We will use a novel software tool we have recently developed to compute the extent of the influence of human DNA on observable physical, clinical, and cognitive characteristics/traits (phenotype). Many of these traits are caused by genetic (heritable), environmental and life-style factors. Our primary aim is to identify those traits, where genetic factors play a significant role. This will enable us and other scientists to prioritize phenotypes for follow-up genetics studies. Our second aim will be to study the genetic overlap between phenotypes. Identifying the genetic factors that influence health-related, observable individual-level traits, such as disease diagnosis, will be critical for understanding the causal mechanisms of various clinical conditions, and developing prevention and treatment strategies. With rich phenotypic datasets such as the UK Biobank, it is going to be critical to prioritize phenotypes based on heritability. Those phenotypes which are largely determined by genetics (i.e., have large heritability) will be good candidates for further examining the underlying genetic causes. We will use a novel analytic strategy, which we recently published, to examine genome-wide marker (single nucleotide polymorphism, or SNP) data and phenotype data to examine the relationship between DNA and observable traits. We will use the full cohort.
|Return ID||App ID||Description||Archive Date|
|2065||32568||Phenome-wide heritability analysis of the UK Biobank||25 Feb 2020|
|2941||32568||The Shared Genetic Basis of Educational Attainment and Cerebral Cortical Morphology||3 Dec 2020|
|2066||Phenome-wide heritability analysis of the UK Biobank||Tian Ge et al||2017||PLOS Genetics 2017|
|2942||The Shared Genetic Basis of Educational Attainment and Cerebral Cortical Morphology||Tian Ge et al||2019||Cerebral Cortex (2019)|