C-reactive protein (CRP) is recognized as a biomarker of chronic, low-grade inflammation associated with vascular disorders. Lately, the role of neutrophils and neutrophil extracellular traps (NETs) has been investigated as a potential source of chronic inflammation and cardiovascular complications. This study investigated NETs as a marker of inflammation in patients with symptomatic heart failure (HF) with or without type 2 diabetes (T2DM) and examined the correlation between NETs and CRP. We performed a noninterventional study including patients with HF with or without T2DM, T2DM, and a healthy control (HC) group. NETs and other inflammatory markers in serum were measured by ELISA. The release of NETs (NETosis) in vitro under various stimuli was measured by confocal microscopy. The levels of NETs in the serum of HF patients were significantly higher compared with HC (112%). Serum CRP concentrations were significantly increased in HF and HF plus T2DM patients compared with HC, and a positive correlation was observed between serum CRP and NETs levels. Neutrophils from HF and HF plus T2DM patients underwent in vitro NETs release faster than T2DM and HC without any stimuli. In vitro, serum collected from the HF and the HF plus T2DM group induced NETosis in healthy neutrophils significantly more when compared with HC and T2DM, which was prevented by depletion from CRP. We confirmed in vitro that CRP induces a concentration-dependent NETs synthesis. This study proposes a mechanism by which CRP increases the risk of future cardiovascular events and supports mounting evidences on the role of neutrophils in chronic low-grade inflammation associated with HF.

Heart failure (HF) is defined as a chronic and progressive condition in which the heart is unable to meet the requirements of metabolizing tissues in a situation of increased demand, such as during exercise. In healthy men and women, the left ventricular ejection fraction (LVEF) ranges from 52 to 74%. Phenotypically, HF can be present with a reduced LVEF (HFrEF) ≤40%, whereas patients with symptoms and signs of HF with LVEF ≥50% are classified as HF with a preserved LVEF (HFpEF). More recently, the European Society of Cardiology has proposed new guidelines for the inclusion of a third type of HF with LVEF between 41 and 49%, named HF with midrange ejection fraction (1, 2). Chronic, low-grade inflammation is one of the major factors impacting the development and progression of HF (3). It also contributes to an increase in a broad range of inflammatory cytokines and biomarkers in both HFrEF and HFpEF (4). Moreover, coexistence of HF with other proinflammatory conditions, such as type 2 diabetes (T2DM) has been associated with an increase of adverse outcomes and mortality (5), both in acute and chronic HFrEF and HFpEF (6). Despite numerous differences in the pathophysiology and the clinical features of these two forms of HF, with or without T2DM, significant relationships between selected inflammatory markers and adverse cardiovascular outcomes have been reported (7).

One of these inflammatory markers and predictors of future cardiovascular events, C-reactive protein (CRP), produced in liver, has been used as a common indicator of both acute infection and subclinical inflammation (3). CRP is increased in patients with chronic stable HF (8), but the mechanisms connecting CRP and the severity of HF remain unknown. Lately, multiple studies are reporting a correlation between CRP and neutrophil counts (9) and an association between increased neutrophil counts and higher prevalence of coronary disease (10), suggesting possible connections between CRP, neutrophils, and progression of cardiovascular disorders. Furthermore, mounting evidence is reporting novel mechanisms by which neutrophils can promote proinflammatory activities through the generation and release of neutrophil extracellular traps (NETs), termed NETosis (11). NETosis occurs primarily through a cell death process, following a nuclear envelope disassembly and nuclear chromatin decondensation into the cytoplasm of intact cells, mixing with cytoplasmic and granule components (12). Under physiological conditions, this process takes 3–8 hours after neutrophil activation (12). However, it has been reported that neutrophils from patients suffering from acute or low-inflammatory pathologic conditions are primed to release NETs; thus, a rapid release of NETs can be observed within minutes under various conditions (1318). NETs are composed of dsDNA decorated with cytosolic and granule-derived proinflammatory cytokines and enzymes (19); their composition depends on the state of neutrophil activation and possible conditions that affect them (e.g., systemic lupus erythematosus, rheumatoid arthritis, cystic fibrosis, and conditions associated with metabolic disorders) (17). One of the unchangeable and obligatory protein components of NETs is myeloperoxidase (MPO) (20). In vasculature, besides their original role as a bacterial traps, NETs can contribute to thrombi formation and vulnerable plaque destabilization (21). Previous studies reported a correlation between CRP and NETs production under hemodialysis (22), rheumatoid arthritis, or sepsis conditions (17, 23). However, there are as yet no studies reporting the relationship between CRP and NETs release in HF patients. Thus, our objectives were to characterize the changes in NETs in patients with HF with or without T2DM and to assess whether there is a link between CRP level and NETs in these patients.

This was a prospective nonrandomized, noninterventional study that included HF patients with reduced ejection fraction (rEF) or preserved ejection fraction (pEF) with or without T2DM and patients diagnosed with T2DM but without any heart pathologic condition. Nineteen patients with HF and 26 patients with HF plus T2DM were recruited at the Montreal Heart Institute (MHI). Twenty-one T2DM patients with no symptoms or signs of HF were recruited from the Clinique d’Endocrinologie de Montréal. The blood collection from all patients (66) and healthy controls (HC; n = 25) was performed at the MHI. This study was approved by the Scientific Research Committee and the Ethics Committee of the MHI (ethics No. ICM #01-406 and No. ICM #12-1374) and conform to the principles outlined in the Declaration of Helsinki. Donors were informed about the procedures and signed a written-informed consent before participating in the study.

HC volunteers recruited in this study were enrolled assuming they were not having any significant medical conditions and were not on any anti-inflammatory medication for at least 14 d before blood collection. All patients with T2DM alone had an HbA1c <10% and undiagnosed for HF conditions. These T2DM patients were controlled by any available hypoglycemic medications and, as per guidelines, were treated with preventive hypertension medication. The characterization and recruitment of HF patients was in concordance with the guidelines set in the Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist clinical trial (24), which was prior to the setting of the new European Society for Cardiology guidelines (1). Therefore, HF patients recruited from the MHI Heart Failure Clinic were classified as HFrEF if their LVEF was ≤40% or HFpEF if their LVEF was ≥45% (2426), as documented by contrast ventriculography, magnetic resonance imaging, radionuclide ventriculography, or quantitative echocardiography within the previous 12 mo if no cardiac event occurred since the measurement of their LVEF (24). In addition to the previous inclusion criteria for the HF patients, the HF plus T2DM patients had also an HbA1c <10% and were controlled by any available hypoglycemic medications and, as per guidelines, were treated with preventive hypertension medication. HF patients had a New York Heart Association (NYHA) functional class II or III and, unless contraindicated, were treated with an angiotensin-converting enzyme inhibitor or with angiotensin II receptor blockers and stable doses of β-blockers for at least 30 d. Patients with severe chronic pulmonary disease, chronic active inflammatory disease, severe renal failure (creatinine >250 μmol/l), liver dysfunction (transaminases ≥3-fold upper normal values), and ongoing cancer malignancy were not eligible for the study. HF patients with or without T2DM, T2DM patients, and HC having ongoing and/or recent infection (within 2 wk prior to the study, as this would affect neutrophil counts) or had CRP values higher than 15 mg/l (suggesting potential acute unrelated inflammatory state) were excluded from this study. Other exclusion factors were as follows: recent myocardial infarction, recent stroke, HF functional NYHA class IV, unstable clinical condition, and recent open-heart surgery.

Venous blood samples (20 ml) were obtained from HC, T2DM patients, and HF patients with or without T2DM in Vacutainer serum separation tubes. Upon centrifugation (1000 × g for 15 min) at least 3 ml of serum was collected, aliquoted, and frozen at −80°C. Another 25 ml sample of venous blood was mixed with Anticoagulant Citrate Dextrose Solution USP Formula A (MP Biomedicals, Solon, OH). Neutrophils were isolated and resuspended in RPMI medium supplemented with 25 mM HEPES and 1% penicillin/streptomycin, as described previously (27). Contamination with PBMCs was <0.1% as determined by morphological analysis and flow cytometry (data not shown), and viability was >98% (trypan blue dye exclusion) (27). Pure neutrophil population was used for all in vitro studies.

As NETs are defined as chromatin bound to MPO, for their detection in serum, an ELISA method that detects exclusively MPO-bound DNA complexes in serum samples was used, and results were analyzed by comparison of OD values between groups, as previously described (28). The biomarkers IL-6 and MPO were quantified by ELISA kits (Bio-Techne, Minneapolis, MN). High-sensitivity CRP (hsCRP) in serum samples was quantified by nephelometry at the biochemistry laboratory at the MHI.

Neutrophils (1 × 106 cells per ml) in RPMI medium were incubated at 37°C, 5% CO2 for 15 or 60 min with different agonists: PBS and Tris (control buffer solutions), homopentamer recombinant human CRP (rhCRP; 1, 5, and 10 mg/l) (R&D Systems, Minneapolis, MN), IL-8 (25 nM, positive control) (PeproTech, Rocky Hill, NJ), blood serum collected from volunteers (HC, T2DM patients, HF patients, and HF patients with T2DM) and CRP-depleted serums from HF patients and HF patients with T2DM. Green-fluorescent nuclear and chromosome counterstain that is nonpermeable to live cells (SYTOX Green, 1 μM; Life Technologies, Burlington, ON, Canada) was then added to detect dsDNA NETs released by neutrophils. Images were obtained by confocal microscopy (LSM 710; Carl Zeiss, Toronto, ON, Canada) and set to acquire a mosaic of pictures (5 × 5 images) (Zen 2; Carl Zeiss) (magnification, 200×). To calculate the percentage of total area of image covered by NETs, an algorithm in Image-Pro Plus 7 (Media Cybernetics, Rockville, MD) was used, and a threshold to exclude low-fluorescence background was applied (27).

Serum CRP depletion was performed by using agarose-coated beads with immobilized phosphorylcholine with specific affinity for CRP (Life Technologies) (29). As negative control, serum aliquots were treated with noncoated agarose beads. As per protocol, after 30 min of incubation, the beads were centrifuged and hsCRP content in the depleted serum was analyzed by nephelometry at the biochemistry laboratory at the MHI. Incubation with phosphorylcholine-coated beads produced serum depleted of CRP (values <0.16 mg/l), whereas agarose beads had no effect on CRP values.

Any differences in variables between HC, T2DM patients, and the HF with or without T2DM population were evaluated using a one-way ANOVA followed by a Dunnett post hoc test. The relations between variables were assessed by using Pearson regression analyses. Differences between groups for in vitro studies were compared using a one-way ANOVA or a paired Student t test (for neutrophil response to CRP and CRP-depleted serum). Statistical significance was set at p < 0.05. All analyses were performed using SPSS for Windows.

Ninety-one volunteers were enrolled in this study. A total of 45 patients with HF NYHA functional class II to III were studied; 34 (75.6%) of them were having rEF with or without T2DM. Baseline demographics and clinical characteristics are summarized in Table I. The group of patients with HF with or without T2DM was significantly older than the HC group. However, we performed a Pearson correlation analysis that showed no correlation between NETs concentration in serum and aging (p = 0.196) in this population.

Table I.
Baseline patient characteristics
Control Group (n = 25)T2DM Group (n = 21)HF Group (n = 19)HF with T2DM Group (n = 26)p Value
Age (y) 58.4 ± 1.6 62.0 ± 1.0 66.4 ± 1.1 67.8 ± 1.2 p ≤ 0.03 
Males n (%) 18 (72) 19 (90.5) 12 (63.2) 19 (73.1) NS 
NYHA classification n (%)      
 Class II 15 (78.9) 19 (73.1)  
 Class III 4 (21.1) 7 (26.9)  
LVEF n (%) 30.4 ± 3 36.8 ± 2.5  
rEF n (%) 15 (78.9) 19 (73.1)  
pEF n (%) 4 (21.1) 7 (26.9)  
Ischemic HF n (%) 9 (47.4) 15 (57.7)  
Nonischemic HF n (%)   10 (52.6) 11 (42.3)  
Cardiomyopathy n (%) 3 (15.8) 1 (3.9)  
Valvular n (%) 3 (15.8) 3 (11.6)  
Others n (%) 4 (21.1) 7 (26.9)  
Medical conditions n (%)      
 Hypertension 8 (38.1) 15 (78.9) 10 (38.5) p = 0.006 
 Dyslipidemia 9 (43.0) 15 (78.9) 19 (73.1)  
 Stroke 0 (0) 5 (26.4) 9 (34.6)  
 Chronic kidney disease 3 (14.3) 5 (26.4) 10 (38.5)  
Treatment n (%)      
 ACEi 8 (38.1) 3 (15.8) 9 (34.6)  
 ARBs 5 (23.8) 12 (63.2) 13 (50)  
 β-blockers 4 (19.1) 18 (94.7) 26 (100)  
 Diuretic agent 2 (9.5) 16 (84.2) 26 (100)  
 Statin 6 (24) 17 (81) 16 (84.2) 21 (80.8)  
 Anticoagulant 1 (4) 0 (0) 8 (42.1) 15 (57.7)  
 Sulfonylureas 5 (23.8) 7 (26.9)  
 DPP-4 inhibitor 9 (42.9) 8 (42.1) 12 (46.2)  
 α-Glucosidase inhibitors 1 (4.8) 4 (21.1) 8 (30.8)  
 Agonists GLP-1 3 (14.3)  
 SGLT2 inhibitor 5 (23.8)  
 Metformin 18 (85.7) 5 (19.2)  
 Insulin 7 (33.3) 4 (15.4)  
Creatinine (μmol/l) 78.5 79.4 126.4 125.8 p < 0.001 
Glucose (mmol/l) 5.25 8.60 6.64 9.40 p < 0.001 
Cholesterol (mmol/l) 4.97 3.52 3.63 3.10 NS 
Triglyceride (mmol/l) 1.79 1.57 1.56 1.93 NS 
LDL (mmol/l) 3.10 1.75 201 1.54 NS 
Control Group (n = 25)T2DM Group (n = 21)HF Group (n = 19)HF with T2DM Group (n = 26)p Value
Age (y) 58.4 ± 1.6 62.0 ± 1.0 66.4 ± 1.1 67.8 ± 1.2 p ≤ 0.03 
Males n (%) 18 (72) 19 (90.5) 12 (63.2) 19 (73.1) NS 
NYHA classification n (%)      
 Class II 15 (78.9) 19 (73.1)  
 Class III 4 (21.1) 7 (26.9)  
LVEF n (%) 30.4 ± 3 36.8 ± 2.5  
rEF n (%) 15 (78.9) 19 (73.1)  
pEF n (%) 4 (21.1) 7 (26.9)  
Ischemic HF n (%) 9 (47.4) 15 (57.7)  
Nonischemic HF n (%)   10 (52.6) 11 (42.3)  
Cardiomyopathy n (%) 3 (15.8) 1 (3.9)  
Valvular n (%) 3 (15.8) 3 (11.6)  
Others n (%) 4 (21.1) 7 (26.9)  
Medical conditions n (%)      
 Hypertension 8 (38.1) 15 (78.9) 10 (38.5) p = 0.006 
 Dyslipidemia 9 (43.0) 15 (78.9) 19 (73.1)  
 Stroke 0 (0) 5 (26.4) 9 (34.6)  
 Chronic kidney disease 3 (14.3) 5 (26.4) 10 (38.5)  
Treatment n (%)      
 ACEi 8 (38.1) 3 (15.8) 9 (34.6)  
 ARBs 5 (23.8) 12 (63.2) 13 (50)  
 β-blockers 4 (19.1) 18 (94.7) 26 (100)  
 Diuretic agent 2 (9.5) 16 (84.2) 26 (100)  
 Statin 6 (24) 17 (81) 16 (84.2) 21 (80.8)  
 Anticoagulant 1 (4) 0 (0) 8 (42.1) 15 (57.7)  
 Sulfonylureas 5 (23.8) 7 (26.9)  
 DPP-4 inhibitor 9 (42.9) 8 (42.1) 12 (46.2)  
 α-Glucosidase inhibitors 1 (4.8) 4 (21.1) 8 (30.8)  
 Agonists GLP-1 3 (14.3)  
 SGLT2 inhibitor 5 (23.8)  
 Metformin 18 (85.7) 5 (19.2)  
 Insulin 7 (33.3) 4 (15.4)  
Creatinine (μmol/l) 78.5 79.4 126.4 125.8 p < 0.001 
Glucose (mmol/l) 5.25 8.60 6.64 9.40 p < 0.001 
Cholesterol (mmol/l) 4.97 3.52 3.63 3.10 NS 
Triglyceride (mmol/l) 1.79 1.57 1.56 1.93 NS 
LDL (mmol/l) 3.10 1.75 201 1.54 NS 

Values are mean ± SE or percentage.

ACEi, angiotensin-converting enzyme; ARBs, angiotensin receptor blocker; DPP-4 inhibitor, dipeptidyl peptidase-4 inhibitor; GLP-1, glucagon-like peptide 1; SGLT2, sodium/glucose cotransporter 2.

We performed a time-dependent study to assess the optimal time needed for the release of NETs from patients with T2DM, HF, and HF with T2DM as compared with HC. In that study, we were able to test whether low-grade inflammation present in patients with T2DM and/or HF prompts neutrophils to undergo NETosis. In our study, we observed by confocal microscopy that neutrophils from patients with T2DM, HF, and HF with T2DM were already capable of promoting a significant release of NETs as compared with HC within 15–60 min postisolation (representative images in Fig. 1a–d). Neutrophils isolated from all three patient groups (T2DM, HF, and HF with T2DM) under basal condition increased NETs synthesis within 15 min by 5.5-, 6.2-, and 7.4-fold, respectively, as compared with HC (Fig. 1e for HF and HF with T2DM, p ≤ 0.04). After 60 min, NETosis was increased by 2.2-, 3.6-, and 4.1-fold in patients with T2DM, HF, and HF with T2DM, respectively (Fig. 1e for HF and HF with T2DM, p ≤ 0.02).

FIGURE 1.

NETs release by neutrophils.

Neutrophils from patients with T2DM and HF with T2DM are preconditioned to produce NETs as compared with neutrophils from HC. Representative pictures of NETs release at 60 min from the following groups: (a) HC, (b) T2DM, (c) HF and (d) HF with T2DM neutrophils. Neutrophils are labeled with wheat germ agglutinin (conjugated with Alexa 647; red) and NETs are labeled with SYTOX Green (green). Neutrophils collected from all three patient groups showed increased tendency for NETs release at 15 and 60 min. Data shown as mean ± SEM (n = 6–7 for each group, including HC). *p ≤ 0.04 (e).

FIGURE 1.

NETs release by neutrophils.

Neutrophils from patients with T2DM and HF with T2DM are preconditioned to produce NETs as compared with neutrophils from HC. Representative pictures of NETs release at 60 min from the following groups: (a) HC, (b) T2DM, (c) HF and (d) HF with T2DM neutrophils. Neutrophils are labeled with wheat germ agglutinin (conjugated with Alexa 647; red) and NETs are labeled with SYTOX Green (green). Neutrophils collected from all three patient groups showed increased tendency for NETs release at 15 and 60 min. Data shown as mean ± SEM (n = 6–7 for each group, including HC). *p ≤ 0.04 (e).

Close modal

The levels of NETs in serum from HF patients were significantly higher than in HC (2.12-fold, p = 0.011), whereas patients with T2DM and HF with T2DM had 1.61- and 1.58-fold increase compared with HC (Fig. 2a, p = 0.16). Our data showed a significant increase of MPO levels (both chromatin bound and free) in both HF patients and patients with HF with T2DM groups (Fig. 2b, p ≤ 0.011) but not in T2DM patients, compared with HC (p = 0.14). All three patient groups had a significant increase of IL-6, whereas IL-6 (except for one healthy volunteer) was below the minimum detectable concentration in the HC group (Fig. 2c, p ≤ 0.026). CRP levels of all three patient groups were also significantly increased (Fig. 2d, p ≤ 0.039 compared with HC).

FIGURE 2.

Measures of inflammatory markers in the serum.

Serum from all three patient groups was analyzed by ELISA for the presence of NETs, MPO, and IL-6 and by nephelometry for hsCRP. (a) NETs from HF patients were increased compared with HC, *p = 0.015. (b) The concentration of MPO in the HF and HF with T2DM serum was increased compared with HC, *p ≤ 0.012, whereas (c) IL-6 and (d) CRP concentrations in all three groups were increased when compared with HC, *p ≤ 0.025; (n = 25 for HC, n = 21 for T2DM, n = 19 for HF, and n = 26 for HF with T2DM for NETs and CRP; n = 14–18 in each group for MPO and n = 8–11 in each group for IL-6).

FIGURE 2.

Measures of inflammatory markers in the serum.

Serum from all three patient groups was analyzed by ELISA for the presence of NETs, MPO, and IL-6 and by nephelometry for hsCRP. (a) NETs from HF patients were increased compared with HC, *p = 0.015. (b) The concentration of MPO in the HF and HF with T2DM serum was increased compared with HC, *p ≤ 0.012, whereas (c) IL-6 and (d) CRP concentrations in all three groups were increased when compared with HC, *p ≤ 0.025; (n = 25 for HC, n = 21 for T2DM, n = 19 for HF, and n = 26 for HF with T2DM for NETs and CRP; n = 14–18 in each group for MPO and n = 8–11 in each group for IL-6).

Close modal

The presence of NETs in serum positively correlated with CRP (Fig. 3a, p = 0.033) and MPO levels (Fig. 3b, p = 0.003). IL-6 (Fig. 3c, p = 0.234) and NETs had no correlation, but IL-6 was positively correlated with CRP (Fig. 3d, p = 0.039).

FIGURE 3.

Correlation between proinflammatory cytokines and NETs in serum.

A significant positive correlation (Pearson regression) was found between NETs and CRP (a), NETs and MPO (b), CRP and IL-6 (d), and no correlation was found between NETs and IL-6 (c).

FIGURE 3.

Correlation between proinflammatory cytokines and NETs in serum.

A significant positive correlation (Pearson regression) was found between NETs and CRP (a), NETs and MPO (b), CRP and IL-6 (d), and no correlation was found between NETs and IL-6 (c).

Close modal

Examining the results of NETs content in the serum and the correlation between CRP and NETs in all three patient groups prompted us to differently regroup the collected data on NETs in serum. By grouping the patients and HC based on their serum CRP levels into three different categories (e.g., <1, 1–3, and >3 mg/l), we found a new perspective of the CRP–NETs correlation. The group with CRP levels between 1 and 3 mg/l had a significant increase in NETs content (Fig. 4, Table II, p = 0.011). The increase in IL-6 was significant (p = 0.034), whereas the ST2 increase was noticeable but NS (Table II, p = 0.39), and there was no significant rise in total MPO (Table II). The group with a CRP concentration >3 mg/l, besides having an increase in NETs serum level (Fig. 4, p = 0.015), had an increase in all analyzed inflammatory markers (Table II, IL-6 and MPO, p < 0.001 and p = 0.034, respectively) more comorbidities (e.g., previous occurrence of stroke, renal disease, pulmonary hypertension, and previous history of gout), higher fasting glucose and low-density lipoprotein (LDL), and higher levels of ST2, a protein biomarker of cardiac stress (Table II).

FIGURE 4.

Relationship between the levels of NETs and CRP in serum.

The concentration of NETs in serum is increased in patients with CRP levels >1 mg/l as compared with low CRP levels (<1 mg/l) (n = 25 in the CRP <1 mg/l, n = 35 in the CRP = 1–3 mg/l, and n = 31 in the CRP >3 mg/l groups, respectively). *p ≤ 0.015.

FIGURE 4.

Relationship between the levels of NETs and CRP in serum.

The concentration of NETs in serum is increased in patients with CRP levels >1 mg/l as compared with low CRP levels (<1 mg/l) (n = 25 in the CRP <1 mg/l, n = 35 in the CRP = 1–3 mg/l, and n = 31 in the CRP >3 mg/l groups, respectively). *p ≤ 0.015.

Close modal
Table II.
Characteristics of populations based on the CRP level
CRP < 1 mg/l (n = 25)CRP = 1–3 mg/l (n = 35)CRP > 3 mg/l (n = 31)p Value
NETs (OD) 0.079 ± 0.010 0.160 ± 0.022 0.158 ± 0.026 p ≤ 0.015 
CRP (mg/l) 0.65 ± 0.06 1.94 ± 0.10 7.18 ± 0.61 p ≤ 0.016 
MPO (ng/ml) 292.1 ± 33.0 311.0 ± 32 411.8 ± 48.3 p = 0.034 
IL-6 (pg/ml) 1.74 ± 0.51 4.77 ± 0.57 p = 0.0001 
ST2 (ng/ml) 22.0 ± 1.8 31.1 ± 4.8 58.0 ± 15.6 p = 0.045 
Creatinine (mmol/l) 90.0 ± 3 100.4 ± 6.6 126.1 ± 10 p = 0.002 
Fasting glucose (mmol/l) 6.34 ± 0.53 7.12 ± 0.43 7.77 ± 0.47 p = 0.036 
Total cholesterol (mmol/l) 4.49 ± 0.28 3.85 ± 0.17 3.26 ± 0.19 p = 0.001 
LDL (mmol/l) 2.66 ± 0.27 2.11 ± 0.16 1.65 ± 0.14 p = 0.001 
Triglycerides (mmol/l) 1.80 ± 0.15 1.81 ± 0.17 1.58 ± 0.15  
Statins (%) 11 (44) 16 (45.7) 21 (67.7)  
Comorbidity n (%) 4 (16) 16 (45.7) 16 (51.6) p = 0.005 
Age (y) 60.2 ± 1.6 65.6 ± 2 65.6 ± 2  
Sex: male n (%) 21 (84) 24 (68.6) 23 (74.2)  
HC n (%) 15 (60) 9 (25.7) 1 (3.2)  
T2DM n (%) 3 (12) 12 (34.3) 6 (19.4)  
HF n (%) 3 (12) 8 (22.9) 8 (25.8)  
HF with T2DM n (%) 4 (16) 6 (17.1) 16 (51.6)  
CRP < 1 mg/l (n = 25)CRP = 1–3 mg/l (n = 35)CRP > 3 mg/l (n = 31)p Value
NETs (OD) 0.079 ± 0.010 0.160 ± 0.022 0.158 ± 0.026 p ≤ 0.015 
CRP (mg/l) 0.65 ± 0.06 1.94 ± 0.10 7.18 ± 0.61 p ≤ 0.016 
MPO (ng/ml) 292.1 ± 33.0 311.0 ± 32 411.8 ± 48.3 p = 0.034 
IL-6 (pg/ml) 1.74 ± 0.51 4.77 ± 0.57 p = 0.0001 
ST2 (ng/ml) 22.0 ± 1.8 31.1 ± 4.8 58.0 ± 15.6 p = 0.045 
Creatinine (mmol/l) 90.0 ± 3 100.4 ± 6.6 126.1 ± 10 p = 0.002 
Fasting glucose (mmol/l) 6.34 ± 0.53 7.12 ± 0.43 7.77 ± 0.47 p = 0.036 
Total cholesterol (mmol/l) 4.49 ± 0.28 3.85 ± 0.17 3.26 ± 0.19 p = 0.001 
LDL (mmol/l) 2.66 ± 0.27 2.11 ± 0.16 1.65 ± 0.14 p = 0.001 
Triglycerides (mmol/l) 1.80 ± 0.15 1.81 ± 0.17 1.58 ± 0.15  
Statins (%) 11 (44) 16 (45.7) 21 (67.7)  
Comorbidity n (%) 4 (16) 16 (45.7) 16 (51.6) p = 0.005 
Age (y) 60.2 ± 1.6 65.6 ± 2 65.6 ± 2  
Sex: male n (%) 21 (84) 24 (68.6) 23 (74.2)  
HC n (%) 15 (60) 9 (25.7) 1 (3.2)  
T2DM n (%) 3 (12) 12 (34.3) 6 (19.4)  
HF n (%) 3 (12) 8 (22.9) 8 (25.8)  
HF with T2DM n (%) 4 (16) 6 (17.1) 16 (51.6)  

Values are mean ± SE or percentage.

ST2, cardiac damage biomarker.

Neutrophils from HC were exposed to PBS (basal control) and four types of serum (HC, T2DM, HF and HF with T2DM) for 60 min and observed by confocal microscopy (representative images Fig. 5a–e). Serum from HF and HF with T2DM patients significantly augmented NETosis by 3.68- and 4.58-fold, respectively (Fig. 5f, p ≤ 0.03). The serums of HC and T2DM patients increased (but nonsignificantly) the release of NETs by 1.95- (p = 0.33) and 2.88-fold (p = 0.06), respectively (Fig. 5f).

FIGURE 5.

NETs release by neutrophils in presence of serum.

Neutrophils were incubated for 60 min with serum from all three patient groups (T2DM, HF, HF with T2DM) and from HC (ae). A significant increase of NETs release was observed with the serum from HF and HF with T2DM (f). Data shown as mean ± SEM (n = 7). *p ≤ 0.03 as compared with PBS.

FIGURE 5.

NETs release by neutrophils in presence of serum.

Neutrophils were incubated for 60 min with serum from all three patient groups (T2DM, HF, HF with T2DM) and from HC (ae). A significant increase of NETs release was observed with the serum from HF and HF with T2DM (f). Data shown as mean ± SEM (n = 7). *p ≤ 0.03 as compared with PBS.

Close modal

Using the serum from HF and HF with T2DM patients with CRP values of ≈4 ± 1 mg/l, we tested if the CRP found in the serum is a possible inducer of NETosis. The same serum sample but CRP depleted (<0.16 mg/l minimal detectable value) was used at the same time and on the same HC neutrophils to induce NETosis (Fig. 6a). Serum containing more than 4 mg/l of CRP significantly increased NETosis, (Fig. 6a, p ≤ 0.04), whereas CRP-depleted serum had no effect.

FIGURE 6.

CRP is an essential serum element for NETosis induction.

Neutrophils were treated for 60 min with controls (PBS, PBS plus CRP-depletion beads, and PBS plus agarose beads) with serums from patients (CRP ≈4 mg/l), matched CRP-depleted serums (CRP <0.16 mg/l), and matched serums (CRP ≈4 mg/l) with control agarose beads (a). The serums from patients (CRP ≈4 mg/l) and matched serums (CRP ≈4 mg/l) with control beads significantly increased NETosis, *p ≤ 0.04 compared with PBS, whereas matched CRP-depleted serums (CRP <0.16 mg/l) were unable to increase NETs release (a). In another set of experiments, neutrophils were incubated with control vehicles (PBS and Tris buffer) for 60 min, IL-8 (25 nM; positive control), and rhCRP (1, 5, 10 mg/l). At the highest concentration, rhCRP induced a significant increase in NETs release (b), *p ≤ 0.025 compared with PBS. Data shown as mean ± SEM (n = 6–7 for each group, including HC).

FIGURE 6.

CRP is an essential serum element for NETosis induction.

Neutrophils were treated for 60 min with controls (PBS, PBS plus CRP-depletion beads, and PBS plus agarose beads) with serums from patients (CRP ≈4 mg/l), matched CRP-depleted serums (CRP <0.16 mg/l), and matched serums (CRP ≈4 mg/l) with control agarose beads (a). The serums from patients (CRP ≈4 mg/l) and matched serums (CRP ≈4 mg/l) with control beads significantly increased NETosis, *p ≤ 0.04 compared with PBS, whereas matched CRP-depleted serums (CRP <0.16 mg/l) were unable to increase NETs release (a). In another set of experiments, neutrophils were incubated with control vehicles (PBS and Tris buffer) for 60 min, IL-8 (25 nM; positive control), and rhCRP (1, 5, 10 mg/l). At the highest concentration, rhCRP induced a significant increase in NETs release (b), *p ≤ 0.025 compared with PBS. Data shown as mean ± SEM (n = 6–7 for each group, including HC).

Close modal

To demonstrate that CRP has a direct capacity to induce NETs release, neutrophils from HC were treated for 60 min with rhCRP (1, 5, and 10 mg/l), which is comparable to the range of CRP concentrations observed in donors’ blood (HC and patients). rhCRP induced NETosis in a concentration-dependent manner. At the lowest rhCRP concentration (1 mg/l), as observed in healthy individuals, NETosis was increased by 1.5-fold, whereas at 5 mg/l, NETosis was increased by 2.5-fold, and a treatment with 10 mg/l significantly increased NETosis up to 3.5-fold (Fig. 6b, p ≤ 0.025). In addition, we observed that rhCRP (10 mg/l) was as potent as IL-8 (25 nM), a known inducer of NETosis (30) (Fig. 6b). Together, our results are summarized in an illustration showing how HF and diabetes are leading to NETs formation (Fig. 7).

FIGURE 7.

Proposed schematic illustration on the role of CRP in the induction of NETosis and its implication in HF and diabetes.

HF and/or T2DM are marked by low-grade inflammation that increases concentration of inflammatory proteins in serum including IL-6 and CRP. IL-6 will increase hepatic CRP release in the bloodstream, which, in turn, activates neutrophils to induce NETosis, leading to further aggravated vasculature injury and associated cardiovascular events.

FIGURE 7.

Proposed schematic illustration on the role of CRP in the induction of NETosis and its implication in HF and diabetes.

HF and/or T2DM are marked by low-grade inflammation that increases concentration of inflammatory proteins in serum including IL-6 and CRP. IL-6 will increase hepatic CRP release in the bloodstream, which, in turn, activates neutrophils to induce NETosis, leading to further aggravated vasculature injury and associated cardiovascular events.

Close modal

In the current study we observed that patients with HF and/or T2DM who have higher CRP levels in their serum also have higher NETs concentration, and their neutrophils are primed to synthesize NETs in vitro even in absence of stimulation. We also observed that a treatment with the serums from these patients is capable of promoting NETosis in HC neutrophils, and this latter effect was lost when the serums were depleted from CRP. Finally, we also experimentally confirmed the in vitro capacity of rhCRP to promote NETosis. Our study provides, to our knowledge, the first evidence that CRP is a direct inducer of NETosis and that elevated serum concentration of CRP participates in NETs formation.

It has been demonstrated that neutrophils are not just first responders to acute infections but also active contributors to low-grade chronic inflammation (31), which can be explained, in part, by their capacity to release NETs (32). Despite growing evidences that various pathological conditions prime neutrophils for NETosis (17), the prognostic value of NETs release in serum is still debatable (33, 34). However, NETs can be considered as a risk factor of future cardiovascular events because of their role in atherosclerosis, inflammation, and thrombosis in small blood vessels (17, 22, 35, 36).

Previous findings reported a circulating increase of NETs in T2DM patients (37) and that local stimuli affect spontaneous NETosis in isolated neutrophils from diabetic patients (18). In contrast, Miyoshi et al. (38) reported a nonsignificant increase in circulating NETs from well-controlled T2DM patients when compared with HC. In their study, when the authors separated the T2DM cohort in two distinct groups (<3 antidiabetes drugs or ≥3 antidiabetes drugs), they did observe a significant increase of circulating NETs in the serum of patients taking ≥3 antidiabetes drugs. In another study, it has also been reported that circulating NETs concentration is significantly increased in newly diagnosed/uncontrolled diabetic patients that returned to nonsignificant increase within 12 mo posttreatment on metformin (39). In our study, we observed a trend but nonsignificant increase of circulating NETs in a cohort of well-controlled T2DM patients. Together, these data suggest that, depending on the glycemic status, medication, and treatment duration since T2DM diagnosis (3739), the increase of circulating NETs can fluctuate from significant to nonsignificant.

To our knowledge, our study is the first one to report a significant increase of NETs levels in the serum of HF patients. As T2DM is a common comorbidity factor in HF patients with a significant negative impact of prognosis (40), as well as higher mortality rates among patients with HF with T2DM compared with HF alone (41), we assessed the comorbidity effect of T2DM on the release of NETs in HF patients. Although, we did not observe an increase of NETs levels in the serum of HF with T2DM patients as compared with HF alone, we did observe an increasing trend on the release of NETs from the isolated neutrophils of HF with T2DM patients as compared with HF alone. CRP is one of the early markers of inflammation, and it is used to predict the likelihood of developing cardiovascular events (42) and coronary disease progression (43). Patients at risk for future vascular events present stable elevations of CRP over time, probably because of sustained vascular inflammation (44). Based on the study from Pearson et al. (45), it has been recommended by the Centers of Disease Control and Prevention/American Heart Association, to categorize patients as low- (<1 mg/l CRP), mid- (1–3 mg/l CRP), or high-risk (>3 mg/l CRP) for cardiovascular events, and an inflammatory status was set for CRP values ≥3 mg/l (45, 46). In our study, in each of the three patient groups (T2DM, HF, and HF with T2DM), 50% of them had CRP serum levels higher than 3 mg/l, even in absence of any acute inflammatory condition. In all four groups (T2DM, HF, HF with T2DM, and HC), we observed a correlation between the levels of NETs and CRP concentration. Therefore, we used CRP risk classification (low, mid and high) to assess its effect on NETs synthesis. The two groups with CRP levels in the mid- and high-risk range had a significant increase of NETs in serum. Surprisingly, the group with CRP >3 mg/l had lower cholesterol, LDL, and triglyceride levels compared with the other two groups. This can be explained by lipid-lowering treatment routinely prescribed to T2DM and cardiovascular disease patients. Despite these treatments, there was an increase in MPO and IL-6 serum concentrations in the group with CRP >3 mg/l as well as NETs.

The correlation between MPO and NETs concentrations was expected, as both increase upon neutrophil activation (17). MPO serum levels are characterized by pro-oxidative and proinflammatory properties and correlate with CRP levels and WBC count (47). T2DM is associated with a mild increase of MPO independent of other clinical variables, but MPO has been shown as an influential factor in the progression of cardiovascular disease among these patients (48). We selected T2DM patients with stable and controlled glycaemia and without diagnosed heart conditions, which reflected in a nonsignificant MPO and NETs increase in the serum. Similarly, the basal activation of healthy neutrophils tested in vitro was not exacerbated by the serum of T2DM patients.

All three groups of patients in our study had significant increases in IL-6 levels. Besides being the primary cytokine promoting hepatic CRP production, IL-6 can lead to cardiomyocytes hypertrophy, myocardial dysfunction, and muscle wasting (49). Increased IL-6 concentrations have been previously shown in the circulation of HF and T2DM patients (50). Although, in our study, it did not correlate directly with NETs content in serum, the indirect relationship can be assumed through induction of CRP produced in the liver.

As it was previously described, elevated levels of ST2 (biomarker of cardiac stress) at baseline and follow-up were shown to be associated with an increased risk of adverse clinical events (39, 40). In our study, a random selection of serum collected from each group of volunteers was tested for ST2, and the average value in the group with CRP concentration >3 mg/l was above the diagnostic cut-off value for chronic HF (>35 ng/ml) (39).

In addition to its predictive role in determining cardiovascular risk, there is evidence that CRP might serve as an active participant in atherogenesis, as it is detected in human atherosclerotic plaques (51). Our study proposes an additional mechanism by which CRP is directly involved in NETosis, which is itself more accepted as a cause of cardiovascular complications. Recently, Martinod et al. (52) proposed a role for NETs in age-related cardiac fibrosis in mice, but such a study has not yet been conducted in humans. Furthermore, “netting” neutrophils may play important roles in the promotion of atherosclerosis, vasculitis of different aetiologies, and other vascular disorders (17, 22).

To further validate whether the CRP contained in the serum plays a role in NETs release, we treated neutrophils with CRP-depleted serums, showing that they lost their capacity to induce NETosis. We also showed that rhCRP induces NETosis in a concentration-dependent manner. In addition, to our knowledge, our novel finding that CRP can promote NETosis, other studies have reported the capacity of CRP to induce neutrophil phagocytosis, motility, and binding to endothelium (53, 54). Together these data reinforce the notion that CRP is not simply a predictive biomarker of inflammation but also a proinflammatory agonist acting likely through its binding capacity onto FcγR expressed on neutrophils (5457). Forthcoming studies will be needed to better delineate the cellular mechanisms involved in CRP-mediated NETosis.

In summary, our study proposes, to our knowledge, a novel mechanism by which CRP may increase the risk of cardiovascular events in these high-risk patients through NETs induction. In this study, we report that neutrophils can respond to chronic inflammatory cytokines and can have a damaging effect on the overall inflammatory state (Fig. 7). Further studies that will examine the relationship of anti-inflammatory therapies aiming to reduce CRP levels and changes in NETosis are needed.

This is a small observational study with the primary goal to assess the effects of chronic inflammation in patients with HF and/or T2DM on neutrophil activation. No discrimination was made between HFrEF and HFpEF. Despite their different phenotypes, the increase of inflammatory biomarkers has been reported in both conditions. Nevertheless, additional studies are needed to define the role of CRP and NETs in both forms of HF (4). As detailed earlier, although there is significant difference between the age of HC and patients with HF with T2DM, this did not affect the correlation between NETs and CRP or other inflammatory markers.

We are thankful to the volunteers for kindly providing blood samples and to Louis Villeneuve for confocal microscopy technical support.

This work was supported by grants from the Canadian Institutes of Health Research (MOP-97943 to M.G.S.), Fonds de Recherche du Québec - Santé (FRQS) - Research Network on Cardiometabolic Health, Diabetes and Obesity (to M.W., A.R., and M.G.S.), and Fondation de l’Institut de Cardiologie de Montréal (FICM) (to M.G.S.). B.V. and E.D. were recipients of a fellowship and doctoral studentship, respectively, from FRQS, and S.S.L. was a recipient of an FICM studentship. M.W. is the recipient of the Carolyn and Richard Renaud Endowed Research Chair in Heart Failure of the Montreal Heart Institute.

Abbreviations used in this article:

CRP

C-reactive protein

HC

healthy control

HF

heart failure

HFpEF

HF with a preserved LVEF

HFrEF

HF with a reduced LVEF

hsCRP

high-sensitivity CRP

LDL

low-density lipoprotein

LVEF

left ventricular ejection fraction

MHI

Montreal Heart Institute

MPO

myeloperoxidase

NET

neutrophil extracellular trap

NYHA

New York Heart Association

pEF

preserved ejection fraction

rEF

reduced ejection fraction

rhCRP

recombinant human CRP

T2DM

type 2 diabetes.

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The authors have no financial conflicts of interest.

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