Background and aims
Some studies reported that mildly elevated serum bilirubin levels were associated with decreased risk of cardiovascular disease (CVD) and diabetes. Whether these are causal relationships remains unclear. This study aims to examine the causal effects of bilirubin on CVD, diabetes and their subtypes.
The data we used in this study includes individual data from the UK Biobank cohort with 331,002 white British participants, and summary data from published genome wide associations studies (GWAS) findings. We used individual data to perform logistic regression for the observational study and two-stage least squares method for the Mendelian randomization (MR) study. We also performed several traditional MR methods and MR-TRYX by summary data.
The observational study supported the association relationships between bilirubin and CVD and diabetes and their subtypes. Results of MR showed strong evidence for negative causal associations of loge total bilirubin with CVD [OR 0.92, 95%CI 0.88-0.95, p-value 2.15 10-6], coronary heart disease [OR 0.90, 95%CI 0.85-0.96, p-value 1.54 10-3] and hypertensive diseases [OR 0.91, 95%CI 0.88-0.95, p-value 5.89 10-6], but no evidence for diabetes [OR 0.94, 95%CI 0.86-1.02, p-value 0.14] and its subtypes. We also obtained similar results for direct bilirubin. We found that blood pressure, cholesterol, C-reactive protein, alcohol and white blood cell count played important roles in the causal pathway from bilirubin to CVD. Two sample MR and sensitivity analyses showed consistent results with one sample MR.
Genetically determined bilirubin was negatively associated with the risk of CVD but had no evident causal association with diabetes in the UK Biobank cohort of white British.
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|
|3794||51470||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||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|
|3791||Exploring the causal pathway from bilirubin to CVD and diabetes in the UK biobank cohort study: Observational findings and Mendelian randomization studies||Hou L et al.||2021||Atherosclerosis|