Background: Adiposity has been shown to be linked with atypical energy-related symptoms (AES) of depression. We used genomics to separate the effect of adiposity from that of metabolic... Show moreBackground: Adiposity has been shown to be linked with atypical energy-related symptoms (AES) of depression. We used genomics to separate the effect of adiposity from that of metabolic dysregulations to examine whether the link between obesity and AES is dependent on the presence of metabolic dysregulations. Method: Data were from NEO (n = 5734 individuals) and NESDA (n = 2238 individuals) cohorts, in which the Inventory of Depressive Symptomatology (IDS-SR30) was assessed. AES profile was based on four symptoms: increased appetite, increased weight, low energy level, and leaden paralysis. We estimated associations between AES and two genetic risk scores (GRS) indexing increasing total body fat with (metabolically unhealthy adiposity, GRS-MUA) and without (metabolically healthy adiposity, GRS-MHA) metabolic dysregulations. Results: We validated that both GRS-MUA and GRS-MHA were associated with higher total body fat in NEO study, but divergently associated with biomarkers of metabolic health (e.g., fasting glucose and HDL-cholesterol) in both cohorts. In the pooled results, per standard deviation, GRS-MUA was specifically associated with a higher AES score (beta = 0.03, 95%CI: 0.01; 0.05), while there was no association between GRS-MHA and AES (beta =-0.01, 95%CI:-0.03; 0.01). Conclusion: These results suggest that the established link between adiposity and AES profile emerges in the presence of metabolic dysregulations, which may represent the connecting substrate between the two conditions. Show less
Background A recent hypothesis postulates the existence of an 'immune-metabolic depression' (IMD) dimension characterized by metabolic dysregulations. Combining data on metabolomics and depressive... Show moreBackground 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 H-1-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 cm(2) (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 cm(2) (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. Show less
BackgroundA recent hypothesis postulates the existence of an ‘immune-metabolic depression’ (IMD) dimension characterized by metabolic dysregulations. Combining data on metabolomics and depressive... Show moreBackgroundA 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.MethodClustering 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).ResultsCCA 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).ConclusionsCombining 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. Show less
Alshehri, T.; Boone, S.; Mutsert, R. de; Penninx, B.; Rosendaal, F.; Cessie, S. le; ... ; Mook-Kanamori, D. 2019
