Nutri-microbiome epidemiology, an emerging field to disentangle the interplay between nutrition and microbiome for human health

Wanglong Gou, Zelei Miao, Kui Deng, Ju-Sheng Zheng

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Protein Cell ›› 2023, Vol. 14 ›› Issue (11) : 787-806. DOI: 10.1093/procel/pwad023
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Nutri-microbiome epidemiology, an emerging field to disentangle the interplay between nutrition and microbiome for human health

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Abstract

Diet and nutrition have a substantial impact on the human microbiome, and interact with the microbiome, especially gut microbiome, to modulate various diseases and health status. Microbiome research has also guided the nutrition field to a more integrative direction, becoming an essential component of the rising area of precision nutrition. In this review, we provide a broad insight into the interplay among diet, nutrition, microbiome, and microbial metabolites for their roles in the human health. Among the microbiome epidemiological studies regarding the associations of diet and nutrition with microbiome and its derived metabolites, we summarize those most reliable findings and highlight evidence for the relationships between diet and disease-associated microbiome and its functional readout. Then, the latest advances of the microbiome-based precision nutrition research and multidisciplinary integration are described. Finally, we discuss several outstanding challenges and opportunities in the field of nutri-microbiome epidemiology.

Keywords

microbiome / nutrition / human health / epidemiology

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Wanglong Gou, Zelei Miao, Kui Deng, Ju-Sheng Zheng. Nutri-microbiome epidemiology, an emerging field to disentangle the interplay between nutrition and microbiome for human health. Protein Cell, 2023, 14(11): 787‒806 https://doi.org/10.1093/procel/pwad023

References

[1]
Ang QY, Alexander M, Newman JC et al. Ketogenic diets alter the gut microbiome resulting in decreased intestinal Th17 cells. Cell 2020;181:1263–1275.e16.
CrossRef Google scholar
[2]
Asnicar F, Berry SE, Valdes AM et al. Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals. Nat Med 2021;12:13.
CrossRef Google scholar
[3]
Bar N, Korem T, Weissbrod O et al. A reference map of potential determinants for the human serum metabolome. Nature 2020;588:135–140.
CrossRef Google scholar
[4]
Bennet SMP, Böhn L, Störsrud S et al. Multivariate modelling of faecal bacterial profiles of patients with IBS predicts responsiveness to a diet low in FODMAPs. Gut 2018;67:872–881.
CrossRef Google scholar
[5]
Ben-Yacov O, Godneva A, Rein M et al. Personalized postprandial glucose response-targeting diet versus Mediterranean diet for glycemic control in prediabetes. Diabetes Care 2021;44:1980–1991.
CrossRef Google scholar
[6]
Berry SE, Valdes AM, Drew DA et al. Human postprandial responses to food and potential for precision nutrition. Nat Med 2020;26:964–973.
CrossRef Google scholar
[7]
Bolte LA, Vich Vila A, Imhann F et al. Long-term dietary patterns are associated with pro-inflammatory and anti-inflammatory features of the gut microbiome. Gut 2021;70:1–12.
CrossRef Google scholar
[8]
Borodulin K, Tolonen H, Jousilahti P et al. Cohort profile: the National FINRISK Study. Int J Epidemiol 2018;47:696–696i.
CrossRef Google scholar
[9]
Boronat A, Rodriguez-Morató J, Serreli G et al. Contribution of biotransformations carried out by the microbiota, drug-metabolizing enzymes, and transport proteins to the biological activities of phytochemicals found in the diet. Adv Nutr 2021;12:2172–2189.
CrossRef Google scholar
[10]
Breuninger TA, Wawro N, Breuninger J et al. Associations between habitual diet, metabolic disease, and the gut microbiota using latent Dirichlet allocation. Microbiome 2021;9:1–18.
CrossRef Google scholar
[11]
Brown JM, Hazen SL. Microbial modulation of cardiovascular disease. Nat Rev Microbiol 2018;16:171–181.
CrossRef Google scholar
[12]
Chassaing B, Koren O, Goodrich JK et al. Dietary emulsifiers impact the mouse gut microbiota promoting colitis and metabolic syndrome. Nature 2015;519:92–96.
CrossRef Google scholar
[13]
Chen L, Zhernakova DV, Kurilshikov A et al. Influence of the micro-biome, diet and genetics on inter-individual variation in the human plasma metabolome. Nat Med 2022;28:2333–2343.
CrossRef Google scholar
[14]
Costantini L, Molinari R, Farinon B et al. Impact of Omega-3 fatty acids on the gut microbiota. Int J Mol Sci 2017;18:2645.
CrossRef Google scholar
[15]
Cotillard A, Kennedy SP, Kong LC et al. Dietary intervention impact on gut microbial gene richness. Nature 2013;500:585–588.
CrossRef Google scholar
[16]
Cuevas-Sierra A, Milagro FI, Aranaz P et al. Gut microbiota differences according to ultra-processed food consumption in a Spanish population. Nutrients 2021;13:2710.
CrossRef Google scholar
[17]
Dall’Asta M, Laghi L, Morselli S et al. Pre-pregnancy diet and vaginal environment in caucasian pregnant women: an exploratory study. Front Mol Biosci 2021;8:702370.
CrossRef Google scholar
[18]
Dang AT, Marsland BJ. Microbes, metabolites, and the gut–lung axis. Mucosal Immunol 2019;12:843–850.
CrossRef Google scholar
[19]
Deehan EC, Yang C, Perez-Muñoz ME et al. Precision microbiome modulation with discrete dietary fiber structures directs short-chain fatty acid production. Cell Host Microbe 2020;27:389–404.e6.
CrossRef Google scholar
[20]
De Filippis F, Pellegrini N, Vannini L et al. High-level adherence to a Mediterranean diet beneficially impacts the gut microbiota and associated metabolome. Gut 2016;65:1812–1821.
CrossRef Google scholar
[21]
Dehghan P, Farhangi MA, Nikniaz L et al. Gut microbiota-derived metabolite trimethylamine N-oxide (TMAO) potentially increases the risk of obesity in adults: an exploratory systematic review and dose-response meta- analysis. Obes Rev 2020;21:e12993.
CrossRef Google scholar
[22]
Deleu S, Machiels K, Raes J et al. Short chain fatty acids and its producing organisms: an overlooked therapy for IBD? EBioMedicine 2021;66:103293.
CrossRef Google scholar
[23]
de la Cuesta-Zuluaga J, Mueller NT, Álvarez-Quintero R et al. Higher fecal short-chain fatty acid levels are associated with gut microbiome dysbiosis, obesity, hypertension and cardiometabolic disease risk factors. Nutrients 2018;11:1–16.
CrossRef Google scholar
[24]
Ecklu-Mensah G, Gilbert J, Devkota S. Dietary selection pressures and their impact on the gut microbiome. Cell Mol Gastroenterol Hepatol 2022;13:7–18.
CrossRef Google scholar
[25]
Esberg A, Eriksson L, Hasslöf P et al. Using oral microbiota data to design a short sucrose intake index. Nutrients 2021;13:1400.
CrossRef Google scholar
[26]
Fan Y, Pedersen O. Gut microbiota in human metabolic health and disease. Nat Rev Microbiol 2021;19:55–71.
CrossRef Google scholar
[27]
Faria A, Fernandes I, Norberto S et al. Interplay between anthocyanins and gut microbiota. J Agric Food Chem 2014;62:6898–6902.
CrossRef Google scholar
[28]
France M, Alizadeh M, Brown S et al. Towards a deeper understanding of the vaginal microbiota. Nat Microbiol 2022;7:367–378.
CrossRef Google scholar
[29]
Gabler NB, Duan N, Vohra S et al. N-of-1 trials in the medical literature: a systematic review. Med Care 2011;49:761–768.
CrossRef Google scholar
[30]
Garcia-Mantrana I, Selma-Royo M, Alcantara C et al. Shifts on gut microbiota associated to Mediterranean diet adherence and specific dietary intakes on general adult population. Front Microbiol 2018;9:890.
CrossRef Google scholar
[31]
Ghosh TS, Rampelli S, Jeffery B 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 2020;69:1218–1228.
CrossRef Google scholar
[32]
Gou W, Ling C-W, He Y et al. Interpretable machine learning framework reveals robust gut microbiome features associated with Type 2 diabetes. Diabetes Care 2021;44:358–366.
CrossRef Google scholar
[33]
Gou W, Ling C-W, He Y et al. Westlake gut project: a consortium of microbiome epidemiology for the gut microbiome and health research in China. Med Microecol 2022;14:100064.
CrossRef Google scholar
[34]
He J, Zhang P, Shen L et al. Short-chain fatty acids and their association with signalling pathways in inflammation, glucose and lipid metabolism. Int J Mol Sci 2020;21:6356.
CrossRef Google scholar
[35]
Hjorth MF, Roager HM, Larsen TM et al. Pre-treatment microbial Prevotella-to-Bacteroides ratio, determines body fat loss success during a 6-month randomized controlled diet intervention. Int J Obes (Lond) 2018;42:580–583.
CrossRef Google scholar
[36]
Hjorth MF, Blædel T, Bendtsen LQ et al. Prevotella-to-Bacteroides ratio predicts body weight and fat loss success on 24-week diets varying in macronutrient composition and dietary fiber: results from a post-hoc analysis. Int J Obes (Lond) 2019;43:149–157.
CrossRef Google scholar
[37]
Hu Y, Song Y, Franke AA et al. A prospective investigation of the association between urinary excretion of dietary lignan metabolites and weight change in US women. Am J Epidemiol 2015;182:503–511.
CrossRef Google scholar
[38]
Huang X, Gao Y, Chen W et al. Dietary variety relates to gut microbiota diversity and abundance in humans. Eur J Nutr 2022;61:3915–3928.
CrossRef Google scholar
[39]
Jiang Z, Sun T, He Y et al. Dietary fruit and vegetable intake, gut microbiota, and type 2 diabetes: results from two large human cohort studies. BMC Med 2020;18:1–11.
CrossRef Google scholar
[40]
Jiang Z, Zhuo L, He Y et al. The gut microbiota-bile acid axis links the positive association between chronic insomnia and cardiometabolic diseases. Nat Commun 2022;13:3002.
CrossRef Google scholar
[41]
Johnson AJ, Vangay P, Al-Ghalith GA et al. Daily sampling reveals personalized diet-microbiome associations in humans. Cell Host Microbe 2019;25:789–802.e5.
CrossRef Google scholar
[42]
Kang JW, Tang X, Walton CJ et al. Multi-omic analyses reveal bifidogenic effect and metabolomic shifts in healthy human cohort supplemented with a prebiotic dietary fiber blend. Front Nutr 2022;9:908534.
CrossRef Google scholar
[43]
Kim H, Caulfield LE, Garcia-Larsen V et al. Plant-based diets are associated with a lower risk of incident cardiovascular disease, cardiovascular disease mortality, and all-cause mortality in a general population of middle-aged adults. J Am Heart Assoc 2019;8:e012865.
CrossRef Google scholar
[44]
Koeth RA, Wang Z, Levison BS et al. Intestinal microbiota metabolism of L-carnitine, a nutrient in red meat, promotes atherosclerosis. Nat Med 2013;19:576–585.
CrossRef Google scholar
[45]
Kolodziejczyk AA, Zheng D, Elinav E. Diet-microbiota interactions and personalized nutrition. Nat Rev Microbiol 2019;17:742–753.
CrossRef Google scholar
[46]
Korem T, Zeevi D, Zmora N et al. Bread affects clinical parameters and induces gut microbiome-associated personal glycemic responses. Cell Metab 2017;25:1243–1253.e5.
CrossRef Google scholar
[47]
Krautkramer KA, Fan J, Bäckhed F. Gut microbial metabolites as multi-kingdom intermediates. Nat Rev Microbiol 2021;19:77–94.
CrossRef Google scholar
[48]
Lam KC, Araya RE, Huang A et al. Microbiota triggers STING-type I IFN-dependent monocyte reprogramming of the tumor microenvironment. Cell 2021;184:5338–5356.e21.
CrossRef Google scholar
[49]
Lamont RJ, Koo H, Hajishengallis G. The oral microbiota: dynamic communities and host interactions. Nat Rev Microbiol 2018;16:745–759.
CrossRef Google scholar
[50]
Lee Y, Nemet I, Wang Z et al. Longitudinal plasma measures of trimethylamine N-Oxide and risk of atherosclerotic cardiovascular disease events in community-based older adults. J Am Heart Assoc 2021;10:e020646.
CrossRef Google scholar
[51]
LeMay-Nedjelski L, Asbury MR, Butcher J et al. Maternal diet and infant feeding practices are associated with variation in the human milk microbiota at 3 months postpartum in a cohort of women with high rates of gestational glucose intolerance. J Nutr 2021;151:320–329.
CrossRef Google scholar
[52]
Li XS, Obeid S, Klingenberg R et al. Gut microbiota-dependent trimethylamine N-oxide in acute coronary syndromes: a prognostic marker for incident cardiovascular events beyond traditional risk factors. Eur Heart J 2017;38:814–824.
CrossRef Google scholar
[53]
Li J, Li Y, Ivey KL et al. Interplay between diet and gut microbiome, and circulating concentrations of trimethylamine N-oxide: findings from a longitudinal cohort of US men. Gut 2022;71:724–733.
CrossRef Google scholar
[54]
Liu Y, Ajami NJ, El-Serag HB et al. Dietary quality and the colonic mucosa–associated gut microbiome in humans. Am J Clin Nutr 2019;110:701.
CrossRef Google scholar
[55]
Liu B, Zhao J, Liu Y et al. Diversity and temporal dynamics of breast milk microbiome and its influencing factors in Chinese women during the first 6 months postpartum. Front Microbiol 2022;13:1016759.
CrossRef Google scholar
[56]
Lommi S, Manzoor M, Engberg E et al. The composition and functional capacities of saliva microbiota differ between children with low and high sweet treat consumption. Front Nutr 2022;9:864687.
CrossRef Google scholar
[57]
Losasso C, Eckert EM, Mastrorilli E et al. Assessing the influence of vegan, vegetarian and omnivore oriented westernized dietary styles on human gut microbiota: a cross sectional study. Front Microbiol 2018;9:317.
CrossRef Google scholar
[58]
Ma Y, Fu Y, Tian Y et al. Individual postprandial glycemic responses to diet in n-of-1 trials: Westlake N-of-1 trials for macronutrient intake (WE-MACNUTR). J Nutr 2021;151:3158–3167.
CrossRef Google scholar
[59]
Mardinoglu A, Wu H, Bjornson E et al. An integrated understanding of the rapid metabolic benefits of a carbohydrate-restricted diet on hepatic steatosis in humans. Cell Metab 2018;27:559–571.e5.
CrossRef Google scholar
[60]
McDonald D, Hyde E, Debelius JW et al. American gut: an open platform for citizen science microbiome research. MSystems 2018;3:e00031-18.
[61]
Mendes-Soares H, Raveh-Sadka T, Azulay S et al. Model of personalized postprandial glycemic response to food developed for an Israeli cohort predicts responses in Midwestern American individuals. Am J Clin Nutr 2019;110:63–75.
CrossRef Google scholar
[62]
Menni C, Zierer J, Pallister T et al. Omega-3 fatty acids correlate with gut microbiome diversity and production of N-carbamylglutamate in middle aged and elderly women. Sci Rep 2017;7:11079.
CrossRef Google scholar
[63]
Menni C, Louca P, Berry SE et al. High intake of vegetables is linked to lower white blood cell profile and the effect is mediated by the gut microbiome. BMC Med 2021;19:1–10.
CrossRef Google scholar
[64]
Merino J, Linenberg I, Bermingham KM et al. Validity of continuous glucose monitoring for categorizing glycemic responses to diet: implications for use in personalized nutrition. Am J Clin Nutr 2022;115:1569–1576.
CrossRef Google scholar
[65]
Merra G, Noce A, Marrone G et al. Influence of mediterranean diet on human gut microbiota. Nutrients 2021;13:1–12.
CrossRef Google scholar
[66]
Miao Z, Lin J-S, Mao Y et al. Erythrocyte n-6 polyunsaturated fatty acids, gut microbiota, and incident Type 2 diabetes: a prospective cohort study. 2020;43:2435–2443.
CrossRef Google scholar
[67]
Miao Z, Du W, Xiao C et al. Gut microbiota signatures of long-term and short-term plant-based dietary pattern and cardiometabolic health: a prospective cohort study. BMC Med 2022;20:1–15.
CrossRef Google scholar
[68]
Miao Z, Chen GD, Huo S et.al. Interaction of n-3 polyunsaturated fatty acids with host CD36 genetic variant for gut microbiome and blood lipids in human cohorts. Clin Nutr 2022;41:1724–1734.
CrossRef Google scholar
[69]
Millen AE, Dahhan R, Freudenheim JL et al. Dietary carbohydrate intake is associated with the subgingival plaque oral microbiome abundance and diversity in a cohort of postmenopausal women. Sci Rep 2022;12:2643.
CrossRef Google scholar
[70]
Mitsou EK, Kakali A, Antonopoulou S et al. Adherence to the Mediterranean diet is associated with the gut microbiota pattern and gastrointestinal characteristics in an adult population. Br J Nutr 2017;117:1645–1655.
CrossRef Google scholar
[71]
Molina-Montes E, Salamanca-Fernández E, Garcia-Villanova B et al. The impact of plant-based dietary patterns on cancer-related outcomes: a rapid review and meta-analysis. Nutrients 2020;12:20101–20131.
CrossRef Google scholar
[72]
Molinaro A, Bel Lassen P, Henricsson M et al. Imidazole propionate is increased in diabetes and associated with dietary patterns and altered microbial ecology. Nat Commun 2020;11:5881.
CrossRef Google scholar
[73]
Moreno-Indias I, Sánchez-Alcoholado L, Pérez-Martínez P et al. Red wine polyphenols modulate fecal microbiota and reduce markers of the metabolic syndrome in obese patients. Food Funct 2016;7:1775–1787.
CrossRef Google scholar
[74]
Murdoch WJ, Singh C, Kumbier K et al. Definitions, methods, and applications in interpretable machine learning. Proc Natl Acad Sci USA 2019;116:22071–22080.
CrossRef Google scholar
[75]
Naimi S, Viennois E, Gewirtz AT et al. Direct impact of commonly used dietary emulsifiers on human gut microbiota. Microbiome 2021;9:66.
CrossRef Google scholar
[76]
Neuffer J, González-Domínguez R, Lefèvre-Arbogast S et al. Exploration of the gut-brain axis through metabolomics identifies serum propionic acid associated with higher cognitive decline in older persons. Nutrients 2022;14:4688.
CrossRef Google scholar
[77]
Nishimoto Y, Mizuguchi Y, Mori Y et al. Resistant maltodextrin intake reduces virulent metabolites in the gut environment: a randomized control study in a Japanese cohort. Front Microbiol 2022;13:644146.
CrossRef Google scholar
[78]
Nordlund E, Aura A-M, Mattila I et al. Formation of phenolic microbial metabolites and short-chain fatty acids from rye, wheat, and oat bran and their fractions in the metabolical in vitro colon model. J Agric Food Chem 2012;60:8134–8145.
CrossRef Google scholar
[79]
Olsson LM, Boulund F, Nilsson S et al. Dynamics of the normal gut microbiota: a longitudinal one-year population study in Sweden. Cell Host Microbe 2022;30:726–739.e3.
CrossRef Google scholar
[80]
Peters BA, McCullough ML, Purdue MP et al. Association of coffee and tea intake with the oral microbiome: results from a large cross-sectional study. Cancer Epidemiol Biomarkers Prev 2018;27:814–821.
CrossRef Google scholar
[81]
Pignanelli M, Bogiatzi C, Gloor G et al. Moderate renal impairment and toxic metabolites produced by the intestinal microbiome: dietary implications. J Ren Nutr 2019;29:55–64.
CrossRef Google scholar
[82]
Potter T, Vieira R, de Roos B. Perspective: application of N-of-1 methods in personalized nutrition research. Adv Nutr 2021;12:579–589.
CrossRef Google scholar
[83]
Qi Q, Li J, Yu B et al. 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. Gut 2022;71:1095–1105.
CrossRef Google scholar
[84]
Qian F, Liu G, Hu FB et al. Association between plant-based dietary patterns and risk of type 2 diabetes: a systematic review and meta-analysis. JAMA Intern Med 2019;179:1335–1344.
CrossRef Google scholar
[85]
Queipo-Ortuño MI, Boto-Ordóñez M, Murri M et al. Influence of red wine polyphenols and ethanol on the gut microbiota ecology and biochemical biomarkers. Am J Clin Nutr 2012;95:1323–1334.
CrossRef Google scholar
[86]
Rath S, Rox K, Kleine Bardenhorst S et al. Higher Trimethylamine-N-Oxide plasma levels with increasing age are mediated by diet and trimethylamine-forming bacteria. MSystems 2021;6:e0094521.
CrossRef Google scholar
[87]
Ren Z, Shi Y, Xu S et al. Gut bacteria selectively promoted by dietary fibers alleviate type 2 diabetes. Science 2018;359:1151–1156.
CrossRef Google scholar
[88]
Rinott E, Meir AY, Tsaban G et al. The effects of the Green-Mediterranean diet on cardiometabolic health are linked to gut microbiome modifications: a randomized controlled trial. Genome Med 2022;14:29.
CrossRef Google scholar
[89]
Roager HM, Licht TR. Microbial tryptophan catabolites in health and disease. Nat Commun 2018;9:3294.
CrossRef Google scholar
[90]
Rodgers GP, Collins FS. Precision nutrition-the answer to “What to Eat to Stay Healthy”. JAMA 2020;324:735–736.
CrossRef Google scholar
[91]
Rosen EM, Martin CL, Siega-Riz AM et al. Is prenatal diet associated with the composition of the vaginal microbiome? Paediatr Perinat Epidemiol 2022;36:243–253.
CrossRef Google scholar
[92]
Sánchez-Patán F, Cueva C, Monagas M et al. In vitro fermentation of a red wine extract by human gut microbiota: changes in microbial groups and formation of phenolic metabolites. J Agric Food Chem 2012;60:2136–2147.
CrossRef Google scholar
[93]
Sanna S, van Zuydam NR, Mahajan A et al. Causal relationships among the gut microbiome, short-chain fatty acids and metabolic diseases. Nat Genet 2019;51:600–605.
CrossRef Google scholar
[94]
Sempionatto JR, Montiel VR-V, Vargas E et al. Wearable and mobile sensors for personalized nutrition. ACS Sensors 2021;6:1745–1760.
CrossRef Google scholar
[95]
Sender R, Fuchs S, Milo R. Revised estimates for the number of human and bacteria cells in the body. PLoS Biol 2016;14:e1002533.
CrossRef Google scholar
[96]
Senthong V, Wang Z, Li XS et al. Intestinal microbiota-generated metabolite Trimethylamine-N-Oxide and 5-year mortality risk in stable coronary artery disease: the contributory role of intestinal microbiota in a COURAGE-like patient cohort. J Am Heart Assoc 2016;5:e002816.
CrossRef Google scholar
[97]
Shaalan A, Lee S, Feart C et al. Alterations in the oral microbiome associated with diabetes, overweight, and dietary components. Front Nutr 2022;9:914715.
CrossRef Google scholar
[98]
Shankar Ghosh T, Rampelli S, Jeffery B et al. Gut microbiota 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 2020:1–11.
CrossRef Google scholar
[99]
Shuai M, Zuo LSY, Miao Z et al. Multi-omics analyses reveal relationships among dairy consumption, gut microbiota and cardiometabolic health. EBioMedicine 2021;66:103284.
CrossRef Google scholar
[100]
Singh RK, Chang HW, Yan D et al. Influence of diet on the gut microbiome and implications for human health. J Transl Med 2017;15:1–17.
CrossRef Google scholar
[101]
Suez J, Cohen Y, Valdés-Mas R et al. Personalized microbiome-driven effects of non-nutritive sweeteners on human glucose tolerance. Cell 2022;185:3307–3328.e19.
CrossRef Google scholar
[102]
Szabo de Edelenyi F, Philippe C, Druesne-Pecollo N et al. Depressive symptoms, fruit and vegetables consumption and urinary 3-indoxylsulfate concentration: a nested case-control study in the French Nutrinet-Sante cohort. Eur J Nutr 2021;60:1059–1069.
CrossRef Google scholar
[103]
Tigchelaar EF, Zhernakova A, Dekens JAM et al. Cohort profile: LifeLines DEEP, a prospective, general population cohort study in the northern Netherlands: study design and baseline characteristics. BMJ Open 2015;5:e006772.
CrossRef Google scholar
[104]
Trefflich I, Marschall H-U, Giuseppe R et al. Associations between dietary patterns and bile acids-results from a cross-sectional study in vegans and omnivores. Nutrients 2019;12:47.
CrossRef Google scholar
[105]
Tripathi A, Debelius J, Brenner DA et al. The gut–liver axis and the intersection with the microbiome. Nat Rev Gastroenterol Hepatol 2018;15:397–411.
CrossRef Google scholar
[106]
Valdes AM, Walter J, Segal E et al. Role of the gut microbiota in nutrition and health. BMJ 2018a;361:k2179.
CrossRef Google scholar
[107]
Valdes AM, Walter J, Segal E et al. Role of the gut microbiota in nutrition and health. BMJ 2018b;361:36–44.
CrossRef Google scholar
[108]
Van de Wouw M, Schellekens H, Dinan TG et al. Microbiota-gutbrain axis: modulator of host metabolism and appetite. J Nutr 2017;147:727–745.
CrossRef Google scholar
[109]
Vanegas SM, Meydani M, Barnett JB et al. Substituting whole grains for refined grains in a 6-wk randomized trial has a modest effect on gut microbiota and immune and inflammatory markers of healthy adults. Am J Clin Nutr 2017;105:635–650.
CrossRef Google scholar
[110]
Vendrame S, Guglielmetti S, Riso P et al. Six-week consumption of a wild blueberry powder drink increases bifidobacteria in the human gut. J Agric Food Chem 2011;59:12815–12820.
CrossRef Google scholar
[111]
Vetrani C, Costabile G, Luongo D et al. Effects of whole-grain cereal foods on plasma short chain fatty acid concentrations in individuals with the metabolic syndrome. Nutrition 2016;32:217–221.
CrossRef Google scholar
[112]
Wan Y, Wang F, Yuan J et al. Effects of dietary fat on gut microbiota and faecal metabolites, and their relationship with cardiometabolic risk factors: a 6-month randomised controlled-feeding trial. Gut 2019;68:1417–1429.
CrossRef Google scholar
[113]
Wang Z, Tang WH, Buffa JA et al. Prognostic value of choline and betaine depends on intestinal microbiota-generated metabolite trimethylamine-N-oxide. Eur Heart J 2014;35:904–910.
CrossRef Google scholar
[114]
Wang DD, Nguyen LH, Li Y et al. The gut microbiome modulates the protective association between a Mediterranean diet and cardiometabolic disease risk. Nat Med 2021a;27:333–343.
CrossRef Google scholar
[115]
Wang D, Doestzada M, Chen L et al. Characterization of gut microbial structural variations as determinants of human bile acid metabolism. Cell Host Microbe 2021b;29:1802–1814.e5.
CrossRef Google scholar
[116]
Wang H, Gou W, Su C et al. Association of gut microbiota with glycaemic traits and incident type 2 diabetes, and modulation by habitual diet: a population-based longitudinal cohort study in Chinese adults. Diabetologia 2022a;65:1145–1156.
CrossRef Google scholar
[117]
Wang M, Wang Z, Lee Y et al. Dietary meat, Trimethylamine N-oxiderelated metabolites, and incident cardiovascular disease among older adults: the Cardiovascular Health Study. Arterioscler Thromb Vasc Biol 2022b;42:e273–e288.
CrossRef Google scholar
[118]
Wang Y, Dong Q, Hu S et al. Decoding microbial genomes to understand their functional roles in human complex diseases. IMeta 2022c;1:e14.
CrossRef Google scholar
[119]
Watson H, Mitra S, Croden FC et al. A randomised trial of the effect of omega-3 polyunsaturated fatty acid supplements on the human intestinal microbiota. Gut 2018;67:1974–1983.
CrossRef Google scholar
[120]
Wedlake L, Slack N, Andreyev HJN et al. Fiber in the treatment and maintenance of inflammatory bowel disease: a systematic review of randomized controlled trials. Inflamm Bowel Dis 2014;20:576–586.
CrossRef Google scholar
[121]
Wei H, Zhao M, Huang M et al. FMO3-TMAO axis modulates the clinical outcome in chronic heart-failure patients with reduced ejection fraction: evidence from an Asian population. Front Med 2022;16:295–305.
CrossRef Google scholar
[122]
Wu GD, Compher C, Chen EZ et al. Comparative metabolomics in vegans and omnivores reveal constraints on diet-dependent gut microbiota metabolite production. Gut 2016;65:63–72.
CrossRef Google scholar
[123]
Wu TT, Xiao J, Manning S et al. Multimodal data integration reveals mode of delivery and snack consumption outrank salivary microbiome in association with caries outcome in Thai children. Front Cell Infect Microbiol 2022a;12:881899.
CrossRef Google scholar
[124]
Wu Y, Gou W, Yan Y et al. Gut microbiota and acylcarnitine metabolites connect the beneficial association between equol and adiposity in adults: a prospective cohort study. Am J Clin Nutr 2022b;116:1831–1841.
CrossRef Google scholar
[125]
Xiao C, Wang JT, Su C et al. Associations of dietary diversity with the gut microbiome, fecal metabolites, and host metabolism: results from 2 prospective Chinese cohorts. Am J Clin Nutr 2022;116:1049–1058.
CrossRef Google scholar
[126]
Yu D, Shu XO, Rivera ES et al. Urinary levels of Trimethylamine-N-oxide and incident coronary heart disease: a prospective investigation among urban Chinese Adults. J Am Heart Assoc 2019;8:e010606.
CrossRef Google scholar
[127]
Yu D, Nguyen SM, Yang Y et al. Long-term diet quality is associated with gut microbiome diversity and composition among urban Chinese adults. Am J Clin Nutr 2021;113:684–694.
CrossRef Google scholar
[128]
Zaramela LS, Martino C, Alisson-Silva F et al. Gut bacteria responding to dietary change encode sialidases that exhibit preference for red meat-associated carbohydrates. Nat Microbiol 2019;4:2082–2089.
CrossRef Google scholar
[129]
Zeevi D, Korem T, Zmora N et al. Personalized nutrition by prediction of glycemic responses. Cell 2015;163:1079–1095.
CrossRef Google scholar
[130]
Zheng J-S, Ordovás JM. Precision nutrition for gut microbiome and diabetes research: application of nutritional n-of-1 clinical trials. J Diabetes 2021;13:1059–1061.
CrossRef Google scholar
[131]
Zhernakova A, Kurilshikov A, Bonder MJ et al. Population-based metagenomics analysis reveals markers for gut microbiome composition and diversity. Science 2016;352:565–569.
CrossRef Google scholar

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