Albert T Higgins-Chen1, Marco P Boks2, Christiaan H Vinkers3, René S Kahn4, Morgan E Levine5. 1. Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut. Electronic address: a.higginschen@yale.edu. 2. Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, The Netherlands. 3. Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands; Department of Anatomy and Neurosciences, Amsterdam University Medical Center, Amsterdam, The Netherlands. 4. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, The Netherlands. 5. Department of Pathology, Yale University School of Medicine, New Haven, Connecticut.
Abstract
BACKGROUND: Schizophrenia (SZ) is associated with increased all-cause mortality, smoking, and age-associated proteins, yet multiple previous studies found no association between SZ and biological age using Horvath's epigenetic clock, a well-established aging biomarker based on DNA methylation. However, numerous epigenetic clocks that may capture distinct aspects of aging have been developed. This study tested the hypothesis that altered aging in SZ manifests in these other clocks. METHODS: We performed a comprehensive analysis of 14 epigenetic clocks categorized according to what they were trained to predict: chronological age, mortality, mitotic divisions, or telomere length. To understand the etiology of biological age differences, we also examined DNA methylation predictors of smoking, alcohol, body mass index, serum proteins, and cell proportions. We independently analyzed 3 publicly available multiethnic DNA methylation data sets from whole blood, a total of 567 SZ cases and 594 nonpsychiatric controls. RESULTS: All data sets showed accelerations in SZ for the 3 mortality clocks up to 5 years, driven by smoking and elevated levels of 6 age-associated proteins. The 2 mitotic clocks were decelerated in SZ related to antitumor natural killer and CD8T cells, which may help explain conflicting reports about low cancer rates in epidemiological studies of SZ. One cohort with available medication data showed that clozapine is associated with male-specific decelerations up to 7 years in multiple chronological age clocks. CONCLUSIONS: Our study demonstrates the utility of studying the various epigenetic clocks in tandem and highlights potential mechanisms by which mental illness influences long-term outcomes, including cancer and early mortality.
BACKGROUND:Schizophrenia (SZ) is associated with increased all-cause mortality, smoking, and age-associated proteins, yet multiple previous studies found no association between SZ and biological age using Horvath's epigenetic clock, a well-established aging biomarker based on DNA methylation. However, numerous epigenetic clocks that may capture distinct aspects of aging have been developed. This study tested the hypothesis that altered aging in SZ manifests in these other clocks. METHODS: We performed a comprehensive analysis of 14 epigenetic clocks categorized according to what they were trained to predict: chronological age, mortality, mitotic divisions, or telomere length. To understand the etiology of biological age differences, we also examined DNA methylation predictors of smoking, alcohol, body mass index, serum proteins, and cell proportions. We independently analyzed 3 publicly available multiethnic DNA methylation data sets from whole blood, a total of 567 SZ cases and 594 nonpsychiatric controls. RESULTS: All data sets showed accelerations in SZ for the 3 mortality clocks up to 5 years, driven by smoking and elevated levels of 6 age-associated proteins. The 2 mitotic clocks were decelerated in SZ related to antitumor natural killer and CD8T cells, which may help explain conflicting reports about low cancer rates in epidemiological studies of SZ. One cohort with available medication data showed that clozapine is associated with male-specific decelerations up to 7 years in multiple chronological age clocks. CONCLUSIONS: Our study demonstrates the utility of studying the various epigenetic clocks in tandem and highlights potential mechanisms by which mental illness influences long-term outcomes, including cancer and early mortality.
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