Danish Saleheen, Benjamin Voight and colleagues perform genome-wide analysis of multi-ancestry cohorts to identify genetic associations with type 2 diabetes (T2D) and coronary heart disease (CHD). They find novel loci and show that 24% of T2D loci are also associated with CHD and that greater genetic risk of T2D increases risk of CHD. To evaluate the shared genetic etiology of type 2 diabetes (T2D) and coronary heart disease (CHD), we conducted a genome-wide, multi-ancestry study of genetic variation for both diseases in up to 265,678 subjects for T2D and 260,365 subjects for CHD. We identify 16 previously unreported loci for T2D and 1 locus for CHD, including a new T2D association at a missense variant in HLA-DRB5 (odds ratio (OR) = 1.29). We show that genetically mediated increase in T2D risk also confers higher CHD risk. Joint T2D–CHD analysis identified eight variants—two of which are coding—where T2D and CHD associations appear to colocalize, including a new joint T2D–CHD association at the CCDC92 locus that also replicated for T2D. The variants associated with both outcomes implicate new pathways as well as targets of existing drugs, including icosapent ethyl and adipocyte fatty-acid-binding protein.

Recent genetic association studies have identified 55 genetic loci associated with obesity or body mass index (BMI). The vast majority, 51 loci, however, were identified in European-ancestry populations. We conducted a meta-analysis of associations between BMI and ∼2.5 million genotyped or imputed single nucleotide polymorphisms among 86 757 individuals of Asian ancestry, followed by in silico and de novo replication among 7488–47 352 additional Asian-ancestry individuals. We identified four novel BMI-associated loci near the KCNQ1 (rs2237892, P = 9.29 × 10⁻¹³), ALDH2/MYL2 (rs671, P = 3.40 × 10⁻¹¹; rs12229654, P = 4.56 × 10⁻⁹), ITIH4 (rs2535633, P = 1.77 × 10⁻¹⁰) and NT5C2 (rs11191580, P = 3.83 × 10⁻⁸) genes. The association of BMI with rs2237892, rs671 and rs12229654 was significantly stronger among men than among women. Of the 51 BMI-associated loci initially identified in European-ancestry populations, we confirmed eight loci at the genome-wide significance level (P < 5.0 × 10⁻⁸) and an additional 14 at P < 1.0 × 10⁻³ with the same direction of effect as reported previously. Findings from this analysis expand our knowledge of the genetic basis of obesity.

Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10⁻⁸) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10⁻⁹), NCOA2 (P = 1.6 × 10⁻⁸), and NID2-PTGDR (P = 4.2 × 10⁻⁸), and one novel locus associated with TG near WDR11-FGFR2 (P = 2.7 × 10⁻¹⁰). Conditional analyses identified a second signal near CD163-APOBEC1. We then combined results from the East Asian meta-analysis with association results from up to 187,365 European individuals from the Global Lipids Genetics Consortium in a trans-ancestry meta-analysis. This analysis identified (log₁₀Bayes Factor ≥6.1) eight additional novel lipid loci. Among the twelve total loci identified, the index variants at eight loci have demonstrated at least nominal significance with other metabolic traits in prior studies, and two loci exhibited coincident eQTLs (P < 1 × 10⁻⁵) in subcutaneous adipose tissue for BPTF and PDGFC. Taken together, these analyses identified multiple novel lipid loci, providing new potential therapeutic targets.

Genome-wide association studies (GWAS) have identified ∼100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1×10⁻⁴ in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies. Lipid traits are heritable, but many of the DNA variants that influence lipid levels remain unknown. In a genomic region, more than one variant may affect gene expression or function, and the frequencies of these variants can differ across populations. Genotyping densely spaced variants in individuals with different ancestries may increase the chance of identifying variants that affect gene expression or function. We analyzed high-density genotyped variants for association with TG, HDL-C, and LDL-C in African Americans, East Asians, and Europeans. At several genomic regions, we provide evidence that two or more variants can influence lipid traits; across loci, these additional signals increase the proportion of trait variation that can be explained by genes. At some association signals shared across populations, combining data from individuals of different ancestries narrowed the set of likely functional variants. At PCSK9 and APOA5, the data suggest that different variants influence trait levels in different populations. Variants previously reported to alter gene expression or function frequently exhibited the strongest association at those signals. The multiple signals and population-specific characteristics of the loci described here may be shared by genetic loci for other complex traits.

In 1992, the Brugada syndrome (BrS) was recognized as a disease responsible for sudden cardiac death, characterized by a right bundle‐branch block with ST segment elevation in the leads V1 and V2. This syndrome is highly associated with sudden cardiac death, especially in young males. BrS is currently diagnosed in patients with ST‐segment elevation showing type 1 morphology ≥ 2 mm in ≥1 leads among the right precordial leads V1 or V2 positioned in the 2nd, 3rd, or 4th intercostal space, and occurring either spontaneously or after a provocative drug test by the intravenous administration of Class I antiarrhythmic drugs. With accumulated findings, the BrS inheritance model is believed to be an autosomal dominant inheritable model with incomplete penetrance, although most patients with BrS were sporadic cases. SCN5A, which was identified as the first BrS‐associated gene in 1998, has emerged as the most common gene associated with BrS, and more than 10 BrS‐associated genes have been identified thereafter. Mutation‐specific genetic testing is recommended for the family members and appropriate relatives following the identification of BrS‐causative mutations in an index patient. In addition, comprehensive or BrS1 (SCN5A) targeted genetic testing could be useful for patients in whom a cardiologist has established a clinical index of suspicion for BrS based on the patient's clinical history, family history, and the expressed electrocardiographic (resting 12‐lead ECGs and/or provocative drug challenge testing) phenotype.Over the past 20 years, extensive research in this field has allowed better understanding of the pathophysiology, genetic background, and management of BrS even though controversies still exist. In this review article, a background of genetics, the genetic background of BrS, the genotype and phenotype relationship, the role of genetic screening in clinical practice, and the interpretation of the identified genetic variants have been addressed based on this understanding.