Circulating proprotein convertase subtilisin/kexin type 9 (PCSK9) positively correlates with the atherogenic dyslipidaemia characteristic of diabetic patients.

CLINICAL PERSPECTIVES

  • The effect of circulating PCSK9 on LDL cholesterol levels is perfectly established. Having such a huge effect on cholesterol concentrations, we wondered whether it would have any effect on lipid metabolism in subjects with rather normal LDL cholesterol and a very prevalent and high cardiovascular risk condition such as type 2 diabetics.

  • Our results show that in these patients, with rather normal LDL, the more circulating PCSK9 they have, the more atherogenic their lipoprotein profile. This is characterized by large VLDL, small LDL and small HDL, precisely the atherogenic dyslipidaemia that mostly contributes to cardiovascular risk in these patients.

  • Our findings are of clinical interest in the light of the extraordinary therapeutic potential of PCSK9 inhibition that, so far, has been restricted to the treatment of hypercholesterolaemia.

INTRODUCTION

The proprotein convertase subtilisin/kexin 9 (PCSK9) gene is located on chromosome 1p34.1-p32 and codes for a proprotein convertase that belongs to the subtilase subfamily [1]. It was first described as being primarily synthesized and secreted by hepatocytes [1] where it regulates cholesterol homoeostasis by accelerating endosomal and lysosomal LDLR (low-density lipoprotein receptor) degradation [2]. Reduced LDLR levels result in decreased catabolism of LDL (low-density lipoprotein) leading to hypercholesterolaemia.

Shortly after its discovery in 2003, it was reported that gain-of-function PCSK9 mutations are associated with autosomal dominant hypercholesterolaemia [3] and increased cardiovascular risk. Conversely, loss-of-function mutations are linked to low LDL cholesterol levels and reduced cardiovascular risk [4].

Many articles have shown that PCSK9 may affect atherosclerosis through several mechanisms and not only through LDLR degradation.

Systemic inflammation in mice led to increased PCSK9 expression in the liver [5] and gain-of-function PCSK9 mutations reduced hepatic expression of stress response genes and specific inflammatory pathways [6]. PCSK9 silencing showed reduced endothelial ox-LDL-induced apoptosis [7] and its deficiency in the intestine resulted in lower postprandial lipaemia with less plasma TG and higher chylomicron clearance [8]. Furthermore, it has recently been described that circulating PCSK9 strongly correlates with remnant intermediate-density lipoprotein (IDL) particles, suggesting a link between PCSK9 and triglyceride (TG)-rich lipoproteins metabolism [9].

Therefore, we wanted to explore the potential role of circulating PCSK9 in a lipid profile secondary to the high TG levels that are characteristic of patients with metabolic disturbances that lead to high cardiovascular risk, such as atherogenic dyslipidaemia. In atherogenic dyslipidaemia, high plasma TG levels modulate the size and the number of certain lipoproteins, which triggers an imbalance and promotes an increase in circulating pro-atherogenic particles, small dense LDL (sdLDL) particles and cholesterol-rich remnant particles, as well as a decrease in anti-atherogenic high-density lipoprotein (HDL) particles.

To this end, we studied a group of diabetic and metabolic syndrome patients and analysed the correlation of circulating PCSK9 levels with a detailed lipoprotein profile measured by NMR and with cholesterol in circulating remnant lipoproteins (RLPc).

MATERIALS AND METHODS

Study subjects

We included 267 high cardiovascular risk patients who were not receiving any lipid-lowering treatment. These patients were enrolled in the Vascular Medicine and Metabolism Unit of the Sant Joan University Hospital in Reus.

The Adult Treatment Panel (ATP)III criteria were used to define the presence of metabolic syndrome and type 2 diabetes mellitus. Patients with the following conditions were not included: coronary heart disease (CHD), cerebral or peripheral vascular disease, hepatic, renal, lung and endocrine cancer and chronic inflammatory diseases. A complete physical examination, anthropometry and cardiovascular assessment were performed on each participant. Seventy one patients were not receiving any anti-diabetic medication; 123 patients were receiving anti-diabetic noninsulin oral drugs; 71 patients were receiving insulin; and the information was missing for two patients.

The present study was approved by the Ethical and Clinical Investigation Committee of the hospital and all participants signed written informed consent forms.

Biochemical analysis

Indirect enzymatic colorimetric methods were used to quantify total cholesterol and TGs whereas HDL cholesterol was determined using a direct enzymatic colorimetric technique. LDL cholesterol was calculated using the Friedewald formula. Apolipoproteins AI and B100 were measured with immunoturbidimetry using antisera that were specific for apoA-I and apoB (Hoffman–La Roche).

RLPc levels were measured in the plasma according to the method described by Nakajima et al. [10] using the RLP-Cholesterol Assay Kit (Jimro-II, Japan Immunoresearch Laboratories). Briefly, the technique involved the addition of plasma EDTA (5 μl) to a 300-μl gel suspension of anti-human apoA-I and apoB-100 mouse monoclonal antibodies bound to Sepharose®; 200 μl of the supernatant containing unbound fraction was analysed using a sensitive cholesterol assay in a Cobas Mira centrifugal analyser (Roche).

PCSK9 was measured in the plasma using a quantitative sandwich enzyme immunoassay kit (R&D Systems Europe Abingdon).

NMR

Lipoprotein subclass particle concentrations and the average size of the lipoprotein particles were measured using proton NMR spectroscopy (LipoScience), as previously described [11]. Particle concentrations of lipoprotein subclasses of different sizes were obtained directly from the measured amplitudes of the NMR signals of their spectroscopically distinct lipid methyl group. Weighted-average lipoprotein particle sizes are derived from the sum of the diameter of each subclass multiplied by its relative mass percentage based on the amplitude of its methyl NMR signal. The concentrations of the following subclasses were measured: small LDL (diameter 18.0–21.2 nm), large LDL (21.2–23.0 nm), IDL (23.0–27.0 nm), large HDL (8.8–13.0 nm), medium HDL (8.2–8.8 nm), small HDL (7.3–8.2 nm), large very low-density lipoprotein (VLDL; >60 nm), medium VLDL (35.0–60.0 nm) and small VLDL (27.0–35.0 nm). VLDL and LDL particle concentrations are expressed in nmol/l and HDL in μmol/l.

Statistical analysis

The statistical analysis was performed using SPSS version 19 (SPSS Inc.). All of the study variables are represented descriptively. Continuous variables are described using the mean (S.D.). Correlations between circulating PCSK9 and continuous variables were performed with partial correlations adjusted for age, body mass index (BMI) and gender. We also considered testing the effect of plasma TG and/ or the anti-diabetic treatment on the correlations. To test whether the observed association was independent on the anti-diabetic treatment we created a categorical variable dividing the patients into those not receiving any anti-diabetic medication, those receiving insulin and those receiving anti-diabetic non-insulin oral drugs.

RESULTS

Our objective was to analyse the correlation between PCSK9 circulating levels with plasma lipoprotein subclasses determined using NMR technology in a population with atherogenic dyslipidaemia.

Participants

We studied 267 metabolic patients with high cardiovascular risk who met the criteria for type 2 diabetes (n=257, representing 96%) and the criteria for metabolic syndrome (n=196, representing 81%); 70% of our metabolic patients met the criteria for both DM (diabetes mellitus) and MS (metabolic syndrome) (n=186).

The baseline characteristics of the studied subjects are presented in Table 1. As expected, metabolic patients were older, with high BMI and, as a feature of atherogenic dyslipidaemia, they had high TG levels, normal levels of LDL cholesterol and low levels of HDL cholesterol.

Table 1
Baseline characteristics
Subjects (N=267)
Age (years) 60.69 (10.06) 
Gender (% women) 47 
BMI (kg/m231.85 (6.90) 
TGs (mmol/l) 2.09 (1.88) 
Total cholesterol (mmol/l) 5.49 (1.36) 
LDL cholesterol (mmol/l) 3.43 (1.15) 
HDL cholesterol (mmol/l) 1.18 (0.34) 
Non-HDLc (mmol/l) 4.31 (1.39) 
ApoB-100 (mg/dl) 131.69 (35.74) 
ApoA-I (mg/dl) 143.05 (24.28) 
Glucose (mmol/l) 8.88 (3.58) 
HbA1c (%) 7.10 (1.70) 
Subjects (N=267)
Age (years) 60.69 (10.06) 
Gender (% women) 47 
BMI (kg/m231.85 (6.90) 
TGs (mmol/l) 2.09 (1.88) 
Total cholesterol (mmol/l) 5.49 (1.36) 
LDL cholesterol (mmol/l) 3.43 (1.15) 
HDL cholesterol (mmol/l) 1.18 (0.34) 
Non-HDLc (mmol/l) 4.31 (1.39) 
ApoB-100 (mg/dl) 131.69 (35.74) 
ApoA-I (mg/dl) 143.05 (24.28) 
Glucose (mmol/l) 8.88 (3.58) 
HbA1c (%) 7.10 (1.70) 

Mean (S.D.)

Table 2
Correlations between circulating PCSK9 levels and RLPc and lipoproteins determined by NMR

Abbreviation: NS, non significant.

Correlation among PCSK9 (ng/ml) andrP
RLPc (mg/dl) 0.171 0.006 
Non-HDLc (mmol/l) 0.213 0.001 
VLDL and Chylo particles (nmol/l) 0.079 Ns 
 large particles (nmol/l) 0.210 0.001 
 median particles (nmol/l) 0.048 Ns 
 small particles (nmol/l) 0.018 Ns 
IDL 0.206 0.001 
LDL particles (nmol/l) 0.257 2.75 × 10−5 
 large particles (nmol/l) −0.039 Ns 
 small particles (nmol/l) 0.224 2.70 × 10−4 
 median small particles (nmol/l) 0.235 1.39 × 10−4 
 very small particles (nmol/l) 0.220 3.70 × 10−4 
HDL particles (μmol/l) 0.148 0.017 
 large particles (μmol/l) −0.042 Ns 
 median particles (μmol/l) 0.077 Ns 
 small particles (μmol/l) 0.130 0.037 
VLDL size (nm) 0.158 0.011 
LDL size (nm) −0.129 0.038 
HDL size (nm) −0.137 0.028 
Correlation among PCSK9 (ng/ml) andrP
RLPc (mg/dl) 0.171 0.006 
Non-HDLc (mmol/l) 0.213 0.001 
VLDL and Chylo particles (nmol/l) 0.079 Ns 
 large particles (nmol/l) 0.210 0.001 
 median particles (nmol/l) 0.048 Ns 
 small particles (nmol/l) 0.018 Ns 
IDL 0.206 0.001 
LDL particles (nmol/l) 0.257 2.75 × 10−5 
 large particles (nmol/l) −0.039 Ns 
 small particles (nmol/l) 0.224 2.70 × 10−4 
 median small particles (nmol/l) 0.235 1.39 × 10−4 
 very small particles (nmol/l) 0.220 3.70 × 10−4 
HDL particles (μmol/l) 0.148 0.017 
 large particles (μmol/l) −0.042 Ns 
 median particles (μmol/l) 0.077 Ns 
 small particles (μmol/l) 0.130 0.037 
VLDL size (nm) 0.158 0.011 
LDL size (nm) −0.129 0.038 
HDL size (nm) −0.137 0.028 

Adjusted by age, gender and BMI.

Circulating PCSK9, lipids and lipoproteins

Plasma PCSK9 levels were significantly and positively correlated with TG (r=0.136, P=0.033), total cholesterol (r=0.219, P<0.001) and apoB (r=0.226, P=0.006) circulating levels, after adjustment for age, gender and BMI.

We evaluated the correlation between circulating PCSK9 levels and the lipoprotein profile in our patients with metabolic disturbances (n=267) and found that PCSK9 levels were significantly correlated with an atherogenic lipoprotein profile involving lipoprotein subclasses in the different fractions (i.e., VLDL, LDL and HDL subclasses determined by NMR) (Table 2). In more detail, circulating PCSK9 levels were positively correlated with VLDL particles, specifically with large VLDL particles, (r=0.210, P=0.001) and also with their remnants, the IDL particles (r=0.206, P=0.001). The small LDL particles were also positively correlated with the PCSK9 levels (for small LDL: r=0.224, P<0.001; for medium small LDL: r=0.235, P<0.001; and for very small LDL: r=0.220, P<0.001). The PCSK9 levels were also positively correlated with HDL particles (r=0.146, P<0.001), which is mainly explained by a correlation with the smallest HDL particles (r=0.130, P=0.037). In addition, the circulating PCSK9 levels were positively correlated with the pro-atherogenic circulating RLPc levels (r=0.171, P=0.006). All of the correlations were adjusted by age, gender and BMI. We also tested the influence of plasma TG and/or antidiabetic treatment on the correlations adding these variables into the adjustment and the results were comparable to those described above (result not shown).

DISCUSSION

Our aim was to study the relationship between PCSK9 and the lipid and lipoprotein profile; thus, we used a group of diabetic and metabolic syndrome patients and analysed the correlation of circulating PCSK9 levels with a detailed lipoprotein profile measured by NMR.

Similar studies have been conducted recently. Xu et al [12] have described that plasma PCSK9 positively correlates with medium and small LDL particles in patients with coronary artery disease. In a study conducted by Kwakernaak et al. [9], they showed that in a group of people without metabolic or cardiovascular diseases, plasma PCSK9 levels only correlated strongly and positively with IDL particles suggesting that PCSK9 modulates TG metabolism. Another similar study showed that the decrease in PCSK9 due to fenofibrate treatment in type 2 diabetic patients correlates with a decrease in VLDL particle concentrations and the decrease in the different VLDL subclasses [13].

In the present paper, we present a study in a group of patients with metabolic disturbances who were not receiving any lipopenic treatment and found that circulating PCSK9 levels were significantly correlated with the most atherogenic combination of lipoproteins, meaning that they were positively correlated with large VLDL, IDL, the smallest LDL and the smallest HDL particles, as well as with levels of the pro-atherogenic RLPc particles. Therefore, circulating PCSK9 levels were correlated with atherogenic dyslipidaemia in patients with high cardiovascular risk.

This atherogenic lipoprotein profile is a common feature of metabolic disturbances associated with an increased cardiovascular risk, such as diabetes mellitus, insulin resistance, metabolic syndrome and other conditions that are linked to high TG levels [1416]. It is well known that the onset of this atherogenic profile is due to increased fatty acid efflux from adipose tissue, which induces increased synthesis and secretion of TG-rich particles (VLDL) [17]. These VLDLs are larger, contain more TG and possess a greater proportion of apoC-III compared with apoC-II; therefore, the LPL is not normally active and less hydrolysis of TG occurs. The derived particles are poorly recognized by both the LDLR and the LRP (LDLR-related protein), which are responsible for the elimination of these particles from the circulation. This increases the time that these lipoproteins remain in the circulation and allows for the formation of more remnant particles. Due to the actions of CETP (cholesteryl ester transfer protein) and HL (hepatic lipase), these particles become sdLDL. These sdLDL particles are highly susceptible to oxidation and are also atherogenic, as they are associated with at least a 3-fold increase in CHD risk. CETP and HL also promote changes that cause large cholesterol-rich HDL particles to become TG-rich and cholesterol poor; the hydrolysis of TG induces rapid changes that yield much smaller α-HDL particles, which are subject to renal excretion due to their smaller sizes. Therefore, high TG levels are one of the main features of atherogenic dyslipidaemia. PCSK9 has been previously associated with TG metabolism.

In 2005, it was noted that hypercholesterolaemic patients with PCSK9 mutations were somehow different from hypercholesterolaemics without these mutations because of the LDLR defect. Familial hypercholesterolaemia (FH) patients had smaller LDL particles due to PCSK9 mutations and exhibited increased apoB synthesis and increased fasting TG levels [18].

PCSK9 transgenic mice showed higher fasting TG levels and higher VLDL–TG secretion [19] and conversely mice that are deficient in PCSK9 showed reduced postprandial triglyceridaemia [8].

Several studies have shown correlations between circulating PCSK9 and TG levels [13,2024], but not all of the studies showed the same relationship [2528]; in obese non-diabetic patients, with rather normal lipid profile, the circulating PCSK9 levels were not correlated with VLDL–TG secretion, clearance or circulating levels [29], suggesting that the correlation of PCSK9 with atherogenic dyslipidaemia may be restricted to certain metabolic conditions.

Trying to unravel the mechanisms by which PCSK9 may participate in TG metabolism we found some majors obstacles or limitations:

  1. 1.

    In our study, we cannot differentiate between free, LDL-bound or furin-cleaved circulating PCSK9. Whether PCSK9 might have different affinity for different LDL subclasses could also be an interesting question in relation to atherogenic dyslipidaemia.

  2. 2.

    We do not know what proportion of the active circulating PCSK9 binds to other members of the LDLR family [30] more likely to act on TG-rich lipoproteins.

  3. 3.

    In measuring circulating PCSK9, we did not assess the intracellular action of PCSK9 [31] in the liver and, most importantly in relation to TG metabolism, in the intestine [32].

Although specific studies are needed to gain insight into theses aspects, in our opinion the binding of TG-rich lipoproteins to other members of the LDLR family and the role of the intracellular PCSK9 in the process of synthesis and secretion of TG-rich lipoproteins are plausible processes to explain our observations.

Apart from cholesterol and TG, plasma PCSK9 has been associated with multiple metabolic risk factors such as fasting glucose, insulin, HOMA–IR (homoeostatic model assessment–insulin resistance), HDLc and apoA-I and apoB [20,22].

Thus numerous effects on lipid metabolism may be explained in part because PCSK9 apparently has the ability to target other receptors.

The major binding site of PCSK9 to the LDLR involves its catalytic domain, which interacts with epidermal growth factor (EGF)-A present in the extracellular domain of the LDLR. The LDLR family consists of structurally closely related transmembrane proteins and among them VLDL receptor (VLDLR) and apolipoprotein E receptor 2 (APOER2) are the two receptors that are most similar to LDLR [33]. The levels of both receptors were shown to be reduced by PCSK9 [34].

Although APOER2 is mainly present in the brain, VLDLR is highly expressed in the heart, skeletal muscle and adipose tissue.

VLDLR contributes to the delivery of fatty acids derived from TG-rich lipoproteins to peripheral tissues. VLDLR can recognize apolipoprotein E but not apoB, thus VLDLR binds to VLDL and their remnants, the IDL, but not LDL [35].

PCSK9 is mainly expressed in the liver and is expressed at lower levels in the kidney, intestine and brain. The PCSK9 promoter contains an SRE-1 (serum response element 1) motif recognized by SREBP-2 (sterol-regulatory element-binding protein 2) transcription factor; an Sp-1(specificity protein 1) site; and a binding site for HNF-1α (hepatocyte nuclear factor 1 α) [36].

SREBP-2 regulates cellular cholesterol homoeostasis and HNF-1α is a transcription factor that co-operates with SREBP-2 and controls genes involved in cholesterol and bile acid metabolism and regulate genes of acute-phase proteins [37,38].

PCSK9 discovery was shortly followed by the clinical interest in developing strategies as a potential therapeutic target to lower LDLc levels. There are currently different approaches aimed at reducing PCSK9 binding to LDLR and they are summarized in [39]; preliminary results have demonstrated successful reductions in circulating LDLc levels [40,41].

Our findings are of clinical interest because we believe they illustrate a new point of view regarding the role of PCSK9 in atherosclerosis suggesting that PCSK9 inhibition may also be a useful approach in the treatment of atherogenic dyslipidaemia.

Abbreviations

     
  • APOER

    apolipoprotein E receptor

  •  
  • BMI

    body mass index

  •  
  • CETP

    cholesteryl ester transfer protein

  •  
  • CHD

    coronary heart disease

  •  
  • HDL

    high-density lipoprotein

  •  
  • HL

    hepatic lipase

  •  
  • HNF

    hepatocyte nuclear factor

  •  
  • IDL

    intermediate-density lipoprotein

  •  
  • LDL

    low-density lipoprotein

  •  
  • LDLR

    low-density lipoprotein receptor

  •  
  • PCSK9

    proprotein convertase subtilisin/kexin type 9

  •  
  • RLPc

    remnant lipoproteins

  •  
  • sdLDL

    small dense LDL

  •  
  • SREBP

    sterol-regulatory element-binding protein

  •  
  • TG

    triglyceride

  •  
  • VLDL

    very-low density lipoprotein

  •  
  • VLDLR

    VLDL receptor

AUTHOR CONTRIBUTION

Montse Guardiola participated in the study design, data analysis, preparation and critical review of the manuscript. Núria Plana participated in the patient selection and critical review of the manuscript. Daiana Ibarretxe participated in patient selection and in the critical review of the manuscript. Anna Cabré performed biochemical determinations and participated in the critical review of the manuscript. Marta González performed biochemical determinations and critical reviewing of the manuscript. Josep Ribalta participated in the study design, data analysis, preparation and critical review of the manuscript. Lluís Masana participated in the study design, data analysis, preparation and critical review of the manuscript.

FUNDING

This study was supported by CIBER de Diabetes y Enfermedades Metabólicas Asociadas [grant numbers FIS PI11/02216 and FIS PI12/01766].

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