RESUMO
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.
Assuntos
Diabetes Mellitus Tipo 2 , Progressão da Doença , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Humanos , Adipócitos/metabolismo , Cromatina/genética , Cromatina/metabolismo , Doença da Artéria Coronariana/complicações , Doença da Artéria Coronariana/genética , Diabetes Mellitus Tipo 2/classificação , Diabetes Mellitus Tipo 2/complicações , Diabetes Mellitus Tipo 2/genética , Diabetes Mellitus Tipo 2/patologia , Diabetes Mellitus Tipo 2/fisiopatologia , Nefropatias Diabéticas/complicações , Nefropatias Diabéticas/genética , Células Endoteliais/metabolismo , Células Enteroendócrinas , Epigenômica , Predisposição Genética para Doença/genética , Ilhotas Pancreáticas/metabolismo , Herança Multifatorial/genética , Doença Arterial Periférica/complicações , Doença Arterial Periférica/genética , Análise de Célula ÚnicaRESUMO
INTRODUCTION: Genome-wide association studies (GWAS) have identified loci associated with Alzheimer's disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates the entire genome and captures rare variations, may identify causal variants within GWAS loci. METHODS: We performed single common variant association analysis and rare variant aggregate analyses in the pooled population (N cases = 2184, N controls = 2383) and targeted analyses in subpopulations using WGS data from the Alzheimer's Disease Sequencing Project (ADSP). The analyses were restricted to variants within 100 kb of 83 previously identified GWAS lead variants. RESULTS: Seventeen variants were significantly associated with AD within five genomic regions implicating the genes OARD1/NFYA/TREML1, JAZF1, FERMT2, and SLC24A4. KAT8 was implicated by both single variant and rare variant aggregate analyses. DISCUSSION: This study demonstrates the utility of leveraging WGS to gain insights into AD loci identified via GWAS.