Evidence map›Paper›PMID 32821701›Full record

ReviewJournal of lipid and atherosclerosis2019

Mendelian Randomization Analysis in Observational Epidemiology.

Kwan Lee, Chi-Yeon Lim

Open access · diamondAbstract readReview
In one paragraph

Review in Journal of lipid and atherosclerosis, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 1 pooled it
3.4field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

82 citing papers in PubMed, 1 synthesis or guideline pooled it, 162 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Genetic Susceptibility toLife (Basel, Switzerland) · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Shared genetic associations between CHAInternational journal of cardiology. Cardiovascular risk and prevention · 2025
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

22 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Kwan LeeDepartment of Preventive Medicine, Dongguk University College of Medicine, Goyang, Korea.ORCID https://orcid.org/0000-0003-2554-4170
Chi-Yeon LimDepartment of Biostatistics, Dongguk University College of Medicine, Goyang, Korea.ORCID https://orcid.org/0000-0003-0178-6976
Dongguk University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mendelian randomization (MR) in epidemiology is the use of genetic variants as instrumental variables (IVs) in non-experimental design to make causality of a modifiable exposure on an outcome or disease. It assesses the causal effect between risk factor and a clinical outcome. The main reason to approach MR is to avoid the problem of residual confounding. There is no association between the genotype of early pregnancy and the disease, and the genotype of an individual cannot be changed. For this reason, it results with randomly assigned case-control studies can be set by regressing the measurements. IVs in MR are used genetic variants for estimating the causality. Usually an outcome is a disease and an exposure is risk factor, intermediate phenotype which may be a biomarker. The choice of the genetic variable as IV (Z) is essential to a successful in MR analysis. MR is named 'Mendelian deconfounding' as it gives to estimate of the causality free from biases due to confounding (C). To estimate unbiased estimation of the causality of the exposure (X) on the clinically relevant outcome (Y), Z has the 3 core assumptions (A1-A3). A1) Z is independent of C; A2) Z is associated with X; and A3) Z is independent of Y given X and C; The purpose of this review provides an overview of the MR analysis and is to explain that using an IV is proposed as an alternative statistical method to estimate causal effect of exposure and outcome under controlling for a confounder.

Indexed as

CausalityConfounding factorsGenetic epidemiologyInstrumentMendelian randomization analysis

Identifiers

PMID32821701
PMCPMC7379124
OpenAlexW2971891034

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.