title: Software for generating liability distributions for pedigrees conditional on their observed disease states and covariates.
abstract: For many multifactorial diseases, aetiology is poorly understood. A major research aim is the identification of disease predictors (environmental, biological, and genetic markers). In order to achieve this, a two-stage approach is proposed. The initial or synthesis stage combines observed pedigree data with previous genetic epidemiological research findings, to produce estimates of pedigree members' disease risk and predictions of their disease liability. A further analysis stage uses the latter as inputs to look for associations with potential disease markers. The incorporation of previous research findings into an analysis should lead to power gains. It also allows separate predictions for environmental and genetic liabilities to be generated. This should increase power for detecting disease predictors that are environmental or genetic in nature. Finally, the approach brings pragmatic benefits in terms of data reduction and synthesis, improving comprehensibility, and facilitating the use of existing statistical genetics tools. In this article we present a statistical model and Gibbs sampling approach to generate liability predictions for multifactorial disease for the synthesis stage. We have implemented the approach in a software program. We apply this program to a specimen disease pedigree, and discuss the results produced, comparing its results with those generated under a more naïve model. We also detail simulation studies that validate the software's operation.
authors.affiliation: Department of Biostatistics, Institute of Psychiatry, King's College London, United Kingdom.
authors.forename: Desmond D
authors.initials: DD
authors.lastname: Campbell
authors.forename: Pak C
authors.initials: PC
authors.lastname: Sham
authors.forename: Jo
authors.initials: J
authors.lastname: Knight
authors.forename: Harvey
authors.initials: H
authors.lastname: Wickham
authors.forename: Sabine
authors.initials: S
authors.lastname: Landau
mesh_terms: D003863:Depression / Q000235:genetics; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D010375:Pedigree; D011237:Predictive Value of Tests; D011336:Probability; D018570:Risk Assessment; D012984:Software; D012986:Software Validation
chemical_list: D005819:Genetic Markers