WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
The world s largest GWAS of osteoporosis involving ~142,000 subjects with genome-wide genotyping and quantitative ultrasound derived bone mineral density (i.e. a predictor of osteoporosis susceptability) . Identified 153 novel loci, screened 120 candidate genes using phenotyped KO mice, and implicated candidate gene GPC6 as a promising new drug target for osteoporosis. Awarded prestigious presentations at American Society of Bone Mineral Research and American Society of Human Genetics in 2016. Received considerable interest, with 17 global media reports, several media interviews (estimated audience 2.5M) and has already scored in the top 5% of all research outputs (Altmetric).
Investigating the Genetic Architecture Underlying the Developmental Origins of Health and Disease
The prevalence of cardiovascular disease, diabetes, osteoporosis and infertility are increasing and the financial burden on society is substantial. Research has shown a link between birth weight and increased risk of these diseases and other cardiovascular/metabolic disorders. Genetics may be involved as not all individuals born of suboptimal weight go on to develop disease. The aims of this research are to: (1) identify novel genes that explain the adverse relationship between birth weight and cardiometabolic disorders, osteoporosis or infertility, (2) determine biological intermediates that partially mediate the relationship between birth weight and these disorders, using genetic profile scores. Currently, most interventions target individuals after the onset of clinical symptoms, by which time treatment is expensive and of limited effectiveness. The Developmental Origins of Health and Disease (DOHaD) paradigm suggests that there may be critical windows earlier in life that offer opportunities for disease treatment and prevention. The overall aim of this project is to use novel statistical genetics methods to identify genes that explain part of the observational association between birth weight and risk of cardiometabolic disease, osteoporosis or infertility, providing a better understanding of this relationship and its implications for future development of disease. We will conduct a genome-wide association study to identify individual genetic variants and regions of the genome that are 1) jointly associated with birth weight and cardiometabolic disorders or osteoporosis, 2) associated with fracture risk or bone related phenotypes and 3) associated with fertility defects. In addition, we will use genetic risk scores for biological characteristics to investigate whether those characteristics partially mediate the observed relationship between birth weight and subsequent risk of disease in later life. Whole cohort with genetic data that have reported their birth weight, diagnosis of cardiometabolic diseases, osteoporosis or fertility defects.