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@ARTICLE{Went:157090,
      author       = {M. Went and A. J. Cornish and P. J. Law and B. Kinnersley
                      and M. van Duin and N. Weinhold and A. Försti$^*$ and M.
                      Hansson and P. Sonneveld and H. Goldschmidt and G. J. Morgan
                      and K. Hemminki$^*$ and B. Nilsson and M. Kaiser and R. S.
                      Houlston},
      title        = {{S}earch for multiple myeloma risk factors using
                      {M}endelian randomization.},
      journal      = {Blood advances},
      volume       = {4},
      number       = {10},
      issn         = {2473-9537},
      address      = {Washington, DC},
      publisher    = {American Society of Hematology},
      reportid     = {DKFZ-2020-01381},
      pages        = {2172 - 2179},
      year         = {2020},
      abstract     = {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.},
      cin          = {C050 / HD01 / B062},
      ddc          = {610},
      cid          = {I:(DE-He78)C050-20160331 / I:(DE-He78)HD01-20160331 /
                      I:(DE-He78)B062-20160331},
      pnm          = {312 - Functional and structural genomics (POF3-312)},
      pid          = {G:(DE-HGF)POF3-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:32433745},
      pmc          = {pmc:PMC7252541},
      doi          = {10.1182/bloodadvances.2020001502},
      url          = {https://inrepo02.dkfz.de/record/157090},
}