Multi-trait genome-wide characterization of non-traditional glycemic biomarkers and type 2 diabetes

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PROJECT SUMMARY Type 2 diabetes (T2D) and its long-term complications has reached epidemic proportions worldwide. Currently, there are major gaps in the knowledge of T2D genetics and its underlying mechanisms, which is critical for identifying novel therapies and strategies that can reduce the impact of T2D. Genetic studies of clinically relevant biomarkers in relation to T2D, beyond the classical glycemic biomarkers (e.g. glucose, HbA1c, and insulin- related traits), can help us get a wholesome view of T2D mechanisms. There is growing epidemiologic evidence that nontraditional biomarkers of hyperglycemia – fructosamine, glycated albumin, and 1,5-anhydroglucitol – improve risk stratification of diabetes and its long-term complications, provide information beyond the classical glycemic biomarkers, and hold promise in providing unique insights into hyperglycemia and diabetes physiology. A limited number of previous genome-wide association studies (GWAS) have examined genetic determinants of these newer biomarkers using data from the Atherosclerosis Risk in Communities (ARIC) Study. Thus far, ARIC (or any other study) has not been fully exploited to unravel genetic associations of these newer biomarkers or investigate underlying causal mechanisms using more advanced statistical methods that can leverage overlapping genetic architecture of these biomarkers, among themselves and with traditional glycemic biomarkers and T2D taking into account sex-specific differences. In this proposal, we will use modern statistical approaches to exploit the unique data available on these newer glycemic biomarkers, in two major ethnic groups (Black and White) in the ARIC Study to identify genetic associations across the entire allele-frequency spectrum (Aims 1, 3); to explore genetic overlap with traditional biomarkers (Aim 2) and with known T2D-relevant genes (Aims 2, 3); to investigate independent causal role of all biomarkers on T2D by leveraging genetic overlap (Aim 2); and characterize sex-specific and ancestry-specific differences if any (Aims 1-3). We will attempt to replicate our findings in the Coronary Artery Risk Development in Young Adults (CARDIA) study. Our innovations include going beyond the current paradigm of T2D locus discovery using classical biomarkers; novel use of modern multi-trait approaches on existing data; novel follow-up analysis of pleiotropic loci to better characterize underlying causal mechanisms using Mendelian Randomization; use of trans-ethnic analysis to boost GWAS power; and exploring rare variant associations of fructosamine and glycated albumin for the first time. Successful completion of these aims will provide preliminary data for a subsequent multi-omics proposal to study these biomarkers using DNA methylation, proteomic, and whole genome sequence data in ARIC. Thus, our pipeline for systematic examination of unique and shared genetics of these newer glycemic biomarkers with classical biomarkers and T2D can lead to a better understanding of the mechanisms by which they act in concert in delineating T2D risk, and can impact clinical guidelines and diabetes care. Intriguing results from this proposal will encourage other cohorts to do assays of these newer biomarkers that will increase power of future GWAS.