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

A corrigendum to this article was published on 09 December 2015: https://doi.org/10.1038/ncomms10203. The corrigendum is also available at: http://hdl.handle.net/1822/62281 Here we perform the first genome-wide association study (GWAS) of multiple myeloma (MM) survival. In a meta-analysis of 306 MM patients treated at UCSF and 239 patients treated at the Mayo clinic, we find a significant association between SNPs near the gene FOPNL on chromosome 16p13 and survival (rs72773978; P=6 × 10(-10)). Patients with the minor allele are at increased risk for mortality (HR: 2.65; 95% CI: 1.94-3.58) relative to patients homozygous for the major allele. We replicate the association in the IMMEnSE cohort including 772 patients, and a University of Utah cohort including 318 patients (rs72773978 P=0.044). Using publicly available data, we find that the minor allele was associated with increased expression of FOPNL and increased expression of FOPNL was associated with higher expression of centrosomal genes and with shorter survival. Polymorphisms at the FOPNL locus are associated with survival among MM patients. This work was supported by the Steve and Nancy Grand Multiple Myeloma Translational Initiative and a grant from Expression Analysis and a grant from the National Cancer Institute (R21CA191896). E.Z. is supported in part by a mid-career award in patient research from the National Cancer Institute (K24169004). Collection of blood samples from Polish patients and controls from Łodz area, and DNA extraction was supported by a grant from Polish Ministry of Science and Higher Education (No. NN402178334).DNA extraction from Danish healthy controls was supported by The Research Fund at Region Sjælland, Denmark. The Utah study was supported by LLS 6067–09, CA152336and CA134674, with data collection made possible, in part, by the Utah Population Database (UPDB) and the Utah Cancer Registry (UCR). Partial support for all data sets within the UPDB is provided by the Huntsman Cancer Institute (HCI) and the HCICancer Center Support grant, P30 CA42014. The UCR is supported in part by NIH contract HHSN261201000026C from the NCI SEER Program with additional support from the Utah State Department of Health and the University of Utah. In Utah, we thank Jathine Wong for support in formatting files and advice on R programming. Several authors (E.Z., N.C., F.C., C.V.) are members of the International Multiple Myeloma Consortium. We are grateful to the leadership and other members of th