Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
Transl Psychiatry. 2022 Jan 11;12(1):17. doi: 10.1038/s41398-022-01782-8.
It is well-accepted that both environment and genetic factors contribute to the development of mental disorders (MD). However, few genetic studies used time-to-event data analysis to identify the susceptibility genetic variants associated with MD and explore the role of environment factors in these associations. In order to detect novel genetic loci associated with MD based on the time-to-event data and identify the role of environmental factors in them, this study recruited 376,806 participants from the UK Biobank cohort. The MD outcomes (including overall MD status, anxiety, depression and substance use disorders (SUD)) were defined based on in-patient hospital, self-reported and death registry data collected in the UK Biobank. SPACOX approach was used to identify the susceptibility loci for MD using the time-to-event data of the UK Biobank cohort. And then we estimated the associations between identified candidate loci, fourteen environment factors and MD through a phenome-wide association study and mediation analysis. SPACOX identified multiple candidate loci for overall MD status, depression and SUD, such as rs139813674 (P value = 8.39 × 10, ZNF684) for overall MD status, rs7231178 (DCC, P value = 2.11 × 10) for depression, and rs10228494 (FOXP2, P value = 6.58 × 10) for SUD. Multiple environment factors could influence the associations between identified loci and MD, such as confide in others and felt hated. Our study identified novel candidate loci for MD, highlighting the strength of time-to-event data based genetic association studies. We also observed that multiple environment factors could influence the association between susceptibility loci and MD.
人们普遍认为，环境和遗传因素都有助于精神障碍（MD）的发展。然而，很少有遗传研究使用事件时间数据分析来识别与 MD 相关的易感遗传变异，并探讨环境因素在这些关联中的作用。为了根据事件时间数据检测与 MD 相关的新遗传基因座，并确定环境因素在其中的作用，本研究从英国生物库队列中招募了 376806 名参与者。MD 结局（包括 MD 总体状况、焦虑、抑郁和物质使用障碍（SUD））是根据英国生物库中收集的住院、自我报告和死亡登记数据来定义的。使用英国生物库队列的事件时间数据，通过 SPACOX 方法识别 MD 的易感基因座。然后，我们通过全表型关联研究和中介分析，估计了鉴定出的候选基因座、14 个环境因素与 MD 之间的关联。SPACOX 确定了多个候选基因座与 MD 总体状况、抑郁和 SUD 相关，例如 rs139813674（P 值=8.39×10，ZNF684）与 MD 总体状况相关，rs7231178（DCC，P 值=2.11×10）与抑郁相关，rs10228494（FOXP2，P 值=6.58×10）与 SUD 相关。多个环境因素可能会影响鉴定出的基因座与 MD 之间的关联，例如信任他人和感到被讨厌。我们的研究确定了 MD 的新候选基因座，强调了基于事件时间数据的遗传关联研究的优势。我们还观察到，多个环境因素可能会影响易感基因座与 MD 之间的关联。
