Abstract Background A number of genetic variants have been discovered by recent genome-wide association studies for their associations with clinical coronary heart disease (CHD). However, it is ...unclear whether these variants are also associated with the development of CHD as measured by subclinical atherosclerosis phenotypes, ankle brachial index (ABI), carotid artery intima-media thickness (cIMT) and carotid plaque. Methods Ten CHD risk single nucleotide polymorphisms (SNPs) were genotyped in individuals of European American (EA), African American (AA), American Indian (AI), and Mexican American (MA) ancestry in the Population Architecture using Genomics and Epidemiology (PAGE) study. In each individual study, we performed linear or logistic regression to examine population-specific associations between SNPs and ABI, common and internal cIMT, and plaque. The results from individual studies were meta-analyzed using a fixed effect inverse variance weighted model. Results None of the ten SNPs was significantly associated with ABI and common or internal cIMT, after Bonferroni correction. In the sample of 13,337 EA, 3809 AA, and 5353 AI individuals with carotid plaque measurement, the GCKR SNP rs780094 was significantly associated with the presence of plaque in AI only (OR = 1.32, 95% confidence interval: 1.17, 1.49, P = 1.08 × 10−5 ), but not in the other populations ( P = 0.90 in EA and P = 0.99 in AA). A 9p21 region SNP, rs1333049, was nominally associated with plaque in EA (OR = 1.07, P = 0.02) and in AI (OR = 1.10, P = 0.05). Conclusions We identified a significant association between rs780094 and plaque in AI populations, which needs to be replicated in future studies. There was little evidence that the index CHD risk variants identified through genome-wide association studies in EA influence the development of CHD through subclinical atherosclerosis as assessed by cIMT and ABI across ancestries.
The Metabochip is a custom genotyping array designed for replication and fine mapping of metabolic, cardiovascular, and anthropometric trait loci and includes low frequency variation content ...identified from the 1000 Genomes Project. It has 196,725 SNPs concentrated in 257 genomic regions. We evaluated the Metabochip in 5,863 African Americans; 89% of all SNPs passed rigorous quality control with a call rate of 99.9%. Two examples illustrate the value of fine mapping with the Metabochip in African-ancestry populations. At CELSR2/PSRC1/SORT1, we found the strongest associated SNP for LDL-C to be rs12740374 (p = 3.5 × 10(-11)), a SNP indistinguishable from multiple SNPs in European ancestry samples due to high correlation. Its distinct signal supports functional studies elsewhere suggesting a causal role in LDL-C. At CETP we found rs17231520, with risk allele frequency 0.07 in African Americans, to be associated with HDL-C (p = 7.2 × 10(-36)). This variant is very rare in Europeans and not tagged in common GWAS arrays, but was identified as associated with HDL-C in African Americans in a single-gene study. Our results, one narrowing the risk interval and the other revealing an associated variant not found in Europeans, demonstrate the advantages of high-density genotyping of common and rare variation for fine mapping of trait loci in African American samples.
When a Case Is Not a Case Buyske, Steven; Yang, Guang; Matise, Tara C. ...
Human heredity,
01/2009, Letnik:
67, Številka:
4
Journal Article
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Phenotype misclassification in genetic studies can decrease the power to detect association between a disease locus and a marker locus. To date, studies of misclassification have focused primarily on ...case-control designs. The purpose of this work is to quantify the effects of phenotype misclassification on the transmission disequilibrium test (TDT) applied to affected child trios, where both parents are genotyped. We compute the non-centrality parameter of the distribution corresponding to the TDT statistic when there is linkage and association of a marker locus with a disease locus and there is phenotype misclassification. We verify our analytic calculations with simulations and provide an example sample size calculation. In our simulation studies, the maximum absolute difference between statistical power computed by simulation and analytic methods is 0.018. In an example sample size calculation, we observe that to maintain equivalent power, the required sample size increases when the disease prevalence decreases or when the misclassification rate increases. A 39-fold sample size increase is required when the misclassification rate is 5% and the disease prevalence is 1%. Given the potentially substantial power loss for the TDT in the presence of misclassification, we recommend that researchers incorporate phenotype misclassification into their study design for genetic association using trio data. We have developed freely available software that computes power loss for a fixed sample size or sample size for a fixed power in the presence of phenotype misclassification.
The prospect of using linkage disequilibrium (LD) for fine-scale mapping in humans has attracted considerable attention, and, during the validation of a set of single-nucleotide polymorphisms (SNPs) ...for linkage analysis, a set of data for 4,833 SNPs in 538 clusters was produced that provides a rich picture of local attributes of LD across the genome. LD estimates may be biased depending on the means by which SNPs are first identified, and a particular problem of ascertainment bias arises when SNPs identified in small heterogeneous panels are subsequently typed in larger population samples. Understanding and correcting ascertainment bias is essential for a useful quantitative assessment of the landscape of LD across the human genome. Heterogeneity in the population recombination rate, ρ=4Nr, along the genome reflects how variable the density of markers will have to be for optimal coverage. We find that ascertainment-corrected ρ varies along the genome by more than two orders of magnitude, implying great differences in the recombinational history of different portions of our genome. The distribution of
ρ
ˆ
is unimodal, and we show that this is compatible with a wide range of mixtures of hotspots in a background of variable recombination rate. Although
ρ
ˆ
is significantly correlated across the three population samples, some regions of the genome exhibit population-specific spikes or troughs in ρ that are too large to be explained by sampling. This result is consistent with differences in the genealogical depth of local genomic regions, a finding that has direct bearing on the design and utility of LD mapping and on the National Institutes of Health HapMap project.
Accurate genetic maps are required for successful and efficient linkage mapping of disease genes. However, most available genome-wide genetic maps were built using only small collections of ...pedigrees, and therefore have large sampling errors. A large set of genetic studies genotyped by the NHLBI Mammalian Genotyping Service (MGS) provide appropriate data for generating more accurate maps.
We collected a large sample of uncleaned genotype data for 461 markers generated by the MGS using the Weber screening sets 9 and 10. This collection includes genotypes for over 4,400 pedigrees containing over 17,000 genotyped individuals from different populations. We identified and cleaned numerous relationship and genotyping errors, as well as verified the marker orders. We used this dataset to test for population-specific genetic maps, and to re-estimate the genetic map distances with greater precision; standard errors for all intervals are provided. The map-interval sizes from the European (or European descent), Chinese, and Hispanic samples are in quite good agreement with each other. We found one map interval on chromosome 8p with a statistically significant size difference between the European and Chinese samples, and several map intervals with significant size differences between the African American and Chinese samples. When comparing Palauan with European samples, a statistically significant difference was detected at the telomeric region of chromosome 11p. Several significant differences were also identified between populations in chromosomal and genome lengths.
Our new population-specific screening set maps can be used to improve the accuracy of disease-mapping studies. As a result of the large sample size, the average length of the 95% confidence interval (CI) for a 10 cM map interval is only 2.4 cM, which is considerably smaller than on previously published maps.
Recent advances in technologies for high-throughout single-nucleotide polymorphism (SNP)–based genotyping have improved efficiency and cost so that it is now becoming reasonable to consider the use ...of SNPs for genomewide linkage analysis. However, a suitable screening set of SNPs and a corresponding linkage map have yet to be described. The SNP maps described here fill this void and provide a resource for fast genome scanning for disease genes. We have evaluated 6,297 SNPs in a diversity panel composed of European Americans, African Americans, and Asians. The markers were assessed for assay robustness, suitable allele frequencies, and informativeness of multi-SNP clusters. Individuals from 56 Centre d'Etude du Polymorphisme Humain pedigrees, with >770 potentially informative meioses altogether, were genotyped with a subset of 2,988 SNPs, for map construction. Extensive genotyping-error analysis was performed, and the resulting SNP linkage map has an average map resolution of 3.9 cM, with map positions containing either a single SNP or several tightly linked SNPs. The order of markers on this map compares favorably with several other linkage and physical maps. We compared map distances between the SNP linkage map and the interpolated SNP linkage map constructed by the deCode Genetics group. We also evaluated cM/Mb distance ratios in females and males, along each chromosome, showing broadly defined regions of increased and decreased rates of recombination. Evaluations indicate that this SNP screening set is more informative than the Marshfield Clinic’s commonly used microsatellite-based screening set.
Genome-wide association studies (GWAS) have identified loci associated with ischemic stroke (IS) and cardiovascular disease (CVD) in European-descent individuals, but their replication in different ...populations has been largely unexplored.
Nine single nucleotide polymorphisms (SNPs) selected from GWAS and meta-analyses of stroke, and 86 SNPs previously associated with myocardial infarction and CVD risk factors, including blood lipids (high density lipoprotein HDL, low density lipoprotein LDL, and triglycerides), type 2 diabetes, and body mass index (BMI), were investigated for associations with incident IS in European Americans (EA) N=26 276, African-Americans (AA) N=8970, and American Indians (AI) N=3570 from the Population Architecture using Genomics and Epidemiology Study. Ancestry-specific fixed effects meta-analysis with inverse variance weighting was used to combine study-specific log hazard ratios from Cox proportional hazards models. Two of 9 stroke SNPs (rs783396 and rs1804689) were significantly associated with corrected IS hazard in AA; none were significant in this large EA cohort. Of 73 CVD risk factor SNPs tested in EA, 2 (HDL and triglycerides SNPs) were associated with IS. In AA, SNPs associated with LDL, HDL, and BMI were significantly associated with IS (3 of 86 SNPs tested). Out of 58 SNPs tested in AI, 1 LDL SNP was significantly associated with IS.
Our analyses showing lack of replication in spite of reasonable power for many stroke SNPs and differing results by ancestry highlight the need to follow up on GWAS findings and conduct genetic association studies in diverse populations. We found modest IS associations with BMI and lipids SNPs, though these findings require confirmation.
A 5000ᵣₐd whole-genome radiation hybrid (RH) panel was created for the horse. The usefulness of the panel for generating physically ordered maps of individual equine chromosomes was tested by typing ...24 markers on horse Chromosome 11 (ECA11). The overall retention of markers on this chromosome was 43.6%. Almost complete retention of two of the typed markers—CA062 and AHT44—clearly indicated the location of thymidine kinase gene on the short arm of ECA11. Seven of the typed markers were FISH mapped to align the RH and cytogenetic maps. With the RH-MAPPER approach, a physically ordered map comprising four linkage groups and incorporating all the markers was obtained. The study provides the first comprehensive map for a horse chromosome that integrates all available mapping data and adds new information that spans the entire length of the equine chromosome. The map clearly underlines the resolving power and utility of the panel and emphasizes the need to have uniformly distributed cytogenetic markers for appropriate alignment of RH map with the chromosome. A comparative status of the ECA11 map in relation to the corresponding human/mouse chromosome is presented.
Knowledge of genes influencing longitudinal patterns may offer information about predicting disease progression. We developed a systematic procedure for testing association between SNP genotypes and ...longitudinal phenotypes. We evaluated false positive rates and statistical power to localize genes for disease progression. We used genome-wide SNP data from the Framingham Heart Study. With longitudinal data from two real studies unrelated to Framingham, we estimated three trajectory curves from each study. We performed simulations by randomly selecting 500 individuals. In each simulation replicate, we assigned each individual to one of the three trajectory groups based on the underlying hypothesis (null or alternative), and generated corresponding longitudinal data. Individual Bayesian posterior probabilities (BPPs) for belonging to a specific trajectory curve were estimated. These BPPs were treated as a quantitative trait and tested (using the Wald test) for genome-wide association. Empirical false positive rates and power were calculated. Our method maintained the expected false positive rate for all simulation models. Also, our method achieved high empirical power for most simulations. Our work presents a method for disease progression gene mapping. This method is potentially clinically significant as it may allow doctors to predict disease progression based on genotype and determine treatment accordingly.
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