MRI Studies of Brain Function and Metabolism

识别与精神分裂症风险相关的基因使我们能够产生与疾病生物学方面相关的分子和神经系统机制的假说。通过使用认知、神经成像和基础科学的融合验证策略，提供了基于已证实的机制识别新的治疗方法的能力，并可能在分子通路和网络中产生潜在的新治疗靶点。我们对精神分裂症与基因相关的生物学验证的目的是提供生物学证据，证明精神分裂症相关风险等位基因对通过认知和神经成像方法分析的健康和疾病受试者大脑发育和功能的相关测量的影响。要做到这一点，需要基于新的认知范式和成像分析策略来精炼大脑功能中间表型。源自精细靶向大脑信息处理动态的表型可能会导致干扰这些过程的更强的基因效应。 Lemaitre等人。(《神经科学杂志》，2010)研究了与帕金森氏病风险相关的成纤维细胞生长因子(FGF20)基因多态性对年轻和老年男性受试者大脑结构和功能的影响。结合收敛生物验证策略，我们使用基于体素的形态计量学分析高分辨率解剖磁共振图像，并测量了人死后脑组织中FGF20mRNA的表达。我们的结果表明，携带T等位基因的受试者海马体体积更大，言语情景记忆减少，并且随着正常年龄的增长，海马体体积急剧下降。T携带者也有更高的海马区FGF20mRNA表达，这与先前报道的数据一致。携带C等位基因的个体与预期的microRNA结合域匹配，而T携带者扰乱了microRNA的结合能力，导致FGF20蛋白增加。最后，成纤维细胞生长因子受体1在人的海马体中含量最丰富，被认为在海马体中介导了成纤维细胞生长因子20的强大遗传效应。总之，在健康受试者中，帕金森病风险关联、mRNA表达、脑形态、认知缺陷以及与衰老的相互作用的一致证据证实了FGF20在发育和衰老过程中对人脑结构和功能的作用。 我们研究的另一个方面是成像遗传学，它在我们确认神经精神障碍所涉及的神经机制的整体收敛验证策略中发挥着重要作用。精神分裂症是复杂的、可遗传的和遗传异质性的。精神分裂症易感基因通过影响调节行为、认知和执行功能表达的神经系统的发育和功能，与无数症状相关。人类大脑的这种功能障碍仍有待很好地了解。成像遗传学在将可能的疾病机制的基本生物学与活着的大脑中的生理相关特征相结合方面发挥了作用。具体地说，这种方法的目的是测试与临床诊断统计相关的等位基因是否预测大脑结构和功能的偏差，这些偏差与精神分裂症患者及其健康兄弟姐妹的发现有关。Tan等人(认知神经精神病学，2009)回顾了成像遗传学如何解释与工作记忆和执行功能相关的前额脑系统，从多巴胺系统中通过儿茶酚-O-甲基转移酶(COMT)的遗传变异和主动认知处理过程中对前额脑网络的调制开始。也有证据表明，AKT1(一种细胞内信号分子)下游的多巴胺相关表达发生了变化。这些遗传变异是神经成像测量上位性的证据，表明多个基因的非相加组合调节着活跃的认知大脑机制。成像遗传学增加了我们对与神经精神障碍相关的人类认知脑过程的遗传机制的了解。 有已发表的报道表明，Reelin基因(RELN)与神经发育缺陷有关，与精神分裂症风险增加有关。RELN编码糖蛋白reelin，这是一种分泌型蛋白酶，在抑制神经元迁移和突触可塑性的分子过程中发挥关键作用。精神分裂症发病机制的一致证据来自基因关联和基因表达研究，这些研究表明精神分裂症患者死后脑组织中的mRNA和蛋白质水平降低。关于这些措施也有不一致的结论。托斯特等人。(生物精神病学，2010)使用基于体素的形态测量和扩散张量成像来评估大脑结构。在工作记忆任务中使用功能磁共振成像研究大脑功能，并测量死后脑组织中前额叶皮质和海马区的基因表达。这些分析没有显示出该基因或基因-性别相互作用的显著影响的证据，这是已经报道的。我们的结论是，测试和其他相关的多态不会影响与精神分裂症神经生物学相关的大脑测量。

Identifying genes associated with risk for schizophrenia has allowed us to generate hypotheses about molecular and neural system mechanisms related to biologic aspects of the illness. By using a convergent validation strategy of cognitive, neuroimaging and basic science offers the ability to identify new approaches to treatment based on confirmed mechanisms and may lead to potentially new therapeutic targets within molecular pathways and networks. Our aim for biological validation of genetic association with schizophrenia is to provide biologic evidence of the effect of schizophrenia associated risk alleles on relevant measures of brain development and function assayed with cognitive and neuroimaging approaches in healthy and ill subjects. Accomplishing this will require refinement of brain functional intermediate phenotypes based on novel cognitive paradigms and analytic strategies in imaging. Phenotypes that derive from finely targeting brain information processing dynamics may result in stronger gene effects that interfere with these processes. Lemaitre et al. (Journal of Neuroscience, 2010) examined the effect of the fibroblast growth factor (FGF20) gene polymorphism associated with risk for Parkinsons disease on brain structure and function in a large sample of young and elderly male subjects. Incorporating the convergent biologic validation strategy, we used voxel-based morphometry to analyze high-resolution anatomical magnetic resonance images and FGF20 mRNA expression was measured in human postmortem brain tissue. Our results showed subjects carrying the T allele had larger hippocampal volume, reduced verbal episodic memory and demonstrated a sharp decline in hippocampal volume with normal aging. The T carriers also had greater expression of hippocampal FGF20 mRNA which is consistent with previously reported data. Individuals carrying the C allele matched the expected microRNA binding domain, whereas the T carriers disrupt the binding ability of microRNA resulting in an increase in FGF20 protein. Lastly, FGF receptor 1 is found most abundantly in the human hippocampus and is thought to mediate the strong genetic effects of FGF20 in the hippocampus. Altogether the convergent evidence in healthy subjects of Parkinsons disease risk association, mRNA expression, brain morphology, cognitive deficits and an interaction with aging confirmed the role of FGF20 in human brain structure and function during development and aging. Another aspect of our research is in imaging genetics, which plays an important role in our overall convergent validation strategy for confirming neural mechanisms implicated in neuropsychiatric disorders. Schizophrenia is complex, heritable and genetically heterogeneous. Schizophrenia susceptibility genes are associated with a myriad of symptoms by affecting the development and function of neural systems that mediate expression of behavior, cognition and executive function. This dysfunction of the human brain remains to be well understood. Imaging genetics plays a role in integrating the basic biology of putative disease mechanisms with physiological correlated traits in the living brain. Specifically, the aim of this approach is to test whether alleles that are statistically associated with clinical diagnosis predict deviations in brain structure and function that are related to findings in patients with schizophrenia and their healthy siblings. Tan et al. (Cognitive Neuropsychiatry, 2009) reviewed how imaging genetics elucidates prefrontal brain systems associated with working memory and executive function beginning with genetic variation in the dopamine system via catechol-O-methyltransferase (COMT) and modulation of prefrontal brain networks during active cognitive processing. There is also evidence of variation of dopamine-related expression downstream on AKT1 (an intracellular signaling molecule). These genetic variants are evidence of epistasis on neuroimaging measures, suggesting that a non-additive combination of multiple genes modulate active cognitive brain mechanisms. Imaging genetics has added to our knowledge of genetic mechanisms of human cognitive brain processes related to neuropsychiatric disorders. There are published reports of convergent evidence implicating the reelin gene (RELN) in neurodevelopmental deficits associated with an increased risk for schizophrenia. RELN encodes for the glycoprotein reelin, a secretory protease which plays a pivotal role in the molecular processes that subserve neuronal migration and synaptic plasticity. The convergent evidence of schizophrenia pathogenesis is from genetic association and gene expression studies showing a reduction in mRNA and protein levels in postmortem brain tissue of patients with schizophrenia. There have also been inconsistent findings regarding these measures. Tost et al. (Biological Psychiatry, 2010) evaluated brain structure using voxel-based morphometry and diffusion tensor imaging. Brain function was studied using fMRI during working memory tasks, and gene expression was measured in both prefrontal cortex and hippocampus in postmortem brain tissue. These analyses did not show evidence of a significant effect of the gene or a gene-sex interaction, which had been reported. We concluded that the tested and other related polymorphisms do not affect brain measures related to the neurobiology of schizophrenia.