基于并行独立成分分析方法研究精神分裂症的影像遗传学特征

The Study of Imaging Genetic Characteristics of Schizophrenia Based on Parallel ICA

近年来影像遗传学领域的发展,为精神分裂症的研究开启了新的方向。该文运用并行独立成分分析方法处理63个受试者的fMRI数据和SNP数据,通过在两种数据类型之间增加约束项,提取与精神分裂症相关的独立成分。研究结果显示,一个fMRI成分和一个SNP成分之间的相关性最大,fMRI成分主要包括楔前叶、舌回、楔叶脑区,SNPs主要在CHRNA7和DISC1等基因中。同时,该fMRI成分和SNP成分在精神分裂症患者和对照组的混合系数上有显著差异,P值分别为0.0009和0.0014。该文运用一种分析影像遗传学的新方法,来识别与精神分裂症相关的大脑功能和遗传信息之间的相互关系,为精神分裂症的辅助诊断提供了帮助。

In recent years,the development of imaging genetics has shown a new threshold for the study of schizophrenia.In this paper,the fMRI data and SNP data of 63 subjects were processed by parallel independent component analysis,and independent components related to schizophrenia were extracted by adding constraint terms between two types of data.The results showed the greatest correlation between an fMRI component mainly including three brain regions:precuneus,sublingual gyrus and cuneus,and an SNP component mainly found in genes such as CHRNA7 and DISC1.Meanwhile,the fMRI components and SNP components were statistically significant in the mixing coefficient between patients with schizophrenia and the control group,with P values of 0.000 9 and 0.001 4,respectively.In summary,this work used a new method of analyzing genetic imaging to identify the interrelationship between brain function and genetic information related to schizophrenia,providing assistance in the diagnosis of schizophrenia.