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Originally Published 17 April 2010
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Genomic Variation Associated With Mortality Among Adults of European and African Ancestry With Heart Failure: The Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium

Alanna C. Morrison, PhD, Janine F. Felix, MD, PhD, L. Adrienne Cupples, PhD, Nicole L. Glazer, PhD, Laura R. Loehr, MD, PhD, Abbas Dehghan, MD, PhD, Serkalem Demissie, PhD, … Show All … , Joshua C. Bis, PhD, Wayne D. Rosamond, PhD, Yurii S. Aulchenko, PhD, Ying A. Wang, PhD, Talin Haritunians, PhD, Aaron R. Folsom, MD, Fernando Rivadeneira, MD, PhD, Emelia J. Benjamin, MD, Thomas Lumley, PhD, David Couper, PhD, Bruno H. Stricker, MD, PhD, Christopher J. O'Donnell, MD, Kenneth M. Rice, PhD, Patricia P. Chang, MD, MHS, Albert Hofman, MD, PhD, Daniel Levy, MD, Jerome I. Rotter, MD, Ervin R. Fox, MD, Andre G. Uitterlinden, PhD, Thomas J. Wang, MD, Bruce M. Psaty, MD, PhD, James T. Willerson, MD, Cornelia M. van Duijn, PhD, Eric Boerwinkle, PhD, Jacqueline C.M. Witteman, PhD, Ramachandran S. Vasan, MD, and Nicholas L. Smith, PhDAuthor Info & Affiliations
Circulation: Cardiovascular Genetics
Volume 3, Number 3
https://doi.org/10.1161/CIRCGENETICS.109.895995
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Abstract

Background—

Prognosis and survival are significant concerns for individuals with heart failure (HF). To better understand the pathophysiology of HF prognosis, the association between 2 366 858 single-nucleotide polymorphisms (SNPs) and all-cause mortality was evaluated among individuals with incident HF from 4 community-based prospective cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study.

Methods and Results—

Participants were 2526 individuals of European ancestry and 466 individuals of African ancestry who experienced an incident HF event during follow-up in the respective cohorts. Within each study, the association between genetic variants and time to mortality among individuals with HF was assessed by Cox proportional hazards models that included adjustment for sex and age at the time of the HF event. Prospective fixed-effect meta-analyses were conducted for the 4 study populations of European ancestry (N=1645 deaths) and for the 2 populations of African ancestry (N=281 deaths). Genome-wide significance was set at P=5.0×10−7. Meta-analytic findings among individuals of European ancestry revealed 1 genome-wide significant locus on chromosome 3p22 in an intron of CKLF-like MARVEL transmembrane domain containing 7 (CMTM7, P=3.2×10−7). Eight additional loci in individuals of European ancestry and 4 loci in individuals of African ancestry were identified by high-signal SNPs (P<1.0×10−5) but did not meet genome-wide significance.

Conclusions—

This study identified a novel locus associated with all-cause mortality among individuals of European ancestry with HF. This finding warrants additional investigation, including replication, in other studies of HF.
Heart failure (HF) is a relatively common chronic condition characterized by the inability of the heart to efficiently pump blood and represents a significant public health burden, affecting nearly 6 million Americans. Prognosis and survival are a significant concern; after HF is diagnosed, 1 in 5 die within 1 year,1 often by sudden cardiac death, which occurs 6 to 9 times more often than in the general population.1,2
Editorial on p 226
Clinical Perspective on p 255
The public health burden of HF and its associated mortality are likely to intensify because of the aging population and an increase in the prevalence of HF risk factors, such as coronary artery disease, obesity, and diabetes. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium includes the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), the Rotterdam Study (RS), and the National Institute of Aging's Iceland Age, Gene/Environment Susceptibility Study.3 The CHARGE consortium provided an opportunity to evaluate genetic factors associated with the prognosis of HF, and the association between genome-wide variation and all-cause mortality was investigated among 2526 incident HF cases of European ancestry and 466 incident HF cases of African ancestry.4

Methods

Design and Study Population

The design for this study is a cohort of individuals with incident HF nested within 4 of the population-based studies (ARIC, CHS, FHS, and RS) of the CHARGE consortium. A detailed description of each cohort study design has been published elsewhere.5–9 Selection of eligible incident HF cases (with available genome-wide scan data) and methodology for genotyping and genotype imputation are published.4 HF cases were identified during 1987–2004 for ARIC, 1989–2007 for CHS, 1988–2006 for FHS, and 1990–2006 for RS. Details regarding HF diagnostic criteria are shown in supplemental Table I.
In brief, eligible participants for these analyses were individuals of European or African ancestry who experienced an incident HF event during follow-up and had genome-wide association data. Identification of incident HF events relied on multiple sources of clinical and administrative data. The approach was similar across the 4 studies and is described in more detail in previously published reports.4,10,11 A total of 2526 incident HF events were identified from 20 926 participants of European ancestry from all 4 cohorts over a weighted average of 11.5 years of follow-up.4 A total of 466 HF events were identified over an average of 13.7 years among 2895 individuals of African ancestry from ARIC and CHS.4 Each study received institutional review board approval, and all participants provided written informed consent for the use of their DNA for research.

Genotyping and Imputation

For the individuals of European ancestry, each study independently imputed their genotype data to ≈2.4 million autosomal single-nucleotide polymorphisms (SNPs) identified in HapMap CEU samples. For this study, imputation genotypes were not determined in ARIC individuals of African ancestry, and genotypes available for analysis were restricted to successfully genotyped SNPs on the Affymetrix 6.0 chip. In CHS individuals of African ancestry, SNP data were imputed using information from HapMap YRI and CEU samples and were then restricted to the same set of SNPs evaluated in ARIC individuals of African ancestry. Imputation results were summarized as an “allele dosage” defined as the expected number of copies of the minor allele at that SNP (a fractional value between 0.0 and 2.0). A ratio of observed versus expected variance of the dosage for each SNP was calculated within each cohort as a measure of imputation quality.

Characteristics of Participants With HF

For these analyses, measures of clinical and demographic characteristics were obtained from the clinical visit preceding HF onset. At in-person visits, clinical measures were collected (annually in CHS from 1989–1999, biennially in the original cohort, and approximately every 4 years in the offspring cohort of FHS, every 3 years in ARIC through 1998, and every 3 years in RS). Measures were taken using standardized methods as specified by each study and included in-person measures of height, weight, systolic and diastolic blood pressure, and total cholesterol. Each study also identified individuals with hypertension, diabetes, or myocardial infarction that occurred before HF diagnosis.

Mortality Ascertainment

Participants were prospectively followed up with in-person visits and telephone contact in most cohorts. Deaths were defined as all-cause mortality. In the ARIC study, deaths were ascertained through annual phone calls or through ongoing surveillance of health department death certificate files through December 31, 2004. In CHS, participant mortality was identified at 6-month surveillance contacts, National Death Index searches, and from obituaries through June 30, 2007. Additional information about cause of death was collected from death certificates, proxy interviews, and medical records.11 In the RS, deaths were ascertained through general practitioner medical records and from municipal records through January 1, 2007. All FHS participants are under continuous surveillance based on periodic Heart Study visits and biannual health history updates. Information on death (and cause of death) is obtained from hospitalization records, medical records, death certificate, family members, and obituaries. All deaths are reviewed by an end points adjudication panel consisting of 3 FHS physicians. The mortality ascertainment rate for each cohort is >99%.

Statistical Analyses

The association between genomic variation and time to death among individuals with incident HF was evaluated separately in each cohort by Cox proportional hazards models. The follow-up time interval was defined as the time between the date of incident HF and the date of death, last contact if lost to follow-up, or the end of follow-up, whichever came first. Each model was evaluated separately in individuals with HF of European or African ancestry and included adjustment for sex and age at the time of the HF event. In addition, CHS adjusted for study site, and FHS adjusted for generation and ancestry using principal components.12 ARIC and RS did not include additional adjustments in the analysis model. All SNPs were evaluated for association under an additive genetic model.
Across the 4 study populations of European ancestry and separately the 2 populations of African ancestry, fixed-effect meta-analyses combined β-coefficients and study-specific P values using genomic control lambdas to adjust for remaining population substructure. The meta-analysis produced an overall hazards ratio (HR), standard error, and a P value. Before meta-analysis, a filter was applied to SNPs with a β-coefficient >5.0 or <−5.0 to avoid numeric instabilities. Meta-analyses were performed using MetABEL software (http://mga.bionet.nsc.ru/≈yurii/ABEL/)13 and METAL (http://www.sph.umich.edu/csg/abecasis/Metal/index.html) for confirmation. To avoid inaccuracies in the asymptotic assumptions of Cox models when the number of events carrying the variant allele was small (ie, <70 individuals with an end point and carrying the minor allele), SNPs were excluded from further consideration when the postmeta-analysis population size–weighted minor allele frequency (MAF) was ≤0.03 in individuals of European ancestry and ≤0.135 in individuals of African ancestry.
For each ancestry group, a quantile-quantile plot was generated from Cox proportional hazards models and shows the distribution of the observed and expected P values for all SNPs. Also, meta-analyzed P values were plotted according to location across the 22 autosomes. An a priori threshold of 5.0×10−7 was used to indicate genome-wide significance in the analysis of individuals of European and African ancestry.14 High-signal SNPs had a P value <1.0×10−5 but did not meet genome-wide significance. If more than 1 significant or high-signal SNP clustered at a locus, the SNP with the smallest P value was reported as the locus marker. Regional plots showing detailed linkage disequilibrium and gene location information and forest plots were created for genome-wide significant markers. Additionally, top hits from the meta-analysis in the European and African ancestry populations were compared. The MAFs, HRs, and P values for these markers are reported for each ancestral population.

Results

Among the 2526 participants of European ancestry with incident HF, a total of 1645 deaths from all causes occurred at a weighted average of 3.6 years. A total of 281 deaths occurred among the 466 individuals with incident HF of African ancestry at a weighted average of 3.4 years. Baseline characteristics of cohort participants with incident HF are shown in Table 1. The weighted average age at diagnosis of HF was 77.3 years (range from 44 to 101) among individuals of European ancestry and 70.0 years (range from 46 to 96) among individuals of African ancestry.
Table 1. Characteristics of Individuals With Incident HF Stratified by Study and Ancestral Group
CharacteristicsARICCHSRS EAFHS EA
EAAAEAAA
Individuals with HF, n691331838135748249
Mean age at HF event, y67.365.682.480.979.680.7
Age range, y47 to 8146 to 8166 to 9867 to 9657 to 10144 to 99
Male, %60.140.556.366.748.847.8
Body mass index, kg/m229.531.527.029.727.028.5
Systolic blood pressure, mm Hg132140141144146143
Diastolic blood pressure, mm Hg707769737470
Total cholesterol, mg/dL203209201210252193
Hypertensive,* %58.580.073.585.944.776.3
Diabetic,* %28.753.315.631.917.417.7
Myocardial infarction†, %25.220.20.00.028.127.7
Current smoker, %28.629.98.814.123.110.4
Mean follow-up, y3.93.43.53.33.91.8
One-year mortality rates‡0.120.170.200.200.190.34
All-cause deaths, n32719160690556156
EA indicates European ancestry; and AA, African ancestry.
*
Self-reported history of treated hypertension and diabetes was determined in CHS and FHS. In RS, the definition of hypertension included use of antihypertensive medication and measured blood pressure (systolic blood pressure >=160 mm Hg, diastolic blood pressure >=100), and diabetes was defined by fasting glucose >126 or nonfasting glucose >198, or use of insulin or oral antidiabetics. Measurements of blood pressure and blood glucose were also used for the diagnosis of hypertension and diabetes in FHS, using standardized criteria. In the ARIC study, the definition of hypertension included use of antihypertensive medication and measured blood pressure (systolic blood pressure ≤140 mm Hg, diastolic blood pressure ≤90 mm Hg), and diabetes was defined by a fasting glucose level ≤126 mg/dL, a nonfasting glucose level ≤200 mg/dL, or a self-reported diagnosis of diabetes or use of diabetic medication.
†
Myocardial infarction that occurs before HF diagnosis.
‡
Among individuals with heart failure.

Participants of European Ancestry

Figure 1 shows the quantile-quantile plot of P values derived from the ≈2.4 million tests performed in participants of European ancestry plotted against the expected distribution. Except for some of the very lowest P values, the observed and expected distributions of P values were similar. The genomic inflation lambda values for the individual cohorts were 0.95 for CHS, 0.99 for RS, 1.00 for ARIC, and 1.09 for FHS. The meta-analysis genomic inflation lambda value for those of European ancestry was equal to 1.0, suggesting minimal population stratification or other technical artifacts. Figure 2 presents P values for the ≈2.4 million SNPs organized by chromosome and genomic position. As shown in Table 2, 1 SNP (rs12638540, P value=3.21×10−7, HR=1.53, genome-wide confidence interval 1.01 to 2.31, MAF of 0.04) on chromosome 3p22 exceeded the prespecified genome-wide significance threshold. This SNP resides in an intron of CKLF-like MARVEL transmembrane domain containing 7 (CMTM7) and was genotyped in RS and FHS and imputed with high quality in ARIC (observed versus expected variance=0.981) and CHS (observed versus expected variance=0.921). Figure 3 presents detailed information about linkage disequilibrium structure and P values for other SNPs in this region, and a forest plot of the meta-analysis findings is shown in Figure 4.
Figure 1. Plot of the expected and observed −log P values from analyses of participants of European ancestry.
Figure 2. Among participants of European ancestry, the −log P value of the additive genetic model for each SNP with a study size-weighted average MAF of ≥3%, according to location in the 22 autosomal chromosomes. Horizontal line indicates the 5.0×10−7threshold of genome-wide significance.
Table 2. Description of All SNPs by Chromosome and Position With Meta-Analysis P Values <1.0×10−5
PopulationRS No.ChrPositionVariant*MAFPHR (GWAS CI)Closest Gene
EArs12638540332463538A/G0.0433.21×10−71.53 (1.01 to 2.31)CMTM7 (intron)
EArs45286841914212574C/T0.0941.13×10−61.42 (0.99 to 2.03)34.6 kb from LPHN1
EArs21256231529616999C/T0.2851.37×10−60.81 (0.65 to 1.01)OTUD7A (intron)
EArs796544512130428856G/A0.0981.68×10−61.30 (0.99 to 1.72)11.9 kb from LOC338797
EArs1242252112130426315T/C0.0991.78×10−61.30 (0.99 to 1.72)9.4 kb from LOC338797
EArs1242297312130430537G/C0.0971.80×10−61.30 (0.99 to 1.72)13.6 kb from LOC338797
EArs729937412130428360G/T0.0991.86×10−61.30 (0.99 to 1.72)11.4 kb from LOC338797
EArs797725112130436978C/T0.0952.22×10−61.30 (0.98 to 1.73)20.0 kb from LOC338797
EArs797650412130437027G/A0.0952.38×10−61.31 (0.98 to 1.73)20.1 kb from LOC338797
EArs648665812130432243C/T0.0972.94×10−61.29 (0.98 to 1.70)15.3 kb from LOC338797
EArs76879214177096020A/T0.0393.74×10−61.77 (0.95 to 3.28)†GPM6A (intron)
EArs71204891112425973G/A0.0696.94×10−61.35 (0.96 to 1.90)PARVA (intron)
EArs49799061079114759A/G0.1867.13×10−61.23 (0.98 to 1.55)46.6 kb from KCNMA1
EArs171596407111873569A/T0.0488.52×10−61.59 (0.94 to 2.68)IFRD1 (intron)
EArs98854135110204027G/T0.0659.76×10−61.34 (0.96 to 1.87)77.6 kb from SLC25A46
AArs6868223533672351G/A0.3381.78×10−61.58 (0.98 to 2.56)ADAMTS12 (intron)
AArs127338561219618162C/A0.3822.86×10−61.56 (0.97 to 2.51)42.0 kb from LOC400804
AArs80174231489749663T/C0.3767.02×10−60.61 (0.36 to 1.06)27.7 kb from KCNK13
AArs7690441489740891A/G0.3729.52×10−60.62 (0.36 to 1.07)18.9 kb from KCNK13
AArs65730131454805626G/T0.1419.64×10−61.74 (0.93 to 3.26)2.2 kb from FBXO34
HR for the minor allele from the additive genetic model is given. EA indicates European ancestry; AA, African ancestry; Chr, chromosome; and GWAS CI, CI for alpha=5.0×10−7.
*
Major/minor allele.
†
Only in CHS, RS, and FHS.
Figure 3. Regional association plot for the genome-wide significant marker, rs12638540, in individuals of European ancestry. The top marker is presented in black font and neighboring variants are presented in different colors based on linkage disequilibrium: yellow, r2≥0.2 and <0.5; and white, r2<0.2. There were no SNPs in the area with linkage disequilibrium ≥0.5 with the top marker.
Figure 4. Meta-analysis and study-specific HRs and CI (α=5.0×10−7) for rs12638540 associated with all-cause mortality in individuals of European ancestry.
In addition to the 1 SNP exceeding genome-wide significance, 14 additional high-signal SNPs were identified with P values <1.0×10−5 that marked 8 chromosomal regions of interest. Table 2 provides details about those loci identified in individuals of European ancestry. Of these 8 loci, the ovarian tumor (OTU) domain containing 7A (OTUD7A), glycoprotein M6A (GPM6A), alpha parvin (PARVA), and interferon-related developmental regulator 1 (IFRD1) genes were identified by a single intronic SNP. An intergenic SNP on chromosome 19 was 34.6 kb from the latrophilin 1 (LPHN1) gene. An intergenic SNP on chromosome 10 was 46.6 kb from the potassium large conductance calcium-activated channel, subfamily M, alpha member 1 (KCNMA1) gene, and an intergenic SNP on chromosome 5 was 77.6 kb from the solute carrier family 25, member 46 (SLC25A46) gene. An intergenic region on chromosome 12 was also identified. Cohort-specific results for the index markers for each locus are provided in supplemental Table II.

Participants of African Ancestry

Figure 5 shows the quantile-quantile plot of P values derived from the 560 383 tests performed in participants of African ancestry. Except for some of the very lowest P values, the observed and expected distributions of P values were similar. Figure 6 presents all P values organized by chromosome and genomic position. In individuals of African ancestry with incident HF, no SNP exceeded the prespecified genome-wide significance threshold for an association with mortality. Five high-signal SNPs were identified with P values <1.0×10−5 that marked 4 loci of interest (Table 2). The smallest P value among individuals of African ancestry was for an intronic SNP in the a disintegrin and metalloproteinase with thrombospondin type 1 motif, 12 (ADAM) metallopeptidase with thrombospondin type 1 motif, 12 (ADAMTS12) gene. Two SNPs were within 27.7 kb from the potassium channel, subfamily K, member 13 (KCNK13) gene, and 1 SNP was in the promoter region of F-box protein 34 (FBXO34). An additional intergenic SNP was >100 kb from a known gene on chromosome 1. Cohort-specific results are provided in supplemental Table II.
Figure 5. Plot of the expected and observed −log P values from analyses of participants of African ancestry.
Figure 6. Among participants of African ancestry, the −log P value of the additive genetic model for each SNP with a study size-weighted average MAF of ≥13.5%, according to location in the 22 autosomal chromosomes. Horizontal line indicates the 5.0×10−7 threshold of genome-wide significance.

Cross-Ancestry Comparisons

None of the loci identified in the African ancestry analysis were associated with mortality in individuals with HF of European ancestry (all P values >0.05). The genome-wide significant and high-signal SNPs among individuals of European ancestry were not associated with mortality among African ancestry CHS participants (all P values >0.05). These SNPs were only imputed and evaluated for an association in CHS participants of African ancestry and were not imputed in individuals of African ancestry from the ARIC study. The MAF for rs12638540 is 0.07 in CHS individuals with HF of African ancestry.

Discussion

This study evaluated the association between genome-wide genetic variation and all-cause mortality among individuals with incident HF. The meta-analysis included 2526 individuals of European ancestry with HF and revealed an intronic SNP in CMTM7 on chromosome 3 that exceeded genome-wide significance and was associated with a 53% increase in risk of death. Approximately 8% of the HF population carried this variant. Among African ancestry participants, no SNP had a P value that exceeded genome-wide significance. Additional high-signal SNPs identified in either the European or African ancestry populations were in or close to LPHN1, OTUD7A, GPM6A, PARVA, KCNMA1, IFRD1, SLC25A46, ADAMTS12, KCNK13, and FBXO34 (P value range between 1.10×10−6 and 9.64×10−6). Regions of the genome without known genes also identified in these analyses reside on chromosome 1q41 and 12q24. SNPs identified in a genome-wide association study (GWAS) for incident HF4 did not overlap with those identified here.
The genome-wide significant association was for CMTM7, 1 of several chemokine-like factor genes clustered in the same region on chromosome 3p22. The protein encoded by CMTM7 is highly expressed in leukocytes and is also expressed in the heart, but its function is unknown. A recent study indicates that chemokine receptor gene expression is upregulated among patients with HF compared with controls.15 The CMTM7 chemokine-like factor may act as a chemoattractant to guide migration of cells in the heart. Some chemokines play a role as a proinflammatory marker in the context of an immune response or may promote angiogenesis during HF.
Of the 12 loci that did not meet genome-wide significance, 4 merit further discussion. The observed association with OTUD7A in individuals of European ancestry and the association with FBXO34 in individuals of African ancestry suggest that these genes may play a role in HF progression and survival by contributing to inadequate degradation of ubiquitin-protein conjugates and resulting in autophagic myocyte death. A mouse model for desmin-related cardiomyopathy indicates that accumulation of polyubiquitinated proteins is correlated with hastened HF progression.16 Other studies show that ubiquitinated proteins accumulate in the cytosol of human hearts with idiopathic or ischemic cardiomyopathies.17,18 The observed association with potassium channels encoded by KCNMA1 in individuals of European ancestry and KCNK13 in individuals of African ancestry provides evidence that control of vascular tone and regulation of the contraction of cardiac smooth muscle may be important components of HF progression and survival. Substantial previous work has documented that potassium channels are associated with cardiovascular and mortality end points.19–24
Although there was not a consistent finding for a particular SNP across the European and African ancestry populations, genes involved in deubiquitinating activity and genes encoding potassium channels were identified in each ethnic group. It is important to note that for many loci, there was a clear difference in the MAF between ethnic groups. This difference in MAF coupled with variable patterns of linkage disequilibrium between the populations obfuscates the interpretability of cross-ancestral comparisons. In addition, it is known that certain HF treatments affect length of survival with HF, and access to care and treatment practices are known to vary by region and ethnicity.25,26

Study Strengths and Limitations

Although this is the largest study to date of individuals with incident HF evaluated for an association between genome-wide genetic variation and all-cause mortality, there are study limitations also. SNP imputation in individuals of European ancestry resulted in the ability to meta-analyze results across ≈2.4 million SNPs. Given 2.4 million tests, 1 significant SNP is what would have been expected by chance for the a priori level of genome-wide significance and only 1 SNP exceeded this threshold in individuals of European ancestry. This finding may represent a false-positive result and requires replication in other studies. Similarly, the number of high-signal loci identified in either ancestry groups was far fewer than would be expected by chance given a threshold of P=1.0×10−5.
For some variants, imputation quality varied, and there was reduced statistical power to detect an association for poorly imputed SNPs. Cross-ancestry comparisons were limited to data from CHS individuals of African ancestry, and the overall statistical power to detect an association was limited in African ancestry participants given a total sample of 466 individuals.
Because of limited data availability across the cohorts, this study did not account for ejection fraction, treatment for HF, socioeconomic status, access to medical care, or hospitalizations subsequent to HF diagnosis. Heterogeneity among the individuals investigated for this study may have resulted from variation in HF diagnostic criteria across the 4 studies. However, a study comparing diagnostic criteria between CHS and FHS showed that all-cause mortality rates were similar across these diagnostic classifications.27 A study evaluating HF diagnosis by central adjudication compared with hospital discharge diagnoses showed that mortality rates are similar.28 A limitation of this study is that, given differences in diagnostic criteria, the HF cases may not represent the same disease. Because the 4 study populations likely comprise both systolic and diastolic HF, it is important to note that the cause of death may be markedly different between these 2 disease states. This study addressed all-cause mortality, and there was lack of information across cohorts to adequately conduct analyses of cause-specific mortality.
Finally, the observed signals are described in the context of the nearest gene; however, it is possible that true causal variants may be in neighboring genes or intergenic regions. Additional signals may have been missed because of coverage in particular genomic regions or the lack of statistical power to detect modest effects.

Conclusions

This study investigated 2526 incident HF cases of European ancestry from ARIC, CHS, FHS, and RS and 466 incident HF cases of African ancestry from ARIC and CHS for an association between genome-wide variation and all-cause mortality. One SNP in CMTM7 was significantly associated with all-cause mortality in individuals of European ancestry with HF, suggesting a role of chemokines with survival. However, no SNP was found to be significantly associated with mortality in individuals with HF of African ancestry. Future studies of this type, especially those that address some of the limitations of this study, may identify genes that lead to an improved understanding of HF pathophysiology and treatment of the disease. These findings warrant additional investigation, including replication, in other studies of HF.

Acknowledgments

The Rotterdam Study thanks the staff and participants of the ARIC study for their important contributions. We thank Mila Jhamai, Pascal Arp, Dr Michael J. Moorhouse, Marijn Verkerk, and Sander Bervoets for their help in creating the database and Maxim Struchalin for his contributions to the imputations of the data. We acknowledge the essential role of the CHARGE Consortium in development and support of this manuscript. CHARGE members include ARIC, CHS, FHS, RS, and Age, Gene/Environment Susceptibility. The funding sources had no role in the study design, analyses, or drafting of the manuscript. The National Heart, Lung, and Blood Institute reviews all manuscripts submitted for publication, but it was not involved in the decision to publish.

Clinical Perspective

This study investigated 2526 incident heart failure (HF) cases of European ancestry and 466 incident HF cases of African ancestry for an association between genome-wide variation and all-cause mortality. One variant in the CKLF-like MARVEL transmembrane domain containing 7 (CMTM7) genes was significantly associated with all-cause mortality in individuals of European ancestry with HF. CMTM7 is 1 of several chemokine-like factor genes clustered in the same region on chromosome 3p22. These results suggest that chemokines may play a role in survival of patients with HF. No genomic variation was significantly associated with mortality in individuals with HF of African ancestry. Future studies of this type may identify genes that lead to an improved understanding of HF pathophysiology and treatment of the disease. These findings warrant additional investigation, including replication, in other studies of HF.

Supplemental Material

File (895995_supplemental_material.pdf)

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Go to Circulation: Cardiovascular Genetics
Circulation: Cardiovascular Genetics
Volume 3 • Number 3 • June 2010
Pages: 248 - 255

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© 2010 American Heart Association, Inc.

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History

Received: 20 July 2009
Accepted: 16 March 2010
Published online: 17 April 2010
Published in print: June 2010

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Keywords

  1. heart failure
  2. all-cause mortality
  3. genetics
  4. genome-wide variation
  5. mortality

Subjects

  1. Congenital Heart Disease
  2. Epidemiology
  3. Genetics
  4. Omics

Authors

Affiliations

Alanna C. Morrison, PhD
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Janine F. Felix, MD, PhD
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L. Adrienne Cupples, PhD
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Laura R. Loehr, MD, PhD
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Abbas Dehghan, MD, PhD
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Serkalem Demissie, PhD
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Wayne D. Rosamond, PhD
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Yurii S. Aulchenko, PhD
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Talin Haritunians, PhD
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Fernando Rivadeneira, MD, PhD
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Emelia J. Benjamin, MD
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Bruno H. Stricker, MD, PhD
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Christopher J. O'Donnell, MD
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Patricia P. Chang, MD, MHS
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Albert Hofman, MD, PhD
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Andre G. Uitterlinden, PhD
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Bruce M. Psaty, MD, PhD
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James T. Willerson, MD
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Cornelia M. van Duijn, PhD
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Jacqueline C.M. Witteman, PhD
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Ramachandran S. Vasan, MD
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Nicholas L. Smith, PhD
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Atherosclerosis Risk in Communities Study: University of Texas Health Science Center at Houston (A.C.M., E.B., J.T.W.), Tex; Departments of Medicine ( P.P.C.), Biostatistics (D.C.), and Epidemiology (W.R.), University of North Carolina at Chapel Hill, Nature Institute of Environmental Health Sciences (L.R.L., W.R.), Research Triangle Park, NC; Division of Epidemiology and Community Health, School of Public Health (A.F.), University of Minnesota, Minneapolis; Department of Medicine (E.R.F.), University of Mississippi Medical Center; Nature Heart, Lung, and Blood Institute Jackson Heart Study (E.R.F.); Texas Heart Institute (J.T.W.), Houston.
Rotterdam Study: Departments of Epidemiology (J.F.F., A.D., Y.S.A., B.H.S., A.H., C.M.v.D., J.C.M.W.) and Internal Medicine (F.R., A.G.U.), Erasmus Medical Center, Rotterdam, The Netherlands and Netherlands Consortium for Healthy Aging, Leiden, The Netherlands (J.F.F., J.C.M.W.).
Framingham Heart Study: Department of Biostatistics (L.A.C., S.D., Y.A.W.), Boston University School of Public Health and Department of Medicine and Preventive Medicine (E.J.B., R.S.V.), Boston University School of Medicine, Boston University, Boston, Mass; National Heart Lung Blood Institute's Framingham Heart Study (L.A.C., E.J.B., C.O.D., D.L., R.S.V.); Department of Epidemiology (R.S.V.), Boston University School of Public Health, Boston University, Boston, Mass; National Heart Lung Blood Institute (C.O.D., D.L.); and Massachusetts General Hospital (C.O.D., T.J.W.), Harvard Medical School.
Cardiovascular Health Study: Departments of Epidemiology (N.L.S., B.M.P.), Medicine (N.L.G., J.C.B., B.M.P.), Biostatistics (T.L., K.M.R.), and Health Services (B.M.P.) University of Washington, Seattle, Wash; Seattle Epidemiologic Research and Information Center of the Department of Veterans Affairs Office of Research and Development, Seattle, Wash (N.L.S.); Group Health Research Institute (N.L.S., B.M.P.), Group Health, Seattle, Wash; and Medical Genetics Institute (T.H., J.I.R.), Cedars-Sinai Medical Center, Los Angeles, Calif.

Notes

Guest Editor for this article was Barbara V. Howard, PhD.
Drs Morrison, Felix, Cupples, Glazer, Boerwinkle, Witteman, Vasan, and Smith contributed equally to this work.
Correspondence to Alanna C. Morrison, PhD, Human Genetics Center, University of Texas at Houston Health Science Center, 1200 Herman Pressler, Suite 453E, Houston, TX 77030. E-mail [email protected]

Funding Information

Sources of Funding
The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute (N01-HC-55015, N01-HC-55016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC-55021, N01-HC-55022, R01HL087641, R01HL59367, and R01HL086694); National Human Genome Research Institute (U01HG004402); and National Institutes of Health (HHSN268200625226C). Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. This research was supported in part by the intramural research program of the National Institutes of Health, National Institutes of Environmental Health Sciences. The Cardiovascular Health Study is supported by contract numbers N01-HC-85079 through N01-HC-85086, N01-HC-35129, N01 HC-15103, N01 HC-55222, N01-HC-75150, N01-HC-45133, grant numbers U01 HL080295, and R01 HL 087652 from National Heart Lung and Blood Institute with additional contribution from the National Institute of Neurological Disorders and Stroke. A full list of principal Cardiovascular Health Study investigators and institutions can be found at http://www.chs-nhlbi.org/pi.htm. DNA handling and genotyping was supported in part by National Center for Research Resources grant M01RR00425-39 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. The Framingham Heart Study was supported by National Heart Lung and Blood Institute (Contract No. N01-HC-25195) and its contract with Affymetrix, Inc for genotyping services (Contract No. N02-HL-6–4278). This work was also supported in part by grants from the National Heart Lung Blood Institute 2K24HL04334, R01HL077477, and R01HL093328 (all to Dr Vasan). This study is based on analyses by Framingham Heart Study investigators participating in the SNP Health Association Resource project. The Rotterdam Study is supported by the Erasmus Medical Center and Erasmus University Rotterdam; the Netherlands Organization for Scientific Research; the Netherlands Organization for Health Research and Development; the Research Institute for Diseases in the Elderly; The Netherlands Heart Foundation; the Ministry of Health, Welfare and Sports; the Ministry of Education, Culture and Science; the European Commission (DG XII); and the Municipality of Rotterdam. Abbas Dehghan and Janine Felix are supported by a VICI grant from the Netherlands Organization for Scientific Research (NWO) no. 918-76-619. The GWAS database of the Rotterdam study was funded through Netherlands Organization for Scientific Research (175.010.2005.011, 911.03.012) and Research Institute for Diseases in the Elderly. This study was supported by the Netherlands Genomics Initiative/Netherlands Organization for Scientific Research, project number 050-60-810.
Disclosures
None.

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Genomic Variation Associated With Mortality Among Adults of European and African Ancestry With Heart Failure
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