CN110241205A - A kind of schizophrenia biomarker combinations and its application and screening based on intestinal flora - Google Patents
A kind of schizophrenia biomarker combinations and its application and screening based on intestinal flora Download PDFInfo
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Abstract
The schizophrenia biomarker combinations and application that the invention discloses a kind of based on intestinal flora, drug candidate be can use using the influence after preceding and use to these biomarkers, so that it is determined that whether drug candidate can be used for treating or preventing schizophrenia.Overcome existing schizophrenia diagnosis method that cannot accomplish early warning, cannot predict the disadvantages of schizophrenic onset and development trend.So as to be applied to the trend of prediction schizophrenic onset and development, and the application and preparation of the kit applied to disease pathology parting.
Description
Technical field
The invention belongs to biomedicine technical fields, are related to a kind of schizoid biological marker based on intestinal flora
Object, diagnosis or kit and the application of predicting schizophrenia risk.
Background technique
Schizophrenia (English: Schizophrenia) is the unknown mental disease of one group of cause of disease, mostly slow in person between twenty and fifty
Slow or subacute onset clinically often shows as the different syndrome of symptom, is related to sensory perception, thinking, emotion and behavior etc.
Various obstacles and cerebration it is uncoordinated.The general Clear consciousness of patient, intelligence is normal, but some patientss are in disease
It can be with the damage of cognitive function during disease.The course of disease is generally delayed, and is in recurrent exerbation, exacerbation or deterioration, and most of patients is final
Appearance is failed and mental disorder, and only small number of patients can reach recovery from illness or the state that is almost recovered after treatment.
Schizoid whole world illness rate is about 0.3-0.7%.Cut-off 2016, the whole world is estimated to be more than 21,000,000
Schizophreniac, average life expectancy shorten 10 years to 25 years compared with normal person.
Although previously research shows that schizophrenic onset be caused by inherent cause and environmental factor collective effect, and suffer from
Part abnormal change is all presented in the serum and brain tissue of person, but still relies on semiotics to schizoid diagnosis at present and comment
Valence there is no reliable biological marker to identify.In addition, existing diagnostic criteria is unable to the morbidity of early prediction schizophrenia,
Curative effect and prognosis.
Summary of the invention
Present invention solves the problem in that provide a kind of schizophrenia biomarker combinations based on intestinal flora and
Its apply, can overcome existing schizophrenia diagnosis that cannot accomplish early warning, cannot predict schizophrenic onset and
The disadvantages of development trend, can help disease pathology parting and for drug target research, accurate medication, pathogenetic
Research etc..
The present invention is to be achieved through the following technical solutions:
A kind of schizophrenia biomarker combinations based on intestinal flora, the biomarker combinations are for providing phase
To abundance messages, it includes below a variety of:
Biomarker 1:Streptococcus_parasanguinis；
Biomarker 2:Bacteroides_finegoldii；
Biomarker 3:Bifidobacterium_bifidum；
Biomarker 4:Citrobacter_unclassified；
Biomarker 5:Bacteroides_eggerthii；
Biomarker 6:Prevotella_stercorea；
Biomarker 7:Clostridium_hathewayi；
Biomarker 8:Lachnospiraceae_bacterium_5_1_63FAA；
Biomarker 9:Dorea_formicigenerans；
Biomarker 10:Clostridium_asparagiforme；
Biomarker 11:Bifidobacterium_breve；
Biomarker 12:Streptococcus_anginosus；
Biomarker 13:Butyrivibrio_crossotus；
Biomarker 14:Clostridium_perfringens；
Biomarker 15:Bacteroides_oleiciplenus；
Biomarker 16:Lactobacillus_fermentum.
The relative abundance information that the biomarker combinations provide is used for and reference value is compared.
The relative abundance information of the biomarker 1~16 is based on the gene sequence that can carry out abundance calculating to it
It arranges to provide.
The schizophrenia biomarker combinations based on intestinal flora exist as detection target spot or detection target
Prepare the application in detection kit.
The screening technique of the schizophrenia biomarker combinations based on intestinal flora, steps are as follows:
1) sample collection: acquisition fecal specimens after refrigeration transportation and be quickly transferred to -80 DEG C preservation, carry out DNA extraction, obtain
To the DNA sample of extraction, sample subject includes schizophrenia patients and Healthy People；
2) macro gene order-checking and assembling
3) sequencing fragment of high quality is input to the relative abundance that software Metaphlan2 calculates species:
3.1) high quality sequencing fragment is compared onto the marker gene of reference；
3.2) quantity of Insert Fragment is counted according to comparison result；
3.3) it is standardized length of the quantity of Insert Fragment to marker gene to obtain corresponding abundance；
4) schizophrenia patients and Healthy People are randomly chosen from sample set as training set, remaining sample is used as and tests
Card collection calculates the relative abundance of species in each sample in training set, then by the species input random forest classification of training set
Device carries out 5 10 folding cross validations to classifier, calculates its essence to each individual using the species relative abundance of RF model discrimination
Refreshing Split disease risk draws ROC curve, and calculates AUC as discrimination model efficiency evaluation parameter, chooses marker group
Number < 30 is closed, and differentiates the optimal combination of efficiency, exports the significance index of each species in a model, significance index is got over
Height represents the marker and is used to differentiate that schizophrenia and non-schizoid importance are higher.
In the sample set, sample subject includes 90 schizophrenia patients and 81 Healthy Peoples, and verifying is concentrated, sample
This subject includes 10 schizophrenia patients and 10 Healthy Peoples.
The application method of above-mentioned marker diagnoses whether object suffers from schizophrenia or whether prediction object suffers from
The method of schizoid risk are as follows:
1) collecting sample from object；
2) the relative abundance information of the biomarker in the sample obtained in step 1) is determined；
3) relative abundance information described in step 2) is compared with reference data set or reference value.The method is not
It can be only used to the medical diagnosis on disease on patent law purposes, while may be used as scientific research or other personal genetic informations
Abundant and hereditary information library the non-disease diagnosis such as abundant.Believed using the relative abundance of each biomarker in test object
Breath is compared with reference data set or reference value, to determine whether object suffers from schizophrenia, or predicts it with essence
The risk of refreshing Split disease.
The reference data set includes the biology in the sample from multiple schizophreniacs and multiple normal healthy controls
The relative abundance information of marker.
The reference data set refers to operating the sample for being diagnosed as diseased individuals and healthy individuals, is obtained
Each biomarker relative abundance information, be used as the reference of the relative abundance of every kind of biomarker.Specifically, ginseng
Training dataset can be referred to by examining data set.According to the present invention, it is well known in the art to refer to and verify that collection has for the training set
Meaning.In one embodiment of the invention, the training set refers to the schizophrenia subject comprising certain sample number
With the data acquisition system of the content of each biomarker in non-schizophrenia subject sample to be tested.Verifying collection be for
Test the independent data set of training set performance.
Heretofore described reference value refers to the reference value or normal value of normal healthy controls.It is known to those skilled in the art that
When sample size is sufficiently large, each biomarker in sample is obtained using detection well known in the art and calculation method
The range of normal value (absolute value).When using the level of measuring method detection biomarker, the biology in sample can be marked
The absolute value of will object level is directly compared with reference value, to assess risk and diagnosis or early diagnosis schizophrenia
Disease, it is optionally possible to include statistical method.
It further include that execution is polynary in the step of relative abundance information described in step 2) is compared with reference data set
Statistical model is to obtain probability of illness.It may be implemented rapidly and efficiently to detect using multivariate statistical model.Specifically, the polynary system
Meter model is Random Forest model.
The probability of illness is greater than threshold value and shows the object with schizophrenia or related disease or have with essence
The risk of refreshing Split disease or related disease.Specifically, the threshold value is 0.5.
The relative abundance information of biomarker described in step 2) is obtained using sequencing approach, further comprises:
The isolated sample of nucleic acid from the sample of the object is based on the sample of nucleic acid obtained, constructs DNA library,
The DNA library is sequenced, to obtain sequencing result；And it is based on the sequencing result, by sequencing result and reference
Gene set is compared, with the relative abundance information of the determination biomarker.
According to an embodiment of the present, it can use at least one by sequencing result and with reference to base of SOAP2 and MAQ
Because collection is compared, thus, it is possible to improve the efficiency of comparison, and then the efficiency of schizophrenia detection can be improved.According to this
The embodiment of invention can simultaneously detect a variety of (at least two) biomarkers, and schizophrenia inspection can be improved
The efficiency of survey.
Described with reference to gene set includes that macro base is carried out from the sample of multiple schizophreniacs and multiple normal healthy controls
Because of a group sequencing, nonredundancy gene set is obtained, the nonredundancy gene set is merged with enteric microorganism gene set then, obtains institute
It states with reference to gene set.Reference gene set in the present invention can be existing gene set, and such as existing enteron aisle having disclosed is micro-
Reference biomolecule gene set；It is also possible to the sample of multiple schizophreniacs and multiple normal healthy controls carrying out macro genome survey
Sequence obtains nonredundancy gene set, then merges the nonredundancy gene set with enteric microorganism gene set, obtain the reference
Gene set, more comprehensively, testing result is more reliable for thus obtained reference gene set information.
The nonredundancy gene set makees the common understanding of those skilled in the art to explain, is removal redundancy base in simple terms
The set of remaining gene because after.Redundancy gene is commonly referred to as multiple duplications of occur on item chromosome gene.
Specifically, the sample is fecal sample.The sequencing approach is surveyed by second generation sequencing approach or the third generation
What sequence method carried out.The means being sequenced are not particularly restricted, and are sequenced by the method that two generations or three generations are sequenced,
Sequencing rapidly and efficiently may be implemented.
The sequencing approach is by at least one selected from Hiseq2000, SOLiD, 454 and single-molecule sequencing device
It carries out.Thereby, it is possible to utilize the high throughput of these sequencing devices, deep sequencing, to be conducive to subsequent sequencing
Data are analyzed, and accuracy and accuracy when statistical test are especially carried out.
The invention proposes described, and the schizophrenia biomarker combinations based on intestinal flora are used as detection target spot
Or detection target preparation detection kit in application, the kit for diagnose object whether suffer from schizophrenia or
Whether related disease or prediction object suffer from the risk of schizophrenia or related disease.
That is, the invention proposes it is a kind of include kit for detecting the reagent of biomarker, using the kit,
It can determine relative abundance of these markers in intestinal flora, thus, it is possible to by obtained relative abundance value, thus
Determine whether object suffers from or susceptible schizophrenia, and the effect of the therapeutic effect for monitoring schizophreniac
Rate.
The invention proposes the schizophrenia biomarker combinations based on intestinal flora to treat as target spot in screening
And/or the application in the schizoid drug of prevention.The biomarker is the biological marker that aforementioned present invention proposes
Object can use drug candidate using the influence after preceding and use to these biomarkers, so that it is determined that drug candidate whether
It can be used for treating or preventing schizophrenia.
The variation of the biomarker combinations relative abundance is to determine whether drug candidate effectively provides foundation.
Compared with prior art, the invention has the following beneficial technical effects:
Make the present invention is based on the discovery of following facts and problem and understanding: enteric microorganism is to be present in human body intestinal canal
In microbiologic population, be human body " the second genome ".Human body intestinal canal flora and host constitute the entirety that is mutually related.
Enteric microorganism can generate the most of neurotransmitters found in human brain.More and more evidences support enteric microorganism shadow
The viewpoint of nervous centralis chemistry and behavior is rung, irritable bowel syndrome is considered as the allusion quotation that brain-enteric microorganism axis adjusts disorder
Type case.Study on Transformation shows that certain specific floras may be reacted pressure and cognitive function has an impact.Use probiotics
Or antibiotic changes intestinal microbiota, provides to improve cerebral function and the intestines-brain axis disease such as treatment depression and self-closing disease
A kind of new method.Therefore, the present invention passes through the intestinal flora and gene order to schizophreniac and healthy population
It is analyzed, to filter out the biomarker high with associated with schizophrenia, and can be accurate using the marker
Ground diagnoses schizophrenia or prediction risk, and can be used for monitoring therapeuticing effect.
Excrement is the metabolite of human body, inside not only includes the metabolite of human body, further includes the body generation to us
It thanks and is immunized and the closely related enteric microorganism of variation of brain function.Excrement is studied, is found in schizophrenia
There are apparent differences on the composition of the intestinal flora of patient and healthy population, can accurately carry out to schizophreniac
Risk assessment, early diagnosis.The present invention is based on the comparison to schizophreniac and healthy population intestinal flora and divide
Analysis, obtains a variety of relevant enteric microorganism, schizophrenia crowd and healthy population species relative abundance in conjunction with high quality
Data accurately can carry out risk assessment, early diagnosis to schizophreniac as training set.This method and mesh
Preceding common diagnostic method is compared, and is had the characteristics that convenient, fast.
The relevant biomarker of schizophrenia proposed by the present invention is valuable to early diagnosis.First, this hair
Bright marker specificity with higher and sensitivity.Second, the analysis of excrement guarantees accuracy, safety, affordability
And patient compliance.And the sample of excrement is transportable.Test based on polymerase chain reaction (PCR) is comfortable and noninvasive,
So people can be easier to participate in given screening sequence.Third, marker of the invention are also used as in schizophrenia
Disease patient carries out the tool of Treatment monitoring to detect the response to treatment.Due to abundance measurement, 16 kinds of labels of the present invention
The case where combination of object is especially suitable for based on marker gene comparison method measurement abundance.
Detailed description of the invention
Fig. 1 is according to schizophreniac and normal healthy controls beta diversity on one embodiment of the invention object species level
The case where.Diagram shows schizophreniac and normal healthy controls, and there are significant differences.
Fig. 2 is according to the error rate of 5 10 folding cross validations in one embodiment of the present of invention random forest grader point
Cloth situation.
Fig. 3 is to be based on Random Forest model (16 enteron aisle markers) according to one embodiment of the present of invention, by spirit point
Split recipient's operating characteristics (Receiver Operating of the training set of disease patient and normal healthy controls composition
Characteristic, ROC) curve and area under the curve (Area under Curve, AUC).
Fig. 4 is to be based on Random Forest model (16 enteron aisle markers) according to one embodiment of the present of invention, by spirit point
Split the ROC curve and AUC of the verifying collection of disease patient and normal healthy controls composition.
Specific embodiment
Term used herein has the normally understood meaning of person of ordinary skill in the relevant.However, in order to preferably
Understand the present invention, some definition and relational language be explained as follows:
" schizophrenia " is the unknown mental disease of one group of cause of disease, mostly between twenty and fifty slow or subacute onset, is faced
The different syndrome of symptom is often shown as on bed, is related to various obstacles such as sensory perception, thinking, emotion and behavior and essence
Mind is movable uncoordinated.
" biomarker ", also referred to as " biological markers " refer to the measurable index of the biological aspect of individual.In this way
Biomarker can be any substance in individual, if they and be detected individual particular biological status (for example, disease
Disease) there is relationship, for example, nucleic acids marker (being referred to as gene marker, such as DNA), protein markers, cell factor
Marker, chemotactic factor (CF) marker, carbohydrate marker, antigen markers, antibody marlcers, species marker (kind/category
Label) and function marker (KO/OG label) etc..Wherein, the meaning of nucleic acids marker is not limited to existing to express
Further include any nucleic acid fragment for the gene of biologically active protein, can be DNA, or RNA can be
Perhaps RNA is also possible to unmodified DNA or RNA, and the set being made of them to DNA by modification.Herein
Amplifying nucleic acid marker is referred to as characteristic fragment sometimes.In the present invention, biomarker can also use " enteron aisle marker "
It indicates, because the biomarker relevant to schizophrenia found is present in the enteron aisle of subject.Biology mark
Remember that object by measurement and assessment, is often used to check normal biological processes, pathogenic course or the response of therapy intervention pharmacology, and
It is all useful in many scientific domains.
The biomarker can use high-flux sequence, batch quantity analysis healthy population and schizophreniac
Fecal sample.Based on high-flux sequence data, healthy population is compared with schizophreniac group, so that it is determined that with
The relevant specific nucleic acid sequence of schizophreniac group.In short, its step are as follows:
The collection and processing of sample: the fecal sample of healthy population and schizophreniac group is collected, kit is used
DNA extraction is carried out, sample of nucleic acid is obtained；
Library construction and sequencing: DNA library constructs and sequencing is carried out using high-flux sequence, to obtain fecal specimens
Included in enteric microorganism nucleic acid sequence；
By the analysis method of bioinformatics, specific enteric microorganism core relevant to schizophreniac is determined
Acid sequence.Firstly, (also referred to as referring to gene set, being the gene newly constructed sequencing sequence (reads) and reference gene collection
The database of collection or any known sequence, for example, using known people's intestinal microflora nonredundancy gene set) compare
It is right.Next, being based on comparison result, the nucleic acid sample from healthy population and schizophreniac's group's fecal specimens is determined respectively
The relative abundance of each gene in this.It, can be by sequencing sequence and reference by the way that sequencing sequence to be compared with reference gene collection
Gene in gene set establishes corresponding relationship, thus for the specific gene in sample of nucleic acid, sequencing sequence corresponding thereto
Number can effectively reflect the relative abundance of the gene.Thus, it is possible to by comparison result, according to conventional statistical
Analysis determines the relative abundance of the gene in sample of nucleic acid.Finally, in determining sample of nucleic acid after the relative abundance of each gene, it is right
The relative abundance of each gene carries out statistical check in sample of nucleic acid from healthy population and schizophreniac's group's excrement, by
This, it can be determined that it whether there is the relative abundance gene that there were significant differences in healthy population and schizophreniac crowd,
It is significant difference if there is gene, then the gene is treated as the biomarker of abnormality, i.e. nucleic acids marker.
In addition, gene species information and functional annotation are generally comprised for reference gene collection that is known or newly constructing, by
This can be further by being divided the species information of gene and functional annotation on the basis of determining gene relative abundance
Class, so that it is determined that in intestinal flora each microorganism species relative abundance and function relative abundance, can also further determine that
The species marker and function marker of abnormality.In short, determining the method for species marker and function marker into one
Step includes: that the sequencing sequence of healthy population and schizophreniac group is compared with reference gene collection；It is tied based on comparing
Fruit determines the species relative abundance and function of each gene in healthy population and the sample of nucleic acid of schizophrenia patient group respectively
Relative abundance；Species relative abundance to each gene in the sample of nucleic acid from healthy population and schizophrenia patient group and
Function relative abundance carries out statistical test；And nucleic acid sample in healthy population and schizophrenia patient group is determined respectively
There are the species marker of significant difference and function markers for relative abundance between this.According to an embodiment of the invention, can adopt
Statistics inspection is carried out with the relative abundance of the relative abundance to the gene from same species and the gene with identical function annotation
It tests, such as sums it up, is averaged, I d median etc., to determine function relative abundance and species relative abundance.
Unless otherwise specified, the conventional hand that technological means employed in embodiment is well known to those skilled in the art
Section, is referred to " Molecular Cloning:A Laboratory guide " third edition or Related product carries out, and used reagent and product are also
Available commercial.The various processes and method being not described in detail are conventional methods as known in the art, and agents useful for same comes
Source, trade name and it is necessary to list its constituent person, are indicated on the first occurrence, same reagents used is such as without spy thereafter
Different explanation is identical as the content indicated for the first time.
The present invention is using macro genome association analysis (Metagenome-Wide Association Study, MWAS)
Analysis method, the flora composition through sequencing analysis fecal sample, function difference；Schizophrenia is differentiated with random forest discrimination model
Disease group and non-schizophrenia group obtain probability of illness, for the assessment of schizoid risk, diagnosis, early stage
Potential drug target spot is found in diagnosis.
According to the present invention, term " individual " refers to animal, especially mammal, such as primate, preferably people.
According to the present invention, term such as " one ", "one" and " this " refers not only to the individual of odd number, but including that can use for
Common one kind of bright particular implementation.
In the present invention, the sequencing (sequencing of two generations) and MWAS have it is known in the art, those skilled in the art
It can be adjusted as the case may be.According to an embodiment of the invention, can be according to document (Jun Wang, and Huijue
Jia.Metagenome-wide association studies:fine-mining the microbiome.Nature
Reviews Microbiology14.8 (2016): 508-522.) method recorded in carries out.
In the present invention, the application method of Random Forest model and ROC curve is well known in the art, those skilled in the art
Member can carry out parameter setting and adjustment as the case may be.According to an embodiment of the invention, can be according to document (Drogan
D,Dunn WB,Lin W,Buijsse B,Schulze MB,Langenberg C,Brown M,Floegel a.,Dietrich
S,Rolandsson O,Wedge DC,Goodacre R,Forouhi NG,Sharp SJ,Spranger J,Wareham NJ,
Boeing H:Untargeted Metabolic Profiling Identifies Altered Serum Metabolites
of Type 2-Diabetes Mellitus in a Prospective,Nested Case Control Study.Clin
Chem 2015,61:487-497.；Mihalik SJ,Michaliszyn SF,de las Heras J,Bacha F,Lee S,
Chace DH,DeJesus VR,Vockley J,Arslanian SA:Metabolomic profiling of fatty
acid and amino acid metabolism in youth with obesity and type 2diabetes:
Evidence for enhanced mitochondrial oxidation.Diabetes Care 2012,35:605-611.,
Be incorporated to by reference of text herein) in record method carry out.
In the present invention, the instruction of the biomarker of schizophrenia subject and non-schizophrenia subject is constructed
Practice collection, and as benchmark, the biomarker content value of sample to be tested is assessed.
As known to those skilled in the art, when further expansion sample size, pattern detection well known in the art and meter are utilized
Calculation method, it can be deduced that the normal contents value section (absolute figure) of every kind of biomarker in the sample.It can will test
To the absolute value of biomarker content be compared with normal contents value, optionally, can be combined with statistical method, with
Obtain the evaluation of schizophrenia risk, diagnosis and efficiency of the therapeutic effect for monitoring schizophreniac etc..
It does not wish to be bound by any theory restrictions, inventor points out that these biomarkers are the enterobacteriaceaes being present in human body
Group.The method is associated analysis to subject's intestinal flora through the invention, obtains the described of schizophrenia group
Biomarker shows certain content range value in bacteria detection.
Below with reference to specific embodiment, the present invention is described in further detail, it is described be explanation of the invention and
It is not to limit.
Embodiment 1
1.1 sample collection
Reference literature A metagenome-wide association study of gut microbiota in type
The method that 2diabetes (Qin J et al.Nature.2012,490,55-60) is recorded acquires refrigeration transportation after fecal specimens
And -80 DEG C of preservations are quickly transferred to, carry out DNA extraction, the DNA sample extracted.Schizophrenia and non-essence of the invention
The fecal sample of refreshing Split disease subject is from China.It is 171 total, wherein 81, healthy sample and schizophrenia sample 90
Example.
1.2 macro gene order-checkings and assembling
Sequencing library is constructed using extracted DNA sample, is carried out in Illumina HiSeq2000 microarray dataset double
To (Paired-end) macro gene order-checking (Insert Fragment 350bp reads long 100bp).The data generated to sequencing are filtered
(quality-controlled), adapter polluted sequence, low quality sequence and host genome polluted sequence are removed, is obtained
The sequencing fragment (reads) of high quality.
1.3 genome alignment and abundance calculate
The high quality sequencing fragment (reads) of above-mentioned " 1.2 macro gene order-checkings and screening " is input to software
Metaphlan2 (http://segatalab.cibio.unitn.it/tools/metaphlan2/) can calculate species
Relative abundance.Reference literature MetaPhlAn2for enhanced metagenomic taxonomic profiling,
The method that Nature Methods 12,902-903 (2015) is recorded.Steps are as follows for the calculating of its abundance: 1) piece is sequenced in high quality
Section is compared onto the marker gene of reference；2) quantity of Insert Fragment is counted according to comparison result；3) by the quantity of Insert Fragment
The length of marker gene is standardized and (is standardized by average gene length, and is obtained in the way of being rounded downwards
The abundance of corresponding species) obtain corresponding abundance.
1.4 screen the potential source biomolecule marker of schizophrenia occurrence and development using random forest (ROC/AUC)
Further to screen potential disease enteron aisle biomarker, the present embodiment constructs schizophrenia subject and non-
The training set of the biomarker of schizophrenia subject, and as benchmark, to the biomarker content of sample to be tested
Value is assessed.Wherein, in the present invention, the training set and verifying collection have meaning known in the field.At this
In the embodiment of invention, training set refers to that the schizophrenia subject comprising certain sample number and non-schizophrenia are tested
The data acquisition system of the content of each biomarker in person's sample to be tested.Verifying collection is the independent digit for testing training set performance
According to set.Wherein, non-schizophrenia subject is the good subject of the state of mind, and subject can be dynamic for people or model
Object is tested taking human as subject in the present embodiment.
Specifically comprise the following steps:
The present invention randomly chooses 80 essences from 171 samples (90 schizophrenia patients and 81 Healthy Peoples)
Refreshing Split disease patient and 71 Healthy Peoples are as training set (table 1-1,1-2), remaining sample is as verifying collection (10 schizophrenias
Disease patient and 10 Healthy Peoples).
1.4.1 the biomarker screened using training set data
Firstly, calculating the relative abundance of species in each sample in training set according to the method for 1.3 descriptions.Then it will train
The species of collection input random forest (randomForest 4.6-12in R 3.2.5, RF) classifier.Classifier is carried out 5 times
10 folding cross validations calculate its schizophrenia risk to each individual using the species relative abundance of RF model discrimination,
ROC curve is drawn, and calculates AUC as discrimination model efficiency evaluation parameter.Marker number of combinations < 30 is chosen, and differentiates effect
Optimal group of energy is combined into combination of the present invention.The significance index of each species is exported in a model, and significance index is higher, represents
The marker is used to differentiate that schizophrenia and non-schizoid importance are higher.
Gained RF classifier of the invention contains 16 metabolins (i.e. 16 biomarkers), this 16 biomarkers
Relative abundance respectively as shown in table 1-1,1-2, details are as shown in table 2.Table 3 shows 16 kinds of biomarkers and combines
Predict the probability of illness of training set, wherein probability of illness >=0.5 confirmation individual has the risk for suffering from schizophrenia or suffers from
Schizophrenia.
Fig. 2 shows the error rate distribution situations of 5 10 folding cross validations in random forest grader.The model training
Collection sample is trained in the species relative abundance for meeting target obtained through MWAS flow processing, and thick solid black curve represents 5
The average value of secondary test (thin black curve represents 5 tests), black vertical line represent species number in selected optimal combination.
Fig. 3 is shown based on Random Forest model (16 biomarkers) by schizophreniac and healthy control group
At training set ROC curve and AUC, wherein specificity characterization is the probability sentenced for not illness pair, sensibility is referred to
For the probability that illness is sentenced pair, to the differentiation efficiency of training set sample are as follows: AUC=81.21%, 95% confidence interval CI=
74.33-88.1%.The result shows that the model obtain metabolin combination can be used as distinguish schizophrenia with it is non-schizoid
Potential source biomolecule marker.
1.4.2 the biomarker screened using verifying collection data verification
The present invention immediately verifies the model using independent crowd, and probability of illness >=0.5 prediction individual has spirit
Split disease suffers from the disease risk or with schizophrenia.Firstly, calculating each sample in training set according to the method for 1.3 descriptions
In each biomarker relative abundance.Then verifying collection data are carried out using Random Forest model according to the method for 1.4.1
Verifying.
Based on this model:
16 biomarkers are verifying the relative abundance concentrated as shown in table 4-1,4-2.Table 5 is shown based on 16 lifes
The probability of illness of object marker prediction verifying collection.
Fig. 4 is shown based on Random Forest model (16 biomarkers) by schizophreniac and healthy control group
At individual authentication collection ROC curve and AUC, the differentiation AUC=80.5% (95%CI=59.59%-100%) of model.
In 3.2.5 version R use " randomForest 4.6-12package " carry out Random Forest model classification and
It returns.Input includes training set data (relative abundance for the species marker selected i.e. in training sample, be shown in Table 1-1,1-2),
Sample morbid state (the sample morbid state of training sample is vector, and ' 1 ' represents schizophrenia, and ' 0 ' represents normal healthy controls),
An and verifying collection (relative abundance of selected species marker is concentrated in verifying, is shown in Table 4-1,4-2).Then, inventor utilizes R
The random forest function of random forest packet establishes classification and anticipation function and predicts that output is to verifying collection data in software
Prediction result (probability of illness)；Threshold value is 0.5, if probability >=0.5 of disease, then it is assumed that have suffer from schizoid risk or
Person suffers from schizophrenia.
Table 1-1 Random Forest model training set enteron aisle marker (Metaphlan2) relative abundance data
* SZ: schizophrenic patients；N: normal healthy controls
Table 1-2 Random Forest model training set enteron aisle marker (Metaphlan2) relative abundance data
2 16 kinds of biomarker details of table
# verifying collection AUC, indicates in the case where training set data obtains model, to the differentiation degree of verifying collection data.
&txid indicates number of the biomarker in ncbi database.
Table 3 is based on 11 kinds of marker combined training collection probability of illness
Table 4-1 Random Forest model verifying collection enteron aisle marker relative abundance data
Table 4-2 Random Forest model verifying collection enteron aisle marker relative abundance data
Table 5 is based on 16 kinds of marker combined authentication collection probability of illness
| Sample number | Probability of illness | Sample number | Probability of illness | |
| N_72 | 0.26 | SZ_81 | 0.534 | |
| N_73 | 0.19 | SZ_82 | 0.614 | |
| N_74 | 0.228 | SZ_83 | 0.356 | |
| N_75 | 0.274 | SZ_84 | 0.61 | |
| N_76 | 0.396 | SZ_85 | 0.418 | |
| N_77 | 0.506 | SZ_86 | 0.714 | |
| N_78 | 0.516 | SZ_87 | 0.528 | |
| N_79 | 0.778 | SZ_88 | 0.63 | |
| N_80 | 0.21 | SZ_89 | 0.814 | |
| N_81 | 0.614 | SZ_90 | 0.678 |
The above result shows that biomarker disclosed by the invention accuracy with higher and specificity, have good
Exploitation be diagnostic method prospect, thus for schizoid risk assessment, diagnosis, early diagnosis, find it is potential
Drug target provides foundation.
Therefore, the present invention proposes following application:
The schizophrenia biomarker combinations based on intestinal flora exist as detection target spot or detection target
Prepare the application in detection kit.
The schizophrenia biomarker combinations based on intestinal flora as target spot screening treatment and/or
Prevent the application in schizoid drug.
The variation of the biomarker combinations relative abundance is to determine whether drug candidate effectively provides foundation.
Although the embodiments of the present invention has been shown and described above, it is to be understood that above-described embodiment is example
Property, it is not considered as limiting the invention, those skilled in the art within the scope of the invention can be to above-mentioned
Embodiment is changed, modifies, replacement and variant.
Claims (8)
1. a kind of schizophrenia biomarker combinations based on intestinal flora, which is characterized in that the biomarker combinations
For providing relative abundance information, it includes below a variety of:
Biomarker 1:Streptococcus_parasanguinis；
Biomarker 2:Bacteroides_finegoldii；
Biomarker 3:Bifidobacterium_bifidum；
Biomarker 4:Citrobacter_unclassified；
Biomarker 5:Bacteroides_eggerthii；
Biomarker 6:Prevotella_stercorea；
Biomarker 7:Clostridium_hathewayi；
Biomarker 8:Lachnospiraceae_bacterium_5_1_63FAA；
Biomarker 9:Dorea_formicigenerans；
Biomarker 10:Clostridium_asparagiforme；
Biomarker 11:Bifidobacterium_breve；
Biomarker 12:Streptococcus_anginosus；
Biomarker 13:Butyrivibrio_crossotus；
Biomarker 14:Clostridium_perfringens；
Biomarker 15:Bacteroides_oleiciplenus；
Biomarker 16:Lactobacillus_fermentum.
2. the schizophrenia biomarker combinations based on intestinal flora as described in claim 1, which is characterized in that described
Biomarker combinations provide relative abundance information be used for and reference value be compared.
3. the schizophrenia biomarker combinations based on intestinal flora as described in claim 1, which is characterized in that described
The relative abundance information of biomarker 1~16 be to be provided based on the gene order of abundance calculating can be carried out to it.
4. the schizophrenia biomarker combinations described in claim 1 based on intestinal flora are as detection target spot or detection
Application of the target in preparation detection kit.
5. the schizophrenia biomarker combinations described in claim 1 based on intestinal flora are treated as target spot in screening
And/or the application in the schizoid drug of prevention.
6. application as claimed in claim 5, which is characterized in that the variation of the biomarker combinations relative abundance is true
Determine whether drug candidate effectively provides foundation.
7. the screening technique of the schizophrenia biomarker combinations described in claim 1 based on intestinal flora, feature
It is, steps are as follows:
1) sample collection: acquisition fecal specimens after refrigeration transportation and be quickly transferred to -80 DEG C preservation, carry out DNA extraction, mentioned
The DNA sample taken, sample subject include schizophrenia patients and Healthy People；
2) macro gene order-checking and assembling
3) sequencing fragment of high quality is input to the relative abundance that software Metaphlan2 calculates species:
3.1) high quality sequencing fragment is compared onto the marker gene of reference；
3.2) quantity of Insert Fragment is counted according to comparison result；
3.3) it is standardized length of the quantity of Insert Fragment to marker gene to obtain corresponding abundance；
4) schizophrenia patients and Healthy People are randomly chosen from sample set as training set, remaining sample is as verifying
Collection calculates the relative abundance of species in each sample in training set, the species of training set is then inputted random forest grader,
5 10 folding cross validations are carried out to classifier, its spirit is calculated to each individual using the species relative abundance of RF model discrimination
Split disease risk draws ROC curve, and calculates AUC as discrimination model efficiency evaluation parameter, chooses marker combination
Number < 30, and differentiate the optimal combination of efficiency, the significance index of each species is exported in a model, significance index is higher,
The marker is represented to be used to differentiate that schizophrenia and non-schizoid importance are higher.
8. screening technique described in claim 7, which is characterized in that in the sample set, sample subject includes 90 spirit point
Disease patient and 81 Healthy Peoples are split, verifying is concentrated, and sample subject includes 10 schizophrenia patients and 10 Healthy Peoples.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111370116A (en) * | 2020-03-18 | 2020-07-03 | 浙江大学 | Intestinal microbial marker for predicting curative effect of bipolar affective disorder and screening application thereof |
| CN112011602A (en) * | 2020-07-23 | 2020-12-01 | 翊康生物科技发展(辽宁)有限公司 | Intestinal flora related to immune recovery and application thereof |
| CN112011605A (en) * | 2020-09-15 | 2020-12-01 | 石家庄市人民医院(石家庄市第一医院、石家庄市肿瘤医院、河北省重症肌无力医院、石家庄市心血管病医院) | Use of microbial flora in disease diagnosis |
| WO2021184412A1 (en) * | 2020-03-18 | 2021-09-23 | 浙江大学 | Enteric microorganism-based bipolar affective disorder biomarkers, and application thereof in screening |
| CN113817853A (en) * | 2021-09-24 | 2021-12-21 | 西安交通大学 | Application of intestinal microorganisms as marker of mild traumatic brain trauma |
| CN117854720A (en) * | 2023-12-06 | 2024-04-09 | 广州达安临床检验中心有限公司 | Autism risk prediction device and computer equipment based on fungus genus characteristic |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113493849A (en) * | 2021-09-09 | 2021-10-12 | 北京泱深生物信息技术有限公司 | A product for diagnosing growth retardation |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107480474A (en) * | 2017-08-01 | 2017-12-15 | 山东师范大学 | Grader modeling evaluation method of calibration and system based on gut flora abundance |
| CN107746874A (en) * | 2017-11-06 | 2018-03-02 | 张猛 | Schizophrenia mark |
| US20180100177A1 (en) * | 2015-04-16 | 2018-04-12 | National Center Of Neurology And Psychiatry | Biomarker for mental disease |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030096264A1 (en) * | 2001-06-18 | 2003-05-22 | Psychiatric Genomics, Inc. | Multi-parameter high throughput screening assays (MPHTS) |
| JP2021003001A (en) * | 2017-09-07 | 2021-01-14 | 国立大学法人千葉大学 | Depression symptom examination method and therapeutic agent screening method |
-
2019
- 2019-07-05 WO PCT/CN2019/094923 patent/WO2020244017A1/en active Application Filing
- 2019-07-05 CN CN201910605140.4A patent/CN110241205A/en active Pending
- 2019-07-05 WO PCT/CN2019/094924 patent/WO2020244018A1/en active Application Filing
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180100177A1 (en) * | 2015-04-16 | 2018-04-12 | National Center Of Neurology And Psychiatry | Biomarker for mental disease |
| CN107480474A (en) * | 2017-08-01 | 2017-12-15 | 山东师范大学 | Grader modeling evaluation method of calibration and system based on gut flora abundance |
| CN107746874A (en) * | 2017-11-06 | 2018-03-02 | 张猛 | Schizophrenia mark |
Non-Patent Citations (1)
| Title |
|---|
| 任广旭等: "《肠道菌群与精准营养健康》", 31 March 2019, 中国科学技术出版社 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111370116A (en) * | 2020-03-18 | 2020-07-03 | 浙江大学 | Intestinal microbial marker for predicting curative effect of bipolar affective disorder and screening application thereof |
| WO2021184412A1 (en) * | 2020-03-18 | 2021-09-23 | 浙江大学 | Enteric microorganism-based bipolar affective disorder biomarkers, and application thereof in screening |
| CN112011602A (en) * | 2020-07-23 | 2020-12-01 | 翊康生物科技发展(辽宁)有限公司 | Intestinal flora related to immune recovery and application thereof |
| CN112011605A (en) * | 2020-09-15 | 2020-12-01 | 石家庄市人民医院(石家庄市第一医院、石家庄市肿瘤医院、河北省重症肌无力医院、石家庄市心血管病医院) | Use of microbial flora in disease diagnosis |
| CN112011605B (en) * | 2020-09-15 | 2023-04-28 | 石家庄市人民医院(石家庄市第一医院、石家庄市肿瘤医院、河北省重症肌无力医院、石家庄市心血管病医院) | Use of microbial flora in disease diagnosis |
| CN113817853A (en) * | 2021-09-24 | 2021-12-21 | 西安交通大学 | Application of intestinal microorganisms as marker of mild traumatic brain trauma |
| CN117854720A (en) * | 2023-12-06 | 2024-04-09 | 广州达安临床检验中心有限公司 | Autism risk prediction device and computer equipment based on fungus genus characteristic |
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