IP Library Granted Patent US 8,825,587
Granted Patent B2
US 8,825,587 · App. 13/264,360 · Granted Sep 2, 2014

Predictive models and method for assessing age

Inventors: Steve Rosenberg (Oakland, CA); Whittemore G. Tingley (San Francisco, CA); Michael R. Elashoff (Redwood City, CA); James A. Winrove (Sunnyvale, CA)
Assignee: Cardiodx, Inc.
C12Q1/6883G06Q10/04G06Q30/02C12Q2600/158C12Q1/6809
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Quick Facts
Patent No.
US 8,825,587
App. No.
13/264,360
Granted
Sep 2, 2014
Kind
B2
Abstract

Biomarkers useful for diagnosing and assessing physiological age are provided, along with kits for measuring their expression. The invention also provides predictive models, based on the biomarkers, as well as computer systems, and software embodiments of the models for scoring and optionally classifying samples. In a preferred embodiment, the biomarkers include a group of biomarkers whose expression levels are highly correlated to each other. In a preferred embodiment, expression levels of CD248; CD248 and SLC 1A7; CD248 and one, two, three or four of the group consisting of CCR7, B3GAT1, VSIG4 and LRRN3; or CD248, SLC1A7 and one, two, three or four of the group consisting of CCR7, B3GAT1, VSIG4 and LRRN3 are determined.

Claims (30)

1. A method for assessing a physiological age of a mammalian subject comprising:

obtaining a dataset associated with a sample obtained from said mammalian subject, wherein said dataset comprises the expression value of CD248 and the expression value of SLC1A7;

inputting said dataset into an interpretation function that uses said dataset to determine a score wherein said score indicates a physiological age wherein said interpretation function is a function produced by a predictive model selected from the group consisting of a partial least squares model, a logistic regression model, a linear regression model, a linear discriminant analysis model, and a tree-based recursive partitioning model; and

outputting said score.

2. The method of claim 1 wherein the dataset further comprises the expression value of a gene selected from the group consisting of CCR7, B3GAT1, VSIG4 and LRRN3.

3. The method of claim 1 wherein the dataset further comprises the expression values of two genes selected from the group consisting of CCR7, B3GAT1, VSIG4 and LRRN3.

4. The method of claim 1 wherein the dataset further comprises the expression values of three genes selected from the group consisting of CCR7, B3GAT1, VSIG4 and LRRN3.

5. The method of claim 1 wherein the dataset further comprises the expression values of CCR7, B3GAT1, VSIG4 and LRRN3.

6. The method of claim 1 , further comprising classifying said sample according to said score.

7. The method of claim 6 wherein said classifying is according to the physiological age of said mammalian subject.

8. The method of claim 1 , wherein said sample comprises peripheral blood cells.

9. The method of claim 1 , wherein said sample comprises RNA extracted from peripheral blood cells.

10. The method of claim 1 , wherein said gene expression values are derived from microarray hybridization data.

11. The method of claim 1 , wherein said gene expression values are derived from polymerase chain reaction data.

12. The method of claim 1 , wherein said gene expression values are obtained using a method selected from the group consisting of nucleic acid hybridization and nucleic acid amplification.

13. A computer-implemented method for assessing a physiological age of a mammalian subject by a computer comprising:

receiving a dataset associated with a sample obtained from said mammalian subject, wherein said dataset comprises the expression value of CD248 and the expression value of SLC1A7;

determining, by a computer processor, a score by inputting said dataset into an interpretive function wherein said score indicates a physiological age wherein said interpretation function is a function produced by a predictive model selected from the group consisting of a partial least squares model, a logistic regression model, a linear regression model, a linear discriminant analysis model, and a tree-based recursive partitioning model; and

outputting said score.

14. The method of claim 13 wherein the dataset further comprises the expression value of a gene selected from the group consisting of CCR7, B3GAT1, VSIG4 and LRRN3.

15. The method of claim 13 wherein the dataset further comprises the expression values of two genes selected from the group consisting of CCR7, B3GAT1, VSIG4 and LRRN3.

16. The method of claim 13 wherein the dataset further comprises the expression values of three genes selected from the group consisting of CCR7, B3GAT1, VSIG4 and LRRN3.

17. The method of claim 13 wherein the dataset further comprises the expression values of CCR7, B3GAT1, VSIG4 and LRRN3.

18. The method of claim 13 further comprising classifying said sample according to said score.

19. The method of claim 18 wherein said classifying is according to the physiological age of said mammalian subject.

20. The method of claim 13 wherein said sample comprises peripheral blood cells.

21. The method of claim 13 wherein said sample comprises RNA extracted from peripheral blood cells.

22. The method of claim 13 wherein said gene expression values are derived from microarray hybridization data.

23. The method of claim 13 wherein said gene expression values are derived from polymerase chain reaction data.

24. The method of claim 13 wherein said gene expression values are obtained using a method selected from the group consisting of nucleic acid hybridization and nucleic acid amplification.

Assignments (2)
INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Feb 1, 2016
From: CARDIODX, INC.
To: SOLAR CAPITAL LTD., AS COLLATERAL AGENT
Reel/Frame 037664/0314 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 26, 2012
From: ROSENBERG, STEVE; TINGLEY, WHITTEMORE G.; ELASHOFF, MICHAEL R.; WINGROVE, JAMES A.
To: CARDIODX, INC.
Reel/Frame 027596/0292 →
Continuity (2)
Provisional Application 61169241 · Apr 14, 2009
Related Publication 20120036101A1 · Feb 9, 2012