WO2014140833A2 - Methods for differentiating between disease states - Google Patents

Abstract

This disclosure relates to methods for differentiating between mammals having active and latent Tuberculosis disease.

Description

METHODS FOR DIFFERENTIATING BETWEEN DISEASE STATES

Related Applications

This application claims priority to U.S. Ser. No. 61/776,882 filed March 12, 2013 which is hereby incorporated in its entirety into this application.

Field of the Disclosure

This disclosure relates to methods for differentiating between mammals having active and latent Tuberculosis disease.

Background of the Disclosure

Cellular immunity and particularly CD4⁺ T-cells have a central role in the control of Mycobacterium tuberculosis {Mtb) infection. IFN-γ and TNF-a are thought to be crucial for protection against Mtb. Diagnosis of Mtb infection remains complex and requires several clinical, radiological, histo-pathological, bacteriological and molecular parameters. IFN-y-release assays (IGRAs), i.e. Quantiferon and ELISpot, measure responses to antigens (e.g., ESAT-6 or CFP-10) that are mainly limited to Mtb, and discriminate infection from immunity induced by vaccination with Bacille Calmette- Guerin (BCG). IGRAs however do not discriminate between active disease and latent infection. While IFN-γ production alone showed no correlation with disease activity in chronic virus infection, polyfunctional (IFN-y+IL-2+TNF-a) profiles of pathogen- specific T-cell responses have been correlated with disease activity. A definite correlation between active and latent Mtb infection by measuring CD4⁺ T-cells has been previously described ((e.g., WO 2012/085652 A2 pub. June 28, 2012). There is a need for improved reagents and methods for detecting and diagnosing Mtb infection, including the differentiation of individuals with active and latent Mtb infection (LTBI). As described below, a surprising and useful correlation regarding to CD4⁺ and CD8⁺ T cells during active Tuberculosis and LTBI has been identified and used to produce an accurate, reproducible assay system for differentiating these states. BRIEF DESCRIPTION OF THE DRAWINGS

Table 1. Demographic and clinical description of the 37 TB patients included in this study. Figure 1. M¾>-specific CD4 and CD8 T-cell responses. A. Analysis of the functional profile of t^-specific CD4 T cells on the basis of IFN-γ, IL-2 or TNF-a production. All 178 individuals had t^-specific CD4 T-cell responses and 216 and 57 t^-specific CD4 T-cell responses against ESAT-6 or CFP-10 were analyzed in the 141 LTBI subjects and 37 TB patients, respectively. The combinations of the different functions are shown on the x axis whereas the percentages of the distinct cytokine -producing cell subsets within t¾-specific CD4 T cells are shown on the y axis. The pie charts summarize the data. Comparisons of markers distribution were performed using a student's t-test and a partial permutation test as described (Roederer et al, Cytometry. Part A, 2011). B. Proportion of LTBI subjects and TB patients with detectable t^-specific CD8 T-cell responses. Mtb- specific CD8 T-cell responses were defined by the presence of IFN-γ -producing CD8 CD4 CD3⁺ T cells following stimulation with ESAT-6 and/or CFP-10 peptide pools. Statistical significance was calculated using two-tailed Fisher's exact test. C. Magnitude (mean with 95% CI) of t^-specific CD8 T-cell responses (against ESAT-6 and/or CFP-10) in the 21 LTBI and 27 TB patients with detectable ώ-specific CD8 T- cell responses. An unpaired two-tailed Student's t-test was performed.

Figure 2. Individual and combined performances of the distinct components of the M¾>-specific T-cell response to diagnose active TB. A. Logistic regression analysis showing the association between the proportion of single TNF-a-producing CD4 T cells with the ability to discriminate between active TB disease and latent Mtb infection (AUC=0.842; [95% CI: 0.780-0.892]). B. Logistic regression analysis showing the association between the presence of a detectable t^-specific CD8 T-cell response with the ability to discriminate between active TB disease and latent Mtb infection (AUC=0.798; [95% CI: 0.732-0.853]). C. Logistic regression analysis showing the association between the SCORE (integrated combination of the proportion of single TNF-a-producing CD4 T cells and the presence of a detectable t^-specific CD8 T-cell response) with the ability to discriminate between active TB disease and latent Mtb infection (AUC=0.944; [95% CI: 0.899-0.973]). D. Analysis of the distribution of SCORE results on the 141 LTBI subjects and the 37 TB patients from this study (with values being rounded up to the superior half).

Figure 3. Sub-analysis of the distribution of SCORE results on the 141 LTBI subjects and the 37 TB patients based on their TB clinical localization (i.e. pulmonary (PTB) or extrapulmonary (ETB) TB). SUMMARY OF THE DISCLOSURE

This disclosure relates to methods for differentiating between mammals having active Tuberculosis disease and latent Mycobacterium tuberculosis (Mtb) infection. In one embodiment, a method for identifying an individual having active Tuberculosis disease by determining the relative percentage of one or more particular types of reactive CD4 T cells and the presence of t^-specific CD8 T cells in the indvidual. In certain embodiments, the method comprises isolating mononuclear cells from the mammal, incubating the cells with a peptide derived from Mtb (e.g. from proteins such as ESAT-6 or CFP-10), and assaying the mononuclear cells to determine the relative percentage of CD4 T-cells for expression of TNFa, IFN-γ, and IL-2 therein to produce a "CD4 value" and for the presence of Mtb-specific CD8 T cells to produce a "CD8 value". The combining the CD4 value and the CD8 value using a logistic regression model to provide a "combined value". In certain embodiments, the logistic regression model comprises the formula:

Log(odds) = SCORE ~ 0.097 * (%TNF-a) + 3.157 *(CD8) wherein:

%TNF-a refers to the percentage of t^-specific single TNF-a-producing CD4 T cells; and,

CD8 refers to 0 (zero) or 1, wherein:

0 indicates the absence of an t£-specific CD8 T-cell response; and,

1 indicates the presence of an t£-specific CD8 T-cell response. In certain embodiments, an individual is identified as having active Tuberculosis disease where SCORE is equal to or greater than four. If the relative percentage of mononuclear CD4 T-cells producing TNFa but not IFN-γ or IL-2 is greater than about 35%, 37.4%, or 38.8%) and Mtb-specific CD8 T cells are detected, the individual is typically identified as having active Tuberculosis disease. In such embodiments, SCORE may be equal to or greater than four. Conversely, if the relative percentage of mononuclear CD4 T-cells producing TNFa but not IFN-γ or IL-2 is less than about 35%, 37.4%, or 38.8% and Mtb- specific CD8 T cells are detected, the individual is typically identified as not having active Tuberculosis disease but latent Mtb infection. In such embodiments, SCORE may be less than four. In some embodiments, the relative percentage is determined using flow cytometry.

Also provided are methods for monitoring Tuberculosis disease in an individual being treated for the disease (e.g., by an antibiotic), the method comprising isolating mononuclear cells from the individual 4 weeks, 3 months and / or 6 months after initiation of antibiotic therapy; incubating the cells with a peptide derived from Mycobacterium tuberculosis; assaying the relative percentage of CD4 T-cells producing TNFa, IFN-γ, and IL-2 and determining whether t¾-specific CD8 T cells are also present therein; and continuing and / or modifying the current course of antibiotic therapy depending on whether the individual is determined to have active Tuberculosis disease (e.g., SCORE is equal to or greater than four). In some embodiments, the methods further comprise repeating these steps. The methods may also comprise administering an antibiotic to an individual having active Tuberculosis disease for 6 months prior to conducting such analyses.

Another measure that may be used to distinguish between latent Mtb infection and active TB disease relates to the expression of IL-17 (e.g., IL-17A, IL-17B, IL17C, IL17D, IL17E and IL17F; preferably IL-17A) by mononuclear cells, such as T cells, especially CD4⁺ T cells. This measurement may be made in addition to those described above (e.g., determining the SCORE value of the individual). In certain embodiments, the IL-17 assay comprising exposing mononuclear cells of the individual (which may be the same population of cells from which the SCORE value is determined) to one or more Mtb antigens and detecting the expression of IL-17, wherein the expression of IL-17 indicates the patient has latent Mtb infection is provided. In one embodiment, the method may include exposing mononuclear cells of the individual to one or more Mtb antigen(s); culturing said mononuclear cells in vitro; restimulating the cultured mononuclear cells; and, assaying supernatant in which the mononuclear cells of step c) were cultured or assaying the cells of step c) to detect IL-17 therein where detection of IL-17 indicates the individual may have latent Mtb infection; and, lack of detection of IL-17 indicates the individual may have active TB disease. In certain embodiments, methods for distinguishing a patient having latent Mtb infection from a patient having active TB disease, the method comprising identifying within a biological sample of a patient having latent Mtb infection, but not in a biological sample of a patient having active TB disease, mononuclear cells that express IL-17 in the presence of Mtb antigen are provided. In some embodiments, the mononuclear cells are peripheral blood mononuclear cells (PBMCs). In certain embodiments, the IL-17 is IL-17A. Some embodiments provide for detection of IL-17 in the culture supernatant of mononuclear cells that have been exposed to one or more Mtb antigens in vitro. Some embodiments provide for detection of IL-17 within the mononuclear cells that have been exposed to one or more Mtb antigens in vitro. In certain embodiments, the mononuclear cells are CD4⁺ T cells. Methods for treating individuals are also provided. For examples, an individual may be treated for latent Mtb infection if IL-17 in detected using the methods described herein, or treated for active TB disease if IL-17 is not detected using these methods.

Other embodiments of these methods will be evident to the skilled artisan from this disclosure.

DETAILED DESCRIPTION

This disclosure relates to methods for differentiating between mammals having active Tuberculosis (TB) disease and latent Mtb infection. This is of particular importance at both the individual (e.g., one mammal) but also population level (e.g., multiple mammals) since only individuals with active TB infection are infectious. Related methods have been described previously, but none have been found to have the required sensitivity and specificity as those described herein. For example, an IFN-γ ELISpot assay has been described but found not to be useful for differentiating between active TB disease and latent Mtb infection. Other studies have shown that Mtb-specific CD4⁺ T-cells with latent infection were mostly polyfunctional (e.g., composed of more than 50% of TNFa⁺IFNy⁺IL-2⁺) while more than 50% of the CD4⁺ T cells in patients with active TB disease were monofunctional (e.g., TNF X⁺IFNYTL-2^~). While a lack of overlap between the functional profiles of CD4⁺ cells of patients with active TB disease and latent infection suggested that this assay may be useful as a diagnosis tool, it was found not to provide either the required sensitivity or specificity. Furthermore, Mtb- specific CD8 T-cell responses have been detected in the majority of TB patients (72%) and in few (15%) LTBI subjects ( O.0001 ; Fig. IB; Rozot, et al. (2012)). But the magnitude of rf?-specific CD8 T-cell responses, as determined by the frequency of IFN- γ-producing CD8 T cells, was found not to be significantly different between LTBI and TB subjects (Fig. 1C; Rozot, et al. (2012)). This disclosure provides an assay by which measurements relating to both CD4 T cells and CD8 T cells have been surprisingly found to provide an even more robust method for identifying individuals with active Tuberculosis disease than was previously possible.

Thus, in one embodiment, a method for identifying with sufficient sensitivity and specificity an individual having active TB disease by determining the relative percentage of one or more particular types of reactive CD4⁺ T cells and CD8⁺ T cells is provided. In one embodiment, t¾-specific CD4⁺ T cells and CD8⁺ T cells may be characterized by isolating the cells from an individual (e.g., having either latent Mtb infection or active TB disease), contacting those cells with Mtb antigens (e.g., peptides such as ESAT-6, CFP- 10, and / or tuberculin purified-Protein-Derivative (PPD RT23) and / or derivatives thereof as described herein), assaying said cells to determine the types of cells therein and / or cytokines (e.g., IL-2, IFN-γ, and TNF-a) expressed thereby. Cytokine expression may be measured using any suitable assay system. Such systems include, for example, immunoprecipitation, particle immunoassays, immunoephelometry, radioimmunoassay, enzyme immunoassay (e.g., ELISA), fluorescent immunoassay (e.g., flow cytometry), and / or chemiluminescent assays. As shown in the Examples below, polychromatic flow cytometry may be especially suitable. Additional assay systems that may be useful in making these determinations are described in, for example, the Examples section. In certain embodiments, the methods comprise isolating mononuclear cells from the mammal, incubating the cells with one or more Mtb antigens and assaying the mononuclear cells to determine the relative percentage of CD4 T-cells for expression of TNFa, IFN-γ, and IL-2 therein to produce a "CD4 value" and for the presence of Mtb- specific CD8 T cells to produce a "CD8 value". The CD4 value and the CD8 value are then combined using a logistic regression model to provide a "combined value". In certain embodiments, the logistic regression model comprises the formula:

Log(odds) = SCORE ~ 0.097 * (%TNF-a) + 3.157 *(CD8) wherein:

%TNF-a refers to the percentage of rf?-specific single TNF-a-producing CD4 T cells; and,

CD 8 refers to 0 (zero) or 1, wherein:

0 indicates the absence of an rf?-specific CD 8 T-cell response; and,

1 indicates the presence of an t£-specific CD8 T-cell response. In certain embodiments, an individual is identified as having active Tuberculosis disease where SCORE is equal to or greater than four. If the relative percentage of mononuclear CD4 T-cells producing TNFa but not IFN-γ or IL-2 is greater than about 35%, 37.4%, or 38.8%) and t^-specific CD8 T cells are detected, the individual is typically identified as having active Tuberculosis disease. In such embodiments, SCORE may be equal to or greater than four. Conversely, if the relative percentage of mononuclear CD4 T-cells producing TNFa but not IFN-γ or IL-2 is less than about 35%, 37.4%, or 38.8% and Mtb- specific CD8 T cells are detected, the individual is typically identified as not having active Tuberculosis disease but latent Mtb infection. In such embodiments, the SCORE value may be less than four. In some embodiments, the relative percentage and / or detection of CD8 T cells may be accomplished using an assay system such as flow cytometry.

In certain embodiments, these methods may be combined with an IL-17-based assay. Production of IL-17 in response to exposure to Mtb antigen(s) may be considered an IL-17 effector function. An "immediate" IL-17 effector function is typically one that is observed in mononuclear cells (e.g., PBMCs) after isolation from an individual without further exposure (e.g., in vitro) to Mtb antigen(s). In certain embodiments, an individual having latent Mtb infection may be distinguished from an individual with active TB disease by measuring the expression of IL-17 (e.g., IL-17A, IL17B, IL17C, IL17D, IL17E and IL17F; preferably IL-17A) by mononuclear cells (e.g., peripheral blood mononuclear cells (PBMC), T cells (e.g., CD4⁺ T cells and / or CD8⁺ T cells) of the individual after exposing such cells to Mtb antigen(s). For instance, mononuclear cells obtained from a mammal with latent Mtb infection may be determined to express IL-17 following exposure to Mtb antigen(s) (e.g., in vitro). In contrast, mononuclear cells of a mammal having active TB disease assayed in this way typically do not to express IL-17. Thus, the presence of IL-17-producing mononuclear cells (e.g., CD4⁺ T cells) in a biological sample of an individual (e.g., after stimulation with Mtb antigen) may allow one to exclude the diagnosis of active TB disease and / or diagnose latent Mtb infection. Such mononuclear cells may be t¾-specific CD4⁺ T cells that exhibit an IL-17 effector function, and may be detected in patients with latent Mtb infection but not those with active TB disease. As shown herein, acquisition of IL-17 effector function by Mtb- specific CD4⁺ T cells may also directly correlate with expression (e.g., co-expression) of CXCR3 and / or CCR6. Thus, this disclosure provides methods for identifying an individual having latent Mtb infection, a mammal having active TB disease, and / or distinguishing an individual having latent Mtb infection from one having active TB disease by detecting in a biological sample of the mammal mononuclear cells (e.g., CD4⁺ T cells) that express IL-17 in the presence of Mtb antigen(s). Such methods may also be used to predict and / or determine disease status (e.g., latent Mtb infection vs. active TB disease) of a mammal. Such methods typically include assays that comprise exposing mononuclear cells (e.g., CD4⁺ T cells) to Mtb antigen and detecting IL-17 in the cell culture supernatant and / or within the cells per se (e.g., intracellular), wherein the detection of IL-17 indicates the mammal may have (e.g., has) latent Mtb infection and / or the lack of detection of IL-17 indicates the mammal may have (e.g., has) active TB disease. As described herein, cytokine expression may be measured using any suitable assay system such as, for example, immunoprecipitation, particle immunoassays, immunoephelometry, radioimmunoassay, enzyme immunoassay (e.g., ELISA), fluorescent immunoassay (e.g., flow cytometry), and / or chemiluminescent assays. As shown in the Examples below, polychromatic flow cytometry may be especially suitable. Additional assay systems that may be useful in making these determinations are also available as would be understood by one of ordinary skill in the art.

Cytokines that may suitable to measurement in the assays described herein include, for example, IFN-γ, TNF-a, IL-2, and / or IL-17, among others. The results derived from the any of assays described herein may be combined to provide added confidence to the diagnosis of active TB disease or latent Mtb infection. The assays per se may be also combined such that the expression of multiple cytokines and / or cell surface (or other) markers may be measured essentially simultaneously. Cell surface markers that may be suitable for measurement in the assays described herein include, for example, CD3, CD4, CD8, CD19, CD28, CD127, CD154, CD45RA, and / or CCR7, among others. In certain embodiments, expression (e.g., co-expression) of CXCR3 and / or CCR6 may be useful in making the determinations described herein. For cytokine measurement, ELISpot assays may be performed per the instructions of the manufacturer (e.g., Becton Dickinson). Other assay systems that may utilized include, for example, enzyme-linked immunosorbent assay (ELISA), multiplex assays (e.g., arrays, Luminex platform), radioimmunoassay, bioassay, microspheres, intracellular detection (e.g., permeabilization and detection using antibodies), detection of RNA (e.g., messenger RNA (mRNA), using microarrays, polymerase chain reaction, northern blot, and / or similar techniques), flow cytometry, and the like, and / or combinations of such assays. Cell culture supernatants and / or cells per se (e.g., intracellular cytokines) may be assayed for the presence of cytokines. Flow cytometric techniques may also be useful for measuring cytokine expression, which is typically measured by intracellular cytokine staining (ICS). In any such assays, cells may first be assessed for viability by, for example, LIVE/DEAD staining (e.g., Aqua or ViViD from Invitrogen). Typically, the population of cells studied will be at least about 80% viable. In some embodiments, the cells may be at least about any of 85%, 90%, 95%, or 99% viable. Assays are also typically performed in duplicate, triplicate, or quadruplicate. It is standard practice to use software for data procurement and analysis. Statistical analysis is also typically performed (e.g., Fisher's exact test, two-tailed student t test, logistic regression analysis) to provide sensitivity, specificity, positive predictive value (PPV), and / or negative predictive value (NPV). A sensitivity / specificity graph (e.g., ROC-curve graph) may also be generated to determine the probability cutoff. Other cytokines, cell surface markers, and percentages may also be useful in carrying out the methods described herein as would be understood by the skilled artisan.

In carrying out the methods described herein, it may be particularly useful to measure expression of IFN-γ, TNF-a, and IL-2 in circulating peripheral blood mononuclear cells (PBMC) of individuals having active TB disease and / or individuals having latent Mtb infection. In some embodiments, expression of IFN-γ, TNF-a, and IL- 2 of CD4⁺ T cells in such individuals may be assayed (additional cytokines may also be assayed). As shown herein, the expression of TNF-a without substantial co-expression of IFN-γ and / or IL-2 may be used as a measure differentiating between individuals experiencing active Tuberculosis disease and latent Mtb infection. For instance, in some embodiments, greater than about 35% to 40% of circulating CD4⁺ T cells in an individual with active TB disease will express TNF-a without substantially co-expressing IFN-γ and / or IL-2. In certain embodiments, greater than about 37.4% of circulating CD4⁺ T cells in an individual with active TB disease will express TNF-a without substantially co- expressing IFN-γ and / or IL-2. And in other embodiments, greater than about 38.8% of circulating CD4⁺ T cells in an individual with active active Tuberculosis will express TNF-a without substantially co-expressing IFN-γ and / or IL-2. These determinations may also be combined with a determination regarding the presence and / or absence of CD8+ T cells in the mononuclear cells. As described above, these determinations may be combined to provide a SCORE value from which a determination may be made regarding whether an individual has active Tuberculosis disease or not (e.g., LTBI).

As described in certain embodiments of this disclosure, it may also be particularly useful to measure expression of IL-17 in mononuclear cells (e.g., peripheral blood mononuclear cells (PBMC), T cells, and / or CD4⁺ T cells) of individuals having active TB disease and / or individuals having latent Mtb infection. In some embodiments, it may be useful to measure and / or compare the expression of IL-17 in mononuclear cells (e.g., after stimulation with Mtb antigen(s)) of individuals suspected to have either active TB disease or latent Mtb infection. In some embodiments, the expression of IL-17 by or within mononuclear cells may be assayed along with other additional cytokines and / or cell surface markers. As shown in the Examples, the expression of IL-17 may be used as a measure differentiating individuals experiencing active TB disease from those with latent Mtb infection. For instance, it has been determined that mononuclear cells that produce IL-17 (e.g., IL-17 producing cells) in the presence of Mtb antigen may be detected in greater than about 50% of individuals with latent Mtb infection while such cells are typically not detected in individuals with active TB disease. Certain of these mononuclear cells also express cell surface markers such as CXCR3 and / or CCR6. As described in the Examples, to carry out such assays, mononuclear cells (e.g., PBMCs) of an individual may be stimulated with Mtb antigen(s) followed by a short term in vitro culture (e.g., typically 5-7 days) and then a short (e.g., 6-hour) re-stimulation (e.g., polyclonal) of the expanded cells. The cells are then assayed to detect IL-17 expression (e.g., in the culture supernatant and / or within and / or upon the cells per se). As shown in the results presented in the Examples, the samples of about half the patients with latent Mtb infection will typically contain IL-17 producing cells while, typically, samples from individuals with active TB disease will not contain any IL-17 producing cells. Thus, the presence of IL-17-producing mononuclear cells (e.g., CD4⁺ T cells), optionally following exposure of such cells to Mtb antigen(s), may allow one to exclude the diagnosis of active TB disease and / or conclude that the individual may have or has a latent Mtb infection. Other embodiments may also be derived from the Examples described herein.

It is preferred that the measurement (e.g., combined values, SCORE values) are determined to be statistically significant (e.g., <0.05-0.0001 including but not limited to O.004). In some embodiments, these assays provide a PPV of at least about 60%>, an NPV of at least about 90% or about 95% or about 99% (e.g., 97.5%), a sensitivity of at least about 80%> or about 90%> (e.g., 92%), a specificity of greater than at least about 80%, about 90% (e.g., 83.5%), and an OR of at least about 50 or about 60 (e.g., 58). In addition, there should also be concordance between the results of the assay and clinical determinations of, for example, at least about 90%. It is preferred that these assays accurately diagnose active Tuberculosis disease in at least about 80%> of cases, preferably greater than about 84% of cases, and even more preferably greater than about 90% of cases. In some instances, the assays may assays accurately diagnose active Tuberculosis disease in at least about 95% or all cases. As mentioned above, a SCORE value of four (e.g., an "optimal" value as explained in the Examples) was found to be indicative of active Tuberculosis disease. As shown herein, the multivariate analysis methods described herein (e.g., combining both the functional profile of CD4 T cells and the presence of t£-specific CD8 T cells) surprisingly provides the skilled artisan with the ability to efficiently and accurately discriminate between patients having active Tuberculosis disease and those with LTBI. These methods surprisingly provide a substantial improvement in the OR (e.g., 70% increase) and specificity (e.g., 30% increase) as compared to the CD4⁺ T cell measurements alone. Other variables may also be measured, and statistics calculated, that may also be useful in using the methods described herein as would be understood by the skilled artisan.

Assays systems that may be used in making these determinations may be, for instance, any of those described in the Examples or otherwise available to one of ordinary skill in the art. Expression of such cytokines may be determined after stimulating PBMCs (e.g., or purified sub-populations thereof) with peptides derived from Mtb. For instance, PMBCs may be stimulated with antigens ESAT-6 (e.g., GenBank NC 000962; MTEQQWNFAGIEAAASAIQGNVTSIHSLLDEGKQSLTKLAAAWGGSGSEAYQG VQQKWDATATELNNALQNLARTISEAGQAMASTEGNVTGMFA (SEQ ID NO.: 1)), CFP-10 (e.g., GenBank NC 000962;

MAEMKTDAATLAQEAGNFERISGDLKTQIDQVESTAGSLQGQWRGAAGTAAQA AVVRFQEAANKQKQELDEISTNIRQAGVQYSRADEEQQQALSSQMGF (SEQ ID NO.: 2)), tuberculin purified-Protein-Derivative (PPD RT23) (Statens Serum Institute, Denmark), and / or derivatives thereof. Peptide pools derived from such antigens may also be used to stimulate the cells. For instance, a collection of 9-20 amino acid peptides being adjacent to one another on the parent antigen, or overlapping one another, such at least about all of the amino acid sequences of the parent antigen are represented, may be used to stimulate the cells. In certain embodiments, overlapping 15 amino acid peptides (e.g., "15-mers") may be generated. In some embodiments, the amino acid sequences of such 15-mers may overlap by 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 amino acids and may represent some or all of the amino acid sequences present in the parent antigen. In certain embodiments, the 15-mers overlap one another by 11 amino acid sequences in series such that together the collection represents part of or the entire parental antigen sequence. For instance, a set of 15-mers derived from ESAT-6 and / or CFP-10 that overlap each other by 11 amino acids where at least part, and optionally all, of SEQ ID NOS.: 1 and / or 2 are represented may be used. The peptides may be placed into culture with PBMCs for a sufficient period of time (e.g., eight hours) prior to further analysis. Positive control assays may include, for example, Staphylococcal enterotoxin B. Other peptides may also be used as would be understood by the skilled artisan.

The methods described herein may also be used to monitor and / or guide therapy. For instance, individuals diagnosed as having active TB disease are typically treated with antibiotics including, for example, isoniazid, rifmpicin (e.g., rifampin), pyrazinamide, ethambutol, and streptomycin. Typically, combinations of such antibiotics are used. A standard antibiotic therapy for treating active TB disease consists of administration of isoniazid, rifmpicin (e.g., rifampin), pyrazinamide, and ethambutol for two months, then isoniazid and rifampicin alone for a further four months. The individual is typically considered cured at six months, although relapse rate of 2 to 3% has been observed. In some instances, treatment with such antibiotics is not completely effective. Additional drugs that may be used include, for example, aminoglycosides (e.g., amikacin (AMK), kanamycin (KM)), polypeptides (e.g., capreomycin, viomycin, enviomycin), fluoroquinolones (e.g., ciprofloxacin (CIP), levofloxacin, moxifloxacin (MXF)), thioamides (e.g., ethionamide, prothionamide), cycloserine, and / or /^-aminosalicylic acid (PAS or P), rifabutin, macrolides (e.g., clarithromycin (CLR)), linezolid (LZD), thioacetazone (T), thioridazine, arginine, vitamin D, and / or R207910 (also known as TMC207). For treatment of latent Mtb infection, the standard treatment is six to nine months of isoniazid alone. Other treatment regimens that have been used to treat latent infection include, for example, rifampin for four months, daily administration of isoniazid and rifampin for three months, or administration of rifampin and pyrazinamide for two months (not typically used). Other treatment regimens may also be in use or developed in the future, as would be understood by the skilled artisan.

The treatment of active TB disease and / or latent Mtb infection may be monitored using the methods described herein. Depending on the results, the treatment regimen may be continued or changed as required. For example, it may be beneficial to determine the relative percentage of CD4⁺ T cells that express TNF-a without substantially co- expressing IFN-γ and / or IL-2 relative to total number of CD4⁺ T cells in an individual being treated for active TB disease or latent Mtb infection and the presence of Mtb- specific CD8+ T cells. Where the relative percentage of CD4⁺ T cells expressing TNF-a without substantially co-expressing IFN-γ and / or IL-2 is greater than about 35% (e.g., 37.4%, 38.8%o) and rf?-specific CD8+ T cells are detected (e.g., using an in vitro assay), it may be concluded that the individual is experiencing active TB disease and that the current treatment regimen may need to be continued and / or modified. This is especially so where the SCORE value is equal to or greater than four. Where the relative percentage of CD4⁺ T cells expressing TNF-a without substantially co-expressing IFN-γ and / or IL-2 is less than about 35% (e.g., 37.4%, 38.8%) and 6-specific CD8+ T cells are not detected, and / or the SCORE value is less than four, it may be concluded that the individual is experiencing latent Mtb infection (LTBI) and that the current treatment regimen is effective and may not need to be continued and / or modified. In some instances, treatment of a patient may be monitored over a period of time (e.g., after one, two, three, or four weeks, or one, two three, four, five six months, or more following the initiation of the antibiotic therapy). During that time period, the relative percentage of CD4⁺ T cells expressing TNF-a without substantially co-expressing IFN-γ and / or IL-2 and / or the number of t£-specific CD8+ T cells detected, and / or the SCORE value, may change indicating that the disease status of the individual has changed. In such instances, the treatment regimen may also need to be changed. For example, an increase in the relative percentage of CD4⁺ T cells expressing TNF-a without substantially co- expressing IFN-γ and / or IL-2 and / or an increase the number of t^-specific CD8+ T cells detected, and / or an increased SCORE value (e.g., to four or above), at the six month time point as compared to the four-week time point may indicate a shift from latent Mtb infection to active TB disease, thus requiring a change in the treatment regimen (e.g., from no treatment to a combination of isoniazid, rifmpicin (e.g., rifampin), pyrazinamide, and ethambutol for two months, and / or isoniazid and rifampicin alone for a further four months). Similarly, the methods relating to the measurement of IL-17 may be alternatively, or additionally, utilized to make such determinations. For example, if is determined that the number of IL-17 producing cells has decreased in an individual (e.g., as determined using the IL-17 related assays described herein) during treatment, it may indicate the individual is beginning to experience active TB disease. Conversely, if the number of IL-17 producing cells increases in an individual (e.g., as determined using the IL-17 assays described herein) during treatment, it may indicate the individual is beginning to experience latent Mtb infection. As mentioned above, the results of TNF- related and IL-17-related assays may be combined to design an appropriate treatment regimen for a particular individual. The TNF -related and IL-17-related assays per se may be also combined such that the expression of multiple cytokines may be measured essentially simultaneously. Thus, the methods described herein may be used to monitor and / or guide treatment of TB disease (e.g., active TB disease) and / or latent Mtb infection. Other embodiments of such methods may also be suitable as would be understood by the skilled artisan.

Also provided herein are kits for detecting the cytokines and / or cell surface (or other) markers in an individual. As described above, various types of detection systems may be utilized to detect the cytokines and / or cell surface (or other) markers in order to diagnose, exclude, and / or distinguish between active TB disease and latent Mtb infection (e.g., ELISpot assays, ELISA, multiplex assays (e.g., arrays, Luminex platform), radioimmunoassay, bioassay, microspheres, intracellular detection (e.g., permeabilization and detection using antibodies), detection of RNA (e.g., messenger RNA (mRNA), using microarrays, polymerase chain reaction, northern blot, and / or similar techniques), flow cytometry, and the like). Kits for detecting TNF-a, IFN-γ, IL- 2, and / or IL-17, for example, may include the reagents required to carry out an assay using one or more of the formats available to one of skill in the art, optionally a control reaction (e.g., a known positive or negative reaction (e.g., supernatant known to contain a certain amount of one or more cytokines, cells known to intracellularly express one or more cytokines, and / or either of these known to lack an amount of one more cytokines), and instructions for using the same (e.g., regarding set-up, interpretation of results). The kit may also include reagents used to isolate (e.g., for ficoll-histopaque separation), stimulate (e.g., control antigens, Mtb antigens, phorbol myristate), and / or detect (e.g., optionally labeled antibodies, optionally labeled oligonucleotides, one or more reagents to detect an antibody and / or oligonucleotide) mononuclear cells. The label is typically a detectable label, for example a fluorescent or chromogenic label or a binding moiety such as biotin. The reagents may be free in solution or may be immobilized on a solid support, such as a magnetic bead, tube, microplate well, or chip. The kit may further comprise detection reagents such as a substrate, for example a chromogenic, fluorescent or chemiluminescent substrate, which reacts with the label, or with molecules, such as enzyme conjugates, which bind to the label, to produce a signal, and / or reagents for immunoprecipitation (i.e., protein A or protein G reagents). The detection reagents may further comprise buffer solutions, wash solutions, and other useful reagents. The reagents may be provided in one or more suitable containers (e.g., a vial) in which the contents are protected from the external environment. The kit may also comprise one or both of an apparatus for handling and/or storing the sample obtained from the individual and an apparatus for obtaining the sample from the individual (i.e., a needle, lancet, and collection tube or vessel). Where the assay is to be combined with another type of assay such as PCR, the required reagents for each of such assays (i.e., primers, buffers and the like) along with, optionally, instructions for the use thereof, may also be included. Other types of kits may also be provided, as would be understood by one of ordinary skill in the art.

Throughout this disclosure, exemplification and / or definition of specific terms should be considered non-limiting. For example, the singular forms "a", "an" and "the" include the plural unless the context clearly dictates otherwise. Approximating language, as used herein throughout the specification and claims, may be applied to modify any quantitative representation that could permissibly vary without resulting in a change in the basic function to which it is related. Accordingly, a value modified by a term such as "about" is not to be limited to the precise value specified. Where necessary, ranges have been supplied, and those ranges are inclusive of all sub-ranges there between. The use of the singular may include the plural unless specifically stated otherwise or unless, as will be understood by one of skill in the art in light of the present disclosure, the singular is the only functional embodiment. Thus, for example, "a" may mean more than one, and "one embodiment" may mean that the description applies to multiple embodiments. The phrase "and/or" denotes a shorthand way of indicating that the specific combination is contemplated in combination and, separately, in the alternative.

It will be appreciated that there is an implied "about" prior to the temperatures, concentrations, times, etc. discussed in the present teachings, such that slight and insubstantial deviations are within the scope of the present teachings herein. Also, the use of "comprise", "comprises", "comprising", "contain", "contains", "containing", "include", "includes", and "including" are not intended to be limiting. It is to be understood that both the foregoing general description and detailed description are exemplary and explanatory only and are not restrictive of the invention.

Unless specifically noted in the above specification, embodiments in the above specification that recite "comprising" various components may also be contemplated as "consisting of or "consisting essentially of the recited components; embodiments in the specification that recite "consisting of various components may also be contemplated as "comprising" or "consisting essentially of the recited components; and embodiments in the specification that recite "consisting essentially of various components may also be contemplated as "consisting of or "comprising" the recited components.

All references cited within this disclosure are hereby incorporated by reference in their entirety. While certain embodiments have been described in terms of the preferred embodiments, it is understood that variations and modifications will occur to those skilled in the art. Therefore, it is intended that the appended claims cover all such equivalent variations that come within the scope of the following claims.

EXAMPLES

Example 1

A. Methods

Study groups. The 37 TB patients from this study had a diagnosis based on laboratory isolation of Mtb on mycobacterial culture from sputum, broncho-alveolar lavage fluid or biopsies and/or tuberculin skin-test and/or ELISpot and/or PCR as described (Harari, et al. 2011; WO 2012/085652 A2 pub. June 28, 2012). Five patients with clinical TB (culture negative) presented specific symptoms and responded to treatment. Epidemiological, clinical and microbiological data of TB patients are detailed in Suppl. Table 1. All 141 LTBI subjects were asymptomatic and had t¾-specific T-cell responses specific to ESAT-6 and/or CFP-10. LTBI subjects were either health-care workers routinely screened at the Centre Hospitalier Universitaire Vaudois (CHUV) or were investigated for Mtb infection prior to the initiation of anti-TNF-a antibody treatment and had negative chest radiographs. These studies were approved by the Institutional Review Board of the CHUV and all subjects gave written informed consent.

Flow cytometry analyses and T-cell stimulations. In brief, cryopreserved peripheral blood mononuclear cells were thawed, rested and stimulated overnight with pools of overlapping peptides encompassing ESAT-6 or CFP-10 and were then labeled (viability dye, CD3, CD4, CD8, IFN-γ, TNF-a and IL-2), acquired on a 4-laser flow-cytometer and analyzed as described (Harari, et al. 2011; WO 2012/085652 A2 pub. June 28, 2012). Statistical analyses. Comparisons of categorical variables were performed using Fisher's exact test. Statistical significance of the magnitude of ICS responses was calculated by unpaired two-tailed Student's t-test using GraphPad Prism 6.00. Logistic regression followed by a Receiver Operating Characteristic (ROC) curve analyses were used to evaluate the performances of each parameter (presence of t^-specific CD8 T cells and the frequency of single TNF-a-producing CD4 T cells) to identify active TB (Zweig, 1993). A logistic regression model was used to assess the potential benefit of the combination of both covariates. This model estimated the log odds of active TB disease probability as a function of both variables (i.e. SCORE). Results for the distinct variables were summarized as a contingency table giving sensitivity, specificity, positive and negative predictive value (PPV and NPV). These analyses were performed using MedCalc 12.3.0.

B. Experimental Results

LTBI subjects (141) and 37 untreated TB patients (Suppl. Table 1) were studied as described below. t£-specific CD4 and CD8 T-cell responses were assessed using polychromatic flow cytometry following stimulation with ESAT-6 and/or CFP-10 peptide pools and labeled with a viability marker and anti-CD3, -CD4 and -CD8, -IFN-γ, -TNF-a and -IL-2 antibodies as described (Harari, et al. 2011; WO 2012/085652 A2 pub. June 28, 2012). Consistent with previous observations, the cytokine profile of Mtb- specific CD4 T-cell response was distinct between TB patients and LTBI subjects and a significantly (P<0.00001) higher proportion of single-TNF-a-producing CD4 T cells was found in TB patients (Fig. 1A). Furthermore, as previously shown (Rozot, et al. (2012)), t£-specific CD8 T-cell responses were detected in the majority of TB patients (72%) and in few (15%) LTBI subjects ( <0.0001; Fig. IB). In contrast, the magnitude of Mtb- specific CD8 T-cell responses, as determined by the frequency of IFN-y-producing CD8 T cells, was not significantly different between LTBI and TB subjects (Fig. 1C).

The capacity for each parameter {i.e. the cytokines profile of t^-specific CD4 T cells or the detection of t£-specific CD8 T-cell responses) to distinguish TB patients from LTBI subjects was then studied. On the basis of a logistic regression analysis, it was confirmed that the cytokines profile of rf?-specific CD4 T cells alone is a strong predictor measure of discrimination between active disease and latent infection (AUC=0.842 [95% CI: 0.780-0.892]; Fig. 2A) than δ-specific CD8 T-cell responses alone. Using the previously determined pre-defined threshold of 37.4%> of single TNF-a- producing CD4 T cells, the Odds-Ratio (OR) was 34.6, the specificity was 93.6%>, the sensitivity was 70.3%>, and the positive (PPV) and negative predictive values (NPV) were 74.3 %> and 92.3%>, respectively. The detection of rf?-specific CD8 T cells was also a strong predictor of discrimination between active disease and latent infection, but it was less accurate than the CD4 T-cell cytokines profile (AUC=0.798 [95% CI: 0.732-0.853]; OR=15.4; specificity=85.1%; sensitivity=73%; PPV=56.3%; NPV=92.3%; Fig. 2B).

In an attempt to develop an improved diagnostic assay, both components of the rf?-specific T-cell response {i.e. the cytokines profile of t£-specific CD4 T cells and the detection of t£-specific CD8 T-cell responses) were combined. A logistic regression model was used to assess the potential benefit of the combination of both covariates. This model estimated the log odds of active TB disease probability as a function of both variables, identifying a new covariate, termed "SCORE", which was defined as follows:

Log(odds) = SCORE ~ 0.097 * [%TNF-a] + 3.157 *[ CD8J where %TNF-a refers to the percentage of t^-specific single TNF-a-producing CD4 T cells and where CD8 refers to 0 (zero) or 1 according to the absence or presence of an Mtb-specific CD8 T-cell response, respectively ( <0.0001 for both coefficients). Surprisingly, the SCORE was found to be a significantly improved predictor measure of discrimination between active disease and latent infection (AUC=0,944 (95% CI: 899- 0.973); Fig. 2C) as compared to each individual variable analyzed independently (both <0.004). Analysis of the distribution of SCORE results from TB and LTBI subjects showed a significant difference between both groups ( O.0001; Fig. 2D). On the basis of the logistic regression analysis, an optimal cutoff of SCORE of 4 was determined (Fig. 2D). Assay performances were: OR=58; specificity=83.5%; sensitivity=92%; PPV=60% and NPV=97.5%. As compared to the individual use of the percentage of single TNF-a- producing CD4 T cells, the combined use of CD4 and CD8 T-cell responses was associated with substantial improvement in the OR (70% increase) and specificity (30% increase). It is important to note that assay performance was not influenced by TB clinical status (pulmonary vs. extrapulmonary TB; Fig. 3).

It is shown herein that the detection of CD8 T-cell responses may discriminate between active TB and latent infection but is less powerful than the t^-specific CD4 T cell response, i.e. single TNF-a producing CD4 T-cells. However, the multivariate analysis combining both the functional profile of CD4 T cells and the presence of Mtb- specific CD8 T cells surprisingly led to the identification of a new variable (SCORE) and significant improvement in discriminating between TB patients and LTBI subjects. This combined T-cell assay provides an additional and more sensitive assay to solve problems encountered by those of ordinary skill in the art (e.g., IGRA-positive subjects with undetectable t£-specific CD4 T-cell responses). Thus, as shown herein, the combination of two immunological measures, e.g., t^-specific CD4 and CD8 T-cell responses, represents a powerful diagnostic tool to discriminate between active and latent TB.

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Claims

CLAIMS What is claimed is:

1. A method for identifying an individual having active Tuberculosis disease, the method comprising:

a) incubating mononuclear cells of the individual with a peptide derived from

Mycobacterium tuberculosis (Mtb);

b) assaying the CD4 T-cells in the mononuclear cells of step a) for expression of TNFa, IFN-γ, and IL-2, wherein the relative percentage of mononuclear CD4 T- cells producing TNFa but not IFN-γ or IL-2 provides a CD4 value if the relative percentage is greater than 35%;

c) detecting t¾-specific CD8 T cells in the mononuclear cells of step a) to determine a CD 8 value; and,

d) combining the CD4 value and the CD8 value using a logistic regression model to provide a combined value.

2. The method of claim 1 wherein the combined value is obtained using the formula:

Log(odds) = SCORE ~ 0.097 * (%TNF-a) + 3.157 *(CD8) wherein:

%TNF-a refers to the percentage of rf?-specific single TNF-a-producing CD4 T cells; and,

CD 8 refers to 0 (zero) or 1, wherein:

0 indicates the absence of an rf?-specific CD 8 T-cell response; and,

1 indicates the presence of an t£-specific CD8 T-cell response.

3. The method of claim 2 wherein an individual is identified as having active Tuberculosis disease where the SCORE value is equal to or greater than four.

4. The method of any one of claims 1-3 wherein the relative percentage is greater than 37.4%.

5. The method of any one of claims 1-4 wherein the relative percentage is greater than 38.8%.

6. The method of any one of claims 1-5 wherein the relative percentage and the CD8 value are determined using flow cytometry.

7. A method for monitoring active Tuberculosis disease comprising:

a) administering to an individual having active Tuberculosis disease with an antibiotic for 6 months;

b) determining whether the individual has active Tuberculosis disease using the method of any one of claims 1-6; and,

c) continuing or modifying administration of the antibiotic therapy depending on whether the individual is determined to have active Tuberculosis disease in step b).

8. The method of claim 7 wherein step b is performed about four weeks, three months or six months following the initiation of the antibiotic therapy.

9. The method of claim 7 or 8 wherein the antibiotic therapy comprises administering to the individual drug selected from the group consisting of isoniazid, rifmpicin pyrazinamide, ethambutol, streptomycin, an aminoglycoside, amikacin, kanamycin, a polypeptide, capreomycin, viomycin, enviomycin, a fluoroquinolone, ciprofloxacin, levofloxacin, moxifloxacin, a thioamide, ethionamide, prothionamide, cycloserine, p- aminosalicylic acid, rifabutin, a macrolide, clarithromycin, linezolid, thioacetazone, thioridazine, arginine, vitamin D, R207910, and combinations thereof.

10. The method of claim 9 wherein the antibiotic therapy is selected from the group consisting of isoniazid alone, rifampin for four months, daily administration of isoniazid and rifampin for three months, and administration of rifampin and pyrazinamide for two months.

11. The method of any one of claims 7-10 wherein the antibiotic therapy is a combination of isoniazid, rifmpicin, pyrazinamide, and ethambutol; or a combination of isoniazid and rifampicin alone.

12. The method of any one of claims 7-11 further comprising repeating step b).

13. The method of any one of claims 1-12, further comprising exposing mononuclear cells of the individual to one or more Mtb antigens and detecting the expression of IL- 17, wherein the expression of IL-17 confirms that the patient does not have active Mtb infection.

14. The method of claim 13 wherein the mononuclear cells are peripheral blood mononuclear cells.

15. The method of claim 13 or 14 wherein the IL-17 is IL-17 A.

16. The method of any one of claims 13-15 wherein the IL-17 is detected in culture supernatant of said mononuclear cells that have been exposed to one or more Mtb antigens in vitro.

17. The method of any one of claims 13-16 wherein the IL-17 is detected in within said mononuclear cells that have been exposed to one or more Mtb antigens in vitro.

18. The method of any one of claims 13-17 wherein the mononuclear cells are CD4⁺ T cells.