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Research Paper|Volume 13, Issue 19|pp 22732—22751

The central role of the glutamate metabolism in long-term antiretroviral treated HIV-infected individuals with metabolic syndrome

Marco Gelpi1, Flora Mikaeloff2, Andreas D. Knudsen1, Rui Benfeitas3, Shuba Krishnan2, Sara Svenssson Akusjärvi2, Julie Høgh1, Daniel D. Murray4, Henrik Ullum5, Ujjwal Neogi2,6, Susanne D. Nielsen1
  • 1Department of Infectious Diseases, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
  • 2The Systems Virology Laboratory, Division of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institute, ANA Futura, Campus Flemingsberg, Stockholm, Sweden
  • 3National Bioinformatics Infrastructure Sweden (NBIS), Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm S-10691, Sweden
  • 4Centre for Health and Infectious Diseases Research (CHIP), Rigshospitalet, Copenhagen DK-2100, Denmark
  • 5Department of Clinical Immunology, Copenhagen University Hospital, Copenhagen, Denmark
  • 6Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA
* Equal contribution
Received: August 20, 2021Accepted: September 28, 2021Published: October 11, 2021
https://doi.org/10.18632/aging.203622

Copyright: © 2021 Gelpi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

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.