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Leukocyte-related parameters in older adults with metabolic syndrome

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Abstract

Purpose

We aimed to examine the association between leukocyte-related parameters and the risk of metabolic syndrome (MetS) in community-dwelling older Chinese adults, with a special focus on assessing the diagnostic ability of leukocyte-related parameters in detecting MetS and the potential interaction effect of sex in the leukocyte–MetS relationship.

Methods

Study sample was from the Weitang Geriatric Diseases Study, which included 4579 individuals aged 60 years or above. MetS was diagnosed based on the Adult Treatment Panel III criteria. Leukocyte-related parameters were assessed using an automated hematology analyzer.

Results

The adjusted odds ratio (95% confidence interval (CI)) of MetS for the highest quartile of leukocyte-related parameters (leukocyte, lymphocyte, neutrophil, monocyte, eosinophil, and basophil), when compared with the lowest quartile were 2.87 (2.30, 3.59), 2.69 (2.15, 3.36), 2.09 (1.67, 2.62), 2.12 (1.71, 2.64), 1.62 (1.31, 2.00), and 1.36 (1.11, 1.65), respectively. Adding leukocyte, lymphocyte, monocyte, and neutrophil to a model containing conventional risk factors improved risk prediction for MetS. Furthermore, significant interactions between leukocyte, monocyte, neutrophil, and sex on MetS were observed (all P value for interaction <0.01).

Conclusion

The numbers of total leukocytes, lymphocyte, monocyte, neutrophil, and eosinophil counts were elevated in older adults with MetS, suggesting that leukocyte-related parameters may be meaningful biomarkers for MetS. Adding leukocyte-related parameters to the conventional models increased the ability of predicting MetS among older adults. These parameters may be useful biomarkers for further risk appraisal of MetS in older adults.

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References

  1. R.H. Eckel, S.M. Grundy, P.Z. Zimmet, The metabolic syndrome. Lancet 365(9468), 1415–1428 (2005)

    Article  CAS  Google Scholar 

  2. J. Lu, L. Wang, M. Li, Y. Xu, Y. Jiang, W. Wang, J. Li, S. Mi, M. Zhang, Y. Li, T. Wang, M. Xu, Z. Zhao, M. Dai, S. Lai, W. Zhao, L. Wang, Y. Bi, G. Ning, Metabolic syndrome among adults in China: the 2010 China Noncommunicable Disease Surveillance. J. Clin. Endocrinol. Metab. 102(2), 507–515 (2017)

    PubMed  Google Scholar 

  3. B. Isomaa, P. Almgren, T. Tuomi, B. Forsen, K. Lahti, M. Nissen, M.R. Taskinen, L. Groop, Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care 24(4), 683–689 (2001)

    Article  CAS  Google Scholar 

  4. X. Huo, L. Gao, L. Guo, W. Xu, W. Wang, X. Zhi, L. Li, Y. Ren, X. Qi, Z. Sun, W. Li, Q. Ji, X. Ran, B. Su, C. Hao, J. Lu, X. Guo, H. Zhuo, D. Zhang, C. Pan, J. Weng, D. Hu, X. Yang, L. Ji, Risk of non-fatal cardiovascular diseases in early-onset versus late-onset type 2 diabetes in China: a cross-sectional study. Lancet Diabetes Endocrinol. 4(2), 115–124 (2016)

    Article  Google Scholar 

  5. P. Zimmet, D. Magliano, Y. Matsuzawa, G. Alberti, J. Shaw, The metabolic syndrome: a global public health problem and a new definition. J. Atheroscler. Thromb. 12(6), 295–300 (2005)

    Article  CAS  Google Scholar 

  6. P. Dandona, A. Aljada, A. Chaudhuri, P. Mohanty, R. Garg, Metabolic syndrome: a comprehensive perspective based on interactions between obesity, diabetes, and inflammation. Circulation 111(11), 1448–1454 (2005)

    Article  Google Scholar 

  7. G.S. Hotamisligil, Inflammation and metabolic disorders. Nature 444(7121), 860–867 (2006)

    Article  CAS  Google Scholar 

  8. W. Meng, C. Zhang, Q. Zhang, X. Song, H. Lin, D. Zhang, Y. Zhang, Z. Zhu, S. Wu, Y. Liu, F. Tang, X. Yang, F. Xue, Association between leukocyte and metabolic syndrome in urban Han Chinese: a longitudinal cohort study. PloS One 7(11), e49875 (2012)

    Article  CAS  Google Scholar 

  9. A. Jesri, E.C. Okonofua, B.M. Egan, Platelet and white blood cell counts are elevated in patients with the metabolic syndrome. J. Clin. Hypertens. 7(12), 705–711 (2005)

    Article  Google Scholar 

  10. N. Nagasawa, K. Tamakoshi, H. Yatsuya, Y. Hori, M. Ishikawa, C. Murata, H. Zhang, K. Wada, R. Otsuka, T. Mabuchi, T. Kondo, H. Toyoshima, Association of white blood cell count and clustered components of metabolic syndrome in Japanese men. Circ. J. 68(10), 892–897 (2004)

    Article  Google Scholar 

  11. E. Oda, R. Kawai, The prevalence of metabolic syndrome and diabetes increases through the quartiles of white blood cell count in Japanese men and women. Intern. Med. 48(13), 1127–1134 (2009)

    Article  Google Scholar 

  12. K. Odagiri, A. Uehara, I. Mizuta, M. Yamamoto, C. Kurata, Longitudinal study on white blood cell count and the incidence of metabolic syndrome. Intern. Med. 50(21), 2491–2498 (2011)

    Article  Google Scholar 

  13. D. Fairweather, S. Frisancho-Kiss, N.R. Rose, Sex differences in autoimmune disease from a pathological perspective. Am. J. Pathol. 173(3), 600–609 (2008)

    Article  CAS  Google Scholar 

  14. C.W. Pan, X. Wang, Q. Ma, H.P. Sun, Y. Xu, P. Wang, Cognitive dysfunction and health-related quality of life among older Chinese. Sci. Rep. 5, 17301 (2015)

    Article  Google Scholar 

  15. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA 285(19), 2486–2497 (2001). https://doi.org/10.1001/jama.285.19.2486

  16. M.J. Pencina, R.B. D’Agostino, R.B. D’Agostino Sr., R.S. Vasan Jr., Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat. Med. 27(2), 157–172 (2008). https://doi.org/10.1002/sim.2929

    Article  PubMed  Google Scholar 

  17. B.D. Horne, J.L. Anderson, J.M. John, A. Weaver, T.L. Bair, K.R. Jensen, D.G. Renlund, J.B. Muhlestein, Which white blood cell subtypes predict increased cardiovascular risk? J. Am. Coll. Cardiol. 45(10), 1638–1643 (2005). https://doi.org/10.1016/j.jacc.2005.02.054

    Article  PubMed  Google Scholar 

  18. P.M. Sweetnam, H.F. Thomas, J.W. Yarnell, I.A. Baker, P.C. Elwood, Total and differential leukocyte counts as predictors of ischemic heart disease: the Caerphilly and Speedwell studies. Am. J. Epidemiol. 145(5), 416–421 (1997). https://doi.org/10.1093/oxfordjournals.aje.a009123

    Article  CAS  PubMed  Google Scholar 

  19. B.Y. Su, C.F. Tian, B.L. Gao, Y.H. Tong, X.H. Zhao, Y. Zheng, Correlation of the leucocyte count with traditional and non-traditional components of metabolic syndrome. Postgrad. Med. 128(8), 805–809 (2016). https://doi.org/10.1080/00325481.2016.1243980

    Article  PubMed  Google Scholar 

  20. J.A. Kim, Y.S. Choi, J.I. Hong, S.H. Kim, H.H. Jung, S.M. Kim, Association of metabolic syndrome with white blood cell subtype and red blood cells. Endocr. J. 53(1), 133–139 (2006)

    Article  Google Scholar 

  21. H. Yang, Y.Q. Fu, B. Yang, J.S. Zheng, X.Y. Zeng, W. Zeng, Z.F. Fan, M. Chen, L. Wang, D. Li, Positive association between the metabolic syndrome and white blood cell counts in Chinese. Asia Pac. J. Clin. Nutr. 26(1), 141–147 (2017). https://doi.org/10.6133/apjcn.102015.13

    Article  PubMed  Google Scholar 

  22. X.Q. Lao, G. Neil Thomas, C. Jiang, W. Zhang, P. Adab, T.H. Lam, K.K. Cheng, White blood cell count and the metabolic syndrome in older Chinese: the Guangzhou Biobank Cohort Study. Atherosclerosis 201(2), 418–424 (2008). https://doi.org/10.1016/j.atherosclerosis.2007.12.053

    Article  CAS  PubMed  Google Scholar 

  23. A.E. Kitabchi, M. Temprosa, W.C. Knowler, S.E. Kahn, S.E. Fowler, S.M. Haffner, R. Andres, C. Saudek, S.L. Edelstein, R. Arakaki, M.B. Murphy, H. Shamoon, Role of insulin secretion and sensitivity in the evolution of type 2 diabetes in the diabetes prevention program: effects of lifestyle intervention and metformin. Diabetes 54(8), 2404–2414 (2005). https://doi.org/10.2337/diabetes.54.8.2404

    Article  PubMed  Google Scholar 

  24. B. Razani, M.V. Chakravarthy, C.F. Semenkovich, Insulin resistance and atherosclerosis. Endocrinol. Metab. Clin. N. Am. 37(3), 603–621, viii (2008). https://doi.org/10.1016/j.ecl.2008.05.001

    Article  CAS  Google Scholar 

  25. S. Hagita, M. Osaka, K. Shimokado, M. Yoshida, Adipose inflammation initiates recruitment of leukocytes to mouse femoral artery: role of adipo-vascular axis in chronic inflammation. PloS One 6(5), e19871 (2011). https://doi.org/10.1371/journal.pone.0019871

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. N. Kawanishi, H. Yano, Y. Yokogawa, K. Suzuki, Exercise training inhibits inflammation in adipose tissue via both suppression of macrophage infiltration and acceleration of phenotypic switching from M1 to M2 macrophages in high-fat-diet-induced obese mice. Exerc. Immunol. Rev. 16, 105–118 (2010)

    PubMed  Google Scholar 

  27. K. Ohashi, J.L. Parker, N. Ouchi, A. Higuchi, J.A. Vita, N. Gokce, A.A. Pedersen, C. Kalthoff, S. Tullin, A. Sams, R. Summer, K. Walsh, Adiponectin promotes macrophage polarization toward an anti-inflammatory phenotype. J. Biol. Chem. 285(9), 6153–6160 (2010). https://doi.org/10.1074/jbc.M109.088708

    Article  CAS  PubMed  Google Scholar 

  28. K. Li, W. Xu, Q. Guo, Z. Jiang, P. Wang, Y. Yue, S. Xiong, Differential macrophage polarization in male and female BALB/c mice infected with coxsackievirus B3 defines susceptibility to viral myocarditis. Circ. Res. 105(4), 353–364 (2009). https://doi.org/10.1161/circresaha.109.195230

    Article  CAS  PubMed  Google Scholar 

  29. N. Nakanishi, K. Suzuki, K. Tatara, White blood cell count and clustered features of metabolic syndrome in Japanese male office workers. Occup. Med. 52(4), 213–218 (2002). https://doi.org/10.1093/occmed/52.4.213

    Article  CAS  Google Scholar 

  30. V. Mohamed-Ali, S. Goodrick, A. Rawesh, D.R. Katz, J.M. Miles, J.S. Yudkin, S. Klein, S.W. Coppack, Subcutaneous adipose tissue releases interleukin-6, but not tumor necrosis factor-alpha, in vivo. J. Clin. Endocrinol. Metab. 82(12), 4196–4200 (1997). https://doi.org/10.1210/jcem.82.12.4450

    Article  CAS  PubMed  Google Scholar 

  31. M. Benagiano, A. Azzurri, A. Ciervo, A. Amedei, C. Tamburini, M. Ferrari, J.L. Telford, C.T. Baldari, S. Romagnani, A. Cassone, M.M. D’Elios, G. Del Prete, T helper type 1 lymphocytes drive inflammation in human atherosclerotic lesions. Proc. Natl Acad. Sci. USA 100(11), 6658–6663 (2003). https://doi.org/10.1073/pnas.1135726100

    Article  CAS  PubMed  Google Scholar 

  32. B. Osterud, Tissue factor/TFPI and blood cells. Thromb. Res. 129(3), 274–278 (2012). https://doi.org/10.1016/j.thromres.2011.11.049

    Article  CAS  PubMed  Google Scholar 

  33. N.P. Kumar, K. Moideen, Y. Bhootra, A. Nancy, V. Viswanathan, B.S. Shruthi, S. Sivakumar, M. Natarajan, H. Kornfeld, S. Babu, Elevated circulating levels of monocyte activation markers among tuberculosis. Immunology 156(3), 249–258 (2019). https://doi.org/10.1111/imm.13023

    Article  CAS  PubMed  Google Scholar 

  34. E. Palella, R. Cimino, S.A. Pullano, A.S. Fiorillo, E. Gulletta, A. Brunetti, D.P. Foti, M. Greco, Laboratory parameters of hemostasis, adhesion molecules, and inflammation in type 2 diabetes mellitus: correlation with glycemic control. Int. J. Environ. Res. Public. Health 17(1), E300 (2020). https://doi.org/10.3390/ijerph17010300

    Article  PubMed  Google Scholar 

  35. G. Twig, A. Afek, A. Shamiss, E. Derazne, D. Tzur, B. Gordon, A. Tirosh, White blood cells count and incidence of type 2 diabetes in young men. Diabetes Care 36(2), 276–282 (2013). https://doi.org/10.2337/dc11-2298

    Article  PubMed  PubMed Central  Google Scholar 

  36. K.C. Sung, S. Ryu, J.W. Sung, Y.B. Kim, Y.S. Won, D.S. Cho, S.H. Kim, A. Liu, Inflammation in the prediction of type 2 diabetes and hypertension in healthy. Arch. Med. Res. 48(6), 535–545 (2017). https://doi.org/10.1016/j.arcmed.2017.11.010

    Article  CAS  PubMed  Google Scholar 

  37. E.S. Androulakis, D. Tousoulis, N. Papageorgiou, C. Tsioufis, I. Kallikazaros, C. Stefanadis, Essential hypertension: is there a role for inflammatory mechanisms?. Cardiol. Rev. 17(5), 216–221 (2009). https://doi.org/10.1097/CRD.0b013e3181b18e03

    Article  PubMed  Google Scholar 

  38. D.J. Kim, J.H. Noh, B.W. Lee, Y.H. Choi, J.H. Chung, Y.K. Min, M.S. Lee, M.K. Lee, K.W. Kim, The associations of total and differential white blood cell counts with obesity, hypertension, dyslipidemia and glucose intolerance in a Korean population. J. Korean Med. Sci. 23(2), 193–198 (2008). https://doi.org/10.3346/jkms.2008.23.2.193

    Article  PubMed  PubMed Central  Google Scholar 

  39. V. Lohsoonthorn, W. Jiamjarasrungsi, M.A. Williams, Association of hematological parameters with clustered components of metabolic syndrome among professional and office workers in Bangkok, Thailand. Diabetes Metab. Syndr. 1(3), 143–149 (2007). https://doi.org/10.1016/j.dsx.2007.05.002

    Article  PubMed  PubMed Central  Google Scholar 

  40. P. Zhou, Z. Meng, M. Liu, X. Ren, M. Zhu, Q. He, Q. Zhang, L. Liu, K. Song, Q. Jia, J. Tan, X. Li, N. Liu, T. Hu, A. Upadhyaya, The associations between leukocyte, erythrocyte or platelet, and metabolic syndrome in different genders of Chinese. Medicine 95(44), e5189 (2016). https://doi.org/10.1097/md.0000000000005189

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. N. Ishizaka, Y. Ishizaka, E. Toda, R. Nagai, M. Yamakado, Association between cigarette smoking, white blood cell count, and metabolic syndrome as defined by the Japanese criteria. Intern. Med. 46(15), 1167–1170 (2007). https://doi.org/10.2169/internalmedicine.46.0136

    Article  PubMed  Google Scholar 

  42. Y. Ogawa, M. Imaki, Y. Yoshida, M. Shibakawa, S. Tanada, An epidemiological study on the association between the total leukocyte and neutrophil counts, and risk factors of ischemic heart disease by smoking status in Japanese factory workers. Appl. Hum. Sci. 17(6), 239–247 (1998). https://doi.org/10.2114/jpa.17.239

    Article  CAS  Google Scholar 

  43. J. Schwartz, S.T. Weiss, Cigarette smoking and peripheral blood leukocyte differentials. Ann. Epidemiol. 4(3), 236–242 (1994). https://doi.org/10.1016/1047-2797(94)90102-3

    Article  CAS  PubMed  Google Scholar 

  44. Y.Y. Cheng, T.W. Kao, Y.W. Chang, C.J. Wu, T.C. Peng, L.W. Wu, H.F. Yang, F.Y. Liaw, W.L. Chen, Examining the gender difference in the association between metabolic syndrome and the mean leukocyte telomere length. PLoS ONE 12(7), e0180687 (2017). https://doi.org/10.1371/journal.pone.0180687

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. J.H. Kim, J.A. Im, D.C. Lee, The relationship between leukocyte mitochondrial DNA contents and metabolic syndrome in postmenopausal women. Menopause 19(5), 582–587 (2012). https://doi.org/10.1097/gme.0b013e31823a3e46

    Article  PubMed  Google Scholar 

  46. C. Duffaut, A. Zakaroff-Girard, V. Bourlier, P. Decaunes, M. Maumus, P. Chiotasso, C. Sengenes, M. Lafontan, J. Galitzky, A. Bouloumie, Interplay between human adipocytes and T lymphocytes in obesity: CCL20 as an adipochemokine and T lymphocytes as lipogenic modulators. Arterioscler. Thromb. Vasc. Biol. 29(10), 1608–1614 (2009). https://doi.org/10.1161/atvbaha.109.192583

    Article  CAS  PubMed  Google Scholar 

  47. E. Oda, High-sensitivity C-reactive protein and white blood cell count equally predict development of the metabolic syndrome in a Japanese health screening population. Acta Diabetol. 50(4), 633–638 (2013). https://doi.org/10.1007/s00592-013-0477-7

    Article  CAS  PubMed  Google Scholar 

  48. E. Oda, R. Kawai, Comparison between high-sensitivity C-reactive protein (hs-CRP) and white blood cell count (WBC) as an inflammatory component of metabolic syndrome in Japanese. Intern. Med. 49(2), 117–124 (2010). https://doi.org/10.2169/internalmedicine.49.2670

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This study was supported by the Science and Technology Bureau of Xiangcheng District in Suzhou, China under grant no. XJ201706 and the Health Commission of Suzhou under grant no. GSWS2019090.

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Authors and Affiliations

  1. School of Public Health, Medical College of Soochow University, Suzhou, China

    Xue-Jiao Yang, Shun Tian, Hong-Peng Sun, Yong Xu & Chen-Wei Pan

  2. The 3rd People’s Hospital of Xiangcheng District, Suzhou, China

    Qing-Hua Ma

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  1. Xue-Jiao Yang
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Correspondence to Chen-Wei Pan.

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Yang, XJ., Tian, S., Ma, QH. et al. Leukocyte-related parameters in older adults with metabolic syndrome. Endocrine 68, 312–319 (2020). https://doi.org/10.1007/s12020-020-02243-2

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