Abstract:

Objective:

To investigate the correlation among pro- or anti-inflammatory cytokines and the two main gut microbiota phyla in obese children.

Materials and methods:

Anthropometric data were obtained from 890 children under 14 years old to determine the degree of obesity. Serum cytokine concentration was measured by ELISA. Relative abundance of gut microbiota in feces was evaluated by quantitative Real-Time PCR assays.

Results:

Anthropometric and biochemical parameters were statistically higher in overweight /obese children than in lean ones. Increased TNF-α levels were found in obese children that also have a high relative abundance of Firmicutes.

Conclusions:

Obese children have a high relative abundance of Firmicutes that correlates with increased levels of TNF-α. This is the first study that shows a relation between Firmicute abundance and TNF-α serum concentration in obese children.

Keywords:
microbiota; obesity; child; TNF-α

Resumen:

Objetivo:

Investigar la correlación entre las citocinas proinflamatorias o antiinflamatorias y los dos principales filos de la microbiota intestinal en niños obesos.

Material y métodos:

Se obtuvieron mediciones antropométricas de 890 niños de 6 a 14 años; posteriormente se clasificaron en normopeso y sobrepeso/obeso. Las concentraciones séricas fueron medidas por el método de ELISA. La abundancia relativa de la microbiota intestinal en heces se evaluó por PCR tiempo real.

Resultados:

Los parámetros bioquímicos y antropométricos fueron estadísticamente más altos en niños con sobrepeso / obesidad que en niños delgados. Se encontraron niveles más altos de FNT-α en niños obesos que también tenían una abundancia relativa alta de Firmicutes.

Conclusiones:

Los niños obesos tienen una alta abundancia relativa de Firmicutes, la cual se correlaciona con un incremento de los niveles de FNT-α. Este es el primer estudio que evalúa la reacción entre la abundancia de Firmicutes y la concentración sérica de FNT-α en niños obesos.

Palabras clave:
microbiota; obesidad; niños; TNF-α

Introduction

Obesity is considered an important global health problem. In 2014, the World Health Organization (WHO) reported that 2.8 millions of people die each year as a consequence of health complications related to obesity.¹1. World Health Organization. Obesity: preventing and managing the global epidemic. Report of a WHO Consultation. Geneva: WHO Technical Report Series; 2000;894:i-xii,1-253. Obesity also affected 42 million children under the age of 5 in 2013. Mexico has the highest prevalence in childhood obesity according information from Ensanut 2012.²2. Rivera JÁ, de Cosio TG, Pedraza LS, Aburto TC, Sánchez TG, Martorell R. Childhood and adolescent overweight and obesity in Latin America: a systematic review. Lancet Diabetes Endocrinol 2014;2(4):321-332. https://doi.org/10.1016/S2213-8587(13)70173-6
https://doi.org/10.1016/S2213-8587(13)70... ^,33. Romero-Martínez M, Shamah-Levy T, Franco-Núñez A, Villalpando S, Cuevas-Nasu L, Gutiérrez JP, et al. National Health and Nutrition Survey 2012: design and coverage. Salud Publica Mex 2013;55(2):S332-S340. http://dx.doi.org/10.21149/spm.v55s2.5132
https://doi.org/10.21149/spm.v55s2.5132...

Imbalance of consumed/expended calories originates a physical state of obesity where different genetic and environmental factors also contribute.⁴4. Giles-Corti B, Macintyre S, Clarkson JP, Pikora T, Donovan RJ. Environmental and lifestyle factors associated with overweight and obesity in Perth, Australia. Am J Health Promot 2003;18(1):93-102. https://doi.org/10.4278/0890-1171-18.1.93
https://doi.org/10.4278/0890-1171-18.1.9... Altered ratio of gut microbiota (dysbiosis)⁵5. Kang S, Denman SE, Morrison M, Yu Z, Dore J, Leclerc M, et al. Dysbiosis of fecal microbiota in Crohn’s disease patients as revealed by accustom phylogenetic microarray. Inflamm Bowel Dis 2010;16(12):2034-2042. https://doi.org/10.1002/ibd.21319
https://doi.org/10.1002/ibd.21319... composed mainly by Firmicutes and Bacteroidetes,⁶6. Eckburg PB, Bik EM, Bernstein CN, Purdom E, Dethlefsen L, Sargent M, et al. Diversity of the human intestinal microbial flora. Science 2005;308(5728):1635-1638. https://doi.org/10.1126/science.1110591
https://doi.org/10.1126/science.1110591... is another factor that contributes to obesity.⁷7. Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature 2006;444(7122):1022-1023. https://doi.org/10.1038/4441022a
https://doi.org/10.1038/4441022a... A high relative abundance (RA) of Firmicutes and a low proportion of Bacteroidetes are found in adults with overweight/obesity (OW/O) compared to lean subjects.⁶6. Eckburg PB, Bik EM, Bernstein CN, Purdom E, Dethlefsen L, Sargent M, et al. Diversity of the human intestinal microbial flora. Science 2005;308(5728):1635-1638. https://doi.org/10.1126/science.1110591
https://doi.org/10.1126/science.1110591... ^,88. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, et al. A core gut microbiome in obese and lean twins. Nature 2009;457(7228):480-484. https://doi.org/10.1038/nature07540
https://doi.org/10.1038/nature07540... Recent studies including ours have shown similar findings in obese children.⁹9. Abdallah-Ismail N, Ragab SH, Abd-Elbaky A, Shoeib AR, Alhosary Y, Fekry D. Frequency of Firmicutes and Bacteroidetes in gut microbiota in obese and normal weight Egyptian children and adults. Arch Med Sci 2011;7(3):501-507. https://doi.org/10.5114/aoms.2011.23418
https://doi.org/10.5114/aoms.2011.23418... ^,1010. Bervoets L, van Hoorenbeeck K, Kortleven I, Van Noten C, Hens N, Vael C, et al. Differences in gut microbiota composition between obese and lean children: a cross-sectional study. Gut Pathog 2013;5(1):10. https://doi.org/10.1186/1757-4749-5-10
https://doi.org/10.1186/1757-4749-5-10... ^,1111. Estrada-Velasco BI, Cruz M, García-Mena J, Valladares-Salgado A, Peralta-Romero J, Guna-Serrano M de L, et al. Childhood obesity is associated to the interaction between firmicutes and high energy food consumption. Nutr Hosp 2015;31(3):1074-1081. The risk of OW/O is associated with the high abundance of Firmicutes that is dependent on the high consumption of simple carbohydrates and saturated fats, and low ingestion of micronutrients and fiber.¹¹11. Estrada-Velasco BI, Cruz M, García-Mena J, Valladares-Salgado A, Peralta-Romero J, Guna-Serrano M de L, et al. Childhood obesity is associated to the interaction between firmicutes and high energy food consumption. Nutr Hosp 2015;31(3):1074-1081.

Pro-inflammatory cytokines are known to be increased in serum of subjects with OW/O; particularly, IL-6 and TNF-α (which are also referred as adipokines released by adipocytes), that favor insulin resistance and hypertension.¹²12. Popko K, Gorska E, Stelmaszczyk-Emmel A, Plywaczewski R, Stoklosa A, Gorecka D, et al. Proinflamatory cytokines IL-6 and TNF-α and the development of inflammation in obese subjects. Eur J Med Res 2010;15(2):120-122. In contrast, the anti-inflammatory cytokine IL-10 is decreased in these subjects.¹³13. Jung SH, Park HS, Kim KS, Choi WH, Ahn CW, Kim BT, et al. Effect of weight loss on some serum cytokines in human obesity: increase in IL-10 after weight loss. J Nutr Biochem 2008;19(6):371-375. https://doi.org/10.1016/j.jnutbio.2007.05.007
https://doi.org/10.1016/j.jnutbio.2007.0... In order to determine if a pro-inflammatory state associated with a type of gut microbiota is found in obese children, we investigated the correlation of Firmicutes and Bacteroidetes with both pro- or anti-inflammatory cytokines in this population.

Materials and methods

Subject and study design

To accomplish the present study, samples from 890 children residents from Mexico City were obtained from a previous study.¹¹11. Estrada-Velasco BI, Cruz M, García-Mena J, Valladares-Salgado A, Peralta-Romero J, Guna-Serrano M de L, et al. Childhood obesity is associated to the interaction between firmicutes and high energy food consumption. Nutr Hosp 2015;31(3):1074-1081. Participants answered a semi-quantitative food frequency questionnaire (FFQ) that included 107-items. All these options were coded for daily consumption of each item for each individual in the study. The grams per serving of each food included in the FFQ to obtain the total energy consumption per day (k/calories) were based on those used for the National Health and Nutrition Survey (Ensanut).¹⁴14. Gutiérrez JP, Rivera-Dommarco J, Shamah-Levy T, Villalpando-Hernández S, Franco A, Cuevas-Nasu L, et al. Encuesta Nacional de Salud y Nutrición 2012. Resultados Nacionales. Cuernavaca, México: Instituto Nacional de Salud Pública, 2012.

Physical activity (PA) was measured as physical activity in leisure time, in which frequency (days per week) and duration were asked (never, minutes per day or hours per day). The answers were expressed as metabolic equivalents by hour per week (Mets: h/wk.). Inclusion criteria for the study were non-relative children of 6 to 14 years old. Exclusion criteria were children who had diagnosis of infectious disease, gastrointestinal disorders, administration of antimicrobial agents (within 6 months previous to study), incomplete questionnaires or biological samples. All parents signed the informed consent. The study was approved by the ethics and research committee of Instituto Nacional de Salud Pública (INSP) CI:1129, No. 1294.

Anthropometric features and blood biochemical parameters

Variables of anthropometric features included weight (kg), height (cm), waist circumference (cm) and hip circumference (cm). BMI (kg/m²) was calculated from weight and height. Measurements were performed by previously trained personnel that used standardized techniques and calibrated instruments. Children were evaluated without shoes and with the least amount of clothing. Condition of NW and OW/O were assessed according to the BMI z-score for age and gender as reported by the WHO:¹⁵15. De Onis M, Onyango A, Borghi E, Siyam A, Nishida Ch, Siekmann J. Development of a WHO growth reference for schoolaged children and adolescents. Bull World Health Organ 2007;85:660-667. https://doi.org/10.2471/BLT.07.043497
https://doi.org/10.2471/BLT.07.043497... Normal weight -2 to -1 SD, Overweight >+1 to 2 SD and Obesity >+2 SD).

Venous blood samples were collected after 12 hours fasting for biochemical studies. Values of fasting glucose, total cholesterol, plasma high-density lipoprotein cholesterol fraction (HDL-c), plasma low-density lipoprotein cholesterol fraction (LDL-c) and triglycerides were obtained by using the ILab 350 Clinical Chemistry System (Instrumentation Laboratory IL. Barcelona, Spain). Insulin (μU/mL) was measured by the IMMULITE Chemiluminescent Immunoassay System, and the insulin resistance was calculated by the homeostasis model assessment (HOMA). Systolic blood pressure (SBP) and dyastolic blood pressure (DBP) were measured with calibrated Sphygmomanometer. Two measurements were taken to obtain a blood pressure average.

DNA purification and quantitative Real-Time PCR (qPCR) assays

A container sterile of polypropylene was provided to the parents for a stool sample collection. Fecal aliquots (180 to 220 mg) were stored in a cryogenic vial at -80 °C until use. DNA extraction from feces was carried out using QIAamp DNA stool kit (Qiagen, Hilden, North Rhine-Westphalia, Germany), according to the manufacturer´s instructions. DNA concentration and purity (260/280) was evaluated using NanoDrop 1000 LITE Spectrophotometer (Thermo Scientific, Wilmington, DE, USA). We used the previously reported¹⁶16. Bacchetti De Gregoris T, Aldred N, Clare AS, Burgess JG. Improvement of phylum- and class-specific primers for real-time PCR quantification of bacterial taxa. J Microbiol Methods 2011;86(3):351-356. https://doi.org/10.1016/j.mimet.2011.06.010
https://doi.org/10.1016/j.mimet.2011.06.... taxon-specific primers to detect the presence of Bacteroidetes/Firmicutes, and universal primers to amplify all members of the taxon. qPCR was performed in a total volume of 10 μl containing 5 ng of DNA, 5 ml of 2X Maxima SYBR Green/ROX qPCR Master Mix (Thermo Fisher Scientific, Foster City, California, USA), 1 pmol and 5 pmol of forward and reverse primers respectively, and 2 ml of DNase/ RNase-Free Water. The PCR program for all primers was as follows: 5 min at 95°C; 30 cycles of 15 s at 95°C, 15 s at 63°C (Universal and Bacteroidetes primers) or 58°C (Firmicutes) and a final cycle of 20 s at 72 °C. PCR amplifications were performed in an ABI PRISM-7900HT sequence detection system (Applied Biosystems, Foster City, California, USA). The specificity of the amplification products and the absence of primer dimers were determined by performing melting curve analyses in all cases. The standard curve for each primer was generated by 5-fold serial dilutions of bacterial DNA. The efficiency of PCR amplification for each gene was calculated using the standard curve method, E=10^(−1/slope) −1. Relative abundance of Firmicutes and Bacteroidetes (RA) were calculated using the following formula: 2^-∆CT [2^{-(CT of the Firmicutes/Bacteroidetes primer- CT Universal primer)}].¹⁷17. Schmittgen TD, Livak KJ. Analyzing real-time PCR data by the comparative CT method. Nat Protoc 2008;3(6):1101-1108. https://doi.org/10.1038/nprot.2008.73
https://doi.org/10.1038/nprot.2008.73... The RA of microbiota is an estimation of a phylum density over another expressed as bacterial units. It reveals the distribution difference of bacterial population in certain area.

Cytokines measurement in blood

In the same conditions previously mentioned for biochemical studies, another blood sample was obtained and centrifuged to obtain the serum and stored it at -80 °C until use. Serum concentrations of TNF-α, IL-6, IL-10 were measured by ELISA kits according to the manufacturer’s instructions (Peprotech Rock Hill, NJ,8 USA). The absorbance was determined in a Labsystems Multiskan MS. Results were expressed as pg/ml.

Statistical analysis

Results were organized to generate databases for the different variables. In the first analysis, a descriptive study of quantitative data was performed, obtaining data for qualitative variables, frequencies and percentages. Additionally, the Shapiro-Wilk test was used to determine if data have a normal distribution. A non-parametric analysis was carried out with non-normal distributed data calculated by Kruskall Wallis. Logistic regression models were performed to evaluate the association of RA of microbiota and inflammatory cytokines profile within each category of BMI, which were categorized in NW vs OW/O. All models were adjusted for age, gender, total energy intake and heredofamilial history of obesity (variable of family history was based on one or both parents who were or had been obese). The correlation between cytokine profiles and BMI in relation to tertiles of Firmicutes and Bacteroidetes RA was calculated by the Spearman rank correlation coefficient. Statistical analyses were carried out using the version 13.0 from the STATA SE software (StataCorp. 2013. Stata Statistical Software: Release 13. College Station, TX: StataCorp LP.). Statistical significant level was considered as P value <0.05.

Results

Clinical characteristics associated with obesity

According to the z-score BMI children were classified in the category of NW (n=383) and OW/O (n=507). These children had a mean age of 9.1 (± 2.04) and 9.3 (± 1.9) years old, respectively. Waist circumference, a potential indicator of metabolic syndrome, was increased in children with OW/O. SBP, DBP, LDL-c, glucose, triglycerides, insulin, insulin resistance and cholesterol were statistically higher in children with OW/O than in children with NW. In contrast, a low HDL-c was found in OW/O children compared to NW subjects. No statistical differences were identified in total energy intake, the total metabolic equivalent task (METs) and gender (table I).

Relative abundance of Firmicutes and Bacteroidetes in obese children

We observed a significant increase in the RA of Firmicutes (1.7±5.9; p <0.001) and a decrease in Bacteroidetes (0.7±1.4; p = 0.03) in children with OW/O compared with NW children (table I).

Association of medium and high RA of Firmicutes in childhood obesity

To evaluate the association of Firmicutes and Bacteroidetes RA with the degree of adiposity, we used a model of multiple logistic regression adjusted for age, gender, total energy intake and heredofamilial history of obesity. RA was classified into tertiles of high, medium and low abundance considering a cut-off based on NW children. We observed a statistically significant association between medium (OR= 2.07) or high (OR=1.69) proportion of Firmicutes and obesity. Furthermore, an inverse association between high tertiles of Bacteroidetes RA was observed in children with OW/O (table II).

Increased TNF-α is related to children obesity

Serum concentrations of TNF-α were significantly increased in the group of obese children (p= 0.01). No significant differences were observed in the levels of IL-6 and IL-10 (table III).

Cytokines and BMI correlation by relative abundance of microbiota in obese children

To evaluate the correlation between cytokine profile and degree of adiposity dependent on gut microbiota RA stratified by tertiles, we calculated the Spearman correlation coefficient. We observed a positive correlation between the concentration of TNF-α with BMI in the highest tertile of Firmicutes (p = 0.02). We also showed a positive correlation of TNF-α levels with BMI in the low tertiles of Bacteroidetes being statistically significant (p = 0.04) (table IV).

Discussion

Gut microbiota plays an important role in the steady state of metabolism and immune responses; thus, an altered ratio of different phyla may lead to diverse health imbalances. In this work, we found a positive correlation between TNF-α serum concentration and the degree of obesity in the highest tertile of Firmicutes RA in children. Other authors have reported an increase in the proportion of Firmicutes in animal models and adults with obesity.¹⁸18. DiBaise JK, Zhang H, Crowell MD, Krajmalnik-Brown R, Decker GA, Rittmann BE. Gut Microbiota and its possible relationship with obesity. Mayo Clin Proc 2008;83(4):460-469. https://doi.org/10.4065/83.4.460
https://doi.org/10.4065/83.4.460... ^,1919. Ley RE, Bäckhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI. Obesity alters gut microbial ecology. Proc Natl Acad Sci USA 2005;102(31):11070-11075. https://doi.org/10.1073/pnas.0504978102
https://doi.org/10.1073/pnas.0504978102... Similar to our results, an increase in the proportion of these phyla was observed in European and African OW/W children compared to NW children.⁹9. Abdallah-Ismail N, Ragab SH, Abd-Elbaky A, Shoeib AR, Alhosary Y, Fekry D. Frequency of Firmicutes and Bacteroidetes in gut microbiota in obese and normal weight Egyptian children and adults. Arch Med Sci 2011;7(3):501-507. https://doi.org/10.5114/aoms.2011.23418
https://doi.org/10.5114/aoms.2011.23418... ^,1010. Bervoets L, van Hoorenbeeck K, Kortleven I, Van Noten C, Hens N, Vael C, et al. Differences in gut microbiota composition between obese and lean children: a cross-sectional study. Gut Pathog 2013;5(1):10. https://doi.org/10.1186/1757-4749-5-10
https://doi.org/10.1186/1757-4749-5-10... ^,2020. Sepp E, Loivukene K, Julge K, Voor T, Mikelsaar M. The association of gut microbiota with body weight and body mass index in preschool children of Estonia. Microb Ecol Health Dis 2013;24:19231. https://doi.org/10.3402/mehd.v24i0.19231
https://doi.org/10.3402/mehd.v24i0.19231... However, several studies in adults have found an increase of Bacteroidetes,²¹21. Schwiertz A, Taras D, Schäfer K, Beijer S, Bos NA, Donus C, et al. Microbiota and SCFA in lean and overweight healthy subjects. Obesity (Silver Spring) 2010;18(1):190-195. https://doi.org/10.1038/oby.2009.167
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https://doi.org/10.1007/s12038-012-9244-... less proportion of Firmicutes, unaltered Bacteroidetes ratio,²³23. Escobar JS, Klotz B, Valdes BE, Agudelo GM. The gut microbiota of Colombians differs from that of Americans, Europeans and Asians. BMC Microbiol 2014;14:311. https://doi.org/10.1186/s12866-014-0311-6
https://doi.org/10.1186/s12866-014-0311-... or no differences in the proportions between these two phyla with the obesity degree.²⁴24. Fernandes J, Su W, Rahat-Rozenbloom S, Wolever TM, Comelli EM. Adiposity, gut microbiota and faecal short chain fatty acids are linked in adult humans. Nutr Diabetes 2014;4:e121. https://doi.org/10.1038/nutd.2014.23
https://doi.org/10.1038/nutd.2014.23... ^,2525. Kocelak P, Zak-Golab A, Zahorska-Markiewicz B, Aptekorz M, Zientara M, Martirosian G, et al. Resting energy expenditure and gut microbiota in obese and normal weight subjects. Eur Rev Med Pharmacol Sci 2013;17(20):2816-2821. In the present study, we found a high relation of Firmicutes/Bacteroidetes in obese children which is consistent with other studies.⁷7. Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature 2006;444(7122):1022-1023. https://doi.org/10.1038/4441022a
https://doi.org/10.1038/4441022a... ^,2626. Turnbaugh PJ, Ley ER, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006;444(7122):1027-1031. https://doi.org/10.1038/nature05414
https://doi.org/10.1038/nature05414... ^,2727. Mariat D, Firmesse O, Levenez F, Guimarăes V, Sokol H, Doré J, et al. The Firmicutes/Bacteroidetes ratio of the human microbiota changes with age. BMC Microbiol 2009;9:123. https://doi.org/10.1186/1471-2180-9-123
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These controversial results could be explained by lifestyles, ethnic groups,²⁹29. Ishikawa E, Matsuki T, Kubota H, Makino H, Sakai T, Oishi K, et al. Ethnic diversity of gut microbiota: species characterization of Bacteroides fragilis group and genus Bifidobacterium in healthy Belgian adults, and comparison with data from Japanese subjects. J Biosci Bioeng 2013;116(2):265-270. https://doi.org/10.1016/j.jbiosc.2013.02.010
https://doi.org/10.1016/j.jbiosc.2013.02... ^,3030. Yasir M, Angelakis M, Bibi F, Azhar EI, Bachar D, Lagier JC, et al. Comparison of the gut microbiota of people in France and Saudi Arabia. Nutr Diabetes 2015;5:e153. https://doi.org/10.1038/nutd.2015.3
https://doi.org/10.1038/nutd.2015.3... geographic origin²³23. Escobar JS, Klotz B, Valdes BE, Agudelo GM. The gut microbiota of Colombians differs from that of Americans, Europeans and Asians. BMC Microbiol 2014;14:311. https://doi.org/10.1186/s12866-014-0311-6
https://doi.org/10.1186/s12866-014-0311-... and even by the different experimental, bioinformatics and cohort selection methodologies used.³¹31. William A Walters, Zech Xu, Rob Knight. Meta-analyses of human gut microbes associated with obesity and IBD. FEBS Lett 2014:588(22):4223-4233. https://doi.org/10.1016/j.febslet.2014.09.039
https://doi.org/10.1016/j.febslet.2014.0... Diet is considered a trigger of intestinal microbiota diversity by altering the gut microenvironment.³²32. De Filippo C, Cavalieri D, Di Paola M, Ramazzotti M, Poullet JB, Massart S, et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci USA 2010;107(33):14691-14696. https://doi.org/10.1073/pnas.1005963107
https://doi.org/10.1073/pnas.1005963107... ^,3333. Yatsunenko T, Rey FE, Manary MJ, Trehan I, Dominguez-Bello MG, Contreras M, et al. Human gut microbiome viewed across age and geography. Nature 2012;486(7402):222-227. https://doi.org/10.1038/nature11053
https://doi.org/10.1038/nature11053... ^,3434. Nakayama J, Watanabe K, Jiang J, Matsuda K, Chao SH, Haryono P, et al. Diversity in gut bacterial community of school-age children in Asia. Sci Rep 2015;5:8397. https://doi.org/10.1038/srep08397
https://doi.org/10.1038/srep08397... ^,3535. La-Ongkham O, Nakphaichit M, Leelavatcharamas V, Keawsompong S, Nitisinprasert S. Distinct gut microbiota of healthy children from two different geographic regions of Thailand. Arch Microbiol 2015;197(4):561-573. https://doi.org/10.1007/s00203-015-1089-0
https://doi.org/10.1007/s00203-015-1089-... Recently, we reported that gut microbiota, particularly the phylum Firmicutes and a high fat diet increases the chance of developing obesity.¹¹11. Estrada-Velasco BI, Cruz M, García-Mena J, Valladares-Salgado A, Peralta-Romero J, Guna-Serrano M de L, et al. Childhood obesity is associated to the interaction between firmicutes and high energy food consumption. Nutr Hosp 2015;31(3):1074-1081. This observation is in agreement with our data (table II), where the medium and high tertiles of Firmicutes RA were statistically associated with obesity, suggesting that the amount of Firmicutes RA is important to get a state of obesity. This finding is also related to a previous study where it is suggested that gut microbiota affects the expression of secretory proteins in the gut, which modulate lipid metabolism in peripheral organs.³⁶36. Bäckhed F. Programming of host metabolism by the gut microbiota. Ann Nutr Metab 2011;58(2):44-52. https://doi.org/10.1159/000328042
https://doi.org/10.1159/000328042... Furthermore, metagenomic analysis have shown an overrepresentation of genes involved in energy storage in the obese mice microbiome.²⁶26. Turnbaugh PJ, Ley ER, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006;444(7122):1027-1031. https://doi.org/10.1038/nature05414
https://doi.org/10.1038/nature05414... These results are of great importance since Firmicutes have a greater number of genes encoding for hydrolases and other genes involved in promoting energy uptake from the host diet than Bacteroidetes.²⁶26. Turnbaugh PJ, Ley ER, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006;444(7122):1027-1031. https://doi.org/10.1038/nature05414
https://doi.org/10.1038/nature05414... It was observed in mice that hydrolysis of high concentration of saturated short chain fatty acids is favored by enzymes from Firmicutes. This activity is determinated by the inhibition of intestinal epithelium tight junctions,³⁷37. Osborn O, Olefsky J. The cellular and signaling networks linking the immune system and metabolism in disease. Nat Med 2012;18(3):1-10. https://doi.org/10.1038/nm.2627
https://doi.org/10.1038/nm.2627... favoring a translocation of LPS to circulation, which is recognized by the Toll like Receptor 4 (TLR4). This receptor activates the NF-kB pathway resulting in overexpression of TNF-α that promotes inflammation.³⁸38. Cani PD, Bibiloni R, Knauf C, Waget A, Neyrinck AM, Delzene NM, Burcelin R. Changes in gut microbiota control metabolic endotoxemia-induced inflammation in high-fat diet-induced obesity and diabetes in mice. Diabetes 2008;57(6):1470-1481. https://doi.org/10.2337/db07-1403
https://doi.org/10.2337/db07-1403...

A remarkable finding in our study was the presence of inflammation markers associated with microbiota and childhood obesity. We found a positive correlation of TNF-α serum concentrations, with BMI adjusted by age and dependent on the microbiota profile. A correlation of 16% of TNF-α levels was observed in those children with the highest tertile of Firmicutes RA and 13% with the lowest tertile of Bacteroidetes RA. Our findings are consistent with those studies. Although gut microbiota is considered a source of pro-inflammatory molecules that enhance adipose inflammation and macrophage recruitment by signaling through the innate immune system, also is a good source of anti-inflammatory molecules such as the genus Lactobacillus and Bifidobacterium and bacterial species like Faecalibacterium prausnitzii and Lactobacillus plantarum.³⁶36. Bäckhed F. Programming of host metabolism by the gut microbiota. Ann Nutr Metab 2011;58(2):44-52. https://doi.org/10.1159/000328042
https://doi.org/10.1159/000328042... ^,3737. Osborn O, Olefsky J. The cellular and signaling networks linking the immune system and metabolism in disease. Nat Med 2012;18(3):1-10. https://doi.org/10.1038/nm.2627
https://doi.org/10.1038/nm.2627... ^,3838. Cani PD, Bibiloni R, Knauf C, Waget A, Neyrinck AM, Delzene NM, Burcelin R. Changes in gut microbiota control metabolic endotoxemia-induced inflammation in high-fat diet-induced obesity and diabetes in mice. Diabetes 2008;57(6):1470-1481. https://doi.org/10.2337/db07-1403
https://doi.org/10.2337/db07-1403... ^,3939. Cavalcante-Silva LH, Galvão JG, da Silva JS, de Sales-Neto JM, Rodrigues-Mascarenhas S. Obesity-Driven Gut Microbiota Inflammatory Pathways to Metabolic Syndrome. Front Physiol 2015;6:341. https://doi.org/10.3389/fphys.2015.00341
https://doi.org/10.3389/fphys.2015.00341...

According to our results, we suggest that a constant state of obesity in children is followed by a degree of chronic inflammation with a high expression of TNF-α that may be induced by the altered gut microbiota where Firmicutes phylum prevails. As far as we know, this is the first study that shows a relation between increase of Firmicutes and TNF-α expression in obese children. This study has the limitations of a cross-sectional study to determine the causal effects, however, one of the study strengths is that parameters analyzed were double-blind to avoid bias in measuring.

Acknowledgments

We are grateful to all children and parents participating in this study. To the nutritionist Andrea Bustos Bonfil for her advice on the project. This work was supported by the SSA/IMSS/ISSSTE-CONACYT 2012 -180808, the CONACYT SALUD-2005-C02-14412 and Proyectos Estratégicos IMSS 2004-3601-0020 Fundación IMSS, A.C.

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