Abstract
Background: A recent hypothesis postulates the existence of an "immune-metabolic depression" (IMD) dimension characterized by metabolic dysregulations. Combining data on metabolomics and depressive symptoms, we aimed to identify depressions associated with an increased risk of adverse metabolic alterations.
Method:
Clustering data were from 1094 individuals with current major depressive disorder and measures of 149 metabolites from a 1H-NMR platform and 30 depressive symptoms (IDS-SR30). Canonical correlation analyses (CCA) were used to identify main independent metabolite-symptom axes of variance. Then, for the replication, we examined the association of the identified dimensions with metabolites from the same platform and cardiometabolic endpoints in an independent population-based cohort (n=6572).
Results: CCA identified an overall depression dimension and a dimension resembling IMD, in which symptoms such as sleeping too much, increased appetite, and low energy level had higher relative loading. In the independent sample, the overall depression dimension was associated with lower levels of metabolites linked to cardiometabolic risk, such as HOMA-1B -0.09 (95% CI:-0.13--0.06), and visceral adipose tissue -0.15 cm2 (95% CI:-0.20--0.10). In contrast, the IMD dimension was associated with well-known adverse cardiometabolic metabolites such as higher visceral adipose tissue 0.11 cm2 (95% CI:0.06-0.16), HOMA-1B 0.08 (95% CI: 0.05-0.12), and lower HDL levels -0.04 mmol/L (95% CI:-0.07--0.01).
Conclusions: Combining metabolomics and clinical symptoms we identified a replicable depression dimension associated with adverse metabolic alterations, in line with the IMD hypothesis. Patients with IMD may be at higher cardiometabolic risk and may benefit from specific treatment targeting underlying metabolic dysregulations.
Clinical utility of visceral adipose tissue for the identification of cardiometabolic risk in white and African American adults
