Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease Based on an Ancestrally Diverse Genome-Wide Association Study and Population-Specific Optimization
BACKGROUND: Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (CHD; PRS CHD ) for 5 genetic ancestry groups. METHODS: We derived ancestry-specific and multi-ancestry PRS CHD based on pruning and thresholding (PRS PT ) and ancestry-based continuous shrinkage priors (PRS CSx ) applied to summary statistics from the largest multi-ancestry genome-wide association study meta-analysis for CHD to date, including 1.1 million participants from 5 major genetic ancestry groups. Following training and optimization in the Million Veteran Program, we evaluated the best-performing PRS CHD in 176,988 individuals across 9 diverse cohorts. RESULTS: Multi-ancestry PRS PT and PRS CSx outperformed ancestry-specific PRS PT and PRS CSx across a range of tuning values. Two best-performing multi-ancestry PRS CHD (ie, PRS PTmult and PRS CSxmult ) and 1 ancestry-specific (PRS CSxEUR ) were taken forward for validation. PRS PTmult demonstrated the strongest association with CHD in individuals of South Asian ancestry and European ancestry (odds ratio per 1 SD [95% CI, 2.75 [2.41–3.14], 1.65 [1.59–1.72]), followed by East Asian ancestry (1.56 [1.50–1.61]), Hispanic/Latino ancestry (1.38 [1.24–1.54]), and African ancestry (1.16 [1.11–1.21]). PRS CSxmult showed the strongest associations in South Asian ancestry (2.67 [2.38–3.00]) and European ancestry (1.65 [1.59–1.71]), lower in East Asian ancestry (1.59 [1.54–1.64]), Hispanic/Latino ancestry (1.51 [1.35–1.69]), and the lowest in African ancestry (1.20 [1.15–1.26]). CONCLUSIONS: The use of summary statistics from a large multi-ancestry genome-wide meta-analysis improved the performance of PRS CHD in most ancestry groups compared with single-ancestry methods. Despite the use of one of the largest and most diverse sets of training and validation cohorts to date, improvement of predictive performance was limited in African ancestry. This highlights the need for larger genome-wide association study datasets of underrepresented populations to enhance the performance of PRS CHD .
Lymphocyte activation gene 3 and coronary artery disease
BACKGROUND: The lipoprotein scavenger receptor BI ( SCARB1 ) rs10846744 noncoding variant is significantly associated with atherosclerotic disease independently of traditional cardiovascular risk factors. We identified a potentially novel connection between rs10846744, the immune checkpoint inhibitor lymphocyte activation gene 3 ( LAG3 ), and atherosclerosis. METHODS: In vitro approaches included flow cytometry, lipid raft isolation, phosphosignaling, cytokine measurements, and overexpressing and silencing LAG3 protein. Fasting plasma LAG3 protein was measured in hyperalphalipoproteinemic (HALP) and Multi-Ethnic Study of Atherosclerosis (MESA) participants. RESULTS: In comparison with rs10846744 reference (GG homozygous) cells, LAG3 protein levels by flow cytometry ( P < 0.001), in lipid rafts stimulated and unstimulated ( P = 0.03), and phosphosignaling downstream of B cell receptor engagement of CD79A ( P = 0.04), CD19 ( P = 0.04), and LYN ( P = 0.001) were lower in rs10846744 risk (CC homozygous) cells. Overexpressing LAG3 protein in risk cells and silencing LAG3 in reference cells confirmed its importance in phosphosignaling. Secretion of TNF-α was higher ( P = 0.04) and IL-10 was lower ( P = 0.04) in risk cells. Plasma LAG3 levels were lower in HALP carriers of the CC allele ( P < 0.0001) and by race ( P = 0.004). In MESA, race ( P = 0.0005), age ( P = 0.003), lipid medications ( P = 0.03), smoking history ( P < 0.0001), and rs10846744 genotype ( P = 0.002) were independent predictors of plasma LAG3. In multivariable regression models, plasma LAG3 was significantly associated with HDL-cholesterol (HDL-C) ( P = 0.007), plasma IL-10 ( P < 0.0001), and provided additional predictive value above the Framingham risk score ( P = 0.04). In MESA, when stratified by high HDL-C, plasma LAG3 was associated with coronary heart disease (CHD) (odds ratio 1.45, P = 0.004). CONCLUSION: Plasma LAG3 is a potentially novel independent predictor of HDL-C levels and CHD risk. FUNDING: This work was supported by an NIH RO1 grant (HL075646), the endowed Linda and David Roth Chair for Cardiovascular Research, and the Harold S. Geneen Charitable Trust Coronary Heart Disease Research award to Annabelle Rodriguez. MESA is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts HHSN268201500003I, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-001079, UL1-TR-000040, and DK063491. Cardiometabochip genotyping data for the MESA samples was supported in part by grants and contracts R01HL98077, N02-HL-64278, HL071205, UL1TR000124, DK063491, RD831697, and P50 ES015915.
Genetic loci associated with nonobstructive coronary artery disease in Caucasian women
Nonobstructive coronary artery disease (CAD) in women is associated with adverse cardiovascular (CV) outcomes; however, information regarding genetic variants that predispose women to nonobstructive CAD is lacking. Women from the Women's Ischemia Syndrome Evaluation (WISE) Study and the St. James Women Take Heart (WTH) Study were genotyped with the Cardio-MetaboChip. WISE enrolled women with symptoms and signs of ischemia referred for coronary angiography; WTH enrolled asymptomatic, community-based women without heart disease. Analyses were conducted with a case (WISE) - control (WTH) design and multivariate logistic regression models to investigate genetic variation associated with likelihood of nonobstructive CAD. One genetic marker, single nucleotide polymorphism (SNP) rs2301753 on chromosome 6 in RNF39, achieved chip-wide significance for nonobstructive CAD ( P < 9.5 × 10−7). After adjusting for baseline characteristics, we found no variants achieved chip-wide significance. However, SNP rs2301753 on chromosome 6 in RNF39 was associated with reduced likelihood of nonobstructive CAD [odds ratio (OR) 0.42 and 95% confidence interval (CI) of 0.29 to 0.68], at a nominal level of P = 5.6 × 10−6, while SNP rs12818945 in the ATP2B1 locus on chromosome 12 was associated with increased odds for nonobstructive CAD (OR 2.38 and 95% CI of 1.63 to 3.45) and nominal P = 5.8 × 10−6. The functions of RNF39 and ATP2B1 raise the possibility that genes involved in cardio-dysfunction may contribute to nonobstructive CAD in Caucasian women and may provide insights into novel approaches for therapy and prevention. If replicated, incorporation of these genetic variants into diagnostic evaluation may identify women at high risk for nonobstructive CAD.
A Bivariate Genome-Wide Approach to Metabolic Syndrome
OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.
Genome-Wide Linkage Analysis for Loci Affecting Pulse Pressure
Pulse pressure, the difference between systolic and diastolic blood pressure, is an independent risk factor for cardiovascular disease. Increased pulse pressure reflects reduced compliance of arteries and is a marker of atherosclerosis. To locate genes that affect pulse pressure, a genome-wide linkage scan for quantitative trait loci influencing pulse pressure was performed using variance components methods as implemented in sequential oligogenic linkage analysis routines. The analysis sample included 10 798 participants in 3320 families who were recruited as part of the Family Blood Pressure Program and were phenotyped with an oscillometric blood pressure measurement device using a consistent protocol across centers. Pulse pressure was adjusted for the effects of sex, age, age 2 , age-by-sex interaction, age 2 -by-sex interaction, body mass index, and field center to remove sources of variation other than the genetic effects related to pulse pressure. Significant linkage was observed on chromosome 18 (logarithm of odds [LOD]=3.2) in a combined racial sample, chromosome 20 (LOD=4.4), and 17 (LOD=3.6) in Hispanics, chromosome 21 (LOD=4.3) in whites, chromosome 19 (LOD=3.1) in a combined sample of blacks and whites, and chromosome 7 (logarithm of odds [LOD]=3.1) in blacks from the GenNet Network. Our genome scan shows significant evidence for linkage for pulse pressure in multiple areas of the genome, supporting previous published linkage studies. The identification of these loci for pulse pressure and the apparent congruence with other blood pressure phenotypes provide increased support that these regions contain genes influencing blood pressure phenotypes.