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Purpose: The multicenter OPTIMUM (MUKnine) phase II trial investigated daratumumab, low-dose cyclophosphamide, lenalidomide, bortezomib, and dexamethasone (Dara-CVRd) before and after autologous stem-cell transplant (ASCT) in newly diagnosed patients with molecularly defined ultra-high-risk (UHiR) multiple myeloma (NDMM) or plasma cell leukemia (PCL). To provide clinical context, progression-free survival (PFS) and overall survival (OS) were referenced to contemporaneous outcomes seen in patients with UHiR NDMM treated in the recent Myeloma XI (MyeXI) trial., Methods: Transplant-eligible all-comers NDMM patients were profiled for UHiR disease, defined by presence of ≥2 genetic risk markers t(4;14)/t(14;16)/t(14;20), del(1p), gain(1q), and del(17p), and/or SKY92 gene expression risk signature. Patients with UHiR MM/PCL were offered treatment with Dara-CVRd induction, V-augmented ASCT, extended Dara-VR(d) consolidation, and Dara-R maintenance. UHiR patients treated in MyeXI with carfilzomib, lenalidomide, dexamethasone, and cyclophosphamide, or lenalidomide, dexamethasone, and cyclophosphamide, ASCT, and R maintenance or observation were identified by mirrored molecular screening. OPTIMUM PFS at 18 months (PFS18m) was compared against MyeXI using a Bayesian framework, and patients were followed up to the end of consolidation for PFS and OS., Results: Of 412 screened NDMM OPTIMUM patients, 103 were identified as UHiR or PCL and subsequently treated on trial with Dara-CVRd; 117 MyeXI patients identified as UHiR formed the external comparator arm, with comparable clinical and molecular characteristics to OPTIMUM. Comparison of PFS18m per Bayesian framework resulted in a 99.5% chance of OPTIMUM being superior to MyeXI. At 30 months' follow-up, PFS was 77% for OPTIMUM versus 39.8% for MyeXI, and OS 83.5% versus 73.5%, respectively. Extended post-ASCT Dara-VRd consolidation therapy was highly deliverable, with limited toxicity., Conclusion: Our results suggest that Dara-CVRd induction and extended post-ASCT Dara-VRd consolidation markedly improve PFS for UHiR NDMM patients over conventional management, supporting further evaluation of this strategy.

Despite recent advances in therapy, multiple myeloma essentially remains an incurable malignancy. Targeting tumour-specific essential genes, which constitute a druggable dependency, potentially offers a strategy for developing new therapeutic agents to treat MM and overcome drug resistance. To explore this possibility, we analysed DepMap project data identifying 23 MM essential genes and examined the relationship between their expression and patient outcome in three independent series totalling 1503 cases. The expression of TCF3 and FLVCR1 were both significantly associated with progression-free survival. IKBKB is already a drug target in other diseases, offering the prospect of repurposing to treat MM, while PIM2 is currently being investigated as a treatment for the disease. Our analysis supports the rationale of using large-scale genetic perturbation screens to guide the development of new therapeutic agents for MM., (© 2022. The Author(s).)

Structural chromosomal changes including copy number aberrations (CNAs) are a major feature of multiple myeloma (MM), however their evolution in context of modern biological therapy is not well characterized. To investigate acquisition of CNAs and their prognostic relevance in context of first-line therapy, we profiled tumor diagnosis-relapse pairs from 178 NCRI Myeloma XI (ISRCTN49407852) trial patients using digital multiplex ligation-dependent probe amplification. CNA profiles acquired at relapse differed substantially between MM subtypes: hyperdiploid (HRD) tumors evolved predominantly in branching pattern vs. linear pattern in t(4;14) vs. stable pattern in t(11;14). CNA acquisition also differed between subtypes based on CCND expression, with a marked enrichment of acquired del(17p) in CCND2 over CCND1 tumors. Acquired CNAs were not influenced by high-dose melphalan or lenalidomide maintenance randomization. A branching evolution pattern was significantly associated with inferior overall survival (OS; hazard ratio (HR) 2.61, P = 0.0048). As an individual lesion, acquisition of gain(1q) at relapse was associated with shorter OS, independent of other risk markers or time of relapse (HR = 2.00; P = 0.021). There is an increasing need for rational therapy sequencing in MM. Our data supports the value of repeat molecular profiling to characterize disease evolution and inform management of MM relapse.

Most patients with multiple myeloma (MM) die from progressive disease after relapse. To advance our understanding of MM evolution mechanisms, we performed whole-genome sequencing of 80 IGH-translocated tumour-normal newly diagnosed pairs and 24 matched relapsed tumours from the Myeloma XI trial. We identify multiple events as potentially important for survival and therapy-resistance at relapse including driver point mutations (e.g., TET2), translocations (MAP3K14), lengthened telomeres, and increased genomic instability (e.g., 17p deletions). Despite heterogeneous mutational processes contributing to relapsed mutations across MM subtypes, increased AID/APOBEC activity is particularly associated with shorter progression time to relapse, and contributes to higher mutational burden at relapse. In addition, we identify three enhanced major clonal evolution patterns of MM relapse, independent of treatment strategies and molecular karyotypes, questioning the viability of "evolutionary herding" approach in treating drug-resistant MM. Our data show that MM relapse is associated with acquisition of new mutations and clonal selection, and suggest APOBEC enzymes among potential targets for therapy-resistant MM.

The etiology of multiple myeloma (MM) is poorly understood. Summary data from genome-wide association studies (GWASs) of multiple phenotypes can be exploited in a Mendelian randomization (MR) phenome-wide association study (PheWAS) to search for factors influencing MM risk. We performed an MR-PheWAS analyzing 249 phenotypes, proxied by 10 225 genetic variants, and summary genetic data from a GWAS of 7717 MM cases and 29 304 controls. Odds ratios (ORs) per 1 standard deviation increase in each phenotype were estimated under an inverse variance weighted random effects model. A Bonferroni-corrected threshold of P = 2 × 10-4 was considered significant, whereas P < .05 was considered suggestive of an association. Although no significant associations with MM risk were observed among the 249 phenotypes, 28 phenotypes showed evidence suggestive of association, including increased levels of serum vitamin B6 and blood carnitine (P = 1.1 × 10-3) with greater MM risk and ω-3 fatty acids (P = 5.4 × 10-4) with reduced MM risk. A suggestive association between increased telomere length and reduced MM risk was also noted; however, this association was primarily driven by the previously identified risk variant rs10936599 at 3q26 (TERC). Although not statistically significant, increased body mass index was associated with increased risk (OR, 1.10; 95% confidence interval, 0.99-1.22), supporting findings from a previous meta-analysis of prospective observational studies. Our study did not provide evidence supporting any modifiable factors examined as having a major influence on MM risk; however, it provides insight into factors for which the evidence has previously been mixed., (© 2020 by The American Society of Hematology.)

Multiple myeloma (MM) is the second most common blood malignancy. Epidemiological family studies going back to the 1920s have provided evidence for familial aggregation, suggesting a subset of cases have an inherited genetic background. Recently, studies aimed at explaining this phenomenon have begun to provide direct evidence for genetic predisposition to MM. Genome-wide association studies have identified common risk alleles at 24 independent loci. Sequencing studies of familial cases and kindreds have begun to identify promising candidate genes where variants with strong effects on MM risk might reside. Finally, functional studies are starting to give insight into how identified risk alleles promote the development of MM. Here, we review recent findings in MM predisposition field, and highlight open questions and future directions.

Background: While genome-wide association studies (GWAS) of multiple myeloma (MM) have identified variants at 23 regions influencing risk, the genes underlying these associations are largely unknown. To identify candidate causal genes at these regions and search for novel risk regions, we performed a multi-tissue transcriptome-wide association study (TWAS)., Results: GWAS data on 7319 MM cases and 234,385 controls was integrated with Genotype-Tissue Expression Project (GTEx) data assayed in 48 tissues (sample sizes, N = 80-491), including lymphocyte cell lines and whole blood, to predict gene expression. We identified 108 genes at 13 independent regions associated with MM risk, all of which were in 1 Mb of known MM GWAS risk variants. Of these, 94 genes, located in eight regions, had not previously been considered as a candidate gene for that locus., Conclusions: Our findings highlight the value of leveraging expression data from multiple tissues to identify candidate genes responsible for GWAS associations which provide insight into MM tumorigenesis. Among the genes identified, a number have plausible roles in MM biology, notably APOBEC3C, APOBEC3H, APOBEC3D, APOBEC3F, APOBEC3G, or have been previously implicated in other malignancies. The genes identified in this TWAS can be explored for follow-up and validation to further understand their role in MM biology.

To gain insight into multiple myeloma (MM) tumorigenesis, we analyzed the mutational signatures in 874 whole-exome and 850 whole-genome data from the CoMMpass Study. We identified that coding and non-coding regions are differentially dominated by distinct single-nucleotide variant (SNV) mutational signatures, as well as five de novo structural rearrangement signatures. Mutational signatures reflective of different principle mutational processes-aging, defective DNA repair, and apolipoprotein B editing complex (APOBEC)/activation-induced deaminase activity-characterize MM. These mutational signatures show evidence of subgroup specificity-APOBEC-attributed signatures associated with MAF translocation t(14;16) and t(14;20) MM; potentially DNA repair deficiency with t(11;14) and t(4;14); and aging with hyperdiploidy. Mutational signatures beyond that associated with APOBEC are independent of established prognostic markers and appear to have relevance to predicting high-risk MM.

Genomic regions of homozygosity (ROH), detectable in outbred populations, have been implicated as determinants of inherited risk. To examine whether ROH is associated with risk of multiple myeloma (MM), we performed whole-genome homozygosity analysis using single-nucleotide polymorphism genotype data from 2,282 MM cases and 5,197 controls, with replication in an additional 878 MM cases and 7,083 controls. Globally, the distribution of ROH between cases and controls was not significantly different. However, one ROH at chromosome 9q21, harboring the B-cell transcription factor gene KLF9, showed evidence of a consistent association and may therefore warrant further investigation as a candidate risk factor for MM. Overall, our analysis provides little support for a homozygosity signature being a significant factor in MM risk., (© 2019 The Authors. Annals of Human Genetics published by University College London (UCL) and John Wiley & Sons Ltd.)

The clustering of different types of B-cell malignancies in families raises the possibility of shared aetiology. To examine this, we performed cross-trait linkage disequilibrium (LD)-score regression of multiple myeloma (MM) and chronic lymphocytic leukaemia (CLL) genome-wide association study (GWAS) data sets, totalling 11,734 cases and 29,468 controls. A significant genetic correlation between these two B-cell malignancies was shown (R g  = 0.4, P = 0.0046). Furthermore, four of the 45 known CLL risk loci were shown to associate with MM risk and five of the 23 known MM risk loci associate with CLL risk. By integrating eQTL, Hi-C and ChIP-seq data, we show that these pleiotropic risk loci are enriched for B-cell regulatory elements and implicate B-cell developmental genes. These data identify shared biological pathways influencing the development of CLL and, MM and further our understanding of the aetiological basis of these B-cell malignancies.

Multiple myeloma (MM) is a genetically heterogeneous cancer of bone marrow plasma cells with variable outcome. To assess the prognostic relevance of clonal heterogeneity of TP53 copy number, we profiled tumors from 1777 newly diagnosed Myeloma XI trial patients with multiplex ligation-dependent probe amplification (MLPA). Subclonal TP53 deletions were independently associated with shorter overall survival, with a hazard ratio of 1.8 (95% confidence interval, 1.2-2.8; P = .01). Clonal, but not subclonal, TP53 deletions were associated with clinical markers of advanced disease, specifically lower platelet counts ( P < .001) and increased lactate dehydrogenase ( P < .001), as well as a higher frequency of features indicative of genomic instability, del(13q) ( P = .002) or del(1p) ( P = .006). Biallelic TP53 loss-of-function by mutation and deletion was rare (2.4%) and associated with advanced disease. We present a framework for identifying subclonal TP53 deletions by MLPA, to improve patient stratification in MM and tailor therapy, enabling management strategies., (© 2018 by The American Society of Hematology.)

Multiple myeloma (MM) is a biologically heterogeneous malignancy, however, the mechanisms underlying this complexity are incompletely understood. We report an analysis of the whole-genome sequencing of 765 MM patients from CoMMpass. By employing promoter capture Hi-C in naïve B-cells, we identify cis-regulatory elements (CREs) that represent a highly enriched subset of the non-coding genome in which to search for driver mutations. We identify regulatory regions whose mutation significantly alters the expression of genes as candidate non-coding drivers, including copy number variation (CNV) at CREs of MYC and single-nucleotide variants (SNVs) in a PAX5 enhancer. To better inform the interplay between non-coding driver mutations with other driver mechanisms, and their respective roles in oncogenic pathways, we extended our analysis identifying coding drivers in 40 genes, including 11 novel candidates. We demonstrate the same pathways can be targeted by coding and non-coding mutations; exemplified by IRF4 and PRDM1, along with BCL6 and PAX5, genes that are central to plasma cell differentiation. This study reveals new insights into the complex genetic alterations driving MM development and an enhanced understanding of oncogenic pathways.

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.

Robust establishment of survival in multiple myeloma (MM) and its relationship to recurrent genetic aberrations is required as outcomes are variable despite apparent similar staging. We assayed copy number alterations (CNA) and translocations in 1036 patients from the NCRI Myeloma XI trial and linked these to overall survival (OS) and progression-free survival. Through a meta-anlysis of these data with data from MRC Myeloma IX trial, totalling 1905 newly diagnosed MM patients (NDMM), we confirm the association of t(4;14), t(14;16), t(14;20), del(17p) and gain(1q21) with poor prognosis with hazard ratios (HRs) for OS of 1.60 (P=4.77 × 10 -7 ), 1.74 (P=0.0005), 1.90 (P=0.0089), 2.10 (P=8.86 × 10 -14 ) and 1.68 (P=2.18 × 10 -14 ), respectively. Patients with 'double-hit' defined by co-occurrence of at least two adverse lesions have an especially poor prognosis with HRs for OS of 2.67 (P=8.13 × 10 -27 ) for all patients and 3.19 (P=1.23 × 10 -18 ) for intensively treated patients. Using comprehensive CNA and translocation profiling in Myeloma XI we also demonstrate a strong association between t(4;14) and BIRC2/BIRC3 deletion (P=8.7 × 10 -15 ), including homozygous deletion. Finally, we define distinct sub-groups of hyperdiploid MM, with either gain(1q21) and CCND2 overexpression (P<0.0001) or gain(11q25) and CCND1 overexpression (P<0.0001). Profiling multiple genetic lesions can identify MM patients likely to relapse early allowing stratification of treatment.

Background: Multiple Myeloma is a cancer of plasma cells associated with significantly reduced survival. Long term survivorship from myeloma is very rare and despite advances in its treatment the disease is generally considered incurable. We report a patient diagnosed with myeloma carrying a germline mutation of a tumour suppressor gene who has effectively been cured., Case Presentation: A 36-year-old woman was diagnosed with IgG lambda myeloma in 1985. She was treated with melphalan chemotherapy followed by high-dose melphalan and autologous stem cell rescue and since remained in complete remission despite not having received any additional therapy. After eliciting a prior history of multiple primary melanomas and breast cancer, she was tested for and shown to be a carrier for a germline mutation in CDKN2A., Conclusions: This is the second case report of germline mutation of CDKN2A being associated with myeloma. CDKN2A is a stabiliser of p53. Long term survivorship after high dose DNA damaging chemotherapy with melphalan in this patient is compatible with an increased chemo-sensitivity due to impairment of the DNA repair pathway.

Recent studies suggest that the evolutionary history of a cancer is important in forecasting clinical outlook. To gain insight into the clonal dynamics of multiple myeloma (MM) and its possible influence on patient outcomes, we analyzed whole exome sequencing tumor data for 333 patients from Myeloma XI, a UK phase 3 trial and 434 patients from the CoMMpass study, all of which had received immunomodulatory drug (IMiD) therapy. By analyzing mutant allele frequency distributions in tumors, we found that 17% to 20% of MM is under neutral evolutionary dynamics. These tumors are associated with poorer patient survival in nonintensively treated patients, which is consistent with the reduced therapeutic efficacy of microenvironment-modulating IMiDs. Our findings provide evidence that knowledge of the evolutionary history of MM has relevance for predicting patient outcomes and personalizing therapy., (© 2017 by The American Society of Hematology.)

Multiple myeloma (MM) is a malignancy of plasma cells. Genome-wide association studies have shown that variation at 5q15 influences MM risk. Here, we have sought to decipher the causal variant at 5q15 and the mechanism by which it influences tumorigenesis. We show that rs6877329 G > C resides in a predicted enhancer element that physically interacts with the transcription start site of ELL2. The rs6877329-C risk allele is associated with reduced enhancer activity and lowered ELL2 expression. Since ELL2 is critical to the B cell differentiation process, reduced ELL2 expression is consistent with inherited genetic variation contributing to arrest of plasma cell development, facilitating MM clonal expansion. These data provide evidence for a biological mechanism underlying a hereditary risk of MM at 5q15., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

The genetic basis underlying the inherited risk of developing multiple myeloma (MM) is largely unknown. To examine the impact of rare protein altering variants on the risk of developing MM we analyzed high-coverage exome sequencing data on 513 MM cases and 1,569 healthy controls, performing both single variant and gene burden tests. We did not identify any recurrent coding low-frequency alleles (1-5%) with moderate effect that were statistically associated with MM. In a gene burden analysis we did however identify a promising relationship between variation in the marrow kinetochore microtubule stromal gene KIF18A, which plays a role in control mitotic chromosome positioning dynamics, and risk of MM (P =3.6x10-6). Further analysis showed KIF18A displays a distinct pattern of expression across molecular subgroups of MM as well as being associated with patient survival. Our results inform future study design and provide a resource for contextualizing the impact of candidate MM susceptibility genes.

B-cell malignancies (BCM) originate from the same cell of origin, but at different maturation stages and have distinct clinical phenotypes. Although genetic risk variants for individual BCMs have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. We explored genome-wide association studies of chronic lymphocytic leukaemia (CLL, N = 1,842), Hodgkin lymphoma (HL, N = 1,465) and multiple myeloma (MM, N = 3,790). We identified a novel pleiotropic risk locus at 3q22.2 (NCK1, rs11715604, P = 1.60 × 10 -9 ) with opposing effects between CLL (P = 1.97 × 10 -8 ) and HL (P = 3.31 × 10 -3 ). Eight established non-HLA risk loci showed pleiotropic associations. Within the HLA region, Ser37 + Phe37 in HLA-DRB1 (P = 1.84 × 10 -12 ) was associated with increased CLL and HL risk (P = 4.68 × 10 -12 ), and reduced MM risk (P = 1.12 × 10 -2 ), and Gly70 in HLA-DQB1 (P = 3.15 × 10 -10 ) showed opposing effects between CLL (P = 3.52 × 10 -3 ) and HL (P = 3.41 × 10 -9 ). By integrating eQTL, Hi-C and ChIP-seq data, we show that the pleiotropic risk loci are enriched for B-cell regulatory elements, as well as an over-representation of binding of key B-cell transcription factors. These data identify shared biological pathways influencing the development of CLL, HL and MM. The identification of these risk loci furthers our understanding of the aetiological basis of BCMs.

Genome-wide association studies have identified several risk loci for multiple myeloma (MM); however, the mechanisms by which they influence MM are unknown. Here by using genetic association data and functional characterization, we demonstrate that rs4487645 G>T, the most highly associated variant (P = 5.30 × 10 -25 ), resides in an enhancer element 47 kb upstream of the transcription start site of c-Myc-interacting CDCA7L. The G-risk allele, associated with increased CDCA7L expression (P=1.95 × 10 -36 ), increases IRF4 binding and the enhancer interacts with the CDCA7L promoter. We show that suppression of CDCA7L limits MM proliferation through apoptosis, and increased CDCA7L expression is associated with adverse patient survival. These findings implicate IRF4-mediated CDCA7L expression in MM biology and indicate how germline variation might confer susceptibility to MM.

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.

A major complication of multiple myeloma (MM) is the development of osteolytic lesions, fractures and bone pain. To identify genetic variants influencing the development of MM bone disease (MBD), we analyzed MM patients of European ancestry (totaling 3774), which had been radiologically surveyed for MBD. Each patient had been genotyped for ~6 00 000 single-nucleotide polymorphisms with genotypes for six million common variants imputed using 1000 Genomes Project and UK10K as reference. We identified a locus at 8q24.12 for MBD (rs4407910, OPG/TNFRSF11B, odds ratio=1.38, P=4.09 × 10(-9)) and a promising association at 19q13.43 (rs74676832, odds ratio=1.97, P=9.33 × 10(-7)). Our findings demonstrate that germline variation influences MBD and highlights the importance of RANK/RANKL/OPG pathway in MBD development. These findings will contribute to the development of future strategies for prevention of MBD in the early precancerous phases of MM.

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 ∼600,000 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.

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.

Monoclonal gammopathy of undetermined significance (MGUS) is present in ∼2% of individuals age >50 years. The increased risk of multiple myeloma (MM) in relatives of individuals with MGUS is consistent with MGUS being a marker of inherited genetic susceptibility to MM. Common single-nucleotide polymorphisms (SNPs) at 2p23.3 (rs6746082), 3p22.1 (rs1052501), 3q26.2 (rs10936599), 6p21.33 (rs2285803), 7p15.3 (rs4487645), 17p11.2 (rs4273077), and 22q13.1 (rs877529) have recently been shown to influence MM risk. To examine the impact of these 7 SNPs on MGUS, we analyzed two case-control series totaling 492 cases and 7306 controls. Each SNP independently influenced MGUS risk with statistically significant associations (P < .02) for rs1052501, rs2285803, rs4487645, and rs4273077. SNP associations were independent, with risk increasing with a larger number of risk alleles carried (per allele odds ratio, 1.18; P < 10(-7)). Collectively these data are consistent with a polygenic model of disease susceptibility to MGUS.

Although the familial clustering of multiple myeloma (MM) supports the role of inherited susceptibility, only recently has direct evidence for genetic predisposition been demonstrated. A meta-analysis of two genome-wide association (GWA) studies has identified single-nucleotide polymorphisms (SNPs) localising to a number of genomic regions that are robustly associated with MM risk. In this review, we provide an overview of the evidence supporting a genetic contribution to the predisposition to MM and MGUS (monoclonal gammopathy of unknown significance), and the insight this gives into the biological basis of disease aetiology. We also highlight the promise of future approaches to identify further specific risk factors and their potential clinical utility.

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., Competing Interests: Statement The authors declare no competing financial interests.

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., Competing Interests: Statement The authors declare no competing financial interests.

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., Competing Interests: Statement The authors declare no competing financial interests.