International Multiple Myeloma rESEarch Research Articles

A pleiotropic variant in DNAJB4 is associated with multiple myeloma risk.

Pleiotropy, which consists of a single gene or allelic variant affecting multiple unrelated traits, is common across cancers, with evidence for genome-wide significant loci shared across cancer and noncancer traits. This feature is particularly relevant in multiple myeloma (MM) because several susceptibility loci that have been identified to date are pleiotropic. Therefore, the aim of this study was to identify novel pleiotropic variants involved in MM risk using 28 684 independent single nucleotide polymorphisms (SNPs) from GWAS Catalog that reached a significant association (P < 5× 10-8 ) with their respective trait. The selected SNPs were analyzed in 2434 MM cases and 3446 controls from the International Lymphoma Epidemiology Consortium (InterLymph). The 10 SNPs showing the strongest associations with MM risk in InterLymph were selected for replication in an independent set of 1955 MM cases and 1549 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and 418 MM cases and 147 282 controls from the FinnGen project. The combined analysis of the three studies identified an association between DNAJB4-rs34517439-A and an increased risk of developing MM (OR=1.22, 95%CI 1.13-1.32, P=4.81× 10-7 ). rs34517439-A is associated with a modified expression of the FUBP1 gene, which encodes a multifunctional DNA and RNA-binding protein that it was observed to influence the regulation of various genes involved in cell cycle regulation, among which various oncogenes and oncosuppressors. In conclusion, with a pleiotropic scan approach we identified DNAJB4-rs34517439 as a potentially novel MM risk locus.

Does a Multiple Myeloma Polygenic Risk Score Predict Overall Survival of Patients with Myeloma?

Genome-wide association studies (GWAS) of multiple myeloma in populations of European ancestry (EA) identified and confirmed 24 susceptibility loci. For other cancers (e.g., colorectum and melanoma), risk loci have also been associated with patient survival. We explored the possible association of all the known risk variants and their polygenic risk score (PRS) with multiple myeloma overall survival (OS) in multiple populations of EA [the International Multiple Myeloma rESEarch (IMMEnSE) consortium, the International Lymphoma Epidemiology consortium, CoMMpass, and the German GWAS] for a total of 3,748 multiple myeloma cases. Cox proportional hazards regression was used to assess the association between each risk SNP with OS under the allelic and codominant models of inheritance. All analyses were adjusted for age, sex, country of origin (for IMMEnSE) or principal components (for the others) and disease stage (ISS). SNP associations were meta-analyzed. SNP associations were meta-analyzed. From the meta-analysis, two multiple myeloma risk SNPs were associated with OS (P &lt; 0.05), specifically POT1-AS1-rs2170352 [HR = 1.37; 95% confidence interval (CI) = 1.09-1.73; P = 0.007] and TNFRSF13B-rs4273077 (HR = 1.19; 95% CI = 1.01-1.41; P = 0.04). The association between the combined 24 SNP MM-PRS and OS, however, was not significant. Overall, our results did not support an association between the majority of multiple myeloma risk SNPs and OS. This is the first study to investigate the association between multiple myeloma PRS and OS in multiple myeloma.

A polygenic risk score for multiple myeloma risk prediction

There is overwhelming epidemiologic evidence that the risk of multiple myeloma (MM) has a solid genetic background. Genome-wide association studies (GWAS) have identified 23 risk loci that contribute to the genetic susceptibility of MM, but have low individual penetrance. Combining the SNPs in a polygenic risk score (PRS) is a possible approach to improve their usefulness. Using 2361 MM cases and 1415 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium, we computed a weighted and an unweighted PRS. We observed associations with MM risk with OR = 3.44, 95% CI 2.53–4.69, p = 3.55 × 10−15 for the highest vs. lowest quintile of the weighted score, and OR = 3.18, 95% CI 2.1 = 34–4.33, p = 1.62 × 10−13 for the highest vs. lowest quintile of the unweighted score. We found a convincing association of a PRS generated with 23 SNPs and risk of MM. Our work provides additional validation of previously discovered MM risk variants and of their combination into a PRS, which is a first step towards the use of genetics for risk stratification in the general population.

P-052: Identification of novel genetic loci for risk of multiple myeloma by functional annotation

<h3>Background</h3> Genetic factors have proven to have an impact on multiple myeloma (MM) susceptibility, with genome-wide association studies (GWAS) discovering 23 loci associated with MM risk. However, much of the heritability of MM remains unexplained. The stringent significance threshold used in GWAS (p<5×10^-8) accounts for the numerous statistical tests being performed but is prone to the risk of false negatives. One strategy for reducing the number of tests is to consider only SNPs with heightened prior probabilities of association, according to meaningful biological criteria. The best candidate SNPs identified with this approach can then be tested in additional MM cases and controls from independent populations. We aimed at surveying the effect of single nucleotide polymorphisms (SNPs), predicted to have a functional role, on MM risk. <h3>Methods</h3> The association study consisted of two GWAS as discovery datasets, namely the InterLymph consortium and the German GWAS and a replication dataset, namely the the International Multiple Myeloma rESEarch (IMMEnSE) consortium, for an overall total of 5442 MM cases and 6174 controls. SNPs were first ranked according to p-value and concordance of the association between the two discovery datasets, then ranked by functional annotation, using bioinformatic tools and databases. We considered the following classes of functional SNPs: missense, synonymous and non-sense SNPs, expression quantitative trait loci (eQTLs), splicing quantitative trait loci (sQTLs),), SNPs in SNPs affecting function of long non-coding RNAs (lncRNA), and SNPs modifying transcription factor binding sites. We prioritized the resulting SNPs for replication in IMMEnSE by p-values for association in InterLymph and German GWAS and by evidence for a functional role. <h3>Results</h3> In the two discovery datasets, 136 SNPs fit the criteria of association with MM risk with p<10^-4 and did not map close to known MM risk loci. After pruning for linkage disequilibrium, four SNPs (rs12038685, rs2664188, rs12652920, rs29794) were chosen for replication in IMMEnSE. Among these, rs2664188 showed to be significantly associated also in the replication dataset (OR=1.30, 95% CI=1.16-1.46, p=0.001). The final meta-analysis including the three datasets, using a random-effect model, confirmed the association (OR=1.18, 95% CI=1.07-1.30, p=0.0007). <h3>Conclusion</h3> The G-allele of rs2664188, that showed a consistent association with increased risk of developing MM in all phases of our analysis is an eQTL, according to GTEx., The G-allele is associated with increased expression of the N4BP2 gene in whole blood. N4BP2 encodes a protein which binds to B-cell leukemia/lymphoma 3 (BCL-3), a well-known proto-oncogene, known to play a role in cell proliferation and apoptosis inhibition in myeloma cell lines.

Genetically determined telomere length and multiple myeloma risk and outcome

Telomeres are involved in processes like cellular growth, chromosomal stability, and proper segregation to daughter cells. Telomere length measured in leukocytes (LTL) has been investigated in different cancer types, including multiple myeloma (MM). However, LTL measurement is prone to heterogeneity due to sample handling and study design (retrospective vs. prospective). LTL is genetically determined; genome-wide association studies identified 11 SNPs that, combined in a score, can be used as a genetic instrument to measure LTL and evaluate its association with MM risk. This approach has been already successfully attempted in various cancer types but never in MM. We tested the “teloscore” in 2407 MM patients and 1741 controls from the International Multiple Myeloma rESEarch (IMMeNSE) consortium. We observed an increased risk for longer genetically determined telomere length (gdTL) (OR = 1.69; 95% CI 1.36–2.11; P = 2.97 × 10−6 for highest vs. lowest quintile of the score). Furthermore, in a subset of 1376 MM patients we tested the relationship between the teloscore and MM patients survival, observing a better prognosis for longer gdTL compared with shorter gdTL (HR = 0.93; 95% CI 0.86–0.99; P = 0.049). In conclusion, we report convincing evidence that longer gdTL is a risk marker for MM risk, and that it is potentially involved in increasing MM survival.

Expression quantitative trait loci of genes predicting outcome are associated with survival of multiple myeloma patients.

Gene expression profiling can be used for predicting survival in multiple myeloma (MM) and identifying patients who will benefit from particular types of therapy. Some germline single nucleotide polymorphisms (SNPs) act as expression quantitative trait loci (eQTLs) showing strong associations with gene expression levels. We performed an association study to test whether eQTLs of genes reported to be associated with prognosis of MM patients are directly associated with measures of adverse outcome. Using the genotype-tissue expression portal, we identified a total of 16 candidate genes with at least one eQTL SNP associated with their expression with P < 10-7 either in EBV-transformed B-lymphocytes or whole blood. We genotyped the resulting 22 SNPs in 1327 MM cases from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and examined their association with overall survival (OS) and progression-free survival (PFS), adjusting for age, sex, country of origin and disease stage. Three polymorphisms in two genes (TBRG4-rs1992292, TBRG4-rs2287535 and ENTPD1-rs2153913) showed associations with OS at P < .05, with the former two also associated with PFS. The associations of two polymorphisms in TBRG4 with OS were replicated in 1277 MM cases from the International Lymphoma Epidemiology (InterLymph) Consortium. A meta-analysis of the data from IMMEnSE and InterLymph (2579 cases) showed that TBRG4-rs1992292 is associated with OS (hazard ratio=1.14, 95% confidence interval 1.04-1.26, P=.007). In conclusion, we found biologically a plausible association between a SNP in TBRG4 and OS of MM patients.

Common gene variants within 3′‐untranslated regions as modulators of multiple myeloma risk and survival

We evaluated the association between germline genetic variants located within the 3'-untranlsated region (polymorphic 3'UTR, ie, p3UTR) of candidate genes involved in multiple myeloma (MM). We performed a case-control study within the International Multiple Myeloma rESEarch (IMMEnSE) consortium, consisting of 3056 MM patients and 1960 controls recruited from eight countries. We selected p3UTR of six genes known to act in different pathways relevant in MM pathogenesis, namely KRAS (rs12587 and rs7973623), VEGFA (rs10434), SPP1 (rs1126772), IRF4 (rs12211228) and IL10 (rs3024496). We found that IL10-rs3024496 was associated with increased risk of developing MM and with a worse overall survival of MM patients. The variant allele was assayed in a vector expressing eGFP chimerized with the IL10 3'-UTR and it was found functionally active following transfection in human myeloma cells. In this experiment, the A-allele caused a lower expression of the reporter gene and this was also in agreement with the in vivo expression of mRNA measured in whole blood as reported in the GTEx portal. Overall, these data are suggestive of an effect of the IL10-rs3024496 SNP on the regulation of IL10 mRNA expression and it could have clinical implications for better characterization of MM patients in terms of prognosis.

Identification of miRSNPs associated with the risk of multiple myeloma.

Multiple myeloma (MM) is a malignancy of plasma cells usually infiltrating the bone marrow, associated with the production of a monoclonal immunoglobulin (M protein) which can be detected in the blood and/or urine. Multiple lines of evidence suggest that genetic factors are involved in MM pathogenesis, and several studies have identified single nucleotide polymorphisms (SNPs) associated with the susceptibility to the disease. SNPs within miRNA-binding sites in target genes (miRSNPs) may alter the strength of miRNA-mRNA interactions, thus deregulating protein expression. MiRSNPs are known to be associated with risk of various types of cancer, but they have never been investigated in MM. We performed an in silico genome-wide search for miRSNPs predicted to alter binding of miRNAs to their target sequences. We selected 12 miRSNPs and tested their association with MM risk. Our study population consisted of 1,832 controls and 2,894 MM cases recruited from seven European countries and Israel in the context of the IMMEnSE (International Multiple Myeloma rESEarch) consortium. In this population two SNPs showed an association with p < 0.05: rs286595 (located in gene MRLP22) and rs14191881 (located in gene TCF19). Results from IMMEnSE were meta-analyzed with data from a previously published genome-wide association study (GWAS). The SNPs rs13409 (located in the 3'UTR of the POU5F1 gene), rs1419881 (TCF19), rs1049633, rs1049623 (both in DDR1) showed significant associations with MM risk. In conclusion, we sought to identify genetic polymorphisms associated with MM risk starting from genome-wide prediction of miRSNPs. For some mirSNPs, we have shown promising associations with MM risk.

A common variant within the HNF1B gene is associated with overall survival of multiple myeloma patients: results from the IMMEnSE consortium and meta-analysis.

Diabetogenic single nucleotide polymorphisms (SNPs) have recently been associated with multiple myeloma (MM) risk but their impact on overall survival (OS) of MM patients has not been analysed yet. In order to investigate the impact of 58 GWAS-identified variants for type 2 diabetes (T2D) on OS of patients with MM, we analysed genotyping data of 936 MM patients collected by the International Multiple Myeloma rESEarch (IMMENSE) consortium and an independent set of 700 MM patients recruited by the University Clinic of Heidelberg. A meta-analysis of the cox regression results of the two sets showed that rs7501939 located in the HNF1B gene negatively impacted OS (HRRec= 1.44, 95% CI = 1.18–1.76, P = 0.0001). The meta-analysis also showed a noteworthy gender-specific association of the SLC30A8rs13266634 SNP with OS. The presence of each additional copy of the minor allele at rs13266634 was associated with poor OS in men whereas no association was seen in women (HRMen-Add = 1.32, 95% CI 1.13–1.54, P = 0.0003). In conclusion, these data suggest that the HNF1Brs7501939 SNP confers poor OS in patients with MM and that a SNP in SLC30A8 affect OS in men.

The International Multiple Myeloma Research (IMMEnSE) Consortium: Genetics of Multiple Myeloma Risk and Prognosis

We established the IMMEnSE (International Multiple Myeloma rESEarch) consortium, to increase our understanding of the genetic determinants of multiple myeloma (MM) risk, response to therapy and survival. At present we have DNA samples of over 3200 MM cases and 3000 healthy controls from 10 countries, mainly in Europe. For the majority of the cases clinical data on known prognostic factors, therapy outcome and survival have been also collected.We already performed several association studies in the context of the IMMEnSE consortium. In particular, associations were found between MM risk and SNPs in the ABCB1 gene, which encodes for an efflux pump that has a key role in protecting cells from chemical damage (rs10264990: odds ratio (OR) =0.79, 95% confidence interval (CI) 0.68-0.91; p=0.001, and rs17327442: OR=1.99; 95%CI 1.32-3.02; p=0.001). We also investigated the 8q24 region, which has been shown to harbor multiple loci of susceptibility to various cancers, and found an association between a SNP mapping in this region and MM risk (rs2456449: OR=1.37; 95%CI 1.12-1.68; p=0.0022). In addition, IMMEnSE cases and controls were also genotyped for three MM risk SNPs from the first genome-wide association study (GWAS), and the association of two of them (rs4487645 on chromosome 7p15.3 and rs6746082 on chromosome 2p23.3) was confirmed. Finally, SNPs of key telomere-related genes were genotyped and telomere length was measured in MM cases and controls, and a pleiotropic and functional variant of the TERT gene was found to be associated with reduced MM risk (rs2242652: OR=0.81; 95%CI 0.72-0.92; p=0.001). A suggestive association between longer telomeres and increased MM risk was also found (ptrend=0.01).We will study new SNPs emerging as promising candidates from ongoing GWAS on MM risk and survival, as well as SNPs of key genes involved in the pathogenesis of MM. Finally, we plan to study methylation status of key genes involved in MM etiology, and mitochondrial copy number. The role of all these factors will be investigated in relation to MM risk and prognosis.Collection of samples and data of MM cases and controls is ongoing, as well as of subjects with monoclonal gammopathy of undetermined significance (MGUS).Table 1MM cases and healthy controls collected in the IMMEnSE consortiumCountryCasesMedian age(5th-95th percentile)ControlsMedian age(5th-95th percentile)Control typeItaly23263 (46-78)23759 (42-76)General populationPoland1,28663 (42-82)20068 (43-79)Blood donorsSpain32264 (46-82)1,13166 (43-84)Hospitalized subjectsFrance64257 (37-68)19148 (18-63)Blood donorsPortugal7068 (45-82)10058 (53-79)Blood donorsHungary14868 (34-90)10574 (55-87)Hospitalized subjectsDenmark34856 (43-65)1,00063 (52-73)Blood donorsIsrael10960 (41-77)95-Blood donorsCanada6258 (42-70)---Japan5166 (47-84)---Total3,27063 (37-84)3,05963 (18-92) [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Abstract 5078: Genome wide association study identifies variants at 16p13 associated with survival in multiple myeloma patients

Abstract Background: Genome wide association studies (GWAS) have recently identified 8 loci identified with multiple myeloma (MM) susceptibility. We hypothesized that germ line genetic variants may also affect MM progression. We performed the first GWAS of MM survival, by conducting a meta-analysis of two existing studies at University of California San Francisco (UCSF) and the Mayo Clinic, and replicating findings in the International Multiple Myeloma rESEarch (IMMEnSE) consortium. Methods: The UCSF study included 353 MM patients genotyped on an Illumina Omni5 and Illumina 660 array. The Mayo clinic study included 239 MM patients genotyped on an Affymetrix 6.0 array. We imputed missing genotypes using the 1000 Genomes dataset and performed a GWAS for survival using proportional hazards models adjusting for age and gender and genetic ancestry using principal components analysis. We conducted a meta-analysis of the results from the two GWAS. We replicated the top SNPs in the IMMEnSE cohort which included 772 patients with survival data from 7 European countries and one North American site. We used the dataset from Grundberg et al (Nat Genetics 2012) to test for an association between SNPs associated with survival and gene expression in immortalized lymphocytes. We used gene expression data from Zhan et al (Blood 2006) to analyze the association between expression and survival. Results: In meta-analysis, we found a genome wide significant association between SNPs on a region at 16p13 and survival (rs72773978; p=2.9x10e-10). Patients with the minor allele were at increased risk for mortality (HR 2.73; 95% CI: 1.99 - 3.73). The top associated SNPs were all in strong linkage disequilibrium and were centered over the gene FOPNL. We replicated the association in the IMMEnSE cohort and found a significant association between the top SNP from the discovery dataset (rs72773978 p=0.037). We used previously published data to determine the association between gene expression and the top associated SNPs from the GWAS. The top SNP (rs72773978) was not in previously published eQTL databases, so we used rs7201759 which was also associated with survival in our data (p=3.8x10e-10) as a proxy. The minor allele for this SNP was associated with increased levels of expression of FOPNL (p=9x10e-5), but not with expression of any other genes within a 1 megabase region. Finally, we also observed an association between increased expression of FOPNL and shorter survival (HR: 2.62 per standard deviation.; 95% CI: 1.08 - 6.32). Conclusion: Germ line variants at 16p13 near the FOPNL gene are associated with survival among MM patients. FOPNL is thought to be involved in centrosomal function, and centrosomal activity has previously been associated with survival in MM patients. Our results support this previous observation. Furthermore, they suggest that germ line variants could also be useful in assessing prognosis for patients with MM. Citation Format: Elad Ziv, Eric Dean, Donglei Hu, Alessandro Martino, Daniel Serie, Daniele Campa, Blake Aftab, Paige Bracci, Gabriele Buda, Jennifer Caswell, Charles Dumontet, Marek Dudziński, Laura Fejerman, Alexandra Greenberg, Scott Hunstman, Artur Jurczyszyn, Krzysztof Jamroziak, Shaji Kumar, Herlander Marques, Thomas Martin, Joaquin Martinez-Lopez, Vincent Rajkumar, Juan Sainz, Annette Juul Vangsted, Marzena Watek, Jeffrey Wolf, Susan Slager, Federico Canzian, Celine Vachon. Genome wide association study identifies variants at 16p13 associated with survival in multiple myeloma patients. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5078. doi:10.1158/1538-7445.AM2014-5078

Genetic Variants and Multiple Myeloma Risk: IMMEnSE Validation of the Best Reported Associations—An Extensive Replication of the Associations from the Candidate Gene Era

Genetic background plays a role in multiple myeloma susceptibility. Several single-nucleotide polymorphisms (SNP) associated with genetic susceptibility to multiple myeloma were identified in the last years, but only a few of them were validated in independent studies. With the aim to conclusively validate the strongest associations so far reported, we selected the polymorphisms rs2227667 (SERPINE1), rs17501108 (HGF), rs3136685 (CCR7), rs16944 (IL1B), rs12147254 (TRAF3), rs1805087 (MTR), rs1800629 (TNF-α), rs7516435 (CASP9), rs1042265 (BAX), rs2234922 (mEH), and rs1801133 (MTHFR). We genotyped them in 1,498 multiple myeloma cases and 1,934 controls ascertained in the context of the International Multiple Myeloma rESEarch (IMMEnSE) consortium, and meta-analyzed our results with previously published ones. None of the selected SNPs were significantly associated with multiple myeloma risk (P value range, 0.055-0.981), possibly with the exception of the SNP rs2227667 (SERPINE1) in women. We can exclude that the selected polymorphisms are major multiple myeloma risk factors. Independent validation studies are crucial to identify true genetic risk factors. Our large-scale study clarifies the role of previously published polymorphisms in multiple myeloma risk.

Erratum: Polymorphisms in xenobiotic transporters ABCB1, ABCG2, ABCC2, ABCC1, ABCC3 and multiple myeloma risk: a case—control study in the context of the International Multiple Myeloma rESEarch (IMMEnSE) consortium

Correction to: Leukemia (2012) 26, 1419–1422; doi:10.1038/leu.2011.352 Since the publication of this article the authors have noticed errors within the original text of the manuscript. Allele nomenclature of some SNP have been wrongly reported with the name of the two homozygous group inverted, as illustrated in the example below:

Polymorphisms in regulators of xenobiotic transport and metabolism genes PXR and CAR do not affect multiple myeloma risk: a case–control study in the context of the IMMEnSE consortium

The exposure to pesticides and toxic compounds in xenobiotic transport and metabolism genes has been shown to affect risk of developing multiple myeloma (MM). Therefore, we hypothesized that genetic variations in xenobiotic transport and metabolism regulator genes PXR (NR1I2) and CAR (NR1I3) could determine a difference in MM susceptibility. Ten tagging single-nucleotide polymorphisms (SNPs) for PXR and seven for the CAR genes were selected and genotyped in 627 MM cases and 883 controls collected in the context of the International Multiple Myeloma rESEarch (IMMEnSE) consortium. None of the 17 SNPs investigated showed significant association with MM risk either alone or when combined in haplotypes. Significant SNP-SNP interactions were not found, neither with 58 previously genotyped polymorphisms in ABC transporters. We can therefore exclude that common genetic variants in the xenobiotic transport and metabolism regulator genes PXR and CAR affect MM risk.

Impact of polymorphic variation at 7p15.3, 3p22.1 and 2p23.3 loci on risk of multiple myeloma

Impact of polymorphic variation at 7p15.3, 3p22.1 and 2p23.3 loci on risk of multiple myeloma

Polymorphisms in xenobiotic transporters ABCB1, ABCG2, ABCC2, ABCC1, ABCC3 and multiple myeloma risk: a case–control study in the context of the International Multiple Myeloma rESEarch (IMMEnSE) consortium

Polymorphisms in xenobiotic transporters ABCB1 , ABCG2 , ABCC2 , ABCC1 , ABCC3 and multiple myeloma risk: a case–control study in the context of the International Multiple Myeloma rESEarch (IMMEnSE) consortium

Genetics and molecular epidemiology of multiple myeloma: The rationale for the IMMEnSE consortium (Review)

There is strong evidence suggesting the presence of a genetic component in the aetiology of multiple myeloma (MM). However no genetic risk factors have been unequivocally established so far. To further our understanding of the genetic determinants of MM risk, a promising strategy is to collect a large set of patients in a consortium, as successfully done for other cancers. In this article, we review the main findings in the genetic susceptibility and pharmacogenetics of MM and present the strategy of the IMMEnSE (International Multiple Myeloma rESEarch) consortium in contributing to determine the role of genetic variation in pharmacogenetics and in MM risk.