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Cardiometabolic health, diet and the gut microbiome: a meta-omics perspective

Nature Medicine volume 29, pages 551–561 (2023)Cite this article

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Abstract

Cardiometabolic diseases have become a leading cause of morbidity and mortality globally. They have been tightly linked to microbiome taxonomic and functional composition, with diet possibly mediating some of the associations described. Both the microbiome and diet are modifiable, which opens the way for novel therapeutic strategies. High-throughput omics techniques applied on microbiome samples (meta-omics) hold the unprecedented potential to shed light on the intricate links between diet, the microbiome, the metabolome and cardiometabolic health, with a top-down approach. However, effective integration of complementary meta-omic techniques is an open challenge and their application on large cohorts is still limited. Here we review meta-omics techniques and discuss their potential in this context, highlighting recent large-scale efforts and the novel insights they provided. Finally, we look to the next decade of meta-omics research and discuss various translational and clinical pathways to improving cardiometabolic health.

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Fig. 1: The intricate, multidirectional relationship between diet, lifestyle, the gut microbiome and the metabolome and their influence on CMH.
Fig. 2: Metabolite trafficking and their detection with metabolomics.

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References

  1. Mathers, C. D. & Loncar, D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med. 3, e442 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  2. National Academies of Sciences, Engineering, and Medicine et al. in High and Rising Mortality Rates Among Working-Age Adults Ch. 9 (National Academies Press, 2021).

  3. Jagannathan, R., Patel, S. A., Ali, M. K. & Narayan, K. M. V. Global updates on cardiovascular disease mortality trends and attribution of traditional risk factors. Curr. Diab. Rep. 19, 44 (2019).

    Article  PubMed  Google Scholar 

  4. Korecka, A. & Arulampalam, V. The gut microbiome: scourge, sentinel or spectator? J. Oral Microbiol. 4, https://doi.org/10.3402/jom.v4i0.9367 (2012).

  5. Tang, W. H. W. & Hazen, S. L. The gut microbiome and its role in cardiovascular diseases. Circulation 135, 1008–1010 (2017).

    Article  PubMed  Google Scholar 

  6. Menni, C. et al. Gut microbial diversity is associated with lower arterial stiffness in women. Eur. Heart J. 39, 2390–2397 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Nogal, A., Valdes, A. M. & Menni, C. The role of short-chain fatty acids in the interplay between gut microbiota and diet in cardio-metabolic health. Gut Microbes 13, 1–24 (2021).

    Article  PubMed  Google Scholar 

  8. Hansen, T. H., Gøbel, R. J., Hansen, T. & Pedersen, O. The gut microbiome in cardio-metabolic health. Genome Med. 7, 33 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Jardon, K. M., Canfora, E. E., Goossens, G. H. & Blaak, E. E. Dietary macronutrients and the gut microbiome: a precision nutrition approach to improve cardiometabolic health. Gut 71, 1214–1226 (2022).

    Article  PubMed  Google Scholar 

  10. Wan, Y. et al. Contribution of diet to gut microbiota and related host cardiometabolic health: diet–gut interaction in human health. Gut Microbes 11, 603–609 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Karlsson, F. H. et al. Gut metagenome in European women with normal, impaired and diabetic glucose control. Nature 498, 99–103 (2013).

    Article  CAS  PubMed  Google Scholar 

  12. Talmor-Barkan, Y. et al. Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease. Nat. Med. 28, 295–302 (2022).

    Article  CAS  PubMed  Google Scholar 

  13. Sumida, K. et al. Circulating microbiota in cardiometabolic disease. Front. Cell. Infect. Microbiol. 12, 892232 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Brunius, C., Shi, L. & Landberg, R. Metabolomics for improved understanding and prediction of cardiometabolic diseases—recent findings from human studies. Curr. Nutr. Rep. 4, 348–364 (2015).

    Article  CAS  Google Scholar 

  15. Johnson, M. Diet and nutrition: implications to cardiometabolic health. J. Cardiol. Cardiovasc. Sci. 3, 4–9 (2019).

  16. Doran, S. et al. Multi-omics approaches for revealing the complexity of cardiovascular disease. Brief. Bioinformatics 22, bbab061 (2021).

    Article  PubMed  Google Scholar 

  17. Joshi, A., Rienks, M., Theofilatos, K. & Mayr, M. Systems biology in cardiovascular disease: a multiomics approach. Nat. Rev. Cardiol. 18, 313–330 (2020).

    Article  PubMed  Google Scholar 

  18. Abu-Ali, G. S. et al. Metatranscriptome of human faecal microbial communities in a cohort of adult men. Nat. Microbiol. 3, 356–366 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Schirmer, M. et al. Dynamics of metatranscription in the inflammatory bowel disease gut microbiome. Nat. Microbiol. 3, 337–346 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Zierer, J. et al. The fecal metabolome as a functional readout of the gut microbiome. Nat. Genet. 50, 790–795 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Quince, C., Walker, A. W., Simpson, J. T., Loman, N. J. & Segata, N. Shotgun metagenomics, from sampling to analysis. Nat. Biotechnol. 35, 833–844 (2017).

    Article  CAS  PubMed  Google Scholar 

  22. Martinez, K. B., Leone, V. & Chang, E. B. Microbial metabolites in health and disease: navigating the unknown in search of function. J. Biol. Chem. 292, 8553–8559 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Douglas, G. M. et al. PICRUSt2 for prediction of metagenome functions. Nat. Biotechnol. 38, 685–688 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Shakya, M., Lo, C.-C. & Chain, P. S. G. Advances and challenges in metatranscriptomic analysis. Front. Genet. 10, 904 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Valles-Colomer, M. et al. Meta-omics in inflammatory bowel disease research: applications, challenges, and guidelines. J. Chrons Colitis 10, 735–746 (2016).

    Article  Google Scholar 

  26. Kleiner, M. Metaproteomics: much more than measuring gene expression in microbial communities. mSystems 4, e00115-19 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Roberts, L. D., Souza, A. L., Gerszten, R. E. & Clish, C. B. Targeted metabolomics. Curr. Protoc. Mol. Biol. 98, 30.2.1–30.2.24 (2012).

    Article  Google Scholar 

  28. Menni, C., Zierer, J., Valdes, A. M. & Spector, T. D. Mixing omics: combining genetics and metabolomics to study rheumatic diseases. Nat. Rev. Rheumatol. 13, 174–181 (2017).

    Article  CAS  PubMed  Google Scholar 

  29. Kuleš, J. et al. Combined untargeted and targeted metabolomics approaches reveal urinary changes of amino acids and energy metabolism in canine babesiosis with different levels of kidney function. Front. Microbiol. 12, 715701 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Hollywood, K., Brison, D. R. & Goodacre, R. Metabolomics: current technologies and future trends. Proteomics 6, 4716–4723 (2006).

    Article  CAS  PubMed  Google Scholar 

  31. Linnarsson, S. & Teichmann, S. A. Single-cell genomics: coming of age. Genome Biol. 17, 97 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Pasolli, E. et al. Extensive unexplored human microbiome diversity revealed by over 150,000 genomes from metagenomes spanning age, geography, and lifestyle. Cell 176, 649–662.e20 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Almeida, A. et al. A unified catalog of 204,938 reference genomes from the human gut microbiome. Nat. Biotechnol. 39, 105–114 (2021).

    Article  CAS  PubMed  Google Scholar 

  34. Lloréns-Rico, V., Simcock, J. A., Huys, G. R. B. & Raes, J. Single-cell approaches in human microbiome research. Cell 185, 2725–2738 (2022).

    Article  PubMed  Google Scholar 

  35. Lagier, J.-C. et al. Culturing the human microbiota and culturomics. Nat. Rev. Microbiol. 16, 540–550 (2018).

    Article  CAS  PubMed  Google Scholar 

  36. Van de Wiele, T., Van den Abbeele, P., Ossieur, W., Possemiers, S. & Marzorati, M. in The Impact of Food Bioactives on Health: In Vitro and Ex Vivo Models 305–317 (Springer International Publishing, 2015).

  37. Minot, S. et al. The human gut virome: inter-individual variation and dynamic response to diet. Genome Res. 21, 1616–1625 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Garmaeva, S. et al. Stability of the human gut virome and effect of gluten-free diet. Cell Rep. 35, 109132 (2021).

    Article  CAS  PubMed  Google Scholar 

  39. Scarpellini, E. et al. The human gut microbiota and virome: potential therapeutic implications. Dig. Liver Dis. 47, 1007–1012 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Warmbrunn, M. V. et al. Gut microbiota: a promising target against cardiometabolic diseases. Expert Rev. Endocrinol. Metab. 15, 13–27 (2020).

    Article  CAS  PubMed  Google Scholar 

  41. Herold, M. et al. Integration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance. Nat. Commun. 11, 5281 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Falony, G. et al. Population-level analysis of gut microbiome variation. Science 352, 560–564 (2016).

    Article  CAS  PubMed  Google Scholar 

  43. Zhernakova, A. et al. Population-based metagenomics analysis reveals markers for gut microbiome composition and diversity. Science 352, 565–569 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Fromentin, S. et al. Microbiome and metabolome features of the cardiometabolic disease spectrum. Nat. Med. 28, 303–314 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Asnicar, F. et al. Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals. Nat. Med. 27, 321–332 (2021).

  46. Wilmes, P., Heintz-Buschart, A. & Bond, P. L. A decade of metaproteomics: where we stand and what the future holds. Proteomics 15, 3409–3417 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Lloyd-Price, J. et al. Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases. Nature 569, 655–662 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Zhou, W. et al. Longitudinal multi-omics of host–microbe dynamics in prediabetes. Nature 569, 663–671 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Zhang, Y. et al. Discovery of bioactive microbial gene products in inflammatory bowel disease. Nature 606, 754–760 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Oliveira, P. H. Bacterial epigenomics: coming of age. mSystems 6, e0074721 (2021).

    Article  PubMed  Google Scholar 

  51. Hiraoka, S. et al. Metaepigenomic analysis reveals the unexplored diversity of DNA methylation in an environmental prokaryotic community. Nat. Commun. 10, 159 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Singh, R. K. et al. Influence of diet on the gut microbiome and implications for human health. J. Transl. Med. 15, 73 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Rothschild, D. et al. Environment dominates over host genetics in shaping human gut microbiota. Nature 555, 210–215 (2018).

    Article  CAS  PubMed  Google Scholar 

  54. Tramontano, M. et al. Nutritional preferences of human gut bacteria reveal their metabolic idiosyncrasies. Nat. Microbiol. 3, 514–522 (2018).

    Article  CAS  PubMed  Google Scholar 

  55. Cummings, J. H. & Macfarlane, G. T. The control and consequences of bacterial fermentation in the human colon. J. Appl. Bacteriol. 70, 443–459 (1991).

    Article  CAS  PubMed  Google Scholar 

  56. Vieira-Silva, S. et al. Species–function relationships shape ecological properties of the human gut microbiome. Nat. Microbiol. 1, 16088 (2016).

    Article  CAS  PubMed  Google Scholar 

  57. Fehlner-Peach, H. et al. Distinct polysaccharide utilization profiles of human intestinal Prevotella copri isolates. Cell Host Microbe 26, 680–690.e5 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Wu, G. D. et al. Linking long-term dietary patterns with gut microbial enterotypes. Science 334, 105–108 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Walker, A. W. et al. Dominant and diet-responsive groups of bacteria within the human colonic microbiota. ISME J. 5, 220–230 (2011).

    Article  CAS  PubMed  Google Scholar 

  60. Ley, R. E., Turnbaugh, P. J., Klein, S. & Gordon, J. I. Microbial ecology: human gut microbes associated with obesity. Nature 444, 1022–1023 (2006).

    Article  CAS  PubMed  Google Scholar 

  61. David, L. A. et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505, 559–563 (2014).

    Article  CAS  PubMed  Google Scholar 

  62. Johnson, A. J. et al. Daily sampling reveals personalized diet–microbiome associations in humans. Cell Host Microbe 25, 789–802.e5 (2019).

    Article  CAS  PubMed  Google Scholar 

  63. Wang, D. D. et al. The gut microbiome modulates the protective association between a Mediterranean diet and cardiometabolic disease risk. Nat. Med. 27, 333–343 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Ferro-Luzzi, A. et al. Changing the Mediterranean diet: effects on blood lipids. Am. J. Clin. Nutr. 40, 1027–1037 (1984).

    Article  CAS  PubMed  Google Scholar 

  65. Ghosh, T. S. et al. Mediterranean diet intervention alters the gut microbiome in older people reducing frailty and improving health status: the NU-AGE 1-year dietary intervention across five European countries. Gut 69, 1218–1228 (2020).

    Article  CAS  PubMed  Google Scholar 

  66. Turpin, W. et al. Mediterranean-like dietary pattern associations with gut microbiome composition and subclinical gastrointestinal inflammation. Gastroenterology 163, 685–698 (2022).

    Article  CAS  PubMed  Google Scholar 

  67. Nakayama, J. et al. Impact of Westernized diet on gut microbiota in children on Leyte Island. Front. Microbiol. 8, 197 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  68. Tett, A. et al. The Prevotella copri complex comprises four distinct clades underrepresented in Westernized populations. Cell Host Microbe 26, 666–679.e7 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Kovatcheva-Datchary, P. et al. Dietary fiber-induced improvement in glucose metabolism is associated with increased abundance of Prevotella. Cell Metab. 22, 971–982 (2015).

    Article  CAS  PubMed  Google Scholar 

  70. Tett, A., Pasolli, E., Masetti, G., Ercolini, D. & Segata, N. Prevotella diversity, niches and interactions with the human host. Nat. Rev. Microbiol. 19, 585–599 (2021).

    Article  CAS  PubMed  Google Scholar 

  71. Meslier, V. et al. Mediterranean diet intervention in overweight and obese subjects lowers plasma cholesterol and causes changes in the gut microbiome and metabolome independently of energy intake. Gut 69, 1258–1268 (2020).

    Article  CAS  PubMed  Google Scholar 

  72. Ang, Q. Y. et al. Ketogenic diets alter the gut microbiome resulting in decreased intestinal TH17 cells. Cell 181, 1263–1275.e16 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Rondanelli, M. et al. The potential roles of very low calorie, very low calorie ketogenic diets and very low carbohydrate diets on the gut microbiota composition. Front. Endocrinol. 12, 662591 (2021).

    Article  Google Scholar 

  74. Guo, Y. et al. Intermittent fasting improves cardiometabolic risk factors and alters gut microbiota in metabolic syndrome patients. J. Clin. Endocrinol. Metab. 106, 64–79 (2021).

    Article  PubMed  Google Scholar 

  75. Ratiner, K., Shapiro, H., Goldenberg, K. & Elinav, E. Time-limited diets and the gut microbiota in cardiometabolic disease. J. Diabetes 14, 377–393 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  76. Attaye, I., van Oppenraaij, S., Warmbrunn, M. V. & Nieuwdorp, M. The role of the gut microbiota on the beneficial effects of ketogenic diets. Nutrients 14, 191 (2022).

    Article  CAS  Google Scholar 

  77. Barabási, A.-L., Menichetti, G. & Loscalzo, J. The unmapped chemical complexity of our diet. Nat. Food 1, 33–37 (2019).

    Article  Google Scholar 

  78. Clarke, R. J. Coffee: Chemistry Vol. 1 (Springer Science & Business Media, 2012).

  79. Ruskovska, T., Maksimova, V. & Milenkovic, D. Polyphenols in human nutrition: from the in vitro antioxidant capacity to the beneficial effects on cardiometabolic health and related inter-individual variability—an overview and perspective. Br. J. Nutr. 123, 241–254 (2020).

    Article  CAS  PubMed  Google Scholar 

  80. Corrêa, T. A. F., Rogero, M. M., Hassimotto, N. M. A. & Lajolo, F. M. The two-way polyphenols–microbiota interactions and their effects on obesity and related metabolic diseases. Front. Nutr. 6, 188 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  81. Cardona, F., Andrés-Lacueva, C., Tulipani, S., Tinahones, F. J. & Queipo-Ortuño, M. I. Benefits of polyphenols on gut microbiota and implications in human health. J. Nutr. Biochem. 24, 1415–1422 (2013).

    Article  CAS  PubMed  Google Scholar 

  82. Mompeo, O. et al. Consumption of stilbenes and flavonoids is linked to reduced risk of obesity independently of fiber intake. Nutrients 12, 1871 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Namazi, N., Irandoost, P., Larijani, B. & Azadbakht, L. The effects of supplementation with conjugated linoleic acid on anthropometric indices and body composition in overweight and obese subjects: a systematic review and meta-analysis. Crit. Rev. Food Sci. Nutr. 59, 2720–2733 (2019).

    Article  CAS  PubMed  Google Scholar 

  84. Chen, Y. et al. Orally administered CLA ameliorates DSS-induced colitis in mice via intestinal barrier improvement, oxidative stress reduction, and inflammatory cytokine and gut microbiota modulation. J. Agric. Food Chem. 67, 13282–13298 (2019).

    Article  CAS  PubMed  Google Scholar 

  85. Rosberg-Cody, E. et al. Recombinant lactobacilli expressing linoleic acid isomerase can modulate the fatty acid composition of host adipose tissue in mice. Microbiology 157, 609–615 (2011).

    Article  CAS  PubMed  Google Scholar 

  86. He, Y. et al. Metabolomic changes upon conjugated linoleic acid supplementation and predictions of body composition responsiveness. J. Clin. Endocrinol. Metab. 107, 2606–2615 (2022).

    Article  PubMed  Google Scholar 

  87. Valdes, A. M., Walter, J., Segal, E. & Spector, T. D. Role of the gut microbiota in nutrition and health. Brit. Med. J. 361, k2179 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  88. Cryan, J. F. et al. The microbiota–gut–brain axis. Physiol. Rev. 99, 1877–2013 (2019).

  89. Yoo, W. et al. High-fat diet-induced colonocyte dysfunction escalates microbiota-derived trimethylamine N-oxide. Science 373, 813–818 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Dodd, D. et al. A gut bacterial pathway metabolizes aromatic amino acids into nine circulating metabolites. Nature 551, 648–652 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Dekkers, K. F. et al. An online atlas of human plasma metabolite signatures of gut microbiome composition. Nat. Commun. 13, 5370 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Rath, S., Heidrich, B., Pieper, D. H. & Vital, M. Uncovering the trimethylamine-producing bacteria of the human gut microbiota. Microbiome 5, 54 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  93. Thomas, A. M. et al. Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation. Nat. Med. 25, 667–678 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Falony, G., Vieira-Silva, S. & Raes, J. Microbiology meets big data: the case of gut microbiota-derived trimethylamine. Annu. Rev. Microbiol. 69, 305–321 (2015).

    Article  CAS  PubMed  Google Scholar 

  95. Cai, Y.-Y. et al. Integrated metagenomics identifies a crucial role for trimethylamine-producing Lachnoclostridium in promoting atherosclerosis. npj Biofilms Microbiomes 8, 11 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Schugar, R. C. et al. Gut microbe-targeted choline trimethylamine lyase inhibition improves obesity via rewiring of host circadian rhythms. eLife 11, e63998 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Louis, P. & Flint, H. J. Formation of propionate and butyrate by the human colonic microbiota. Environ. Microbiol. 19, 29–41 (2017).

    Article  CAS  PubMed  Google Scholar 

  98. Gasaly, N., Hermoso, M. A. & Gotteland, M. Butyrate and the fine-tuning of colonic homeostasis: implication for inflammatory bowel diseases. Int. J. Mol. Sci. 22, 3061 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Morrison, D. J. & Preston, T. Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism. Gut Microbes 7, 189–200 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  100. Valles-Colomer, M. et al. The neuroactive potential of the human gut microbiota in quality of life and depression. Nat. Microbiol. 4, 623–632 (2019).

    Article  CAS  PubMed  Google Scholar 

  101. Lai, Y. et al. High-coverage metabolomics uncovers microbiota-driven biochemical landscape of interorgan transport and gut–brain communication in mice. Nat. Commun. 12, –166000 (2021).

    Article  Google Scholar 

  102. Lefort, C. & Cani, P. D. The liver under the spotlight: bile acids and oxysterols as pivotal actors controlling metabolism. Cells 10, 400 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Xie, A.-J., Mai, C.-T., Zhu, Y.-Z., Liu, X.-C. & Xie, Y. Bile acids as regulatory molecules and potential targets in metabolic diseases. Life Sci. 287, 120152 (2021).

    Article  CAS  PubMed  Google Scholar 

  104. De Vos, W. M., Tilg, H., Van Hul, M. & Cani, P. D. Gut microbiome and health: mechanistic insights. Gut 71, 1020–1032 (2022).

  105. De Aguiar Vallim, T. Q., Tarling, E. J. & Edwards, P. A. Pleiotropic roles of bile acids in metabolism. Cell Metab. 17, 657–669 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  106. Sato, Y. et al. Novel bile acid biosynthetic pathways are enriched in the microbiome of centenarians. Nature 599, 458–464 (2021).

    Article  CAS  PubMed  Google Scholar 

  107. Tomasova, L., Grman, M., Ondrias, K. & Ufnal, M. The impact of gut microbiota metabolites on cellular bioenergetics and cardiometabolic health. Nutr. Metab. 18, 72 (2021).

    Article  Google Scholar 

  108. Maier, L. et al. Extensive impact of non-antibiotic drugs on human gut bacteria. Nature 555, 623–628 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Zimmermann, M., Zimmermann-Kogadeeva, M., Wegmann, R. & Goodman, A. L. Mapping human microbiome drug metabolism by gut bacteria and their genes. Nature 570, 462–467 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Forslund, K. et al. Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota. Nature 528, 262–266 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Wu, H. et al. Metformin alters the gut microbiome of individuals with treatment-naive type 2 diabetes, contributing to the therapeutic effects of the drug. Nat. Med. 23, 850–858 (2017).

    Article  CAS  PubMed  Google Scholar 

  112. Sun, L. et al. Gut microbiota and intestinal FXR mediate the clinical benefits of metformin. Nat. Med. 24, 1919–1929 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Vieira-Silva, S. et al. Statin therapy is associated with lower prevalence of gut microbiota dysbiosis. Nature 581, 310–315 (2020).

    Article  CAS  PubMed  Google Scholar 

  114. Wilmanski, T. et al. Heterogeneity in statin responses explained by variation in the human gut microbiome. Med 3, 388–405.e6 (2022).

    Article  CAS  PubMed  Google Scholar 

  115. Klünemann, M. et al. Bioaccumulation of therapeutic drugs by human gut bacteria. Nature 597, 533–538 (2021).

    Article  PubMed  Google Scholar 

  116. Haiser, H. J. et al. Predicting and manipulating cardiac drug inactivation by the human gut bacterium Eggerthella lenta. Science 341, 295–298 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Maini Rekdal, V., Bess, E. N., Bisanz, J. E., Turnbaugh, P. J. & Balskus, E. P. Discovery and inhibition of an interspecies gut bacterial pathway for Levodopa metabolism. Science 364, eaau6323 (2019).

  118. Zimmermann, M., Raosaheb Patil, K., Typas, A. & Maier, L. Towards a mechanistic understanding of reciprocal drug–microbiome interactions. Mol. Syst. Biol. 17, e10116 (2021).

  119. Maier, L. & Typas, A. Systematically investigating the impact of medication on the gut microbiome. Curr. Opin. Microbiol. 39, 128–135 (2017).

    Article  CAS  PubMed  Google Scholar 

  120. Huang, S., Chaudhary, K. & Garmire, L. X. More is better: recent progress in multi-omics data integration methods. Front. Genet. 8, 84 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Bar, N. et al. A reference map of potential determinants for the human serum metabolome. Nature 588, 135–140 (2020).

    Article  PubMed  Google Scholar 

  122. Zeevi, D. et al. Personalized nutrition by prediction of glycemic responses. Cell 163, 1079–1094 (2015).

    Article  CAS  PubMed  Google Scholar 

  123. Berry, S. E. et al. Human postprandial responses to food and potential for precision nutrition. Nat. Med. 26, 964–973 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Doust, C. et al. Discovery of 42 genome-wide significant loci associated with dyslexia. Nat. Genet. 54, 1621–1629 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Gibson, G. R. et al. Dietary prebiotics: current status and new definition. Food Sci. Technol. Bull. 7, 1–19 (2010).

    Google Scholar 

  126. Hill, C. et al. Expert consensus document. The International Scientific Association for Probiotics and Prebiotics consensus statement on the scope and appropriate use of the term probiotic. Nat. Rev. Gastroenterol. Hepatol. 11, 506–514 (2014).

    Article  PubMed  Google Scholar 

  127. Swanson, K. S. et al. The International Scientific Association for Probiotics and Prebiotics (ISAPP) consensus statement on the definition and scope of synbiotics. Nat. Rev. Gastroenterol. Hepatol. 17, 687–701 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  128. Salminen, S. et al. The International Scientific Association of Probiotics and Prebiotics (ISAPP) consensus statement on the definition and scope of postbiotics. Nat. Rev. Gastroenterol. Hepatol. 18, 649–667 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  129. O’Toole, P. W., Marchesi, J. R. & Hill, C. Next-generation probiotics: the spectrum from probiotics to live biotherapeutics. Nat. Microbiol. 2, 17057 (2017).

    Article  PubMed  Google Scholar 

  130. Karcher, N. et al. Genomic diversity and ecology of human-associated Akkermansia species in the gut microbiome revealed by extensive metagenomic assembly. Genome Biol. 22, 209 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Depommier, C. et al. Supplementation with Akkermansia muciniphila in overweight and obese human volunteers: a proof-of-concept exploratory study. Nat. Med. 25, 1096–1103 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. De Filippis, F., Esposito, A. & Ercolini, D. Outlook on next-generation probiotics from the human gut. Cell. Mol. Life Sci. 79, 76 (2022).

    Article  PubMed  Google Scholar 

  133. Baxter, M. & Colville, A. Adverse events in faecal microbiota transplant: a review of the literature. J. Hosp. Infect. 92, 117–127 (2016).

    Article  CAS  PubMed  Google Scholar 

  134. Maida, M., Mcilroy, J., Ianiro, G. & Cammarota, G. Faecal microbiota transplantation as emerging treatment in European countries. Adv. Exp. Med. Biol. 1050, 177–195 (2018).

    Article  PubMed  Google Scholar 

  135. Baunwall, S. M. D. et al. Danish national guideline for the treatment of infection and use of faecal microbiota transplantation (FMT). Scand. J. Gastroenterol. 56, 1056–1077 (2021).

    Article  CAS  PubMed  Google Scholar 

  136. Suskind, D. L. et al. Fecal microbial transplant effect on clinical outcomes and fecal microbiome in active Crohn’s disease. Inflamm. Bowel Dis. 21, 556–563 (2015).

    Article  PubMed  Google Scholar 

  137. Davar, D. et al. Fecal microbiota transplant overcomes resistance to anti–PD-1 therapy in melanoma patients. Science 371, 595–602 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Baruch, E. N. et al. Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients. Science 371, 602–609 (2021).

    Article  CAS  PubMed  Google Scholar 

  139. Koopen, A. M. et al. Effect of fecal microbiota transplantation combined with mediterranean diet on insulin sensitivity in subjects with metabolic syndrome. Front. Microbiol. 12, 662159 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  140. Ianiro, G. et al. Variability of strain engraftment and predictability of microbiome composition after fecal microbiota transplantation across different diseases. Nat. Med. 28, 1913–1923 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Valles-Colomer, M. et al. The person-to-person transmission landscape of the gut and oral microbiomes. Nature 614, 125–135 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  142. Finlay, B. B., CIFAR Humans & The Microbiome. Are noncommunicable diseases communicable? Science 367, 250–251 (2020).

    Article  CAS  PubMed  Google Scholar 

  143. Aasmets, O., Krigul, K. L., Lüll, K., Metspalu, A. & Org, E. Gut metagenome associations with extensive digital health data in a volunteer-based Estonian microbiome cohort. Nat. Commun. 13, 869 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. Gacesa, R. et al. Environmental factors shaping the gut microbiome in a Dutch population. Nature 604, 732–739 (2022).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This work was supported by the European Research Council (ERC-STG project MetaPG-716575 and ERC-CoG microTOUCH-101045015) to N.S. and by EMBO ALTF 593-2020 to M.V.-C. The work was also partially supported by the European Union’s Horizon 2020 program (ONCOBIOME-825410 project, MASTER-818368 project and IHMCSA-964590) to N.S., the European Union NextGenerationEU (Interconnected Nord-Est Innovation program, INEST) to N.S., the National Cancer Institute of the National Institutes of Health (1U01CA230551) to N.S. and the Premio Internazionale Lombardia e Ricerca 2019 to N.S. C.M. is funded by the Chronic Disease Research Foundation.

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Author notes

  1. These authors contributed equally: Mireia Valles-Colomer, Cristina Menni, Ana M. Valdes, Tim D. Spector, Nicola Segata.

Authors and Affiliations

  1. Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy

    Mireia Valles-Colomer & Nicola Segata

  2. Department of Twin Research, King’s College London, London, UK

    Cristina Menni & Tim D. Spector

  3. Department of Nutritional Sciences, King’s College London, London, UK

    Sarah E. Berry

  4. School of Medicine, University of Nottingham, Nottingham, UK

    Ana M. Valdes

  5. Nottingham National Institute for Health Research Biomedical Research Centre, Nottingham, UK

    Ana M. Valdes

  6. European Institute of Oncology, Scientific Institute for Research, Hospitalization and Healthcare, Milan, Italy

    Nicola Segata

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Correspondence to Nicola Segata.

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Competing interests

S.E.B., A.M.V., T.D.S. and N.S. are consultants to Zoe Global. N.S. reports consultancy and/or Scientific Advisory Board contracts with Roche, YSOPIA Bioscience, Freya Biosciences and Alia Therapeutics and speaker fees from Illumina and is cofounder of PreBiomics. The other authors declare no competing interests.

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Valles-Colomer, M., Menni, C., Berry, S.E. et al. Cardiometabolic health, diet and the gut microbiome: a meta-omics perspective. Nat Med 29, 551–561 (2023). https://doi.org/10.1038/s41591-023-02260-4

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