Novel insights into the consequences of obesity: a phenotype-wide Mendelian randomization study

Chang He, Miaoran Zhang, Jiuling Li, Yiqing Wang, Lanlan Chen, Baiyu Qi, Jianping Wen, Jianli Yang, Sitong Lin, Dianyuan Liu, Ying Dong, Liying Wang, Qing Wang, Peng Chen

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Obesity is thought to significantly impact the quality of life. In this study, we sought to evaluate the health consequences of obesity on the risk of a broad spectrum of human diseases. The causal effects of exposing to obesity on health outcomes were inferred using Mendelian randomization (MR) analyses using a fixed effects inverse-variance weighted model. The instrumental variables were SNPs associated with obesity as measured by body mass index (BMI) reported by GIANT consortium. The spectrum of outcome consisted of the phenotypes from published GWAS and the UK Biobank. The MR-Egger intercept test was applied to estimate horizontal pleiotropic effects, along with Cochran’s Q test to assess heterogeneity among the causal effects of instrumental variables. Our MR results confirmed many putative disease risks due to obesity, such as diabetes, dyslipidemia, sleep disorder, gout, smoking behaviors, arthritis, myocardial infarction, and diabetes-related eye disease. The novel findings indicated that elevated red blood cell count was inferred as a mediator of BMI-induced type 2 diabetes in our bidirectional MR analysis. Intriguingly, the effects that higher BMI could decrease the risk of both skin and prostate cancers, reduce calorie intake, and increase the portion size warrant further studies. Our results shed light on a novel mechanism of the disease-causing roles of obesity.

Original languageEnglish (US)
Pages (from-to)540-546
Number of pages7
JournalEuropean Journal of Human Genetics
Volume30
Issue number5
DOIs
StatePublished - May 2022

Keywords

  • Genome-Wide Association Study
  • Humans
  • Mendelian Randomization Analysis
  • Obesity/epidemiology
  • Phenotype
  • Polymorphism, Single Nucleotide
  • Quality of Life

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