Unique genetic and risk-factor profiles in clusters of major depressive disorder-related multimorbidity trajectories.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
21 Aug 2024
21 Aug 2024
Historique:
received:
07
08
2023
accepted:
07
08
2024
medline:
22
8
2024
pubmed:
22
8
2024
entrez:
21
8
2024
Statut:
epublish
Résumé
The heterogeneity and complexity of symptom presentation, comorbidities and genetic factors pose challenges to the identification of biological mechanisms underlying complex diseases. Current approaches used to identify biological subtypes of major depressive disorder (MDD) mainly focus on clinical characteristics that cannot be linked to specific biological models. Here, we examined multimorbidities to identify MDD subtypes with distinct genetic and non-genetic factors. We leveraged dynamic Bayesian network approaches to determine a minimal set of multimorbidities relevant to MDD and identified seven clusters of disease-burden trajectories throughout the lifespan among 1.2 million participants from cohorts in the UK, Finland, and Spain. The clusters had clear protective- and risk-factor profiles as well as age-specific clinical courses mainly driven by inflammatory processes, and a comprehensive map of heritability and genetic correlations among these clusters was revealed. Our results can guide the development of personalized treatments for MDD based on the unique genetic, clinical and non-genetic risk-factor profiles of patients.
Identifiants
pubmed: 39168988
doi: 10.1038/s41467-024-51467-7
pii: 10.1038/s41467-024-51467-7
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
7190Informations de copyright
© 2024. The Author(s).
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