Type 2 diabetes (T2D) is an important risk factor for heart failure (HF) independent of traditional risk factors for
cardiovascular disease. However, lowering hemoglobin A1c levels has little effect on reducing HF risk among
T2D patients. These findings highlight the importance of primordial prevention strategies to curb T2D-related
HF and suggest that pathophysiologic mechanisms independent of hyperglycemia may link these conditions.
Hence, molecular phenotyping to better predict T2D and articulate biological pathways relating T2D to HF are
critically needed and in line with recommendations by the American Heart Association and Heart Failure
Society of America urging further research into the shared genomic susceptibility of these conditions.
Recently, a novel genome-wide polygenic risk score (PRS) that combined contributions of millions of genetic
variants showed promise for classifying individuals according to T2D status. However, its value for
longitudinally predicting the development of T2D from childhood was not assessed and its generalizability was
limited to European populations. We hypothesize that a PRS developed using large-scale multi-ancestry
genomics datasets will have optimal risk prediction accuracy and be applicable to ancestrally diverse samples.
We further hypothesize that the serum metabolomes of individuals with high genetic risk for T2D contain
endogenous molecules reflecting mechanisms of diabetic cardiomyopathy, an important T2D-related HF
endophenotype. Therefore, the objectives of this proposed study are to develop a PRS to predict T2D risk from
early life to midlife and to identify mechanisms underlying diabetes-induced HF. Our PRS will be generated by
combining summary statistics from a multi-ethnic GWAS of T2D among more than 1.4 million participants with
linkage disequilibrium data from a nationally representative sample of US adults (Aim 1a). Following PRS
testing using individual level genomic data from ~600,000 multi-ancestry participants, we will apply our PRS to
biracial cohorts of the Bogalusa Heart Study (BHS; n=1,808) and Coronary Artery Risk Development in Young
Adults (n=2,341) with measures of glycemic status and glucose lowering medication across the lifespan.
Leveraging these unique resources, we will be the first to evaluate the clinical utility of genomic information in
the prediction of T2D in childhood and early adulthood (Aim 1b). Finally, we will perform mediation analyses to
identify circulating metabolites and metabolic pathways linking genetically elevated T2D risk to subclinical
measures of HF leveraging combined sample of 10,929 BHS and the Trans-omics for Precision Medicine
program participants (Aim 2). This innovative multi-omics study will likely aid in developing targeted primordial
interventions by providing a genomic algorithm to identify individuals at high risk for T2D at an early age and
prior to the manifestation of clinical risk factors. Further, our findings may reveal novel molecular mechanisms
for diabetic cardiomyopathy, helping to guide pharmaceutical development to treat this condition.