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Evaluation of genetic risk scores for lipid levels using genome-wide markers in the Framingham Heart Study.

ABSTRACT: BACKGROUND:Multiple single-nucleotide polymorphisms have been associated with low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels. In this paper, we evaluate a weighted and an unweighted approach for estimating the combined effect of multiple markers (using genotypes and haplotypes) on lipid levels for a given individual. METHODS:Using data from the Framingham Heart Study SHARe genome-wide association study, we tested genome-wide genotypes and haplotypes for association with lipid levels and constructed genetic risk scores (GRS) based on multiple markers that were weighted according to their estimated effects on LDL-C, HDL-C, and TG. These scores (GRS-LDL, GRS-HDL, and GRS-TG) were then evaluated for associations with LDL-C, HDL-C, and TG, and compared with results of an unweighted method based on risk-allele counts. For comparability of metrics, GRS variables were divided into quartiles. RESULTS:GRS-LDL quartiles were associated with LDL-C levels (p = 2.1 x 10-24), GRS-HDL quartiles with HDL-C (p = 5.9 x 10-22), and GRS-TG quartiles with TG (p = 5.4 x 10-25). In comparison, these p-values were considerably lower than those for the associations of the unweighted GRS quartiles for LDL-C (p = 3.6 x 10-7), HDL-C (p = 6.4 x 10-16), and TG (p = 4.1 x 10-10). CONCLUSION:GRS variables were highly predictive of LDL-C, HDL-C, and TG measurements, especially when weighted based on each marker's individual association with those intermediate risk phenotypes. The allele-count GRS approach that does not weight the GRS by individual marker associations was considerably less predictive of lipid and lipoprotein measures when the same genetic markers were utilized, suggesting that substantially more risk-associated genetic marker information is encapsulated by the weighted GRS variables.

SUBMITTER: Piccolo SR

PROVIDER: S-EPMC2795945 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

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Evaluation of genetic risk scores for lipid levels using genome-wide markers in the Framingham Heart Study.

Piccolo Stephen R SR Abo Ryan P RP Allen-Brady Kristina K Camp Nicola J NJ Knight Stacey S Anderson Jeffrey L JL Horne Benjamin D BD

BMC proceedings 20091215

<h4>Background</h4>Multiple single-nucleotide polymorphisms have been associated with low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels. In this paper, we evaluate a weighted and an unweighted approach for estimating the combined effect of multiple markers (using genotypes and haplotypes) on lipid levels for a given individual.<h4>Methods</h4>Using data from the Framingham Heart Study SHARe genome-wide association study, we te ...[more]

PMID: 20018038

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Project description: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.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 approximately 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 > or =10%, genotypic call rate > or =80%, and Hardy-Weinberg equilibrium p > or = 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 approximately 1450 individuals) and 40 SNPs (P < 0.001 in joint analysis of Stages I and II) tested in Stage III (n approximately 6650 individuals).Long-term averages of LDL-C, HDL-C, and TG were highly heritable (h2 = 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.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.

Project description:Pulmonary function measures obtained by spirometry are used to diagnose chronic obstructive pulmonary disease (COPD) and are highly heritable. We conducted genome-wide association (GWA) analyses (Affymetrix 100K SNP GeneChip) for measures of lung function in the Framingham Heart Study.Ten spirometry phenotypes including percent of predicted measures, mean spirometry measures over two examinations, and rates of change based on forced expiratory volume in one second (FEV1), forced vital capacity (FVC), forced expiratory flow from the 25th to 75th percentile (FEF25-75), the FEV1/FVC ratio, and the FEF25-75/FVC ratio were examined. Percent predicted phenotypes were created using each participant's latest exam with spirometry. Predicted lung function was estimated using models defined in the set of healthy never-smokers, and standardized residuals of percent predicted measures were created adjusting for smoking status, pack-years, and body mass index (BMI). All modeling was performed stratified by sex and cohort. Mean spirometry phenotypes were created using data from two examinations and adjusting for age, BMI, height, smoking and pack-years. Change in pulmonary function over time was studied using two to four examinations with spirometry to calculate slopes, which were then adjusted for age, height, smoking and pack-years.Analyses were restricted to 70,987 autosomal SNPs with minor allele frequency > or = 10%, genotype call rate > or = 80%, and Hardy-Weinberg equilibrium p-value > or = 0.001. A SNP in the interleukin 6 receptor (IL6R) on chromosome 1 was among the best results for percent predicted FEF25-75. A non-synonymous coding SNP in glutathione S-transferase omega 2 (GSTO2) on chromosome 10 had top-ranked results studying the mean FEV1 and FVC measurements from two examinations. SNPs nearby the SOD3 and vitamin D binding protein genes, candidate genes for COPD, exhibited association to percent predicted phenotypes.GSTO2 and IL6R are credible candidate genes for association to pulmonary function identified by GWA. These and other observed associations warrant replication studies. This resource of GWA results for pulmonary function measures is publicly available at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite.

Project description:BACKGROUND: Cholesterol concentrations in blood are related to cardiovascular diseases. Recent genome-wide association studies (GWAS) of cholesterol levels identified a number of single-locus effects on total cholesterol (TC) and high-density lipoprotein cholesterol (HDL-C) levels. Here, we report single-locus and epistasis SNP effects on TC and HDL-C using the Framingham Heart Study (FHS) data. RESULTS: Single-locus effects and pairwise epistasis effects of 432,096 SNP markers were tested for their significance on log-transformed TC and HDL-C levels. Twenty nine additive SNP effects reached single-locus genome-wide significance (p < 7.2 x 10-8) and no dominance effect reached genome-wide significance. Two new gene regions were detected, the RAB3GAP1-R3HDM1-LCT-MCM6 region of chr02 for TC identified by six new SNPs, and the OSBPL8-ZDHHC17 region (chr12) for HDL-C identified by one new SNP. The remaining 22 single-locus SNP effects confirmed previously reported genes or gene regions. For TC, three SNPs identified two gene regions that were tightly linked with previously reported genes associated with TC, including rs599839 that was 10 bases downstream PSRC1 and 3.498 kb downstream CELSR2, rs4970834 in CELSR2, and rs4245791 in ABCG8 that slightly overlapped with ABCG5. For HDL-C, LPL was confirmed by 12 SNPs 8-45 kb downstream, CETP by two SNPs 0.5-11 kb upstream, and the LIPG-ACAA2 region by five SNPs inside this region. Two epistasis effects on TC and thirteen epistasis effects on HDL-C reached the significance of "suggestive linkage". The most significant epistasis effect (p = 5.72 x 10-13) was close to reaching "significant linkage" and was a dominance x dominance effect of HDL-C between LMBRD1 (chr06) and the LRIG3 region (chr12), and this pair of gene regions had six other D x D effects with "suggestive linkage". CONCLUSIONS: Genome-wide association analysis of the FHS data detected two new gene regions with genome-wide significance, detected epistatic SNP effects on TC and HDL-C with the significance of suggestive linkage in seven pairs of gene regions, and confirmed some previously reported gene regions associated with TC and HDL-C.

Project description:BACKGROUND:Systemic biomarkers provide insights into disease pathogenesis, diagnosis, and risk stratification. Many systemic biomarker concentrations are heritable phenotypes. Genome-wide association studies (GWAS) provide mechanisms to investigate the genetic contributions to biomarker variability unconstrained by current knowledge of physiological relations. METHODS:We examined the association of Affymetrix 100K GeneChip single nucleotide polymorphisms (SNPs) to 22 systemic biomarker concentrations in 4 biological domains: inflammation/oxidative stress; natriuretic peptides; liver function; and vitamins. Related members of the Framingham Offspring cohort (n = 1012; mean age 59 +/- 10 years, 51% women) had both phenotype and genotype data (minimum-maximum per phenotype n = 507-1008). We used Generalized Estimating Equations (GEE), Family Based Association Tests (FBAT) and variance components linkage to relate SNPs to multivariable-adjusted biomarker residuals. Autosomal SNPs (n = 70,987) meeting the following criteria were studied: minor allele frequency > or = 10%, call rate > or = 80% and Hardy-Weinberg equilibrium p > or = 0.001. RESULTS:With GEE, 58 SNPs had p < 10(-6): the top SNPs were rs2494250 (p = 1.00*10(-14)) and rs4128725 (p = 3.68*10(-12)) for monocyte chemoattractant protein-1 (MCP1), and rs2794520 (p = 2.83*10(-8)) and rs2808629 (p = 3.19*10(-8)) for C-reactive protein (CRP) averaged from 3 examinations (over about 20 years). With FBAT, 11 SNPs had p < 10(-6): the top SNPs were the same for MCP1 (rs4128725, p = 3.28*10(-8), and rs2494250, p = 3.55*10(-8)), and also included B-type natriuretic peptide (rs437021, p = 1.01*10(-6)) and Vitamin K percent undercarboxylated osteocalcin (rs2052028, p = 1.07*10(-6)). The peak LOD (logarithm of the odds) scores were for MCP1 (4.38, chromosome 1) and CRP (3.28, chromosome 1; previously described) concentrations; of note the 1.5 support interval included the MCP1 and CRP SNPs reported above (GEE model). Previous candidate SNP associations with circulating CRP concentrations were replicated at p < 0.05; the SNPs rs2794520 and rs2808629 are in linkage disequilibrium with previously reported SNPs. GEE, FBAT and linkage results are posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite. CONCLUSION:The Framingham GWAS represents a resource to describe potentially novel genetic influences on systemic biomarker variability. The newly described associations will need to be replicated in other studies.

Project description:BACKGROUND:Cardiovascular disease (CVD) and its most common manifestations--including coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF)--are major causes of morbidity and mortality. In many industrialized countries, cardiovascular disease (CVD) claims more lives each year than any other disease. Heart disease and stroke are the first and third leading causes of death in the United States. Prior investigations have reported several single gene variants associated with CHD, stroke, HF, and AF. We report a community-based genome-wide association study of major CVD outcomes. METHODS:In 1345 Framingham Heart Study participants from the largest 310 pedigrees (54% women, mean age 33 years at entry), we analyzed associations of 70,987 qualifying SNPs (Affymetrix 100K GeneChip) to four major CVD outcomes: major atherosclerotic CVD (n = 142; myocardial infarction, stroke, CHD death), major CHD (n = 118; myocardial infarction, CHD death), AF (n = 151), and HF (n = 73). Participants free of the condition at entry were included in proportional hazards models. We analyzed model-based deviance residuals using generalized estimating equations to test associations between SNP genotypes and traits in additive genetic models restricted to autosomal SNPs with minor allele frequency > or =0.10, genotype call rate > or =0.80, and Hardy-Weinberg equilibrium p-value > or = 0.001. RESULTS:Six associations yielded p < 10(-5). The lowest p-values for each CVD trait were as follows: major CVD, rs499818, p = 6.6 x 10(-6); major CHD, rs2549513, p = 9.7 x 10(-6); AF, rs958546, p = 4.8 x 10(-6); HF: rs740363, p = 8.8 x 10(-6). Of note, we found associations of a 13 Kb region on chromosome 9p21 with major CVD (p 1.7-1.9 x 10(-5)) and major CHD (p 2.5-3.5 x 10(-4)) that confirm associations with CHD in two recently reported genome-wide association studies. Also, rs10501920 in CNTN5 was associated with AF (p = 9.4 x 10(-6)) and HF (p = 1.2 x 10(-4)). Complete results for these phenotypes can be found at the dbgap website http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite. CONCLUSION:No association attained genome-wide significance, but several intriguing findings emerged. Notably, we replicated associations of chromosome 9p21 with major CVD. Additional studies are needed to validate these results. Finding genetic variants associated with CVD may point to novel disease pathways and identify potential targeted preventive therapies.

Project description:Susceptibility to type 2 diabetes may be conferred by genetic variants having modest effects on risk. Genome-wide fixed marker arrays offer a novel approach to detect these variants.We used the Affymetrix 100K SNP array in 1,087 Framingham Offspring Study family members to examine genetic associations with three diabetes-related quantitative glucose traits (fasting plasma glucose (FPG), hemoglobin A1c, 28-yr time-averaged FPG (tFPG)), three insulin traits (fasting insulin, HOMA-insulin resistance, and 0-120 min insulin sensitivity index); and with risk for diabetes. We used additive generalized estimating equations (GEE) and family-based association test (FBAT) models to test associations of SNP genotypes with sex-age-age2-adjusted residual trait values, and Cox survival models to test incident diabetes.We found 415 SNPs associated (at p < 0.001) with at least one of the six quantitative traits in GEE, 242 in FBAT (18 overlapped with GEE for 639 non-overlapping SNPs), and 128 associated with incident diabetes (31 overlapped with the 639) giving 736 non-overlapping SNPs. Of these 736 SNPs, 439 were within 60 kb of a known gene. Additionally, 53 SNPs (of which 42 had r2 < 0.80 with each other) had p < 0.01 for incident diabetes AND (all 3 glucose traits OR all 3 insulin traits, OR 2 glucose traits and 2 insulin traits); of these, 36 overlapped with the 736 other SNPs. Of 100K SNPs, one (rs7100927) was in moderate LD (r2 = 0.50) with TCF7L2 (rs7903146), and was associated with risk of diabetes (Cox p-value 0.007, additive hazard ratio for diabetes = 1.56) and with tFPG (GEE p-value 0.03). There were no common (MAF > 1%) 100K SNPs in LD (r2 > 0.05) with ABCC8 A1369S (rs757110), KCNJ11 E23K (rs5219), or SNPs in CAPN10 or HNFa. PPARG P12A (rs1801282) was not significantly associated with diabetes or related traits.Framingham 100K SNP data is a resource for association tests of known and novel genes with diabetes and related traits posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite. Framingham 100K data replicate the TCF7L2 association with diabetes.

Project description:Heritable electrocardiographic (ECG) and heart rate variability (HRV) measures, reflecting pacemaking, conduction, repolarization and autonomic function in the heart have been associated with risks for cardiac arrhythmias. Whereas several rare monogenic conditions with extreme phenotypes have been noted, few common genetic factors contributing to interindividual variability in ECG and HRV measures have been identified. We report the results of a community-based genomewide association study of six ECG and HRV intermediate traits.Genotyping using Affymetrix 100K GeneChip was conducted on 1345 related Framingham Heart Study Original and Offspring cohort participants. We analyzed 1175 Original and Offspring participants with ECG data (mean age 52 years, 52% women) and 548 Offspring participants with HRV data (mean age 48 years, 51% women), in relation to 70,987 SNPs with minor allele frequency > or = 0.10, call rate > or = 80%, Hardy-Weinberg p-value > or = 0.001. We used generalized estimating equations to test association of SNP alleles with multivariable-adjusted residuals for QT, RR, and PR intervals, the ratio of low frequency to high frequency power (LF/HFP), total power (TP) and the standard deviation of normal RR intervals (SDNN).Associations at p < 10(-3) were found for 117 (QT), 105 (RR), 111 (PR), 102 (LF/HF), 121 (TP), and 102 (SDNN) SNPs. Several common variants in NOS1AP (4 SNPs with p-values < 10(-3); lowest p-value, rs6683968, p = 1 x 10(-4)) were associated with adjusted QT residuals, consistent with our previously reported finding for NOS1AP in an unrelated sample of FHS Offspring and other cohorts. All results are publicly available at NCBI's dbGaP at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite.In the community-based Framingham Heart Study none of the ECG and HRV results individually attained genomewide significance. However, the presence of bona fide QT-associated SNPs among the top 117 results for QT duration supports the importance of efforts to validate top results from the reported scans. Finding genetic variants associated with ECG and HRV quantitative traits may identify novel genes and pathways implicated in arrhythmogenesis and allow for improved recognition of individuals at high risk for arrhythmias in the general population.

Project description:Osteoporosis is characterized by low bone mass and compromised bone structure, heritable traits that contribute to fracture risk. There have been no genome-wide association and linkage studies for these traits using high-density genotyping platforms.We used the Affymetrix 100K SNP GeneChip marker set in the Framingham Heart Study (FHS) to examine genetic associations with ten primary quantitative traits: bone mineral density (BMD), calcaneal ultrasound, and geometric indices of the hip. To test associations with multivariable-adjusted residual trait values, we used additive generalized estimating equation (GEE) and family-based association tests (FBAT) models within each sex as well as sexes combined. We evaluated 70,987 autosomal SNPs with genotypic call rates > or =80%, HWE p > or = 0.001, and MAF > or =10% in up to 1141 phenotyped individuals (495 men and 646 women, mean age 62.5 yrs). Variance component linkage analysis was performed using 11,200 markers.Heritability estimates for all bone phenotypes were 30-66%. LOD scores > or =3.0 were found on chromosomes 15 (1.5 LOD confidence interval: 51,336,679-58,934,236 bp) and 22 (35,890,398-48,603,847 bp) for femoral shaft section modulus. The ten primary phenotypes had 12 associations with 100K SNPs in GEE models at p < 0.000001 and 2 associations in FBAT models at p < 0.000001. The 25 most significant p-values for GEE and FBAT were all less than 3.5 x 10(-6) and 2.5 x 10(-5), respectively. Of the 40 top SNPs with the greatest numbers of significantly associated BMD traits (including femoral neck, trochanter, and lumbar spine), one half to two-thirds were in or near genes that have not previously been studied for osteoporosis. Notably, pleiotropic associations between BMD and bone geometric traits were uncommon. Evidence for association (FBAT or GEE p < 0.05) was observed for several SNPs in candidate genes for osteoporosis, such as rs1801133 in MTHFR; rs1884052 and rs3778099 in ESR1; rs4988300 in LRP5; rs2189480 in VDR; rs2075555 in COLIA1; rs10519297 and rs2008691 in CYP19, as well as SNPs in PPARG (rs10510418 and rs2938392) and ANKH (rs2454873 and rs379016). All GEE, FBAT and linkage results are provided as an open-access results resource at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite.The FHS 100K SNP project offers an unbiased genome-wide strategy to identify new candidate loci and to replicate previously suggested candidate genes for osteoporosis.

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Evaluation of genetic risk scores for lipid levels using genome-wide markers in the Framingham Heart Study.

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Evaluation of genetic risk scores for lipid levels using genome-wide markers in the Framingham Heart Study.

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