Population stratification is one of the major causes of spurious associations in association studies. association studies. Several approaches have been developed to deal with this problem. The genomic control [1], structured association [2,3], and principal-component analysis methods [4-8] correct for population stratification in population-based case-control studies by using a set of markers across the genome. The transmission-disequilibrium test (TDT) makes use of family structure to match the cases and controls on their genetic background and thus avoids the inflated type I error rate due to population stratification. For a binary trait, it tests association by comparing the frequencies of alleles transmitted and those of alleles not transmitted from heterozygous parents to affected children. A unified association method (family-case-control, or FamCC), which utilizes both unrelated and family samples, was developed based on principal-component analysis [9]. The population background, represented by the principal components, is calculated from a large number of genetic markers typed on unrelated subjects and family members, and then used to adjust the genotype and phenotype values. Because it can make use of both unrelated and family samples, this method uses more information than the TDT. It has no rare disease assumption, while accepting multiple affected and unaffected siblings, which is a limitation of another association method that combines family and unrelated samples [10]. In this study, the unified association method FamCC [9] and the Senkyunolide H TDT were compared for association tests of the binary trait hypertension and quantitative characteristics systolic blood pressure (SBP) and diastolic blood pressure (DBP) in the Framingham Heart Study data. Methods Samples A total of 13,336 subjects in 1,231 pedigrees are included in the Framingham Heart Study. They are from three decades: the original generation, their offspring, and the third generation. Subjects in the original generation were discarded for this analysis because of concern over the age of their Senkyunolide H DNA samples. There are 6,395 genotyped and phenotyped subjects in the offspring generation and the third generation, from 1,144 pedigrees, and they were all used as the family sample for this association study. When the initial generation was discarded, some large pedigrees were broken, which resulted in 1,705 nuclear family members and 1,022 singletons. In order to determine how FamCC would handle a completely unrelated sample, 1,109 biologically unrelated best genotyped individuals with age greater than 20, solitary founders or founder couples, were taken from the offspring generation of the family sample to form a subsample of unrelated individuals. Markers There were 487,014 single-nucleotide polymorphisms (SNPs) across the genome genotyped for each subject within the Affymetrix 500k chip. In all, 22,775 SNPs on chromosome 9 were used for our association study of blood pressure because of the linkage evidence recognized on chromosome 9 inside a earlier study [11]. After removing SNPs with more than 10% missing genotypes, 20,266 SNPs remained. Then the SNPs with small allele frequency less than 5% or with Hardy-Weinberg equilibrium test p-value < 2.47 10-6 were dropped, resulting in 15,622 SNPs for the final analysis. Blood pressure phenotypes SBP and DBP were measured for the two cohorts (offspring and generation 3) at four examinations (exam 1, exam 3, exam 5, and exam 7). One binary trait, hypertension, and two quantitative characteristics, SBP and DBP, were used as the phenotypes with this study. Hypertension was defined as having been treated Rabbit polyclonal to SP1.SP1 is a transcription factor of the Sp1 C2H2-type zinc-finger protein family.Phosphorylated and activated by MAPK. for hypertension or if, at any of the four examinations, SBP was higher than 140 mm Hg or DBP was higher than 90 mm Hg. For the quantitative SBP and DBP phenotypes, we 1st added Senkyunolide H 10 mm Hg to SBP and 5 mm Hg to DBP for individuals on hypertension treatment, as suggested by Tobin et al. [12]. Then for SBP and DPB, adjustments were made for sex, age, BMI, and cohort effects for each exam using multiple linear regression. The average residuals.