A genome-wide association study for blood lipid phenotypes in the Framingham Heart Study

被引:224
作者
Kathiresan, Sekar [1 ]
Manning, Alisa K.
Demissie, Serkalem
D'Agostino, Ralph B.
Surti, Aarti
Guiducci, Candace
Gianniny, Lauren
Burtt, Noeel P.
Melander, Olle
Orho-Melander, Marju
Arnett, Donna K.
Peloso, Gina M.
Ordovas, Jose M.
Cupples, L. Adrienne
机构
[1] Framingham Heart Dis Epidemiol Study, NHLBI, Framingham, MA 01702 USA
[2] Harvard Univ, Cambridge, MA 02138 USA
[3] MIT, Broad Inst, Cambridge, MA 02139 USA
[4] Harvard Univ, Massachusetts Gen Hosp, Sch Med, Cardiovasc Dis Prevent Ctr,Cardiol Div, Boston, MA 02115 USA
[5] Boston Univ, Sch Publ Hlth, Boston, MA 02215 USA
[6] Boston Univ, Dept Math & Stat, Boston, MA 02215 USA
[7] Lund Univ, Malmo Univ Hosp, Dept Clin Sci, Malmo, Sweden
[8] Univ Alabama Birmingham, Dept Epidemiol, Birmingham, AL USA
[9] Tufts Univ, Jean Mayer USDA Human Nutr Res Ctr, Nutr & Genom Lab, Boston, MA 02111 USA
来源
BMC MEDICAL GENETICS | 2007年 / 8卷
关键词
D O I
10.1186/1471-2350-8-S1-S17
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Background: Blood lipid levels including low-density lipoprotein cholesterol ( LDL-C), high-density lipoprotein cholesterol ( HDL-C), and triglycerides ( TG) are highly heritable. Genome-wide association is a promising approach to map genetic loci related to these heritable phenotypes. Methods: In 1087 Framingham Heart Study Offspring cohort participants ( mean age 47 years, 52% women), we conducted genome-wide analyses ( Affymetrix 100K GeneChip) for fasting blood lipid traits. Total cholesterol, HDL-C, and TG were measured by standard enzymatic methods and LDL-C was calculated using the Friedewald formula. The long-term averages of up to seven measurements of LDL-C, HDL-C, and TG over a similar to 30 year span were the primary phenotypes. We used generalized estimating equations ( GEE), family-based association tests ( FBAT) and variance components linkage to investigate the relationships between SNPs ( on autosomes, with minor allele frequency >= 10%, genotypic call rate >= 80%, and Hardy-Weinberg equilibrium p >= 0.001) and multivariable-adjusted residuals. We pursued a three-stage replication strategy of the GEE association results with 287 SNPs ( P < 0.001 in Stage I) tested in Stage II ( n similar to 1450 individuals) and 40 SNPs ( P < 0.001 in joint analysis of Stages I and II) tested in Stage III ( n similar to 6650 individuals). Results: Long-term averages of LDL-C, HDL-C, and TG were highly heritable ( h(2) = 0.66, 0.69, 0.58, respectively; each P < 0.0001). Of 70,987 tests for each of the phenotypes, two SNPs had p < 10(-5) in GEE results for LDL-C, four for HDL-C, and one for TG. For each multivariable-adjusted phenotype, the number of SNPs with association p < 10(-4) ranged from 13 to 18 and with p < 10(-3), from 94 to 149. Some results confirmed previously reported associations with candidate genes including variation in the lipoprotein lipase gene ( LPL) and HDL-C and TG ( rs7007797; P = 0.0005 for HDL-C and 0.002 for TG). The full set of GEE, FBAT and linkage results are posted at the database of Genotype and Phenotype (dbGaP). After three stages of replication, there was no convincing statistical evidence for association ( i.e., combined P < 10(-5) across all three stages) between any of the tested SNPs and lipid phenotypes. Conclusion: Using a 100K genome-wide scan, we have generated a set of putative associations for common sequence variants and lipid phenotypes. Validation of selected hypotheses in additional samples did not identify any new loci underlying variability in blood lipids. Lack of replication may be due to inadequate statistical power to detect modest quantitative trait locus effects ( i.e., < 1% of trait variance explained) or reduced genomic coverage of the 100K array. GWAS in FHS using a denser genome-wide genotyping platform and a better-powered replication strategy may identify novel loci underlying blood lipids.
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