Longitudinal relationships between depression and cardiovascular disease risk in two major population cohorts

Background: Depression is one of the most common mental illnesses worldwide. People who have been diagnosed with depression have a reduced life expectancy of 10-15 years, which can partly be explained by an increased risk of cardiovascular disease [1]. It is not yet clear exactly why depression is associated with cardiovascular disease risk. The associations could be due to causal mechanisms, in which case important mediating factors need to be considered, including lifestyle, psychotropic medication use, and social influences [2]. Additionally, while there is evidence that both depression and cardiovascular disease presents differently across biological sexes and different ethnic groups, there is currently a stark lack of studies in non-white European populations. Objective: The aim of this multi-ethnic study is to assess evidence for potentially causal effects between depression and cardiovascular disease risk across two major cohorts: The Lifelines cohort (N=167,770, predominately white European ancestry, three time-points available) [3] and the HELIUS cohort (N=4671 Dutch, 3369 South-Asian Surinamese, 4458 African Surinamese, 2735 Ghanaian, 4200 Turkish, 4502 Moroccan, two time-points available) [4]. Additionally, we intend to study whether lifestyle (e.g. physical activity, BMI, smoking, diabetes), social factors (e.g. loneliness, perceived social support), and psychotropic medication use mediate these effects. Lastly, we aim to analyse whether the aforementioned relationships differ across biological sexes and ethnic groups. Methods: In order to study the bidirectional longitudinal relationships between depression and cardiovascular disease risk, we will use random-intercept cross-lagged panel models [5]. The random intercepts capture time-invariant individual level differences in the data, which allows one to capture unmodelled mediators and to separate individual deviations of the group mean from potentially causal longitudinal relationships between observed variables. In the model, depression as well as cardiovascular disease can be considered as both an exposure and outcome. By conducting ‘nested’ models, in which some of the paths are omitted, it can be tested whether it is more likely that depression precedes changes in cardiovascular disease risk, or the reverse. The main variables of interest are depression (measured as depressive symptoms) and cardiovascular disease risk (measured as mean blood pressure, metabolic syndrome, ECG variables). One can also include mediators in the model; we will include sex, ethnicity, lifestyle factors (compound or physical activity, smoking, diabetes and BMI separately), social mediators (compound or loneliness, perceived social support and perceived discrimination separately), and psychotropic medication use. Hypotheses: We expect to find that depression and cardiovascular disease are longitudinally associated in both directions, but that there is stronger evidence that depression increases subsequent cardiovascular disease risk. Additionally, we hypothesize that these associations are mediated by factors such as smoking, physical activity, medication use, and loneliness. However, we cannot be sure yet about the relative strengths of the mentioned factors. Lastly, we expect to find differences in the strengths of the associations between men and women and across different ethnic backgrounds. Conclusion: Data analysis is currently still ongoing, results will be presented at the ECNP workshop in March 2024. References [1] Correll, C.U., Solmi, M., Veronese, N., Bortolato, B., Rosson, S., Santonastaso, P., Thapa-Chhetri, N., Fornaro, M., Gallicchio, D., Collantoni, E., Pigato, G., Favaro, A., Monaco, F., Kohler, C., Vancampfort, D., Ward, P.B., Gaughran, F., Carvalho, A.F., Stubbs, B., 2017. Prevalence, incidence and mortality from cardiovascular disease in patients with pooled and specific severe mental illness: a large-scale meta-analysis of 3,211,768 patients and 113,383,368 controls. World Psychiatry 16, 163-180. [2] Berk, M., Kohler-Forsberg, O., Turner, M., Penninx, B.W.J.H., Wrobel, A., Firth, J., Loughman, A., Reavley, N.J., McGrath, J.J., Momen, N. C., Plana-Ripoll, O., O'Neil, A., Siskind, D., Williams, L.J., Carvalho, A.F., Schmaal, L., Walker, A.J., Dean, O., Walder, K., Berk, L., Dodd, S., Yung, A.R., Marx, W., 2023. Comorbidity between major depressive disorder and physical diseases: a comprehensive review of epidemiology, mechanisms and management. World Psychiatry 22(3), 366-387. [3] Sijtsma, A., Rienks, J., van der Harst, P., Navis, G., Rosmalen, J.G.M., Dotinga, A., 2022. Cohort Profile Update: Lifelines, a three-generation cohort study and biobank. Int J Epidemiol 51(5), 295-302. [4] Snijder, M.B., Galenkamp, H., Prins, M., Derks, E.M., Peters, R.J.G., Zwinderman, A.H., Stronks, K., 2017. Cohort profile: the Healthy Life in an Urban Setting (HELIUS) study in Amsterdam, The Netherlands. BMJ Open 7(12), e017873. [5] Hamaker, E.L., Kuiper, R.M., Grasman, R.P., 2015. A critique of the cross-lagged panel model. Psychol Methods 20(1), 102-116.

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