Genomic, gene-environment and casual inference studies in diabetic complications

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Over 34 million Americans (~10% of population) have diabetes, 90-95% of which is type 2 diabetes (T2D). T2D is a leading cause of health complications in the US, and minority populations with diabetes are more likely to experience microvascular complications, macrovascular disease, and subsequent death than their White counterparts even when access to care is comparable. The pathophysiology of hyperglycemic organ damage, and why some patients are relatively spared, remains largely unknown. Aggressive glycemic control is known to decrease the frequency of diabetic complications, particularly microvascular, however, few patients are able reach recommended glycemic targets. Inherited variation is known to contribute to the risk of T2D complications. However, genetic associations studies of diabetic complications have only recently begun to reveal the specific genes and pathways responsible for increased susceptibility. While these findings show the promise of this approach, there is an urgent need to better understand the mechanisms by which hyperglycemia leads to organ damage and increase genetic discoveries in diabetic complications. To achieve this goal, we hypothesize that genetics can further enhance the biological insights into diabetic complications by using large-scale sample size, consideration of pleiotropy, environmental modulation and genetic subtyping. The following Specific Aims are proposed to test this hypothesis 1) Genomic and pleiotropy analyses of diabetic complications in 185K subjects with T2D across five racial- ethnic groups; 2) Gene x environment (GxE) interaction analyses of diabetic complications to consider the role of environmental modulation on genetic risk T2D complications in up to 1.3M subjects with and without T2D; and 3) genetic risk profiles and causal inference in diabetic complications to identify causal risk factors and disentangle the relationship between the factors and T2D and its complications. This work has the potential to elucidate the mechanisms of diabetic complications and provide insights into biology and knowledge critical to guide the development of potential clinical predictors, strategies for prevention and guide development of new therapies.