USE OF PROTEINS PD-1 AND CD38 AS MARKERS OF AN ACTIVE AUTO-IMMUNE PATHOLOGY

Abstract

The present invention relates to a method for diagnosis, prediction and/or prognosis of an active autoimmune pathology in a subject, comprising detecting the co-expression of PD-1 and CD38 proteins at the surface of T lymphocytes in a biological sample from the subject.

The present invention also relates to a use of the pool of PD-1 (Programmed cell death 1) and CD38 protein as biomarkers for diagnosis, prediction and/or prognosis of an active autoimmune pathology in a subject.

The present invention further relates to a test device for detecting the co-expression of PD-1 and CD38 in a sample from a subject, comprising: (i) optionally means for obtaining a sample from the subject, and (ii) means for detecting the co-expression of PD-1 and CD38 at the surface of the T lymphocytes in said sample, and (iii) means for determining the frequency of co-expression of PD-1 and CD38 in the sample

Claims

1. A method for diagnosis, prediction and/or prognosis of an active autoimmune pathology in a subject, comprising detecting the co-expression of the proteins PD-1 (Programmed cell death 1) and CD38 at the surface of T lymphocytes in a biological sample of the subject.

2. The method according to claim 1, wherein said biological sample is a blood fraction or a whole blood sample, or a biopsy fraction, for example liver, of tissue.

3. The method according to claim 1, wherein the proteins PD-1 and CD38 are detected at the surface of CD3 and/or CD8 T lymphocytes and/or CD4 T lymphocytes.

4. The method according to claim 1, further comprising the steps of: (i) detecting the co-expression, at the surface of T lymphocytes, of PD-1 and CD38 in said sample and determining the frequency of co-expression of PD-1 and CD38; (ii) comparing the frequency of co-expression of PD-1 and CD38 determined in (i) with a reference value of the frequency of co-expression of PD-1 and CD38; (iii) testing for the presence or absence of a deviation of the frequency of co-expression of PD-1 and CD38 determined in (ii) from the reference value; and (iv) attributing the presence or absence of a deviation to a diagnosis, prediction and/or prognosis of the subject's active autoimmune pathology.

5. The method according to claim 1, wherein a frequency of co-expression of PD-1 and CD38 in said sample above a reference value indicates that the subject has the active autoimmune pathology or presents a risk of relapse of the active autoimmune pathology.

6. The method according to claim 1, wherein expression of at least one other biomarker selected from CD3, CD4, CD8, CD45RA, CXCR5, CD127 and/or CD27 is detected.

7. The method according to claim 6, wherein co-expression of biomarker associations selected from PD-1/CD38/CD3, PD-1/CD38/CD3/CD4/CD8/CD45RA, PD-1/CD38/CD3/CD4/CD8/CD45RA/CD127, PD-1/CD38/CD3/CD4/CD8/CD45RA/CXCR5/CD127, and/or PD-1/CD38/CD3/CD4/CD8/CD45RA/CXCR5/CD127/CD27 associations are detected.

8. The method according to claim 6, wherein the frequency of lymphocyte populations defined by the following phenotypes is detected: a) CD3+CD45RA-PD-1+CD38+; b) CD3+CD4+CD8-CD45RA-PD-1+CD38+and/or CD3+CD4-CD8+CD45RA-PD-1+CD38+; c) CD3+CD4+CD8-CD45RA-CD127-PD-1+CD38+and/or CD3+CD4-CD8+CD45RA-CD127-PD-1+CD38+; d) CD3+CD4+CD8-CD45RA-CD127-CXCR5-PD-1+CD38+and/or CD3+CD4-CD8+CD45RA-CD127-CXCR5-PD-1+CD38+; and/or e) CD3+CD4+CD8-CD45RA-CD127-CXCR5-CD27+PD-1+CD38+and/or CD3+CD4-CD8+CD45RA-CD127-CXCR5-CD27+PD-1+CD38+.

9. The method according to claim 1, wherein the detection is performed by a method selected from flow or mass cytometry, an immunoassay technology, such as direct ELISA, indirect ELISA, sandwich ELISA, competitive ELISA, multiplex ELISA, radioimmunoassay (RIA) or ELISPOT technology, a mass spectrometry analysis method, a chromatography method, a qPCR method, and a combination of at least two of these methods.

10. The method according to claim 1, wherein said prediction is a prediction of the risk of relapse, in particular following the cessation or adjustment of a treatment.

11. The method according to claim 1, wherein said prediction is a prediction of the risk of developing an autoimmune pathology.

12. The method according to claim 1, wherein said active autoimmune pathology is autoimmune hepatitis, primary biliary cholangitis, primary sclerosing cholangitis, type 1 diabetes, multiple sclerosis, rheumatoid arthritis, lupus, or vasculitis or immunological toxicity related to immunotherapies in cancer treatment.

13. The method according to claim 1, wherein said active autoimmune pathology is autoimmune hepatitis.

14. The method according to claim 13, wherein said autoimmune hepatitis is an atypical form autoimmune hepatitis, including a seronegative form and/or with little or no lymphocytic infiltrate of the liver tissue.

15. The method according to claim 13, wherein the diagnosis is a discrimination of patients with autoimmune hepatitis from patients with non-alcoholic steatohepatisis (NASH), or a demonstration of hepatic autoimmunity in patients with NASH.

16. (canceled)

17. A test device for detecting the co-expression of PD-1 and CD38 at the surface of T lymphocytes in a sample from a subject, comprising: (i) optionally means for obtaining a sample from the subject, and (ii) means for detecting the co-expression of PD-1 and CD38 at the surface of T lymphocytes in said sample, and (iii) means for determining the frequency of co-expression of PD-1 and CD38 in the sample.

Description

BRIEF DESCRIPTION OF THE FIGURES

[0051] [FIG. 1] represents: A) representation of the unsupervised analysis strategy (FIowSOM) of flow cytometry data in 12 AIH and 12 NASH patients. B) Heatmap representing the expression of surface markers of the 4 lymphocyte populations (nodes) showing a significant increase (p<0.05) in AIH. Expression intensity ranging from striped (high expression) to white (low expression).

[0052] [FIG. 2] represents: A and D) Flow cytometry data representation of PD-1 and CD38 markers on CD3+CD4+CD45RA-CXCR5-CD127-CD27+(A) and CD3+CD8+CD45RA-CXCR5-CD127-CD27+(D) populations. B) and E) graphs representing the percentage of PD-1+CD38+cells per CD3+CD4+CD45RA-CXCR5-CD127-CD27+ cells (B) and per CD3+CD8+CD45RA-CXCR5-CD127-CD27+cells (E) in 32 AIH and 18 NASH patients. C and F) graphs representing the percentage of CD4+CD45RA-CXCR5-CD127-CD27+PD-1+CD38+(C) and CD8+CD45RA-CXCR5-CD127-CD27+PD1+CD38+(F) cells per CD3+cell. The p values were determined using the Mann-Whitney statistical test.

[0053] [FIG. 3] shows ROC curves based on the percentage of PD-1+CD38+cells of TLCD4 and TLCD3 in the parent population identified with the annotated markers above the ROC curve. In italics the cut-off value is shown in black with sensitivity and specificity values in parentheses. AUC values are shown on each graph.

[0054] [FIG. 4] shows ROC curves based on the percentage of PD-1+CD38+cells of TLCD8 and TLCD3 in the parent population identified with the annotated markers above the ROC curve. In italics the cut-off value is shown in black with sensitivity and specificity values in parenthesis. AUC values are shown on each graph.

[0055] [FIG. 5] is a representation of flow cytometry data values of PD-1 and CD38 markers in AIH patients in complete remission under treatment. A) Heatmap representing flow cytometry data values of PD-1 and CD38 markers in AIH patients in complete remission under treatment. In grey the data above the threshold values identified previously. B) Graphs representing the percentage of patients in complete remission under treatment with PD-1 and CD38 marker values above the previously determined threshold values (FIGS. 3 and 4).

[0056] [FIG. 6] is a representation of the analysis data between the simple measurement of PD-1 at the surface of T lymphocytes versus the measurement of co-expression of PD-1 with CD38 at the surface of T lymphocytes. Comparison of the percentage of CD3+PD-1+CD38+(A), CD3+PD-1+(B), CD3+CD4+PD-1+CD38+(C), CD3+CD4+PD-1+(D), CD3+CD8+PD-1+CD38+(E), and CD3+CD8+PD-1+(F) CD3+ cells between AIH and NASH patients. The p values were determined using the Mann-Whitney statistical test. ROC curves (% sensitivity/specificity) based on the percentage of CD3+PD-1+CD38+(G), CD3+PD-1+(H), CD3+CD4+PD-1+CD38+(I), CD3+CD4+PD-1+(J), CD3+CD8+PD-1+CD38+(K), and CD3+CD8+PD-1+(L) CD3+ cells between AIH and NASH patients are shown. AUC values are shown on each graph.

EXAMPLES

Example 1

Identification of Differential Lymphocyte Populations Between AIH and NASH Patients

[0057] In order to identify a specific signature of hepatic autoimmunity, we performed analyses of multiparametric flow cytometry data by unsupervised statistical methods (FIowSOM) between 12 AIH patients and 12 NASH patients, which represent the best choice as control population to answer our question.

[0058] This unsupervised approach allowed us to establish a flow cytometric identification strategy, using a total of 13 parameters including 10 cell surface markers (CD3, CD4, CD8, CD45RA, CXCR5, CCR6, CD27, CD127, PD-1 and CD38) and 1 viability marker, of two cell populations (TL CD4 and CD8) that are characterized by PD-1 and CD38 expression (FIG. 1).

[0059] In a cohort of 32 active AIH patients and 18 NASH patients, the two cell populations TL CD4 and TL CD8 expressing PD-1 and CD38 are significantly increased in the blood of AIH patients compared to NASH patients (FIG. 2). This strategy allows easy discrimination between hepatic autoimmunity (AIH) and hepatic inflammation (ROC curve; FIGS. 3 and 4).

[0060] In comparison, the single measurement of PD-1 expression at the surface of T lymphocytes (CD3+, CD3+CD4+ and CD3+CD8+) is much less sensitive to discriminate between hepatic autoimmunity (AIH) and hepatic inflammation (NASH) than the measurement of PD-1 and CD38 co-expression at the surface of T lymphocytes (FIG. 6. ROC curve). Indeed, the analysis of the difference in the frequency of T lymphocytes expressing PD-1 between active AIH patients and NASH patients is much less significant than the results obtained with the measurement of PD-1 and CD38 co-expression (FIG. 6).

[0061] These results demonstrate the interest of using these markers, especially in flow cytometry, as potential biomarkers of hepatic autoimmunity.

Example 2

Determining Biomarker Cut-Off Values

[0062] In order to propose the most sensitive threshold values possible, we analyzed the generated results in various ways (FIGS. 3 and 4). The principle was to carry out the analysis of the percentage of PD-1 and CD38 expression by modifying the number of associated markers, in particular with a view to simplifying subsequent use.

[0063] In the CD4 TL (FIG. 3) and CD8 TL (FIG. 4) populations, and in the total CD3 TL population (FIGS. 3 and 4), the percentage of PD-1 and CD38 expression (in the parent cell population according to a “gating” strategy for the analysis of flow cytometry results) was analyzed in the CD45RA−(6m); CD45RA-CD127−(7m); CD45RA-CD127-CXCR5−(8m) and CD45RA-CD127-CXCR5-CD27+(9m) subpopulations (FIGS. 3 and 4). The analysis was performed using ROC curves. In all conditions of analysis we obtain areas under the curve (AUC) greater than 0.85, demonstrating the strong potential of these markers as biomarkers of hepatic autoimmunity.

[0064] Threshold values for the autoimmune signature could thus be defined with sensitivities ranging from 77% to 100% and specificities ranging from 78% to 87%.

[0065] In a small group of AIH patients in complete remission under treatment (pilot study), we observed that about 50% of AIH patients in complete remission under treatment (n=19) maintained an elevated level of these biomarkers, whereas the level was normalized in the others (FIG. 5). This suggests a possible association between the persistence of these blood biomarkers and patient outcome (risk of relapse).

[0066] All these results demonstrate that it is possible to define an autoimmune lymphocyte signature in the blood of patients that is discriminative of non-specific inflammation.

Example 3

Searching for Combinations of Biomarkers of Interest

[0067] The study focuses on 1) the clinical interpretation of the cytometry data; 2) the validation of the data in a larger number of patients and in other autoimmune pathologies; and 3) the simplification and development of a test prototype on whole blood.

[0068] Concerning the simplification and development of a test prototype on whole blood, different associations of grouping of the previously mentioned markers are tested, in order to group the negative markers together to create “windows” of exclusions and thus facilitate the reading of the test.

[0069] For example, for the 9m panel, an initial selection of CD3+CD45RA-CXCR5-CD127-T cells is made, with CD45RA, CXCR5 and CD127 grouped in the same reading channel to facilitate their exclusion. It is thus possible to go from 9 reading channels in flow cytometry to 6 or 7 channels.

[0070] This makes it possible to find the best possible combinations to offer a simple and most sensitive test.

[0071] A sensitivity study is further performed on the analysis of the co-expression of PD-1 and CD38 at the surface of CD3 TL (CD3+) in association with the marker(s): (a) CD45RA (study of the CD3+CD45RA-PD-1+CD38+subpopulation); (b) CD45RA, CD4 and CD8 (study of the CD3+CD4+CD8-CD45RA-PD-1+CD38+and CD3+CD4-CD8+CD45RA-PD-1+CD38+ subpopulations); c) CD45RA, CD4, CD8 and CD127 (study of CD3+CD4+CD8-CD45RA-CD127-PD-1+CD38+ and CD3+CD4-CD8+CD45RA-CD127-PD-1+CD38+ subpopulations); d) CD45RA, CD4, CD8, CD127 and CXCR5 (study of CD3+CD4+CD8-CD45RA-CD127-CXCR5-PD-1+CD38+and CD3+CD4-CD8+CD45RA-CD127-CXCR5-PD-1+CD38+ subpopulations); and e) CD45RA, CD4, CD8, CD127, CXCR5 and CD27 (study of the CD3+CD4+CD8-CD45RA-CD127-CXCR5-CD27+PD-1+CD38+and CD3+CD4-CD8+CD45RA-CD127-CXCR5-CD27+PD-1+CD38+ subpopulations)

[0072] The purpose of this study is to identify the most sensitive association of marker associated with the co-expression of PD-1 and CD38 to measure autoimmune activity in patients with autoimmune hepatitis.

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