Genome-Wide Association Study of Cardiac Structure and Systolic Function in African AmericansClinical Perspective
The Candidate Gene Association Resource (CARe) Study
Background—Using data from 4 community-based cohorts of African Americans, we tested the association between genome-wide markers (single-nucleotide polymorphisms) and cardiac phenotypes in the Candidate-gene Association Resource study.
Methods and Results—Among 6765 African Americans, we related age, sex, height, and weight-adjusted residuals for 9 cardiac phenotypes (assessed by echocardiogram or magnetic resonance imaging) to 2.5 million single-nucleotide polymorphisms genotyped using Genome-wide Affymetrix Human SNP Array 6.0 (Affy6.0) and the remainder imputed. Within the cohort, genome-wide association analysis was conducted, followed by meta-analysis across cohorts using inverse variance weights (genome-wide significance threshold=4.0 ×10−7). Supplementary pathway analysis was performed. We attempted replication in 3 smaller cohorts of African ancestry and tested lookups in 1 consortium of European ancestry (EchoGEN). Across the 9 phenotypes, variants in 4 genetic loci reached genome-wide significance: rs4552931 in UBE2V2 (P=1.43×10−7) for left ventricular mass, rs7213314 in WIPI1 (P=1.68×10−7) for left ventricular internal diastolic diameter, rs1571099 in PPAPDC1A (P=2.57×10−8) for interventricular septal wall thickness, and rs9530176 in KLF5 (P=4.02×10−7) for ejection fraction. Associated variants were enriched in 3 signaling pathways involved in cardiac remodeling. None of the 4 loci replicated in cohorts of African ancestry was confirmed in lookups in EchoGEN.
Conclusions—In the largest genome-wide association study of cardiac structure and function to date in African Americans, we identified 4 genetic loci related to left ventricular mass, interventricular septal wall thickness, left ventricular internal diastolic diameter, and ejection fraction, which reached genome-wide significance. Replication results suggest that these loci may be unique to individuals of African ancestry. Additional large-scale studies are warranted for these complex phenotypes.
- genome-wide association studies
- left atrium genetics
- left ventricular mass genetics
Although several traditional cardiovascular risk factors contribute substantially to interindividual variation in cardiac structure and systolic function, much of the observed variation in cardiac target organ damage is unexplained by established environmental risk factors and may be attributable to genetic factors.1 Both animal2–4 and human5–10 studies support a genetic influence on left ventricular (LV) structure and function. In a relatively recent 100K single-nucleotide polymorphism (SNP) genome-wide association (GWA) study in the Framingham Heart Study, investigators confirmed modest-to-strong heritabilities (estimates, 0.30–0.52) for several echocardiographic traits in white participants of European descent.11 More recently, Vasan et al12 conducted a GWA study using 2.5 million SNPs in a combined sample of 12 612 individuals of European ancestry from 5 community-based cohorts and identified 5 genetic loci associated with variation in phenotypes of cardiac structure. Data on genetic influences on cardiac structure and function in African Americans are quite limited. Analyses from the Hypertension Genetic Epidemiology Network (HyperGEN) and the Genetic Epidemiology Network of Arteriopathy (GENOA) studies suggest a high heritability of LV mass (estimates ranging from 0.55 to 0.88) and genetic influences on LV geometric remodeling.8
Clinical Perspective on p 46
The GWA method to identify novel SNPs contributing to the underlying risk for complex diseases has been successful.13 Data from the Candidate-gene Association REsource (CARe) Study allowed us to perform the first African American GWA study on cardiac phenotypes assessed by either echocardiography or magnetic resonance imaging (MRI).
Details of the CARe consortium are described elsewhere.14 Briefly, the CARe Study consists of 9 population-based cohort studies sponsored by the National Heart, Lung, and Blood Institute. Within CARe, 4 cohorts with African Americans (the Atherosclerosis Risk In Communities [ARIC], the Coronary Artery Risk Development in Young Adults [CARDIA], the Jackson Heart Study [JHS], and the Multi-Ethnic Study of Atherosclerosis (MESA]) had both echocardiography or MRI and DNA data available to investigate GWAs. These 4 cohorts were used for the discovery phase of this investigation. Guidelines on collaboration, phenotype harmonization, covariate selection, and the analysis plan for both within-cohort GWA and prospective meta-analysis of results across studies were adopted by each study. Also, each CARe cohort obtained approval from the respective institutional review boards for consent procedures, examination and surveillance components, data security measures, and DNA collection and its use for genetic research.
Echocardiographic and MRI Methods
Details on the collection of echocardiographic and MRI data by cohort are discussed in online-only Data Supplement Section I. In 3 of the cohorts, participants underwent routine transthoracic echocardiography at selected examinations (visit 1 for JHS and ARIC and visit 3 for CARDIA). For MESA, participants underwent cardiac MRI at visit 1. For participants undergoing echocardiography, M-mode measurements of LV internal diastolic and systolic diameter, the thickness at end-diastole of the posterior wall, interventricular septal wall thickness (IVST) diameter, the diameter at end-systole of the aortic root (ARD), and the left atrial diameter were obtained using the American Society of Echocardiography guidelines. LV mass (LVM) was calculated by using the American Society of Echocardiography–corrected formula by Devereux et al15:
LV systolic dysfunction on echocardiogram was defined as the presence of reduced fractional shortening (<0.29, which corresponds to an ejection fraction of 0.50) on M-mode or a depressed ejection fraction (<0.50) on 2-dimensional echocardiography.
For MESA, LVM and LV ejection fraction were determined by cardiac MRI using 1.5-T magnets. Specifically, LVM was determined by taking the difference between the epicardial and endocardial areas for all slices, multiplying the result by the slice thickness and section gap, and multiplying that result by the specific gravity of myocardium.
Genotyping Methods and Imputation
Genotyping and Quality Control
Genotyping of all cohorts was performed at the BROAD Institute of Harvard and MIT using Affymetrix Genome-Wide Human SNP array 6.0 (Affy6.0), which interrogates simultaneously 1.8 million markers for genetic variation (906 600 SNPs and 946 000 copy number variation probes) under the CARe consortium.16 Quality control of genotyped data (SNPs) was performed using the BROAD genetic analysis platform that consists of PLINK17 and Birdseed v1.3316 software. Quality control measures included removal of samples with genotyping success rate <95%, monomorphic SNPs, SNPs that mapped to several loci in the human genome, and SNPs with minor allele frequency <1%. Samples with very low (<4 SDs) heterozygosity, suggesting poor DNA quality, and samples with very high (>4 SDs) heterozygosity, suggesting sample contamination, were also removed. In all cohorts except for JHS, relatedness was identified by computing identical by descent and identical by state scores across the data sets. All pairs that shared ≥5% of their genome were removed, as were samples that did not cluster well when subjected to multidimensional scaling or genome-wide neighbor analysis in PLINK. This was done to eliminate familial correlation. For the family-based subcohort of the JHS, early analytic assessment by CARe investigators found little effect on inflation factor as a result of familial correlation. Other quality control filters included removing SNPs, for which genotype missingness can be predicted by surrounding haplotypes, with mendelian inconsistencies and removing SNPs with significant deviation from Hardy-Wienberg equilibrium. In total, 113 238 SNPs were excluded in ARIC, 69 710 in CARDIA, 40 653 in JHS, and 27 956 in MESA (ie, >99% genotyping success rate).
Genotype imputation performed in CARe has been detailed elsewhere. Briefly, in CARe, imputation was performed using the MACH (http://www.sph.umich.edu/csg/abecasis/MaCH/) program with HapMap phase 2 (build 36 release 22) as input. Because the African American population is admixed with the proportion of European ancestry, which is estimated to be ≈17% to 19%,18,19 an artificial reference panel consisting of equal proportions of the YRI and CEU HapMap phased haplotypes (using only SNPs found in both YRI and CEU panels, ie, ≈2.2M SNPs) was constructed. Hao et al20 suggested that the accuracy of using the mixed panel for African Americans is comparable with the accuracy reported when imputing a population of Nigerians using YRI as a reference panel.
Because participants within and between cohorts were unrelated, we used logistic or linear regression (implemented in PLINK genetic software) to investigate the association of SNP alleles with dichotomous or continuous echo trait, respectively, assuming an additive genetic model. Fractional shortening and ejection fraction were the only 2 dichotomous cardiac traits. In these 2 traits, we compared cases with controls while adjusting for age, sex, weight, height, and site (for CARDIA and MESA cohorts only) after excluding participants who had a previous myocardial infarction. For the 7 continuous traits (LVM, thickness at end-diastole of the posterior wall, IVST diameter, LV internal diastolic diameter, LV internal systolic diameter, left atrial diameter, ARD), we used linear regression of log-transformed measures to obtain sex-specific residuals after adjusting for age, weight, and height. The sex-specific residuals were then pooled, and within-cohort linear associations of SNP alleles with each echocardiographic continuous trait were performed. Ten principal components calculated from selected ancestry informative markers were used to account for population stratification common in African Americans because of admixture.
Genomic control correction was applied in each study before the meta-analysis, which ensured that the inflation factor lambda (λ) is maintained around unity.
Within-cohort GWA results included parameter estimates (β regression coefficient and their SEs). Meta-analysis was conducted using METAL software (http://www.sph.umich.edu/csg/abecasis/metal/). For each SNP, METAL calculated an overall β estimate, z-statistic, and P value from the weighted average of individuals’ statistic. No filtering on minor allele frequency was used.
A priori genome-wide statistical significance threshold of ≤4.0×10−7 was chosen to represent the probability for at least 1 SNP to have a P value below a stringent threshold. This strategy has been used in GWA studies to reduce false discovery rates.12,21
We assigned the overall association significance of each genetic variant to the cardiac structure equivalent to the most significant P value among the 9 cardiac traits. We then mapped these genetic variants back to the human genome (NCBI Build 36, 2006) and RefSeq genes. A gene region was defined as between 110 kb upstream and 40 kb downstream of the gene’s most extreme transcript boundaries, which would encompass the majority of its cis-eQTLs (expression quantitative trait loci).22 The lowest P value of SNPs within the gene region was assigned as the significance score for the gene. Of the 22 374 genes evaluated, 1718 reached significance scores <1.0×10−4. These genes were then imported into Ingenuity IPA for pathway analysis (Ingenuity Systems, Redwood, CA). Fisher exact test was used to justify the enrichment significance of each of the canonical pathways.
Replication Analysis in Cohorts of African and European Ancestry and Reciprocal Lookups of Top Loci in Cohorts of European Ancestry
Genome-wide significant SNPs discovered in the meta-analysis of the 3 cohorts were subjected to replication analysis in 3 cohorts of African ancestry (GENOA, n=651; HyperGEN, n=1316; Cardiovascular Health Study, n=501) and 1 cohort of European ancestry (Echo Genetics-EchoGEN, n=12 612). We adopted a criterion for declaring significance in the replication analysis at significance level P≤0.05/number of SNPs sent for replication. In addition, we performed a lookup of the top 50 CARe hits in the EchoGEN cohort. Subsequently, we tested the 5 published genome-wide significant SNPs from the EchoGEN cohort analysis in our CARe African American sample.
The demographic and clinical characteristics of the 4 populations in the discovery meta-analysis are summarized in Table 1. The age range for most of the participants was comparable, except for CARDIA, which had younger participants (<31 years old) overall. Of the 4 cohorts, only JHS had all 9 echocardiographic phenotypes, and the remaining 3 cohorts measured different subsets of phenotypes. MRI was available in MESA only.
The per-cohort genomic inflation factor (λ) was consistently <1.02 for all traits studied. The post–meta-analytic λ was also <1.02, indicating absence of systematic inflation. The meta-analysis quantile-quantile plots of observed against expected P value distributions are shown in online-only Data Supplement Figure IA–IH.
We identified 4 genome-wide significant loci associated with LV mass, IVST, LV internal diastolic diameter, and LV ejection fraction <0.50 (Table 2). Genetic effects (β) and SEs, minor and major alleles, minor allele frequency, SNP type, and the nearest genes (within ≈500 kb of either site of the SNP) are also shown in Table 2. Figure 1A–1D summarizes the primary findings from meta-analysis and displays the genome-wide −log10 P values for interrogated SNPs across the 22 autosomal chromosomes separately for the 4 cardiac traits that were significantly associated with the 4 loci. Figure 2A–2D shows the forest plots associated with the top loci. β coefficients (for continuous traits LV mass, IVST, and LV diastolic diameter) and odds ratios (for the dichotomous trait LV ejection fraction <0.50) from each cohort analysis and from the meta-analysis are shown. Figure 3A–3D shows the regional plots for the 4 top SNPs. The nearest gene loci to the top SNPs within 500 kb are also shown.
Online-only Data Supplement Table I lists 7 additional top genetic loci (and the SNP at each locus with the lowest P value) associated with cardiac traits based on the criterion 5.0×10−7<P<9.9×10−7 (arbitrary threshold). In online-only Data Supplement Figure IIA–IIG, the regional plots of the 7 additional top loci are presented.
We examined the interaction and relationship between the top GWA study loci. Accumulating evidence suggests that complex diseases and traits usually result from the incremental effects of many genetic variants.23–25 Pathway analysis provides a potential route to investigate the collective effects of multiple genetic variants on biological systems.26–28
A total of 1718 genes were found to be moderately related to cardiac structure. Ingenuity IPA (Ingenuity Systems, Redwood, CA) was used to study whether these genes were significantly enriched in some specific biological pathways beyond that expected from random distribution. Our analysis reveals that 3 canonical pathways were most significantly enriched with cardiac-related genes, including the sonic hedgehog signaling pathway (6 CARe genes/33 total genes in the pathway [18.2%]; P=1.88×10−2), the cardiac β-adrenergic signaling pathway (16 CARe genes/151 total genes in the pathway [10.6%]; P=3.22×10−2), and the oncostatin M signaling pathway (6 CARe genes/35 total genes in the pathway [17.1%]; P=3.88×10−2). The results suggest that the disruption of these signaling pathways might be the potential mechanisms affecting cardiac structure and related echocardiographic traits, which are also implicated in previous studies. A table showing the list of the gene symbols and names from the CARe data set identified in each of the 3 pathways is shown in online-only Data Supplement Table II.
We applied the same pathway approach to EchoGen data set and identified 942 cardiac-related genes with P<1.0×10−4 (see Methods section). Only a small proportion of them (97 genes) were also classified as cardiac-related genes from CARe data set because of factors such as the sample size and population stratification. Interestingly, one of the most enriched pathways from CARe data set, cardiac β-adrenergic signaling pathway, was also moderately enriched in the EchoGen data set (P=0.069; online-only Data Supplement Figure III).
Independent Replication of Top CARe SNPs in Cohorts of African and European Ancestry
Replication cohorts for the study are described in detail in online-only Data Supplement Section II. The 4 top genome-wide significant SNPs in the CARe analyses were submitted for lookup in 3 African American cohorts: the GENOA study (n=651), the HyperGEN study (n=1316), and Cardiovascular Health Study (n=501). In addition, top SNPs were submitted for lookup in 1 large cohort of individuals of European ancestry (EchoGEN [n=12 612]). None of the top SNPs met the a priori criteria for replication in the meta-analysis of African American cohorts after correcting for multiple comparisons. None of 3 SNPs available in EchoGEN (rs4552931, rs7213314, and rs9530176) replicated.
Reciprocal Lookups of Top Loci in Cohorts of European Ancestry
We tested the top 50 CARe SNPs for each trait in the EchoGen consortium (exclusively European ancestry). There was a moderate association between 9 of the CARe SNPs and key phenotypes of cardiac structure in EchoGen. Specifically, rs13241730 (ARD, P=1.18×10−5) was associated with systolic dysfunction (P=0.00925), rs11187518 (ejection fraction, P=4.44×10−6) with LV wall thickness (P=3.94×10−5), rs7159121 (fractional shortening [FS], P=4.67×10−6) with FS (P=0.000862), rs1549850 (internal systolic diameter, P=1.36×10−5) with ARD (P=0.00142), rs4752424 (interventricular septal wall thickness [IVST], P=1.95×10−5) with LVM (P=0.00088), rs11758777 (left atrial diameter, P=9.29×10−6) with left atrial size (P=0.00911), rs9536417 (LVDD, P=1.19×10−5) with FS (P=0.00113), rs6907666 (LVM, P=1.45×10−5) with ARD (P=0.000566), and rs33432 (PWT, P=1.94×10−5) with LVDD (P=0.0106). We tested whether the top 5 hits from EchoGEN replicated in CARe and did not find replication of any of the 5 SNPs.
In this largest study assessing the influence of genetic variation on cardiac structure and function in African Americans, we identified 4 genome-wide significant loci associated with LV structure (1 SNP for LV mass, 1 SNP for IVST, and 1 for LV internal diastolic dimension) and 1 significant locus associated with LV systolic dysfunction based on LV ejection fraction <0.50 or fractional shorting <0.29. Findings from the replication analysis of the 4 genome-wide significant loci in European ancestry suggest that these SNPs may represent loci specific to African ancestry. In further analysis, we found that 9 of the top 50 hits were noted to be moderately associated with cardiac structure in a large European ancestry cohort.
All of the genome-wide significant loci and several other top loci identified that were near (but did not reach) the threshold for genome-wide significance were near genes that can be linked to biological pathways implicated in influencing cardiac structure and function. Descriptions of these loci and nearby genes are noted in online-only Data Supplement Sections V and VI.
In a pathway analysis, we noted that top loci were enriched in cardiac genes from 3 signaling pathways (the sonic hedgehog pathway, the cardiac β-adrenergic signaling pathway, and the oncostatin M signaling pathway). Genes in the sonic hedgehog pathway have been identified in the adult heart and probably play a role in normal cardiac homeostasis and function. This pathway is key in the embryonic development of the coronary vasculature. Several genes in the β-adrenergic signaling pathway were represented among the top hits. It is established that this pathway is important in the induction and maintenance of cardiac hypertrophy, redistribution of myosin isoforms, and cardiac contractility. Further supporting our finding in the adrenergic pathway is that a similar analysis performed in the EchoGen consortium also revealed genes moderately enriched in this pathway. Finally, the oncostatin M signaling pathway was identified in the supplemental analysis. Oncostatin M is an inflammatory mediator; the signaling pathway involving oncostatin M has been found to induce stromal-derived factor-1 protein secretion in human cardiac cells and play a role in repair and tissue regeneration.
Our results suggest that population stratification may complicate the discovery of genetic variants associated with cardiac structure and function, despite the evidence of shared mechanisms. It is thus necessary to investigate genetic variants specific to African Americans.
Strengths and Limitations
The fact that there was no replication of the top loci in populations of European ancestry suggests that the association of these loci with cardiac structure and function may be unique to African ancestry. One limitation to replication is that the African American community represents an admixed population with smaller linkage equilibrium blocks compared with those of European ancestry. There is significant heterogeneity among individuals within the ethnic group. Therefore, replicating findings of our study population is more challenging compared with those from cohorts of European ancestry, despite the use of ancestral informative markers. Because HyperGEN and GENOA are family studies ascertained on hypertension, and therefore enriched with genes that contribute to elevated blood pressure (assuming blood pressure is genetically determined, which remains the prevailing thought), it is not completely unexpected that our results did not replicate in these cohorts. These families might have a distinct hypertension-induced phenotype. Another limitation of the current study is that differences in study design and data collection between cohorts may lower our statistical power to detect modest genetic effects in GWA. Using GWA, we are focused on detecting multiple variants with small effects that influence complex diseases; our statistical power in this study to detect rare variants associated with phenotypes of cardiac structure and function is limited. In addition, we acknowledge that we are only able to identify an association between genetic loci and phenotypes of interest; we are not able to establish a cause–effect relationship or identify a mechanism leading to the association. Finally, the cohorts studied were all of African ancestry descent, limiting the generalizability of our findings to individuals of non-African ancestry.
These limitations are balanced against our ability to conduct the largest GWA on African Americans with participants from community-based cohorts (each using standardized methods of M-mode echocardiography or MRI with quality control procedures in individual imaging laboratories) and with harmonization of imputation strategies and analytic methods into a prospective meta-analysis.
Our prospective meta-analysis of cardiac structure and function from more than 6765 participants in 4 community-based cohorts identified 4 loci: rs4552931 in UBE2V2 on chromosome 8 for LVM, rs7213314 in WIPI1 on chromosome 17 for LV internal diameter in diastole, rs1571099 in PPAPDC1A on chromosome 10 for IVST, and rs9530176 in KLF5 on chromosome 13 for ejection fraction.
In a pathway analysis, top loci in the meta-analysis were significantly enriched with genes from the sonic hedgehog signaling pathway, the cardiac β-adrenergic signaling pathway, and the oncostatin M signaling pathway.
After testing the top 50 CARe SNPs for each trait in the EchoGen consortium, we observed moderate association between 9 of these SNPs and cardiac structure in EchoGen.
Identification of genetic variations that contribute to cardiac structure and function through GWA analysis may help us better understand the role that genes play in the development and progression of cardiac end-organ damage in African Americans. This is particularly important given the current racial disparity in LV hypertrophy and dysfunction (both of which are predictors of cardiovascular morbidity and mortality). Findings in this study warrant further investigation, including replication analysis in much larger samples and identification of potential biological mechanisms explaining the association of these variants with phenotypic findings on cardiac imaging.
From the Department of Medicine, University of Mississippi School of Medicine, Jackson (E.R.F., S.K.M., B.Y.M., T.E.S., A.D.P., T.H.M., H.A.T.); Human Genetics Center, University of Texas Health Science Center, School of Public Health, Houston (M.B., A.C.M.); Department of Medicine, Boston University School of Medicine, Boston, MA (H.L., N.L.G., R.S.V); Department of Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL (K.O.O); Department of Epidemiology, University of Washington School of Medicine and Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Group Health Research Institute, Group Health Cooperative, Seattle, WA (N.L.S.); Department of Medicine, Georgia Health Sciences University, Augusta, GA (A.K.); Department of Medicine, Division of Cardiology, John Hopkins School of Medicine, Baltimore, MD (W.S.P.); National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD (D.N.P.); Department of Medicine, Cardiovascular Division, Yale School of Medicine, New Haven, CT (D.L.D.); Broad Institute of Massachusetts Institute of Technology and Harvard University, Boston, MA (D.N.F.); Department of Biostatistics (C.W.D., A.A.P., X.C.) and Department of Epidemiology, School of Public Health (D.K.A., J.S.), University of Alabama at Birmingham, Birmingham, AL; Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI (S.L.K.); Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison (K.J.M.); Department of Epidemiology, Rollins School of Public Health, Emory University School of Medicine, Atlanta, GA (Y.V.S.); Department of Medicine, University of California-San Francisco (K.B.-D.); Department of Biostatistics, University of Washington, Seattle, WA (P.B.); Department of Epidemiology, Boston University School of Public Health, Boston, MA (E.J.B.); Radiology and Imaging Sciences, National Institutes of Health, Clinical Center, Bethesda, MD (D.A.B.); Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill (G.H.); Wake Forest University School of Medicine, Public Health and Translational Sciences, Salem, NC (J.J.C.); Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington (R.P.T.); Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle (B.M.P., S.R.H.); and Department of Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA (J.P.C.).
We acknowledge the support of the National Heart, Lung, and Blood Institute and the contributions of the research institutions, study investigators, field staff, and study participants in creating this resource for biomedical research. We provide below 9 parent studies that have contributed parent study data, ancillary study data, and DNA samples through the Broad Institute (N01-HC-65226) and their respective funding sources to create this genotype/phenotype database for wide dissemination to the biomedical research community.
Sources of Funding
Atherosclerotic Risk in Communities: University of North Carolina at Chapel Hill (N01-HC-55015), Baylor Medical College (N01-HC-55016), University of Mississippi Medical Center (N01-HC-55021), University of Minnesota (N01-HC-55019), Johns Hopkins University (N01-HC-55020), University of Texas, Houston (N01-HC-55017), and University of North Carolina, Forsyth County (N01-HC-55018); Cardiovascular Health Study: University of Washington (N01-HC-85079), Wake Forest University (N01-HC-85080), Johns Hopkins University (N01-HC-85081), University of Pittsburgh (N01-HC-85082), University of California, Davis (N01-HC-85083), University of California, Irvine (N01-HC-85084), New England Medical Center (N01-HC-85085), University of Vermont (N01-HC-85086), Georgetown University (N01-HC-35129), Johns Hopkins University (N01 HC-15103), University of Wisconsin (N01-HC-75150), Geisinger Clinic (N01-HC-45133), and University of Washington (N01 HC-55222, U01 HL080295); Cleveland Family Study: Case Western Reserve University (RO1 HL46380-01-16); Cooperative Study of Sickle Cell Disease: University of Illinois (N01-HB-72982, N01-HB-97062), Howard University (N01-HB-72991, N01-HB-97061), University of Miami (N01-HB-72992, N01-HB-97064), Duke University (N01-HB-72993), George Washington University (N01-HB-72994), University of Tennessee (N01-HB-72995, N01-HB-97070), Yale University (N01-HB-72996, N01-HB-97072), Children’s Hospital-Philadelphia (N01-HB-72997, N01-HB-97056), University of Chicago (N01-HB-72998, N01-HB-97053), Medical College of Georgia (N01-HB-73000, N01-HB-97060), Washington University (N01-HB-73001, N01-HB-97071), Jewish Hospital and Medical Center of Brooklyn (N01-HB-73002), Trustees of Health and Hospitals of the City of Boston, Inc. (N01-HB-73003), Children’s Hospital-Oakland (N01-HB-73004, N01-HB-97054), University of Mississippi (N01-HB-73005), St. Luke’s Hospital-New York (N01-HB-73006), Alta Bates-Herrick Hospital (N01-HB-97051), Columbia University (N01-HB-97058), St. Jude’s Children’s Research Hospital (N01-HB-97066), Research Foundation, State University of New York-Albany (N01-HB-97068, N01-HB-97069), New England Research Institute (N01-HB-97073), and Interfaith Medical Center-Brooklyn (N01-HB-97085); Coronary Artery Risk in Young Adults: University of Alabama at Birmingham (N01-HC-48047), University of Minnesota (N01-HC-48048), Northwestern University (N01-HC-48049), Kaiser Foundation Research Institute (N01-HC-48050), University of Alabama at Birmingham (N01-HC-95095), Tufts-New England Medical Center (N01-HC-45204), Wake Forest University (N01-HC-45205), Harbor-UCLA Research and Education Institute (N01-HC-05187), and University of California, Irvine (N01-HC-45134, N01-HC-95100); Framingham Heart Study: Boston University (N01-HC-25195); Jackson Heart Study: Jackson State University (N01-HC-95170), University of Mississippi (N01-HC-95171), and Tougaloo College (N01-HC-95172); Multi-Ethnic Study of Atherosclerosis: University of Washington (N01-HC-95159), Regents of the University of California (N01-HC-95160), Columbia University (N01-HC-95161), Johns Hopkins University (N01-HC-95162), University of Minnesota (N01-HC-95163), Northwestern University (N01-HC-95164), Wake Forest University (N01-HC-95165), University of Vermont (N01-HC-95166), New England Medical Center (N01-HC-95167), Johns Hopkins University (N01-HC-95168), and Harbor-UCLA Research and Education Institute (N01-HC-95169); Sleep Heart Health Study: Johns Hopkins University (U01 HL064360), Case Western University (U01 HL063463), University of California, Davis (U01 HL053916), University of Arizona (U01 HL053938), University of Minnesota (relocating in 2006 to University Arizona) (U01 HL053934), University of Pittsburgh (U01 HL077813), Boston University (U01 HL053941), MedStar Research Institute (U01 HL063429), and Johns Hopkins University (U01 HL053937).
EchoGEN: The support for the Echo Genetics cohort is listed by study:
Cardiovascular Health Study: Contract numbers N01-HC-85079 through N01-HC-85086, N01-HC-35129, N01-HC-15103, N01-HC-55222, N01-HC-75150, N01-HC-45133, and grant numbers U01 HL080295 and R01 HL087652 from the National Heart, Lung, and Blood Institute. DNA handling and genotyping were supported, in part, by National Center for Research Resources grant M01 RR00069 to the Cedars-Sinai General Clinical Research Center Genotyping core and National Institute of Diabetes and Digestive and Kidney Diseases grant DK063491 to the Southern California Diabetes Endocrinology Research Center.
Rotterdam Study: The genome-wide association’s database of the Rotterdam Study was funded through the Netherlands Organization of Scientific Research (No. 175.010.2005.011, 911.03.012) and the Research Institute for Diseases in the Elderly.
This study was supported by the Netherlands Genomics Initiative/Netherlands Organization of Scientific Research project number 050 60 810. The Rotterdam Study is supported by the Erasmus Medical Center and Erasmus University, Rotterdam; the Netherlands Organization of Scientific Research, the Netherlands Organization for Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly, the Netherlands Heart Foundation, the Ministry of Education, Culture and Science, the Ministry of Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. We thank Michael Moorhouse, PhD, Department of Bioinformatics, and Pascal Arp, BSc, Mila Jhamai, BSc, Marijn Verkerk, BSc, and Sander Bervoets, BSc, Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands, for their help in creating the database.
MONICA-KORA: The study was funded by the European Union-sponsored project Cardiogenics (LSHM-CT 2006–037593), the National Genome Network (01GS0418 to Drs Schunkert and Erdmann; 01GR0466 to Dr Ziegler), and the National Genome Network Plus sponsored by the German Federal Ministry of Education and Research (BMBF). The MONICA/KORA Augsburg studies were financed by the Helmholtz Zentrum München (former GSF)–National Research Center for Environmental Health, Neuherberg, Germany, and supported by grants from the BMBF and Munich Center of Health Sciences (MC Health) as part of LMUinnovativ.
Framingham Heart Study: This work was supported by the National Heart, Lung, and Blood Institute’s Framingham Heart Study (Contract No. N01-HC-25195) and its contract with Affymetrix, Inc. for genotyping services (Contract No. N02-HL-64278) and by grants from the National Heart, Lung, and Blood Institute (2K24HL04334, RO1HL080124, RO1HL077477, and R01HL093328) (Dr Vasan).
Gutenberg Heart Study: This work is funded through the government of Rheinland-Pfalz (Stiftung Rheinland Pfalz für Innovation, Contract No. AZ 961–386261/733), the research programs Wissen schafft Zukunft and Schwerpunkt Vaskuläre Prävention of the Johannes Gutenberg-University of Mainz, and its contract with Boehringer Ingelheim and PHILIPS Medical Systems, including an unrestricted grant for the Gutenberg Heart Study. Specifically, the research reported in this article was supported by the National Genome Network NGFNplus (Contract No. A3 01GS0833) by the Federal Ministry of Education and Research, Germany.
Study of Health in Pomerania: This work is funded by the Federal Ministry of Education and Research (grant nos. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs, as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Echocardiography in the 5-year follow-up was funded by the Competence Network Heart.
Failure of the Federal Ministry of Education and Research and statistical analyses were supported by Deutsche Forschungsgemeinschaft (grant SFB TR 19). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthcare, Erlangen, Germany, and by the Federal State of Mecklenburg-West Pomerania.
Austrian Stroke Prevention Study: Current analyses of the Austrian Stroke Prevention Study are funded by the Austrian Science Fund Project P20545_P05 Genetics of cerebral small vessel disease (Dr H. Schmidt).
Mayo Clinic, Olmsted County: Dr Rodheffer was supported, in part, by RO1 HL55502.
GENOA: This study is supported by the National Institutes of Health grant numbers HL087660 and HL100245 from the National Heart, Lung, and Blood Institute and grant MD002249 from the National Institute on Minority Health and Health Disparities. Dr Meyers received additional funding through the National Center for Advancing Translation Sciences grant 9U54TR000021.
HyperGEN: The HyperGEN network is funded by cooperative agreements (U10) with the National Heart, Lung, and Blood Institute: HL54471, HL54472, HL54473, HL54495, HL54496, HL54497, HL54509, HL54515, and 2 R01 HL55673-12.
The funding sources had no role in the study design, analyses, or drafting of the article. The National Heart, Lung, and Blood Institute reviews all manuscripts submitted for publication, but it was not involved in the decision to publish.
Dr Kutlar received research grants from National Institutes of Health (NIH)/National Institute on Minority Health and Health Disparities (NIMHD)-P20, Novartis, Celgene Corp. (≥$10 000), and Global Iron Summit (<$10 000). Dr Paltoo has ownership interest in a 529 College Plan and a Thrift Saving Plan (>$10 000). Dr Kardia received research grants from R01 HD067264, RC4 AG039029, R01 HL101161-01-A1, R01 DK077950-03, RC1 HL100185, and P60 MD002249 (>$10 000). Dr Sun received research grants from NIH HL 100245, Genetics of Hypertension Risk Factors, and Sequela in African Americans (>$10 000). Dr Benjamin received research grants from R01 HL09257, RC1 HD101056, R01 HL102214, and R01 AG028321 (all NIH grants >$10 000). Dr Tracy received research grants from Candidate Gene Association Resource Study, Exome Sequencing Project (>$10 000). Dr Mosley received research grants from ARIC, ARIC-Neurocognitive Study, Predictors of Coronary Artery Calcification in an African American Cohort, GWAS of Ischemic Brain Vascular Injury, ARIC PET Amyloid Imaging Study, the Intracranial Atherosclerosis Disease and Cognitive Impairment Study, Parkinson Disease and Olfactory Function in the ARIC Study, and Identify Epidemiological Risk Factors for Abdominal Aortic Aneurysm Study (all NIH grants >$10 000). Dr Taylor received research grants for the Jackson Heart Study (NIH grant >$10 000). Dr Psaty received NIH grants (<$10 000); he serves on the Data and Safety Monitoring Board for a clinical trial for a device (Zoll Life Cor <$10 000) and service on the Steering Committee for Yale Open Data Project (Medtronic <$10 000). Dr Heckbert received research grants from HL 087652 Whole Genome Association Study in the Cardiovascular Health Study (National Heart, Lung, and Blood Institute >$10 000). Dr Vasan received an NIH grant (>$10 000). The other authors report no conflicts.
The online-only Data Supplement is available at http://circgenetics.ahajournals.org/lookup/suppl/doi:10.1161/CIRCGENETICS.111.962365/-/DC1.
- Received December 4, 2011.
- Accepted October 2, 2012.
- © 2013 American Heart Association, Inc.
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We investigated the association between genome-wide markers with cardiac structure and systolic function using data from 4 community-based cohorts of African Americans in the Candidate-gene Association Resource study. Findings from this analysis may help us better understand the role that genes play in the development and progression of cardiac end-organ damage in African Americans. This is particularly important given the current racial disparity in left ventricular hypertrophy and dysfunction (both of which are predictors of cardiovascular morbidity and mortality). Findings in this study warrant further investigation, including replication analysis in much larger samples and identification of potential biological mechanisms explaining the association of these variants with phenotypic findings on cardiac imaging.