E. coli ST131 is an important extraintestinal pathogen that can colonize the gastrointestinal tracts of humans and food animals. Here, we combined detection of accessory traits associated with avian adaptation (ColV plasmids) with high-resolution phylogenetics to quantify the portion of human infections caused by ST131 strains of food animal origin. Our results suggest that one ST131 sublineage—ST131-H22—has become established in poultry populations around the world and that meat may serve as a vehicle for human exposure and infection. ST131-H22 is just one of many E. coli lineages that may be transmitted from food animals to humans. Additional studies that combine detection of host-associated accessory elements with phylogenetics may allow us to quantify the total fraction of human extraintestinal infections attributable to food animal E. coli strains.

Sexual transmission of HIV requires exposure to the virus and infection of activated mucosal immune cells, specifically CD4+ T cells or dendritic cells. The foreskin is a major site of viral entry in heterosexual transmission of HIV. Although the probability of acquiring HIV from a sexual encounter is low, the risk varies even after adjusting for known HIV risk factors. The genital microbiome may account for some of the variability in risk by interacting with the host immune system to trigger inflammatory responses that mediate the infection of mucosal immune cells. We conducted a case-control study of uncircumcised participants nested within a randomized-controlled trial of male circumcision in Rakai, Uganda. Using penile (coronal sulcus) swabs collected by study personnel at trial enrollment, we characterized the penile microbiome by sequencing and real-time PCR and cytokine levels by electrochemiluminescence assays. The absolute abundances of penile anaerobes at enrollment were associated with later risk of HIV seroconversion, with a 10-fold increase in Prevotella, Dialister, Finegoldia, and Peptoniphilus increasing the odds of HIV acquisition by 54 to 63%, after controlling for other known HIV risk factors. Increased abundances of anaerobic bacteria were also correlated with increased cytokines, including interleukin-8, which can trigger an inflammatory response that recruits susceptible immune cells, suggesting a mechanism underlying the increased risk. These same anaerobic genera can be shared between heterosexual partners and are associated with increased HIV acquisition in women, pointing to anaerobic dysbiosis in the genital microbiome and an accompanying inflammatory response as a novel, independent, and transmissible risk factor for HIV infection.

Objective Polygenic risk scores (PRSs) assess the individual genetic propensity to a condition by combining sparse information scattered across genetic loci, often displaying small effect sizes. Most PRSs are constructed in European‐ancestry populations, limiting their use in other ethnicities. Here we constructed and validated a PRS for late‐onset Alzheimer's Disease (LOAD) in Caribbean Hispanics (CH). Methods We used a CH discovery (n = 4,312) and independent validation sample (n = 1,850) to construct an ancestry‐specific PRS (“CH‐PRS”) and evaluated its performance alone and with other predictors using the area under curve (AUC) and logistic regression (strength of association with LOAD and statistical significance). We tested if CH‐PRS predicted conversion to LOAD in a subsample with longitudinal data (n = 1,239). We also tested the CH‐PRS in an independent replication CH cohort (n = 200) and brain autopsy cohort (n = 33). Finally, we tested the effect of ancestry on PRS by using European and African American discovery cohorts to construct alternative PRSs (“EUR‐PRS”, “AA‐PRS”). Results The full model (LOAD ~ CH‐PRS + sex + age + APOE‐ɛ4), achieved an AUC = 74% (ORCH‐PRS = 1.51 95%CI = 1.36–1.68), raising to >75% in APOE‐ɛ4 non‐carriers. CH‐PRS alone achieved an AUC = 72% in the autopsy cohort, raising to AUC = 83% in full model. Higher CH‐PRS was significantly associated with clinical LOAD in the replication CH cohort (OR = 1.61, 95%CI = 1.19–2.17) and significantly predicted conversion to LOAD (HR = 1.93, CI = 1.70–2.20) in the longitudinal subsample. EUR‐PRS and AA‐PRS reached lower prediction accuracy (AUC = 58% and 53%, respectively). Interpretation Enriching diversity in genetic studies is critical to provide an effective PRS in profiling LOAD risk across populations. ANN NEUROL 2021;90:366–376