DIAGNOSIS OF SEPSIS

• US 20090104605A1
• Filed: 04/04/2008
• Published: 04/23/2009
• Est. Priority Date: 12/14/2006
• Status: Abandoned Application

• Current Assignee: Becton, Dickinson & Co
• Original Assignee: Becton, Dickinson & Co
• Inventors: Nussbaumer, William A., Whiteford, Craig C., Moore, Richard L., Siuzdak, Gary
• Application Number:
  US12/098,398
• Publication Number:
  US 20090104605A1
• Time in Patent Office: Days
• US Class Current: 435/6
• CPC Class Codes: C12Q 1/6883 for diseases caused by alterations of genetic material
• CPC Class Codes: C12Q 2600/106 Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
• CPC Class Codes: C12Q 2600/112 Disease subtyping, staging or classification
• CPC Class Codes: C12Q 2600/118 Prognosis of disease development
• CPC Class Codes: C12Q 2600/158 Expression markers
• CPC Class Codes: G01N 2800/26 Infectious diseases, e.g. generalised sepsis
• CPC Class Codes: G16B 25/00 ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
• CPC Class Codes: G16B 25/30 Microarray design
• 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

Methods and apparatus for predicting the development of sepsis in a subject at risk for developing sepsis are provided. Features in a biomarker profile of the subject are evaluated. The subject is likely to develop sepsis if these features satisfy a particular value set. Methods and apparatus for predicting the development of a stage of sepsis in a subject at risk for developing a stage of sepsis are provided. A plurality of features in a biomarker profile of the subject is evaluated. The subject is likely to have the stage of sepsis if these feature values satisfy a particular value set. Methods and apparatus for diagnosing sepsis in a subject are provided. A plurality of features in a biomarker profile of the subject is evaluated. The subject is likely to develop sepsis when the plurality of features satisfies a particular value set.

Claims

1. A method of predicting the development of sepsis in a test subject at risk for developing sepsis, the method comprising:

evaluating whether a plurality of features in a biomarker profile of the test subject satisfies a first value set, wherein satisfying the first value set predicts that the test subject is likely to develop sepsis, and wherein the plurality of features are measurable aspects of a plurality of biomarkers listed in Table 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19 20 and/or 21, wherein, when the plurality of biomarkers comprises complement component C3 and complement component C4, the plurality of biomarkers comprises three or more biomarkers.

2. The method of claim 1, the method further comprising:

evaluating whether the plurality of features in the biomarker profile of the test subject satisfies a second value set, wherein satisfying the second value set predicts that the test subject is not likely to develop sepsis.

3. The method of claim 1, wherein said plurality of biomarkers consists of between 3 and 25 biomarkers listed in one of Tables 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19 20, and 21.

4. The method of claim 1, wherein said plurality of biomarkers consists of between 4 and 25 biomarkers listed in one of Tables 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19 20, and 21.

5. The method of claim 1, wherein said plurality of biomarkers consists of between 5 and 25 biomarkers listed in one of Tables 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19 20, and 21.

6. The method of claim 1, wherein said plurality of biomarkers comprises at least four biomarkers listed in one of Tables 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19 20, and 21.

7. The method of claim 1, wherein said plurality of biomarkers comprises at least five biomarkers listed in one of Table 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19 20, and 21.

8. The method of claim 1, wherein said plurality of biomarkers comprises C-reactive protein, apolipoprotein All, and antithrombin-III.

9. The method of claim 1, wherein said plurality of features consists of between 3 and 100 features corresponding to between 3 and 100 biomarkers in the plurality of biomarkers.

10. The method of claim 1, wherein said plurality of features consists of between 4 and 40 features corresponding to between 4 and 40 biomarkers in the plurality of biomarkers.

11. The method of claim 1, wherein said plurality of features consists of between 5 and 25 features corresponding to between 5 and 25 biomarkers in the plurality of biomarkers.

12. The method of claim 1, wherein said plurality of features comprises at least 4 features corresponding to at least 4 biomarkers in said plurality of biomarkers.

13. The method of claim 1, wherein said plurality of features comprises at least 5 features corresponding to at least 5 biomarkers in said plurality of biomarkers.

14. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 1.

15. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 4.

16. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 5.

17. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 6.

18. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 7.

19. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 12.

20. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 13.

21. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 14.

22. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 15.

23. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 16.

24. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 17.

25. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 18.

26. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 19.

27. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a biomarker listed in Table 20.

28. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a nucleic acid.

29. The method of claim 1, wherein each biomarker in said plurality of biomarkers is a protein.

30. The method of claim 1, wherein a feature in said plurality of features is a measurable aspect of a biomarker in said plurality of biomarkers and a feature value for said feature is determined using a biological sample taken from said test subject at a single point in time.

31. The method of claim 30, wherein said feature is abundance of said biomarker in said sample.

32. The method of claim 30, wherein said feature is absence or presence of said biomarker in said sample.

33. The method of claim 30, wherein said feature is an identification of a species of said biomarker in said sample.

34. The method of claim 30, wherein said biological sample is whole blood.

35. The method of claim 30, wherein said biological sample is plasma, serum, saliva, sputum, urine, cerebral spinal fluid, cells, a cellular extract, a tissue specimen, a tissue biopsy, or a stool specimen.

36. The method of claim 30, wherein said biological sample is isolated neutrophils, isolated eosinophils, isolated basophils, isolated lymphocytes, or isolated monocytes.

37. The method of claim 1, wherein a feature in said plurality of features is a measurable aspect of a biomarker in said biomarker profile and a feature value for said feature is determined using a plurality of samples taken from said test subject at different points in time.

38. The method of claim 37, wherein said feature indicates whether an abundance of said biomarker is increasing or decreasing over time.

39. The method of claim 37, wherein a first sample in said plurality of samples is taken on a first day before the subject acquires sepsis and a second sample in said plurality of samples is taken on a second day before the subject acquires sepsis.

40. The method of claim 1, wherein a biomarker in said biomarker profile is an indication of a nucleic acid, an indication of a protein, an indication of a metabolite, or an indication of a carbohydrate.

41. The method of claim 1, wherein a biomarker in said biomarker profile is an indication of mRNA molecule or an indication of a cDNA molecule.

42. The method of claim 1, wherein a biomarker in said biomarker profile is an indication of an antibody.

43. The method of claim 1, wherein a first biomarker in said biomarker profile is an indication of a nucleic acid and a second biomarker in said biomarker profile is an indication of a protein.

44. The method of claim 1, the method further comprising constructing, prior to the evaluating step, said biomarker profile.

45. The method of claim 44, wherein said constructing step comprises obtaining said plurality of features from a sample of said test subject.

46. The method of claim 45, wherein said sample is whole blood.

47. The method of claim 45, wherein said sample is plasma, serum, saliva, sputum, urine, cerebral spinal fluid, cells, a cellular extract, a tissue specimen, a tissue biopsy, or a stool specimen.

48. The method of claim 45, wherein said sample is isolated neutrophils, isolated eosinophiles, isolated basophils, isolated lymphocytes, or isolated monocytes.

49. The method of claim 44, wherein the constructing step comprises applying a data analysis algorithm to features corresponding to biomarkers listed in Table 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19, 20 and/or 21 that are obtained from members of a population.

50. The method of claim 49, wherein said population comprises subjects that subsequently develop sepsis (sepsis subjects) and subjects that do not subsequently develop sepsis (SIRS subjects).

51. The method of claim 49, wherein the features corresponding to biomarkers listed in Table 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19, 20 and/or 21 that are obtained from members of said population are obtained at a time prior to when subjects in the population acquire sepsis.

52. The method of claim 49, wherein said data analysis algorithm is a decision tree, predictive analysis of microarrays, a multiple additive regression tree, a neural network, a clustering algorithm, principal component analysis, a nearest neighbor analysis, a linear discriminant analysis, a quadratic discriminant analysis, a support vector machine, an evolutionary method, a projection pursuit, or weighted voting.

53. The method of claim 1, the method further comprising constructing, prior to the evaluating step, said first value set.

54. The method of claim 53, wherein the constructing step comprises applying a data analysis algorithm to a plurality of features obtained from members of a population.

55. The method of claim 54, wherein said population comprises subjects that develop sepsis during an observation time period and subjects that do not develop sepsis during an observation time period.

56. The method of claim 54, wherein said data analysis algorithm is a decision tree, predictive analysis of microarrays, a multiple additive regression tree, a neural network, a clustering algorithm, principal component analysis, a nearest neighbor analysis, a linear discriminant analysis, a quadratic discriminant analysis, a support vector machine, an evolutionary method, a projection pursuit, or weighted voting.

57. The method of claim 54, wherein the constructing step generates a decision rule and wherein said evaluating step comprises applying said decision rule to the plurality of features in order to determine whether they satisfy the first value set.

58. The method of claim 57, wherein said decision rule classifies subjects in said population as (i) subjects that subsequently develop sepsis and (ii) subjects that do not subsequently develop sepsis with an accuracy of seventy percent or greater.

59. The method of claim 57, wherein said decision rule classifies subjects in said population as (i) subjects that subsequently develop sepsis and (ii) subjects that do not subsequently develop sepsis with an accuracy, specificity, or sensitivity of ninety percent or greater.

60. The method of claim 1, wherein a first biomarker in said biomarker profile is up-regulated in patients likely to develop sepsis.

61. The method of claim 1, wherein at least five biomarkers in said biomarker profile are up-regulated in patients likely to develop sepsis.

62. The method of claim 1, wherein a first biomarker in said biomarker profile is down-regulated in patients likely to develop sepsis.

63. The method of claim 1, wherein at least five biomarkers in said biomarker profile are down-regulated in patients likely to develop sepsis.

64. The method of claim 1, wherein a first biomarker in said biomarker profile is up-regulated at a first time point, and down-regulated at a second time point in a converter population relative to a nonconverter population.

65. The method of claim 1, wherein at least five biomarkers in said biomarker profile are up-regulated at a first time point, and down-regulated at a second time point in a converter population relative to a nonconverter population.

66. The method of claim 1, wherein a first biomarker in said biomarker profile is down-regulated at a first time point, and up-regulated at a second time point in a converter population relative to a nonconverter population.

67. The method of claim 1, wherein at least five biomarkers in said biomarker profile are down-regulated at a first time point, and up-regulated at a second time point in a converter population relative to a nonconverter population.

68. The method of claim 1, wherein the test subject has a likelihood of developing sepsis within 4 to 8 hours.

69. The method of claim 1, wherein the test subject has a likelihood of developing sepsis within 8 to 12 hours.

70. The method of claim 1, wherein the test subject has a likelihood of developing sepsis within 12 to 24 hours.

71. The method of claim 1, wherein the test subject has a likelihood of developing sepsis within 24 to 36 hours.

72. The method of claim 1, wherein the test subject has a likelihood of developing sepsis within 36 to 48 hours.

73. The method of claim 1, wherein the test subject has a likelihood of developing sepsis within 48 to 72 hours.

80. The method of claim 1, wherein a first biomarker in said biomarker profile is up-regulated in a converter population relative to a nonconverter population.

81. The method of claim 1, wherein at least five biomarkers in said biomarker profile are up-regulated in a converter population relative to a nonconverter population.

82. The method of claim 1, wherein a first biomarker in said biomarker profile is down-regulated in a converter population relative to a nonconverter population.

83. The method of claim 1, wherein at least five biomarkers in said biomarker profile are down-regulated in a converter population relative to a nonconverter population.

74. A method of diagnosing sepsis in a test subject, comprising:

evaluating whether a plurality of features in a biomarker profile of the test subject satisfies a first value set, wherein satisfying the first value set predicts that the test subject is likely to develop sepsis, wherein the plurality of features correspond to a plurality of biomarkers, the plurality of biomarkers comprising at least two biomarkers listed in any one of Tables 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19, 20, and 21 wherein, when the plurality of biomarkers comprises complement component C3 and complement component C4, the plurality of biomarkers comprises three or more biomarkers.

75. A microarray comprising a plurality of probe spots, wherein at least twenty percent of the probe spots in the plurality of probe spots correspond to a plurality of biomarkers listed in Table 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19, or 20.

76. A kit for predicting the development of sepsis in a test subject, the kit comprising a plurality of antibodies that specifically bind a plurality of biomarkers listed in Table 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19, or 20.

77. A computer program product for use in conjunction with a computer system, wherein the computer program product comprises a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising:

instructions for evaluating whether a plurality of features in a biomarker profile of a test subject at risk for developing sepsis satisfies a first value set, wherein satisfying the first value set predicts that the test subject is likely to develop sepsis, and wherein the plurality of features are measurable aspects of a plurality of biomarkers, the plurality of biomarkers comprising at least two biomarkers listed in Table 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19 20 and/or 21, wherein, when the plurality of biomarkers comprises complement component C3 and complement component C4, the plurality of biomarkers comprises three or more biomarkers.

78. A computer comprising:

a central processing unit;

a memory coupled to the central processing unit, the memory storing;

instructions for evaluating whether a plurality of features in a biomarker profile of a test subject at risk for developing sepsis satisfies a first value set, wherein satisfying the first value set predicts that the test subject is likely to develop sepsis, and wherein the plurality of features are measurable aspects of a plurality of biomarkers, the plurality of biomarkers comprising at least two biomarkers listed in Table 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19 and/or 20, wherein, when the plurality of biomarkers comprises complement component C3 and complement component C4, the plurality of biomarkers comprises three or more biomarkers.

79. A computer system for determining whether a subject is likely to develop sepsis, the computer system comprising:

a central processing unit; and

a memory, coupled to the central processing unit, the memory storing;

instructions for obtaining a biomarker profile of a test subject, wherein said biomarker profile comprises a plurality of features and wherein the plurality of features are measurable aspects of a plurality of biomarkers, the plurality of biomarkers comprising at least two biomarkers listed in any one of Tables 1, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 19, 20, and 21, wherein, when the plurality of biomarkers comprises complement component C3 and complement component C4, the plurality of biomarkers comprises three or more biomarkers;

instructions for transmitting the biomarker profile to a remote computer, wherein the remote computer includes instructions for evaluating whether the plurality of features in the biomarker profile of the test subject satisfies a first value set, wherein satisfying the first value set predicts that the test subject is likely to develop sepsis; and

instructions for receiving a determination, from the remote computer, as to whether the plurality of features in the biomarker profile of the test subject satisfies the first value set; and

instructions for reporting whether the plurality of features in the biomarker profile of the test subject satisfies the first value set.