Serum level of hdl particles are independently associated with long-term prognosis in patients with coronary artery disease: the genes study

ABSTRACT HDL-Cholesterol (HDL-C) is not an accurate surrogate marker to measure the cardioprotective functions of HDL in coronary artery diseases (CAD) patients. Hence, measurement of other

HDL-related parameters may have prognostic superiority over HDL-C. In this work, we examined the predictive value of HDL particles profile for long-term mortality in CAD patients and to

compare its informative value to that of HDL-C and apoA-I. HDL particles profiles were measured by nuclear magnetic resonance (NMR) spectroscopy in 214 male participants with stable CAD

(45–74 years). Median follow up was 12.5 years with a 36.4% mortality rate. Cardiovascular mortality accounted for 64.5%. Mean concentrations of total HDL particles (HDL-P), small-sized HDL

(SHDL-P) and apoA-I were lower in deceased than in surviving patients whereas no difference was observed according to HDL-C and large HDL particles. All NMR-HDL measures were correlated

between themselves and with other HDL markers (HDL-C, apoA-I and LpA-I). In a multivariate model adjusted for cardiovascular risk factors and bioclinical variables, HDL-P and SHDL-P

displayed the strongest inverse association with all-cause and cardiovascular mortality. Weaker associations were recorded for apoA-I. Based on our results, we conclude that HDL particle

profile measured by NMR spectroscopy should be considered to better stratify risk in population at high risk or in the setting of pharmacotherapy. SIMILAR CONTENT BEING VIEWED BY OTHERS

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PATIENTS WITH STABLE ANGINA Article Open access 20 October 2021 INTRODUCTION HDL-Cholesterol (HDL-C) has been repeatedly inversely related to cardiovascular risk in all epidemiological

studies. However, pharmacological trials aimed at increasing HDL-C have failed to demonstrate a beneficial effect on clinical outcomes1. Also, some genetic variants associated to increased

HDL-C have not been found associated to a decreased cardiovascular risk2 but those HDL randomization studies are questionable because they disregarded the complexity of lipoprotein

metabolism by excluding from their analyses important genes that not exclusively regulate HDL-C levels but also those of other lipoproteins3,4. This has led to the concept that a single

measurement of HDL-C does not necessarily reflect the functional properties of HDL particles and their effects against atherosclerosis. Indeed, HDL particles are heterogeneous in size and

biochemical composition, and HDL subpopulations might have different functional properties5. NMR-spectroscopy has been recently proposed as a tool to quantify HDL particles and HDL

subpopulations5. This technology enables to measure the total concentration of HDL particles and their size distribution. Numerous recent studies have shown that the atheroprotective

properties of HDL are supported by small and medium-sized HDL particles6, which were inversely related to cardiovascular risk in various clinical settings7,8. In the present study, we have

evaluated HDL particles concentration and distribution in a cohort of patients with established, angiographically documented, coronary artery disease9,10 taking into account an extended

panel of potential confounders related to cardiovascular risk and heart condition. The patients’ vital status was yearly assessed and mortality was recorded, distinguishing all-cause

mortality, cardiovascular mortality and other causes of death, during a 12.5-year median follow-up. In addition, one objective of the study was to compare HDL particles measurements to

routinely available HDL markers, HDL-C and apoA-I, as predictors of mortality in CAD patients. Indeed, apoA-I is the major HDL protein, its immunoassay is today referred to international

standards and now available on automated analyzers. Moreover apoA-I is much less influenced than HDL-C by other components of the lipoprotein profile, like VLDL or LDL, which may have an

impact on HDL lipid composition through action of lipid transfer proteins. RESULTS CHARACTERISTICS OF CAD PATIENTS ACCORDING TO VITAL STATUS The present cohort was constituted of 214 CAD

male patients. After inclusion, the vital patients’ status was yearly assessed. The median follow-up period was 12.5 years (mean: 10.7 years). During follow-up, 78 deaths had been recorded

giving a death rate of 36.4% and a mean annual rate of 3.4%. Cardiovascular mortality accounted for the majority of deaths recorded (64.1%, n = 50) and cancers accounted for 16.7% (n = 13).

Comparison of patients’ data when they were included in the cohort is given in Table 1. Results are presented distinguishing two groups: the “alive group” (patients living at the end of the

follow-up) and the “deceased group” (patients who died during follow-up). Hypertension was diagnosed or treated in 65.6% patients (45.5% under treatment) with no difference between the

deceased and alive groups (p = 0.95). Dyslipidemia was diagnosed or treated in 71.3% (65.4% treated) of the alive group, and in 50.6% (43.6% upon treatment) of the deceased group and the

difference was statistically significant (p = 0.002). Among patients treated for dyslipidemia, 87.8% were treated with statins, 16.2% with fibrates, 4% with both statins and fibrates and

none were treated with niacin or other lipid-lowering therapy. Diabetes was diagnosed in 18.7% (16.9% treated) of the alive group and in 41.8% (37.2% upon treatment) of the deceased group

and the difference was statistically significant (p = 0.001). Patients having deceased during the follow-up period had a longer duration of CAD, a decreased left ventricle ejection volume

(LVEF), a higher heart rate and a more severe angiographic lesion score (Gensini). Regarding cardiovascular risk factors, smoking habits and treatment for diabetes were more frequent in the

deceased group, whereas lipid-lowering therapy was less frequent. Among lipoprotein parameters, only apoA-I, a major HDL marker, was significantly lower in further deceased patients. Hs-CRP,

an inflammatory marker, was lower in surviving than in deceasing patients. NT-proBNP levels were significantly higher in further deceased patients but no difference was observed in the

concentration of hs-TnT between the two groups, indicating that deceased patients suffered from a more severe myocardial dysfunction rather than from a more extended myocardial necrosis. The

distribution of prior cardiovascular events in the studied population of stable CAD patients is shown in Supplementary Table 1. The majority is represented by myocardial infarction (MI,

52.3%), followed by revascularization procedures (37.9%) and then by other ischemic heart disease (IHD, 9.8%, _e.g_. stable angina). Logically, among patients deceased during follow-up, past

history of MI and other IHD were more frequent than in alive patients. HDL PARTICLES ACCORDING TO VITAL STATUS HDL particles’ profile was determined by NMR spectroscopy, enabling to

distinguish large HDL (LHDL-P, 8.8–13 nm) and small-sized HDL (SHDL-P, 7.3–8.7 nm) particles. The latter accounted for about ∼85% of total HDL particles (HDL-P). HDL-P was ∼10% lower in

deceased than in surviving patients (24.6 μmol/L [SD, 6.0] vs. 27.5 μmol/L [SD, 4.9], p = 0.001, Table 2). This difference was entirely due to a decreased number of SHDL-P, whereas number

LHDL-P was not different according to the vital status (Table 2). The average size of total HDL particles (HDL size) was found higher in deceased patients (8.94 nm _versus_ 8.82 nm, p = 

0.014). CORRELATIONS BETWEEN HDL PARTICLES MEASURES AND CLINICAL AND BIOLOGICAL PARAMETERS Correlations were investigated between markers of HDL particles and other clinical or biological

parameters in the study population (Table 3). All NMR-HDL measures were correlated between themselves and with other HDL markers: HDL-C, apoA-I and lipoprotein A-I (LpA-I). Logically, the

average HDL size was correlated positively with the number of LHDL-P, and negatively, with the number of SHDL-P. Triglycerides were associated positively with HDL-P and SHDL-P but negatively

with LHDL-P, mean HDL size and HDL-C. No association was observed with apoA-I. These correlations might reflect the remodeling of HDL lipids induced by the cholesterol ester transfer

protein (CETP) acting between HDL particles and triglyceride-rich lipoproteins. Alcohol consumption positively correlated with HDL-C and HDL-P, and more specifically with SHDL-P but not with

apoA-I. Inflammation, as documented by plasma hs-CRP, was inversely associated with apo A-I, HDL-P and SHDL-P, but not with LHDL-P. HDL-P, SHDL-P and apoA-I were negatively associated with

NT-proBNP and hs-TnT. The severity of coronary lesions, as illustrated by the Gensini score, was inversely related to HDL-P. Strong positive associations were observed between LVEF and both

HDL-P and SHDL-P. ApoA-I levels correlated with LVEF but not significantly with the Gensini score. For comparison, no relationship was recorded between HDL-C and either LVEF or the Gensini

score. Thus, although HDL markers were strongly correlated between themselves, total and subclasses of HDL particles displayed specific association with clinical variables. TOTAL AND

CARDIOVASCULAR MORTALITY ACCORDING TO TERTILES OF HDL MARKERS Each one HDL marker was considered according to tertiles of its distribution in the whole study population (Table 4). Death

rates during follow-up were determined across the different tertiles and associations were determined after adjustment on classical risk factors including age, smoking and treatments for

hypertension, diabetes and dyslipidemia. Similar associations were observed without adjustment. The strongest association to total and cardiovascular mortality was observed for HDL-P

distribution. A 45% reduction in death rates was recorded in tertiles 2 and 3, as compared to tertile 1. Each 1 SD increase in HDL particles number was found associated with ∼42% reduction

in total or cardiovascular mortality (HR = 0.58 [95% CI, 0.45–0.75] and 0.59 [95% CI, 0.44–0.80], respectively). Results were almost identical considering SHDL-P (HR = 0.60 [95% CI,

0.46–0.77] and 0.61 [95% CI, 0.45–0.82], respectively). Taking into account fibrate and/or statin use in statistical analyses had no effect on the association of HDL-P and SHDL-P particles

with mortality (not shown). By contrast, no association between LHDL-P and mortality was observed, except for an almost significant positive trend (p = 0.07) between LHDL-P and death rates.

Concordantly, death rates were significantly different across HDL size distribution, an increase in particles size being associated with highest death rates. Considering classical HDL

markers, HDL-C tertiles did not display different death rates, yet a 1 SD increase in HDL-C was associated with a significantly lower HR for total mortality (0.78, p = 0.03). ApoA-I

distribution was associated to total and cardiovascular mortality; each 1 standard deviation increase of apoA-I was associated to a ∼31% risk reduction (HR = 0.69 [95% CI, 0.54–0.88] and

0.67 [95% CI, 0.49–0.91], respectively). A further multivariate analysis was conducted using a forward stepwise selection of adjustment variables (Fig. 1). Regarding total mortality, the

variables retained in the model were age, smoking, treatment for dyslipidemia, renal function (eGFR), LVEF, duration of CAD and Gensini score, the 3 last parameters reflecting heart

condition. For cardiovascular mortality, similar variables were retained except for age, smoking and eGFR. Hazard ratios for mortality per 1-SD increase of HDL-P, SHDL-P, of apoA-I and HDL-C

were all significant (Fig. 1). HR were almost identical for all-cause and CV mortality (Fig. 1). They were the lowest for HDL-P or total and cardiovascular mortality (HR = 0.60 [95% CI,

0.46–0.79] and HR = 0.63 [95% CI, 0.46–0.86], respectively) and the highest and at the limit of significance for HDL-C (HR = 0.71 [95% CI, 0.55–0.92] and HR = 0.72 [95% CI, 0.53–0.99]

respectively). Intermediate values of HR were found for apoA-I. Associations between HDL markers and mortality are illustrated in the survival curves established during the whole follow-up

period for the different tertiles (Fig. 2). Death rates were regular during the whole time course of follow-up. For both HDL-P and SHDL-P, patients in the first tertile had a poorer survival

than patients in tertiles 2 and 3. This was particularly evident for early events: of the 17 deaths recorded during the 0–3 year follow-up, 11 (65%) were in the lowest tertile of HDL-P as

compared to 8 out of 20 (40%) for the deaths recorded in the 9–12 year period. A comparable trend was observed for apoA-I distribution yet survival differences during the whole period did

not reach statistical significance. DISCUSSION In the present study, serum levels of total HDL particles (HDL-P) and of small-sized HDL particles (SHDL-P) were inversely related to all-cause

as well as to specific cardiovascular mortality in CAD patients. Every 1-SD increase of HDL particle number was associated to a 41% decrease in cardiovascular mortality, after multiple

adjustments on cardiovascular risk factors and on clinical markers of heart condition, including LVEF, duration of CAD and Gensini score. Among other HDL markers, apoA-I was also inversely

related, though to a lesser extent, to total and cardiovascular mortality, and HDL-C was found weakly associated to all-cause mortality. Conversely, large HDL particles (LHDL-P) were not

associated with total and cardiovascular mortality. However, higher death rates were recorded as average HDL particle size increased. NMR-based lipoprotein profiling methods are not yet

standardized and the estimated diameter range of HDL subclasses depends on the analytical methods used. Also, no classification for HDL subclasses analysed by NMR has been yet approved for

routine purpose. For instance, the analytical method developed by LipoScience (now LabCorp, Raleigh, NC) grouped HDL particles into 3 subclasses from small (S-HDL-P, 7.3–8.2 nm), medium

(M-HDL-P, 8.2–9.4 nm) to large (L-HDL-P, 9.4–14 nm) with small and medium-sized HDL particles being sometimes grouped (MS-HDL-P, 7.3–9.4 nm), while the AXINON lipoFIT-S100 system (Numares

AG, Regensburg, Germany) used in the present study grouped HDL subclasses into small (SHDL-P, 7.3–8.7 nm) and large (LHDL-P, 8.8–13 nm)11,12. In this latest classification, it is worth

mentioning that the estimated diameter ranges for SHDL-P and LHDL-P were similar to those for HDL3c+3b+3a (7.2–7.8 nm; 7.8–8.2 nm; 8.2–8.8 nm) and HDL2a+2b (8.8–9.7 nm; 9.7–12.9 nm),

respectively, as isolated from plasma by density gradient ultracentrifugation and analyzed by electrophoresis on a nondenaturing gel13,14. To date, the inverse and independent association

between HDL-P / MS-HDL-P and cardiovascular risk has been extensively documented with respect to primary prevention, either in individuals without baseline CAD7,15,16,17,18 and in those with

pre-clinical atherosclerosis, as documented by carotid intima-media thickness7,19, or coronary calcifications20. More recently, in a large study carried out in high-risk individuals

undergoing coronary catheterization for suspicion of CAD, followed-up during 8 years, HDL-P and MS-HDL-P were independent predictors of all-cause mortality8. With respect to secondary

prevention, only a few studies have evaluated the relationship of NMR-derived HDL particle subclasses with cardiovascular disease outcomes in CAD patients. In a prospective nested

case-control study of 364 men with new CAD events (non-fatal myocardial infarction or cardiac death) during a 5.1 year follow-up paired to 697 age-matched control, total HDL-P and small

HDL-P (7.3–8.2 nm) were strong, independent, predictors of recurrent coronary events, whereas levels of HDL-C were not21. Similarly, inverse association between HDL-P and coronary events has

also been reported in a large mixed-gender cohort of CAD patients during a 5.3 years of follow up22. In patients suffering from acute heart failure, concentrations of both HDL-P and small

HDL-P (7.3–8.7 nm) were inversely related to short-term (3-month) mortality, after multiple adjustments on confounding variables, including NT-proBNP, a classical marker of heart failure23.

The present study brings some additional insights on this relation between NMR-derived HDL particles subclasses and long-term prognosis in CAD patients, with angiographically documented

coronary lesions. Association of HDL markers to all-cause and cardiovascular mortality was assessed after adjustment on a large variety of confounders: life-style parameters, clinical and

biological variables documenting cardiovascular risk factors, inflammatory status, renal function and heart condition. In addition, this study has enabled to compare the predictive value of

apoA-I versus HDL-P measurements, which showed comparable associations, although Hazard ratios were better with HDL-P levels. HDL particles, and most particularly small-sized HDL, may act

against atherosclerosis through different mechanisms. Small HDL behave as the best acceptors of ABCA1-mediated cholesterol efflux from macrophages, leading subsequently to the mobilization

of intracellular cholesterol to the plasma membrane24,25. Small and dense HDL particles also protect LDL from oxidation. HDL particles act through removing phospholipid hydroperoxides from

LDL and by inactivating oxidized lipids by specific enzymes like paraoxonase-1 (PON-1) and PAF-acetylhydrolase26,27. Moreover small protein-rich HDL exert anti-inflammatory properties by

depressing expression of VCAM-1 at the surface of endothelial cells28. On these cells, HDL particles appear to be cytoprotective by inhibiting apoptosis induced by oxidized LDL, and small

HDL3 would be the most effective in this function29. Altogether those observations suggest that the proteome associated to small HDL particles support various biological activities, which

impair atherosclerosis development. Moreover, HDL particles may exert beneficial effects on myocardial functions. Indeed, in different experimental contexts, it was demonstrated that HDL

particles protect against ischemia reperfusion injury30, leading to a reduction in infarct size. HDL may also improve myocardial function by reducing ventricular remodelling following

infarction31. In isolated cardiomyocytes, HDL particles were shown to prevent apoptosis through an AMP-kinase dependent mechanism32. These experimental observations on a direct impact of HDL

on myocardial functions might translate into clinical impacts. In support of this concept is the positive correlation observed here between HDL-P, small HDL-P and the left ventricular

ejection fraction, concordant with the negative association between HDL-P, small HDL-P and NT-proBNP observed here and previously reported23, although potential confounders might interfere

with these associations. In this study, concentrations of large HDL particles were not associated to mortality. However, higher death rates were recorded as HDL size increased (p < 0.01);

following multiple adjustments, association to total mortality for the upper tertile of HDL size was close to statistical significance (p = 0.06). Similar observations regarding all-cause

mortality in individuals who are at high cardiovascular risk have been previously reported8. Large HDL-P might be less effective than SHDL-P regarding various atheroprotective functions,

like cholesterol efflux, anti-oxidative and anti-inflammatory properties, and cytoprotective effects on endothelium6,33. Moreover, accumulation of large HDL might reflect a defect in HDL

catabolism, and particularly in HDL liver uptake, which constitutes the last step of reverse cholesterol transport34. Similarly, we did not observe any association of HDL-C with mortality.

This is concordant with the lack of association between LHDL-P and mortality, since HDL-C mainly reflects cholesterol associated with large, lipid rich, HDL particles. ApoA-I was inversely

related to mortality: for each 1-SD increase of apoA-I, a 31% and 33% decrease in all-cause and cardiovascular mortality was recorded, respectively. So far, apoA-I has been little used in

epidemiological studies. However, calibration on reference international standards has made the immunoassay of apoA-I robust and comparable between studies. Furthermore, apoA-I measurement

is much less influenced than HDL-C by intravascular enzymes and lipid transfer proteins, which participate in HDL remodelling. Thus, apoA-I measurement may improve assessment of

cardiovascular risk35. Association to mortality was somewhat weaker for apoA-I than for HDL-P or SHDL-P. This might be explained by the fact that the apoA-I content per particle varies on

average from 2 to 4, between small HDL3 and large HDL2 36, so that large HDL particles are somewhat overrepresented in apoA-I quantification. A number of limitations of the present study

must be noted. First, the small size of the study is a limitation. Indeed, the first 214 consecutive CAD patients from the GENES cohort where included in the present study, which represent

25% of the whole cohort (n = 834). Accordingly, mortality rate was higher in included patients than in the whole cohort (36.4% _versus_ 29.1%, data not shown), probably because of the longer

duration of follow-up for those first included patients. Clinical and biological characteristics were comparable, between included and non-included patients, except for dyslipidemia

treatment, somewhat less frequent in included patients (57.5% vs 65.8%, p = 0.04, Supplementary Table 2). This difference might result from difference in statin administration practice

between the beginning (year 2001) and the end (2004) of the GENES study. Second, this study was designed only with men, which has the advantage of recording a larger number of events than in

a mixed all-gender cohort, particularly in south-western France where the incidence rates are particularly low for women under 65 years of age37 but limited the translatability of our

results to women. Third, despite adjustments on established CVD risk factors the possibility remains that other important confounding variables with effects on HDL parameters were not

measured or considered in our analyses. Finally, NMR-based HDL classification in large and small HDL particles provides limited insights into the biology of these complex particles, now

known to include more than 10 subspecies, for which proteome and lipidome compositions affect functional properties38. In particular the pre-beta HDL which are the principal acceptors for

cholesterol effluxed from the arterial wall39 are not accurately quantified by this method. Thus, comparison with other methods of analysis of HDL subfractions40 would be relevant to confirm

our findings and to improve our understanding of HDL functions. In conclusion, the present study demonstrated that the concentration of total HDL particles and small-sized HDL particles may

serve as a better prediction tool than HDL-C and apoA-I to assess long term prognosis in coronary patients. Studies on HDL metabolism had progressively led to the schematic view of an

interconversion cycle of HDL particles in the plasma compartment, driven by cell cholesterol efflux, enzymes like LCAT, lipases and lipid transfer proteins41,42. More recently the concept

has emerged that HDL particles of different geometry and chemical composition have distinct metabolic fate and display specific functional properties5,6,43. This supports the idea that HDL

functionality might be more precisely assessed by the quantification of specific HDL particles with high atheroprotective effects. In the future, quantification of HDL particle concentration

and HDL subclasses along with HDL functional measurement could be clinically useful in CVD risk assessment. METHODS STUDY PARTICIPANTS The “Génétique et Environnement en Europe du Sud”

(GENES) study is a case-control study designed to assess the role of genetic, biological and environmental determinants in the occurrence of CAD44. Written informed consent was obtained from

all participants, and the study protocol was conducted in accordance with the Helsinki Declaration and approved by the local ethics committee (Comité consultatif de protection des personnes

dans la recherche biomédicale (CCPPRB), Toulouse/Sud-Ouest, file #1-99-48, Feb 2000). All research was performed in accordance with procedures and regulations at the Toulouse University

Hospital. A blood sample collection has been constituted (declared as DC-2008-463 #1 to the Ministry of Research and to the Regional Health Authority). As previously described, cases were

stable male CAD patients living in the Toulouse area (South-west France), aged 45–74 and prospectively recruited from 2001 to 2004 after admission to the Cardiology department, Toulouse

University Hospital, for cardiovascular examination and referred for evaluation and management of their CAD45. Patients included in the present study presented a stable CAD that was defined

by a previous history of acute coronary syndrome, a previous history of coronary artery revascularization, a stable angina or a documented myocardial ischemia, as assessed by presence of

coronary stenosis of ≥50% of luminal narrowing at the coronary angiography. Patients who had presented an acute coronary episode in the seven days prior to the recruitment were not included

in the study, because they were considered unstable. In the present analysis, we only took into account the first 214 consecutive patients (i.e. those with CAD) in whom NMR-HDL profile was

measured and complete data were available for all the subjects. The minimal sample size (n = 186), increased by 15% to take into account missing data, was calculated to detect a HR of 0.8

(for one SD increase of HDL-C) with a 80% power at a 0.05 significance level. The sample size was adjusted for an anticipated event rate of ∼35% corresponding to a median follow-up of 12.5

years. ASSESSMENT OF THE VITAL STATUS Vital status was obtained for each participant through the national database (“RNIPP”), which records, every year, all deaths occurring in the French

population (http://cesp.vjf.inserm.fr/svcd). For each patients, vital status was assessed yearly from the year of recruitment until December 31, 2014, with a median follow up of 12.5 years.

All dates and causes of death were obtained for participants who died during the follow-up. Main and associated causes of deaths were provided by the French National Institute of Health

Research (CépiDc-INSERM), which systematically collects and codes (using the International Classification of Diseases coding system) data recorded on death certificates. Death from a

cardiovascular cause during follow-up was assessed by a committee of four medical doctors, every time cardiovascular disease was reported as the main cause of death, or when it was mentioned

as an associated cause, if the main cause was a plausible complication of cardiovascular disease. Authorizations to use these data were obtained in accordance with French law (Commission

nationale de l’informatique et des libertés (CNIL): authorization 355152v1, September 3, 2008). BIOLOGICAL MEASUREMENT Blood was collected after an overnight fast. Serum sample aliquots were

subsequently stored at −80 °C until biological analyses. The following biomarkers were assayed with enzymatic reagents on automated analyzers (Hitachi 912 and Cobas 8000, Roche Diagnostics,

Meylan, France): serum total cholesterol, HDL-C, triglycerides, fasting glucose, creatinin. eGFR was calculated using the abbreviated Modification of Diet in Renal Disease (MDRD) Study

equation46. ApoA-I, high-sensitive C-Reactive protein (hs-CRP), N-terminal pro-brain natriuretic peptide (NT-proBNP) and high-sensitive cardiac troponin T (hs-TnT) were determined on the

same analyzer by immunoturbidimetry assays (Roche Diagnostics). Lipoprotein A-I, which refers to lipoproteins containing apoA-I but not apoA-II, were measured by an electroimmunodiffusion

technique47 using the HYDRAGEL LPAI PARTICLES Kit (Sebia, Issy-les-Moulineaux, France). DATA COLLECTION Age, environmental characteristics and information on cardiovascular risk factors were

collected through standardized face-to-face interviews, performed by a single physician. Past medical history was collected and checked in the patients’ medical files. Presence of

dyslipidemia, diabetes mellitus or hypertension was assessed from the subjects’ current treatments. Dyslipidemia was defined as treatment with drugs or fasting serum total cholesterol ≥2.40 

g/L. Hypertension was defined as treatment with drugs or systolic blood pressure ≥160 mmHg or diastolic blood pressure ≥95 mmHg. Diabetes was defined as treatment with drugs or fasting blood

glucose ≥7.8 mmol/L. Smoking status was classified as current smokers, past smokers having quit for more than 3 years and patients having never smoked. Among current smokers, cigarette

consumption was estimated with the pack-year quantification and recorded as the average number of cigarettes per day. Alcohol consumption was assessed using a typical week pattern. The total

amount of pure alcohol consumption was calculated as the sum of different types of drinks and was expressed as grams per day. Physical activity was investigated through a standardized

questionnaire48 and categorized into three levels as: no physical activity, moderate physical activity during 20 minutes no more than once a week, and high physical activity during 20 

minutes, at least twice a week. Blood pressure and resting heart rate were measured with an automatic sphygmomanometer (OMRON 705 CP). Measurements were performed after a minimum of 5 

minutes rest; average values from two different measurements were recorded for further analysis. ASSESSMENT OF CAD SEVERITY AND EXTENSION AND ESTIMATION OF CARDIAC FUNCTION All stable CAD

patients enrolled had a coronary angiography even without evidence of active chronic ischemia. Coronary artery stenoses of ≥50% luminal narrowing were considered significant. Extent of

coronary artery disease lesions was assessed by calculating the Gensini Score, based on data from coronary angiography49,50,51. Left Ventricular Ejection Fraction (LVEF) was assessed by

contrast ventriculography using an isotopic method, and/or by echocardiography. HDL MEASUREMENT BY NUCLEAR MAGNETIC RESONANCE (NMR) SPECTROSCOPY HDL particle concentration and size were

measured by NMR spectroscopy using the AXINON lipoFIT-S100 test system (Numares AG, Regensburg, Germany) as previously described11,12,23. Serum samples for NMR spectroscopy were stored at

−80 °C and kept unthawed until the day of NMR measurements. Serum (630 μL) gently mixed with 70 μL of an additives solution containing reference substances, NaN3 and D2O, and 600 μL of the

mixture were transferred into 5 mm NMR tubes with barcode-labeled caps. Briefly, 1H NMR spectra were recorded at a temperature of 310 K on a shielded 600 MHz Avance III HD NMR spectrometer

(Bruker Biospin) with a 5 mm triple resonance TXI probe head including deuterium lock channel, a z-gradient coil and automatic frequency tuning and matching. Prior to each analytical run,

calibration was performed using a calibration sample comprising an aqueous solution of various calibration substances with different molecular masses, 0.01% (w/v) NaN3, 10% (v/v) D2O as a

locking substance and 1% glycerol to adjust viscosity. Two identical control samples were measured directly after calibration and at the end of each run. Each spectrum was referenced,

normalized and subjected to a set of quality checks including checks of baseline properties, noise level, shift, width, and symmetry properties of quality control signals. Lipoprotein

analysis was conducted via deconvolution of the broad methyl group signal at about 0.9–0.8 ppm. In this process, lipoprotein subclasses are reflected by a fixed number of pre-defined

bell-shaped (e.g. Gaussian or Lorentzian) base functions, each of which has a constant position and defined width. The concentrations of lipoprotein particle subclasses as well as the

average particle size were calculated based on the integrals attributable to specific base functions. Fit quality was checked by calculating the residual deviation between fit and spectrum

intensity. In this study, the concentrations of large-sized HDL particles (LHDL-P), small-sized HDL-particle (SHDL-P) and total HDL particles (HDL-P, reported in μmol/L) as well as the

average HDL particle size (HDL size, reported in nm) are used. The two measured HDL subclasses had the following estimated diameter ranges: LHDL-P, 8.8–13 nm; SHDL-P, 7.3–8.7 nm. STATISTICAL

ANALYSES Continuous variables are displayed as means and standard deviations (SD). Categorical variables are presented as proportions. We first described and compared characteristics of

participants according to vital status. Categorical variables were compared between groups using the χ2-test (or Fisher’s exact test when necessary). Student’s _t_-test was used to compare

the distribution of continuous data. A Wilcoxon Mann-Whitney’s test (or logarithmic transformation of the variable when necessary) was performed when distribution departed from normality, or

when homoscedasticity was rejected. Spearman rank correlations were used to test the associations of NMR-HDL parameters and HDL-C with cardiovascular risk factors, severity, extension and

estimation of cardiac function of the disease. Cumulative survival of patients were determined by the Kaplan-Meier method and compared, using the Log-rank test for the individual endpoints

of all-cause mortality. The relation between baseline variables and mortality was assessed using Cox proportional hazards regression analysis. We tested the proportionality assumption using

cumulative sums of martingale-based residuals. We performed regression analyses with polynomial models (quadratic and cubic) to examine for possible non-linear relations between continuous

variables and mortality. Cox regression analyses were performed first without any adjustment for co-variables and, second, with adjustment on classical cardiovascular risk factors (age,

smoking, treatments for dyslipidemia, hypertension and diabetes). In addition, a forward stepwise selection was used to create the multivariate models. Variables with an entry criterion of p

 ≤ 0.20 were used as candidate covariates in a multivariate cox regression model. Variables were maintained in the model with a retention criterion of p ≤ 0.10 for all-cause of death

analyses and p ≤ 0.05 for cardiovascular mortality. The same covariates were identified for all HDL markers studied. The following variables were introduced into the model as covariates when

considering all cause of death: age, smoking, treatment for dyslipidemia, eGFR, LVEF, duration of CAD and Gensini score. For cardiovascular mortality the variables retained were treatment

for dyslipidemia, LVEF, duration of CAD and Gensini score. All statistical analyses were carried out using the SAS statistical software package 9.4 (SAS Institute, Cary, NC). Analyses were

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Download references ACKNOWLEDGEMENTS This work was supported by the French National Research Agency (ANR, #ANR-16-CE18-0014-01), European Regional Development Fund (ERDF, Fonds Européen de

Développement Régional) and “La Région Occitanie” (Project THERANOVASC n° ESR_R&S_DF-000094/2018-003303/18009464). AUTHOR INFORMATION Author notes * These authors contributed equally:

Bertrand Perret and Laurent O. Martinez. AUTHORS AND AFFILIATIONS * Institut National de la Santé et de la Recherche Médicale (INSERM), UMR 1048, Institute of Metabolic and Cardiovascular

Diseases, Toulouse, France Thibaut Duparc, Annelise Genoux, Cécile Ingueneau, Souad Najib, Bertrand Perret & Laurent O. Martinez * University of Toulouse, UMR1048, Paul Sabatier

University, Toulouse, France Thibaut Duparc, Annelise Genoux, Cécile Ingueneau, Souad Najib, Bertrand Perret & Laurent O. Martinez * Department of Epidemiology, Health Economics and

Public Health, UMR1027 INSERM, Toulouse University, Toulouse University Hospital (CHU), Toulouse, France Jean-Bernard Ruidavets & Jean Ferrières * Service de Biochimie, Pôle biologie,

Hôpital de Purpan, CHU de Toulouse, Toulouse, France Annelise Genoux, Cécile Ingueneau & Bertrand Perret * Fédération de Cardiologie, Toulouse University Hospital, Toulouse, France Jean

Ferrières Authors * Thibaut Duparc View author publications You can also search for this author inPubMed Google Scholar * Jean-Bernard Ruidavets View author publications You can also search

for this author inPubMed Google Scholar * Annelise Genoux View author publications You can also search for this author inPubMed Google Scholar * Cécile Ingueneau View author publications You

can also search for this author inPubMed Google Scholar * Souad Najib View author publications You can also search for this author inPubMed Google Scholar * Jean Ferrières View author

publications You can also search for this author inPubMed Google Scholar * Bertrand Perret View author publications You can also search for this author inPubMed Google Scholar * Laurent O.

Martinez View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS Conception and design of the study: J.F., B.P., L.O.M.; acquisition of data, or

analysis and interpretation of data: T.D., J.B.R., A.G., C.I., S.N., L.O.M.; drafting the article or revising it critically for important intellectual content: A.G., J.B.R., J.F., L.M.,

B.P.; all Authors have read and approved the final version of the manuscript. CORRESPONDING AUTHOR Correspondence to Laurent O. Martinez. ETHICS DECLARATIONS COMPETING INTERESTS The authors

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