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Updated: Jan 30, 2026

Amplifying and Quantifying HIV-1 RNA in HIV Infected Individuals with Viral Loads Below the Limit of Detection by Standard Clinical Assays
Published on: September 26, 2011
Effects of HIV viremia on the gastrointestinal microbiome of young MSM
Ryan R Cook1, Jennifer A Fulcher2,3, Nicole H Tobin4
1Department of Epidemiology, Fielding School of Public Health at the University of California.
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 (R = 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.
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