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Genetics of coronary artery calcification among African Americans, a meta-analysis.

Wojczynski MK, Li M, Bielak LF, Kerr KF, Reiner AP, Wong ND, Yanek LR, Qu L, White CC, Lange LA, Ferguson JF, He J, Young T, Mosley TH, Smith JA, Kral BG, Guo X, Wong Q, Ganesh SK, Heckbert SR, Griswold ME, O'Leary DH, Budoff M, Carr JJ, Taylor HA, Bluemke DA, Demissie S, Hwang SJ, Paltoo DN, Polak JF, Psaty BM, Becker DM, Province MA, Post WS, O'Donnell CJ, Wilson JG, Harris TB, Kavousi M, Cupples LA, Rotter JI, Fornage M, Becker LC, Peyser PA, Borecki IB, Reilly MP - BMC Med. Genet. (2013)

Bottom Line: We assembled the largest AA data resource currently available with measured CAC to identify associated genetic variants.While we observed substantial heritability for CAC in AA, we failed to identify loci for CAC at genome-wide significant levels despite having adequate power to detect alleles with moderate to large effects.Although suggestive signals in AA were apparent at 9p21 and additional CAC and CAD EA loci, overall the data suggest that even larger samples and an ethnic specific focus will be required for GWAS discoveries for CAC in AA populations.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA. mwojczynski@wustl.edu

ABSTRACT

Background: Coronary heart disease (CHD) is the major cause of death in the United States. Coronary artery calcification (CAC) scores are independent predictors of CHD. African Americans (AA) have higher rates of CHD but are less well-studied in genomic studies. We assembled the largest AA data resource currently available with measured CAC to identify associated genetic variants.

Methods: We analyzed log transformed CAC quantity (ln(CAC + 1)), for association with ~2.5 million single nucleotide polymorphisms (SNPs) and performed an inverse-variance weighted meta-analysis on results for 5,823 AA from 8 studies. Heritability was calculated using family studies. The most significant SNPs among AAs were evaluated in European Ancestry (EA) CAC data; conversely, the significance of published SNPs for CAC/CHD in EA was queried within our AA meta-analysis.

Results: Heritability of CAC was lower in AA (~30%) than previously reported for EA (~50%). No SNP reached genome wide significance (p < 5E-08). Of 67 SNPs with p < 1E-05 in AA there was no evidence of association in EA CAC data. Four SNPs in regions previously implicated in CAC/CHD (at 9p21 and PHACTR1) in EA reached nominal significance for CAC in AA, with concordant direction. Among AA, rs16905644 (p = 4.08E-05) had the strongest association in the 9p21 region.

Conclusions: While we observed substantial heritability for CAC in AA, we failed to identify loci for CAC at genome-wide significant levels despite having adequate power to detect alleles with moderate to large effects. Although suggestive signals in AA were apparent at 9p21 and additional CAC and CAD EA loci, overall the data suggest that even larger samples and an ethnic specific focus will be required for GWAS discoveries for CAC in AA populations.

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Power curves. Power curves calculated using QUANTO [32,33] software, as described in the text. In brief, we specified a quantitative outcome, assumed an additive genetic model and used an effective sample size of 5,186 with the estimated mean and standard deviation of ln(CAC + 1). Allelic frequency variation did not affect the power estimates. We characterized the effect size as r2.
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Figure 1: Power curves. Power curves calculated using QUANTO [32,33] software, as described in the text. In brief, we specified a quantitative outcome, assumed an additive genetic model and used an effective sample size of 5,186 with the estimated mean and standard deviation of ln(CAC + 1). Allelic frequency variation did not affect the power estimates. We characterized the effect size as r2.

Mentions: We estimated that our sample size of 5,823 represented an effective sample size of 5,186 taking account of the non-independent observations in the family studies. With this sample size, we had 80% power to detect a genetic variant accounting for as little as 0.77% of the variance in CAC quantity with genome-wide significance and as little as 0.15% with nominal significance (p <0.05) (Figure 1). Our sample had >80% power to detect a variant with comparable effect size to that in 9p21 associated with CAC in EA (effect size = 0.009, or 0.9%; unpublished data, 2012). Thus, our AA CAC study was adequately powered to detect effect sizes comparable to those observed for the top associated SNPs in the EA GWAS of CAC. However lower allele frequencies in African descent samples could lead to a lower overall effect size, even if the effect of the allele is the same as in European samples.


Genetics of coronary artery calcification among African Americans, a meta-analysis.

Wojczynski MK, Li M, Bielak LF, Kerr KF, Reiner AP, Wong ND, Yanek LR, Qu L, White CC, Lange LA, Ferguson JF, He J, Young T, Mosley TH, Smith JA, Kral BG, Guo X, Wong Q, Ganesh SK, Heckbert SR, Griswold ME, O'Leary DH, Budoff M, Carr JJ, Taylor HA, Bluemke DA, Demissie S, Hwang SJ, Paltoo DN, Polak JF, Psaty BM, Becker DM, Province MA, Post WS, O'Donnell CJ, Wilson JG, Harris TB, Kavousi M, Cupples LA, Rotter JI, Fornage M, Becker LC, Peyser PA, Borecki IB, Reilly MP - BMC Med. Genet. (2013)

Power curves. Power curves calculated using QUANTO [32,33] software, as described in the text. In brief, we specified a quantitative outcome, assumed an additive genetic model and used an effective sample size of 5,186 with the estimated mean and standard deviation of ln(CAC + 1). Allelic frequency variation did not affect the power estimates. We characterized the effect size as r2.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3733595&req=5

Figure 1: Power curves. Power curves calculated using QUANTO [32,33] software, as described in the text. In brief, we specified a quantitative outcome, assumed an additive genetic model and used an effective sample size of 5,186 with the estimated mean and standard deviation of ln(CAC + 1). Allelic frequency variation did not affect the power estimates. We characterized the effect size as r2.
Mentions: We estimated that our sample size of 5,823 represented an effective sample size of 5,186 taking account of the non-independent observations in the family studies. With this sample size, we had 80% power to detect a genetic variant accounting for as little as 0.77% of the variance in CAC quantity with genome-wide significance and as little as 0.15% with nominal significance (p <0.05) (Figure 1). Our sample had >80% power to detect a variant with comparable effect size to that in 9p21 associated with CAC in EA (effect size = 0.009, or 0.9%; unpublished data, 2012). Thus, our AA CAC study was adequately powered to detect effect sizes comparable to those observed for the top associated SNPs in the EA GWAS of CAC. However lower allele frequencies in African descent samples could lead to a lower overall effect size, even if the effect of the allele is the same as in European samples.

Bottom Line: We assembled the largest AA data resource currently available with measured CAC to identify associated genetic variants.While we observed substantial heritability for CAC in AA, we failed to identify loci for CAC at genome-wide significant levels despite having adequate power to detect alleles with moderate to large effects.Although suggestive signals in AA were apparent at 9p21 and additional CAC and CAD EA loci, overall the data suggest that even larger samples and an ethnic specific focus will be required for GWAS discoveries for CAC in AA populations.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA. mwojczynski@wustl.edu

ABSTRACT

Background: Coronary heart disease (CHD) is the major cause of death in the United States. Coronary artery calcification (CAC) scores are independent predictors of CHD. African Americans (AA) have higher rates of CHD but are less well-studied in genomic studies. We assembled the largest AA data resource currently available with measured CAC to identify associated genetic variants.

Methods: We analyzed log transformed CAC quantity (ln(CAC + 1)), for association with ~2.5 million single nucleotide polymorphisms (SNPs) and performed an inverse-variance weighted meta-analysis on results for 5,823 AA from 8 studies. Heritability was calculated using family studies. The most significant SNPs among AAs were evaluated in European Ancestry (EA) CAC data; conversely, the significance of published SNPs for CAC/CHD in EA was queried within our AA meta-analysis.

Results: Heritability of CAC was lower in AA (~30%) than previously reported for EA (~50%). No SNP reached genome wide significance (p < 5E-08). Of 67 SNPs with p < 1E-05 in AA there was no evidence of association in EA CAC data. Four SNPs in regions previously implicated in CAC/CHD (at 9p21 and PHACTR1) in EA reached nominal significance for CAC in AA, with concordant direction. Among AA, rs16905644 (p = 4.08E-05) had the strongest association in the 9p21 region.

Conclusions: While we observed substantial heritability for CAC in AA, we failed to identify loci for CAC at genome-wide significant levels despite having adequate power to detect alleles with moderate to large effects. Although suggestive signals in AA were apparent at 9p21 and additional CAC and CAD EA loci, overall the data suggest that even larger samples and an ethnic specific focus will be required for GWAS discoveries for CAC in AA populations.

Show MeSH
Related in: MedlinePlus