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Gut microbiota
Original research
Long-term dietary patterns are associated with pro-inflammatory and anti-inflammatory features of the gut microbiome
  1. Laura A Bolte1,2,
  2. Arnau Vich Vila1,2,
  3. Floris Imhann1,2,
  4. Valerie Collij1,2,
  5. Ranko Gacesa1,2,
  6. Vera Peters1,
  7. Cisca Wijmenga2,
  8. Alexander Kurilshikov2,
  9. Marjo J E Campmans-Kuijpers1,
  10. Jingyuan Fu2,3,
  11. Gerard Dijkstra1,
  12. Alexandra Zhernakova2,
  13. Rinse K Weersma1
  1. 1 Department of Gastroenterology and Hepatology, University of Groningen and University Medical Centre Groningen, Groningen, The Netherlands
  2. 2 Department of Genetics, University of Groningen and University Medical Centre Groningen, Groningen, The Netherlands
  3. 3 Department of Pediatrics, University of Groningen and University Medical Centre Groningen, Groningen, The Netherlands
  1. Correspondence to Prof Dr Rinse K Weersma, Department of Gastroenterology and Hepatology, University of Groningen and University Medical Centre Groningen, P.O. Box 30.001, Groningen 9700 RB, The Netherlands; r.k.weersma{at}umcg.nl

Abstract

Objective The microbiome directly affects the balance of pro-inflammatory and anti-inflammatory responses in the gut. As microbes thrive on dietary substrates, the question arises whether we can nourish an anti-inflammatory gut ecosystem. We aim to unravel interactions between diet, gut microbiota and their functional ability to induce intestinal inflammation.

Design We investigated the relation between 173 dietary factors and the microbiome of 1425 individuals spanning four cohorts: Crohn’s disease, ulcerative colitis, irritable bowel syndrome and the general population. Shotgun metagenomic sequencing was performed to profile gut microbial composition and function. Dietary intake was assessed through food frequency questionnaires. We performed unsupervised clustering to identify dietary patterns and microbial clusters. Associations between diet and microbial features were explored per cohort, followed by a meta-analysis and heterogeneity estimation.

Results We identified 38 associations between dietary patterns and microbial clusters. Moreover, 61 individual foods and nutrients were associated with 61 species and 249 metabolic pathways in the meta-analysis across healthy individuals and patients with IBS, Crohn’s disease and UC (false discovery rate<0.05). Processed foods and animal-derived foods were consistently associated with higher abundances of Firmicutes, Ruminococcus species of the Blautia genus and endotoxin synthesis pathways. The opposite was found for plant foods and fish, which were positively associated with short-chain fatty acid-producing commensals and pathways of nutrient metabolism.

Conclusion We identified dietary patterns that consistently correlate with groups of bacteria with shared functional roles in both, health and disease. Moreover, specific foods and nutrients were associated with species known to infer mucosal protection and anti-inflammatory effects. We propose microbial mechanisms through which the diet affects inflammatory responses in the gut as a rationale for future intervention studies.

  • diet
  • intestinal microbiology
  • meta-analysis
  • inflammatory bowel disease
  • irritable bowel syndrome

Data availability statement

All relevant data supporting the key findings of this study are available within the article and the supplementary files. Raw metagenomic sequencing reads and extended phenotypic data are available from the European Genome-phenome Archive data repository: 1000 IBD cohort [EGAD00001004194] and LifeLines Deep cohort [EGAD00001001991]. Codes used for generating the microbial profiles are publicly available at:[https://github.com/WeersmaLabIBD/Microbiome/blob/master/Protocol_metagenomic_pipeline.md]. All statistical analysis scripts are written in R and can be found here: https://github.com/WeersmaLabIBD/Microbiome/blob/master/Diet_Microbiome.md.

https://creativecommons.org/licenses/by/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

https://doi.org/10.1136/gutjnl-2020-322670

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    Data availability statement

    All relevant data supporting the key findings of this study are available within the article and the supplementary files. Raw metagenomic sequencing reads and extended phenotypic data are available from the European Genome-phenome Archive data repository: 1000 IBD cohort [EGAD00001004194] and LifeLines Deep cohort [EGAD00001001991]. Codes used for generating the microbial profiles are publicly available at:[https://github.com/WeersmaLabIBD/Microbiome/blob/master/Protocol_metagenomic_pipeline.md]. All statistical analysis scripts are written in R and can be found here: https://github.com/WeersmaLabIBD/Microbiome/blob/master/Diet_Microbiome.md.

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    Supplementary materials

    Footnotes

    • LAB and AVV are joint first authors.

    • Contributors RKW designed the study. LAB and AVV performed analyses. LAB wrote the manuscript. LAB, AVV, FI and RKW gathered during the study. RG and AK provided statistical advice. AVV, FI, VC, VP, CW, AK, MJECK, JF, GD, AZ and RKW were involved in data collection and preparation and critically reviewed the manuscript.

    • Funding LAB and RKW are supported by a research grant from the Seerave Foundation. RG and RKW are supported by the collaborative TIMID project (LSHM18057-SGF) financed by the PPP allowance made available by Top Sector Life Sciences & Health to Samenwerkende Gezondheidsfondsen (SGF) to stimulate public–private partnerships and co-financing by health foundations that are part of the SGF. JF, AZ and AK are supported by the Gravitation grant ExposomeNL from the from the Dutch Organization for Scientific Research (Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO) (024.004.017). AZ is further supported by a European Research Council (ERC) Starting Grant (715772) and a NWO-VIDI grant (016.178.056). JF is supported by the NWO Gravitation Netherlands Organ-on-Chip Initiative (024.003.001) and the ERC Consolidator grant (101001678). JF and AZ are further supported by a grant from the Dutch Heart Foundation (CardioVasculair Onderzoek Nederland, CVON) (2018-27). CW is supported by the NWO Gravitation grant (024.003.001), a Spinoza award (NWO SPI 92-266) and a grant from the Netherlands’ Top Institute Food and Nutrition (GH001).

    • Competing interests RKW acted as consultant for Takeda and received unrestricted research grants from Takeda and Johnson and Johnson pharmaceuticals and speaker fees from AbbVie, MSD, Olympus and AstraZeneca. FI received a speaker fee from AbbVie. GD reports speakers’ fees from Janssen Pharmaceuticals, Takeda and Pfizer. MC received invited speaking fees from Takeda. No disclosures: All other authors have nothing to disclose.

    • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

    • Provenance and peer review Not commissioned; externally peer reviewed.