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Total cholesterol to high-density lipoprotein cholesterol ratio is independently associated with CKD progression

  • Nephrology - Original Paper
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Abstract

Purpose

Although dyslipidemia can cause kidney damage, whether it independently contributes to the progression of chronic kidney disease (CKD) remains controversial. The research aims to evaluate the predictive value of serum lipids and their ratios in the progression of CKD.

Methods

The retrospective, case–control study included 380 adult subjects with CKD stage 3–4 (G3-4) at baseline. The end point of follow-up was the progression of CKD, defined as a composite of renal function rapid decline [an annual estimated glomerular filtration rate (eGFR) decline > 5 mL/min/1.73 m2] or the new-onset end-stage renal disease (ESRD) [eGFR < 15 mL/min/1.73 m2]. Logistic regression analysis was performed to examine the association between CKD progression and lipid parameters. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive power of lipid parameters in the progression of CKD.

Results

Over a median follow-up of 3.0 years, 96 participants (25.3%) developed CKD progression. In multivariable logistic regression analysis, logarithm-transformed urinary albumin-to-creatinine ratio (log ACR) [odds ratio (OR) 1.834;95% confidence interval (CI) 1.253–2.685; P = 0.002] and total cholesterol to high-density lipoprotein cholesterol ratio (TC/HDL-C) [OR 1.345; 95% CI 1.079–1.677; P = 0.008] were independently associated with CKD progression. The ROC curve showed the combined predictor of ACR and TC/HDL-C ratio was acceptable for CKD progression diagnosis (area under the ROC curve [AUC] = 0.716, sensitivity 50.0%, specificity 84.2%), and the cut-off value was − 0.98.

Conclusions

The combination of TC/HDL-C ratio and ACR had predictive value in the progression of CKD, and may help identify the high-risk population with CKD.

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Data availability

All data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Aleksandra Pikula ASB, Wang J (2015) Lipid and lipoprotein measurements and the risk of ischemic vascular events: Framingham Study. Neurology 84(5):472–479

    Article  Google Scholar 

  2. Diamond JR (1991) Analogous pathobiologic mechanisms in glomerulosclerosis and atherosclerosis. Kidney Int Suppl 31:S29-34

    CAS  PubMed  Google Scholar 

  3. Moorhead JF, Chan MK, El-Nahas M (1982) Lipid nephrotoxicity in chronic progressive glomerular and tubulo-interstitial disease. Lancet 2(8311):1309–1311

    Article  CAS  Google Scholar 

  4. Merscher S, Pedigo CE, Mendez AJ (2014) Metabolism, energetics, and lipid biology in the podocyte—cellular cholesterol-mediated glomerular injury. Front Endocrinol (Lausanne) 5:169

    Google Scholar 

  5. Johnson AC, Stahl A, Zager RA (2005) Triglyceride accumulation in injured renal tubular cells: alterations in both synthetic and catabolic pathways. Kidney Int 67(6):2196–2209

    Article  CAS  Google Scholar 

  6. Trevisan R, Dodesini AR, Lepore G (2006) Lipids and renal disease. J Am Soc Nephrol 17(4 Suppl 2):S145-147

    Article  CAS  Google Scholar 

  7. Cachofeiro V, Goicochea M, de Vinuesa SG, Oubina P, Lahera V, Luno J (2008) Oxidative stress and inflammation, a link between chronic kidney disease and cardiovascular disease. Kidney Int Suppl 111:S4-9

    Article  CAS  Google Scholar 

  8. Rajendran P, Rengarajan T, Thangavel J et al (2013) The vascular endothelium and human diseases. Int J Biol Sci 9(10):1057–1069

    Article  CAS  Google Scholar 

  9. Joles JA, Kunter U, Janssen U et al (2000) Early mechanisms of renal injury in hypercholesterolemic or hypertriglyceridemic rats. J Am Soc Nephrol 11(4):669–683

    Article  CAS  Google Scholar 

  10. Blanco S, Vaquero M, Gomez-Guerrero C, Lopez D, Egido J, Romero R (2005) Potential role of angiotensin-converting enzyme inhibitors and statins on early podocyte damage in a model of type 2 diabetes mellitus, obesity, and mild hypertension. Am J Hypertens 18(4 Pt 1):557–565

    Article  CAS  Google Scholar 

  11. Rahman M, Yang W, Akkina S et al (2014) Relation of serum lipids and lipoproteins with progression of CKD: the CRIC study. Clin J Am Soc Nephrol 9(7):1190–1198

    Article  CAS  Google Scholar 

  12. Nam KH, Chang TI, Joo YS et al (2019) Association between serum high-density lipoprotein cholesterol levels and progression of chronic kidney disease: results from the KNOW-CKD. J Am Heart Assoc 8(6):e011162

    Article  Google Scholar 

  13. Bowe B, Xie Y, Xian H, Balasubramanian S, Al-Aly Z (2016) Low levels of high-density lipoprotein cholesterol increase the risk of incident kidney disease and its progression. Kidney Int 89(4):886–896

    Article  CAS  Google Scholar 

  14. Sanchez-Inigo L, Navarro-Gonzalez D, Pastrana-Delgado J, Fernandez-Montero A, Martinez JA (2016) Association of triglycerides and new lipid markers with the incidence of hypertension in a Spanish cohort. J Hypertens 34(7):1257–1265

    Article  CAS  Google Scholar 

  15. Edwards MK, Blaha MJ, Loprinzi PD (2017) Atherogenic index of plasma and triglyceride/high-density lipoprotein cholesterol ratio predict mortality risk better than individual cholesterol risk factors, among an older adult population. Mayo Clin Proc 92(4):680–681

    Article  Google Scholar 

  16. Zhang X, Wang B, Yang J et al (2019) Serum lipids and risk of rapid renal function decline in treated hypertensive adults with normal renal function. Am J Hypertens 32(4):393–401

    Article  CAS  Google Scholar 

  17. Schaeffner ES, Kurth T, Curhan GC et al (2003) Cholesterol and the risk of renal dysfunction in apparently healthy men. J Am Soc Nephrol 14(8):2084–2091

    Article  CAS  Google Scholar 

  18. Zuo PY, Chen XL, Liu YW, Zhang R, He XX, Liu CY (2015) Non-HDL-cholesterol to HDL-cholesterol ratio as an independent risk factor for the development of chronic kidney disease. Nutr Metab Cardiovasc Dis 25(6):582–587

    Article  CAS  Google Scholar 

  19. Zhang L, Yuan Z, Chen W et al (2014) Serum lipid profiles, lipid ratios and chronic kidney disease in a Chinese population. Int J Environ Res Public Health 11(8):7622–7635

    Article  CAS  Google Scholar 

  20. Bikbov B, Purcell CA, Levey AS et al (2020) Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 395(10225):709–733

    Article  Google Scholar 

  21. Zhang L, Wang F, Wang L et al (2012) Prevalence of chronic kidney disease in China: a cross-sectional survey. Lancet 379(9818):815–822

    Article  Google Scholar 

  22. Huang Y, Gao L, Xie X, Tan SC (2014) Epidemiology of dyslipidemia in Chinese adults: meta-analysis of prevalence, awareness, treatment, and control. Popul Health Metr 12(1):28

    Article  Google Scholar 

  23. Inker LA, Astor BC, Fox CH et al (2014) KDOQI US commentary on the 2012 KDIGO clinical practice guideline for the evaluation and management of CKD. Am J Kidney Dis 63(5):713–735

    Article  Google Scholar 

  24. Levin A, Stevens PE (2014) Summary of KDIGO 2012 CKD guideline: behind the scenes, need for guidance, and a framework for moving forward. Kidney Int 85(1):49–61

    Article  Google Scholar 

  25. Levey AS, Stevens LA, Schmid CH et al (2009) A new equation to estimate glomerular filtration rate. Ann Intern Med 150(9):604–612

    Article  Google Scholar 

  26. Visconti L, Benvenga S, Lacquaniti A et al (2016) Lipid disorders in patients with renal failure: role in cardiovascular events and progression of chronic kidney disease. J Clin Transl Endocrinol 6:8–14

    PubMed  PubMed Central  Google Scholar 

  27. Kwan BC, Kronenberg F, Beddhu S, Cheung AK (2007) Lipoprotein metabolism and lipid management in chronic kidney disease. J Am Soc Nephrol 18(4):1246–1261

    Article  CAS  Google Scholar 

  28. Bulbul MC, Dagel T, Afsar B et al (2018) Disorders of lipid metabolism in chronic kidney disease. Blood Purif 46(2):144–152

    Article  CAS  Google Scholar 

  29. Mikolasevic I, Zutelija M, Mavrinac V, Orlic L (2017) Dyslipidemia in patients with chronic kidney disease: etiology and management. Int J Nephrol Renovasc Dis 10:35–45

    Article  CAS  Google Scholar 

  30. Vaziri ND (2006) Dyslipidemia of chronic renal failure: the nature, mechanisms, and potential consequences. Am J Physiol Renal Physiol 290(2):F262-272

    Article  CAS  Google Scholar 

  31. Kronenberg F (2018) HDL in CKD-the devil is in the detail. J Am Soc Nephrol 29(5):1356–1371

    Article  CAS  Google Scholar 

  32. Rysz J, Gluba-Brzozka A, Rysz-Gorzynska M, Franczyk B (2020) The role and function of HDL in patients with chronic kidney disease and the risk of cardiovascular disease. Int J Mol Sci 21(2):601

    Article  CAS  Google Scholar 

  33. Ji B, Zhang S, Gong L et al (2013) The risk factors of mild decline in estimated glomerular filtration rate in a community-based population. Clin Biochem 46(9):750–754

    Article  CAS  Google Scholar 

  34. Stevens LA, Schmid CH, Greene T et al (2010) Comparative performance of the CKD epidemiology collaboration (CKD-EPI) and the modification of diet in renal disease (MDRD) study equations for estimating GFR levels above 60 mL/min/1.73 m2. Am J Kidney Dis 56(3):486–495

    Article  Google Scholar 

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Funding

This work was financially supported by Wuhan Health and Family Planning Commission research projects (No. WX18Q31).

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Authors and Affiliations

  1. Department of Nephrology, Wuhan Fourth Hospital, Puai Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430033, Hubei, People’s Republic of China

    Wei Li, Zhijie Du, Honglan Wei & Junwu Dong

Authors
  1. Wei Li
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  2. Zhijie Du
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  3. Honglan Wei
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  4. Junwu Dong
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Contributions

HW and JD conceived and designed the study. WL screened the abstract and full text, assessed studies and drafted the manuscript. ZD performed statistical analyses. HW revised the manuscript. All authors read the manuscript and approved the final version.

Corresponding authors

Correspondence to Honglan Wei or Junwu Dong.

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Conflict of interest

All the authors declared no competing interests.

Ethical approval

This study was performed in accordance with the ethical principles of the Declaration of Helsinki and was approved by the ethics Committee of Wuhan Fourth Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (KY2021-0021-01). All participants have written informed consent before the study.

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Li, W., Du, Z., Wei, H. et al. Total cholesterol to high-density lipoprotein cholesterol ratio is independently associated with CKD progression. Int Urol Nephrol 54, 2057–2063 (2022). https://doi.org/10.1007/s11255-021-03099-9

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  • DOI: https://doi.org/10.1007/s11255-021-03099-9

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