Paraoxonase 1 Activity in Patients with Chronic Obstructive Pulmonary Disease

Abstract

Introduction: Paraoxonase 1 (PON1) is an antioxidative enzyme manly associated with high density lipoproteins (HDL) in the peripheral blood. The aim of this study was to determine the PON1 paraoxonase and arylesterase activities in patients with chronic obstructive pulmonary disease (COPD). We also aimed to determine the concentration of reduced thiol groups as a marker of protein oxidation. Materials and methods: The study included 105 patients with stable COPD and 44 healthy controls. PON1 activities and thiols concentration were assayed in sera by spectrophotometry. Results: PON1 basal (POX) and salt-stimulated paraoxonase activity (POX1) as well as arylesterase activity (ARE) were significantly reduced in COPD patients. In addition, concentration of reduced thiol groups was significantly decreased in COPD group. PON1 activities were similar in patients with different disease severity (GOLD stages). However, a significant reduction in POX, POX1 and ARE was observed already in GOLD II stage when compared to controls. POX and POX1 showed modest while ARE yielded very good power for discrimination between healthy subjects and COPD patients. Univariate and multivariate logistic regression analysis indicated that ARE is a good COPD predictor. Conclusion: Reduction of PON1 activity observed in COPD patients could be partly caused by oxidative environment. Lower concentrations of reduced thiol groups in COPD patients suggest that a decrease in PON1 activity could reflect oxidative changes of enzyme free cysteine residues. Furthermore, decreased PON1 arylesterase activity might indicate a down-regulation of PON1 concentration. Our results suggest that ARE could be considered as potential biomarker for COPD diagnosis.

Keywords: :

• paraoxonase 1
• chronic obstructive pulmonary disease
• thiols
• oxidative stress
• paraoxonase activity
• arylesterase activity

Introduction

Chronic obstructive pulmonary disease (COPD) is the most common chronic respiratory disease with increasing prevalence, morbidity and mortality (1,2). Cigarette smoking, air pollution and increase of free radicals in respiratory tract (by inflammation and infections) are the leading causes of oxidative stress in COPD patients (3,4). Smoking may enhance oxidative stress directly through the release of reactive oxygen and nitrogen radicals, and indirectly by weakening the antioxidant defence systems. Paraoxonase 1 (PON1) is an enzyme localized in Clara cells, endothelial cells, and type 1 cells of the alveolar epithelium with supposed protective role against oxidative stress (3, 5–7).

After being synthesized in the liver, PON1 is secreted into plasma where it is mainly bound to the high density lipoproteins (HDL) (8). PON1 hydrolyzes different substrates by its organophosphatase, arylesterase and lactonase activities (8–14). PON1 acts as antioxidative and antiatherogenic enzyme by hydrolyzing lipid peroxides in oxidized lipoproteins, thus protecting both HDL and low density lipoproteins (LDL) from oxidation (8,15,16,17). It was shown that three cysteine residues at positions 42, 284 and 353 (C42, C284, C353) are important for PON1 activity. C42 and C353 form a disulfide bond and these residues are important for secretion and catalytic activity of the enzyme (14,18). C284 is free and is assumed to be located closely to the active centre of the enzyme, thus possibly participating in orientation or binding of the substrate (14,19). Furthermore, it is not specifically required for paraoxonase/arylesterase activity, but is required for prevention of copper-induced LDL oxidation (14,19). Decreased, but not abolished, paraoxonase and arylesterase activities were observed when mutating the C284 residue to alanine or serine (8,19).

Large inter-individual variability of up to 13 times for PON1 concentration and up to 40 times for PON1 activity was demonstrated. Both genetic and non-genetic factors affect PON1 concentration and activity. Genetic factors include polymorphisms in promoter and coding regions of the pon1 gene, while non-genetic factors comprise diet, alcohol consumption, exposure to environmental toxins, and different physiological and pathological conditions (8,20–25). Cigarette smoke is considered as one of the non-genetic factors associated with down-regulation of PON1 concentration and activity (3,5,6,20,22,23). Furthermore, reduced PON1 activity is reported in different diseases where aethiology is associated with increased oxidative stress (8,20,22).

In the present study, we aimed to investigate PON1 paraoxonase and arylesterase activity in COPD patients. Furthermore, we explored the effect of disease severity and smoking history on PON1 activity. As PON1 antioxidative role depends on reduced sulfhydryl groups, and oxidation of those groups is indicator of oxidative stress in general, we measured thiol concentration in healthy and COPD individuals.

Materials and methods

Study design

The study included 105 patients with clinically stable COPD (32 smokers, 27 ex-smokers, 46 non-smokers) and control group of 44 healthy subjects (16 smokers, 13 ex-smokers, 15 non-smokers). Smokers were defined as current smokers who smoke more that 2 cigarettes daily and those who quit smoking up to 6 months before study enrolment; ex-smokers were defined as subjects who had smoking history during their lifetime but quit smoking more than 6 months before study enrolment; non-smokers were defined as subjects who had never smoked.

Inclusion criterion for the COPD group was clinical diagnosis of COPD according to GOLD (Global Initiative for Chronic Obstructive Lung Disease) report (26). COPD was diagnosed by a pulmonary specialist according to clinical examination (chronic and progressive dyspnoea, cough and sputum production) and spirometry results, measured on the first admission at the Department for Pulmology in Dr. Ivo Pedi喨ć General Hospital (Sisak, Croatia). Fixed forced expiratory volume in 1 second (FEV₁) to forced vital capacity (FVC) ratio FEV₁/FVC <0.70 and percentage of FEV₁ predicted were used to diagnose and classify patients into GOLD subgroups, according to disease severity (stage GOLD II: 50% ≤ FEV₁ < 80% predicted; stage GOLD III: 30% ≤ FEV₁ < 50% predicted; stage GOLD IV: FEV₁ < 30% predicted or FEV₁ < 50% predicted with the presence of chronic respiratory failure). Healthy subjects were recruited from the same geographic area by a general practitioner and all were apparently healthy according to the exclusion criteria with normal spirometry results. Exclusion criteria, for both COPD patients and healthy subjects, included the presence of pulmonary diseases other than COPD, infective and inflammatory diseases, neoplastic pathologies, renal, gastrointestinal, endocrine and hepatic diseases, and excessive alcohol consumption (≥40 g/day).

All patients were in the stable phase of the disease for at least 3 months without need for hospitalization. Their medication therapy consisted of bronchodilators, anticholinergic agents, theophylline and inhaled corticosteroids. No therapy modification was applied. The study was approved by the Medical Ethics Committee for Human Studies of Dr. Ivo Pedišić General Hospital, and informed consent was signed by all subjects enrolled in the study. The study was designed according to the Declaration of Helsinki.

Serum samples were collected from all subjects after an overnight fast and they were stored at −20°C until further analysis.

Methods

Lipid parameters

Concentrations of triglycerides and total cholesterol were determined on Alcyon 300 (Abbott Diagnostics, IL, USA) with commercially available reagents (Herbos Diagnostic d.o.o, Sisak, Hrvatska). Concentration of HDL-cholesterol was measured on Dimension Xpand Plus (Siemens Healthcare Diagnostics, Deerfield, Illinois USA) with commercial reagent (Siemens Healthcare Diagnostics, Deerfield, Illinois USA). Concentration of LDL-cholesterol was calculated using Friedwald equation [LDL-cholesterol (mmol/L) = total cholesterol –HDL-cholesterol –(triglycerides/2.2)].

PON1 paraoxonase and arylesterase activities

PON1 activity in serum was assessed by two different substrates: paraoxon (PON1 paraoxonase activity) and phenylacetate (PON1 arylesterase activity).

PON1 paraoxonase activity was measured in the absence and in the presence of NaCl (basal and salt-stimulated paraoxonase activity), using the Olympus 540 analyzer (Beckman Coulter, Brea, CA, USA) at 37°C, as described previously (27). Briefly, reaction mixture contained 15 μL of serum and 300 μL of reagent (2.5 mmol/L paraoxon of ∼ 90% purity, 2.2 mmol/L CaCl₂ in 0.1 mol/l Tris-HCl buffer, pH 8.0). For salt-stimulated paraoxonase activity buffer contained 1.0 mol/L NaCl. The release of p-nitrophenol was measured at 410/480 nm (ε = 17900 L/mol cm) and the PON1 enzyme activity was calculated.

PON1 arylesterase activity was determined by previously described methods (28,29), with some modifications. Briefly, 200 μL of freshly prepared substrate (3.26 mmol/L phenylacetate in 20 mmol/L Tris-HCL buffer with 1 mmol/L CaCl₂, pH 8.0) was added to 20 μL of serum samples (diluted 1:80 with buffer). Reaction mixture for determination of spontaneous substrate hydrolysis contained 20 μL of buffer and 200 μL of substrate. Distilled water was used as blank. The release of phenol was measured at room temperature continuously (every 30 seconds) during 4 minutes at 260 nm (ε = 1310 l/mol cm) on a microplate reader (1420 Victor³, PerkinElmer, USA). Calculated PON1 arylesterase activities in serum samples were corrected for spontaneous substrate hydrolysis.

Concentration of reduced thiol groups

Concentration of reduced thiol groups in serum was measured by the method described by Hu et al. (30).

Statistical analysis

Statistical analysis was performed using SigmaStat for Windows, version 3.0, and MedCalc for Windows version 12.4.0. Normality of distribution was tested by the Kolmogorov-Smirnov test. Depending on the distribution, the difference between two groups was tested using Mann–Whitney Rank Sum Test or t-test for nonparametric and parametric data, respectively. The difference between more than two groups was tested using the Kruskal–Wallis Analysis of Variance on Ranks or by One Way Analysis of Variance, for nonparametric and parametric data, respectively. Post hoc testing was performed using pairwise comparisons by the Holm–Sidak or Dunn methods. Linear regression analysis was used to assess the relationship of gender, age, BMI, smoking status, lung function parameters, lipid parameters and thiol concentration with PON1 activities.

Diagnostic accuracy for PON1 activities was assessed using receiver operating characteristic (ROC) curve analysis. Univariate and multivariate logistic regression were used to analyze the suitability of PON1 activities in predicting COPD. Chi-square test was used for comparison of proportions. Quantitative data are presented as mean and standard deviation or as median and interquartile range, while qualitative data are presented as absolute numbers and percentages. All p values lower than 0.05 were considered statistically significant.

Results

Demographic characteristics of healthy individuals and COPD patients enrolled in this study, their lung function, lipid and oxidative stress parameters are presented in Table 1. Control and COPD groups significantly differ in age and gender distribution, but not in smoking status. As expected, COPD patients had lower body mass index (BMI) and lung function parameters (FEV₁ and FEV₁/FVC). Lipid profile was altered in COPD subjects who had lower concentrations of triglycerides, total cholesterol and LDL-cholesterol as compared to controls, while concentration of HDL-cholesterol did not differ between studied groups. In addition, thiol groups were determined as a marker of proteins oxidation to confirm the presence of oxidative stress in COPD patients. Our results have shown that concentration of reduced sulfhydryl groups was significantly decreased in COPD patients compared to healthy subjects.

Table 1.  Demographic characteristics, lung function, lipid and oxidative stress parameters of healthy and COPD individuals

	Controls n = 44	COPD n = 105	p
Age	52 (46–56)	71 (65–76)	<0.001
Gender (n, %)
male	20 (45)	79 (75)	<0.001
female	24 (55)	26 (25)
Smoking status (n, %)
Smokers	16 (36)	32 (30)	0.544
Ex-smokers	13 (30)	27 (26)
Non-smokers	15 (34)	46 (44)
BMI (kg/m2)	27.5 (25.7–30.3)	24.2 (21.5–27.2)	<0.001
FEV1 (% pred.)	105 ± 16	40 ± 14	<0.001
FEV1/FVC (%)	86 (82–89)	63 (56–68)	<0.001
Triglycerides (mmol/L)	1.7 (1.2–2.5)	1.1 (0.8–1.4)	<0.001
Cholesterol (mmol/L)	5.5 ｱ 1.0	4.9 ± 1.1	0.002
HDL (mmol/L)	1.5 (1.2–1.7)	1.5 (1.1–1.8)	0.784
LDL (mmol/L)	3.2 (2.4–3.7)	2.7 (2.3–3.4)	0.030
Thiols (mmol/L)	0.158 ± 0.052	0.085 ± 0.047	<0.001

Data are shown as the median (interquartile range), as the mean ± standard deviation or as the absolute numbers (percentages); checked by the Mann-Whitney Rank Sum test, t-test or Chi-square test. BMI, body mass index; FEV₁, forced expiratory volume in 1 second; FVC, forced vital capacity.

PON1 basal (POX) and salt-stimulated paraoxonase activity (POX1) as well as PON1 arylesterase activity (ARE) differ significantly between COPD patients and controls (p* in Table 2). Compared to healthy subjects, group of total COPD patients had lower values of POX (20%), POX1 (18%) and ARE (50%). Since PON1 is mainly associated with HDL in serum, we also standardized PON1 paraoxonase and arylesterase activities to HDL-cholesterol concentrations. POX/HDL and POX1/HDL as well as ARE/HDL were reduced in total COPD group for 23%, 17% and 50%, respectively. The observed differences in PON1 values could not be attributed to age and gender differences between controls and patients (Table 1) because linear regression analysis showed no significant association between PON1 activities and either age or gender (data not shown).

Table 2.  PON1 paraoxonase and arylesterase activity in healthy subjects and COPD patients subdivided or not by disease severity (GOLD stages)

	Total controls	Total COPD	p*	COPD GOLD II	COPD GOLD III	COPD GOLD IV	p**
	n = 44	n = 105		n = 27	n = 50	n = 28
POX (U/L)	90 (71–160)	72 (47–133)	0.005	63 (54–109)	77 (43–154)	80 (56–137)	0.021^a
POX/HDL (U/mmol)	61 (51–114)	47 (34–97)	0.002	44 (34–75)	56 (32–104)	51 (35–106)	0.019^a
POX1 (U/L)	167 (131–317)	137 (88–272)	0.013	114 (96–220)	145 (77–308)	145 (102–277)	0.048^a
POX1/HDL (U/mmol)	110 (91–223)	91 (61–193)	0.006	85 (62–153)	105 (59–202)	92 (68–213)	0.039
ARE (kU/L)	40 (30–53)	20 (14–27)	<0.001	23 (16–28)	20 (15–28)	17 (13–25)	<0.001^b
ARE/HDL (kU/mmol)	28 (19–34)	14 (10–18)	<0.001	15 (11–21)	14 (10–19)	14 (8–17)	<0.001^b

Data are shown as the median (interquartile range).

p* total COPD patients compared to total control subjects; test by Mann–Whitney Rank Sum test

p** different COPD GOLD stages compared to total control subjects; test by Kruskall–Wallis One Way Analysis of Variance on Ranks.

^aPost hoc testing by Dunn's method: significantly different POX, POX/HDL and POX1 values between total control subjects and COPD GOLD II stage.

^bPost hoc testing by Dunn's method: significantly different ARE and ARE/HDL values between total control subjects and COPD GOLD II, GOLD III and GOLD IV stages.

Furthermore, we wanted to assess if PON1 activities were associated with severity of the disease. Our patients were subdivided according to GOLD stages into three groups (GOLD II, III and IV). No significant difference in PON1 activities was demonstrated between GOLD stages. However, significant difference in POX and POX1 activities between controls and COPD GOLD II patients was observed as well as in ARE activity between controls and COPD GOLD II, COPD GOLD III and COPD GOLD IV patients (p** in Table 2).

To explore if smoking status influenced PON1 activities, the study participants were subdivided into smokers, ex-smokers and non-smokers, according to the criterion given in Materials and method section. In the control group, cigarette smoking significantly affected POX, POX1 and ARE activities. Post hoc testing showed significant difference in POX, POX/HDL, PON1 and PON1/HDL between control smokers and non-smokers. On the other hand, ARE was significantly different between control smokers and ex-smokers as well as between control ex-smokers and non-smokers, and ARE/HDL between control smokers and ex-smokers. However, no influence of smoking on PON1 activities was observed in COPD group (Table 3). We also tested the relation between PON1 activities and smoking by linear regression analysis, and we found that POX and POX1 were significantly associated to smoking status in control group only (R² = 0.22, p = 0.001 and R² = 0.21, p = 0.002, respectively).

Table 3.  PON1 paraoxonase and arylesterase activity in control and COPD groups subdivided by smoking status

Control subjects	Smokers n = 16	Ex-smokers n = 13	Non-smokers n = 15	p
POX (U/L)	71 (65–89)	91 (77–167)	148 (91–250)	0.003^a
POX/HDL (U/mmol)	52 (45–68)	73 (55–129)	103 (57–189)	0.005^a
POX1 (U/L)	131 (112–171)	164 (144–325)	289 (169–442)	0.004^a
POX1/HDL (U/mmol)	90 (80–118)	137 (99–251)	202 (104–324)	0.004^a
ARE (kU/L)	33 ± 14	50 ± 10	39 ± 15	0.006^b
ARE/HDL (kU/mmol)	20 (17–29)	33 (29–51)	27 (21–34)	0.006^c
COPD	Smokers n = 32	Ex-smokers n = 27	Non-smokers n = 46	p
POX (U/L)	71 (49–95)	64 (39–128)	83 (50–154)	0.720
POX/HDL (U/mmol)	42 (34–67)	58 (29–91)	59 (35–104)	0.637
POX1 (U/L)	131 (89–198)	116 (69–267)	152 (94–308)	0.697
POX1/HDL (U/mmol)	75 (61–132)	108 (50–186)	108 (64–206)	0.586
ARE (kU/L)	21 ± 8	20 ± 12	22 ± 11	0.832
ARE/HDL (kU/mmol)	15 ± 8	15 ± 10	15 ± 6	0.971

Data are shown as the median (interquartile range) or as the mean ± standard deviation; checked by the Kruskal-Wallis One Way Analysis of Variance on Ranks or One Way Analysis of Variance.

^aPost hoc testing by Dunn's method: significantly different POX, POX/HDL, POX1 and POX1/HDL values between control smokers and non-smokers.

^bPost hoc testing by the Holm-Sidak method: significantly different ARE values between control smokers and ex-smokers as well as between control ex-smokers and non-smokers.

^cPost hoc testing by Dunn's method: significantly different ARE/HDL values between control smokers and ex-smokers.

Diagnostic accuracy of POX, POX1 and ARE in discriminating between healthy subjects and patients with COPD was described in Table 4 with area under the ROC curve (AUC), sensitivity and specificity with corresponding 95% confidence intervals (95% CI), and cut off value for each parameter. POX and POX1 showed modest performance, while ARE yielded very good discrimination power.

Table 4.  Diagnostic accuracy of PON1 paraoxonase and arylesterase activity

	AUC (95% CI)	Sensitivity (95% CI)	Specificity (95% CI)	Cut-off value
POX (U/L)	0.65 (0.57–0.73)	41.9 (32.3–51.9)	90.9 (78.3–97.4)	≤63
POX1 (U/L)	0.63 (0.55–0.71)	44.8 (35.0–54.8)	86.4 (72.6–94.8)	≤119
ARE (kU/L)	0.85 (0.78–0.90)	79.1 (70.0–86.4)	79.6 (64.7–90.2)	≤28

Diagnostic accuracy was assessed on the basis of the AUC values.

Finally, we tested the significance of PON1 activities as diagnostic predictors for the presence of COPD by using univariate and multivariate logistic regression analysis. The results are presented in Table 5. The univariate regression model indicated that POX, POX1 and ARE could be considered as diagnostic predictors of COPD. The multivariate regression model including all three PON1 activities yielded an AUC (95% CI) of 0.85 (0.78–0.90), correctly classifying 79% of COPD cases. No association between POX or POX1 and COPD was found when the parameters investigated were combined in the multivariate model.

Table 5.  Univariate and multivariate logistic regression analysis of PON1 paraoxonase and arylesterase activity

	Univariate regression analysis		Multivariate regression analysis
	OR (95% CI)	p	OR (95% CI)	p
POX (U/L)	0.99 (0.99–0.10)	0.020	–	–
POX1 (U/L)	1.00 (1.00–1.00)	0.036	–	–
ARE (kU/L)	0.90 (0.86–0.93)	<0.001	0.90 (0.86–0.93)	<0.001

Data are presented as odds ratio (95% confidence interval).

Discussion

PON1 is an enzyme with antioxidative and antiatherogenic properties. Its activity was found to be reduced in different diseases associated with oxidative stress, and imbalance between oxidants and antioxidants plays an important role in the pathogenesis of COPD as well (2,8,14,31–38). In this study we have demonstrated that COPD patients had decreased PON1 paraoxonase activity and PON1 arylesterase activity compared to control subjects, as it was previously shown (3,4,6,32). The association of PON1 with HDL is important for maintenance of normal serum enzyme activity (39,40) and reduction in HDL levels can lead to lower PON1 activity. However, no significant difference in HDL concentrations between healthy subjects and COPD patients was observed in our study, suggesting that differences in PON1 activities are not related to HDL. These findings are in agreement with previous publication (32).

It was demonstrated that PON1 arylesterase activity does not have polymorphic distribution and provides an accurate estimation of the enzyme amount (41). Thus, it is reasonable to suggest that reduced ARE activity might reflect lower PON1 concentration in sera of COPD patients. In this study we also assessed diagnostic accuracy of PON1 paraoxonase and arylesterase activities in discriminating between healthy and COPD individuals. POX and POX1 yielded an AUC of 0.65 and 0.63, respectively, showing only modest performance. In addition, diagnostic sensitivity for POX and for POX1 was quite low (41.9% and 44.8%, respectively), making their use as potential biomarkers for disease diagnosis rather questionable. Conversely, discrimination power for ARE was very good, with AUC of 0.85, sensitivity of 79.1% and specificity of 79.6%. Univariate logistic regression showed that POX, POX1 and ARE might be diagnostic predictors for the presence of COPD. However, in the multivariate regression model only ARE remained predictive of the disease. Thus, it seems that ARE could be considered as a potentially valuable COPD biomarker.

PON1 paraoxonase and arylesterase activities in COPD patients with different GOLD stages were similar in our study. Those results suggest a lack of association between decrease in PON1 activities and disease severity, indicating that POX, POX1 and ARE cannot be used for distinguishing patients according to the GOLD stages. However, it is important to emphasize that we observed a significant reduction of all PON1 activities in GOLD II stage already when compared to healthy volunteers. Thus, a reduction in PON1 activity could be used as an early indicator of the disease presence. Yet, while PON1 paraoxonase activity was restored to the control values in GOLD III and GOLD IV stages, PON1 arylesterase activity remained decreased even during more severe disease stages. As ARE correlates well with the enzyme concentration, we suppose that some signalling pathways leading to the persistent down-regulation of the pon1 gene are triggered in COPD individuals.

Smoking may enhance oxidative stress through release of reactive oxygen and nitrogen species in cigarette smoke and by wakening antioxidant defence mechanisms (5). It has been demonstrated that cigarette smoke led to the reduction of PON1 activity (4,5,42,43), although some contradictory data were also observed showing no difference in PON1 paraoxonase activity between healthy smokers and non-smokers (44). PON1 activity was associated with smoking status in our control group. However, smoking status did not affect PON1 activities in COPD patients group. Contrary to our results, Isik et al. reported significantly lower PON1 paraoxonase activity in COPD smokers compared to COPD non-smokers, and they did not measure PON1 arylesterase activity (4). Still, different study design and small sample size (25 COPD patients) could be the reason for discrepancies of results. It seems that smoking might be a very important factor affecting PON1 activities in health but not necessarily in disease conditions. Some other non-genetic and/or genetic factors could be more significant when oxidative overload derived not just from smoking but from inflammatory processes is present as well.

It has been shown that decreased PON1 activity during oxidative stress is often associated with changes in the redox status of the protein free sulfhydryl groups (15,45,46,47). Our study showed significantly lower concentrations of total reduced thiol groups in sera of COPD patients compared to healthy subjects. Thus, it could be assumed that PON1 thiol groups are oxidized in COPD, leading to the reduction of PON1 paraoxonase and arylesterase activities, but also to the reduction of its antioxidative function which can further aggravate oxidative stress.

Our study has several shortcomings. First, small sample size (105 COPD patients, 44 healthy controls) is restrictive for an unambiguous conclusions, and a larger epidemiological study with age and gender matched healthy subject will be needed (48). Second, cross-sectional design of the study cannot definitively establish causal or temporal relationship, thus the longitudinal study is needed with following up the patients over time to evaluate the strength of the association between decreased PON1 activities and COPD development. Third, we did not assess PON1 activities in COPD patients suffering from exacerbation episode.

However, despite these potential limitations, our results showed that patients with COPD had significantly lower PON1 activity compared to the healthy subjects. The reduction in PON1 activity could be partly caused by oxidative environment. Decreased concentration of reduced thiol groups in COPD patients emphasized this assumption. Observed data suggest that COPD patients might have lower concentration of PON1 that is responsible for the reduction of enzyme activity. Finally, our results propose a potential role of PON1 arylesterase activity as biomarker for COPD diagnosis. However, further studies exploring both genetic and non-genetic parameters are needed to establish an involvement of PON1 enzyme in COPD aethiology.

Declaration of Interest Statement

The authors declare no competing interests. The authors are responsible for the content and writing of this paper.

Acknowledgments

This work was supported by the Croatian Ministry of Science, Education and Sports (grant number 006-0061245-0977).