Abstract
Background: We evaluated the relationship between an early inflammatory biomarker, chemokine (C-C motif) ligand 2 (CCL2), and other clinical biomarkers and lifestyle behaviors, in overweight/obese adolescents at high risk of developing cardiometabolic derangements.
Methods: We collected anthropometric measurements, clinical biomarkers, and three 24-h dietary recalls from 21 vocational high school students (91% male), 14–19 years, with body mass index (BMI) ≥25 kg/m2. Pearson’s or Spearman’s correlation coefficients were used to examine relationships.
Results: Mean BMI was 33.2 kg/m2 (range 25.7–45.6) and 38% were prediabetic by fasting glucose. Mean CCL2 was 512.9 pg/mL (range 220–917) and positively correlated with triglycerides (r=0.45; p=0.04) and TNF-α (r=0.57; p=0.007) and marginally negatively correlated with fruit/vegetable intake (r=–0.42, p=0.06) and omega-3 fatty acids (r=–0.41, p=0.07).
Conclusions: CCL2 was positively associated with pro-inflammatory biomarkers and negatively associated with some anti-inflammatory dietary factors.
Acknowledgments
This study was supported by a La Tierra Sagrada Society Community Grant and by CTSC grant DHHS/NIH/NCRR #8UL1TR000041. We sincerely appreciate the participating students and the support we received from the school and school health clinic staff, especially Zach Chavez, Keith Haynie, James Shoemate and Tori Stephens-Shauger. We are also grateful for the contributions of Amanda Harris from the UNM Division of Adolescent Medicine in the Department of Pediatrics, Sarah Sanders from the UNM Prevention Research Center, and Amanda Hernandez, Valerie Vieira, and Brittany Mally from the UNM Nutrition Program to data collection.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: See Acknowledgments section above.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
References
1. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011–2012. J Am Med Assoc 2014;311:806–14.10.1001/jama.2014.732Search in Google Scholar PubMed PubMed Central
2. Harris KM, Gordon-Larsen P, Chantala K, Udry JR. Longitudinal trends in race/ethnic disparities in leading health indicators from adolescence to young adulthood. Arch Pediat Adol Med 2006;160:74–81.10.1001/archpedi.160.1.74Search in Google Scholar PubMed
3. Must A, Strauss RS. Risks and consequences of childhood and adolescent obesity. Int J Obesity 1999;23:S2–11.10.1038/sj.ijo.0800852Search in Google Scholar PubMed
4. Freedman DS, Dietz WH, Srinivasan SR, Berenson GS. The relation of overweight to cardiovascular risk factors among children and adolescents: the Bogalusa heart study. Pediatrics 1999;103:1175–82.10.1542/peds.103.6.1175Search in Google Scholar PubMed
5. Uusitupa M, Schwab U. Diet, Inflammation and prediabetes-impact of quality of diet. Can J Diabetes 2013;37:327–31.10.1016/j.jcjd.2013.07.029Search in Google Scholar PubMed
6. Gregor MF, Hotamisligil GS. Inflammatory mechanisms in obesity. In: Paul WE, Littman DR, Yokoyama WM, editors. Annual review of immunology, Vol 29. Palo Alto: Annual Reviews, 2011:415–45.Search in Google Scholar
7. Dali-Youcef N, Mecili M, Ricci R, Andres E. Metabolic inflammation: connecting obesity and insulin resistance. Ann Med 2013;45:242–53.10.3109/07853890.2012.705015Search in Google Scholar PubMed
8. Rull A, Camps J, Alonso-Villaverde C, Joven J. Insulin resistance, inflammation, and obesity: role of monocyte chemoattractant protein-1 (or CCL2) in the regulation of metabolism. Mediat Inflamm 2010;2010.10.1155/2010/326580Search in Google Scholar PubMed PubMed Central
9. Virdis A, Dell’Agnello U, Taddei S. Impact of inflammation on vascular disease in hypertension. Maturitas 2014;78:179–83.10.1016/j.maturitas.2014.04.012Search in Google Scholar PubMed
10. Chung S, LaPoint K, Martinez K, Kennedy A, Sandberg MB, McIntosh MK. Preadipocytes mediate lipopolysaccharide-induced inflammation and insulin resistance in primary cultures of newly differentiated human adipocytes. Endocrinology 2006;147:5340–51.10.1210/en.2006-0536Search in Google Scholar PubMed
11. Daniele G, Mendoza RG, Winnier D, Fiorentino TV, Pengou Z, Cornell J, et al. The inflammatory status score including IL-6, TNF-alpha, osteopontin, fractalkine, MCP-1 and adiponectin underlies whole-body insulin resistance and hyperglycemia in type 2 diabetes mellitus. Acta Diabetol 2014;51:123–31.10.1007/s00592-013-0543-1Search in Google Scholar PubMed
12. Kouyama K, Miyake K, Zenibayashi M, Hirota Y, Teranishi T, Tamori Y, et al. Association of serum MCP-1 concentration and MCP-1 polymorphism with insulin resistance in Japanese individuals with obese type 2 diabetes. Kobe J Med Sci 2007;53:345–54.Search in Google Scholar
13. Kanda H, Tateya S, Tamori Y, Kotani K, Hiasa KI, Kitazawa R, et al. MCP-1 contributes to macrophage infiltration into adipose tissue, insulin resistance, and hepatic steatosis in obesity. J Clin Invest 2006;116:1494–505.10.1172/JCI26498Search in Google Scholar PubMed PubMed Central
14. Breslin WL, Johnston CA, Strohacker K, Carpenter KC, Davidson TR, Moreno JP, et al. Obese Mexican American children have elevated MCP-1, TNF-alpha, monocyte concentration, and dyslipidemia. Pediatrics 2012;129:E1180–6.10.1542/peds.2011-2477Search in Google Scholar PubMed
15. Samaan MC, Obeid J, Nguyen T, Thabane L, Timmons BW. Chemokine (C-C motif) ligand 2 is a potential biomarker of inflammation and physical fitness in obese children: a cross-sectional study. BMC Pediatr 2013;13:47.10.1186/1471-2431-13-47Search in Google Scholar PubMed PubMed Central
16. Stoppa-Vaucher S, Dirlewanger MA, Meier CA, de Moerloose P, Reber G, Roux-Lombard P, et al. Inflammatory and prothrombotic states in obese children of European descent. Obesity 2012;20:1662–8.10.1038/oby.2012.85Search in Google Scholar PubMed
17. Hauner H. Secretory factors from human adipose tissue and their functional role. P Nutr Soc 2005;64:163–9.10.1079/PNS2005428Search in Google Scholar
18. Roth CL, Kratz M, Ralston MM, Reinehr T. Changes in adipose-derived inflammatory cytokines and chemokines after successful lifestyle intervention in obese children. Metabolism 2011;60:445–52.10.1016/j.metabol.2010.03.023Search in Google Scholar PubMed
19. Lee JY, Zhao L, Youn HS, Weatherill AR, Tapping R, Feng LL, et al. Saturated fatty acid activates but polyunsaturated fatty acid inhibits toll-like receptor 2 dimerized with toll-like receptor 6 or 1. J Biol Chem 2004;279:16971–9.10.1074/jbc.M312990200Search in Google Scholar PubMed
20. Lee JY, Zhao L, Hwang DH. Modulation of pattern recognition receptor-mediated inflammation and risk of chronic diseases by dietary fatty acids. Nutr Rev 2010;68:38–61.10.1111/j.1753-4887.2009.00259.xSearch in Google Scholar PubMed
21. Zhao L, Lee JY, Hwang DH. Inhibition of pattern recognition receptor-mediated inflammation by bioactive phytochemicals. Nutr Rev 2011;69:310–20.10.1111/j.1753-4887.2011.00394.xSearch in Google Scholar PubMed PubMed Central
22. Thota C, Farmer T, Garfield RE, Menon R, Al-Hendy A. Vitamin D elicits anti-inflammatory response, inhibits contractile-associated proteins, and modulates Toll-like receptors in human myometrial cells. Reprod Sci 2013;20:463–75.10.1177/1933719112459225Search in Google Scholar PubMed PubMed Central
23. Wang LK, Gao SJ, Jiang W, Luo C, Xu MN, Bohlin L, et al. Antioxidative dietary compounds modulate gene expression associated with apoptosis, DNA repair, inhibition of cell proliferation and migration. Int J Mol Sci 2014;15:16226–45.10.3390/ijms150916226Search in Google Scholar PubMed PubMed Central
24. Gonzalez-Gallego J, Garcia-Mediavilla MV, Sanchez-Campos S, Tunon MJ. Fruit polyphenols, immunity and inflammation. Brit J Nutr 2010;104:S15–27.10.1017/S0007114510003910Search in Google Scholar PubMed
25. Wang Y, Yang M, Lee SG, Davis CG, Koo SI, Fernandez ML, et al. Diets high in total antioxidant capacity improve risk biomarkers of cardiovascular disease: a 9-month observational study among overweight/obese postmenopausal women. Eur J Nutr 2014;53:1363–9.10.1007/s00394-013-0637-0Search in Google Scholar PubMed
26. Spencer M, Finlin BS, Unal R, Zhu BB, Morris AJ, Shipp LR, et al. Omega-3 fatty acids reduce adipose tissue macrophages in human subjects with insulin resistance. Diabetes 2013;62:1709–17.10.2337/db12-1042Search in Google Scholar PubMed PubMed Central
27. Jones KW, Eller LK, Parnell JA, Doyle-Baker PK, Edwards AL, Reimer RA. Effect of a dairy- and calcium-rich diet on weight loss and appetite during energy restriction in overweight and obese adults: a randomized trial. Eur J Clin Nutr 2013;67:371–6.10.1038/ejcn.2013.52Search in Google Scholar PubMed PubMed Central
28. Kovacikova M, Sengenes C, Kovacova Z, Siklova-Vitkova M, Klimcakova E, Polak J, et al. Dietary intervention-induced weight loss decreases macrophage content in adipose tissue of obese women. Int J Obesity 2011;35:91–8.10.1038/ijo.2010.112Search in Google Scholar PubMed
29. Lucotti P, Monti LD, Setola E, Galluccio E, Gatti R, Bosi E, et al. Aerobic and resistance training effects compared to aerobic training alone in obese type 2 diabetic patients on diet treatment. Diabetes Res Clin Pr 2011;94:395–403.10.1016/j.diabres.2011.08.002Search in Google Scholar PubMed
30. Dangardt F, Osika W, Chen Y, Nilsson U, Gan LM, Gronowitz E, et al. Omega-3 fatty acid supplementation improves vascular function and reduces inflammation in obese adolescents. Atherosclerosis 2010;212:580–5.10.1016/j.atherosclerosis.2010.06.046Search in Google Scholar PubMed
31. Centers for Disease Control and Prevention (CDC). Defining childhood obesity 2015 [cited 2015 Sept 10]. Available from: http://www.cdc.gov/obesity/childhood/defining.html.Search in Google Scholar
32. Lohman TG, Roche AF, Martorell R, eds. Anthropometric standardization reference manual. Champaign, IL: Human Kinetics Books, 1988.Search in Google Scholar
33. National Health and Nutrition Examination Survey (NHANES): anthropometry procedures manual. Atlanta, GA, USA: Centers For Disease Control and Prevention, 2007. Available from: http://www.cdc.gov/nchs/data/nhanes/nhanes_07_08/manual_an.pdf.Search in Google Scholar
34. Prevention CfDCa. Percentile Data Files with LMS values, 2000.Search in Google Scholar
35. Cook S, Auinger P, Huang TT. Growth curves for cardio-metabolic risk factors in children and adolescents. J Pediatr 2009;155:S6.e15–26.10.1016/j.jpeds.2009.04.051Search in Google Scholar PubMed PubMed Central
36. National Health and Nutrition Examination Survey (NHANES): high tech/blood pressures procedures manual. Atlanta, GA, USA: Centers for Disease Control and Prevention, 2009. Available from: http://www.cdc.gov/nchs/data/nhanes/nhanes_09_10/bp.pdf.Search in Google Scholar
37. National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and A. The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Pediatrics 2004;114(2 Suppl 4th Report):555–76.10.1542/peds.114.S2.555Search in Google Scholar
38. Association AD. Diabetes Advocacy Sec 14. In Standards of Medical Care in Diabetes-2015. Diabetes Care, 2015:S86–7.10.2337/dc15-S017Search in Google Scholar PubMed
39. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment – insulin resistance and beta-cell function from fasting plasma-glucose and insulin concentrations in man. Diabetologia 1985;28:412–9.10.1007/BF00280883Search in Google Scholar PubMed
40. Conwell LS, Trost SG, Brown WJ, Batch JA. Indexes of insulin resistance and secretion in obese children and adolescents – a validation study. Diabetes Care 2004;27:314–9.10.2337/diacare.27.2.314Search in Google Scholar PubMed
41. Keskin M, Kurtoglu S, Kendirci M, Atabek ME, Yazici C. Homeostasis model assessment is more reliable than the fasting glucose/insulin ratio and quantitative insulin sensitivity check index for assessing insulin resistance among obese children and adolescents. Pediatrics 2005;115:E500–3.10.1542/peds.2004-1921Search in Google Scholar PubMed
42. New Mexico: Youth Risk and Resiliency Survey (YRRS) High School Questionnaire, 2013. Available from: http://www.youthrisk.org/pdf/YRRS-2013-HS-E-Std.pdf.Search in Google Scholar
43. U.S. Department of Health and Human Services. Physical activity guidelines for Americans. Washington, DC: U.S. Department of Health and Human Services, 2008.Search in Google Scholar
44. Moshfegh AJ, Rhodes DG, Baer DJ, Murayi T, Clemens JC, Rumpler WV, et al. The US department of agriculture automated multiple-pass method reduces bias in the collection of energy intakes. Am J Clin Nutr 2008;88:324–32.10.1093/ajcn/88.2.324Search in Google Scholar PubMed
45. Blanton CA, Moshfegh AJ, Baer DJ, Kretsch MJ. The USDA automated multiple-pass method accurately estimates group total energy and nutrient intake. J Nutr 2006;136:2594–9.10.1093/jn/136.10.2594Search in Google Scholar PubMed
46. Burrows TL, Martin RJ, Collins CE. Systematic review of the validity of dietary assessment methods in children when compared with the method of doubly labeled water. J Am Diet Assoc 2010;110:1501–10.10.1016/j.jada.2010.07.008Search in Google Scholar PubMed
47. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)-A metadata- driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42:377–81.10.1016/j.jbi.2008.08.010Search in Google Scholar PubMed PubMed Central
48. Inadera H, Egashira K, Takemoto M, Ouchi Y, Matsushima K. Increase in circulating levels of monocyte chemoattractant protein-1 with aging. J Interf Cytok Res 1999;19:1179–82.10.1089/107999099313127Search in Google Scholar PubMed
49. Fain JN, Madan AK. Regulation of monocyte chemoattractant protein 1 (MCP-1) release by explants of human visceral adipose tissue. Int J Obesity 2005;29:1299–307.10.1038/sj.ijo.0803032Search in Google Scholar PubMed
50. Ting HJ, Stice JP, Schaff UY, Hui DY, Rutledge JC, Knowlton AA, et al. Triglyceride-rich lipoproteins prime aortic endothelium for an enhanced inflammatory response to tumor necrosis factor-alpha. Circ Res 2007;100:381–90.10.1161/01.RES.0000258023.76515.a3Search in Google Scholar PubMed
51. Sutliffe JT, Wilson LD, de Heer HD, Foster RL, Carnot MJ. C-reactive protein response to a vegan lifestyle intervention. Complement Ther Med 2015;23:32–7.10.1016/j.ctim.2014.11.001Search in Google Scholar PubMed
52. Root MM, McGinn MC, Nieman DC, Henson DA, Heinz SA, Shanely RA, et al. Combined fruit and vegetable intake is correlated with improved inflammatory and oxidant status from a cross-sectional study in a community setting. Nutrients 2012;4:29–41.10.3390/nu4010029Search in Google Scholar PubMed PubMed Central
53. Henes ST, Cummings DM, Hickner RC, Houmard JA, Kolasa KM, Lazorick S, et al. Comparison of predictive equations and measured resting energy expenditure among obese youth attending a pediatric healthy weight clinic: one size does not fit all. Nutr Clin Pract 2013;28:617–24.10.1177/0884533613497237Search in Google Scholar PubMed PubMed Central
54. Santos LC, Pascoal MN, Fisberg M, Cintra IP, Martini LA. Misreporting of dietary energy intake in adolescents. J Pediatr (Rio J) 2010;86:400–4.10.2223/JPED.2025Search in Google Scholar PubMed
55. Ribas-Barba L, Serra-Majem L, Roman-Vinas B, Ngo J, Garcia-Alvarez A. Effects of dietary assessment methods on assessing risk of nutrient intake adequacy at the population level: from theory to practice. Brit J Nutr 2009;101:S64–72.10.1017/S0007114509990596Search in Google Scholar PubMed
56. Berner LA, Keast DR, Bailey RL, Dwyer JT. Fortified foods are major contributors to nutrient intakes in diets of US children and adolescents. J Acad Nutr Diet 2014;114:1009–22.10.1016/j.jand.2013.10.012Search in Google Scholar PubMed
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