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

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.

Quantifying the phenome‐wide disease burden of obesity using electronic health records and genomics

“…Prior studies have suggested that obesity‐risk SNPs are associated with ischemic heart disease [13,14], hypertension [14], type 2 diabetes [14], atrial fibrillation [15], symptomatic cholelithiasis [16], osteoarthritis [17], and deep venous thrombosis [18], among others [19–25]. Further evidence validated genomic risk for obesity as a causal factor for diabetes, myocardial infarction, and dyslipidemia [26]. These studies are limited by the use of either a single or limited number of genetic polymorphisms associated with BMI as well as evaluation for an association with a single comorbid phenotype.…”

Advancing a causal role of type 2 diabetes and its components in developing macro‐ and microvascular complications via genetic studies

“…Contrary to the findings of some observational studies, which reported a lower risk of diabetic retinopathy to be associated with a higher BMI, 44 this study found that genetically elevated BMI was an independent causal risk factor for diabetic retinopathy. This study once again suggests that results from observational studies which examine risks linked to BMI, may be misleading due to the unintentional loss of weight associated with long‐standing diabetes 45 …”

“…This study once again suggests that results from observational studies which examine risks linked to BMI, may be misleading due to the unintentional loss of weight associated with long‐standing diabetes. 45 …”

The potential of DNA methylation as a biomarker for obesity and smoking

“…Both ABGC1 (ATP binding cassette subfamily G member 1) and SREBF1 (sterol regulatory element binding transcription factor 1) have also been associated with other closely related traits such as dyslipidemia and T2D [80,81]. Gene expression levels of CPT1A (carnitine palmitoyltransferase 1A) have been previously linked to blood lipid profiles CVD [162,163] Mortality [164] Easy to measure Correlates with fat mass Not a measure of body composition…”