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. 2023 Jan;53(1):248-257.
doi: 10.1017/S0033291721001471. Epub 2021 Jun 3.

Metabolomics dissection of depression heterogeneity and related cardiometabolic risk

Tahani Alshehri  1 , Dennis O Mook-Kanamori  1   2 , Ko Willems van Dijk  3   4 , Richard Dinga  5 , Brenda W J H Penninx  6 , Frits R Rosendaal  1 , Saskia le Cessie  1   7 , Yuri Milaneschi  6   8
Affiliations

Metabolomics dissection of depression heterogeneity and related cardiometabolic risk

Tahani Alshehri et al. Psychol Med. 2023 Jan.

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 major depressive disorder in the last 6 months 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 diseases 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 cardiometabolic risk, such as (i.e. per s.d.) HOMA-1B -0.06 (95% CI -0.09 - -0.04), and visceral adipose tissue -0.10 cm2 (95% CI -0.14 - -0.07). In contrast, the IMD dimension was associated with well-known cardiometabolic diseases such as higher visceral adipose tissue 0.08 cm2 (95% CI 0.04-0.12), HOMA-1B 0.06 (95% CI 0.04-0.09), and lower HDL-cholesterol levels -0.03 mmol/L (95% CI -0.05 - -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.

Keywords: Body fat distribution; body mass index; depression; metabolic syndrome; metabolomics.

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Figures

Fig. 1.
Fig. 1.
An illustration of the method.
Fig. 2.
Fig. 2.
Level plots of the predicted cardiometabolic diseases as functions of the first and second metabolic canonical variates. sCV I: First symptoms canonical variates I. sCV II: Second symptoms canonical variates.
Fig. 3.
Fig. 3.
Canonical loading of depressive symptoms on the symptoms canonical variates.
Fig. 4.
Fig. 4.
The linear regression analysis of the association between the weighted depressive symptoms scores and the cardiometabolic diseases and metabolites in individuals from NEO study. The weights extracted from the metabolite-symptom clustering step. * FDR significant (q < 0.05) at least for one of the two depressive symptom scales. Number of individuals with data for BMI: 6572, total body fat: 6541, waist circumference: 6566, visceral adipose tissue: 2537, fasting glucose: 6554, HOMA-1B: 6541, HOMA-IR: 6545, HbA1c: 6543, total cholesterol: 6562, HDL-cholesterol: 6561, triglycerides: 6561, LDL-cholesterol: 6560.
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References

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