WO2016151702A1 - Procédé et système pour extraire un sujet d'une recherche génétique - Google Patents

Procédé et système pour extraire un sujet d'une recherche génétique Download PDF

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WO2016151702A1
WO2016151702A1 PCT/JP2015/058573 JP2015058573W WO2016151702A1 WO 2016151702 A1 WO2016151702 A1 WO 2016151702A1 JP 2015058573 W JP2015058573 W JP 2015058573W WO 2016151702 A1 WO2016151702 A1 WO 2016151702A1
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attribute
user
gene
group
management table
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PCT/JP2015/058573
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English (en)
Japanese (ja)
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中原　周一
隆 千種
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株式会社日立製作所
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    • 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

Definitions

  • the present invention relates to a technique for identifying a user who possesses a specific gene.
  • the human genome (genetic information) consisting of about 3.1 billion base pairs was almost completely analyzed in 2003 by the Human Genome Project, and the number of human genes was found to be about 26800.
  • research is also progressing on the function of each gene. For example, it is known that the holder of the ⁇ 3AR gene has a basal metabolism lower by about 200 kcal than the non-carrier, and is called an obesity gene.
  • Patent Document 1 gene information is made into a database, individual gene characteristics are associated with diseases, drug responsiveness, etc., patient data is stratified by disease level, etc., and commercialized therapeutic drugs, diagnostic methods, etc. There is a disclosure about the business model to do.
  • DNA data the entire base sequence of DNA is read from the sample of the service user and converted into text data (hereinafter referred to as DNA data).
  • DNA data text data
  • the service user From the viewpoint of time and cost, it is advantageous to make a decision focusing on the presence or absence of one or more specific genes related to information useful for the body, ie, constitution or disease risk. This is because, when trying to analyze all genes, the time required for the analysis becomes a problem due to an increase in the error detection rate of the base sequence.
  • Analyzed DNA data and determination results of specific genes are accumulated in a database (hereinafter referred to as gene management database).
  • gene management database a database
  • the presence or absence of the gene has been determined in the initial analysis. In cases where there is no, it is necessary to rescan the DNA data.
  • the number of rescan targets is large, a large amount of DNA data has to be processed, and it takes an enormous amount of time to identify the gene holder. Therefore, there is a time delay until the result is obtained, and during that time, the result report to the subject to be fed back is delayed.
  • Patent Document 1 is effective when known gene information or already rescanned and diagnosis of the gene is possible, but whether or not it has the target gene as described above. It does not solve the problem in an unknown situation / stage.
  • This invention makes it a subject to identify the user who has a gene at an early stage, when the gene which has a new function is discovered.
  • One aspect of the present invention for solving the above-described problem is that an input device and a processing device are used to extract a target user who should investigate DNA data for a survey target gene from a plurality of users (service users).
  • a genetic investigation target extraction method executed by an information processing apparatus having a storage device and an output device.
  • a plurality of extraction conditions for extracting a user are defined, and each of the plurality of extraction conditions includes a group definition management table associated with one or more attributes of the user, a survey target gene, and an attribute.
  • An attribute-related strength management table that defines the strength of association is used.
  • the processing device refers to the attribute-related strength management table and evaluates the degree of association between the plurality of extraction conditions and the gene to be investigated, and the processing device determines one or more from the plurality of extraction conditions based on the evaluation.
  • the above extraction conditions may be hierarchized.
  • the structure may be such that all users are included in the highest extraction condition and the users can be classified and narrowed down in the lower extraction condition.
  • Another aspect of the present invention relates to a genetic investigation target having an input device, a processing device, a storage device, and an output device in order to extract a target user whose DNA data should be examined for a survey target gene from a plurality of users.
  • Extraction system The storage device determines a user attribute based on a predetermined condition, and based on the determination, each user belongs to one or a plurality of attribute groups, and the member list of the user created for each attribute group, and a survey target
  • An attribute relation strength management table that defines the relation strength between genes and attributes is stored.
  • the processing device refers to the attribute-related strength management table, and evaluates the degree of association between the plurality of attribute groups and the gene to be investigated, and the processing device determines one or more from the plurality of attribute groups based on the evaluation. And an extraction unit that extracts a member list corresponding to the selected attribute group as a target member list.
  • the above member list may be hierarchized.
  • the top extracted member list may include all users, and the lower member list may be structured such that a part of the users can be extracted.
  • attributes include information about the user's genes, information about the body, and information about life.
  • a category or level can be specified as a subordinate concept of an attribute, and a condition can be added by selecting the category or level.
  • the database configuration described in the embodiments described below is merely an example, and other configurations may be used as long as the relevance of data is maintained.
  • the physical position is not limited.
  • the identification of newly discovered gene holders is efficient. It can be done. As a result, quick service based on the latest research data becomes possible.
  • the conceptual diagram which shows the general concept of the service of the example of application of an Example.
  • the flowchart which shows the outline
  • the ladder chart at the time of normal operation of the system of an Example (the 1).
  • the ladder chart at the time of normal operation of the system of an Example (the 2).
  • the ladder chart at the time of normal operation of the system of an Example (the 3).
  • the table figure which shows the example of a gene management database.
  • the table figure which shows the example of a user attribute database.
  • the table figure which shows the example of an attribute definition table (invariant attribute).
  • the table figure which shows the example of an attribute definition table (long-term change attribute).
  • the table figure which shows the example of an attribute definition table (medium-term change attribute).
  • the table figure which shows the example of an attribute definition table (short-term change attribute).
  • the table figure which shows the example of an attribute definition table (attribute group management table).
  • the table figure which shows the example of a group definition management table (attribute group management table).
  • the table figure which shows the example of a group definition management table (attribute group management table).
  • the flowchart explaining the detail of a group definition / member list creation process The top view which shows the example of the setting screen of a data processing system.
  • the flowchart explaining the addition / change process of a gene management database etc.
  • the detailed flowchart of a member list update / addition process Overall flow chart of processing at the time of new gene discovery.
  • the flowchart which shows the detail of the reexamination of DND data.
  • the table figure which shows the example of an attribute related intensity
  • notations such as “first”, “second”, and “third” are attached to identify the constituent elements, and do not necessarily limit the number or order.
  • a number for identifying a component is used for each context, and a number used in one context does not necessarily indicate the same configuration in another context. Further, it does not preclude that a component identified by a certain number also functions as a component identified by another number.
  • a new function of a gene needs to be rescanned for the presence or absence of the gene in the gene database, it is selected based on the characteristics of the new function and based on the attributes of the person to be scanned.
  • a rescan target person is extracted using a plurality of attribute groups including one or a plurality of attributes.
  • the characteristics of the new function of the gene include, for example, the body temperature and blood due to the expression of the gene, other numerical effects on the body, and the strength of the relationship between the gene and the other gene. Includes general gene characteristics. Such features of new gene functions are converted into data as knowledge based on logical or clinical research results.
  • the attributes of the person being scanned include biological universal attributes such as blood type, gender, presence of specific genes, physical attributes such as height, weight, and age, and attributes related to living environment such as residence and occupation , Sleep time and exercise amount, eating habits, attributes related to lifestyle such as smoking and drinking, health checkup results, medical information such as medical history, and the like.
  • biological universal attributes such as blood type, gender, presence of specific genes, physical attributes such as height, weight, and age, and attributes related to living environment such as residence and occupation , Sleep time and exercise amount, eating habits, attributes related to lifestyle such as smoking and drinking, health checkup results, medical information such as medical history, and the like.
  • invariant attribute that does not change in time and a change attribute that changes in time
  • the change attribute includes a long-term attribute and a short-term attribute depending on the cycle of the change.
  • there are two types of attributes that is, subdivided by classification (category) and subdivided by strength (level).
  • a plurality of attribute groups composed of one or a plurality of attributes are created based on past knowledge such as expert knowledge and medical literature contents.
  • Each of these attribute groups has a predetermined meaning or definition based on past knowledge. For example, “relevant to visual acuity”, “relevant to obesity”, and the like.
  • the following describes a system that provides users with risk reports and health advice based on the functions of newly discovered genes in a service that provides health advice based on genetic analysis.
  • FIG. 1A is a diagram showing an overall concept of a service according to an application example of this embodiment.
  • the information provider 110 describes a service that provides significant information regarding the maintenance and promotion of the health of the user (service user) 100 and disease prevention.
  • a partner organization of the information provider 110 a gene analysis company 120, a partner hospital 130, a disease research institute, a genetic research institute, and various research institutions 140 such as a university are assumed. May be.
  • the user 100 makes an application 190 for receiving service provision to the information provider 110 in electronic form or paper format via the Internet, and at the same time or at a later date, a sample to be subjected to gene analysis processing is sent to the information provider 110. provide.
  • the service provider 110 Upon receiving the application, the service provider 110 performs an application process 111, and performs predetermined processes such as user registration in various databases and issuance of IDs.
  • the sample is sent to the gene analysis company 120 with which the sample is affiliated (191).
  • the sent specimen is subjected to gene analysis processing 121 using various methods such as a DNA sequencer to obtain DNA sequence information (gene information).
  • the obtained genetic information is digitized and sent to the information provider 110 as DNA data (192).
  • the information provider 110 stores the user ID and gene data created by the application process 111 in the gene management database 112 that accumulates the user ID of the user 100 and the user's DNA data in association (added for new users). )
  • User 100 receives a wearable device for obtaining physical information after applying for a service.
  • the user uses a wearable device or the like to send various physical information to the information user (193).
  • These pieces of information are stored in the activity information database 113.
  • the data stored in the activity information database 113 is subjected to data editing 114 according to separately defined attributes and their classifications (or levels) and stored in the user attribute database 115.
  • attributes and their classification considering the health implications of various data, we have obtained knowledge from 140 partners, researchers 141, various research institutes such as disease research institutes and genetic research institutes, and various databases 142. Decide on the basis.
  • the information acquired at that time is converted into data and stored in the medical examination database 131.
  • All or a part of the data in the medical examination database 131 is provided to the information provider 110 based on a data use license agreement given in advance from the user 100 to the hospital 130 (194).
  • the provided data is also edited according to the attribute group definition and stored in the user attribute database 115.
  • the user attribute database 115 various kinds of information relating to or affecting the health condition and physical condition of the user 100 are converted into data according to the attribute group definition and stored.
  • the user attribute database 115 can also store data based on information in the gene management database 112, data based on information obtained when the user 100 applied for service, and others.
  • the information provider 110 creates data as service content to be provided to the user 100 based on the information in the gene management database 112, the user attribute database 115, or other information (195), and the portal database 116. To store. When creating content, it is preferable to receive support from a partner hospital 130, a disease research institute, a genetic research institute 140, or the like. The information provider 110 performs portal operation 117 based on the content of the portal database 116. The user 100 can use the portal via the Internet, for example, to receive information useful for his / her health promotion and disease prevention (196).
  • annotation information related to the gene may be stored by, for example, the affiliated gene research institute 140a.
  • Annotation information is also provided to the information provider 110 (197).
  • Annotation refers to a process of estimating where a base sequence is a gene. Further, a process for estimating the function of the gene may be included.
  • annotation information may include the name of the researcher who determined the base sequence and function, a reference, gene and plant information that approximates the position information of the gene (chromosome number, position on the chromosome, etc.), and the like.
  • the annotation information may be registered in the gene management database 112, for example.
  • a target member list that identifies the user 100 to be rescanned (preferentially) is created.
  • the user attribute database 115 defined by various attributes and classifications is used to extract users who satisfy a predetermined condition from them and create a member list. Under what conditions the attributes are defined and the user attribute database 115 is configured, and under what conditions the users are extracted and the member list is created, with support 198 from the affiliated research institution 140 and the like. decide.
  • the target member list is a list that is selected from the member list or created from the member list and to be rescanned.
  • the genetic research institute 140a it is assumed that a new gene is discovered in the genetic research institute 140a and the knowledge that this is deeply related to visual acuity is obtained. At this time, if it is known that the new gene causes a physically significant phenomenon in relation to the known gene, the presence or absence of the known gene is set as an attribute. In addition, the research results are shared with the disease research institute 140b.
  • the Research Institute for Diseases extracts factors (attributes) other than genes that are considered to be related to visual acuity from various clinical research data, expert knowledge and medical literature. For example, the outdoor ultraviolet irradiation amount, the workplace environment, and the like. In this way, a related attribute is extracted with a certain medical purpose, and an attribute group is created.
  • the attributes related to the new gene are the presence or absence of a known gene, the amount of ultraviolet irradiation, and the work environment. Then, using the attribute group definition, the members that satisfy the predetermined condition for each attribute are extracted, and the target member list is created.
  • a member having a known gene, an ultraviolet ray irradiation amount of a predetermined value or more, and a work environment that is an outdoor member is extracted.
  • Members listed in the created target member list are likely to have a significant effect on visual acuity in relation to new genes. Therefore, it is desired to preferentially confirm the presence or absence of a new gene.
  • FIG. 1B shows an outline of data processing in this embodiment.
  • the user attribute definition and the attribute data are collected as described above, and the user attribute database 115 is constructed.
  • an attribute group including a predetermined combination of attributes is defined, and a group definition management table 306 (described later) is constructed. Thereby, the user is classified according to the condition and level of each attribute of the user, and a member list is obtained in which the user is classified into a plurality of attribute groups that match the predetermined condition and level.
  • the above is constructed at the start of system operation, and is newly constructed, modified, and modified during system operation. Separately from this, the DNA data of the user 100 is stored in the gene management database 112.
  • step S103 as a preparation for selecting a group to be used for extracting a user to be scanned for a new gene from a defined attribute group and creating a target member list, the relation strength between the new gene and each attribute Is defined or set, and an attribute-related strength management table 307 (described later) is created.
  • the attribute-related strength management table 307 is referred to, and based on this, each attribute group is evaluated or scored, and an attribute group having a large relationship strength with a new gene is used to extract users to be scanned. Select as an attribute group. Along with this, a list of service users belonging to the attribute group is also generated.
  • process S105 conditions are added to the attributes of the selected attribute group as necessary, and further filtering is performed to create a target member list.
  • the user's DNA data included in the target member list stored in the gene management database 112 is scanned for new genes.
  • the processing in FIG. 1B is an example, and it is not always necessary to perform the same processing.
  • the attribute that is the framework of the extraction condition is evaluated by the attribute-related strength management table, the highly relevant attribute is selected, the selected attributes are combined, the condition is set for each attribute, and the extraction is performed at the timing before processing S106.
  • Conditions may be designed. In this case, the processes S102, S104, and S105 in FIG. 1B can be omitted.
  • the attribute strength management table creation S103 may not be performed every time a new gene is discovered, but may be prepared and selected in advance.
  • the attribute group definition S102 may be selected from the attributes after the processing of S103 each time, instead of preparing the definition in advance.
  • FIG. 2 is a ladder chart during normal operation showing the concept of processing in this embodiment.
  • FIG. 2A is a chart for explaining a use start phase of a service user (individual user).
  • the service user 100 displays an intention to apply for the service to the information provider 110. These may be performed online such as the Internet or may be performed by filling in a predetermined form.
  • the information provider 110 creates an associated database entry for the service user.
  • a prescribed form (document) conforming to the law such as a contract for providing the service, an agreement on the use of the personal information of the obtained service user, an entry sheet for personal information necessary for the service, etc. It is sent to the service user 100.
  • a test kit for gene information analysis is sent to the service user.
  • process S203 the service user 100 fills in a document and collects samples, and sends them to the information provider 110. At the same time or at a later date, the usage fee will be paid.
  • process S204 the document content is converted into data and stored in a database. After anonymizing the sample, the gene analysis company 120 is requested to perform analysis.
  • FIG. 2B is a chart for explaining a phase of creating a service user related information database following the processing of FIG. 2A.
  • the gene analysis company 120 analyzes the gene of the sample sent from the information provider 110 and sends the analysis data to the information provider 110.
  • gene analysis refers to analyzing a sample with a DNA sequencer or the like, clarifying the base sequence and converting it into data.
  • process S206 the DNA data of the service user provided from the gene analysis company 120 is (added) registered in the gene management database 112. At this time, all DNA data may be registered, but only a necessary part may be registered.
  • process S207 the analysis result and advice information based on the analysis result are provided to the service user 100. It also provides services such as providing medical checkup coupons at partner hospitals and types of health equipment and measuring devices (for example, wearable devices) suitable for users.
  • FIG. 2C is a chart for explaining the service flow that the service user 100 can receive during the contract with the information provider 110 following the processing of FIG. 2B.
  • process S208 the service user 100 receives a regular health checkup at the affiliated hospital 150.
  • the hospital 150 notifies the service user 100 and the information provider 110 of the examination / diagnosis results.
  • the examination / diagnosis result is, for example, data stored in the health diagnosis database 131.
  • the consent of the service user 100 is obtained in advance.
  • the service user 100 can constantly monitor his / her health condition by using the measuring device provided (or lent) to the service user 100 in the process S207.
  • data on a user's exercise state for example, the number of steps, sleep time
  • health state for example, pulse, body temperature
  • a wristwatch-type wearable device incorporating various sensors such as an acceleration sensor and a temperature sensor.
  • the data acquired by the measuring device is transmitted to the information provider 110 through a network, for example.
  • the transmission may be performed according to an instruction from the service user, or may be automatically performed periodically by software built in the measuring device. Needless to say, legal requirements are required in the series of processing.
  • the information provider 110 registers the health check data, measurement device data, and the like in the health check database 131 and the activity information database 113. Also, it is registered in the user attribute database 115 at a predetermined timing.
  • the experts of the genetic research institute 140a and the disease research institute 140b comprehensively view the gene analysis results, the medical examination data, and the data of the measuring equipment to create advice information and report it to the information provider 110. At this time, it is assumed that the service user information is anonymized.
  • additional information is created based on the advice information of the gene research institute 140a and the disease research institute 140b, in addition to the gene analysis result and the medical examination data, and provided to the service user 110.
  • an incentive may be provided according to the status of the service user.
  • process S214 the service user uses or requests the information service in response to a notification from the information provider 110 or voluntarily. Requests are easy to make using email or an internet browser.
  • the portal 117 established by the information provider 110 can be used (see FIG. 1A).
  • Processing S208 to processing S214 are executed once or a plurality of times periodically or at an arbitrary timing during the contract of the service user 100.
  • the information provider 110 deletes data related to the service user 100 in the database managed by the information provider 110, and also instructs the affiliated genetic research institute 140a and disease research institute 140b to delete the data. Such an obligation to delete data may be specified in advance in the contract.
  • the affiliated genetic research institute 140a and disease research institute 140b delete the data and report it to the information provider 110.
  • process S218 after confirming the deletion of all related data, the information provider 110 notifies the service user 100 of data deletion and cancellation completion, and the service ends in process S219.
  • FIG. 3 is a block diagram illustrating an example of a data processing system 300 for the information provider 110 to process data.
  • Data processing is performed by an input device 301 such as a keyboard and an interface, a processing device 302 for processing data, a storage device 303 including a magnetic storage device and a semiconductor memory, and an output device 304 including an image display device (monitor) and a printer.
  • an input device 301 such as a keyboard and an interface
  • a processing device 302 for processing data a storage device 303 including a magnetic storage device and a semiconductor memory
  • an output device 304 including an image display device (monitor) and a printer.
  • the data to be processed and created is stored as the gene management database 112, the activity information database 113, and the user attribute database 115 described in FIG. Moreover, you may have copies, such as the medical examination database 131 which the hospital 130 has, the gene related information database 142 which the research institution 140 has. Further, it has an attribute definition table 305, a group definition management table 306, an attribute related strength table 307, a member list 308, a group detail management table 309, and a group condition policy management table 310 which will be described later.
  • the user database 311 stores various types of user information obtained when the service user 100 applied for a service (S201 in FIG. 2A).
  • FIG. 4 shows an example of the gene management database 112.
  • DNA data 402 obtained by the gene analysis processing 121 is stored.
  • additional information 403 additional information such as data on the user 100 obtained in the application process 111 of FIG. 1 may be added.
  • an entry for a new user is added.
  • the DNA data 402 may store all base sequences, but may store only a necessary part in consideration of management costs and the like.
  • the gene management database 112 can be used for rescanning for a new gene search.
  • the gene management database 112 can be a scan target in order to identify the gene holder when a new gene is discovered.
  • the user ID 401 is preferably anonymized so that an individual cannot be identified.
  • FIG. 5 shows an example of the user attribute database 115.
  • Various attribute IDs 501 (described later) are stored for the user ID 401.
  • an entry for the new user is added, and data relating to the user is classified by the attribute classification described with reference to FIG.
  • the user attribute database 115 is referred to when a member corresponding to a predetermined condition is extracted from a predetermined attribute group (described later).
  • FIG. 6 is an example of the attribute definition table 305 that defines the definition of the user attribute database 115. These tables are managed in association with the user attribute database 115. There are various ways of defining attributes. In the example of FIG. 6, the attributes are classified from the viewpoint of temporal change.
  • FIG. 6A shows an example of a table for managing definitions of invariant attributes that are temporally invariant attributes.
  • Reference numeral 601 denotes an attribute ID, which uniquely indicates the type of attribute.
  • Reference numeral 602 denotes an invariant attribute type, which stores temporally invariant attributes such as sex and blood type.
  • 603 indicates the type of attribute, for example, C indicates an attribute indicating classification (category), and L indicates an attribute indicating level (intensity).
  • the column to the right of 604 shows the classification or level in each invariant attribute.
  • FIG. 6B shows an example of a table for managing the definition of long-term change attributes that change at long-term time intervals (for example, yearly).
  • Reference numeral 605 denotes an attribute ID, which indicates the type of attribute.
  • Reference numeral 606 denotes a type of long-term change attribute. For example, it stores medically meaningful attributes that change in one to ten years or more, such as a place of residence and age.
  • the column to the right of 607 shows the classification or level in each invariant attribute.
  • FIG. 6C shows an example of a table for managing definitions of medium-term change attributes that change at medium-term time intervals (for example, monthly).
  • Reference numeral 608 denotes an attribute ID, which indicates the type of attribute.
  • 609 is a type of medium-term change attribute, and stores medically meaningful attributes that change from about a month to one year, such as weight and smoking habits.
  • the column to the right of 610 shows the classification or level in each invariant attribute.
  • FIG. 6D shows an example of a table for managing the definition of the short-term change attribute that fluctuates at a short-term time interval (for example, in units of days).
  • Reference numeral 611 denotes an attribute ID, which indicates the type of attribute.
  • 612 is a type of short-term change attribute, and stores medically meaningful attributes that change from day to week, such as sleep time and exercise time.
  • the column to the right of 613 shows the classification or level in each invariant attribute.
  • the method is not limited to the method of determining the large classification based on the temporal change, but may be organized by other ways of thinking. For example, you may arrange
  • FIG. 6E shows an example of the attribute group management table 305 that defines attribute groups.
  • Reference numeral 614 denotes an attribute group ID indicating an attribute group.
  • 615 and subsequent attributes are attributes selected to form an attribute group.
  • templates are formed so that one each is selected from an invariant attribute, a long-term change attribute, a medium-term change attribute, and a short-term change attribute.
  • a template such as one from the long-term change attribute and five from the short-term change attribute may be used. That is, the combination of attributes is free.
  • the combination of attributes is constrained by a certain template to facilitate management and operation.
  • an attribute group can be configured by a combination of free attributes without forming a template. May be.
  • the user attribute database 115 defined by various attributes is used to extract users who satisfy a predetermined condition and create a target member list.
  • the attribute group management table is created in advance with the cooperation of researchers and experts 141 from the genetic research institute 140a and the disease research institute 140b.
  • each attribute table is generally registered (eg, gender, age, etc.), and data obtained from wearable devices and health check data by experts 141. You can define and add.
  • the classification of the subject includes a category (for example, blood type and place of residence) and a direct level (for example, smoking habit and sleep time).
  • a category for example, blood type and place of residence
  • a direct level for example, smoking habit and sleep time
  • what represents a category can also be associated with a level by digitizing the standard deviation in the set. For example, in the case of the attribute “Za02” indicating the blood type in FIG. 6C, if the blood type is Japanese, the type A with a high ratio can be positioned at a low level, and the type AB with a low ratio can be positioned at a high level.
  • an attribute group is selected from the attribute group management table of the attribute definition table 305, a condition is added to the attributes constituting the attribute group, and filtering is performed.
  • Create a target member list A specific example of setting conditions for creating the target member list will be described with reference to FIG.
  • FIG. 7A is an example of the group definition management table 306 describing the group definition of the member list 308.
  • the target member list is selected from the defined member list, or the target member list is generated based on the member list (for example, narrowing down is performed).
  • Reference numeral 701 is a group ID for uniquely determining a group.
  • the group includes a set of service users whose attributes satisfy a predetermined condition. As will be described later, when searching for a holder for a new gene, an efficient search can be performed by selecting one of these groups.
  • Reference numerals 702 to 704 denote areas for setting group definitions.
  • Reference numeral 702 denotes the number of subgroups defined below the group.
  • Reference numeral 703 denotes a field for designating policy condition entries for extracting the member.
  • Reference numeral 704 denotes a column for setting the handling of the intermediate value subgroup when the subgroup is set based on the attribute level.
  • Sub-groups can be set as a kind of narrowing-down condition. For example, when the attribute has a level (intensity), it is considered that the phenomenon that is manifested becomes more remarkable as the subject has an extremely large or extremely small intensity. Therefore, it is desirable to increase the priority as the survey target. On the other hand, a subject with an intermediate strength has a low priority as a survey target, but it is difficult to be a survey target, and thus there may be a poor sense of receiving a service. Therefore, it may be possible to give consideration to the target person of the intermediate value, such as providing a service suitable for the target person. In this case, it is desirable for data protection to separate the medical data from the service list.
  • Reference numeral 705 and subsequent items are items to be referred to when selecting a group to be scanned for a new gene.
  • Reference numeral 705 denotes an area in which points added at the time of prioritizing groups are expressed numerically.
  • Reference numeral 706 denotes the presence or absence of an additional narrowing condition.
  • Reference numeral 707 denotes an entry point when there is an additional narrowing condition. By specifying additional refinement conditions, a more detailed extraction method becomes possible.
  • Reference numeral 708 denotes a priority order based on the priority addition result 705.
  • 705 to 708 are the evaluation results of the priority order by one evaluation item, and the columns after 709 are columns for additional evaluation items. These will be described in detail later.
  • FIG. 7B shows a group detail management table.
  • the group detail management table is a table showing details of each group 701 defined in FIG. 7A. For example, since the group “Fat_G01” in FIG. 7A has two subgroups, the group “Fat_G01” in the group ID 710 and the two subgroups “Fat_G01-01” and “Fat_G01-02” in FIG. To manage.
  • the sub group flag 711 indicates whether or not the group is a sub group.
  • a list ID 712 indicates a list of service users 100 (for example, a list of user IDs 401) included in the group, and 713 indicates the number of members.
  • the column after 714 is a column indicating the result of scanning the new gene when the group is selected.
  • Reference numeral 714 represents the number of rescanned members
  • reference numeral 715 represents the number of members having the target new gene.
  • FIG. 7C shows a group condition policy management table.
  • Reference numeral 716 denotes a policy ID for specifying the policy
  • 717 denotes a logical expression that is the content of the policy
  • 718 and subsequent figures indicate the contents of each item of the logical expression.
  • FIG. 8 is a diagram for explaining the setting / creating process of the gene management database 112, the user attribute database 115, and the member list 308 in the present embodiment. Basically, it is assumed that a plurality of users are registered and the related database is constructed first.
  • process S801 a record in the gene management database 112 is defined and data is set.
  • the database is created when the system service starts.
  • data is added each time or by batch processing (step S207 in FIG. 2B).
  • process S802 a process for defining and setting a record in the attribute definition table 305 and the user attribute database 115 is performed.
  • the database is created when the system service starts. Further, when a new user 100 is added or data is changed, a process for adding, changing, or deleting data is performed each time or by batch processing (process S212 in FIG. 2C, etc.).
  • attribute information there are various types of attribute information as described above, but in addition to what should be generally registered (for example, gender, age, etc.), based on data acquired from wearable devices and medical examination data, Defined by expert knowledge and consideration, added as needed.
  • a service user attribute database in which the service user ID is associated with various attribute information of the service user is constructed.
  • process S803 a group of search members is defined and a member list 308 is created.
  • FIG. 9 is a flowchart for explaining details of the group definition / member list creation processing S803 in FIG. Basically, it is assumed that a plurality of users are registered and the related database is constructed first.
  • process S901 the group ID 701 in the group definition management table 306 shown in FIG. 7A is input / selected. In the case of new creation, a new entry is created. If you want to recall or modify an existing group, you can select it.
  • process S902 the policy condition 703 in FIG. 7A is set / changed. Further, an intermediate value subgroup handling 704 is set as necessary. Alternatively, a desired policy is set by changing the logical expression 717 and conditions 718 to 720 after the group condition policy management table of FIG. 7C.
  • a member list for storing a member list that matches the policy set above is initialized.
  • the member list is a file that associates the group ID 701 or 710 with the ID 401 of the user 100 belonging to the group.
  • the list ID is an ID for identifying the list, which is indicated by 712 in FIG. 7B.
  • process S904 the head of the user attribute database 115 is pointed and the subsequent processes are sequentially performed on the service user data.
  • process S905 the user attribute database 115 is referred to and it is determined whether or not the attribute of the service user matches the designated policy. If they do not match, the process proceeds to step S907.
  • process S906 information that can be associated with the target personal ID is added to the member list 308.
  • information that can be associated with the target personal ID in the member list for example, there is a personal ID itself.
  • another ID may be used.
  • process S907 the presence / absence of the next entry in the user attribute database 115 is checked. If there is no next entry, the process ends. If there is a next entry, the process proceeds to step S908.
  • process S908 the next entry in the user attribute database 115 is pointed, and the same process is repeated from process 905 to the end.
  • the members extracted as a result of the processing are stored in the list indicated by the list ID 712 in FIG. 7B.
  • the number of members is displayed at 713 in FIG. 7B.
  • the result of the new gene scan performed on the extracted list members is stored in the tables 714 to 715 of FIG. 7B.
  • various database information is once redefined and integrated into the user attribute database 115. Therefore, it is only necessary to refer to the user attribute database 115 as to whether the user attribute matches the policy.
  • the user attribute database 115 is not created, and the base database (the activity information database 113, the health check database 131, the user database 311, etc.) is directly searched based on a specified policy. Good.
  • the base database the activity information database 113, the health check database 131, the user database 311, etc.
  • FIG. 10 is an example of the setting screen of the data processing system 300 shown in FIG. 3 used in the group definition / member list creation processing S803 described with reference to FIG. Show.
  • the group name input area 1001 sets the group name. That is, an easy-to-understand name can be set in association with the group ID indicated by 701 in FIG. 7A.
  • the set data is called with the Load button 1002 on the right side.
  • An area 1003 displays a group ID.
  • a group attribute condition can be set by designating a group name or attribute name.
  • the set condition is displayed in the conditional expression display field 1005.
  • the display method of the conditional expression is arbitrary, in this example, the attribute ID is expressed in a format of attribute ID-condition number [number of sub groups].
  • an attribute classification, an attribute name, an attribute ID, an attribute classification or level, a filter condition, a sub group, a target number of people, etc. are designated or displayed.
  • the attribute category can be selected in a pull-down format. From the selected attribute category, pull-down items for which choices such as attribute names and attribute members / levels that can be selected are determined. Can be configured to select.
  • the attributes registered in FIG. 6A to 6D can be selected by selecting the attribute classification (invariant / long term / medium term / short term). If the attribute group is made into a template as shown in FIG. 6E, the work becomes easy. For example, in the example of FIG. 10, the structure of the attribute group is made into a template, and a genotype can be designated with each one from the invariant / long-term / medium-term / short-term attributes.
  • Attribute name an individual attribute item or gene name is selected.
  • attribute ID an identifier assigned to each of the selected attribute and gene is called from the attribute definition table of FIG. 6 and automatically displayed.
  • attribute classification / level is used to specify the target of the lower hierarchy group of the attribute or gene, and is used in combination with the filter condition.
  • filter condition selection conditions such as “select all”, “designation”, “more than”, and “less than” can be designated.
  • Sub group is used to input a policy for managing the attribute group as a sub group.
  • intermediate value deletion number of non-target groups
  • intermediate value priority number of target groups
  • attribute for example, in the case of blood types, a subgroup is created for each blood type.
  • the intermediate value deletion when the attribute indicates a level, the intermediate level is deleted from the target. For example, in the case of “intermediate value deletion 3” at five levels, only the highest and lowest levels are extracted. Intermediate value priority is the opposite.
  • “Number of target persons (guideline)” automatically displays the number of target persons who meet the conditions. By pressing the “Add” button, a condition is added to the conditional expression, and it is possible to select with the “ ⁇ / ⁇ ” key to edit or delete the line concerned.
  • the group definition management table 306, the group condition policy management table 310, and the member list 308 are set, and data is stored in each.
  • the member list 308 needs to be changed when the user 100 is added or when the attribute information is added and the user attribute database 115 is changed. Whether to perform the processing each time or batch processing is arbitrary, but batch processing seems to be more efficient. An example of the addition / change process will be described with reference to FIG.
  • FIG. 11 is a diagram illustrating the addition / change processing of the gene management database 112, the user attribute database 115, and the member list 308 in the present embodiment.
  • process S1101 the definition of the record in the gene management database 112 is changed as necessary, and the data is reset.
  • data is added each time or by batch processing (processing S206 in FIG. 2B, etc.).
  • process S1102 a process for changing and adding records to the attribute definition table 305 and the user attribute database 115 is performed. Further, when a new user 100 is added or data is changed, a process of adding, changing, or deleting data is performed each time or by batch processing (process S211 in FIG. 2C, etc.).
  • the member list 308 is updated or additionally created.
  • FIG. 12 is a detailed flowchart of the member list 308 update / addition processing S1103.
  • process S1201 the first entry of the group definition management table 306 shown in FIG. 7A is designated.
  • process S1202 the condition policy defined in the group definition management table 306 is read with reference to the group condition policy management table 310.
  • process S1203 the data of the user attribute database 115 is referred to, and the user 100 that matches the condition policy is extracted.
  • process S1204 the user who matches the policy set above is added to the member list 308 as information that can be associated with the target personal ID.
  • process S1205 the number of members of the corresponding entry in the group detail management table 309 is incremented by 1 (column 713 in FIG. 7B).
  • process S1206 it is confirmed whether or not the next entry exists in the group definition management table 306. If there is an entry, the process proceeds to step S1207. If not, all member lists have been updated, and the process ends.
  • process S1207 the next entry in the group definition management table 306 is designated, and the process is repeated from process S1202.
  • FIG. 13A is an overall flow of processing when discovering a new gene.
  • processing S1301 it is assumed that a new function of a gene that has not been analyzed at first is discovered in the genetic research institute 140a or the like.
  • step S1302 with the cooperation of the genetic research institute 110, the disease research institute 140, etc. with the information provider 110 as the main subject, the attribute that is considered to be related to the gene is selected, and the strength of association (association strength) is set .
  • the information provider 110 uses the data processing system 300 to determine relevance with an attribute group and determine priority.
  • step S1304 the attribute group is selected and the target member is registered in the list.
  • the service users specified in the attribute group may be registered as target members as they are, or additional conditions are added from the service users specified in the attribute group to extract members. Also good.
  • process S1305 the members of the target member list are rescanned for the presence or absence of a new gene.
  • the rescan can be rescanned using that data. Such processing can be performed by the information provider when the information provider 110 has sufficient hardware and software resources.
  • the gene analysis company 120 is supported. receive. At this time, it can be performed again from the collection of the specimen. The flow of processing in this case will be described with reference to FIG. 13B.
  • FIG. 13B shows details of the DND data review S1305.
  • the information provider 110 makes a reanalysis request to the gene analysis company 120.
  • the sample of the service user included in the target member list is sent if necessary.
  • the gene analysis company 120 reanalyzes the sample with a DNA sequencer to obtain DNA data. In addition, whether or not a new gene is included in the DNA data is analyzed. The obtained data is sent to the information provider 110.
  • the information provider 110 registers and updates the obtained data in various databases.
  • process S13054 based on the data registered in various databases of the information provider 110, the service users included in the target member list are determined one by one for the final gene existence. This process is repeated as necessary (process S13055).
  • Processing S1306 is optional, but may cooperate with the genetic research institute 140a or the like to share various information and provide information and infrastructure that contribute to genetic research.
  • Processing S1307 requests the service user 100, which is assumed to be related to the new gene, to perform additional additional hearing and data provision.
  • step S1308 after obtaining information from the service user 100, the acquired data is registered in various databases in step S1309. Until the correspondence is completed for all the users, the period between the symbols (A) and (A) in FIG. 13A is repeated.
  • FIG. 14 is a detailed flowchart of the preparatory process S1302 for the group priority determination process.
  • process S1401 a new gene is registered in the gene database 311.
  • process S1402 attribute information is associated with gene-related information. Details of the process S1402 will be described below. This processing is performed using existing knowledge mainly by the information provider 110 and in cooperation with the affiliated genetic research institute and disease research institute 140.
  • step S1403 attribute information related to the new gene is selected.
  • process S1405 it is examined whether there are other related attributes.
  • the attribute-related strength information evaluated is converted into electronic data and set (input) in the attribute-related strength management table 307 of the storage device.
  • the attribute-related strength of the gene is defined by the following processing procedure.
  • a new functional gene Xn is related to lipid metabolism, and among the Xn types, Xnz type is information that is three times higher than the normal hypertension risk is new gene-related information. .
  • attribute information related to obesity, hypertension, lipid metabolism, etc. is selected, and the strength of each attribute information is determined.
  • attributes with low relevance may be excluded at the selection stage.
  • Such processes S1403 to S1405 are usually determined by a meeting (conference) between experts of the genetic research institute or disease research institute.
  • FIG. 15 shows an example of the attribute-related strength management table 307 set (input) in step S1406.
  • 1501 indicates a gene name.
  • 1502 shows the target genotype.
  • Reference numeral 1503 indicates the number of attributes associated with the gene.
  • the attribute name 1504 and the relation strength 1505 for each attribute are stored.
  • FIG. 16 is a detailed flow of attribute group and relevance determination and priority determination processing S1303.
  • the target gene name and target type are set. That is, one or more genes are selected from the gene names 1501 in the attribute-related strength management table 307 (FIG. 15) in FIG. Also, the priority ranking additional area 705 and the priority ranking storage area 708 of the group definition management table 306 (FIG. 7A) are initialized.
  • process S1603 the determination policy of the corresponding group condition policy management table 310 (FIG. 7C) is referred to.
  • condition columns 718 to 720 and the subsequent items in the group condition policy management table 310 are referred to and it is determined whether or not the attribute related to the target gene is included in the determination policy. That is, it is checked whether the condition column 718 to 720 of the group condition policy management table 310 has an attribute stored in the attribute column 1504 of the selected gene of the attribute related strength management table 307.
  • step S1605 if the determination policy includes an attribute related to the target gene, the attribute-related strength management table 307 is referred to, and a score corresponding to the strength level of the target attribute is stored in the group definition management table 306. It adds to the priority addition point area 705.
  • process S1606 the group condition policy management table 310 is checked for the presence of the next entry. If there is a next entry, the process proceeds to step S1607, and if not, the process proceeds to step S1608.
  • process S1607 the next entry in the group condition policy management table 310 is pointed, and the process is repeated from process S1603 until the last entry.
  • step S1608 after the processing is completed up to the last entry, the rank is stored in the priority storage area 708 in the order of high score in the priority adding area 705 of the group definition management table 306.
  • the rank is stored in the priority storage area 708 in the order of high score in the priority adding area 705 of the group definition management table 306.
  • process S1609 if the highest score in the priority adding area 705 is equal to or greater than the threshold value, the process ends.
  • step S1610 If the highest score in the priority adding area 705 is less than the threshold value, the process proceeds to step S1610. In this case, it means that there is no correlation between the target gene and the attribute group, so the configuration of the group definition management table 306 (FIG. 7A) is reviewed to create a new group, or the attribute-related strength management table 307. The configuration of FIG. 15 will be reviewed. Alternatively, existing attribute groups may be narrowed down with predetermined attributes. The above-mentioned various methods may be compared to select a method that is superior in terms of time and cost.
  • the user of the member list corresponding to the attribute group having a higher priority is selected to create the target member list (S1304).
  • the service user of the target member list rescans whether or not the target gene is present (S1305).
  • the members are filtered so as not to be rescanned. Output a list.
  • This example can also be applied to prioritization when a specific gene is rescanned in a research institute such as a genetic laboratory or a disease laboratory.
  • the reanalysis group can be narrowed down by this example when reanalyzing a newly discovered gene.
  • the configuration for realizing the processes and systems of the above embodiments may be configured by a single computer, or any part of the input device, output device, processing device, and storage device may be connected via a network.
  • the computer may be configured.
  • the idea of the invention is equivalent and unchanged.
  • the present invention is not limited to the above-described embodiment, and includes various modifications.
  • a part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment.

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  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Epidemiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Primary Health Care (AREA)
  • Public Health (AREA)
  • Apparatus Associated With Microorganisms And Enzymes (AREA)

Abstract

La présente invention a pour but d'identifier un utilisateur transportant un gène ayant une nouvelle fonction lorsque le gène est découvert. La présente invention concerne un procédé pour extraire un sujet d'une recherche génétique qui est réalisée avec un dispositif de traitement d'informations équipé d'une unité d'entrée, d'une unité de traitement, d'une unité de stockage et d'une unité de sortie, en vue de l'extraction d'un utilisateur sujet sur lequel est effectuée la recherche dans une base de données d'ADN pour un gène d'intérêt parmi de multiples utilisateurs. Dans le procédé, une table de gestion de définition de groupe et une table de gestion d'intensité de relation d'attribut sont utilisées. La table de gestion de définition de groupe définit de multiples conditions d'extraction pour extraire l'utilisateur, chacune des multiples conditions d'extraction étant mise en corrélation avec au moins un attribut de l'utilisateur. La table de gestion d'intensité de relation d'attribut définit l'intensité de la relation entre le gène d'intérêt et l'attribut. Le procédé comprend : une étape d'évaluation consistant à évaluer le degré de la relation entre les multiples conditions d'extraction et le gène d'intérêt en référence à la table de gestion d'intensité de relation d'attribut ; et une étape d'extraction consistant à sélectionner au moins une condition d'extraction parmi les multiples conditions d'extraction sur la base des résultats d'évaluation puis à extraire une liste de membres sujet sur la base de la condition d'extraction sélectionnée.
PCT/JP2015/058573 2015-03-20 2015-03-20 Procédé et système pour extraire un sujet d'une recherche génétique WO2016151702A1 (fr)

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Cited By (1)

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Publication number Priority date Publication date Assignee Title
EP4128679A4 (fr) * 2020-03-26 2024-04-24 Janssen Biotech, Inc. Annotation et gestion de données numériques thérapeutiques ou biologiques

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WO2002044967A1 (fr) * 2000-11-30 2002-06-06 Hitachi, Ltd. Procede et systeme permettant de delivrer des informations d'analyse genetique et procede d'identification permettant une authentification
JP2008226166A (ja) * 2007-03-15 2008-09-25 Japan Health Science Foundation 健康管理介入支援装置、健康管理介入支援システム、健康管理介入支援方法並びに健康管理介入支援プログラムおよびこれを記録したコンピュータ読み取り可能な記録媒体
JP2012003750A (ja) * 2010-06-15 2012-01-05 Genome Research Foundation ゲノム情報を用いてオンライン上のソーシャルネットワークを形成するシステムおよびその形成方法

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WO2002044967A1 (fr) * 2000-11-30 2002-06-06 Hitachi, Ltd. Procede et systeme permettant de delivrer des informations d'analyse genetique et procede d'identification permettant une authentification
JP2008226166A (ja) * 2007-03-15 2008-09-25 Japan Health Science Foundation 健康管理介入支援装置、健康管理介入支援システム、健康管理介入支援方法並びに健康管理介入支援プログラムおよびこれを記録したコンピュータ読み取り可能な記録媒体
JP2012003750A (ja) * 2010-06-15 2012-01-05 Genome Research Foundation ゲノム情報を用いてオンライン上のソーシャルネットワークを形成するシステムおよびその形成方法

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