Host lipidome and tuberculosis treatment failure

INTRODUCTION: Host lipids play important roles in tuberculosis (TB) pathogenesis. Whether host lipids at TB treatment initiation (baseline) affect subsequent treatment outcomes has not been well characterised. We used unbiased lipidomics to study the prospective association of host lipids with TB treatment failure. METHODS: A case–control study (n=192), nested within a prospective cohort study, was used to investigate the association of baseline plasma lipids with TB treatment failure among adults with pulmonary TB. Cases (n=46) were defined as TB treatment failure, while controls (n=146) were those without failure. Complex lipids and inflammatory lipid mediators were measured using liquid chromatography mass spectrometry techniques. Adjusted least-square regression was used to assess differences in groups. In addition, machine learning identified lipids with highest area under the curve (AUC) to classify cases and controls. RESULTS: Baseline levels of 32 lipids differed between controls and those with treatment failure after false discovery rate adjustment. Treatment failure was associated with lower baseline levels of cholesteryl esters and oxylipin, and higher baseline levels of ceramides and triglycerides compared to controls. Two cholesteryl ester lipids combined in a unique classifier model provided an AUC of 0.79 (95% CI 0.65–0.93) in the test dataset for prediction of TB treatment failure. CONCLUSIONS: We identified lipids, some with known roles in TB pathogenesis, associated with TB treatment failure. In addition, a lipid signature with prognostic accuracy for TB treatment failure was identified. These lipids could be potential targets for risk-stratification, adjunct therapy and treatment monitoring

An integrative multi-omics approach to characterize interactions between tuberculosis and diabetes mellitus

Summary: Tuberculosis-diabetes mellitus (TB-DM) is linked to a distinct inflammatory profile, which can be assessed using multi-omics analyses. Here, a machine learning algorithm was applied to multi-platform data, including cytokines and gene expression in peripheral blood and eicosanoids in urine, in a Brazilian multi-center TB cohort. There were four clinical groups: TB-DM(n = 24), TB only(n = 28), DM(HbA1c ≥ 6.5%) only(n = 11), and a control group of close TB contacts who did not have TB or DM(n = 13). After cross-validation, baseline expression or abundance of MMP-28, LTE-4, 11-dTxB2, PGDM, FBXO6, SECTM1, and LINCO2009 differentiated the four patient groups. A distinct multi-omic-derived, dimensionally reduced, signature was associated with TB, regardless of glycemic status. SECTM1 and FBXO6 mRNA levels were positively correlated with sputum acid-fast bacilli grade in TB-DM. Values of the biomarkers decreased during the course of anti-TB therapy. Our study identified several markers associated with the pathophysiology of TB-DM that could be evaluated in future mechanistic investigations

Eosinophils are an integral component of the pulmonary granulocyte response in Tuberculosis and promote host resistance in mice

Host resistance to Mycobacterium tuberculosis (Mtb) infection requires the activities of multiple leukocyte subsets, yet the roles of the different innate effector cells during tuberculosis are incompletely understood. Here we uncover an unexpected association between eosinophils and Mtb infection. In humans, eosinophils are decreased in the blood but enriched in resected human tuberculosis lung lesions and autopsy granulomas. An influx of eosinophils is also evident in infected zebrafish, mice, and nonhuman primate granulomas, where they are functionally activated and degranulate. Importantly, using complementary genetic models of eosinophil deficiency, we demonstrate that in mice, eosinophils are required for optimal pulmonary bacterial control and host survival after Mtb infection. Collectively, our findings uncover an unexpected recruitment of eosinophils to the infected lung tissue and a protective role for these cells in the control of Mtb infection in mice