The causal evidence of the triglyceride glucose (TyG) index, as well as the joint exposure of higher glucose and triglyceride on the risk of cardio-cerebrovascular diseases (CVD), was lacking.
A comprehensive factorial Mendelian randomization (MR) was performed in the UK Biobank cohort involving 273,368 individuals with European ancestry to assess and quantify these effects. The factorial MR, MR-PRESSO, MR-Egger, meta-regression, sensitivity analysis, positive control, and external verification were utilized. Outcomes include major outcomes [overall CVD, ischemic heart diseases (IHD), and cerebrovascular diseases (CED)] and minor outcomes [angina pectoris (AP), acute myocardial infarction (AMI), chronic IHD (CIHD), heart failure (HF), hemorrhagic stroke (HS), and ischemic stroke (IS)].
The TyG index significantly increased the risk of overall CVD [OR (95% CI): 1.20 (1.14-1.25)], IHD [OR (95% CI): 1.22 (1.15-1.29)], CED [OR (95% CI): 1.14 (1.05-1.23)], AP [OR (95% CI): 1.29 (1.20-1.39)], AMI [OR (95% CI): 1.27 (1.16-1.39)], CIHD [OR (95% CI): 1.21 (1.13-1.29)], and IS [OR (95% CI): 1.22 (1.06-1.40)]. Joint exposure to genetically higher GLU and TG was significantly associated with a higher risk of overall CVD [OR (95% CI): 1.17 (1.12-1.23)] and IHD [OR (95% CI): 1.22 (1.16-1.29)], but not with CED. The effect of GLU and TG was independent of each other genetically and presented dose-response effects in bivariate meta-regression analysis.
Lifelong genetic exposure to higher GLU and TG was jointly associated with higher cardiac metabolic risk while the TyG index additionally associated with several cerebrovascular diseases. The TyG index could serve as a more sensitive pre-diagnostic indicator for CVD while the joint GLU and TG could offer a quantitative risk for cardiac metabolic outcomes.
Physical measurement, blood biochemistry, lifestyle, environmental exposure: causality, gene-environment interaction in relation to metabolic diseases and cancer risk.
Cancer and metabolic diseases account for a large proportion of the global burden of disease. Epidemiological association studies reported a variety of environmental risk factors and risk genes for these diseases. However, limited studies have definite causal effects on metabolic disease or cancer, except for few widely recognized risk factors such as smoking for lung cancer and high-calorie diet for obesity. In fact, the effects of these exposures and genes on the diseases are very complicated including direct effects, indirect effects, mediating effects, gene-environment interactions, gene pleiotropy, effect modification and so on. Meanwhile, routine observational studies inevitably suffer from confounding or reverse causality. Besides, metabolic diseases and cancer may also share common risk factors with each other, however, the causal effect and pathogenic mechanism of these factors may be highly heterogeneous.
Therefore, for each potential risk factor, if the causal association with a specific disease was determined, we could intervene the exposure levels of risk factors promptly to reduce the morbidity or mortality of metabolic diseases and cancer. So we aimed to explore the potential causal effect of specific exposure or pathway (physical measurement, blood biochemistry, lifestyle, environment, genes, interactions) on chronic metabolic diseases or cancer and to provide evidence for intervention and prevention. Then we also expect to develop some novel causal inference methods and effective disease prediction methods.
We intend to perform our research for the duration of three years. The study may have certain practicality values for public health and further research if our results are supported. Study on both genes and environmental exposures would provide strong evidence to clarify the relationship between various exposures and diseases. Causal findings may contribute to identify novel biological pathways for disease prevention, diagnosis and treatment or provide suitable prediction indicators. This is of great significance to public health for cancer and metabolic diseases controlling. Additionally, we may also provide new analytical strategies and methods, which may have some application values for further research.
|Lead investigator:||Professor Fuzhong Xue|
|Lead institution:||Shandong University|
4 related Returns
|Return ID||App ID||Description||Archive Date|
|3790||51470||Exploring the causal pathway from bilirubin to CVD and diabetes in the UK biobank cohort study: Observational findings and Mendelian randomization studies||6 Sep 2021|
|3795||51470||Genetically Determined Chronic Low-Grade Inflammation and Hundreds of Health Outcomes in the UK Biobank and the FinnGen Population: A Phenome-Wide Mendelian Randomization Study||6 Sep 2021|
|3796||51470||Genetically Predicted Insomnia in Relation to 14 Cardiovascular Conditions and 17 Cardiometabolic Risk Factors: A Mendelian Randomization Study||6 Sep 2021|
|3789||51470||Genomic risk score provides predictive performance for type 2 diabetes in the UK biobank||6 Sep 2021|
|3795||Causal Effect of the Triglyceride-Glucose Index and the Joint Exposure of Higher Glucose and Triglyceride With Extensive Cardio-Cerebrovascular Metabolic Outcomes in the UK Biobank: A Mendelian Randomization Study||Si S et al.||2021||Front Cardiovasc Med|