Signatures and determinants for distinguishing between a bacterial and viral infection and methods of use thereof

Patent metadata

Field	Value
Publication number	US-2016153993-A1
Application number	US-201615015309-A
Country	US
Kind code	A1
Filing date	Feb 4, 2016
Priority date	Apr 21, 2010
Publication date	Jun 2, 2016
Grant date	—

Abstract

The present invention provides methods of detecting infection using biomarkers. The methods disclosed herein include measuring the expression level of one or more polypeptide determinants in which the alteration of the expression level indicates infection of the patient. The methods provided herein are for distinguishing between bacterial infection, mixed infection, and/or viral infection. The methods disclosed herein may also further comprise measuring one or more non-polypeptide determinants. The present disclosure also provides methods for selection of a treatment regimen for the subject based on whether the subject is identified as having a bacterial or mixed infection, or a viral infection.

First claim

What is claimed is:

1 . A method of treating a subject in need thereof, the method comprising:
(a) measuring the level of MX dynamin-like GTPase 1 (MX1) and the level of C-reactive protein (CRP) in a sample of the subject; (b) classifying whether the subject has a bacterial infection, viral infection, mixed infection or no infection using a hyperplane having been calculated by combining the measurements of said CRP and said MX1 of a training population; and (c) treating the subject according to the classification of said hyperplane, thereby treating the subject.

2 . The method of claim 1 , wherein said hyperplane is calculated using a statistical classification algorithm.

3 . The method of claim 2 , wherein said statistical classification algorithm is selected from the group consisting of a Support Vector Machine (SVM), Logistic Regression (LogReg), Neural Network, Bayesian Network, and a Hidden Markov Model.

4 . The method of claim 2 , wherein said statistical classification algorithm is a Support Vector Machine (SVM) or a Logistic Regression (LogReg).

5 . The method of claim 1 , further comprising measuring the level of white blood cells of the subject.

6 . The method of claim 1 , further comprising measuring the level of neutrophils of the subject.

7 . The method of claim 1 , further comprising measuring the level of RSAD2 in the sample of the subject.

8 . The method of claim 1 , wherein the sample is whole blood or a fraction thereof.

9 . The method of claim 8 , wherein said blood fraction sample comprises cells selected from the group consisting of lymphocytes, monocytes and granulocytes.

10 . The method of claim 1 , wherein said measuring is effected by electrophoretic detection or immunochemical detection.

11 . The method of claim 10 , wherein said immunochemical detection is selected from the group consisting of flow cytometry, radioimmunoassay, immunofluorescence assay and enzyme-linked immunosorbent assay.

12 . The method of claim 2 , wherein when said subject is classified as having a bacterial infection, the treating comprises administering an antibiotic.

13 . A method of diagnosing an infection of a subject comprising:
(a) measuring the level of MX dynamin-like GTPase 1 (MX1) and the level of C-reactive protein (CRP) in a sample of the subject; and (b) classifying whether the subject has a bacterial infection, viral infection, mixed infection or no infection using a hyperplane having been calculated by combining the measurements of said CRP and said MX1 of a training population.

14 . The method of claim 13 , wherein said hyperplane is calculated using a statistical classification algorithm.

15 . The method of claim 14 , wherein said statistical classification algorithm is selected from the group consisting of a Support Vector Machine (SVM), Logistic Regression (LogReg), Neural Network, Bayesian Network, and a Hidden Markov Model.

16 . The method of claim 14 , wherein said statistical classification algorithm is a Support Vector Machine (SVM) or a Logistic Regression (LogReg).

17 . The method of claim 13 , further comprising measuring the level of white blood cells of the subject.

18 . The method of claim 13 , further comprising measuring the level of neutrophils of the subject.

19 . The method of claim 13 , further comprising measuring the level of RSAD2 in the sample of the subject.

20 . The method of claim 13 , wherein the sample is whole blood or a fraction thereof.

21 . The method of claim 20 , wherein said blood fraction sample comprises cells selected from the group consisting of lymphocytes, monocytes and granulocytes.

22 . The method of claim 13 , wherein said measuring is effected by electrophoretic detection or immunochemical detection.

23 . The method of claim 22 , wherein said immunochemical detection is selected from the group consisting of flow cytometry, radioimmunoassay, immunofluorescence assay and enzyme-linked immunosorbent assay.

Assignees

• Memed Diagnostics Ltd

Inventors

• Eden Eran
• Oved Kfir

Classifications

• G01N2333/4737

  C-reactive protein · CPC title

• G01N33/569 Primary

  for microorganisms, e.g. protozoa, bacteria, viruses · CPC title

• G01N2333/914

  Hydrolases (3) · CPC title

• G01N33/56911

  Bacteria · CPC title

• A61K45/06

  Mixtures of active ingredients without chemical characterisation, e.g. antiphlogistics and cardiaca · CPC title