ABSTRACT
We introduce an approximate model for linkage curves which accommodates the polygenic structure of complex diseases and accounts for the simultaneous action of closely located genes. The model is extended so that information on biological pathways can be integrated. Using data on rheumatoid arthritis, we describe some of the many applications which the model allows: it can be used to test for residual linkage in the presence of already established loci, to derive a global test for linkage, to test for the relevance of a gene list in terms of linkage and to help in candidate gene prioritization by integration of gene-pathway annotation data.
Subject(s)
Genetic Linkage , Models, Genetic , Disease/genetics , HumansABSTRACT
We derive a test for linkage in a Generalized Linear Mixed Model (GLMM) framework which provides a natural adjustment for marginal covariate effects. The method boils down to the score test of a quasi-likelihood derived from the GLMM, it is computationally inexpensive and can be applied to arbitrary pedigrees. In particular, for binary traits, relative pairs of different nature (affected and discordant) and individuals with different covariate values can be naturally combined in a single test. The model introduced could explain a number of situations usually described as gene by covariate interaction phenomena, and offers substantial gains in efficiency compared to methods classically used in those instances.
Subject(s)
Linear Models , Models, Genetic , Breast Neoplasms/genetics , Female , Humans , Likelihood Functions , Male , Migraine Disorders/genetics , Regression Analysis , Research DesignABSTRACT
The mean identity-by-descent (IBD) specification used in the Generalized Estimating Equations (GEE) methodology for linkage is only valid, strictly speaking, under the assumption of fully polymorphic markers. In practice, markers often provide only partial IBD information, which can potentially result in inconsistency of the locus location and gene effect estimates obtained by the GEE method. Using both simulations and theory, we identify some realistic conditions about marker information under which the validity of the GEE linkage methods may be arguable. Namely, researchers should not trust the GEE parameters' estimates and their associated confidence intervals in areas of the genome where IBD information is sparse or when this information changes abruptly. We show that properly standardized statistics based on IBD sharing provide a valid alternative.
Subject(s)
Bias , Chromosome Mapping/methods , Cytogenetic Analysis/methods , Genetic Markers/genetics , Alleles , Confidence Intervals , Humans , Models, GeneticABSTRACT
We present a unified approach to selection and linkage analysis of selected samples, for both quantitative and dichotomous complex traits. It is based on the score test for the variance attributable to the trait locus and applies to general pedigrees. The method is equivalent to regressing excess IBD sharing on a function of the traits. It is shown that when population parameters for the trait are known, such inversion does not entail any loss of information. For dichotomous traits, pairs of pedigree members of different phenotypic nature (e.g., affected sib pairs and discordant sib pairs) can easily be combined as well as populations with different trait prevalences.
Subject(s)
Chromosome Mapping/methods , Lod Score , Quantitative Trait Loci/genetics , Analysis of Variance , Genetic Linkage/genetics , Humans , Inheritance Patterns/genetics , Models, Genetic , Sample SizeABSTRACT
This study defines the psychometric properties of the European Organisation for Research and Treatment of Cancer (EORTC) quality of life (QOL) questionnaire designed to measure the QOL of patients with ovarian cancer. The ovarian cancer module (EORTC QLQ-OV28) was developed to supplement the EORTC QLQ-C30. The core questionnaire and the QLQ-OV28 were prospectively administered to 368 ovarian cancer patients after they had been treated with radical or debulking surgery followed by chemotherapy. The QLQ-OV28 module assesses abdominal/gastrointestinal symptoms, peripheral neuropathy, other chemotherapy side-effects, hormonal/menopausal symptoms, body image, attitude to disease/treatment and sexual functioning. Questionnaires were well accepted by patients, baseline compliance rates were 86%, 72% provided a second assessment, less than 3% of the items had missing data. Multi-trait scaling analyses confirmed the hypothesised scales. All hypothesised scales exhibited good psychometric properties. These results support the clinical and psychometric validity of the EORTC QLQ-OV28 module as a supplement to the EORTC QLQ-C30.
