Side Effects Prediction Using Co-associating Bioattributes

• US 20090043795A1
• Filed: 01/03/2008
• Published: 02/12/2009
• Est. Priority Date: 08/08/2007
• Status: Active Grant

• Current Assignee: 23andme Incorporated (23andMe Holding Co.)
• Original Assignee: Expanse Networks, Inc.
• Inventors: Eldering, Charles Anthony, Kenedy, Andrew Alexander
• Granted Patent: US 8,788,286 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 50/00 Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism healthcare informatics G16H
• 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: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A bioinformatics method, software, database and system for predicting side effects resulting from predisposition modification are presented in which a set of attributes is used to modify an individual'"'"'s attribute profile to generate a modified attribute profile. The modified attribute profile is compared against a predetermined set of attribute combinations that are statistically associated with one or more candidate side effect attributes. Attribute combinations from the set that also occur in the modified attribute profile are identified, and those candidate side effect attributes that are statistically associated with the identified attribute combinations are stored as a set of predicted side effect attributes resulting from modification of the individual'"'"'s attribute profile.

Claims

1. A bioinformatics method for predicting side effects that result from modifying an attribute profile of an individual, comprising:

a) accessing a modified attribute profile, wherein the modified attribute profile comprises an attribute profile of an individual that has been modified with a set of attributes;

b) accessing a set containing attribute combinations and corresponding statistical results that indicate the strength of association of each of the attribute combinations with one or more candidate side effect attributes;

c) identifying attribute combinations contained in the set that also occur in the modified attribute profile; and

d) transmitting one or more candidate side effect attributes that are statistically associated with the identified attribute combinations as output, to generate a set of predicted side effect attributes that result from modifying the attribute profile of the individual.

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 each of the attribute combinations comprises at least one pangenetic attribute and at least one non-pangenetic attribute, and wherein the one or more candidate side effect attributes comprise pangenetic attributes and non-pangenetic attributes that do not occur in the modified attribute profile.

4. The bioinformatics method of claim 1, wherein the candidate side effect attributes are filtered to exclude user specified attributes.

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

e) updating the modified attribute profile with the predicted side effect attributes; and

f) repeating steps (a)-(e) until no further attribute combinations can be identified in step (c).

6. The bioinformatics method of claim 1, wherein the corresponding statistical results meet at least one predetermined statistical threshold.

7. The bioinformatics method of claim 1, wherein the strength of association of an identified attribute combination with a candidate side effect attribute must meet at least one predetermined statistical threshold in order for the candidate side effect attribute to be transmitted as output.

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

e) ranking each of the predicted side effect attributes based on the strength of association of each of the predicted side effect attributes with the identified attribute combinations.

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

e) compiling the predicted side effect attributes into at least two subgroups corresponding to desirable and undesirable side effects.

10. The bioinformatics method of claim 1, wherein the candidate side effect attributes transmitted as output are transmitted as a rank-ordered tabulation containing corresponding statistical results that indicate the strength of association of the candidate side effect attributes in the tabulation with the identified attribute combinations.

11. The bioinformatics method of claim 10, wherein the corresponding statistical results contained in the tabulation indicate the individual'"'"'s potential for association with each of the predicted side effect attributes.

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

e) associating the set of predicted side effect attributes with the individual and storing the association.

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 predicting side effects that result from modifying an attribute profile of an individual, comprising:

a) accessing a modified attribute profile, wherein the modified attribute profile comprises an attribute profile of an individual that has been modified with a set of attributes;

b) accessing a set containing attribute combinations and corresponding statistical results that indicate the strength of association of each of the attribute combinations with one or more candidate side effect attributes;

c) identifying attribute combinations contained in the set that also occur in the modified attribute profile; and

d) transmitting one or more candidate side effect attributes that are statistically associated with the identified attribute combinations as output, to generate a set of predicted side effect attributes that result from modifying the attribute profile of the individual.

16. The program storage device of claim 15, wherein each of the attribute combinations comprises at least one pangenetic attribute and at least one non-pangenetic attribute, and wherein the one or more candidate side effect attributes comprise pangenetic attributes and non-pangenetic attributes that do not occur in the modified attribute profile.

17. A bioinformatics database system for predicting side effects that result from modifying an attribute profile of an individual, comprising:

a) a memory containing;

i) a first data structure containing a modified attribute profile, wherein the modified attribute profile comprises an attribute profile of an individual that has been modified with a set of 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 one or more candidate side effect attributes;

b) a processor for;

i) accessing the first data structure;

ii) accessing the second data structure;

iii) identifying attribute combinations contained in the second data structure that also occur in the modified attribute profile contained in the first data structure; and

iv) transmitting one or more candidate side effect attributes that are statistically associated with the identified attribute combinations as output, to generate a set of predicted side effect attributes that result from modifying the attribute profile of the individual.

18. The bioinformatics database system of claim 17, wherein each of the attribute combinations comprises at least one pangenetic attribute and at least one non-pangenetic attribute, and wherein the one or more candidate side effect attributes comprise pangenetic attributes and non-pangenetic attributes that do not occur in the modified attribute profile.

19. A bioinformatics computer-based system for predicting side effects that result from modifying an attribute profile of an individual, comprising:

a) a first data accessing subsystem for accessing a modified attribute profile, wherein the modified attribute profile comprises an attribute profile of an individual that has been modified with a set of attributes;

b) 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 one or more candidate side effect attributes;

c) a data processing subsystem for identifying attribute combinations contained in the set that also occur in the modified attribute profile; and

d) a data communications subsystem for transmitting one or more candidate side effect attributes that are statistically associated with the identified attribute combinations as output, to generate a set of predicted side effect attributes that result from modifying the attribute profile of the individual.

20. The bioinformatics computer-based system of claim 19, wherein each of the attribute combinations comprises at least one pangenetic attribute and at least one non-pangenetic attribute, and wherein the one or more candidate side effect attributes comprise pangenetic attributes and non-pangenetic attributes that do not occur in the modified attribute profile.