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Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
Published on: May 6, 2022
Associations of polygenic risks, depression, and obesity-related traits in Taiwan Biobank
Shu-Fen Liao1, Chun-Yun Su2, Mei-Hsin Su3
1Department of Medical Research, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan; School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan.
Background:
The comorbidity of obesity and major depressive disorder (MDD) may be attributable to a bidirectional relationship and shared genetic influence. We aimed to examine the polygenic associations between obesity and MDD and to characterize their corresponding impacts on the obesity mechanism.
Methods:
Genome-wide genotyping was available in 106,604 unrelated individuals from Taiwan Biobank. Polygenic risk score (PRS) for body mass index (BMI) and MDD was derived to evaluate their effects on obesity-related traits. Stratified analyses were performed for the modified effect of depression on the polygenic associations.
Results:
The MDD PRS was positively associated with waistline (beta in per SD increase in PRS = 0.12), hipline (beta = 0.08), waist-hip ratio (WHR) (beta = 0.05), body fat rate (beta = 0.08), BMI (beta = 0.05), overweight (OR = 1.02 for BMI ≥ 25), and obesity (OR = 1.05 for BMI ≥ 30). For the synergism between depression and BMI PRS, the presence of active depression symptoms defined by the PHQ-4 (p for interaction < 0.05 for waistline, WHR, and BMI) was more salient than lifetime MDD.
Limitations:
Limitations include recall bias for MDD due to a retrospective self-reporting questionnaire, a low response rate of the PHQ-4 for evaluating active psychological symptoms, and limited generalizability to non-Taiwanese ancestries.
Conclusions:
The shared genetic etiology of obesity and depression was demonstrated. The amplified effect of BMI polygenic effect on obesity for individuals with active depressive symptoms was also characterized. The study may be helpful for designing public health interventions to reduce the disease burden caused by obesity and depression.
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