Associations of smoking status and serious psychological distress with chronic obstructive pulmonary disease.

Background: Chronic obstructive pulmonary disease (COPD) has been a major public health problem due to its high prevalence, morbidity, and mortality. Smoking is a major risk factor for COPD, while serious psychological distress (SPD) is prevalent among COPD patients. However, no study focusing on the effect of SPD on COPD has been so far conducted, while few studies have focused on the associations of SPD and behavioral factors with COPD by smoking status.

Genome-wide association studies of maximum number of drinks.

Maximum number of drinks (MaxDrinks) defined as "Maximum number of alcoholic drinks consumed in a 24-h period" is an intermediate phenotype that is closely related to alcohol dependence (AD). Family, twin and adoption studies have shown that the heritability of MaxDrinks is approximately 0.5.

Common variants in HLA-DRA gene are associated with alcohol dependence in two Caucasian samples.

HLA-DRA gene polymorphisms might play an important role in alcohol dependence (AD). We examined genetic associations of 29 single-nucleotide polymorphisms (SNPs) within the HLA-DRA gene with AD using two Caucasian samples-the Collaborative Study on the Genetics of Alcoholism (COGA) sample (660 AD cases and 400 controls) and the Study of Addiction: Genetics and Environment (SAGE) sample (623 cases and 1,016 controls). Logistic regression analysis using PLINK showed that 16 SNPs were associated with AD in the COGA sample and 13 SNPs were associated with AD in the SAGE sample (p < 0.

Genome-wide association study identifies 5q21 and 9p24.1 (KDM4C) loci associated with alcohol withdrawal symptoms.

Several genome-wide association (GWA) studies of alcohol dependence (AD) and alcohol-related phenotypes have been conducted; however, little is known about genetic variants influencing alcohol withdrawal symptoms (AWS). We conducted the first GWA study of AWS using 461 cases of AD with AWS and 408 controls in Caucasian population in the Collaborative Study on the Genetics of Alcoholism (COGA) sample. Logistic regression analysis of AWS as a binary trait, adjusted for age and sex, was performed using PLINK.

A Bayesian segmentation approach to ascertain copy number variations at the population level.

Motivation: Efficient and accurate ascertainment of copy number variations (CNVs) at the population level is essential to understand the evolutionary process and population genetics, and to apply CNVs in population-based genome-wide association studies for complex human diseases. We propose a novel Bayesian segmentation approach to identify CNVs in a defined population of any size. It is computationally efficient and provides statistical evidence for the detected CNVs through the Bayes factor.

Locus-specific heritability estimation via the bootstrap in linkage scans for quantitative trait loci.

Background/aims: In genome-wide linkage analysis of quantitative trait loci (QTL), locus-specific heritability estimates are biased when the original data are used to both localize linkage and estimate effects, due to maximization of the LOD score over the genome. Positive bias is increased by adoption of stringent significance levels to control genome-wide type I error. We propose multi-locus bootstrap resampling estimators for bias reduction in the situation in which linkage peaks at more than one QTL are of interest.

Comparison of family-based association tests in chromosome regions selected by linkage-based confidence intervals.

We use the Genetic Analysis Workshop 14 simulated data to explore the effectiveness of a two-stage strategy for mapping complex disease loci consisting of an initial genome scan with confidence interval construction for gene location, followed by fine mapping with family-based tests of association on a dense set of single-nucleotide polymorphisms. We considered four types of intervals: the 1-LOD interval, a basic percentile bootstrap confidence interval based on the position of the maximum Zlr score, and asymptotic and bootstrap confidence intervals based on a generalized estimating equations method. For fine mapping we considered two family-based tests of association: a test based on a likelihood ratio statistic and a transmission-disequilibrium-type test implemented in the software FBAT.

Resampling methods to reduce the selection bias in genetic effect estimation in genome-wide scans.

Using the simulated data of Problem 2 for Genetic Analysis Workshop 14 (GAW14), we investigated the ability of three bootstrap-based resampling estimators (a shrinkage, an out-of-sample, and a weighted estimator) to reduce the selection bias for genetic effect estimation in genome-wide linkage scans. For the given marker density in the preliminary genome scans (7 cM for microsatellite and 3 cM for SNP), we found that the two sets of markers produce comparable results in terms of power to detect linkage, localization accuracy, and magnitude of test statistic at the peak location. At the locations detected in the scan, application of the three bootstrap-based estimators substantially reduced the upward selection bias in genetic effect estimation for both true and false positives.