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An in-depth analysis shows a hidden atherogenic lipoprotein profile in non-diabetic chronic kidney disease patients.
Expert Opin Ther Targets. 2019 07; 23(7):619-630.EO

Abstract

Background: Chronic kidney disease (CKD) is an independent risk factor for atherosclerotic disease. We hypothesized that CKD promotes a proatherogenic lipid profile modifying lipoprotein composition and particle number. Methods: Cross-sectional study in 395 non-diabetic individuals (209 CKD patients and 186 controls) without statin therapy. Conventional lipid determinations were combined with advanced lipoprotein profiling by nuclear magnetic resonance, and their discrimination ability was assessed by machine learning. Results: CKD patients showed an increase of very-low-density (VLDL) particles and a reduction of LDL particle size. Cholesterol and triglyceride content of VLDLs and intermediate-density (IDL) particles increased. However, low-density (LDL) and high-density (HDL) lipoproteins gained triglycerides and lost cholesterol. Total-Cholesterol, HDL-Cholesterol, LDL-Cholesterol, non-HDL-Cholesterol and Proprotein convertase subtilisin-kexin type (PCSK9) were negatively associated with CKD stages, whereas triglycerides, lipoprotein(a), remnant cholesterol, and the PCSK9/LDL-Cholesterol ratio were positively associated. PCSK9 was positively associated with total-Cholesterol, LDL-Cholesterol, LDL-triglycerides, LDL particle number, IDL-Cholesterol, and remnant cholesterol. Machine learning analysis by random forest revealed that new parameters have a higher discrimination ability to classify patients into the CKD group, compared to traditional parameters alone: area under the ROC curve (95% CI), .789 (.711, .853) vs .687 (.611, .755). Conclusions: non-diabetic CKD patients have a hidden proatherogenic lipoprotein profile.

Authors+Show Affiliations

a Vascular & Renal Translational Research Group , IRBLleida, Spain and Spanish Research Network for Renal Diseases (RedInRen. ISCIII) , Lleida , Spain.b Biostatistics Unit , IRBLleida , Lleida , Spain. c Department of Basic Medical Sciences , University of Lleida , Lleida , Spain.d Biosfer Teslab SL , Reus , Spain.a Vascular & Renal Translational Research Group , IRBLleida, Spain and Spanish Research Network for Renal Diseases (RedInRen. ISCIII) , Lleida , Spain.a Vascular & Renal Translational Research Group , IRBLleida, Spain and Spanish Research Network for Renal Diseases (RedInRen. ISCIII) , Lleida , Spain. e Servicio de nefrología , Hospital Universitario Severo Ochoa , Leganés , Spain.f Department of Cardiology , Hospital Universitario Puerta del Mar , Cádiz , Spain.g Endocrinology and Nutrition Department , Hospital Universitari Germans Trias i Pujol , Badalona , Spain. h Center for Biomedical Research on Diabetes and Associated Metabolic Diseases (CIBERDEM) , Barcelona , Spain.a Vascular & Renal Translational Research Group , IRBLleida, Spain and Spanish Research Network for Renal Diseases (RedInRen. ISCIII) , Lleida , Spain.i Department of Nephrology , Centro Hospitalario Torrecardenas , Almeria , Spain.a Vascular & Renal Translational Research Group , IRBLleida, Spain and Spanish Research Network for Renal Diseases (RedInRen. ISCIII) , Lleida , Spain. h Center for Biomedical Research on Diabetes and Associated Metabolic Diseases (CIBERDEM) , Barcelona , Spain. j Endocrinology and Nutrition Department , Hospital de la Santa Creu i Sant Pau , Barcelona , Spain.k Hospital Clínico Universitario Valencia , Universitat de Valencia, INCLIVA , Lleida , Spain.a Vascular & Renal Translational Research Group , IRBLleida, Spain and Spanish Research Network for Renal Diseases (RedInRen. ISCIII) , Lleida , Spain.a Vascular & Renal Translational Research Group , IRBLleida, Spain and Spanish Research Network for Renal Diseases (RedInRen. ISCIII) , Lleida , Spain.

Pub Type(s)

Journal Article
Multicenter Study
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

31100024

Citation

Bermudez-Lopez, Marcelino, et al. "An In-depth Analysis Shows a Hidden Atherogenic Lipoprotein Profile in Non-diabetic Chronic Kidney Disease Patients." Expert Opinion On Therapeutic Targets, vol. 23, no. 7, 2019, pp. 619-630.
Bermudez-Lopez M, Forne C, Amigo N, et al. An in-depth analysis shows a hidden atherogenic lipoprotein profile in non-diabetic chronic kidney disease patients. Expert Opin Ther Targets. 2019;23(7):619-630.
Bermudez-Lopez, M., Forne, C., Amigo, N., Bozic, M., Arroyo, D., Bretones, T., Alonso, N., Cambray, S., Del Pino, M. D., Mauricio, D., Gorriz, J. L., Fernandez, E., & Valdivielso, J. M. (2019). An in-depth analysis shows a hidden atherogenic lipoprotein profile in non-diabetic chronic kidney disease patients. Expert Opinion On Therapeutic Targets, 23(7), 619-630. https://doi.org/10.1080/14728222.2019.1620206
Bermudez-Lopez M, et al. An In-depth Analysis Shows a Hidden Atherogenic Lipoprotein Profile in Non-diabetic Chronic Kidney Disease Patients. Expert Opin Ther Targets. 2019;23(7):619-630. PubMed PMID: 31100024.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - An in-depth analysis shows a hidden atherogenic lipoprotein profile in non-diabetic chronic kidney disease patients. AU - Bermudez-Lopez,Marcelino, AU - Forne,Carles, AU - Amigo,Nuria, AU - Bozic,Milica, AU - Arroyo,David, AU - Bretones,Teresa, AU - Alonso,Nuria, AU - Cambray,Serafi, AU - Del Pino,Maria Dolores, AU - Mauricio,Didac, AU - Gorriz,Jose Luis, AU - Fernandez,Elvira, AU - Valdivielso,Jose Manuel, Y1 - 2019/05/23/ PY - 2019/5/18/pubmed PY - 2020/3/12/medline PY - 2019/5/18/entrez KW - Atherosclerosis KW - Lp(a) KW - PCSK9 KW - chronic kidney disease KW - dyslipidemia KW - lipoprotein subfractions SP - 619 EP - 630 JF - Expert opinion on therapeutic targets JO - Expert Opin Ther Targets VL - 23 IS - 7 N2 - Background: Chronic kidney disease (CKD) is an independent risk factor for atherosclerotic disease. We hypothesized that CKD promotes a proatherogenic lipid profile modifying lipoprotein composition and particle number. Methods: Cross-sectional study in 395 non-diabetic individuals (209 CKD patients and 186 controls) without statin therapy. Conventional lipid determinations were combined with advanced lipoprotein profiling by nuclear magnetic resonance, and their discrimination ability was assessed by machine learning. Results: CKD patients showed an increase of very-low-density (VLDL) particles and a reduction of LDL particle size. Cholesterol and triglyceride content of VLDLs and intermediate-density (IDL) particles increased. However, low-density (LDL) and high-density (HDL) lipoproteins gained triglycerides and lost cholesterol. Total-Cholesterol, HDL-Cholesterol, LDL-Cholesterol, non-HDL-Cholesterol and Proprotein convertase subtilisin-kexin type (PCSK9) were negatively associated with CKD stages, whereas triglycerides, lipoprotein(a), remnant cholesterol, and the PCSK9/LDL-Cholesterol ratio were positively associated. PCSK9 was positively associated with total-Cholesterol, LDL-Cholesterol, LDL-triglycerides, LDL particle number, IDL-Cholesterol, and remnant cholesterol. Machine learning analysis by random forest revealed that new parameters have a higher discrimination ability to classify patients into the CKD group, compared to traditional parameters alone: area under the ROC curve (95% CI), .789 (.711, .853) vs .687 (.611, .755). Conclusions: non-diabetic CKD patients have a hidden proatherogenic lipoprotein profile. SN - 1744-7631 UR - https://www.unboundmedicine.com/medline/citation/31100024/An_in_depth_analysis_shows_a_hidden_atherogenic_lipoprotein_profile_in_non_diabetic_chronic_kidney_disease_patients_ DB - PRIME DP - Unbound Medicine ER -