Genomewide linkage analysis in Costa Rican families implicates chromosome 15q14 as a candidate region for OCD.

Obsessive compulsive disorder (OCD) has a complex etiology that encompasses both genetic and environmental factors. However, to date, despite the identification of several promising candidate genes and linkage regions, the genetic causes of OCD are largely unknown. The objective of this study was to conduct linkage studies of childhood-onset OCD, which is thought to have the strongest genetic etiology, in several OCD-affected families from the genetically isolated population of the Central Valley of Costa Rica (CVCR). The authors used parametric and non-parametric approaches to conduct genome-wide linkage analyses using 5,786 single nucleotide repeat polymorphisms (SNPs) in three CVCR families with multiple childhood-onset OCD-affected individuals. We identified areas of suggestive linkage (LOD score ≥ 2) on chromosomes 1p21, 15q14, 16q24, and 17p12. The strongest evidence for linkage was on chromosome 15q14 (LOD = 3.13), identified using parametric linkage analysis with a recessive model, and overlapping a region identified in a prior linkage study using a Caucasian population. Each CVCR family had a haplotype that co-segregated with OCD across a ~7 Mbp interval within this region, which contains 18 identified brain expressed genes, several of which are potentially relevant to OCD. Exonic sequencing of the strongest candidate gene in this region, the ryanodine receptor 3 (RYR3), identified several genetic variants of potential interest, although none co-segregated with OCD in all three families. These findings provide evidence that chromosome 15q14 is linked to OCD in families from the CVCR, and supports previous findings to suggest that this region may contain one or more OCD susceptibility loci.

A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC.

The proteins encoded by the classical HLA class I and class II genes in the major histocompatibility complex (MHC) are highly polymorphic and are essential in self versus non-self immune recognition. HLA variation is a crucial determinant of transplant rejection and susceptibility to a large number of infectious and autoimmune diseases. Yet identification of causal variants is problematic owing to linkage disequilibrium that extends across multiple HLA and non-HLA genes in the MHC. We therefore set out to characterize the linkage disequilibrium patterns between the highly polymorphic HLA genes and background variation by typing the classical HLA genes and >7,500 common SNPs and deletion-insertion polymorphisms across four population samples. The analysis provides informative tag SNPs that capture much of the common variation in the MHC region and that could be used in disease association studies, and it provides new insight into the evolutionary dynamics and ancestral origins of the HLA loci and their haplotypes.

Description of the data from the Collaborative Study on the Genetics of Alcoholism (COGA) and single-nucleotide polymorphism genotyping for Genetic Analysis Workshop 14.

The data provided to the Genetic Analysis Workshop 14 (GAW 14) was the result of a collaboration among several different groups, catalyzed by Elizabeth Pugh from The Center for Inherited Disease Research (CIDR) and the organizers of GAW 14, Jean MacCluer and Laura Almasy. The DNA, phenotypic characterization, and microsatellite genomic survey were provided by the Collaborative Study on the Genetics of Alcoholism (COGA), a nine-site national collaboration funded by the National Institute of Alcohol and Alcoholism (NIAAA) and the National Institute of Drug Abuse (NIDA) with the overarching goal of identifying and characterizing genes that affect the susceptibility to develop alcohol dependence and related phenotypes. CIDR, Affymetrix, and Illumina provided single-nucleotide polymorphism genotyping of a large subset of the COGA subjects. This article briefly describes the dataset that was provided.

Evaluation of linkage disequilibrium and its effect on non-parametric multipoint linkage analysis using two high density single-nucleotide polymorphism mapping panels.

Genotype data from the Illumina Linkage III SNP panel (n = 4,720 SNPs) and the Affymetrix 10 k mapping array (n = 11,120 SNPs) were used to test the effects of linkage disequilibrium (LD) between SNPs in a linkage analysis in the Collaborative Study on the Genetics of Alcoholism pedigree collection (143 pedigrees; 1,614 individuals). The average r2 between adjacent markers across the genetic map was 0.099 +/- 0.003 in the Illumina III panel and 0.17 +/- 0.003 in the Affymetrix 10 k array. In order to determine the effect of LD between marker loci in a nonparametric multipoint linkage analysis, markers in strong LD with another marker (r2 > 0.40) were removed (n = 471 loci in the Illumina panel; n = 1,804 loci in the Affymetrix panel) and the linkage analysis results were compared to the results using the entire marker sets. In all analyses using the ALDX1 phenotype, 8 linkage regions on 5 chromosomes (2, 7, 10, 11, X) were detected (peak markers p < 0.01), and the Illumina panel detected an additional region on chromosome 6. Analysis of the same pedigree set and ALDX1 phenotype using short tandem repeat markers (STRs) resulted in 3 linkage regions on 3 chromosomes (peak markers p < 0.01). These results suggest that in this pedigree set, LD between loci with spacing similar to the SNP panels tested may not significantly affect the overall detection of linkage regions in a genome scan. Moreover, since the data quality and information content are greatly improved in the SNP panels over STR genotyping methods, new linkage regions may be identified due to higher information content and data quality in a dense SNP linkage panel.

A highly informative SNP linkage panel for human genetic studies.

We have developed a highly informative set of single-nucleotide polymorphism (SNP) assays designed for linkage mapping of the human genome. These assays were developed on a robust multiplexed assay system to provide a combination of very high accuracy and data completeness with high throughput for linkage studies. The linkage panel is comprised of approximately 4,700 SNPs with 0.39 average minor allele frequency and 624-kb average spacing. Based on almost 2 million genotypes, data quality was shown to be extremely high, with a 99.94% call rate, >99.99% reproducibility and 99.995% genotypes consistent with mendelian inheritance. We constructed a genetic map with an average 1.5-cM resolution using series of 28 CEPH pedigrees. The relative information content of this panel was higher than those of commonly used STR marker panels. The potent combination of this SNP linkage panel with the multiplexed assay system provides a previously unattainable level of performance for linkage studies.