Inherited genetic susceptibility to multiple myeloma

REVIEW

Inherited genetic susceptibility to multiple myelomaGJ Morgan1, DC Johnson1, N Weinhold2, H Goldschmidt2, O Landgren3, HT Lynch4, K Hemminki5,6 and RS Houlston7

Although the familial clustering of multiple myeloma (MM) supports the role of inherited susceptibility, only recently has directevidence for genetic predisposition been demonstrated. A meta-analysis of two genome-wide association (GWA) studies hasidentified single-nucleotide polymorphisms (SNPs) localising to a number of genomic regions that are robustly associated with MMrisk. In this review, we provide an overview of the evidence supporting a genetic contribution to the predisposition to MM andMGUS (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.

Leukemia (2014) 28, 518–524; doi:10.1038/leu.2013.344

Keywords: myeloma; SNP; MGUS

EPIDEMIOLOGICAL STUDIESEpidemiological studies have established increasing age, malegender, familial background and a past history of MGUS as beingrisk factors for MM.1 MGUS is detectable in 3–5% of individualsaged 50 years or older in European populations2 and is typicallyassociated with an annual risk of progression to MM of around 1%.As MGUS plasma cells have many of the genetic characteristics ofMM plasma cells, it has been suggested that MM is alwayspreceded by a MGUS phase. This is supported by long-termfollow-up studies in a sample set of 77 469 healthy adults who hadbanked serum samples3 and a military cohort.2,4 Observationstherefore indicate that susceptibility to MM is either shared withMGUS risk or related to the transition between the twopathological states.

A number of lifestyle and environmental risk factors have beenproposed to increase MM risk, including obesity,5 immunedysfunction, agricultural, chemical6 and radiation exposure.1 Theresults from these purported associations are, however, notconcordant between independent studies possibly reflectingissues with study design.1 Obesity is probably the mostconsistently reported association and various mechanisms havebeen proposed to explain the relationship including increasedoxidative stress, alterations in immunologic response, metabolicresponse and the levels of endogenous hormones (for example,sex steroids, insulin and insulin-like growth factor-1). A number ofstudies have also suggested that the risk of MM may be related toautoimmunity or its treatment.7

FAMILIAL EPIDEMIOLOGICAL STUDIESCase reports of the familial clustering of MM provide support forthe role of inherited factors in disease aetiology. Epidemiologicalcase–control and cohort studies have consistently shown anincreased risk of MM or MGUS in first-degree relatives of patientswith MM or MGUS.8–11 The largest study to date, involving

11 752 MM patients diagnosed in Sweden between 1958 and2002, showed that the risk of MM was increased 4.25-fold in first-degree relatives (95% CI: 1.81–8.41).8 A survey carried out by theUtah Cancer Registry, making use of family data from 1354 cases,confirms this association but also demonstrated a relationshipwith risk of prostate and melanoma,12 a finding supported by twoother reports.13–15 Two studies have shown the risk of MM andMGUS is increased threefold in relatives of individuals withMGUS.16,17 In addition, it was observed that there was also anincreased risk of developing NHL and CLL8,9,18,19 Collectively, thesedata are consistent with an inherited genetic susceptibility to MM,which is somewhere in the order of two- to fourfold. In addition tothis epidemiological data, over 100 MM families (Table 1) havebeen described in the literature, recent reports coming fromUS,20,21 France,22,23 Sweden8 and Iceland.10 As well as providingevidence for inherited predisposition to MM some of thesefamilies show MM present in three generations (Figure 1)compatible with Mendelian transmission of the risk.23–26

RACIAL DIFFERENCESRacial differences in the risk of developing MM are wellrecognised, with a greater prevalence of MGUS and MM beingseen in African Americans as compared with those with EuropeanAncestry.4,27,28 A study based on US Veterans found a two tothreefold higher prevalence of MGUS among African Americanscompared with Caucasians, while the risk of transformation fromMGUS to MM was the same.29 An increased prevalence of MGUSrelative to whites has also been reported from Ghana,4,30 whereasrates of MGUS and MM in American Chinese, Japanese andMexicans populations are lower.31,32 Recent data from the UnitedStates has found that the mean age at diagnosis of myeloma is65.8 and 69.8 years for African Americans and Caucasians,respectively.33 Although inequalities and confounding effectsdue to environment and behavioural factors cannot beexcluded, both the higher rates and earlier age of onset of MM

1Haemato-Oncology Research Unit, Division of Molecular Pathology, Institute of Cancer Research, Surrey, UK; 2Department of Internal Medicine V, University of Heidelberg,Heidelberg, Germany; 3Multiple Myeloma Section, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA; 4Department of Preventive Medicine, Creighton’sHereditary Cancer Center, Omaha, NE, USA; 5Division of Molecular Genetic Epidemiology, German Cancer Research Centre (DKFZ), Heidelberg, Germany; 6Center for PrimaryHealth Care Research, Lund University, Malmo, Sweden and 7Division of Genetics and Epidemiology, Institute of Cancer Research, Surrey, UK. Correspondence: ProfessorGJ Morgan, Haemato-Oncology Research Unit, Division of Molecular Pathology, The Institute of Cancer Research, 15 Cotswold Road, Sutton SM2 5NG, UK.E-mail: [email protected] 30 July 2013; revised 15 October 2013; accepted 17 October 2013; accepted article preview online 19 November 2013; advance online publication, 20 December 2013

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in African Americans is supportive of a genetic contribution to theaetiology of MM.33

GENETIC ASSOCIATIONSUntil recently, the search for genetic variants influencing MM riskhas almost exclusively been based on analyses of polymorphismsin candidate genes. In reviewing the published literature ongenetic association studies in MM catalogued by PUBMED since2000, six major hypotheses have been examined, including therole of cytokines and immune response, DNA repair, folatemetabolism, ADME (absorption, distribution, metabolism andexcretion), insulin-like growth factors and apoptosis.29,47–52

Studies have reported positive associations with MM risk, butnone of these studies report associations lower than the stringentthreshold of genome-wide significance of 5� 10� 8 withindependent replication. Most of these associations have beenbased on small sample sizes with limited accountancy forpopulation substructure or cryptic-relatedness, and thereforehave limited power to robustly demonstrate a relationship

between genotype and MM risk. The nature and design of thesestudies have been reviewed previously.52–54 Importantly, withouta clear understanding of the biological basis of MM developmentdeciding what represents a candidate gene is inherently difficult.Although future association studies with greater cases andcontrols may be powered to replicate some of these previouslydescribed candidate gene study associations.

GENOME-WIDE ANALYSESCataloguing the haplotype structure of the human genome hasled to the development of a comprehensive set of tagging SNPsthat capture common genetic variation. The analysis of around500 000 of these tagSNPs allows for the search of commonvariants influencing cancer risk to be conducted on a genome-wide basis. Such studies are agnostic and are not based onpreconceptions of biology such as those used in candidate genestudies. Genome-wide association studies (GWAS) have beenconducted on most common cancers and multiple risk lociidentified. As well as vindicating the long-held hypothesis of

Table 1. A summary of MM families with 42MM cases that have been described in the literature

Author Year No. offamilies

No. of MMindividuals

No. of MGUSindividuals

Relationship of another MMindividual with proband

Relationship of another MGUSindividual with proband

MM Pedigrees/case reportsShoenfeld et al.34 1982 37 94 NA 4—Parent–child

26—sibling pairs3—larger sibling group

NA

McCrea and Morris35 1986 6 13 NA 3—parent–child7—sibling pairs3—larger sibling group

NA

Roddie et al.36 1998 1 3 NA 2—Sibling pairs NAGrosbois et al.22 1999 15 30 3 6—Parent–child

10—Sibling pairs1—Larger sibling group

3—Larger sibling group

Lynch et al.37 2001 1 3 2 2—Sibling pairs 2—Sibling pairsSobol et al.23 2001 1 6 NA 2—Parent-child

2—Sibling pairs1—Larger sibling group

NA

Lynch et al.21 2005 39 74 4 20—Parent–child12—Sibling pairs2—Larger sibling group

NA

Ogmundsdottir et al.11 2005 4 8 6 2—Sibling pairs2—Larger sibling group

1—parent–child1—sibling pairs4—larger sibling group

Gerkes et al.38 2007 2 5 NA 3—Parent–child1—Sibling pairs

NA

Lynch et al.26 2008 1 5 1 2—Sibling pairs2—Larger sibling group

3—sibling pairs1—larger sibling group

Jain et al.24 2009 8 11 8 2—Parent–child3—Sibling pairs

2—parent–child5—sibling pairs

Grass et al.39 2011 4 6 4 1—Parent–child2—Sibling pairs

1—Parent–child2—sibling pairs1—larger sibling group

MM TwinsOgawa et al.40 1970 1 2 NA Monozygotic twin NAJudson et al.41 1985 1 2 NA Monozygotic twin NAMcCrea and Morris35 1986 1 2 NA Monozygotic twin NAComotti et al.42 1987 1 2 NA Monozygotic twin NASnowden and Greaves43 1995 1 2 NA Monozygotic twin NAOlujohungbe et al.44 2006 1 2 NA Monozygotic twin NA

MM families within cancer registriesLichtenstein et al.45 2000 1 2 NA Monozygotic twin NAHemminki46 2002 8 16 NA 8—Parent-child NAAltieri et al.8 2006 32 NA NA NA NA

Abbreviation: NA, not applicable.

Inherited genetic susceptibility to MMGJ Morgan et al

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polygenic inheritance to cancer, the loci identified haveprovided novel insights into the genes influencing risk. Twogenome-wide association studies of MM have been recentlyreported.55,56 The initial meta-analysis of UK and German GWASstudies comprises 1675 MM cases and 5903 controls;55 thesestudies were then extended in a second meta-analysis combining4692 MM cases and 10 990 controls.56 Cases and controls weredrawn from populations of Northern and Western Europeandescent. The studies identified SNPs at chromosomes 2p23.3,3p22.1, 3q26.2, 6p21.33, 7p15.3, 17p11.2 and 22q13.1 robustlyassociated with risk of MM, Table 2. Importantly none of the genesannotated by SNPs at these loci have previously been evaluated incandidate gene studies.

The 2p23.3 association annotates a gene, DNA (cytosine-5)-methyltransferase 3 alpha (DNMT3A) that encodes a DNAmethyltransferase.57–59 DNMT3A is highly expressed gene in MM-regulating cytokines such as IFN-g, TNFa and IL-4.60,61 In addition,DNMT3A directly interacts with MYC, a key myeloma related gene,as well as acting as a co-repressor through methylation ofpromoters at genes including the cyclin-dependent kinaseinhibitors p21Cip1 and p15INK4B.62

The 3p22.1 association is associated with the A542T poly-morphism in the serine/threonine-protein kinase unc-51-like kinase4 (ULK4) gene. ULK4 is highly expressed in MM, and the Atg1/ULKcomplex is a key regulator of mTOR-mediated autophagy. Theregion of LD to which ULK1 A542T maps also encompasses theB-catenin gene (CTNNB1), which is known to activate transcriptionfactors including MYC.63 A correlation between the expression ofthe ULK4 and CTNNB1 exists, suggesting the possibility of theshared regulation of this region in MM.64,65

The 3q26.2 association is defined by a SNP mapping 50 to thetelomerase RNA component gene (TERC). TERC is the ncRNAcomponent of telomerase that together with telomerase reversetranscriptase (TERT) form part of a ribonuclear protein complex thathelps maintains telomere ends. Interestingly, telomerase reactivationand telomerase-mediated elongation of shorter telomeres is afeature of MM66 and the major allele is associated with longertelomeres; thus there is strong a priori evidence for genetic variationat this locus having a role in MM.67,68 Variants at this locus have alsobeen associated with prostate cancer69 and colorectal cancer.70

The 6p21.33 SNP association localises to intron 5 of a putativepsoriasis susceptibility gene (PSORS1C1), but it is entirely possiblebecause of the LD structure across this region, that the associationreflects variation within the extended MHC region and hence HLAgenotype.

The 7p15.3 SNP association encompasses the 30 part of theCDCA7L (cell division cycle associated 7-like) gene and theDNAH11 (dynein, axonemal, heavy chain 11 (MIM 603339)) gene.DNAH11 has exonic mutations and is also affected by translocationin cases of MM.71 CDCA7L is expressed at relatively high levels andincreases on the progression from ‘MGUS’ to ‘MM’ in mice.72

Interestingly, in the context of the mechanism underlying MM risk,CDCA7L is a cell cycle-related gene that directly interacts with MYC(c-Myc).73–75 Expression of a set of conserved miRNAs in the 30-UTRof CDCA7L is higher in MM cell lines compared with a normalplasma cell control.76 hsa-miR-25 and hsa-miR-32 are among agroup miRNA that are upregulated in MM and predicted toregulate CDCA7L.77,78 Thus, there is a plausible hypothesissupporting a role for CDCA7L in mediating MM risk throughactivation of downstream growth control genes.79

Figure 1. Pedigree showing family members with multiple myeloma or monoclonal gammopathy of undetermined significance (MGUS). Thisis an updated pedigree first published, Lynch et al.26


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The 17p11.2 SNP association maps within intron 2 of tumournecrosis factor receptor superfamily member 13B (TNFRSF13B).TNFRSF13B also known as TACI (transmembrane activator andcalcium modulator and cyclophilin ligand interactor) has a key rolein promoting differentiation of Ig-secreting cells. Variation at thischromosome region has been implicated as a determinant ofcirculating immunoglobulin levels.80,81 TNFRSF13B is preferentiallyexpressed on marginal zone B cells, CD27þ memory B-cellsubsets and plasma cells.82 TNFRSF13B is receptor for key MMgrowth factors BAFF and APRIL,83 and mutations identified inTNFRSF13B can activate the classical NFkB pathway.84

The 22q13.1 SNP association localises to intron 2 of the geneencoding chromobox homologue 7 (CBX7). CBX7 encodes apolycomb group protein (PcG) known to be downregulated inmany cancers.85–88 It is thought to be a tumour suppressornegatively regulating CCNE1 expression.89 These proteins formpart of a gene regulatory mechanism that determines cell fateduring development as well as contributing to the control of cellgrowth and differentiation.90 High levels of CBX7 are seen ingerminal center lymphocytes and in follicular lymphoma.88 CBX7can cooperate with MYC to promote lymphomagenesis as well asaffecting cellular lifespan through regulation of both the p16Ink4a/Rb and the Arf/p53 pathways.91,92

ASSOCIATIONS WITH MOLECULAR SUBGROUPSIt is being increasingly recognised that genetic susceptibilitiesare subtype specific reflecting differences in biology andthat analysis by specific molecular features can reveal keyrisk relationships. Myeloma displays considerable molecularheterogeneity, which is reflected in clinical outcome. Thesubgroups defined by t(11;14)(q13;q32), t(4;14)(p16;q32),t(6;14)(p21;q32), t(14;16)(q32;q23) and t(14;20)(q32;q11) transloca-tions93 show transcriptional activation of CCND1, FGFR3/MMSET,CCND3, MAF and MAFB, respectively, which directly contribute tothe development of MM.93 The other major subgroup of myelomaare patients without a primary translocation, who commonlydisplay hyperdiploidy.

A case-only analysis of the identified MM risk loci in theoriginal GWAS data sets provided little evidence forsubtype-specific associations, apart from the CBX7 SNP rs877529that showed evidence of an association driven by non-t(11;14)MM.56 As subset-only analyses are powered by a sectionof the available cases, larger samples sets will be required todefinitively determine whether these genetic risk loci arerestricted to subsets or that these regions have a generic effecton MM risk.

Through a stratified analysis of GWAS data, it has been shownthat the G870A polymorphism in cyclin D1 is a determinant of therisk of developing t(11;14) MM.94 Cyclin D1 is a component of thecore cell cycle machinery and increased levels are seen in manycancers including MM. In addition to activating cyclin-dependent

kinases CDKN4 and CDK6, cyclin D1 has kinase-independentfunctions in DNA repair, notably directly binding RAD51, arecombinase that drives homologous recombination.95,96

Overproduction of a D group cyclin is common biologicalfeature of MM and in the t(11;14) subtype it is CCND1, which isupregulated through its close proximity to the powerful Emenhancer of the IgH locus as a result of a reciprocaltranslocation.93,97

The G870 allele creates an optimal splice donor site at theintron 4/exon 5 boundary resulting in the cyclin D1a transcript. Bycontrast, A870 hinders splicing allowing for read-through intointron 4 and production of the variant cyclin D1b transcript.Although 870A is preferentially associated with D1b production,the A allele is not fully penetrant.96 D1a/D1b transcript ratios havebeen shown to be enhanced in some cancers, suggesting thatdifferential alternative splicing can influence tumourigenesis.96

Recent data have demonstrated that while cyclin D1b is a potentoncogene operating through aberrant kinase activity cyclin D1arecruits RAD51 to local chromatin in response to DNAdamage.95,98 However, although the association between G870Aand t(11;14) MM represents the first report of germline variationbeing a determinant of risk for a specific chromosometranslocation, the biological basis remains to be established.G870A cannot operate through a general DNA repair mechanismas increased risk in other translocation groups of MM is not seen.As an association with t(11;14) MGUS is seen but no associationshown for Mantle cell lymphoma, it suggests the impact of G870Aoperates through a as yet unidentified mechanism early on in thedevelopment of t(11;14) MM.94,99

DEFINING INDIVIDUAL RISKAlthough the risk of MM associated with each of the variantsidentified through GWAS is individually modest, they are commonin the population; therefore, they contribute significantly to theoverall disease burden. Moreover, alleles can act additivelyconferring substantive risks to those carrying multiple risk alleles.Currently the seven known risk alleles account for B13% of thefamilial risk of MM;56 therefore, the discriminatory value ofgenotyping individuals based on such a panel is very limitedand we have a long way to go before we can predict high riskindividuals confidently. If we are to effectively identify high-riskindividuals with the sensitivity and specificity required in a clinicalsetting, it has been reasoned that we would need to identifyupwards of 150 independent risk loci at OR¼ 1.5 or 250 atOR¼ 1.25 with minor allele frequencies greater than 10%.100 Tofacilitate the identification of additional risk alleles throughassociation-based and analyses, it requires access to largesample series something only achievable through multi-centrecollaborative efforts such as the ‘MyelomA Genetics InternationalConsortium’ (MAGIC).101

Table 2. Regions associated with multiple myeloma that reached genome-wide significance in GWAS studies

Study Proximal risk gene Region SNP Risk allele Cases RAF Controls RAF OR P-value (adjusted)

Broderick et al.55 CDCA7AL, DNAH11 7p15.3 rs4487645 C 0.72-0.76 0.65–0.67 1.38 2.62� 10� 14

ULK4 3p22.1 rs1052501 G 0.19–0.21 0.16 1.32 1.81� 10� 8

DNMT3A, DTNB 2p23.3 rs6746082 A 0.82–0.84 0.77–0.79 1.29 4.02� 10� 7

Chubb et al.56 MYNN, TERC 3q26.2 rs10936599 C 0.78–0.80 0.75–0.76 0.78 1.74� 10� 13

PSORS1C2, POUF51 6p21.3 rs2285803 A 0.29–0.36 0.26–0.31 1.21 1.18� 10� 10

TNFRSF13B 17p11.2 rs4273077 G 0.11–0.14 0.09–0.11 1.26 1.41� 10� 7

CBX7 22q13.1 rs877529 A 0.45–0.51 0.41–0.44 1.29 2.29� 10� 16

Weinhold et al.94 CCND1 (t11;14) 11q13.3 rs603965 (rs9344) G 0.67–0.72 0.52–0.55 1.83 2.07� 10� 11

Abbreviations: OR, odds ratio; RAF, relative allele frequency.


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BIOLOGICAL INSIGHTS BASED ON THESE VARIANTSUntil now it has been possible to gain important insights into thelater stages of myeloma pathogenesis by the study of tumour-acquired genetic lesions such as copy-number variants andmutations. These studies have defined important pathologicallyderegulated genes and pathways that re-wire the biologicalfunction of a normal plasma cell into one that has the ‘molecularhallmarks’ of a myelomatous plasma cell. Early events in thismalignant transformation process, however, have been moredifficult to study and largely it has only been the class switchdriven translocations that have given relevant insights. Theassociation studies we describe here are important because theycan give insights into the potential mechanisms relevant early inthe pathogenesis of MM as well as highlighting how inheritedgenetic variants might interact with tumour-acquired variants toenhance progression towards myeloma.

Interestingly, we find few abnormalities, in this first pass of thedata, that would have been predicted to be associated withmyeloma based on a priori hypotheses and that have beenincluded in previous candidate gene studies. However, we seederegulation of pathways involved in DNA methylation, telomerelength, differentiation and autophagy, which is consistent withMM risk being governed by pathways important in the longevityof plasma cells and the adaptation to paraprotein production. Wesee an association with TNFRSF13B, the receptor for BAFF andAPRIL that activates the NFkB pathway, a key growth and survivalpathway in plasma cells. This association argues that constitutiveactivation of the NFkB pathway may be an important early eventincreasing the likelihood that a cell, bearing this variant, may bedirected down a pathway eventually leading to MM.

MYC deregulation has been reported to be critical to myelomapathogenesis and is deregulated in the majority of cell lines aswell as in a significant proportion of clinical cases. Thederegulation of MYC, late in the natural history of myeloma, isbrought about by a range of molecular mechanisms includingtumour-acquired DNA insertion, deletion and translocation. Themyeloma risk genes CDCA7L, DNMT3A and CBX7 are all reported tohave interactions with MYC and indicate that the deregulation ofMYC early in the pathogenesis of myeloma is, in some part,mediated by the inheritance of risk variants. This observation, ofinherited variation in MYC function and predisposition tomyeloma, seems to be a common mechanism in a range of B-celltumours. Associations with MYC are seen in the results of GWAstudies in other B-cell entities including non-Hodgkin lym-phoma,102 Hodgkin’s lymphoma103 and chronic lymphocyticleukaemia.104 The mechanisms deregulating MYC are, however,different in these tumour types involving inherited variants in agene desert upstream of MYC.

Cell cycle abnormalities are critical features of myelomapathogenesis and a number of MM risk genes have functionsthat may influence the cell cycle pathway early in the naturalhistory of the disease. The expression of checkpoint genesp16Ink4a/Rb, Arf/p53 and CCNE1 can be altered by activity of theMM risk gene CBX7. Whereas DNMT3A can repress p21Cip1 andp15INK4B, and CDCA7L can influence the expression of CCND1. It isof course fascinating that an inherited variant in CCND1, a criticalcell cycle gene deregulated in a significant proportion ofmyeloma, seemingly predisposes patients to develop transloca-tions into that locus. This observation further informs us of thecritical nature of deregulation of the G1S cell cycle checkpoint inthe transformation of a normal to a malignant plasma cell.

The key conclusions of these initial GWAS analyses are that thepathways deregulated by the acquisition of genomic changesgiving rise to the ‘molecular hallmarks of myeloma’ are alsoimportant early in the disease natural history where their functionis impacted by inherited variants. Analogous to tumour-acquiredvariants such inherited variants can also be considered as ‘genetic

hits’ pushing a normal cell along the pathway to a malignantplasma cell. Thus, a person with an inherited variant is either onestep further along the pathway and so more likely to develop MMor alternatively they may have an increased likelihood ofdeveloping MM-specific variants.

RARE MODERATE-HIGH PENETRANCE SUSCEPTIBILITY TO MMIn addition to common variation influencing MM risk, it is likelythat other classes of susceptibility exist, an assertion supported byfamilies in which the inheritance of MM is compatible with a majordisease locus. An example of a rare low-penetrance susceptibilityallele in MM is provided by the germ-line mutations observed inCDKN2A (p16INK4A).13 Current GWA-based strategies are notoptimally configured to identify such low frequency variants;however, genotyping strategies using increased density arraysinformed by sequence studies such as the 1000 genomes willallow rarer variants important to the pathogenesis of MM to beidentified.

Despite this current deficiency in array-based approaches,recent advances in molecular-based technologies make theutilisation of sequencing approaches a feasible proposition.Association testing using either exome or whole-genomesequence heralds a fundamental development that will allowinvestigation of the full spectrum of inherited variation impactingthe risk developing MM. In addition, although the computingchallenges of processing the large data sets for sequence-basedassociation testing are considerable, the bioinformatic tools arebeginning to be developed to undertake such analyses.105–107

Confirming rarer variants predisposing to MM will require evenlarger case series and is even stronger rationale for collaborativestudies across the MM community.

CONCLUSIONAssociation testing offers hypothesis-free testing of cases thatcombined with powerful sequence-based technologies will lead toa deeper understanding of genes and interactions underlying thepathogenesis of MM. Recent developments in the functionalannotation by the ENCODE projects will no doubt accelerate thefunctional characterisation of these associations. Ultimately, thistype of strategy will highlight novel therapeutic molecular targetsfor the development of new therapeutic strategies. In addition, theidentification of variants that predisposes individuals to distinctgenetic pathogenetic subtypes hold the promise of providingclinicians with screening tools to allow greater personalisation oftherapies and clinical management. To date, MM GWAS studieshave only considered patients with a Northern and WesternEuropean descent (CEU), it is important to follow-up these findingsin other populations. In addition to new therapies and improvedmanagement of MM patients, further elucidation of MM andMGUS risk factors may eventually allow related family members ofMM patients or individuals with MGUS to be more informed oftheir potential predisposing risk of developing MM.

CONFLICT OF INTERESTThe authors declare no conflict of interest.

ACKNOWLEDGEMENTSLaboratory work of GJM is supported by funding from Myeloma UK. The work ofRSH is supported by grants from Leukaemia Lymphoma Research and MyelomaUK. HG and KH are supported by funding was provided to Dietmar-Hopp-Stiftungin Walldorf, The German Ministry of Education and Science (Gliomics 01ZX1309B),the German Cancer Aid, Deursche Krebshilfe and the University HospitalHeidelberg.


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Inherited genetic susceptibility to multiple myeloma