Identification, monitoring and treatment of disease and characterization of biological condition using gene expression profiles

• US 6,964,850 B2
• Filed: 11/08/2002
• Issued: 11/15/2005
• Est. Priority Date: 11/09/2001
• Status: Active Grant

• Current Assignee: Life Technologies Corporation (Thermo Fisher Scientific Incorporated)
• Original Assignee: Source Precision Medicine Inc.
• Inventors: Bankaitis-Davis, Danute M., Cheronis, John C., Tryon, Victor, Bevilacqua, Michael P.
• Primary Examiner(s): Allen, Marianne P.
• Application Number:
  US10/291,856
• Publication Number:
  US 20030219771A1
• Time in Patent Office: 1,103 Days
• Field of Search: 702/19, 702/20, 435/6
• US Class Current: 435/6.11
• CPC Class Codes: G01N 2800/042 Disorders of carbohydrate metabolism, e.g. diabetes, glucose metabolism
• CPC Class Codes: G01N 33/57415 of breast
• CPC Class Codes: G01N 33/6803 General methods of protein analysis not limited to specific proteins or families of proteins
• CPC Class Codes: G01N 33/6863 Cytokines, i.e. immune system proteins modifying a biological response such as cell growth proliferation or differentiation, e.g. TNF, CNF, GM-CSF, lymphotoxin, MIF or their receptors
• CPC Class Codes: G01N 33/6869 Interleukin
• CPC Class Codes: G01N 33/6893 related to diseases not provided for elsewhere
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 25/00 ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
• CPC Class Codes: G16B 25/10 Gene or protein expression profiling; Expression-ratio estimation or normalisation
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

Gene expression data, in particular gene expression profiles, are created and used in the identification, monitoring and treatment of disease and characterization of biological conditions. Profile data sets are derived from subject samples and include quantitative substantially repeatable measures of a distinct amount of RNA or protein constituent in a panel selected to enable evaluation of a biological condition. Such profile data sets may be used to provide an index indicative of the biological state of a subject, which may be compared to a normative value of the index determined with respect to a relevant population of subjects.

Claims

1. A method of providing an index that is indicative of the state of a subject, as to a biological condition characterized by inflammation, based on a sample from the subject, the method comprising:

using amplification for measuring the amount of RNA or constituents from the sample of the subject, where a panel of constituents is selected so that measurement of the constituents enables evaluation of said biological condition and the measures of all constituents in the panel form a first profile data set,

wherein the measures for each constituent are performed under measurement conditions that are substantially repeatable and the efficiencies of amplification for all constituents are substantially similar; and

applying values from said first profile data set to an index function I=Σ

C_iM_i^P(i) where I is the index, M_i is the value of the member i of the profile data set, C_i is a constant, and P(i) is a power to which M_i is raised, the sum being formed for all integral values of i up to the number of members in the data set, thereby providing a single-valued measure of the biological condition so as to produce art index pertinent to the biological condition of the subject.

4. A method according to any of claims 1-3, further comprising providing with the index a normative value of the index function, determined with respect to a relevant population, so that the index may be interpreted in relation to the normative value.

5. A method according to claim 4, wherein providing the normative value includes constructing the index function so that the normative value is approximately 1.

6. A method according to claim 4, wherein providing the normative value includes constructing the index function so that the nonnative value is approximately 0 and deviations in the index function from 0 are expressed in standard deviation units.

7. A method according to claim 4, wherein the relevant population has in common a property that is at least one of age group, gender, ethnicity, geographic location, diet, medical disorder, clinical indicator, medication, physical activity, body mass, and environmental exposure.

8. A method according to any of claims 1-3, wherein efficiencies of amplification, expressed as a percent, for all constituents lie within a range of approximately 2 percent.

9. A method according to claim 8, wherein measurement conditions are repeatable so that such measure for each constituent has a coefficient of variation, on repeated derivation of such measure from the sample, that is less than approximately 3 percent.

10. A method according to any of claims 1-3, wherein efficiencies of amplification, expressed as a percent, for all constituents lie within a range of approximately 1 percent.

11. A method according to claim 10, wherein measurement conditions are repeatable so that such measure for each constituent has a coefficient of variation, on repeated derivation of such measure from the sample, that is less than approximately 3 percent.

12. A method according to any of claims 1-3, wherein measurement conditions are repeatable so that such measure for each constituent has a coefficient of variation, on repeated derivation of such measure from the sample, that is less than approximately 3 percent.

13. A method according to any of claims 1-3, wherein the panel includes at least three constituents.

14. A method according to any of claims 1-3, wherein the panel has fewer than approximately 500 constituents.

15. A method according to any of claims 1-3, wherein the biological condition is inflammation and the panel of constituents includes at least two of the constituents of the Inflammation Gene Expression Panel of Table 1.

16. A method according to any of claims 1-3, wherein the biological condition is diabetes and the panel of constituents includes at least two of the constituents of the Diabetes Gene Expression Panel of Table 2.

17. A method according to any of claims 1-3, wherein the biological condition is prostate health or disease and the panel of constituents includes at least two of the constituents of the Prostate Gene Expression Panel of Table 3.

18. A method according to any of claims 1-3, wherein the biological condition is manifested in skin and the panel of constituents includes at least two of the constituents of the Skin Response Gene Expression Panel of Table 4.

19. A method according to any of claims 1-3, wherein the biological condition is liver metabolism and disease and the panel of constituents includes at least two of the constituents of the Liver Metabolism and Disease Gene Expression Panel of Table 5.

20. A method according to any of claims 1-3, wherein the biological condition is vascular and the panel of constituents includes at least two of the constituents of the Endothelial Gene Expression Panel of Table 6.

21. A method according to any of claims 1-3, wherein the biological condition is abnormal cell development and the panel of constituents includes at least two of the constituents of the Cell Health and Apoptosis Gene Expression Panel of Table 7.

22. A method according to any of claims 1-3, wherein the biological condition is inflammation and the panel of constituents includes at least two of the constituents of the Cytokine Gene Expression Panel of Table 8.

23. A method according to any of claims 1-3, wherein the biological condition is inflammation and the panel of constituents includes at least two of the constituents of the TNF/IL1 Inhibition Gene Expression Panel of Table 9.

24. A method according to any of claims 1-3, wherein the biological condition is inflammation and the panel of constituents includes at least two of the constituents of the Chemokine Gene Expression Panel of Table 10.

25. A method according to any of claims 1-3, wherein the biological condition is cancer and the panel of constituents includes at least two of the constituents of the Breast Cancer Gene Expression Panel of Table 11.

26. A method according to any of claims 1-3, wherein the biological condition is infectious disease and the panel of constituents includes at least two of the constituents of the Infectious Disease Gene Expression Panel of Table 12.

42. A method of providing an index according to any of claims 1, 2, 27, wherein the terms C_i and P(i) are determined using latent class modeling.

2. A method of providing an index that is indicative of the state of a subject, as to a biological condition characterized by inflammation, based on a sample from the subject, the sample providing a source of RNAs, the method comprising:

using amplification for measuring the amount of RNA of at least two constituents from arty one of Tables 1 through 12 from the sample of the subject, where a panel of constituents is selected so that measurement of the constituents enables evaluation of said biological condition and wherein the measures of all constituents in the panel form a first profile data set, wherein the measures for each constituent are performed under measurement conditions that are substantially repeatable and the efficiencies of amplification for all constituents are substantially similar; and

applying values from said first profile data set to an index function I=Σ

C_iM_i^P(i) where I is the index, M_i is the value of the member i of the profile data set, C_i is a constant, and P(i) is a power to which M_i is raised, the sum being formed for all integral values of i up to the number of members in the data set, thereby providing a single-valued measure of the biological condition so as to produce an index pertinent to the biological condition of the subject.

3. A method of providing an index that is indicative of the state of a subject as to a biological condition characterized by inflammation based on a sample from the subject, the sample providing a source of RNAs, the method comprising:

using amplification for measuring the amount of RNA of constituents from the sample of the subject, where a panel of constituents is selected so that measurement of the constituents enables evaluation of said biological condition and the measures of all constituents in the panel form a profile data set, wherein the measures for each constituent are performed under measurement conditions that are substantially repeatable and the efficiencies of amplification for all constituents are substantially similar, and

applying values from said profile data set to an index function derived using latent class modeling, thereby providing a single-valued measure of the biological condition so as to produce an index pertinent to the biological condition of the subject.

27. A method of providing an index that is indicative of the biological state characterized by inflammation of a subject based on a sample from the subject, the sample providing a source of RNAs, the method comprising:

using amplification for measuring the amount of RNA of at least two constituents from the Inflammation Gene Expression Panel of Table 1;

wherein a panel of constituents is selected so that measurement of the constituents enables evaluation of said biological condition and the measures of all constituents in the panel form a first profile data set, wherein the measures for each constituent are performed under measurement conditions that are substantially repeatable and the efficiencies of amplification for all constituents are substantially similar; and

applying values from said first profile data set to an index function I=Σ

C_iM_i^P(i) where I is the index, M_i is the value of the member i of the profile data set, C_i is a constant, and P(i) is a power to which M_i is raised, the sum being formed for all integral values of i up to the number of members in the data set, thereby providing a single-valued measure of the biological condition so as to produce an index pertinent to the biological condition of the subject.

28. A method according to claim 27, wherein the panel includes at least three of the constituents in the Inflammation Gene Expression Panel of Table 1.

29. A method according to claim 27, wherein the panel includes at least four of the constituents in the Inflammation Gene Expression Panel of Table 1.

30. A method according to claim 27, wherein the panel includes at least five of the constituents in the Inflammation Gene Expression Panel of Table 1.

31. A method according to claim 27, wherein the panel includes at least six of the constituents in the Inflammation Gene Expression Panel of Table 1.

32. A method according to claim 27, wherein the panel includes at least 10 of the constituents in the Inflammation Gene Expression Panel of Table 1.

33. A method according to claim 27, wherein the index function is derived using latent class modeling and is constructed to deviate from a normative value generally upwardly in an instance of an increase in expression of a constituent whose increase is associated with an increase of inflammation and also in an instance of a decrease in expression of a constituent whose decrease is associated with an increase of inflammation.

34. A method according to claim 33, wherein the index function derived using latent class modeling is constructed to weigh the expression value of a constituent in the panel generally in accordance with the extent to which its expression level is determined to be correlated with extent of inflammation.

35. A method according to claim 27, wherein measurement of a portion of the RNA constituents for said first profile data set is performed at a first location and applying the values from said first profile data set is performed at a second location, and data associated with measurement of the portion of the RNA constituents for said first profile data set are communicated to the second location over a network to enable, at the second location, applying the values from said first profile data set.

36. A method according to claim 27, wherein each term in the index function is a contribution function of a member of the profile data set.

37. A method according to claim 36, wherein the contribution function is a weighted power of the member.

38. A method according to claim 37, wherein the power is integral, so that the index function is a linear polynomial.

39. A method according to claim 38, wherein the profile data set includes at least three members corresponding to constituents selected from the group consisting of IL1A, IL1B, TNF, IFNG and IL10.

40. A method according to claim 38, wherein the profile data set includes at least four members corresponding to constituents selected from the group consisting of IL1A, IL1B, TNF, IFNG and IL10.

41. A method according to claim 40, wherein the index function is approximately proportional to ¼

{IL1A}+¼

{IL1B}+¼

{TNF}+¼

{INFG}−

1/{IL10} and braces around a constituent designate measurement of such constituent.