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基于多基因遗传风险的精神分裂症神经机制研究
刘书
Subtype硕士
Thesis Advisor刘冰
2019-05-31
Degree Grantor中国科学院自动化研究所
Place of Conferral中国科学院自动化研究所
Degree Name工学硕士
Degree Discipline模式识别与智能系统
Keyword精神分裂症 多基因遗传 Mir137 灰质体积 功能连接
Abstract

精神分裂症是一种多基因遗传的精神疾病,持续性强且危害性极大,探究精神分裂症多基因遗传的神经机制可以为疾病的预防和治疗提供重要的线索。因此本文使用影像遗传学方法,基于中国汉族人群的多模态磁共振成像并结合全基因组数据系统地考察精神分裂症多基因遗传的神经机制。
本文首先从全局出发,考察全基因组范围内精神分裂症的遗传效应对大脑结构和功能的影响,从而反映精神分裂症整体的神经生物学特性。具体上,为了评价整体遗传效应,本文首先参考一项包含大量汉族被试的精神分裂症全基因组关联分析结果,计算每个被试的多基因风险分数。接着,基于结构和静息态功能磁共振影像,探究精神分裂症患者与健康对照之间在灰质体积和功能连接上出现显著差异的脑区,并进一步分析多基因风险分数与这些异常的灰质体积和功能连接的关联。结果发现,在病例组中,海马的灰质体积以及海马到内侧前额叶的功能连接显著低于健康对照,并且它们受到多基因遗传的影响。另外,对于未患病的一级亲属,这些结构和功能指标均显著低于健康对照,与病例组具有相似的变化。可以看出,受多基因遗传影响的海马灰质体积以及海马到内侧前额叶的功能连接可能是精神分裂症重要的病理生理学机制,同时可能作为生物标记物,为精神分裂症早期诊断提供重要的线索。
除此之外,研究特定风险基因相关的神经机制对理解精神分裂症的病理同样十分重要。以往的全基因组关联分析研究发现MIR137 是精神分裂症的关键风险基因之一,而且MIR137 会调节许多其他基因的表达,因此本文接着考察了MIR137 调节的基因集特定的神经机制。首先,为了评估受MIR137 调节的1274个基因对精神分裂症的累积遗传效应,本文计算每个被试的MIR137 多基因风险分数,并进一步考察了MIR137 多基因风险分数在精神分裂症患者和健康对照之间是否具有显著差异。而且已有的研究表明背外侧前额叶的功能活动与MIR137紧密相关,因此本文计算了背外侧前额叶到全脑的功能连接,并在两个独立的健康数据集上分别分析MIR137 多基因风险分数与背外侧前额叶功能连接的关联。结果发现,相比于单个基因,MIR137 多基因风险分数可以更好地反映精神分裂症的遗传特性,同时在两个独立的数据集上均发现MIR137 多基因风险分数与背外侧前额叶到上顶叶皮层以及下颞叶皮层的功能连接呈现显著的负相关关系。可以看出,这两条背外侧前额叶功能连接可能是重要的内表型,搭建了MIR137调节的基因集到精神分裂症临床表型之间的桥梁,提示了与精神分裂症MIR137相关的一个重要的神经机制。
总之,本文分别从全基因组和单基因集的角度出发,对精神分裂症多基因遗传的神经机制进行了较为系统的研究,为理解精神分裂症复杂的致病机制提供了重要的线索。

Other Abstract

Schizophrenia is a severe and chronic mental disorder with high heritability and polygenic inheritance. Investigating the neural mechanism underlying the polygenic risk of schizophrenia can provide important clues for the prevention and treatment of the disorder. Therefore, the study combined the genomic and multimodal neuroimaging data from Han Chinese population to investigate the neural mechanism underlying the polygenic risk of schizophrenia.
From the whole situation, this stduy investigated the overall impacts of genomewide variants related to schizophrenia on brain structure and function, which can reflect the neurobiological characterization of schizophrenia. Specifically, to assess the overall genetic influences of schizophrenia, we calculated a polygenic risk score (PGRS) for each participant based on the data from a recent meta-analysis of genome-wide association study (GWAS) that comprised a large number of Chinese samples. Next, neuroimaging data from a large sample of Han Chinese were included in this study. Comparing schizophrenia patients with healthy controls, we examined abnormal gray matter volume and functional connectivity via structural and functional magnetic resonance imaging respectively, and further investigated the association between PGRS and these abnormal neuroimaging measures. The imaging genetic analysis revealed that the individual PGRS showed a significantly negative correlation with the hippocampal gray matter volume and hippocampus-medial prefrontal cortex functional connectivity, both of which were lower in the schizophrenia patients than in the controls. We further found that the observed neuroimaging measures showed weak, but similar changes in unaffected first-degree relatives to those in the patients. These findings suggested that genetically influenced brain gray matter volume and functional connectivity may provide important clues for understanding the pathological mechanisms of schizophrenia and for the early diagnosis of schizophrenia.
In addition, investiageting the neural mechanisms of a specifc gene set is also important for the understanding of schizophrenia. GWAS have consistently revealed that a variant of microRNA 137 (MIR137) shows a quite significant association with schizophrenia, and MIR137 regulated the expression of many genes. Therefore, this study examined the neural mechanisms of MIR137-regulated genes. Specifcally, To evaluate the additive effects of the MIR137 regulated genes (N = 1274), we calculated a MIR137 PGRS for schizophrenia and tested its association with the risk for schizophrenia in the genomic data of a Han Chinese population that included schizophrenia patients and healthy controls. Meanwhile, dorsolateral prefrontal cortex (DLPFC) functional connectivity, a robust correlate of MIR137, may provide plausible endophenotypes.
We then investigated the association between MIR137 PGRS and DLPFC functional connectivity in two independent young healthy cohorts. We found that the MIR137 PGRS successfully captured the differences in genetic structure between the patients and controls, but the single gene MIR137 did not. We then consistently found that a higher MIR137 PRS was correlated with lower functional connectivities between the DLPFC and both the superior parietal cortex and the inferior temporal cortex in two independent cohorts. The findings suggested that these two functional connectivities of the DLPFC could be important endophenotypes linking the MIR137-regulated genetic structure to schizophrenia.
In summary, from whole-genome data to a single gene set, this study investigated the neural mechanisms underlying the polygenic risk of schizophrenia. Our findings may provide important clues for the understanding of complex pathological mechanisms.

Pages78
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23800
Collection脑网络组研究中心
Recommended Citation
GB/T 7714
刘书. 基于多基因遗传风险的精神分裂症神经机制研究[D]. 中国科学院自动化研究所. 中国科学院自动化研究所,2019.
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