A network of transcriptomic signatures identifies novel comorbidity mechanisms between schizophrenia and somatic disorders.

ABSTRACT: The clinical burden of mental illness, in particular schizophrenia and bipolar disorder, are driven by frequent chronic courses and increased mortality, as well as the risk for comorbid conditions such as cardiovascular disease and type 2 diabetes. Evidence suggests an overlap of molecular pathways between psychotic disorders and somatic comorbidities. In this study, we developed a computational framework to perform comorbidity modeling via an improved integrative unsupervised machine learning approach based on multi-rank non-negative matrix factorization (mrNMF). Using this procedure, we extracted molecular signatures potentially explaining shared comorbidity mechanisms. For this, 27 case-control microarray transcriptomic datasets across multiple tissues were collected, covering three mai

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC10994898 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature