Mendelian randomization, a method for inferring causal relationships in observational studies and an alternative to clinical trial studies: a brief report

Background: Mendelian randomization (MR) is a new generation in the statistical method that uses genetic variants as instrumental variables in data from non-experimental studies to evaluate and estimate the causal effects of risk factors. Methods: The weakness of observational studies to detect caus...

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Main Authors: Mahdi Akbarzadeh, Danial Habibi, Goodarz Kolifarhood, Mohammad Bidkhori, Fereidoun Azizi, Maryam S. Daneshpour
Format: Article
Language:fas
Published: Tehran University of Medical Sciences 2023-01-01
Series:Tehran University Medical Journal
Subjects:
Online Access:http://tumj.tums.ac.ir/article-1-12186-en.html
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author Mahdi Akbarzadeh
Danial Habibi
Goodarz Kolifarhood
Mohammad Bidkhori
Fereidoun Azizi
Maryam S. Daneshpour
author_facet Mahdi Akbarzadeh
Danial Habibi
Goodarz Kolifarhood
Mohammad Bidkhori
Fereidoun Azizi
Maryam S. Daneshpour
author_sort Mahdi Akbarzadeh
collection DOAJ
description Background: Mendelian randomization (MR) is a new generation in the statistical method that uses genetic variants as instrumental variables in data from non-experimental studies to evaluate and estimate the causal effects of risk factors. Methods: The weakness of observational studies to detect causality, the difficulties of conducting clinical trials, the dramatic advancement of Genome-Wide Association Studies (GWAS) have led to the emergence of a new type of study called MR. It is increasingly being used to determine causality MR is an approach based on meta-analysis methods. The main idea of the MR is based on using the instrument variable (IV) to find the causality between exposure and outcome. This variable does not need to adjust the confounding effects found in observational studies. Results: Data for this study were collected from the beginning of January 2003 to October 2020 in PubMed. Our results showed that MR has an increasing trend. The data used in MR includes summarized statistical data, individual-level data, and meta-analysis. Choosing the suitable IV is essential to successfully conduct an MR. For an unbiased estimate, three main hypotheses should be considered: 1) The IV has a strong relationship with the desired exposure (i.e., potential risk factor), 2) The IV is not related to the confounding variable, and 3) The IV is not directly related to the outcome and should only relate to the outcome through exposure. If these conditions are not met, one solution is to use robust methods. Besides, this research introduced the study designs, estimation methods, limitations, software packages, and some applications of MR in medical research. Conclusion: When we seek to find a causal relationship, but it is not possible to use a clinical trial as a standard method, the MR design can be used in observational studies. Therefore, it is possible to obtain causal relationships between exposure and outcome using the MR.
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spelling doaj.art-33a5248928504d42a9abd6409c4e247e2023-04-24T08:35:01ZfasTehran University of Medical SciencesTehran University Medical Journal1683-17641735-73222023-01-018011908915Mendelian randomization, a method for inferring causal relationships in observational studies and an alternative to clinical trial studies: a brief reportMahdi Akbarzadeh0Danial Habibi1Goodarz Kolifarhood2Mohammad Bidkhori3Fereidoun Azizi4Maryam S. Daneshpour5 Cellular and Molecular Endocrine Research Center, University of Medical Sciences, Tehran, Iran. Cellular and Molecular Endocrine Research Center, University of Medical Sciences, Tehran, Iran. Cellular and Molecular Endocrine Research Center, University of Medical Sciences, Tehran, Iran. Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. Endocrine Research Center, University of Medical Sciences, Tehran, Iran. Cellular and Molecular Endocrine Research Center, University of Medical Sciences, Tehran, Iran. Background: Mendelian randomization (MR) is a new generation in the statistical method that uses genetic variants as instrumental variables in data from non-experimental studies to evaluate and estimate the causal effects of risk factors. Methods: The weakness of observational studies to detect causality, the difficulties of conducting clinical trials, the dramatic advancement of Genome-Wide Association Studies (GWAS) have led to the emergence of a new type of study called MR. It is increasingly being used to determine causality MR is an approach based on meta-analysis methods. The main idea of the MR is based on using the instrument variable (IV) to find the causality between exposure and outcome. This variable does not need to adjust the confounding effects found in observational studies. Results: Data for this study were collected from the beginning of January 2003 to October 2020 in PubMed. Our results showed that MR has an increasing trend. The data used in MR includes summarized statistical data, individual-level data, and meta-analysis. Choosing the suitable IV is essential to successfully conduct an MR. For an unbiased estimate, three main hypotheses should be considered: 1) The IV has a strong relationship with the desired exposure (i.e., potential risk factor), 2) The IV is not related to the confounding variable, and 3) The IV is not directly related to the outcome and should only relate to the outcome through exposure. If these conditions are not met, one solution is to use robust methods. Besides, this research introduced the study designs, estimation methods, limitations, software packages, and some applications of MR in medical research. Conclusion: When we seek to find a causal relationship, but it is not possible to use a clinical trial as a standard method, the MR design can be used in observational studies. Therefore, it is possible to obtain causal relationships between exposure and outcome using the MR.http://tumj.tums.ac.ir/article-1-12186-en.htmlcausalitygeneticsmedical researchmendelian randomizationobservational study.
spellingShingle Mahdi Akbarzadeh
Danial Habibi
Goodarz Kolifarhood
Mohammad Bidkhori
Fereidoun Azizi
Maryam S. Daneshpour
Mendelian randomization, a method for inferring causal relationships in observational studies and an alternative to clinical trial studies: a brief report
Tehran University Medical Journal
causality
genetics
medical research
mendelian randomization
observational study.
title Mendelian randomization, a method for inferring causal relationships in observational studies and an alternative to clinical trial studies: a brief report
title_full Mendelian randomization, a method for inferring causal relationships in observational studies and an alternative to clinical trial studies: a brief report
title_fullStr Mendelian randomization, a method for inferring causal relationships in observational studies and an alternative to clinical trial studies: a brief report
title_full_unstemmed Mendelian randomization, a method for inferring causal relationships in observational studies and an alternative to clinical trial studies: a brief report
title_short Mendelian randomization, a method for inferring causal relationships in observational studies and an alternative to clinical trial studies: a brief report
title_sort mendelian randomization a method for inferring causal relationships in observational studies and an alternative to clinical trial studies a brief report
topic causality
genetics
medical research
mendelian randomization
observational study.
url http://tumj.tums.ac.ir/article-1-12186-en.html
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