Quantitative trait locus-specific genotype x alcoholism interaction on linkage for evoked electroencephalogram oscillations

A genomic imprinting test for ordinal traits in pedigree data

Genomic imprinting can lead maternally and paternally derived alleles with identical nucleotide sequences to function differently and has been found to affect the complex inheritance of a variety of human disorders. Statistical methods that differentiate the parent-of-origin effects on human diseases are available for binary traits and continuous traits. However, numerous common diseases are measured on discrete ordinal scales. Imprinting may also contribute to the complex genetic basis of these traits. In a previous study, we proposed a latent variable model and developed computationally efficient score statistic to test linkage of ordinal traits for any size pedigree while adjusting for non-genetic covariates. In this study, we extend the latent variable model to incorporate parent-of-origin information and further develop a score statistic for testing the imprinting effect in linkage analysis. We evaluated the properties of our test statistic using simulations. We then applied our method to the Collaborative Study on the Genetics of Alcoholism and found a novel locus on chromosome 18 that shows a strong signal for imprinting. In addition, we identified two loci on chromosomes 3 and 4 significantly (p<0.0001) linked with alcoholism.

A score test for linkage analysis of ordinal traits based on IBD sharing

Statistical methods for linkage analysis are well established for both binary and quantitative traits. However, numerous diseases including cancer and psychiatric disorders are rated on discrete ordinal scales. To analyze pedigree data with ordinal traits, we recently proposed a latent variable model which has higher power to detect linkage using ordinal traits than methods using the dichotomized traits. The challenge with the latent variable model is that the likelihood is usually very complicated, and as a result, the computation of the likelihood ratio statistic is too intensive for large pedigrees. In this paper, we derive a computationally efficient score statistic based on the identity-by-decent sharing information between relatives. Using simulation studies, we examined the asymptotic distribution of the test statistic and the power of our proposed test under various levels of heritability. We compared the computing time as well as power of the score test with the likelihood ratio test. We then applied our method for the Collaborative Study on the Genetics of Alcoholism and performed a genome scan to map susceptibility genes for alcohol dependence. We found a strong linkage signal on chromosome 4.

Alcoholism and related traits: a summary of Group 13 contributions

Ten groups set out to study the genetics of alcoholism, using various measures of alcohol dependence such as Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria, and related endophenotypes such as the electrophysiological evaluation of event-related potentials. The groups used both genome-wide microsatellite and single-nucleotide polymorphism (SNP) genotyping data in families selected from the Collaborative Study on the Genetics of Alcoholism. The majority of investigators studied alcohol-related phenotypes and chose linkage rather than association analysis. The analysis of SNP data presented several challenges, including marker linkage disequilibrium issues and computational limitations. Many groups pursued novel techniques, both in dealing with the SNP data and the definition of phenotypes. While there was a limited amount of concordance among linkage findings, it was very instructive to see so many new strategies at work. Generally the SNP genotype data seemed to yield more information for multipoint linkage analysis than the microsatellite data, a finding that will benefit the genetic analysis of complex disease in the future. A novel linkage peak was detected using the SNP markers.