Search

SUMMARYAging is characterized by degeneration in cellular and organismal functions leading to increased disease susceptibility and death. Although our understanding of aging biology in model systems has increased dramatically, large-scale sequencing studies to understand human aging are now just beginning. We applied exome sequencing and association analyses (ExWAS) to identify age-related variants on 58,470 participants of the DiscovEHR cohort. Linear Mixed Model regression analyses of age at last encounter revealed variants in genes known to be linked with clonal hematopoiesis of indeterminate potential, which are associated with myelodysplastic syndromes, as top signals in our analysis, suggestive of age-related somatic mutation accumulation in hematopoietic cells despite patients lacking clinical diagnoses. In addition to APOE, we identified rare DISP2 rs183775254 (p = 7.40×10−10) and ZYG11A rs74227999 (p = 2.50×10−08) variants that were negatively associated with age in either both sexes combined and females, respectively, which were replicated with directional consistency in two independent cohorts. Epigenetic mapping showed these variants are located within cell-type-specific enhancers, suggestive of important transcriptional regulatory functions. To discover variants associated with extreme age, we performed exome-sequencing on persons of Ashkenazi Jewish descent ascertained for extensive lifespans. Case-Control analyses in 525 Ashkenazi Jews cases (Males ≥ 92 years, Females ≥ 95years) were compared to 482 controls. Our results showed variants in APOE (rs429358, rs6857), and TMTC2 (rs7976168) passed Bonferroni-adjusted p-value, as well as several nominally-associated population-specific variants. Collectively, our Age-ExWAS, the largest performed to date, confirmed and identified previously unreported candidate variants associated with human age.

Competitive cyclists seek to maximize their efficiency by minimizing the influence of resistive forces. At the high speeds maintained during competition, aerodynamic drag is the primary resistive force. This paper investigates the influence of a cyclist’s body position using models of aerodynamic drag and elucidates the time benefit of various body positions. Mathematical models from prior work, which use cyclist mass and body position angles, have been used to determine the projected frontal area of a cyclist and the aerodynamic drag. Graphical representation of the non-linear relationship between aerodynamic drag and an increasing velocity are also provided. Finally, simulations are produced for a 40 km time trial course, and the results indicate a maximum performance increase of 20.71% due entirely to rider body position when exerting 400 W. We conclude aerodynamic efficiency is crucial in competitive cycling, and its significant correlation with rider body position should not be ignored.Copyright © 2013 by ASME