AbstractBackgroundMetabolic syndrome (MetS) is one of the major factors for cardiometabolic comorbidities in people living with HIV (PLWH). The long-term consequences of HIV-infection and combination antiretroviral therapy (cART) in metabolic reprogramming are unknown. In this study, we aim to investigate metabolic alterations in long-term well-treated PLWH with MetS to identify the potential mechanism behind the MetS phenotype using advanced statistical and machine learning algorithms.MethodsWe included 200 PLWH ≥40 years old from the Copenhagen Comorbidity in HIV-infection (COCOMO) study. PLWH were grouped into PLWH with MetS (n=100) and without MetS (n=100). The clinical data were collected from the COCOMO database and untargeted plasma metabolomics was performed using ultra-high-performance liquid chromatography/mass spectrometry (UHPLC/MS/MS). Both clinical characteristics and plasma samples were collected at study baseline. We applied several conventional approaches, machine learning algorithm and linear classification model to identify the biologically relevant metabolites associated with MetS in PLWH.FindingsA total of 877 characterized biochemicals were identified. Of these, 9% (76/877) biochemicals differed significantly between PLWH with and without MetS (false discovery rate <0.05). The majority belonged to the amino acid metabolism (n=33, 43%). A consensus identification by combining supervised and unsupervised methods indicates 11 biomarkers of MetS phenotype in PLWH, of which seven (63%) have higher abundance in PLWH with MetS compared to the PLWH without MetS. A weighted co-expression network by Leiden partitioning analysis identified seven communities of positively intercorrelated metabolites, of which a single community contained six of the potential biomarkers mainly related to glutamate metabolism (glutamate, 4-hydroxyglutamate, α-ketoglutamate and γ-glutamylglutamate).InterpretationAltered amino acid metabolism is a central characteristic of PLWH with MetS and a potential central role for glutamate metabolism in establishing this phenotype is suggested.FundingRigshospitalet Research Council, Danish National Research Foundation (DNRF126) NovoNordisk Foundation, the Swedish Research Council (2017-01330 and 2018-06156)
Cell Surface Proteomic Map of HIV Infection Reveals Antagonism of Amino Acid Metabolism by Vpu and Nef
