Trans-ethnic association study of blood pressure determinants in over 750,000 individuals. - Giri, Ayush; Hellwege, Jacklyn N; Keaton, Jacob M; Park, Jihwan; Qiu, Chengxiang; Warren, Helen R; Torstenson, Eric S; Kovesdy, Csaba P; Sun, Yan V; Wilson, Otis D; Robinson-Cohen, Cassianne; Roumie, Christianne L; et al. (Nat Genet, 2019)
In this trans-ethnic multi-omic study, we reinterpret the genetic architecture of blood pressure to identify genes, tissues, phenomes and medication contexts of blood pressure homeostasis. We discovered 208 novel common blood pressure SNPs and 53 rare variants in genome-wide association studies of systolic, diastolic and pulse pressure in up to 776,078 participants from the Million Veteran Program (MVP) and collaborating studies, with analysis of the blood pressure clinical phenome in MVP. Our transcriptome-wide association study detected 4,043 blood pressure associations with genetically predicted gene expression of 840 genes in 45 tissues, and mouse renal single-cell RNA sequencing identified upregulated blood pressure genes in kidney tubule cells.

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. - Mahajan, Anubha; Spracklen, Cassandra N; Zhang, Weihua; Ng, Maggie C Y; Petty, Lauren E; Kitajima, Hidetoshi; Yu, Grace Z; Rüeger, Sina; Speidel, Leo; Kim, Young Jin; Horikoshi, Momoko; Mercader, Josep M; et al. (Nat Genet, 2022)
We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.
Keywords: Diabetes Mellitus, Type 2; Ethnicity; Genetic Predisposition to Disease; Genome-Wide Association Study; Humans; Polymorphism, Single Nucleotide; Risk Factors

Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications. - Suzuki, Ken; Hatzikotoulas, Konstantinos; Southam, Lorraine; Taylor, Henry J; Yin, Xianyong; Lorenz, Kim M; Mandla, Ravi; Huerta-Chagoya, Alicia; Rayner, Nigel W; Bocher, Ozvan; Ana Luiza de, S V Arruda; Sonehara, Kyuto; et al. (medRxiv, 2023)
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5×10 ) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised 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, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. - Suzuki, Ken; Hatzikotoulas, Konstantinos; Southam, Lorraine; Taylor, Henry J; Yin, Xianyong; Lorenz, Kim M; Mandla, Ravi; Huerta-Chagoya, Alicia; Melloni, Giorgio E M; Kanoni, Stavroula; Rayner, Nigel W; Bocher, Ozvan; et al. (Nature, 2024)
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. 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) 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 scores 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.

Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits. - Keaton, Jacob M; Kamali, Zoha; Xie, Tian; Vaez, Ahmad; Williams, Ariel; Goleva, Slavina B; Ani, Alireza; Evangelou, Evangelos; Hellwege, Jacklyn N; Yengo, Loic; Young, William J; Traylor, Matthew; et al. (Nat Genet, 2024)
Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P < 5 × 10) from the largest single-stage blood pressure (BP) genome-wide association study to date (n = 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5-18.2 mmHg, P = 2.22 × 10) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54-9.70; P = 4.13 × 10) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781-0.801) to 0.826 (95% CI, 0.817-0.836, ∆AUROC, 0.035, P = 1.98 × 10). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research.