Epidemiological studies have established various observational associations between modifiable human behaviors and disease risk. However, observational studies are prone to unmeasured confounding bias and cannot establish causal associations, which are important to investigate disease treatment and drug development. In 1991, Gray and Wheatley proposed the term “Mendelian Randomization”, a method that were applied to obtain unbiased estimations of the impact of cancer treatment within a family-based design. The term has since been applied to describe statistical genomic studies that used genetic instruments as proxy for modifiable risk factors or behaviors to infer causal association with diseases.The principle of Mendelian Randomization relies on Mendel’s laws of inheritance and random segregation. It is less prone to unmeasured confounding bias and reverse causation compared to observational studies and can be applied to address questions of causality without any typical bias that impact the validity of traditional epidemiological methods. Studies based on Mendelian Randomization have become more conventional with the enhancement of genome-wide association studies (GWAS) and genome sequencing technologies. These methods have the potential to reveal the aetiological importance of environmental/casual factors in common chronic diseases, with minimal influence of confounding, reverse causation, and various other sources of bias.Mendelian Randomization has made significant progress in advancing the fields of precision medicine and public health, but further research is needed. Therefore, this Research Topic will focus on recent advances related to empirical and methodological studies of Mendelian Randomization.The scope may include but is not limited to:• Casual association between disease and human health• Multivariable Mendelian randomization• Advancement in medical and public health• Comparative studies of existing statistical methods• Causal inference between novel data sets• Application of Mendelian randomization
Epidemiological studies have established various observational associations between modifiable human behaviors and disease risk. However, observational studies are prone to unmeasured confounding bias and cannot establish causal associations, which are important to investigate disease treatment and drug development. In 1991, Gray and Wheatley proposed the term “Mendelian Randomization”, a method that were applied to obtain unbiased estimations of the impact of cancer treatment within a family-based design. The term has since been applied to describe statistical genomic studies that used genetic instruments as proxy for modifiable risk factors or behaviors to infer causal association with diseases.The principle of Mendelian Randomization relies on Mendel’s laws of inheritance and random segregation. It is less prone to unmeasured confounding bias and reverse causation compared to observational studies and can be applied to address questions of causality without any typical bias that impact the validity of traditional epidemiological methods. Studies based on Mendelian Randomization have become more conventional with the enhancement of genome-wide association studies (GWAS) and genome sequencing technologies. These methods have the potential to reveal the aetiological importance of environmental/casual factors in common chronic diseases, with minimal influence of confounding, reverse causation, and various other sources of bias.Mendelian Randomization has made significant progress in advancing the fields of precision medicine and public health, but further research is needed. Therefore, this Research Topic will focus on recent advances related to empirical and methodological studies of Mendelian Randomization.The scope may include but is not limited to:• Casual association between disease and human health• Multivariable Mendelian randomization• Advancement in medical and public health• Comparative studies of existing statistical methods• Causal inference between novel data sets• Application of Mendelian randomization