Comprehensive analysis of interactions between brain aging and late-onset psychoses using heuristic mapping models.

Area of Science:

• Gerontology
• Neuroscience
• Psychiatry

Background:

• Advanced brain aging is linked to late-onset psychoses such as bipolar disorder (BD), schizophrenia (SP), and major depressive disorder (MDD).
• Imbalances in neuroimmune homeostasis are implicated in the progression of these psychiatric conditions.
• The interplay between brain aging and these psychoses requires further elucidation.

Purpose of the Study:

• To systematically explore the key interrelationships between brain aging and late-onset psychoses.
• To identify shared and specific pathogenetic features of BD, SP, and MDD in the context of aging.
• To develop a computational framework for understanding and potentially treating aging-related psychiatric disorders.

Main Methods:

• Machine learning was employed to identify aging and disease-related features and to devise an aging score.
• Mapping models were optimized to explore relationships between aging and disease.
• Bioinformatics approaches, including sensitivity, enrichment, and network analyses, were used to investigate crucial links.

Main Results:

• Identified shared and specific features of psychoses within the context of brain aging.
• Highlighted the role of neuroimmune homeostasis, cellular and vascular homeostasis, and the heart-brain axis.
• Revealed potential pathogenic features for individual conditions, supporting neuro-immunosenescence and vascular-lymphatic aging theories.

Conclusions:

• The study integrates various risk factors by exploring an aging index across different late-onset psychoses.
• It proposes an approach applicable to other aging-related diseases.
• A computational framework is provided for therapeutic interventions targeting the interplay between aging and psychosis.