Background

HIV intervention activities directed toward both those most likely to transmit and their HIV-negative partners have the potential to substantially disrupt HIV transmission. Using HIV sequence data to construct molecular transmission clusters can reveal individuals whose viruses are connected. The utility of various cluster prioritization schemes measuring cluster growth have been demonstrated using surveillance data in New York City and across the United States, by the Centers for Disease Control and Prevention (CDC).

Methods

We examined clustering and cluster growth prioritization schemes using Illinois HIV sequence data that include cases from Chicago, a large urban center with high HIV prevalence, to compare their ability to predict future cluster growth.

Results

We found that past cluster growth was a far better predictor of future cluster growth than cluster membership alone but found no substantive difference between the schemes used by CDC and the relative cluster growth scheme previously used in New York City (NYC). Focusing on individuals selected simultaneously by both the CDC and the NYC schemes did not provide additional improvements.

Conclusion

Growth-based prioritization schemes can easily be automated in HIV surveillance tools and can be used by health departments to identify and respond to clusters where HIV transmission may be actively occurring.

Background

Alterations in the gut microbiome have been associated with HIV infection, but the relative impact of HIV versus other factors on the gut microbiome has been difficult to determine in cross-sectional studies.

Methods

To address this, we examined the gut microbiome, serum metabolome, and cytokines longitudinally within 27 individuals before and during acute HIV using samples collected from several ongoing cohort studies. Matched control participants (n=28) from the same cohort studies without HIV but at similar behavioral risk were used for comparison.

Findings

We identified few changes in the microbiome during acute HIV infection, but did find alterations in serum metabolites involving secondary bile acid (lithocholate sulfate, glycocholenate sulfate) and amino acid metabolism (3-methyl-2-oxovalerate, serine, cysteine, N-acetylputrescine). Greater microbiome differences, including decreased Bacteroides spp and increased Megasphaera elsdenii, were seen when comparing pre-HIV infection visits to matched at-risk controls. Those who acquired HIV also had elevated inflammatory cytokines (TNF-α, B cell activating factor, IL-8) and bioactive lipids (palmitoyl-sphingosine-phosphoethanolamide and glycerophosphoinositol) prior to HIV acquisition compared to matched controls.

Interpretation

Longitudinal sampling identified pre-existing microbiome differences in participants with acute HIV compared to matched control participants observed over the same period. These data highlight the importance of increasing understanding of the role of the microbiome in HIV susceptibility.

Funding

This work was supported by NIH/NIAID (K08AI124979; P30AI117943), NIH/NIDA (U01DA036267; U01DA036939; U01DA036926; U24DA044554), and NIH/NIMH (P30MH058107; R34MH105272).