@article{01025f1c81a94633a1994cb418f11839,
title = "Sexual role and HIV-1 set point viral load among men who have sex with men",
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 log 10 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",
author = "Stansfield, {Sarah E.} and Mittler, {John E.} and Gottlieb, {Geoffrey S.} and Murphy, {James T.} and Hamilton, {Deven T.} and Roger Detels and Wolinsky, {Steven M.} and Jacobson, {Lisa P.} and Margolick, {Joseph B.} and Rinaldo, {Charles R.} and Herbeck, {Joshua T.} and Goodreau, {Steven M.}",
note = "Funding Information: This work was supported by the National Institutes of Health [R01-AI108490, R21-HD075662, and R01-HD068395]. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Partial support for this research came from a Eunice Kennedy Shriver National Institute of Child Health and Human Development research infrastructure grant, R24 HD042828, to the Center for Studies in Demography & Ecology at the University of Washington. Data in this article were collected by the MACS with centers (Principal Investigators) at Johns Hopkins Bloomberg School of Public Health (Joseph B. Margolick, Lisa P. Jacobson), Northwestern University (Steven Wolinsky), University of California, Los Angeles (Roger Detels), and University of Pittsburgh (Charles Rinaldo). The MACS is funded primarily by the National Institute of Allergy and Infectious Diseases (NIAID), with additional supplemental funding from the National Cancer Institute (NCI), the National Institute on Drug Abuse (NIDA), and the National Institute of Mental Health (NIMH) (UO1-AI-35042, UL1-RR025005, UM1-AI-35043, UO1-AI-35039, UO1-AI-35040, and UO1-AI-35041). The funding for this substudy was supported by the National Institute of Allergy and Infectious Diseases (R21-AI-109817). This work was facilitated though the use of advanced computational, storage, and networking infrastructure provided by the Hyak supercomputer system and funded by the STF at the University of Washington. The funding sources had no involvement in the study design, data interpretation, manuscript preparation, or submission decisions. We thank the researchers, staff and participants of the Multicenter AIDS Cohort Study, the members of the Evonet project (Neil Abernethy, Juandalyn Burke, Kathryn Peebles, Molly Reid), the EpiModel and statnet teams, especially Martina Morris and Sam Jenness, the members of the Network Modeling Group at the University of Washington, and Eli Rosenberg. We also thank Chris Wymant for an exceptionally detailed and helpful review, and an additional anonymous reviewer. Funding Information: This work was supported by the National Institutes of Health [ R01-AI108490 , R21-HD075662 , and R01-HD068395 ]. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Partial support for this research came from a Eunice Kennedy Shriver National Institute of Child Health and Human Development research infrastructure grant, R24 HD042828 , to the Center for Studies in Demography & Ecology at the University of Washington. Data in this article were collected by the MACS with centers (Principal Investigators) at Johns Hopkins Bloomberg School of Public Health (Joseph B. Margolick, Lisa P. Jacobson), Northwestern University (Steven Wolinsky), University of California, Los Angeles (Roger Detels), and University of Pittsburgh (Charles Rinaldo). The MACS is funded primarily by the National Institute of Allergy and Infectious Diseases (NIAID) , with additional supplemental funding from the National Cancer Institute (NCI) , the National Institute on Drug Abuse (NIDA) , and the National Institute of Mental Health (NIMH) (UO1-AI-35042, UL1-RR025005, UM1-AI-35043, UO1-AI-35039, UO1-AI-35040, and UO1-AI-35041). The funding for this substudy was supported by the National Institute of Allergy and Infectious Diseases ( R21-AI-109817 ). This work was facilitated though the use of advanced computational, storage, and networking infrastructure provided by the Hyak supercomputer system and funded by the STF at the University of Washington . The funding sources had no involvement in the study design, data interpretation, manuscript preparation, or submission decisions. Publisher Copyright: {\textcopyright} 2018 The Authors",
year = "2019",
month = mar,
doi = "10.1016/j.epidem.2018.08.006",
language = "English (US)",
volume = "26",
pages = "68--76",
journal = "Epidemics",
issn = "1755-4365",
publisher = "Elsevier",
}