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Why do not all high schizotypes develop schizophrenia? Protective factors in people with high risk for schizophrenia using machine learning methods

为什么并非所有高度精神分裂型患者都会患上精神分裂症？

基本信息

批准号：
278205181
负责人：
Professor Dr. Ulrich Ettinger
金额：
--
依托单位：
Klinik für Psychiatrie und Psychotherapie (Campus Innenstadt)
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2018-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/278205181?language=en
关键词：
Why do schizotypes develop schizophrenia

项目摘要

Schizophrenia is a severe psychiatric illness with unknown aetiology. An important step in the search for aetiological factors has been the realisation that schizophrenia does not represent a binary phenotype (present, absent) with sudden disease onset. Instead, there is growing agreement that continua between normal and patient populations play an important role. Numerous findings point to phenomenological, genetic, cognitive and neural similarity between schizophrenia and the personality trait of schizotypy. Given this overlap there remains, however, an important question: Why do most people with high levels of schizotypy do not develop schizophrenia? This question leads immediately to a related problem: What are the neural and cognitive differences between highly schizotypal but clinically unaffected individuals and patients with schizophrenia? Put differently, the neural mechanisms (e.g. of resilience) that prevent the outbreak of schizophrenia in high schizotypes are unknown. The present study aims to systematically investigate these mechanisms, for the first time, using machine learning methods. In addition to characterising neural mechanisms we will also assess environmental risk factors and we will obtain a polygenic risk score for schizophrenia in order to investigate the association of these variables with schizotypy and brain structure and function.

精神分裂症是一种病因不明的严重精神疾病。寻找病因因素的一个重要步骤是认识到精神分裂症并不代表突然发病的二元表型（存在或不存在）。相反，越来越多的人认为正常人群和患者群体之间的连续性发挥着重要作用。许多研究结果表明，精神分裂症和精神分裂型的人格特征在现象学、遗传、认知和神经方面存在相似性。然而，考虑到这种重叠，仍然存在一个重要的问题：为什么大多数患有高水平分裂型的人不会患上精神分裂症？这个问题立即引出了一个相关的问题：在高度分裂型但临床未受影响的个体和精神分裂症患者之间的神经和认知差异是什么？换句话说，防止精神分裂症在高分裂型中爆发的神经机制（例如恢复力）是未知的。本研究旨在首次使用机器学习方法系统地研究这些机制。除了描述神经机制外，我们还将评估环境风险因素，我们将获得精神分裂症的多基因风险评分，以调查这些变量与精神分裂型和大脑结构和功能的关系。