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Integrative Lipidomics and Metabolomics for System-Level Understanding of the Metabolic Syndrome in Long-Term Treated HIV-Infected Individuals.

ABSTRACT: 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.

SUBMITTER: Olund Villumsen S

PROVIDER: S-EPMC8791652 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Metabolic syndrome (MetS) is a significant factor for cardiometabolic comorbidities in people living with HIV (PLWH) and a barrier to healthy aging. The long-term consequences of HIV-infection and combination antiretroviral therapy (cART) in metabolic reprogramming are unknown. In this study, we investigated metabolic alterations in well-treated PLWH with MetS to identify potential mechanisms behind the MetS phenotype using advanced statistical and machine learning algorithms. We included 200 PLWH from the Copenhagen Comorbidity in HIV-infection (COCOMO) study. PLWH were grouped into PLWH with MetS (n = 100) defined according to the International Diabetes Federation (IDF) consensus worldwide definition of the MetS or without MetS (n = 100). The untargeted plasma metabolomics was performed using ultra-high-performance liquid chromatography/mass spectrometry (UHPLC/MS/MS) and immune-phenotyping of Glut1 (glucose transporter), xCT (glutamate/cysteine transporter) and MCT1 (pyruvate/lactate transporter) by flow cytometry. We applied several conventional approaches, machine learning algorithms, and linear classification models to identify the biologically relevant metabolites associated with MetS in PLWH. Of the 877 identified biochemicals, 9% (76/877) differed significantly between PLWH with and without MetS (false discovery rate < 0.05). The majority belonged to amino acid metabolism (43%). A consensus identification by combining supervised and unsupervised methods indicated 11 biomarkers of MetS phenotype in PLWH. A weighted co-expression network identified seven communities of positively intercorrelated metabolites. A single community contained six of the potential biomarkers mainly related to glutamate metabolism. Transporter expression identified altered xCT and MCT in both lymphocytic and monocytic cells. Combining metabolomics and immune-phenotyping indicated altered glutamate metabolism associated with MetS in PLWH, which has clinical significance.

Dataset Information

Integrative Lipidomics and Metabolomics for System-Level Understanding of the Metabolic Syndrome in Long-Term Treated HIV-Infected Individuals.

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