Relationship of Endothelial Microparticles to Obesity and Cardiovascular Disease Risk in Children and Adolescents

Abstract

Background

Microparticles and endothelial microparticles (EMPs) are implicated in accelerating cardiovascular disease (CVD); however, data in pediatrics are limited. We examined the relationship of microparticles and EMPs with adiposity and subclinical CVD risk measures in a pediatric population to determine their potential as biomarkers of CVD risk.

Methods and Results

A cross‐sectional study of youth (n=280; ages 8–20 years) with a range of body mass index categories was used. Microparticles, EMPs, and activated EMPs were measured by flow cytometry. %Body fat and %visceral adipose tissue were measured by dual X‐ray absorptiometry. Measures of arterial stiffness and vascular wall structure were obtained. Linear regression (with log‐transformed outcomes) and logistic regression were used to evaluate associations and all results were exponentiated. Youth with overweight/obesity and severe obesity had 2.50 (95% CI, 1.56–4.01) and 3.42 (95% CI, 2.15–5.43) times the geometric means of the total number of microparticles, respectively, compared with those with normal weight. Youth with overweight/obesity and severe obesity had 1.97 (95% CI, 1.09–3.55) and 2.34 (95% CI, 1.31–4.19) times the geometric means of the total number of EMPs, respectively, compared with those with normal weight. There were positive associations between the levels of both microparticles and EMPs with higher adiposity measures and poor CVD risk measures. Youth with higher adiposity showed 1.84 times the odds of having high levels of activated EMPs (%) (odds ratio, 1.84; 95% CI, 1.08–3.14) compared with those with normal weight.

Conclusions

Levels of microparticles, EMPs, and activated EMPs were positively associated with adiposity and poor subclinical CVD risk in a pediatric population.

Nonstandard Abbreviations and Acronyms

cCSC

carotid artery cross‐sectional compliance

cCSD

carotid cross‐sectional distensibility

cIEM

carotid incremental elastic modulus

cIMT

carotid intima‐media thickness

EMP

endothelial microparticle

PWV

pulse wave velocity

VAT

visceral adipose tissue

Clinical Perspective

What Is New?

• To our knowledge, this is the first study to provide evidence of elevated levels of endothelial microparticles and its magnitude among children and adolescents with obesity and severe obesity.

• Furthermore, we demonstrate positive associations of endothelial microparticles with adiposity and subclinical cardiovascular disease risk measures.

What Are the Clinical Implications?

• Our findings indicate that youth with higher adiposity may have high and early risk of cardiovascular disease.

• The potential role of microparticles and endothelial microparticles as useful biomarkers of cardiovascular disease risk appears promising and merits further study.

Endothelial activation represents one of the earliest signs of the atherosclerotic process. ¹ , ² Microparticles are small vesicles shed from multiple eukaryotic cells and released into circulation during cell activation, which can be classified as endothelial microparticles (EMPs), leukocyte microparticles, or platelet microparticles. Microparticles can be used as circulating surrogate markers for pathophysiological conditions, including inflammation and coagulation. ³ Microparticles shed from the endothelium by endothelial blebbing are termed EMPs, which represent a small fraction (≈5%–15%) of the total MPs in circulation. ³ , ⁴ Both microparticles and EMPs have been shown to play a significant role in endothelial activation and dysfunction. ⁴ , ⁵ It has been shown that microparticles and EMPs decrease with healthy diet and exercise. ⁶ , ⁷ Studies addressing race and ethnic differences in microparticles and EMPs are limited.

There has been growing evidence suggesting that microparticles and EMPs may be useful as novel biomarkers for cardiovascular diseases and metabolic diseases in adults, including acute coronary syndromes, ⁸ dyslipidemia, ⁹ endothelial dysfunctions, ¹⁰ ischemic stroke, ¹¹ and metabolic syndrome. ¹² Compared with other cardiovascular disease (CVD) risk measures such as flow‐mediated dilation, carotid intimal‐media thickness (cIMT), coronary artery calcification, and pulse wave velocity (PWV), which require specialized equipment and trained staff, microparticles and EMPs can be measured in the laboratory from a simple blood draw.

Despite the known role of microparticles, EMPs, and activated EMPs in accelerating CVD risk, little is known regarding their abundance and associations with CVD risk factors in the pediatric population. Major gaps of understanding the role of excess adiposity in levels of microparticles, EMPs, and activated EMPs, and their relationship with traditional CVD risk factors and subclinical measures of CVD limit the ability to move these biomarkers toward potential utility within clinical research.

Therefore, the goal of this study was to examine the relationship of microparticles, EMPs, and activated EMPs with adiposity, traditional CVD risk factors, and subclinical CVD measures. We hypothesized that youth with overweight/obesity or severe obesity would have higher levels of microparticles, EMPs, and activated EMPs as compared with youth with normal weight. We additionally hypothesized that higher levels of microparticles, EMPs, and activated EMPs would be associated with traditional CVD risk factors, arterial stiffness (measured by PWV, carotid cross‐sectional distensibility [cCSD], carotid artery cross‐sectional compliance [cCSC], a carotid incremental elastic modulus [cIEM], and vascular wall structure carotid intima‐media thickness [cIMT]). We have previously reported on the reproducibility of microparticles and EMPs among children and adolescents by demonstrating limited change in each of the microparticle indices (total microparticles, EMPs, and percent active EMPs) between visits separated by 1 week. ¹³

METHODS

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Study Design and Participants

Two hundred eighty children and adolescents recruited from 2011 to 2016 with EMP measurement data from a larger cross‐sectional study, reported in detail elsewhere, were used for this analysis. ¹⁴ , ¹⁵ The cohort consisted of participants with obesity (≥95th to <1.2 times the 95th body mass index [BMI] percentile) and severe obesity (≥1.2 times the 95th BMI percentile) who were recruited from the University of Minnesota Masonic Children's Hospital Pediatric Weight Management Clinic. Participants with normal weight (<85th BMI percentile) and overweight (85th to <95th BMI percentile) were recruited from general pediatric clinics in the community (the greater Minneapolis and St. Paul metropolitan area) and by advertisement. Individuals with obstructive sleep apnea, obesity from a known genetic cause, history of bariatric surgery, use of medication affecting endothelial health, and diagnosis of chronic conditions that may affect endothelial health were excluded. Demographic data including age, sex, race/ethnicity, smoking status, secondhand smoking status, eligibility for free or reduced cost lunch, and highest level of parent/guardian education were collected. We categorized race as either White or Non‐White because of small sample sizes of Non‐White subcategories. The study protocols were approved by the University of Minnesota Institutional Review Board, and consent/assent was obtained from participants or their guardians.

Anthropometrics, Pubertal Maturation, and Body Composition

BMI (kg/m²) was calculated using height squared (m²) and weight (kg), which were measured using a wall‐mounted stadiometer and electronic scale, respectively. BMI percentile was determined using age‐ and sex‐specific values from the Centers for Disease Control and Prevention. ¹⁶ , ¹⁷ Sexual maturity was measured using Tanner stage (stage 1: immature and stage 5: fully mature) by a trained physician or registered nurse. Body composition was measured using dual X‐ray absorptiometry (iDXA; GE Healthcare, Madison, WI) and analyzed using enCore version 16.2 (GE Healthcare). Visceral adipose tissue (VAT) was estimated within the android region using CoreScan (GE Healthcare). Percent VAT (%VAT) was calculated by dividing VAT (g) by total body fat mass (g) × 100. These were all reported previously. ¹⁴ , ¹⁸ , ¹⁹ , ²⁰

Microparticles, Endothelial Microparticles, and Activated EMPs

Measurement of microparticles and EMPs has been described in detail previously, and we recently established the reproducibility of these biomarkers in a pediatric population. ¹³ , ²¹ Whole venous blood was collected and processed for platelet‐free plasma (PFP) collection <3 hours after being drawn. PFP samples were prepared using serial centrifugations and then frozen as 100‐μL aliquots at −80°C. The measurement of microparticle was performed by using the flow cytometric method described by Nielsen et al ²² on a BD FACSAria III High Speed Cell sorter (BD Biosciences, San Diego, CA). To quantitate microparticles, the TruCount tube (BD Biosciences) was used for each sample for fluorescent labeling and flow cytometry analysis. Antibodies to identify endothelial cell–origin microparticles were (AF647)‐conjugated mouse anti‐human CD31, (PerCP‐ Cy5.5)‐conjugated mouse anti‐human CD144. Antibodies to identify activated endothelial cell–origin MP was (PE)‐conjugated mouse anti‐human CD106. All the fluorescence‐conjugated mouse anti‐human antibodies were purchased from BD Biosciences. Before running the PFP samples, microparticle‐size gate was established according to Nielsen's protocol by using a mixture of size‐calibrated fluorescent beads with the sizes of 0.1 μm (Invitrogen, Carlsbad, CA), 0.2 μm (Invitrogen), and Megamix beads (0.5, 0.9, and 3.0 μm; Biocytex, Marseille, France). Microparticles size ranging from 0.3 to 1.0 μm with or without lactadherin staining were collected for analysis. We defined EMP as microparticle with CD31(+)/CD41(−) plus microparticle with CD144(+)/CD31(−). Activated EMP was identified as EMP with CD106 (+). We then calculated the total microparticle per microliter PFP, total EMPs per microliter PFP, and activated EMPs (%) of total EMPs. A single‐flow cytometry technician analyzed all samples while being blinded to the adiposity group of each participant, which precludes the need to assess intertester reproducibility.

Cardiometabolic Risk Factors and Vascular Measures

Participants were fasted for >8 hours before testing. Seated blood pressure was measured 3 consecutive times, and the average of the last 2 measures was reported for systolic blood pressure (SBP) and diastolic blood pressure. High‐density lipoprotein cholesterol and triglycerides were measured and analyzed using standard procedures at the Fairview Diagnostics Laboratories at the Fairview‐University Medical Center (Minneapolis, MN), a Centers for Disease Control and Prevention–certified laboratory. C‐reactive protein, adiponectin, and oxidized low‐density lipoprotein cholesterol were assayed with multiplex in the University of Minnesota Cytokine Reference Laboratory. ¹⁴

A trained sonographer performed vascular testing in the Vascular Biology Laboratory in a quiet, temperature‐controlled environment. ²³ Patients had 15 minutes of quiet rest in the supine position, after which vascular images of the carotid artery including cIMT were obtained using a conventional ultrasound scanner (Acuson, Sequoia 512; Siemens Medical Solutions USA, Inc., Mountain View, CA) with a 7.5‐MHz linear array probe. The transducer was held at a constant distance from the skin and at a fixed point over the common carotid artery, ≈1 cm proximal from the carotid bifurcation bulb, to capture the diastolic and systolic diameters of the lumen of the left common carotid artery. All images were digitized and analyzed using electronic wall‐tracking software (Vascular Research Tools 5; Medical Imaging Application, LLC). Images were collected at 20 frames per second for 10 seconds (200 frames) to ensure the capture of full arterial diameter change during a cardiac cycle. The mean diameter through the 10‐second cycle was used to calculate compliance and distensibility. To measure the carotid elasticity properties, the following formulas for distensibility and compliance were used:

• Cross‐sectional distensibility (CSD, %) was calculated as [($\pi$(0.5 D _max)²−$\pi$(0.5 D _min)²)/$\pi$(0.5 D _min)²]×100%.

• Cross‐sectional compliance (CSC, 1/mm Hg) was calculated as [($\pi$(0.5 D _max)²− $\pi$(0.5 D _min)²)/($∆$ P)].

• Incremental elastic modulus (IEM, mm Hg) was calculated as 3 (1 + [($\pi$(0.5 D _max)²−$\pi$(0.5 D _min)²)]/CSC).

where D _min is the minimum (diastolic) arterial lumen diameter, a D _max is the maximum (systolic) arterial lumen diameter, and pulse pressure ($∆$ P) is calculated as the difference between SBP and diastolic blood pressure. ²³

Right radial and carotid artery waveforms, as well as carotid radial PWV, were recorded by applanation tonometry using SphygmoCor MM3 (AtCor Medical, Sydney, Australia, software version 8.0). Radial and carotid artery augmentation index, both corrected to a heart rate of 75 beats per minute, were derived from a validated integral transfer function applied by SphygmoCor MM3. PWV was measured by the sequential acquisition of pressure waveforms from the carotid and radial artery using the same tonometer. Carotid‐radial PWV was calculated from the transit time between the 2 arteries relative to the R wave within the ECG complex using the foot‐to‐foot method and the intersecting tangent algorithm. ¹⁴ , ²⁴ , ²⁵ , ²⁶ Although multiple technicians were involved in the data collection, the software program used for vascular image assessment and interpretation was automated and operator‐independent, minimizing any variability among technicians. ²³

Statistical Analysis

Descriptive statistics are presented as mean and SD for continuous variables and frequency and percentage for categorical variables. Because of smaller sample size compared with other groups, overweight and obesity groups were combined. Linear regression models were used to evaluate associations between the total log number of microparticles and EMPs with various measures of adiposity and CVD risk factors. Models examining SBP and diastolic blood pressure were adjusted for sex, age, and height while all other models were adjusted for Tanner stage and sex, where Tanner stage was a 3‐level categorical variable (I, II/III/IV, V). Results were exponentiated and represent ratios of geometric means. Logistic regression evaluated the associations between measures of adiposity, vascular stiffness, and vascular wall structure and the odds of high (70%–100%) versus low (0%–30%) activated EMPs after controlling for Tanner stage and sex. One data point was excluded because the value was neither high‐level nor low‐level. Graphical displays show unadjusted linear trends between various measures and log number of microparticles and EMPs stratified by sex. Graphs of activated EMPs include mean and 95% CI bars for high‐ and low‐level groups. All statistical analyses were performed using SAS software, version 9.4 (SAS Institute, Inc., Cary, NC) and R version 3.5.3 (R Foundation for Statistical Computing, Vienna, Austria).

RESULTS

Demographic Characteristics

Table 1 describes the demographics, microparticles, arterial stiffness, and vascular wall structure characteristics of the sample population. Among the 280 children and adolescents included in this study, the mean age was 12.7 ± 2.7 years (range, 8–20 years; 47.5% male; 76.8% White; and 11.8% Latino/Hispanic). Participants were distributed among 3 BMI categories: 112 normal weight, 77 overweight/obesity, and 91 severe obesity. Youth with overweight/obesity and severe obesity tended to be more advanced in Tanner stage compared with those with normal weight; 2.5% were current or previous smokers, 14.7% were secondhand smokers, and 12.4% were eligible for free or reduced price lunch. For those who responded to the question, 76.1% of the participants had parent or guardian with at least college‐level education.

Table 1.

Demographics, Microparticles, and Arterial Stiffness and Structure Characteristics of the Cohort

	N	Normal weight (N=112)	Overweight/obesity (N=77)	Severe obesity (N=91)
Age, mean (SD), y	280	12.5 (2.6)	12.5 (2.5)	13.1 (3.0)
Male, n (%)	280	62 (55.4)	36 (46.8)	35 (38.5)
White, n (%)	280	93 (83.0)	59 (76.6)	63 (69.2)
Latino/Hispanic, n (%)	279	7 (6.3)	8 (10.4)	18 (19.8)
Tanner stage	273
I, n (%)	…	45 (42.1)	21 (28.0)	12 (13.2)
II/III/IV, n (%)	…	52 (48.6)	44 (58.7)	63 (69.2)
V, n (%)	…	10 (9.4)	10 (13.3)	16 (17.6)
BMI, mean (SD), kg/m2	280	18.3 (2.4)	26.5 (3.6)	36.4 (6.6)
BMI percentile, mean (SD), %	279	47.6 (22.5)	95.5 (3.7)	99.3 (0.4)
BMI % of the 95th percentile, mean (SD), %	279	73.6 (6.5)	106.0 (10.0)	141.9 (18.0)
Visceral adipose tissue, mean (SD), %	278	0.8 (0.6)	1.5 (0.8)	2.4 (0.8)
Body fat, mean (SD), %	279	24.9 (5.9)	39.8 (7.1)	48.3 (5.0)
Microparticles, mean (SD), per microliter PFP	280	11853.5 (39013.9)	41682.5 (95725.6)	68211.1 (149957.2)
EMPs, mean (SD), per microliter PFP	280	532.0 (829.2)	901.3 (1008.8)	870.8 (903.0)
Active EMPs, mean (SD), %	280	33.3 (42.9)	43.9 (45.4)	42.0 (42.9)
PWV, mean (SD), m/s	277	6.6 (1.2)	6.6 (1.2)	6.5 (1.1)
cIMT, mean (SD), mm	266	0.54 (0.04)	0.52 (0.06)	0.47 (0.10)
cCSD, mean (SD), %	273	29.0 (6.1)	30.2 (6.5)	29.6 (7.3)
cCSC, mean (SD), mm Hg	273	0.16 (0.04)	0.16 (0.04)	0.15 (0.07)
cIEM, mean (SD), mm Hg	273	999 (264)	1067 (267)	1182 (368)
Smoking, n (%)	280
Never, n (%)	…	109 (97.3)	76 (98.7)	88 (96.7)
Current, n (%)	…	2 (1.8)	0 (0.0)	1 (1.1)
Previous, n (%)	…	1 (0.9)	1 (1.3)	2 (2.2)
Secondhand smoke, n (%)	279	3 (2.7)	9 (11.8)	29 (31.9)
Free/reduced price lunch, n (%)	194	11 (12.0)	2 (4.4)	11 (19.6)
Parent/guardian education, n (%)	134
Some high school, n (%)	…	1 (1.3)	1 (3.6)	3 (10.7)
High school/GED, n (%)	…	14 (18.0)	4 (14.3)	9 (32.1)
College graduate, n (%)	…	35 (44.9)	14 (50.0)	12 (42.9)
Postgraduate, n (%)	…	28 (35.9)	9 (32.1)	4 (14.3)

Normal weight, BMI <85th percentile; overweight/obesity, BMI 85th—<1.2 times the 95th percentile; severe obesity, BMI≥1.2 times the 95th percentile or BMI≥35 kg/m². BMI indicates body mass index; cCSD, carotid cross‐sectional distensibility; cIEM, carotid incremental elastic modulus; cIMT, carotid intima‐media thickness; EMPs, endothelial microparticles; GED, general equivalency diploma; PFP, platelet‐free plasma; and PWV, pulse wave velocity.

Relationship Between Microparticles and Body Composition

Figure 1 shows the distribution of microparticles and EMPs across adiposity level. Higher levels of microparticles were positively associated with each adiposity measure (BMI, %Body Fat, and %VAT) (slope of 0.063, 0.038, 0.382, respectively, with P<0.05 for all measures). In addition, higher levels of EMPs were positively associated with each adiposity measure (BMI, %Body Fat, and %VAT) (slope of 0.038, 0.026, 0.218, respectively, with P<0.05 for BMI and %Body Fat), although the association between the total number of EMP and %VAT were not statistically significant (P=0.076). Neither microparticles nor EMPs had linear trend differences between males and females (P>0.05 for all interaction terms).

Figure 1. Distribution of MPs and EMPs across adipose level by sex (unadjusted): (A) MPs versus BMI; (B) MPs versus %Body Fat; (C) MPs VAT; (D) EMPs versus BMI; (E) EMPs versus %Body Fat; (F) EMPs versus %VAT.

Linear association among males (red) and females (blue) are calculated for each graph and the slope is recorded. BMI indicates body mass index; MP, microparticle; PFP, platelet‐free plasma; and VAT, visceral adipose tissue.

Youth with overweight/obesity and severe obesity had 2.50 (95% CI, 1.56–4.01) and 3.42 (95% CI, 2.15–5.43) times the geometric means of the total number of microparticles, respectively, compared with those with normal weight (Table 2). Compared with those with normal weight, the geometric means of the total number of EMPs were 1.97 (95% CI, 1.09–3.55) and 2.34 (95% CI, 1.31–4.19) times in those with overweight/obesity and severe obesity, respectively. The geometric means of the total number of microparticles and EMPs were 1.04 (95% CI, 1.03–1.06) and 1.03 (95% CI, 1.01–1.05) times for each percent increase in %Body Fat, respectively. Each 1% higher %VAT was associated with 39% higher the geometric mean of the total number of microparticles (95% CI, 13–70), but the higher degree of EMPs failed to reach statistical significance (1.23; 95% CI, 0.95–1.57).

Table 2.

Association Between the Total Number of Microparticles and Endothelial Microparticles (EMPs) With Adiposity, Cardiovascular Diseases (CVD), and Arterial Stiffness and Structure Measures Adjusted for Tanner Stage and Sex

	Multiplicative difference in total microparticles (95% CI)	P value	Multiplicative difference in total EMPs (95% CI)	P value
BMI group
Normal weight	Ref	…	Ref	…
Overweight/obesity	2.50 [1.56–4.01]	<0.001	1.97 [1.09–3.55]	0.025
Severe obesity	3.42 [2.15–5.43]	<0.001	2.34 [1.31–4.19]	0.004
Body fat (%)	1.04 [1.03–1.06]	<0.001	1.03 [1.01–1.05]	0.007
Visceral adipose tissue (%)	1.39 [1.13–1.70]	0.002	1.23 [0.95–1.57]	0.111
SBP (per 5 mm Hg)*	1.24 [1.14–1.34]	<0.001	1.26 [1.14–1.39]	<0.001
DBP (per 5 mm Hg)*	1.13 [1.00–1.27]	0.053	1.11 [0.96–1.28]	0.158
Triglycerides/HDL ratio	1.33 [1.20–1.48]	<0.001	1.15 [1.00–1.31]	0.044
Oxidized LDL (per 1 U/L)	1.03 [1.02–1.04]	<0.001	1.02 [1.02–1.03]	<0.001
C‐reactive protein (per 1 g/L)	1.01 [0.99–1.04]	0.348	1.00 [0.97–1.04]	0.956
HMW adiponectin (per 1 mg/mL)	0.86 [0.80–0.92]	<0.001	0.86 [0.79–0.93]	<0.001
PWV (per 1 m/s)	1.22 [1.03–1.45]	0.022	1.31 [1.07–1.61]	0.011
cIMT (per 0.1 mm)	0.66 [0.50–0.87]	0.003	0.50 [0.36–0.68]	<0.001
cCSD (%)	0.95 [0.93–0.98]	0.002	0.95 [0.91–0.98]	0.002
cCSC (per 0.01 mm Hg)	0.94 [0.90–0.97]	0.001	0.93 [0.88–0.97]	0.003
cIEM (per 20 mm Hg)	1.03 [1.02–1.04]	<0.001	1.03 [1.01–1.04]	<0.001

Normal weight, BMI <85th percentile; overweight/obesity, BMI 85th to <1.2 times the 95th percentile; severe obesity, BMI≥1.2 times the 95th percentile or BMI≥35 kg/m². BMI indicates body mass index; cCSC, carotid cross‐sectional compliance; cCSD, carotid cross‐sectional distensibility; cIEM, carotid incremental elastic modulus; cIMT, carotid intima–media thickness; DBP, diastolic blood pressure; EMP, endothelial microparticle; HDL, high‐density lipoprotein; HMW, high‐molecular‐weight; LDL, low‐density lipoprotein; MP, microparticle; PWV, pulse wave velocity; and SBP, systolic blood pressure.

^*Adjusted for age, sex, and height.

Relationship Between Microparticles and Cardiometabolic Risk Factors

Figure 2 shows the distribution of microparticles and EMPs across arterial stiffness and structure measures. Microparticles have positive association across SBP, PWV, cIEM, and negative association across cIMT (slope of 0.046, 0.216, 0.002, −4.672, respectively, with P<0.05 for all measures). In addition, EMPs have positive association across SBP, PWV, cIEM, and negative association across cIMT (slope of 0.044, 0.276, 0.001, −7.156, respectively, with P<0.05 for all measures). There was no significant difference in distribution pattern between males and females (P>0.05 for all interaction terms).

Figure 2. Distribution of MPs and EMPs across arterial stiffness and structure measures by sex (unadjusted): (A) MPs versus SBP; (B) MPs versus PWV; (C) MPs versus cIMT; (D) MPs versus cIEM; (E) EMPs versus SBP; (F) EMPs versus PWV; (G) EMPs versus cIMT; (H) EMPs versus cIEM.

Linear association among males (red) and females (blue) are calculated for each graph and the slope is recorded. cIEM indicates carotid incremental elastic modulus; cIMT, carotid intima‐media thickness; PFP, platelet‐free plasma; PWV, pulse wave velocity; and SBP, systolic blood pressure.

Table 2 describes the association between the total number of microparticles and EMPs with CVD risk factors and arterial stiffness and vascular wall structure. Most of the measures of adiposity, CVD risk factors, and vascular health were statistically significantly associated with the total number of microparticles and EMPs. A 5‐mm Hg higher SBP, 1 unit higher triglyceride/high‐density lipoprotein ratio, and 1 U/L higher oxidized low‐density lipoprotein were associated with 1.24 (95% CI, 1.14–1.34), 1.33 (95% CI, 1.20–1.48), and 1.03 (95% CI, 1.02–1.04) times the geometric means of the total number of microparticles, respectively, and 1.26 (95% CI, 1.14–1.39), 1.15 (95% CI, 1.00–1.31), and 1.02 (95% CI, 1.02–1.03) times the geometric means of the total number of EMPs, respectively. A 1 mg/mL higher high‐molecular‐weight adiponectin value was negatively associated with both microparticles (0.86; 95% CI, 0.80–0.92) and EMPs (0.86; 95% CI, 0.79–0.93).

In addition, the measures of vascular health were statistically significantly associated with the number of microparticles and EMPs. A 1 m/s higher PWV and a 20‐mm Hg higher cIEM were associated with 22% and 3% higher the geometric means of the total number of microparticles and 31% and 3% higher the geometric means of the total number of EMPs, whereas cIMT, cCSD, and cCSC were all negatively associated with the total number of microparticles and EMPs. A 0.1‐mm higher cIMT, 1% higher cCSD, and 0.01‐mm Hg higher cCSC were associated with 0.66, 0.95, and 0.94 times the geometric means of the total number of microparticles and 0.50, 0.95, and 0.93 times the geometric means of the total number of EMPs, respectively.

Relationship Between Activated Endothelial Microparticles (%) and Body Composition

Figure S1 shows how adiposity level and arterial stiffness measures (BMI, %Body Fat, PWV, and cIEM) are distributed in each activated EMPs group and describes dichotomized level of activated EMPs (%) across all 4 measures. Logistic regression models show that youth with overweight/obesity/severe obesity had 1.84 times (95% CI, 1.08–3.14) the odds of having high activated EMPs (%) compared with those with normal weight when adjusted for Tanner stage and sex (Table 3). There was a positive association between activated EMPs with BMI (odds ratio [OR], 1.03; 95% CI, 1.00–1.06), %Body Fat (OR, 1.02; 95% CI, 1.00–1.05), and %VAT (OR, 1.11; 95% CI, 0.86–1.44). In addition, PWV (m/s) (OR, 1.44; 95% CI, 1.15–1.80) and cIEM (per 10 mm Hg) (OR, 1.01; 95% CI, 1.00–1.02) also showed positive association with activated EMPs (%). cIMT (per 0.1 mm) (OR, 0.61; 95% CI, 0.43–0.87), cCSD (%) (OR, 0.94; 95% CI, 0.91–0.98), and cCSC (per 0.01 mm Hg) (OR, 0.90; 95% CI, 0.84–0.96) had negative association with activated EMPs. Figure S2 presents additional information on distribution of microparticles and EMPs across other CVD risk and arterial stiffness and structure measures. Figure S2 also includes additional information on scatterplots for activated EMPs (%) across other adiposity and arterial stiffness and structure measures.

Table 3.

Association Between the Activated Endothelial Microparticles (EMPs) (%) With Adiposity and Arterial Stiffness and Structure Measures Adjusted for Tanner Stage and Sex

	High % activated EMPs (versus low)
	OR [95% CI]	P value
BMI group
Normal	Ref	Ref
Overweight/obesity/severe obesity	1.84 [1.08–3.14]	0.026
BMI, kg/m2	1.03 [1.00–1.06]	0.092
Body fat, %	1.02 [1.00–1.05]	0.064
Visceral adipose tissue, %	1.11 [0.86–1.44]	0.422
PWV, m/s	1.44 [1.15–1.80]	0.002
cIMT (per 0.1 mm)	0.61 [0.43–0.87]	0.006
cCSD, %	0.94 [0.91–0.98]	0.004
cCSC (per 0.01 mm Hg)	0.90 [0.84–0.96]	0.003
cIEM (per 20 mm Hg)	1.03 [1.01–1.04]	0.003

Normal weight, BMI <85th percentile; overweight/obesity/severe obesity, BMI≥85th percentile. BMI indicates body mass index; cCSC, carotid artery cross‐sectional compliance; cCSD, carotid cross‐sectional distensibility; cIEM, carotid incremental elastic modulus; cIMT, carotid intima‐media thickness; OR, odds ratio; and PWV, pulse wave velocity.

DISCUSSION

To our knowledge, this is the first study to provide evidence of higher levels of microparticles, EMPs, and activated EMPs among children and adolescents with severe obesity. In addition, we observed associations between each microparticle subclass (microparticles, EMPs, and activated EMPs) with traditional CVD risk factors (blood pressure, triglyceride/high‐density lipoprotein ratio, oxidized low‐density lipoprotein, C‐reactive protein, and high‐molecular‐weight adiponectin) and measures of subclinical CVD risk (PWV, cIMT, cCSD, cCSC, and cIEM). This study represents another step toward the validation of microparticles and EMPs as potential novel biomarkers of subclinical CVD among children and adolescents.

Our finding that microparticles and EMPs levels are higher in youth with higher adiposity level is congruent with many other biomarkers of CVD risk, including other markers of subclinical endothelial dysfunction. ¹⁴ , ²⁷ , ²⁸ , ²⁹ , ³⁰ There are a number of reasons for the underlying association between adiposity and microparticle/EMP levels, including higher inflammation, dysregulated coagulation, and the independent role obesity may have on nitric oxide availability through a cascade of events. ¹⁰ , ³¹ , ³² , ³³ However, this study does not provide the evidence for a causal link, and the underlying cause requires further investigation. Importantly, our data are consistent with observations from previous studies with adult population. Esposito et al described higher EMP levels among women with obesity and demonstrated a significant correlation (r=−0.56) of EMPs with endothelium‐dependent vasodilation in the brachial artery. ¹⁰ In addition, Amabile et al described the associations between EMPs and CVD risk factors using the Framingham Heart Study Offspring Study. This study included a community cohort of 844 individuals and presented that EMP levels were associated with several CVD risk factors, including higher triglyceride levels, hypertension, metabolic syndrome, and lower high‐density lipoprotein cholesterol. ⁹ Whether there is a causal link between obesity mediating endothelial dysfunction through EMPs requires further investigation and cannot be elucidated from this cross‐sectional study.

One potentially important novel finding from our study is the distribution of activated EMPs, where we observed a dichotomized distribution (between 0 and 30% or 70% to 100%), suggesting high or low activation of EMPs may be a potential phenotype. Although the underlying cause of this distribution was not clear, we did observe that high levels of activated EMPs (%) were associated with higher BMI, body fat, PWV, and cIEM. We did not anticipate the dichotomized distribution, nor has it been previously reported, and thus represents an important area for future exploration.

Our study has strengths and limitations. For a pediatric study, the sample size was relatively large with a varied demographic distribution. Moreover, our study has representation of individuals within each BMI category, which is often underappreciated in pediatric biomarker research. Our study is limited by the relatively small number of participants with overweight and obesity that were combined as 1 group, lack of longitudinal timepoints to examine temporal relationships, and an inability to determine causal versus correlative relationships. In addition, there was no randomization because of the nature of cross‐sectional study and we did not address racial differences. Uneven racial distribution may introduce bias to the study. Lastly, no adjustment for multiple testing was performed. A potential next step to this study would be examining the association between degree of adiposity and EMP levels with a longitudinal study with deep characterization of robust markers of CVD risk, including weight management therapies/treatments such as lifestyle modification, pharmacotherapy, and bariatric surgery in a pediatric population.

In conclusion, higher levels of microparticles, EMPs, and activated EMPs are associated with excess adiposity and markers of subclinical CVD risk in children and adolescents. The potential role of microparticles and EMPs as useful biomarkers of CVD risk appears promising and merits further study.

Sources of Funding

Research reported in this publication was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number R01HL110957 (awarded to A.S.K.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Additional support was provided by the National Center for Advancing Translational Sciences (UL1TR002494) and an individual National Research Service Award from the National Heart, Lung, and Blood Institute (F32 HL127851‐01 to J.R.R).

Disclosures

J. Ryder receives donation of drug/placebo from Boehringer Ingelheim. A. Kelly serves as an unpaid consultant for Novo Nordisk, Vivus, Eli Lilly, and Boehringer Ingelheim as well as receives donated drug/placebo from Vivus for a National Institutes of Health‐funded clinical trial. Dr Fox receives research support from Novo Nordisk. The other authors have no disclosures to report.

Supporting information

Figure S1

Figure S2