Dataset Information

Segment-wise genome-wide association analysis identifies a candidate region associated with schizophrenia in three independent samples.

ABSTRACT: Recent studies suggest that variation in complex disorders (e.g., schizophrenia) is explained by a large number of genetic variants with small effect size (Odds Ratio ? 1.05-1.1). The statistical power to detect these genetic variants in Genome Wide Association (GWA) studies with large numbers of cases and controls (v 15,000) is still low. As it will be difficult to further increase sample size, we decided to explore an alternative method for analyzing GWA data in a study of schizophrenia, dramatically reducing the number of statistical tests. The underlying hypothesis was that at least some of the genetic variants related to a common outcome are collocated in segments of chromosomes at a wider scale than single genes. Our approach was therefore to study the association between relatively large segments of DNA and disease status. An association test was performed for each SNP and the number of nominally significant tests in a segment was counted. We then performed a permutation-based binomial test to determine whether this region contained significantly more nominally significant SNPs than expected under the null hypothesis of no association, taking linkage into account. Genome Wide Association data of three independent schizophrenia case/control cohorts with European ancestry (Dutch, German, and US) using segments of DNA with variable length (2 to 32 Mbp) was analyzed. Using this approach we identified a region at chromosome 5q23.3-q31.3 (128-160 Mbp) that was significantly enriched with nominally associated SNPs in three independent case-control samples. We conclude that considering relatively wide segments of chromosomes may reveal reliable relationships between the genome and schizophrenia, suggesting novel methodological possibilities as well as raising theoretical questions.

SUBMITTER: Gladwin TE

PROVIDER: S-EPMC3377732 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Segment-wise genome-wide association analysis identifies a candidate region associated with schizophrenia in three independent samples.

Gladwin Thomas E TE Derks Eske M EM Rietschel Marcella M Mattheisen Manuel M Breuer René R Schulze Thomas G TG Nöthen Markus M MM Levinson Douglas D Shi Jianxin J Gejman Pablo V PV Cichon Sven S Ophoff Roel A RA

PloS one 20120618 6

Recent studies suggest that variation in complex disorders (e.g., schizophrenia) is explained by a large number of genetic variants with small effect size (Odds Ratio ≈ 1.05-1.1). The statistical power to detect these genetic variants in Genome Wide Association (GWA) studies with large numbers of cases and controls (v 15,000) is still low. As it will be difficult to further increase sample size, we decided to explore an alternative method for analyzing GWA data in a study of schizophrenia, drama ...[more]

PMID: 22723893

Shared Molecules

Only show the datasets with similarity scores above: 0.5

Threshold

0.5

Similar Datasets

Project description:BACKGROUND: Schizophrenia is a highly heritable complex psychiatric disorder with an underlying pathophysiology that is still not well understood. Metaanalyses of schizophrenia linkage studies indicate numerous but rather large disease-associated genomic regions, whereas accumulating gene- and protein expression studies have indicated an equally large set of candidate genes that only partially overlap linkage genes. A thorough assessment, beyond the resolution of current GWA studies, of the disease risk conferred by the numerous schizophrenia candidate genes is a daunting and presently not feasible task. We undertook these challenges by using an established clinical paradigm, the estrogen hypothesis of schizophrenia, as the criterion to select candidates among the numerous genes experimentally implicated in schizophrenia. Bioinformatic tools were used to build and priorities the signaling networks implicated by the candidate genes resulting from the estrogen selection. We identified ten candidate genes using this approach that are all active in glucose metabolism and particularly in the glycolysis. Thus, we tested the hypothesis that variants of the glycolytic genes are associated with schizophrenia or at least with gender-associated aspects of the illness. RESULTS: We genotyped 185 SNPs in three independent case-control samples of Scandinavian origin (a total of 765 patients and 1274 control subjects). Variants of the mitogen-activated protein kinase 14 gene (MAPK14) and the phosphoenolpyruvate carboxykinase 1 (PCK1) and fructose-1,6-biphosphatase (FBP1) were nominal significantly associated with schizophrenia, and several haplotypes within enolase 2 gene (ENO2) consist of the same SNP allele having elevated risk of schizophrenia. Importantly, we find no evidence of stratification due to nationality or gender. CONCLUSION: Several gene variants in the Glycolysis were associated with schizophrenia in three independent samples. However, the findings are weak and not resistant to correction for multiple testing, which may indicate that they are either spurious or may relate to a particular subtype or aspect of the illness.

Project description:BackgroundRecent genome-wide association studies (GWAS) for asthma have been successful in identifying novel associations which have been well replicated. The aim of this study is to identify the genetic variants that influence predisposition towards asthma in an ethnic Chinese population in Singapore using a GWAS approach.MethodsA two-stage GWAS was performed in case samples with allergic asthma, and in control samples without asthma and atopy. In the discovery stage, 490 case and 490 control samples were analysed by pooled genotyping. Significant associations from the first stage were evaluated in a replication cohort of 521 case and 524 control samples in the second stage. The same 980 samples used in the discovery phase were also individually genotyped for purposes of a combined analysis. An additional 1445 non-asthmatic atopic control samples were also genotyped.Results19 promising SNPs which passed our genome-wide P value threshold of 5.52 × 10-8 were individually genotyped. In the combined analysis of 1011 case and 1014 control samples, SNP rs2941504 in PERLD1 on chromosome 17q12 was found to be significantly associated with asthma at the genotypic level (P = 1.48 × 10-6, ORAG = 0.526 (0.369-0.700), ORAA = 0.480 (0.361-0.639)) and at the allelic level (P = 9.56 × 10-6, OR = 0.745 (0.654-0.848)). These findings were found to be replicated in 3 other asthma GWAS studies, thus validating our own results. Analysis against the atopy control samples suggested that the SNP was associated with allergic asthma and not to either the asthma or allergy components. Genotyping of additional SNPs in 100 kb flanking rs2941504 further confirmed that the association was indeed to PERLD1. PERLD1 is involved in the modification of the glycosylphosphatidylinositol anchors for cell surface markers such as CD48 and CD59 which are known to play multiple roles in T-cell activation and proliferation.ConclusionsThese findings reveal the association of a PERLD1 as a novel asthma candidate gene and reinforce the involvement of genes on the 17q12-21 chromosomal region in the etiology of asthma.

Dataset Information

Segment-wise genome-wide association analysis identifies a candidate region associated with schizophrenia in three independent samples.

Publications

Segment-wise genome-wide association analysis identifies a candidate region associated with schizophrenia in three independent samples.

Shared Molecules

Only show the datasets with similarity scores above: 0.5

Threshold

0.5

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets