ATHENA Study – The Role of Circulating Plasma MicroRNAs in Paediatric Patients with Untreated Primary Hypertension: Baseline Expression and Exercise-Induced Changes

Abstract

Introduction

The role of microRNA in primary hypertension (PH) remains unclear. This study examined the expression of microRNA-16, -21, -27a, -27b, -133a, and -145 in untreated hypertensive children, their response to aerobic exercise, and correlations with blood pressure (BP) and related parameters.

Methods

A pre-post observational, hypothesis-generating study included 56 hypertensive (study group [SG]) and 59 healthy children (control group [CG]). Plasma microRNA levels and clinical, biochemical, BP, vascular, and hypertension-mediated organ damage (HMOD) parameters were assessed before and after one session of standardized aerobic exercise.

Results

The baseline relative microRNA-27b (p < 0.001) and microRNA-133a (p = 0.018) expressions were significantly lower in the SG; similarly, after an exercise bout. After an exercise bout, the expression of microRNA-27b, -133a, and -145 increased in CG, whereas only the expression of microRNA-145 increased in SG. In SG, microRNA-16, -21, -27a, and -145 correlated positively with pre-exercise BP. There were no correlations between the analysed microRNA particles and parameters of HMOD. ROC analysis identified the best prognostic profile for relative microRNA-27b expression as a potential biomarker of the absence of PH. Multivariate analysis revealed the relative microRNA-16 expression as the only significant predictor of elevated diastolic BP.

Conclusions

MicroRNA-27b and microRNA-133a are underexpressed in children with PH. These particles may represent potential markers of hypertension in children and may also be associated with a lower burden of hypertension-related alterations. MicroRNA-16 may serve as a marker of diastolic hypertension.

Introduction

Arterial hypertension (AH) affects 3–5% of children globally [1]. While secondary hypertension (SH) is more common in early childhood, the rising obesity epidemic has led to an increasing prevalence of primary hypertension (PH), now the dominant form in adolescents [2]. Recent studies suggest that PH accounts for approximately half of all cases of AH during the developmental period [3]. Children diagnosed with AH have a higher risk of cardiovascular events compared with normotensive peers [4]. Thus, improved detection, follow-up, and control of paediatric hypertension might reduce the risk of adult cardiovascular disease.

MicroRNAs have recently gained attention for their presumed role in hypertension pathogenesis [5]. Their discovery was recognized with a Nobel Prize (2024), and emerging therapies, such as zilebesiran, show promise in lowering blood pressure (BP) for up to 24 weeks after injection [6]. Despite significant research in adults, studies of microRNAs in paediatric PH are scarce [7].

Many complex factors and interactions influence the development of PH: genetic and environmental factors, the renin-angiotensin-aldosterone system, the sympathetic nervous system, and substances produced by the vascular endothelium [8]. However, the exact process of hypertension development is not yet fully understood, and the molecular pathways remain to be elucidated [2]. One of the fascinating clues that have yet to be fully explored in the pathogenesis of hypertension is epigenetic changes, including microRNA-mediated gene regulation. They might be a key but an underexplored aspect [9]. MicroRNA expression also changes with exercise [10], which is a well-established non-pharmacological approach to BP control [11]. Post-exercise hypotension, observed for up to 24 h after physical activity, further underscores the role of exercise in hypertension management [12].

MicroRNA-16 is recognized as an essential regulator of vascular smooth muscle cell (VSMC) growth and migration and participates in angiotensin II-mediated signalling in these cells. Its overexpression is also thought to inhibit VSMC proliferation [13]. Notably, microRNA-16 appears to exert a bidirectional influence on inflammatory processes – acting in an anti-inflammatory manner by promoting the secretion of IL-10 and TGF-β, or conversely, enhancing inflammation by stimulating NF-κB activation and increasing IL-8 production [14, 15]. Several studies have demonstrated elevated circulating plasma levels of microRNA-21 in hypertensive patients with hypertension-mediated organ damage (HMOD) [16, 17]. Other clinical investigations have reported a positive correlation between microRNA-21 levels and both BP values [18] as well as carotid intima-media thickness [19], and a negative association with arterial stiffness [20]. MicroRNA-27a and microRNA-27b have emerged as potent molecules of interest, acting as positive regulators of angiogenesis [21] and contributing to the regulation of endothelial cell repulsion – processes essential for the formation of a functional vascular network [22]. Furthermore, it has been suggested that both microRNA-27a and microRNA-27b may inhibit angiotensin-converting enzyme (ACE) expression by targeting specific binding sites within ACE transcripts [23]. MicroRNA-133a has similarly attracted attention, with studies reporting lower expression levels in patients with PH compared to healthy controls, as well as significant correlations with BP parameters [24]. Its expression has also been independently associated with urinary albumin excretion [25], and notably, circulating levels of microRNA-133a increase in healthy individuals following exercise [26]. Santovito et al. [27] reported significantly higher microRNA-145 levels within atherosclerotic plaques from hypertensive patients undergoing carotid endarterectomy. In contrast, Özkan et al. [28] observed significantly lower circulating microRNA-145 levels in newly diagnosed patients with PH during cohort follow-up, suggesting a potentially context-dependent role of this microRNA in hypertension.

Thus, we selected the six aforementioned microRNAs – microRNA-16, microRNA-21, microRNA-27a, microRNA-27b, microRNA-133a, and microRNA-145, as molecules with a potentially promising role in the development of PH. The study aimed to examine the expression of the six microRNAs in untreated adolescents with PH compared with healthy peers, assess changes in expression after exercise, and evaluate their correlations with BP and HMOD.

Materials and Methods

Study Design

The study employed a controlled single exercise session as an experimental intervention and standardized pre- and post-exercise analyses and measurements in a group of children with PH and their healthy peers. Since random allocation to groups was not feasible – group membership being determined by the presence or absence of pre-existing hypertension – the design qualifies as quasi-experimental, combining a pretest-post-test design and a nonequivalent groups design. Accordingly, the study should also be regarded as an observational, hypothesis-generating investigation.

The study protocol was reviewed and accepted by the National Science Centre in Poland (grant No. 2021/41/N/NZ5/04194) and approved by the Bioethics Committee of the Medical University of Warsaw (KB 154/2020). All procedures adhered to the highest ethical standards set by the Institutional Research Committee and were conducted in accordance with the principles of the Declaration of Helsinki and its subsequent amendments. The study protocol is summarized in Figure 1 and described in detail in online supplementary Table 1 (for all online suppl. material, see https://doi.org/10.1159/000552984). In brief, patients enrolled in the study underwent a cardiopulmonary exercise test (CPET) to determine the anaerobic threshold, which was used to standardize the training session. Two to 6 weeks after this test – to avoid the influence of maximal exertion on microRNA levels (see circulating microRNA kinetics and justification of the CPET interval in online supplementary Methods Section) – participants were invited for the first part of the study (day 1). The following day (day 2), participants performed a 60-min cycle ergometer exercise session in the afternoon, using a workload determined by the CPET results. After the exercise test, a new ambulatory blood pressure monitoring (ABPM) measurement was initiated. The next morning (day 3), blood, urine, and arterial examinations were repeated. All participants underwent the same protocol.

Fig. 1.

Summarized protocol of patients’ examinations. Cardiopulmonary exercise test (CPET) was performed 2–6 weeks before the study to determine individualized exercise intensity. Baseline assessments were conducted on the morning of day 1. A 60-min aerobic exercise session was performed approximately 36 h later. Second ambulatory blood pressure monitoring (ABPM) was initiated immediately after exercise. The remaining post-exercise assessments were performed on the morning of day 3 (12–16 h after exercise). Blood samples were collected after ≥10 h of fasting. BP, blood pressure; PWV, pulse wave velocity; cIMT, common carotid artery intima-media thickness; ECHO, echocardiography.

Study Groups

Participants were recruited from a single paediatric nephrology centre between November 2021 and June 2023. The study group (SG) included children with untreated PH diagnosed at our university hospital. The control group (CG) consisted of age- and sex-matched children without hypertension, who met the same exclusion criteria.

Inclusion criteria for the SG were as follows: a diagnosis of untreated AH based on current European guidelines [29], confirmed by ABPM [30]; height ≥120 cm; and written informed consent from a parent or legal guardian. Exclusion criteria included SH; severe renal, hepatic, or cardiac disease; inflammatory conditions; contraindications to physical exercise; and acute infections (temporary 2-week exclusion). Children with behavioural disorders, disabilities, or noncompliance with study procedures were also excluded. Secondary causes of hypertension were excluded based on clinical evaluation and a standardized diagnostic workup, including laboratory testing and imaging, as described in detail in the online supplementary Methods.

General Laboratory Procedures

All blood samples collected during the study (days 1 and 3 morning) were taken after at least 10 h of fasting (no meal) between 7 and 11 a.m. Blood sampling was conducted 12–16 h following the exercise session, not immediately after exertion. First, baseline blood was collected under controlled fasting and circadian conditions. Then, after the exercise, blood was drawn in the same conditions the next morning to assess sustained changes in circulating microRNA levels while maintaining comparability with baseline measurements. The supplementary materials describe the exact centrifugation conditions and the various sample processing steps (see supplementary methodology: evaluation of microRNA). All urine samples were the first morning samples. BP measurements and vascular tests were performed on each patient in the morning after fasting. Immediately after the exercise session, 24 h ABPM was initiated.

Basic Clinical, Biochemical, BP, and Arterial Parameters

To avoid residual exertional effects on baseline biochemical or molecular analyses, a CPET was conducted at least 2 weeks before blood, urine, and BP assessments (see circulating microRNA kinetics and justification of the CPET interval in online supplementary Methods Section). Our previous manuscripts provide a detailed description of the methodology used for these parameters, including the preliminary study conducted to ensure proper study protocol management [7, 31]. Among measured parameters were as follows: NLR, neutrophil-to-lymphocyte ratio; MLR, monocyte-to-lymphocyte ratio; SBP, systolic blood pressure; office: DBP, diastolic blood pressure; MAP, mean arterial pressure; AoSBP, aortic systolic blood pressure; AoDBP, aortic diastolic blood pressure; AoMAP, aortic mean arterial pressure; AIx75-HR, augmentation index at a heart rate of 75/min; Buckberg SEVR, subendocardial viability ratio; ESP, end systolic pressure; 24 h-hour, 24 h; ABPM [32]: SBP 24 h, DBP 24 h, MAP 24 h (and their Z-score values according to paediatric normalized reference values [32]); cSBP 24 h, central systolic blood pressure; cDBP 24 h, central diastolic blood pressure; PP 24 h, pulse pressure; PWV 24 h, pulse wave velocity; TVR 24 h, total vascular resistance, AIx-24 h, augmentation index; CO 24 h, cardiac output; SV 24 h, stroke volume; RM 24 h, reflection magnitude; ET, ECHO tracking; beta, stiffness index; Ep, pressure strain elasticity modulus; AC, arterial compliance; AI, augmentation index; D_max, maximal diameter of common carotid artery; D_min, minimal diameter of common carotid artery; DAT_max, acceleration time to common carotid artery maximal diameter. Additional details can be found in the online supplementary Materials.

Exercise Session

All participants underwent CPET (Cyclus 2, RMB elektronik-automation GmbH, Leipzig, Germany) to determine individualized exercise intensity. Subsequently, after 2–6 weeks, participants performed a 60-min supervised cycling session at 90–110% of the workload corresponding to each participant’s anaerobic threshold (AT), in accordance with ACSM recommendations for moderate-intensity exercise [33]. A detailed description of CPET and the standardized exercise protocol is provided in the online supplementary Methods.

HMOD and Vascular Parameters

Four indicators of HMOD were measured during the study: left ventricular mass index (LVMI) (g/m^2.7 or g/m²) [34, 35], urinary albumin excretion, common carotid artery intima-media thickness (cIMT), and carotid-femoral pulse wave velocity (cfPWV). cIMT and cfPWV equal to or greater than the 95th percentile for age and height were considered abnormal [36, 37]. An exact description of the technique was included in the online supplementary material.

All remaining vascular and haemodynamic parameters – including central BP indices, augmentation index, parameters derived from 24 h ABPM, as well as ultrasound- and applanation tonometry-derived measures of vascular stiffness – were treated as exploratory variables and used for comprehensive characterization of cardiovascular function in the study population; accordingly, results derived from these exploratory variables should be interpreted as hypothesis-generating.

Evaluation of microRNA

MicroRNA extraction was performed using mirVana PARIS kits (Thermo Fisher Scientific, Waltham, MA, USA) per the manufacturer’s instructions. C. elegans miRNAs, cel-microRNA-39 and cel-microRNA-54 (synthetic RNA oligonucleotides synthesized by Thermo Fisher), were added in equal amounts to each sample: immediately after combining the plasma sample with the denaturing solution (cel-microRNA-39) and at the beginning of the poly(A) tailing reaction (cel-microRNA-54) [38]. Total RNA was isolated from plasma samples without the use of an enrichment procedure for small RNAs. RNA quantity, quality, and purity were assessed via NanoDrop Lite (Thermo Fisher Scientific, Waltham, MA, USA). Reverse transcription was conducted with TaqMan kits, followed by real-time PCR using TaqMan Advanced microRNA Assays (Thermo Fisher Scientific, Waltham, MA, USA) and the LightCycler 480 II (Roche Diagnostics GmbH, Mannheim, Germany). All samples were run in triplicate. Each assay was run with 2 no-template controls to rule out nonspecific amplification. No sample included in the study demonstrated a Ct value near the no-template control or exceeded 40 cycles.

Data were analysed using LightCycler 480 II software, with relative microRNA levels calculated via the 2^−ΔΔCt method [39]. In addition to two spike-in normalizers, one randomly selected sample was used as a calibrator (reference sample) across all qPCR runs to enable relative quantification using the 2^−ΔΔCt method. qPCR runs to ensure inter-run comparability, and miRNA expressions were expressed as 2^−ΔΔCT [40] (all the data normalization is present as online suppl. file 1). Expression levels were log 10-transformed for statistical analysis. All microRNA sequences and accession numbers (https://www.mirbase.org/) are listed in online supplementary Table 2 for reference and further study.

Statistical Methods

A sample size assessment based on previous microRNA studies in adult hypertensive patients [16, 19, 20, 24, 28], indicated that 55 participants per group would be required (power 0.80, p = 0.05, Δr = 0.4) (online suppl. Fig. 1). Assuming a 20% dropout rate, we recruited 140 patients. Statistical analyses were performed using Dell Statistica 13.0 PL (TIBCO Software Inc.) and SPSS 22.0 (IBM Corp.). Data distribution was assessed using the Shapiro-Wilk test. Continuous variables were expressed as mean ± SD and interquartile range, and categorical variables as percentages. All tests were two-sided with a significance level of p < 0.05.

Group comparisons were performed using Student’s t test or Mann-Whitney U test and paired comparisons using paired t test or Wilcoxon test, as appropriate. Correlations were assessed using Spearman’s or Pearson’s coefficients. Multivariable regression and ROC analyses were performed to identify predictors of hypertension. Detailed further statistical procedures are described in the online supplementary Methods.

Results

Five participants, including three from the study group and two from the control group, were unable to complete CPET despite repeated attempts (3) and were excluded prior to the intervention (online suppl. S2 Figure). During the exercise protocol, 3 participants, 2 from the study group and 1 from the control group, did not complete the session at the first attempt due to transient factors. All subsequently repeated the protocol after the predefined interval of 2–6 weeks, resulting in a final sample of 56 participants in the SG and 59 in the CG who completed all study phases and had complete data (online suppl. S2 Figure). Tables 1 and 2 and online supplementary Table 3 summarize the data obtained during both groups’ measurements and the parameters’ values tested before and after the standardized training session.

Table 1.

Comparison of the studied parameters in the study and control group (baseline value)

Parameter	Study group±SD (IQR)	Control group±SD (IQR)	p value
Number of patients (n)	56	59	N/A
Age, years	15.4±1.9 (14.3–16.9)	15.3±1.6 (13.8–16.6)	0.435
Boys/girls	42/14	41/18	0.378
Hypertensive mother, %	29%	8%	0.053
Hypertensive father, %	50%	29%	0.020
Height, cm	173.1±8.8 (167.0–179.0)	171.7±10.5 (165.0–180.0)	0.731
Height Z-score	0.64±1.04 (−0.05–1.30)	0.57±1.00 (−0.24–1.20)	0.461
Weight, kg	80.2±19.7 (66.5–87.5)	61.7±11.5 (55.0–69.0)	<0.001
Weight Z-score	1.51±1.10 (0.73–2.27)	0.43±0.84 (0.01–1.03)	<0.001
BMI, kg/m2	26.8±6.6 (22.5–30.1)	20.9±3.4 (18.7–22.4)	<0.001
BMI Z-score	1.39±1.1 (0.68–2.22)	0.16±1.1 (−0.42–0.83)	<0.001
Waist circumference, cm	84.9±15.0 (74.5–90.4)	71.1±6.7 (67.5–74.5)	<0.001
Hip circumference, cm	100.8±12.0 (92.8–106.5)	91.4±8.2 (86.5–96.0)	<0.001
WHR	0.84±0.11 (0.79–0.88)	0.78±0.04 (0.75–0.81)	<0.001
Duration of hypertension, months	10.2±14.0 (1.0–12.5)	0	N/A
Duration of pregnancy, weeks	38.5±2.5 (37.3–40.0)	38.7±1.9 (38.0–40.0)	0.797
Birth weight, g	3,252±550 (3,073–3,500)	3,324±583 (3,160–3,650)	0.185
Sodium serum, mmol/L	139.3±2.0 (138.0–140.5)	139.33±2.1 (138.0–140.0)	0.950
Potassium serum, mmol/L	4.28±0.23 (4.10–4.43)	4.243±0.30 (4.05–4.50)	0.460
Uric acid, mg/dL	5.8±1.1 (5.1–6.6)	5.0±0.9 (4.5–5.7)	<0.001
Cholesterol, mg/dL	163.3±34.2 (137.0–187.0)	155.4±30.3 (136.0–168.00)	0.154
LDL cholesterol, mg/dL	91.1±26.9 (74.0–104.0)	83.6±25.4 (67.0–95.0)	0.091
HDL cholesterol, mg/dL	52.3±15.0 (42.5–59.5)	57.6±11.7 (49.0–65.3)	0.009
Triglycerides, mg/dL	99.8±46.0 (64.5–126.5)	71.1±24.8 (57.0–80.0)	<0.001
eGFR, mL/min/1.73 m2	108.7±18.3 (97.5–121.8)	107.0±17.3 (92.4–117.0)	0.603
Renin, mU/L	34.4±21.6 (18.8–44.7)	35.8±25.0 (21.0–44.1)	0.838
Aldosterone, ng/dL	12.1±7.8 (7.4–13.8)	12.8±6.6 (7.6–16.9)	0.383
PAC/PRC	0.40±0.2 (0.25–0.52)	0.45±0.3 (0.26–0.57)	0.467
NLR	1.65±0.8 (1.09–1.93)	1.79±3.2 (0.95–1.57)	0.014
PLR	130.12±38.7 (100.43–150.89)	118.91±37.7 (93.75–139.26)	0.082
MLR	0.26±0.1 (0.20–0.28)	0.28±0.3 (0.20–0.29)	0.889
MNR	0.18±0.08 (0.12–0.22)	0.19±0.06 (0.15–0.22)	0.086
ACR, mg/g	12.32±22.0 (2.77–9.22)	8.12±8.0 (3.58–9.10)	0.332
U. Na/creat, mmol/mg	0.75±0.46 (0.39–1.00)	0.75±0.42 (0.49–0.92)	0.714
U. K/creat, mmol/mg	0.23±0.14 (0.16–0.26)	0.21±0.19 (0.13–0.24)	0.119
U. UA/creat, mg/mg	0.28±0.10 (0.21–0.34)	0.33±0.16 (0.23–0.37)	0.109
U. Ca/creat, mg/mg	0.07±0.05 (0.03–0.10)	0.09±0.06 (0.05–0.13)	0.017
U. P/creat, mg/mg	0.68±0.17 (0.53–0.78)	0.78±0.43 (0.60–0.86)	0.098
SBP, mm Hg	136.8±10.4 (131.0–145.5)	118.8±9.6 (113.0–126.0)	<0.001
SBP Z-score	1.82±0.86 (1.34–2.38)	0.25±0.81 (−0.34–0.85)	<0.001
DBP, mm Hg	82.1±8.1 (76.0–88.0)	72.9±6.3 (69.0–77.0)	<0.001
DBP Z-score	2.24±1.13 (1.44–3.06)	1.00±0.81 (0.44–1.52)	<0.001
MAP, mm Hg	98.3±7.7 (92.9–103.0)	86.8±6.6 (81.7–91.7)	<0.001
HR, 1/min	75.9±13.2 (66.9–84.3)	68.8±11.0 (62.2–74.0)	0.001
SBP 24 h, mm Hg	131.2±9.5 (124.0–137.5)	114.9±6.9 (109.0–121.0)	<0.001
DBP 24 h, mm Hg	73.6±6.6 (68.0–78.0)	66.1±5.1 (64.0–69.0)	<0.001
MAP 24 h, mm Hg	100.0±7.3 (94.0–105.0)	88.5±5.1 (85.0–92.0)	<0.001
PP 24 h, mm Hg	57.1±6.9 (53.0–60.0)	48.3±6.7 (43.0–52.0)	<0.001
HR 24 h, 1/min	73.5±9.1 (67.0–79.5)	71.2±9.7 (63.0–79.0)	0.146
cSBP 24 h, mm Hg	114.5±8.5 (108.0–119.5)	100.4±5.5 (96.0–104.0)	<0.001
cDBP 24 h, mm Hg	76.0±6.8 (70.0–80.5)	67.9±5.2 (65.0–72.0)	<0.001
AIx@75-HR 24 h, %	15.0±6.2 (10.0–18.5)	12.2±6.2 (8.0–15.0)	0.013
PWV 24 h, m/s	4.7±0.46 (4.0–5.0)	4.0±0.18 (4.0–4.0)	<0.001
SV, mL	74.6±7.7 (71.0–80.5)	73.6±10.4 (65.0–82.0)	0.561
CO, L/min	4.79±0.41 (5.00–5.00)	4.51±0.50 (4.00–5.00)	0.010
TVR, dyn*s/cm5	1,552.5±125.8 (1,447.0–1,612.5)	1,461.5±106.8 (1,375.0–1,540.0)	<0.001
RM, %	57±6.4 (54–62)	54±5.4 (50–57)	0.003
Systolic DIP, %	11.0±6.0 (7.1–14.8)	10.6±4.6 (7.3–13.5)	0.676
Diastolic DIP, %	14.0±6.9 (8.4–19.1)	17.5±6.0 (13.4–22.1)	0.005
LVMI, g/m2.7	33.02±8.17 (26.64–37.78)	28.12±5.90 (22.68–34.09)	<0.001
LVMI, g/m2	74.59±17.92 (63.19–85.44)	70.83±13.98 (62.96−81.60)	0.210
LVMI Z-score	−0.554±1.474 (−1.465–0.415)	−1.334±1.455 (−2.510 to −0.050)	0.003
cfPWV, m/s	5.26±0.71 (4.77–5.63)	4.69±0.60 (4.20–5.07)	<0.001
cfPWV Z-score	−0.19±0.95 (−0.81–0.23)	−0.96±0.80 (−1.49 to −0.30)	<0.001
AoSBP, mm Hg	114.9±8.6 (110.2–119.1)	100.7±7.7 (94.0–107.0)	<0.001
AoDBP, mm Hg	83.5±8.1 (77.1–89.0)	74.2±6.4 (70.0–78.5)	<0.001
AoMAP, mm Hg	98.3±7.7 (92.9–103.0)	86.8±6.6 (81.7–91.7)	<0.001
AIx, %	−6.78±11.86 (−15.84–1.10)	−4.64±10.77 (−13.50–1.00)	0.254
AIx@HR75, %	−6.47±11.85 (−14.75–2.53)	−7.79±10.09 (−13.75 to −2.20)	0.778
Buckberg SEVR	184.7±47.3 (151.5–209.1)	190.7±33.5 (166.7–214.2)	0.147
ESP, mm Hg	105.5±9.1 (100.2–109.5)	92.7±7.7 (86.3–99.0)	<0.001
cIMT, mm	0.48±0.06 (0.45–0.52)	0.46±0.04 (0.43–0.49)	0.067
cIMT Z-score	1.77±1.12 (1.04–2.58)	1.46±0.89 (0.67–2.07)	0.108
ET beta	3.3±0.7 (2.7–3.6)	3.0±0.6 (2.7–3.3)	0.451
ET Ep, kPa	45.9±11.5 (38.5–51.5)	37.5±8.2 (32.0–42.5)	<0.001
ET AC, mm2/kPa	1.30±0.30 (1.11–1.46)	1.48±0.36 (1.18–1.73)	0.007
ET AI, %	−4.8±11.4 (−11.48–0.45)	−6.0±9.5 (−13.8 to −0.9)	0.814
ET PWVβ, m/s	4.1±0.5 (3.8–4.3)	3.7±0.4 (3.5–4.0)	<0.001
ET Dmax, mm	6.75±0.62 (6.32–7.14)	6.46±0.51 (6.07–6.76)	0.024
ET Dmin, mm	5.81±0.62 (5.33–6.10)	5.53±0.48 (5.24–5.76)	0.066
ET DATmax, ms	134.0±32.3 (116.0–142.8)	134.2±17.4 (120.5–142.0)	0.102

SD, standard deviation; IQR, interquartile range; N/A, non-applicable; BMI, body mass index; WHR, waist-to-hip ratio; LDL, low-density lipoprotein; HDL, high-density lipoprotein; eGFR, estimated glomerular filtration rate; PAC, plasma aldosterone concentration; PRC, plasma renin concentration; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; MLR, monocyte-to-lymphocyte ratio; MNR, monocyte-to-neutrophil ratio; ACR, albumin-to-creatinine ratio; U, urine; Na, sodium; K, potassium; UA, uric acid; Ca, calcium; P, phosphorus; creat, creatinine; SBP, systolic blood pressure; DBP, diastolic blood pressure; MAP, mean arterial pressure; HR, heart rate; PP, pulse pressure; 24 h, 24-hour; c, central blood pressure; AIx@75-HR, augmentation index normalized to heart rate of 75 beats per minute; PWV, pulse wave velocity; SV, stroke volume; CO, cardiac output; TVR, total vascular resistance; RM, reflection magnitude; DIP, blood pressure night dipping; LVMI, the left ventricular mass index; cf, carotid-femoral; Ao, central blood pressure (aortic); AIx, augmentation index; Buckberg SEVR, subendocardial viability ratio; ESP, end systolic pressure; cIMT, common carotid artery intima-media thickness; ET, ECHO tracking; beta, stiffness index; Ep, pressure strain elasticity modulus; AC, arterial compliance; AI, augmentation index; D_max, maximal diameter of common carotid artery; D_min, minimal diameter of common carotid artery; DAT_max, acceleration time to common carotid artery maximal diameter.

Table 2.

Comparison of the studied parameters in the study group before and after the aerobic exercise session

Parameter	Before exercise	After exercise	p
	mean±SD (IQR)
Uric acid, mg/dL	5.8±1.1 (5.1–6.6)	6.3±1.4 (5.2–7.3)	<0.001
Creatinine, mg/dL	0.80±0.2 (0.66–0.95)	0.81±0.2 (0.67–0.93)	0.378
eGFR, mL/min/1.73 m2	108.7±18.3 (97.5–121.8)	107.6±19.7 (93.4–123.4)	0.287
Renin, mU/L	34.4±21.6 (18.8–44.7)	36.1±21.3 (20.5–47.7)	0.324
Aldosterone, ng/dL	12.1±7.8 (7.4–13.8)	13.8±6.5 (9.3–17.1)	0.054
PAC/PRC	0.40±0.2 (0.25–0.52)	0.45±0.2 (0.31–0.54)	0.081
ACR, mg/g	12.32±22.0 (2.77–9.22)	8.47±10.4 (2.87–8.01)	0.424
U. Na/creat, mmol/mg	0.75±0.46 (0.39–1.00)	0.50±0.34 (0.26–0.60)	0.002
U. K/creat, mmol/mg	0.23±0.14 (0.16–0.26)	0.20±0.08 (0.14–0.24)	0.071
U. UA/creat, mg/mg	0.28±0.10 (0.21–0.34)	0.32±0.10 (0.25–0.38)	0.007
U. Ca/creat, mg/mg	0.07±0.05 (0.03–0.10)	0.08±0.06 (0.04–0.11)	0.166
U. P/creat, mg/mg	0.68±0.17 (0.53–0.78)	0.67±0.20 (0.53–0.79)	0.726
SBP, mm Hg	136.8±10.4 (131.0–145.5)	133.1±9.8 (127.0–140.0)	0.006
SBP Z-score	1.82±0.86 (1.34–2.38)	1.51±0.78 (1.02–2.04)	0.006
DBP, mm Hg	82.1±8.1 (76.0–88.0)	78.6±7.6 (72.5–84.5)	<0.001
DBP Z-score	2.24±1.13 (1.44–3.06)	1.76±1.02 (0.98–2.44)	<0.001
MAP, mm Hg	98.3±7.7 (92.9–103.0)	94.9±7.3 (89.7–100.0)	<0.001
HR, 1/min	75.9±13.2 (66.9–84.3)	77.1±12.9 (68.4–83.1)	0.245
SBP 24 h, mm Hg	131.2±9.5 (124.0–137.5)	129.1±8.4 (123.5–135.0)	0.008
DBP 24 h, mm Hg	73.6±6.6 (68.0–78.0)	71.6±6.5 (67.0–75.5)	<0.001
MAP 24 h, mm Hg	100.0±7.3 (94.0–105.0)	98.1±6.6 (93.5–102.0)	0.001
PP 24 h, mm Hg	57.1±6.9 (53.0–60.0)	57.0±7.1 (51.5–61.0)	0.851
HR 24 h, 1/min	73.5±9.1 (67.0–79.5)	78.0±9.3 (72.0–82.5)	<0.001
cSBP 24 h, mm Hg	114.5±8.5 (108.0–119.5)	112.2±7.3 (107.5–116.5)	0.002
cDBP 24 h, mm Hg	76.0±6.8 (70.0–80.5)	74.2±6.7 (69.0–78.5)	<0.001
AIx@75-HR 24 h, %	15.0±6.2 (10.0–18.5)	16.3±5.9 (12.5–20.0)	0.002
PWV 24 h, m/s	4.7±0.46 (4.0–5.0)	4.6±0.48 (4.0–5.0)	0.370
SV, mL	74.6±7.7 (71.0–80.5)	71.8±8.2 (67.0–77.5)	<0.001
CO, L/min	4.79±0.41 (5.00–5.00)	4.89±0.37 (5.00–5.00)	0.033
TVR, dyn*s/cm5	1,552.5±125.8 (1,447.0–1,612.5)	1,491.9±94.0 (1,418.0–1,551.5)	<0.001
RM, %	57±6.4 (54–62)	55±6.6 (50–60)	<0.001
Systolic DIP, %	11.0±6.0 (7.1–14.8)	10.6±6.7 (5.5–15.4)	0.941
Diastolic DIP, %	14.0±6.9 (8.4–19.1)	15.4±7.2 (11.1–20.6)	0.112
cfPWV, m/s	5.26±0.71 (4.77–5.63)	5.22±0.68 (4.89–5.63)	0.388
cfPWV Z-score	−0.19±0.95 (−0.81–0.23)	−0.25±0.90 (−0.75–0.16)	0.366
AoSBP, mm Hg	114.9±8.6 (110.2–119.1)	111.2±7.8 (105.4–116.6)	<0.001
AoDBP, mm Hg	83.5±8.1 (77.1–89.0)	80.1±7.8 (74.4–86.8)	<0.001
AoMAP, mm Hg	98.3±7.7 (92.9–103.0)	94.9±7.3 (89.7–100.0)	<0.001
AIx, %	−6.78±11.86 (−15.84–1.10)	−6.61±10.45 (−14.35–0.71)	0.864
AIx@HR75, %	−6.47±11.85 (−14.75–2.53)	−5.54±11.06 (−13.88–2.10)	0.365
Buckberg SEVR	184.7±47.3 (151.5–209.1)	181.0±50.7 (145.1–200.6)	0.291
ESP, mm Hg	105.5±9.1 (100.2–109.5)	101.6±7.8 (96.0–106.9)	<0.001
ET beta	3.3±0.7 (2.7–3.6)	3.3±0.7 (2.7–3.6)	0.901
ET Ep, kPa	45.9±11.5 (38.5–51.5)	44.6±11.0 (36.5–50.5)	0.223
ET AC, mm2/kPa	1.30±0.30 (1.11–1.46)	1.35±0.27 (1.19–1.51)	0.141
ET AI, %	−4.8±11.4 (−11.48–0.45)	−6.8±8.7 (−12.8 to −4.0)	0.120
ET PWVβ, m/s	4.1±0.5 (3.8–4.3)	4.0±0.5 (3.7–4.3)	0.124
ET Dmax, mm	6.75±0.62 (6.32–7.14)	6.81±0.56 (6.44–7.13)	0.269
ET Dmin, mm	5.81±0.62 (5.33–6.10)	5.84±0.56 (5.44–6.15)	0.426
ET DATmax, ms	134.0±32.3 (116.0–142.8)	126.4±22.8 (111.9–135.6)	0.082

SD, standard deviation; IQR, interquartile range; eGFR, estimated glomerular filtration rate; PAC, plasma aldosterone concentration; PRC, plasma renin concentration; ACR, albumin-to-creatinine ratio; U, urine; Na, sodium; K, potassium; UA, uric acid; Ca, calcium; P, phosphorus; creat, creatinine; SBP, systolic blood pressure; DBP, diastolic blood pressure; MAP, mean arterial pressure; HR, heart rate; PP, pulse pressure; 24 h, 24-hour; c, central blood pressure; AIx@75-HR, augmentation index normalized to heart rate of 75 beats per minute; PWV, pulse wave velocity; SV, stroke volume; CO, cardiac output; TVR, total vascular resistance; RM, reflection magnitude; DIP, blood pressure night dipping; cf, carotid-femoral; Ao, central blood pressure (aortic); AIx, augmentation index; Buckberg SEVR, subendocardial viability ratio; ESP, end systolic pressure; ET, ECHO tracking; beta, stiffness index; Ep, pressure strain elasticity modulus; AC, arterial compliance; AI, augmentation index; D_max, maximal diameter of common carotid artery; D_min, minimal diameter of common carotid artery; DAT_max, acceleration time to common carotid artery maximal diameter.

Basic Clinical, Blood, and Urine Parameters

The groups did not differ in age, sex, height Z-scores, gestational age, or birth weight. However, the SG had significantly higher weight Z-scores, body mass index (BMI) Z-scores, waist and hip circumferences, and waist-hip-ratio. Kidney function and most biochemical parameters (total cholesterol, sodium, potassium, renin, aldosterone, aldosterone/renin ratio, and inflammatory markers) were similar. Significant differences were found in uric acid, HDL cholesterol, triglycerides, and NLR. After exercise, the SG had lower sodium-to-creatinine (p = 0.029) and phosphorus-to-creatinine (p = 0.001) excretion. Before exercise, the SG showed lower calciuria. Following exercise, the urinary sodium-to-creatinine ratio showed negative correlations with renin (R = −0.471, p < 0.001) and aldosterone levels (R = −0.465, p < 0.001) in the study group. In contrast, the urinary potassium-to-creatinine ratio exhibited a positive correlation with renin (R = 0.286, p = 0.028) in the control group.

BP and Vascular Parameters, Including HMOD

There was a significant difference in BP parameters between hypertensive and normotensive children, in terms of SBP, DBP, and their Z-scores, as well as parameters measured during 24 h: SBP 24 h, DBP 24 h, MAP 24 h, PP 24 h, cSBP 24 h, cDBP 24 h, PWV 24 h, and TVR 24 h before exercise. The groups did not differ in HR at the 24 h measurement.

In the SG, all BP indices, except for 24 h pulse pressure, decreased significantly after an exercise session. Conversely, in the CG, BP indices did not change except for a significant rise in 24 h systolic BP and 24 h pulse pressure.

Concerning HMOD, the groups differed in LVMI [g/m^2.7], LVMI Z-score, cfPWV and its Z-score, and central pressures AoSBP, AoDBP, AoMAP, and ESP, as well as in arterial parameters and local stiffness of the common carotid artery: ET Ep and ET-PVWB. No difference was found for AIx, AIx@75-HR, Buckberg SEVR index, ET beta, ET AC, ET AI, ET D_min, ET D_max, and ET DAT_max (using Bonferroni correction and Benjamini-Hochberg FDR corrections). There was a trend towards a higher mean cIMT value in the SG.

MicroRNA Expression

MicroRNA-27b expression was significantly higher (p < 0.001) in the control group than in the study group both before and after exercise, and its expression after physical exercise increased significantly only in the control group (Fig. 2). Similar relationships were observed in microRNA-133a expression across the studied groups: it was higher in the control group both before and after exercise, and it increased after physical exercise in the control group (Fig. 2). In multivariable linear regression analyses, hypertension status remained independently associated with both microRNA-27b and microRNA-133a expression after adjustment for BMI Z-score, age, and sex. Specifically, hypertensive patients exhibited lower microRNA-133a and microRNA-27b levels compared to controls (online suppl. S4 Table). These associations were consistent across models adjusted for different measures of body composition, including waist and hip circumference.

Fig. 2.

Alteration of analysed microRNAs between the groups and after a single training session. Individual microRNAs are presented in the following subpanels: (a) microRNA-21, (b) microRNA-16, (c) microRNA-27a, (d) microRNA-27b, (e) microRNA-133a, and (f) microRNA-145. PH, primary hypertension.

MicroRNA-27b was the best indicator for determining the presence or absence of hypertension among the subjects (Fig. 3). MicroRNA-133 was also a significant predictor of hypertension in the studied children, though with a lower AUC.

Fig. 3.

Heatmap (R-value) of correlations of microRNA expression levels in study group before exercise (baseline) and analyzed parameters. P-values < 0.05 are presented with *. BMI – body mass index, MLR - monocyte-to-limphocyte ratio, SBP – systolic blood pressure, DBP - diastolic blood pressure, MAP - mean arterial pressure, Ao - central (aortic), Buckberg SEVR - subendocardial viability ratio, Na – sodium, 24h – 24-hour, c – central blood pressure, A – after exercise, B – before exercise.

Among the six microRNAs tested, in multivariate analysis, microRNA-16 expression level was the best marker for predicting the 24 h DBP Z-score at the time of examination (Fig. 4, online suppl. Table S5). In the multivariate logistic regression model, high baseline expression of microRNA-16 was identified as an independent determinant differentiating patients with higher (>2.1) versus lower DBP Z-score values (Table 3).

Fig. 4.

Diagnostic utility of microRNAs based on baseline expression. Individual microRNAs are presented in the following subpanels: (a) baseline microRNA-27b expression, (b) receiver operating characteristic (ROC) curve for baseline microRNA-27b, (c) baseline microRNA-133a expression, and (d) receiver operating characteristic (ROC) curve for baseline microRNA-133a. PH, primary hypertension; AUC, area under the curve.

Table 3.

Multivariate logistic regression model including high level of microRNA-16 on the baseline and clinical data for PH severity based on >2.1 DBP Z-score

Variable	OR	Lower	Upper	p value
MicroRNA-16 high vs. low expression on baseline	4.556	1.130	18.376	0.033
Age	1.187	0.809	1.742	0.380
Gender	2.245	0.303	16.648	0.429
BMI	1.006	0.888	1.140	0.921
TVR 24 h	1.005	0.997	1.013	0.228

*Bolded p value indicates <0.05.

The study also revealed that microRNA-145 expression increased after exercise in both groups; however, no statistically significant differences were observed between groups at baseline or post-exercise (Fig. 4). Circulating levels of microRNA-16, microRNA-21, and microRNA-27a were comparable between the groups and remained unchanged following exercise.

The most significant results of the univariate analysis of associations between relative microRNA expression levels in SG and clinical and biochemical parameters are presented in Figure 5 (the heatmap). MicroRNA-27a and microRNA-133a positively correlated with BMI Z-scores (r = 0.313, p = 0.019; r = 0.485, p < 0.001), while microRNA-133a positively correlated with waist and hip circumference (r = 0.392, p = 0.003; r = 0.362, p = 0.006). As for biochemical parameters, we found the following significant correlations: between microRNA-133a and serum sodium before exercise bout (r = −0.283, p = 0.034); between microRNA-145 and MLR (r = −0.268, p = 0.046). MicroRNA-16, −27a, −27b, and -133a correlated negatively with aldosterone after an exercise bout. Regarding urinary indices, in the control group, post-exercise urinary sodium-to-creatinine ratio was negatively correlated with microRNA-16 (R = −0.311, p = 0.016) and microRNA-27a (R = −0.264, p = 0.044). At baseline, a positive correlation was observed between microRNA-133a and urinary uric acid-to-creatinine ratio (R = 0.258, p = 0.049). In contrast to the control group, no significant associations were found in the hypertensive group.

Fig. 5.

Boxplot and ROC curve for microRNA-16 baseline association on primary hypertension severity based on 24h DBP Z-score for a cut-off of 2.1.DBP - diastolic blood pressure; PH - primary hypertension; AUC - area under the curve.

Regarding BP before the exercise session, microRNA-16 correlated positively with peripheral and central office BP. MicroRNA-21 and -145 correlated positively with ABPM BP values. MicroRNA-27a correlated positively with office and ambulatory DBP. Also, microRNA-21, -27a, -27b, and -133a correlated negatively with Buckberg SEVR. No significant correlations between microRNA particle expression levels and the analysed indices of HMOD were observed.

Discussion

Our prospective, pre-post, observational, and hypothesis-generating study is the first to analyse microRNA expression in children with PH compared to healthy age- and sex-matched peers. We found lower expression levels of microRNA-27b and microRNA-133a in hypertensive children compared to the healthy group. In response to physical exertion, the expression of microRNA-27b, microRNA-133a, and microRNA-145 increased significantly in healthy children, whereas in hypertensive children, only microRNA-145 increased. Positive correlations were observed between the expression of microRNAs-16, -21, -27a, and -145 and numerous BP indices. ROC analysis identified baseline microRNA-27b expression as the best performing marker distinguishing children with PH in our cohort. Multivariate analysis unmasked baseline microRNA-16 expression as the only significant predictor of elevated diastolic BP. Concerning HMOD, groups differed in LVMI, cfPWV, ET PWVβ, and ET Ep. Hypertensive children showed a significant decrease in both office and ABPM measurements (peripheral and central) after exercise. In contrast, the CG showed no changes in BP, except for an increase in 24 h SBP.

When we launched in 2020 the ATHENA study, we made the decision, based on the literature available at the time, to select six microRNA molecules that, based on experimental data and studies in adults, were associated with the pathogenesis of hypertension and the development of HMOD, and for which there was also evidence suggesting that their expression levels may change in response to physical exercise.

MicroRNA-133a is a promising molecule in the pathogenesis of AH. It was found that the prorenin receptor and angiotensinogen are targets of microRNA-133a and that this microRNA may affect BP through this pathway [41]. Studies on microRNA-133a typically show reduced expression in hypertensive adults [42]. Our study found similar results: lower microRNA-133a expression in hypertensive children compared with healthy peers. Importantly, our cohort consisted of newly diagnosed patients without pharmacological treatment, suggesting that microRNA-133a expression is reduced in the early stages of hypertension and may be associated with pathways relevant to its pathogenesis. Moreover, microRNA-133a is highly expressed in the myocardium, and this particle appears to play an important role in hypertension-induced left ventricular hypertrophy (LVH) [43]. In adults, a negative correlation between left ventricular mass and risk of LVH was unmasked [17, 43]. MicroRNA-133a is also studied in exercise physiology. Its expression increases in athletes after endurance exercise [44]. In our study, microRNA-133a expression increased after exercise, however, only in CG. MicroRNA-133a belongs to the group of muscle microRNAs (originating from cardiomyocytes and skeletal muscles), and its expression is thought to increase during exercise by release from skeletal muscle [10]. Due to its lower expression in PH patients and statistically significant increase after physical exercise only in healthy children, this molecule may be associated with a more favourable cardiovascular profile. Even more importantly, the expression level of this microRNA was significantly lower in the group of children with hypertension, even after the exercise session. It may serve as a marker for monitoring patient compliance with physical activity and may be a potential target for future antihypertensive drugs; however, further research and observation are certainly required to understand how this molecule changes over longer periods of regular physical exercise.

MicroRNA-27b is a key regulator of lipid metabolism and plays a role in obesity and metabolic syndrome, with reduced levels observed in obese patients [10]. It is also involved in angiogenesis and is highly expressed in the heart after myocardial infarction, influencing capillary formation and fibrosis [45]. MicroRNA-27b expression influences the angiogenic activity of endothelial cells by regulating among others Naa15 gene in a mouse model [46]. Zhu et al. [47] found increased serum microRNA-27b-3p expression in hypertensive and pre-eclamptic patients. Wang et al. [48] reported higher levels in hypertensive patients with LVH compared to those without LVH and healthy subjects. It was also shown that ACE gene expression and production of ACE are regulated by both microRNA-27a and microRNA-27b [23]. Our study revealed significantly higher microRNA-27b expression in healthy children compared to hypertensive children. In our cohort, expression of microRNA-27b was the strongest negative predictor of hypertension, also in the ROC analysis. This suggests impaired upregulation in hypertensive children. Our findings align with most exercise-related studies but contrast with adult hypertension research showing lower microRNA-27b levels. The discrepancy between our findings and other studies may be due to differences in the age of study participants. Additionally, our study utilized plasma-based samples, whereas others used serum-based measurements, which may include more cell-derived microRNAs, such as those released from ruptured platelets. Given microRNA-27b’s known role in angiogenesis, another possible explanation is that our hypertensive patients had relatively short disease duration and had not yet undergone pharmacological treatment. Another explanation may be that microRNA-27b levels decrease in the early stages of hypertension but significantly increase in later stages of disease progression. Studies on exercise-induced changes in microRNA-27b expression are limited. Some reported a twofold increase after regular aerobic exercise [10], while others found decreased levels after high-intensity interval training in women with polycystic ovary syndrome [49]. In our cohort, microRNA-27b expression increased after physical exercise in the control group. However, no such effect was observed in the group of children with PH. This may indicate an impairment in the mechanism connected with microRNA-27b production at the beginning of the development of PH. Further research is needed to explore microRNA-27b’s role in hypertension.

Of note, we found no significant correlations between BP, HMOD, and microRNA-27a. This particle is a potent regulator of cardiomyocytes and VSMCs proliferation and apoptosis [50, 51]. In adults, expression of microRNA-27a was lower in newly recognized hypertensive patients compared to normotensive ones [42]. The fact that our study did not reveal such differences may be due to the slightly different pathophysiological basis of PH in adolescents and certainly warrants further investigation in prospective studies.

MicroRNA-145 is the most abundant microRNA in VSMCs, where it helps maintain their contractile phenotype, and is also found in plasma and the endothelium [52]. MicroRNA-145 targets numerous crucial pathways involved in BP regulation, including ACE [52, 53]. Targeting the SLC7A1 gene, which is involved in arginine metabolism and nitric oxide production, is another possible pathway underlying this particle’s role in the pathogenesis of PH [54]. Most of the microRNA-145 studies have been conducted in newly diagnosed adults with PH, showing decreased microRNA-145 expression [28]. Our study also found a trend towards lower microRNA-145 expression levels (p = 0.061) in hypertensive children, which is consistent with the aforementioned studies. Its expression increased after an acute bout of bike exercise in both groups.

Numerous papers suggest the role of MicroRNA-16 in the pathogenesis of both systemic and pulmonary hypertension [55, 56]. One possible explanation is targeting by microRNA-16 ADRA1A gene, encoding the α1A-adrenergic receptor [57]. Although we did not demonstrate a correlation between microRNA-16 and the parameters studied in this study, another study from the ATHENA project revealed an association between increased microRNA-16 expression and impaired left ventricular global longitudinal strain [58]. This promising particle also requires further studies in a population of adolescents with PH.

MicroRNA-21 appears to be a key molecule in the pathogenesis of PH by influencing the TGF-β1 pathway and the renin-angiotensin-aldosterone system, particularly in VSMCs [59]. A recently published meta-analysis of studies in adults clearly demonstrated that microRNA-21 expression is higher in patients with hypertension [60]. Furthermore, a positive correlation between its expression and cIMT was demonstrated [16]. Our study is negative in this regard-in our cohort, there was no association with BP or arterial damage. It is possible that our results can be explained by differences in the pathogenesis of PH in young people (most commonly isolated systolic hypertension, a greater role of sympathetic overdrive than activation of the RAA system, and established vascular changes) [8]. This difference also requires further investigation at the molecular and clinical levels.

In our hypertensive patients, we found an increase in both serum uric and uric acid urine excretion after an exercise bout. Rise in serum uric acid is a well-known phenomenon, reflecting increased purine metabolism and ATP turnover, revealed in many adults studies [61, 62]. Conversely, most studies show exercise-induced inhibition of uric acid excretion caused by lactic acid accumulation [63, 64]. Therefore, the increased renal excretion of uric acid following exercise that we observed is surprising. It is possible that a well-designed exercise session did not generate excess lactic acid in our young patients, so the negative feedback mechanism was not triggered, and uric acid excretion increased simply as a result of its overproduction. It should be emphasized that, to the best of our knowledge, there are no reliable data in the literature on urinary uric acid excretion after exercise in children, let alone in children with hypertension.

Exercise may promote sodium conservation by increasing renal tubular sodium reabsorption and attenuating volume-regulatory responses, thereby reducing urinary sodium excretion in the post-exercise period [65]. The lower post-exercise urinary sodium excretion in our hypertensive group compared to controls may indicate more active sodium-retaining mechanisms (according to Guyton’s classic hypothesis on the pathogenesis of PH) [8]. This view might be supported by the increase in aldosterone after exercise in SG, which approached statistical significance, and by the negative correlations between both renin and aldosterone, and urinary sodium excretion. Nevertheless, this finding should also be seen as exploratory and hypothesis-generating.

In our study, post-exercise phosphate excretion was significantly higher in the group of children with hypertension. However, as our data show, excretion is also higher (albeit not significantly, p = 0.098) before exercise. Higher phosphate excretion may reflect, on the one hand, a less healthy diet rich in highly processed foods in patients with hypertension. On the other hand, the significant difference after exercise may indicate greater energy expenditure and higher ATP consumption in patients with hypertension. The relationship between BP and urinary phosphate excretion is complex and inconsistent across studies [66]. One mechanism by which a high phosphate diet negatively affects the cardiovascular system is the generation of FGF23, which activates the sympathetic nervous system and renin-angiotensin-aldosterone system, increases vascular stiffness, and causes LVH [67].

Previous research has demonstrated that microRNA-145 expression decreases, while microRNA-27b expression remains unchanged following a 10-day fasting period [68]. Another study reported upregulation of microRNA-133a expression after a 28-day reduction of total energy intake to 70% of daily requirements in overweight males aged 60–75 years [69]. Additionally, consuming a portion of extra-virgin olive oil was shown to significantly decrease microRNA-21 levels 2 h after ingestion, with levels returning close to baseline after 6 h [70]. Notably, the majority of studies investigating the influence of diet on circulating microRNA levels have implemented a 12-h fasting period prior to blood sampling [71]. In line with this approach, our study adopted a similar fasting protocol to assess baseline and post-exercise changes in microRNA levels. However, it is important to emphasize that our investigation did not aim to evaluate diet-related changes in microRNA expression among children with PH and their healthy peers.

Last but not least, our study also provides valuable data on BP and vascular parameters before and after a standardized aerobic exercise session. The findings are particularly useful given the homogeneous nature of the SG (untreated children with PH without other comorbidities, e.g., diabetes mellitus, coronary heart disease) and the CG, which consists of healthy peers. A review by Falkner et al. [2] summarized that while physical activity is known to have beneficial health effects, its impact on BP in children remains unclear. It ranges from a drop of 12 mm Hg in SBP and 7 mm Hg in DBP to almost none, with an average of around 2 mm Hg [29]. Our study adds important knowledge about post-exercise BP changes, showing a significant reduction in SBP and DBP in hypertensive children (3.9 mm Hg and 3.3 mm Hg, respectively). At the same time, no such effect was seen in the CG. This might suggest different mechanisms of post-exercise BP changes in normotensive and hypertensive patients. It should also be emphasized that the observed effects are short-term and reflect a single exercise session. These results pertain solely to the effects of a single exercise session; therefore, no inferences regarding long-term BP regulation or the impact of habitual physical activity can be drawn from the current data.

Limitations

We acknowledge a few limitations in our study. First, all patients were from a single centre, with limited ethnic and age diversity, making it difficult to generalize the results. Second, the study is limited by a narrow focus on a small set of preselected microRNAs (6) and by the inability to perform global normalization of microRNA expression. Therefore, future studies are necessary to identify and validate the most stable reference microRNAs in the paediatric population. Moreover, despite the strict pre-analytical procedures that were applied, haemolysis was assessed solely by visual inspection rather than by molecular indicators (e.g., the microRNA-451a/microRNA-23a-3p ratio)which should be acknowledged as a limitation of the study. However, our study also has key strengths. It is the first to compare microRNA expression in children with PH with that of healthy peers. We used a well-established method for measuring microRNA expression, with all analyses conducted by a single investigator to reduce bias. Independent bodies reviewed the study protocol, and a preliminary study was done and published to validate the procedures. Additionally, we thoroughly assessed the patients’ vascular phenotype and BP and included a standardized intervention based on a cardiopulmonary exercise test, with numerous parameters evaluated.

Conclusions

MicroRNA-27b and microRNA-133a are underexpressed in children with PH. These molecules may be useful as potential markers of hypertension in children and may also be associated with a lower burden of hypertension-related alterations. Clarifying the exact place of these molecules in the pathogenesis of hypertension in children requires further research. MicroRNA-16 may serve as a marker of diastolic hypertension. Finally, our study demonstrates a significant decrease in BP after a standardized exercise session in hypertensive children, highlighting the importance of exercise interventions for managing hypertension in this population.

Acknowledgments

The authors thank the Małgorzata Pańczyk-Tomaszewska (Department of Pediatrics and Nephrology, Medical University of Warsaw), Urszula Demkow and Dorota Czapczak (Department of Laboratory Diagnostics and Clinical Immunology of Developmental Age, Medical University of Warsaw, Warsaw, Poland), Marta Bazańska and Aleksandra Piechuta (National Centre for Sports Medicine, Poland), and Klaudia Obsznajczyk (Department of Pediatric Cardiology and General Pediatrics, Medical University of Warsaw, 02–091 Warsaw, Poland) for invaluable assistance throughout the study, support in difficult times, and the joint search for solutions to the difficult path of the study.

Statement of Ethics

The study approved by the Bioethics Committee of the Medical University of Warsaw (KB 154/2020). All procedures adhered to the highest ethical standards set by the Institutional Research Committee and were conducted in accordance with the principles of the Declaration of Helsinki and its subsequent amendments. Written informed consent was obtained from their parent or legal guardian to participate in the study.

Conflict of Interest Statement

Jolanta Malyszko was a member of the journal’s Editorial Board at the time of submission. Other authors declare no conflicts of interest.

Funding Sources

This research was funded by the National Science Centre, Poland (2021/41/N/NZ5/04194). The funder provided financial support for the study but had no role in the study design, study execution, data analysis, manuscript conception, manuscript planning, manuscript writing, interpretation of the findings, or the decision to publish the results.

Author Contributions

Conceptualization and data curation: M.S. and P.S.; methodology: M.S., P.S., C.E., and H.K.; investigation: M.S., P.S., R.P., and K.S.; formal analysis and visualization: M.S., P.S., and C.E.; resources: M.S., P.S., and H.K.; original draft preparation: M.S., P.S., C.E., and J.M.; review and editing: M.S., P.S., C.E., J.M., K.S., R.P., and H.K.; and supervision: P.S. All authors have read and agreed to the published version of the manuscript. Drs Szyszka and Skrzypczyk had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Funding Statement

This research was funded by the National Science Centre, Poland (2021/41/N/NZ5/04194). The funder provided financial support for the study but had no role in the study design, study execution, data analysis, manuscript conception, manuscript planning, manuscript writing, interpretation of the findings, or the decision to publish the results.

Data Availability Statement

The data that support the findings of this study are not publicly available due to privacy reasons but are available from the corresponding author upon request.