精神分裂症相关的拷贝数变异及其致病机制的研究

Schizophrenia is a chronic and complex mental disorder with a prevalence of approximately 1% in the population worldwide, and is reported to rank the third of disabling effects of health conditions. According to the WHO, there are 24 million people with schizophrenia throughout the world with an estimated lifetime suicide risk of 4.9%. As in China, there are about a hundred million people with all kinds of psychoses, among which approximately 10 million people are suffering from schizophrenia. Relevant studies provide strong evidence that genetic factors play a crucial etiological role in the schizophrenia, with heritability estimated at up to 80%. However, key components and relevant pathways underlying the disease have still to be identified. Copy number variations (CNVs) have emerged in the last decade as a category of structural genetic diversity that plays a key role in human health and common diseases, thanks to the rapid development and expanded use of microarray technologies, including array comparative genomic hybridization (aCGH) and next-generation sequencing methods. A number of studies have suggested the role of CNVs in schizophrenia susceptibility, however, most of the evidence was from studies in populations with European ancestry. Cross-ethnic validation of the susceptibility CNVs and identifying novel ones in Han Chinese populations is important for understanding the etiology and genetic risk factors for schizophrenia. In our previous work, we performed Agilent Human whole-genome 1x1M aCGH analysis in 100 tios sample of Han Chinese population. We have replicated several associated loci that were previously identified in European populations, and also identified potential novel loci conferring risk of schizophrenia. Next, we plan to develop a high-resolution customized aCGH, which targets the new CNV loci found in the tios sample, and to validate these CNVs in an independent data set with 5000 cases with schizophrenia and 5000 control subjects of Han Chinese origin using this customized aCGH. Then we will generate mouse models carrying the deletions or duplications in murine chromosomes orthologous to these human CNVs using the Cre/loxP-based chromosome engineering technique. In addition, behavior experiments will be performed to see whether the CNV mouse models exhibit behavioral phenotypes related to schizophrenia. In conclusion, our study may provide new evidence for the role of CNVs in the etiology of schizophrenia and offer new insight into prevention and treatment of schizophrenia.

精神分裂症是一种严重的复杂慢性精神类疾病，在全球人群中终身患病率约为1%。导致精神分裂症的原因至今不明，既往研究已发现拷贝数变异（CNV）与精神分裂症相关，但大多数研究是在欧美人群中开展的，而且基于核心家系的相关研究也较少，因此中国汉族人群中与精神分裂症相关的新的CNV易感位点仍有待探索。我们前期应用aCGH芯片对中国汉族100个核心家系开展了全基因组扫描，发现了一些新的潜在的CNV位点。本课题拟针对这些CNV位点设计个性化aCGH芯片，并以大样本量病例-对照研究进行验证，进一步确定这些CNV与精神分裂症的相关性；对于可以重复的CNV，拟建立小鼠模型，开展行为学实验，考察其是否产生类似精神分裂症的症状。我们的研究不仅可以发现与精神分裂症相关的新的CNV易感位点，还可以揭示CNV在精神分裂症致病机制中所起的作用，有望为精神分裂症的预防、诊断和治疗提供新的思路。

精神分裂症是一种严重的复杂慢性精神类疾病，在全球人群中终身患病率约为1%。导致精神分裂症的原因至今不明，目前普遍认为遗传因素在精神分裂症的致病机制中起到了决定性作用。既往研究已发现拷贝数变异（copy number variation，CNV）与精神分裂症发病相关，但大多数研究是在欧美人群中开展的，而且基于核心家系的相关研究也较少。本项目通过高分辨率的人类全基因组比较基因组杂交芯片（array comparative genomic hybridization，aCGH）对我国100个汉族核心家系（精神分裂症患者及其父母）所携带的拷贝数变异进行了研究，找到了几个潜在的可能与精神分裂症发病相关的新的CNV易感位点。通过后续在散发精神分裂症病例和正常对照中开展的case-control研究，进一步发现其中一个CNV（5q35.1）区域内所包含的KCNIP1基因可能是中国汉族人群中的精神分裂症候选基因。通过首次构建小鼠模型并开展一系列行为学实验，我们初步对该基因进行了功能研究，在成年小鼠的海马区域敲减Kcnip1基因后，发现基因缺陷小鼠表现出轻微的社交障碍和学习记忆障碍。本项目的研究结果为进一步阐明精神分裂症的发病机制提供了新的线索，有望为精神分裂症的预防、诊断和治疗提供新的思路。