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

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.