摘要
成像遗传学是一个综合的研究方法,利用神经影像学和遗传学来评估遗传变异对大脑功能和结构的影响。成像遗传学既是对精神疾病风险基因发现的工具,又是描述风险基因变异对神经系统的影响,阐明大脑功能与精神疾病有关的定量和机理方面的策略。成像遗传学的早期研究功能包括大脑形态和单核苷酸多态性之间的关联分析,其功能是众总所周知的,如儿茶酚氧位甲基转移酶(COMT)和脑源性神经营养因子(BDNF)。精神疾病的全基因组关联分析已经鉴定了未知功能的基因,如ZNF804A,成像遗传学已经被用于调查这些基因的生物学功能线索。小样本研究的结果难以复制,促使大规模的合作研究的建立,如ENIGMA、CHARGE和IMAGEN,用以收集成千上万的图像。在一项全基因组关联的研究中,ENIGMA联合成功识别了与海马体积相关的常见基因组变异12q24,CHARGE联合研究再次发现了这一现象。成像遗传学的新时代刚刚开始,我们面临的下一个挑战是从遗传学和神经成像中获得的大型数据中发现小尺寸效应的信号。通过适当的统计阈值简化数据的新方法和技术,如多基因分析和并行独立分量分析(ICA)是必要的。成像遗传学未来的进步将有助于发现基因和提供了解精神疾病的机理。
关键词: 躁郁症,成像遗传学和精神疾病,基因,成像遗传学,中间表型,神经成像,精神分裂症,结构磁共振成像
Current Molecular Medicine
Title:Imaging Genetics and Psychiatric Disorders
Volume: 15 Issue: 2
关键词: 躁郁症,成像遗传学和精神疾病,基因,成像遗传学,中间表型,神经成像,精神分裂症,结构磁共振成像
摘要: Imaging genetics is an integrated research method that uses neuroimaging and genetics to assess the impact of genetic variation on brain function and structure. Imaging genetics is both a tool for the discovery of risk genes for psychiatric disorders and a strategy for characterizing the neural systems affected by risk gene variants to elucidate quantitative and mechanistic aspects of brain function implicated in psychiatric disease. Early studies of imaging genetics included association analyses between brain morphology and single nucleotide polymorphisms whose function is well known, such as catechol-Omethyltransferase (COMT) and brain-derived neurotrophic factor (BDNF). GWAS of psychiatric disorders have identified genes with unknown functions, such as ZNF804A, and imaging genetics has been used to investigate clues of the biological function of these genes. The difficulty in replicating the findings of studies with small sample sizes has motivated the creation of largescale collaborative consortiums, such as ENIGMA, CHARGE and IMAGEN, to collect thousands of images. In a genome-wide association study, the ENIGMA consortium successfully identified common variants in the genome associated with hippocampal volume at 12q24, and the CHARGE consortium replicated this finding. The new era of imaging genetics has just begun, and the next challenge we face is the discovery of small effect size signals from large data sets obtained from genetics and neuroimaging. New methods and technologies for data reduction with appropriate statistical thresholds, such as polygenic analysis and parallel independent component analysis (ICA), are warranted. Future advances in imaging genetics will aid in the discovery of genes and provide mechanistic insight into psychiatric disorders.
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Cite this article as:
Imaging Genetics and Psychiatric Disorders, Current Molecular Medicine 2015; 15 (2) . https://dx.doi.org/10.2174/1566524015666150303104159
DOI https://dx.doi.org/10.2174/1566524015666150303104159 |
Print ISSN 1566-5240 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5666 |
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