Symptomatology of depression and onset of cardiometabolic diseases - A 7-year follow-up study

Abstract

Background: Our study aimed to investigate the association of depressive mood and two depressive symptom profiles with the risk of cardiometabolic diseases (CMD) and to explore the underlying mechanisms of these associations through CMD-related metabolites and proteins.

Methods: In the Netherlands Epidemiology of Obesity study, depressive mood was measured with the Inventory of Depressive Symptomatology questionnaire, and two depressive symptom profiles, namely atypical energy-related symptom (AES) and melancholic, were created. The AES profile was derived by summing the score of five items: increased sleepiness, increased appetite, weight gain, low energy level and leaden paralysis. The melancholic symptom profile was used as another clinically established symptom profile for comparison with AES. The incidence of CMD (defined as development of cardiovascular diseases or type 2 diabetes (T2D)) was identified during a median follow-up of 6.7 years. Cox proportional hazards models assessed the association between depressive symptom profiles and CMD incidence, adjusted for confounders, while linear regression models examined associations with CMD-related proteins and metabolites identified in the UK Biobank.

Results: Compared to participants without depressive mood, those in the severe depressive mood group had the highest risk of developing CMD, with a hazard ratio (HR) of 1.65 (95% CI: 1.22-2.22). Regarding depressive symptom profiles, individuals with a severe AES profile showed a significantly increased risk of T2D (HR: 2.87, 95% CI: 1.92-4.30) compared to those without symptoms, whereas no significant association was observed for the melancholic symptom profile. The AES profile was more strongly associated with CMD-related metabolites, including glycoprotein acetyls, isoleucine and lipoproteins, and proteins predominantly enriched in the cytokine-cytokine receptor interaction pathway.

Conclusion: The AES profile is specifically associated with the incidence of T2D, and some specific metabolites and proteins were suggested to influence such association. Acknowledging the heterogeneity of depression may aid in tailoring CMD prevention.

Keywords: Cardiovascular diseases; Depression; Longitudinal; Metabolomics; Proteomics; Symptom profiles; Type 2 diabetes.