Sexual behavior is linked to changes in gut microbiome and systemic inflammation that lead to HIV-1 infection in men who have sex with men

Abstract

Pathogenic changes in gut microbial composition precede the onset of HIV-1 infection in men who have sex with men (MSM). This process is associated with increased levels of systemic inflammatory biomarkers and risk for AIDS development. Using mediation analysis framework, in this report we link the effects of unprotected receptive intercourse among MSM prior to primary HIV-1 infection to higher levels of proinflammatory cytokines sCD14 and sCD163 in plasma and a significant decrease in the abundance of A. muciniphila, B. caccae, B. fragilis, B. uniformis, Bacteroides spp., Butyricimonas spp., and Odoribacter spp., and a potential increase in the abundance of Dehalobacterium spp. and Methanobrevibacter spp. in stools of MSM with the highest number of sexual partners. These differences in microbiota, together with a reduction in the pairwise correlations among commensal and short-chain fatty acid-producing bacteria with a number of sexual partners, support an increase in gut dysbiosis with the number of sexual partners. These results demonstrate the interconnectedness of sexual behavior, immune response, and microbiota composition, notably among MSM participating in high-risk sexual behaviors.

Fig. 1. HIV-1 infection monotonically increases with the number of receptive anal intercourse partners.

The X-axis categorizes participants (N = 241) into exposure groups, ranging from Group 1 (G1) through Group 4 (G4). The Y-axis represents the percentage distribution of the participants with subsequent HIV-1 infection (Case, depicted in red) and negative controls (Ctrl, depicted in blue). Combined, these percentages total 100%. As participants move from G1 to G4, indicative of an increase in the number of partners, there is a marked rise in the percentage of HIV infection. This increase is statistically significant supported by the likelihood ratio test (LRT) statistics of 0.0021 and a p-value (one-sided) of less than 0.001, as determined by the constrained linear mixed effects (CLME) test, suggesting a monotonic increasing trend.

Fig. 2. Forest plot depicting the associations of demographic, clinical, and behavior features with exposures and the outcome.

This forest plot visualizes the associations of participants’ features (N = 241) with a sexual exposure groups, analyzed using ordinal logistic regression models, and b the HIV-1 infection status outcome, analyzed using logistic regression models. The X-axis denotes the odds ratio (OR), while the Y-axis lists the various demographic and clinical characteristics. Each feature’s effect size (OR) is symbolized by a diamond. An accompanying horizontal line represents the 95% confidence interval (CI), indicating the range in which the actual effect size is likely to reside. A vertical red line at the OR of 1.0 serves as a reference for no effect. For each feature, the exact OR, 95% CI, and the p-value (two-sided)—derived from logistic regression models—are presented in an adjacent table.

Fig. 3. Bar plots demonstrating monotonically increasing trends between exposure groups and cytokines levels.

Effect sizes of a CRP, b sCD14, and c sCD163 levels from participants’ plasma samples (N = 241) were shown here. The X-axis details the exposure groups of participants (N = 241), from G1 to G4. The Y-axis reflects the cytokine’s effect size determined by the CLME model. It is important to note that these are not raw concentrations but fitted values under a monotonic trend. Each bar’s error bars denote the 95% CI. Pairwise p-values (one-sided), used for contrasting the exposure groups, are displayed above the brackets that span the respective bars. The p-value for a monotonically increasing trend is provided within the plot.

Fig. 4. Heatmaps depict the ANCOM-BC2 pattern analysis.

Monotonic increasing and decreasing trends in microbial species abundances from participants’ stool samples (N = 241) were assessed in relation to a exposure groups (G1 is the reference) and b outcome of HIV-1 infection status. The X-axis delineates contrasts between exposure groups or outcomes, while the Y-axis lists species identified as significant via ANCOM-BC2 pattern analysis. Species that remained significant post-adjustment for multiple comparisons using the Benjamini–Yekutieli (BY) are highlighted in green. Fold-changes (natural log base) are superimposed within each cell. The color spectrum, from blue to red with a neutral white midpoint, visualizes the fold changes. Specifically, blue cells indicate reduced abundance relative to the reference group, and red cells signal increased abundance compared to the reference group. A white cell represents no effect, where the fold change equals 1. Species that are significantly associated with both sexual exposure groups, as well as HIV-1 infection status are highlighted in the red boxes.