Went Molly, Cornish Alex J, Law Philip J, Kinnersley Ben, van Duin Mark, Weinhold Niels, Försti Asta, Hansson Markus, Sonneveld Pieter, Goldschmidt Hartmut, Morgan Gareth J, Hemminki Kari, Nilsson Björn, Kaiser Martin, Houlston Richard S
Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.
Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
Blood Adv. 2020 May 26;4(10):2172-2179. doi: 10.1182/bloodadvances.2020001502.
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.
多发性骨髓瘤（MM）的病因尚不清楚。多表型全基因组关联研究（GWAS）的汇总数据可用于孟德尔随机化（MR）全表型关联研究（PheWAS），以寻找影响MM风险的因素。我们进行了一项MR-PheWAS，分析了由10225个遗传变异代理的249种表型，以及来自一项对7717例MM病例和29304例对照进行的GWAS的汇总遗传数据。在逆方差加权随机效应模型下，估计每种表型每增加1个标准差的优势比（OR）。经Bonferroni校正的P = 2×10-4阈值被认为具有显著性，而P <.05被认为提示存在关联。尽管在249种表型中未观察到与MM风险有显著关联，但有28种表型显示出存在关联的证据，包括血清维生素B6和血液肉碱水平升高（P = 1.1×10-3）与MM风险增加以及ω-3脂肪酸（P = 5.4×10-4）与MM风险降低有关。还注意到端粒长度增加与MM风险降低之间存在提示性关联；然而，这种关联主要由先前在3q26（TERC）处鉴定的风险变异rs10936599驱动。尽管无统计学显著性，但体重指数增加与风险增加相关（OR，1.10；95%置信区间，0.99 - 1.22），这支持了先前一项前瞻性观察性研究的荟萃分析结果。我们的研究没有提供证据支持所研究的任何可改变因素对MM风险有重大影响；然而，它为先前证据不一的因素提供了见解。
