About this Research Topic
The malignant tumor is a major global public health problem threatening human health. At present, association studies can be used to analyze the occurrence and development of tumors. Association studies, such as the classic study of smoking and lung cancer and the popular genome-wide association study (GWAS), form the basis of medical research. These studies provided initial evidence for subsequent mechanistic exploration and functional studies, but could not illustrate a causal relationship. R.A. Fisher first proposed the concept and method of Mendelian randomization (MR) in a 1936 book called “The Design of Experiments”. Based on the principles of Mendelian genetics, he regarded randomly assigned genotypes as "natural randomization experiments" to evaluate the causal effect of a factor on a particular phenotypic trait.
Mendelian randomization (MR) is a statistical method based on whole-genome sequencing data(GWAS), which can effectively reduce bias and is used to reveal causality similar to randomized controlled trials (RCT). MR can be used to evaluate causal inference, using genetic variants as instrumental variables to represent specific exposures, infer causal relationships between exposures and outcomes, and transform phenotype-to-phenotype causal studies into genotype studies. The advantage is that an individual's genetic variation precedes the outcome of a disease, which eliminates confounding bias due to reverse causality. Modern bioinformatics techniques can measure genetic variation with high precision, which largely reduces the estimation bias caused by measurement errors.
Mendelian randomization has made remarkable progress in oncology and epidemiology, but further research is needed. Therefore, this research topic will focus on the recent advances in the use of Mendelian randomization methods to study the causal relationship between tumors and underlying pathogenic factors.
• Causal relationship between tumors and underlying pathogenic factors
• Application of Mendelian randomization
• Various types of tumors, in particular, the study of gut microbiota and tumors
• Advancement in oncology and epidemiology
• Anti-cancer therapy and anti-angiogenesis drugs
Mendelian randomization (MR) is a statistical method based on whole-genome sequencing data(GWAS), which can effectively reduce bias and is used to reveal causality similar to randomized controlled trials (RCT). MR can be used to evaluate causal inference, using genetic variants as instrumental variables to represent specific exposures, infer causal relationships between exposures and outcomes, and transform phenotype-to-phenotype causal studies into genotype studies. The advantage is that an individual's genetic variation precedes the outcome of a disease, which eliminates confounding bias due to reverse causality. Modern bioinformatics techniques can measure genetic variation with high precision, which largely reduces the estimation bias caused by measurement errors.
Mendelian randomization has made remarkable progress in oncology and epidemiology, but further research is needed. Therefore, this research topic will focus on the recent advances in the use of Mendelian randomization methods to study the causal relationship between tumors and underlying pathogenic factors.
• Causal relationship between tumors and underlying pathogenic factors
• Application of Mendelian randomization
• Various types of tumors, in particular, the study of gut microbiota and tumors
• Advancement in oncology and epidemiology
• Anti-cancer therapy and anti-angiogenesis drugs
Keywords: Mendelian randomization, Oncology, GWAS, randomized controlled trials, Phenotype, Genotype
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