AI Article Synopsis

  • The study aims to understand the molecular basis of major depression by integrating findings from proteomic research conducted on rodent models, focusing on key pathways involved in depressive behaviors.
  • Using network analysis and protein interaction databases, the researchers identified molecular processes linked to human depression, particularly those affected by antidepressants, immune responses, and energy metabolism.
  • The results suggest that animal models can be valuable in advancing our understanding of depression's biology and potential therapeutic approaches.

Article Abstract

Purpose: The pathophysiological basis of major depression is incompletely understood. Recently, numerous proteomic studies have been performed in rodent models of depression to investigate the molecular underpinnings of depressive-like behaviours with an unbiased approach. The objective of the study is to integrate the results of these proteomic studies in depression models to shed light on the most relevant molecular pathways involved in the disease.

Experimental Design: Network analysis is performed integrating preexisting proteomic data from rodent models of depression. The IntAct mouse and the HRPD are used as reference protein-protein interaction databases. The functionality analyses of the networks are then performed by testing overrepresented GO biological process terms and pathways.

Results: Functional enrichment analyses of the networks revealed an association with molecular processes related to depression in humans, such as those involved in the immune response. Pathways impacted by clinically effective antidepressants are modulated, including glutamatergic signaling and neurotrophic responses. Moreover, dysregulations of proteins regulating energy metabolism and circadian rhythms are implicated. The comparison with protein pathways modulated in depressive patients revealed significant overlapping.

Conclusions And Clinical Relevance: This systems biology study supports the notion that animal models can contribute to the research into the biology and therapeutics of depression.

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Source
http://dx.doi.org/10.1002/prca.201500149DOI Listing

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