Effects of HIV viremia on the gastrointestinal microbiome of young MSM

Ryan R. Cook, Jennifer A. Fulcher, Nicole H. Tobin, Fan Li, David Lee, Marjan Javanbakht, Ron Brookmeyer, Steve Shoptaw, Robert Bolan, Grace M. Aldrovandi, Pamina M. Gorbach

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Objective:We employed a high-dimensional covariate adjustment method in microbiome analysis to better control for behavioural and clinical confounders, and in doing so examine the effects of HIV on the rectal microbiome.Design:Three hundred and eighty-three MSM were grouped into four HIV viremia categories: HIV negative (n = 200), HIV-positive undetectable (HIV RNA < 20 copies/ml; n = 66), HIV-positive suppressed (RNA 20-200 copies/ml; n = 72) and HIV-positive viremic (RNA > 200 copies/ml; n = 45).Methods:We performed 16S rRNA gene sequencing on rectal swab samples and used inverse probability of treatment-weighted marginal structural models to examine differences in microbial composition by HIV viremia category.Results:HIV viremia explained a significant amount of variability in microbial composition in both unadjusted and covariate-adjusted analyses (R2 = 0.011, P = 0.02). Alterations in bacterial taxa were more apparent with increasing viremia. Relative to the HIV-negative group, HIV-positive undetectable participants showed depletions in Brachyspira, Campylobacter and Parasutterella, while suppressed participants demonstrated depletions in Barnesiella, Brachyspira and Helicobacter. The microbial signature of viremic men was most distinct, showing enrichment in inflammatory genera Peptoniphilus, Porphyromonas and Prevotella and depletion of Bacteroides, Brachyspira and Faecalibacterium, among others.Conclusion:Our study shows that, after accounting for the influence of multiple confounding factors, HIV is associated with dysbiosis in the gastrointestinal microbiome in a dose-dependent manner. This analytic approach may allow for better identification of true microbial associations by limiting the effects of confounding, and thus improve comparability across future studies.

Original languageEnglish (US)
Pages (from-to)793-804
Number of pages12
JournalAIDS
Volume33
Issue number5
DOIs
StatePublished - Apr 1 2019
Externally publishedYes

Keywords

  • causal inference
  • dysbiosis
  • HIV
  • inverse probability of treatment weighting
  • microbiome
  • MSM
  • propensity scores

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology
  • Infectious Diseases

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