Longitudinal metabolomics and lipidomic uninfected and HIV treated human plasma signatures over ten years reveal stability of metabolome differences

Metabolomics has been applied for biomarker discovery and disease mechanism understanding. For clinical studies, especially for large cohort collection, it will take a long time. Therefore, the samples will be stored for different time durations. In this study, we investigated 10-HIV infected and 10 age and gender matching non-infected individuals. We applied widely targeted metabolomics screening (WTSMS) and widely targeted lipidomics screening (WTLS) assays comprising a “Chem2000” (~600 potential small molecules and ~1400 lipid species) to analyze yearly collected samples. In this way, we could investigate the potential degradation along 10-year storage, and the stability of metabolome variations in the healthy controls and HIV infected patients.

Plasma samples were extracted with methanol (metabolites) or ethanol (lipids), each spiked with internal standards. Metabolites were separated on an Ace C18-PFP column, while lipids were analyzed on a CSH-C18-PFP column using a Sciex 6500+ Q TRAP. Data was processed with Multiquanta and analyzed in SIMCA-p, and Genedata Expressionist.

There are 240 small metabolites, and 878 lipids were detected with CVs less than 30% in the QC samples from the WTSMS and WTLS assays. Distinct separations were detected constantly between HIV positive and HIV-negative patients at samples collected in different years. Among all these differentially expressed metabolites or lipids, 164 shared compounds were constantly detected, 34 of them were lower, and 130 were higher in HIV patients compared with non-HIV controls. The analyte changes showing stability over the years include down-regulated lysophospholipids, succinate, tryptophan, and up-regulated phospholipids, carnitines, and pantothenic acid.

This study revealed stable metabolites/lipids variations in plasma samples collected from HIV-positive and HIV-negative subjects over 10 year time period, which can be useful in monitoring overall metabolic health.