Causality Of Metabolic Syndrome Related Biomarkers Based On Mendelian Randomization

Metabolic Syndrome(MetS)refers to the pathological state of the body of carbohydrates,proteins,fat and other substances metabolic disorders.It is an important risk factor for cardiovascular disease.At present,there are many studies focus on MetS and its components,but few explore the interaction relationship between MetS related biomarkers,which including:systolic blood pressure(SBP),diastolic blood pressure(DBP),fasting plasma glucose(FPG),body mass index(BMI),total cholesterol(TC),triglyceride(TG),high-density lipoprotein(HDL-C),and low-density lipoprotein(LDL-C).Additionally,in observational epidemiological studies,logistic regression or Cox proportional hazards regression models were often conducted to avoid confounding.But they are susceptible of the unobserved confounding,and the reverse causation.The Mendelian randomization method is a causal inference method based on the development of instrumental variables.It can avoid confounding and reverse causation,thus allow us to access to the more real causal effects.Based on Shandong Multi-center Longitudinal Cohort for Health Management,our study randomly selected 1405 women participating in physical examination at the Health Management Center of Qianfoshan Hospital of Shandong Province.According to the MetS related biomarkers,7 cohort studies(hypertension,hyperglycemia,overweight/obesity,hypercholesterolemia,hypertriglyceridemia,hypo-HDL-C,and hyper-LDL-C)were established from 1405 subjects during the observational period.Then,through the health questionnaires,physical examination,and genotyping,we used Mendelian randomization to explore the causality between MetS related biomarkers.Aimed to form a causal direction pathway between MetS related biomarkers,and provide a scientific basis for MetS prevention strategies,as well as some new ideas for clinical basic research.Results:1.A total of 1405 women were surveyed in our study,with an average age of 39.82± 12.28 and a median age of 37.The incidence densities of hypertension,hyperglycemia,overweight/obesity,hypercholesterolemia,hypertriglyceridemia,hypo-HDL-C,and hyper-LDL-C were 47.802,20.159,63.169,27.618,20.209,30.376,and 18.623/1000 person-year,respectively.2.Cox regression analysis showed that ?increasing SBP can increase BMI;?increasing BMI can increase the risk of hypertension,increase FPG and reduce HDL-C levels;?increasing FPG can increase TC levels;?there is a certain correlation between serum lipids.TC,TG,LDL-C and HDL-C levels increase along with TC level increases;increasing TG can reduce HDL-C levels;increasing HDL-C can increase TC and decrease TG levels.Increased LDL-C can increase TG and HDL-C levels.3.Mendelian randomized analysis showed that ?increasing BMI can cause high blood pressure;?FPG can cause TC and LDL-C levels increase;?TC and TG levels can increase LDL-C levels;?blood pressure(SBP and DBP)is independent of FPG and serum lipid levels;?BMI is independent of FPG and serum lipid levels.Conclusion:1.Increasing BMI can cause high blood pressure.2.There is a causal relationship between FPG and serum lipid levels,FPG can increase the level of TC and LDL-C,but independent of TG and HDL-C.3.Hyper-LDL-C can be caused by the increased FPG,TC and TG.4.Blood pressures are independent of FPG and serum lipid levels,and BMI is relatively independent of FPG and serum lipid levels.