Genome scan of M. tuberculosis infection and disease in Ugandans.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is an enduring public health problem globally, particularly in sub-Saharan Africa. Several studies have suggested a role for host genetic susceptibility in increased risk for TB but results across studies have been equivocal. As part of a household contact study of Mtb infection and disease in Kampala, Uganda, we have taken a unique approach to the study of genetic susceptibility to TB, by studying three phenotypes.

Studying genetic determinants of natural variation in human gene expression using Bayesian ANOVA.

Standard genetic mapping techniques scan chromosomal segments for location of genetic linkage and association signals. The majority of these methods consider only correlations at single markers and/or phenotypes with explicit detailing of the genetic structure. These methods tend to be limited by their inability to consider the effect of large numbers of model variables jointly.

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.

Linkage and association analysis of candidate genes for TB and TNFalpha cytokine expression: evidence for association with IFNGR1, IL-10, and TNF receptor 1 genes.

Tuberculosis (TB) is a growing public health threat globally and several studies suggest a role of host genetic susceptibility in increased TB risk. As part of a household contact study in Kampala, Uganda, we have taken a unique approach to the study of genetic susceptibility to TB by developing an intermediate phenotype model for TB susceptibility, analyzing levels of tumor necrosis factor-alpha (TNFalpha) in response to culture filtrate as the phenotype. In the present study, we analyzed candidate genes related to TNFalpha regulation and found that interleukin (IL)-10, interferon-gamma receptor 1 (IFNGR1), and TNFalpha receptor 1 (TNFR1) genes were linked and associated to both TB and TNFalpha.

Speech sound disorder influenced by a locus in 15q14 region.

Despite a growing body of evidence indicating that speech sound disorder (SSD) has an underlying genetic etiology, researchers have not yet identified specific genes predisposing to this condition. The speech and language deficits associated with SSD are shared with several other disorders, including dyslexia, autism, Prader-Willi Syndrome (PWS), and Angelman's Syndrome (AS), raising the possibility of gene sharing. Furthermore, we previously demonstrated that dyslexia and SSD share genetic susceptibility loci.

A regression based transmission/disequilibrium test for binary traits: the power of joint tests for linkage and association.

Background: In this analysis we applied a regression based transmission disequilibrium test to the binary trait presence or absence of Kofendred Personality Disorder in the Genetic Analysis Workshop 14 (GAW14) simulated dataset and determined the power and type I error rate of the method at varying map densities and sample sizes. To conduct this transmission disequilibrium test, the logit transformation was applied to a binary outcome and regressed on an indicator variable for the transmitted allele from informative matings. All 100 replicates from chromosomes 1, 3, 5, and 9 for the Aipotu and the combined Aipotu, Karangar, and Danacaa populations were used at densities of 3, 1, and 0.

An artificial neural network for estimating haplotype frequencies.

The problem of estimating haplotype frequencies from population data has been considered by numerous investigators, resulting in a wide variety of possible algorithmic and statistical solutions. We propose a relatively unique approach that employs an artificial neural network (ANN) to predict the most likely haplotype frequencies from a sample of population genotype data. Through an innovative ANN design for mapping genotype patterns to diplotypes, we have produced a prototype that demonstrates the feasibility of this approach, with provisional results that correlate well with estimates produced by the expectation maximization algorithm for haplotype frequency estimation.

Data mining.

Group 14 used data-mining strategies to evaluate a number of issues, including appropriate diagnosis, haplotype estimation, genetic linkage and association studies, and type I error. Methods ranged from exploratory analyses, to machine learning strategies (neural networks, supervised learning, and tree-based methods), to false discovery rate control of type I errors. The general motivations were to find the "story" in the data and to summarize information from a multitude of measures.

Genome-wide linkage scan for genes affecting longitudinal trends in systolic blood pressure.

Only one genome scan to date has attempted to make use of the longitudinal data available in the Framingham Heart Study, and this attempt yielded evidence of linkage to a gene for mean systolic blood pressure. We show how the additional information available in these longitudinal data can be utilized to examine linkages for not only mean systolic blood pressure (SBP), but also for its trend with age and its variability. Prior to linkage analysis, individuals treated for hypertension were adjusted to account for right-censoring of SBP.