Insula activity in resting-state differentiates bipolar from unipolar depression: a systematic review and meta-analysis.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
20 08 2021
20 08 2021
Historique:
received:
02
06
2020
accepted:
26
07
2021
entrez:
21
8
2021
pubmed:
22
8
2021
medline:
10
11
2021
Statut:
epublish
Résumé
Symptomatic overlap of depressive episodes in bipolar disorder (BD) and major depressive disorder (MDD) is a major diagnostic and therapeutic problem. Mania in medical history remains the only reliable distinguishing marker which is problematic given that episodes of depression compared to episodes of mania are more frequent and predominantly present at the beginning of BD. Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive, task-free, and well-tolerated method that may provide diagnostic markers acquired from spontaneous neural activity. Previous rs-fMRI studies focused on differentiating BD from MDD depression were inconsistent in their findings due to low sample power, heterogeneity of compared samples, and diversity of analytical methods. This meta-analysis investigated resting-state activity differences in BD and MDD depression using activation likelihood estimation. PubMed, Web of Science, Scopus and Google Scholar databases were searched for whole-brain rs-fMRI studies which compared MDD and BD currently depressed patients between Jan 2000 and August 2020. Ten studies were included, representing 234 BD and 296 MDD patients. The meta-analysis found increased activity in the left insula and adjacent area in MDD compared to BD. The finding suggests that the insula is involved in neural activity patterns during resting-state that can be potentially used as a biomarker differentiating both disorders.
Identifiants
pubmed: 34417487
doi: 10.1038/s41598-021-96319-2
pii: 10.1038/s41598-021-96319-2
pmc: PMC8379217
doi:
Types de publication
Journal Article
Meta-Analysis
Research Support, Non-U.S. Gov't
Systematic Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
16930Informations de copyright
© 2021. The Author(s).
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