About this Research Topic
Despite fruitful causal relationships being established by the MR approach, the progress is limited. While MR offers an attractive solution to causal inference using observational data, violation of some assumptions of MR may invalidate the findings. Specifically, the issue of pleiotropy, among others, has received much attention of empirical applications and methodological development in the past years. Progress towards comparative performance of existing methods as well as novel methodological development is expected.
The application of MR has extended from epidemiological analyses to new scenarios, such as mRNA or protein level research, to study causal relationships between metabolic biomarkers or molecular phenotypes. Other more sophisticated scenarios include microbiota-oriented causal inference as well as drug target discovery. All these applications will deepen the understanding of the pathophysiological mechanisms behind health problems.
This Research Topic will focus on all MR related empirical and methodological studies. The scope may include but is not limited to:
• Novel statistical method development;
• Comparative studies of existing statistical methods;
• Empirical causal inference between traditional traits/diseases;
• Causal inference between novel data types, such as microbiome, mRNA, and protein data;
• Application of drug target discovery.
Keywords: Mendelian randomization, Causal inference, Horizontal pleiotropy, Genome-wide association study, Confounding factor
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.