title: Implementation of genome-wide complex trait analysis to quantify the heritability in multiple myeloma.
abstract: A sizeable fraction of multiple myeloma (MM) is expected to be explained by heritable factors. Genome-wide association studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) influencing MM 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 2,282 cases and 5,197 controls individuals to estimate the heritability of MM. We estimated that the heritability explained by known common MM risk SNPs identified in GWAS was 2.9% (± 2.4%), whereas the heritability explained by all common SNPs was 15.2% (± 2.8%). Comparing the heritability explained by the common variants with that from family studies, a fraction of the heritability may be explained by other genetic variants, such as rare variants. In summary, our results suggest that known MM SNPs only explain a small proportion of the heritability and more common SNPs remain to be identified.
authors.affiliation: Molecular and Population Genetics, Division of Genetics and Epidemiology, The Institute of Cancer Research, Surrey, UK.
authors.forename: Jonathan S
authors.initials: JS
authors.lastname: Mitchell
authors.affiliation: Department of Haemato-Oncology, Division of Pathology, The Institute of Cancer Research, Surrey, UK.
authors.forename: David C
authors.initials: DC
authors.lastname: Johnson
authors.affiliation: Molecular and Population Genetics, Division of Genetics and Epidemiology, The Institute of Cancer Research, Surrey, UK.
authors.forename: Kevin
authors.initials: K
authors.lastname: Litchfield
authors.affiliation: Molecular and Population Genetics, Division of Genetics and Epidemiology, The Institute of Cancer Research, Surrey, UK.
authors.forename: Peter
authors.initials: P
authors.lastname: Broderick
authors.affiliation: Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
authors.forename: Niels
authors.initials: N
authors.lastname: Weinhold
authors.affiliation: Department of Haemato-Oncology, Division of Pathology, The Institute of Cancer Research, Surrey, UK.
authors.forename: Faith E
authors.initials: FE
authors.lastname: Davies
authors.affiliation: Leeds Institute of Molecular Medicine, Section of Clinical Trials Research, University of Leeds, Leeds, UK.
authors.forename: Walter A
authors.initials: WA
authors.lastname: Gregory
authors.affiliation: Royal Victoria Infirmary, Newcastle upon Tyne, UK.
authors.forename: Graham H
authors.initials: GH
authors.lastname: Jackson
authors.affiliation: Centre for Myeloma Research, Division of Molecular Pathology, The Institute of Cancer Research, Sutton, UK.
authors.forename: Martin
authors.initials: M
authors.lastname: Kaiser
authors.affiliation: Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
authors.forename: Gareth J
authors.initials: GJ
authors.lastname: Morgan
authors.affiliation: Molecular and Population Genetics, Division of Genetics and Epidemiology, The Institute of Cancer Research, Surrey, UK.
authors.forename: Richard S
authors.initials: RS
authors.lastname: Houlston
mesh_terms: D016022:Case-Control Studies; D020022:Genetic Predisposition to Disease; D014644:Genetic Variation; D015894:Genome, Human; D055106:Genome-Wide Association Study; D006801:Humans; D008957:Models, Genetic; D009101:Multiple Myeloma / Q000235:genetics* / Q000473:pathology; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D019655:Quantitative Trait, Heritable