期刊
FRONTIERS IN IMMUNOLOGY
卷 12, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fimmu.2021.742736
关键词
HIV-1; metabolic syndrome; antiretroviral treatment; machine learning; lipidomics
类别
资金
- Rigshospitalet Research Council
- Danish National Research Foundation [DNRF126]
- NovoNordisk Foundation
- Swedish Research Council [2017-01330, 2018-06156, 2021-01756]
- Swedish Research Council [2021-01756, 2018-06156] Funding Source: Swedish Research Council
This study investigated the lipidomics characteristics and their association with metabolic syndrome (MetS) in people living with HIV (PLWH). The results showed differential abundance of certain lipids between PLWH with and without MetS, and revealed interactions between specific glycerolipid patterns and key metabolites involved in glutamate metabolism. The integration of clinical data further identified the association between visceral adipose tissue and exposure to earlier generations of antiretroviral therapy. These findings suggest that disruptions in glutamate and fatty acid metabolism may contribute to the development of MetS in PLWH.
People living with HIV (PLWH) require life-long anti-retroviral treatment and often present with comorbidities such as metabolic syndrome (MetS). Systematic lipidomic characterization and its association with the metabolism are currently missing. We included 100 PLWH with MetS and 100 without MetS from the Copenhagen Comorbidity in HIV Infection (COCOMO) cohort to examine whether and how lipidome profiles are associated with MetS in PLWH. We combined several standard biostatistical, machine learning, and network analysis techniques to investigate the lipidome systematically and comprehensively and its association with clinical parameters. Additionally, we generated weighted lipid-metabolite networks to understand the relationship between lipidomic profiles with those metabolites associated with MetS in PLWH. The lipidomic dataset consisted of 917 lipid species including 602 glycerolipids, 228 glycerophospholipids, 61 sphingolipids, and 26 steroids. With a consensus approach using four different statistical and machine learning methods, we observed 13 differentially abundant lipids between PLWH without MetS and PLWH with MetS, which mainly belongs to diacylglyceride (DAG, n = 2) and triacylglyceride (TAG, n = 11). The comprehensive network integration of the lipidomics and metabolomics data suggested interactions between specific glycerolipids' structural composition patterns and key metabolites involved in glutamate metabolism. Further integration of the clinical data with metabolomics and lipidomics resulted in the association of visceral adipose tissue (VAT) and exposure to earlier generations of antiretroviral therapy (ART). Our integrative omics data indicated disruption of glutamate and fatty acid metabolism, suggesting their involvement in the pathogenesis of PLWH with MetS. Alterations in the lipid homeostasis and glutaminolysis need clinical interventions to prevent accelerated aging in PLWH with MetS.
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