Dataset Information

Quantifying the heritability of glioma using genome-wide complex trait analysis.

ABSTRACT: Genome-wide association studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) influencing glioma risk. While these SNPs only explain a small proportion of the genetic risk it is unclear how much is left to be detected by other, yet to be identified, common SNPs. Therefore, we applied Genome-Wide Complex Trait Analysis (GCTA) to three GWAS datasets totalling 3,373 cases and 4,571 controls and performed a meta-analysis to estimate the heritability of glioma. Our results identify heritability estimates of 25% (95% CI: 20-31%, P?=?1.15?×?10(-17)) for all forms of glioma - 26% (95% CI: 17-35%, P?=?1.05?×?10(-8)) for glioblastoma multiforme (GBM) and 25% (95% CI: 17-32%, P?=?1.26?×?10(-10)) for non-GBM tumors. This is a substantial increase from the genetic variance identified by the currently identified GWAS risk loci (~6% of common heritability), indicating that most of the heritable risk attributable to common genetic variants remains to be identified.

SUBMITTER: Kinnersley B

PROVIDER: S-EPMC4667278 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Quantifying the heritability of glioma using genome-wide complex trait analysis.

Kinnersley Ben B Mitchell Jonathan S JS Gousias Konstantinos K Schramm Johannes J Idbaih Ahmed A Labussière Marianne M Marie Yannick Y Rahimian Amithys A Wichmann H-Erich HE Schreiber Stefan S Hoang-Xuan Khe K Delattre Jean-Yves JY Nöthen Markus M MM Mokhtari Karima K Lathrop Mark M Bondy Melissa M Simon Matthias M Sanson Marc M Houlston Richard S RS

Scientific reports 20151202

Genome-wide association studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) influencing glioma risk. While these SNPs only explain a small proportion of the genetic risk it is unclear how much is left to be detected by other, yet to be identified, common SNPs. Therefore, we applied Genome-Wide Complex Trait Analysis (GCTA) to three GWAS datasets totalling 3,373 cases and 4,571 controls and performed a meta-analysis to estimate the heritability of ...[more]

PMID: 26625949

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Project description:BackgroundMetformin is a first-line oral agent used in the treatment of type 2 diabetes, but glycaemic response to this drug is highly variable. Understanding the genetic contribution to metformin response might increase the possibility of personalising metformin treatment. We aimed to establish the heritability of glycaemic response to metformin using the genome-wide complex trait analysis (GCTA) method.MethodsIn this GCTA study, we obtained data about HbA1c concentrations before and during metformin treatment from patients in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) study, which includes a cohort of patients with type 2 diabetes and is linked to comprehensive clinical databases and genome-wide association study data. We applied the GCTA method to estimate heritability for four definitions of glycaemic response to metformin: absolute reduction in HbA1c; proportional reduction in HbA1c; adjusted reduction in HbA1c; and whether or not the target on-treatment HbA1c of less than 7% (53 mmol/mol) was achieved, with adjustment for baseline HbA1c and known clinical covariates. Chromosome-wise heritability estimation was used to obtain further information about the genetic architecture.Findings5386 individuals were included in the final dataset, of whom 2085 had enough clinical data to define glycaemic response to metformin. The heritability of glycaemic response to metformin varied by response phenotype, with a heritability of 34% (95% CI 1-68; p=0·022) for the absolute reduction in HbA1c, adjusted for pretreatment HbA1c. Chromosome-wise heritability estimates suggest that the genetic contribution is probably from individual variants scattered across the genome, which each have a small to moderate effect, rather than from a few loci that each have a large effect.InterpretationGlycaemic response to metformin is heritable, thus glycaemic response to metformin is, in part, intrinsic to individual biological variation. Further genetic analysis might enable us to make better predictions for stratified medicine and to unravel new mechanisms of metformin action.FundingWellcome Trust.

Dataset Information

Quantifying the heritability of glioma using genome-wide complex trait analysis.

Publications

Quantifying the heritability of glioma using genome-wide complex trait analysis.

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