Functional imaging and genetics in Schizophrenia; search for endophenotypes

精神分裂症是一组异质性疾病，在症状和神经病理上有一些共同之处。精神分裂症中的这些不同症状的特点是具有不同的症状特征。这项建议的主要主题是使用脑功能成像、遗传标记和神经认知测试的组合方法，从临床证候特征中区分生物学亚型。 临床定义的综合征对抗精神病药物治疗的反应不同；常规 例如，抗精神病药物可以缓解阳性症状，而不是特别有助于治疗阴性症状，而非典型的抗精神病药物对阴性症状的影响很小，但可以测量。神经影像和基因分析已经开始阐明临床特征和治疗反应之间的关系。我们已经发现，有遗传标记可以区分某些药物应答者和无应答者。遗传标记也可以预测某些药物干预的副作用的发生。这些治疗反应亚型可能代表更同质的精神分裂症形式，而精神分裂症又可能具有不同的大脑结构/功能特征。 这项建议的目的是调查这样一种假设，即这些证候群是一种 不同脑区或环路功能障碍的后果，所有这些脑区或环路都与背侧前额叶皮质(DPFC)通信。DPFC包括背外侧前额叶皮质(DLPFC；BA46/腹侧9)和额前上回(BA9背侧)。我们假设，精神分裂症中常见的DPFC功能障碍可能源于DPFC输出本身的异常，或者来自最终与DPFC相互作用的各种电路和电路组合。 我们使用fMRI将专注于局部和扩展电路，我们假设这些电路参与了精神分裂症的不同方面的产生。在背景部分(下文)中，我们讨论与精神分裂症有关的特定大脑区域，以及我们关于这些区域在产生功能障碍方面如何功能联系的假设。为了验证这些假设，需要改进和更准确地识别和分割这些大脑区域的方法。我们建议通过增加临床测量、神经认知评估和遗传数据来扩展我们的电路分析，以确定可以作为内表型的常见模式。这种结合的动力是这样一个事实，即精神分裂症是可遗传的，并与特定的神经认知缺陷有关。合并这些数据是一个发展中的领域，由于相对于受试者的数量有大量的变量，因此带来了许多计算和统计方面的挑战。作为一项推动生物学项目(DPB)，这项工作需要计算能力和战略实施软件，在由这笔赠款资助的项目之间进行互动合作，以应对新兴领域联合成像和基因数据分析的挑战。

Schizophrenia is a heterogeneous group of disorders, which shares some commonality in symptoms and neuropathology. These different syndromes within schizophrenia are characterized by the predominance of distinct symptom profiles. The overarching theme of this proposal is to distinguish biological subtypes from among the clinical syndrome profiles, using the combined approach of functional brain imaging, genetic markers, and neurocognitive testing. Clinically defined syndromes respond differently to antipsychotic treatments; conventional antipsychotics can mitigate positive symptoms, for example, without particularly aiding in treating negative symptoms, while atypical antipsychotics have a small but measurable effect on negative symptoms. Neuroimaging and genetic analyses have begun to elucidate the relationships among the clinical profiles and treatment response. We have found that there are genetic markers that can differentiate certain drug responders from nonresponders. Genetic markers as well can predict the occurrence of side effects to certain pharmacological interventions. These treatment response subtypes could represent more homogeneous forms of schizophrenia that may, in turn, have distinct brain structure/function characteristics. The aim of this proposal is to investigate the hypothesis that these syndrome profiles are a consequence of dysfunction in separate brain areas or circuits, all of which communicate with the dorsal prefrontal cortex (DPFC). The DPFC includes the dorsolateral prefrontal cortex (DLPFC; BA 46/ventral 9) and anterior superior frontal gyrus (dorsal BA 9). We hypothesize that the DPFC dysfunction commonly found in schizophrenia can arise from abnormalities in the DPFC output, itself, or from various circuits and combinations of circuits that ultimately interact with the DPFC. Our use of fMRI will focus on both local and extended circuitry that we hypothesize is involved in producing different aspects of schizophrenia. In the Background section (below) we discuss the specific brain areas that are implicated in schizophrenia and our hypotheses as to how these areas are functionally linked in producing dysfunction. To test these hypotheses, improved and more accurate methods of identification and segmentation of these brain areas are required. We propose to extend our circuitry analyses by adding clinical measures, neurocognitive assessments, and genetic data to determine common patterns that could serve as endophenotypes. The impetus for this combination is the fact that schizophrenia is heritable and associated with specific neurocognitive deficits. Combining such data is a developing field and brings with it many computational and statistical challenges due to the large numbers of variables relative to the number of subjects. As a Driving Biological Project (DPB), this endeavor requires computational strengths and strategies implementation software in an interactive collaboration among the projects funded by this grant to address the challenges of the emerging field of combined imaging and genetic data analysis.