Evaluating the effect of metabolic traits on oral and oropharyngeal cancer risk using Mendelian randomization.
Mark GormleyTom DuddingSteven J ThomasJessica TyrrellAndrew R NessMiranda PringDanny Nigel LeggeGeorge Davey SmithRebecca C RichmondEmma E VincentCaroline J BullPublished in: eLife (2023)
A recent World Health Organization report states that at least 40% of all cancer cases may be preventable, with smoking, alcohol consumption and obesity identified as three of the most important modifiable lifestyle factors. Given the significant decline in smoking rates, particularly within developed countries, other potentially modifiable risk factors for head and neck cancer warrant investigation. Obesity and related metabolic disorders such as type 2 diabetes and hypertension have been associated with head and neck cancer risk in multiple observational studies. However, adiposity has also been correlated with smoking, with bias, confounding or reverse causality possibly explaining these findings. To overcome the challenges of observational studies, we conducted two-sample Mendelian randomization (inverse variance weighted (IVW) method) using genetic variants which were robustly associated with adiposity, glycaemic and blood pressure traits in genome-wide association studies (GWAS). Outcome data was taken from the largest available GWAS of 6,034 oral and oropharyngeal cases, with 6,585 controls. We found limited evidence of a causal effect of genetically proxied body mass index (OR IVW = 0.89, 95%CI 0.72-1.09, p = 0.26 per 1 SD in BMI (4.81 kg/m2)) on oral and oropharyngeal cancer risk. Similarly, there was limited evidence for related traits including type 2 diabetes and hypertension.
Keyphrases
- type diabetes
- blood pressure
- insulin resistance
- weight gain
- body mass index
- alcohol consumption
- metabolic syndrome
- smoking cessation
- weight loss
- glycemic control
- genome wide
- cardiovascular disease
- genome wide association
- high fat diet induced
- heart rate
- adipose tissue
- hypertensive patients
- physical activity
- skeletal muscle
- magnetic resonance
- papillary thyroid
- adverse drug
- dna methylation
- machine learning
- big data
- squamous cell carcinoma
- blood glucose
- drug induced
- lymph node metastasis
- computed tomography