Predisposition Modification Using Co-associating Bioattributes

• US 20080228705A1
• Filed: 01/11/2008
• Published: 09/18/2008
• Est. Priority Date: 03/16/2007
• Status: Abandoned Application

• Current Assignee: 23andme Incorporated (23andMe Holding Co.)
• Original Assignee: Expanse Networks, Inc.
• Inventors: Eldering, Charles Anthony, Kenedy, Andrew Alexander
• Application Number:
  US11/972,640
• Publication Number:
  US 20080228705A1
• Time in Patent Office: Days
• US Class Current: 707/2
• CPC Class Codes: G06F 16/00 Information retrieval; Database structures therefor; File system structures therefor
• CPC Class Codes: G06F 16/2282 Tablespace storage structures; Management thereof
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: G06F 16/955 using information identifiers, e.g. uniform resource locators [URL]
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G09B 19/00 Teaching not covered by other main groups of this subclass teaching or practice apparatus for gun-aiming or gun-laying F41G3/26
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 20/20 Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• CPC Class Codes: G16B 20/40 Population genetics; Linkage disequilibrium
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/70 : for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16H 70/20 : relating to practices or guidelines
• CPC Class Codes: H04L 67/306 : User profiles

Abstract

A bioinformatics method, software, database and system are presented in which attributes that modify an individual'"'"'s predisposition for association with a query attribute (i.e., an attribute of interest) are identified. A predetermined set of attribute combinations that are statistically associated with the query attribute is used as the basis for identifying those attributes that can be added to or eliminated from the attribute profile of the individual in order to modify the individual'"'"'s statistical predisposition for association with the query attribute.

Claims

1. A bioinformatics method for identifying attributes that modify an individual'"'"'s predisposition for association with a query attribute, comprising:

a) receiving a query attribute;

b) accessing an attribute profile of an individual, wherein the attribute profile comprises pangenetic attributes and non-pangenetic attributes;

c) accessing a set containing attribute combinations and corresponding statistical results that indicate the strength of association of each of the attribute combinations with the query attribute;

d) identifying, from among the attribute combinations contained in the set, one or more attribute combinations each containing at least one attribute from the attribute profile; and

e) transmitting one or more attributes that constitute differences between the identified attribute combinations and the attribute profile as output to indicate attributes that modify the individual'"'"'s predisposition for association with the query attribute.

2. The bioinformatics method of claim 1, wherein the output is transmitted to at least one destination selected from the group consisting of a user, a database, a dataset, a computer readable memory, a computer readable medium, a computer processor, a computer network, a printout device, a visual display, and a wireless receiver.

3. The bioinformatics method of claim 1, wherein the query attribute is a combination of two or more attributes.

4. The bioinformatics method of claim 1, wherein the attributes transmitted as output are non-pangenetic attributes that can be used to modify the attribute profile of the individual.

5. The bioinformatics method of claim 1, wherein step (e) further comprises transmitting at least a portion of the corresponding statistical results as output to indicate the individual'"'"'s statistical predisposition for association with the query attribute upon modifying the attribute profile of the individual with the transmitted attributes.

6. The bioinformatics method of claim 1, further comprising:

f) associating the output with the individual and storing the association.

7. The bioinformatics method of claim 1, wherein the attributes transmitted as output in step (e) are stored to generate a set of attributes for predisposition modification of the individual, the method further comprising:

f) repeating steps (a)-(e) for a succession of query attributes to generate a plurality of sets of attributes for predisposition modification of the individual;

g) identifying how many of the plurality of sets of attributes contain each of the attributes that occurs in at least one of the plurality of sets of attributes; and

h) generating a tabulation containing the attributes that occur in the plurality of sets of attributes, wherein the attributes in the tabulation are rank-ordered based on how many of the plurality of sets of attributes contain each attribute and the corresponding statistical results, to indicate which of the attributes have the largest influence on the individual'"'"'s predisposition for association with the succession of query attributes.

8. The bioinformatics method of claim 1, wherein step (d) further comprises:

i) rank-ordering the identified attribute combinations based on their attribute content and the corresponding statistical results; and

ii) selecting the identified attribute combinations that meet a predetermined threshold applied to rank for transmission as output.

9. The bioinformatics method of claim 1, wherein step (d) further comprises:

i) identifying modifiable attributes within each of the identified attribute combinations; and

ii) identifying a subset of the modifiable attributes for transmission as output, wherein the subset comprises modifiable attributes that do not occur in the attribute profile of the individual.

10. The bioinformatics method of claim 1, wherein step (d) further comprises generating a rank-ordered tabulation of the identified attribute combinations, wherein the rank-order of the identified attribute combinations contained in the tabulation is based on the corresponding statistical results and the number of attributes contained in each of the identified attribute combinations that do not occur in the attribute profile of the individual.

11. The bioinformatics method of claim 1, wherein identifying attribute combinations in step (d) further comprises:

i) identifying, from among the attribute combinations contained in the set, the largest attribute combination that consists of attributes occurring in the attribute profile; and

ii) identifying, from among the attribute combinations contained in the set, even larger attribute combinations that contain the largest attribute combination identified in step (i), wherein the difference in attribute content between the largest attribute combination and each of the even larger attribute combinations comprises attributes that can be added to the attribute profile to modify the individual'"'"'s predisposition for association with the query attribute.

12. The bioinformatics method of claim 1, wherein identifying attribute combinations in step (d) further comprises:

i) identifying, from among the attribute combinations contained in the set, the largest attribute combination that consists of attributes occurring in the attribute profile; and

ii) identifying, from among the attribute combinations contained in the set, smaller attribute combinations that consist of attributes from the largest attribute combination identified in step (i), wherein the difference in attribute content between the largest attribute combination and each of the smaller attribute combinations comprises attributes that can be eliminated from the attribute profile of the individual to modify the individual'"'"'s predisposition for association with the query attribute.

13. The bioinformatics method of claim 1, wherein the identity of the individual is masked or anonymized.

14. The bioinformatics method of claim 1, wherein each of the attribute combinations contains at least one pangenetic attribute, at least one physical attribute, at least one behavioral attribute, and at least one situational attribute.

15. A program storage device readable by a machine and containing a set of instructions which, when read by the machine, causes execution of a bioinformatics method for identifying attributes that modify an individual'"'"'s predisposition for association with a query attribute, comprising:

a) receiving a query attribute;

b) accessing an attribute profile of an individual, wherein the attribute profile comprises pangenetic attributes and non-pangenetic attributes;

c) accessing a set containing attribute combinations and corresponding statistical results that indicate the strength of association of each of the attribute combinations with the query attribute;

d) identifying, from among the attribute combinations contained in the set, one or more attribute combinations each containing at least one attribute from the attribute profile; and

e) transmitting one or more attributes that constitute differences between the identified attribute combinations and the attribute profile as output to indicate attributes that modify the individual'"'"'s predisposition for association with the query attribute.

16. The program storage device of claim 15, wherein step (e) further comprises transmitting at least a portion of the corresponding statistical results as output to indicate the individual'"'"'s statistical predisposition for association with the query attribute upon modifying the attribute profile of the individual with the transmitted attributes.

17. A bioinformatics database system for identifying attributes that modify an individual'"'"'s predisposition for association with a query attribute, comprising:

a) a memory containing;

i) a first data structure containing an attribute profile of an individual, wherein the attribute profile comprises pangenetic attributes and non-pangenetic attributes;

ii) a second data structure containing attribute combinations and corresponding statistical results that indicate the strength of association of each of the attribute combinations with the query attribute;

b) a processor for;

i) receiving the query attribute;

ii) accessing the first data structure;

iii) accessing the second data structure;

iv) identifying, from among the attribute combinations contained in the second data structure, one or more attribute combinations each containing at least one attribute from the attribute profile in the first data structure; and

v) transmitting one or more attributes that constitute differences between the identified attribute combinations and the attribute profile as output to indicate attributes that modify the individual'"'"'s predisposition for association with the query attribute.

18. The bioinformatics database system of claim 17, wherein transmitting in (v) further comprises transmitting at least a portion of the corresponding statistical results as output to indicate the individual'"'"'s statistical predisposition for association with the query attribute upon modifying the attribute profile of the individual with the transmitted attributes.

19. A bioinformatics computer-based system for identifying attributes that modify an individual'"'"'s predisposition for association with a query attribute, comprising:

a) a first data communications subsystem for receiving a query attribute;

b) a first data accessing subsystem for accessing an attribute profile of an individual, wherein the attribute profile comprises pangenetic attributes and non-pangenetic attributes;

c) a second data accessing subsystem for accessing a set containing attribute combinations and corresponding statistical results that indicate the strength of association of each of the attribute combinations with the query attribute;

d) a data processing subsystem for identifying, from among the attribute combinations contained in the set, one or more attribute combinations each containing at least one attribute from the attribute profile; and

e) a second data communications subsystem for transmitting one or more attributes that constitute differences between the identified attribute combinations and the attribute profile as output to indicate attributes that modify the individual'"'"'s predisposition for association with the query attribute.

20. The bioinformatics computer-based system of claim 19, wherein the second data communications subsystem is also for transmitting at least a portion of the corresponding statistical results as output to indicate the individual'"'"'s statistical predisposition for association with the query attribute upon modifying the attribute profile of the individual with the transmitted attributes