Evidence map›Paper›PMID 37845826›Full record

ArticleObesity (Silver Spring, Md.)2023

Challenges in undertaking nonlinear Mendelian randomization.

Kaitlin H Wade, Fergus W Hamilton, David Carslake, Naveed Sattar, George Davey Smith, Nicholas J Timpson

Abstract read
In one paragraph

Article in Obesity (Silver Spring, Md.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  14. Detecting Non-linear Dependence through Genome Wide Analysis.bioRxiv : the preprint server for biology · 2025
    Article
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  16. Observational
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  19. Causal inference in health and disease: a review of the principles and applications of Mendelian randomization.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2024
    Review
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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

6 authors.

Kaitlin H WadeMedical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK.ORCID 0000-0003-3362-6280
Fergus W HamiltonMedical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK.ORCID 0000-0002-9760-4059
David CarslakeMedical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK.ORCID 0000-0003-2916-4546
Naveed SattarInstitute of Cardiovascular and Medical Sciences, British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK.ORCID 0000-0002-1604-2593
George Davey SmithMedical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK.ORCID 0000-0002-1407-8314
Nicholas J TimpsonMedical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK.ORCID 0000-0002-7141-9189

Funding

Cancer Research UK RCCPDF\100007Medical Research Council MC_UU_00011/1Medical Research Council MC_UU_00032/1Wellcome TrustWellcome Trust 202802/Z/16/ZWellcome Trust 222894/Z/21/Z
6 · The paper itself

Abstract

Mendelian randomization (MR) is a widely used method that exploits the unique properties of germline genetic variation to strengthen causal inference in relationships between exposures and outcomes. Nonlinear MR allows estimation of the shape of these relationships. In a previous paper, the authors applied linear and nonlinear MR to estimate the effect of BMI on mortality in UK Biobank, providing evidence for a J-shaped association. However, it is now clear that there are problems with widely used nonlinear MR methods, which draws attention to the likely erroneous nature of the conclusions regarding the shapes of several explored relationships. Here, the authors explore the utility and likely biases of these nonlinear MR methods with the use of a negative control design. Although there remains good evidence for a causal effect of higher BMI increasing the risk of mortality, the pattern of this association across different levels of BMI requires further characterization.

Indexed as

Genome-Wide Association StudyMendelian Randomization AnalysisBody Mass IndexCausality

Identifiers

PMID37845826
PMCPMC7615556

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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.