精神分裂症是临床常见重性精神疾病之一，受多重异质性病因的影响。尽管广泛使用的国际精神疾病诊断标准为精神分裂症分类提供了具有较好的一致性和可靠性的临床标准，但对精神分裂症的病因、发病机制和治疗的研究缺乏根本性的帮助。本研究将针对精神分裂症生物学诊断标记及治疗反应预测指标这一亟待解决的关键问题，顺应国际前沿有关精神疾病生物学标记研究的发展趋势，采用先进的大数据分析技术，通过“横断面研究发现-纵向研究证实”两步法策略，在系统水平（临床、认知、影像、电生理等）和分子水平（基因结构变异、基因表达及表观遗传学、免疫生化等）上发现与精神分裂症发生、发展、治疗反应及预后相关的生物学标记，揭示精神分裂症多模态多水平的综合性生物学指标。本研究的实施，将为不同类别精神分裂症的诊断和治疗指导提供客观生物学依据，也是最终阐明精神分裂症这一类临床综合征复杂病因、发病机制及开发有效治疗新药物的切入点和必要步骤。

Schizophrenia is one of the most common and severe psychiatric disorders, which is affected by heterogeneous factors. Although widely used international classification and diagnostic criteria for schizophrenia provide a relatively good consistency and reliability for clinical diagnosis, there is still a lack of fundamental understanding in etiology, pathogenesis and treatment of schizophrenia. Along with the forefront of research and development in this field, the current project will focus on above-mentioned unsolved problems in order toidentify the biological markers for diagnosis and treatment response inschizophrenia. Furthermore, this project will adopt the two-stage strategy by combining the findings from cross-sectional and longitudinal studies, with the state-of-the-art techniques including clinical, neurocognition, brain imaging, electrophysiology and genetics, neuroimmunology, and big data mining etc. This project aims to identify the key biomarkers to inform the etiology, progress, treatment response and prognosis of schizophrenia with the multiple module andmultilevel datasets at systematic level (clinical, neuroimaging, electrophysiology etc.) and molecular level (genetic mutations, gene expression epigenetics and neuroimmunology etc.). The implementation of the project will provide objective biological evidences for the diagnosis and treatment in the point of view of different subtypes (or subgroups) of schizophrenia. There is also important significance for making breakthrough to finally identify the complex etiology, pathogenesis, as well as to develop the novel medication for the clinical syndrome.