Biological aging in major depressive disorder

Laura Kim Mae Han

    Research output: PhD ThesisPhD-Thesis - Research and graduation internal

    934 Downloads (Pure)


    The aim of this thesis was to investigate multisystem quantifications of the biological age in depression in order to better understand the complex interplay between mental health and biological aging. The most important finding to emerge from this thesis is that there is convergent support across multiple biological systems that depression is associated with an older appearing biological state of the brain and body, as measured by epigenetics, transcriptomics, proteomics, and brain-based biological clocks. This potentially offers an explanation as to why depressed persons have an increased risk of developing age-related diseases earlier in life than non-depressed peers. Several factors contribute to the observed biological aging, but specifically BMI was consistently associated with advanced aging across six biological levels and studies. Whilst this thesis did not establish accelerated biological aging in depression, it did partially substantiate that, at least at the epigenetic level, most considered correlates were unlikely to have causal accelerating effects on biological aging, because many of the wave-level changes in correlates were unaccompanied by a change in epigenetic aging. Although it remains to be elucidated if the different biological aging indicators considered in this thesis may represent potential targets for intervention, it strongly emphasizes, yet again, that depression has health consequences that go beyond psychological disturbances. A promising lead that requires follow-up investigation is the finding that antidepressant medication use may have protective effects on brain aging. Future longitudinal studies including multiple assessments are needed to further characterize the complex interplay between psychological, biological, and social factors and aging.
    Original languageEnglish
    Awarding Institution
    • Vrije Universiteit Amsterdam
    • Penninx, B.W.J.H., Supervisor
    • Aghajani, M., Co-supervisor, External person
    Award date4 Jun 2021
    Place of Publications.l.
    Print ISBNs9789493184916
    Electronic ISBNs9789493184916
    Publication statusPublished - 4 Jun 2021


    • Depression
    • Psychiatry
    • Biological aging
    • Anxiety
    • Omics
    • sMRI
    • Machine learning
    • Cellular aging
    • Brain age
    • Epigenetic age


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