5/9/2023 0 Comments Lee vmd calculator![]() The analogy between randomized controlled trial and Mendelian randomization (A) and principle of Mendelian randomization (B). However, MR studies depend on three assumptions, and it is important to assess the plausibility of such assumptions to validate the results from MR studies. The increasing size and scope of genome-wide association studies (GWASs) to identify risk factors (exposures) and diseases (outcomes) has led to increased use of MR studies. The MR approach uses genetic variants linked to modifiable traits/exposures to identify causal associations with disease. Thus, the MR experiment resembles a RCT ( Figure 1). In MR, the random segregation of alleles (genes) separates them independently into exposed and controlled groups, which results in unmeasured confounding factors that are also distributed equally between two groups. One of the alternative approaches is to perform Mendelian randomization (MR) experiments that are based on Mendel’s independent assortment rule: each trait is inherited to the next generation independently of other traits. To deal with the confounders in observational studies and identify causal relationships, an alternative approach is needed. In addition, RCTs cannot be done often, because they can be costly, impractical, or even unethical. Associations found in observational studies, in many cases, do not reveal any relationship in RCTs. A randomized controlled trial (RCT) is widely recognized as the gold standard, which has the best possibility to establish a relationship between a risk factor and an outcome. Consequently, in observational studies, a link between the modifiable risk factor or exposure and outcome cannot be causal. Concluding causality from observational data, however, is troublesome, as observational studies conducted to identify correlations between modifiable exposures and disease outcomes often include confounding factors or reverse causation, which lead to misunderstood and biased findings. Understanding the causal role of risk factors to diseases is important to uncover the pathogenesis of disease and plan treatment strategy. Keywords: Mendelian randomization, Causality, Review The validity of results from MR studies depends on three assumptions that should be carefully checked and interpreted in the context of prior biological information. However, there are some limitations in MR analyses, and an awareness of these limitations is essential to interpret the results. MR approaches are increasingly being used to evaluate the causality of associations with risk factors, because well-performed MR studies can be a powerful method for exploring causality in complex diseases. ![]() Therefore, MR can make a substantial contribution to our understanding of complex disease etiology. MR can provide more credible estimates of the causal effect of a risk factor on an outcome than those obtained in observational studies by overcoming the limitations of observational studies. The MR technique uses genetic variants related to modifiable traits/exposures as tools to detect causal associations with outcomes. One of the alternatives is to perform Mendelian randomization (MR) experiments that are similar to RCTs in terms of study design. However, RCTs cannot always be performed, because they can be costly, impractical, or even unethical. A randomized controlled trial (RCT) is considered the gold standard, because it has the best possibility to establish a relationship between a risk factor and an outcome. Thus, in observational studies, the association between a risk factor and a disease of interest may not be causal. Abstract The inference of causality from observational evidence may be problematic, as observational studies frequently include confounding factors or reverse causation for the identification of associations between exposure and outcome.
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