Disease Severity Across Psychiatric Disorders Is Linked to Pro-Inflammatory Cytokines

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This longitudinal study used deep phenotyping from 443 participants with severe mental disorders (schizophrenia, bipolar disorder, and major depressive disorder) to identify transdiagnostic clusters based on symptom trajectories and cognitive performance, independent of traditional diagnoses. Two distinct clusters differed significantly in illness severity without differences in age, sex, or diagnostic proportions; comparative cross-sectional analyses implicated 19 serum proteins that were significantly dysregulated between clusters, with functional enrichment indicating convergence of immune system dysregulation and neurodevelopmental processes, including inflammation-related pathways. A key caveat is that the authors report discovering and correcting an error in their proteomic analysis and modifying the differential-analysis workflow (using limma) to identify the dysregulated proteins. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Importance Numerous studies indicate that the traditional categorical classification of severe mental disorders (SMD), such as schizophrenia, bipolar disorders, and major depressive disorders, does not align with the underlying biology of those disorders as they frequently overlap in terms of symptoms and risk factors. Objective This study aimed to identify transdiagnostic patient clusters based on disease severity and explore the underlying biological mechanisms independently of the traditional categorical classification. Design We utilized data from 443 participants diagnosed with SMD of the PsyCourse Study, a longitudinal study with deep phenotyping across up to four visits. We performed longitudinal clustering to group patients based on symptom trajectories and cognitive performance. The resulting clusters were compared on cross-sectional variables, including independent measures of severity as well as polygenic risk scores, serum protein quantification, miRNA expression, and DNA methylation. Results We identified two distinct clusters of patients that exhibited marked differences in illness severity but did not differ significantly in age, sex, or diagnostic proportions. We found 19 serum proteins significantly dysregulated between the two clusters. Functional enrichment pointed to a convergence of immune system dysregulation and neurodevelopmental processes. Conclusion The observed differences in serum protein expression suggest that disease severity is associated with the convergence of immune system dysregulation and neurodevelopmental alterations, particularly involving pathways related to inflammation and brain plasticity. The identification of pro-inflammatory proteins among the differentially expressed markers underscores the potential role of systemic inflammation in the pathophysiology of SMD. These results highlight the importance of considering illness severity as a core dimension in psychiatric research and clinical practice and suggest that targeting immune-related mechanisms may offer promising new therapeutic avenues for patients with SMD. Key points Question Can analyzing symptom trajectories and cognitive profiles across diagnostic categories reveal clinically relevant subgroups in severe mental disorders? Findings In this longitudinal study of 443 individuals with severe mental disorders, two distinct clusters emerged, differing significantly in illness severity, with the more severe group displaying elevated pro-inflammatory serum proteins, suggesting an association between disease severity and inflammation. Meaning These findings suggest that transdiagnostic clustering clarifies shared mechanisms, underscores the importance of inflammation in severe mental disorders, and highlights a promising avenue for novel therapeutic approaches.
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Abstract

Importance Numerous studies indicate that the traditional categorical classification of severe mental disorders (SMD), such as schizophrenia, bipolar disorders, and major depressive disorders, does not align with the underlying biology of those disorders as they frequently overlap in terms of symptoms and risk factors.

Objective

This study aimed to identify transdiagnostic patient clusters based on disease severity and explore the underlying biological mechanisms independently of the traditional categorical classification. Design We utilized data from 443 participants diagnosed with SMD of the PsyCourse Study, a longitudinal study with deep phenotyping across up to four visits. We performed longitudinal clustering to group patients based on symptom trajectories and cognitive performance. The resulting clusters were compared on cross-sectional variables, including independent measures of severity as well as polygenic risk scores, serum protein quantification, miRNA expression, and DNA methylation.

Results

We identified two distinct clusters of patients that exhibited marked differences in illness severity but did not differ significantly in age, sex, or diagnostic proportions. We found 19 serum proteins significantly dysregulated between the two clusters. Functional enrichment pointed to a convergence of immune system dysregulation and neurodevelopmental processes.

Conclusion

The observed differences in serum protein expression suggest that disease severity is associated with the convergence of immune system dysregulation and neurodevelopmental alterations, particularly involving pathways related to inflammation and brain plasticity. The identification of pro-inflammatory proteins among the differentially expressed markers underscores the potential role of systemic inflammation in the pathophysiology of SMD. These results highlight the importance of considering illness severity as a core dimension in psychiatric research and clinical practice and suggest that targeting immune-related mechanisms may offer promising new therapeutic avenues for patients with SMD. Question Can analyzing symptom trajectories and cognitive profiles across diagnostic categories reveal clinically relevant subgroups in severe mental disorders? Findings In this longitudinal study of 443 individuals with severe mental disorders, two distinct clusters emerged, differing significantly in illness severity, with the more severe group displaying elevated pro-inflammatory serum proteins, suggesting an association between disease severity and inflammation. Meaning These findings suggest that transdiagnostic clustering clarifies shared mechanisms, underscores the importance of inflammation in severe mental disorders, and highlights a promising avenue for novel therapeutic approaches. Competing Interest Statement Volker Arolt has been working as a counselor for Sanofi-Aventis Germany and Springer-Nature Verlag, Germany. Ion-George Anghelescu has served as a counselor, advisor or CME speaker for the following entities: Aristo Pharma, Janssen Pharmaceutica, Merck, Dr. Willmar Schwabe, Recordati Pharma. Jens Wiltfang acted as a consultant for Immungenetics, Noselab, Roboscreen, served on a scientific advisory board for Abbott, Biogen, Boehringer Ingelheim, Lilly, Immungenetics, MSD Sharp-Dohme, Noselab, Roboscreen, Roche, and received honoraria for presentations by Beeijing Yibai Science and Technology Ltd, Eisai, Gloryren, Janssen, Pfizer, Med Update GmbH, Roche, Lilly. Carsten Konrad has been working as advisor for Janssen Pharmaceuticals and received speakers honorary from Janssen, Lundbeck, Neuraxpharm, and Servier. Peter Falkai is currently president of the WFSBP. Peter Falkai has been EPA president in 2022 and is a co-editor of the German (DGPPN) schizophrenia treatment guidelines and a co-author of the WFSBP schizophrenia treatment guidelines. Peter Falkai received speaking fees from Boehringer-Ingelheim, Janssen, Otsuka, Lundbeck, Recordati, and Richter and was a member of the advisory boards of these companies and Rovi. Jorg Zimmermann served as an advisor for Biogen concerning Aducanumab (Alzheimer s Disease). All other authors report no biomedical financial interests or potential conflicts of interest. Footnotes ↵# These authors directed the study We discovered an error in our proteomic analysis. We corrected it and modified our workflow to use limma in our differential analysis which allowed us to identify 19 proteins dysregulated between our two severity clusters. The functionnal enrichment of those proteins pointed to a convergence of immune system dysregulation and neurodevelopmental process.

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