The Framingham Heart Study 100K SNP genome-wide association study resource: overview of 17 phenotype working group reports

BACKGROUND:The Framingham Heart Study (FHS), founded in 1948 to examine the epidemiology of cardiovascular disease, is among the most comprehensively characterized multi-generational studies in the world. Many collected phenotypes have substantial genetic contributors; yet most genetic determinants remain to be identified. Using single nucleotide polymorphisms (SNPs) from a 100K genome-wide scan, we examine the associations of common polymorphisms with phenotypic variation in this community-based cohort and provide a full-disclosure, web-based resource of results for future replication studies.METHODS:Adult participants (n = 1345) of the largest 310 pedigrees in the FHS, many biologically related, were genotyped with the 100K Affymetrix GeneChip. These genotypes were used to assess their contribution to 987 phenotypes collected in FHS over 56 years of follow up, including: cardiovascular risk factors and biomarkers; subclinical and clinical cardiovascular disease; cancer and longevity traits; and traits in pulmonary, sleep, neurology, renal, and bone domains. We conducted genome-wide variance components linkage and population-based and family-based association tests.RESULTS:The participants were white of European descent and from the FHS Original and Offspring Cohorts (examination 1 Offspring mean age 32 +/- 9 years, 54% women). This overview summarizes the methods, selected findings and limitations of the results presented in the accompanying series of 17 manuscripts. The presented association results are based on 70,897 autosomal SNPs meeting the following criteria: minor allele frequency [greater than or equal to] 10%, genotype call rate [greater than or equal to] 80%, Hardy-Weinberg equilibrium p-value [greater than or equal to] 0.001, and satisfying Mendelian consistency. Linkage analyses are based on 11,200 SNPs and short-tandem repeats. Results of phenotype-genotype linkages and associations for all autosomal SNPs are posted on the NCBI dbGaP website at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007.CONCLUSION:We have created a full-disclosure resource of results, posted on the dbGaP website, from a genome-wide association study in the FHS. Because we used three analytical approaches to examine the association and linkage of 987 phenotypes with thousands of SNPs, our results must be considered hypothesis-generating and need to be replicated. Results from the FHS 100K project with NCBI web posting provides a resource for investigators to identify high priority findings for replication.

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

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 ~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 [greater than or equal to]10%, genotypic call rate [greater than or equal to]80%, and Hardy-Weinberg equilibrium p [greater than or equal to] 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 ~1450 individuals) and 40 SNPs (P < 0.001 in joint analysis of Stages I and II) tested in Stage III (n~6650 individuals).RESULTS: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.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.

Web Mediators for Accessible Browsing

We present a highly accurate method for classifying web pages based on link percentage, which is the percentage of text characters that are parts of links normalized by the number of all text characters on a web page. K-means clustering is used to create unique thresholds to differentiate index pages and article pages on individual web sites. Index pages contain mostly links to articles and other indices, while article pages contain mostly text. We also present a novel link grouping algorithm using agglomerative hierarchical clustering that groups links in the same spatial neighborhood together while preserving link structure. Grouping allows users with severe disabilities to use a scan-based mechanism to tab through a web page and select items. In experiments, we saw up to a 40-fold reduction in the number of commands needed to click on a link with a scan-based interface, which shows that we can vastly improve the rate of communication for users with disabilities. We used web page classification and link grouping to alter web page display on an accessible web browser that we developed to make a usable browsing interface for users with disabilities. Our classification method consistently outperformed a baseline classifier even when using minimal data to generate article and index clusters, and achieved classification accuracy of 94.0% on web sites with well-formed or slightly malformed HTML, compared with 80.1% accuracy for the baseline classifier.