Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131-0001, USA.
Neuroimage. 2012 Jul 16;61(4):866-75. doi: 10.1016/j.neuroimage.2012.03.022. Epub 2012 Mar 13.
Recently, deriving candidate endophenotypes from brain imaging data has become a valuable approach to study genetic influences on schizophrenia (SZ), whose pathophysiology remains unclear. In this work we utilized a multivariate approach, parallel independent component analysis, to identify genomic risk components associated with brain function abnormalities in SZ. 5157 candidate single nucleotide polymorphisms (SNPs) were derived from genome-wide array based on their possible connections with SZ and further investigated for their associations with brain activations captured with functional magnetic resonance imaging (fMRI) during a sensorimotor task. Using data from 92 SZ patients and 116 healthy controls, we detected a significant correlation (r=0.29; p=2.41 × 10(-5)) between one fMRI component and one SNP component, both of which significantly differentiated patients from controls. The fMRI component mainly consisted of precentral and postcentral gyri, the major activated regions in the motor task. On average, higher activation in these regions was observed in participants with higher loadings of the linked SNP component, predominantly contributed to by 253 SNPs. 138 identified SNPs were from known coding regions of 100 unique genes. 31 identified SNPs did not differ between groups, but moderately correlated with some other group-discriminating SNPs, indicating interactions among alleles contributing toward elevated SZ susceptibility. The genes associated with the identified SNPs participated in four neurotransmitter pathways: GABA receptor signaling, dopamine receptor signaling, neuregulin signaling and glutamate receptor signaling. In summary, our work provides further evidence for the complexity of genomic risk to the functional brain abnormality in SZ and suggests a pathological role of interactions between SNPs, genes and multiple neurotransmitter pathways.
最近，从脑影像数据中推导出候选内表型已成为研究精神分裂症（SZ）遗传影响的一种有价值的方法，而其病理生理学仍不清楚。在这项工作中，我们利用多元方法，即平行独立成分分析，来识别与 SZ 大脑功能异常相关的基因组风险成分。根据与 SZ 可能的关联，从全基因组芯片中提取了 5157 个候选单核苷酸多态性（SNP），并进一步研究了它们与功能磁共振成像（fMRI）在感觉运动任务中捕获的大脑激活之间的关联。使用来自 92 名 SZ 患者和 116 名健康对照者的数据，我们检测到一个 fMRI 成分和一个 SNP 成分之间的显著相关性（r=0.29;p=2.41×10(-5)），这两个成分都显著地区分了患者和对照者。fMRI 成分主要由中央前回和中央后回组成，这是运动任务中的主要激活区域。平均而言，在与链接 SNP 成分具有较高负荷的参与者中，这些区域的激活较高，主要由 253 个 SNP 贡献。138 个确定的 SNP 来自 100 个独特基因的已知编码区域。31 个确定的 SNP 在组间没有差异，但与其他一些具有组间区分能力的 SNP 中度相关，表明等位基因之间的相互作用导致 SZ 易感性增加。与确定的 SNP 相关的基因参与了四个神经递质途径：GABA 受体信号、多巴胺受体信号、神经调节素信号和谷氨酸受体信号。总之，我们的工作进一步证明了 SZ 功能性大脑异常的基因组风险的复杂性，并表明 SNP、基因和多个神经递质途径之间的相互作用具有病理性作用。
