Evidence map›Paper›PMID 35776947›Full record

ArticleAdvances in nutrition (Bethesda, Md.)2022

Perspective: Leveraging the Gut Microbiota to Predict Personalized Responses to Dietary, Prebiotic, and Probiotic Interventions.

Sean M Gibbons, Thomas Gurry, Johanna W Lampe, Anirikh Chakrabarti, Veerle Dam, Amandine Everard, Almudena Goas, Gabriele Gross, Michiel Kleerebezem, Jonathan Lane and 9 more

Abstract read
In one paragraph

Article in Advances in nutrition (Bethesda, Md.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing 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

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

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3 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

19 authors.

Sean M GibbonsInstitute for Systems Biology, Seattle, WA, USA.ORCID 0000-0002-8724-7916
Thomas GurryPharmaceutical Biochemistry group, School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.
Johanna W LampePublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Anirikh ChakrabartiCargill R&D Center Europe, Vilvoorde, Belgium.
Veerle DamSensus BV (Royal Cosun), Roosendaal, The Netherlands.
Amandine EverardMetabolism and Nutrition Research Group, Louvain Drug Research Institute, Walloon Excellence in Life Sciences and BIOtechnology (WELBIO), UCLouvain, Université Catholique de Louvain, Brussels, Belgium.
Almudena GoasDepartment of Food, Nutrition, and Exercise Sciences, University of Surrey, Guildford, United Kingdom.
Gabriele GrossMedical and Scientific Affairs, Reckitt| Mead Johnson Nutrition Institute, Nijmegen, The Netherlands.
Michiel KleerebezemHost Microbe Interactomics Group, Wageningen University & Research, Wageningen, The Netherlands.
Jonathan LaneHealth and Happiness Group, H&H Research, Cork, Ireland.
Johanna MaukonenIFF Health & Biosciences, Kantvik, Finland.
Ana Lucia Barretto PennaDepartment of Food Engineering and Technology, São Paulo State University, São José do Rio Preto, Brazil.
Bruno PotYakult Europe BV, Almere, The Netherlands.
Ana M ValdesNottingham NIHR Biomedical Research Centre at the School of Medicine, University of Nottingham, Nottingham, United Kingdom.
Gemma WaltonFood and Nutritional Sciences, University of Reading, Reading, United Kingdom.
Adrienne WeissYili Innovation Center Europe, Wageningen, The Netherlands.
Yoghatama Cindya ZanzerBENEO-Institute/Südzucker Group, Obrigheim/Pfalz, Germany.
Naomi V VenletInternational Life Sciences Institute, European Branch, Brussels, Belgium.
Michela MianiInternational Life Sciences Institute, European Branch, Brussels, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Humans often show variable responses to dietary, prebiotic, and probiotic interventions. Emerging evidence indicates that the gut microbiota is a key determinant for this population heterogeneity. Here, we provide an overview of some of the major computational and experimental tools being applied to critical questions of microbiota-mediated personalized nutrition and health. First, we discuss the latest advances in in silico modeling of the microbiota-nutrition-health axis, including the application of statistical, mechanistic, and hybrid artificial intelligence models. Second, we address high-throughput in vitro techniques for assessing interindividual heterogeneity, from ex vivo batch culturing of stool and continuous culturing in anaerobic bioreactors, to more sophisticated organ-on-a-chip models that integrate both host and microbial compartments. Third, we explore in vivo approaches for better understanding of personalized, microbiota-mediated responses to diet, prebiotics, and probiotics, from nonhuman animal models and human observational studies, to human feeding trials and crossover interventions. We highlight examples of existing, consumer-facing precision nutrition platforms that are currently leveraging the gut microbiota. Furthermore, we discuss how the integration of a broader set of the tools and techniques described in this piece can generate the data necessary to support a greater diversity of precision nutrition strategies. Finally, we present a vision of a precision nutrition and healthcare future, which leverages the gut microbiota to design effective, individual-specific interventions.

Indexed as

Gastrointestinal MicrobiomeProbioticsAnimalsArtificial IntelligenceDietHumansPrebioticsPrebioticsdietmicrobiomemicrobiotapersonalized healthcarepersonalized nutritionprebioticprecision healthcareprecision nutritionprobiotic

Identifiers

PMID35776947
PMCPMC9526856

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.