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精神疾病遗传易感性的结构大脑网络。

A structural brain network of genetic vulnerability to psychiatric illness.

机构信息

Department of Psychiatry, University of Oxford, Oxford, UK.

Computational Radiology Laboratory, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.

出版信息

Mol Psychiatry. 2021 Jun;26(6):2089-2100. doi: 10.1038/s41380-020-0723-7. Epub 2020 May 6.

Abstract

Psychiatry is undergoing a paradigm shift from the acceptance of distinct diagnoses to a representation of psychiatric illness that crosses diagnostic boundaries. How this transition is supported by a shared neurobiology remains largely unknown. In this study, we first identify single nucleotide polymorphisms (SNPs) associated with psychiatric disorders based on 136 genome-wide association studies. We then conduct a joint analysis of these SNPs and brain structural connectomes in 678 healthy children in the PING study. We discovered a strong, robust, and transdiagnostic mode of genome-connectome covariation which is positively and specifically correlated with genetic risk for psychiatric illness at the level of individual SNPs. Similarly, this mode is also significantly positively correlated with polygenic risk scores for schizophrenia, alcohol use disorder, major depressive disorder, a combined bipolar disorder-schizophrenia phenotype, and a broader cross-disorder phenotype, and significantly negatively correlated with a polygenic risk score for educational attainment. The resulting "vulnerability network" is shown to mediate the influence of genetic risks onto behaviors related to psychiatric vulnerability (e.g., marijuana, alcohol, and caffeine misuse, perceived stress, and impulsive behavior). Its anatomy overlaps with the default-mode network, with a network of cognitive control, and with the occipital cortex. These findings suggest that the brain vulnerability network represents an endophenotype funneling genetic risks for various psychiatric illnesses through a common neurobiological root. It may form part of the neural underpinning of the well-recognized but poorly explained overlap and comorbidity between psychiatric disorders.

摘要

精神病学正在从接受明确的诊断转变为跨越诊断界限的精神病描述。这种转变如何得到共同的神经生物学支持在很大程度上尚不清楚。在这项研究中,我们首先根据 136 项全基因组关联研究,确定与精神疾病相关的单核苷酸多态性(SNP)。然后,我们在 PING 研究中的 678 名健康儿童中对这些 SNP 和大脑结构连接组进行联合分析。我们发现了一种强大、稳健且跨诊断的基因组-连接组共变模式,这种模式与个体 SNP 水平上的精神疾病遗传风险呈正相关,具有特异性。同样,这种模式也与精神分裂症、酒精使用障碍、重度抑郁症、双相障碍-精神分裂症综合表型和更广泛的跨疾病表型的多基因风险评分显著正相关,与教育程度的多基因风险评分显著负相关。结果表明,“易损性网络”介导遗传风险对与精神易损性相关的行为的影响(例如,大麻、酒精和咖啡因滥用、感知压力和冲动行为)。其解剖结构与默认模式网络、认知控制网络和枕叶重叠。这些发现表明,大脑易损性网络代表了一种内表型,通过共同的神经生物学根源将各种精神疾病的遗传风险汇集在一起。它可能构成公认但解释不足的精神障碍之间重叠和共病的神经基础的一部分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/908f/8440183/4f6add5c3d0e/41380_2020_723_Fig1_HTML.jpg

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