Abstract: The present invention includes methods, systems and kits for distinguishing between active and latent mycobacterium tuberculosis infection in a patient suspected of being infected with Mycobacterium tuberculosis, the method including the steps of obtaining a patient gene expression dataset from a patient suspected of being infected with Mycobacterium tuberculosis; sorting the patient gene expression dataset into one or more gene modules associated with Mycobacterium tuberculosis infection; and comparing the patient gene expression dataset for each of the one or more gene modules to a gene expression dataset from a non-patient; wherein an increase or decrease in the totality of gene expression in the patient gene expression dataset for the one or more gene modules is indicative of active Mycobacterium tuberculosis infection.

Abstract: The present invention includes methods, systems and kits for distinguishing between active and latent mycobacterium tuberculosis infection in a patient suspected of being infected with mycobacterium tuberculosis, and distinguishing such patients from uninfected individuals, the method including the steps of obtaining a gene expression dataset from a whole blood obtained sample from the patient and determining the differential expression of one or more transcriptional gene expression modules that distinguish between infected and non-infected patients, wherein the dataset demonstrates an aggregate change in the levels of polynucleotides in the one or more transcriptional gene expression modules as compared to matched non-infected patients, thereby distinguishing between active and latent mycobacterium tuberculosis infection.

Abstract: The present invention includes methods, systems and kits for distinguishing between active and latent mycobacterium tuberculosis infection in a patient suspected of being infected with Mycobacterium tuberculosis, the method including the steps of obtaining a patient gene expression dataset from a patient suspected of being infected with Mycobacterium tuberculosis; sorting the patient gene expression dataset into one or more gene modules associated with Mycobacterium tuberculosis infection; and comparing the patient gene expression dataset for each of the one or more gene modules to a gene expression dataset from a non-patient; wherein an increase or decrease in the totality of gene expression in the patient gene expression dataset for the one or more gene modules is indicative of active Mycobacterium tuberculosis infection.