Elevated circulating levels of lipoprotein- associated ...

Clin Chem Lab Med 2015; aop

Sophia Sakka, Tania Siahanidou, Chronis Voyatzis, Panagiota Pervanidou, Christina Kaminioti, Natalia Lazopoulou, Christina Kanaka-Gantenbein, George P. Chrousos and Ioannis Papassotiriou*

Elevated circulating levels of lipoproteinassociated phospholipase A2 in obese children DOI 10.1515/cclm-2014-1081 Received November 4, 2014; accepted December 4, 2014

Abstract Background: Obesity and cardiovascular disease (CVD) often co-exist, but the pathophysiologic mechanisms that link the two are not fully understood. Lipoproteinassociated phospholipase A2 (Lp-PLA2) is involved in the modification of lipids within atheromatous plaques. Recently, circulating Lp-PLA2 was found to be predictive of thromboembolic episodes in adults, independently of a variety of other potential risk factors, including markers of inflammation, renal function, and hemodynamic stress. However, the function of this lipase and its importance as a biomarker in childhood obesity is much less studied. The aim of the study was to study Lp-PLA2, a non-traditional risk factor of CVD, in obese children. Methods: Sixty-seven lean [39 boys and 28 girls, mean body mass index (BMI) z-score –0.2 ± 0.8] and 66 obese (32 boys and 34 girls, mean BMI z-score 4.4 ± 1.2) age-matched (p = 0.251) children, aged 6–12 years, were studied. BMI z-score was calculated based on the Greek BMI growth curves, and children were categorized as obese according to the Cole criteria. All children underwent physical examination and a fasting morning blood sample was obtained for glucose, insulin, lipid profile, and Lp-PLA2 assessment. Plasma concentrations of Lp-PLA2 were determined by a commercially available Lp-PLA2 enzyme-linked

*Corresponding author: Dr Ioannis Papassotiriou, Department of Clinical Biochemistry, “Aghia Sophia” Children’s Hospital Athens 11527, Greece, Phone/Fax: +30-213-2013171, E-mail: [email protected]; [email protected] Sophia Sakka, Tania Siahanidou, Panagiota Pervanidou, Natalia Lazopoulou, Christina Kanaka-Gantenbein and George P. Chrousos: Division of Endocrinology, Metabolism and Diabetes, First Department of Pediatrics, Athens University Medical School, Athens, Greece Chronis Voyatzis and Christina Kaminioti: Department of Clinical Biochemistry, “Aghia Sophia” Children’s Hospital, Athens, Greece

immunosorbent assay kit (PLAC Test), while other measurements were performed using standard methods. Results: Plasma Lp-PLA2 levels were significantly higher in obese children (322.5 ± 77.8 ng/mL) compared with normal-weight ones (278.0 ± 64.4 ng/mL, p < 0.001). Lp-PLA2 concentrations were significantly correlated with the BMI z-score (p = 0.004). Receiver operating characteristic analysis on Lp-PLA2 values resulted in significant areas under the curve (AUC) for distinguishing between obese and normal-weight groups of children (AUC, 0.726; p < 0.001). Conclusions: We found significantly higher Lp-PLA2 levels in obese children than lean controls. Interestingly, they all had levels > 200 ng/mL, which are considered to correlate with atherosclerosis and a high thromboembolic risk in adults. The positive correlation of Lp-PLA2 with BMI suggests that Lp-PLA2 might be the link between obesity and increased cardiovascular risk, which can be elevated even at a very young age. Measurement of LpPLA2 in plasma could therefore represent a further biomarker for assessing increased CVD risk in obese children and adolescents. Keywords: biomarkers; BMI; cardiovascular risk; children; lipids; lipoprotein-associated phospholipase A2 (LpPLA2); obesity.

Introduction Obesity and cardiovascular disease (CVD) often co-exist, although the exact pathophysiologic mechanisms that link the two are not fully understood. For a long time, atherosclerosis was considered as a lipid-driven disease; however, it became progressively evident that it also involves the combined effect of insulin resistance and inflammation [1]. Lipoprotein-associated phospholipase A2 (Lp-PLA2), also known as plasma platelet activating factor acetylhydrolase (PAF-AH), is a Ca2+-independent enzyme implicated in inflammation and atherosclerosis

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2 Sakka et al.: Lp-PLA2 and childhood obesity

[2]. It has been established that the Lp-PLA2 enzyme specifically hydrolyzes oxidized phospholipids on oxidized low-density lipoprotein cholesterol (LDL-C) particles within the arterial intima media. The products of this reaction, oxidized free fatty acids and lysophosphatidylcholine, in turn, stimulate the expression of endothelial adhesion molecules and cytokines [3], which leads to recruitment of monocytes to the intima, where they are activated to become macrophages, and ultimately, apoptotic foam cells [4]. Various studies (WOSCOPS, ARIC, MONICA, Rotterdam study) have pointed to the role of Lp-PLA2 as a predictor of coronary heart disease (CHD) independent of a variety of potential risk factors including markers of inflammation, renal function, and hemodynamic stress [5–9]. Recently, the predictive value of Lp-PLA2 in stroke risk was also explored [10]. In cross-sectional studies, both Lp-PLA2 activity and/or concentration were higher among individuals with diabetes than among those without diabetes, while Lp-PLA2 activity has been found to predict the incidence of type 2 diabetes [11, 12]. Furthermore, Lp-PLA2 activity was increased in patients with the metabolic syndrome compared with controls [13, 14]. The significant increase of childhood obesity and the associated co-morbidities such as the metabolic syndrome, insulin resistance, and diabetes will undoubtedly lead to increased incidence of premature atherosclerosis and CVD [15]. Biomarkers beyond total cholesterol, LDL-C, triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C), such as Lp-PLA2, may ultimately be useful and more specific in monitoring early events in atherogenesis in pediatric age groups. Two recent studies found increased levels of Lp-PLA2 activity in obese adolescents compared with controls [16] and an association between increased Lp-PLA2 mass concentrations and higher body mass index (BMI) percentiles in children [17]. However, there is still lack of evidence concerning the role of Lp-PLA2 in childhood obesity and future CVD risk. In the current study, we aimed to investigate the effect of obesity on Lp-PLA2 in children because obesity is the most prevalent risk factor for CVD in this age group. We assessed the circulating concentrations of Lp-PLA2 mass in obese children and compared the results with those of lean healthy, age-matched controls. We studied the correlations of concentrations of this enzyme with BMI, lipid profile, and markers of insulin resistance. Additional study advantages in this group are the absence of concurrent drug therapy, smoking, or other co-morbid situations.

Materials and methods Study groups We divided our population on the basis of their BMI z-score into two groups, the “obese” and the “control” group. Sixty-seven control (39 boys and 28 girls, mean BMI z-score –0.2 ± 0.8) and 66 obese (32 boys and 34 girls, mean BMI z-score 4.4 ± 1.2) age-matched (p = 0.261) children, aged 6–12 years, were studied (Table 1). The obese children and adolescents included in this study were recruited from the outpatient Obesity Clinic of the Division of Endocrinology, Diabetes and Metabolism of the First Department of Pediatrics of the University of Athens, “Aghia Sophia” Children’s Hospital, Athens, Greece. The controls were randomly selected among healthy children routinely examined in “Aghia Sophia” Children’s Hospital. No participant was receiving any medication and all were in a good general condition. The obese group was defined according to the World Health Organization criteria on the basis of BMI (the weight in kilograms divided by the square of the height in meters) [18] modified for childhood and adolescent obesity as suggested by Cole et al. [19]. The Ethics Committee of the “Aghia Sophia” Children’s Hospital approved the study protocol and children were included in the study only after informed parental consent was obtained. Table 1 Anthropometric and blood chemistry parameters in normalweight and obese children.

Age, years Sex Girls Boys BMI z-score SBP, mmHg DBP, mmHg Glucose, mmol/L Insulinc, mU/L Cortisolc, μmol/L Total cholesterol, mmol/L TG, mmol/L HDL-C, mmol/L LDL-C, mmol/L ApoA1, g/L ApoB, g/L ApoB/ApoA1 Lp(a)c, g/L HOMAc Lp-PLA2, ng/mL

Controls, n = 67, mean (SD)

Obese, n = 66, mean (SD)

p-Valuea

9.1 (2.9)

9.7 (3.1)

0.251

28 (41.8) 39 (58.2) –0.2 (0.8) 99.3 (14) 64.1 (10.6) 4.59 (0.44) 7.1 (3.6) 0.30 (0.12) 2.65 (1.92) 0.55 (0.18) 1.43 (0.26) 2.59 (0.56) 1.56 (0.24) 0.70 (0.17) 0.45 (0.12) 0.20 (0.23) 1.5 (0.8) 278 (64.4)

34 (51.5) 32 (48.5) 4.4 (1.2) 120 (16.2) 75.2 (10.8) 4.87 (0.52) 18.2 (14) 0.34 (0.13) 4.28 (0.70) 0.63 (0.41) 0.88 (0.54) 3.53 (1.14) 1.43 (0.20) 0.84 (0.20) 0.59 (0.16) 0.20 (0.23) 4.1 (3.6) 322.5 (77.8)

0.261b < 0.001 < 0.001 < 0.001 0.001 < 0.001 0.043 < 0.001 0.153 < 0.001 < 0.001 0.001 < 0.001 < 0.001 0.802 < 0.001 < 0.001

Student t-test. bχ2-test. cTest performed on the log-transformed values. SD, standard deviation; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; TG, triglycerides; HDL-C, high-density lipoprotein; LDL-C, low-density lipoprotein; apoA1, apolipoprotein A1; apoB, apolipoprotein B; Lp(a), lipoprotein (a); HOMA, homeostasis model assessment; Lp-PLA2, lipoproteinassociated phospholipase A2.

a


Sakka et al.: Lp-PLA2 and childhood obesity 3

Physical examination

Results

The same trained physician examined all children recording their height, weight, head circumference, waist-to-hip ratio (W/H), BMI, pubertal status, and systolic (SBP) and diastolic (DBP) blood pressure. For BMI standard deviation score (SDS) calculations, the Greek National Growth Charts were employed [20]. BP-SDS estimations were based on Pediatrics 2004-4th report [21], according to the children’s age and height, using the mean of three measurements.

The demographics and biochemical data of obese and normal-weight children are shown in Table 1. No significant difference existed between the studied groups in age and gender. For all study markers, except for TG and Lp(a), significant differences were found between the obese group and controls; values were higher in obese groups with the exception of HDL-C and apoA levels, which, as expected, were significantly lower in obese children than controls (Table 1). Lp-PLA2 mean values were 278.0 ± 64.4 ng/mL in the control group and 322.5 ± 77.8 ng/mL in the obese group (p < 0.001) (Figure 1). The correlations of Lp-PLA2 with BMI z-score and all biochemical parameters in obese children are presented in Table 2. Lp-PLA2 was significantly and positively correlated with BMI z-score (r = 0.25, p = 0.004). Moreover, a significant positive correlation was found between Lp-PLA2 and total cholesterol, LDL-C (Figure 2), apoB, apoB/apoA1 ratio, as well as with cortisol, while HDL-C correlated negatively with Lp-PLA2 (r = –0.27, p = 0.002). When multiple linear regression analysis was conducted, it was found that LDL-C was independently associated with Lp-PLA2 levels (β = 0.64, SE = 0.32, p = 0.046). Additionally, multiple regression analysis showed that obesity had an independent effect on Lp-PLA2 levels (β = 51.71, SE = 21.05, p = 0.016). On the contrary, the effect of SBP, DBP, TG, total cholesterol, HDL-C, apoA1, apoB, Lp(a), and HOMA on LP-PLA2 concentrations was not significant.

Biochemical and metabolic risk factors After an overnight fast, venous blood was withdrawn at 8 am and fasting glucose, insulin, cortisol, total cholesterol, TG, HDL-C, LDL-C, apolipoprotein A1 (apoA1), apolipoprotein B (apoB), lipoprotein (a) (Lp(a)), and Lp-PLA2 were measured in all participants. Serum glucose, total cholesterol, TG, HDL-C, and LDL-C were determined using the Siemens Advia 1800 Clinical Chemistry System (Siemens Healthcare Diagnostics, Erlangen, Germany) and apoA1, apoB, and Lp(a) using latex particle-enhanced immunonephelometric assay on the BN ProSpecnephelometer (Siemens Healthcare Diagnostics, Liederbach, Germany), whereas serum insulin and cortisol were measured using the automated chemiluminescence Siemens ACS180 System Analyzer (Siemens Healthcare Diagnostics, Liederbach, Germany). The intra- and inter-assay coefficients of variation (CVs) of all variables did not exceed 5%, with the exception of insulin assay’s CVs that did not exceed 10%. Lp-PLA2 levels were determined with an immuno-turbidimetric method (PLAC Test Reagent Kit; DiaDexus, San Francisco, CA, USA) applied in the Siemens ADVIA 1800 Chemistry Analyzer. The analytical sensitivity of the assay was 2.4 ng/mL, as calculated by the interpolation of the mean ± 2 standard deviations (SD) of 20 replicates of the 0-ng/mL Lp-PLA2 calibrator from the standard curve. Intra-assay (1.2% and 0.6%) and inter-assay (3.8% and 4.7%) variability were determined by testing two human serum samples with Lp-PLA2 concentrations distributed throughout the calibration range of the assay. The homeostasis model assessment (HOMA), according to the formula HOMA index = fasting insulin (mIU/mL) × fasting glucose (mmol/L)/22.5, was used as a marker of insulin resistance [22].

Lean

Statistical analysis Continuous variables are presented with mean and SD. Qualitative variables are presented with absolute and relative frequencies. For the comparison of the mean values between two groups, Student t-test was used. When the normality assumption was not satisfied, log-transformations were performed. For the comparisons of proportions, χ2-test was used. Pearson (r) correlation coefficients were computed to explore the association of Lp-PLA2 with all study markers. Multiple linear regression analysis was performed to find independently associated variables with Lp-PLA2 levels. Regressions coefficients with their standard errors were computed from the results of the regression analyses. Receiver operating characteristic (ROC) analysis was performed on Lp-PLA2 values to examine what is the clinical utility of this marker to distinguish between obese and normal-weight groups in children population. All p-values reported are two-tailed. Statistical significance was set at 0.05, and analyses were conducted using SPSS statistical software (version 19.0).

Obese

170

270

370 Lp-PLA2, ng/mL

470

570

Figure 1 Comparison of Lp-PLA2 levels in lean children (mean ± SEM, 278.0 ± 15.7 ng/mL; 95.0% CI for mean, 262.3–293.7 ng/mL) vs. obese children (mean ± SEM 322.5 ± 19.1, ng/mL; 95.0% CI for mean 303.4–341.6 ng/mL) (p < 0.001). Boxes represent the interquartile range; lines inside boxes, median value; cross, mean marker; whiskers, lowest and highest observations, respectively.


4 Sakka et al.: Lp-PLA2 and childhood obesity Table 2 Significant and borderline significant correlations of Lp-PLA2 with other clinical and blood chemistry markers in obese children.

1.0

0.8

BMI z-score Glucose, mmol/L Insulina, mU/L Cortisola, μmol/L Total cholesterol, mmol/L HDL-C, mmol/L LDL-C, mmol/L ApoB, g/L ApoB/ApoA1 HOMAa

r

p-Value

0.25 0.15 0.16 0.20 0.21 –0.27 0.40 0.27 0.19 0.17

0.004 0.07 0.07 0.03 0.01 0.002 < 0.001 0.002 0.03 0.06

a

Test performed on the log-transformed values. No significant correlations were found between Lp-PLA2 and SBP, DBP, TG, apoA1 and Lp(a) in obese children.

ROC analysis on Lp-PLA2 values resulted in significant areas under the curve (AUC) for distinguishing obese and normal-weight groups of children (AUC, 0.726; 95% CI, 0.640–0.813; p < 0.001) (Figure 3). However, due to high overlapping of Lp-PLA2 values between obese children and controls, a cutoff value with both high sensitivity and high specificity could not be defined. Lp-PLA2 values higher than 235 ng/mL could discriminate obese from normal-weight children with sensitivity 95% but specificity 40% [positive predictive value (PPV) 63% and negative predictive value (NPV) 89%], whereas values >300 ng/mL could discriminate obese and normal-weight children with sensitivity approximately 60% and specificity 80% (PPV 76% and NPV 66%). Interestingly, Lp-PLA2 values higher than 200 ng/mL, which are considered to correlate

Lp-PLA2, ng/mL

550

450

350

250

150 0

2

4 LDL-C, mmol/L

6

8

Figure 2 Correlation of Lp-PLA2 with LDL-C concentrations in obese children at the 95.0% confidence level (r = 0.40, p < 0.001).

Sensitivity

Lp-PLA2 0.6

0.4

0.2

0.0

0.0

0.2

0.4 0.6 1-specificity

0.8

1.0

Figure 3 ROC curve on Lp-PLA2 values for distinguishing between obese and normal-weight groups of children (AUC, 0.726; p < 0.001).

with atherosclerosis and a high thromboembolic risk in adults, were found to present very high sensitivity (97%) in discriminating obese from normal-weight children, but the specificity was only 10% (PPV 53% and NPV 75%).

Discussion We found significantly higher Lp-PLA2 mass levels in obese children compared with controls. Our study is the first one to compare Lp-PLA2 mass between obese and control children in such a young age group. The results of this study are in accordance with those of da Silva et al. [16], who measured Lp-PLA2 activity in adolescents. Two more studies in children found an association between increased Lp-PLA2 concentrations and higher BMI percentiles [17, 23]; however, Hirschler et al. [23], contrary to our results, failed to show higher Lp-PLA2 activity in adolescents with obesity. In that study, multiple regression analysis showed that Lp-PLA2 was significantly associated only with apoB adjusted for age, BMI, TG and LDL-C [23]. An interesting aspect of our study is the fact that the mean levels of Lp-PLA2 in both groups were above 200 ng/mL. However, the latest cutoff point that the consensus panel recommended for incorporating Lp-PLA2 testing into CVD risk assessment is 200 ng/mL, above which value a patient is considered at high risk and one might consider initiating more aggressive treatment strategies [24]. Mean Lp-PLA2 mass values in children with familiar hypercholesterolemia and their unaffected siblings were also above 200 ng/mL, irrespective of obesity [25]. These results indicate the need for cutoff points in



children because they seem to follow a different pattern of Lp-PLA2 normal values than that of adults. Although we showed by ROC analysis that Lp-PLA2 has indeed clinical value in distinguishing between obese and normal-weight groups of children, a cutoff value with both high sensitivity and specificity could not be defined due to large overlap of values between obese children and controls. Overlapping Lp-PLA2 values is a common finding in relevant studies [16, 23] and can possibly be attributed to inter-individual variation associated with genetic variants that control Lp-PLA2 activity and mass; Lp-PLA2 is under genetic control as shown by twin studies [26], and also, SNPs in the Lp-PLA2 gene have recently been associated with increased plasma LP-PLA2 activity and cardiovascular risk [27]. In our study, obesity and also LDL-C, but not HDL-C, were found to be independently associated to Lp-PLA2 levels in multiple regression analysis. This correlation reinforces the results of previous studies in children showing positive correlations of Lp-PLA2 with LDL-C [16, 28] and can be easily explained by the fact that Lp-PLA2 is transported in the circulation bound mainly with LDL molecules, while < 20% of Lp-PLA2 is associated with HDL [29, 30]. Although Lp-PLA2 has been related to diabetes in adults [11, 12], we found no significant correlations between Lp-PLA2 mass and glucose, insulin, or HOMA index, which is in accordance with the findings of Hirschler et al. [23] in children. Interestingly, in the study of Nelson et al., Lp-PLA2 activity, but not Lp-PLA2 mass, was associated with increased risk of type 2 diabetes [12]. This was attributed to the fact that the mass measure represents Lp-PLA2’s mass in intact lipoproteins, whereas the activity assay represents phospholipase activity. The authors suggested that total Lp-PLA2 activity in plasma is the more relevant measure in relation to diabetes. However, discrepancy between studies still exists whether measurement of Lp-PLA2 activity is advantageous as compared with Lp-PLA2 mass determination. Both Lp-PLA2 mass and activity have been reported to be associated with CVD risk [31], whereas Lp-PLA2 activity was more strongly related than mass to lipid markers [31]. On the contrary, other studies have shown that Lp-PLA2 mass is better as predictive marker [10]. Whether the absence of significant correlations between Lp-PLA2 and markers of insulin resistance in our study population may be related to the fact that Lp-PLA2 mass instead of activity levels was measured is not known. However, as other studies in children did not also find such correlations despite using Lp-PLA2 activity assay [23], we suggest that differences in Lp-PLA2 associations between children and adults may exist. It is well known that “children are not small adults”

and also the associations between predictive markers and manifestations of a disease may take years to appear. It is probably too early to introduce Lp-PLA2 as a population-wide biomarker for coronary heart disease risk; however, with accumulating evidence, it might find a place in a stepwise risk assessment of individuals, even children, who require more aggressive intervention to prevent vascular disease [10]. The clustering of multiple unfavorable biomarkers strongly supports the need for early intervention. Motykova et al. [32] showed that intensive lifestyle modification, leading to BMI decrease, results in significant changes of plasma lipoprotein levels and, also, in a drop of Lp-PLA2 levels in pediatric obese patients. However, even after the intervention, Lp-PLA2 concentrations in that patient group remained elevated (above the 200 ng/mL), suggesting possible increased atherosclerosis risk in later life [32]. Furthermore, physical activity was inversely associated with Lp-PLA2 in other studies [33]. Animal and human adult studies have shown that the use of Lp-PLA2 inhibitors, such as darapladip, can reduce the development of coronary atherosclerosis and, more notably, inhibit the subsequent progression to advanced lesions, resulting in a more stable plaque phenotype, in the absence of an effect on cholesterol abundance [34, 35]. However, Lp-PLA2 inhibitors have very little been tested in children as yet. Ryu et al. [25] studied the effect of pravastatin treatment in children with familial hypercholesterolemia and found that it significantly reduced Lp-PLA2 levels compared with placebo. The determination of Lp-PLA2 levels may aid in the identification of individuals at high risk for coronary heart disease. Whether Lp-PLA2 may ultimately be useful in monitoring early events in atherogenesis in pediatric and adolescence age groups remains to be elucidated by further prospective cohort studies. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission. Financial support: Funding was received from Athens University to G.P. and I.P. (ELKE 70/3/ 5924-7303), while Lp-PLA2 reagents and the protocol for the method installation were provided by dia-Dexus (San Francisco, CA, USA). Employment or leadership: None declared. Honorarium: None declared. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.


6 Sakka et al.: Lp-PLA2 and childhood obesity

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