International Journal of Molecular Sciences Article HDL Function and Size in Patients with On-Target LDL Plasma Levels and a First-Onset ACS Alberto Cordero 1,2,3,† , Natàlia Muñoz-García 4,† , Teresa Padró 3,4 , Gemma Vilahur 3,4 , Vicente Bertomeu-González 2,3 , David Escribano 2,3 , Emilio Flores 5 , Pilar Zuazola 2 and Lina Badimon 3,4,6, * 1 Cardiology Department, Hospital Universitario de San Juan, 03550 Alicante, Spain 2 Unidad de Investigación en Cardiología, Fundación Para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO), 46020 Valencia, Spain 3 Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), 28029 Madrid, Spain 4 Cardiovascular-Program ICCC, Institut d’Investigació Biomèdica Sant Pau (IIB SANT PAU), 08041 Barcelona, Spain 5 Departamento de Análisis Clínicos, Hospital Universitario de San Juan, 03550 Alicante, Spain 6 Cardiovascular Research Chair, Autonomous University of Barcelona, 08193 Barcelona, Spain * Correspondence: lbadimon@santpau.cat; Tel.: +34-935-565-882; Fax: +34-935-565-559 † These authors contributed equally to this work. Abstract: Patients admitted for acute coronary syndrome (ACS) usually have high cardiovascular risk scores with low levels of high-density lipoprotein cholesterol (HDL-C) and high low-density lipoprotein cholesterol (LDL-C) levels. Here, we investigated the role of lipoprotein functionality as well as particle number and size in patients with a first-onset ACS with on-target LDL-C levels. Ninety-seven patients with chest pain and first-onset ACS with LDL-C levels of 100 ± 4 mg/dL and non-HDL-C levels of 128 ± 4.0 mg/dL were included in the study. Patients were categorized as ACS and non-ACS after all diagnostic tests were performed (electrocardiogram, echocardiogram, troponin levels and angiography) on admission. HDL-C and LDL-C functionality and particle number/size by nuclear magnetic resonance (NMR) were blindly investigated. A group of matched healthy volunteers (n = 31) was included as a reference for these novel laboratory variables. LDL Citation: Cordero, A.; Muñoz-García, N.; Padró, T.; Vilahur, G.; susceptibility to oxidation was higher and HDL-antioxidant capacity lower in the ACS patients than Bertomeu-González, V.; Escribano, D.; in the non-ACS individuals. ACS patients had lower HDL-C and Apolipoprotein A-I levels than Flores, E.; Zuazola, P.; Badimon, L. non-ACS patients despite the same prevalence of classical cardiovascular risk factors. Cholesterol HDL Function and Size in Patients efflux potential was impaired only in the ACS patients. ACS-STEMI (Acute Coronary Syndrome—ST- with On-Target LDL Plasma Levels segment-elevation myocardial infarction) patients, had a larger HDL particle diameter than non-ACS and a First-Onset ACS. Int. J. Mol. Sci. individuals (8.4 ± 0.02 vs. 8.3 ± 0.02 and, ANOVA test, p = 0.004). In conclusion, patients admitted 2023, 24, 5391. https://doi.org/ for chest pain with a first-onset ACS and on-target lipid levels had impaired lipoprotein functionality 10.3390/ijms24065391 and NMR measured larger HDL particles. This study shows the relevance of HDL functionality Academic Editor: Frances T. Yen rather than HDL-C concentration in ACS patients. Received: 17 February 2023 Keywords: ACS; NSTEMI; STEMI; lipoprotein functionality; HDL-C; LDL-C; cholesterol efflux Revised: 7 March 2023 Accepted: 9 March 2023 Published: 11 March 2023 1. Introduction Coronary artery disease (CAD) is the major cause of mortality worldwide and is Copyright: © 2023 by the authors. characterized by the chronic and initially silent development of atherosclerotic plaques Licensee MDPI, Basel, Switzerland. in the coronary arteries [1,2]. Acute coronary syndromes (ACSs) are unstable and abrupt This article is an open access article clinical manifestations of atherosclerosis, including a wide range of presentations such distributed under the terms and as unstable angina, non-ST-segment-elevation myocardial infarction (NSTEMI) and ST- conditions of the Creative Commons segment-elevation myocardial infarction (STEMI) [3]. Attribution (CC BY) license (https:// High levels of low-density lipoprotein cholesterol (LDL-C) is the leading effector creativecommons.org/licenses/by/ for atherosclerosis development and, also, for recurrent cardiovascular events after an 4.0/). Int. J. Mol. Sci. 2023, 24, 5391. https://doi.org/10.3390/ijms24065391 https://www.mdpi.com/journal/ijms Int. J. Mol. Sci. 2023, 24, 5391 2 of 13 initial ACS [4]. Conversely, high-density lipoprotein cholesterol (HDL-C) is a strong independent predictor that inversely correlates with the risk of CAD and its thrombotic complications [5–9]. However, there are controversial results regarding HDL-C levels and CAD coming from Mendelian randomization studies [10] and pharmacological studies raising HDL-C levels [11]. Therefore, a new concept has arisen considering that cholesterol carried by HDL (HDL-C) does not reflect HDL functionality; in fact, it is the HDL micelle and not HDL-C that has shown different anti-atherogenic properties [12–14]. Moreover, traditional measures of cholesterol quantify the cholesterol and triglyceride content of lipoproteins in milligrams per decilitre and use the amount of cholesterol measured to assess risk. However, individuals can vary in their lipoprotein particle numbers and sizes, meaning that even though they might have equivalent cholesterol levels, they can vary in their risk for cardiovascular disease (CVD). Measuring particle number and size by nuclear magnetic resonance (NMR) spectroscopy could be a better read-out for CVD risk assessment [15,16]. Clinical registries have highlighted that a large percentage of patients admitted for an ACS have non-elevated LDL-C levels [8,9] and that atherosclerotic plaques can be detected even in patients with very low levels of LDL-C [17]. Therefore, HDL function and its interplay with other lipid and non-lipid molecules represent a challenge in ACS risk and onset [18,19]. Based on this evidence, we designed a real-world clinical study (as indicated in the Graphical Abstract) to investigate HDL/LDL functionality and lipoprotein particle number and size in patients with a first-onset ACS presentation having LDL-C and non-HDL-C with average levels of 100 ± 3.6 mg/dL and 128 ± 4.0 mg/dL, respectively, and intermediate cardiovascular risk scores. 2. Results 2.1. Patient Characteristics Ninety-seven subjects (72 men, 25 women) with an average age of 64.9 ± 1.2 years who were initially recruited for the study were included in the final analysis. Categoriza- tion of the patients according to electrocardiogram pattern on admission (Table 1) found that (NSTEMI) patients were older (mean ± SEM; 70.3 ± 1.9) and more likely to have hypertension, diabetes mellitus (DM) and dyslipidaemia than STEMI patients. Conversely, STEMI patients were younger (mean ± SEM; 60.0 ± 1.7) and had higher smoking habits. No differences regarding body mass index (BMI) were reported between groups (p = 0.354). HDL-C and apolipoprotein A-I (ApoA-I) levels were significantly lower in (ACS) patients compared with non-ACS patients. Nevertheless, no differences were observed in LDL-C and non-HDL-C levels between groups. The STEMI group had lower left ventricular ejection fraction (LVEF) and higher cardiac damage (troponins) than the NSTEMI and non-ACS groups (Student’s t-test, p = 0.007 and p < 0.001, respectively) and more subse- quent intervention for revascularization (χ2 test, p < 0.001) and coronary stents (χ2 test, p = 0.007). Interestingly, preadmission medication use was higher in the NSTEMI and non- ACS groups, the use of acetylsalicylic acid (ASA) (χ2 test, p = 0.044), angiotensin receptor blocker (χ2 test, p = 0.048), calcium antagonists (χ2 test, p = 0.022) and beta-blockers (χ2 test, p = 0.004) being significantly higher. As shown in Table S1, patients had an average of 100 ± 3.6 mg/dL of LDL-C at arrival, as well as 146 ± 8.8 mg/dL of triglycerides and 128 ± 4.0 mg/dL of non-HDL-C (on-target levels for primary prevention). Int. J. Mol. Sci. 2023, 24, 5391 3 of 13 Table 1. Patient characteristics: Electrocardiogram classification. The chi-squared test was applied for categorical variables and the ANOVA test for numerical variables. The Bonferroni post hoc test was run for two group comparisons after ANOVA: *, Significant differences versus non-ACS; ‡, Significant differences between STEMI and NSTEMI. Values of p < 0.05 are considered significant. Abbreviations: ACS = acute coronary syndrome, ApoA-I = Apolipoprotein A-I, NSTEMI = non-ST-segment-elevation myocardial infarction, STEMI = ST-segment-elevation myocardial infarction, BMI = body mass index, COPD = chronic obstructive pulmonary disease, BNP = B-type natriuretic peptide, LVEF = left ventricular ejection fraction. GOT = glutamic-oxaloacetic transaminase, GPT = glutamic-pyruvic transaminase, ACE inhibitor = angiotensin-converting enzyme inhibitor, OAD = oral anti-diabetic agents, DPP-4 inhibitors = dipeptidyl peptidase 4 inhibitors. ACS (n = 70) NSTEMI STEMI p-Value Non-ACS (n = 27) (n = 31) (n = 39) Age (years, mean ± SEM) 65.8 ± 2.6 70.3 ± 1.9 60.0 ± 1.7 *‡ 0.001 Male/Female, n 14/13 26/5 32/7 0.007 Weight (Kg) 84.1 ± 5.1 79.5 ± 2.7 85.2 ± 2.5 0.375 BMI (Kg/m2 , mean ± SEM) 29.6 ± 1.4 27.7 ± 0.6 28.7 ± 0.7 0.354 Risk Factor, n (%) Diabetes Mellitus 8 (30%) 10 (32%) 6 (15%) 0.210 Hypertension 15 (55%) 25 (81%) 15 (38%) 0.002 Obesity (>30%) 8 (30%) 7 (23%) 13 (33%) 0.517 Dyslipidaemia 11 (41%) 17 (55%) 11 (28%) 0.078 Smoking habits 4 (15%) 5 (16%) 22 (56%) <0.001 COPD 0 (0%) 3 (10%) 2 (5%) 0.251 Lipid profile Total cholesterol (mg/dL) 182.2 ± 8.6 167.5 ± 6.6 169.1 ± 5.6 0.292 Triglycerides (mg/dL) 140.3 ± 11.1 154.2 ± 21.4 143.6 ± 11.7 0.811 LDL-C (mg/dL) 102.4 ± 8.4 95.8 ± 5.4 101.8 ± 5.2 0.715 HDL-C (mg/dL) 52.0 ± 2.8 44.3 ± 2.4 * 39.4 ± 1.7 * <0.001 ApoA-I (mg/ml) 1.8 ± 0.1 1.5 ± 0.1 * 1.4 ± 0.1 * <0.001 HDL-C/LDL-C 0.61 ± 0.07 0.50 ± 0.04 0.43 ± 0.03 * 0.021 Triglycerides/HDL-C 3.1 ± 0.3 4.2 ± 0.8 4.1 ± 0.5 0.395 Non-HDL-C (mg/dL) 130.2 ± 8.8 123.1 ± 6.7 129.6 ± 5.7 0.734 Lp(a) (mg/dL) 27.3 ± 5.9 35.1 ± 6.1 49.7 ± 7.3 * 0.058 Cardiac parameters BNP (pg/mL) 401 ± 220 1600 ± 556 2082 ± 594 * 0.081 Troponin-I (ng/L) 720 ± 484 9355 ± 3208 83,307 ± 17,824 *‡ <0.001 LVEF (%) 59.4 ± 1.5 57.2 ± 1.5 51.7 ± 1.9 *‡ 0.007 Hepatic and renal parameters GOT (UI/l) 24.2 ± 2.8 40.2 ± 8.1 66.2 ± 11.4 *‡ 0.006 GPT (UI/l) 24.7 ± 3.9 31.6 ± 5.1 40.1 ± 4.0 * 0.050 Creatinine (mg/dL) 0.8 ± 0.06 1.0 ± 0.05 * 0.9 ± 0.04 0.060 Medication at admission, n (%) Acetylsalicylic acid 7 (26%) 7 (23%) 2 (5%) 0.044 Clopidogrel 2 (7%) 0 (0%) 1 (3%) 0.259 Angiotensin II receptor blocker 12 (44%) 14 (45%) 8 (20%) 0.048 ACE inhibitor 2 (7%) 4 (13%) 2 (5%) 0.493 Diuretics 7 (26%) 6 (19%) 4 (10%) 0.245 Calcium antagonists 2 (7%) 8 (26%) 2 (5%) 0.022 Beta-Blockers 8 (30%) 9 (29%) 1 (3%) 0.004 Omeprazole 6 (22%) 11 (35%) 3 (8%) 0.016 Statins 8 (30%) 11 (35%) 9 (23%) 0.521 Fibrates 1 (4%) 1 (3%) 2 (5%) 0.916 OADs 4 (15%) 7 (23%) 3 (8%) 0.212 Metformin 5 (16%) 4 (13%) 2 (5%) 0.228 DPP-4 inhibitors 2 (7%) 2 (6%) 1 (3%) 0.631 Others, n (%) Coronary stent 0 (0%) 7 (23%) 12 (31%) 0.007 Cathetherization/Revascularization 8 (30%) 15 (48%) 32 (82%) <0.001 Risk Scores (%) Framingham risk score 10.4 ± 1.4 17.9 ± 1.2 12.1 ± 1.1 <0.001 European Heart Score 2.7 ± 0.3 4.6 ± 0.3 3.1 ± 0.3 <0.001 Int. J. Mol. Sci. 2023, 24, 5391 4 of 13 2.2. Lipoprotein Particle Number and Size As shown in Table 2, ACS patients (especially STEMI) had a decreased number of small HDL particles (HDL-P) (ANOVA test, p < 0.001) compared with non-ACS individuals. Overall, ACS patients had a larger HDL particle diameter than non-ACS individuals (8.4 ± 0.02 vs. 8.3 ± 0.02 and, ANOVA test, p = 0.004). The triglyceride content (mg/dL) was similar in all lipoproteins. Table 2. Lipoprotein particle number and size. Results are expressed as mean ± SEM. The ANOVA test was applied for multiple comparisons; the Bonferroni post hoc test was run for two group comparisons after ANOVA: *, significant changes versus non-ACS group; ‡, significant changes between NSTEMI and STEMI groups. Values of p < 0.05 are considered significant. Abbrevia- tions: ACS = acute coronary syndrome, NSTEMI = non-ST-segment-elevation myocardial infarc- tion, STEMI = ST-segment-elevation myocardial infarction, VLDL = very low density lipoprotein, IDL = intermediate density lipoprotein, HDL = high density lipoprotein, TG = triglycerides. ACS (n = 69) Non-ACS NSTEMI STEMI p-Value (n = 25) (n = 30) (n = 39) Triglyceride content in lipoprotein particles (mg/dL) VLDL-TG 85.6 ± 6.9 77.2 ± 5.6 87.1 ± 6.5 0.504 IDL-TG 11.4 ± 0.3 11.2 ± 0.5 12.1 ± 0.6 0.428 LDL-TG 14.1 ± 0.9 13.4 ± 0.7 15.0 ± 0.7 0.312 HDL-TG 13.9 ± 0.5 12.2 ± 0.5 12.3 ± 0.7 0.148 VLDL particle number (nmol/L) Small VLDL-P 54.7 ± 4.7 48.9 ± 3.8 54.8 ± 4.3 0.549 Medium VLDL-P 5.7 ± 0.4 5.6 ± 0.3 6.8 ± 0.4 ‡ 0.066 Large VLDL-P 1.5 ± 0.1 1.4 ± 0.1 1.5 ± 0.1 0.488 Total VLDL-P 61.9 ± 5.1 55.9 ± 4.2 63.1 ± 4.7 0.513 LDL particle number (nmol/L) Small LDL-P 691.9 ± 28.6 642.8 ± 19.6 677.5 ± 24.7 0.387 Medium LDL-P 367.3 ± 32.4 312.8 ± 17.1 336.7 ± 14.9 0.225 Large LDL-P 194.3 ± 9.9 184.9 ± 4.8 191.3 ± 4.9 0.594 Total LDL-P 1253.5 ± 62.7 1140.5 ± 35.2 1205.5 ± 40.6 0.257 HDL particle number (nmol/L) Small HDL-P 18.3 ± 0.8 14.8 ± 0.7 * 13.8 ± 0.6 * <0.001 Medium HDL-P 10.6 ± 0.4 10.7 ± 0.3 10.0 ± 0.2 0.171 Large HDL-P 0.31 ± 0.01 0.30 ± 0.01 0.30 ± 0.01 0.501 Total HDL-P 29.2 ± 1.0 25.8 ± 0.8 * 24.1 ± 0.6 * <0.001 Average particle diameter (nm) VLDL 42.1 ± 0.05 42.1 ± 0.04 42.2 ± 0.04 * 0.119 LDL 21.0 ± 0.06 21.0 ± 0.04 21.0 ± 0.04 0.913 HDL 8.3 ± 0.02 8.4 ± 0.02 * 8.4 ± 0.02 * 0.004 Particle numbers of each lipoprotein class (expressed in percentage) are provided in Table S2. ACS patients (especially STEMI) had a lower percentage of small very low- density but a higher percentage of medium small very low-density particles (VLDL-P) compared with non-ACS individuals (Student’s t-test for unpaired samples, p = 0.026 and p = 0.020, respectively). Furthermore, ACS patients (especially STEMI) had a lower percentage of small HDL particles (HDL-P) (ANOVA test, p = 0.004) but higher medium (ANOVA test, p = 0.004) and large HDL-P percentages (ANOVA test, p = 0.012) compared with non-ACS individuals. As shown in Tables S3 and S4, the reference group of volunteers without cardiovascular disease had a lower proportion of pro-atherogenic LDL particles despite having higher levels of LDL-C, though these differences did not reach statistical significance. However, similarly to non-ACS individuals, the reference group had a smaller average particle Int. J. Mol. Sci. 2023, 24, 5391 5 of 13 diameter of HDL compared with ACS patients (Bonferroni post hoc test: reference vs. NSTEMI p = 0.004 and reference vs. STEMI, p < 0.001). 2.3. Assays for Lipoprotein Functionality Although patients had on-target LDL-C levels (lower than the reference healthy group), LDL susceptibility to oxidation was higher in patients than in the reference individuals (p < 0.001, Figure 1A), presenting approximately a 10 min faster LDL oxidation (time to Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW half maximum) even in the presence of medication. In addition, HDL antioxidant6 of 15 capacity and cholesterol efflux were also impaired in ACS patients compared with the reference group (Figure 1B,C; Student’s t-test, p = 0.002 and p = 0.038, respectively). Figure 1. Figure Lipoprotein functionality 1. Lipoprotein in the reference functionality in the group (n =group reference 31) vs.(npatients (n patients = 31) vs. = 97). (A)(nTime to (A) Time = 97). half-maximum oxidation (minutes). to half-maximum oxidation (B)(minutes). HDL inhibition of oxidation (B) HDL inhibition(%)of and (C) cholesterol oxidation (%) and efflux (C) cholesterol capacity (CEC efflux [%]). Results capacity (CECare[%]).expressed Results areas expressed median and quartileand as median 1–3quartile range (horizontal lines). 1–3 range (horizontal lines). Student’sStudent’s t-test values of values t-test p < 0.05offor p 40 mg/dL have a lower incidence of cardiovascular events [5,8]. Nonetheless, the therapies that were designed to increase HDL-C levels, such as Cholesteryl Ester Transfer Protein (CETP) inhibitors [35] or nicotinic acid [36], did not reduce the incidence of major cardiovascu- lar events. Thereafter, HDL functionality is probably impaired by some pharmacologic strategies in what reflects one of the many gaps in the knowledge of HDL particles. Our results, show significant differences in HDL particle functionality that might warrant future investigations to improve HDL functionality in subjects with high cardiovascular risk. Our study has the limitations of being cross-sectional, performed in a single centre and having a small sample size and a low number of women. Moreover, due to logistic factors that cannot be controlled in the clinical practice, samples were obtained after admission at different times. However, despite the described limitations and the heterogeneity of groups, the study is based on a well-characterized real-world cohort of patients admitted for first-onset chest pain with on-target LDL-C levels. In conclusion, patients treated as per guidelines in their primary care management with intermediate CVD risk that suffered a first chest pain episode had an impaired lipopro- tein function, which might lead to a higher oxidative status, and an altered number/size of lipoprotein particles irrespective of the LDL-C level and optimal treatment. Interest- ingly, triglycerides transported by all lipoproteins were within the normal range as well as non-HDL-C levels. This study shows the relevance of changes in lipoprotein functionality and in particle number/size on first onset ACS presentation. The on-going follow-up of this cohort might add more information about recurrent events and long-term mortality according to the determinations obtained at baseline. Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW 9 of 15 Int. J. Mol. Sci. 2023, 24, 5391 8 of 13 Ninety-seven patients admitted from January 2018 to April 2018 into “Hospital San Juan de Alicante” with chest pain were clinically diagnosed as ACS (ACS; n = 70) or non-ACS patients (non-ACS; n = 27) with high cardiovascular risk. Patients were classi- 4. Materials and Methods fied as ACS or non-ACS after all diagnostic tests were performed, including an exercise 4.1. Clinical Diagnosis of Chest Pain Categories test, echocardiogram or angiography. In addition, ACS patients were further categorized Ninety-seven patients admitted from January 2018 to April 2018 into “Hospital San by electrocardiogram pattern on admission into NSTEMI (n = 31) and STEMI (n = 39) Juan de Alicante” with chest pain were clinically diagnosed as ACS (ACS; n = 70) or non- (Table 1). ACS patients (non-ACS; n = 27) with high cardiovascular risk. Patients were classified Non-ACS as ACS was diagnosed or non-ACS by the exclusion after all diagnostic of acute ischemia tests were performed, including (noantroponin elevation exercise test, and no dynamic or electrocardiographic changes suggestive echocardiogram or angiography. In addition, ACS patients were further categorized byof myocardial ischemia), inducible ischemiapattern electrocardiogram (conclusive stress into on admission test)NSTEMI or unstable orand (n = 31) severe STEMIcoronary lesions (n = 39) (Table 1).in the Non-ACSas angiography, was diagnosed published previously by the exclusion [5]. of acute ischemiacharacteristics Demographic (no troponin elevation of theand patients, no factors risk dynamicfor or electrocardiographic coronary artery disease changes suggestivehypertension, (smoking, of myocardial ischemia), inducible dyslipidaemia and dia- ischemia (conclusive stress test) or unstable or severe coronary lesions in the angiography, betes mellitus), medical history, laboratory data during the hospitalization, vital signs on as previously published [5]. Demographic characteristics of the patients, risk factors for admission, treatment and diagnosis at discharge were collected from all patients. A his- coronary artery disease (smoking, hypertension, dyslipidaemia and diabetes mellitus), tory of heart medical failure history, was codified laboratory data during if patients had at least the hospitalization, vitalone hospitalization signs with such on admission, treat- diagnosis ment andat discharge diagnosis or the typical at discharge signs and were collected symptoms from of A all patients. heart failure history andfailure of heart a compati- ble echocardiogram. Patients underwent an echocardiography within was codified if patients had at least one hospitalization with such diagnosis at discharge or 48 h of admission, and thethe left signs typical ventricular ejectionoffraction and symptoms (LVEF) heart failure and awas calculated compatible using Simpson’s echocardiogram. Patientsmethod underwent [37]. Patientsan echocardiography were excluded from within 48 h ofifadmission, the study they had ageand the > 85,left ventricular previous ejec- of is- history tion fraction chemic (LVEF) was heart disease calculated or heart using failure, Simpson’s diagnosis ofmethod hypo- or [37]. Patients were excluded hyperthyroidism, presence of from the study if they had age > 85, previous history of ischemic previous valve disease, initial haemoglobin < 10 g/dl, initial presentation of ACS heart disease or heartas car- failure, diagnosis of hypo- or hyperthyroidism, presence of previous valve disease, initial diogenic shock, treatment with anti-retrovirals, pregnancy or died in the first < 24 h or haemoglobin < 10 g/dL, initial presentation of ACS as cardiogenic shock, treatment with before the first blood anti-retrovirals, test after pregnancy a fasting or died in the night could first <24 h orbe obtained before (see the first Flowchart blood test afterinaFigure 3).fasting night could be obtained (see Flowchart in Figure 3). Figure Figure3.3. Flowchart Flowchart ofof patient patient selection selection and exclusion and exclusion criteria. criteria criteria. Exclusion Exclusion criteria includes includes the the number number of patients of patients excludedexcluded for each criteria. for each criteria. Allpatients All patients had hadmoderate moderate cardiovascular disease cardiovascular (CVD)(CVD) disease risk following the European risk following the Euro- Heart Score (below 5% and higher than 1%) [38] and the Framingham Risk Score (10–19%) [39] pean Heart Score (below 5% and higher than 1%) [38] and the Framingham Risk Score (Table 1). (10–19%) [39] (Table Additionally, 1). a reference group of 31 healthy, non-treated, overweight or obese vol- Additionally, a reference grouporofclinical unteers without additional risk factors 31 healthy, non-treated, symptoms overweight of disease was or obese included for volunteers without additional risk factors or clinical symptoms of disease was included for baseline comparative purposes of the novel techniques investigated in this study. Pa- tient at admission and volunteer characteristics are shown in Table S1. Int. J. Mol. Sci. 2023, 24, 5391 9 of 13 baseline comparative purposes of the novel techniques investigated in this study. Patient at admission and volunteer characteristics are shown in Table S1. The study complies with the Declaration of Helsinki and was approved by the Ethics Committee of Clinical Research of “Hospital San Juan de Alicante”, Spain (Ref 17/314; 7 June 2017); informed consent was obtained from all subjects. 4.2. Biochemical and Laboratory Parameters Blood samples were obtained within a mean ± SEM of 2.60 ± 2.02 days. Briefly, blood samples were collected without anticoagulant or in EDTA-containing vacutainer tubes for serum and plasma preparation. Routine standard biochemical determinations including troponins and haemogram were performed for the on-going ACS registry of our institution [5]. Aliquots of both serum and plasma were kept at −80 ◦ C for the specific assays involved in this study. 4.3. LDL and HDL Sample Preparation and Purity Control LDL (density 1.019 to 1.063 g/mL) and HDL (density range 1.063–1.210 g/mL) were obtained from 1 mL plasma-EDTA from individual samples by sequential ultracentrifu- gation according to the method originally described by Havel et al. [40] and modified by De Juan-Franco et al. [41]. To avoid lipoperoxidation, all solutions contained 1 mmol/L EDTA and 2 µmol/L butylated hydroxytoluene (BHT) and centrifugations were performed at 4 ◦ C using rotors stored in a cold room. Briefly, plasma was adjusted to a density of 1.019 g/mL with a concentrated salt solution (potassium bromide) and centrifuged at 225,000× g for 18 h in a Beckman L-60 preparative ultracentrifuge with a fixed-angle type 50.4 Ti rotor (Beckman, Brea, CA, USA). After removal of the top layer containing very low and intermediate density lipoproteins (VLDL and IDL), the density of the infranatant was adjusted to 1.063 g/mL, followed by centrifugation for 20 h at 225,000× g before LDL was collected from the top of the tube. Lastly, the process was repeated adjusting the plasma density to 1.210 g/mL and samples were ultracentrifuged at 225,000× g for 24 h at 4 ◦ C to allow HDL to float and separate from lipoprotein-deficient serum. In addition, LDL to be used in the TRAP assay was isolated from a pool of plasma (180 mL) obtained from normolipidemic subjects and obtained as described above in a Beckman Optima L-100 XP with a fixed-angle type 50.2 Ti (Beckman, Brea, CA, USA). LDL and HDL fractions were dialyzed against phosphate-buffered saline (PBS) for 24 h. After dialysis, LDL and HDL protein content was determined by the colorimetric BCA assay (Pierce) and adjusted to 100 µg/mL with PBS. Samples were left protected from light at 4 ◦ C until analysis. LDL and HDL purity was routinely analysed by electrophoresis (2 µL sample) in agarose gels using a commercial assay (SAS-MX Lipo 10 kit, Helena Biosciences, London, UK) as described by the providers. 4.4. Conjugated Diene Assay Susceptibility of LDL to copper-induced oxidation was assessed by determining the formation of conjugated dienes. Briefly, freshly prepared LDL samples adjusted to 100 µg/mL with PBS were analysed in 96 well plates by incubation with a copper (II) sul- phate (CuSO4 •5H2 O) solution at a final concentration of 5 µM. The change of absorbance was monitored for 2 h 30 min at 37 ◦ C using a SpectraMax 190 Microplate reader (Molecular Devices, San José, CA, USA) by continuously following the formation of conjugated diene, a product of lipid peroxidation with absorbance peak at 234 nm. The total amount of conju- gated diene was calculated using the molar extinction coefficient of 29,500 M−1 cm−1 [42]. 4.5. HDL Antioxidant Potential The antioxidant potential of HDL was assessed by performing the total-radical- trapping antioxidative potential (TRAP) test [43]. This method is based on the capability of HDL to prevent LDL (control LDL) oxidation. Briefly, HDL and LDL lipoproteins were diluted in PBS 1× to a final concentration of 100 µg protein/mL. HDL from each individual Int. J. Mol. Sci. 2023, 24, 5391 10 of 13 subject was incubated for 4 h at 37 ◦ C with copper (II) sulphate (CuSO4 •5H2 O) at final concentration of 20 µM either alone or in the presence of LDL control (plasma pool). As a baseline value, the LDL sample was incubated alone with and without CuSO4 during the same time period. Oxidation was stopped by adding 50 µL of EDTA 1 mM. Thereupon, 100 µL of each sample was transferred to a fluorescence 96-well plate (Corning® , TC Black plate with clear bottom, New York, NY, USA). Eventually, samples were incubated with 50 µL of freshly prepared DCFH-DA (20 ,70 -dichlorodihydrofluorescein diacetate, Molec- ular Probes, Eugene, OR, USA) at a final concentration of 10 µM for 1 h 30 min at 37 ◦ C and 100 rpm. Dichlorofluorescin-diacetate was employed as the marker of the oxidative reaction [44]. Lipid oxidation products convert DCFH to DCF, which produces intense fluorescence. The intensity of fluorescence was determined with a Typhoon FLA9500 set at λex = 500 nm and λem = 520 nm. Final fluorescence measurements were expressed as the percentage of inhibition of oxidized LDL in the presence of HDL relative to the oxidation level when LDL was incubated in absence of HDL. 4.6. HDL Cholesterol Efflux Capacity Assay The cholesterol efflux capacity (CEC) of HDL was determined in cholesterol-loaded murine macrophages as previously reported [45]. To this end, J774A.1 mouse macrophages (at passage seven) were cultured in RPMI 1640 (Roswell Park Memorial Institute medium) containing 10% of heat-inactivated FBS (Foetal bovine serum), 2 mM glutamine, 100 U/mL penicillin, 100 U/mL streptomycin and 10 µg/mL gentamicin at 37 ◦ C in a humidified atmosphere of 5% CO2 . For the experiments, macrophages (1.5 × 105 cells/well) were seeded in 6-well culture plates (Falcon 6-well Clear Flat Bottom TC-treated culture plate, Corning® , New York, NY, USA) and labelled for 48 h with [1α, 2α (n)-3 H]-cholesterol] (GE Healthcare, Chicago, IL, USA) at 1 µCi per well. Cells were equilibrated overnight in 0.2% bovine serum albumin and thereafter incubated with RPMI media containing 5% ApoB-depleted serum (4 h, 37 ◦ C) to promote cholesterol efflux from the [3 H] cholesterol- labelled cells. ApoB-depleted serum was obtained by precipitation of ApoB particles with a solution containing phosphotungstic acid (0.484 mM) and MgCl2 (22 mM). ApoA-I and ApoB measurements in ApoB-depleted serum samples were determined by immunotur- bidimetric assays using commercial kits adapted to a COBAS 501c autoanalyzer (Roche Diagnostics, Basilea, Switzerland). ApoB reported values in ApoB-depleted serum were below 0.06 mg/mL. The radioactivity signal was quantified in both media and cells and the percentages of cholesterol efflux calculated by expressing the radioactive cholesterol released to the medium as the fraction (%) of the total radioactive cholesterol present in the well (radioac- tivity in the cell + radioactivity in medium). 4.7. Lipoprotein Particle Number and Size Measurements Lipoprotein size was directly measured in serum (500 µL) by nuclear magnetic reso- nance (NMR) as described by Mallol et al. [46] using the two-dimensional diffusion-ordered 1H-NMR spectroscopy (2D DOSY) Liposcale® (Biosfer Teslab, Reus, Spain). Briefly, particle concentration was obtained from the measured amplitudes and attenuation of their spec- troscopically distinct lipid methyl group NMR signals using the 2D diffusion-ordered 1H NMR spectroscopy (DSTE) pulse. The methyl signal was surface fitted with nine Lorentzian functions associated with each lipoprotein subtype of the LDL: large, medium and small. The area of each Lorentzian function was related to the lipid concentration of each lipopro- tein subtype, and the size of each subtype was calculated from their diffusion coefficient. The particle numbers for each lipoprotein subtype were calculated by dividing the lipid volume by the particle volume of a given class. The lipid volumes were determined by using common conversion factors to convert concentration units into volume units [47]. Int. J. Mol. Sci. 2023, 24, 5391 11 of 13 4.8. Statistical Analysis Statistical analyses were conducted using StatView 5.0.1 software (SAS Institute, Cary, NC, USA) and SPSS software (IBM SPSS Statistics 25.0.0, New York, NY, USA) except when indicated. Data are expressed by the number of cases (qualitative variable) and as mean ± standard error of the mean (SEM) or median [IQR] for the quantitative vari- able. The normal distribution of variables was analysed by the Kolmogorov–Smirnov test. Differences between characteristics of the groups were analysed by unpaired Student’s t-test or an analysis of variance (ANOVA) for parametric variables. A Bonferroni post hoc test was run for two group comparisons after ANOVA. Slope differences between groups in regression analysis were assessed by analysis of covariance (ANCOVA). When normality failed, Mann–Whitney or Wilcoxon tests was performed for non-parametric variables. When needed, chi-squared analysis was performed as indicated in the Results section. All reported p-values are two-sided, and a p-value of 0.05 or less was considered to indicate statistical significance. Supplementary Materials: The supporting information can be downloaded at: https://www.mdpi. com/article/10.3390/ijms24065391/s1. Author Contributions: Conceptualization, A.C. and L.B.; methodology, A.C., V.B.-G., D.E., E.F., P.Z. and N.M.-G.; validation, A.C., T.P., G.V. and L.B.; formal analysis, N.M.-G.; investigation, A.C. and N.M.-G.; resources, A.C. and L.B.; data curation, A.C. and N.M.-G.; writing—original draft preparation, A.C., L.B. and N.M.-G.; writing—review and editing, A.C., L.B., T.P., G.V. and N.M.-G.; visualization, all authors contributed; supervision, A.C., T.P., G.V. and L.B.; project administration, A.C. and L.B.; funding acquisition, A.C. and L.B. All authors have read and agreed to the published version of the manuscript. Funding: This work was supported by the Spanish Society of Cardiology (SEC) by a grant titled “Investigación Clínica 2017 (to A.C.); preliminary analyses received the support of a grant from the So- ciedad Valenciana de Cardiología (to A.C. in 2017); Spanish Ministry of Economy and Competitiveness of Science and Agencia Estatal de Investigación (AEI /10.13039/501100011033-[PID2019-107160RB- I00]) to L.B.; PID2021-128891OB-I00 to G.V. CIBERCV to L.B., A.C. and V.B.-G. (CB16/11/00411; CB16/11/00226; CB16/11/00420), and FIS PI19/01687, to T.P., cofounded by “Fondo Europeo de Desarrollo Regional (FEDER): A way of making Europe”. Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya [2017 SGR 1480]. We thank Fundación Jesus Serra and Fundación de Investigación Cardiovascular, Barcelona, for their continu- ous support. Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of Hospital San Juan de Alicante, Spain (Ref 17/314; 7 June 2017). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: The data presented in this study are available on request, due to privacy restrictions. Conflicts of Interest: A.C. reports (a) honoraria for lectures from AstraZeneca, Bristol-Myers Squibb, Ferrer, Boehringer Ingelheim, MSD, Novartis and Bristol-Myers Squibb and AMGEN; (b) consulting fees from Novartis, AstraZeneca, Ferrer and AMGEN. V.B.-G. reports (a) honoraria for lectures from Daiichi Sankyo, Boehringer Ingelheim, Bayer, Pfizer-BMS, LivaNova, Ferrer, Cardiome, MSD; (b) consulting fees none; (c) research grants from Medtronic Iberica. T.P. and G.V. declare to be co-founders of the spin-offs Glycardial Diagnostics SL and Ivastatin Therapeutics S (all unrelated to this work). L.B. declares to have acted as SAB member of Sanofi, Novartis and Pfizer; speaker fees from Sanofi and Novartis and to have founded the spin-offs Glycardial Diagnostics SL and Ivastatin Therapeutics S (all unrelated to this work). The remaining authors (N.M.-G.; D.E.; E.F. and P.Z.) have nothing to disclose. Int. J. Mol. Sci. 2023, 24, 5391 12 of 13 References 1. Nowbar, A.N.; Gitto, M.; Howard, J.P.; Francis, D.P.; Al-Lamee, R. Mortality From Ischemic Heart Disease. Circ. Cardiovasc. Qual. Outcomes 2019, 12, e005375. [CrossRef] 2. Sanchis-Gomar, F.; Perez-Quilis, C.; Leischik, R.; Lucia, A. Epidemiology of coronary heart disease and acute coronary syndrome. Ann. Transl. Med. 2016, 4, 256. [CrossRef] 3. Claessen, B.E.; Guedeney, P.; Gibson, C.M.; Angiolillo, D.J.; Cao, D.; Lepor, N.; Mehran, R. 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