Genetics and Bioengineering Program, Faculty of Engineering and Natural Sciences, International University of Sarajevo, Hrasnica cesta, 15 Ilidza, Sarajevo 71210, Bosnia and Herzegovina.
Department of Molecular Biology and Genetics, Faculty of Engineering and Natural Sciences, Uskudar University, Istanbul 34662, Turkey.
Int J Mol Sci. 2018 Jan 11;19(1):219. doi: 10.3390/ijms19010219.
Schizophrenia (SZ) is a heritable brain disease originating from a complex interaction of genetic and environmental factors. The genes underpinning the neurobiology of SZ are largely unknown but recent data suggest strong evidence for genetic variations, such as single nucleotide polymorphisms, making the brain vulnerable to the risk of SZ. Structural and functional brain mapping of these genetic variations are essential for the development of agents and tools for better diagnosis, treatment and prevention of SZ. Addressing this, neuroimaging methods in combination with genetic analysis have been increasingly used for almost 20 years. So-called imaging genetics, the opportunities of this approach along with its limitations for SZ research will be outlined in this invited paper. While the problems such as reproducibility, genetic effect size, specificity and sensitivity exist, opportunities such as multivariate analysis, development of multisite consortia for large-scale data collection, emergence of non-candidate gene (hypothesis-free) approach of neuroimaging genetics are likely to contribute to a rapid progress for gene discovery besides to gene validation studies that are related to SZ.
精神分裂症（SZ）是一种遗传性脑疾病，源自遗传和环境因素的复杂相互作用。SZ 神经生物学背后的基因在很大程度上尚不清楚，但最近的数据表明，遗传变异（如单核苷酸多态性）具有很强的证据，使大脑容易受到 SZ 的风险影响。对这些遗传变异进行结构和功能脑映射对于开发更好的诊断、治疗和预防 SZ 的药物和工具至关重要。为了解决这个问题，神经影像学方法结合遗传分析已经被越来越多地使用了将近 20 年。所谓的影像遗传学，本文将概述这种方法的机会及其在 SZ 研究中的局限性。虽然存在可重复性、遗传效应大小、特异性和敏感性等问题，但像多元分析、为大规模数据收集建立多地点联盟、出现非候选基因（无假设）神经影像学遗传学方法等机会可能会有助于基因发现的快速进展，除了与 SZ 相关的基因验证研究之外。
