Evidence map›Paper›PMID 32048336›Full record

ArticleGenetic epidemiology2020

Power calculation for the general two-sample Mendelian randomization analysis.

Lu Deng, Han Zhang, Kai Yu

Open access · greenAbstract read
In one paragraph

Article in Genetic epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 6 pooled it
4.3field-weighted citation impact, top 6% 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

26 citing papers in PubMed, 6 syntheses or guidelines pooled it, 39 citations in OpenAlex.

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  14. Introduction to Mendelian randomization.Annals of clinical epidemiology · 2025
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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

3 authors at 1 institution in 1 country.

Lu DengDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland.
Han ZhangDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland.
Kai YuDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland.ORCID 0000-0002-5337-137X
National Cancer Institute · US

Funding

Intramural NIH HHS Z99 CA999999
6 · The paper itself

Abstract

Mendelian randomization (MR) study has become a powerful approach to assess the potential causal effect of a risk exposure on an outcome. Most current MR studies are conducted under the two-sample setting by combining summary data from two separate genome-wide association studies (GWAS), with one providing measures on associations between genetic markers and the risk exposure, and the other on associations between genetic markers and the outcome. We develop a power calculation procedure for the general two-sample MR study, allowing for the use of multiple genetic markers, and shared participants between the two GWAS. This procedure requires a few easy-to-interpret parameters and is validated through extensive simulation studies.

Indexed as

Mendelian Randomization AnalysisFemaleGenome-Wide Association StudyHumansMaleModels, GeneticObesitygenome-wide association studiesMendelian randomizationpower calculationtwo-stage least squares estimator

Identifiers

PMID32048336
PMCPMC8766247
OpenAlexW3006234351

What OpenQuestion holds

Textmetadata
LicenceTDM
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.