Dietary patterns differently associate with inflammation and gut microbiota in overweight and obese subjects
Ling Chun Kong, Bridget A Holmes, Aurelie Cotillard, Fatiha Habi-Rachedi, Rémi Brazeilles, Sophie Gougis, Nicolas Gausserès, Patrice D Cani, Soraya Fellahi, Jean-Philippe Bastard, Sean P Kennedy, Joel Doré, Stanislav Dusko Ehrlich, Jean-Daniel Zucker, Salwa W Rizkalla, Karine Clément, Ling Chun Kong, Bridget A Holmes, Aurelie Cotillard, Fatiha Habi-Rachedi, Rémi Brazeilles, Sophie Gougis, Nicolas Gausserès, Patrice D Cani, Soraya Fellahi, Jean-Philippe Bastard, Sean P Kennedy, Joel Doré, Stanislav Dusko Ehrlich, Jean-Daniel Zucker, Salwa W Rizkalla, Karine Clément
Abstract
Background: Associations between dietary patterns, metabolic and inflammatory markers and gut microbiota are yet to be elucidated.
Objectives: We aimed to characterize dietary patterns in overweight and obese subjects and evaluate the different dietary patterns in relation to metabolic and inflammatory variables as well as gut microbiota.
Design: Dietary patterns, plasma and adipose tissue markers, and gut microbiota were evaluated in a group of 45 overweight and obese subjects (6 men and 39 women). A group of 14 lean subjects were also evaluated as a reference group.
Results: Three clusters of dietary patterns were identified in overweight/obese subjects. Cluster 1 had the least healthy eating behavior (highest consumption of potatoes, confectionary and sugary drinks, and the lowest consumption of fruits that was associated also with low consumption of yogurt, and water). This dietary pattern was associated with the highest LDL cholesterol, plasma soluble CD14 (p = 0.01) a marker of systemic inflammation but the lowest accumulation of CD163+ macrophages with anti-inflammatory profile in adipose tissue (p = 0.05). Cluster 3 had the healthiest eating behavior (lower consumption of confectionary and sugary drinks, and highest consumption of fruits but also yogurts and soups). Subjects in this Cluster had the lowest inflammatory markers (sCD14) and the highest anti-inflammatory adipose tissue CD163+ macrophages. Dietary intakes, insulin sensitivity and some inflammatory markers (plasma IL6) in Cluster 3 were close to those of lean subjects. Cluster 2 was in-between clusters 1 and 3 in terms of healthfulness. The 7 gut microbiota groups measured by qPCR were similar across the clusters. However, the healthiest dietary cluster had the highest microbial gene richness, as evaluated by quantitative metagenomics.
Conclusion: A healthier dietary pattern was associated with lower inflammatory markers as well as greater gut microbiota richness in overweight and obese subjects.
Trial registration: ClinicalTrials.gov NCT01314690.
Conflict of interest statement
Competing Interests: KOT-Ceprodi Laboratory provided funding towards this study. BH and NG were employees of Danone Research at the time that this work was conducted. FHR and RB were contracted to work on behalf of Danone Research at the time that this work was conducted. LCK received a grant from Danone Research to undertake this work as part of a PhD program. There are no patents, products in development, or marketed products to declare. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.
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References
- Schulze MB, Hoffmann K, Kroke A, Boeing H (2001) Dietary patterns and their association with food and nutrient intake in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study. Br J Nutr 85: 363–73.
- Costacou T, Bamia C, Ferrari P, Riboli E, Trichopoulos D, et al. (2003) Tracing the Mediterranean diet through principal components and cluster analyses in the Greek population. Eur J Clin Nutr 57: 1378–85.
- Kant AK (2004) Dietary patterns and health outcomes. J Am Diet Assoc 104: 615–35.
- Newby PK, Weismayer C, Akesson A, Tucker KL, Wolk A (2006) Longitudinal changes in food patterns predict changes in weight and body mass index and the effects are greatest in obese women. J Nutr 136: 2580–7.
- Schulze MB, Fung TT, Manson JE, Willett WC, Hu FB (2006) Dietary patterns and changes in body weight in women. Obesity (Silver Spring) 14: 1444–53.
- McNaughton SA, Mishra GD, Stephen AM, Wadsworth ME (2007) Dietary patterns throughout adult life are associated with body mass index, waist circumference, blood pressure, and red cell folate. J Nutr 137: 99–105.
- Schulz M, Kroke A, Liese AD, Hoffmann K, Bergmann MM, et al. (2002) Food groups as predictors for short-term weight changes in men and women of the EPIC-Potsdam cohort. J Nutr 132: 1335–40.
- Esmaillzadeh A, Kimiagar M, Mehrabi Y, Azadbakht L, Hu FB, et al. (2007) Dietary patterns and markers of systemic inflammation among Iranian women. J Nutr 137: 992–8.
- Lopez-Garcia E, Schulze MB, Fung TT, Meigs JB, Rifai N, et al. (2004) Major dietary patterns are related to plasma concentrations of markers of inflammation and endothelial dysfunction. Am J Clin Nutr 80: 1029–35.
- Ahluwalia N, Andreeva VA, Kesse-Guyot E, Hercberg S (2013) Dietary patterns, inflammation and the metabolic syndrome. Diabetes Metab 39: 99–110.
- Griep L, Wang H, Chan Q (2013) Empirically Derived Dietary Patterns, Diet Quality Scores, and Markers of Inflammation and Endothelial Dysfunction. Current Nutrition Reports 2: 97–104.
- Anderson AL, Harris TB, Tylavsky FA, Perry SE, Houston DK, et al. (2012) Dietary patterns, insulin sensitivity and inflammation in older adults. Eur J Clin Nutr 66: 18–24.
- Kesse-Guyot E, Ahluwalia N, Lassale C, Hercberg S, Fezeu L (2013) Adherence to Mediterranean diet reduces the risk of metabolic syndrome: a 6-year prospective study. Nutr Metab Cardiovasc Dis 23: 677–83.
- Cani PD, Delzenne NM (2010) Involvement of the gut microbiota in the development of low grade inflammation associated with obesity: focus on this neglected partner. Acta Gastroenterol Bel 73: 267–9.
- Turnbaugh PJ, Ridaura VK, Faith JJ, Rey FE, Knight R, et al. (2009) The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Sci Transl Med 1: 6ra14.
- Wu GD, Chen J, Hoffmann C, Bittinger K, Chen YY, et al. (2011) Linking long-term dietary patterns with gut microbial enterotypes. Science 334: 105–8.
- Cotillard A, Kennedy S, Chun Kong L, Prifti E, Pons N, et al. (2013) Dietary intervention impact on gut microbial gene richness. Nature 500: 585–588.
- Bouché C, Rizkalla S, Luo J, Vidal H, Veronese A, et al. (2002) Five week, low-glycemic idex diet decreases total fat mass and improves plasma lipid profile in moderately overweight non diabetic subjects. Diabetes Care 25: 822–828.
- Castetbon K, Bonaldi C, Deschamps V, Vernay M, Malon A, et al. (2014) Diet in 45- to 74-year-old individuals with diagnosed diabetes: comparison to counterparts without diabetes in a nationally representative survey (Etude Nationale Nutrition Sante 2006–2007). J Acad Nutr Diet 114: 918–25.
- Report E (2007) Unité de surveillance et d’épidémiologie nutritionnelle (Usen). Étude nationale nutrition santé (ENNS, 2006) – Situation nutritionnelle en France en 2006 selon les indicateurs d’objectif et les repères du Programme national nutrition santé (PNNS). Institut de veille sanitaire, Université de Paris 13, Conservatoire national des arts et métiers. Available: .
- Rizkalla SW, Prifti E, Cotillard A, Pelloux V, Rouault C, et al. (2012) Differential effects of macronutrient content in 2 energy-restricted diets on cardiovascular risk factors and adipose tissue cell size in moderately obese individuals: a randomized controlled trial. Am J Clin Nutr 95: 49–63.
- Tam CS, Viardot A, Clement K, Tordjman J, Tonks K (2011) et al. Short-term overfeeding may induce peripheral insulin resistance without altering subcutaneous adipose tissue macrophages in humans. Diabetes 2011 59: 2164–70.
- Furet JP, Kong LC, Tap J, Poitou C, Basdevant A, et al. (2010) Differential adaptation of human gut microbiota to bariatric surgery-induced weight loss: links with metabolic and low-grade inflammation markers. Diabetes 2010 59: 3049–57.
- Le Chatelier E, Nielsen T, Qin J, Prifti E, Hildebrand F, et al. (2013) Richness of human gut microbial communities correlates with metabolic markers. Nature 500: 541–546.
- Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, et al. (2010) A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464: 59–65.
- Pons N, Batto JM, Kennedy S, Almeida M, Boumezbeur F, et al. (2010) METEOR, a platform for quantitative meta-genomic profiling of complex ecosystems. in JOBIM, Montpelier, France 7–9 September: 127.
- Habi-Rachedi F, Rondeau P, Marque S, Holmes B (2012) A robust multivariate analysis to identify dietary patterns. Agrostat; 12th European symposium on statistical methods for the food industry. Paris. France 28/02-2/02.
- Estaquio C, Castetbon K, Kesse-Guyot E, Bertrais S, Deschamps V, et al. (2008) The French National Nutrition and Health Program score is associated with nutritional status and risk of major chronic diseases. J Nutr 138: 946–53.
- Liu RH (2013) Health-promoting components of fruits and vegetables in the diet. Adv Nutr 4: 384S–92S.
- Rosner B (2006) Hypothesis testing: categorical data. In: Rosner B, ed. Fundamentals of Biostatistics. Thomson-Brooks/Cole: Belmont, CA, 385–463.
- O'Connor LM, Lentjes MA, Luben RN, Khaw KT, Wareham N, et al. (2014) Dietary dairy product intake and incident type 2 diabetes: a prospective study using dietary data from a 7-day food diary. Diabetologia 57: 909–17.
- Sluijs I, Forouhi NG, Beulens JW, van der Schouw YT, Agnoli C, et al. (2012) The amount and type of dairy product intake and incident type 2 diabetes: results from the EPIC-InterAct Study. Am J Clin Nutr 96: 382–90.
- Buijsse B, Feskens EJ, Schulze MB, Forouhi NG, Wareham NJ, et al. (2009) Fruit and vegetable intakes and subsequent changes in body weight in European populations: results from the project on Diet, Obesity, and Genes (DiOGenes). Am J Clin Nutr 90: 202–9.
- Vergnaud AC, Norat T, Romaguera D, Mouw T, May AM, et al. (2012) Fruit and vegetable consumption and prospective weight change in participants of the European Prospective Investigation into Cancer and Nutrition-Physical Activity, Nutrition, Alcohol, Cessation of Smoking, Eating Out of Home, and Obesity study. Am J Clin Nutr 95: 184–93.
- Liu S, Willett W, Manson J, Hu F, Rosner B, et al. (2003) Relation between changes in intakes of dietary fiber and grain products and changes in weight and development of obesity among middle-aged women. Am J Clin Nutr 78: 920–7.
- Hu FB, Rimm EB, Stampfer MJ, Ascherio A, Spiegelman D, et al. (2000) Prospective study of major dietary patterns and risk of coronary heart disease in men. Am J Clin Nutr 72: 912–21.
- Fung TT, Willett WC, Stampfer MJ, Manson JE, Hu FB (2001) Dietary patterns and the risk of coronary heart disease in women. Arch Intern Med 161: 1857–62.
- Aron-Wisnewsky J, Tordjman J, Poitou C, Darakhshan F, Hugol D, et al. (2009) Human adipose tissue macrophages: m1 and m2 cell surface markers in subcutaneous and omental depots and after weight loss. J Clin Endocrinol Metab 94: 4619–23.
- Fujisaka S, Usui I, Kanatani Y, Ikutani M, Takasaki I, et al. (2011) Telmisartan improves insulin resistance and modulates adipose tissue macrophage polarization in high-fat-fed mice. Endocrinology 152: 1789–99.
- Odegaard JI, Ricardo-Gonzalez RR, Goforth MH, Morel CR, Subramanian V, et al. (2007) Macrophage-specific PPARgamma controls alternative activation and improves insulin resistance. Nature 447: 1116–20.
- Shi H, Kokoeva MV, Inouye K, Tzameli I, Yin H, et al. (2006) TLR4 links innate immunity and fatty acid-induced insulin resistance. J Clin Invest 116: 3015–25.
- Livingstone MB, Black AE (2003) Markers of the validity of reported energy intake. JNutr 133 Suppl 3: 895S–920S.
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