The novel pathway phenotype major neurocognitive psychosis is validated as a distinct class through the analysis of immune-linked neurotoxicity biomarkers and neurocognitive deficits

Abstract Background Using machine learning methods based on neurocognitive deficits and neuroimmune biomarkers, two distinct classes were discovered within schizophrenia patient samples. The first, major neurocognitive psychosis (MNP) was characterized by cognitive deficits in executive functions and memory, higher prevalence of psychomotor retardation, formal thought disorders, mannerisms, psychosis, hostility, excitation, and negative symptoms, and diverse neuroimmune aberrations. 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 cytokines, IL-17, IL-21, IL-22, and IL-23 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 IL-6/IL-23/Th-17 axis, we found that MNP and SNP are qualitatively distinct classes. Future biomarker research should always examine biomarkers in the MNP versus SNP phenotypes, rather than in the combined MNP + SNP or schizophrenia group.