Genome-wide expression for diagnosis of pulmonary tuberculosis: a multicohort analysis

Abstract

Summary Background Active pulmonary tuberculosis is difficult to diagnose and treatment response is difficult to effectively monitor. A WHO consensus statement has called for new non-sputum diagnostics. The aim of this study was to use an integrated multicohort analysis of samples from publically available datasets to derive a diagnostic gene set in the peripheral blood of patients with active tuberculosis. Methods We searched two public gene expression microarray repositories and retained datasets that examined clinical cohorts of active pulmonary tuberculosis infection in whole blood. We compared gene expression in patients with either latent tuberculosis or other diseases versus patients with active tuberculosis using our validated multicohort analysis framework. Three datasets were used as discovery datasets and meta-analytical methods were used to assess gene effects in these cohorts. We then validated the diagnostic capacity of the three gene set in the remaining 11 datasets. Findings A total of 14 datasets containing 2572 samples from 10 countries from both adult and paediatric patients were included in the analysis. Of these, three datasets (N=1023) were used to discover a set of three genes (GBP5, DUSP3, and KLF2) that are highly diagnostic for active tuberculosis. We validated the diagnostic power of the three gene set to separate active tuberculosis from healthy controls (global area under the ROC curve (AUC) 0·90 [95% CI 0·85–0·95]), latent tuberculosis (0·88 [0·84–0·92]), and other diseases (0·84 [0·80–0·95]) in eight independent datasets composed of both children and adults from ten countries. Expression of the three-gene set was not confounded by HIV infection status, bacterial drug resistance, or BCG vaccination. Furthermore, in four additional cohorts, we showed that the tuberculosis score declined during treatment of patients with active tuberculosis. Interpretation Overall, our integrated multicohort analysis yielded a three-gene set in whole blood that is robustly diagnostic for active tuberculosis, that was validated in multiple independent cohorts, and that has potential clinical application for diagnosis and monitoring treatment response. Prospective laboratory validation will be required before it can be used in a clinical setting. Funding National Institute of Allergy and Infectious Diseases, National Library of Medicine, the Stanford Child Health Research Institute, the Society for University Surgeons, and the Bill and Melinda Gates Foundation.

Integrated, multicohort analysis of systemic sclerosis identifies robust transcriptional signature of disease severity

“…PCs are difficult to implement into clinical practice owing to variance introduced by different treatment and technology protocols in individual PCs. Therefore, similar to our previous results (14,17,19,20), we defined SSc skin severity score (4S) for a skin biopsy as the difference between the mean of overexpressed genes and mean of underexpressed genes in the 415-gene set. 4S distinguished SSc skin samples from healthy skin biopsies with very high accuracy in both discovery and validation cohorts (range = 0.88-1 in validation cohorts; Supplemental Figure 5, A and B).…”

“…We have repeatedly demonstrated the utility of this approach in identifying novel drug targets, diagnostic and prognostic biomarkers, and repurposing FDA-approved drugs in a broad spectrum of diseases including organ transplant, cancer, sepsis, and bacterial and viral infections (14)(15)(16)(17)(18)(19)(20)(21). Here, we applied our multicohort analytical method to 2 SSc gene expression datasets, obtained from 158 skin biopsies from SSc patients, referred to as the UCSF1 cohort (GSE9285) (11) and the Boston cohort (GSE32413) (10) to identify a 415-gene signature.…”

Inflammatory macrophage–associated 3-gene signature predicts subclinical allograft injury and graft survival

“…We performed immune cell-type enrichment as described previously (45,46). Briefly, we searched GEO for gene expression profiles of clinical samples of relevant immune cell types.…”

Quantification of circulating Mycobacterium tuberculosis antigen peptides allows rapid diagnosis of active disease and treatment monitoring

“…Non-sputum-based IFN-γ release assays (IGRAs), which measure ex vivo immune responses to Mtb antigens, have received negative policy recommendations for active TB diagnosis owing to their inability to distinguish active TB and latent TB infection (LTBI), as well as their poor diagnostic performance in HIV/TB-coinfected patients and EPTB patients (14). One recent report used the expression of a set of host innate immune response genes in blood to diagnose pulmonary TB (PTB) cases, but that retrospective study did not examine blood samples of EPTB patients, and could not identify culture-negative TB cases (15). Detection of Mtb antigens in patient blood samples can provide direct evidence of TB, but no currently available method has demonstrated adequate diagnostic sensitivity and specificity,…”