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  • Host and gut microbial tryptophan metabolism and type 2 diabetes: an integrative analysis of host genetics, diet, gut microbiome and circulating metabolites in cohort studies

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Gut microbiota
Original research
Host and gut microbial tryptophan metabolism and type 2 diabetes: an integrative analysis of host genetics, diet, gut microbiome and circulating metabolites in cohort studies
  1. Qibin Qi1,2,
  2. Jun Li2,3,
  3. Bing Yu4,
  4. Jee-Young Moon1,
  5. Jin C Chai1,
  6. Jordi Merino5,6,
  7. Jie Hu7,
  8. Miguel Ruiz-Canela8,9,
  9. Casey Rebholz10,
  10. Zheng Wang1,
  11. Mykhaylo Usyk11,
  12. Guo-Chong Chen1,
  13. Bianca C Porneala12,
  14. Wenshuang Wang4,13,
  15. Ngoc Quynh Nguyen4,
  16. Elena V Feofanova4,
  17. Megan L Grove4,
  18. Thomas J Wang14,
  19. Robert E Gerszten15,16,
  20. Josée Dupuis17,
  21. Jordi Salas-Salvadó9,18,
  22. Wei Bao19,
  23. David L Perkins20,
  24. Martha L Daviglus20,
  25. Bharat Thyagarajan21,
  26. Jianwen Cai22,
  27. Tao Wang1,
  28. JoAnn E Manson3,23,
  29. Miguel A Martínez-González8,9,
  30. Elizabeth Selvin10,
  31. Kathryn M Rexrode7,
  32. Clary B Clish24,
  33. Frank B Hu25,
  34. James B Meigs6,12,
  35. Rob Knight26,
  36. Robert D Burk1,11,
  37. Eric Boerwinkle4,
  38. Robert C Kaplan1,27
  1. 1 Department of Epidemiology and Population Health, Yeshiva University Albert Einstein College of Medicine, Bronx, New York, USA
  2. 2 Department of Nutrtion, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
  3. 3 Department of Epidemiology, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
  4. 4 Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health, Houston, Texas, USA
  5. 5 Diabetes Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
  6. 6 Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
  7. 7 Division of Women's Health, Department of Medicine at Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
  8. 8 Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain
  9. 9 CIBER Fisiopatologıa de la Obesidad y Nutricion, Instituto de Salud Carlos III, Madrid, Spain
  10. 10 Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
  11. 11 Departments of Pediatrics, Microbiology and Immunology, and Gynecology and Women's Health, Yeshiva University Albert Einstein College of Medicine, Bronx, New York, USA
  12. 12 Division of General Internal Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
  13. 13 Department of Mathematics, University of Houston, Houston, Texas, USA
  14. 14 Department of Internal Medicine, The University of Texas Southwestern Medical Center, Dallas, Texas, USA
  15. 15 Programs in Metabolism and Medical & Population Genetics, Eli and Edythe L. Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
  16. 16 Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
  17. 17 Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
  18. 18 Human Nutrition Unit, Faculty of Medicine and Health Sciences, Universidad Rovira i Virgili Departamento de Medicina y Cirurgía, Reus, Spain
  19. 19 Department of Epidemiology, The University of Iowa College of Public Health, Iowa City, Iowa, USA
  20. 20 Institute of Minority Health Research, University of Illinois College of Medicine, Chicago, Illinois, USA
  21. 21 Department of Laboratory Medicine and Pathology, University of Minnesota Medical Center, Minneapolis, Minnesota, USA
  22. 22 Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
  23. 23 Division of Preventive Medicine, Department of Medicine at Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
  24. 24 Metabolomics Platform, Eli and Edythe L. Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
  25. 25 Channing Division of Network Medicine, Department of Medicine at Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
  26. 26 Department of Pediatrics, School of Medicine; Center for Microbiome Innovation, Department of Computer Science and Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
  27. 27 Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
  1. Correspondence to Dr Qibin Qi, Department of Epidemiology and Population Health, Yeshiva University Albert Einstein College of Medicine, Bronx, New York, USA; qibin.qi{at}einsteinmed.org

Abstract

Objective Tryptophan can be catabolised to various metabolites through host kynurenine and microbial indole pathways. We aimed to examine relationships of host and microbial tryptophan metabolites with incident type 2 diabetes (T2D), host genetics, diet and gut microbiota.

Method We analysed associations between circulating levels of 11 tryptophan metabolites and incident T2D in 9180 participants of diverse racial/ethnic backgrounds from five cohorts. We examined host genome-wide variants, dietary intake and gut microbiome associated with these metabolites.

Results Tryptophan, four kynurenine-pathway metabolites (kynurenine, kynurenate, xanthurenate and quinolinate) and indolelactate were positively associated with T2D risk, while indolepropionate was inversely associated with T2D risk. We identified multiple host genetic variants, dietary factors, gut bacteria and their potential interplay associated with these T2D-relaetd metabolites. Intakes of fibre-rich foods, but not protein/tryptophan-rich foods, were the dietary factors most strongly associated with tryptophan metabolites. The fibre-indolepropionate association was partially explained by indolepropionate-associated gut bacteria, mostly fibre-using Firmicutes. We identified a novel association between a host functional LCT variant (determining lactase persistence) and serum indolepropionate, which might be related to a host gene-diet interaction on gut Bifidobacterium, a probiotic bacterium significantly associated with indolepropionate independent of other fibre-related bacteria. Higher milk intake was associated with higher levels of gut Bifidobacterium and serum indolepropionate only among genetically lactase non-persistent individuals.

Conclusion Higher milk intake among lactase non-persistent individuals, and higher fibre intake were associated with a favourable profile of circulating tryptophan metabolites for T2D, potentially through the host–microbial cross-talk shifting tryptophan metabolism toward gut microbial indolepropionate production.

  • diabetes mellitus
  • dietary factors
  • genetics

Data availability statement

Data are available in a public, open access repository. Data are available on reasonable request. Anonymised individual participant data are available on reasonable request and with the agreement of the authors of original studies.Gut microbiome data in this study are deposited in QIITA, ID 11666 and EMBL-EBI ENA, ERP117287.

https://doi.org/10.1136/gutjnl-2021-324053

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    Data availability statement

    Data are available in a public, open access repository. Data are available on reasonable request. Anonymised individual participant data are available on reasonable request and with the agreement of the authors of original studies.Gut microbiome data in this study are deposited in QIITA, ID 11666 and EMBL-EBI ENA, ERP117287.

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    Footnotes

    • QQ, JL and BY contributed equally.

    • Correction notice This article has been corrected since it published Online First. The equal contributor statement has been added.

    • Contributors QQ: study concept and design; study supervision; obtained funding; acquisition of data; analysis and interpretation of data; drafting of the manuscript; critical revision of the manuscript for important intellectual content. JL: study concept and design; acquisition of data; analysis and interpretation of data; drafting of the manuscript; critical revision of the manuscript for important intellectual content; BY: study concept and design; obtained funding; acquisition of data; analysis and interpretation of data; critical revision of the manuscript for important intellectual content; J-YM, JC, JM, JH, MR-C, CR, ZW, MU, G-CC, BP, WW, QN, EVF and TW: analysis and interpretation of data; critical revision of the manuscript for important intellectual content; MG, TW, RG, JD, JSS, WB, DP, MD, BT, JC, JM, MAMG, ES, CC and JM: acquisition of data; critical revision of the manuscript for important intellectual content. KMR, FH, RB, RB, EB and RK: obtained funding; acquisition of data; critical revision of the manuscript for important intellectual content.

    • Funding This work is supported by R01-DK119268 (QQ) from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), R01-MD011389 (RK, RDB and RCK) from the National Institute on Minority Health and Health Disparities, and R01-HL060712 (QQ and FBH) from the National Heart, Lung and Blood Institute (NHLBI). Other funding sources for this study include UM1-HG008898 from the National Human Genome Research Institute; R01-HL140976, and R01-HL136266 from the NHLBI; and R01-DK120870, R01 DK126698 and the New York Regional Center for Diabetes Translation Research (P30DK111022) from NIDDK. Support for metabolomics data was graciously provided by the JLH Foundation (Houston, Texas). JL is supported by 9-17-CMF-011 from the American Diabetes Association (ADA); K99-DK122128 from NIDDK; and a pilot and feasibility grant from the NIDDK-funded Boston Nutrition Obesity Research Center (P30-DK046200). BY is supported by the American Heart Association (17SDG33661228); and R01-HL141824 and R01-HL142003 from NHLBI. JM and JD are supported by U01-DK078616 from NIDDK. JM is supported by a postdoctoral fellowship funded by the European Commission Horizon 2020 programme; Marie Skłodowska-Curie actions (H2020-MSCA-IF-2015-703787); and P30DK040561 from NIDDK. Funding and acknowledgment information for each participating studies is provided in online supplements.

    • Competing interests None declared.

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

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.