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New inflammatory biomarkers (lymphocyte and monocyte percentage to high-density lipoprotein cholesterol ratio and lymphocyte to monocyte percentage ratio) and their association with some cardiometabolic diseases

Results from a large Kurdish cohort study in Iran

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Summary

Background

The incidence of metabolic heart diseases has increased significantly in Middle Eastern countries such as Iran. The present study aimed to investigate the association between monocyte percentage to high-density cholesterol ratio (MHR), lymphocyte percentage to high-density cholesterol ratio (LHR), and lymphocyte to monocyte percentage ratio (LMR) and cardiometabolic diseases in a Kurdish population in the west of Iran.

Methods

This study recruited 9803 individuals, 4728 (48.2%) were male and 5084 (51.8%) were female from Ravansar, Iran. All biomarkers were analyzed by the standard methods.

Results

The prevalence of cardiometabolic diseases was higher in overweight/obese participants and increased with age. MHR and LHR increased significantly in cardiometabolic individuals compared with healthy controls. Individuals in the fourth quartiles of LHR and MHR had higher odds ratio (ORs) for metabolic syndrome (MetS) and diabetes mellitus (DM) than the first quartiles. The LMR had a statistical association with non-alcoholic fatty liver disease (NAFLD) ORs and FLI. Besides, all these associations were stronger for females, and increased physical activity decreased inflammatory biomarkers.

Conclusion

The present study showed MHR and LHR had significant associations with ORs of MetS and DM. Also, MHR and LHR had a significant positive correlation with cardiometabolic risk factors. The LMR only had a statistical association with NAFLD and fatty liver index (FLI). Besides, the strong correlation between inflammatory biomarkers and cardiometabolic risk factors in females might be relevant to higher fat accumulation and metabolic inflammation background, and lower physical activity.

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References

  1. Sattar N, Gill JM, Alazawi W. Improving prevention strategies for cardiometabolic disease. Nat Med. 2020;263:320–5.

    Article  Google Scholar 

  2. Cai J, Zhang X-J, Ji Y-X, Zhang P, She Z-G, Li H. Nonalcoholic fatty liver disease pandemic fuels the upsurge in cardiovascular diseases. Circulation research. 2020;1265:679–704.https://doi.org/10.1161/CIRCRESAHA.119.316337.

    Article  CAS  Google Scholar 

  3. Faasse S, Braun H, Vos M. The role of NAFLD in cardiometabolic disease: an update. F1000Res. 2018. https://doi.org/10.12688/f1000research.12028.1.

    Book  Google Scholar 

  4. Ndisang JF, Rastogi S. Cardiometabolic diseases and related complications: current status and future perspective. Hindawi. 2013. https://doi.org/10.1155/2013/467682.

    Article  Google Scholar 

  5. Nichols GA, Horberg M, Koebnick C, et al. Cardiometabolic risk factors among 1.3 million adults with overweight or obesity, but not diabetes, in 10 geographically diverse regions of the United States, 2012–2013. Prev Chronic Dis. 2017;14:E22.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Aksentijevich M, Lateef SS, Anzenberg P, et al. Chronic inflammation, cardiometabolic diseases and effects of treatment: psoriasis as a human model. Trends Cardiovasc Med. 2020;308:472–8.

    Article  Google Scholar 

  7. Donath MY, Meier DT, Böni-Schnetzler M. Inflammation in the pathophysiology and therapy of cardiometabolic disease. Endocr Rev. 2019;404:1080–91.

    Article  Google Scholar 

  8. Kantari C, Pederzoli-Ribeil M, Witko-Sarsat V. The role of neutrophils and monocytes in innate immunity. Trends Innate Immun. 2008;15:118–46.

    Article  CAS  Google Scholar 

  9. Chapman CM, Beilby JP, McQuillan BM, et al. Monocyte count, but not C‑reactive protein or interleukin‑6, is an independent risk marker for subclinical carotid atherosclerosis. Stroke. 2004;357:1619–24.

    Article  Google Scholar 

  10. Moro-García MA, Mayo JC, Sainz RM, et al. Influence of inflammation in the process of T lymphocyte differentiation: proliferative, metabolic, and oxidative changes. Front Immunol. 2018;9:339.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Ely BR, Clayton ZS, McCurdy CE, et al. Meta-inflammation and cardiometabolic disease in obesity: can heat therapy help? Temperature. 2018;51:9–21.

    Article  Google Scholar 

  12. Berg A, Scherer P. The Online version of this article, along with updated information and services, is located on the World Wide Web. JAHA. 2005;96:939–49.

    CAS  Google Scholar 

  13. Osmond JM, Mintz JD, Dalton B, et al. Obesity increases blood pressure, cerebral vascular remodeling, and severity of stroke in the Zucker rat. Hypertension. 2009;532:381–6.

    Article  Google Scholar 

  14. Ouchi N, Kihara S, Funahashi T, et al. Obesity, adiponectin and vascular inflammatory disease. Curr Opin Lipidol. 2003;146:561–6.

    Article  Google Scholar 

  15. Shulman GI. Ectopic fat in insulin resistance, dyslipidemia, and cardiometabolic disease. N Engl J Med. 2014;371(12):1131–41.

    Article  PubMed  Google Scholar 

  16. Zhu X, Parks JS. New roles of HDL in inflammation and hematopoiesis. Annu Rev Nutr. 2012;32:161–82.

    Article  CAS  PubMed  Google Scholar 

  17. Mousa H, Islam N, Ganji V, et al. Serum 25-hydroxyvitamin D is inversely associated with monocyte percentage to HDL cholesterol ratio among young healthy adults in qatar. Nutrients. 2021;131:127.

    Google Scholar 

  18. Chen H, Xiong C, Shao X, et al. Lymphocyte to high-density lipoprotein ratio as a new indicator of inflammation and metabolic syndrome. Diabetes Metab Syndr Obes. 2019;12:2117.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Kizilgül M, Çalişkan M, Uçan B, et al. Monocyte to HDL cholesterol ratio and its association with cardio-metabolic risk factors in primary hyperparathyroidism. Medeniyet Med J. 2018;332:94–9.

    Google Scholar 

  20. Cekici Y, Yılmaz M, Seçen Ö. New inflammatory indicators: association of high eosinophil-to-lymphocyte ratio and low lymphocyte-to-monocyte ratio with smoking. J Int Med Res. 2019;479:4292–303.

    Article  Google Scholar 

  21. Demirbaş A, Elmas ÖF, Atasoy M, et al. Can monocyte to HDL cholesterol ratio and monocyte to lymphocyte ratio be markers for inflammation and oxidative stress in patients with vitiligo? A preliminary study. Arch Dermatol Res. 2020. https://doi.org/10.1007/s00403-020-02129-3.

    Article  PubMed  Google Scholar 

  22. Sirin MC, Korkmaz S, Erturan I, et al. Evaluation of monocyte to HDL cholesterol ratio and other inflammatory markers in patients with psoriasis. An Bras Dermatol. 2020;95:575–82.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Yakar HI, Kanbay A, Ceylan E. Could monocyte/HDL cholesterol ratio predict cardiovascular events in patients with chronic obstructive pulmonary disease? Eur Respiratory Soc. 2017. https://doi.org/10.1183/1393003.congress-2017.PA1007.

    Article  Google Scholar 

  24. Acikgoz N, Kurtoğlu E, Yagmur J, et al. Elevated monocyte to high-density lipoprotein cholesterol ratio and endothelial dysfunction in Behçet disease. Angiology. 2018;691:65–70.

    Article  Google Scholar 

  25. X‑b WCF, J‑l H, et al. Novel risk biomarker for infective endocarditis patients with normal left ventricular ejection fraction—monocyte to high-density lipoprotein cholesterol ratio. Circ J. 2017;821:283–8.

    Google Scholar 

  26. Oh SW, Yi HJ, Lee DH, et al. Prognostic significance of various inflammation-based scores in patients with mechanical thrombectomy for acute ischemic stroke. World Neurosurg. 2020;141:e710–e7.

    Article  PubMed  Google Scholar 

  27. Asgari S, Moosaie F, Khalili D, et al. External validation of the European risk assessment tool for chronic cardio-metabolic disorders in a Middle Eastern population. J Transl Med. 2020;181:1–12.

    Google Scholar 

  28. Pasdar Y, Najafi F, Moradinazar M, et al. Cohort profile: ravansar non-communicable disease cohort study: the first cohort study in a Kurdish population. Int J Epidemiol. 2019;483:682–3f.

    Article  Google Scholar 

  29. Ryan H, Trosclair A, Gfroerer J. Adult current smoking: differences in definitions and prevalence estimates—NHIS and NSDUH, 2008. J Environ Public Health. 2012. https://doi.org/10.1155/2012/918368.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Aadahl M, Jørgensen T. Validation of a new self-report instrument for measuring physical activity. Med Sci Sports Exerc. 2003;357:1196–202.

    Article  Google Scholar 

  31. Rajati F, Hamzeh B, Pasdar Y, et al. Prevalence, awareness, treatment, and control of hypertension and their determinants: results from the first cohort of non-communicable diseases in a Kurdish settlement. Sci Rep. 2019;91:1–10.

    Google Scholar 

  32. Alberti K, Eckel RH, Grundy SM, et al. Harmonizing the metabolic syndrome: a joint interim statement of the international diabetes federation task force on epidemiology and prevention; national heart, lung, and blood institute; American heart association; world heart federation; international atherosclerosis society; and international association for the study of obesity. Circulation. 2009;120(16):1640–5.

    Article  CAS  PubMed  Google Scholar 

  33. Chobanian AV. National heart, lung, and blood institute joint national committee on prevention, detection, evaluation, and treatment of high blood pressure; national high blood pressure education program coordinating committee: the seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure: the JNC 7 report. JAMA. 2003;289:2560–72.

    Article  CAS  PubMed  Google Scholar 

  34. Huang X, Xu M, Chen Y, et al. Validation of the fatty liver index for nonalcoholic fatty liver disease in middle-aged and elderly Chinese. Medicine. 2015;94(40):e1682.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Foster M, Samman S. Zinc and regulation of inflammatory cytokines: implications for cardiometabolic disease. Nutrients. 2012;47:676–94.

    Article  Google Scholar 

  36. Marseglia L, Manti S, D’Angelo G, et al. Oxidative stress in obesity: a critical component in human diseases. IJMS. 2015;161:378–400.

    Google Scholar 

  37. Yu S, Guo X, Li G, et al. Lymphocyte to high-density lipoprotein ratio but not platelet to lymphocyte ratio effectively predicts metabolic syndrome among subjects from rural China. Front Cardiovasc Med. 2021;8:107.

    CAS  Google Scholar 

  38. Yamamoto S, Narita I, Kotani K. The macrophage and its related cholesterol efflux as a HDL function index in atherosclerosis. Clin Chimica Acta. 2016;457:117–22.

    Article  CAS  Google Scholar 

  39. Hu Y, Zhang H, Li J, et al. Gut-derived lymphocyte recruitment to liver and induce liver injury in non-alcoholic fatty liver disease mouse model. J Gastroenterol Hepatol. 2016;313:676–84.

    Article  Google Scholar 

  40. Zhang J, Chen W, Fang L, et al. Increased intermediate monocyte fraction in peripheral blood is associated with nonalcoholic fatty liver disease. Wien Klin Wochenschr. 2018;130(11-12):390–7.

    Article  CAS  PubMed  Google Scholar 

  41. Monteiro R, Teixeira D, Calhau C. Estrogen signaling in metabolic inflammation. Mediators Inflamm. 2014. https://doi.org/10.1155/2014/615917.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Onat A, Karadeniz Y, Tusun E, et al. Advances in understanding gender difference in cardiometabolic disease risk. Expert Rev Cardiovasc Ther. 2016;144:513–23.

    Article  Google Scholar 

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Acknowledgements

The authors are deeply grateful to the investigators of PERSIAN for their valuable support for designing the methods and developing the questionnaire. We also appreciate our interviewers, RaNCD staff, and Ravansar population for their significant cooperation in data collection.

Funding

This study was supported by the Ministry of Health and Medical Education of Iran and Kermanshah University of Medical Science (Grant No: 92472). The funder had no role in the design of the study, collection, analysis, and interpretation of the data, or writing and approval of manuscript.

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Authors and Affiliations

Authors

Contributions

Maryam Kohsari conceived this study. Mehdi Moradinazar and Maryam Kohsari analyzed the data. All authors, including Maryam Kohsari, Mehdi Moradinazar, Zohreh Rahimi, Farid Najafi, Yahya Pasdar, and Ebrahim Shakiba, produced the first draft. All authors contributed to the multiple revisions and approved the final submission.

Corresponding author

Correspondence to Ebrahim Shakiba.

Ethics declarations

Conflict of interest

M. Kohsari, M. Moradinazar, Z. Rahimi, F. Najafi, Y. Pasdar and E. Shakiba declare that they have no competing interests.

Ethical standards

All procedures performed in studies involving human participants or on human tissue were in accordance with the ethical standards of the institutional and/or national research committee and with the 1975 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the ethics committees of Kermanshah University of Medical Sciences (KUMS.REC.1394.315), Kermanshah, Iran. All participants entered the study after they were fully informed of the process and signed a written consent.

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Data availability

The datasets used and analyzed during the current study are available on reasonable request from the corresponding author

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Kohsari, M., Moradinazar, M., Rahimi, Z. et al. New inflammatory biomarkers (lymphocyte and monocyte percentage to high-density lipoprotein cholesterol ratio and lymphocyte to monocyte percentage ratio) and their association with some cardiometabolic diseases. Wien Klin Wochenschr 134, 626–635 (2022). https://doi.org/10.1007/s00508-022-02029-8

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