Dataset Information

Meta-analysis of 23 type 2 diabetes linkage studies from the International Type 2 Diabetes Linkage Analysis Consortium.

ABSTRACT: The International Type 2 Diabetes Linkage Analysis Consortium was formed to localize type 2 diabetes predisposing variants based on 23 autosomal linkage scans.We carried out meta-analysis using the genome scan meta-analysis (GSMA) method which divides the genome into bins of approximately 30 cM, ranks the best linkage results in each bin for each sample, and then sums the ranks across samples. We repeated the meta-analysis using 2 cM bins, and/or replacing bin ranks with measures of linkage evidence: bin maximum LOD score or bin minimum p value for bins with p value <0.05 (truncated p value). We also carried out computer simulations to assess the empirical type I error rates of these meta-analysis methods.Our analyses provided modest evidence for type 2 diabetes-predisposing variants on chromosomes 4, 10, and 14 (using LOD scores or truncated p values), or chromosome 10 and 16 (using ranks). Our simulation results suggested that uneven marker density across studies results in substantial variation in empirical type I error rates for all meta-analysis methods, but that 2 cM bins and scores that make more explicit use of linkage evidence, especially the truncated p values, reduce this problem.We identified regions modestly linked with type 2 diabetes by summarizing results from 23 autosomal genome scans.

SUBMITTER: Guan W

PROVIDER: S-EPMC2855874 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Meta-analysis of 23 type 2 diabetes linkage studies from the International Type 2 Diabetes Linkage Analysis Consortium.

Guan Weihua W Pluzhnikov Anna A Cox Nancy J NJ Boehnke Michael M

Human heredity 20070128 1

<h4>Background</h4>The International Type 2 Diabetes Linkage Analysis Consortium was formed to localize type 2 diabetes predisposing variants based on 23 autosomal linkage scans.<h4>Methods</h4>We carried out meta-analysis using the genome scan meta-analysis (GSMA) method which divides the genome into bins of approximately 30 cM, ranks the best linkage results in each bin for each sample, and then sums the ranks across samples. We repeated the meta-analysis using 2 cM bins, and/or replacing bin ...[more]

PMID: 18223311

Similar Datasets

Project description:Although human leukocyte antigen (HLA) DQ and DR loci appear to confer the strongest genetic risk for type 1 diabetes, more detailed information is required for other loci within the HLA region to understand causality and stratify additional risk factors. The Type 1 Diabetes Genetics Consortium (T1DGC) study design included high-resolution genotyping of HLA-A, B, C, DRB1, DQ, and DP loci in all affected sibling pair and trio families, and cases and controls, recruited from four networks worldwide, for analysis with clinical phenotypes and immunological markers.In this article, we present the operational strategy of training, classification, reporting, and quality control of HLA genotyping in four laboratories on three continents over nearly 5 years.Methods to standardize HLA genotyping at eight loci included: central training and initial certification testing; the use of uniform reagents, protocols, instrumentation, and software versions; an automated data transfer; and the use of standardized nomenclature and allele databases. We implemented a rigorous and consistent quality control process, reinforced by repeated workshops, yearly meetings, and telephone conferences.A total of 15,246 samples have been HLA genotyped at eight loci to four-digit resolution; an additional 6797 samples have been HLA genotyped at two loci. The genotyping repeat rate decreased significantly over time, with an estimated unresolved Mendelian inconsistency rate of 0.21%. Annual quality control exercises tested 2192 genotypes (4384 alleles) and achieved 99.82% intra-laboratory and 99.68% inter-laboratory concordances.The chosen genotyping platform was unable to distinguish many allele combinations, which would require further multiple stepwise testing to resolve. For these combinations, a standard allele assignment was agreed upon, allowing further analysis if required.High-resolution HLA genotyping can be performed in multiple laboratories using standard equipment, reagents, protocols, software, and communication to produce consistent and reproducible data with minimal systematic error. Many of the strategies used in this study are generally applicable to other large multi-center studies.

Project description:BACKGROUND:Genetic variants are likely to contribute to a portion of prostate cancer risk. Full elucidation of the genetic etiology of prostate cancer is difficult because of incomplete penetrance and genetic and phenotypic heterogeneity. Current evidence suggests that genetic linkage to prostate cancer has been found on several chromosomes including the X; however, identification of causative genes has been elusive. METHODS:Parametric and non-parametric linkage analyses were performed using 26 microsatellite markers in each of 11 groups of multiple-case prostate cancer families from the International Consortium for Prostate Cancer Genetics (ICPCG). Meta-analyses of the resultant family-specific linkage statistics across the entire 1,323 families and in several predefined subsets were then performed. RESULTS:Meta-analyses of linkage statistics resulted in a maximum parametric heterogeneity lod score (HLOD) of 1.28, and an allele-sharing lod score (LOD) of 2.0 in favor of linkage to Xq27-q28 at 138 cM. In subset analyses, families with average age at onset less than 65 years exhibited a maximum HLOD of 1.8 (at 138 cM) versus a maximum regional HLOD of only 0.32 in families with average age at onset of 65 years or older. Surprisingly, the subset of families with only 2-3 affected men and some evidence of male-to-male transmission of prostate cancer gave the strongest evidence of linkage to the region (HLOD = 3.24, 134 cM). For this subset, the HLOD was slightly increased (HLOD = 3.47 at 134 cM) when families used in the original published report of linkage to Xq27-28 were excluded. CONCLUSIONS:Although there was not strong support for linkage to the Xq27-28 region in the complete set of families, the subset of families with earlier age at onset exhibited more evidence of linkage than families with later onset of disease. A subset of families with 2-3 affected individuals and with some evidence of male to male disease transmission showed stronger linkage signals. Our results suggest that the genetic basis for prostate cancer in our families is much more complex than a single susceptibility locus on the X chromosome, and that future explorations of the Xq27-28 region should focus on the subset of families identified here with the strongest evidence of linkage to this region.

Project description:We sought to identify genome-wide variants influencing antihypertensive drug response and adverse cardiovascular outcomes, utilizing data from four randomized controlled trials in the International Consortium for Antihypertensive Pharmacogenomics Studies (ICAPS). Genome-wide antihypertensive drug-single nucleotide polymorphism (SNP) interaction tests for four drug classes (β-blockers, n = 9,195; calcium channel blockers (CCBs), n = 10,511; thiazide/thiazide-like diuretics, n = 3,516; ACE-inhibitors/ARBs, n = 2,559) and cardiovascular outcomes (incident myocardial infarction, stroke, or death) were analyzed among patients with hypertension of European ancestry. Top SNPs from the meta-analyses were tested for replication of cardiovascular outcomes in an independent Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) study (n = 21,267), blood pressure (BP) response in independent ICAPS studies (n = 1,552), and ethnic validation in African Americans from the Genetics of Hypertension Associated Treatment study (GenHAT; n = 5,115). One signal reached genome-wide significance in the β-blocker-SNP interaction analysis (rs139945292, Interaction P = 1.56 × 10-8 ). rs139945292 was validated through BP response to β-blockers, with the T-allele associated with less BP reduction (systolic BP response P = 6 × 10-4 , Beta = 3.09, diastolic BP response P = 5 × 10-3 , Beta = 1.53). The T-allele was also associated with increased adverse cardiovascular risk within the β-blocker treated patients' subgroup (P = 2.35 × 10-4 , odds ratio = 1.57, 95% confidence interval = 1.23-1.99). The locus showed nominal replication in CHARGE, and consistent directional trends in β-blocker treated African Americans. rs139945292 is an expression quantitative trait locus for the 50 kb upstream gene NTM (neurotrimin). No SNPs attained genome-wide significance for any other drugs classes. Top SNPs were located near CALB1 (CCB), FLJ367777 (ACE-inhibitor), and CES5AP1 (thiazide). The NTM region is associated with increased risk for adverse cardiovascular outcomes and less BP reduction in β-blocker treated patients. Further investigation into this region is warranted.

Dataset Information

Meta-analysis of 23 type 2 diabetes linkage studies from the International Type 2 Diabetes Linkage Analysis Consortium.

Publications

Meta-analysis of 23 type 2 diabetes linkage studies from the International Type 2 Diabetes Linkage Analysis Consortium.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets