IP Library Granted Patent US 8,458,121
Granted Patent B2
US 8,458,121 · App. 13/272,737 · Granted Jun 4, 2013

Predisposition prediction using attribute combinations

Inventors: Andrew Alexander Kenedy (Sugar Land, TX); Charles Anthony Eldering (Furlong, PA)
Assignee: Expanse Networks, Inc.
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 8,458,121
App. No.
13/272,737
Granted
Jun 4, 2013
Kind
B2
Abstract

A method and system are presented in which predisposition predictions are generated for an individual with respect to an attribute indicated in a query. The predictions are based on the identification of predisposing attribute combinations within the attribute profile of the individual and statistical results that indicate the strength of association of the identified attribute combinations with the query attribute.

Claims (50)

1. A computer based method for predisposition prediction wherein a relative likelihood of medical disease predisposition for an individual may be determined based on datasets containing predetermined association of attributes combining pangenetic and non-pangenetic attributes and combinations thereof with said disease, said method performed on a computer including a user interface, a processor, a memory, and a display, comprising:

a) said computer receiving a medical disease associated query attribute via said user interface into said processor;

b) said processor accessing an attribute profile of said individual contained in said memory;

c) said processor accessing a stored dataset in said memory containing said predetermined attribute combinations combining pangenetic and non-pangenetic attributes and statistical results that indicate the strength of association of each of the attribute combinations in said stored dataset, said statistical association having been created by comparing previously submitted and assessed attribute profiles of individuals with the medical disease query attribute and comparing the submitted attribute profiles with attributes profiles of those not having the medical disease query, so as to minimize the impact of shared attribute combinations;

d) identifying attribute combinations from the stored dataset of predetermined attribute combinations associated with said medical disease that occur in the attribute profile of said individual by comparing the attribute combinations occurring in both the attribute profile of the individual and in the dataset attribute profiles; and

e) generating a dataset ranked output of one or more predisposition predictions for the individual based on the identified attribute combinations appearing in both the predetermined dataset and in the attribute profile of said individual and the statistical results indicating a relative predisposition of said individual to acquire said disease.

2. The computer based method of claim 1 , wherein the predisposition predictions are generated based on the statistical results for the largest identified attribute combination.

3. The computer based method of claim 1 , further comprising:

f) storing the predisposition predictions in said memory.

4. The computer based method of claim 1 , further comprising:

f) associating the predisposition predictions with the individual and storing the association in said memory.

5. The computer based method of claim 4 , wherein storing the association comprises storing a link to one or more of an identifier of the individual, the attribute profile of the individual, and a record of the individual.

6. The computer based method of claim 1 , further comprising:

f) repeating steps (a)-(e) for a succession of query attributes to create a tabulated predisposition prediction report, profile or record.

7. The computer based method of claim 1 , further comprising:

f) transmitting the predisposition predictions as output.

8. The computer based method of claim 1 , further comprising:

f) transmitting the predisposition predictions to create an attribute prediction report, profile or record.

9. The computer based method of claim 1 , further comprising:

f) updating attribute combinations and statistical results contained in the dataset based on the content of the attribute profile.

10. The computer based method of claim 1 , wherein the query attribute comprises a combination of two or more attributes.

11. The computer based method of claim 4 , wherein the predisposition predictions meet one or more statistical requirements.

12. The computer based method of claim 8 , wherein the predisposition predictions meet one or more statistical requirements.

13. The computer based method of claim 12 , wherein the one or more statistical requirements are selected from the group consisting of a minimum statistical value, a maximum statistical value, and a value of statistical significance.

14. The computer based method of claim 1 , further comprising:

f) eliminating predisposition predictions that are based on attribute combinations which lack one or more specified attributes.

15. The computer based method of claim 1 , further comprising:

f) eliminating predisposition predictions that are based on attribute combinations which contain one or more specified attributes.

16. A computer based system for predisposition prediction wherein a relative likelihood of medical disease predisposition for an individual may be determined based on datasets containing predetermined association of attributes combining pangenetic and non-pangenetic attributes and combinations thereof with said disease, comprising:

a) a data receiving subsystem processor for receiving a query attribute associated with said medical disease;

b) a first data accessing subsystem memory for accessing a previously stored attribute profile of said individual;

c) a second data accessing subsystem memory for accessing a dataset containing previously stored attribute combinations combining pangenetic and non-pangenetic attributes and statistical results that indicate the strength of association of each of the attribute combinations in said stored dataset with the medical disease query attribute, said statistical strength of association having been created by comparing previously submitted and assessed attribute profiles of individuals with the medical disease query attribute and comparing the submitted attribute profiles with attributes profiles of those not having the medical disease query, so as to minimize the impact of shared attribute combinations;

d) a data processing subsystem processor comprising:

i) a data comparison subsystem means for identifying attribute combinations from the stored data set that occur in the attribute profile of said individual; and

ii) a statistical predisposition prediction subsystem means for generating and displaying one or more predisposition predictions for the individual based on the identified attribute combinations and the statistical results indicating a relative predisposition of said individual to acquire said disease, said prediction of relative predisposition obtained by comparing the attribute combinations occurring in both the attribute profile of the individual and in the respective dataset of attribute profiles.

17. The computer based system of claim 16 , further comprising:

e) a data storage subsystem means for storing the predisposition predictions and for storing an association between the predisposition predictions and the individual.

18. The computer based system of claim 16 , further comprising:

e) a communications subsystem means for transmitting the predisposition predictions.

19. The computer based system of claim 16 , wherein the data processing subsystem further comprises:

iii) a database updating subsystem means for updating attribute combinations and statistical results contained in the set based on the content of the attribute profile.

20. The computer based system of claim 16 , wherein the data processing subsystem further comprises:

iii) a data elimination subsystem means for eliminating predisposition predictions that are based on attribute combinations which lack one or more specified attributes, or alternatively, which contain one or more specified attributes.

21. A computer based system for predisposition prediction wherein a relative likelihood of medical disease predisposition for an individual may be determined based on datasets containing predetermined association of attributes combining pangenetic and non-pangenetic attributes and combinations thereof with the disease, the computer based system comprising:

a) a data receiving subsystem for receiving a query attribute associated with said medical disease;

b) a first data accessing subsystem for accessing a first computer memory containing a previously stored attribute profile of the individual;

c) a second data accessing subsystem for accessing a second computer memory containing a dataset having previously stored attribute combinations combining pangenetic and non-pangenetic attributes and statistical results that indicate the strength of association of each of the attribute combinations in said stored dataset with the medical disease query attribute, said statistical strength of association having been created by comparing previously submitted and assessed attribute profiles of individuals with the medical disease query attribute and comparing the submitted attribute profiles with attributes profiles of those not having the medical disease query, so as to eliminate the impact of shared attribute combinations;

d) a data processor and an associated memory, wherein the associated memory contains machine readable instructions which upon execution by the data processor, execute the method of:

i) identifying attribute combinations from the stored data set that occur in the attribute profile of said individual; and

ii) generating and transmitting for display one or more predisposition predictions for the individual based on the identified attribute combinations and the statistical results indicating a relative predisposition of said individual to acquire the disease, the prediction of relative predisposition obtained by comparing the attribute combinations occurring in both the attribute profile of the individual and in the respective dataset of attribute profiles.

Assignments (9)
CORRECTIVE ASSIGNMENT TO CORRECT THE APP. NO. 63806415 TO 63806145 AND APPL NO. 17721779 TO 17731779 PREVIOUSLY RECORDED ON REEL 73168 FRAME 531. ASSIGNOR(S) HEREBY CONFIRMS THE CHANGE OF NAME. Recorded Jan 6, 2026
From: 23ANDME PGS LLC
To: 23ANDME GENOMICS LLC
Reel/Frame 074434/0334 →
CHANGE OF NAME Recorded Oct 22, 2025
From: 23ANDME PGS LLC
To: 23ANDME GENOMICS LLC
Reel/Frame 073168/0531 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 26, 2025
From: 23ANDME, INC.
To: 23ANDME PGS LLC
Reel/Frame 072562/0795 →
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE ADDRESS PREVIOUSLY RECORDED AT REEL: 058554 FRAME: 0021. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT . Recorded Jan 7, 2022
From: EXPANSE BIOINFORMATICS, INC.
To: 23ANDME, INC.
Reel/Frame 058982/0739 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 5, 2022
From: EXPANSE BIOINFORMATICS, INC.
To: 23ANDME, INC.
Reel/Frame 058554/0021 →
CHANGE OF ADDRESS BY ASSIGNEE Recorded Apr 5, 2021
From: EXPANSE BIOINFORMATICS, INC.
To: EXPANSE BIOINFORMATICS, INC.
Reel/Frame 055823/0714 →
CHANGE OF NAME Recorded Sep 23, 2013
From: EXPANSE NETWORKS, INC.
To: EXPANSE BIOINFORMATICS, INC.
Reel/Frame 031289/0003 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 29, 2011
From: KENEDY, ANDREW A.
To: EXPANSE NETWORKS, INC.
Reel/Frame 027296/0520 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 29, 2011
From: ELDERING, CHARLES A.
To: EXPANSE NETWORKS, INC.
Reel/Frame 027294/0915 →
Continuity (3)
Continuation 11747913 · May 13, 2007
Provisional Application 60895236 · Mar 16, 2007
Related Publication 20120036128A1 · Feb 9, 2012