GENESTAT: an information portal for design and analysis of genetic association studies.

We present the rationale, the background and the structure for version 2.0 of the GENESTAT information portal (www.genestat.

Testing association in the presence of linkage using the GRE and multiple markers.

It has recently been shown that testing for association in the presence of linkage using a score test based on a gamma random effects (GRE) model is substantially more powerful than using the Family-Based Association Test. A reason for the increased power lies in better specification of the within family correlation structure, induced by linkage. The GRE, as presented in (Jonasdottir et al.

Multivariate analysis of complex gene expression and clinical phenotypes with genetic marker data.

This paper summarizes contributions to group 12 of the 15th Genetic Analysis Workshop. The papers in this group focused on multivariate methods and applications for the analysis of molecular data including genotypic data as well as gene expression microarray measurements and clinical phenotypes. A range of multivariate techniques have been employed to extract signals from the multi-feature data sets that were provided by the workshop organizers.

HLA-A confers an HLA-DRB1 independent influence on the risk of multiple sclerosis.

A recent high-density linkage screen confirmed that the HLA complex contains the strongest genetic factor for the risk of multiple sclerosis (MS). In parallel, a linkage disequilibrium analysis using 650 single nucleotide polymorphisms (SNP) markers of the HLA complex mapped the entire genetic effect to the HLA-DR-DQ subregion, reflected by the well-established risk haplotype HLA-DRB1*15,DQB1*06. Contrary to this, in a cohort of 1,084 MS patients and 1,347 controls, we show that the HLA-A gene confers an HLA-DRB1 independent influence on the risk of MS (P = 8.

Testing association in the presence of linkage--a powerful score for binary traits.

We present a score for testing association in the presence of linkage for binary traits. The score is robust to varying degrees of linkage, and it is valid under any ascertainment scheme based on trait values as well as under population stratification. The score test is derived from a mixed effects model where population level association is modeled using a fixed effect and where correlation among related individuals is allowed for by using log-gamma random effects.

Analysis of binary traits: testing association in the presence of linkage.

Most methods for testing association in the presence of linkage, using family-based studies, have been developed for continuous traits. FBAT (family-based association tests) is one of few methods appropriate for discrete outcomes. In this article we describe a new test of association in the presence of linkage for binary traits.

CYP17 gene polymorphism in relation to breast cancer risk: a case-control study.

Introduction: The c.1-34T>C 5' promoter region polymorphism in cytochrome P450c17 (CYP17), a key enzyme in the biosynthesis of estrogen, has been associated with breast cancer risk, but most previous studies have been relatively small.

Methods: We genotyped 1,544 incident cases of primary breast cancer and 1,502 population controls, all postmenopausal Swedish women, for the CYP17 c.

Cytochrome P450 1B1 gene polymorphisms and postmenopausal endometrial cancer risk.

Estrogen unopposed by progestins is a key factor in endometrial cancer etiology. Cytochrome P450 1B1 (CYP1B1), responsible for the 4-hydroxylation of estrogen, may be important in endometrial carcinogenesis, either as a regulator of estrogen availability or as a producer of potentially genotoxic estrogen metabolites. We investigated the association of CYP1B1 genotype and endometrial cancer risk in a population-based case-control study of postmenopausal Swedish women.