Sexual role and HIV-1 set point viral load among men who have sex with men

Epidemics. 2019 Mar:26:68-76. doi: 10.1016/j.epidem.2018.08.006. Epub 2018 Aug 30.

Abstract

Background: HIV-1 set point viral load (SPVL) is a highly variable trait that influences disease progression and transmission risk. Men who are exclusively insertive (EI) during anal intercourse require more sexual contacts to become infected than exclusively receptive (ER) men. Thus, we hypothesize that EIs are more likely to acquire their viruses from highly infectious partners (i.e., with high SPVLs) and to have higher SPVLs than infected ERs.

Methods: We used a one-generation Bernoulli model, a dynamic network model, and data from the Multicenter AIDS Cohort Study (MACS) to examine whether and under what circumstances MSM differ in SPVL by sexual role.

Results: Both models predicted higher SPVLs in EIs than role versatile (RV) or ER men, but only in scenarios where longer-term relationships predominated. ER and RV men displayed similar SPVLs. EI men remained far less likely than ER men to become infected, however. When the MACS data were limited by some estimates of lower sex partner counts (a proxy for longer relationships), EI men had higher SPVLs; these differences were clinically relevant (>0.3 log10 copies/mL) and statistically significant (p < 0.05).

Conclusions: Mode of acquisition may be an important aspect of SPVL evolution in MSM, with clinical implications.

Keywords: HIV-1; MACS study; Mathematical modeling; Men who have sex with men (MSM); Network modeling; Set point viral load; Sexual role.

Publication types

  • Multicenter Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Biomarkers / blood
  • Cohort Studies
  • HIV Infections / blood*
  • HIV Infections / epidemiology*
  • HIV Infections / transmission
  • HIV-1 / metabolism*
  • Homosexuality, Male / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • Sexual Behavior / statistics & numerical data*
  • Sexual Partners
  • Viral Load / statistics & numerical data*

Substances

  • Biomarkers