Neuroticism heterogeneity through item-level associations in resting-state functional connectivity.

Area of Science:

• Neuroscience
• Psychology
• Genetics

Background:

• Neuroticism is traditionally viewed as a single trait but is increasingly recognized as heterogeneous.
• This heterogeneity is evident in genetic underpinnings and impacts on health and social outcomes.

Purpose of the Study:

• To investigate the neurofunctional heterogeneity of neuroticism using resting-state functional connectivity (RSFC).
• To identify specific RSFC patterns linked to individual neuroticism facets.
• To establish RSFC as a potential intermediate phenotype for neuroticism.

Main Methods:

• Analyzed RSFC in a large UK Biobank dataset (n=33,180) using machine learning regression.
• Correlated RSFC patterns with item-level neuroticism scores from the Eysenck Personality Questionnaire.
• Validated findings in a separate UK Biobank MRI scan session.

Main Results:

• Identified specific RSFC patterns associated with neuroticism facets, correlating with genetic clusters (Worry, Depressed Affect) and psychometric factors (Anxiety/Tension, Worry/Vulnerability).
• Replicated these neurofunctional signatures in an independent dataset.
• Observed associated connectivity primarily within cognitive control, sensory integration, and self-referential processing networks.

Conclusions:

• Resting-state functional connectivity (RSFC) patterns reflect the heterogeneity of neuroticism.
• RSFC serves as a robust intermediate phenotype linking genetic predisposition to psychological states.
• This framework may improve prediction of psychiatric vulnerability and guide personalized interventions.