A sequence variation scan of the coagulation factor VIII (FVIII) structural gene and associations with plasma FVIII activity levels.

Plasma factor VIII coagulant activity (FVIII:C) level is a highly heritable quantitative trait that is strongly correlated with thrombosis risk. Polymorphisms within only 1 gene, the ABO blood-group locus, have been unequivocally demonstrated to contribute to the broad population variability observed for this trait. Because less than 2.5% of the structural FVIII gene (F8) has been examined previously, we resequenced all known functional regions in 222 potentially distinct alleles from 137 unrelated nonhemophilic individuals representing 7 racial groups. Eighteen of the 47 variants identified, including 17 single-nucleotide polymorphisms (SNPs), were previously unknown. As the degree of linkage disequilibrium across F8 was weak overall, we used measured-genotype association analysis to evaluate the influence of each polymorphism on the FVIII:C levels in 398 subjects from 21 pedigrees known as the Genetic Analysis of Idiopathic Thrombophilia project (GAIT). Our results suggested that 92714C>G, a nonsynonymous SNP encoding the B-domain substitution D1241E, was significantly associated with FVIII:C level. After accounting for important covariates, including age and ABO genotype, the association persisted with each C-allele additively increasing the FVIII:C level by 14.3 IU dL(-1) (P = .016). Nevertheless, because the alleles of 56010G>A, a SNP within the 3' splice junction of intron 7, are strongly associated with 92714C>G in GAIT, additional studies are required to determine whether D1241E is itself a functional variant.

Heritability and linkage analysis of hand, foot, and eye preference in Mexican Americans.

Functional lateralities are of interest due to their relationship with cerebral lateralisation and language development. However, genes influencing sidedness remain elusive. We measured direction and consistency of hand, foot, and eye preference in 584 Mexican-Americans from families participating in the San Antonio Family Diabetes/Gallbladder Study. Using maximum-likelihood-based variance components methods, we estimated weak (.11

Software for quantitative trait analysis.

This paper provides a brief overview of software currently available for the genetic analysis of quantitative traits in humans. Programs that implement variance components, Markov Chain Monte Carlo (MCMC), Haseman-Elston (H-E) and penetrance model-based linkage analyses are discussed, as are programs for measured genotype association analyses and quantitative trait transmission disequilibrium tests. The software compared includes LINKAGE, FASTLINK, PAP, SOLAR, SEGPATH, ACT, Mx, MERLIN, GENEHUNTER, Loki, Mendel, SAGE, QTDT and FBAT. Where possible, the paper provides URLs for acquiring these programs through the internet, details of the platforms for which the software is available and the types of analyses performed.

Heritability of hemostasis phenotypes and their correlation with type 2 diabetes status in Mexican Americans.

Hypercoagulation often occurs in type 2 diabetes, suggesting pleiotropy of the genes that influence disease liability and hemostasis-related phenotypes. To better understand the relationship between hemostasis and diabetes, we first used maximum-likelihood methods to estimate the relative contribution of additive genetic, measured environmental, and shared household effects to the normal variance of 16 hemostasis-related traits in 813 individuals participating in the San Antonio Family Heart Study. We estimated moderate to high heritabilities (0.20-0.60) for each phenotype. Von Willebrand factor (VWF), thrombin activatable fibrinolysis inhibitor, activated protein C (APC) ratio, factor V, and prothrombin time had heritabilities greater than 0.50. The correlation between type 2 diabetes status and the hemostasis-related traits was then partitioned into genetic and environmental components using bivariate variance-components methods. Significant (p < or = 0.05) positive genetic correlations (0.37-0.51) occurred with factors II and VIII, VWF, total protein S (tPS), and tissue factor pathway inhibitor. Significant negative genetic correlations were estimated for activated partial thromboplastin time (-0.49) and APC ratio (-0.38). By contrast, significant environmental correlations occurred only with factor II (-0.40) and tPS (-0.31). Our results suggest that genes are important contributors to the normal variation in hemostasis-related traits and that genes influencing hemostasis-related traits pleiotropically influence diabetes risk.

A comparison of univariate, bivariate, and trivariate whole-genome linkage screens of genetically correlated electrophysiological endophenotypes.

We used a maximum-likelihood based multipoint linkage approach implemented in SOLAR to examine simultaneously linkage for three electrophysiological endophenotypes from the Collaborative Study of the Genetics of Alcoholism: TTTH1, TTTH2, and TTTH3. These endophenotypes have been identified as markers of alcohol dependence susceptibility. Data were from 905 individuals in 143 families. Measured covariates considered included sex, age at electrophysiology data collection, habitual smoking status, and the maximum number of drinks consumed in a 24-hour period. Comparisons were made among genome-wide univariate, bivariate, and trivariate linkage analyses using genotypes based on microsatellite markers supplied by the Center for Inherited Disease Research, and genotypes based on single-nucleotide polymorphism markers provided by Illumina. All LODs were corrected to a standard equivalent to 1 degree of freedom. Using the trivariate approach and the microsatellite-based genotypes, we estimated a maximum multipoint linkage signal of LOD = 2.66 on chromosome 7q at 157 cM. Analyses using the Illumina SNP genotypes produced similar results, yielding a maximum multipoint LOD of 2.95 on 7q at 174 cM. These regions of interest correspond to those identified in the univariate and bivariate linkage screens. Our results suggest that trivariate multipoint linkage analyses have utility in the further characterization of chromosomal regions potentially containing genes influencing the phenotypes being examined. Based on a comparison of the number of LOD scores achieving statistical significance, our results suggest that the microsatellite- and Illumina SNP-based genotypes have similar utility for detecting genomic regions of interest.

Effect of genotype x alcoholism interaction on linkage analysis of an alcoholism-related quantitative phenotype.

Studies have shown that genetic and environmental factors and their interactions affect several alcoholism phenotypes. Genotype x alcoholism (GxA) interaction refers to the environmental (alcoholic and non-alcoholic) influences on the autosomal genes contributing to variation in an alcoholism-related quantitative phenotype. The purpose of this study was to examine the effects of GxA interaction on the detection of linkage for alcoholism-related phenotypes. We used phenotypic and genotypic data from the Collaborative Study on the Genetics of Alcoholism relating to 1,388 subjects as part of Genetic Analysis Workshop 14 problem 1. We analyzed the MXDRNK phenotype to detect GxA interaction using SOLAR. Upon detecting significant interaction, we conducted variance-component linkage analyses using microsatellite marker data. For maximum number of drinks per a 24 hour period, the highest LODs were observed on chromosomes 1, 4, and 13 without GxA interaction. Interaction analysis yielded four regions on chromosomes 1, 4, 13, and 15. On chromosome 4, a maximum LOD of 1.5 at the same location as the initial analysis was obtained after incorporating GxA interaction effects. However, after correcting for extra parameters, the LOD score was reduced to a corrected LOD of 1.1, which is similar to the LOD observed in the non-interaction analysis. Thus, we see little differences in LOD scores, while some linkage regions showed large differences in the magnitudes of estimated quantitative trait loci heritabilities between the alcoholic and non-alcoholic groups. These potential hints of differences in genetic effect may influence future analyses of variants under these linkage peaks.

A comparison of discrete versus continuous environment in a variance components-based linkage analysis of the COGA data.

BACKGROUND: The information content of a continuous variable exceeds that of its categorical counterpart. The parameterization of a model may diminish the benefit of using a continuous variable. We explored the use of continuous versus discrete environment in variance components based analyses examining gene x environment interaction in the electrophysiological phenotypes from the Collaborative Study on the Genetics of Alcoholism. RESULTS: The parameterization using the continuous environment produced a greater number of significant gene x environment interactions and lower AICs (Akaike's information criterion). In these cases, the genetic variance increased with increasing cigarette pack-years, the continuous environment of interest. This did not, however, result in enhanced LOD scores when linkage analyses incorporated the gene x continuous environment interaction. CONCLUSION: Alternative parameterizations may better represent the functional relationship between the continuous environment and the genetic variance.

Linkage disequilibrium across two different single-nucleotide polymorphism genome scans.

Linkage disequilibrium (LD) content was calculated for the Genetic Analysis Workshop 14 Affymetrix and Illumina single-nucleotide polymorphism (SNP) genome scans of the Collaborative Study on the Genetics of Alcoholism samples. Pair-wise LD was measured as both D' and r2 on 505 pedigree founder individuals. The r2 estimates were then used to correct the multipoint identity by descent matrix (MIBD) calculation to account for LD and LOD scores on chromosomes 3 and 18 were calculated for COGA's ttdt3 electrophysiological trait using those MIBDs. Extensive LD was observed throughout both marker sets, and it was higher in Affymetrix's more dense SNP map. However, SNP density did not solely account for Affymetrix's higher LD. MIBD estimation procedures assume linkage equilibrium to construct genotypes of non-genotyped pedigree founder individuals, and dense SNP genotyping maps are likely to contain moderate to high LD between markers. LOD score plots calculated after correction for LD followed the same general pattern as uncorrected ones. Since in our study almost half of the pedigree founders were genotyped, it is possible that LD had a minor impact on the LOD scores. Caution should probably be taken when using high density SNP maps when many non-genotyped founders are present in the study pedigrees.