The identification of subjects at high risk for Alzheimer's disease is important for prognosis and early intervention. We investigated the polygenic architecture of Alzheimer's disease and the accuracy of Alzheimer's disease prediction models, including and excluding the polygenic component in the model. This study used genotype data from the powerful dataset comprising 17 008 cases and 37 154 controls obtained from the International Genomics of Alzheimer's Project (IGAP). Polygenic score analysis tested whether the alleles identified to associate with disease in one sample set were significantly enriched in the cases relative to the controls in an independent sample. The disease prediction accuracy was investigated in a subset of the IGAP data, a sample of 3049 cases and 1554 controls (for whom APOE genotype data were available) by means of sensitivity, specificity, area under the receiver operating characteristic curve (AUC) and positive and negative predictive values. We observed significant evidence for a polygenic component enriched in Alzheimer's disease (P = 4.9 × 10(-26)). This enrichment remained significant after APOE and other genome-wide associated regions were excluded (P = 3.4 × 10(-19)). The best prediction accuracy AUC = 78.2% (95% confidence interval 77-80%) was achieved by a logistic regression model with APOE, the polygenic score, sex and age as predictors. In conclusion, Alzheimer's disease has a significant polygenic component, which has predictive utility for Alzheimer's disease risk and could be a valuable research tool complementing experimental designs, including preventative clinical trials, stem cell selection and high/low risk clinical studies. In modelling a range of sample disease prevalences, we found that polygenic scores almost doubles case prediction from chance with increased prediction at polygenic extremes.

Patients with type 2 diabetes initiated with metformin monotherapy had longer survival than did matched, non-diabetic controls. Those treated with sulphonylurea had markedly reduced survival compared with both matched controls and those receiving metformin monotherapy. This supports the position of metformin as first-line therapy and implies that metformin may confer benefit in non-diabetes. Sulphonylurea remains a concern.

No abstract

Background: In the United States, young men who have sex with men (YMSM) of color represent a high number of new human immunodeficiency virus (HIV) diagnoses annually. HIV pre-exposure prophylaxis (PrEP) is effective and acceptable to YMSM of color, yet PrEP uptake is low in those communities due to barriers including stigma, cost, adherence concerns, and medical distrust. A telehealth-based approach to PrEP initiation may be a solution to those barriers. This pilot study investigates one such intervention called PrEPTECH. Methods: We enrolled 25 HIV-uninfected YMSM, aged 18–25 years, from the San Francisco Bay Area into a 180-day longitudinal study between November 2016 and May 2017. Participants received cost-free PrEP services via telehealth (e.g., telemedicine visits, home delivery of Truvada® and sexually transmitted infection [STI] testing kits), except for two laboratory visits. Online survey assessments querying PrEPTECH features and experiences were administered to participants at 90- and 180-days. Results: Eighty-four percent of participants were YMSM of color. Among the 21 who completed the study, 11 of the 16 who wanted to continue PrEP were transitioned to sustainable PrEP providers. At least 75% felt that PrEPTECH was confidential, fast, convenient, and easy to use. Less than 15% personally experienced PrEP stigma during the study. The median time to PrEP initiation was 46 days. STI positivity was 20% and 19% at baseline and 90-days respectively. No HIV infections were detected. Conclusions: Telehealth programs like PrEPTECH increase PrEP access for YMSM of color by eliminating barriers inherent in traditional clinic-based models.