Lipid Parameters and the Development of Chronic Kidney Disease: A Prospective Cohort Study in Middle-Aged and Elderly Chinese Individuals
Abstract
:1. Introduction
2. Methods
2.1. Population and Study Design
2.2. Clinical and Biochemical Measurements
2.3. Definition of CKD
2.4. Statistical Analysis
3. Results
3.1. Clinical Features of the Research Group
3.2. Relationship between Lipid Profiles and Clinical Factors Associated with Renal Function
3.3. Associations between Lipid Parameters and CKD
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Collaboration, G.C.K.D. Global, regional, and national burden of chronic kidney disease, 1990–2017 a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2020, 395, 709–733. [Google Scholar]
- Bulbul, M.C.; Dagel, T.; Afsar, B.; Ulusu, N.N.; Kuwabara, M.; Covic, A.; Kanbay, M. Disorders of Lipid Metabolism in Chronic Kidney Disease. Blood Purif. 2018, 46, 144–152. [Google Scholar] [CrossRef] [PubMed]
- Zabetian, A.; Coca, S.G. Plasma and urine biomarkers in chronic kidney disease: Closer to clinical application. Curr. Opin. Nephrol. Hypertens. 2021, 30, 531–537. [Google Scholar] [CrossRef] [PubMed]
- Reiss, A.B.; Voloshyna, I.; De Leon, J.; Miyawaki, N.; Mattana, J. Cholesterol Metabolism in CKD. Am. J. Kidney Dis. 2015, 66, 1071–1082. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Visconti, L.; Benvenga, S.; Lacquaniti, A.; Cernaro, V.; Bruzzese, A.; Conti, G.; Buemi, M.; Santoro, D. Lipid disorders in patients with renal failure: Role in cardiovascular events and progression of chronic kidney disease. J. Clin. Transl. Endocrinol. 2016, 6, 8–14. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sun, K.; Lin, D.; Li, F.; Huang, C.; Qi, Y.; Xue, S.; Tang, J.; Yang, C.; Li, Y.; Ren, M.; et al. Discordant associations of lipid parameters with albuminuria and chronic kidney disease: A population-based study. Lipids Health Dis. 2015, 14, 152. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zeng, W.; Beyene, H.B.; Kuokkanen, M.; Miao, G.; Magliano, D.J.; Umans, J.G.; Franceschini, N.; Cole, S.A.; Michailidis, G.; Lee, E.T.; et al. Lipidomic profiling in the Strong Heart Study identified American Indians at risk of chronic kidney disease. Kidney Int. 2022, 102, 1154–1166. [Google Scholar] [CrossRef] [PubMed]
- Lanktree, M.B.; Thériault, S.; Walsh, M.; Pare, G. HDL Cholesterol, LDL Cholesterol, and Triglycerides as Risk Factors for CKD: A Mendelian Randomization Study. Am. J. Kidney Dis. 2018, 71, 166–172. [Google Scholar] [CrossRef] [PubMed]
- Wang, Y.-X.; Wang, A.-P.; Ye, Y.-N.; Gao, Z.-N.; Tang, X.-L.; Yan, L.; Wan, Q.; Wang, W.-Q.; Luo, Z.-J.; Qin, G.-J.; et al. Elevated triglycerides rather than other lipid parameters are associated with increased urinary albumin to creatinine ratio in the general population of China: A report from the REACTION study. Cardiovasc. Diabetol. 2019, 18, 57. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhang, L.; Yuan, Z.; Chen, W.; Chen, S.; Liu, X.; Liang, Y.; Shao, X.; Zou, H. Serum Lipid Profiles, Lipid Ratios and Chronic Kidney Disease in a Chinese Population. Int. J. Environ. Res. Public Health 2014, 11, 7622–7635. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ning, G. Reaction Study, Risk Evaluation of Cancers in Chinese Diabetic Individuals: A Longitudinal (REACTION) Study. J. Diabetes 2012, 4, 172–173. [Google Scholar] [CrossRef] [PubMed]
- Bi, Y.; Lu, J.; Wang, W.; Mu, Y.; Zhao, J.; Liu, C.; Chen, L.; Shi, L.; Li, Q.; Wan, Q.; et al. Cohort profile: Risk evaluation of cancers in Chinese diabetic individuals: A longitudinal (REACTION) study. J. Diabetes 2013, 6, 147–157. [Google Scholar] [CrossRef] [PubMed]
- Tomioka, K.; Iwamoto, J.; Saeki, K.; Okamoto, N. Reliability and Validity of the International Physical Activity Questionnaire (IPAQ) in Elderly Adults: The Fujiwara-kyo Study. J. Epidemiol. 2011, 21, 459–465. [Google Scholar] [CrossRef] [Green Version]
- De Leeuw, P.W.; Thijs, L.; Birkenhäger, W.H.; Voyaki, S.M.; Efstratopoulos, A.D.; Fagard, R.H.; Leonetti, G.; Nachev, C.; Petrie, J.C.; Rodicio, J.L.; et al. Prognostic Significance of Renal Function in Elderly Patients with Isolated Systolic Hypertension: Results from the Syst-Eur Trial. J. Am. Soc. Nephrol. 2002, 13, 2213–2222. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Xue, J.; Wang, Y.; Li, B.; Yu, S.; Wang, A.; Wang, W.; Gao, Z.; Tang, X.; Yan, L.; Wan, Q.; et al. Triglycerides to high-density lipoprotein cholesterol ratio is superior to triglycerides and other lipid ratios as an indicator of increased urinary albumin-to-creatinine ratio in the general population of China: A cross-sectional study. Lipids Health Dis. 2021, 20, 1–12. [Google Scholar] [CrossRef] [PubMed]
- Gai, Z.; Wang, T.; Visentin, M.; Kullak-Ublick, G.; Fu, X.; Wang, Z. Lipid Accumulation and Chronic Kidney Disease. Nutrients 2019, 11, 722. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Stadler, K.; Goldberg, I.J.; Susztak, K. The Evolving Understanding of the Contribution of Lipid Metabolism to Diabetic Kidney Disease. Curr. Diabetes Rep. 2015, 15, 40. [Google Scholar] [CrossRef] [Green Version]
- Yuan, Q.; Ben Tang, B.; Zhang, C. Signaling pathways of chronic kidney diseases, implications for therapeutics. Signal Transduct. Target. Ther. 2022, 7, 182. [Google Scholar] [CrossRef]
- Merscher, S.; Pedigo, C.; Mendez, A. Metabolism, energetics, and lipid biology in the podocyte-cellular cholesterol-mediated glomerular injury. Front. Endocrinol. 2014, 5, 169. [Google Scholar] [CrossRef] [Green Version]
- Sun, Y.; Cui, S.; Hou, Y.; Yi, F. The Updates of Podocyte Lipid Metabolism in Proteinuric Kidney Disease. Kidney Dis. 2021, 7, 438–451. [Google Scholar] [CrossRef]
- Castro, B.B.A.; Foresto-Neto, O.; Saraiva-Camara, N.O.; Sanders-Pinheiro, H. Renal lipotoxicity: Insights from experimental models. Clin. Exp. Pharmacol. Physiol. 2021, 48, 1579–1588. [Google Scholar] [CrossRef] [PubMed]
- Florens, N.; Calzada, C.; Lyasko, E.; Juillard, L.; Soulage, C.O. Modified Lipids and Lipoproteins in Chronic Kidney Disease: A New Class of Uremic Toxins. Toxins 2016, 8, 376. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Krata, N.; Zagożdżon, R.; Foroncewicz, B.; Mucha, K. Oxidative Stress in Kidney Diseases: The Cause or the Consequence? Arch. Immunol. Ther. Exp. 2018, 66, 211–220. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kachhawa, K.; Varma, M.; Agrawal, D.; Shaikh, M.; Kumar, S. Study of dyslipidemia and antioxidant status in chronic kidney disease patients at a hospital in South East Asia. Neurol. India 2016, 3, 28. [Google Scholar] [CrossRef]
- Zuo, P.; Chen, X.; Liu, Y.; Zhang, R.; He, X.; Liu, C. Non-HDL-cholesterol to HDL-cholesterol ratio as an independent risk factor for the development of chronic kidney disease. Nutr. Metab. Cardiovasc. Dis. 2015, 25, 582–587. [Google Scholar] [CrossRef]
- Lee, S.; Lee, Y.; Kang, M.W.; Park, S.; Park, S.; Han, K.; Paek, J.H.; Park, W.Y.; Jin, K.; Han, S. Predictive value of triglyceride/high-density lipoprotein cholesterol for major clinical outcomes in advanced chronic kidney disease: A nationwide population-based study. Clin. Kidney J. 2021, 14, 1961–1968. [Google Scholar]
- Bajaj, A.; Xie, D.; Cedillo-Couvert, E.; Charleston, J.; Chen, J.; Deo, R.; Feldman, H.I.; Go, A.S.; He, J.; Horwitz, E.; et al. Lipids, Apolipoproteins, and Risk of Atherosclerotic Cardiovascular Disease in Persons With CKD. Am. J. Kidney Dis. 2019, 73, 827–836. [Google Scholar] [CrossRef] [Green Version]
- Tada, H.; Nohara, A.; Kawashiri, M.-A. Serum Triglycerides and Atherosclerotic Cardiovascular Disease: Insights from Clinical and Genetic Studies. Nutrients 2018, 10, 1789. [Google Scholar] [CrossRef] [Green Version]
- Vaziri, N.D.; Norris, K. Lipid Disorders and Their Relevance to Outcomes in Chronic Kidney Disease. Blood Purif. 2011, 31, 189–196. [Google Scholar] [CrossRef]
- Huang, F.; Wang, L.; Zhang, Q.; Wan, Z.; Hu, L.; Xu, R.; Cheng, A.; Lv, Y.; Liu, Q. Elevated atherogenic index and higher triglyceride increase risk of kidney function decline: A 7-year cohort study in Chinese adults. Ren. Fail. 2020, 43, 32–39. [Google Scholar] [CrossRef]
- Toth, P.P.; Philip, S.; Hull, M.; Granowitz, C. Elevated Triglycerides (>/=150 mg/dL) and High Triglycerides (200–499 mg/dL) Are Significant Predictors of Hospitalization for New-Onset Kidney Disease: A Real-World Analysis of High-Risk Statin-Treated Patients. Cardiorenal Med. 2019, 9, 400–407. [Google Scholar] [CrossRef]
- Ferro, C.J.; Mark, P.B.; Kanbay, M.; Sarafidis, P.; Heine, G.H.; Rossignol, P.; Massy, Z.A.; Mallamaci, F.; Valdivielso, J.M.; Malyszko, J.; et al. Lipid management in patients with chronic kidney disease. Nat. Rev. Nephrol. 2018, 14, 727–749. [Google Scholar] [CrossRef] [PubMed]
- Dincer, N.; Dagel, T.; Afsar, B.; Covic, A.; Ortiz, A.; Kanbay, M. The effect of chronic kidney disease on lipid metabolism. Int. Urol. Nephrol. 2018, 51, 265–277. [Google Scholar] [CrossRef] [PubMed]
- Toba, H.; Lindsey, M.L. Extracellular matrix roles in cardiorenal fibrosis: Potential therapeutic targets for CVD and CKD in the elderly. Pharmacol. Ther. 2019, 193, 99–120. [Google Scholar] [CrossRef]
- Lamprea-Montealegre, J.A.; Staplin, N.; Herrington, W.G.; Haynes, R.; Emberson, J.; Baigent, C.; de Boer, I.H.; SHARP Collaborative Group. Apolipoprotein B, Triglyceride-Rich Lipoproteins, and Risk of Cardiovascular Events in Persons with CKD. Clin. J. Am. Soc. Nephrol. 2019, 15, 47–60. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhao, W.-B.; Zhu, L.; Rahman, T. Increased serum concentration of apolipoprotein B is associated with an increased risk of reaching renal replacement therapy in patients with diabetic kidney disease. Ren. Fail. 2020, 42, 323–328. [Google Scholar] [CrossRef] [Green Version]
- Jensen, J.S.; Feldt-Rasmussen, B.; Strandgaard, S.; Schroll, M.; Borch-Johnsen, K. Arterial Hypertension, Microalbuminuria, and Risk of Ischemic Heart Disease. Hypertension 2000, 35, 898–903. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Eknoyan, G.; Hostetter, T.; Bakris, G.L.; Hebert, L.; Levey, A.S.; Parving, H.-H.; Steffes, M.W.; Toto, R. Proteinuria and other markers of chronic kidney disease: A position statement of the national kidney foundation (NKF) and the national institute of diabetes and digestive and kidney diseases (NIDDK). Am. J. Kidney Dis. 2003, 42, 617–622. [Google Scholar] [CrossRef]
- Zhang, L.; Wang, F.; Wang, L.; Wang, W.; Liu, B.; Liu, J.; Chen, M.; He, Q.; Liao, Y.; Yu, X.; et al. Prevalence of chronic kidney disease in China: A cross-sectional survey. Lancet 2012, 379, 815–822. [Google Scholar] [CrossRef]
without CKD | with CKD | p | |
---|---|---|---|
n (%) * | 5005 (93.6) | 340 (6.4) | <0.0001 |
UACR (mg/g) | 7.63 (5.59–10.79) | 11.19 (7.15–16.79) | <0.0001 |
eGFR (ml/min per 1.73 m2) | 103.1 ± 21.3 | 94.6 ± 24.5 | <0.0001 |
TG (mmol/L) | 1.25 (0.92–1.81) | 1.49 (1.02–2.16) | <0.0001 |
TC (mmol/L) | 5.22 ± 1.23 | 5.19 ± 1.24 | 0.6318 |
HDL-C (mmol/L) | 1.34 ± 0.36 | 1.23 ± 0.33 | <0.0001 |
LDL-C (mmol/L) | 3.16 ± 0.95 | 3.13 ± 0.95 | 0.5898 |
Non-HDL-C (mmol/L) | 3.89 ± 1.09 | 3.96 ± 1.09 | 0.2166 |
Non-HDL-C/HDL-C | 3.05 ± 1.02 | 3.37 ± 1.05 | <0.0001 |
TG/HDL-C | 2.19 (1.47–3.48) | 2.78 (1.85–4.69) | <0.0001 |
Age (years) | 55.5 ± 7.0 | 58.5 ± 8.5 | <0.0001 |
Male [n (%)] | 1370 (27.4) | 130 (38.2) | <0.0001 |
BMI (kg/m2) | 23.5 ± 3.2 | 24.6 ± 3.3 | <0.0001 |
WC (cm) | 81.1 ± 9.3 | 84.2 ± 9.3 | <0.0001 |
SBP (mmHg) | 124.8 ± 15.6 | 132.5 ± 16.6 | <0.0001 |
DBP (mmHg) | 74.9 ± 9.7 | 77.5 ± 9.9 | <0.0001 |
Current smoking [n (%)] | 411 (8.4) | 40 (12.1) | 0.0215 |
Current drinking [n (%)] | 156 (3.2) | 13 (3.9) | 0.4669 |
FPG (mmol/L) | 5.40 (5.00–5.90) | 5.60 (5.10–6.17) | <0.0001 |
OGTT 2 h glucose (mmol/L) | 7.27 (6.09–9.00) | 7.96 (6.53–10.29) | <0.0001 |
HbA1c | 5.90 (5.60–6.20) | 6.00 (5.70–6.40) | <0.0001 |
Fasting insulin (μIU/mL) | 7.10 (5.20–9.60) | 7.95 (5.85–11.20) | <0.0001 |
γ-GGT (U/L) | 19.0 (14.0–28.0) | 22.0 (15.0–30.0) | 0.0047 |
Physical activity (MET-h/week) | 22.0 (10.5–46.0) | 24.5 (10.5–47.0) | 0.9665 |
UACR (mg/g) | Creatinine (μmol/L) | eGFR (mL/min per 1.73 m2) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
r | p | St. β | p | r | p | St. β | p | r | p | St. β | p | |
TG (mmol/L) | 0.090 | <0.0001 | 0.091 | <0.0001 | 0.122 | <0.0001 | 0.055 | <0.0001 | −0.107 | <0.0001 | −0.070 | <0.0001 |
TC (mmol/L) | 0.020 | 0.1486 | −0.001 | 0.9231 | −0.035 | 0.0100 | −0.002 | 0.8720 | −0.018 | 0.1866 | 0.001 | 0.9278 |
HDL-C (mmol/L) | −0.033 | 0.0163 | −0.062 | <0.0001 | −0.193 | <0.0001 | −0.057 | <0.0001 | 0.099 | <0.0001 | 0.071 | <0.0001 |
LDL-C (mmol/L) | 0.006 | 0.6737 | −0.011 | 0.4239 | −0.023 | 0.0977 | −0.008 | 0.4226 | −0.012 | 0.3702 | 0.010 | 0.4583 |
Non-HDL-C (mmol/L) | 0.034 | 0.0128 | 0.018 | 0.1899 | 0.021 | 0.1248 | 0.015 | 0.1539 | −0.053 | 0.0001 | −0.020 | 0.1319 |
Non-HDL-C/HDL-C | 0.062 | <0.0001 | 0.073 | <0.0001 | 0.196 | <0.0001 | 0.066 | <0.0001 | −0.140 | <0.0001 | −0.083 | <0.0001 |
TG/HDL-C | 0.089 | <0.0001 | 0.104 | <0.0001 | 0.187 | <0.0001 | 0.071 | <0.0001 | −0.132 | <0.0001 | −0.090 | <0.0001 |
Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | 1-Quartile Change # | AUC (95% CI) * | ||
---|---|---|---|---|---|---|---|
TG | Model 1 | 1 | 1.02 (0.72–1.45) | 1.48 (1.06–2.05) | 1.83 (1.33–2.50) | 1.25 (1.13–1.38) | 0.577 (0.545–0.609) |
Model 2 | 1 | 0.98 (0.69–1.39) | 1.37 (0.99–1.91) | 1.68 (1.22–2.31) | 1.22 (1.10–1.35) | ||
Model 3 | 1 | 0.99 (0.69–1.42) | 1.31 (0.93–1.85) | 1.48 (1.06–2.08) | 1.16 (1.04–1.29) | ||
TC | Model 1 | 1 | 0.96 (0.70–1.32) | 1.12 (0.83–1.52) | 0.89 (0.65–1.23) | 0.98 (0.89–1.09) | 0.495 (0.464–0.527) |
Model 2 | 1 | 0.94 (0.69–1.29) | 1.08 (0.80–1.47) | 0.81 (0.59–1.12) | 0.96 (0.87–1.06) | ||
Model 3 | 1 | 0.96 (0.70–1.33) | 1.09 (0.80–1.50) | 0.84 (0.60–1.17) | 0.96 (0.87–1.07) | ||
HDL-C | Model 1 | 1 | 1.23 (0.93–1.63) | 1.76 (1.29–2.40) | 2.07 (1.50–2.85) | 1.29 (1.17–1.43) | 0.411 (0.381–0.441) |
Model 2 | 1 | 1.24 (0.94–1.65) | 1.75 (1.28–2.38) | 1.99 (1.44 - 2.75) | 1.28 (1.15–1.41) | ||
Model 3 | 1 | 1.19 (0.88–1.59) | 1.53 (1.11–2.12) | 1.62 (1.15–2.30) | 1.19 (1.07–1.33) | ||
LDL-C | Model 1 | 1 | 0.85 (0.62–1.16) | 1.00 (0.74–1.35) | 0.87 (0.63 0 1.18) | 0.98 (0.88–1.08) | 0.495 (0.463–0.527) |
Model 2 | 1 | 0.83 (0.61–1.14) | 0.96 (0.71–1.30) | 0.78 (0.57–1.07) | 0.94 (0.85–1.04) | ||
Model 3 | 1 | 0.85 (0.62–1.18) | 0.97 (0.71–1.33) | 0.78 (0.56–1.08) | 0.94 (0.85–1.04) | ||
Non-HDL-C | Model 1 | 1 | 1.32 (0.96–1.82) | 1.32 (0.95–1.82) | 1.35 (0.98–1.86) | 1.09 (0.99–1.20) | 0.526 (0.494–0.557) |
Model 2 | 1 | 1.27 (0.92–1.75) | 1.23 (0.89–1.71) | 1.21 (0.87–1.67) | 1.05 (0.95–1.16) | ||
Model 3 | 1 | 1.32 (0.95–1.85) | 1.20 (0.86–1.68) | 1.18 (0.84–1.65) | 1.03 (0.93–1.15) | ||
Non-HDL-C/HDL-C | Model 1 | 1 | 1.36 (0.95–1.95) | 2.02 (1.42–2.86) | 2.32 (1.65–3.28) | 1.33 (1.20–1.47) | 0.595 (0.564–0.625) |
Model 2 | 1 | 1.33 (0.93–1.92) | 1.88 (1.32–2.66) | 2.07 (1.47–2.93) | 1.28 (1.15–1.42) | ||
Model 3 | 1 | 1.24 (0.85–1.81) | 1.66 (1.16–2.41) | 1.66 (1.15–2.42) | 1.19 (1.06–1.33) | ||
TG/HDL-C | Model 1 | 1 | 1.15 (0.80–1.66) | 1.78 (1.27–2.50) | 2.31 (1.67–3.20) | 1.35 (1.22–1.49) | 0.599 (0.568–0.630) |
Model 2 | 1 | 1.08 (0.74–1.55) | 1.66 (1.18–2.33) | 2.11 (1.52–2.93) | 1.32 (1.19–1.46) | ||
Model 3 | 1 | 0.98 (0.67–1.44) | 1.46 (1.03–2.10) | 1.72 (1.22–2.46) | 1.24 (1.11–1.38) |
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Liao, S.; Lin, D.; Feng, Q.; Li, F.; Qi, Y.; Feng, W.; Yang, C.; Yan, L.; Ren, M.; Sun, K. Lipid Parameters and the Development of Chronic Kidney Disease: A Prospective Cohort Study in Middle-Aged and Elderly Chinese Individuals. Nutrients 2023, 15, 112. https://doi.org/10.3390/nu15010112
Liao S, Lin D, Feng Q, Li F, Qi Y, Feng W, Yang C, Yan L, Ren M, Sun K. Lipid Parameters and the Development of Chronic Kidney Disease: A Prospective Cohort Study in Middle-Aged and Elderly Chinese Individuals. Nutrients. 2023; 15(1):112. https://doi.org/10.3390/nu15010112
Chicago/Turabian StyleLiao, Shumei, Diaozhu Lin, Qiling Feng, Feng Li, Yiqin Qi, Wanting Feng, Chuan Yang, Li Yan, Meng Ren, and Kan Sun. 2023. "Lipid Parameters and the Development of Chronic Kidney Disease: A Prospective Cohort Study in Middle-Aged and Elderly Chinese Individuals" Nutrients 15, no. 1: 112. https://doi.org/10.3390/nu15010112