Clinical Kidney Journal, 2021, vol. 14, no. 12, 2591 –2599 doi: 10.1093/ckj/sfab113 Advance Access Publication Date: 6 July 2021 Original Article Clinical Kidney Journal Downloaded from https://academic.oup.com/ckj/article/14/12/2591/6316255 by Fundacio Biblioteca Josep Laporte user on 30 January 2023 ORIGINAL ARTICLE Advanced lipoprotein parameters could better explain atheromatosis in non-diabetic chronic kidney disease patients Marcelino Bermudez-Lopez1, Hector Perpin ~ an2, Nuria Amigo3, Eva Castro1, Nuria Alonso4,5,6, Didac Mauricio5,6, Elvira Fernandez1, and Jose M. Valdivielso 1, on behalf of the NEFRONA Investigators 1 Vascular and Renal Translational Research Group, Spanish Research Network for Renal Diseases (REDINREN del ISCIII), IRBLleida, Lleida, Spain, 2Conselleria de Sanitat Universal i Salut Pública, Generalitat Valenciana, Valencia, Spain, 3Biosfer Teslab SL, Reus, Spain, 4Endocrinology and Nutrition Department, Hospital Universitari Germans Trias i Pujol, Barcelona, Spain, 5Center for Biomedical Research on Diabetes and Associated Metabolic Diseases (CIBERDEM), Barcelona, Spain and 6Endocrinology and Nutrition Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain Correspondence to: Jose M. Valdivielso; E-mail: valdivielso@medicina.udl.es and Marcelino Bermudez-Lopez; E-mail: mbermudez@irblleida.cat ABSTRACT Background. Chronic kidney disease (CKD) patients have a high burden of atheromatous cardiovascular disease (ASCVD) not fully explained by traditional lipid parameters. Lipoprotein composition and subclass particle number information could improve ASCVD risk assessment. The objective of this study is to investigate the association of advanced lipoprotein parameters with the risk of atheromatosis in a subpopulation of the NEFRONA study. Methods. This was a cross-sectional study in 395 non-diabetic individuals (209 CKD and 186 non-diabetic and non-CKD) without statin therapy. Vascular ultrasound examination assessing 10 territories was combined with advanced lipoprotein testing performed by nuclear magnetic resonance spectroscopy. Logistic regression was used to estimate adjusted odds ratios (ORs) per 1 standard deviation increment. Results. Atheromatosis was more prevalent in CKD patients (33.9% versus 64.6%). After adjusting for age, gender, smoking habit and CKD stage, the amount of triglycerides (TGs) within low-density lipoprotein (LDL) lipoproteins was independently and positively associated with atheromatosis [OR 1.33; 95% confidence interval (CI) 1.03–1.74; P ¼ 0.03]. Similarly, total and medium LDL particles (LDL-Ps) showed a positive association (OR 1.29; 95% CI 1.00–1.68; P ¼ 0.05 and OR 1.34; 95% CI 1.04– 1.75; P ¼ 0.03, respectively). TG-loaded medium LDL-Ps were higher in CKD patients compared with controls and showed an adjusted OR of 1.40 (95% CI 1.09–1.82; P ¼ 0.01) in non-diabetic patients (CKD and non-CKD individuals). In contrast, non- diabetic CKD patients showed a similar coefficient but the significance was lost (OR 1.2; 95% CI 0.8–1.7; P ¼ 0.359). Received: 9.3.2021; Editorial decision: 14.6.2021 C The Author(s) 2021. Published by Oxford University Press on behalf of ERA-EDTA. V This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/ licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com 2591 2592 | M. Bermudez-Lopez et al. Conclusions. Non-diabetic CKD patients showed a higher amount of TG-loaded medium LDL-Ps compared with controls. These particles were independently associated with atheromatosis in non-diabetic patients. Keywords: atherosclerosis, chronic kidney disease, dyslipidemia, LDL cholesterol, lipoprotein subfractions, triglycerides INTRODUCTION of the NEFRONA study [22] composed of non-diabetic individu- Downloaded from https://academic.oup.com/ckj/article/14/12/2591/6316255 by Fundacio Biblioteca Josep Laporte user on 30 January 2023 als without statin therapy. Atheromatous cardiovascular disease (ASCVD) is the leading cause of mortality and morbidity in many countries [1]. It is a systemic multifactorial disease that has a long silent phase MATERIALS AND METHODS before manifesting as an incident cardiovascular event [2]. Study design and participants Atheromatosis is closely related to lipid abnormalities. In the general population, traditional lipid parameters, such as high Cross-sectional study in 209 CKD patients at various stages of the total cholesterol (TC), high low-density lipoprotein cholesterol disease (86 CKD stage 3, 71 CKD stages 4–5 and 52 dialysis) and (LDL-C) and low high-density lipoprotein cholesterol (HDL-C), 186 controls (non-diabetic and non-CKD individuals) belonging to are associated with atheromatosis [3]. The European Society the NEFRONA study were selected. The design and objectives of of Atherosclerosis recently stated that LDL-C directly causes the NEFRONA study have already been published in detail [22, ASCVD [4]. 23]. Briefly, the NEFRONA study was designed as a multicentre Traditional lipid parameters cannot detect changes in lipo- prospective observational cohort study to evaluate subclinical protein size, number and composition. For instance, LDL-C, atheromatosis burden in CKD. A total of 2445 CKD patients were which refers to the cholesterol content within LDL particles enrolled in 81 Spanish hospitals and dialysis clinics, from (LDL-Ps), omits information about particle size, subclass particle October 2010 to June 2012. Inclusion criteria were: patients be- number and composition [5]. Similarly, conventional triglycer- tween 18 and 74 years of age were eligible if they had CKD stage 3 ide (TG) levels measurement indicates total TG with no or higher as defined by current guidelines (glomerular filtration information about its distribution in different types of lipopro- rate <60 mL/min/1.73 m2). In addition, 559 individuals with a glo- teins. On the contrary, advanced lipoprotein testing (ALT) merular filtration rate >60 mL/min/1.73 m2 were recruited from allows a detailed characterization of lipoprotein particles and it primary care centres. Exclusion criteria for both groups were: ac- has been proposed as an important new tool for cardiovascular tive infections, pregnancy, active neoplasia, life expectancy risk assessment [6]. The size, lipid content and number of shorter than 12 months, previous cardiovascular event, carotid lipoprotein particles can be measured by nuclear magnetic reso- surgery or any organ transplantation. To avoid interference with nance (NMR)-based advanced lipoprotein profiling and subfrac- lipid parameters, patients with diabetes and/or on statin therapy tionating. Therefore, we can not only divide the different were excluded from this substudy. Thus, 395 non-diabetic indi- lipoproteins into large, medium and small particles according to viduals (209 CKD and 186 non-diabetic and non-CKD) without their size, but also determine the total number and its specific statin therapy were selected. The study protocol was approved lipid load [7]. by the ethics committees of each hospital. It was conducted In the general population, several studies have revealed that according to the principles of the declaration of Helsinki and all ASCVD risk is more closely related to LDL-P number than to to- patients were included after signing an informed consent. tal levels of LDL-C [8]. In addition, the TG content in LDLs, HDLs and very-low-density lipoproteins (VLDLs) has been shown to be positively associated with myocardial infarction and ischae- Clinical and laboratory determinations mic stroke [9]. Diagnosis of dyslipidaemia and hypertension was collected Chronic kidney disease (CKD) is a worldwide concern with from clinical records. Anthropometrical parameters, smoking an increasing incidence [10]. Compared with individuals with habit and blood samples were obtained at the moment of arte- normal renal function, CKD patients show a higher prevalence rial ultrasound. After processing, serum samples were aliquoted and burden of ASCVD from early stages [11] and this prevalence to avoid freeze–thaw cycles and stored at 80 C. Glomerular fil- rises as kidney disease progresses [12, 13]. CKD patients show tration rate was estimated according to international guidelines an unacceptable high residual cardiovascular risk even with an using the CKD Epidemiology Collaboration equation [24]. TC, accurate control of traditional lipid parameters [14]. Indeed, the HDL-C and TG were measured by colorimetric methods accord- traditional lipid profile in CKD is different from the one found in ing to standardized protocols with an AU5800 Analyzer a conventional high-risk individual; it is characterized by hyper- (Beckman Coulter Inc., Fullerton, CA, USA) in the Clinical triglyceridaemia, varying levels of LDL-C and low HDL-C levels Analysis Laboratory, Arnau de Vilanova University Hospital, [15, 16]. Thus, since these parameters do not explain the excess Lleida, Spain. LDL-C was calculated by Friedewald equation if and the rapid progression of atheromatosis in the CKD popula- TG <250 mg/dL. tion [13, 17], information beyond the traditional lipid profile is needed to fully understand the underlying cause of the acceler- Advanced lipoprotein profiling by NMR ated atherosclerosis in this population. Although some studies have performed ALT in patients with A detailed protocol of NMRS has been previously published [25]. CKD, the association of these parameters with atheromatosis Briefly, frozen serum samples (250 lL) were shipped on dry ice remains elusive [18–20]. Thus, the present study combines tra- to Biosfer Teslab (Reus, Spain) for the analysis of lipoprotein ditional lipid parameters with an advanced lipoprotein profiling profile. Particle concentration and diffusion coefficients were performed by NMR spectroscopy (NMRS) [21] to elucidate their obtained from the measured amplitudes and attenuation of the association with atheroma plaque presence in a subpopulation spectroscopically distinct lipid methyl group NMR signals, using Medium LDL-TG content and atherosclerosis | 2593 the 2D diffusion-ordered 1H NMRS (DSTE) pulse. Methyl signal Table 1. Clinical characteristics and traditional lipid profile according was surface fitted with nine Lorentzian functions associated to atheromatous plaque presence with each lipoprotein subclass of the main lipoprotein groups (VLDL, LDL and HDL). The concentrations of each lipoprotein No plaque Plaque subclass and their lipid composition were calculated [21]. The (n ¼ 197) (n ¼ 198) P-value different lipoprotein subfractions correspond to the following Clinical characteristics diameter size ranges: large VLDL, 68.5–95.9 nm; medium VLDL, Women, n (%) 111 (56.3) 61 (30.8) <0.001 47–68.5 nm; small VLDL, 32.5–47 nm; large LDL, 24–32.5 nm; me- Age (years) 45 (35–56) 62 (53–69) <0.001 Downloaded from https://academic.oup.com/ckj/article/14/12/2591/6316255 by Fundacio Biblioteca Josep Laporte user on 30 January 2023 dium LDL, 20.5–24 nm; small LDL, 17.5–20.5 nm; large HDL, 10.5– CKD stage, n (%) <0.001 13.5 nm; medium HDL, 8.5–10.5 nm; and small HDL, 7.5–8.5 nm. Control 123 (62.4) 63 (31.8) Finally, weighted average VLDL, LDL and HDL particle sizes CKD 3 30 (15.2) 56 (28.3) were calculated from various subfraction concentrations by CKD 4–5 24 (12.2) 47 (23.7) summing the known diameter of each subfraction multiplied by Dialysis 20 (10.2) 32 (16.2) Smoking, n (%) 0.001 its relative percentage of particle number. Non-smoker 100 (50.8) 69 (34.8) Former 62 (31.5) 99 (50) Arterial ultrasound Current 35 (17.8) 30 (15.2) Arterial ultrasound was performed as previously described in the Dyslipidaemia, n (%) 28 (14.2) 71 (35.9) <0.001 NEFRONA study [22]. The VIVID BT09 ultrasound system Hypertension, n (%) 78 (39.6) 150 (75.8) <0.001 (GE Healthcare), equipped with a 6–13 MHz linear probe, a module Systolic BP (mmHg) 125 (115–139) 135 (127–152.8) <0.001 Diastolic BP (mmHg) 77 (71–84) 81.5 (74–87) <0.001 for measuring intima–media thickness (IMT) and a pulsed Doppler Body mass 25.4 (22.8–29.1) 27.4 (25.1–30.5) <0.001 ultrasound, were used to assess haemodynamic abnormalities. index (kg/m2) Atheromatous plaques were defined as an IMT >1.5 mm protrud- Traditional lipid profile ing into the lumen, according to the American Society of TC (mg/dL) 188.7 (32.8) 192.6 (38.6) 0.274 Echocardiography (ASE) consensus statement and the Mannheim HDL-C (mg/dL) 51 (43–60.8) 48 (40–57.8) 0.045 consensus [26, 27]. Plaque presence was considered when it was LDL-C (mg/dL) 115.1 (27.1) 119 (32.6) 0.187 detected in at least 1 of the 10 territories analysed (both internal, TG (mg/dL) 97 (71–132.8) 111.5 (84–154) 0.001 bifurcation and common carotids, and both common and superfi- Non-HDL-C (mg/dL) 136.6 (29.2) 143.1 (34.8) 0.046 cial femoral arteries) by a single reader in blinded fashion, using a semi-automatic software (EchoPAC Dimension, General Electric). Values are shown as means and SDs for normally distributed quantitative varia- bles, and medians and percentiles 25% and 75% for non-normal quantitative variables. BP, blood pressure. Statistical analysis Characteristics of the study sample were described as frequen- cies and percentages for qualitative variables, means and stan- dard deviations for normally distributed quantitative variables Advanced lipoprotein profile (assessed by Shapiro–Wilk tests) and medians and quartiles Patients with atheroma plaque had different lipoprotein com- for non-normal quantitative variables. Bivariate analyses by position and particle number (Table 2). LDL and HDL particles atheromatous plaque presence were performed by means of the had higher TG content (LDL-TG and HDL-TG, respectively). VLDL Pearson’s chi-squared test for qualitative variables and the and intermediate-density lipoprotein (IDL) particles had a ANOVA or the Kruskal–Wallis test for quantitative variables. higher amount of cholesterol (VLDL-C and IDL-C, respectively) The associations for traits measured by NMRS with risk of and TGs (VLDL-TG and IDL-TG, respectively). atheromatosis presence were assessed using logistic regression Participants with atheromatosis had an overall increase of adjusted for age, gender, CKD stage (controls, CKD stage 3, CKD VLDL particle number and a higher amount of large HDL stages 4–5 and dialysis) and smoking habit (non-smoker, former particles. In addition, they also had more LDL-Ps, specifically, and current). For each measure, adjusted odds ratios (ORs) and medium and small molecules (Table 2), which agreed with a 95% confidence intervals (CIs) per 1 standard deviation (SD) higher parameter measure were estimated. All analyses were conducted smaller averaged LDL-P size. using R. The statistical significance was set at a P-value <0.05. Association of lipoprotein composition with RESULTS atheromatosis Clinical characteristics and traditional lipid parameters The relationship of the lipid content (cholesterol and TG) within each lipoprotein class with atheroma plaque presence was inde- Atheroma plaque prevalence was lower in women and non- pendently evaluated. After adjusting for age, gender, smoking smokers, and higher in CKD patients and patients previously di- habit and CKD stage, the amount of TGs within LDL lipoproteins agnosed with dyslipidaemia and hypertension. The median age (LDL-TG) showed an adjusted OR per 1 SD increment of 1.33 (95% and the body mass index were higher in participants with athe- CI 1.03–1.74; P ¼ 0.03; Figure 1). Therefore, LDL-TG was indepen- romatosis, as well as the levels of both systolic and diastolic dently associated with atheroma plaque presence. blood pressure (Table 1). The traditional lipid profile revealed that TG levels and the Association of lipoprotein particle number with cholesterol content in non-HDL lipoproteins (referred as non- atheromatosis HDL-C) were higher in participants with atheroma plaque. In contrast, the cholesterol content in HDL lipoprotein (referred as Multivariate regression analysis revealed that total LDL-P HDL-C) was lower (Table 1). number was positively associated with atheroma plaque 2594 | M. Bermudez-Lopez et al. Table 2. NMR-assessed advanced lipoprotein profile according to atheromatous plaque presence No plaque (n ¼ 197) Plaque (n ¼ 198) P-value VLDL-P composition (mg/dL) VLDL-C 11.8 (7.9–17.5) 14.6 (10.5–22) <0.001 VLDL-TG 43.6 (33.1–64) 52.5 (38.2–75.5) 0.001 VLDL-P number (nmol/L) Total 31 (23.4–45.5) 36.7 (26.8–53.9) 0.001 Downloaded from https://academic.oup.com/ckj/article/14/12/2591/6316255 by Fundacio Biblioteca Josep Laporte user on 30 January 2023 Large 1.1 (0.8–1.4) 1.2 (0.9–1.70) 0.001 Medium 4.9 (3.5–6.8) 5.8 (4.1–8.3) 0.001 Small 25 (19.2–37.9) 29.8 (21.6–44.1) 0.002 VLDL-P size (nm) 42.4 (0.3) 42.5 (0.4) 0.376 LDL-P composition (mg/dL) LDLNMR-C 104 (18.4) 106.2 (21.4) 0.279 LDL-TG 12.3 (10–14.6) 13.7 (11.5–16.2) <0.001 LDL-P number (nmol/L) Total 732.2 (128.8) 760.2 (144.3) 0.043 Large 105.1 (20.4) 105 (22.4) 0.969 Medium 263.8 (49.9) 274.9 (56.5) 0.04 Small 362.5 (316–409.5) 374.5 (322.3–428.7) 0.038 LDL-P size (nm) 21.152 (21.071–21.257) 21.104 (21.038–21.204) 0.004 IDL-P composition (mg/dL) IDL-C 8.2 (6.2–10.7) 9.9 (8.1–12.4) <0.001 IDL-TG 8.3 (6.5–10.3) 9.8 (8.1–11.5) <0.001 HDL-P composition (mg/dL) HDLNMR-C 51.2 (43.7–59) 49.5 (41.8–56.7) 0.182 HDL-TG 14.2 (11.6–17.2) 16 (13–19.2) 0.001 HDL-P number (mmol/L) Total 27.5 (24.5–31.2) 28.4 (24.2–31.1) 0.844 Large 0.193 (0.138–0.262) 0.223 (0.154–0.314) 0.003 Medium 8.4 (7.1–9.8) 8.0 (6.5–9.8) 0.271 Small 19.0 (17–21.6) 19.4 (17.2–22) 0.333 HDL-P size (nm) 8.221 (8.199–8.235) 8.219 (8.193–8.235) 0.43 Values are shown as means and SDs for normally distributed quantitative variables, and medians and percentiles 25% and 75% for non-normal quantitative variables. p-Value Association of LDL-P number and composition with atheromatosis C 1.05 (0.82, 1.36) 0.701 VLDL Since LDL composition and particle number were independently LIPOPROTEIN COMPOSITION TG 1.01 (0.79, 1.30) 0.909 associated with atheroma plaque presence, we decided to in- vestigate the combined effect of both parameters. The com- C 1.27 (0.98, 1.66) 0.069 LDL bined variable LDL-TG–medium LDL-P, a variable that reflects TG 1.33 (1.03, 1.74) 0.030 the TG content in medium LDL-Ps, was higher in CKD patients compared with controls with no CKD (CKD 3650; 95% CI 1233.78– C 1.21 (0.93, 1.60) 0.161 8076.58 versus non-CKD 3334.31; 95% CI 1398.27–7624.04). IDL However, this result had a borderline significance (P ¼ 0.05; TG 1.18 (0.91, 1.55) 0.220 Figure 3). CKD patients showed a higher prevalence of athero- C 1.15 (0.87, 1.54) 0.336 matosis (CKD 64.6% versus non-CKD 33.9%; Figure 3). HDL LDL-TG–medium LDL-P showed an adjusted OR per 1 SD incre- TG 1.07 (0.83, 1.39) 0.593 ment of 1.40 (95% CI 1.09–1.82; P ¼ 0.01; Figure 4). Interestingly, this model showed the lowest Akaike Information Criterion, indi- 0.8 1 1.30 1.75 cating a better likelihood to predict/estimate atheromatosis pres- OR (95% CI) per SD Increment ence compared with isolated models (LDL-TG–medium LDL-P FIGURE 1: Association of lipoprotein composition with atheromatosis. 385.18 versus LDL-TG 387.21 versus LDL-P 388.10 versus medium Multivariate logistic regression model adjusted for age, gender, smoking habit LDL-P 386.91). Therefore, medium LDL-Ps loaded with TGs were and CKD stage. Estimates were ORs per 1 SD increment. SD was expressed in mg/dL (VLDL-C, 8.95; VLDL-TG, 31.65; LDL-C, 19.98; LDL-TG, 4.01; IDL-C, 3.76; IDL- positively and independently associated with atheromatous dis- TG, 2.95; HDL-C, 11.61; and HDL-TG, 5.13). ease in our general population (non-diabetic CKD and non-CKD individuals). Finally, a sensitivity analysis was performed in a subsample of only CKD patients to confirm the association of presence. Furthermore, lipoprotein subclass profiling showed LDL-TG–medium LDL-P with atheromatosis. Although the signifi- that among LDL-Ps, medium LDL-P was associated with pla- cance was lost, the coefficient reported for the variable was simi- que presence (Figure 2). lar (OR 1.2; 95% CI 0.8–1.7; P ¼ 0.359). Medium LDL-TG content and atherosclerosis | 2595 p-Value Total 1.01 (0.79, 1.30) 0.907 Large 1.06 (0.82, 1.37) 0.679 LIPOPROTEIN PARTICLE NUMBER VLDL Medium 1.05 (0.81, 1.35) 0.728 Downloaded from https://academic.oup.com/ckj/article/14/12/2591/6316255 by Fundacio Biblioteca Josep Laporte user on 30 January 2023 Small 1.01 (0.79, 1.30) 0.946 Total 1.29 (1.002, 1.682) 0.050 Large 1.25 (0.96, 1.64) 0.098 LDL Medium 1.34 (1.04, 1.75) 0.026 Small 1.23 (0.96, 1.59) 0.109 Total 1.17 (0.89, 1.55) 0.250 Large 1.27 (0.98, 1.67) 0.084 HDL Medium 1.05 (0.79, 1.41) 0.739 Small 1.20 (0.93, 1.55) 0.175 0.8 1 1.35 1.75 OR (95% CI) per SD Increment FIGURE 2: Association of lipoprotein particle number with atheromatosis. Multivariate logistic regression model adjusted for age, gender, smoking habit and CKD stage. Estimates were ORs per 1 SD increment. SD was expressed in nmol/L (total VLDL-P, 22.83; large VLDL-P, 0.57; medium VLDL-P, 3.31; small VLDL-P, 19.05; total LDL-P, 137.33; large LDL-P, 21.40; medium LDL-P, 53.52; small LDL-P, 71.54; total HDL-P, 5.35; large HDL-P, 0.15; medium HDL-P, 2.19; and small LDL-P, 3.60). 100% 10000 Traditional lipid profiling revealed some statistically signifi- cant differences according to atheromatous plaque presence. However, those values were extremely close and their clinical LDL-TG * Medium LDL-P 75% 7500 Presence of plaque (%) relevance could be at best questionable. These data reinforce 64.6% the importance of an advanced lipoprotein characterization to 50% 5000 elucidate clinically relevant differences. Regarding LDL-P number, previous studies support the pre- 33.9% dictive role of LDL-P number for cardiac events in the general 25% 2500 population [28–30]. Whereas large LDL-Ps showed divergent as- sociation with cardiovascular risk (positive [31], negative [32] or 0% 0 null [29]), medium LDL-Ps normally showed a positive associa- Non-CKD CKD tion [33, 34]. Similarly, our results are in line with a previous FIGURE 3: Atheroma plaque presence and levels of LDL-TG–medium LDL-P in Spanish study in the general population where medium par- non-CKD and CKD patients. Prevalence of atheromatous plaques (P < 0.01) and ticles showed the strongest association with cardiovascular the levels of LDL-TG–medium LDL-P (P ¼ 0.05) were expressed as percentage and events [35]. The combined variable LDL-TG–medium LDL-P was mg/dL  nmol/L, respectively. positively associated with atheromatosis in our cohort and showed the better likelihood of predicting atheromatosis pres- ence compared with isolated models. Therefore, medium LDL- DISCUSSION Ps loaded with TGs are positively associated with atheromatous This cross-sectional study provides a comprehensive examina- disease. However, we cannot affirm with certainty whether this tion of advanced lipoprotein parameters and their association lipid profile is only a marker of atherosclerotic disease or if, in with atheromatosis presence in non-diabetic CKD patients and fact, reducing these values would reduce the risk of cardiovas- controls without statin therapy. The main results of the present cular disease in these patients. study were: (i) the amount of TGs within LDL lipoproteins (LDL- In haemodialysis patients, LDL-P size seemed to be helpful TG), (ii) the total and medium LDL-P number and (iii) the me- to identify those patients who would not be considered at risk dium LDL-Ps loaded with TGs were positively and indepen- with traditional lipid parameters [20]. In fact, a higher LDL-P dently associated with atheromatous disease in non-diabetic concentration was associated with a higher cardiovascular risk CKD and non-diabetic and non-CKD individuals. and mortality in CKD patients [19, 36]. 2596 | M. Bermudez-Lopez et al. p-Value Gender; woman 0.32 (0.19, 0.54) <0.001 Age; years 1.11 (1.08, 1.13) <0.001 Former 2.14 (1.21, 3.81) 0.009 Smoking Downloaded from https://academic.oup.com/ckj/article/14/12/2591/6316255 by Fundacio Biblioteca Josep Laporte user on 30 January 2023 Current 2.38 (1.13, 5.12) 0.024 Stage 3 2.02 (1.03, 3.98) 0.042 CKD Stage 4-5 2.90 (1.43, 5.97) 0.003 Dialysis 3.53 (1.63, 7.83) 0.002 LDL-TG - Medium LDL-P 1.40 (1.09, 1.82) 0.010 0.3 1 3.5 7.8 OR (95% CI) FIGURE 4: Multivariate logistic regression model adjusted for age, gender, smoking habit and CKD stage. LDL-TG–medium LDL-P estimate was ORs per 1 SD increment. SD: 1674.45 mg/dL  nmol/L. Multivariate logistic regression to model presence of atheromatosis in non-diabetic CKD patients. Hypertriglyceridaemia is associated to vascular endothelial dyslipidaemia and hypertension were collected from clinical damage [37]. LDL-P can easily penetrate the artery wall if the records, so memory bias could also be a limitation. endothelium is injured. When LDL-Ps enter artery wall and be- On the other hand, our study has several strengths. First, to come modified (such as oxidized), they provoke an inflamma- the best of our knowledge, this is the first study that combines a tory reaction that triggers atheroma plaque initiation. Oxidized comprehensive analysis of lipoprotein composition and particle LDL particles are essential players in the pathogenesis of number. Second, CKD patients at various stages of the disease ASCVD [38]. Interestingly, they usually have a higher concentra- and controls were selected to obtain a representative study tion of TGs [39]. Therefore, since CKD patients show an accumu- cohort. Finally, the absence of patients with diabetes and/or on lation of LDL-Ps, a higher TG content in LDL-Ps and a pro- statin therapy reduces potential bias and drug interference in oxidative state [40], medium LDL-Ps loaded with TGs could have lipid parameters, but it hinders generalization of results to other the right size to penetrate the artery wall and their lipid cargo populations. Therefore, a non-treated hidden atherogenic could be more prone to initiate atheroma plaque formation. dyslipidaemia was revealed. R In this study, we used the LiposcaleV test, based on 2D- CKD patients show several lipoprotein alterations, such as (i) NMRS, which directly measures the size of lipoprotein particles. an increased number of VLDL-Ps; (ii) a reduced mean LDL-P size; This method has been previously validated and compared with (iii) a higher lipid content in VLDL and IDL; and (iv) a gain of TG the Lipoprint test, the established 1D NMR method developed and a reduction of cholesterol in LDL and HDL particles [25]. by Jeyarajah et al. [41]. The different lipoprotein particle meas- Recently, TG-rich lipoproteins have been associated to cardio- urements (i.e. VLDL, LDL and HDL) obtained by using 1D and 2D- vascular events in CKD patients [42]. Very frequently, CKD NMR techniques were highly correlated, although the particle patients show hypertriglyceridaemia [16]. This is normally due numbers obtained by 2D-NMR method were more in agreement to an increased hepatic production and decreased clearance of with biochemical values such as the concentration of apolipo- TG-rich lipoproteins [43]. In addition, cholesteryl ester transfer proteins A and B (Apo A and Apo B, respectively) in isolated protein modifies lipoprotein lipid content. It transfers TG from fractions than those obtained using the 1D-NMR test [21]. The present results must be considered with the following triglyceride-rich lipoproteins (chylomicrons, VLDL and IDL) to caveats. First, the cross-sectional design of the study does not LDL and HDL, and it exchanges cholesterol esters from LDL and allow establishing a causal relation between atherosclerosis HDL to VLDL and IDL particles [44]. Therefore, in hypertriglyceri- and lipoprotein profiles. Second, there is no information about daemia states, such as CKD, LDL and HDL, particles gain TG, other lipid variables associated with cardiovascular disease, which can increase atheromatous cardiovascular risk in these such as Apo B and Apo A-I. Third, the lack of association of patients. some lipoprotein parameters with atheroma plaque presence High LDL-TG levels have previously been associated with may reflect low statistical power due to the relatively small size coronary heart disease in the general population [45]. Similarly, of the cohort. In addition, the sensitivity analysis using only they were associated with both ischaemic stroke and coronary CKD patients showed the same lack of power. Fourth, there is a heart disease after adjusting for traditional risk factors, includ- substantial collinearity of lipoprotein parameters, which makes ing TC and HDL-C [46]. Interestingly, both studies reported the analysis of interactions between individual parameters (i.e. increased levels of inflammatory markers. Another study particle composition and number) difficult. Finally, data about described that TG content within VLDL, LDL and IDL was Medium LDL-TG content and atherosclerosis | 2597 associated with higher risk of myocardial infarction and, to a Alemany, Hospital Josep Trueta (Girona); Jesús Martı́n lesser extent, of ischaemic stroke [9, 47, 48]. Garcı́a, Hospital Nuestra Sen ~ ora de Sonsoles (Ávila); Alberto In conclusion, changes of advanced lipoprotein profile are Martı́nez Castelao, Hospital Universitari de Bellvitge independently associated with atheromatous disease in non- (Barcelona); Marı́a Martı́nez Villaescusa, Complejo diabetic CKD and non-diabetic and non-CKD individuals. Hospitalario Universitario de Albacete (Albacete); Isabel Although the reported associations provide new insight into the ~ igo Moina Eguren, Martı́nez, Hospital Galdakao (Bilbao); In relation of LDL-Ps with atheromatosis, further mechanistic re- Hospital Basurto (Bilbao); Silvia Moreno Los Huertos, search addressing LDL-P composition change is needed to fully Hospital Santa Bárbara (Soria); Ricardo Mouzo Mirco, Downloaded from https://academic.oup.com/ckj/article/14/12/2591/6316255 by Fundacio Biblioteca Josep Laporte user on 30 January 2023 understand the potential implications of our findings. Hospital El Bierzo, Ponferrada (León); Antonia Munar Vila, Hospital Universitari Son Espases (Palma de Mallorca); Ana ACKNOWLEDGEMENTS ~ oz Dı́az, Hospital Virgen del Consuelo Beatriz Mun The authors would like to thank the NEFRONA team (Eva (Valencia); Juan F. Navarro González, Hospital Universitario Castro, Virtudes Marı́a, Teresa Molı́, Teresa Vidal, Meritxell Nuestra Sen ~ ora de Candelaria (Santa Cruz de Tenerife); Soria) and the Biobank of RedInRen for their invaluable sup- Javier Nieto and Agustı́n Carren ~ o, Hospital General port. The NEFRONA study investigator group is composed Universitario de Ciudad Real (Ciudad Real); Enrique Novoa by the following: Ma José Aladrén Regidor, Hospital Fernández, Complexo Hospitalario de Ourense (Ourense); Comarcal Ernest Lluch (Calatayud); Jaume Almirall and Alberto Ortiz and Beatriz Fernandez, IIS-Fundación Jiménez Esther Ponz, Corporació Parc Taulı́ (Barcelona); Jesús Dı́az (Madrid); Vicente Paraı́so, Hospital Universitario del Arteaga Coloma, Hospital de Navarra (Pamplona); Ma Henares (Madrid); Miguel Pérez Fontán, Complejo Auxiliadora Bajo Rubio, Raquel Dı́az, Raquel Hospital La Paz Hospitalario Universitario A Corun ~ a (A Corun ~ a); Ana Peris (Madrid); Montserrat Belart Rodrı́guez, Sistemes Renals Domingo, Hospital Francesc de Borja (Valencia); Celestino (Lleida); Antonio Gascón, Hospital Obispo Polanco (Teruel); Pin~ era Haces, Hospital Universitario Marqués de Valdecilla Jordi Bover Sanjuan and Fundació Puigvert, IIB Sant Pau (Santander); Ma Dolores Prados Garrido, Hospital (Barcelona); Josep Bronsoms Artero, Clı́nica Girona (Girona); Universitario San Cecilio (Granada); Mario Prieto Velasco, Juan B. Cabezuelo Romero and Salomé Muray Cases, Hospital de León (León); Carmina Puig Marı́, Hospital Hospital Reina Sofı́a (Murcia); Jesús Calvin ~ o Varela, Hospital d’Igualada (Barcelona); Maite Rivera Gorrı́n, Hospital Universitario Lugus Augusti (Lugo); Pilar Caro Acevedo, Universitario Ramón y Cajal (Madrid); Esther Rubio, Hospital Clı́nica Ruber (Madrid); Jordi Carreras Bassa, Diaverum Baix Puerta del Hierro (Madrid); Pilar Ruiz, Hospital Sant Joan Llobregat (Barcelona); Aleix Cases Amenós and Elisabet Despı́ Moisès Broggi (Barcelona); Mercedes Salgueira Lazo Massó Jiménez, Hospital Clı́nic (Barcelona); Rosario Moreno and Ana Isabel Martı́nez Puerto, Hospital Virgen Macarena López, Hospital de la Defensa (Zaragoza); Secundino (Sevilla); José Antonio Sánchez Tomero, Hospital Cigarrán Guldris and Saray López Prieto, Hospital Da Costa Universitario de la Princesa (Madrid); José Emilio Sánchez, (Lugo); Lourdes Comas Mongay, Hospital General de Vic Hospital Universitario Central de Asturias (Oviedo); Ramon (Barcelona); Isabel Comerma, Hospital General de Manresa Sans Lorman, Hospital de Figueres (Girona); Ramon Saracho, (Barcelona); Ma Teresa Compte Jové, Hospital Santa Creu Hospital de Santiago (Vitoria); Maria Sarrias and Daniel Jesús (Tarragona); Marta Cuberes Izquierdo, Hospital Reina Sofı́a (Navarra); Fernando de Álvaro and Covadonga Hevia Serón, Hospital Universitari Vall d’Hebron (Barcelona); Marı́a Ojanguren, Hospital Infanta Sofı́a (Madrid); Gabriel de Arriba José Soler and Clara Barrios, Hospital del Mar (Barcelona); de la Fuente, Hospital Universitario Guadalajara Fernando Sousa, Hospital Rio Carrión (Palencia); Daniel (Guadalajara); Ma Dolores del Pino y Pino, Complejo Toran, Hospital General de Jerez (Cadiz); Fernando Tornero Hospitalario Universitario Torrecardenas (Almerı́a); Rafael Molina, Hospital de Sureste (Arganda del Rey); José Javier Diaz-Tejeiro Izquierdo and Ahijado Hormigos, Francisco Usón Carrasco, Hospital Virgen de la Luz (Cuenca); Ildefonso Hospital Virgen de la Salud (Toledo); Marta Dotori, USP Valera Cortes, Hospital Virgen de la Victoria (Málaga); Ma Marbella (Málaga); Verónica Duarte, Hospital de Terrassa Merce Vilaprinyo del Perugia, Institut Catala d’Urologia i (Barcelona); Sara Estupin ~ an Torres, Hospital Universitario Nefrologia (Barcelona); Rafael C. Virto Ruiz, Hospital San Canarias (Santa Cruz de Tenerife); Ma José Fernández Reyes, Jorge (Huesca); Vicente Pallarés Carratalá, Clinica MEDEFIS Hospital de Segovia (Segovia); Ma Loreto Fernández (Vila-real, Castellón), Carlos Santos Altozano, CS Azuqueca Rodrı́guez, Hospital Prı́ncipe de Asturias (Madrid); de Henares (Guadalajara); Miguel Artigao Ródenas, CS Zona Guillermina Fernández, Clı́nica Santa Isabel (Sevilla); III (Albacete); Inés Gil Gil Área Básica Sanitaria de Arán, CAP Antonio Galán Serrano, Hospital General Universitario de Viella (Lleida); Francisco Adan Gil, CS Alfaro (La Rioja); Valencia (Valencia); Cesar Garcı́a Cantón, Hospital Emilio Garcı́a Criado, Centro de Salud del Carpio (Córdoba); Universitario Insular de Gran Canaria (Las Palmas); Antonio Rafael Durá Belinchón, CS Godella (Valencia); Jose Ma L. Garcı́a Herrera, Hospital Universitario Puerto Real (Cádiz); Fernández Toro, CS Zona Centro (Cáceres); and Juan Mercedes Garcı́a Mena, Hospital San Juan de Dios Antonio, Divisón Garrote Centro de Salud de Casas Ibán ~ ez, (Zaragoza); Luis Gil Sacaluga and Maria Aguilar, Hospital Consultorio de Fuentealbilla (Albacete). Virgen del Rocı́o (Sevilla); José Luis Górriz, Hospital Universitario Doctor Peset (Valencia); Emma Huarte Loza, ~ o); José Luis Lerma, Hospital FUNDING Hospital San Pedro (Logron Universitario Salamanca (Salamanca); Antonio Liebana This work was supported by the intramural program of the Can ~ ada, Hospital de Jaén (Jaén); Jesús Pedro Marı́n Álvarez, IRB Lleida, the Instituto de Salud Carlos III [RETIC RD16/ Hospital San Pedro de Alcántara (Cáceres); Nàdia Martı́n 0009/0011, FIS PI18/00610], the Ministerio de Ciencia, 2598 | M. Bermudez-Lopez et al. Innovación y Universidades [IJC2018-037792-I] and the subclinical atheromatosis and associated risk factors in FEDER funds. chronic kidney disease: the NEFRONA study. Nephrol Dial Transplant 2014; 29: 1415–1422 12. Arroyo D, Betriu A, Martinez-Alonso M et al. Observational AUTHORS’ CONTRIBUTIONS multicenter study to evaluate the prevalence and prognosis M.B.-L. and J.M.V. were responsible for conception and de- of subclinical atheromatosis in a Spanish chronic kidney sign, analysis and interpretation of the data, drafting of the disease cohort: Baseline data from the NEFRONA study. BMC paper, revising it critically for intellectual content and final Nephrol 2014; 15: 168 Downloaded from https://academic.oup.com/ckj/article/14/12/2591/6316255 by Fundacio Biblioteca Josep Laporte user on 30 January 2023 approval of the version to be published. E.F. provided 13. Gracia M, Betriu À, Martı́nez-Alonso M et al.; NEFRONA Investigators. Predictors of subclinical atheromatosis pro- resources, methodology and supervision. H.P. performed gression over 2 years in patients with different stages of statistical analysis, original draft writing, editing and inter- CKD. Clin J Am Soc Nephrol 2016; 11: 287–296 pretation of the data. N.Amigo carried out NMR analysis and 14. Kon V, Yang H, Fazio S. Residual cardiovascular risk in drafting of the manuscript. E.C., N.Alonso and D.M. were in- chronic kidney disease: Role of high-density lipoprotein. volved in draft writing and data analysis. Arch Med Res 2015; 46: 379–391 15. Barter P. Lipoprotein metabolism and CKD: Overview. Clin CONFLICT OF INTEREST STATEMENT Exp Nephrol 2014; 18: 243–246 16. Bermúdez-López M, Betriu À, Valdivielso JM et al. Beyond the N.Amigo is a stock owner of Biosfer Teslab, the company traditional lipid parameters in chronic kidney disease. that commercializes the lipoprotein profiling described in Nefrologia 2018; 38: 109–113 the present manuscript, and has a patent for lipoprotein 17. Navab KD, Elboudwarej O, Gharif M et al. Chronic inflamma- profiling. The other authors have no conflict of interest. tory disorders and accelerated atherosclerosis: chronic kid- ney disease. Curr Pharm Des 2011; 17: 17–20 18. Al-Shahrouri HZ, Ramirez P, Fanti P et al. NMR identifies ath- REFERENCES erogenic lipoprotein abnormalities in early diabetic ne- 1. Roth GA, Forouzanfar MH, Moran AE et al. Demographic and phropathy that are unrecognized by conventional analysis. epidemiologic drivers of global cardiovascular mortality. N Clin Nephrol 2010; 73: 180–189 Engl J Med 2015; 372: 1333–1341 19. Shen H, Xu Y, Lu J et al. Small dense low-density lipoprotein 2. Benjamin EJ, Virani SS, Callaway CW et al.; American Heart cholesterol was associated with future cardiovascular Association Council on Epidemiology and Prevention events in chronic kidney disease patients. BMC Nephrol 2016; Statistics Committee and Stroke Statistics Subcommittee. 17: 143 Heart disease and stroke statistics-2018 update: A report 20. Bowden RG, Wilson RL, Beaujean AA. LDL particle size and from the American Heart Association. Circulation 2018; 137: number compared with LDL cholesterol and risk categoriza- e67–e492 tion in end-stage renal disease patients. J Nephrol 2011; 24: 3. Boekholdt SM, Arsenault BJ, Mora S et al. Association of LDL 771–777 cholesterol, non-HDL cholesterol, and apolipoprotein B lev- 21. Mallol R, Amigó N, Rodrı́guez MA et al. Liposcale: A novel ad- els with risk of cardiovascular events among patients vanced lipoprotein test based on 2D diffusion-ordered 1H treated with statins: a meta-analysis. JAMA 2012; 307: NMR spectroscopy. J Lipid Res 2015; 56: 737–746 1302–1309 22. Junyent M, Martı́nez M, Borràs M et al. Predicting cardiovas- 4. Ference BA, Ginsberg HN, Graham I et al. Low-density lipo- cular disease morbidity and mortality in chronic kidney dis- proteins cause atherosclerotic cardiovascular disease. 1. ease in Spain. The rationale and design of NEFRONA: A Evidence from genetic, epidemiologic, and clinical studies. A prospective, multicenter, observational cohort study. BMC consensus statement from the European Atherosclerosis Nephrol 2010; 11: 14 Society Consensus Panel. Eur Heart J 2017; 38: 2459–2472 23. Junyent M, Martı́nez M, Borrás M et al. Usefulness of imaging 5. Musliner TA, Krauss RM. Lipoprotein subspecies and risk of techniques and novel biomarkers in the prediction of cardio- coronary disease. Clin Chem 1988; 34: B78–B83 vascular risk in patients with chronic kidney disease in 6. Stein JH, McBride PE. Should advanced lipoprotein testing be Spain: The NEFRONA project. Nefrologia 2010; 30: 119–126 used in clinical practice? Nat Clin Pract Cardiovasc Med 2006; 3: 24. Levey AS, Stevens LA, Schmid CH et al.; for the CKD-EPI 640–641 (Chronic Kidney Disease Epidemiology Collaboration). A 7. Williams PT, Zhao XQ, Marcovina SM et al. Comparison of new equation to estimate glomerular filtration rate. Ann four methods of analysis of lipoprotein particle subfractions Intern Med 2009; 150: 604–612 for their association with angiographic progression of coro- 25. Bermudez-Lopez M, Forne C, Amigo N et al. An in-depth nary artery disease. Atherosclerosis 2014; 233: 713–720 analysis shows a hidden atherogenic lipoprotein profile in 8. Otvos JD, Mora S, Shalaurova I et al. Clinical implications of non-diabetic chronic kidney disease patients. Exp Opin Ther discordance between low-density lipoprotein cholesterol Targets 2019; 23: 619–630 and particle number. J Clin Lipidol 2011; 5: 105–113 26. Stein JH, Korcarz CE, Hurst RT et al. Use of carotid ultrasound 9. Holmes MV, Millwood IY, Kartsonaki C et al.; China Kadoorie to identify subclinical vascular disease and evaluate cardio- Biobank Collaborative Group. Lipids, lipoproteins, and vascular disease risk: A consensus statement from the metabolites and risk of myocardial infarction and stroke. J American Society of Echocardiography Carotid Intima– Am Coll Cardiol 2018; 71: 620–632 Media Thickness Task Force. Endorsed by the Society for 10. Coresh J, Selvin E, Stevens LA et al. Prevalence of chronic kid- Vascular Medicine. J Am Soc Echocardiogr 2008; 21: 93–111, ney disease in the United States. JAMA 2007; 298: 2038–2047 quiz 189–190 11. Betriu A, Martinez-Alonso M, Arcidiacono MV et al.; on behalf 27. Touboul PJ, Hennerici MG, Meairs S et al. Mannheim carotid of the Investigators from the NEFRONA Study. Prevalence of intima–media thickness and plaque consensus (2004–2006– Medium LDL-TG content and atherosclerosis | 2599 2011). An update on behalf of the advisory board of the 3rd, mortality in maintenance hemodialysis patients. Clin J Am 4th and 5th watching the risk symposia, at the 13th, 15th Soc Nephrol 2011; 6: 2861–2870 and 20th European Stroke Conferences, Mannheim, 37. Ke LY, Law SH, Mishra VK et al. Molecular and cellular mech- Germany, 2004, Brussels, Belgium, 2006, and Hamburg, anisms of electronegative lipoproteins in cardiovascular dis- Germany, 2011. Cerebrovasc Dis 2012; 34: 290–296 eases. Biomedicines 2020; 8: 550 28. Cromwell WC, Otvos JD, Keyes MJ et al. LDL particle number 38. Carmena R, Duriez P, Fruchart JC. Atherogenic lipoprotein and risk of future cardiovascular disease in the Framingham particles in atherosclerosis. Circulation 2004; 109: III2–III7 Offspring Study—implications for LDL management. J Clin 39. Ke LY, Stancel N, Bair H et al. The underlying chemistry of Downloaded from https://academic.oup.com/ckj/article/14/12/2591/6316255 by Fundacio Biblioteca Josep Laporte user on 30 January 2023 Lipidol 2007; 1: 583–592 electronegative LDL’s atherogenicity. Curr Atheroscler Rep 29. Mora S, Otvos JD, Rifai N et al. Lipoprotein particle profiles by 2014; 16: 428 nuclear magnetic resonance compared with standard lipids 40. Tucker PS, Dalbo VJ, Han T et al. Clinical and research and apolipoproteins in predicting incident cardiovascular markers of oxidative stress in chronic kidney disease. disease in women. Circulation 2009; 119: 931–939 Biomarkers 2013; 18: 103–115 30. El Harchaoui K, van der Steeg WA, Stroes ES et al. Value of 41. Jeyarajah EJ, Cromwell WC, Otvos JD. Lipoprotein particle low-density lipoprotein particle number and size as predic- analysis by nuclear magnetic resonance spectroscopy. Clin tors of coronary artery disease in apparently healthy men Lab Med 2006; 26: 847–870 and women: The EPIC-Norfolk Prospective Population Study. 42. Lamprea-Montealegre JA, Staplin N, Herrington WG et al.; J Am Coll Cardiol 2007; 49: 547–553 SHARP Collaborative Group. Apolipoprotein B, triglyceride- 31. Parish S, Offer A, Clarke R et al.; Heart Protection Study rich lipoproteins, and risk of cardiovascular events in per- Collaborative Group. Lipids and lipoproteins and risk of dif- sons with CKD. Clin J Am Soc Nephrol 2020; 15: 47–60 ferent vascular events in the MRC/BHF Heart Protection 43. Sacks FM. The crucial roles of apolipoproteins E and C-III in Study. Circulation 2012; 125: 2469–2478 apoB lipoprotein metabolism in normolipidemia and hyper- 32. Blake GJ, Otvos JD, Rifai N et al. Low-density lipoprotein par- triglyceridemia. Curr Opin Lipidol 2015; 26: 56–63 ticle concentration and size as determined by nuclear mag- 44. Shrestha S, Wu BJ, Guiney L et al. Cholesteryl ester transfer netic resonance spectroscopy as predictors of protein and its inhibitors. J Lipid Res 2018; 59: 772–783 cardiovascular disease in women. Circulation 2002; 106: 45. MäRz W, Scharnagl H, Winkler K et al. Low-density lipopro- 1930–1937 tein triglycerides associated with low-grade systemic in- 33. Würtz P, Havulinna AS, Soininen P et al. Metabolite profiling flammation, adhesion molecules, and angiographic and cardiovascular event risk: A prospective study of 3 coronary artery disease: The Ludwigshafen Risk and population-based cohorts. Circulation 2015; 131: 774–785 Cardiovascular Health Study. Circulation 2004; 110: 3068–3074 34. Goliasch G, Oravec S, Blessberger H et al. Relative importance 46. Saeed A, Feofanova EV, Yu B et al. Remnant-like particle cho- of different lipid risk factors for the development of myocar- lesterol, low-density lipoprotein triglycerides, and incident dial infarction at a very young age (40 years of age). Eur J cardiovascular disease. J Am Coll Cardiol 2018; 72: 156–169 Clin Invest 2012; 42: 631–636 47. Girona J, Amigó N, Ibarretxe D et al. HDL triglycerides: A new 35. Pichler G, Amigo N, Tellez-Plaza M et al. LDL particle size and marker of metabolic and cardiovascular risk. Int J Mol Sci composition and incident cardiovascular disease in a South- 2019; 20:3151 European population: The Hortega-Liposcale Follow-up 48. Amigó N, Mallol R, Heras M et al. Lipoprotein hydrophobic Study. Int J Cardiol 2018; 264: 172–178 core lipids are partially extruded to surface in smaller HDL: 36. Noori N, Caulfield MP, Salameh WA et al. Novel lipoprotein “Herniated” HDL, a common feature in diabetes. Sci Rep 2016; subfraction and size measurements in prediction of 6: 19249