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本文引用的文献

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The Maudsley environmental risk score for psychosis.精神分裂症的莫兹利环境风险评分。
Psychol Med. 2020 Oct;50(13):2213-2220. doi: 10.1017/S0033291719002319. Epub 2019 Sep 19.
2
Estimating Exposome Score for Schizophrenia Using Predictive Modeling Approach in Two Independent Samples: The Results From the EUGEI Study.使用预测建模方法在两个独立样本中估算精神分裂症的暴露组评分:来自 EUGEI 研究的结果。
Schizophr Bull. 2019 Sep 11;45(5):960-965. doi: 10.1093/schbul/sbz054.
3
One decade of the first episodes project (PEPs): Advancing towards a precision psychiatry.首个发作性疾病项目(PEPs)的十年:迈向精准精神病学。
Rev Psiquiatr Salud Ment (Engl Ed). 2019 Jul-Sep;12(3):135-140. doi: 10.1016/j.rpsm.2019.03.001. Epub 2019 May 16.
4
Examining the independent and joint effects of molecular genetic liability and environmental exposures in schizophrenia: results from the EUGEI study.探究精神分裂症中分子遗传易感性与环境暴露的独立及联合效应:EUGEI研究结果
World Psychiatry. 2019 Jun;18(2):173-182. doi: 10.1002/wps.20629.
5
Transforming Summary Statistics from Logistic Regression to the Liability Scale: Application to Genetic and Environmental Risk Scores.将逻辑回归的汇总统计量转换为易感性量表:在遗传和环境风险评分中的应用。
Hum Hered. 2018;83(4):210-224. doi: 10.1159/000495697. Epub 2019 Mar 13.
6
CIBERSAM: Ten years of collaborative translational research in mental disorders.CIBERSAM:精神疾病十年合作转化研究
Rev Psiquiatr Salud Ment (Engl Ed). 2019 Jan-Mar;12(1):1-8. doi: 10.1016/j.rpsm.2018.10.001. Epub 2018 Nov 9.
7
Cognitive reserve as an outcome predictor: first-episode affective versus non-affective psychosis.认知储备作为结局预测因子:首发情感性与非情感性精神病。
Acta Psychiatr Scand. 2018 Nov;138(5):441-455. doi: 10.1111/acps.12949. Epub 2018 Aug 14.
8
Convergence of placenta biology and genetic risk for schizophrenia.胎盘生物学与精神分裂症遗传风险的趋同。
Nat Med. 2018 Jun;24(6):792-801. doi: 10.1038/s41591-018-0021-y. Epub 2018 May 28.
9
Evidence That Environmental and Familial Risks for Psychosis Additively Impact a Multidimensional Subthreshold Psychosis Syndrome.证据表明,精神分裂症的环境和家庭风险因素会对多维亚临床精神病综合征产生累加影响。
Schizophr Bull. 2018 Jun 6;44(4):710-719. doi: 10.1093/schbul/sby051.
10
The use of polygenic risk scores to identify phenotypes associated with genetic risk of bipolar disorder and depression: A systematic review.使用多基因风险评分识别与双相情感障碍和抑郁症遗传风险相关的表型:系统评价。
J Affect Disord. 2018 Jul;234:148-155. doi: 10.1016/j.jad.2018.02.005. Epub 2018 Feb 15.

使用首发精神病队列的综合评分来研究基因-环境相互作用。

Examining Gene-Environment Interactions Using Aggregate Scores in a First-Episode Psychosis Cohort.

机构信息

Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain.

Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain.

出版信息

Schizophr Bull. 2020 Jul 8;46(4):1019-1025. doi: 10.1093/schbul/sbaa012.

DOI:10.1093/schbul/sbaa012
PMID:32083289
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7342095/
Abstract

Gene-environment (GxE) interactions have been related to psychosis spectrum disorders, involving multiple common genetic variants in multiple genes with very small effect sizes, and several environmental factors that constitute a dense network of exposures named the exposome. Here, we aimed to analyze GxE in a cohort of 310 first-episode psychotic (FEP) and 236 healthy controls, by using aggregate scores estimated in large populations such as the polygenic risk score for schizophrenia and (PRS-SCZ) and the Maudsley environmental risk score (ERS). In contrast to previous findings, in our study, the PRS-SCZ did not discriminate cases from controls, but the ERS score explained a similar percentage of the variance as in other studies using similar approaches. Our study supports a positive additive interaction, indicating synergy between genetic susceptibility to schizophrenia (PRS-SCZ dichotomized according to the highest quartile distribution of the control population) and the exposome (ERS > 75% of the controls). This additive interaction showed genetic and environmental dose dependence. Our study shows that the use of aggregate scores derived from large and powered studies instead of statistics derived from specific sample characteristics is a powerful tool for the study of the effects of GxE on the risk of psychotic spectrum disorders. In conclusion, by using a genetic risk score and an ERS we have provided further evidence for the role of GxE in psychosis.

摘要

基因-环境(GxE)相互作用与精神分裂症谱系障碍有关,涉及多个基因中的多个常见遗传变异,其效应大小非常小,以及构成暴露组学的密集网络的几个环境因素。在这里,我们旨在通过使用聚合分数分析 310 名首发精神病(FEP)和 236 名健康对照者中的 GxE,这些聚合分数是在大人群中估计的,例如精神分裂症的多基因风险评分(PRS-SCZ)和莫兹利环境风险评分(ERS)。与之前的发现相反,在我们的研究中,PRS-SCZ 不能区分病例和对照,但 ERS 评分解释了与使用类似方法的其他研究相似的方差百分比。我们的研究支持积极的加性相互作用,表明精神分裂症遗传易感性(PRS-SCZ 根据对照人群的最高四分位数分布进行二分法)和暴露组学(ERS > 对照组的 75%)之间存在协同作用。这种加性相互作用显示出遗传和环境剂量依赖性。我们的研究表明,使用来自大型和强大研究的聚合分数而不是来自特定样本特征的统计数据是研究 GxE 对精神分裂症谱系障碍风险影响的有力工具。总之,通过使用遗传风险评分和 ERS,我们提供了进一步的证据证明 GxE 在精神病中的作用。