Multiple myeloma (MM) is an incurable malignancy of plasma cells. Epidemiological studies indicate a substantial heritable component, but the underlying mechanisms remain unclear. Here, in a genome-wide association study totaling 10,906 cases and 366,221 controls, we identify 35 MM risk loci, 12 of which are novel. Through functional fine-mapping and Mendelian randomization, we uncover two causal mechanisms for inherited MM risk: longer telomeres; and elevated levels of B-cell maturation antigen (BCMA) and interleukin-5 receptor alpha (IL5RA) in plasma. The largest increase in BCMA and IL5RA levels is mediated by the risk variant rs34562254-A at TNFRSF13B. While individuals with loss-of-function variants in TNFRSF13B develop B-cell immunodeficiency, rs34562254-A exerts a gain-of-function effect, increasing MM risk through amplified B-cell responses. Our results represent an analysis of genetic MM predisposition, highlighting causal mechanisms contributing to MM development.

Broad Institute 415 Main Street Cambridge MA 02142 USA

Department of Cancer Research and Molecular Medicine Norwegian University of Science and Technology Box 8905 N 7491 Trondheim Norway

Department of Haematology University Hospital of Copenhagen at Rigshospitalet Blegdamsvej 9 DK 2100 Copenhagen Denmark

Department of Hematology Erasmus MC Cancer Institute 3075 EA Rotterdam The Netherlands

Department of Integrative Medical Biology Umeå University SE 901 87 Umeå Sweden

Department of Internal Medicine 5 University of Heidelberg 69120 Heidelberg Germany

Department of Laboratory Medicine Lund University SE 221 84 Lund Sweden

Department of Radiation Sciences Umeå University SE 901 87 Umeå Sweden

Division of Genetics and Epidemiology The Institute of Cancer Research London SW7 3RP UK

eCODE Genetics Amgen Sturlugata 8 IS 101 Reykjavik Iceland

Faculty of Medicine in Pilsen Charles University 30605 Pilsen Czech Republic

Faculty of Medicine University of Iceland IS 101 Reykjavik Iceland

German Cancer Research Center D 69120 Heidelberg Germany

Hopp Children's Cancer Center Heidelberg Germany

Institute of Experimental Medicine Academy of Sciences of the Czech Republic Prague Czech Republic

Landspitali National University Hospital of Iceland IS 101 Reykjavik Iceland

Lund Stem Cell Center Lund University SE 221 84 Lund Sweden

MSB Medical School Berlin Berlin Germany

Myeloma Center University of Arkansas for Medical Sciences Little Rock AR USA

Perlmutter Cancer Center Langone Health New York University New York NY USA

Section of Hematology Sahlgrenska University Hospital Gothenburg SE 413 45 Sweden

Skåne University Hospital SE 221 85 Lund Sweden

Southern Älvsborg Hospital SE 501 82 Borås Sweden

University Hospital Ostrava and University of Ostrava Ostrava Czech Republic

Zobrazit více v PubMed

Pertesi, M. et al. Genetic predisposition for multiple myeloma. Leukemia34, 697–708 (2020). 10.1038/s41375-019-0703-6 PubMed DOI

Halvarsson, B. M. et al. Direct evidence for a polygenic etiology in familial multiple myeloma. Blood Adv.1, 619–623 (2017). 10.1182/bloodadvances.2016003111 PubMed DOI PMC

Altieri, A., Chen, B., Bermejo, J. L., Castro, F. & Hemminki, K. Familial risks and temporal incidence trends of multiple myeloma. Eur. J. Cancer42, 1661–1670 (2006). 10.1016/j.ejca.2005.11.033 PubMed DOI

Frank, C. et al. Search for familial clustering of multiple myeloma with any cancer. Leukemia30, 627–632 (2016). 10.1038/leu.2015.279 PubMed DOI

Mitchell, J. S. et al. Genome-wide association study identifies multiple susceptibility loci for multiple myeloma. Nat. Commun.7, 12050 (2016). 10.1038/ncomms12050 PubMed DOI PMC

Went, M. et al. Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma. Nat. Commun.9, 3707 (2018). 10.1038/s41467-018-04989-w PubMed DOI PMC

Swaminathan, B. et al. Variants in ELL2 influencing immunoglobulin levels associate with multiple myeloma. Nat. Commun.6, 7213 (2015). 10.1038/ncomms8213 PubMed DOI PMC

Broderick, P. et al. Common variation at 3p22.1 and 7p15.3 influences multiple myeloma risk. Nat. Genet44, 58–61 (2011). 10.1038/ng.993 PubMed DOI PMC

Chubb, D. et al. Common variation at 3q26.2, 6p21.33, 17p11.2 and 22q13.1 influences multiple myeloma risk. Nat. Genet.45, 1221–1225 (2013). 10.1038/ng.2733 PubMed DOI PMC

Duran-Lozano, L. et al. Germline variants at SOHLH2 influence multiple myeloma risk. Blood Cancer J.11, 76 (2021). 10.1038/s41408-021-00468-6 PubMed DOI PMC

Ajore, R. et al. Functional dissection of inherited non-coding variation influencing multiple myeloma risk. Nat. Commun.13, 151 (2022). 10.1038/s41467-021-27666-x PubMed DOI PMC

Weinhold, N. et al. The CCND1 c.870G>A polymorphism is a risk factor for t(11;14)(q13;q32) multiple myeloma. Nat. Genet.45, 522–525 (2013). 10.1038/ng.2583 PubMed DOI PMC

Li, N. et al. Genetic predisposition to multiple myeloma at 5q15 is mediated by an ELL2 enhancer polymorphism. Cell Rep.20, 2556–2564 (2017). 10.1016/j.celrep.2017.08.062 PubMed DOI PMC

Welter, D. et al. The NHGRI GWAS catalog, a curated resource of SNP-trait associations. Nucleic Acids Res.42, D1001–D1006 (2014). 10.1093/nar/gkt1229 PubMed DOI PMC

Knies, K. et al. Biallelic mutations in the ubiquitin ligase RFWD3 cause Fanconi anemia. J. Clin. Invest127, 3013–3027 (2017). 10.1172/JCI92069 PubMed DOI PMC

Speedy, H. E. et al. Germ line mutations in shelterin complex genes are associated with familial chronic lymphocytic leukemia. Blood128, 2319–2326 (2016). 10.1182/blood-2016-01-695692 PubMed DOI PMC

Castigli, E. et al. TACI is mutant in common variable immunodeficiency and IgA deficiency. Nat. Genet37, 829–834 (2005). 10.1038/ng1601 PubMed DOI

Vanegas, S., Ramirez-Montano, D., Candelo, E., Shinawi, M. & Pachajoa, H. DeSanto-shinawi syndrome: first case in south America. Mol. Syndromol.9, 154–158 (2018). 10.1159/000488815 PubMed DOI PMC

Walker, B. A. et al. Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma. Blood132, 587–597 (2018). 10.1182/blood-2018-03-840132 PubMed DOI PMC

Rustad, E. H. et al. Revealing the impact of structural variants in multiple myeloma. Blood Cancer Discov.1, 258–273 (2020). 10.1158/2643-3230.BCD-20-0132 PubMed DOI PMC

Maura, F. et al. Genomic classification and individualized prognosis in multiple myeloma. J. Clin. Oncol.42, 1229–1240 (2024). 10.1200/JCO.23.01277 PubMed DOI PMC

Lin, M. et al. Identification of novel fusion transcripts in multiple myeloma. J. Clin. Pathol.71, 708–712 (2018). 10.1136/jclinpath-2017-204961 PubMed DOI

Manier, S. et al. Genomic complexity of multiple myeloma and its clinical implications. Nat. Rev. Clin. Oncol.14, 100–113 (2017). 10.1038/nrclinonc.2016.122 PubMed DOI

Amend, S. R. et al. Whole genome sequence of multiple myeloma-prone C57BL/KaLwRij mouse strain suggests the origin of disease involves multiple Cell types. PLoS One10, e0127828 (2015). 10.1371/journal.pone.0127828 PubMed DOI PMC

Moreaux, J. et al. APRIL and TACI interact with syndecan-1 on the surface of multiple myeloma cells to form an essential survival loop. Eur. J. Haematol.83, 119–129 (2009). 10.1111/j.1600-0609.2009.01262.x PubMed DOI

Hengeveld, P. J. & Kersten, M. J. B-cell activating factor in the pathophysiology of multiple myeloma: a target for therapy? Blood Cancer J.5, e282 (2015). 10.1038/bcj.2015.3 PubMed DOI PMC

Ju, S. et al. Correlation of expression levels of BLyS and its receptors with multiple myeloma. Clin. Biochem.42, 387–399 (2009). 10.1016/j.clinbiochem.2008.10.024 PubMed DOI

Novak, A. J. et al. Expression of BCMA, TACI, and BAFF-R in multiple myeloma: a mechanism for growth and survival. Blood103, 689–694 (2004). 10.1182/blood-2003-06-2043 PubMed DOI

Moreaux, J. et al. The level of TACI gene expression in myeloma cells is associated with a signature of microenvironment dependence versus a plasmablastic signature. Blood106, 1021–1030 (2005). 10.1182/blood-2004-11-4512 PubMed DOI PMC

Moreaux, J. et al. TACI expression is associated with a mature bone marrow plasma cell signature and C-MAF overexpression in human myeloma cell lines. Haematologica92, 803–811 (2007). 10.3324/haematol.10574 PubMed DOI PMC

Mackay, F. & Schneider, P. TACI, an enigmatic BAFF/APRIL receptor, with new unappreciated biochemical and biological properties. Cytokine Growth Factor Rev.19, 263–276 (2008). 10.1016/j.cytogfr.2008.04.006 PubMed DOI

Martincic, K., Alkan, S. A., Cheatle, A., Borghesi, L. & Milcarek, C. Transcription elongation factor ELL2 directs immunoglobulin secretion in plasma cells by stimulating altered RNA processing. Nat. Immunol.10, 1102–1109 (2009). 10.1038/ni.1786 PubMed DOI PMC

Park, K. S. et al. Transcription elongation factor ELL2 drives ig secretory-specific mRNA production and the unfolded protein response. J. Immunol.193, 4663–4674 (2014). 10.4049/jimmunol.1401608 PubMed DOI PMC

Nutt, S. L., Hodgkin, P. D., Tarlinton, D. M. & Corcoran, L. M. The generation of antibody-secreting plasma cells. Nat. Rev. Immunol.15, 160–171 (2015). 10.1038/nri3795 PubMed DOI

Shaffer, A. L. et al. IRF4 addiction in multiple myeloma. Nature454, 226–231 (2008). 10.1038/nature07064 PubMed DOI PMC

Pjanic, M. et al. Nuclear factor I genomic binding associates with chromatin boundaries. BMC Genom.14, 99 (2013).10.1186/1471-2164-14-99 PubMed DOI PMC

Su, C. L., Deng, T. R., Shang, Z. & Xiao, Y. JARID2 inhibits leukemia cell proliferation by regulating CCND1 expression. Int J. Hematol.102, 76–85 (2015). 10.1007/s12185-015-1797-x PubMed DOI

Birger, Y., Ito, Y., West, K. L., Landsman, D. & Bustin, M. HMGN4, a newly discovered nucleosome-binding protein encoded by an intronless gene. DNA Cell Biol.20, 257–264 (2001). 10.1089/104454901750232454 PubMed DOI

Sharma, A., Gerard, S. F., Olieric, N. & Steinmetz, M. O. Cep120 promotes microtubule formation through a unique tubulin binding C2 domain. J. Struct. Biol.203, 62–70 (2018). 10.1016/j.jsb.2018.01.009 PubMed DOI

Wang, Y. et al. Rare variants of large effect in BRCA2 and CHEK2 affect risk of lung cancer. Nat. Genet.46, 736–741 (2014). 10.1038/ng.3002 PubMed DOI PMC

Sekulovic, S. et al. Prolonged self-renewal activity unmasks telomerase control of telomere homeostasis and function of mouse hematopoietic stem cells. Blood118, 1766–1773 (2011). 10.1182/blood-2010-11-319632 PubMed DOI PMC

Brümmendorf, T. H. & Balabanov, S. Telomere length dynamics in normal hematopoiesis and in disease states characterized by increased stem cell turnover. Leukemia20, 1706–1716 (2006). 10.1038/sj.leu.2404339 PubMed DOI

Allsopp, R. C., Cheshier, S. & Weissman, I. L. Telomere shortening accompanies increased cell cycle activity during serial transplantation of hematopoietic stem cells. J. Exp. Med.193, 917–924 (2001). 10.1084/jem.193.8.917 PubMed DOI PMC

Fiorini, E., Santoni, A. & Colla, S. Dysfunctional telomeres and hematological disorders. Differ. Res. Biol. Diversity100, 1–11 (2018).10.1016/j.diff.2018.01.001 PubMed DOI PMC

Yamaguchi, H. et al. Mutations in TERT, the gene for telomerase reverse transcriptase, in aplastic anemia. N. Engl. J. Med.352, 1413–1424 (2005). 10.1056/NEJMoa042980 PubMed DOI

Codd, V. et al. Polygenic basis and biomedical consequences of telomere length variation. Nat. Genet.53, 1425–1433 (2021). 10.1038/s41588-021-00944-6 PubMed DOI PMC

Speed, D., Hemani, G., Johnson, M. R. & Balding, D. J. Improved heritability estimation from genome-wide SNPs. Am. J. Hum. Genet.91, 1011–1021 (2012). 10.1016/j.ajhg.2012.10.010 PubMed DOI PMC

Yarmolinsky, J. et al. Causal inference in cancer epidemiology: what Is the role of mendelian randomization? Cancer epidemiology, biomarkers & prevention: a publication of the American association for cancer research, cosponsored by the american society of preventive. Oncology27, 995–1010 (2018). PubMed PMC

Smith, G. D. & Ebrahim, S. Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int. J. Epidemiol.32, 1–22 (2003). 10.1093/ije/dyg070 PubMed DOI

Lawlor, D. A., Harbord, R. M., Sterne, J. A. C., Timpson, N. & Davey Smith, G. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat. Med.27, 1133–1163 (2008). 10.1002/sim.3034 PubMed DOI

Aviv, A., Anderson, J. J. & Shay, J. W. Mutations, cancer and the telomere length paradox. Trends cancer3, 253–258 (2017). 10.1016/j.trecan.2017.02.005 PubMed DOI PMC

Ferkingstad, E. et al. Large-scale integration of the plasma proteome with genetics and disease. Nat. Genet53, 1712–1721 (2021). 10.1038/s41588-021-00978-w PubMed DOI

O’Neill, C. & van de Donk, N. T-cell redirecting bispecific antibodies in multiple myeloma: current landscape and future directions. EJHaem4, 811–822 (2023). 10.1002/jha2.729 PubMed DOI PMC

Cowan, A. J. et al. gamma-Secretase inhibitor in combination with BCMA chimeric antigen receptor T-cell immunotherapy for individuals with relapsed or refractory multiple myeloma: a phase 1, first-in-human trial. Lancet Oncol.24, 811–822 (2023). 10.1016/S1470-2045(23)00246-2 PubMed DOI PMC

Visram, A. et al. Serum BCMA levels predict outcomes in MGUS and smoldering myeloma patients. Blood Cancer J.11, 120 (2021). 10.1038/s41408-021-00505-4 PubMed DOI PMC

Seipel, K. et al. sBCMA plasma level dynamics and anti-BCMA CAR-T-cell treatment in relapsed multiple myeloma. Curr. Issues Mol. Biol.44, 1463–1471 (2022). 10.3390/cimb44040098 PubMed DOI PMC

Girgis, S. et al. Effects of teclistamab and talquetamab on soluble BCMA levels in patients with relapsed/refractory multiple myeloma. Blood Adv.7, 644–648 (2023). 10.1182/bloodadvances.2022007625 PubMed DOI PMC

Alomari, M., Kunacheewa, C. & Manasanch, E. E. The role of soluble B cell maturation antigen as a biomarker in multiple myeloma. Leuk. Lymphoma64, 261–272 (2023). 10.1080/10428194.2022.2133540 PubMed DOI

Wiedemann, A. et al. Soluble B-cell maturation antigen as a monitoring marker for multiple myeloma. Pathol. Oncol. Res29, 1611171 (2023). 10.3389/pore.2023.1611171 PubMed DOI PMC

Xu, C., Gao, M., Zhang, J. & Fu, Y. IL5RA as an immunogenic cell death-related predictor in progression and therapeutic response of multiple myeloma. Sci. Rep.13, 8528 (2023). 10.1038/s41598-023-35378-z PubMed DOI PMC

Horikawa, K. & Takatsu, K. Interleukin-5 regulates genes involved in B-cell terminal maturation. Immunology118, 497–508 (2006). 10.1111/j.1365-2567.2006.02382.x PubMed DOI PMC

Jonsson, S. et al. Identification of sequence variants influencing immunoglobulin levels. Nat. Genet49, 1182–1191 (2017). 10.1038/ng.3897 PubMed DOI

Liao, M. et al. Genome-wide association study identifies common variants at TNFRSF13B associated with IgG level in a healthy Chinese male population. Genes Immun.13, 509–513 (2012). 10.1038/gene.2012.26 PubMed DOI

Osman, W. et al. Association of common variants in TNFRSF13B, TNFSF13, and ANXA3 with serum levels of non-albumin protein and immunoglobulin isotypes in Japanese. PLoS One7, e32683 (2012). 10.1371/journal.pone.0032683 PubMed DOI PMC

Fried, A. J., Rauter, I., Dillon, S. R., Jabara, H. H. & Geha, R. S. Functional analysis of transmembrane activator and calcium-modulating cyclophilin ligand interactor (TACI) mutations associated with common variable immunodeficiency. J. Allergy Clin. Immunol.128, 226–228 e1 (2011). 10.1016/j.jaci.2011.01.048 PubMed DOI PMC

Kumar, P., Henikoff, S. & Ng, P. C. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat. Protoc.4, 1073–1081 (2009). 10.1038/nprot.2009.86 PubMed DOI

Adzhubei, I., Jordan, D. M. & Sunyaev, S. R. Predicting functional effect of human missense mutations using PolyPhen-2. Curr. Protoc. Hum. GenetChapter 7, Unit7 20 (2013). PubMed PMC

Morgan, G. J. et al. Cyclophosphamide, thalidomide, and dexamethasone as induction therapy for newly diagnosed multiple myeloma patients destined for autologous stem-cell transplantation: MRC Myeloma IX randomized trial results. Haematologica97, 442–450 (2012). 10.3324/haematol.2011.043372 PubMed DOI PMC

Morgan, G. J. et al. Long-term follow-up of MRC Myeloma IX trial: Survival outcomes with bisphosphonate and thalidomide treatment. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res.19, 6030–6038 (2013).10.1158/1078-0432.CCR-12-3211 PubMed DOI

Jackson, G. H. et al. Lenalidomide maintenance versus observation for patients with newly diagnosed multiple myeloma (Myeloma XI): a multicentre, open-label, randomised, phase 3 trial. Lancet Oncol.20, 57–73 (2019). 10.1016/S1470-2045(18)30687-9 PubMed DOI PMC

Bycroft, C. et al. Genome-wide genetic data on ~500,000 UK biobank participants. bioRxiv10.1101/166298 (2017).

Marchini, J., Howie, B., Myers, S., McVean, G. & Donnelly, P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet39, 906–913 (2007). 10.1038/ng2088 PubMed DOI

Liu, J. Z. et al. Meta-analysis and imputation refines the association of 15q25 with smoking quantity. Nat. Genet.42, 436–440 (2010). 10.1038/ng.572 PubMed DOI PMC

Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet88, 76–82 (2011). 10.1016/j.ajhg.2010.11.011 PubMed DOI PMC

Huang, J. et al. Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel. Nat. Commun.6, 8111 (2015). 10.1038/ncomms9111 PubMed DOI PMC

Via, M., Gignoux, C. & Burchard, E. G. The 1000 Genomes project: new opportunities for research and social challenges. Genome Med2, 3 (2010). 10.1186/gm124 PubMed DOI PMC

Weinhold, N. et al. The 7p15.3 (rs4487645) association for multiple myeloma shows strong allele-specific regulation of the MYC-interacting gene CDCA7L in malignant plasma cells. Haematologica100, e110 (2015). 10.3324/haematol.2014.118786 PubMed DOI PMC

Gamazon, E. R. et al. SCAN: SNP and copy number annotation. Bioinformatics26, 259–262 (2010). 10.1093/bioinformatics/btp644 PubMed DOI PMC

Stegle, O., Parts, L., Piipari, M., Winn, J. & Durbin, R. Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses. Nat. Protoc.7, 500–507 (2012). 10.1038/nprot.2011.457 PubMed DOI PMC

Gamazon, E. R. et al. A gene-based association method for mapping traits using reference transcriptome data. Nat. Genet.47, 1091–1098 (2015). 10.1038/ng.3367 PubMed DOI PMC

Barbeira, A. N. et al. Integrating predicted transcriptome from multiple tissues improves association detection. bioRxiv10.1101/292649 (2018). PubMed PMC

Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods10, 1213–1218 (2013). 10.1038/nmeth.2688 PubMed DOI PMC

Schmidl, C., Rendeiro, A. F., Sheffield, N. C. & Bock, C. ChIPmentation: fast, robust, low-input ChIP-seq for histones and transcription factors. Nat. Methods12, 963–965 (2015). 10.1038/nmeth.3542 PubMed DOI PMC

Rendeiro, A. F. et al. Chromatin accessibility maps of chronic lymphocytic leukaemia identify subtype-specific epigenome signatures and transcription regulatory networks. Nat. Commun.7, 11938–11938 (2016). 10.1038/ncomms11938 PubMed DOI PMC

Hoffman, M. M. et al. Integrative annotation of chromatin elements from ENCODE data. Nucleic Acids Res.41, 827–841 (2013). 10.1093/nar/gks1284 PubMed DOI PMC

Fiziev, P. et al. Systematic epigenomic analysis reveals chromatin states associated with melanoma progression. Cell Rep.19, 875–889 (2017). 10.1016/j.celrep.2017.03.078 PubMed DOI PMC

Schoenfelder, S. et al. Polycomb repressive complex PRC1 spatially constrains the mouse embryonic stem cell genome. Nat. Genet47, 1179–1186 (2015). 10.1038/ng.3393 PubMed DOI PMC

Satterlee, J. S. et al. Community resources and technologies developed through the NIH roadmap epigenomics program. Methods Mol. Biol.1238, 27–49 (2015). 10.1007/978-1-4939-1804-1_2 PubMed DOI

Bernstein, B. E. et al. The NIH roadmap epigenomics mapping consortium. Nat. Biotechnol.28, 1045–1048 (2010). 10.1038/nbt1010-1045 PubMed DOI PMC

Cowper-Sal lari, R. et al. Breast cancer risk-associated SNPs modulate the affinity of chromatin for FOXA1 and alter gene expression. Nat. Genet44, 1191–1198 (2012). 10.1038/ng.2416 PubMed DOI PMC

Kong, A. et al. Detection of sharing by descent, long-range phasing and haplotype imputation. Nat. Genet40, 1068–1075 (2008). 10.1038/ng.216 PubMed DOI PMC

Gudbjartsson, D. F. et al. Large-scale whole-genome sequencing of the Icelandic population. Nat. Genet47, 435–4 (2015). 10.1038/ng.3247 PubMed DOI

Krietenstein, N. et al. Ultrastructural details of mammalian chromosome architecture. Mol. Cell78, 554–565.e7 (2020). 10.1016/j.molcel.2020.03.003 PubMed DOI PMC

Hsieh, T. S. et al. Resolving the 3D landscape of transcription-linked mammalian chromatin folding. Mol. Cell78, 539–553.e8 (2020). 10.1016/j.molcel.2020.03.002 PubMed DOI PMC

Morgan, G. J. et al. First-line treatment with zoledronic acid as compared with clodronic acid in multiple myeloma (MRC myeloma IX): a randomised controlled trial. Lancet376, 1989–1999 (2010). 10.1016/S0140-6736(10)62051-X PubMed DOI PMC

Ali, M. et al. The multiple myeloma risk allele at 5q15 lowers ELL2 expression and increases ribosomal gene expression. Nat. Commun.9, 1649 (2018). 10.1038/s41467-018-04082-2 PubMed DOI PMC

Manojlovic, Z. et al. Comprehensive molecular profiling of 718 multiple myelomas reveals significant differences in mutation frequencies between African and European descent cases. PLoS Genet13, e1007087 (2017). 10.1371/journal.pgen.1007087 PubMed DOI PMC

Samur, M. K. et al. Long intergenic non-coding RNAs have an independent impact on survival in multiple myeloma. Leukemia32, 2626–2635 (2018). 10.1038/s41375-018-0116-y PubMed DOI PMC

Ota, M. et al. Dynamic landscape of immune cell-specific gene regulation in immune-mediated diseases. Cell184, 3006–3021 e17 (2021). 10.1016/j.cell.2021.03.056 PubMed DOI

Gordon, M. G. et al. lentiMPRA and MPRAflow for high-throughput functional characterization of gene regulatory elements. Nat. Protoc.15, 2387–2412 (2020). 10.1038/s41596-020-0333-5 PubMed DOI PMC

Ashuach, T. et al. MPRAnalyze: statistical framework for massively parallel reporter assays. Genome Biol.20, 183 (2019). 10.1186/s13059-019-1787-z PubMed DOI PMC

Niroula, A., Ajore, R. & Nilsson, B. MPRAscore: robust and non-parametric analysis of massively parallel reporter assays. Bioinformatics35, 5351–5353 (2019). 10.1093/bioinformatics/btz591 PubMed DOI

Ulirsch, J. C. et al. Interrogation of human hematopoiesis at single-cell and single-variant resolution. Nat. Genet.51, 683–693 (2019). 10.1038/s41588-019-0362-6 PubMed DOI PMC

Granja, J. M. et al. Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia. Nat. Biotechnol.37, 1458–1465 (2019). 10.1038/s41587-019-0332-7 PubMed DOI PMC

Sun, B. B. et al. Genomic atlas of the human plasma proteome. Nature558, 73–79 (2018). 10.1038/s41586-018-0175-2 PubMed DOI PMC

Loh, P. R. et al. Efficient Bayesian mixed-model analysis increases association power in large cohorts. Nat. Genet47, 284–290 (2015). 10.1038/ng.3190 PubMed DOI PMC

Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet.47, 291–295 (2015). 10.1038/ng.3211 PubMed DOI PMC

Hemani, G. et al. The MR-base platform supports systematic causal inference across the human phenome. eLife7, e34408 (2018). 10.7554/eLife.34408 PubMed DOI PMC

Hemani, G., Tilling, K. & Davey Smith, G. Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet13, e1007081 (2017). 10.1371/journal.pgen.1007081 PubMed DOI PMC

Giambartolomei, C. et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet10, e1004383 (2014). 10.1371/journal.pgen.1004383 PubMed DOI PMC