Lessons from Mendelian randomization studies on liver biomarkers: response to Abbasi
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چکیده
منابع مشابه
Mendelian randomization studies of biomarkers and type 2 diabetes.
Many biomarkers are associated with type 2 diabetes (T2D) risk in epidemiological observations. The aim of this study was to identify and summarize current evidence for causal effects of biomarkers on T2D. A systematic literature search in PubMed and EMBASE (until April 2015) was done to identify Mendelian randomization studies that examined potential causal effects of biomarkers on T2D. To rep...
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In Mendelian randomization (MR) studies, where genetic variants are used as proxy measures for an exposure trait of interest, obtaining adequate statistical power is frequently a concern due to the small amount of variation in a phenotypic trait that is typically explained by genetic variants. A range of power estimates based on simulations and specific parameters for two-stage least squares (2...
متن کاملRecent Developments in Mendelian Randomization Studies
Purpose of Review Mendelian randomization (MR) is a strategy for evaluating causality in observational epidemiological studies. MR exploits the fact that genotypes are not generally susceptible to reverse causation and confounding, due to their fixed nature and Mendel's First and Second Laws of Inheritance. MR has the potential to provide information on causality in many situations where random...
متن کاملMendelian randomization studies in coronary artery disease.
Epidemiological research over the last 50 years has discovered a plethora of biomarkers (including molecules, traits or other diseases) that associate with coronary artery disease (CAD) risk. Even the strongest association detected in such observational research precludes drawing conclusions about the causality underlying the relationship between biomarker and disease. Mendelian randomization (...
متن کاملAvoiding bias from weak instruments in Mendelian randomization studies.
BACKGROUND Mendelian randomization is used to test and estimate the magnitude of a causal effect of a phenotype on an outcome by using genetic variants as instrumental variables (IVs). Estimates of association from IV analysis are biased in the direction of the confounded, observational association between phenotype and outcome. The magnitude of the bias depends on the F-statistic for the stren...
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ژورنال
عنوان ژورنال: International Journal of Epidemiology
سال: 2017
ISSN: 0300-5771,1464-3685
DOI: 10.1093/ije/dyx064