多发性硬化症的基因-环境相互作用:英国生物银行研究。

Benjamin Meir Jacobs, Alastair J Noyce, Jonathan Bestwick, Daniel Belete, Gavin Giovannoni, Ruth Dobson
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引用次数: 0

摘要

目的:我们试图确定遗传风险是否会改变环境风险因素对多发性硬化症(MS)的影响。为了验证这一假设,我们在UK Biobank中测试了多基因风险评分(PRS)与MS遗传易感性之间的统计相互作用。方法:使用icd -10编码的MS或自我报告在UK Biobank中识别MS患者。环境危险因素与多发性硬化症风险之间的关联采用多变量logistic回归的病例对照设计进行量化。PRS是利用最大的ms全基因组关联研究中带有外部权重的聚块和阈值法得出的,并创建了包括主要组织相容性复合体(MHC) (PRSMHC)和排除MHC位点(PRSnon-MHC)的单独评分。在30%的队列中确定了表现最好的PRS,并在其余70%中得到了验证。采用相互作用归因比例(AP)和乘法相互作用来量化环境与遗传危险因素之间的相互作用。结果:2250名MS患者和48.6万名对照者的数据可用。儿童期肥胖、初潮年龄提前、吸烟与MS相关,验证队列中最佳PRS与MS呈强相关(PRSMHC: Nagelkerke伪r2 0.033, p = 3.92 × 10-111;PRSnon-MHC: Nagelkerke伪r2 0.013, p = 3.73 × 10-43)。有强有力的证据表明多发性硬化症多基因风险与儿童肥胖之间存在相互作用(PRSMHC: AP = 0.17, 95% CI 0.06-0.25, p = 0.004;PRSnon-MHC: AP = 0.17, 95% CI 0.06-0.27, p = 0.006)。结论:本研究为儿童肥胖与高常染色体遗传风险负担之间的相互作用提供了新的证据。这些发现可能对我们对MS生物学的理解有重要意义,并为有针对性的预防策略提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Gene-Environment Interactions in Multiple Sclerosis: A UK Biobank Study.

Gene-Environment Interactions in Multiple Sclerosis: A UK Biobank Study.

Gene-Environment Interactions in Multiple Sclerosis: A UK Biobank Study.

Gene-Environment Interactions in Multiple Sclerosis: A UK Biobank Study.

Objective: We sought to determine whether genetic risk modifies the effect of environmental risk factors for multiple sclerosis (MS). To test this hypothesis, we tested for statistical interaction between polygenic risk scores (PRS) capturing genetic susceptibility to MS and environmental risk factors for MS in UK Biobank.

Methods: People with MS were identified within UK Biobank using ICD-10-coded MS or self-report. Associations between environmental risk factors and MS risk were quantified with a case-control design using multivariable logistic regression. PRS were derived using the clumping-and-thresholding approach with external weights from the largest genome-wide association study of MS. Separate scores were created including major histocompatibility complex (MHC) (PRSMHC) and excluding (PRSnon-MHC) the MHC locus. The best-performing PRS were identified in 30% of the cohort and validated in the remaining 70%. Interaction between environmental and genetic risk factors was quantified using the attributable proportion due to interaction (AP) and multiplicative interaction.

Results: Data were available for 2,250 people with MS and 486,000 controls. Childhood obesity, earlier age at menarche, and smoking were associated with MS. The optimal PRS were strongly associated with MS in the validation cohort (PRSMHC: Nagelkerke's pseudo-R2 0.033, p = 3.92 × 10-111; PRSnon-MHC: Nagelkerke's pseudo-R2 0.013, p = 3.73 × 10-43). There was strong evidence of interaction between polygenic risk for MS and childhood obesity (PRSMHC: AP = 0.17, 95% CI 0.06-0.25, p = 0.004; PRSnon-MHC: AP = 0.17, 95% CI 0.06-0.27, p = 0.006).

Conclusions: This study provides novel evidence for an interaction between childhood obesity and a high burden of autosomal genetic risk. These findings may have significant implications for our understanding of MS biology and inform targeted prevention strategies.

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