Depressive symptoms differ in severity and stability over time. Trajectories depicting these changes, particularly those with high late-life depressive symptoms, have been associated with poor brain health at old age. To better understand these associations across the lifespan, we examined depressive symptoms trajectories in relation to brain health in middle age. We included 1676 participants from the ORACLE Study, all were expecting a child at baseline (mean age 32.8, 66.6% women). Depressive symptoms were assessed at baseline, 3 years and 10 years after baseline. Brain health (global brain volume, subcortical structures volume, white matter lesions, cerebral microbleeds, cortical thickness, cortical surface area) was assessed 15 years after baseline. Using k-means clustering, four depressive symptoms trajectories were identified: low, low increasing, decreasing, and high increasing symptoms. The high increasing trajectory was associated with smaller brain volume compared to low symptoms, not surviving multiple testing correction. The low increasing trajectory was associated with more cortical thickness in a small region encompassing the right lateral occipital cortex compared to low symptoms. These findings show that longitudinal depressive symptoms trajectories are only minimally associated with brain health in middle age, suggesting that associations may only emerge later in life.
Bibliographical noteFunding Information:
The general design of the Generation R Study is funded by the Erasmus Medical Center, Rotterdam, ZonMw, the Netherlands Organization for Scientific Research (NWO), and the Ministry of Health, Welfare and Sport, and is conducted by the Erasmus Medical Center in close collaboration with the Faculty of Social Sciences of the Erasmus University Rotterdam, and the Stichting Trombosedienst & Artsenlaboratorium Rijnmond (STAR-MDC), Rotterdam. This project received funding from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Programme (project: ORACLE, grant agreement No: 678543). The work of CC has received funding from the European Union's Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant (grant agreement No: 707404; project: EarlyCause, grant agreement No: 848158). The financial supporters did not influence the results of this article. The funders had no role in the study design, data collection, analysis, interpretation of the data, or writing of the report.
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