Reporting methodological issues of the mendelian randomization studies in health and medical research: a systematic

Shabab Noor Islam1, Tanvir Ahammed1, Aniqua Anjum1

  • 1Department of Statistics, Shahjalal University of Science and Technology, 3114, Sylhet, Bangladesh.

Abstract

Insights

Mendelian randomization (MR) studies often lack proper reporting of instrumental variable (IV) assumptions. This review highlights common issues in genetic risk score (GRS) based MR studies, potentially misdirecting findings.

Area of Science:

  • Epidemiology
  • Genetics
  • Biostatistics

Background:

  • Mendelian randomization (MR) studies utilize genetic risk scores (GRS) as instrumental variables (IV) to address unmeasured confounding in observational research.
  • Despite the increasing use of MR, there is a notable scarcity in the reporting of methodological details and potential issues.
  • This systematic review addresses the need for improved transparency in MR study reporting.

Purpose of the Study:

  • To systematically review published Mendelian randomization (MR) studies.
  • To identify and categorize common reporting problems related to the assumptions of instrumental variables (IV).
  • To assess the methodological rigor in the application of GRS in MR analyses.

Main Methods:

  • A systematic review of clinical articles published between 2009 and 2019 was conducted.
  • Searches were performed across PubMed, Scopus, and Embase databases.
  • Ninety-seven MR studies were included, adhering to PRISMA guidelines, with data extraction on assumption verification, statistical methods, and sensitivity analyses.

Main Results:

  • Only 68% of studies empirically verified the relevance assumption, with 41.2% reporting appropriate statistical tests (R2, F-test).
  • Theoretical justifications for the second and third IV assumptions were clearly stated and discussed in only 35.1% of studies.
  • Reporting varied for estimation methods (two-stage least square: 30.9%, Wald estimator: 11.3%) and sensitivity analyses (44.3%).

Conclusions:

  • Incompleteness in justifying instrumental variable assumptions is a prevalent issue in MR studies.
  • This lack of rigorous reporting may lead to misinterpretation and misdirection of research findings.
  • Enhanced transparency and adherence to reporting guidelines are crucial for the validity of MR research.

Related Concept Videos

Randomized Experiments01:13

Randomized Experiments

The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
8.1K
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.5K
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

Body:Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to...
5
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
191
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
765
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
172