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.

Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes. - Hindy, George; Dornbos, Peter; Chaffin, Mark D; Liu, Dajiang J; Wang, Minxian; Selvaraj, Margaret Sunitha; Zhang, David; Park, Joseph; Aguilar-Salinas, Carlos A; Antonacci-Fulton, Lucinda; Ardissino, Diego; Arnett, Donna K; et al. (Am J Hum Genet, 2022)
Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.
Keywords: Alleles; Blood Glucose; Case-Control Studies; Computational Biology; Databases, Genetic; Diabetes Mellitus, Type 2; Exome; Genetic Predisposition to Disease; Genetic Variation; Genetics, Population; Genome-Wide Association Study; Humans; Lipid Metabolism; Lipids; Liver; Molecular Sequence Annotation; Multifactorial Inheritance; Open Reading Frames; Phenotype; Polymorphism, Single Nucleotide

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes. - Goodrich, Julia K; Singer-Berk, Moriel; Son, Rachel; Sveden, Abigail; Wood, Jordan; England, Eleina; Cole, Joanne B; Weisburd, Ben; Watts, Nick; Caulkins, Lizz; Dornbos, Peter; Koesterer, Ryan; et al. (Nat Commun, 2021)
Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.
Keywords: Adult; Biological Variation, Population; Biomarkers; Diabetes Mellitus, Type 2; Dyslipidemias; Exome; Genetic Predisposition to Disease; Genotype; Humans; Multifactorial Inheritance; Penetrance; Risk Assessment

Publisher Correction: Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals. - Surendran, Praveen; Feofanova, Elena V; Lahrouchi, Najim; Ntalla, Ioanna; Karthikeyan, Savita; Cook, James; Chen, Lingyan; Mifsud, Borbala; Yao, Chen; Kraja, Aldi T; Cartwright, James H; Hellwege, Jacklyn N; et al. (Nat Genet, 2021)

The trans-ancestral genomic architecture of glycemic traits. - Chen, Ji; Spracklen, Cassandra N; Marenne, Gaëlle; Varshney, Arushi; Corbin, Laura J; Luan, Jian'an; Willems, Sara M; Wu, Ying; Zhang, Xiaoshuai; Horikoshi, Momoko; Boutin, Thibaud S; Mägi, Reedik; et al. (Nat Genet, 2021)
Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
Keywords: Alleles; Blood Glucose; Epigenesis, Genetic; Gene Expression Profiling; Genome, Human; Genome-Wide Association Study; Glycated Hemoglobin; Humans; Multifactorial Inheritance; Physical Chromosome Mapping; Quantitative Trait Loci; Quantitative Trait, Heritable; White People

Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals. - Surendran, Praveen; Feofanova, Elena V; Lahrouchi, Najim; Ntalla, Ioanna; Karthikeyan, Savita; Cook, James; Chen, Lingyan; Mifsud, Borbala; Yao, Chen; Kraja, Aldi T; Cartwright, James H; Hellwege, Jacklyn N; et al. (Nat Genet, 2020)
Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to ~1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency ≤ 0.01) variant BP associations (P < 5 × 10), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were ~8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.
Keywords: Blood Pressure; GATA5 Transcription Factor; Gene Frequency; Genetic Predisposition to Disease; Genome-Wide Association Study; Genotype; Humans; Hypertension; Mutation; Phospholipase C beta; Polymorphism, Single Nucleotide

Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls. - Flannick, Jason; Mercader, Josep M; Fuchsberger, Christian; Udler, Miriam S; Mahajan, Anubha; Wessel, Jennifer; Teslovich, Tanya M; Caulkins, Lizz; Koesterer, Ryan; Barajas-Olmos, Francisco; Blackwell, Thomas W; Eric Boerwinkle; et al. (Nature, 2019)
Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10) and candidate genes from knockout mice (P = 5.2 × 10). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.
Keywords: Animals; Case-Control Studies; Decision Support Techniques; Diabetes Mellitus, Type 2; Exome; Exome Sequencing; Female; Gene Frequency; Genome-Wide Association Study; Humans; Male; Mice; Mice, Knockout

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. - Turcot, Valérie; Lu, Yingchang; Highland, Heather M; Schurmann, Claudia; Justice, Anne E; Fine, Rebecca S; Bradfield, Jonathan P; Esko, Tõnu; Giri, Ayush; Graff, Mariaelisa; Guo, Xiuqing; Hendricks, Audrey E; et al. (Nat Genet, 2019)
An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. - Evangelou, Evangelos; Warren, Helen R; Mosen-Ansorena, David; Mifsud, Borbala; Pazoki, Raha; Gao, He; Ntritsos, Georgios; Dimou, Niki; Cabrera, Claudia P; Karaman, Ibrahim; Ng, Fu Liang; Evangelou, Marina; et al. (Nat Genet, 2018)
High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.
Keywords: Adult; Aged; Aged, 80 and over; Blood Pressure; Cardiovascular Diseases; Cells, Cultured; Female; Genetic Loci; Genetic Predisposition to Disease; Genetic Testing; Genetics, Population; Genome-Wide Association Study; Human Umbilical Vein Endothelial Cells; Humans; Hypertension; Life Style; Male; Middle Aged; Polymorphism, Single Nucleotide; Quantitative Trait Loci; Risk Factors

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. - Turcot, Valérie; Lu, Yingchang; Highland, Heather M; Schurmann, Claudia; Justice, Anne E; Fine, Rebecca S; Bradfield, Jonathan P; Esko, Tõnu; Giri, Ayush; Graff, Mariaelisa; Guo, Xiuqing; Hendricks, Audrey E; et al. (Nat Genet, 2018)
Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
Keywords: Adult; Animals; Body Mass Index; Drosophila; Energy Intake; Energy Metabolism; Female; Gene Frequency; Genetic Variation; Humans; Male; Obesity; Proteins; Syndrome

Publisher Correction: Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. - Evangelou, Evangelos; Warren, Helen R; Mosen-Ansorena, David; Mifsud, Borbala; Pazoki, Raha; Gao, He; Ntritsos, Georgios; Dimou, Niki; Cabrera, Claudia P; Karaman, Ibrahim; Ng, Fu Liang; Evangelou, Marina; et al. (Nat Genet, 2018)
In the version of this article originally published, the name of author Martin H. de Borst was coded incorrectly in the XML. The error has now been corrected in the HTML version of the paper.

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. - Turcot, Valérie; Lu, Yingchang; Highland, Heather M; Schurmann, Claudia; Justice, Anne E; Fine, Rebecca S; Bradfield, Jonathan P; Esko, Tõnu; Giri, Ayush; Graff, Mariaelisa; Guo, Xiuqing; Hendricks, Audrey E; et al. (Nat Genet, 2018)
In the published version of this paper, the name of author Emanuele Di Angelantonio was misspelled. This error has now been corrected in the HTML and PDF versions of the article.

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. - Turcot, Valérie; Lu, Yingchang; Highland, Heather M; Schurmann, Claudia; Justice, Anne E; Fine, Rebecca S; Bradfield, Jonathan P; Esko, Tõnu; Giri, Ayush; Graff, Mariaelisa; Guo, Xiuqing; Hendricks, Audrey E; et al. (Nat Genet, 2018)
In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. - Mahajan, Anubha; Wessel, Jennifer; Willems, Sara M; Zhao, Wei; Robertson, Neil R; Chu, Audrey Y; Gan, Wei; Kitajima, Hidetoshi; Taliun, Daniel; Rayner, N William; Guo, Xiuqing; Lu, Yingchang; et al. (Nat Genet, 2018)
We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
Keywords: Alleles; Chromosome Mapping; Diabetes Mellitus, Type 2; Exome Sequencing; Female; Genetic Predisposition to Disease; Genetic Variation; Genome-Wide Association Study; Humans; Male; White People

Exome-wide association study of plasma lipids in >300,000 individuals. - Liu, Dajiang J; Peloso, Gina M; Yu, Haojie; Butterworth, Adam S; Wang, Xiao; Mahajan, Anubha; Saleheen, Danish; Emdin, Connor; Alam, Dewan; Alves, Alexessander Couto; Amouyel, Philippe; Di Angelantonio, Emanuele; et al. (Nat Genet, 2017)
We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.
Keywords: Coronary Artery Disease; Diabetes Mellitus, Type 2; Exome; Genetic Association Studies; Genetic Predisposition to Disease; Genetic Variation; Genotype; Humans; Lipids; Macular Degeneration; Phenotype; Risk Factors

An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans. - Scott, Robert A; Scott, Laura J; Mägi, Reedik; Marullo, Letizia; Gaulton, Kyle J; Kaakinen, Marika; Pervjakova, Natalia; Pers, Tune H; Johnson, Andrew D; Eicher, John D; Jackson, Anne U; Ferreira, Teresa; et al. (Diabetes, 2017)
To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci ( < 5 × 10), including variants near the , , and genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.
Keywords: Diabetes Mellitus, Type 2; Gene Expression Regulation; Genetic Variation; Genome-Wide Association Study; Humans; White People

Rare and low-frequency coding variants alter human adult height. - Marouli, Eirini; Graff, Mariaelisa; Medina-Gomez, Carolina; Lo, Ken Sin; Wood, Andrew R; Kjaer, Troels R; Fine, Rebecca S; Lu, Yingchang; Schurmann, Claudia; Highland, Heather M; Rüeger, Sina; Thorleifsson, Gudmar; et al. (Nature, 2017)
Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.
Keywords: ADAMTS Proteins; Adult; Alleles; Body Height; Cell Adhesion Molecules; Female; Gene Frequency; Genetic Variation; Genome, Human; Glycoproteins; Glycosaminoglycans; Hedgehog Proteins; Humans; Intercellular Signaling Peptides and Proteins; Interferon Regulatory Factors; Interleukin-11 Receptor alpha Subunit; Male; Multifactorial Inheritance; NADPH Oxidase 4; NADPH Oxidases; Phenotype; Pregnancy-Associated Plasma Protein-A; Procollagen N-Endopeptidase; Proteoglycans; Proteolysis; Receptors, Androgen; Somatomedins