A population response analysis approach to assign class II HLA-epitope restrictions.

Identification of the specific HLA locus and allele presenting an epitope for recognition by specific TCRs (HLA restriction) is necessary to fully characterize the immune response to Ags. Experimental determination of HLA restriction is complex and technically challenging. As an alternative, the restricting HLA locus and allele can be inferred by genetic association, using response data in an HLA-typed population. However, simple odds ratio (OR) calculations can be problematic when dealing with large numbers of subjects and Ags, and because the same epitope can be presented by multiple alleles (epitope promiscuity). In this study, we develop a tool, denominated Restrictor Analysis Tool for Epitopes, to extract inferred restriction from HLA class II-typed epitope responses. This automated method infers HLA class II restriction from large datasets of T cell responses in HLA class II-typed subjects by calculating ORs and relative frequencies from simple data tables. The program is validated by: 1) analyzing data of previously determined HLA restrictions; 2) experimentally determining in selected individuals new HLA restrictions using HLA-transfected cell lines; and 3) predicting HLA restriction of particular peptides and showing that corresponding HLA class II tetramers efficiently bind to epitope-specific T cells. We further design a specific iterative algorithm to account for promiscuous recognition by calculation of OR values for combinations of different HLA molecules while incorporating predicted HLA binding affinity. The Restrictor Analysis Tool for Epitopes program streamlines the prediction of HLA class II restriction across multiple T cell epitopes and HLA types.

Utility of a three-gene transcriptomic signature in the diagnosis of tuberculosis in a low-endemic hospital setting.

BACKGROUND: Host transcriptomic blood signatures have demonstrated diagnostic potential for tuberculosis (TB), requiring further validation across different geographical settings. Discriminating TB from other diseases with similar clinical manifestations is crucial for the development of an accurate immunodiagnostic tool. In this exploratory cohort study, we evaluated the performance of potential blood-based transcriptomic signatures in distinguishing TB disease from non-TB lower respiratory tract infections in hospitalised patients in a TB low-endemic country. METHOD: Quantitative real-time polymerase chain reaction qPCR) was used to evaluate 26 previously published genes in blood from 31 patients (14 TB and 17 lower respiratory tract infection cases) admitted to Oslo University Hospital in Norway. The diagnostic accuracies of differentially expressed genes were determined by receiver operating characteristic curves. RESULTS: A significant difference (p < .01) in the age distribution was observed between patients with TB (mean age, 40 ± 15 years) and lower respiratory tract infection (mean age 59 ± 12 years). Following adjustment for age, ETV7, GBP1, GBP5, P2RY14 and BLK were significantly differentially expressed between patients with TB and those with LRI. A general discriminant analysis generated a three-gene signature (BAFT2, ETV7 and CD1C), which diagnosed TB with an area under the receiver operating characteristic curve (AUC) of 0.86 (95% CI, 0.69 - 1.00), sensitivity of 69.23% (95% CI, 38.57%-90.91%) and specificity of 94.12% (95% CI, 71.31%-99.85%). CONCLUSION: The three-genes signature may have potential to improve diagnosis of TB in a hospitalised low-burden setting. However, the influence of confounding variables or covariates such as age requires further evaluation in larger studies.

Diagnostic accuracy of plasma kynurenine/tryptophan ratio, measured by enzyme-linked immunosorbent assay, for pulmonary tuberculosis.

INTRODUCTION: The World Health Organization has identified the need for a non-sputum-based test capable of detecting active tuberculosis (TB) as a priority. The plasma kynurenine-to-tryptophan (K/T) ratio, largely mediated by activity of the enzyme indoleamine 2,3-dioxygenase, may have potential as a suitable biomarker for active TB. METHOD: We evaluated a commercial enzyme-linked immunosorbent assay (ELISA) in comparison to mass spectrometry for measuring the K/T ratio. We also used ELISA to determine the K/T ratio in plasma from patients with active TB compared to latently infected controls, with and without HIV. RESULTS: The two methods showed good agreement, with a mean bias of 0.01 (limit of agreement from -0.06 to 0.10). Using ELISA, it was found that HIV-infected patients with active TB disease had higher K/T ratios than those without TB (median, 0.101 [interquartile range (IQR), 0.091-0.140] versus 0.061 [IQR, 0.034-0.077], P<0.0001). At a cutoff of 0.080, the K/T ratio produced a sensitivity of 90%, a specificity of 80%, a positive predictive value (PPV) of 82%, and a negative predictive value (NPV) of 90%. In a receiver operating characteristics analysis, the K/T ratio had an area under the curve of 0.93. HIV-uninfected patients with active TB also had higher K/T ratios than those with latent TB infections (median, 0.064 [IQR, 0.040-0.088] versus 0.022 [IQR, 0.016-0.027], P<0.0001). A cutoff of 0.040 gave a sensitivity of 85%, a specificity of 92%, a PPV of 91%, and an NPV of 84%. CONCLUSION: The plasma K/T ratio is a sensitive biomarker for active TB. The K/T ratio can be measured from blood using ELISA. The K/T ratio should be evaluated as an initial test for TB.