (e.g., gut site); Odoribacter (genus) (e.g., gut site); Odoribacter splanchnicus (species) (e.g., gut site); Oscillibacter (genus) (e.g., gut site); Oscillospiraceae (family) (e.g., gut site); Para
  • 11SE39 (species) (e.g., gut site); Ruminococcaceae (family) (e.g., gut site); Sarcina (genus) (e.g., gut site); Selenomonadales (order) (e.g., gut site); Subdoligranulum variabile (species) (e.g., gut site); Tenericutes (phylum) (e.g., gut site); Terrisporobacter (genus) (e.g., gut site); Thalassospira (genus) (e.g., gut site); Veillonella (genus) (e.g., gut site); Verrucomicrobia (phylum) (e.g., gut site); Verrucomicrobiaceae (family) (e.g., gut site); Verrucomicrobiae (class) (e.g., gut site); Verrucomicrobiales (order) (e.g., gut site).
  • Ruminococcaceae family
  • Sarcina genus
  • microbiome features can be associated with one or more of the following taxons in relation to a healthy gut sample site (and/ or other suitable sites and/or healthiness levels): Clostridia (class) (e.g., gut site); Bacteroidia (class) (e.g., gut site); Negativicutes (class) (e.g., gut site); Gammaproteobacteria (class) (e.g., gut site); Alphaproteobacteria (class) (e.g., gut site); Mollicutes (class) (e.g., gut site); Flavobacteriia (class) (e.g., gut site); Clostridia (class) (e.g., gut site); Bacteroidia (class) (e.g., gut site); Erysipelotrichia (class) (e.g., gut site); Negativicutes (class) (e.g., gut site); Alphaproteobacteria (class) (e.g., gut site); Alpha
  • Ser8 (species) (e.g., gut site); Bilophila sp. 4_i_30 (species) (e.g., gut site); Eggerthella sp. HGAi (species) (e.g., gut site); Fusicatenibacter saccharivorans (species) (e.g., gut site); Eisenbergiella tayi (species) (e.g., gut site); Faecalibacterium prausnitzii (species) (e.g., gut site); Erysipelatoclostridium ramosum (species) (e.g., gut site); Lachnospira pectinoschiza (species) (e.g., gut site); Dorea formicigenerans (species) (e.g., gut site); Holdemania filiformis (species) (e.g., gut site); Collinsella aerofaciens (species) (e.g., gut site); Dorea longicatena (
  • 11SE39 (species) (e.g., gut site); Anaerostipes sp. 3_2_56FAA (species) (e.g., gut site); Blautia sp. Ser8 (species) (e.g., gut site); Eggerthella sp. HGAi (species) (e.g., gut site); Anaerostipes sp. 5_i_63FAA (species) (e.g., gut site); Dielma fastidiosa (species) (e.g., gut site); Fusicatenibacter saccharivorans (species) (e.g., gut site); Blautia sp.
  • YHC-4 (species) (e.g., gut site); Eisenbergiella tayi (species) (e.g., gut site); Bacteroides fragilis (species) (e.g., gut site); Bacteroides fragilis (species) (e.g., gut site); Bacteroides vulgatus (species) (e.g., gut site); Erysipelatoclostridium ramosum (species) (e.g., gut site); Erysipelatoclostridium ramosum (species) (e.g., gut site); Lachnospira pectinoschiza (species) (e.g., gut site); Lachnospira pectinoschiza (species) (e.g., gut site); Odoribacter splanchnicus (species) (e.g., gut site); Odoribacter splanchnicus (species) (e.g., gut site); Odoribacter splan
  • 11SE39 (species) (e.g., gut site); Roseburia sp. 11SE39 (species) (e.g., gut site); Bacteroides sp. D22 (species) (e.g., gut site); Bacteroides sp. D22 (species) (e.g., gut site); Bacteroides clarus (species) (e.g., gut site); Bacteroides clarus (species) (e.g., gut site); Alistipes sp. RMA 9912 (species) (e.g., gut site); Alistipes sp. RMA 9912 (species) (e.g., gut site); Lactobacillus sp.
  • BL302 (species) (e.g., gut site); Lactobacillus sp. BL302 (species) (e.g., gut site); Anaerostipes sp. 3_2_56FAA (species) (e.g., gut site); Anaerostipes sp. 3_2_56FAA (species) (e.g., gut site); Blautia sp. Ser8 (species) (e.g., gut site); Blautia sp. Ser8 (species) (e.g., gut site); Bilophila sp. 4_i_30 (species) (e.g., gut site); Bilophila sp.
  • 4_i_30 (species) (e.g., gut site); Eggerthella sp. HGAi (species) (e.g., gut site); Eggerthella sp. HGAi (species) (e.g., gut site); Anaerostipes sp. 5_i_63FAA (species) (e.g., gut site); Anaerostipes sp.
  • 5_i_63FAA (species) (e.g., gut site); Dielma fastidiosa (species) (e.g., gut site); Dielma fastidiosa (species) (e.g., gut site); Fusicatenibacter saccharivorans (species) (e.g., gut site); Fusicatenibacter saccharivorans (species) (e.g., gut site); Fusicatenibacter saccharivorans (species) (e.g., gut site); Fusicatenibacter saccharivorans (species) (e.g., gut site); Fusicatenibacter saccharivorans (species) (e.g., gut site); Blautia sp. YHC-4 (species) (e.g., gut site); Blautia sp. YHC-4 (species) (e.g., gut site); Blautia sp. YHC-4 (species) (e.g.,
  • performing a peanut allergy condition characterization process can be based on microbiome features (e.g., microbiome function features) associated with one or more of (e.g., such as in relation to a corresponding sample site): Translation (KEGG2), Cellular Processes and Signaling (KEGG2), Carbohydrate Metabolism (KEGG2), Metabolism (KEGG2), Replication and Repair (KEGG2), Transport and Catabolism (KEGG2), Nucleotide Metabolism (KEGG2), Lipid Metabolism (KEGG2), Cell Growth and Death (KEGG2), Biosynthesis of Other Secondary Metabolites (KEGG2), Glycan Biosynthesis and Metabolism (KEGG2), and/or other suitable function-related aspects.
  • microbiome features e.g., microbiome function features
  • KEGG2 e.g., microbiome function features associated with one or more of (e.g., such as in relation to a corresponding sample site): Translation (KEGG2), Cellular Processes and Signal
  • microbiome features can be associated with one or more of the following in relation to a sample site (e.g., peanut allergy condition correlations with microorganism-related function observed at a particular sample site): Cell Motility (KEGG_Pathways_Level_2) (e.g., gut site); Metabolism (KEGG_Pathways_Level_2) (e.g., gut site); Translation
  • KEGG_Pathways_Level_3) e.g., gut site
  • Ascorbate and aldarate metabolism KEGG_Pathways_Level_3)
  • Others e.g., gut site
  • Ribosome Biogenesis e.g., gut site
  • Translation proteins e.g., gut site
  • Other ion-coupled transporters KEGG_Pathways_Level_3) (e.g., gut site); Bisphenol degradation (KEGG_Pathways_Level_3) (e.g., gut site); Inorganic ion transport and metabolism (KEGG_Pathways_Level_3) (e.g., gut site); Linoleic acid metabolism (KEGG_Pathways_Level_3) (e.g., gut site); Phenylalanine metabolism (KEGG_Pathways_Level_3) (e
  • KEGG_Pathways_Level_3) e.g., gut site
  • Inositol phosphate metabolism KEGG_Pathways_Level_3
  • Lipopolysaccharide biosynthesis proteins KEGG_Pathways_Level_3) (e.g., gut site); Phosphatidylinositol signaling system (KEGG_Pathways_Level_3) (e.g., gut site); Pores ion channels (KEGG_Pathways_Level_3) (e.g., gut site); Biosynthesis and biodegradation of secondary metabolites (KEGG_Pathways_Level_3) (e.g., gut site); Phosphonate and phosphinate metabolism (KEGG_Pathways_Level_3) (e.g., gut site); Cell motility and secretion (KEGG_Pathways_Level_3) (e.g., gut site); Glycosphingolipid biosynthesis - globo
  • microbiome features can be associated with one or more of the following in relation to a healthy gut sample site (and/or other suitable sites and/or healthiness levels): Biosynthesis of Other Secondary Metabolites (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Excretory System (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Cell Growth and Death (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Cell Motility (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Metabolism (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Signaling Molecules and Interaction (e.g., KEGG_Pathways_Level_2) (e.g., gut site); Gly
  • Determining an allergy-related characterization of a user can include diagnosing a user with a peanut allergy condition based upon one or more of the above microbiome features and/or other suitable features described herein, such as in an additional or alterative manner to typical methods of diagnosis.
  • features used in the peanut allergy characterization process can include any other suitable features (e.g., features useful for diagnostics), and performing the peanut allergy characterization process can be performed in any suitable manner.
  • Block S130 can include performing a egg allergy condition characterization process (e.g., determining and/or applying a egg allergy characterization model; etc.) for one or more users.
  • a characterization process e.g., of Block S130; based upon statistical analyses and/or other suitable approaches described herein; etc.
  • can identify a set of microbiome features e.g., microbiome composition features, microbiome function features, etc.
  • correlations e.g., positive correlations, negative correlations, correlations of greatest magnitude, etc.
  • performing a egg allergy condition characterization process can facilitate identifications of one or more therapies operable to have a positive effect on the egg allergy condition (e.g., based upon a random forest predictor algorithm trained with a training dataset derived from a subset of the population of subjects, and validated with a validation dataset derived from a subset of the population of subjects).
  • a egg allergy condition can include an immune disorder characterized by an abnormal reaction of the immune system of the subject to any food containing eggs (e.g., chicken eggs) or some of its derivatives, and diagnosis can be associated with laboratory analysis (e.g., skin-prick test, blood-samples analysis, IgE tests, etc.) and/or other suitable diagnostic procedures.
  • Performing a egg allergy condition characterization process can be based on microbiome features (e.g., microbiome composition features) associated with (e.g., derived from, informative of, correlated with, etc.) one or more (e.g.
  • microbiome features can be associated with one or more of the following taxons in relation to a sample site (e.g., egg allergy condition correlations with microorganisms observed at a particular sample site): Acidaminococcaceae (family) (e.g., gut site); Acidaminococcus sp.
  • a sample site e.g., egg allergy condition correlations with microorganisms observed at a particular sample site
  • Acidaminococcaceae family
  • Acidaminococcus sp Acidaminococcus sp.
  • D21 (species) (e.g., gut site); Acidobacteria (phylum) (e.g., nose site); Acidobacteriia (class) (e.g., nose site); Acinetobacter (genus) (e.g., nose site); Actinobacillus (genus) (e.g., gut site); Actinobacillus porcinus (species) (e.g., gut site); Actinobacteria (class) (e.g., gut site); Actinobacteria (phylum) (e.g., gut site); Actinomyces (genus) (e.g., nose site); Actinomyces massiliensis (species) (e.g., mouth site); Actinomyces sp.
  • ICM54 (species) (e.g., nose site); Actinomyces sp. oral taxon 175 (species) (e.g., nose site); Actinomyces sp. ZSY-i (species) (e.g., mouth site); Actinomycetaceae (family) (e.g., nose site); Actinomycetales (order) (e.g., gut site); Adlercreutzia (genus) (e.g., gut site); Adlercreutzia equolifaciens (species) (e.g., gut site); Akkermansia (genus) (e.g., gut site); Akkermansia muciniphila (species) (e.g., gut site); Alistipes (genus) (e.g., gut site); Alistipes putredinis (species) (e.g., gut site); Alistipes sp.
  • RMA 9912 (species) (e.g., gut site); Alphaproteobacteria (class) (e.g., nose site); Alphaproteobacteria (class) (e.g., gut site); Anaerobacter (genus) (e.g., gut site); Anaerofilum (genus) (e.g., gut site); Anaerosporobacter (genus) (e.g., gut site); Anaerostipes sp. iy-2 (species) (e.g., gut site); Anaerostipes sp. 3_2_56FAA (species) (e.g., gut site); Anaerostipes sp.
  • 5_i_63FAA (species) (e.g., gut site); Anaerotruncus colihominis (species) (e.g., gut site); Anaerotruncus sp. NML 070203 (species) (e.g., gut site); Anaerovorax (genus) (e.g., gut site); Bacteroidaceae (family) (e.g., gut site); Bacteroidaceae (family) (e.g., mouth site); Bacteroidales (order) (e.g., gut site); Bacteroides (genus) (e.g., gut site); Bacteroides (genus) (e.g., mouth site); Bacteroides acidifaciens (species) (e.g., gut site); Bacteroides caccae (species) (e.g., gut site); Bacteroides clarus (species) (e.g., gut site); Bacteroides dorei (species) (e
  • AR20 (species) (e.g., gut site); Bacteroides sp. AR29 (species) (e.g., gut site); Bacteroides sp. D22 (species) (e.g., gut site); Bacteroides sp. DJF_Bo97 (species) (e.g., gut site); Bacteroides sp. EBA5-17 (species) (e.g., gut site); Bacteroides sp. SLCi-38 (species) (e.g., gut site); Bacteroides sp.
  • XB12B (species) (e.g., gut site); Bacteroides stercoris (species) (e.g., gut site); Bacteroides thetaiotaomicron (species) (e.g., gut site); Bacteroides uniformis (species) (e.g., gut site); Bacteroides vulgatus (species) (e.g., nose site); Bacteroides vulgatus (species) (e.g., genital site); Bacteroides vulgatus (species) (e.g., gut site); Bacteroidetes (phylum) (e.g., gut site); Bacteroidia (class) (e.g., gut site); Barnesiella (genus) (e.g., gut site); Barnesiella intestinihominis (species) (e.g., gut site); Bergeyella (genus) (e.g., nose site); Betaproteobacteria (class) (e.g.
  • 4_i_30 (species) (e.g., gut site); Blautia (genus) (e.g., genital site); Blautia (genus) (e.g., gut site); Blautia faecis (species) (e.g., gut site); Blautia glucerasea (species) (e.g., gut site); Blautia hydrogenotrophica (species) (e.g., gut site); Blautia luti (species) (e.g., gut site); Blautia producta (species) (e.g., gut site); Blautia sp. Ser8 (species) (e.g., gut site); Blautia sp.
  • YHC-4 (species) (e.g., gut site); Blautia wexlerae (species) (e.g., gut site); Burkholderiaceae (family) (e.g., nose site); Burkholderiales (order) (e.g., gut site); Butyricimonas (genus) (e.g., gut site); Campylobacteraceae (family) (e.g., nose site); Campylobacterales (order) (e.g., nose site); Candidatus Soleaferrea (genus) (e.g., gut site); Capnocytophaga (genus) (e.g., nose site); Capnocytophaga sp.
  • AHN9576 (species) (e.g., mouth site); Capnocytophaga sp. CM59 (species) (e.g., nose site); Cardiobacteriaceae (family) (e.g., mouth site); Cardiobacterium valvarum (species) (e.g., mouth site); Carnobacteriaceae (family) (e.g., gut site); Carnobacteriaceae (family) (e.g., mouth site); Centipeda (genus) (e.g., nose site); Cloacibacillus (genus) (e.g., gut site); Cloacibacillus evryensis (species) (e.g., gut site); Clostridia (class) (e.g., gut site); Clostridiaceae (family) (e.g., gut site); Clostridiales (order) (e.g., gut site); Clostridiales (family) XI.
  • Incertae Sedis family (e.g., gut site); Clostridiales (family) XIII. Incertae Sedis (family) (e.g., gut site); Clostridium (genus) (e.g., gut site); Collinsella (genus) (e.g., gut site); Collinsella aerofaciens (species) (e.g., gut site); Comamonadaceae (family) (e.g., mouth site); Comamonas (genus) (e.g., mouth site); Coprobacillus (genus) (e.g., gut site); Coprobacillus sp.
  • D6 (species) (e.g., gut site); Coriobacteriaceae (family) (e.g., gut site); Coriobacteriales (order) (e.g., gut site); Corynebacterium durum (species) (e.g., nose site); Corynebacterium frburgense (species) (e.g., genital site); Corynebacterium matruchotii (species) (e.g., nose site); Corynebacterium sp.
  • NML 97-0186 (species) (e.g., nose site); Cronobacter (genus) (e.g., gut site); Cyanobacteria (phylum) (e.g., nose site); Delftia (genus) (e.g., nose site); Delftia sp.
  • BN-SKY3 (species) (e.g., nose site); Deltaproteobacteria (class) (e.g., gut site); Desulfovibrionaceae (family) (e.g., gut site); Desulfovibrionales (order) (e.g., gut site); Dialister (genus) (e.g., gut site); Dialister propionicifaciens (species) (e.g., gut site); Dielma (genus) (e.g., gut site); Dielma fastidiosa (species) (e.g., gut site); Dorea (genus) (e.g., gut site); Dorea formicigenerans (species) (e.g., gut site); Dorea longicatena (species) (e.g., gut site); Eggerthella (genus) (e.g., gut site); Eggerthella sinensis (species) (e.g., gut site); Eggerthella sp
  • HGAi (species) (e.g., gut site); Eisenbergiella (genus) (e.g., gut site); Eisenbergiella tayi (species) (e.g., gut site); Enterococcaceae (family) (e.g., gut site); Enterococcus (genus) (e.g., gut site); Enterococcus raffinosus (species) (e.g., gut site); Enterococcus sp.
  • C6I11 (species) (e.g., gut site); Erysipelatoclostridium (genus) (e.g., gut site); Erysipelatoclostridium ramosum (species) (e.g., gut site); Erysipelotrichaceae (family) (e.g., gut site); Erysipelotrichales (order) (e.g., gut site); Erysipelotrichia (class) (e.g., gut site); Eubacteriaceae (family) (e.g., gut site); Eubacterium (genus) (e.g., gut site); Eubacterium callanderi (species) (e.g., gut site); Faecalibacterium (genus) (e.g., gut site); Faecalibacterium (genus) (e.g., mouth site); Faecalibacterium prausnitzii (species) (e.g., gut site); Faecalibacterium prausnitz
  • S8 F7 (species) (e.g., gut site); Finegoldia sp. S9 AA1-5 (species) (e.g., gut site); Firmicutes (phylum) (e.g., gut site); Flavobacteriaceae (family) (e.g., gut site); Flavobacteriales (order) (e.g., gut site); Flavobacteriia (class) (e.g., gut site); Flavonifractor (genus) (e.g., gut site); Flavonifractor plautii (species) (e.g., gut site); Fusicatenibacter (genus) (e.g., gut site); Fusicatenibacter saccharivorans (species) (e.g., gut site); Fusobacteria (phylum) (e.g., gut site); Fusobacteriaceae (family) (e.g., nose site); Fusobacteriales (order) (e.g.
  • CM21 (species) (e.g., nose site); Fusobacterium sp. CM21 (species) (e.g., gut site); Gelria (genus) (e.g., gut site); Gemella (genus) (e.g., gut site); Gemella sanguinis (species) (e.g., mouth site); Gemella sp.
  • SOR89 (species) (e.g., gut site); Lachnoanaerobaculum saburreum (species) (e.g., mouth site); Lachnospira (genus) (e.g., gut site); Lachnospira pectinoschiza (species) (e.g., gut site); Lachnospiraceae (family) (e.g., genital site); Lactobacillaceae (family) (e.g., gut site); Lactobacillus (genus) (e.g., gut site); Lactobacillus crispatus (species) (e.g., gut site); Lactobacillus rhamnosus (species) (e.g., gut site); Lactobacillus sp.
  • BL302 (species) (e.g., genital site); Lactobacillus sp. TAB-30 (species) (e.g., gut site); Lactonifactor (genus) (e.g., gut site); Lactonifactor longoviformis (species) (e.g., gut site); Leptotrichia (genus) (e.g., nose site); Leuconostocaceae (family) (e.g., gut site); Marvinbryantia (genus) (e.g., gut site); Megasphaera (genus) (e.g., gut site); Megasphaera genomosp.
  • Ci (species) (e.g., gut site); Methanobacteria (class) (e.g., gut site); Methanobacteriaceae (family) (e.g., gut site); Methanobacteriales (order) (e.g., gut site); Methanobrevibacter (genus) (e.g., gut site); Methanobrevibacter smithii (species) (e.g., gut site); Methylobacteriaceae (family) (e.g., nose site); Methylobacterium (genus) (e.g., nose site); Micrococcaceae (family) (e.g., nose site); Micrococcus (genus) (e.g., nose site); Micrococcus sp.
  • Methanobacteria class
  • Methanobacteriaceae family
  • Methanobacteriales order
  • Methanobrevibacter e.g., gut site
  • Methanobrevibacter smithii (species
  • WB18-01 (species) (e.g., nose site); Mollicutes (class) (e.g., gut site); Moraxella (genus) (e.g., nose site); Moraxella sp. WB19-16 (species) (e.g., nose site); Moraxellaceae (family) (e.g., nose site); Moryella (genus) (e.g., gut site); Murdochiella (genus) (e.g., genital site); Murdochiella asaccharolytica (species) (e.g., genital site); Mycobacteriaceae (family) (e.g., nose site); Mycobacterium (genus) (e.g., nose site); Neisseria (genus) (e.g., nose site); Neisseria elongata (species) (e.g., nose site); Neisseria macacae (species) (e.g., nose site); Neisseria mucos
  • DNF00840 (species) (e.g., gut site); Phascolarctobacterium (genus) (e.g., gut site); Phascolarctobacterium faecium (species) (e.g., gut site); Phascolarctobacterium succinatutens (species) (e.g., gut site); Phyllobacteriaceae (family) (e.g., gut site); Phyllobacterium (genus) (e.g., gut site); Porphyromonadaceae (family) (e.g., gut site); Porphyromonas catoniae (species) (e.g., nose site); Prevotella disiens (species) (e.g., gut site); Prevotella timonensis (species) (e.g., genital site); Prevotellaceae (family) (e.g., gut site); Propionibacteriaceae (family) (e.g., mouth site
  • MSP09A (species) (e.g., mouth site); Pseudoflavonifractor (genus) (e.g., gut site); Pseudoflavonifractor capillosus (species) (e.g., gut site); Pseudomonadaceae (family) (e.g., skin site); Pseudomonadales (order) (e.g., skin site); Pseudomonas (genus) (e.g., skin site); Ralstonia (genus) (e.g., skin site); Rhizobiaceae (family) (e.g., nose site); Rhizobiales (order) (e.g., gut site); Rhodobacteraceae (family) (e.g., nose site); Rhodobacterales (order) (e.g., nose site); Rhodospirillaceae (family) (e.g., gut site); Rhodospirillaceae (family) (
  • 11SE39 (species) (e.g., gut site); Roseburia sp. 499 (species) (e.g., gut site); Rothia dentocariosa (species) (e.g., nose site); Rothia mucilaginosa (species) (e.g., nose site); Ruminococcaceae (family) (e.g., gut site); Sarcina (genus) (e.g., gut site); Solanales (order) (e.g., nose site); Sphingomonadaceae (family) (e.g., nose site); Sphingomonadales (order) (e.g., nose site); Sphingomonas (genus) (e.g., nose site); Staphylococcus sp.
  • families e.g., gut site
  • Roseburia sp. 499 e.g., gut site
  • Rothia dentocariosa e.g., nose site
  • C-D-MA2 (species) (e.g., skin site); Streptococcaceae (family) (e.g., gut site); Streptococcus (genus) (e.g., mouth site); Streptococcus sp. BS35a (species) (e.g., gut site); Streptococcus sp. oral taxon G59 (species) (e.g., nose site); Streptococcus sp.
  • oral taxon G63 (species) (e.g., mouth site); Streptococcus thermophilus (species) (e.g., gut site); Streptophyta (phylum) (e.g., nose site); Subdoligranulum (genus) (e.g., gut site); Subdoligranulum variabile (species) (e.g., gut site); Sutterella (genus) (e.g., gut site); Sutterella wadsworthensis (species) (e.g., gut site); Sutterellaceae (family) (e.g., gut site); Synergistaceae (family) (e.g., gut site); Synergistales (order) (e.g., gut site); Synergistetes (phylum) (e.g., gut site); Synergistia (class) (e.g., gut site); Tenericutes (phylum) (e.g., gut site); Terrisporobacter (genus)
  • 20ii_Oral_VSA_D3 (species) (e.g., gut site); Veillonella sp. CM60 (species) (e.g., gut site); Veillonella sp. MSA12 (species) (e.g., nose site); Veillonellaceae (family) (e.g., gut site); Verrucomicrobia (phylum) (e.g., gut site); Verrucomicrobiaceae (family) (e.g., gut site); Verrucomicrobiae (class) (e.g., gut site); Verrucomicrobiales (order) (e.g., gut site); Xanthomonadales (order) (e.g., gut site).
  • performing a egg allergy condition characterization process can be based on microbiome features (e.g., microbiome function features) associated with one or more of (e.g., such as in relation to a corresponding sample site): Metabolism (KEGG2), Translation (KEGG2), Carbohydrate Metabolism (KEGG2), Cellular Processes and Signaling (KEGG2), Transport and Catabolism (KEGG2), Glycan Biosynthesis and Metabolism (KEGG2), Signaling Molecules and Interaction (KEGG2), Biosynthesis of Other Secondary Metabolites (KEGG2), Replication and Repair (KEGG2), Environmental Adaptation (KEGG2), Genetic Information Processing (KEGG2), Nucleotide Metabolism (KEGG2), Lipid Metabolism (KEGG2), Ribosome Biogenesis (KEGG3), D-Alanine metabolism (KEGG3), Ascorbate and aldarate metabolism (KEGG3), Amino acid metabolism (KEGG3), Translation proteins (KEGG3), Translation proteins (KEGG3)
  • KEGG_Pathways_Leve . 3 e.g., gut site
  • Huntington quote s disease KEGG_Pathways_Leve . 3
  • MAPK signaling pathway - yeast KEGG_Pathways_Leve . 3
  • Inositol phosphate metabolism KEGG_Pathways_Leve .
  • KEGG_Pathways_Leve _3) e.g., gut site
  • Amino acid metabolism KEGG_Pathways_Leve _3)
  • Others KEGG_Pathways_Level_3)
  • Biosynthesis and biodegradation of secondary metabolites KEGG_Pathways_Leve _3) (e.g., gut site); Ribosome Biogenesis (KEGG_Pathways_Leve _3) (e.g., gut site); Translation proteins (KEGG_Pathways_Leve _3) (e.g., gut site); D -Alanine metabolism (KEGG_Pathways_Leve _3) (e.g., gut site); Bisphenol degradation (KEGG_Pathways_Leve _3) (e.g., gut site); "Valine, leucine and isoleucine degradation” (KEGG_Pathways_Leve _3) (e.g., gut site); Oxidative phosphorylation (KEGG
  • KEGG_Pathways_Level_3) e.g., gut site
  • Lipopolysaccharide biosynthesis proteins KEGG_Pathways_Level_3) (e.g., gut site); Phosphatidylinositol signaling system (KEGG_Pathways_Level_3) (e.g., gut site); Pores ion channels (KEGG_Pathways_Level_3) (e.g., gut site); Phosphonate and phosphinate metabolism (KEGG_Pathways_Level_3) (e.g., gut site); Cell motility and secretion (KEGG_Pathways_Level_3) (e.g., gut site); Protein folding and associated processing (KEGG_Pathways_Level_3) (e.g., gut site); Glycosphingolipid biosynthesis - globo series (KEGG_Pathways_Level_3) (e.g., gut site); Lysosome (KEGG_Pathways_
  • KEGG_Pathways_Leve _3) e.g., gut site
  • Pertussis KEGG_Pathways_Level_3
  • Sporulation KEGG_Pathways_Level_3
  • Lipid metabolism e.g., Lipid metabolism
  • KEGG_Pathways_Leve _3) e.g., gut site
  • Toluene degradation KEGG_Pathways_Level_3
  • DNA repair and recombination proteins KEGG_Pathways_Level_3)
  • Ubiquinone and other terpenoid-quinone biosynthesis KEGG_Pathways_Level_3)
  • ABC transporters KEGG_Pathways_Level_3) (e.g., gut site
  • Ubiquitin system KEGG_Pathways_Level_3) (e.g., gut site), and/or other suitable function-related aspects.
  • Determining an allergy-related characterization of a user can include diagnosing a user with a egg allergy condition based upon one or more of the above microbiome features and/or other suitable features described herein, such as in an additional or alterative manner to typical methods of diagnosis.
  • features used in the egg allergy characterization process can include any other suitable features (e.g., features useful for diagnostics), and performing the egg allergy characterization process can be performed in any suitable manner.
  • Block S130 can include performing a dairy allergy condition characterization process (e.g., determining and/or applying a dairy allergy characterization model; etc.) for one or more users.
  • a characterization process e.g., of Block S130; based upon statistical analyses and/or other suitable approaches described herein; etc.
  • can identify a set of microbiome features e.g., microbiome composition features, microbiome function features, etc.
  • correlations e.g., positive correlations, negative correlations, correlations of greatest magnitude, etc.
  • performing a dairy allergy condition characterization process can facilitate identifications of one or more therapies operable to have a positive effect on the dairy allergy condition (e.g., based upon a random forest predictor algorithm trained with a training dataset derived from a subset of the population of subjects, and validated with a validation dataset derived from a subset of the population of subjects).
  • a dairy allergy condition can include an immune disorder characterized by an abnormal reaction of the immune system of the subject to any food containing or some of its derivatives, and diagnosis can be associated with laboratory analysis (e.g., skin-prick test, blood-samples analysis, IgE tests, etc.) and/or other suitable diagnostic procedures.
  • Microbiome features can be associated with one or more of the following taxons in relation to a sample site (e.g., dairy allergy condition correlations with microorganisms observed at a particular sample site): Bacteroidaceae (family) (e.g., genital site); Bacteroides (genus) (e.g., genital site); Corynebacteriaceae (family) (e.g., genital site); Corynebacterium (genus) (e.g., genital site); Betaproteobacteria (class) (e.g., genital site); Propionibacteriaceae (family) (e.g., genital site); Comamonadaceae (family) (e.g., genital site); Lachnospiraceae (family) (e.g., genital site); Lactobacillus sp.
  • Bacteroidaceae family
  • Bacteroides genus
  • BL302 (species) (e.g., genital site); Corynebacterium mastitidis (species) (e.g., genital site); Corynebacterium spheniscorum (species) (e.g., genital site); Finegoldia sp.
  • S8 F7 (species) (e.g., genital site); Corynebacterium glucuronolyticum (species) (e.g., genital site); Rhizobiales (order) (e.g., gut site); Neisseriaceae (family) (e.g., gut site); Neisseria (genus) (e.g., gut site); Enterobacteriaceae (family) (e.g., gut site); Actinobacillus (genus) (e.g., gut site); Haemophilus influenzae (species) (e.g., gut site); Pasteurella (genus) (e.g., gut site); Pasteurella pneumotropica (species) (e.g., gut site); Bacteroidaceae (family) (e.g., gut site); Bacteroides (genus) (e.g., gut site); Bacteroides vulgatus (species) (e.g., gut site); Fusobacter
  • AR29 (species) (e.g., gut site); Collinsella (genus) (e.g., gut site); Granulicatella (genus) (e.g., gut site); Roseburia intestinalis (species) (e.g., gut site); Bacteroidales (order) (e.g., gut site); Rikenellaceae (family) (e.g., gut site); Prevotellaceae (family) (e.g., gut site); Carnobacteriaceae (family) (e.g., gut site); Dorea (genus) (e.g., gut site); Bacteroidia (class) (e.g., gut site); Actinobacteria (phylum) (e.g., gut site); Neisseriales (order) (e.g., gut site); Faecalibacterium (genus) (e.g., gut site); Alistipes (genus) (e.g., gut site); Subdoligranulum (genus) (e.g
  • 11SE39 (species) (e.g., gut site); Selenomonadales (order) (e.g., gut site); Acidaminococcaceae (family) (e.g., gut site); Negativicutes (class) (e.g., gut site); Fusobacterium sp.
  • CM22 (species) (e.g., gut site); Fusicatenibacter saccharivorans (species) (e.g., gut site); Fusicatenibacter (genus) (e.g., gut site); Herbaspirillum (genus) (e.g., gut site); Herbaspirillum seropedicae (species) (e.g., gut site); Oxalobacteraceae (family) (e.g., gut site); Dorea longicatena (species) (e.g., gut site); Intestinibacter (genus) (e.g., gut site); Citrobacter (genus) (e.g., gut site); Kluyvera (genus) (e.g., gut site); Bacteroides fragilis (species) (e.g., gut site); Bacteroides thetaiotaomicron (species) (e.g., gut site); Bacteroides uniformis (species) (e.g., gut site
  • XB12B (species) (e.g., gut site); Barnesiella (genus) (e.g., gut site); Lactonifactor (genus) (e.g., gut site); Adlercreutzia equolifaciens (species) (e.g., gut site); Adlercreutzia (genus) (e.g., gut site); Oscillibacter (genus) (e.g., gut site); Gordonibacter pamelaeae (species) (e.g., gut site); Cloacibacillus (genus) (e.g., gut site); Cloacibacillus evryensis (species) (e.g., gut site); Acidaminococcus sp.
  • D21 (species) (e.g., gut site); Parasutterella (genus) (e.g., gut site); Bifidobacterium stercoris (species) (e.g., gut site); Hydrogenoanaerobacterium (genus) (e.g., gut site); Bifidobacterium kashiwanohense (species) (e.g., gut site); Gordonibacter (genus) (e.g., gut site); Anaerostipes sp. 3_2_56FAA (species) (e.g., gut site); Blautia sp. Ser8 (species) (e.g., gut site); Lactobacillus sp.
  • TAB-30 (species) (e.g., gut site); Eggerthella sp. HGAi (species) (e.g., gut site); Lactococcus sp. MH5-2 (species) (e.g., gut site); Flavonifractor (genus) (e.g., gut site); Enterococcus sp.
  • C6I11 (species) (e.g., gut site); Pseudoflavonifractor (genus) (e.g., gut site); Dielma fastidiosa (species) (e.g., gut site); Intestinimonas butyriciproducens (species) (e.g., gut site); Intestinimonas (genus) (e.g., gut site); Eisenbergiella (genus) (e.g., gut site); Eisenbergiella tayi (species) (e.g., gut site); Candidatus Soleaferrea (genus) (e.g., gut site); Dielma (genus) (e.g., gut site); Lactobacillus johnsonii (species) (e.g., gut site); Citrobacter amalonaticus (species) (e.g., gut site); Roseburia sp.
  • C13EG172 (species) (e.g., gut site); Lactobacillus delbrueckii (species) (e.g., gut site); Anaerosporobacter mobilis (species) (e.g., gut site); Enterococcus faecalis (species) (e.g., gut site); Acinetobacter (genus) (e.g., mouth site); Haemophilus influenzae (species) (e.g., nose site); Corynebacterium sp. (species) (e.g., skin site); Finegoldia (genus) (e.g., skin site); Aerococcaceae (family) (e.g., skin site); Finegoldia sp.
  • S9 AA1-5 (species) (e.g., skin site); Stenotrophomonas (genus) (e.g., skin site); Corynebacterium ulcerans (species) (e.g., skin site); Rhodospirillales (order) (e.g., skin site); Bacteroidaceae (family) (e.g., gut site); Bacteroides (genus) (e.g., gut site); Bacteroides vulgatus (species) (e.g., gut site); Parabacteroides distasonis (species) (e.g., gut site); Faecalibacterium prausnitzii (species) (e.g., gut site); Megasphaera (genus) (e.g., gut site); Bacteroidetes (phylum) (e.g., gut site); Gammaproteobacteria (class) (e.g., gut site); Firmicutes (phylum) (e.g., gut site);
  • AR20 (species) (e.g., gut site); Bacteroides sp. AR29 (species) (e.g., gut site); Collinsella (genus) (e.g., gut site); Flavobacteriia (class) (e.g., gut site); Erysipelotrichaceae (family) (e.g., gut site); Bacteroidales (order) (e.g., gut site); Rikenellaceae (family) (e.g., gut site); Porphyromonadaceae (family) (e.g., gut site); Clostridia (class) (e.g., gut site); Clostridiales (order) (e.g., gut site); Dorea (genus) (e.g., gut site); Desulfovibrionaceae (family) (e.g., gut site); Bacteroidia (class) (e.g., gut site); Flavobacteriales (order) (e.g., gut site); Desulfovi
  • 11SE39 (species) (e.g., gut site); Bacteroides sp. D22 (species) (e.g., gut site); Acidaminococcaceae (family) (e.g., gut site); Bacteroides sp. SLCi-38 (species) (e.g., gut site); Anaerostipes sp.
  • 5_i_63FAA (species) (e.g., gut site); Fusicatenibacter saccharivorans (species) (e.g., gut site); Fusicatenibacter (genus) (e.g., gut site); Lachnospira pectinoschiza (species) (e.g., gut site); Verrucomicrobiales (order) (e.g., gut site); Dorea longicatena (species) (e.g., gut site); Verrucomicrobiae (class) (e.g., gut site); Verrucomicrobiaceae (family) (e.g., gut site); Rhodospirillales (order) (e.g., gut site); Akkermansia (genus) (e.g., gut site); Corynebacterium myburgense (species) (e.g., gut site); Lactobacillus sp.
  • 7_i_47FAA (species) (e.g., gut site); Intestinibacter (genus) (e.g., gut site); Bacteroides fragilis (species) (e.g., gut site); Bacteroides thetaiotaomicron (species) (e.g., gut site); Bacteroides uniformis (species) (e.g., gut site); Streptococcus agalactiae (species) (e.g., gut site); Enterococcus (genus) (e.g., gut site); Lactococcus (genus) (e.g., gut site); Erysipelatoclostridium ramosum (species) (e.g., gut site); Odoribacter splanchnicus (species) (e.g., gut site); Bilophila (genus) (e.g., gut site); Sutterella wadsworthensis (species) (e.g., gut site);
  • XB12B (species) (e.g., gut site); Barnesiella (genus) (e.g., gut site); Howardella (genus) (e.g., gut site); Howardella ureilytica (species) (e.g., gut site); Lactonifactor (genus) (e.g., gut site); Adlercreutzia equolifaciens (species) (e.g., gut site); Adlercreutzia (genus) (e.g., gut site); Alistipes sp.
  • EBA6-25CI2 (species) (e.g., gut site); Oscillibacter (genus) (e.g., gut site); Gordonibacter pamelaeae (species) (e.g., gut site); Alistipes sp.
  • NML05A004 (species) (e.g., gut site); Barnesiella intestinihominis (species) (e.g., gut site); Blautia glucerasea (species) (e.g., gut site); Butyricimonas (genus) (e.g., gut site); Enterorhabdus (genus) (e.g., gut site); Robinsoniella (genus) (e.g., gut site); Bifidobacterium stercoris (species) (e.g., gut site); Gordonibacter (genus) (e.g., gut site); Slackia sp. NATTS (species) (e.g., gut site); Alistipes sp.
  • RMA 9912 (species) (e.g., gut site); Anaerosporobacter (genus) (e.g., gut site); Anaerostipes sp. 3_2_56FAA (species) (e.g., gut site); Blautia sp. Ser8 (species) (e.g., gut site); Bilophila sp. 4_i_30 (species) (e.g., gut site); Eggerthella sp. HGAi (species) (e.g., gut site); Lactococcus sp. MH5-2 (species) (e.g., gut site); Enterococcus sp.
  • SI-4 (species) (e.g., gut site); Enterobacter sp. BS2-1 (species) (e.g., gut site); Pseudoflavonifractor (genus) (e.g., gut site); Dielma fastidiosa (species) (e.g., gut site); Blautia sp. YHC-4 (species) (e.g., gut site); Intestinimonas (genus) (e.g., gut site); Eisenbergiella (genus) (e.g., gut site); Eisenbergiella tayi (species) (e.g., gut site); Butyricimonas sp.
  • JCM 18677 (species) (e.g., gut site); Dielma (genus) (e.g., gut site); Terrisporobacter (genus) (e.g., gut site); Bifidobacterium adolescentis (species) (e.g., gut site).
  • performing a dairy allergy condition characterization process can be based on microbiome features (e.g., microbiome function features) associated with one or more of (e.g., such as in relation to a corresponding sample site): Nucleotide Metabolism (KEGG_Pathways_Level_2) (e.g., gut site); Biosynthesis of Other Secondary Metabolites (KEGG_Pathways_Level_2) (e.g., gut site); Excretory System (KEGG_Pathways_Level_2) (e.g., gut site); Neurodegenerative Diseases (KEGG_Pathways_Level_2) (e.g., gut site); Metabolism (KEGG_Pathways_Level_2) (e.g., gut site); Signaling Molecules and Interaction (KEGG_Pathways_Level_2) (e.g., gut site); Glycan Biosynthesis and Metabolism (KEGG_Pathways_Level_2) (e.g., gut site); Glycan Biosynthesis
  • KEGG_Pathways_Level_2) e.g., gut site
  • Genetic Information Processing KEGG_Pathways_Level_2
  • Environmental Adaptation KEGG_Pathways_Level_2)
  • Bacterial chemotaxis e.g., gut site
  • Cell cycle - Caulobacter KEGG_Pathways_Level_3
  • KEGG_Pathways_Level_3) e gut site
  • Sulfur metabolism KEGG_Pathways_Level_3) (e.g. gut site); Nucleotide excision repair (KEGG_Pathways_Level_3) (e gut site); Biotin metabolism (KEGG_Pathways_Level_3) (e.g gut site); Peptidoglycan biosynthesis (KEGG_Pathways_Level_3) (e.g. gut site); Aminoacyl-tRNA biosynthesis (KEGG_Pathways_Level_3) (e.g., gut site); Ascorbate and aldarate metabolism
  • KEGG_Pathways_Level_3) e.g., gut site
  • RNA degradation e.g., gut site
  • Primary bile acid biosynthesis e.g., gut site
  • MAPK signaling pathway - yeast KEGG_Pathways_Level_3) (e.g., gut site)
  • Inositol phosphate metabolism KEGG_Pathways_Level_3) (e.g., gut site
  • Amino acid metabolism KEGG_Pathways_Level_3) (e.g., gut site); Glycosyltransferases
  • KEGG_Pathways_Level_3) e.g., gut site
  • Others KEGG_Pathways_Level_3) (e.g., gut site); Lipopolysaccharide biosynthesis proteins (KEGG_Pathways_Level_3) (e.g., gut site); Phosphatidylinositol signaling system (KEGG_Pathways_Level_3) (e.g., gut site); Pores ion channels (KEGG_Pathways_Level_3) (e.g., gut site); Biosynthesis and biodegradation of secondary metabolites (KEGG_Pathways_Level_3) (e.g., gut site); Phosphonate and phosphinate metabolism (KEGG_Pathways_Level_3) (e.g., gut site); Ribosome Biogenesis (KEGG_Pathways_Level_3) (e.g., gut site); Benzoate degradation (KEGG_Pathways_Level_3) (e.g
  • KEGG_ _Pathways_ _Level_ .3 e.g., gut site
  • KEGG_ _Pathways_ _Level_ _3) e.g., gut site
  • KEGG_ _Pathways_ _Level_ _3) e.g., gut site
  • KEGG_ _Pathways_ _Level_ _3) e.g., gut site
  • Others KEGG_Pathways_Level_3 (e.g., gut site)
  • KEGG_Pathways_Level_3) e.g., gut site
  • Fructose and man(e.g., nose site) metabolism KEGG_Pathways_Level_3) (e.g., gut site); Terpenoid backbone biosynthesis (KEGG_Pathways_Level_3) (e.g., gut site); Penicillin and cephalosporin biosynthesis (KEGG_Pathways_Level_3) (e.g., gut site); Polycyclic aromatic hydrocarbon degradation (KEGG_Pathways_Level_3) (e.g., gut site); Ribosome (KEGG_Pathways_Level_3) (e.g., gut site); Aminobenzoate degradation (KEGG_Pathways_Level_3) (e.g., gut site); Glyoxylate and dicarboxylate metabolism (KEGG_Pathways_Level_3) (e.g., gut site); Mismatch repair (KEGG_Pathways_Level_3) (e.g.,
  • Determining an allergy-related characterization of a user can include diagnosing a user with a dairy allergy condition based upon one or more of the above microbiome features and/or other suitable features described herein, such as in an additional or alterative manner to typical methods of diagnosis.
  • features used in the dairy allergy characterization process can include any other suitable features (e.g., features useful for diagnostics), and performing the dairy allergy characterization process can be performed in any suitable manner.
  • Block S140 recites: generating a therapy model configured to modulate microorganism distributions in subjects characterized according to the characterization process.
  • Block S140 functions to identify or predict therapies (e.g., probiotic-based therapies, phage-based therapies, small molecule-based therapies, etc.) that can shift a subject's microbiome composition and/or functional features toward a desired equilibrium state in promotion of the subject's health.
  • therapies e.g., probiotic-based therapies, phage-based therapies, small molecule-based therapies, etc.
  • the therapies can be selected from therapies including one or more of: probiotic therapies, phage-based therapies, small molecule-based therapies, cognititive/behavioral therapies, physical rehabilitation therapies, clinical therapies, medication-based therapies, diet-related therapies, and/or any other suitable therapy designed to operate in any other suitable manner in promoting a user's health.
  • a bacteriophage-based therapy one or more populations (e.g., in terms of colony forming units) of bacteriophages specific to a certain bacteria (or other microorganism) represented in the subject can be used to down-regulate or otherwise eliminate populations of the certain bacteria.
  • bacteriophage-based therapies can be used to reduce the size(s) of the undesired population(s) of bacteria represented in the subject.
  • bacteriophage-based therapies can be used to increase the relative abundances of bacterial populations not targeted by the bacteriophage(s) used.
  • candidate therapies of the therapy model can perform one or more of: blocking pathogen entry into an epithelial cell by providing a physical barrier (e.g., by way of colonization resistance), inducing formation of a mucous barrier by stimulation of goblet cells, enhance integrity of apical tight junctions between epithelial cells of a subject (e.g., by stimulating up regulation of zona-occludens 1, by preventing tight junction protein redistribution), producing antimicrobial factors, stimulating production of anti-inflammatory cytokines (e.g., by signaling of dendritic cells and induction of regulatory T-cells), triggering an immune response, and performing any other suitable function that adjusts a subject's microbiome away from a state of dysbiosis.
  • a physical barrier e.g., by way of colonization resistance
  • inducing formation of a mucous barrier by stimulation of goblet cells e.g., by stimulating up regulation of zona-occludens 1, by preventing tight junction protein redistribution
  • therapies can include medical-device based therapies (e.g., allergen detection devices; allergen medication provision devices; etc.).
  • the therapy model is preferably based upon data from a large population of subjects, which can include the population of subjects from which the microbiome diversity datasets are derived in Block S110, where microbiome composition and/ or functional features or states of health, prior exposure to and post exposure to a variety of therapeutic measures, are well characterized.
  • data can be used to train and validate the therapy provision model, in identifying therapeutic measures that provide desired outcomes for subjects based upon different microbiome characterizations.
  • support vector machines as a supervised machine learning algorithm, can be used to generate the therapy provision model.
  • any other suitable machine learning algorithm described above can facilitate generation of the therapy provision model.
  • variations of the method 100 can additionally or alternatively utilize any other suitable algorithms in performing the characterization process.
  • the algorithm(s) can be characterized by a learning style including any one or more of: supervised learning (e.g., using logistic regression, using back propagation neural networks), unsupervised learning (e.g., using an Apriori algorithm, using K-means clustering), semi-supervised learning, reinforcement learning (e.g., using a Q-learning algorithm, using temporal difference learning), and any other suitable learning style.
  • supervised learning e.g., using logistic regression, using back propagation neural networks
  • unsupervised learning e.g., using an Apriori algorithm, using K-means clustering
  • semi-supervised learning e.g., using a Q-learning algorithm, using temporal difference learning
  • reinforcement learning e.g., using a Q-learning algorithm, using temporal difference learning
  • the algorithm(s) can implement any one or more of: a regression algorithm (e.g., ordinary least squares, logistic regression, stepwise regression, multivariate adaptive regression splines, locally estimated scatterplot smoothing, etc.), an instance-based method (e.g., k-nearest neighbor, learning vector quantization, self- organizing map, etc.), a regularization method (e.g., ridge regression, least absolute shrinkage and selection operator, elastic net, etc.), a decision tree learning method (e.g., classification and regression tree, iterative dichotomiser 3, C4.5, chi-squared automatic interaction detection, decision stump, random forest, multivariate adaptive regression splines, gradient boosting machines, etc.), a Bayesian method (e.g., naive Bayes, averaged one-dependence estimators, Bayesian belief network, etc.), a kernel method (e.g., a support vector machine, a radial basis function, a linear discriminate analysis, etc.), a kernel
  • the therapy model can be derived in relation to identification of a "normal" or baseline microbiome composition and/or functional features, as assessed from subjects of a population of subjects who are identified to be in good health.
  • therapies that modulate microbiome compositions and/ or functional features toward those of subjects in good health can be generated in Block S140.
  • Block S140 can thus include identification of one or more baseline microbiome compositions and/or functional features (e.g., one baseline microbiome for each of a set of demographics), and potential therapy formulations and therapy regimens that can shift microbiomes of subjects who are in a state of dysbiosis toward one of the identified baseline microbiome compositions and/ or functional features.
  • the therapy model can, however, be generated and/or refined in any other suitable manner.
  • Microorganism compositions associated with probiotic therapies associated with the therapy model preferably include microorganisms that are culturable (e.g., able to be expanded to provide a scalable therapy) and non-lethal (e.g., non-lethal in their desired therapeutic dosages).
  • microorganism compositions can include a single type of microorganism that has an acute or moderated effect upon a subject's microbiome.
  • microorganism compositions can include balanced combinations of multiple types of microorganisms that are configured to cooperate with each other in driving a subject's microbiome toward a desired state.
  • a combination of multiple types of bacteria in a probiotic therapy can include a first bacteria type that generates products that are used by a second bacteria type that has a strong effect in positively affecting a subject's microbiome.
  • a combination of multiple types of bacteria in a probiotic therapy can include several bacteria types that produce proteins with the same functions that positively affect a subject's microbiome.
  • Probiotic compositions can be naturally or synthetically derived.
  • a probiotic composition can be naturally derived from fecal matter or other biological matter (e.g., of one or more subjects having a baseline microbiome composition and/or functional features, as identified using the characterization process and the therapy model).
  • probiotic compositions can be synthetically derived (e.g., derived using a benchtop method) based upon a baseline microbiome composition and/or functional features, as identified using the characterization process and the therapy model.
  • microorganism agents that can be used in probiotic therapies can include one or more of: yeast (e.g., Saccharomyces boulardii), gram-negative bacteria (e.g., E.
  • coli Nissle gram-positive bacteria
  • gram-positive bacteria e.g., Bifidobacteria bifidum, Bifidobacteria infantis, Lactobacillus rhamnosus, Lactococcus lactis, Lactobacillus plantarum, Lactobacillus acidophilus, Lactobacillus casei, Bacillus polyfermenticus, etc.
  • any other suitable type of microorganism agent e.g., Bifidobacteria bifidum, Bifidobacteria infantis, Lactobacillus rhamnosus, Lactococcus lactis, Lactobacillus plantarum, Lactobacillus acidophilus, Lactobacillus casei, Bacillus polyfermenticus, etc.
  • a probiotic therapy can include a combination of one or more of: Blautia luti, Collinsella aerofaciens, Flavonifr actor plautii, Faecalibacterium prausnitzii, Dorea formicigenerans, Subdoligranulum variabile, Barnesiella intestinihominis, Bacteroides thetaiotaomicron, Roseburia inulinivorans, Parasutterella excrementihominis, Bifidobacterium longum, Erysipelatoclostridium ramosum, Bacteroides fragilis, Bacteroides vulgatus, Bacteroides caccae, Blautia sp.
  • YHC-4 Alistipes putredinis and/or any other suitable microorganisms (e.g., associated with microbiome features described in relation to the wheat allergy condition) and/or phage vector (e.g., bacteriophage, virus, etc.).
  • suitable microorganisms e.g., associated with microbiome features described in relation to the wheat allergy condition
  • phage vector e.g., bacteriophage, virus, etc.
  • a probiotic therapy can include a combination of one or more of: Blautia luti, Collinsella aerofaciens, Parabacteroides distasonis, Flavonifr actor plautii, Bacteroides fragilis, Dorea formicigenerans, Roseburia inulinivorans, and/or any other suitable microorganisms (e.g., associated with microbiome features described in relation to the treenut condition) and/or phage vector (e.g., bacteriophage, virus, etc.).
  • a probiotic therapy can include a combination of one or more of: Parabacteroides distasonis and/or any other suitable microorganisms (e.g., associated with microbiome features described in relation to the shellfish allergy condition) and/or phage vector (e.g., bacteriophage, virus, etc.).
  • a probiotic therapy can include a combination of one or more of: Blautia luti, Collinsella aerofaciens, Dorea formicigenerans, Flavonifr actor plautii, Subdoligranulum variabile, Faecalibacterium prausnitzii, Barnesiella intestinihominis, Roseburia inulinivorans, Blautia sp.
  • YHC-4 Bacteroides caccae, Erysipelatoclostridium ramosum, Bacteroides thetaiotaomicron, Odoribacter splanchnicus, Bacteroides fragilis, Parabacteroides distasonis, and/or any other suitable microorganisms (e.g., associated with microbiome features described in relation to the soy allergy condition) and/or phage vector (e.g., bacteriophage, virus, etc.).
  • suitable microorganisms e.g., associated with microbiome features described in relation to the soy allergy condition
  • phage vector e.g., bacteriophage, virus, etc.
  • a probiotic therapy can include a combination of one or more of: Flavonifr actor plautii, Blautia luti, Collinsella aerofaciens, Dorea formicigenerans, Barnesiella intestinihominis, and/or any other suitable microorganisms (e.g., associated with microbiome features described in relation to the peanut allergy condition) and/or phage vector (e.g., bacteriophage, virus, etc.).
  • a probiotic therapy can include a combination of one or more of: Blautia luti, Collinsella aerofaciens, Subdoligranulum variabile, Flavonifr actor plautii, Faecalibacterium prausnitzii, Alistipes putredinis, Roseburia inulinivorans, Bacteroides caccae, Barnesiella intestinihominis, Parabacteroides distasonis, Odoribacter splanchnicus, Dorea formicigenerans, and/or any other suitable microorganisms (e.g., associated with microbiome features described in relation to the egg allergy condition) and/or phage vector (e.g., bacteriophage, virus, etc.).
  • Probiotics and/or other suitable consumables can be provided at dosages of 0.1 million to 10 billion CFUs (and/or other suitable dosages), such as determined from a therapy model that predicts positive adjustment of a patient's microbiome in response to the therapy.
  • a subject can be instructed to ingest capsules including the probiotic formulation according to a regimen tailored to one or more of his/her: physiology (e.g., body mass index, weight, height), demographics (e.g., gender, age), severity of dysbiosis, sensitivity to medications, and any other suitable factor.
  • associated- microorganisms e.g., corresponding to correlated microbiome composition features
  • the method 100 can additionally or alternatively include Block S150, which recites: processing one or more biological samples from a user (e.g., subject).
  • Block S150 can function to facilitate generation of a microbiome dataset for the subject that can be used to derive inputs for the characterization process (e.g., for generating an allergy- related characterization for the user, etc.).
  • Block S150 can include receiving, processing, and/or analyzing one or more biological samples from one or more users (e.g., multiple biological samples for the same user over time, different biological samples for different users, etc.).
  • the biological sample is preferably generated from the subject and/or an environment of the subject in a non-invasive manner.
  • noninvasive manners of sample reception can use any one or more of: a permeable substrate (e.g., a swab configured to wipe a region of a subject's body, toilet paper, a sponge, etc.), a non-permeable substrate (e.g., a slide, tape, etc.) a container (e.g., vial, tube, bag, etc.) configured to receive a sample from a region of a subject's body, and any other suitable sample-reception element.
  • the biological sample can be collected from one or more of the subject's nose, skin, genitals, mouth, and gut in a non-invasive manner (e.g., using a swab and a vial).
  • the biological sample can additionally or alternatively be received in a semi-invasive manner or an invasive manner.
  • invasive manners of sample reception can use any one or more of: a needle, a syringe, a biopsy element, a lance, and any other suitable instrument for collection of a sample in a semi-invasive or invasive manner.
  • samples can include blood samples, plasma/serum samples (e.g., to enable extraction of cell-free DNA), and tissue samples.
  • the biological sample can be taken from the body of the subject without facilitation by another entity (e.g., a caretaker associated with a subject, a health care professional, an automated or semi-automated sample collection apparatus, etc.), or can alternatively be taken from the body of the subject with the assistance of another entity.
  • a sample-provision kit can be provided to the subject.
  • the kit can include one or more swabs for sample acquisition, one or more containers configured to receive the swab(s) for storage, instructions for sample provision and setup of a user account, elements configured to associate the sample(s) with the subject (e.g., barcode identifiers, tags, etc.), and a receptacle that allows the sample(s) from the subject to be delivered to a sample processing operation (e.g., by a mail delivery system).
  • a sample processing operation e.g., by a mail delivery system.
  • the biological sample is extracted from the subject with the help of another entity
  • one or more samples can be collected in a clinical or research setting from the subject (e.g., during a clinical appointment). The biological sample can, however, be received from the subject in any other suitable manner.
  • processing and analyzing the biological sample (e.g., to generate a user microbiome dataset; etc.) from the subject is preferably performed in a manner similar to that of one of the embodiments, variations, and/or examples of sample reception described in relation to Block Siio above, and/or any other suitable portions of the method 100.
  • reception and processing of the biological sample in Block S150 can be performed for the subject using similar processes as those for receiving and processing biological samples used to generate the characterization process and/or the therapy model of the method 100, in order to provide consistency of process.
  • biological sample reception and processing in Block S150 can alternatively be performed in any other suitable manner.
  • the method 100 can additionally or alternatively include Block S160, which recites: determining, with the characterization process, an allergy-related characterization for the user based upon processing a microbiome dataset (e.g., user microorganism sequence dataset, microbiome composition dataset, microbiome functional diversity dataset, etc.) derived from the biological sample of the user.
  • Block S160 can function to characterize one or more allergy-related conditions for a user, such as through extracting features from microbiome-derived data of the subject, and using the features as inputs into an embodiment, variation, or example of the characterization process described in Block S130 above.
  • Block S160 can include generating an allergy-related characterization for the user based on user microbiome features and an allergy-related condition characterization model (e.g., generated in Block S130). Allergy-related characterizations can be for any number and/ or combination of allergy-related conditions (e.g., a combination of allergy-related conditions, a single allergy-related condition, and/ or other suitable allergy-related conditions; etc.).
  • Allergy-related characterizations can include one or more of: diagnoses (e.g., presence or absence of an allergy-related condition; etc.); allergy trigger profiles, risk (e.g., risk scores for developing and/or the presence of an allergy-related condition; information regarding allergy-related characterizations (e.g., symptoms, signs, triggers, associated conditions, etc.); comparisons (e.g., comparisons with other subgroups, populations, users, historic health statuses of the user such as historic microbiome compositions and/ or functional diversities; comparisons associated with allergy-related conditions; etc.), and/or any other suitable allergy-related data.
  • diagnoses e.g., presence or absence of an allergy-related condition; etc.
  • allergy trigger profiles e.g., risk scores for developing and/or the presence of an allergy-related condition
  • information regarding allergy-related characterizations e.g., symptoms, signs, triggers, associated conditions, etc.
  • comparisons e.g., comparisons with other subgroups, populations, users
  • allergy-related characterization can include one or more allergy-related (e.g., wheat allergy) trigger profiles for the user, where the trigger profile can describe allergy triggers (e.g., conditions correlated with allergy- related symptoms; conditions indicating future allergy-related conditions; causes; presence of allergens; etc.) associated with the user (e.g., known to affect the user; predicted to affect the user, such as based on microbiome features, supplementary data, etc.).
  • allergy triggers e.g., conditions correlated with allergy- related symptoms; conditions indicating future allergy-related conditions; causes; presence of allergens; etc.
  • Allergy triggers can include any one or more of: dietary triggers (e.g., wheat, egg, treenut, peanut, soy, shellfish, caffeine, alcohol, food additives, salty foods, dietary habits, missing meals, too many meals, etc.); hormonal changes; stress; sensory stimuli (e.g., lights, sounds, smells, etc.); sleep triggers (e.g., sleep deprivation, sleep abundance, etc.); physical activity (e.g., excess physical activity, etc.); environmental triggers (e.g., weather, barometric pressure, etc.); medication-based triggers; animal-based triggers and/or any other suitable triggers.
  • dietary triggers e.g., wheat, egg, treenut, peanut, soy, shellfish, caffeine, alcohol, food additives, salty foods, dietary habits, missing meals, too many meals, etc.
  • hormonal changes stress
  • sensory stimuli e.g., lights, sounds, smells, etc.
  • sleep triggers e.g., sleep de
  • Allergy triggers and/or other allergy-related conditions can be associated with (e.g., correlated with, etc.) one or more of: family history, age, gender, weight, height, other demographic characteristics, and/or any other suitable supplementary data.
  • generating an allergy-related characterization can include generating an allergy trigger profile for the user based on user microbiome features (e.g., and an allergy-related condition characterization model), and promoting (e.g., providing) a therapy operable to reduce allergy triggers indicated by the allergy trigger profile for the user.
  • the method 100 can include detecting allergy triggers (e.g., allergy triggers) for a user based on a corresponding allergy-related trigger profile (e.g., for the user, for another user, etc.).
  • the method 100 can include: detecting an allergy trigger based on the allergy trigger profile and user supplementary data including at least one of motion sensor data and location sensor data (e.g., indicating physical activity behaviors; user locations; mobility behaviors; other behaviors correlated with allergy triggers; etc.) collected from a mobile computing device (e.g., smartphone, smart watch, tablet, laptop, etc.) associated with the user; and promoting a therapy in response to detecting the allergy trigger (and/or other suitable allergy triggers; etc.).
  • a mobile computing device e.g., smartphone, smart watch, tablet, laptop, etc.
  • detecting allergy triggers in relation to an allergy-related trigger profile can be based on any one or more of: microbiome features (e.g., a microbiome composition indicating a high risk of allergy symptoms in response to certain allergy triggers; a microbiome functional diversity indicating a high risk of an allergy-related symptom during a future time period, such as within the next 24 hours, etc.), supplementary features (e.g., historic medical data for the user, sensor data, nutrition supplementary data, sleep data such as derived through sensor data, etc.), and/or any other suitable features.
  • microbiome features e.g., a microbiome composition indicating a high risk of allergy symptoms in response to certain allergy triggers; a microbiome functional diversity indicating a high risk of an allergy-related symptom during a future time period, such as within the next 24 hours, etc.
  • supplementary features e.g., historic medical data for the user, sensor data, nutrition supplementary data, sleep data such as derived through sensor data, etc.
  • an allergy-related characterization can include a microbiome diversity score (e.g., in relation to microbiome composition, function, etc.) associated with (e.g., correlated with; negatively correlated with; positively correlated with; etc.) a microbiome diversity score correlated with the allergy-related condition.
  • the method 100 can include promoting a nutrition-related therapy (e.g., probiotics; dietary regimen modifications; etc.) operable to improve the microbiome diversity score for improving a state of the allergy-related condition, such as based on an allergy-related characterization (e.g., including the microbiome diversity score for the user) and/or nutrition-related supplementary data collected from the user.
  • a nutrition-related therapy e.g., probiotics; dietary regimen modifications; etc.
  • the allergy-related characterization can include microbiome diversity scores over time (e.g., calculated for a plurality of biological samples of the user collected over time), comparisons to microbiome diversity scores for other users, and/or any other suitable type of microbiome diversity score.
  • processing microbiome diversity scores e.g., determining microbiome diversity scores; using microbiome diversity scores to determine and/ or provide therapies; etc.
  • processing microbiome diversity scores can be performed in any suitable manner.
  • Determining an allergy-related characterization in Block S160 preferably includes identifying features and/or combinations of features associated with the microbiome composition and/or functional features of the subject, inputting the features into the characterization process, and receiving an output that characterizes the subject as belonging to one or more of: a behavioral group, a gender group, a dietary group, a disease- state group, and any other suitable group capable of being identified by the characterization process.
  • Block S160 can additionally or alternatively include generation of and/ or output of a confidence metric associated with the characterization of the subject.
  • a confidence metric can be derived from the number of features used to generate the characterization, relative weights or rankings of features used to generate the characterization, measures of bias in the characterization process, and/or any other suitable parameter associated with aspects of the characterization process.
  • leveraging user microbiome features can be performed in any suitable manner to generate any suitable allergy-related characterizations.
  • features extracted from the microbiome dataset of the subject can be supplemented with supplementary features (e.g., extracted from supplementary data collected for the user; such as survey-derived features, medical history-derived features, sensor data, etc.), where such data, the user microbiome data, and/or other suitable data can be used to further refme the characterization process of Block S130, Block S160, and/or other suitable portions of the method 100.
  • supplementary features e.g., extracted from supplementary data collected for the user; such as survey-derived features, medical history-derived features, sensor data, etc.
  • Determining an allergy-related characterization preferably includes extracting and applying user microbiome features (e.g., user microbiome composition diversity features; user microbiome functional diversity features; etc.) for the user (e.g., based on a user microbiome dataset), characterization models, and/or other suitable components, such as by employing approaches described in Block S130, and/or by employing any suitable approaches described herein.
  • user microbiome features e.g., user microbiome composition diversity features; user microbiome functional diversity features; etc.
  • Block S160 can include presenting allergy-related characterizations (e.g., information extracted from the characterizations, etc.), such as an a web interface, a mobile application, and/or any other suitable interface, but presentation of allergy-related information can be performed in any suitable manner.
  • allergy-related characterizations e.g., information extracted from the characterizations, etc.
  • the microbiome dataset of the subject can additionally or alternatively be used in any other suitable manner to enhance the models of the method 100, and Block S160 can be performed in any suitable manner.
  • Block S170 can additionally or alternatively include Block S170, which recites: promoting (e.g., providing, facilitating provision of, etc.) a therapy for the allergy-related condition to the user (e.g., based upon the allergy-related characterization and/ or a therapy model).
  • Block S170 can function to recommend or provide a personalized therapy to the subject, in order to shift the microbiome composition and/or functional diversity of a user toward a desired equilibrium state.
  • Block S170 can include provision of a customized therapy to the subject according to their microbiome composition and functional features, as shown in FIGURE 5, where the customized therapy is a formulation of microorganisms configured to correct dysbiosis characteristic of subjects having the identified characterization.
  • outputs of Block S140 can be used to directly promote a customized therapy formulation and regimen (e.g., dosage, usage instructions) to the subject based upon a trained therapy model.
  • therapy provision can include recommendation of available therapeutic measures configured to shift microbiome composition and/ or functional features toward a desired state.
  • therapies can include any one or more of: consumables, topical therapies (e.g., lotions, ointments, antiseptics, etc.), medication (e.g., allergy medications, antihistamines, antibiotics, medication sprays such as nasal sprays, anticholinergic medication, steroid medication, eye drops, leukotriene inhibitors, mast cell inhibitors, allergy shots, medications associated with any suitable medication type and/or dosage, etc.), bacteriophages, environmental treatments (e.g., reducing and/or preventing environmental triggers, such as allergy-proofing a living space; dehumidifiers; pillow covers; dust reducers; acupuncture; etc.), behavioral modification (e.g., stress-reduction therapies, physical activity-related therapies, etc.), diagnostic procedures, other medical- related procedures, and/or any other suitable therapies associated with allergy-related conditions.
  • topical therapies e.g., lotions, ointments, antiseptics, etc.
  • medication e.g., allergy medications
  • Consumables can include any one or more of: food and/or beverage items (e.g., probiotic and/or prebiotic food and/or beverage items, etc.), nutritional supplements (e.g., vitamins, minerals, fiber, fatty acids, amino acids, prebiotics, probiotics, etc.), consumable medications, and/or any other suitable therapeutic measure.
  • food and/or beverage items e.g., probiotic and/or prebiotic food and/or beverage items, etc.
  • nutritional supplements e.g., vitamins, minerals, fiber, fatty acids, amino acids, prebiotics, probiotics, etc.
  • consumable medications e.g., a combination of commercially available probiotic supplements can include a suitable probiotic therapy for the subject according to an output of the therapy model.
  • promoting a therapy can include providing, based on the food-related allergy characterization, a therapy enabling selective modulation of a microbiome of the user in relation to at least one of a population size of a desired taxon and a desired microbiome function, wherein the therapy is associated with improving a state of an allergy-related condition.
  • the method 100 can include determining an allergy risk for the user for the allergy-related condition based on a allergy-related characterization model (e.g., and/or user microbiome features); determining an allergy-related trigger for the allergy-related condition based on the allergy risk; and promoting the therapy to the user based on the allergy-related trigger.
  • promoting a therapy can include promoting a diagnostic procedure (e.g., for facilitating detection of allergy-related conditions, which can motivate subsequent promotion of other therapies, such as for modulation of a user microbiome for improving a user health state associated with one or more allergy-related conditions; etc.).
  • Diagnostic procedures can include any one or more of: skin prick testing, patch testing, blood testing, challenge testing, performing portions of the method 100, and/or any other suitable procedures for facilitating the detecting (e.g., observing, predicting, etc.) of allergy-related conditions.
  • diagnostic device-related information and/or other suitable diagnostic information can be processed as part of a supplementary dataset (e.g., in relation to Block S120, where such data can be used in determining and/or applying characterization models, therapy models, and/or other suitable models; etc.), and/or collected, used, and/or otherwise processed in relation to any suitable portions of the method 100 (e.g., administering diagnostic procedures for users for monitoring therapy efficacy in relation to Block S180; etc.)
  • Block S170 can include promoting a bacteriophage- based therapy.
  • one or more populations (e.g., in terms of colony forming units) of bacteriophages specific to a certain bacteria (or other microorganism) represented in the subject can be used to down-regulate or otherwise eliminate populations of the certain bacteria.
  • bacteriophage-based therapies can be used to reduce the size(s) of the undesired population(s) of bacteria represented in the subject.
  • bacteriophage-based therapies can be used to increase the relative abundances of bacterial populations not targeted by the bacteriophage(s) used.
  • therapy provision in Block S170 can include provision of notifications to a subject regarding the recommended therapy, other forms of therapy, allergy-related characterizations, and/or other suitable allergy-related data.
  • providing a therapy to a user can include providing therapy recommendations (e.g., substantially concurrently with providing information derived from an allergy-related characterization for a user; etc.) and/or other suitable therapy-related information (e.g., therapy efficacy; comparisons to other individual users, subgroups of users, and/or populations of users; therapy comparisons; historic therapies and/or associated therapy- related information; etc.), such as through presenting notifications at a web interface (e.g., through a user account associated with and identifying a user; etc.).
  • Notifications can be provided to a subject by way of an electronic device (e.g., personal computer, mobile device, tablet, wearable, head-mounted wearable computing device, wrist-mounted wearable computing device, etc.) that executes an application, web interface, and/or messaging client configured for notification provision.
  • a web interface of a personal computer or laptop associated with a subject can provide access, by the subject, to a user account of the subject, where the user account includes information regarding the user's allergy-related characterization, detailed characterization of aspects of the user's microbiome (e.g., in relation to correlations with allergy-related conditions; etc.), and/or notifications regarding suggested therapeutic measures (e.g., generated in Blocks S140 and/or S170, etc.).
  • an application executing at a personal electronic device can be configured to provide notifications (e.g., at a display, haptically, in an auditory manner, etc.) regarding therapy suggestions generated by the therapy model of Block S170.
  • Notifications and/or probiotic therapies can additionally or alternatively be provided directly through an entity associated with a subject (e.g., a caretaker, a spouse, a significant other, a healthcare professional, etc.).
  • notifications can additionally or alternatively be provided to an entity (e.g., healthcare professional) associated with a subject, such as where the entity is able to facilitate provision of the therapy (e.g., by way of prescription, by way of conducting a therapeutic session, through a digital telemedicine session using optical and/or audio sensors of a computing device, etc.).
  • entity e.g., healthcare professional
  • providing notifications can be performed in response to and/ or in any suitable temporal relation to a trigger condition (e.g., a trigger for an allergy-related condition).
  • the method 100 can include: determining a risk for an allergy-related condition (and/or other suitable allergy-related characterizations; etc.) based on one or more user microbiome datasets; detecting an allergy-related trigger (e.g., predicting the historic, current, and/or future presence of an allergy-related trigger, etc.) based on the risk for the allergy-related condition (and/or supplementary data such as GPS location sensor data indicating a location correlated with the presence of allergy-related triggers, other supplementary sensor data, etc.); and providing an allergy-related notification (e.g., a warning to the user; recommendations; etc.) and/or other suitable therapies (e.g., contacting emergency services; contacting an individual associated with the user; facilitating application of therapeutics by appropriate medical devices; etc.) to the user in response to detecting the allergy-related trigger. Promoting allergy-related notifications and/ or other suitable therapies can, however, be performed in any suitable manner.
  • an allergy-related trigger e.g., predicting the historic, current, and
  • Block S180 which recites: monitoring effectiveness of the therapy for the subject, based upon processing biological samples, to assess microbiome composition and/or functional features for the subject at a set of time points associated with the probiotic therapy.
  • Block S180 can function to gather additional data regarding positive effects, negative effects, and/or lack of effectiveness of a probiotic therapy suggested by the therapy model for subjects of a given characterization.
  • Monitoring of a subject during the course of a therapy promoted by the therapy model can thus be used to generate a therapy-effectiveness model for each characterization provided by the characterization process of Block S130, and each recommended therapy measure provided in Blocks S140 and S170.
  • Block S180 the subject can be prompted to provide additional biological samples at one or more key time points of a therapy regimen that incorporates the therapy, and the additional biological sample(s) can be processed and analyzed (e.g., in a manner similar to that described in relation to Block S120) to generate metrics characterizing modulation of the subject's microbiome composition and/or functional features.
  • metrics related to one or more of: a change in relative abundance of one or more taxonomic groups represented in the subject's microbiome at an earlier time point, a change in representation of a specific taxonomic group of the subject's microbiome, a ratio between abundance of a first taxonomic group of bacteria and abundance of a second taxonomic group of bacteria of the subject's microbiome, a change in relative abundance of one or more functional families in a subject's microbiome, and any other suitable metrics can be used to assess therapy effectiveness from changes in microbiome composition and/or functional features.
  • the method 100 can include receiving a post-therapy biological sample from the user; collecting a supplementary dataset from the user, where the supplementary dataset describes user adherence to a therapy (e.g., a determined and promoted therapy); generating a post -therapy microbiome characterization of the first user in relation to the allergy-related condition based on the allergy-related condition characterization model and the post -therapy biological sample; and promoting an updated therapy to the user for the allergy-related condition based on the post-therapy microbiome characterization (e.g., based on a comparison between the post-therapy microbiome characterization and a pre-therapy microbiome characterization; etc.) and the user adherence to the therapy (e.g., modifying the therapy based on positive or negative results for the user microbiome in relation to
  • Block S180 can be performed in any suitable manner.
  • the method 100 can, however, include any other suitable blocks or steps configured to facilitate reception of biological samples from subjects, processing of biological samples from subjects, analyzing data derived from biological samples, and generating models that can be used to provide customized diagnostics and/ or probiotic- based therapeutics according to specific microbiome compositions and/or functional features of subjects.
  • the method 100 and/or system of the embodiments can be embodied and/or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions.
  • the instructions can be executed by computer-executable components integrated with the application, applet, host, server, network, website, communication service, communication interface, hardware/firmware/software elements of a patient computer or mobile device, or any suitable combination thereof.
  • Other systems and methods of the embodiments can be embodied and/or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions.
  • the instructions can be executed by computer-executable components integrated by computer-executable components integrated with apparatuses and networks of the type described above.
  • the computer-readable medium can be stored on any suitable computer readable media such as RAMs, ROMs, flash memory, EEPROMs, optical devices (CD or DVD), hard drives, floppy drives, or any suitable device.
  • the computer-executable component can be a processor, though any suitable dedicated hardware device can (alternatively or additionally) execute the instructions.
  • each block in the flowchart or block diagrams may represent a module, segment, step, or portion of code, which includes one or more executable instructions for implementing the specified logical function(s).
  • the functions noted in the block can occur out of the order noted in the FIGURES. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved.

Landscapes

  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Organic Chemistry (AREA)
  • Physics & Mathematics (AREA)
  • Analytical Chemistry (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Zoology (AREA)
  • General Health & Medical Sciences (AREA)
  • Biophysics (AREA)
  • Biotechnology (AREA)
  • Wood Science & Technology (AREA)
  • Genetics & Genomics (AREA)
  • Molecular Biology (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Microbiology (AREA)
  • Immunology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Theoretical Computer Science (AREA)
  • Medical Informatics (AREA)
  • Biochemistry (AREA)
  • General Engineering & Computer Science (AREA)
  • Evolutionary Biology (AREA)
  • Pathology (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
  • Preparation Of Compounds By Using Micro-Organisms (AREA)

Abstract

L'invention concerne des modes de réalisation d'un procédé et/ou d'un système pour caractériser une affection liée à une allergie pour un utilisateur, ledit procédé pouvant comprendre l'une ou plusieurs des étapes suivantes : la génération d'un ensemble de données de microbiome pour chaque échantillon d'un ensemble d'échantillons biologiques associés à une population de sujets, sur la base du traitement des échantillons biologiques ; le traitement d'un ensemble de données supplémentaire associé à une ou plusieurs affections liées à une allergie pour l'ensemble d'utilisateurs ; et la mise en oeuvre d'un processus de caractérisation liée à une allergie pour lesdites une ou plusieurs affections liées à une allergie, sur la base de l'ensemble de données supplémentaire et/ou des caractéristiques de microbiome extraites de l'ensemble de données de microbiome.
PCT/US2017/066866 2016-12-15 2017-12-15 Procédé et système pour caractériser des affections liées à une allergie et associées à des micro-organismes WO2018112437A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
EP17881032.1A EP3775257A4 (fr) 2016-12-15 2017-12-15 Procédé et système pour caractériser des affections liées à une allergie et associées à des micro-organismes

Applications Claiming Priority (30)

Application Number Priority Date Filing Date Title
US201662434923P 2016-12-15 2016-12-15
US201662434902P 2016-12-15 2016-12-15
US201662434881P 2016-12-15 2016-12-15
US201662434894P 2016-12-15 2016-12-15
US201662434912P 2016-12-15 2016-12-15
US201662434917P 2016-12-15 2016-12-15
US62/434,894 2016-12-15
US62/434,902 2016-12-15
US62/434,923 2016-12-15
US62/434,881 2016-12-15
US62/434,917 2016-12-15
US62/434,912 2016-12-15
US15/606,743 US10803991B2 (en) 2014-10-21 2017-05-26 Method and system for microbiome-derived diagnostics and therapeutics
US15/606,743 2017-05-26
US201762522293P 2017-06-20 2017-06-20
US62/522,293 2017-06-20
US201762555782P 2017-09-08 2017-09-08
US62/555,782 2017-09-08
US201762557423P 2017-09-12 2017-09-12
US62/557,423 2017-09-12
US201762558489P 2017-09-14 2017-09-14
US62/558,489 2017-09-14
US201762564777P 2017-09-28 2017-09-28
US62/564,777 2017-09-28
US201762582172P 2017-11-06 2017-11-06
US201762582162P 2017-11-06 2017-11-06
US201762582191P 2017-11-06 2017-11-06
US62/582,162 2017-11-06
US62/582,172 2017-11-06
US62/582,191 2017-11-06

Publications (1)

Publication Number Publication Date
WO2018112437A1 true WO2018112437A1 (fr) 2018-06-21

Family

ID=62559438

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2017/066866 WO2018112437A1 (fr) 2016-12-15 2017-12-15 Procédé et système pour caractériser des affections liées à une allergie et associées à des micro-organismes

Country Status (2)

Country Link
EP (1) EP3775257A4 (fr)
WO (1) WO2018112437A1 (fr)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110343637A (zh) * 2019-06-28 2019-10-18 浙江工业大学 肠杆菌hy1及在降解对苯二甲酸双羟乙酯中的应用
CN114686557A (zh) * 2022-03-07 2022-07-01 中国农业大学 用于评估食物过敏的肠道菌群生物标志物及其用途和试剂盒

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150259728A1 (en) * 2013-07-21 2015-09-17 Whole Biome, Inc. Methods and systems for microbiome characterization, monitoring and treatment
US20160199424A1 (en) * 2014-11-25 2016-07-14 Epiva Biosciences, Inc. Probiotic and prebiotic compositions, and methods of use thereof for modulation of the microbiome
US20160232313A1 (en) * 2014-10-21 2016-08-11 uBiome, Inc. Method and system for microbiome-derived diagnostics and therapeutics for endocrine system conditions

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
AU2016250104B2 (en) * 2015-04-13 2022-02-10 Psomagen, Inc. Method and system for microbiome-derived diagnostics and therapeutics for conditions associated with microbiome functional features
EP3283650A4 (fr) * 2015-04-13 2019-04-10 Ubiome Inc. Procédé et système pour la caractérisation, le diagnostic et le traitement dérivés du microbiome d'affections associées à des caractéristiques fonctionnelles

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150259728A1 (en) * 2013-07-21 2015-09-17 Whole Biome, Inc. Methods and systems for microbiome characterization, monitoring and treatment
US20160232313A1 (en) * 2014-10-21 2016-08-11 uBiome, Inc. Method and system for microbiome-derived diagnostics and therapeutics for endocrine system conditions
US20160199424A1 (en) * 2014-11-25 2016-07-14 Epiva Biosciences, Inc. Probiotic and prebiotic compositions, and methods of use thereof for modulation of the microbiome

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
CHUA, HUEY-HUEY ET AL.: "Intestinal Dysbiosis Featuring Abundance of Ruminococcus gnavus Associates With Allergic Diseases in Infants", GASTROENTEROLOGY, vol. 154, no. 1, January 2018 (2018-01-01), pages 154 - 167, XP085311727 *
See also references of EP3775257A4 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110343637A (zh) * 2019-06-28 2019-10-18 浙江工业大学 肠杆菌hy1及在降解对苯二甲酸双羟乙酯中的应用
CN114686557A (zh) * 2022-03-07 2022-07-01 中国农业大学 用于评估食物过敏的肠道菌群生物标志物及其用途和试剂盒

Also Published As

Publication number Publication date
EP3775257A4 (fr) 2022-03-09
EP3775257A1 (fr) 2021-02-17

Similar Documents

Publication Publication Date Title
US10381112B2 (en) Method and system for characterizing allergy-related conditions associated with microorganisms
US10366793B2 (en) Method and system for characterizing microorganism-related conditions
US10325685B2 (en) Method and system for characterizing diet-related conditions
JP7208223B2 (ja) 疾患関連マイクロバイオーム特徴解析プロセス
US10787714B2 (en) Method and system for microbiome-derived diagnostics and therapeutics for conditions associated with microbiome functional features
US10242160B2 (en) Method and system for microbiome-derived diagnostics and therapeutics
US10354756B2 (en) Method and system for microbiome-derived characterization, diagnostics and therapeutics for cutaneous conditions
US10265009B2 (en) Method and system for microbiome-derived diagnostics and therapeutics for conditions associated with microbiome taxonomic features
US10357157B2 (en) Method and system for microbiome-derived characterization, diagnostics and therapeutics for conditions associated with functional features
AU2016250104B2 (en) Method and system for microbiome-derived diagnostics and therapeutics for conditions associated with microbiome functional features
AU2022202660A1 (en) Method and system for characterization for appendix-related conditions associated with microorganisms
US20180342322A1 (en) Method and system for characterization for appendix-related conditions associated with microorganisms
AU2022200243A1 (en) Method and system for microbiome-derived characterization, diagnostics and therapeutics for cutaneous conditions
WO2018112459A1 (fr) Procédé et système destinés à la caractérisation d'états pathologiques apparentés à un microorganisme
WO2018112437A1 (fr) Procédé et système pour caractériser des affections liées à une allergie et associées à des micro-organismes
WO2018112419A1 (fr) Procédé et système pour caractériser des affections liées au régime alimentaire

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 17881032

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 17881032

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2017881032

Country of ref document: EP

Effective date: 20190715