Obesity and atypical depression symptoms: findings from Mendelian randomization in two European cohorts

Giorgio Pistis1, Yuri Milaneschi2, Caroline L Vandeleur3

  • 1Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland. giorgio.pistis@chuv.ch.

Translational Psychiatry
|February 5, 2021
PubMed

Insights

Obesity, measured by body mass index (BMI), may causally increase appetite in individuals with major depressive disorder (MDD). This Mendelian Randomization study highlights the importance of examining depression symptoms individually for deeper biological insights.

Area of Science:

  • Psychiatry and Genetics
  • Metabolic Health and Mental Well-being

Background:

  • Contradictory findings exist regarding the causal link between body mass index (BMI) and major depressive disorder (MDD).
  • Previous research suggests BMI is associated with atypical depression, indicating potential heterogeneity in MDD subtypes.

Purpose of the Study:

  • To investigate the potential causal role of obesity (BMI and waist-to-hip ratio) in atypical depression and its specific symptoms using a Mendelian Randomization (MR) approach.
  • To analyze data from two large European cohorts: CoLaus|PsyCoLaus and NESDA|NTR.

Main Methods:

  • Employed Mendelian Randomization (MR) analysis to assess the causal relationship between obesity indicators (BMI, WHR) and atypical depression.
  • Utilized data from CoLaus|PsyCoLaus (n=3350) and NESDA|NTR (n=4139) cohorts, including individuals diagnosed with depression.

Main Results:

  • A potential causal relationship was identified between higher BMI and an increased appetite symptom in depressed individuals.
  • No significant causal effect of BMI or waist-to-hip ratio (WHR) was found on the overall risk of atypical depression or its other specific symptoms.

Conclusions:

  • Higher obesity is likely a causal factor for increased appetite in individuals experiencing depression.
  • Studying depression at a granular symptom level is crucial for understanding underlying biological mechanisms and potential causal pathways.

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