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Using genome-wide complex trait analysis to quantify 'missing heritability' in Parkinson's disease.

ABSTRACT: Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trait in a GWAS. We applied GCTA to 8 cohorts containing 7096 case and 19 455 control individuals of European ancestry in order to examine the missing heritability present in Parkinson's disease (PD). We meta-analyzed our initial results to produce robust heritability estimates for PD types across cohorts. Our results identify 27% (95% CI 17-38, P = 8.08E - 08) phenotypic variance associated with all types of PD, 15% (95% CI -0.2 to 33, P = 0.09) phenotypic variance associated with early-onset PD and 31% (95% CI 17-44, P = 1.34E - 05) phenotypic variance associated with late-onset PD. This is a substantial increase from the genetic variance identified by top GWAS hits alone (between 3 and 5%) and indicates there are substantially more risk loci to be identified. Our results suggest that although GWASs are a useful tool in identifying the most common variants associated with complex disease, a great deal of common variants of small effect remain to be discovered.

SUBMITTER: Keller MF

PROVIDER: S-EPMC3576713 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature

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Using genome-wide complex trait analysis to quantify 'missing heritability' in Parkinson's disease.

Keller Margaux F MF Saad Mohamad M Bras Jose J Bettella Francesco F Nicolaou Nayia N Simón-Sánchez Javier J Mittag Florian F Büchel Finja F Sharma Manu M Gibbs J Raphael JR Schulte Claudia C Moskvina Valentina V Durr Alexandra A Holmans Peter P Kilarski Laura L LL Guerreiro Rita R Hernandez Dena G DG Brice Alexis A Ylikotila Pauli P Stefánsson Hreinn H Majamaa Kari K Morris Huw R HR Williams Nigel N Gasser Thomas T Heutink Peter P Wood Nicholas W NW Hardy John J Martinez Maria M Singleton Andrew B AB Nalls Michael A MA

Human molecular genetics 20120813 22

Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trai ...[more]

PMID: 22892372

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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

Using genome-wide complex trait analysis to quantify 'missing heritability' in Parkinson's disease.

Publications

Using genome-wide complex trait analysis to quantify 'missing heritability' in Parkinson's disease.

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