Growing evidence reports an association between inflammatory markers, obesity and blood pressure (BP). Specifically, the intergenic single nucleotide polymorphism (SNP) rs7556897T > C (MAF = 0.34) located between SLC19A3 and the CCL20 was shown to be associated with chronic inflammatory diseases. In addition, CCL20 expression was found increased in pancreatic islets of obese rodents and human pancreatic β cells under the influence of inflammation. In this study, we hypothesized that SNP rs7556897 could affect BP levels, thus providing a link between inflammation, BP and obesity.
BP was measured under supine position with a manual sphygmomanometer; values reported were the means of three readings. We analyzed rs7556897 in 577 normal weight and 689 obese French children. Using real-time polymerase chain reaction (PCR), we quantified CCL20 and SLC19A3 expression in adipose tissue and peripheral blood mononuclear cells (PBMCs) of normal weight and overweight children.
The rs7556897C allele was negatively associated with diastolic BP in normal weight children (β = −0.012 ± 0.004, p = 0.006) but positively associated in obese children (β = 2.178 ± 0.71, p = 0.002). A significant interaction between rs7556897T > C and the obesity status (obese or normal weight) was detected (β = 3.49, p = 9.79 × 10−5) for BP in a combined population analysis. CCL20 mRNA was only expressed in the adipose tissue of overweight children, and its expression levels were 10.7× higher in PBMCs of overweight children than normal weight children. Finally, CCL20 mRNA levels were positively associated with rs7556897T > C in PBMCs of 58 normal weight children (β = 0.43, p = 0.002). SLC19A3 was not expressed in PBMCs, and in adipose tissue, it showed same levels of expression in normal weight and overweight children. The gene expression results may highlight a specific involvement of CCL20 via communicating obesity/inflammation pathways that regulate BP.
Childhood obesity reverses the effect of rs7556897T > C on diastolic BP, possibly via the modulation of CCL20 expression levels.
STANISLAS Family Study and Greek pediatric cohort: The authors would like to thank the study participants and their families for the time and effort spent helping to set up the present study. The authors would also like to thank all the field investigators for the recruitment and examination of the populations involved in this study. As part of the BRC “Interactions Gène-Environnement en Physiopathologie CardioVasculaire” (IGE-PCV) (BB-0033-00051), the STANISLAS Family Study was supported by the “Caisse Nationale d’Assurance Maladies des Travailleurs Salariés” (CNAM), the “Institut National de la Santé et de la Recherche Médicale” (INSERM), the “Région Lorraine,” the “Communauté Urbaine du Grand Nancy,” the University of Lorraine and cofinanced by the European Union within the frames of the Operational Programme FEDER-FSE Lorraine et Massif des Vosges 2014–2020. French Obesity Cases: funding from the French regional program “Contrat Plan Etat Région” entitled “Genetic dissection of polygenic obesity using a GWA approach” and the European Regional Development Fund supported the cohort of obese children.
Author contributions: SES and MGS participated in the study design, performed data analysis and interpretation and drafted the manuscript. AB and SD performed data analysis and interpretation and reviewed the manuscript. NCN performed data analysis and interpretation and drafted a first version of the manuscript. CL, DM, PS, AS and PC participated in data interpretation and reviewed the manuscript. GVD and PF provided data, participated in data interpretation and reviewed the manuscript. SVS participated in the conception and study design, participated in data interpretation and reviewed the manuscript. All authors approved the final version of the manuscript. All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Data availability statement: Data are available from the authors upon request.
Research funding: None declared.
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.
1. World Health Organization. A report about obesity and overweight. 2016. Retrieved from: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight.Search in Google Scholar
2. Park MH, Falconer C, Viner RM, Kinra S. The impact of childhood obesity on morbidity and mortality in adulthood: a systematic review. Obes Rev 2012;13:985–1000.10.1111/j.1467-789X.2012.01015.xSearch in Google Scholar
3. Reilly JJ, Kelly J. Long-term impact of overweight and obesity in childhood and adolescence on morbidity and premature mortality in adulthood: systematic review. Int J Obes (Lond) 2011;35:891–8.10.1038/ijo.2010.222Search in Google Scholar
5. Courtens W, Broeckx W, Ledoux M, Vamosa E. Oculocerebral hypopigmentation syndrome (Cross syndrome) in a Gipsy child. Acta Paediatr Scand 1989;78:806–10.10.1111/j.1651-2227.1989.tb11153.xSearch in Google Scholar PubMed
6. I’Allemand D, Wiegand S, Reinehr T, Muller J, Wabitsch M, Widhalm K, et al. Cardiovascular risk in 26,008 European overweight children as established by a multicenter database. Obesity (Silver Spring) 2008;16:1672–9.10.1038/oby.2008.259Search in Google Scholar PubMed
7. Timpson NJ, Harbord R, Davey Smith G, Zacho J, Tybjaerg-Hansen A, Nordestgaard BG. Does greater adiposity increase blood pressure and hypertension risk?: Mendelian randomization using the FTO/MC4R genotype. Hypertension 2009;54:84–90.10.1161/HYPERTENSIONAHA.109.130005Search in Google Scholar PubMed
8. Bender R, Jockel KH, Richter B, Spraul M, Berger M. Body weight, blood pressure, and mortality in a cohort of obese patients. Am J Epidemiol 2002;156:239–45.10.1093/aje/kwf015Search in Google Scholar PubMed
10. Pi-Sunyer FX, Aronne LJ, Heshmati HM, Devin J, Rosenstock J, Group RI-NAS. Effect of rimonabant, a cannabinoid-1 receptor blocker, on weight and cardiometabolic risk factors in overweight or obese patients: RIO-North America: a randomized controlled trial. J Am Med Assoc 2006;295:761–75.10.1001/jama.295.7.761Search in Google Scholar PubMed
11. Siebenhofer A, Horvath K, Jeitler K, Berghold A, Stich AK, Matyas E, et al. Long-term effects of weight-reducing drugs in hypertensive patients. Cochrane Database Syst Rev 2009;3:CD007654.10.1002/14651858.CD007654.pub2Search in Google Scholar PubMed
12. Munoz M, Pong-Wong R, Canela-Xandri O, Rawlik K, Haley CS, Tenesa A. Evaluating the contribution of genetics and familial shared environment to common disease using the UK Biobank. Nat Genet 2016;48:980–3.10.1038/ng.3618Search in Google Scholar PubMed PubMed Central
13. Levy D, DeStefano AL, Larson MG, O’Donnell CJ, Lifton RP, Gavras H, et al. Evidence for a gene influencing blood pressure on chromosome 17. Genome scan linkage results for longitudinal blood pressure phenotypes in subjects from the framingham heart study. Hypertension 2000;36:477–83.10.1161/01.HYP.36.4.477Search in Google Scholar PubMed
14. Ehret GB. Genome-wide association studies: contribution of genomics to understanding blood pressure and essential hypertension. Curr Hypertens Rep 2010;12:17–25.10.1007/s11906-009-0086-6Search in Google Scholar PubMed PubMed Central
15. Evangelou E, Warren HR, Mosen-Ansorena D, Mifsud B, Pazoki R, Gao H, et al. Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nat Genet 2018;50:1412–25.10.1038/s41588-018-0205-xSearch in Google Scholar PubMed PubMed Central
16. El Shamieh S, Ndiaye NC, Stathopoulou MG, Murray HA, Masson C, Lamont JV, et al. Functional epistatic interaction between rs6046G>A in F7 and rs5355C>T in SELE modifies systolic blood pressure levels. PLoS One 2012;7:e40777.10.1371/journal.pone.0040777Search in Google Scholar PubMed PubMed Central
17. Ndiaye NC, Azimi Nehzad M, El Shamieh S, Stathopoulou MG, Visvikis-Siest S. Cardiovascular diseases and genome-wide association studies. Clin Chim Acta 2011;412:1697–701.10.1016/j.cca.2011.05.035Search in Google Scholar PubMed
18. Baba M, Imai T, Nishimura M, Kakizaki M, Takagi S, Hieshima K, et al. Identification of CCR6, the specific receptor for a novel lymphocyte-directed CC chemokine LARC. J Biol Chem 1997;272:14893–8.10.1074/jbc.272.23.14893Search in Google Scholar PubMed
19. Liu JZ, van Sommeren S, Huang H, Ng SC, Alberts R, Takahashi A, et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet 2015;47:979–86.10.1038/ng.3359Search in Google Scholar PubMed PubMed Central
20. Ellinghaus D, Jostins L, Spain SL, Cortes A, Bethune J, Han B, et al. Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci. Nat Genet 2016;48:510–8.10.1038/ng.3528Search in Google Scholar PubMed PubMed Central
21. Burke SJ, Karlstad MD, Regal KM, Sparer TE, Lu D, Elks CM, et al. CCL20 is elevated during obesity and differentially regulated by NF-kappaB subunits in pancreatic beta-cells. Biochim Biophys Acta 2015;1849:637–52.10.1016/j.bbagrm.2015.03.007Search in Google Scholar PubMed PubMed Central
22. Nijhuis J, Rensen SS, Slaats Y, van Dielen FM, Buurman WA, Greve JW. Neutrophil activation in morbid obesity, chronic activation of acute inflammation. Obesity (Silver Spring) 2009;17:2014–8.10.1038/oby.2009.113Search in Google Scholar PubMed
23. De Miguel C, Rudemiller NP, Abais JM, Mattson DL. Inflammation and hypertension: new understandings and potential therapeutic targets. Current hypertension reports 2015;17:507.10.1007/s11906-014-0507-zSearch in Google Scholar PubMed PubMed Central
25. Siest G, Visvikis S, Herbeth B, Gueguen R, Vincent-Viry M, Sass C, et al. Objectives, design and recruitment of a familial and longitudinal cohort for studying gene-environment interactions in the field of cardiovascular risk: the Stanislas cohort. Clin Chem Lab Med 1998;36:35–42.10.1515/CCLM.1998.007Search in Google Scholar PubMed
26. Visvikis-Siest S, Siest G. The STANISLAS Cohort: a 10-year follow-up of supposed healthy families. Gene-environment interactions, reference values and evaluation of biomarkers in prevention of cardiovascular diseases. Clin Chem Lab Med 2008;46:733–47.10.1515/CCLM.2008.178Search in Google Scholar PubMed
27. Rolland-Cachera MF, Cole TJ, Sempe M, Tichet J, Rossignol C, Charraud A. Body Mass Index variations: centiles from birth to 87 years. Eur J Clin Nutr 1991;45:13–21.Search in Google Scholar
28. Meyre D, Delplanque J, Chevre JC, Lecoeur C, Lobbens S, Gallina S, et al. Genome-wide association study for early-onset and morbid adult obesity identifies three new risk loci in European populations. Nature genetics 2009;41:157–9.10.1038/ng.301Search in Google Scholar PubMed
29. Dedoussis GV, Kapiri A, Kalogeropoulos N, Samara A, Dimitriadis D, Lambert D, et al. Adipokine expression in adipose tissue and in peripheral blood mononuclear cells in children Correlation with BMI and fatty acid content. Clin Chim Acta 2009;410:85–9.10.1016/j.cca.2009.09.028Search in Google Scholar PubMed
30. Marteau JB, Mohr S, Pfister M, Visvikis-Siest S. Collection and storage of human blood cells for mRNA expression profiling: a 15-month stability study. Clin Chem 2005;51:1250–2.10.1373/clinchem.2005.048546Search in Google Scholar PubMed
31. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81:559–75.10.1086/519795Search in Google Scholar PubMed PubMed Central
33. Bao W, Threefoot SA, Srinivasan SR, Berenson GS. Essential hypertension predicted by tracking of elevated blood pressure from childhood to adulthood: the Bogalusa Heart Study. Am J Hypertens 1995;8:657–65.10.1016/0895-7061(95)00116-7Search in Google Scholar
34. Mahoney LT, Burns TL, Stanford W, Thompson BH, Witt JD, Rost CA, et al. Coronary risk factors measured in childhood and young adult life are associated with coronary artery calcification in young adults: the Muscatine Study. J Am Coll Cardiol 1996;27:277–84.10.1016/0735-1097(95)00461-0Search in Google Scholar
36. Caulfield M, Munroe P, Pembroke J, Samani N, Dominiczak A, Brown M, et al. Genome-wide mapping of human loci for essential hypertension. Lancet 2003;361:2118–23.10.1016/S0140-6736(03)13722-1Search in Google Scholar
37. Edwards KL, Hutter CM, Wan JY, Kim H, Monks SA. Genome-wide linkage scan for the metabolic syndrome: the GENNID study. Obesity (Silver Spring) 2008;16:1596–601.10.1038/oby.2008.236Search in Google Scholar PubMed
38. Hsueh WC, Mitchell BD, Schneider JL, Wagner MJ, Bell CJ, Nanthakumar E, et al. QTL influencing blood pressure maps to the region of PPH1 on chromosome 2q31-34 in Old Order Amish. Circulation 2000;101:2810–6.10.1161/01.CIR.101.24.2810Search in Google Scholar
39. Koivukoski L, Fisher SA, Kanninen T, Lewis CM, von Wowern F, Hunt S, et al. Meta-analysis of genome-wide scans for hypertension and blood pressure in Caucasians shows evidence of susceptibility regions on chromosomes 2 and 3. Hum Mol Genet 2004;13:2325–32.10.1093/hmg/ddh237Search in Google Scholar PubMed
40. McArdle PF, Dytch H, O’Connell JR, Shuldiner AR, Mitchell BD, Abney M. Homozygosity by descent mapping of blood pressure in the Old Order Amish: evidence for sex specific genetic architecture. BMC Genet 2007;8:66.10.1186/1471-2156-8-66Search in Google Scholar PubMed PubMed Central
41. Mocci E, Concas MP, Fanciulli M, Pirastu N, Adamo M, Cabras V, et al. Microsatellites and SNPs linkage analysis in a Sardinian genetic isolate confirms several essential hypertension loci previously identified in different populations. BMC Med Genet 2009;10:81.10.1186/1471-2350-10-81Search in Google Scholar PubMed PubMed Central
42. Levy D, Ehret GB, Rice K, Verwoert GC, Launer LJ, Dehghan A, et al. Genome-wide association study of blood pressure and hypertension. Nat Genet 2009;41:677–87.10.1038/ng.384Search in Google Scholar PubMed PubMed Central
43. Newton-Cheh C, Johnson T, Gateva V, Tobin MD, Bochud M, Coin L, et al. Genome-wide association study identifies eight loci associated with blood pressure. Nat Genet 2009;41:666–76.10.1038/ng.361Search in Google Scholar PubMed PubMed Central
44. Levy D, Larson MG, Benjamin EJ, Newton-Cheh C, Wang TJ, Hwang SJ, et al. Framingham Heart Study 100K Project: genome-wide associations for blood pressure and arterial stiffness. BMC Med Genet 2007;8(Suppl 1):S3.10.1186/1471-2350-8-S1-S3Search in Google Scholar PubMed PubMed Central
45. Duffaut C, Zakaroff-Girard A, Bourlier V, Decaunes P, Maumus M, Chiotasso P, et al. Interplay between human adipocytes and T lymphocytes in obesity: CCL20 as an adipochemokine and T lymphocytes as lipogenic modulators. Arterioscler Thromb Vasc Biol 2009;29:1608–14.10.1161/ATVBAHA.109.192583Search in Google Scholar PubMed
46. Purkayastha S, Zhang G, Cai D. Uncoupling the mechanisms of obesity and hypertension by targeting hypothalamic IKK-beta and NF-kappaB. Nat Med 2011;17:883–7.10.1038/nm.2372Search in Google Scholar PubMed PubMed Central
47. Jafarzadeh A, Bagherzadeh S, Ebrahimi HA, Hajghani H, Bazrafshani MR, Khosravimashizi A, et al. Higher circulating levels of chemokine CCL20 in patients with multiple sclerosis: evaluation of the influences of chemokine gene polymorphism, gender, treatment and disease pattern. J Mol Neurosci 2014;53:500–5.10.1007/s12031-013-0214-2Search in Google Scholar PubMed
48. Joehanes R, Johnson AD, Barb JJ, Raghavachari N, Liu P, Woodhouse KA, et al. Gene expression analysis of whole blood, peripheral blood mononuclear cells, and lymphoblastoid cell lines from the Framingham Heart Study. Physiol Genomics 2012;44:59–75.10.1152/physiolgenomics.00130.2011Search in Google Scholar PubMed PubMed Central
49. Visvikis-Siest S, Marteau JB, Samara A, Berrahmoune H, Marie B, Pfister M. Peripheral blood mononuclear cells (PBMCs): a possible model for studying cardiovascular biology systems. Clin Chem Lab Med 2007;45:1154–68.10.1515/CCLM.2007.255Search in Google Scholar PubMed
50. Kontaraki JE, Marketou ME, Zacharis EA, Parthenakis FI, Vardas PE. Early cardiac gene transcript levels in peripheral blood mononuclear cells in patients with untreated essential hypertension. J Hypertens 2011;29:791–7.10.1097/HJH.0b013e3283424bc4Search in Google Scholar PubMed
51. Aziz H, Zaas A, Ginsburg GS. Peripheral blood gene expression profiling for cardiovascular disease assessment. Genomic Med 2007;1:105–12.10.1007/s11568-008-9017-xSearch in Google Scholar PubMed PubMed Central
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