In Schizophrenia, Chronic Fatigue Syndrome- and Fibromyalgia-Like Symptoms are Driven by Breakdown of the Paracellular Pathway with Increased Zonulin and Immune Activation-Associated Neurotoxicity

Abstract

Background: A meaningful part of schizophrenia patients suffer from physiosomatic symptoms (formerly named psychosomatic) which are reminiscent of chronic fatigue syndrome and fibromyalgia (FF) and are associated with signs of immune activation and increased levels of tryptophan catabolites (TRYCATs). Aims: To examine whether FF symptoms in schizophrenia are associated with breakdown of the paracellular pathway, zonulin, lowered natural IgM responses to oxidative specific epitopes (OSEs); and whether FF symptoms belong to the behavioral-cognitive-physical-psychosocial-(BCPS)-worsening index consisting of indices of a general cognitive decline (G-CoDe), symptomatome of schizophrenia, and quality of life (QoL)-phenomenome. Methods: FF symptoms were assessed using the Fibromyalgia and Chronic Fatigue Rating scale in 80 schizophrenia patients and 40 healthy controls and serum cytokines/chemokines, IgA levels to TRYCATs, IgM to OSEs, zonulin and transcellular/paracellular (TRANS/PARA) molecules were assayed using ELISA methods. Results: A large part (42.3%) of the variance in the total FF score was explained by the regression on the PARA/TRANS ratio, pro-inflammatory cytokines, IgM to zonulin, IgA to TRYCATs (all positively) and IgM to OSEs (inversely). There were highly significant correlations between the total FF score and G-CoDe, symtopmatome, QoL phenomenome and BCPS-worsening score. FF symptoms belong to a common core shared by G-CoDe, symtopmatome, and QoL phenomenome. Discussion: The physio-somatic symptoms of schizophrenia are driven by various pathways including increased zonulin, breakdown of the paracellular tight-junctions pathway, immune activation with induction of the TRYCAT pathway, and consequent neurotoxicity. It is concluded that FF symptoms are part of the phenome of schizophrenia and BCPS-worsening as well.

Lowered oxygen saturation and increased body temperature in acute COVID-19 largely predict chronic fatigue syndrome and affective symptoms due to LONG COVID: a precision nomothetic approach

“…This indicates that shared pathways may underpin the physio-affective phenome of the acute as well as chronic phases of the illness. Previously, we observed intertwined associations between increased levels of affective and physiosomatic symptoms not only in acute COVID-19 but also in, for example, schizophrenia, rheumatoid arthritis, and major depression (Kanchanatawan, Sriswasdi et al 2019, Almulla, Al-Hakeim et al 2020, Maes, Andrés-Rodríguez et al 2021, Smesam, Qazmooz et al 2022). Since our previous study (Al-Jassas, Al-Hakeim et al 2022) and the current study were performed using different study samples, we were unable to examine whether patients with acute physio-affective symptoms present the same symptoms in Long COVID.…”

Precision Nomothetic Medicine in Depression Research: A New Depression Model, and New Endophenotype Classes and Pathway Phenotypes, and A Digital Self

“…Support vector machine (SVM), linear discriminant analysis (LDA), neural networks, independent modelling of class analogy (SIMCA), logistic and multivariate regression, and partial least squares (PLS) path modelling are some of the supervised machine learning approaches that can be employed to achieve this goal, and they all significantly enhance prediction accuracy either from prespecified classes (SVM, LDA, neural networks, SIMCA, and logistic regression) or quantitative scores (multivariate regression) [ 18 , 19 , 20 ]. A combination of these methods is recommended because some are better suited for classification (e.g., SVM and neural networks), the prediction of quantitative outcome data with (pathway analysis) and without (multiple regression analysis) mediated effects, and learning from the data (SIMCA, neural networks, multivariate or logistic regression analysis), while other methods (e.g., SIMCA) are better suited for authenticating cases as healthy volunteers or as patients [ 14 , 21 ].…”

“…Principal component analysis (PCA) and factor analysis are adequate tools to detect pathway phenotypes. The prerequisite is that strongly interrelated features belong to the same reflective latent vector, which in fact is the cause of all its manifestations [ 18 , 19 , 20 ]. For example, the abstract construct “HR-QoL” may be conceptualized as a reflective latent vector (factor) extracted from self-rated quality of life domain scores, such that the latent vector HR-QoL is the cause of all its manifestations [ 28 ].…”

“…Before I describe how we utilized SIMCA, PCA, PLS-path and clustering analysis to create digital models and digital selves for patients and controls [ 14 , 15 , 16 , 17 , 19 , 20 , 21 , 26 , 30 ], I will first provide some context for those approaches (see Section 4 ). While these approaches are the cornerstone of our precision psychiatry approach, we always combined them with additional machine learning techniques such as SVM, neural networks, PCA plot, correspondence factor analysis, and regression analysis, as previously mentioned [ 14 , 15 , 16 , 17 , 18 ].…”

Increased lipid peroxidation and lowered antioxidant defenses predict methamphetamine induced psychosis

“…In analogy with our studies in schizophrenia (Al-Dujaili, Mousa et al 2021, Almulla, Al-Hakeim et al 2021, Maes, Vojdani et al 2021…”