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多基因风险评分通过与认知相关的途径增加精神分裂症的易感性。

Polygenic risk score increases schizophrenia liability through cognition-relevant pathways.

机构信息

Department of Psychology, Bilkent University, Bilkent, Ankara, Turkey.

The State Key Laboratory of Brain and Cognitive Sciences, the University of Hong Kong, Hong Kong SAR, China.

出版信息

Brain. 2019 Feb 1;142(2):471-485. doi: 10.1093/brain/awy279.

Abstract

Cognitive deficit is thought to represent, at least in part, genetic mechanisms of risk for schizophrenia, with recent evidence from statistical modelling of twin data suggesting direct causality from the former to the latter. However, earlier evidence was based on inferences from twin not molecular genetic data and it is unclear how much genetic influence 'passes through' cognition on the way to diagnosis. Thus, we included direct measurements of genetic risk (e.g. schizophrenia polygenic risk scores) in causation models to assess the extent to which cognitive deficit mediates some of the effect of polygenic risk scores on the disorder. Causal models of family data tested relationships among key variables and allowed parsing of genetic variance components. Polygenic risk scores were calculated from summary statistics from the current largest genome-wide association study of schizophrenia and were represented as a latent trait. Cognition was also modelled as a latent trait. Participants were 1313 members of 1078 families: 416 patients with schizophrenia, 290 unaffected siblings, and 607 controls. Modelling supported earlier findings that cognitive deficit has a putatively causal role in schizophrenia. In total, polygenic risk score explained 8.07% [confidence interval (CI) 5.45-10.74%] of schizophrenia risk in our sample. Of this, more than a third (2.71%, CI 2.41-3.85%) of the polygenic risk score influence was mediated through cognition paths, exceeding the direct influence of polygenic risk score on schizophrenia risk (1.43%, CI 0.46-3.08%). The remainder of the polygenic risk score influence (3.93%, CI 2.37-4.48%) reflected reciprocal causation between schizophrenia liability and cognition (e.g. mutual influences in a cyclical manner). Analysis of genetic variance components of schizophrenia liability indicated that 26.87% (CI 21.45-32.57%) was associated with cognition-related pathways not captured by polygenic risk score. The remaining variance in schizophrenia was through pathways other than cognition-related and polygenic risk score. Although our results are based on inference through statistical modelling and do not provide an absolute proof of causality, we find that cognition pathways mediate a significant part of the influence of cumulative genetic risk on schizophrenia. We estimate from our model that 33.51% (CI 27.34-43.82%) of overall genetic risk is mediated through influences on cognition, but this requires further studies and analyses as the genetics of schizophrenia becomes better characterized.

摘要

认知缺陷被认为至少部分代表了精神分裂症的遗传风险机制,最近来自双胞胎数据统计建模的证据表明,认知缺陷直接导致了精神分裂症。然而,早期的证据是基于从双胞胎而不是分子遗传学数据的推断,目前尚不清楚遗传影响在通往诊断的过程中有多少是“传递”的。因此,我们在因果模型中纳入了直接测量的遗传风险(例如,精神分裂症多基因风险评分),以评估认知缺陷在多大程度上介导了多基因风险评分对该疾病的部分影响。家庭数据的因果模型测试了关键变量之间的关系,并允许分解遗传方差分量。多基因风险评分是根据当前最大的精神分裂症全基因组关联研究的汇总统计数据计算得出的,并表示为潜在特征。认知也被建模为潜在特征。参与者是来自 1078 个家庭的 1313 名成员:416 名精神分裂症患者、290 名未受影响的兄弟姐妹和 607 名对照。模型支持了早期的发现,即认知缺陷在精神分裂症中具有假定的因果作用。总的来说,多基因风险评分解释了我们样本中精神分裂症风险的 8.07%(置信区间[CI]为 5.45-10.74%)。其中,多基因风险评分影响的三分之一以上(2.71%,CI 2.41-3.85%)是通过认知途径介导的,超过了多基因风险评分对精神分裂症风险的直接影响(1.43%,CI 0.46-3.08%)。多基因风险评分影响的其余部分(3.93%,CI 2.37-4.48%)反映了精神分裂症易感性和认知之间的相互因果关系(例如,以循环方式相互影响)。对精神分裂症易感性遗传方差分量的分析表明,26.87%(CI 21.45-32.57%)与多基因风险评分未捕获的认知相关途径有关。精神分裂症的其余方差是通过认知相关和多基因风险评分以外的途径产生的。尽管我们的结果是基于统计建模的推断得出的,并没有提供因果关系的绝对证据,但我们发现认知途径介导了累积遗传风险对精神分裂症影响的很大一部分。我们根据模型估计,33.51%(CI 27.34-43.82%)的整体遗传风险是通过对认知的影响来介导的,但这需要进一步的研究和分析,因为精神分裂症的遗传学变得更好地描述。

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