The genetic architecture and prediction of anthropomorphic measurements
University of Edinburgh
Professor Albert Tenesa
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Height, weight and related traits (e.g. BMI) are characteristic quantitative phenotypes with large genetic contribution for which most of the genetic variation is yet unidentified. The aim of this proposal is to use the UK Biobank as a proof of principle that the genetic contribution to complex continuos phenotypes can be identified in large cohorts and predicted from genetic markers.
The specific aims are:
To identify the loci that contribute to infant and adult anthropomorphic measurements.
To use genetic markers to construct prediction models of these anthropomorphic measurements as paradigm of complex traits (ie. determined by thousands of genes). The project aims to provide predictions of traits based solely on genetic markers using anthropomorphic traits as a paradigm. If the methodology works for these traits, then the same methodology will be applied to disease traits.
In addition, height and BMI have been associated with devastating diseases such as cancer and heart disease. Understanding, the common genetic pathways between those traits and the diseases they are associated with will help to develop better treatments and preventative measures. Genetic variation will be correlated with phenotypic variation. It is expected that genetic polymorphisms that contribute to the variation of anthropomorphic traits will show statistical associations with the traits. For instance, a given allele might increase one person's height. If that is the case, then the mean height of people that inherited that allele will on average be higher that people that didn't inherit it. Data and genotyping from the whole cohort will be used in this analysis