Type 2 diabetes (T2D) is a growing scourge worldwide, despite attempts to prevent and control it. Innovative approaches are needed to identify new molecular targets for prevention and care. Genome-wide association studies (GWAS) for T2D and related quantitative traits (QTs: fasting glucose [FG], insulin [FI], glycated hemoglobin [HbA1c]) have dramatically advanced molecular understanding of glycemic regulation, with >120 common (minor allele frequency, MAF =1%) single nucleotide variants (SNV) and ~110 genomic loci now associated with T2D and-or QTs. However, the causal variant and the functional basis of associations are unclear at many loci, and most signals reside in non-coding regions. More detailed scans of rare variants (MAF <1%) and non-coding regions available from whole genome sequence (WGS) are needed to help translate T2D genetics into better T2D healthcare. Rare variation makes up ~2/3 of all human genetic variation. Non-coding regions occupy >98% of the genome. Both rare and common variants are captured in WGS data and can be scanned genome-wide for trait associations, then further tested for association with T2D and other clinical phenotypes using extant data. SNVs can be integrated with detailed regulatory maps (e.g. ENCODE, many others) to define molecular function-trait associations. Genomic annotation can point to specific disruptive mutations (altering gene regulation or function, producing phenotype variation) potentially acting at a locus, suggesting specific in vitro assays to confirm the annotation's prediction. The overall goal to renew 2R01DK78616 is to identify T2D-QT- associated functional rare variants using WGS scans in ~3,700 white and black individuals from three cohorts in the CHARGE consortium. We will manage WGS data in the cloud and analyze individual data in a Commons. We will replicate new findings in collaboration with other WGS studies.
Our Aims are 1) test WGS-wide for FG and FI rare variant associations at ~110 known and new T2D-QT loci; 2) Phenotype T2D-QT rare variants with existing physiological and molecular data in CHARGE, including tests of QT variant associations with T2D risk; 3) Annotate T2D-QT SNVs using ENCODE and others, and confirm their predicted allele-specific molecular function in vitro with appropriate experiments in appropriate cells (For instance, test allele-specific effects at transcription facto binding sites with transient transfection, gel shift and luciferase assays in HepG2 cell lines). Ou interdisciplinary, multicenter team has a proven track record based on over six years of R01DK78616 support. We now propose to move T2D genetics from common variant GWAS to rare variant WGS with deep annotation and in vitro validation to generate new molecular hypotheses and advance translation of T2D genetics into better T2D prevention and care.
We aim to identify type 2 diabetes-quantitative trait (T2D-QT)-associated functional rare variants using WGS scans in ~3,700 white and black individuals from three cohorts in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium. We will phenotype T2D-QT rare variants with existing physiological data in CHARGE, including tests for T2D risk, annotate variants using ENCODE and other resources, and confirm predicted allele-specific molecular function in vitro with appropriate experiments in appropriate cells. T2D is a growing scourge worldwide. Innovative approaches are needed to identify new molecular targets for prevention and care. Genome-wide association studies for T2D and related quantitative traits like fasting glucose have dramatically advanced molecular understanding of glycemic regulation, but the causal variant and the functional basis of associations are unclear at many loci. We propose to move T2D genetics from common variant GWAS to rare variant WGS with deep annotation and in vitro validation to generate new molecular hypotheses that advance translation of genetics into better T2D prevention and care.
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