Showing papers by "Laura M. Raffield published in 2018"
TL;DR: The authors identify and prioritize genetic loci for cIMT and plaque by GWAS and colocalization approaches and further demonstrate genetic correlation with CHD and stroke.
Abstract: Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans.
96 citations
Seyedeh M. Zekavat1, Seyedeh M. Zekavat2, Sanni Ruotsalainen3, Robert E. Handsaker4 +352 more•Institutions (60)
TL;DR: In this article, the authors used deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a).
Abstract: Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans.
72 citations
TL;DR: FVIIa may be an ischemic stroke risk factor in older adults and FVIIa‐AT may assess mortality risk, and Polymorphisms in the F7 and PROCR loci were associated with F VIIa and FVI‐AT levels.
24 citations
TL;DR: A robust and powerful two‐step testing procedure Local Ancestry Adjusted Allelic (LAAA) association, which is able to replicate independent groups’ previously identified loci that would have been missed in CARe without joint testing.
Abstract: Genetic association studies in admixed populations allow us to gain deeper understanding of the genetic architecture of human diseases and traits. However, population stratification, complicated linkage disequilibrium (LD) patterns, and the complex interplay of allelic and ancestry effects on phenotypic traits pose challenges in such analyses. These issues may lead to detecting spurious associations and/or result in reduced statistical power. Fortunately, if handled appropriately, these same challenges provide unique opportunities for gene mapping. To address these challenges and to take these opportunities, we propose a robust and powerful two-step testing procedure Local Ancestry Adjusted Allelic (LAAA) association. In the first step, LAAA robustly captures associations due to allelic effect, ancestry effect, and interaction effect, allowing detection of effect heterogeneity across ancestral populations. In the second step, LAAA identifies the source of association, namely allelic, ancestry, or the combination. By jointly modeling allele, local ancestry, and ancestry-specific allelic effects, LAAA is highly powerful in capturing the presence of interaction between ancestry and allele effect. We evaluated the validity and statistical power of LAAA through simulations over a broad spectrum of scenarios. We further illustrated its usefulness by application to the Candidate Gene Association Resource (CARe) African American participants for association with hemoglobin levels. We were able to replicate independent groups' previously identified loci that would have been missed in CARe without joint testing. Moreover, the loci, for which LAAA detected potential effect heterogeneity, were replicated among African Americans from the Women's Health Initiative study. LAAA is freely available at https://yunliweb.its.unc.edu/LAAA.
17 citations
TL;DR: CAC density is not associated with mortality independent from CAC volume in European Americans and African Americans with type 2 diabetes.
Abstract: Coronary artery calcified plaque (CAC) is strongly predictive of cardiovascular disease (CVD) events and mortality, both in general populations and individuals with type 2 diabetes at high risk for CVD. CAC is typically reported as an Agatston score, which is weighted for increased plaque density. However, the role of CAC density in CVD risk prediction, independently and with CAC volume, remains unclear. We examined the role of CAC density in individuals with type 2 diabetes from the family-based Diabetes Heart Study and the African American-Diabetes Heart Study. CAC density was calculated as mass divided by volume, and associations with incident all-cause and CVD mortality [median follow-up 10.2 years European Americans (n = 902, n = 286 deceased), 5.2 years African Americans (n = 552, n = 93 deceased)] were examined using Cox proportional hazards models, independently and in models adjusted for CAC volume. In European Americans, CAC density, like Agatston score and volume, was consistently associated with increased risk of all-cause and CVD mortality (p ≤ 0.002) in models adjusted for age, sex, statin use, total cholesterol, HDL, systolic blood pressure, high blood pressure medication use, and current smoking. However, these associations were no longer significant when models were additionally adjusted for CAC volume. CAC density was not significantly associated with mortality, either alone or adjusted for CAC volume, in African Americans. CAC density is not associated with mortality independent from CAC volume in European Americans and African Americans with type 2 diabetes.
15 citations
Fred Hutchinson Cancer Research Center1, University of North Carolina at Chapel Hill2, University of Southern California3, Icahn School of Medicine at Mount Sinai4, Vanderbilt University5, Vanderbilt University Medical Center6, University of Virginia7, University of Mississippi Medical Center8, University of Wisconsin–Milwaukee9, University of Washington10
TL;DR: Vitamin B12 serves as an enzyme cofactor in the 1-carbon metabolism pathway, which plays a key role in a wide range of biological processes, including red blood cell formation, DNA synthesis, and myelination of the central nervous system.
9 citations
TL;DR: There may be a combination of cross-population and population-specific genetic effects, as well as differences in genetic effects between males and females, in the regulation of Hcy levels.
Abstract: Homocysteine (Hcy) is a heritable biomarker for CVD, peripheral artery disease, stroke, and dementia. Little is known about genetic associations with Hcy in individuals of African ancestry. We performed a genome-wide association study for Hcy in 4927 AAs from the Jackson Heart Study (JHS), the Multi-Ethnic Study of Atherosclerosis (MESA), and the Coronary Artery Risk in Young Adults (CARDIA) study. Analyses were stratified by sex and results were meta-analyzed within and across sex. In the sex-combined meta-analysis, we observed genome-wide significant evidence (p < 5.0 × 10−8) for the NOX4 locus (lead variant rs2289125, β = −0.15, p = 5.3 × 1011). While the NOX4 locus was previously reported as associated with Hcy in European-American populations, rs2289125 remained genome-wide significant when conditioned on the previously reported lead variants. Previously reported genome-wide significant associations at NOX4, MTR, CBS, and MMACHC were also nominally (p < 0.050) replicated in AAs. Associations at the CPS1 locus, previously reported in females only, also was replicated specifically in females in this analysis, supporting sex-specific effects for this locus. These results suggest that there may be a combination of cross-population and population-specific genetic effects, as well as differences in genetic effects between males and females, in the regulation of Hcy levels.
8 citations
TL;DR: Single variant associations in 11 genes/loci at erythrocyte genes exhibit ancestral differences in A1C effect and Minor Allele Frequency (MAF) are detected, which may impact glucose estimation and diabetes diagnosis by A 1C, particularly in minority populations.
Abstract: The latest transethnic genome wide association study on A1C identified 22 loci that modify A1C independently of glycemia. These loci overlap genes implicated in erythrocyte phenotypes that vary in prevalence across populations. We used TOPMed WGS data to estimate ancestral differences in associations with A1C at these loci and 23 additional erythrocyte genes not previously known to be related to A1C. We conducted WGS association analyses of A1C in 5224 nondiabetic individuals [2662 European ancestry (EA): Framingham Heart Study and Amish; 2562 African ancestry (AA): Jackson Heart Study] using age and sex-adjusted linear mixed-effect regression, and meta-analyzed cohort-specific results. We used Cochran heterogeneity and Fisher’s exact tests to assess ancestral differences in effect and Minor Allele Frequency (MAF). We detected single variant associations in 11 genes/loci (P Genetic variation at erythrocyte genes exhibit ancestral differences in A1C effect and MAF. These variants may differ in their contributions to inter-individual A1C variation, which may impact glucose estimation and diabetes diagnosis by A1C, particularly in minority populations. Disclosure C. Sarnowski: None. A. Leong: None. L. Raffield: None.
8 citations
TL;DR: RS5215 and rs5219 of KCNJ11 were not significant predictors of incident diabetes nor effect modifiers of the association between serum K and incident diabetes.
Abstract: Background
In the Atherosclerosis Risk in Communities (ARIC) Study and Jackson Heart Study (JHS) cohorts, serum potassium (K) is an independent predictor of diabetes risk, particularly among African-American participants Experimental studies show that serum K levels affects insulin secretion The KCNJ11 gene encodes for a K channel that regulates insulin secretion and whose function is affected by serum K levels Variants in KCNJ11 are associated with increased diabetes risk We hypothesized that there could be a gene-by-environment interaction between KCNJ11 variation and serum K on diabetes risk
Methods
Evaluating a combined cohort of ARIC and JHS participants, we sought to determine if KCNJ11 variants are risk factors for diabetes; and if KCNJ11 variants modify the association between serum K and diabetes risk Among participants without diabetes at baseline, we performed multivariable logistic regression to determine the effect of serum K, KCNJ11 variants, and their interactions on the odds of incident diabetes mellitus over 8–9 years in the entire cohort and by race
Results
Of 11,812 participants, 3220 (27%) participants developed diabetes 48% and 47% had 1 or 2 diabetes risk alleles of rs5215 and rs5219, respectively Caucasians had higher proportions of these risk alleles compared to African Americans (60% vs 17% for rs5215 and 60% vs 13% for rs5219, p<001) Serum K was a significant independent predictor of incident diabetes Neither rs5215 nor rs5219 was associated with incident diabetes In multivariable models, we found no statistically significant interactions between race and either rs5215 or rs5219 (P-values 0493 and 0496, respectively); nor between serum K and either rs5215 or rs5219 on odds of incident diabetes (P-values 0534 and 0687, respectively)
Conclusion
In this cohort, rs5215 and rs5219 of KCNJ11 were not significant predictors of incident diabetes nor effect modifiers of the association between serum K and incident diabetes
4 citations
TL;DR: Platelets are critical in inflammation, wound healing, and thrombosis, and are heritable, frequently assessed measures for which hundreds of genetic markers are assessed.
Abstract: Platelets are critical in inflammation, wound healing, and thrombosis. Platelet count (PLT) and mean platelet volume (MPV) are heritable, frequently assessed measures for which hundreds of genetic ...
1 citations
Brigham and Women's Hospital1, University of Washington2, University of Pittsburgh3, Broad Institute4, University of Maryland, Baltimore5, Loyola University Chicago6, University of North Carolina at Chapel Hill7, University of Colorado Denver8, University of Mississippi Medical Center9, Boston University10
TL;DR: It is shown that a widely-used two-stage approach to testing genotype-phenotype associations can lead to tests with undesirable statistical properties, due to both a combination of a mis-specified mean-variance relationship, and remaining covariate associations between the rank-normalized residuals and genotypes.
Abstract: When testing genotype-phenotype associations using linear regression, departure of the trait distribution from normality can impact both Type I error rate control and statistical power, with worse consequences for rarer variants. While it has been shown that applying a rank-normalization transformation to trait values before testing may improve these statistical properties, the factor driving them is not the trait distribution itself, but its residual distribution after regression on both covariates and genotype. Because genotype is expected to have a small effect (if any) investigators now routinely use a two-stage method, in which they first regress the trait on covariates, obtain residuals, rank-normalize them, and then secondly use the rank-normalized residuals in association analysis with the genotypes. Potential confounding signals are assumed to be removed at the first stage, so in practice no further adjustment is done in the second stage. Here, we show that this widely-used approach can lead to tests with undesirable statistical properties, due to both a combination of a mis-specified mean-variance relationship, and remaining covariate associations between the rank-normalized residuals and genotypes. We demonstrate these properties theoretically, and also in applications to genome-wide and whole-genome sequencing association studies. We further propose and evaluate an alternative fully-adjusted two-stage approach that adjusts for covariates both when residuals are obtained, and in the subsequent association test. This method can reduce excess Type I errors and improve statistical power.