RESUMEN
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.
Asunto(s)
Diabetes Mellitus Tipo 2 , Progresión de la Enfermedad , Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo , Humanos , Adipocitos/metabolismo , Cromatina/genética , Cromatina/metabolismo , Enfermedad de la Arteria Coronaria/complicaciones , Enfermedad de la Arteria Coronaria/genética , Diabetes Mellitus Tipo 2/clasificación , Diabetes Mellitus Tipo 2/complicaciones , Diabetes Mellitus Tipo 2/genética , Diabetes Mellitus Tipo 2/patología , Diabetes Mellitus Tipo 2/fisiopatología , Nefropatías Diabéticas/complicaciones , Nefropatías Diabéticas/genética , Células Endoteliales/metabolismo , Células Enteroendocrinas , Epigenómica , Predisposición Genética a la Enfermedad/genética , Islotes Pancreáticos/metabolismo , Herencia Multifactorial/genética , Enfermedad Arterial Periférica/complicaciones , Enfermedad Arterial Periférica/genética , Análisis de la Célula IndividualRESUMEN
Discerning the mechanisms driving type 2 diabetes (T2D) pathophysiology from genome-wide association studies (GWAS) remains a challenge. To this end, we integrated omics information from 16 multi-tissue and multi-ancestry expression, protein, and metabolite quantitative trait loci (QTL) studies and 46 multi-ancestry GWAS for T2D-related traits with the largest, most ancestrally diverse T2D GWAS to date. Of the 1,289 T2D GWAS index variants, 716 (56%) demonstrated strong evidence of colocalization with a molecular or T2D-related trait, implicating 657 cis-effector genes, 1,691 distal-effector genes, 731 metabolites, and 43 T2D-related traits. We identified 773 of these cis- and distal-effector genes using either expression QTL data from understudied ancestry groups or inclusion of T2D index variants enriched in underrepresented populations, emphasizing the value of increasing population diversity in functional mapping. Linking these variants, genes, metabolites, and traits into a network, we elucidated mechanisms through which T2D-associated variation may impact disease risk. Finally, we showed that drugs targeting effector proteins were enriched in those approved to treat T2D, highlighting the potential of these results to prioritize drug targets for T2D. These results represent a leap in the molecular characterization of T2D-associated genetic variation and will aid in translating genetic findings into novel therapeutic strategies.