Research On Causality Inference Between Physical Index And Fracture Risk Based On Mendelian Randomization

Osteoporosis is a systemic bone disease,which can cause bone mineral density,bone quality decline,bone microstructure destruction and bone fragility increase,leading to fractures,causing serious complications,and even disability or death.Uncovering additional causal clinical traits and exposure variables is important when studying osteoporosis mechanisms and for the prevention of osteoporosis.Until recently,the causal relationship between anthropometric measurements and osteoporosis had not been fully revealed.In the present study,we utilized several state-of-the-art Mendelian randomization（MR）methods to investigate whether height,body mass index（BMI）,waist-to-hip ratio（WHR）,hip circumference（HC）,and waist circumference（WC）are causally associated with two major characteristics of osteoporosis,bone mineral density（BMD）and fractures.（1）Data collection and preprocessing.The data of anthropometric measurements are obtained from a large-scale Genome-wide Association Studies（GWAS）.These GWAS have obtained SNPs that are significantly related to the five anthropometric measurements in the whole genome(P value<5×10^-8).The aggregated data on bone mineral density and fracture are from the large GWAS results of the UK Biobank.In this thesis,a total of five steps were performed to screen SNP sites to obtain instrumental variables of sufficient quality.（2）Causality inference based on two-sample Mendelian randomization method.In this thesis,five two-sample Mendelian randomization methods are implemented to infer the above-mentioned causality.In the MR method used in this thesis,the inverse variance weighting method is used as the main analysis method,the weighted median,MR-Egger,mode-based estimation,and MR pleiotropic residual sum and outlier methods are used to evaluate stability and reliability of the IVW method.（3）Sensitivity analysis.This study performed three sensitivity analysis methods,including drawing a funnel diagram analysis,leaving one out method,and removing SNP sites with pleiotropic evidence and re-executing the above five two-sample Mendelian randomization methods to verify the stability of the results.The results of this study showed that for every standard deviation（SD）increase in height,the risk of fracture increased by 9.9%(OR=1.099;95%confidence interval（CI）:1.067～1.133;P=8.793×10^-10),BMD decreased 0.080 SD(95%CI:-0.106～-0.054;P=2.322×10^-9).In addition,the results after excluding pleiotropic SNP sites showed that BMI was significantly correlated with increased BMD(beta=0.129;95%CI:0.065～0.194;P=8.113×10^-5).This study did not find a significant causal relationship between WHR,HC,WC and fracture risk and BMD.In summary,this thesis provides genetic evidence for studying the causal relationship between anthropometric measurements,BMD and fracture risk.