HIV Dynamics in Seminal Plasma during Primary HIV Infection

HIV dynamics in seminal plasma during primary HIV infection was evaluated through an observational study of individuals with primary HIV infection at the University of Washington Primary Infection Clinic. Seminal plasma HIV RNA was quantified using a real-time reverse transcription PCR assay. Blood...

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Veröffentlicht in:AIDS research and human retroviruses 2008-10, Vol.24 (10), p.1269-1274
Hauptverfasser: STEKLER, Joanne, SYCKS, Brian J, HOLTE, Sarah, MAENZA, Janine, STEVENS, Claire E, DRAGAVON, Joan, COLLIER, Ann C, COOMBS, Robert W
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Sprache:eng
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Zusammenfassung:HIV dynamics in seminal plasma during primary HIV infection was evaluated through an observational study of individuals with primary HIV infection at the University of Washington Primary Infection Clinic. Seminal plasma HIV RNA was quantified using a real-time reverse transcription PCR assay. Blood plasma RNA was quantified by bDNA or PCR-based assays. Longitudinal analyses of HIV RNA levels over time used random effects regression analysis. From 1993 to 2005, 110 men collected 327 semen specimens. Initial blood and seminal plasma RNA levels in untreated men were only moderately correlated (Spearman r = 0.38, p = 0.0002). Estimated peak and set point levels were lower in semen than blood by 0.8 (p = 0.001) and 0.7 (p < 0.001) log(10) copies/ml, respectively. RNA decay rates were similar in the two compartments (p = 0.4). For 2 months after infection, mean HIV RNA levels in seminal plasma remained above a threshold level (3.8 log(10) copies/ml) that has been associated with recovery of infectious virus in vitro. HIV-positive men are likely to be most infectious in the first months following HIV acquisition. However, the modest relationship between HIV RNA levels in blood and seminal plasma suggests that the relative risk of HIV transmission during primary infection may vary from current estimates that are solely based on blood levels. Incorporating seminal plasma HIV levels into future mathematical models may increase the accuracy of these models.
ISSN:0889-2229
1931-8405
DOI:10.1089/aid.2008.0014