The association between fatigue and cardiometabolic diseases: Insights from the UK biobank study

J Affect Disord. 2024 Nov 20:S0165-0327(24)01903-7. doi: 10.1016/j.jad.2024.11.040. Online ahead of print.

Abstract

Background: Cardiometabolic diseases (CMD) are major global health concerns with significant morbidity and mortality. Fatigue, a common but often overlooked symptom, has been postulated as both a potential risk factor for and a consequence of these conditions. However, the relationships between fatigue and CMD remain unclear. This study aimed to investigate the relationship between fatigue and CMD using observational and genetic approaches.

Method: Observational study was conducted in the UK biobank. Genetic method was employed a bidirectional MR approach to examine the causal relationship between fatigue and CMD. Genetic variants associated with fatigue were identified through a GWAS, and summary statistics from the largest available GWAS were used to obtain variants associated with stroke, CAD, T2D, and HF. Inverse variance weighting (IVW) was conducted, with weighted median, MR-Egger, and MR-PRESSO as sensitivity analyses. Multivariable MR and mediation analysis were also employed.

Results: Observational analyses indicated that individuals with fatigue had a significantly increased risk of developing stroke (HR 1.44, 95 % CI 1.27-1.63), T2D (HR 1.46, 95 % CI 1.41-1.51), CAD (HR 1.45, 95 % CI 1.4-1.5), and HF (HR 1.60, 95 % CI 1.52-1.68). Mendelian randomization analyses further supported a causal relationship. Additionally, observational and genetic analyses showed T2D was found to be associated with increased levels of fatigue. Mediation analysis identified lipid metabolites as mediators in the relationship between fatigue and CMD.

Conclusion: This study highlights a bidirectional relationship between fatigue and CMD, underscoring the importance of considering fatigue in the context of cardiometabolic health.

Clinical trial number: Not applicable.

Keywords: Cardiometabolic disease; Diabetes; Fatigue; Heart failure; Mendelian randomization; Stroke.