Transmission/disequilibrium test analysis of total serum IgE levels in the Hutterite and Collaborative Study on the Genetics of Asthma data sets.

The Hutterite and Collaborative Study on the Genetics of Asthma data sets provided by Genetic Analysis Workshop 12 were analyzed using a regression-based transmission/disequilibrium test that assesses linkage between a marker locus and quantitative trait locus when allelic association is present, as proposed by George et al. [Am J Hum Genet 65:236-45, 1999]. Because the same marker set and analytical technique was used, the results from these data sets are amenable for comparison. Statistically significant results common to both data sets were found on chromosomes 1 and 3. A noteworthy result, significant at p < 10(-4), was detected on chromosome 18 in the Hutterites.

Multilocus linkage tests based on affected relative pairs.

For complex diseases, recent interest has focused on methods that take into account joint effects at interacting loci. Conditioning on effects of disease loci at known locations can lead to increased power to detect effects at other loci. Moreover, use of joint models allows investigation of the etiologic mechanisms that may be involved in the disease. Here we present a method for simultaneous analysis of the joint genetic effects at several loci that uses affected relative pairs. The method is a generalization of the two-locus LOD-score analysis for affected sib pairs proposed by Cordell et al. We derive expressions for the relative risk, lambdaR, to a relative of an affected individual, in terms of the additive and epistatic components of variance at an arbitrary number of disease loci, and we show how these can be used to fit a likelihood model to the identity-by-descent sharing among pairs of affected relatives in extended pedigrees. We implement the method by use of a stepwise strategy in which, given evidence of linkage to disease at m-1 locations on the genome, we calculate the conditional likelihood curve across the genome for an mth disease locus, using multipoint methods similar to those proposed by Kruglyak et al. We evaluate the properties of our method by use of simulated data and present an application to real data from families with insulin-dependent diabetes mellitus.

Model-based and model-free multipoint genome-wide linkage analysis of alcoholism.

We analyzed a subset of the Collaborative Study on the Genetics of Alcoholism (COGA) data set as provided by the 11th Genetic Analysis Workshop (GAW11). Linkage analyses were performed using each of the diagnostic criteria for alcoholism included in the data: the COGA criteria (DSM-III-R plus the Feighner criteria) and the narrower World Health Organization diagnosis ICD-10 criteria. Formal segregation analysis using these data was not attempted because only a subset of all the originally ascertained families was made available. Nevertheless, an attempt was made to estimate the best one-locus two-allele genetic model for these data. Model-based multipoint linkage analysis was performed using the results of our trait model fitting, and model-free multipoint linkage analysis was performed with an improved version of the Haseman and Elston linkage method for sib pairs.

Improving the power for disease locus detection in affected-sib-pair studies by using two-locus analysis and multiple regression methods.

In this paper we present a summary of an analysis of the simulated data (Problem 2) for GAW11. We used sib-pair and affected-sib-pair (ASP) methods to evaluate linkage to the mild form of disease at markers across the genome, in data sets of realistic moderate size (containing between 100 and 300 families selected from the simulated replicates). The true 'answers' were known in advance. Although in most cases we were successful in detecting linkage to disease in the correct regions, it was often difficult to distinguish these results from false positives elsewhere in the genome. We used two-locus methods to see whether the significance was improved by simultaneously modeling linkage to two disease loci, and found a modest increase in significance using two-locus methods in several cases.