Authors
Shirui Peng, Zixuan Li, Tao Huang, Hailun Liang
Published in
Frontiers in psychology. Volume 17. Pages 1876764. Epub Oct 07, 2026.
Abstract
Evidence linking Big Five personality traits to clinical biomarker-based PhenoAge acceleration remains limited, and the behavioral pathways underlying these associations are not well understood.
This study examined the associations between Big Five personality traits and PhenoAge acceleration (PhenoAA), tested health-related coping behavior as a statistical mediator, and explored differences across genetic risk strata.
We conducted a cross-sectional analysis of 119,250 European-ancestry participants from the UK Biobank. PhenoAA was derived from clinical biomarker-based PhenoAge after adjusting for chronological age. Multivariable linear regression, mediation analysis, inverse-probability-weighted sensitivity analysis, and exploratory analyses stratified by a genetic risk score (GRS) based on 29 single-nucleotide polymorphisms were performed.
Neuroticism was positively associated with PhenoAA (β = 0.038, p < 0.001). Extraversion (β = -0.301, p < 0.001), conscientiousness (β = -0.314, p < 0.001), and agreeableness (β = -0.037, p < 0.01) were inversely associated with PhenoAA, while openness was not significant (β = -0.023, p > 0.05). Coping behavior statistically mediated the associations for neuroticism, extraversion, conscientiousness, and agreeableness, accounting for 15.4, 19.5, 12.3, and 28.2% of the total associations, respectively. Weighted sensitivity analyses showed similar patterns. In GRS-stratified analyses, neuroticism, extraversion, and conscientiousness showed broadly consistent associations across low- and high-GRS groups. Agreeableness was inversely associated with PhenoAA only in the high-GRS group. Interaction tests did not provide evidence of genetic effect modification.
Big Five personality traits were associated with PhenoAA, and coping behavior partly accounted for several of these associations. These findings support a biopsychosocial view of biological aging, but they should be interpreted as associations rather than causal relationships.
PMID:
42909058
Bibliographic data and abstract were imported from PubMed on 23 Oct 2026.
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