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首页> 外文期刊>BMC Cancer >Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study
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Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study

机译:系统识别风险因素与胶质瘤之间的因果关系:孟德利安随机化研究

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Whilst epidemiological studies have provided evidence of associations between certain risk factors and glioma onset, inferring causality has proven challenging. Using Mendelian randomization (MR), we assessed whether associations of 36 reported glioma risk factors showed evidence of a causal relationship. We performed a systematic search of MEDLINE from inception to October 2018 to identify candidate risk factors and conducted a meta-analysis of two glioma genome-wide association studies (5739 cases and 5501 controls) to form our exposure and outcome datasets. MR analyses were performed using genetic variants to proxy for candidate risk factors. We investigated whether risk factors differed by subtype diagnosis (either glioblastoma (n?=?3112) or non-glioblastoma (n?=?2411)). MR estimates for each risk factor were determined using multiplicative random effects inverse-variance weighting (IVW). Sensitivity analyses investigated potential pleiotropy using MR-Egger regression, the weighted median estimator, and the mode-based estimator. To increase power, trait-specific polygenic risk scores were used to test the association of a genetically predicated increase in each risk factor with glioma onset. Our systematic search identified 36 risk factors that could be proxied using genetic variants. Using MR, we found evidence that four genetically predicted traits increased risk of glioma, glioblastoma or non-glioblastoma: longer leukocyte telomere length, liability to allergic disease, increased alcohol consumption and liability to childhood extreme obesity (?3 standard deviations from the mean). Two traits decreased risk of non-glioblastoma cancers: increased low-density lipoprotein cholesterol (LDLc) and triglyceride levels. Our findings were similar across sensitivity analyses that made allowance for pleiotropy (genetic confounding). Our comprehensive investigation provides evidence of a causal link between both genetically predicted leukocyte telomere length, allergic disease, alcohol consumption, childhood extreme obesity, and LDLc and triglyceride levels, and glioma. The findings from our study warrant further research to uncover mechanisms that implicate these traits in glioma onset.
机译:虽然流行病学研究提供了某些危险因素和胶质瘤发病之间的关联的证据,但推断因果关系已被证明有挑战性。使用孟德尔随机化(MR),我们评估了36种报告的胶质瘤风险因素的关联是否显示出存在因果关系的证据。我们对2018年10月的裁员进行了系统搜索,以确定候选风险因素,并对两种胶质瘤基因组关联研究进行了荟萃分析(5739例和5501个控制),以形成我们的暴露和结果数据集。 MR分析是使用遗传变体进行候选风险因素的代理进行。我们调查了亚型诊断是否有危险因素(胶质母细胞瘤(N?=β3112)或非胶质母细胞瘤(n?=Δ2411))。使用乘法随机效应逆差异加权(IVW)来确定每个风险因子的MR估计。敏感性分析使用MR-Egger回归,加权中值估计器和基于模式的估算器来分析研究的潜在渗透层。为了提高功率,使用特异性特异性的多基因风险评分来测试与胶质瘤发作的每个危险因素的遗传上预测增加的关联。我们的系统搜索确定了36个可能使用遗传变异来解决的风险因素。使用MR,我们发现有证据表明,四个遗传预测的性状增加了胶质瘤,胶质母细胞瘤或非胶质细胞瘤的风险:Leyuryyte端粒长度,对过敏性疾病的责任,增加酗酒和童年极端肥胖的责任(> 3标准偏差)。两种性状降低了非胶质母细胞瘤癌症的风险:增加低密度脂蛋白胆固醇(LDLC)和甘油三酯水平。我们的研究结果在敏感性分析中具有相似的敏感性分析,这是对肺炎的津贴(遗传混杂化)。我们的综合调查提供了遗传预测白细胞端粒长度,过敏性疾病,醇消费,儿童极端肥胖和LDLC和甘油三酯水平的证据证明了因果关系。我们研究的结果需要进一步研究揭示揭示胶质瘤发病中这些特征的机制。

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