重度神经认知精神病:一种基于机器学习的新型精神分裂症内表型类,类似于Kraepelin和Bleuler的概念。

IF 3.8 4区 医学 Q1 Medicine Acta Neuropsychiatrica Pub Date : 2023-06-01 DOI:10.1017/neu.2022.32
Michael Maes
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引用次数: 5

摘要

本研究的目的是描述如何使用精确的精神病学方法来(a)描述精神分裂症症状域之间的关联,包括阴性症状、精神病、敌意、兴奋、行为举止、形式思维障碍、精神运动迟缓(PHEMFP)、认知功能障碍和神经免疫毒性和神经氧化途径;(b)基于这些特征创建一个新的内表型类别。我们表明,所有症状域(阴性和PHEMFP)可用于得出一个单一的潜在特征,称为精神分裂症的总体严重程度(OSOS)。此外,神经认知测试结果可用于提取基于执行功能、注意力、语义和情景记忆以及延迟回忆分数的一般认知衰退(G-CoDe)指数。根据偏最小二乘分析,不良结局通路(AOPs)对OSOS的影响部分由G-CoDe严重程度的增加介导。AOPs包括神经毒性细胞因子和趋化因子,对蛋白质和脂质的氧化损伤,IgA对神经毒性色氨酸分解代谢物的反应,革兰氏阴性菌易位导致血管和细胞旁通路的破坏,以及由于抗氧化水平降低和先天免疫系统损伤而导致的保护不足。无监督机器学习确定了一种新的精神分裂症内表型类型,称为主要神经认知精神病(MNP),其特征是阴性症状增加,PHEMFP, G-CoDe和上述AOPs。基于这些途径和表型特征,MNP是一个不同于单纯精神病(SP)的独特的内表型类型。如果忽视MNP和SP的区别,就不可能从精神分裂症的研究中得出任何有效的结论。
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Major neurocognitive psychosis: a novel schizophrenia endophenotype class that is based on machine learning and resembles Kraepelin's and Bleuler's conceptions.

The purpose of this study is to describe how to use the precision nomothetic psychiatry approach to (a) delineate the associations between schizophrenia symptom domains, including negative symptoms, psychosis, hostility, excitation, mannerism, formal thought disorders, psychomotor retardation (PHEMFP), and cognitive dysfunctions and neuroimmunotoxic and neuro-oxidative pathways and (b) create a new endophenotype class based on these features. We show that all symptom domains (negative and PHEMFP) may be used to derive a single latent trait called overall severity of schizophrenia (OSOS). In addition, neurocognitive test results may be used to extract a general cognitive decline (G-CoDe) index, based on executive function, attention, semantic and episodic memory, and delayed recall scores. According to partial least squares analysis, the impacts of adverse outcome pathways (AOPs) on OSOS are partially mediated by increasing G-CoDe severity. The AOPs include neurotoxic cytokines and chemokines, oxidative damage to proteins and lipids, IgA responses to neurotoxic tryptophan catabolites, breakdown of the vascular and paracellular pathways with translocation of Gram-negative bacteria, and insufficient protection through lowered antioxidant levels and impairments in the innate immune system. Unsupervised machine learning identified a new schizophrenia endophenotype class, named major neurocognitive psychosis (MNP), which is characterised by increased negative symptoms and PHEMFP, G-CoDe and the above-mentioned AOPs. Based on these pathways and phenome features, MNP is a distinct endophenotype class which is qualitatively different from simple psychosis (SP). It is impossible to draw any valid conclusions from research on schizophrenia that ignores the MNP and SP distinctions.

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来源期刊
Acta Neuropsychiatrica
Acta Neuropsychiatrica 医学-精神病学
CiteScore
8.50
自引率
5.30%
发文量
30
审稿时长
6-12 weeks
期刊介绍: Acta Neuropsychiatrica is an international journal focussing on translational neuropsychiatry. It publishes high-quality original research papers and reviews. The Journal''s scope specifically highlights the pathway from discovery to clinical applications, healthcare and global health that can be viewed broadly as the spectrum of work that marks the pathway from discovery to global health.
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