Diagnosis of sepsis

• US 20060246495A1
• Filed: 04/14/2006
• Published: 11/02/2006
• Est. Priority Date: 04/15/2005
• Status: Active Grant

• Current Assignee: Becton, Dickinson & Co
• Original Assignee: Becton, Dickinson & Co
• Inventors: Thornton, Keith, Whiteford, Craig C., Wang, Sha-Sha, Nussbaumer, William A., Garrett, James A., Keating, William, Moore, Richard L.
• Granted Patent: US 7,767,395 B2
• 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 1/6888 for detection or identification of organisms
• CPC Class Codes: C12Q 2600/112 Disease subtyping, staging or classification
• CPC Class Codes: C12Q 2600/158 Expression markers
• CPC Class Codes: C12Q 2600/16 Primer sets for multiplex assays
• CPC Class Codes: G01N 2333/5412 IL-6
• CPC Class Codes: G01N 2333/5421 IL-8
• CPC Class Codes: G01N 2800/26 Infectious diseases, e.g. generalised sepsis
• CPC Class Codes: G01N 2800/50 Determining the risk of developing a disease
• CPC Class Codes: G01N 33/56911 Bacteria
• CPC Class Codes: G01N 33/6893 related to diseases not provided for elsewhere
• 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 for predicting the development of sepsis in a subject at risk for developing sepsis are provided. In one method, 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 for predicting the development of a stage of sepsis in a subject at risk for developing a stage of sepsis are provided. In one method, 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 of diagnosing sepsis in a subject are provided. In one such method, 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, the plurality of biomarkers comprising at least three biomarkers listed in Table I, wherein

the plurality of biomarkers comprises at least six biomarkers listed in Table I when the plurality of biomarkers comprises both IL-6 and IL-8.

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 54 biomarkers listed in Table I.

4. The method of claim 1, wherein said plurality of biomarkers consists of between 3 and 30 biomarkers listed in Table I.

5. The method of claim 1, wherein said plurality of biomarkers consists of between 4 and 25 biomarkers listed in Table I.

6. The method of claim 1, wherein said plurality of biomarkers comprises at least 3 biomarkers listed in Table I.

7. The method of claim 1, wherein said plurality of biomarkers comprises at least 4 biomarkers listed in Table I.

8. The method of claim 1, wherein said plurality of biomarkers comprises at least 8 biomarkers listed in Table I.

9. The method of claim 1, wherein said plurality of features consists of between 3 and 53 features corresponding to between 3 and 53 biomarkers in the plurality of biomarkers.

10. The method of claim 1, wherein said plurality of features consists of between 3 and 40 features corresponding to between 3 and 40 biomarkers in the plurality of biomarkers.

11. The method of claim 1, wherein said plurality of features consists of between 4 and 25 features corresponding to between 4 and 25 biomarkers in the plurality of biomarkers.

12. The method of claim 1, wherein said plurality of features comprises at least 3 features corresponding to at least 3 biomarkers in the plurality of biomarkers.

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

14. The method of claim 1, wherein said plurality of features comprises at least 8 features corresponding to at least 8 biomarkers in the plurality of biomarkers.

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

16. The method of claim 15, wherein each biomarker is a nucleic acid.

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

18. The method of claim 17, wherein each biomarker is a protein.

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

20. The method of claim 19, wherein each biomarker is a DNA, a cDNA, an amplified DNA, an RNA, or an mRNA.

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

22. The method of claim 1, wherein a first biomarker in said plurality of biomarkers is a nucleic acid biomarker listed in Table J and a second biomarker in said plurality of biomarkers is a protein biomarker listed in Table K.

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

24. The method of claim 23, wherein said feature is abundance of said biomarker in said biological sample.

25. The method of claim 23, wherein said feature is absence or presence of said biomarker in said biological sample.

26. The method of claim 23, wherein said feature is an identification of a species of said biomarker in said biological sample.

27. The method of claim 23, wherein said biological sample is whole blood.

28. The method of claim 23, wherein said biological sample is plasma, serum, saliva, sputum, urine, cerebral spinal fluid, a tissue specimen, a tissue biopsy, or a stool specimen.

29. The method of claim 23, wherein said biological sample is isolated neutrophils, eosinophils, basophils, lymphocytes, or monocytes.

30. 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.

31. The method of claim 30, wherein at least one feature indicates whether an abundance of said biomarker is increasing or decreasing over time.

32. The method of claim 30, 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.

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

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

35. 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.

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

37. The method of claim 36, wherein said constructing step comprises obtaining said plurality of features from a sample of said test subject.

38. The method of claim 37, wherein said sample is whole blood.

39. The method of claim 37, wherein said sample is plasma, serum, saliva, sputum, urine, cerebral spinal fluid, a tissue specimen, a tissue biopsy, or a stool specimen.

40. The method of claim 37, wherein said sample is neutrophils, eosinophils, basophils, lymphocytes, or monocytes.

41. The method of claim 36, wherein the constructing step comprises applying a data analysis algorithm to features corresponding to biomarkers listed in Table I that are obtained from members of a population.

42. The method of claim 41, wherein said population comprises subjects that subsequently develop sepsis (sepsis subjects) and subjects that do not subsequently develop sepsis (SIRS subjects).

43. The method of claim 41, wherein the features corresponding to biomarkers listed in Table I that are obtained from members of the population are obtained at a time prior to when a portion of the subjects in the population acquire sepsis.

44. The method of claim 41, 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.

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

46. The method of claim 45, wherein the constructing step comprises applying a data analysis algorithm to features obtained from members of a population.

47. The method of claim 46, 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.

48. The method of claim 46, 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.

49. The method of claim 46, 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.

50. The method of claim 49, wherein said decision rule classifies subjects in said population as (i) subjects that develop sepsis and (ii) subjects that do not develop sepsis with an accuracy of seventy percent or greater.

51. The method of claim 49, wherein said decision rule classifies subjects in said population as (i) subjects that develop sepsis and (ii) subjects that do not develop sepsis with an accuracy of ninety percent or greater.

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

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

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

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

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

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

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

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

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

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

62. 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 three biomarkers listed in Table I, wherein the plurality of biomarkers comprises at least six biomarkers listed in Table I when the plurality of biomarkers comprises both IL-6 and IL-8.

63. The method of claim 62, the method further comprising constructing, prior to the evaluating step, said biomarker profile.

64. The method of claim 63, wherein said constructing step comprises obtaining said plurality of features from a sample of said test subject.

65. The method of claim 64, wherein said sample is whole blood.

66. The method of claim 64, wherein said sample is plasma, serum, saliva, sputum, urine, cerebral spinal fluid, a tissue specimen, a tissue biopsy, or stool.

67. The method of claim 64, wherein said sample is neutrophils, eosinophils, basophils, lymphocytes, or monocytes.

68. The method of claim 64, wherein said sample is a single tissue.

69. The method of claim 64, wherein said sample is from more than one tissue of said test subject.

70. The method of claim 63, wherein said constructing step comprises determining the identity of the biomarkers in Table I that correspond to the plurality of features.

71. The method of claim 70, wherein the determining step comprises applying a data analysis algorithm to features corresponding to biomarkers listed in Table I that are obtained from members of a population.

72. The method of claim 71, wherein said population comprises subjects that develop sepsis at a later time (sepsis subject) and subjects that do not develop sepsis (SIRS subjects).

73. The method of claim 62, wherein the plurality of biomarkers comprises at least four biomarkers listed in Table I.

74. The method of claim 62, wherein the plurality of biomarkers comprises at least eight biomarkers listed in Table I.

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 I, wherein the plurality of biomarkers comprises at least six biomarkers listed in Table I when the plurality of biomarkers comprises both IL-6 and IL-8.

76. The microarray of claim 75, wherein said microarray comprises one or more control spots.

77. The microarray of claim 75, wherein at least forty percent of the probe spots in the plurality of probe spots correspond to biomarkers listed in Table I.

78. The microarray of claim 75, wherein the microarray consists of between about three and fifty probe spots on a substrate.

79. The microarray of claim 75, wherein said microarray is a nucleic acid microarray.

80. The microarray of claim 75, wherein said microarray is a protein microarray.

81. A kit for predicting the development of sepsis in a test subject, the kit comprising a plurality of antibodies that, collectively, specifically bind at least three biomarkers listed in Table I.

82. A kit for predicting the development of sepsis in a test subject, the kit comprising a plurality of antibodies that, collectively, specifically bind at least three biomarkers listed in Table K.

83. A computer program product, 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 three biomarkers listed in Table I, wherein

the plurality of biomarkers comprises at least six biomarkers listed in Table I when the plurality of biomarkers comprises both IL-6 and IL-8.

84. The computer program product of claim 83, the computer program product further comprising:

instructions for 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.

85. The computer program product of claim 83, wherein said biomarker profile consists of between 3 and 50 biomarkers listed in Table I.

86. The computer program product of claim 83, wherein said biomarker profile consists of between 3 and 40 biomarkers listed in Table I.

87. The computer program product of claim 83, wherein the plurality of biomarkers comprises at least four biomarkers listed in Table I.

88. The computer program product of claim 83, wherein the plurality of biomarkers comprises at least eight biomarkers listed in Table I.

89. 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 three biomarkers from Table I, wherein

the plurality of biomarkers comprises at least six biomarkers listed in Table I when the plurality of biomarkers comprises both IL-6 and IL-8.

90. The computer of claim 89, the memory further storing:

instructions for 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.

91. The computer of claim 89, wherein said biomarker profile consists of between 3 and 50 biomarkers listed in Table I.

92. The computer of claim 89, wherein said biomarker profile consists of between 3 and 40 biomarkers listed in Table I.

93. The computer of claim 89, wherein the plurality of biomarkers comprises at least four biomarkers listed in Table I.

94. The computer of claim 89, wherein the plurality of biomarkers comprises at least eight biomarkers listed in Table I.

95. 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 three biomarkers listed in Table I;

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, wherein

the plurality of biomarkers comprises at least six biomarkers listed in Table I when the plurality of biomarkers comprises both IL-6 and IL-8.

96. The computer system of claim 95, wherein

the remote computer further comprises instructions for 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;

and wherein the memory further comprises;

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 second set; and

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

97. The computer system of claim 95, wherein the plurality of biomarkers comprises at least four biomarkers listed in Table I.

98. The computer system of claim 95, wherein the plurality of biomarkers comprises at least eight biomarkers listed in Table I.

99. A digital signal embodied on a carrier wave comprising a respective value for each of a plurality of features in a biomarker profile;

wherein the plurality of features are measurable aspects of a plurality of biomarkers, the plurality of biomarkers comprising at least three biomarkers listed in Table I, and wherein

the plurality of biomarkers comprises at least six biomarkers listed in Table I when the plurality of biomarkers comprises both IL-6 and IL-8.

100. The digital signal of claim 99, wherein the plurality of biomarkers comprises at least four biomarkers listed in Table I.

101. The digital signal of claim 99, wherein the plurality of biomarkers comprises at least eight biomarkers listed in Table I.

102. A digital signal, embodied on a carrier wave, comprising a determination as to whether a plurality of features in a biomarker profile of a test subject satisfies a value set, wherein the plurality of features are measurable aspects of a plurality of biomarkers, the plurality of biomarkers comprising at least three biomarkers listed in Table I, and wherein satisfying the value set predicts that the test subject is likely to develop sepsis;

and wherein

the plurality of biomarkers comprises at least six biomarkers listed in Table I when the plurality of biomarkers comprises both IL-6 and IL-8.

103. The digital signal of claim 102, wherein the plurality of biomarkers comprises at least four biomarkers listed in Table I.

104. The digital signal of claim 102, wherein the plurality of biomarkers comprises at least eight biomarkers listed in Table I.

105. A digital signal, embodied on a carrier wave, comprising a determination as to whether a plurality of features in a biomarker profile of a test subject satisfies a value set, wherein the plurality of features are measurable aspects of a plurality of biomarkers, the plurality of biomarkers comprising at least three biomarkers listed in Table I, and wherein satisfying the value set predicts that the test subject is not likely to develop sepsis, and wherein

the plurality of biomarkers comprises at least six biomarkers listed in Table I when the plurality of biomarkers comprises both IL-6 and IL-8.

106. The digital signal of claim 105, wherein the plurality of biomarkers comprises at least four biomarkers listed in Table I.

107. The digital signal of claim 105, wherein the plurality of biomarkers comprises at least eight biomarkers listed in Table I.

108. A graphical user interface for determining whether a subject is likely to develop sepsis, the graphical user interface comprising a display field for a displaying a result encoded in a digital signal embodied on a carrier wave received from a remote computer, wherein the plurality of features are measurable aspects of a plurality of biomarkers, the plurality of biomarkers comprising at least three biomarkers listed in Table I, and wherein

said result has a first value when a plurality of features in a biomarker profile of a test subject satisfies a first value set;

and

said result has a second value when a plurality of features in a biomarker profile of a test subject satisfies a second value set; and

wherein

the plurality of biomarkers comprises at least six biomarkers listed in Table I when the plurality of biomarkers comprises both IL-6 and IL-8.

109. The graphical user interface of claim 108, wherein the plurality of biomarkers comprises at least four biomarkers listed in Table I.

110. The graphical user interface of claim 108, wherein the plurality of biomarkers comprises at least eight biomarkers listed in Table I.

111. 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 three biomarkers listed in Table I;

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 reporting whether the plurality of features in the biomarker profile of the test subject satisfies the first value set; and

wherein

the plurality of biomarkers comprises at least six biomarkers listed in Table I when the plurality of biomarkers comprises both IL-6 and IL-8.

112. The computer system of claim 111, wherein the plurality of biomarkers comprises at least four biomarkers listed in Table I.

113. The computer system of claim 111, wherein the plurality of biomarkers comprises at least eight biomarkers listed in Table I.