Evidence map›Paper›PMID 34099926›Full record

ArticleNature metabolism2021

Impact of dietary carbohydrate type and protein-carbohydrate interaction on metabolic health.

Jibran A Wali, Annabelle J Milner, Alison W S Luk, Tamara J Pulpitel, Tim Dodgson, Harrison J W Facey, Devin Wahl, Melkam A Kebede, Alistair M Senior, Mitchell A Sullivan and 16 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature metabolism, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
7.6field-weighted citation impact, top 2% 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

48 citing papers in PubMed, 82 citations in OpenAlex.

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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

26 authors at 2 institutions in 1 country.

Jibran A WaliCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia. jibran.wali@sydney.edu.au.ORCID http://orcid.org/0000-0002-8524-5773
Annabelle J MilnerCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
Alison W S LukCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0003-1221-7023
Tamara J PulpitelCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
Tim DodgsonCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
Harrison J W FaceyCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
Devin WahlCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
Melkam A KebedeCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0001-9686-7378
Alistair M SeniorCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0001-9805-7280
Mitchell A SullivanMater Research Institute, The University of Queensland, Translational Research Institute, Brisbane, Queensland, Australia.
Amanda E BrandonCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
Belinda YauCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0003-2303-7343
Glen P LockwoodThe University of Sydney, ANZAC Research Institute, Sydney, New South Wales, Australia.
Yen Chin KoayCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
Rosilene RibeiroCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0001-8312-185X
Samantha M Solon-BietCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0003-0608-958X
Kim S Bell-AndersonCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0002-7761-3441
John F O'SullivanCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
Laurence MaciaCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0003-0835-851X
Josephine M ForbesMater Research Institute, The University of Queensland, Translational Research Institute, Brisbane, Queensland, Australia.ORCID http://orcid.org/0000-0002-5595-8174
Gregory J CooneyCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
Victoria C CoggerCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0002-6346-9928
Andrew HolmesCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
David RaubenheimerCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.
David G Le CouteurCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0002-4227-5817
Stephen J SimpsonCharles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia. stephen.simpson@sydney.edu.au.ORCID http://orcid.org/0000-0003-0256-7687
The University of Sydney · AUTranslational Research Institute · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reduced protein intake, through dilution with carbohydrate, extends lifespan and improves mid-life metabolic health in animal models. However, with transition to industrialised food systems, reduced dietary protein is associated with poor health outcomes in humans. Here we systematically interrogate the impact of carbohydrate quality in diets with varying carbohydrate and protein content. Studying 700 male mice on 33 isocaloric diets, we find that the type of carbohydrate and its digestibility profoundly shape the behavioural and physiological responses to protein dilution, modulate nutrient processing in the liver and alter the gut microbiota. Low (10%)-protein, high (70%)-carbohydrate diets promote the healthiest metabolic outcomes when carbohydrate comprises resistant starch (RS), yet the worst outcomes were with a 50:50 mixture of monosaccharides fructose and glucose. Our findings could explain the disparity between healthy, high-carbohydrate diets and the obesogenic impact of protein dilution by glucose-fructose mixtures associated with highly processed diets.

Indexed as

DietEnergy MetabolismHomeostasisAnimalsDietary CarbohydratesDietary ProteinsGlucoseHealth StatusMaleMiceObesityStarchDietary CarbohydratesDietary ProteinsGlucoseStarch

Identifiers

PMID34099926
OpenAlexW3166853063

What OpenQuestion holds

Textmetadata
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.