ABSTRACT
The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, in the original HTML version of this Article, the order of authors within the author list was incorrect. The PRACTICAL consortium was incorrectly listed after Richard S. Houlston and should have been listed after Nora Pashayan. This error has been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.
ABSTRACT
Genome-wide association studies (GWAS) have transformed our understanding of susceptibility to multiple myeloma (MM), but much of the heritability remains unexplained. We report a new GWAS, a meta-analysis with previous GWAS and a replication series, totalling 9974 MM cases and 247,556 controls of European ancestry. Collectively, these data provide evidence for six new MM risk loci, bringing the total number to 23. Integration of information from gene expression, epigenetic profiling and in situ Hi-C data for the 23 risk loci implicate disruption of developmental transcriptional regulators as a basis of MM susceptibility, compatible with altered B-cell differentiation as a key mechanism. Dysregulation of autophagy/apoptosis and cell cycle signalling feature as recurrently perturbed pathways. Our findings provide further insight into the biological basis of MM.
Subject(s)
Genetic Predisposition to Disease , Multiple Myeloma/genetics , Polymorphism, Single Nucleotide , Bayes Theorem , Chromatin/chemistry , Chromatin Immunoprecipitation , Female , Gene Expression Regulation , Genome-Wide Association Study , Genotype , Humans , Male , Promoter Regions, Genetic , Quality Control , Quantitative Trait Loci , Risk , White People/geneticsABSTRACT
Multiple myeloma (MM) is a plasma cell malignancy with a significant heritable basis. Genome-wide association studies have transformed our understanding of MM predisposition, but individual studies have had limited power to discover risk loci. Here we perform a meta-analysis of these GWAS, add a new GWAS and perform replication analyses resulting in 9,866 cases and 239,188 controls. We confirm all nine known risk loci and discover eight new loci at 6p22.3 (rs34229995, P=1.31 × 10(-8)), 6q21 (rs9372120, P=9.09 × 10(-15)), 7q36.1 (rs7781265, P=9.71 × 10(-9)), 8q24.21 (rs1948915, P=4.20 × 10(-11)), 9p21.3 (rs2811710, P=1.72 × 10(-13)), 10p12.1 (rs2790457, P=1.77 × 10(-8)), 16q23.1 (rs7193541, P=5.00 × 10(-12)) and 20q13.13 (rs6066835, P=1.36 × 10(-13)), which localize in or near to JARID2, ATG5, SMARCD3, CCAT1, CDKN2A, WAC, RFWD3 and PREX1. These findings provide additional support for a polygenic model of MM and insight into the biological basis of tumour development.
Subject(s)
Multiple Myeloma/genetics , Adaptor Proteins, Signal Transducing/genetics , Autophagy-Related Protein 5/genetics , Case-Control Studies , Chromosomal Proteins, Non-Histone , Cyclin-Dependent Kinase Inhibitor p16 , Cyclin-Dependent Kinase Inhibitor p18/genetics , Genetic Predisposition to Disease , Genome-Wide Association Study , Guanine Nucleotide Exchange Factors/genetics , Humans , Polycomb Repressive Complex 2/genetics , RNA, Long Noncoding/genetics , Transcription Factors/genetics , Ubiquitin-Protein Ligases/geneticsABSTRACT
Survival following a diagnosis of multiple myeloma (MM) varies between patients and some of these differences may be a consequence of inherited genetic variation. In this study, to identify genetic markers associated with MM overall survival (MM-OS), we conduct a meta-analysis of four patient series of European ancestry, totalling 3,256 patients with 1,200 MM-associated deaths. Each series is genotyped for â¼600,000 single nucleotide polymorphisms across the genome; genotypes for six million common variants are imputed using 1000 Genomes Project and UK10K as the reference. The association between genotype and OS is assessed by Cox proportional hazards model adjusting for age, sex, International staging system and treatment. We identify a locus at 6q25.1 marked by rs12374648 associated with MM-OS (hazard ratio=1.34, 95% confidence interval=1.22-1.48, P=4.69 × 10(-9)). Our findings have potential clinical implications since they demonstrate that inherited genotypes can provide prognostic information in addition to conventional tumor acquired prognostic factors.
Subject(s)
Chromosomes, Human, Pair 6/genetics , Multiple Myeloma/genetics , Aged , Female , Genome-Wide Association Study , Genotype , Humans , Male , Middle Aged , Multiple Myeloma/mortality , Polymorphism, Single Nucleotide , Prognosis , Proportional Hazards Models , White People/geneticsABSTRACT
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.
Subject(s)
Genetic Predisposition to Disease , Genome, Human , Multiple Myeloma/genetics , Polymorphism, Single Nucleotide , Quantitative Trait, Heritable , Case-Control Studies , Genetic Variation , Genome-Wide Association Study , Humans , Models, Genetic , Multiple Myeloma/pathology , PhenotypeABSTRACT
To identify variants for multiple myeloma risk, we conducted a genome-wide association study with validation in additional series totaling 4,692 individuals with multiple myeloma (cases) and 10,990 controls. We identified four risk loci at 3q26.2 (rs10936599, P = 8.70 × 10(-14)), 6p21.33 (rs2285803, PSORS1C2, P = 9.67 × 10(-11)), 17p11.2 (rs4273077, TNFRSF13B, P = 7.67 × 10(-9)) and 22q13.1 (rs877529, CBX7, P = 7.63 × 10(-16)). These data provide further evidence for genetic susceptibility to this B-cell hematological malignancy, as well as insight into the biological basis of predisposition.
Subject(s)
Chromosome Aberrations , Chromosomes, Human , Genetic Predisposition to Disease , Multiple Myeloma/genetics , Case-Control Studies , HumansABSTRACT
A number of specific chromosomal abnormalities define the subgroups of multiple myeloma. In a meta-analysis of two genome-wide association studies of multiple myeloma including a total of 1,661 affected individuals, we investigated risk for developing a specific tumor karyotype. The t(11;14)(q13;q32) translocation in which CCND1 is placed under the control of the immunoglobulin heavy chain enhancer was strongly associated with the CCND1 c.870G>A polymorphism (P = 7.96 × 10(-11)). These results provide a model in which a constitutive genetic factor is associated with risk of a specific chromosomal translocation.
Subject(s)
Chromosomes, Human, Pair 11/genetics , Chromosomes, Human, Pair 14/genetics , Cyclin D1/genetics , Genome-Wide Association Study , Multiple Myeloma/etiology , Polymorphism, Single Nucleotide/genetics , Translocation, Genetic , Case-Control Studies , Genome, Human , Genotype , Humans , In Situ Hybridization, Fluorescence , Karyotyping , Phenotype , Risk FactorsABSTRACT
To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control subjects. We identified risk loci for multiple myeloma at 3p22.1 (rs1052501 in ULK4; odds ratio (OR) = 1.32; P = 7.47 × 10(-9)) and 7p15.3 (rs4487645, OR = 1.38; P = 3.33 × 10(-15)). In addition, we observed a promising association at 2p23.3 (rs6746082, OR = 1.29; P = 1.22 × 10(-7)). Our study identifies new genomic regions associated with multiple myeloma risk that may lead to new etiological insights.
