1
|
Guardiola M, Rehues P, Amigó N, Arrieta F, Botana M, Gimeno-Orna JA, Girona J, Martínez-Montoro JI, Ortega E, Pérez-Pérez A, Sánchez-Margalet V, Pedro-Botet J, Ribalta J. Increasing the complexity of lipoprotein characterization for cardiovascular risk in type 2 diabetes. Eur J Clin Invest 2024; 54:e14214. [PMID: 38613414 DOI: 10.1111/eci.14214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 03/28/2024] [Accepted: 03/31/2024] [Indexed: 04/15/2024]
Abstract
The burden of cardiovascular disease is particularly high among individuals with diabetes, even when LDL cholesterol is normal or within the therapeutic target. Despite this, cholesterol accumulates in their arteries, in part, due to persistent atherogenic dyslipidaemia characterized by elevated triglycerides, remnant cholesterol, smaller LDL particles and reduced HDL cholesterol. The causal link between dyslipidaemia and atherosclerosis in T2DM is complex, and our contention is that a deeper understanding of lipoprotein composition and functionality, the vehicle that delivers cholesterol to the artery, will provide insight for improving our understanding of the hidden cardiovascular risk of diabetes. This narrative review covers three levels of complexity in lipoprotein characterization: 1-the information provided by routine clinical biochemistry, 2-advanced nuclear magnetic resonance (NMR)-based lipoprotein profiling and 3-the identification of minor components or physical properties of lipoproteins that can help explain arterial accumulation in individuals with normal LDLc levels, which is typically the case in individuals with T2DM. This document highlights the importance of incorporating these three layers of lipoprotein-related information into population-based studies on ASCVD in T2DM. Such an attempt should inevitably run in parallel with biotechnological solutions that allow large-scale determination of these sets of methodologically diverse parameters.
Collapse
Affiliation(s)
- Montse Guardiola
- Departament de Medicina i Cirurgia, Unitat de Recerca en Lípids i Arteriosclerosi (URLA), Universitat Rovira i Virgili, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Pere Rehues
- Departament de Medicina i Cirurgia, Unitat de Recerca en Lípids i Arteriosclerosi (URLA), Universitat Rovira i Virgili, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Núria Amigó
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Departament de Ciències Mèdiques Bàsiques, Universitat Rovira i Virgili, Reus, Spain
- Biosfer Teslab, Reus, Spain
| | | | - Manuel Botana
- Departamento de Endocrinología y Nutrición, Hospital Universitario Lucus Augusti, Lugo, Spain
| | - José A Gimeno-Orna
- Endocrinology and Nutrition Department, Hospital Clínico Universitario Lozano Blesa, Zaragoza, Spain
| | - Josefa Girona
- Departament de Medicina i Cirurgia, Unitat de Recerca en Lípids i Arteriosclerosi (URLA), Universitat Rovira i Virgili, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - José Ignacio Martínez-Montoro
- Department of Endocrinology and Nutrition, Virgen de la Victoria University Hospital, Málaga, Spain
- Instituto de Investigación Biomédica de Málaga (IBIMA)-Plataforma Bionand, Málaga, Spain
| | - Emilio Ortega
- Department of Endocrinology and Nutrition, Hospital Clínic, Barcelona, Spain
- Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Barcelona, Spain
| | - Antonio Pérez-Pérez
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Servicio de Endocrinología y Nutrición, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Víctor Sánchez-Margalet
- Department of Medical Biochemistry and Molecular Biology, School of Medicine, Virgen Macarena University Hospital, University of Seville, Seville, Spain
| | - Juan Pedro-Botet
- Unidad de Lípidos y Riesgo Vascular, Department of Endocrinology and Nutrition, Hospital del Mar, Barcelona, Spain
- Department of Medicine, Universitat Autónoma de Barcelona, Barcelona, Spain
| | - Josep Ribalta
- Departament de Medicina i Cirurgia, Unitat de Recerca en Lípids i Arteriosclerosi (URLA), Universitat Rovira i Virgili, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| |
Collapse
|
2
|
Candás-Estébanez B, Fernández-Cidón B, Corbella E, Tebé C, Fanlo-Maresma M, Esteve-Luque V, Salas-Salvadó J, Fitó M, Riera-Mestre A, Ros E, Pintó X. The Impact of the Mediterranean Diet and Lifestyle Intervention on Lipoprotein Subclass Profiles among Metabolic Syndrome Patients: Findings of a Randomized Controlled Trial. Int J Mol Sci 2024; 25:1338. [PMID: 38279337 PMCID: PMC10817060 DOI: 10.3390/ijms25021338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 12/31/2023] [Accepted: 01/05/2024] [Indexed: 01/28/2024] Open
Abstract
Metabolic syndrome (MetS) is associated with alterations of lipoprotein structure and function that can be characterized with advanced lipoprotein testing (ADLT). The effect of the Mediterranean diet (MedDiet) and weight loss on the lipoprotein subclass profile has been scarcely studied. Within the PREDIMED-Plus randomized controlled trial, a sub-study conducted at Bellvitge Hospital recruiting center evaluated the effects of a weight loss program based on an energy-reduced MedDiet (er-MedDiet) and physical activity (PA) promotion (intervention group) compared with energy-unrestricted MedDiet recommendations (control group) on ADLT-assessed lipoprotein subclasses. 202 patients with MetS (n = 107, intervention; n = 95, control) were included. Lipid profiles were determined, and ADLT was performed at baseline, 6, and 12 months. Linear mixed models were used to assess the effects of intervention on lipoprotein profiles. Compared to the control diet, at 12 months, the er-MedDiet+PA resulted in a significant additional 4.2 kg of body weight loss, a decrease in body mass index by 1.4 kg/m2, reduction in waist circumference by 2.2 cm, decreased triglycerides, LDL-cholesterol and non-HDL-cholesterol, and increased HDL-cholesterol. In er-MedDiet+PA participants, ADLT revealed a decrease in small dense-LDL-cholesterol (sd-LDL-C), intermediate-density lipoproteins, VLDL-triglyceride, and HDL-Triglyceride, and an increase in large LDL and large VLDL particles. In conclusion, compared to an ad libitum MedDiet (control group), er-MedDiet+PA decreased plasma triglycerides and the triglyceride content in HDL and VLDL particles, decreased sd-LDL-C, and increased large LDL particles, indicating beneficial changes against cardiovascular disease.
Collapse
Affiliation(s)
- Beatriz Candás-Estébanez
- Clinical Laboratory, Bellvitge University Hospital, 08907 L’Hospitalet de Llobregat, Spain; (B.C.-E.); (B.F.-C.)
- Clinical Laboratory, SCIAS-Barcelona Hospital, 08036 Barcelona, Spain
| | - Bárbara Fernández-Cidón
- Clinical Laboratory, Bellvitge University Hospital, 08907 L’Hospitalet de Llobregat, Spain; (B.C.-E.); (B.F.-C.)
- Department of Biochemistry, Molecular Biology and Biomedicine, Autonomous University of Barcelona (UAB), 08193 Barcelona, Spain
| | - Emili Corbella
- Lipids and Vascular Risk Unit, Internal Medicine Department, Bellvitge University Hospital, 08907 L’Hospitalet de Llobregat, Spain; (E.C.); (M.F.-M.); (V.E.-L.); (A.R.-M.)
- Bellvitge Biomedical Research Institute (IDIBELL), 08907 L’Hospitalet de Llobregat, Spain;
- Center for Biomedical Research in Obesity and Nutrition Physiopathology Network (CIBEROBN), Carlos III Health Institute, 28029 Madrid, Spain; (J.S.-S.); (M.F.); (E.R.)
| | - Cristian Tebé
- Bellvitge Biomedical Research Institute (IDIBELL), 08907 L’Hospitalet de Llobregat, Spain;
| | - Marta Fanlo-Maresma
- Lipids and Vascular Risk Unit, Internal Medicine Department, Bellvitge University Hospital, 08907 L’Hospitalet de Llobregat, Spain; (E.C.); (M.F.-M.); (V.E.-L.); (A.R.-M.)
- Bellvitge Biomedical Research Institute (IDIBELL), 08907 L’Hospitalet de Llobregat, Spain;
- Center for Biomedical Research in Obesity and Nutrition Physiopathology Network (CIBEROBN), Carlos III Health Institute, 28029 Madrid, Spain; (J.S.-S.); (M.F.); (E.R.)
| | - Virginia Esteve-Luque
- Lipids and Vascular Risk Unit, Internal Medicine Department, Bellvitge University Hospital, 08907 L’Hospitalet de Llobregat, Spain; (E.C.); (M.F.-M.); (V.E.-L.); (A.R.-M.)
- Bellvitge Biomedical Research Institute (IDIBELL), 08907 L’Hospitalet de Llobregat, Spain;
- Center for Biomedical Research in Obesity and Nutrition Physiopathology Network (CIBEROBN), Carlos III Health Institute, 28029 Madrid, Spain; (J.S.-S.); (M.F.); (E.R.)
| | - Jordi Salas-Salvadó
- Center for Biomedical Research in Obesity and Nutrition Physiopathology Network (CIBEROBN), Carlos III Health Institute, 28029 Madrid, Spain; (J.S.-S.); (M.F.); (E.R.)
- Nutrition Unit, Department of Biochemistry and Biotechnology, Rovira i Virgili University Human, 43204 Reus, Spain
- Pere Virgili Health Research Institute (IISPV), San Joan de Reus University Hospital, 43204 Reus, Spain
| | - Montserrat Fitó
- Center for Biomedical Research in Obesity and Nutrition Physiopathology Network (CIBEROBN), Carlos III Health Institute, 28029 Madrid, Spain; (J.S.-S.); (M.F.); (E.R.)
- Hospital del Mar Medical Research Institute (IMIM), 08003 Barcelona, Spain
| | - Antoni Riera-Mestre
- Lipids and Vascular Risk Unit, Internal Medicine Department, Bellvitge University Hospital, 08907 L’Hospitalet de Llobregat, Spain; (E.C.); (M.F.-M.); (V.E.-L.); (A.R.-M.)
- Bellvitge Biomedical Research Institute (IDIBELL), 08907 L’Hospitalet de Llobregat, Spain;
- Department of Medicine, School of Medicine, Bellvitge Campus, Barcelona University, 08007 Barcelona, Spain
| | - Emilio Ros
- Center for Biomedical Research in Obesity and Nutrition Physiopathology Network (CIBEROBN), Carlos III Health Institute, 28029 Madrid, Spain; (J.S.-S.); (M.F.); (E.R.)
- Lipid Clinic, Department of Endocrinology and Nutrition, Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, 08036 Barcelona, Spain
| | - Xavier Pintó
- Lipids and Vascular Risk Unit, Internal Medicine Department, Bellvitge University Hospital, 08907 L’Hospitalet de Llobregat, Spain; (E.C.); (M.F.-M.); (V.E.-L.); (A.R.-M.)
- Bellvitge Biomedical Research Institute (IDIBELL), 08907 L’Hospitalet de Llobregat, Spain;
- Center for Biomedical Research in Obesity and Nutrition Physiopathology Network (CIBEROBN), Carlos III Health Institute, 28029 Madrid, Spain; (J.S.-S.); (M.F.); (E.R.)
- Department of Medicine, School of Medicine, Bellvitge Campus, Barcelona University, 08007 Barcelona, Spain
| |
Collapse
|
3
|
Reijnders E, van der Laarse A, Jukema JW, Cobbaert CM. High residual cardiovascular risk after lipid-lowering: prime time for Predictive, Preventive, Personalized, Participatory, and Psycho-cognitive medicine. Front Cardiovasc Med 2023; 10:1264319. [PMID: 37908502 PMCID: PMC10613690 DOI: 10.3389/fcvm.2023.1264319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 10/03/2023] [Indexed: 11/02/2023] Open
Abstract
As time has come to translate trial results into individualized medical diagnosis and therapy, we analyzed how to minimize residual risk of cardiovascular disease (CVD) by reviewing papers on "residual cardiovascular disease risk". During this review process we found 989 papers that started off with residual CVD risk after initiating statin therapy, continued with papers on residual CVD risk after initiating therapy to increase high-density lipoprotein-cholesterol (HDL-C), followed by papers on residual CVD risk after initiating therapy to decrease triglyceride (TG) levels. Later on, papers dealing with elevated levels of lipoprotein remnants and lipoprotein(a) [Lp(a)] reported new risk factors of residual CVD risk. And as new risk factors are being discovered and new therapies are being tested, residual CVD risk will be reduced further. As we move from CVD risk reduction to improvement of patient management, a paradigm shift from a reductionistic approach towards a holistic approach is required. To that purpose, a personalized treatment dependent on the individual's CVD risk factors including lipid profile abnormalities should be configured, along the line of P5 medicine for each individual patient, i.e., with Predictive, Preventive, Personalized, Participatory, and Psycho-cognitive approaches.
Collapse
Affiliation(s)
- E. Reijnders
- Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Center, Leiden, Netherlands
| | - A. van der Laarse
- Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Center, Leiden, Netherlands
| | - J. W. Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands
- Netherlands Heart Institute, Utrecht, Netherlands
| | - C. M. Cobbaert
- Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Center, Leiden, Netherlands
| |
Collapse
|
4
|
Qiao YN, Zou YL, Guo SD. Low-density lipoprotein particles in atherosclerosis. Front Physiol 2022; 13:931931. [PMID: 36111155 PMCID: PMC9468243 DOI: 10.3389/fphys.2022.931931] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 08/05/2022] [Indexed: 12/11/2022] Open
Abstract
Among the diseases causing human death, cardiovascular disease (CVD) remains number one according to the World Health Organization report in 2021. It is known that atherosclerosis is the pathological basis of CVD. Low-density lipoprotein (LDL) plays a pivotal role in the initiation and progression of atherosclerotic CVD (ASCVD). LDL cholesterol (LDL-C) is the traditional biological marker of LDL. However, large numbers of patients who have achieved the recommended LDL-C goals still have ASCVD risk. In multiple prospective studies, LDL particle (LDL-P) is reported to be more accurate in predicting CVD risk than LDL-C. LDL-Ps differ in size, density and chemical composition. Numerous clinical studies have proved that the atherogenic mechanisms of LDL-Ps are determined not only by LDL number and size but also by LDL modifications. Of note, small dense LDL (sdLDL) particles possess stronger atherogenic ability compared with large and intermediate LDL subfractions. Besides, oxidized LDL (ox-LDL) is another risk factor in atherosclerosis. Among the traditional lipid-lowering drugs, statins induce dramatic reductions in LDL-C and LDL-P to a lesser extend. Recently, proprotein convertase subtilsin/kexin type 9 inhibitors (PCSK9i) have been demonstrated to be effective in lowering the levels of LDL-C, LDL-P, as well as CVD events. In this article, we will make a short review of LDL metabolism, discuss the discordance between LDL-C and LDL-P, outline the atherogenic mechanisms of action of LDL by focusing on sdLDL and ox-LDL, summarize the methods used for measurement of LDL subclasses, and conclude the advances in LDL-lowering therapies using statins and PCSK9i.
Collapse
|
5
|
Nakayama A, Morita H, Sato T, Kawahara T, Takeda N, Kato S, Itoh H, Komuro I. Small Dense Low-Density Lipoprotein Cholesterol is a Potential Marker for Predicting Laser Treatment for Retinopathy in Diabetic Patients. J Atheroscler Thromb 2022; 29:678-691. [PMID: 33994406 PMCID: PMC9135669 DOI: 10.5551/jat.62889] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 03/31/2021] [Indexed: 11/26/2022] Open
Abstract
AIM We explored the superiority of small dense low-density lipoprotein cholesterol (sdLDL-C) as a marker for predicting not only the occurrence of cardiovascular (CV) events but also the need for laser treatment in patients with hypercholesterolemia and diabetic retinopathy. METHODS We performed a sub-analysis of the intEnsive statin therapy for hyper-cholesteroleMic Patients with diAbetic retinopaTHY (EMPATHY) study (n=5042), in which patients were assigned randomly to intensive or standard statin therapy targeting low-density lipoprotein cholesterol <70 mg/dl or 100-120 mg/dl. Using the survival analysis, the risks for CV events and the need for laser treatment were evaluated according to the lipids one year after registration. RESULTS The patients were 63±11 years old. LDL-C and sdLDL-C levels were 98±25 and 32±14 mg/dl, respectively, one year after registration. The sdLDL-C level had a strong positive correlation with apolipoprotein B level (r=0.83 at registration). SdLDL-C was a sensitive marker for predicting CV events when comparing among the quartiles according to sdLDL-C levels (hazard ratios: HR for quartiles 1-4 were 1.0, 1.4, 1.6, and 2.5, respectively; p for trend <0.01). Also, sdLDL-C was a sensitive marker for predicting the need for laser treatment among lipids (log rank, p=0.009), especially in patients with elderly (≧65 yrs) and obesity (BMI ≧25 kg/m2). CONCLUSIONS SdLDL-C is a sensitive target marker to predict cardiovascular events as well as the need for laser treatment in patients with hypercholesterolemia and diabetic retinopathy.
Collapse
Affiliation(s)
- Atsuko Nakayama
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hiroyuki Morita
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Tatsuyuki Sato
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Takuya Kawahara
- Clinical Research Promotion Center, The University of Tokyo, Tokyo, Japan
| | - Norifumi Takeda
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Satoshi Kato
- Department of Ophthalmology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hiroshi Itoh
- Department of Endocrinology, Metabolism and Nephrology, Keio University School of Medicine, Tokyo, Japan
| | - Issei Komuro
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| |
Collapse
|
6
|
Chen S, Luan H, He J, Wang Y, Liu S, Li Y, Zeng X, Yuan H. Serum concentrations of small dense low-density lipoprotein cholesterol and lipoprotein(a) are related to coronary arteriostenosis in Takayasu arteritis. J Clin Lab Anal 2021; 35:e23966. [PMID: 34709671 PMCID: PMC8649385 DOI: 10.1002/jcla.23966] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 07/30/2021] [Accepted: 08/07/2021] [Indexed: 12/29/2022] Open
Abstract
Background Serum small dense low‐density lipoprotein cholesterol (sdLDL‐C) and lipoprotein(a) [Lp(a)] levels are related to coronary disease, but their specific associations with coronary arteriostenosis in Takayasu arteritis (TA) have not been ascertained. This study explored the correlations between serum sdLDL‐C and Lp(a) levels and coronary arteriostenosis in TA patients as well as the degree of artery stenosis. Methods This retrospective study included 190 TA patients and 154 healthy subjects. TA patients were divided into three categories based on the degree of coronary stenosis: Group I, stenosis >50%; Group II, stenosis 1%–50%; and Group III, stenosis 0%. Independent risk factors for coronary arteriostenosis in TA were identified by logistic regression, followed by receiver operating characteristic curve analysis to determine the specificity and sensitivity of risk factors and Youden's Index score calculation to determine the cutoff points. Results Takayasu arteritis patients had significantly higher serum levels of sdLDL‐C and Lp(a) than healthy controls (p < 0.0001). The total cholesterol, triglyceride, LDL‐C, sdLDL‐C, and Lp(a) levels and the sdLDL‐C/LDL‐C ratio in Group I were significantly higher than those in Groups II and III (p < 0.05). An elevated serum sdLDL‐C level elevated the risk of coronary arteriostenosis by 5‐fold (cutoff value, 0.605 mmol/l). An increased serum Lp(a) level increased the risk of coronary arteriostenosis by 3.9‐fold (cutoff value, 0.045 g/l). An elevated sdLDL‐C/LDL‐C ratio increased the risk of coronary arteriostenosis by 2.1‐fold (cutoff value, 0.258). Conclusions Serum sdLDL‐C and Lp(a) levels and sdLDL‐C/LDL‐C ratio may be used as diagnostic factors for coronary arteriostenosis in TA patients.
Collapse
Affiliation(s)
- Si Chen
- Department of Clinical Laboratory, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Haixia Luan
- Department of Clinical Laboratory, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Jianxun He
- Department of Clinical Laboratory, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Yan Wang
- Department of Clinical Laboratory, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Shuang Liu
- Department of Clinical Laboratory, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Yongzhe Li
- Department of Clinical Laboratory, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Science, Beijing, China
| | - Xiaoli Zeng
- Department of Clinical Laboratory, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Hui Yuan
- Department of Clinical Laboratory, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| |
Collapse
|
7
|
Asymptomatic Carotid Atherosclerosis Cardiovascular Risk Factors and Common Hypertriglyceridemia Genetic Variants in Patients with Systemic Erythematosus Lupus. J Clin Med 2021; 10:jcm10102218. [PMID: 34065555 PMCID: PMC8160900 DOI: 10.3390/jcm10102218] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 05/05/2021] [Accepted: 05/13/2021] [Indexed: 01/06/2023] Open
Abstract
SLE is associated with increased cardiovascular risk. The objective of this study was to determine the prevalence of asymptomatic carotid atherosclerosis to analyze its relationship with dyslipidemia and related genetic factors in a population of patients with SLE. Seventy-one SLE female patients were recruited. Carotid ultrasound, laboratory profiles, and genetic analysis of the ZPR1, APOA5, and GCKR genes were performed. SLE patients were divided into two groups according to the presence or absence of carotid plaques. Patients with carotid plaque had higher plasma TG (1.5 vs. 0.9 mmol/L, p = 0.001), Non-HDL-C (3.5 vs. 3.1 mmol/L, p = 0.025), and apoB concentrations (1.0 vs. 0.9 g/L, p = 0.010) and a higher prevalence of hypertension (80 vs. 37.5%, p = 0.003) than patients without carotid plaque. The GCKR C-allele was present in 83.3% and 16.7% (p = 0.047) of patients with and without carotid plaque, respectively. The GCKR CC genotype (OR = 0.026; 95% CI: 0.001 to 0.473, p = 0.014), an increase of 1 mmol/L in TG concentrations (OR = 12.550; 95% CI: 1.703 to 92.475, p = 0.013) and to be hypertensive (OR = 9.691; 95% CI: 1.703 to 84.874, p = 0.040) were independently associated with carotid atherosclerosis. In summary, plasma TG concentrations, CGKR CC homozygosity, and hypertension are independent predictors of carotid atherosclerosis in women with SLE.
Collapse
|
8
|
Fernández-Cidón B, Candás-Estébanez B, Ribalta J, Rock E, Guardiola-Guionnet M, Amigó N, Padró-Miquel A, Alía-Ramos P, Pintó-Sala X. Precipitated sdLDL: An easy method to estimate LDL particle size. J Clin Lab Anal 2020; 34:e23282. [PMID: 32198796 PMCID: PMC7370712 DOI: 10.1002/jcla.23282] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 01/16/2020] [Accepted: 02/04/2020] [Indexed: 11/10/2022] Open
Abstract
Background LDL‐C lowering is the main measure in cardiovascular disease prevention but a residual risk of ischemic events still remains. Alterations of lipoproteins, specially, increase in small dense LDL (sdLDL) particles are related to this risk. Objective To investigate the potential use of sdLDL cholesterol concentration (sdLDL‐C) isolated by an easy precipitation method and to assess the impact of a set of clinical and biochemical variables determined by NMR on sdLDL concentration. Methods sdLDL‐C and NMR lipid profile were performed in 85 men samples. Association among them was evaluated using Pearson coefficients (rxy). A multivariate regression was performed to identify the influence of NMR variables on sdLDL‐C. Results A strong association between sdLDL‐C and LDLLDL‐P (rxy = 0.687) and with LDL‐Z (rxy = −0.603) was found. The multivariate regression explained a 56.8% in sdLDL‐C variation (P = 8.77.10‐12). BMI, ApoB, triglycerides, FFA, and LDL‐Z showed a significant contribution. The most important ones were ApoB and LDL‐Z; a 1nm increase (LDL‐Z) leads to decrease 126 nmol/L in sdLDL‐C. Conclusion The association between sdLDL‐C, LDL‐Z, and LDL‐P is clear. From a large number of variables, especially LDL‐Z and apoB influence on sdLDL‐C. Results show that the smaller the LDL size, the higher their cholesterol concentration. Therefore, sdLDL‐C determination by using this easy method would be useful to risk stratification and to uncover cardiovascular residual risk.
Collapse
Affiliation(s)
- Bárbara Fernández-Cidón
- Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Spain.,Department of Biochemistry, Molecular Biology and Biomedicine, Autonomous University of Barcelona (UAB), Barcelona, Spain
| | | | - Josep Ribalta
- Institut d'Investigació Sanitària Pere Virgili, Reus, Spain
| | - Edmond Rock
- French National Institute for Agricultural Research, Paris, France
| | | | - Núria Amigó
- Institut d'Investigació Sanitària Pere Virgili, Reus, Spain
| | | | - Pedro Alía-Ramos
- Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Spain
| | - Xavier Pintó-Sala
- Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Spain
| |
Collapse
|