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Dissecting autism and schizophrenia through neuroimaging genomics.通过神经影像学基因组学剖析自闭症和精神分裂症。
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Heritability of individualized cortical network topography.个性化皮质网络拓扑结构的遗传力。
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Structural brain imaging studies offer clues about the effects of the shared genetic etiology among neuropsychiatric disorders.结构脑成像研究为神经精神障碍的共同遗传病因的影响提供了线索。
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Genome-wide analysis of gene dosage in 24,092 individuals estimates that 10,000 genes modulate cognitive ability.对 24092 个人的全基因组分析估计,有 10000 个基因调节认知能力。
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Using common genetic variation to examine phenotypic expression and risk prediction in 22q11.2 deletion syndrome.利用常见遗传变异研究 22q11.2 缺失综合征的表型表达和风险预测。
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Pleiotropy and Cross-Disorder Genetics Among Psychiatric Disorders.精神障碍的多效性和跨疾病遗传学。
Biol Psychiatry. 2021 Jan 1;89(1):20-31. doi: 10.1016/j.biopsych.2020.09.026. Epub 2020 Oct 10.
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Mutations associated with neuropsychiatric conditions delineate functional brain connectivity dimensions contributing to autism and schizophrenia.与神经精神疾病相关的突变描绘了有助于自闭症和精神分裂症的功能性大脑连接维度。
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Dynamic functional network reconfiguration underlying the pathophysiology of schizophrenia and autism spectrum disorder.精神分裂症和自闭症谱系障碍病理生理学基础下的动态功能网络重连。
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Effect Sizes of Deletions and Duplications on Autism Risk Across the Genome.基因组范围内删除和重复对自闭症风险的效应大小。
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脑功能连接反映了精神疾病中的遗传多效性。

Brain functional connectivity mirrors genetic pleiotropy in psychiatric conditions.

机构信息

Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université Paris Cité, Paris, France.

Sainte Justine Research Center, University of Montréal, Montréal, QC H3T 1C5, Canada.

出版信息

Brain. 2023 Apr 19;146(4):1686-1696. doi: 10.1093/brain/awac315.

DOI:10.1093/brain/awac315
PMID:36059063
原文链接:
https://pmc.ncbi.nlm.nih.gov/articles/PMC10319760/
Abstract

Pleiotropy occurs when a genetic variant influences more than one trait. This is a key property of the genomic architecture of psychiatric disorders and has been observed for rare and common genomic variants. It is reasonable to hypothesize that the microscale genetic overlap (pleiotropy) across psychiatric conditions and cognitive traits may lead to similar overlaps at the macroscale brain level such as large-scale brain functional networks. We took advantage of brain connectivity, measured by resting-state functional MRI to measure the effects of pleiotropy on large-scale brain networks, a putative step from genes to behaviour. We processed nine resting-state functional MRI datasets including 32 726 individuals and computed connectome-wide profiles of seven neuropsychiatric copy-number-variants, five polygenic scores, neuroticism and fluid intelligence as well as four idiopathic psychiatric conditions. Nine out of 19 pairs of conditions and traits showed significant functional connectivity correlations (rFunctional connectivity), which could be explained by previously published levels of genomic (rGenetic) and transcriptomic (rTranscriptomic) correlations with moderate to high concordance: rGenetic-rFunctional connectivity = 0.71 [0.40-0.87] and rTranscriptomic-rFunctional connectivity = 0.83 [0.52; 0.94]. Extending this analysis to functional connectivity profiles associated with rare and common genetic risk showed that 30 out of 136 pairs of connectivity profiles were correlated above chance. These similarities between genetic risks and psychiatric disorders at the connectivity level were mainly driven by the overconnectivity of the thalamus and the somatomotor networks. Our findings suggest a substantial genetic component for shared connectivity profiles across conditions and traits, opening avenues to delineate general mechanisms-amenable to intervention-across psychiatric conditions and genetic risks.

摘要

当一个遗传变异影响不止一个特征时,就会出现多效性。这是精神障碍基因组结构的一个关键特征,已经在罕见和常见的基因组变异中观察到。可以合理地假设,精神疾病和认知特征之间的微观遗传重叠(多效性)可能导致大脑水平上的类似重叠,如大规模的大脑功能网络。我们利用静息态功能磁共振成像来测量遗传多效性对大规模大脑网络的影响,这是从基因到行为的一个假设步骤。我们处理了九个静息态功能磁共振成像数据集,其中包括 32726 个人,并计算了七个神经精神拷贝数变异、五个多基因评分、神经质和流体智力以及四个特发性精神疾病的全脑连接组图谱。19 对疾病和特征中有 9 对显示出显著的功能连接相关性(rFunctional connectivity),这可以用之前发表的基因组(rGenetic)和转录组(rTranscriptomic)与中度到高度一致性的相关性来解释:rGenetic-rFunctional connectivity = 0.71 [0.40-0.87] 和 rTranscriptomic-rFunctional connectivity = 0.83 [0.52; 0.94]。将这种分析扩展到与罕见和常见遗传风险相关的功能连接图谱中,表明 136 对连接图谱中有 30 对的相关性超过了随机水平。在连接水平上,遗传风险与精神障碍之间的这些相似性主要是由丘脑和躯体运动网络的过度连接驱动的。我们的发现表明,在不同的条件和特征之间存在着大量的遗传成分共享连接图谱,为在精神障碍和遗传风险之间描绘可干预的一般机制开辟了道路。