Evidence map›Paper›PMID 35653391›Full record

ArticlePLoS genetics2022

Using genetic variation to disentangle the complex relationship between food intake and health outcomes.

Nicola Pirastu, Ciara McDonnell, Eryk J Grzeszkowiak, Ninon Mounier, Fumiaki Imamura, Jordi Merino, Felix R Day, Jie Zheng, Nele Taba, Maria Pina Concas and 11 more

Abstract read
In one paragraph

Article in PLoS genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 3 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

51 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

21 authors.

Nicola PirastuCentre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom.ORCID 0000-0002-5363-3886
Ciara McDonnellCentre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom.
Eryk J GrzeszkowiakCentre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom.ORCID 0000-0002-6550-6366
Ninon MounierCentre for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.ORCID 0000-0001-6663-5402
Fumiaki ImamuraMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom.ORCID 0000-0002-6841-8396
Jordi MerinoDiabetes Unit and Centre for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America.ORCID 0000-0001-8312-1438
Felix R DayMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom.ORCID 0000-0003-3789-7651
Jie ZhengMRC Integrative Epidemiology Unit, Bristol Medical School, Bristol, United Kingdom.ORCID 0000-0002-6623-6839
Nele TabaInstitute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.ORCID 0000-0003-1953-2819
Maria Pina ConcasInstitute for Maternal and Child Health-IRCCS "Burlo Garofolo", Trieste, Italy.ORCID 0000-0003-3598-2537
Linda RepettoCentre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom.ORCID 0000-0002-7901-4549
Katherine A KentistouCentre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom.ORCID 0000-0002-5816-664X
Antonietta RobinoInstitute for Maternal and Child Health-IRCCS "Burlo Garofolo", Trieste, Italy.ORCID 0000-0003-2152-2353
Tõnu EskoEstonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.ORCID 0000-0003-1982-6569
Peter K JoshiCentre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom.ORCID 0000-0002-6361-5059
Krista FischerInstitute of Mathematics and Statistics, University of Tartu, Tartu, Estonia.ORCID 0000-0002-3521-0599
Ken K OngMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom.ORCID 0000-0003-4689-7530
Tom R GauntMRC Integrative Epidemiology Unit, Bristol Medical School, Bristol, United Kingdom.ORCID 0000-0003-0924-3247
Zoltán KutalikCentre for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.
John R B PerryMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom.
James F WilsonCentre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom.ORCID 0000-0001-5751-9178

Funding

ROLE OF DIETARY CONSTITUENTS ON GENE EXPRESSION IN INTESTINAL EPITHELIUMP30DK040561 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI Elizabeth Austen Lawson, Takara Leah Stanley · 1994 to 2026
$31.6M
Cancer Research UK 14136Medical Research Council G0401527Medical Research Council G1000143Medical Research Council MCPC_13048Medical Research Council MC_PC_17228Medical Research Council MC_QA137853Medical Research Council MC_UU_00006/1Medical Research Council MC_UU_00006/2Medical Research Council MC_UU_00006/3Medical Research Council MC_UU_00007/10Medical Research Council MC_UU_00011/4Medical Research Council MC-UU_12015/1Medical Research Council MC_UU_12015/1Medical Research Council MC_UU_12015/2Medical Research Council MC_UU_12015/5Medical Research Council MR/N003284/1NIDDK NIH HHS P30 DK040561Wellcome TrustWellcome Trust 074548
6 · The paper itself

Abstract

Diet is considered as one of the most important modifiable factors influencing human health, but efforts to identify foods or dietary patterns associated with health outcomes often suffer from biases, confounding, and reverse causation. Applying Mendelian randomization in this context may provide evidence to strengthen causality in nutrition research. To this end, we first identified 283 genetic markers associated with dietary intake in 445,779 UK Biobank participants. We then converted these associations into direct genetic effects on food exposures by adjusting them for effects mediated via other traits. The SNPs which did not show evidence of mediation were then used for MR, assessing the association between genetically predicted food choices and other risk factors, health outcomes. We show that using all associated SNPs without omitting those which show evidence of mediation, leads to biases in downstream analyses (genetic correlations, causal inference), similar to those present in observational studies. However, MR analyses using SNPs which have only a direct effect on the exposure on food exposures provided unequivocal evidence of causal associations between specific eating patterns and obesity, blood lipid status, and several other risk factors and health outcomes.

Indexed as

EatingGenetic VariationCausalityHumansOutcome Assessment, Health CareRisk Factors

Identifiers

PMID35653391
PMCPMC9162356

What OpenQuestion holds

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LicenceCC BY
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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.