Combined effects of SNPs and CNVs on brain structure in patients with schizophre

SNPs 和 CNVs 对精神分裂症患者大脑结构的联合影响

• 批准号: 8708151
• 负责人: Jingyu Liu
• 金额: $ 19.05万
• 依托单位: THE MIND RESEARCH NETWORK
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8708151
• 关键词: 11p13; 11q14; 12p13; 13q34; 1q21; 1q42; 22q11; 2q33; 6p22; 8p12; Accounting; Address; Affect; Anisotropy; Anterior; Biological Markers; Bipolar Disorder; Brain; Chromosomes; Chronic; Clinical; Cognitive deficits; Control Groups; Copy Number Polymorphism; Cytogenetics; Data; Detection; Diagnosis; Disease; Dorsal; Employee Strikes; Epidemiology; Equilibrium; Genetic; Genetic Determinism; Genetic Predisposition to Disease; Genetic Variation; Genome; Genomics; Hippocampus (Brain); Image; Individual; Insula of Reil; Investigation; Lateral; Link; Linkage Disequilibrium; Measures; Medial; Methods; Multimodal Imaging; Myelin; Neurobiology; Oligodendroglia; Pathway interactions; Patients; Phenotype; Predisposition; Prefrontal Cortex; Reporting; Sampling; Schizophrenia; Single Nucleotide Polymorphism; Specificity; Structure; Symptoms; Techniques; Variant; base; design; genetic profiling; genetic risk factor; genetic variant; gray matter; improved; neuroimaging; neuromechanism; neuropsychiatry; novel strategies; psychotic symptoms; relating to nervous system; thalamocortical tract; white matter

Albeit being two separate diagnoses, schizophrenia (SZ) and bipolar disorder (BP) share psychotic symptoms, chronic courses and cognitive deficits, as well as genetic determinants from clinical, epidemiological and genetic findings. The underlying mechanism(s) accounting for such a relation is far from clear. This project is designed to improve the understanding of pathways by which genetic predisposition influences brain structure abnormalities associated with clinical symptoms, through combining the advances of genetic and neuroimaging techniques. We propose a hierarchical study that will leverage a large-sample genomic analysis, and specific genetic neuroimaging association analyses. First, we will use a very large sample of single nucleotide polymorphisms and copy number variations from the Psychiatric Genomics Consortium (PGC) SZ and BP patients in order to reliably identify the candidate chromosome regions. Within the candidate regions we will apply multivariate imaging-genetic methods to extract specific genetic factors directly associated with brain structural networks that differentiate patients from controls, using a locally collected sample. Gray matter concentration and white matter integrity within brain networks will be analyzed for their associations with both genetic profiles and patient diagnoses. Through comparison of such associations in SZ, BP and healthy control groups, we will be able to identify common and unique neuropathological mechanisms underlying the two disorders. Such genetic and neural features can act as effective biomarkers for refined patient categorization.

尽管精神分裂症（SZ）和双相情感障碍（BP）是两种不同的诊断，但它们有着共同的精神病症状， 慢性病程和认知缺陷，以及来自临床、流行病学和 基因发现解释这种关系的根本机制还远不清楚。这个项目是 旨在提高对遗传倾向影响大脑结构的途径的理解 与临床症状相关的异常，通过结合遗传学和神经影像学的进展， 技术.我们提出了一个分层的研究，将利用大样本的基因组分析，并具体 遗传神经影像学关联分析。首先，我们将使用非常大的单核苷酸样本， 多态性和拷贝数变异来自精神病基因组学联盟（PGC）SZ和BP 患者，以便可靠地识别候选染色体区域。在候选区域内，我们将 应用多元成像-遗传学方法提取与大脑直接相关的特定遗传因素 使用当地收集的样本，区分患者和对照组的结构网络。灰质 将分析大脑网络内的浓度和白色物质完整性与两者的关联 基因图谱和病人诊断通过SZ、BP和健康对照组的比较， 组，我们将能够确定共同的和独特的神经病理学机制，这两个 紊乱这些遗传和神经特征可以作为有效的生物标志物，用于精确的患者分类。