Gene burden analysis identifies genes associated with increased risk and severity of adult-onset hearing loss in a diverse hospital-based cohort.

Loss or absence of hearing is common at both extremes of human lifespan, in the forms of congenital deafness and age-related hearing loss. While these are often studied separately, there is increasing evidence that their genetic basis is at least partially overlapping. In particular, both common and rare variants in genes associated with monogenic forms of hearing loss also contribute to the more polygenic basis of age-related hearing loss. Here, we directly test this model in the Penn Medicine BioBank-a healthcare system cohort of around 40,000 individuals with linked genetic and electronic health record data. We show that increased burden of predicted deleterious variants in Mendelian hearing loss genes is associated with increased risk and severity of adult-onset hearing loss. As a specific example, we identify one gene-TCOF1, responsible for a syndromic form of congenital hearing loss-in which deleterious variants are also associated with adult-onset hearing loss. We also identify four additional novel candidate genes (COL5A1, HMMR, RAPGEF3, and NNT) in which rare variant burden may be associated with hearing loss. Our results confirm that rare variants in Mendelian hearing loss genes contribute to polygenic risk of hearing loss, and emphasize the utility of healthcare system cohorts to study common complex traits and diseases.

Trends in Twitter Utilization Among Academic Otolaryngologists.

OBJECTIVE: To characterize Twitter utilization among academic otolaryngologists and evaluate the relationship between Twitter utilization and research productivity. METHODS: Data were collected manually from accredited US otolaryngology residency programs from July-November 2021. Program and faculty demographics were documented, including citations and H-index for faculty and Doximity reputation and US News and World Report ranking for programs. Twitter metrics were also recorded. Descriptive analyses and multivariable logistic regression models were used to identify predictors of Twitter utilization. RESULTS: Currently, 333 (16%) faculty and 70 (62%) programs have a Twitter account. Of these, 36 (11%) and 27 (39%), respectively, were created in 2020. The regression model indicates that for each 5 unit increase in H-index, the odds of having a Twitter account increase 22% (OR 1.22, 95% CI 1.10-1.34, p = 0.0009). The number of faculty with a Twitter account predicts the existence of program Twitter accounts (OR:1.49, 95% CI 1.01-2.19, p = 0.04). Finally, of the 323 faculty with a Twitter account and available Scopus profile, we found that the number of individuals with Twitter use out of proportion to their academic productivity was low (n = 8/323). CONCLUSION: The H-index is a significant predictor of faculty Twitter accounts, whereas the number of faculty with Twitter is a significant predictor of program Twitter utilization. Although Twitter utilization is increasing, especially during the coronavirus pandemic, the findings indicate that there is ample room for growth, particularly amongst faculty with strong academic portfolios. LEVEL OF EVIDENCE: NA Laryngoscope, 134:1190-1196, 2024.