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BACKGROUND: In a substantial subgroup of depressed patients, atypical, energy-related depression symptoms (e.g. increased appetite/weight, hypersomnia, loss of energy) tend to cluster with immuno-metabolic dysregulations (e.g. increased BMI and inflammatory markers). This clustering is proposed to reflect a more homogeneous depression pathology. This study examines to what extent energy-related symptoms are associated and share demographic, lifestyle and clinical characteristics. METHODS: Data were available from 13,965 participants from eight Dutch cohorts with DSM-5 lifetime major depression assessed by the Lifetime Depression Assessment Self-report (LIDAS) questionnaire. Information on four energy-related depression symptoms were extracted: energy loss, increased appetite, increased weight, and hypersomnia. Tetrachoric correlations between these symptoms, and associations of these symptoms with sociodemographic (sex, age, education), lifestyle (physical activity, BMI, smoking) and clinical characteristics (age of onset, episode duration, history, treatment and recency, and self-reported comorbidity) were computed. RESULTS: Correlations between energy-related symptoms were overall higher than those with other depression symptoms and varied from 0.90 (increased appetite vs increased weight) to 0.11 (increased appetite vs energy loss). All energy-related symptoms were strongly associated with higher BMI and a more severe clinical profile. Patients with increased appetite were more often smokers, and only patients with increased appetite or weight more often had a self-reported diagnosis of PTSD (OR = 1.17, p = 2.91E-08) and eating disorder (OR = 1.40, p = 4.08E-17). CONCLUSIONS: The symptom-specific associations may have consequences for a profile integrating these symptoms, which can be used to reflect immuno-metabolic depression. They indicate the need to study immuno-metabolic depression at individual symptom resolution as a starting point.

Original publication

DOI

10.1016/j.jad.2022.11.005

Type

Journal article

Journal

J Affect Disord

Publication Date

10/11/2022

Keywords

Clinical characteristics, Depression, Depression symptoms