Host lipidome and tuberculosis treatment failure
| Autor: | Murugesh Selva, Artur T. L. Queiroz, Shashikala Sangle, Akshay Gupte, Rupak Shivakoti, Shri Vijay Bala Yogendra Shivakumar, Vandana Kulkarni, Sanjay Gaikwad, Kannan Thiruvengadam, Ramesh Karunaianantham, Anju Kagal, Amita Gupta, Jonathan E. Golub, Chandrasekaran Padmapriyadarsini, Nikhil Gupte, Pattabiraman Satyamurthi, John W. Newman, Bruno B. Andrade, Renu Bharadwaj, Vidya Mave, Mandar Paradkar, Kamil Borkowski, Neeta Pradhan, Luke Elizabeth Hanna, Oliver Fiehn, Saravanan Natarajan |
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| Rok vydání: | 2022 |
| Předmět: |
Pulmonary and Respiratory Medicine
Adult medicine.medical_specialty Tuberculosis Treatment outcome Respiratory System Gastroenterology Medical and Health Sciences Treatment failure Article Pathogenesis Rare Diseases Clinical Research Internal medicine Lipidomics medicine Humans 2.1 Biological and endogenous factors Treatment Failure Prospective Studies Aetiology Prospective cohort study business.industry Area under the curve Lipidome medicine.disease Infectious Diseases Emerging Infectious Diseases Good Health and Well Being Case-Control Studies business Infection Biomarkers |
| Zdroj: | The European respiratory journal, vol 59, iss 1 Eur Respir J |
| Popis: | IntroductionHost 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.MethodsA 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.ResultsBaseline 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.ConclusionsWe 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. |
| Databáze: | OpenAIRE |
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