The association of host genes with specific sexually transmitted infections

Machine learning for personalized risk assessment of HIV, syphilis, gonorrhoea and chlamydia: A systematic review and meta-analysis

BACKGROUND

Machine learning (ML) shows promise for sexually transmitted infection (STI) risk prediction, but systematic evidence of its effectiveness remains fragmented.

METHODS

We systematically searched six electronic databases, three preprint archives and conference proceedings (January 2010-April 2024). Studies reporting quantitative performance metrics for supervised ML-based STI risk prediction models were included. We used a bivariate random-effects model to estimate pooled sensitivity, specificity and area under the curve (AUC). The risk of bias was assessed using the Prediction model Risk of Bias Assessment Tool. We conducted sequential analyses of studies with complete and reconstructed confusion matrices. Subgroup analyses and meta-regression explored potential sources of heterogeneity.

RESULTS

Among 3877 records screened, 25 studies comprising 45 unique models met inclusion criteria. For HIV, analysis of studies with complete confusion matrices (7 studies, 9 contingency tables) demonstrated summary AUC of 0.91 (95% CI: 0.88-0.93), pooled sensitivity 0.84 (0.76-0.90) and specificity 0.84 (0.70-0.93). Substantial heterogeneity persisted across subgroups (I² > 98%). For other STIs, individual studies reported AUCs ranging from 0.75-0.87 for syphilis (n = 5), 0.73-1.00 for gonorrhoea (n = 6) and 0.67-1.00 for chlamydia (n = 6).

DISCUSSION

While ML models show promising performance, particularly for HIV, significant heterogeneity complicates interpretation. Future research should prioritize external validation, standardized guidelines and multi-centred robust implementation studies to evaluate clinical impact.

Duration of viral persistence in human semen after acute viral infection: a systematic review

The persistence of viruses in human semen following acute infection can contribute to the ongoing transmission of a disease or cause resurgence after an outbreak has been declared ended. Viral persistence in semen affects embryonic development and male fertility, and the development of drugs and vaccines. We conducted a systematic review of viral persistence in semen in accordance with PRISMA guidelines. 373 original studies were included in this Review after screening 29 739 articles from five databases. Evidence was found of detection of 22 viruses in human semen following acute infection, including pathogens with pandemic potential. In addition to collating the largest evidence base to date on viral detection in semen following acute infection, this Review reports the maximal and median viral persistence (in days) after the onset of illness and evidence for sexual transmission and viability of the viruses in semen. Finally, the Review presents research gaps that need to be prioritised to guide further study of the dynamics of viral persistence in semen.

Genetic predictors for bacterial vaginosis in women living with and at risk for HIV infection

PROBLEM

Bacterial vaginosis (BV) disproportionally impacts Black and Hispanic women, placing them at risk for HIV, sexually transmitted infections and preterm birth. It is unknown whether there are differences by genetic ancestry in BV risk or whether polymorphisms associated with BV risk differ by ancestry.

METHODS

Women's Interagency HIV Study (WIHS) participants with longitudinal Nugent scores were dichotomized as having (n = 319, Nugent 7-10) or not having BV (n = 367, Nugent 0-3). Genetic ancestry was defined by clustering of principal components from ancestry informative markers and further stratified by BV status. 627 single nucleotide polymorphisms (SNPs) across 41 genes important in mucosal defense were identified in the WIHS GWAS. A logistic regression analysis was adjusted for nongenetic predictors of BV and self-reported race/ethnicity to assess associations between genetic ancestry and genotype.

RESULTS

Self-reported race and genetic ancestry were associated with BV risk after adjustment for behavioral factors. Polymorphisms in mucosal defense genes including syndecans, cytokines and toll-like receptors (TLRs) were associated with BV in all ancestral groups.

CONCLUSIONS

The common association of syndecan, cytokine and TLR genes and the importance of immune function and inflammatory pathways in BV, suggests these should be targeted for further research on BV pathogenesis and therapeutics.