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  4. Integrative analysis to identify shared mechanisms between schizophrenia and bipolar disorder and their comorbidities
 
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2022
Journal Article
Title

Integrative analysis to identify shared mechanisms between schizophrenia and bipolar disorder and their comorbidities

Abstract
Schizophrenia and bipolar disorder are characterized by highly similar neuropsychological signatures, implying shared neurobiological mechanisms between these two disorders. These disorders also have comorbidities, such as type 2 diabetes mellitus (T2DM). To date, an understanding of the mechanisms that mediate the link between these two disorders remains incomplete. In this work, we identify and investigate shared patterns across multiple schizophrenia, bipolar disorder and T2DM gene expression datasets through multiple strategies. Firstly, we investigate dysregulation patterns at the gene-level and compare our findings against disease-specific knowledge graphs (KGs). Secondly, we analyze the concordance of co-expression patterns across datasets to identify diseasespecific as well as common pathways. Thirdly, we examine enriched pathways across datasets and disorders to identify common biological mechanisms between them. Lastly, we investigate the correspondence of shared genetic variants between these two disorders and T2DM as well as the disease-specific KGs. In conclusion, our work reveals several shared candidate genes and pathways, particularly those related to the immune system, such as TNF signaling pathway, IL-17 signaling pathway and NF-kappa B signaling pathway and nervous system, such as dopaminergic synapse and GABAergic synapse, which we propose mediate the link between schizophrenia and bipolar disorder and its shared comorbidity, T2DM.
Author(s)
Bharadhwaj, Vinay Srinivas  
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Mubeen, Sarah  
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Sargsyan, Astghik  
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Jose, Geena Mariya
Geissler, Stefan
Kairntech
Hofmann-Apitius, Martin  
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Domingo Fernández, Daniel  
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Tom Kodamullil, Alpha
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Journal
Progress in neuro-psychopharmacology & biological psychiatry  
Project(s)
Modeling of comorbidity processes through integrative machine transfer learning for psychiatric disorders  
Funder
Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie -BMBF-, Referat Öffentlichkeitsarbeit  
Open Access
File(s)
Download (1.55 MB)
Rights
CC BY-NC-ND 4.0: Creative Commons Attribution-NonCommercial-NoDerivatives
DOI
10.1016/j.pnpbp.2022.110688
10.24406/publica-600
Language
English
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Keyword(s)
  • Transcriptomic

  • Psychiatric disorders

  • Schizophrenia

  • Bipolar disorder

  • Gene expression

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