Publications

We evaluated motorcycle taxi ('boda-boda') drivers in Kampala for the prevalence of HIV/sexually transmitted infections. We used respondent-driven sampling to recruit a cross-sectional sample of boda-boda drivers. We collected data through audio computer-assisted self-administered interviews. Men were tested for HIV, syphilis serology using Rapid Plasma Reagin and enzyme immunoassay, and Chlamydia and gonorrhoea using urine polymerase chain reaction. We recruited 683 men. Median age was 26 years; 59.4% were single. The prevalence of HIV was 7.5% (95% CI 5.2-10.0), of positive syphilis serology was 6.1% (95% CI 4.3-8.1), of Chlamydia was 1.1% (95% CI 0.4-2.0), and of gonorrhoea was 1.2% (95% CI 0.1-1.2). Many men (67.8%) had both casual and regular partners, sex with other men (8.7%), and commercial sex (33.1%). Factors associated with having HIV included reporting a genital ulcer (odds ratio [OR] =2.4, 95% CI 1.4-4.4), drinking alcohol during last sex (OR 2.0, 95% CI 1.1-3.7), having 4-6 lifetime partners (OR 2.2, 95% CI 1.0-4.8), and having one's last female partner be >24 years of age (OR 2.8, 95% CI 1.2-6.6). Independent predictors of HIV included age ≥31 (adjusted OR (aOR) 5.8, 95% CI 1.5-48.5), having 4-6 partners (aOR 2.2, 95%CI 1.0-5.1), and self-report of a genital ulcer (OR 2.3, 95% CI 1.2-4.1). Only 39.2% of men were circumcised, and 36.9% had been HIV tested in the past. Male boda-boda drivers have a higher prevalence of HIV than the general population, and low frequency of preventive behaviours, such as circumcision and HIV testing. Targeted and intensified interventions for this group are warranted.

The National Institute of Diabetes and Digestive and Kidney Diseases-supported Kidney Research National Dialogue asked the scientific community to formulate and prioritize research objectives that would enhance understanding of kidney function and disease and improve clinical outcomes. An engaged and growing group of investigators working in type 2 translation (from clinical evidence to implementation in the community) identified barriers to improving patient care in CKD and suggested research priorities to test translational strategies that have been effective for other chronic diseases.

Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable researchers to further investigate questions in developmental biology.