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Circulating extracellular vesicles are associated with pathophysiological condition including metabolic syndrome-related dysmetabolism in children and adolescents with obesity

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Abstract

Obesity of children and adolescents (OCA) is often accompanied by metabolic syndrome (MetS), which often leads to adult obesity and subsequent complications, yet the entire pathophysiological response is not fully understood. The number and composition of circulating extracellular vesicles (EV) reflect overall patient condition; therefore, we investigated the pathophysiological condition of OCA, including MetS-associated dysmetabolism, using circulating EVs. In total, 107 children and adolescents with or without obesity (boys, n = 69; girls, n = 38; median age, 10 years) were enrolled. Circulating EV number and EV protein composition were assessed via flow cytometry and liquid chromatography tandem-mass spectrometry, respectively. In a multivariate analysis, relative body weight (standardized partial regression coefficient (SPRC) 0.469, P = 0.012) and serum triglyceride level (SPRC 0.548, P < 0.001) were detected as independent parameters correlating with circulating EV number. Proteomic analysis identified 31 upregulated and 45 downregulated EV proteins in OCA. Gene ontology analysis revealed upregulated proteins to be involved in various biological processes, including intracellular protein transport, protein folding, stress response, leukocyte activation, innate immune response, and platelet degranulation, which can modulate lipid and glucose metabolism, skeletal and cardiac muscle development, inflammation, immune response, carcinogenesis, and cancer progression. Notably, several identified EV proteins are involved in neuro-development, neurotransmitter release, and neuro-protective agents in OCA. Circulating EVs were derived from adipocytes, hepatocytes, B cell lymphocytes, and neurons. Circulating EV number is significantly associated with MetS-related dysmetabolism and the EV protein cargo carries a special “signature” that reflects the alteration of various biological processes under the pathophysiological condition of OCA.

Key messages

  • Circulating EV number correlates with physical and laboratory parameters for obesity in children and adolescents.

  • Relative body weight and triglyceride are independent factors for increased circulating EVs.

  • EV composition is significantly changed in obesity of children and adolescents.

  • Identified EV composition changes associated with obesity and involves in metabolism, immune response, and cancer progression.

  • Circulating EVs are partially derived from adipocyte, hepatocytes, B cells, and neurons.

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References

  1. Di Cesare M, Soric M, Bovet P, Miranda JJ, Bhutta Z, Stevens GA, Laxmaiah A, Kengne AP, Bentham J (2019) The epidemiological burden of obesity in childhood: a worldwide epidemic requiring urgent action. BMC Med 17:212. https://doi.org/10.1186/s12916-019-1449-8

    Article  PubMed  PubMed Central  Google Scholar 

  2. Polyzos SA, Kountouras J, Mantzoros CS (2019) Obesity and nonalcoholic fatty liver disease: from pathophysiology to therapeutics. Metabolism 92:82–97. https://doi.org/10.1016/j.metabol.2018.11.014

    Article  CAS  PubMed  Google Scholar 

  3. Alford S, Patel D, Perakakis N, Mantzoros CS (2018) Obesity as a risk factor for Alzheimer’s disease: weighing the evidence. Obes Rev 19:269–280. https://doi.org/10.1111/obr.12629

    Article  CAS  PubMed  Google Scholar 

  4. Avgerinos KI, Spyrou N, Mantzoros CS, Dalamaga M (2019) Obesity and cancer risk: emerging biological mechanisms and perspectives. Metabolism 92:121–135. https://doi.org/10.1016/j.metabol.2018.11.001

    Article  CAS  PubMed  Google Scholar 

  5. Skinner AC, Steiner MJ, Henderson FW, Perrin EM (2010) Multiple markers of inflammation and weight status: cross-sectional analyses throughout childhood. Pediatrics 125:e801-809. https://doi.org/10.1542/peds.2009-2182

    Article  PubMed  Google Scholar 

  6. Andersen CJ, Murphy KE, Fernandez ML (2016) Impact of obesity and metabolic syndrome on immunity. Adv Nutr 7:66–75. https://doi.org/10.3945/an.115.010207

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. de Oliveira Dos Santos AR, de Oliveira Zanuso B, Miola VFB, Barbalho SM, Santos Bueno PC, Flato UAP, Detregiachi CRP, Buchaim DV, Buchaim RL, Tofano RJ et al. (2021) Adipokines, myokines, and hepatokines: crosstalk and metabolic repercussions. Int J Mol Sci 22. https://doi.org/10.3390/ijms22052639

  8. Kalluri R, LeBleu VS (2020) The biology, function, and biomedical applications of exosomes. Science 367. https://doi.org/10.1126/science.aau6977

  9. Gurunathan S, Kang MH, Jeyaraj M, Qasim M, Kim JH (2019) Review of the isolation, characterization, biological function, and multifarious therapeutic approaches of exosomes. Cells 8. https://doi.org/10.3390/cells8040307

  10. Kobayashi Y, Eguchi A, Tempaku M, Honda T, Togashi K, Iwasa M, Hasegawa H, Takei Y, Sumida Y, Taguchi O (2018) Circulating extracellular vesicles are associated with lipid and insulin metabolism. Am J Physiol Endocrinol Metab 315:E574–E582. https://doi.org/10.1152/ajpendo.00160.2018

    Article  CAS  PubMed  Google Scholar 

  11. Eguchi A, Lazic M, Armando AM, Phillips SA, Katebian R, Maraka S, Quehenberger O, Sears DD, Feldstein AE (2016) Circulating adipocyte-derived extracellular vesicles are novel markers of metabolic stress. J Mol Med (Berl) 94:1241–1253. https://doi.org/10.1007/s00109-016-1446-8

    Article  CAS  PubMed  Google Scholar 

  12. Kobayashi Y, Eguchi A, Tamai Y, Fukuda S, Tempaku M, Izuoka K, Iwasa M, Takei Y, Togashi K (2021) Protein composition of circulating extracellular vesicles immediately changed by particular short time of high-intensity interval training exercise. Front Physiol 12:693007. https://doi.org/10.3389/fphys.2021.693007

    Article  PubMed  PubMed Central  Google Scholar 

  13. Liu Y, Ji Y, Li M, Wang M, Yi X, Yin C, Wang S, Zhang M, Zhao Z, Xiao Y (2018) Integrated analysis of long noncoding RNA and mRNA expression profile in children with obesity by microarray analysis. Sci Rep 8:8750. https://doi.org/10.1038/s41598-018-27113-w

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Chen R, Xin G, Zhang X (2019) Long non-coding RNA HCP5 serves as a ceRNA sponging miR-17-5p and miR-27a/b to regulate the pathogenesis of childhood obesity via the MAPK signaling pathway. J Pediatr Endocrinol Metab 32:1327–1339. https://doi.org/10.1515/jpem-2018-0432

    Article  CAS  PubMed  Google Scholar 

  15. Brandt S, Roos J, Inzaghi E, Kotnik P, Kovac J, Battelino T, Cianfarani S, Nobili V, Colajacomo M, Kratzer W et al (2018) Circulating levels of miR-122 and nonalcoholic fatty liver disease in pre-pubertal obese children. Pediatr Obes 13:175–182. https://doi.org/10.1111/ijpo.12261

    Article  CAS  PubMed  Google Scholar 

  16. Ito Y, Fujieda K, Okuno A (2016) Weight-for-height charts for Japanese children based on the year 2000 Report of School Health Statistics Research. Clin Pediatr Endocrinol 25:77–82. https://doi.org/10.1297/cpe.25.77

    Article  PubMed  PubMed Central  Google Scholar 

  17. Kubo T (2014) Common approach to childhood obesity in Japan. J Pediatr Endocrinol Metab 27:581–592. https://doi.org/10.1515/jpem-2014-0047

    Article  PubMed  Google Scholar 

  18. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC (1985) Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28:412–419. https://doi.org/10.1007/BF00280883

    Article  CAS  PubMed  Google Scholar 

  19. Chung J, Park HS, Kim YJ, Yu MH, Park S, Jung SI (2021) Association of hepatic steatosis index with nonalcoholic fatty liver disease diagnosed by non-enhanced CT in a screening population. Diagnostics (Basel) 11. https://doi.org/10.3390/diagnostics11122168

  20. Lee DH (2017) Imaging evaluation of non-alcoholic fatty liver disease: focused on quantification. Clin Mol Hepatol 23:290–301. https://doi.org/10.3350/cmh.2017.0042

    Article  PubMed  PubMed Central  Google Scholar 

  21. Lee SS, Park SH (2014) Radiologic evaluation of nonalcoholic fatty liver disease. World J Gastroenterol 20:7392–7402. https://doi.org/10.3748/wjg.v20.i23.7392

    Article  PubMed  PubMed Central  Google Scholar 

  22. Rappsilber J, Ishihama Y, Mann M (2003) Stop and go extraction tips for matrix-assisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics. Anal Chem 75:663–670. https://doi.org/10.1021/ac026117i

    Article  PubMed  Google Scholar 

  23. Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26:1367–1372. https://doi.org/10.1038/nbt.1511

    Article  CAS  PubMed  Google Scholar 

  24. Cox J, Neuhauser N, Michalski A, Scheltema RA, Olsen JV, Mann M (2011) Andromeda: a peptide search engine integrated into the MaxQuant environment. J Proteome Res 10:1794–1805. https://doi.org/10.1021/pr101065j

    Article  CAS  PubMed  Google Scholar 

  25. Hebert AS, Prasad S, Belford MW, Bailey DJ, McAlister GC, Abbatiello SE, Huguet R, Wouters ER, Dunyach JJ, Brademan DR et al (2018) Comprehensive single-shot proteomics with FAIMS on a hybrid orbitrap mass spectrometer. Anal Chem 90:9529–9537. https://doi.org/10.1021/acs.analchem.8b02233

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Tyanova S, Temu T, Sinitcyn P, Carlson A, Hein MY, Geiger T, Mann M, Cox J (2016) The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat Methods 13:731–740. https://doi.org/10.1038/nmeth.3901

    Article  CAS  PubMed  Google Scholar 

  27. Babicki S, Arndt D, Marcu A, Liang Y, Grant JR, Maciejewski A, Wishart DS (2016) Heatmapper: web-enabled heat mapping for all. Nucleic Acids Res 44:W147-153. https://doi.org/10.1093/nar/gkw419

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP et al (2015) STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res 43:D447-452. https://doi.org/10.1093/nar/gku1003

    Article  CAS  PubMed  Google Scholar 

  29. McLellan AD (2009) Exosome release by primary B cells. Crit Rev Immunol 29:203–217. https://doi.org/10.1615/critrevimmunol.v29.i3.20

    Article  CAS  PubMed  Google Scholar 

  30. Krautbauer S, Haberl EM, Eisinger K, Pohl R, Rein-Fischboeck L, Rentero C, Alvarez-Guaita A, Enrich C, Grewal T, Buechler C et al (2017) Annexin A6 regulates adipocyte lipid storage and adiponectin release. Mol Cell Endocrinol 439:419–430. https://doi.org/10.1016/j.mce.2016.09.033

    Article  CAS  PubMed  Google Scholar 

  31. Naslavsky N, Rahajeng J, Rapaport D, Horowitz M, Caplan S (2007) EHD1 regulates cholesterol homeostasis and lipid droplet storage. Biochem Biophys Res Commun 357:792–799. https://doi.org/10.1016/j.bbrc.2007.04.022

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Mackness MI, Arrol S, Abbott C, Durrington PN (1993) Protection of low-density lipoprotein against oxidative modification by high-density lipoprotein associated paraoxonase. Atherosclerosis 104:129–135. https://doi.org/10.1016/0021-9150(93)90183-u

    Article  CAS  PubMed  Google Scholar 

  33. Diallo K, Oppong AK, Lim GE (2019) Can 14–3-3 proteins serve as therapeutic targets for the treatment of metabolic diseases? Pharmacol Res 139:199–206. https://doi.org/10.1016/j.phrs.2018.11.021

    Article  CAS  PubMed  Google Scholar 

  34. Ma Y, Gao J, Yin J, Gu L, Liu X, Chen S, Huang Q, Lu H, Yang Y, Zhou H et al (2016) Identification of a novel function of adipocyte plasma membrane-associated protein (APMAP) in gestational diabetes mellitus by proteomic analysis of omental adipose tissue. J Proteome Res 15:628–637. https://doi.org/10.1021/acs.jproteome.5b01030

    Article  CAS  PubMed  Google Scholar 

  35. Guilherme A, Soriano NA, Furcinitti PS, Czech MP (2004) Role of EHD1 and EHBP1 in perinuclear sorting and insulin-regulated GLUT4 recycling in 3T3-L1 adipocytes. J Biol Chem 279:40062–40075. https://doi.org/10.1074/jbc.M401918200

    Article  CAS  PubMed  Google Scholar 

  36. Xiong Y, Lei QY, Zhao S, Guan KL (2011) Regulation of glycolysis and gluconeogenesis by acetylation of PKM and PEPCK. Cold Spring Harb Symp Quant Biol 76:285–289. https://doi.org/10.1101/sqb.2011.76.010942

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. D’Souza RF, Masson SWC, Woodhead JST, James SL, MacRae C, Hedges CP, Merry TL (2021) alpha1-Antitrypsin A treatment attenuates neutrophil elastase accumulation and enhances insulin sensitivity in adipose tissue of mice fed a high-fat diet. Am J Physiol Endocrinol Metab 321:E560–E570. https://doi.org/10.1152/ajpendo.00181.2021

    Article  CAS  PubMed  Google Scholar 

  38. Kubota A, Juanola-Falgarona M, Emmanuele V, Sanchez-Quintero MJ, Kariya S, Sera F, Homma S, Tanji K, Quinzii CM, Hirano M (2019) Cardiomyopathy and altered integrin-actin signaling in Fhl1 mutant female mice. Hum Mol Genet 28:209–219. https://doi.org/10.1093/hmg/ddy299

    Article  CAS  PubMed  Google Scholar 

  39. Aratani Y (2018) Myeloperoxidase: its role for host defense, inflammation, and neutrophil function. Arch Biochem Biophys 640:47–52. https://doi.org/10.1016/j.abb.2018.01.004

    Article  CAS  PubMed  Google Scholar 

  40. Pruenster M, Vogl T, Roth J, Sperandio M (2016) S100A8/A9: from basic science to clinical application. Pharmacol Ther 167:120–131. https://doi.org/10.1016/j.pharmthera.2016.07.015

    Article  CAS  PubMed  Google Scholar 

  41. Nazari A, Khorramdelazad H, Hassanshahi G, Day AS, Sardoo AM, Fard ET, Abedinzadeh M, Nadimi AE (2017) S100A12 in renal and cardiovascular diseases. Life Sci 191:253–258. https://doi.org/10.1016/j.lfs.2017.10.036

    Article  CAS  PubMed  Google Scholar 

  42. Crouch EC (2000) Surfactant protein-D and pulmonary host defense. Respir Res 1:93–108. https://doi.org/10.1186/rr19

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Wang H, Liu B, Wei J (2021) Beta2-microglobulin(B2M) in cancer immunotherapies: biological function, resistance and remedy. Cancer Lett 517:96–104. https://doi.org/10.1016/j.canlet.2021.06.008

    Article  CAS  PubMed  Google Scholar 

  44. Silva RG, Nunes JE, Canduri F, Borges JC, Gava LM, Moreno FB, Basso LA, Santos DS (2007) Purine nucleoside phosphorylase: a potential target for the development of drugs to treat T-cell- and apicomplexan parasite-mediated diseases. Curr Drug Targets 8:413–422. https://doi.org/10.2174/138945007780058997

    Article  CAS  PubMed  Google Scholar 

  45. Qi H, Liu S, Guo C, Wang J, Greenaway FT, Sun MZ (2015) Role of annexin A6 in cancer. Oncol Lett 10:1947–1952. https://doi.org/10.3892/ol.2015.3498

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Kobayashi T, Shiozaki A, Nako Y, Ichikawa D, Kosuga T, Shoda K, Arita T, Konishi H, Komatsu S, Kubota T et al (2018) Chloride intracellular channel 1 as a switch among tumor behaviors in human esophageal squamous cell carcinoma. Oncotarget 9:23237–23252. https://doi.org/10.18632/oncotarget.25296

    Article  PubMed  PubMed Central  Google Scholar 

  47. Wilson MR, Zoubeidi A (2017) Clusterin as a therapeutic target. Expert Opin Ther Targets 21:201–213. https://doi.org/10.1080/14728222.2017.1267142

    Article  CAS  PubMed  Google Scholar 

  48. Wei X, Zhang H (2020) Four and a half LIM domains protein 1 can be as a double-edged sword in cancer progression. Cancer Biol Med 17:270–281. https://doi.org/10.20892/j.issn.2095-3941.2019.0420

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Hu Z, Zhou X, Zeng D, Lai J (2022) Shikonin induces cell autophagy via modulating the microRNA -545-3p/guanine nucleotide binding protein beta polypeptide 1 axis, thereby disrupting cellular carcinogenesis in colon cancer. Bioengineered 13:5928–5941. https://doi.org/10.1080/21655979.2021.2024638

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Yu F, Wu W, Liang M, Huang Y, Chen C (2020) Prognostic significance of Rab27A and Rab27B expression in esophageal squamous cell cancer. Cancer Manag Res 12:6353–6361. https://doi.org/10.2147/CMAR.S258940

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Lohmann K, Masuho I, Patil DN, Baumann H, Hebert E, Steinrucke S, Trujillano D, Skamangas NK, Dobricic V, Huning I et al (2017) Novel GNB1 mutations disrupt assembly and function of G protein heterotrimers and cause global developmental delay in humans. Hum Mol Genet 26:1078–1086. https://doi.org/10.1093/hmg/ddx018

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Li M, Oh TJ, Fan H, Diao J, Zhang K (2020) Syntaxin clustering and optogenetic control for synaptic membrane fusion. J Mol Biol 432:4773–4782. https://doi.org/10.1016/j.jmb.2020.07.005

    Article  CAS  PubMed  Google Scholar 

  53. Vieira M, Saraiva MJ (2014) Transthyretin: a multifaceted protein. Biomol Concepts 5:45–54. https://doi.org/10.1515/bmc-2013-0038

    Article  CAS  PubMed  Google Scholar 

  54. Malaspina A, Kaushik N, de Belleroche J (2000) A 14–3-3 mRNA is up-regulated in amyotrophic lateral sclerosis spinal cord. J Neurochem 75:2511–2520. https://doi.org/10.1046/j.1471-4159.2000.0752511.x

    Article  CAS  PubMed  Google Scholar 

  55. Melzer L, Freiman TM, Derouiche A (2021) Rab6A as a pan-astrocytic marker in mouse and human brain, and comparison with other glial markers (GFAP, GS, Aldh1L1, SOX9). Cells 10. https://doi.org/10.3390/cells10010072

  56. Wang ZV, Scherer PE (2016) Adiponectin, the past two decades. J Mol Cell Biol 8:93–100. https://doi.org/10.1093/jmcb/mjw011

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Dateki S (2017) ACAN mutations as a cause of familial short stature. Clin Pediatr Endocrinol 26:119–125. https://doi.org/10.1297/cpe.26.119

    Article  PubMed  PubMed Central  Google Scholar 

  58. Yuan ZY, Cheng LT, Wang ZF, Wu YQ (2021) Desmoplakin and clinical manifestations of desmoplakin cardiomyopathy. Chin Med J (Engl) 134:1771–1779. https://doi.org/10.1097/CM9.0000000000001581

    Article  CAS  PubMed  Google Scholar 

  59. Akerstrom B, Logdberg L, Berggard T, Osmark P, Lindqvist A (2000) alpha(1)-Microglobulin: a yellow-brown lipocalin. Biochim Biophys Acta 1482:172–184. https://doi.org/10.1016/s0167-4838(00)00157-6

    Article  CAS  PubMed  Google Scholar 

  60. Schittek B (2012) The multiple facets of dermcidin in cell survival and host defense. J Innate Immun 4:349–360. https://doi.org/10.1159/000336844

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Wei H, Wang JY (2021) Role of polymeric immunoglobulin receptor in IgA and IgM transcytosis. Int J Mol Sci 22. https://doi.org/10.3390/ijms22052284

  62. Kataoka H, Kawaguchi M (2010) Hepatocyte growth factor activator (HGFA): pathophysiological functions in vivo. FEBS J 277:2230–2237. https://doi.org/10.1111/j.1742-4658.2010.07640.x

    Article  CAS  PubMed  Google Scholar 

  63. Cnop M, Foufelle F, Velloso LA (2012) Endoplasmic reticulum stress, obesity and diabetes. Trends Mol Med 18:59–68. https://doi.org/10.1016/j.molmed.2011.07.010

    Article  CAS  PubMed  Google Scholar 

  64. Kolb R, Sutterwala FS, Zhang W (2016) Obesity and cancer: inflammation bridges the two. Curr Opin Pharmacol 29:77–89. https://doi.org/10.1016/j.coph.2016.07.005

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Saltiel AR, Olefsky JM (2017) Inflammatory mechanisms linking obesity and metabolic disease. J Clin Invest 127:1–4. https://doi.org/10.1172/JCI92035

    Article  PubMed  PubMed Central  Google Scholar 

  66. Thommen DS, Schumacher TN (2018) T cell dysfunction in cancer. Cancer Cell 33:547–562. https://doi.org/10.1016/j.ccell.2018.03.012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Franchina DG, Grusdat M, Brenner D (2018) B-cell metabolic remodeling and cancer. Trends Cancer 4:138–150. https://doi.org/10.1016/j.trecan.2017.12.006

    Article  CAS  PubMed  Google Scholar 

  68. Van Grouw JM, Volpe SL (2013) Childhood obesity in America. Curr Opin Endocrinol Diabetes Obes 20:396–400. https://doi.org/10.1097/01.med.0000433064.78799.0c

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

The authors would like to thank the paramedical for technical assistance at National Hospital Organization Mie National Hospital.

Funding

This work was supported by JSPS KAKENHI Grant Number 21K11572 to YK, and Japan Science and Technology Agency to AE and KI.

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Authors and Affiliations

  1. Center for Physical and Mental Health, Mie University Graduate School of Medicine, Tsu, Mie, 514-8507, Japan

    Yoshinao Kobayashi & Noriko Furuta

  2. Department of Gastroenterology and Hepatology, Mie University Graduate School of Medicine, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan

    Yoshinao Kobayashi, Akiko Eguchi, Mina Tempaku, Kiyora Izuoka, Motoh Iwasa & Hayato Nakagawa

  3. JST, PRESTO, 4-1-8 Honcho, Kawaguchi, Saitama, 332-0012, Japan

    Akiko Eguchi & Koshi Imami

  4. Biobank Center, Mie University Hospital, Tsu, Mie, 514-8507, Japan

    Akiko Eguchi

  5. Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, 606-8501, Japan

    Koshi Imami

  6. RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan

    Koshi Imami

  7. Department of Pediatrics, National Hospital Organization Mie National Hospital, Tsu, Mie, 514-0125, Japan

    Takafumi Takase, Keigo Kainuma, Mizuho Nagao & Takao Fujisawa

  8. Department of Health and Physical Education, Faculty of Education, Mie University, Tsu, Mie, 514-8507, Japan

    Kenji Togashi

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  1. Yoshinao Kobayashi
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Contributions

YK and AE contributed to study concept and design, interpretation of data, and drafting of the manuscript. KI, MT, KI, TT, KK, MN, and NF contributed to the acquisition of data. MI, HN, TF, and KT contributed to study supervision. All the authors have read and agreed to the published version of the manuscript.

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Correspondence to Akiko Eguchi.

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The study protocol was approved by the Clinical Research Ethics Review Committee of Mie University Hospital (Approval No. 3201) and by the institutional ethics board of the National Hospital Organization Mie Hospital (Approval No. 2020-02). All methods were performed in accordance with the relevant guidelines and regulations.

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The authors declare no competing interests.

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Kobayashi, Y., Eguchi, A., Imami, K. et al. Circulating extracellular vesicles are associated with pathophysiological condition including metabolic syndrome-related dysmetabolism in children and adolescents with obesity. J Mol Med 102, 23–38 (2024). https://doi.org/10.1007/s00109-023-02386-5

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