The novel schizophrenia subgroup “major neurocognitive psychosis” is validated as a distinct class through the analysis of immune-linked neurotoxicity biomarkers and neurocognitive deficits

IF 3.7 Q2 IMMUNOLOGY
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Abstract

Background

Using machine learning methods based on neurocognitive deficits and neuroimmune biomarkers, two distinct classes were discovered within schizophrenia patient samples. Increased frequency of psychomotor retardation, formal thought disorders, mannerisms, psychosis, hostility, excitation, and negative symptoms defined the first subgroup, major neurocognitive psychosis (MNP). Cognitive deficits in executive functions and memory and diverse neuroimmune aberrations were other MNP features. Simple neurocognitive psychosis (SNP) was the less severe phenotype.

Aims

The study comprised a sample of 40 healthy controls and 90 individuals diagnosed with schizophrenia, divided into MNP and SNP based on previously determined criteria. Soft Independent Modelling of Class Analogy (SIMCA) was performed using neurocognitive test results and measurements of serum M1 macrophage and T helper-17 cytokines as discriminatory/modelling variables. The model-to-model distances between controls and MNP + SNP and between MNP and SNP were computed, and the top discriminatory variables were established.

Results

A notable SIMCA distance of 146.1682 was observed between MNP + SNP and the control group. The top-3 discriminatory variables were lowered motor speed, an activated T helper-17 axis, and lowered working memory. This study successfully differentiated MNP from SNP yielding a SIMCA distance of 19.3. M1 macrophage activation, lowered verbal fluency, and executive functions were the prominent features of MNP versus SNP.

Discussion

Based on neurocognitive assessments and the immune-linked neurotoxic M1 and T helper-17 profiles, we found that MNP and SNP are qualitatively distinct classes. Future biomarker research should focus on examining biomarkers specifically in the MNP and SNP subgroups, rather than in the schizophrenia group.

通过分析与免疫相关的神经毒性生物标记物和神经认知缺陷,验证新型精神分裂症亚群 "主要神经认知性精神病 "是一个独特的类别
背景利用基于神经认知缺陷和神经免疫生物标志物的机器学习方法,在精神分裂症患者样本中发现了两个不同的类别。精神运动迟滞、形式化思维障碍、举止失常、精神病、敌意、兴奋和阴性症状的增加定义了第一个亚组,即重性神经认知精神病(MNP)。执行功能和记忆方面的认知缺陷以及多种神经免疫畸变是重性神经认知性精神病的其他特征。该研究的样本包括 40 名健康对照者和 90 名被诊断为精神分裂症的患者,根据之前确定的标准分为 MNP 和 SNP 两组。以神经认知测试结果和血清M1巨噬细胞和T辅助-17细胞因子的测量结果作为判别/建模变量,进行了类比软独立建模(SIMCA)。计算了对照组与 MNP + SNP 之间以及 MNP 与 SNP 之间的模型到模型距离,并确定了最高判别变量。前 3 个判别变量分别是运动速度降低、T 辅助-17 轴激活和工作记忆降低。这项研究成功地将 MNP 与 SNP 区分开来,SIMCA 距离为 19.3。讨论基于神经认知评估以及与免疫相关的神经毒性 M1 和 T 辅助细胞-17 的特征,我们发现 MNP 和 SNP 在本质上是不同的类别。未来的生物标志物研究应侧重于研究 MNP 和 SNP 亚组而非精神分裂症组的生物标志物。
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来源期刊
Brain, behavior, & immunity - health
Brain, behavior, & immunity - health Biological Psychiatry, Behavioral Neuroscience
CiteScore
8.50
自引率
0.00%
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审稿时长
97 days
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