The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR–Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.

Objective: Lp(a) (lipoprotein[a]) concentrations are associated with atherosclerotic cardiovascular disease (ASCVD), and new therapies that enable potent and specific reduction are in development. In the largest study conducted to date, we address 3 areas of uncertainty: (1) the magnitude and shape of ASCVD risk conferred across the distribution of lipoprotein(a) concentrations; (2) variation of risk across racial and clinical subgroups; (3) clinical importance of a high lipoprotein(a) threshold to guide therapy. Approach and Results: Relationship of lipoprotein(a) to incident ASCVD was studied in 460 506 middle-aged UK Biobank participants. Over a median follow-up of 11.2 years, incident ASCVD occurred in 22 401 (4.9%) participants. Median lipoprotein(a) concentration was 19.6 nmol/L (25th–75th percentile 7.6–74.8). The relationship between lipoprotein(a) and ASCVD appeared linear across the distribution, with a hazard ratio of 1.11 (95% CI, 1.10–1.12) per 50 nmol/L increment. Substantial differences in concentrations were noted according to race—median values for white, South Asian, black, and Chinese individuals were 19, 31, 75, and 16 nmol/L, respectively. However, risk per 50 nmol/L appeared similar—hazard ratios of 1.11, 1.10, and 1.07 for white, South Asian, and black individuals, respectively. A high lipoprotein(a) concentration defined as ≥150 nmol/L was present in 12.2% of those without and 20.3% of those with preexisting ASCVD and associated with hazard ratios of 1.50 (95% CI, 1.44–1.56) and 1.16 (95% CI, 1.05–1.27), respectively. Conclusions: Lipoprotein(a) concentrations predict incident ASCVD among middle-aged adults within primary and secondary prevention contexts, with a linear risk gradient across the distribution. Concentrations are variable across racial subgroups, but the associated risk appears similar.

Genetic variation can predispose to disease both through (i) monogenic risk variants that disrupt a physiologic pathway with large effect on disease and (ii) polygenic risk that involves many variants of small effect in different pathways. Few studies have explored the interplay between monogenic and polygenic risk. Here, we study 80,928 individuals to examine whether polygenic background can modify penetrance of disease in tier 1 genomic conditions — familial hypercholesterolemia, hereditary breast and ovarian cancer, and Lynch syndrome. Among carriers of a monogenic risk variant, we estimate substantial gradients in disease risk based on polygenic background — the probability of disease by age 75 years ranged from 17% to 78% for coronary artery disease, 13% to 76% for breast cancer, and 11% to 80% for colon cancer. We propose that accounting for polygenic background is likely to increase accuracy of risk estimation for individuals who inherit a monogenic risk variant.

Telomeres, the end fragments of chromosomes, play key roles in cellular proliferation and senescence. Here we characterize the genetic architecture of naturally occurring variation in leukocyte telomere length (LTL) and identify causal links between LTL and biomedical phenotypes in 472,174 well-characterized UK Biobank participants. We identified 197 independent sentinel variants associated with LTL at 138 genomic loci (108 new). Genetically determined differences in LTL were associated with multiple biological traits, ranging from height to bone marrow function, as well as several diseases spanning neoplastic, vascular and inflammatory pathologies. Finally, we estimated that, at the age of 40 years, people with an LTL >1 s.d. shorter than the population mean had a 2.5-year-lower life expectancy compared with the group with ≥1 s.d. longer LDL. Overall, we furnish new insights into the genetic regulation of LTL, reveal wide-ranging influences of LTL on physiological traits, diseases and longevity, and provide a powerful resource available to the global research community.

Identification of individuals at highest risk of coronary artery disease (CAD)—ideally before onset—remains an important public health need. Prior studies have developed genome-wide polygenic scores to enable risk stratification, reflecting the substantial inherited component to CAD risk. Here we develop a new and significantly improved polygenic score for CAD, termed GPS_Mult, that incorporates genome-wide association data across five ancestries for CAD (>269,000 cases and >1,178,000 controls) and ten CAD risk factors. GPS_Multstrongly associated with prevalent CAD (odds ratio per standard deviation 2.14, 95% confidence interval 2.10–2.19,P < 0.001) in UK Biobank participants of European ancestry, identifying 20.0% of the population with 3-fold increased risk and conversely 13.9% with 3-fold decreased risk as compared with those in the middle quintile. GPS_Multwas also associated with incident CAD events (hazard ratio per standard deviation 1.73, 95% confidence interval 1.70–1.76,P < 0.001), identifying 3% of healthy individuals with risk of future CAD events equivalent to those with existing disease and significantly improving risk discrimination and reclassification. Across multiethnic, external validation datasets inclusive of 33,096, 124,467, 16,433 and 16,874 participants of African, European, Hispanic and South Asian ancestry, respectively, GPS_Multdemonstrated increased strength of associations across all ancestries and outperformed all available previously published CAD polygenic scores. These data contribute a new GPS_Multfor CAD to the field and provide a generalizable framework for how large-scale integration of genetic association data for CAD and related traits from diverse populations can meaningfully improve polygenic risk prediction.

Dilated cardiomyopathy (DCM) is an important cause of heart failure and the leading indication for heart transplantation. Many rare genetic variants have been associated with DCM, but common variant studies of the disease have yielded few associated loci. As structural changes in the heart are a defining feature of DCM, we report a genome-wide association study of cardiac magnetic resonance imaging (MRI)-derived left ventricular measurements in 36,041 UK Biobank participants, with replication in 2184 participants from the Multi-Ethnic Study of Atherosclerosis. We identify 45 previously unreported loci associated with cardiac structure and function, many near well-established genes for Mendelian cardiomyopathies. A polygenic score of MRI-derived left ventricular end systolic volume strongly associates with incident DCM in the general population. Even among carriers of TTN truncating mutations, this polygenic score influences the size and function of the human heart. These results further implicate common genetic polymorphisms in the pathogenesis of DCM.