A pilot metabolomics study of tuberculosis immune reconstitution inflammatory syndrome. (July 2019)

• Record Type: Journal Article
• Authors: Silva, Carlos A.M.; Graham, Barbara; Webb, Kristofor; Ashton, Laura Vari; Harton, Marisa; Luetkemeyer, Annie F.; Bokatzian, Samantha; Almubarak, Reem; Mahapatra, Sebabrata; Hovind, Laura; Kendall, Michelle A.; Havlir, Diane; Belisle, John T.; De Groote, Mary Ann
• Is Part Of: International journal of infectious diseases. Volume 84(2019)
• Page Start: 30
• Page End: 38
• Publication Date: 2019-07
• Subjects: AIDS -- Tuberculosis -- IRIS -- Metabolomics -- Biosignature features; Communicable diseases -- Periodicals; Communicable Diseases -- Periodicals; Communicable diseases; Periodicals; Electronic journals; 616.9
• DOI: 10.1016/j.ijid.2019.04.015
• Languages: English
• ISSNs: 1201-9712

Abstract

Highlights: Plasma signatures of TB immune reconstitution inflammatory syndrome (TB-IRIS) can be identified. Arachidonic acid and glycerophospholipid metabolism pathways were perturbed in TBIRIS group. Metabolic profiling has the potential as a new tool for early diagnosis of TB-IRIS. Abstract: Background: Diagnosis of paradoxical tuberculosis-associated immune reconstitution inflammatory syndrome (TB-IRIS) is challenging and new tools are needed for early diagnosis as well as to understand the biochemical events that underlie the pathology in TB-IRIS. Methods: Plasma samples were obtained from participants from a randomized HIV/TB treatment strategy study (AIDS Clinical Trials Group [ACTG] A5221) with (n = 26) and without TB-IRIS (n = 22) for an untargeted metabolomics pilot study by liquid-chromatography mass spectrometry. The metabolic profile of these participants was compared at the study entry and as close to the diagnosis of TB-IRIS as possible (TB-IRIS window). Molecular features with p < 0.05 and log2 fold change ≥0.58 were submitted for pathway analysis through MetaboAnalyst. We also elucidated potential metabolic signatures for TB-IRIS using a LASSO regression model. Results: At the study entry, we showed that the arachidonic acid and glycerophospholipid metabolism were altered in the TB-IRIS group. Sphingolipid and linoleic acid metabolism were the most affected pathways during the TB-IRIS window. LASSO modeling selected a set of 8 and 7 molecular features with the potential to predict TB-IRIS at study entry and during the TB-IRIS window, respectively. Conclusion: This study suggests that the use of plasma metabolites may distinguish HIV-TB patients with and without TB-IRIS.