A power study of bivariate LOD score analysis of a complex trait and fear/discomfort with strangers

Complex diseases are often reported along with disease-related traits (DRT). Sometimes investigators consider both disease and DRT phenotypes separately and sometimes they consider individuals as affected if they have either the disease or the DRT, or both. We propose instead to consider the joint distribution of the disease and the DRT and do a linkage analysis assuming a pleiotropic model. We evaluated our results through analysis of the simulated datasets provided by Genetic Analysis Workshop 14. We first conducted univariate linkage analysis of the simulated disease, Kofendrerd Personality Disorder and one of its simulated associated traits, phenotype b (fear/discomfort with strangers). Subsequently, we considered the bivariate phenotype, which combined the information on Kofendrerd Personality Disorder and fear/discomfort with strangers. We developed a program to perform bivariate linkage analysis using an extension to the Elston-Stewart peeling method of likelihood calculation. Using this program we considered the microsatellites within 30 cM of the gene pleiotropic for this simulated disease and DRT. Based on 100 simulations of 300 families we observed excellent power to detect linkage within 10 cM of the disease locus using the DRT and the bivariate trait

Characteristics of replicated single-nucleotide polymorphism genotypes from COGA: Affymetrix and Center for Inherited Disease Research

Genetic Analysis Workshop 14 provided re-genotyped single-nucleotide polymorphism (SNP) data. Specifically, both Center for Inherited Disease Research (CIDR) and Affymetrix genotyped the same 11,560 SNPs from the Affymetrix GeneChip Mapping 10K Array marker set on the same 184 individuals from the Collaborative Study on the Genetics of Alcoholism database. While the inconsistency rate between CIDR and Affymetrix (two different genotypes for the same subject) was low (0.2%), the non-replication rate (two different genotypes for the same subject or one identified genotype and one missing genotype) was substantial (9.5%). The missing data could be from no-call regions, which is inconsistent with recent recommendations about the use of no-call regions in association tests. In addition, no-call regions would suggest that the actual inconsistency rate is higher than reported. A high inconsistency rate has significant impact on power in related hypothesis tests. In addition, the data are consistent with assumptions made in a recently proposed likelihood ratio test of association for re-genotyped data

A Bayesian approach for applying Haseman-Elston methods

The main goal of this paper is to couple the Haseman-Elston method with a simple yet effective Bayesian factor-screening approach. This approach selects markers by considering a set of multigenic models that include epistasis effects. The markers are ranked based on their marginal posterior probability. A significant improvement over our previously proposed Bayesian variable selection methodology is a simple Metropolis-Hasting algorithm that requires minimum tuning on the prior settings. The algorithm, however, is also flexible enough for us to easily incorporate our hypotheses and avoid computational pitfalls. We apply our approach to the microsatellite data of Collaborative Studies on Genetics of Alcoholism using the coded values for the ALDX1 variable as our response

Linkage analysis of disease, DRT, and bivariate trait with the three cities dataset: ELOD (A) and power (percentage (LOD3)) (B)

<p><b>Copyright information:</b></p><p>Taken from "A power study of bivariate LOD score analysis of a complex trait and fear/discomfort with strangers"</p><p></p><p>BMC Genetics 2005;6(Suppl 1):S113-S113.</p><p>Published online 30 Dec 2005</p><p>PMCID:PMC1866825.</p><p></p

The power of linkage analysis of a disease-related endophenotype using asymmetrically ascertained sib pairs

A linkage study of a qualitative disease endophenotype in a sample of sib pairs, consisting of one disease affected proband and one sibling is considered. The linkage statistic compares marker allele sharing with the proband in siblings with an abnormal endophenotype to siblings with the normal endophenotype. Expressions are derived for the distribution of this linkage statistic, in terms of the recombination fraction and (1) the genetic parameter values (allele frequency and endophenotype and disease penetrance) and (2) the abnormal endophenotype rates in the population and in classes of relatives of disease affected probands. It is then shown that when either the disease or the abnormal endophenotype has additive penetrance, the expressions simplify to a monotonic function of the difference between abnormal endophenotype rates in siblings and in the population. Thought disorder is considered as a putative schizophrenia endophenotype. Forty sets of genetic parameter values that correspond to the known prevalence values for thought disorder in schizophrenic patients, siblings of schizophrenics and the general population are evaluated. For these genetic parameter values, numerical results show that the test statistic has >70% power ([alpha]=0.0001) in general with a sample of 200 or more proband-sibling pairs to detect linkage between a marker ([theta]=0.01) and a locus pleiotropic for schizophrenia and thought disorder.