Network-based multi-omics integration reveals metabolic at-risk profile within treated HIV-infection
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Network-based multi-omics integration reveals metabolic at-risk profile within treated HIV-infection. / Mikaeloff, Flora; Gelpi, Marco; Benfeitas, Rui; Knudsen, Andreas D.; Vestad, Beate; Høgh, Julie; Hov, Johannes R.; Benfield, Thomas; Murray, Daniel D.; Giske, Christian G.; Mardinoglu, Adil; Trøseid, Marius; Nielsen, Susanne D.; Neogi, Ujjwal.
In: eLife, Vol. 12, e82785, 2023.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Network-based multi-omics integration reveals metabolic at-risk profile within treated HIV-infection
AU - Mikaeloff, Flora
AU - Gelpi, Marco
AU - Benfeitas, Rui
AU - Knudsen, Andreas D.
AU - Vestad, Beate
AU - Høgh, Julie
AU - Hov, Johannes R.
AU - Benfield, Thomas
AU - Murray, Daniel D.
AU - Giske, Christian G.
AU - Mardinoglu, Adil
AU - Trøseid, Marius
AU - Nielsen, Susanne D.
AU - Neogi, Ujjwal
N1 - Publisher Copyright: © 2023, eLife Sciences Publications Ltd. All rights reserved.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
U2 - 10.7554/eLife.82785
DO - 10.7554/eLife.82785
M3 - Journal article
C2 - 36794912
AN - SCOPUS:85149294843
VL - 12
JO - eLife
JF - eLife
SN - 2050-084X
M1 - e82785
ER -
ID: 366032759