Vaginal Prostate Specific Antigen (PSA) Is a Useful Biomarker of Semen Exposure Among HIV-Infected Ugandan Women

The use of PSA as a biomarker of recent semen exposure in female reproductive health studies

Semen contains potent soluble proteins, bacteria, viruses, activated immune cells as well as anti- and pro-inflammatory cytokines that may influence the inflammatory response and alter microbial composition of the female genital tract. The presence of semen in the female genital mucosa may be a significant confounder that most studies have failed to control for in their analysis. Prostate-specific antigen (PSA), a protein secreted by the prostate into the urethra during ejaculation, is a well-established biomarker of semen exposure. Several studies have demonstrated discordance between self-reports of sexual behavior and the presence of PSA. Recent semen exposure has been shown to promote pro-inflammatory responses, stimulate the recruitment of activated immune cells and decrease Lactobacilli abundance in the female genital mucosa. As a result, it is important to understand the concordance between self-reported consistent condom use and the presence of semen biomarkers. Furthermore, to ensure that the interpretation of data in clinical studies of the immunological and microbial environment in the female genital mucosa are accurate, it is essential to establish whether semen is present in the vaginal fluid. This review explores the impact of semen exposure on the mucosal microenvironment and assesses the use of the PSA as an objective biomarker of semen exposure to reduce reliance on self-reported sexual intercourse.

PrEP Use Among Female Sex Workers: No Evidence for Risk Compensation

Supplemental Digital Content is Available in the Text.

Little is known about risk compensation among female sex workers (FSW) on HIV pre-exposure prophylaxis (PrEP), and self-report of sexual behaviors is subject to bias.

A novel nested polymerase chain reaction targeting the testis-specific protein Y-encoded family of genes for high sensitivity of recent semen exposure detection: Comparison with four other assays of semen detection

OBJECTIVES

Because self-report of sexual behaviours is prone to biases, biomarkers of recent semen exposure are increasingly used to assess unprotected sex. We aimed to present a novel nested polymerase chain reaction (PCR) assay targeting testis-specific protein Y-encoded (TSPY) genes and to compare its performance in detecting recent semen exposure with that of four other assays.

METHODS

Forty-five vaginal samples were selected at baseline of a prospective observational demonstration study of early antiretroviral treatment and pre-exposure prophylaxis among female sex workers in Benin. Semen exposure was assessed with: a rapid prostate-specific antigen (PSA) detection assay, a quantitative PCR targeting the sex-determining region (SRY) gene, a standard PCR targeting SRY, a standard PCR targeting TSPY, and a nested PCR targeting TSPY (n-TSPY). Because we had hypothesized that n-TSPY would be the most sensitive of the five assays while remaining specific, and as our results suggested that it was the case, sensitivity and specificity were calculated for each assay in comparison with n-TSPY.

RESULTS

The n-TSPY could detect male DNA at concentration 16 and 64 times lower compared to s-TSPY and s-SRY, respectively. Among the 45 vaginal samples, prevalences of semen exposure according to the different assays varied from 22.2% (95%CI: 11.2%-37.1%) to 70.5% (95%CI: 54.8%-83.2%), with the highest prevalence measured with n-TSPY. The n-TSPY products were of expected size and we observed no false-positive in female DNA controls. The assay that offered the second best performance in detecting semen exposure was the PSA rapid test, with a sensitivity of 61.3% and a specificity of 100% compared to n-TSPY.

CONCLUSIONS

Compared to n-TSPY, all other PCR assays had poor performance to detect semen exposure. The n-TSPY is an accessible assay that may have great utility in assessing semen exposure in studies where many factors are expected to accelerate biomarkers' clearance.

Biological Validation of Self-Reported Unprotected Sex and Comparison of Underreporting Over Two Different Recall Periods Among Female Sex Workers in Benin

Background

Self-reported unprotected sex validity is questionable and is thought to decline with longer recall periods. We used biomarkers of semen to validate self-reported unprotected sex and to compare underreporting of unprotected sex between 2 recall periods among female sex workers (FSW).

Methods

At baseline of an early antiretroviral therapy and pre-exposure prophylaxis demonstration study conducted among FSW in Cotonou, Benin, unprotected sex was assessed with retrospective questionnaires, and with vaginal detection of prostate-specific antigen (PSA) and Y-chromosomal deoxyribonucleic acid (Yc-DNA). Underreporting in the last 2 or 14 days was defined as having reported no unprotected sex in the recall period while testing positive for PSA or Yc-DNA, respectively. Log-binomial regression was used to compare underreporting over the 2 recall periods.

Results

Unprotected sex prevalence among 334 participants was 25.8% (50.3%) according to self-report in the last 2 (or 14) days, 32.0% according to PSA, and 44.3% according to Yc-DNA. The proportion of participants underreporting unprotected sex was similar when considering the last 2 (18.9%) or 14 days (21.0%; proportion ratio = 0.90; 95% confidence interval, 0.72–1.13). Among the 107 participants who tested positive for PSA, 19 (17.8%) tested negative for Yc-DNA.

Conclusions

Underreporting of unprotected sex was high among FSW but did not seem to be influenced by the recall period length. Reasons for discrepancies between PSA and Yc-DNA detection, where women tested positive for PSA but negative for Yc-DNA, should be further investigated.

Alcohol Use and Unprotected Sex Among HIV-Infected Ugandan Adults: Findings from an Event-Level Study

While alcohol is a known risk factor for HIV infection in sub-Saharan Africa (SSA), studies designed to investigate the temporal relationship between alcohol use and unprotected sex are lacking. The purpose of this study was to determine whether alcohol used at the time of a sexual event is associated with unprotected sex at that same event. Data for this study were collected as part of two longitudinal studies of HIV-infected Ugandan adults. A structured questionnaire was administered at regularly scheduled cohort study visits in order to assess the circumstances (e.g., alcohol use, partner type) of the most recent sexual event (MRSE). Generalized estimating equation logistic regression models were used to examine the association between alcohol use (by the participant, the sexual partner, or both the participant and the partner) and the odds of unprotected sex at the sexual event while controlling for participant gender, age, months since HIV diagnosis, unhealthy alcohol use in the prior 3 months, partner type, and HIV status of partner. A total of 627 sexually active participants (57% women) reported 1817 sexual events. Of these events, 19% involved alcohol use and 53% were unprotected. Alcohol use by one's sexual partner (aOR 1.70; 95% CI 1.14, 2.54) or by both partners (aOR 1.78; 95% CI 1.07, 2.98) during the MRSE significantly increased the odds of unprotected sex at that same event. These results add to the growing event-level literature in SSA and support a temporal association between alcohol used prior to a sexual event and subsequent unprotected sex.

Citizen Science for Mining the Biomedical Literature

Biomedical literature represents one of the largest and fastest growing collections of unstructured biomedical knowledge. Finding critical information buried in the literature can be challenging. To extract information from free-flowing text, researchers need to: 1. identify the entities in the text (named entity recognition), 2. apply a standardized vocabulary to these entities (normalization), and 3. identify how entities in the text are related to one another (relationship extraction). Researchers have primarily approached these information extraction tasks through manual expert curation and computational methods. We have previously demonstrated that named entity recognition (NER) tasks can be crowdsourced to a group of non-experts via the paid microtask platform, Amazon Mechanical Turk (AMT), and can dramatically reduce the cost and increase the throughput of biocuration efforts. However, given the size of the biomedical literature, even information extraction via paid microtask platforms is not scalable. With our web-based application Mark2Cure (http://mark2cure.org), we demonstrate that NER tasks also can be performed by volunteer citizen scientists with high accuracy. We apply metrics from the Zooniverse Matrices of Citizen Science Success and provide the results here to serve as a basis of comparison for other citizen science projects. Further, we discuss design considerations, issues, and the application of analytics for successfully moving a crowdsourcing workflow from a paid microtask platform to a citizen science platform. To our knowledge, this study is the first application of citizen science to a natural language processing task.