Network-based multi-omics integration reveals metabolic at-risk profile within treated HIV-infection
- Karolinska Institute, Sweden
- Rigshospitalet, Denmark
- Oslo University Hospital, Norway
- Copenhagen University Hospital, Denmark
- King's College London, United Kingdom
Abstract
Multiomics technologies improve the biological understanding of health status in people living with HIV on antiretroviral therapy (PLWH). Still, a systematic and in-depth characterization of metabolic risk profile during successful long-term treatment is lacking. Here, we used multi-omics (plasma lipidomic, metabolomic, and fecal 16S microbiome) data-driven stratification and characterization to identify the metabolic at-risk profile within PLWH. Through network analysis and similarity network fusion (SNF), we identified three groups of PLWH (SNF-1 to 3): healthy (HC)-like (SNF-1), mild at-risk (SNF-3), and severe at-risk (SNF-2). The PLWH in the SNF-2 (45%) had a severe at-risk metabolic profile with increased visceral adipose tissue, BMI, higher incidence of metabolic syndrome (MetS), and increased di- and triglycerides despite having higher CD4+ T-cell counts than the other two clusters. However, the HC-like and the severe at-risk group had a similar metabolic profile differing from HIV-negative controls (HNC), with dysregulation of amino acid metabolism. At the microbiome profile, the HC-like group had a lower α-diversity, a lower proportion of men having sex with men (MSM) and was enriched in Bacteroides. In contrast, in at-risk groups, there was an increase in Prevotella, with a high proportion of MSM, which could potentially lead to higher systemic inflammation and increased cardiometabolic risk profile. The multi-omics integrative analysis also revealed a complex microbial interplay of the microbiome-derived metabolites in PLWH. Those severely at-risk clusters may benefit from personalized medicine and lifestyle intervention to improve their dysregulated metabolic traits, aiming to achieve healthier aging.
Data availability
All of the data generated or analyzed during this study are included in this published article and/or the supplementary materials. Created datasets and code are publicly available. The metabolomics and lipidomics data are available from https://doi.org/10.6084/m9.figshare.14356754.v1 and https://doi.org/10.6084/m9.figshare.14509452.v1. All the codes are available at github: https://github.com/neogilab/HIV_multiomics
Article and author information
Author details
Funding
Vetenskapsrådet (2017-01330,2018-06156,2021-01756)
- Ujjwal Neogi
Novo Nordisk
- Susanne D Nielsen
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Ethical approval was obtained by the Regional Ethics Committee of Copenhagen (COCOMO: H-15017350) and Etikprövningsmyndigheten, Sweden (Dnr: 2022-01353-01). Informed consent was obtained from all participants and delinked before analysis.
Copyright
© 2023, Mikaeloff et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,698
- views
-
- 255
- downloads
-
- 13
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Network-based multi-omics integration reveals metabolic at-risk profile within treated HIV-infection
eLife 12:e82785.
https://doi.org/10.7554/eLife.82785
