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. 2023 Apr 20;14(1):2277.
doi: 10.1038/s41467-023-38013-7.

Accelerated biological aging and risk of depression and anxiety: evidence from 424,299 UK Biobank participants

Affiliations

Accelerated biological aging and risk of depression and anxiety: evidence from 424,299 UK Biobank participants

Xu Gao et al. Nat Commun. .

Erratum in

Abstract

Theory predicts that biological processes of aging may contribute to poor mental health in late life. To test this hypothesis, we evaluated prospective associations between biological age and incident depression and anxiety in 424,299 UK Biobank participants. We measured biological age from clinical traits using the KDM-BA and PhenoAge algorithms. At baseline, participants who were biologically older more often experienced depression/anxiety. During a median of 8.7 years of follow-up, participants with older biological age were at increased risk of incident depression/anxiety (5.9% increase per standard deviation [SD] of KDM-BA acceleration, 95% confidence intervals [CI]: 3.3%-8.5%; 11.3% increase per SD of PhenoAge acceleration, 95% CI: 9.%-13.0%). Biological-aging-associated risk of depression/anxiety was independent of and additive to genetic risk measured by genome-wide-association-study-based polygenic scores. Advanced biological aging may represent a potential risk factor for incident depression/anxiety in midlife and older adults and a potential target for risk assessment and intervention.

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Conflict of interest statement

The authors declare not competing interests.

Figures

Fig. 1
Fig. 1. Graphs of the best fitting models for relationships of KDM-BA acceleration and PhenoAge acceleration with PHQ-4 score at baseline.
Panels: KDM-BA acceleration (a) and PhenoAge acceleration (b). Solid line: Point estimation; Dash line: Confidence limits; Dots: Knots (5th, 50th, and 95th percentiles). Restricted cubic spline regression model adjusted for age, sex, BMI category, race, smoking status (current/former/never), healthy alcohol intake status, healthy physical activity status, Townsend deprivation index, and prevalent hypertension, CHD, and diabetes. Source data are provided as a Source Data file.
Fig. 2
Fig. 2. Graphs of the best fitting models for relationships of KDM-BA acceleration and PhenoAge acceleration with incident depression/anxiety disorders at follow-up.
Panels: KDM-BA acceleration (ac) and PhenoAge acceleration (df). Solid line: Point estimation; Black dash line: Confidence limits; Green dash line: Reference line; Dots: Knots (5th, 50th, and 95th percentiles). Restricted cubic spline regression model adjusted for age, sex, BMI category, race, smoking status (current/former/never), healthy alcohol intake status, healthy physical activity status, Townsend deprivation index, and prevalent hypertension, CHD, and diabetes. Source data are provided as a Source Data file.
Fig. 3
Fig. 3. Prospective associations of baseline biological age accelerations with odds of depression/anxiety symptoms and mental health scores at follow-up survey for the 124,976 participants that were free of depression and anxiety at baseline with available online mental health survey data.
Dots (centers of error bars): Point estimate; Error bar: 95% confidence limits; Dash line: Reference line; Upper part is the odds ratios of logistic regression, lower part is the coefficients of linear regression; Dots and error bars colored in blue (for odds ratios) or purple (for coefficients) are statistically significant (unadjusted p-values < 0.05), otherwise are colored in grey. The logistic regression model was used in analyses for the odds of depression/anxiety symptoms and the linear regression model was used for the mental health scores. Model adjusted for age, sex, BMI category, race, smoking status (current/former/never), healthy alcohol intake status, healthy physical activity status, Townsend deprivation index, and prevalent hypertension, CHD, and diabetes. The examination center was additionally controlled for a random effect. Two-sided statistical tests were conducted and no adjustments were made for multiple comparisons. Source data are provided as a Source Data file.
Fig. 4
Fig. 4. Joint associations of genetic risk and biological age accelerations with the odds of depression/anxiety disorders at baseline and incident depression/anxiety disorders at follow-up.
Dots (centers of error bars): Point estimate; Error bar: 95% confidence limits; Dash line: Reference line; Logistic regression model was used in analyses for the odds of depression/anxiety at baseline and Cox regression model was used for the risk of incident depression/anxiety during the follow-up. Model adjusted for age, sex, BMI category, race, smoking status (current/former/never), healthy alcohol intake status, healthy physical activity status, Townsend deprivation index, and prevalent hypertension, CHD, and diabetes. The examination center was additionally controlled for as a random effect. Two-sided statistical tests were conducted and no adjustments were made for multiple comparisons. Source data are provided as a Source Data file.

References

    1. World Health Organization. Depression and other common mental disorders: global health estimates. (World Health Organization, 2017).
    1. Moffitt TE, Caspi A. Psychiatry’s opportunity to prevent the rising burden of age-related disease. JAMA Psychiatry. 2019;76:461–462. - PMC - PubMed
    1. Jeste DV, et al. Association between older age and more successful aging: critical role of resilience and depression. Am. J. Psychiatry. 2013;170:188–196. - PMC - PubMed
    1. Han LKM, et al. Contributing factors to advanced brain aging in depression and anxiety disorders. Transl. Psychiatry. 2021;11:402. - PMC - PubMed
    1. Ridout KK, Ridout SJ, Price LH, Sen S, Tyrka AR. Depression and telomere length: a meta-analysis. J. Affect Disord. 2016;191:237–247. - PMC - PubMed

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