1 INTRODUCTION

Obesity in children is one of the most demanding challenges emerging in the modern world of paediatric medicine. It is described in relation to patient's body-mass index (BMI). In children a threshold of obesity is BMI above 95th percentile in a group of the same age and sex. Despite various prevention programs, analyses, and research, its occurrence is still high,1 which exposes youth to complications of obesity, such as endothelial dysfunction (ED),2 non-alcoholic fatty liver disease (NAFLD),3 type 2 diabetes mellitus (T2DM),4 atherosclerosis (AS),5 and obstructive sleep apnea.6 The possibility to quantify the progression of these diseases is necessary in order to overcome their development. As the standard markers and tests in many cases are insufficient measures for this challenge, the novel markers such as microRNA (miRNAs; miRs) may prove to be a sound solution. MiRNAs are small, non-coding molecules that play a suppressive role in expression of genes by binding to 3′UTR end of their target messenger ribonucleic acid (mRNA). They can be found in body tissues or fluids, like saliva, plasma, serum, or whole blood; encapsulated into extracellular vesicles (EVs) or as circulating miRNA.7, 8 Changes in a profile of the circulating and tissue miRNAs directly influence the physiology of tissues and cells involved in glucose and lipid metabolism – pancreatic β-cells, hepatocytes, skeletal muscle tissue, and adipose tissue – by modulating mRNA translation.9, 10 Taking into consideration the easy accessibility and measurability of materials rich in miRNAs, such as blood, plasma, and saliva,11-13 examining the associations between diseases and miRNA levels might lead to creation of diagnostic and prognostic markers of high sensitivity and specificity.

Research on miRNA is nowadays one of the more popular scopes of interest in numerous branches of medicine. Recently the differences in miRNA profiles between the children with and without obesity have been investigated.14, 15 Results of studies on this topic were analysed and summarized into the systematic review in 2019 by Oses et al. It also presented two miRNAs significantly overexpressed in children with NAFLD and T2DM.16 Our study concentrated solely on reviewing studies that examined miRNAs as biomarkers of paediatric obesity comorbidities. The scope of interest was expanded to comorbidities other than NAFLD and T2DM. The set of included studies was updated. In accordance with ‘participants, interventions, comparisons, outcomes, and study design (PICOS)’ scheme, the following question was created for the purpose of review: ‘What are the possible applications of miRNAs in diagnosis, prediction and treatment of obesity comorbidities in paediatric population?’ Results of 16 studies on miRNAs as markers of paediatric obesity comorbidities were enrolled (only 3 of which overlap with the previous review), including not only T2DM and NAFLD, but also ED, metabolic syndrome, insulin resistance, and AS. More than a half of the studies included in this review were published after the last date of literature search conducted in the previous review (23 November 2018). The time range in which the included studies of current review were published was 2016–2021.

2 MATERIALS AND METHODS Entry terms were formulated according to the following scheme: Subject group: ‘child obesity’ OR ‘childhood obesity’ OR ‘obese children’ OR ‘paediatric obesity’ OR ‘overweight children’ OR ‘adolescent obesity’ AND Comorbidity: ‘complications’ OR ‘comorbidities’ OR ‘NAFLD’ OR ‘non-alcoholic fatty liver disease’ OR ‘liver’ OR ‘fatty liver’ OR ‘CVD’ OR ‘cardiovascular diseases’ OR ‘endothelial dysfunction’ OR ‘type 2 diabetes’ OR ‘hypertension’ OR ‘metabolic syndrome’ OR ‘puberty’ OR ‘asthma’ OR ‘obstructive sleep apnea’ OR ‘-’ AND Marker: ‘miRNA’ OR ‘miR’ OR ‘microRNA’ OR ‘circulatory microRNA’

Adequate filters regarding publication dates (up to 5 years prior to search) and text availability were applied. The repeated results of search were ruled out.

Retrieved data underwent further screening on a basis of titles, abstracts, and keywords (performed by MH and JH) according to inclusion and exclusion criteria, which led to exclusion of reviews, systematic reviews, author manuscripts, personal communication, letters to editor, conference material, and case reports. Articles concerning the miRNA as the markers of obesity itself in children, as well as the studies of miRNA not obtained from blood or plasma were ruled out – in order to be plausible for the role of markers, miRNAs must be easily accessible (blood or plasma) and correlate with comorbidities of obesity (rather than the obesity itself). Inadequate matching of experimental and control groups in the matter of age or exceeding upper age threshold were also the discriminating factor.

At the stage of data synthesis the retrieved studies were assessed by two independent researchers (AZ and PM) in terms of methodology quality, as well as relevance of the results. The principal measures of differentiating potential were area under the receiver–operator curve (ROC) (AUC) score, fold change, and p-values (statistical significance threshold: p < 0.05).

3 RESULTS

Multiple browsing of databases, such as PubMed, askMEDLINE, Wiley Online Library, and Elsevier, conducted in the span of January 2020 – September 2021 using search strategy presented in Materials and Methods section, returned a total of 1754 results. That number was reduced to 245 individual articles by excluding 1509 repetitions. The remaining have been found eligible for further title and abstract valuation, of which 34 studies were accepted as fitting for whole text reading according to the inclusion and exclusion criteria, which were as follows:

Inclusion criteria: English literature published in the last 5 years Studies in human subjects Paediatric population (<19 yo) Studies examining miRNA profiles of patients with obesity Exclusion criteria: Publication type: reviews, systematic reviews, author manuscripts, personal communication, letters to editor, conference material, and case report Studies based on miRNA from body fluids other than blood Studies not linking miRNA of patients suffering from obesity to any comorbidity Subjects exceeding at the study time the age criterion of paediatric group (≥19 yo) Control group inadequate in terms of age to the study group Subjects diagnosed with comorbidity other than the examined one

In total 16 studies fully met the inclusion and exclusion criteria.

The process of data collection for this review is presented in Figure 1.

Flow diagram of research process.

Source: Reference 17

Main characteristics of selected articles can be found in Table 1.

TABLE 1. Summary of article characteristics Number Authors Year Complication of obesity Number of subjects Molecules investigated Sample source Evaluation technique 1. Donghui et al.18 2019 ED 67 miR-126 Serum RT-qPCR 2. Zhao et al.19 2021 ED 60 miR-320a Serum RT-qPCR 3. Khalyfa et al.20 2016 ED 70 miR-125a-5p, -342-3p, -365b-3p Plasma RT-qPCR, Microarrays 4. Khalyfa et al.21 2016 ED 69 miR-16-5p, -451a, -5100, -630, -4665-3p Serum EVs RT-qPCR, Microarrays 5. Thompson et al.22 2017 NAFLD 30 miR-15b-5p, -199a-5p, -222-3p, -223-5p, -34a-5p, -122-5p, -23a-5p, -27b-3p, -21-5p, -34a-5p, -451-5p, -192-5p, -16-5p, -29a-3p, -150-5p, -214-3p, -375, -155-5p, -191-5p, -103a-5p Plasma RT-qPCR 6. Brandt et al.23 2017 NAFLD 147 miR-122 Serum/plasma RT-qPCR 7. Cui et al.24 2018 T2DM 718 miR-486, -146b, -15b Serum RT-qPCR 8. Mohany et al.25 2020 T2DM 120 miR-486, -146b, -15b Plasma RT-qPCR 9. Mohany et al.26 2021 T2DM 298 miR-29a, -122 Serum RT-qPCR 10. Al-Rawaf27 2020 MetS 250 miR–142-3p, -140-5p, -222, -143, -130, -532-5p, -423-5p, -520c-3p, -146a, -15a Plasma RT-qPCR 11. Zhang et al.28 2021 MetS 147 miR-24-3p Serum RT-qPCR 12. Lischka et al.29 2021 MetS 109 miR-15a, -19, -23a, -27b, -33a, -33b, -34a, -93, -98, -122, -144-3p, -144-5p, -192, -193b, -197, -1290 Serum RT-qPCR 13. Lin et al.30 2020 IR 33 miR-30d-5p, -122-5p, -221-3p, -215-5p Serum RT-qPCR 14. Yu et al.31 2018 IR 90 miR-27a Serum RT-qPCR 15. Iacomino et al.32 2021 IR 58 miR-191-3p, -375 Serum RT-qPCR 16. Barberio et al.33 2019 AS 93 miR-3129-5p, -20b, -9-5p, -320d, -301a-5p, -155-5p Circulating adipocyte-derived EVs Microarrays Abbreviations: AS, atherosclerosis; ED, endothelial dysfunction; EVs, extracellular vesicles; IR, insulin resistance; MetS, metabolic syndrome; miR, miRNA; NAFLD, non-alcoholic fatty liver disease; RT-qPCR, reverse-transcription quantitative polymerase chain reaction; T2DM, type 2 diabetes mellitus.

Enrolled studies focused on associations between changes in miRNA profiles of patients with obesity and presence of 6 obesity comorbidities. Their methodology is discussed in the following sections separately for each complication.

3.1 Endothelial dysfunction

The highest number of articles was linked to ED – a total of four studies (articles 1.; 2.; 3.; 4.), which examined among others the miRNAs: miR-126, miR-320a, miR-125a-5p, miR-342-3p, miR-365b-3p, and miR-630. ED is a pathological state characterized by impaired maintenance of vascular tone and oxidative stress, resulting from dysregulation of synthesis of endothelial mediators – nitric oxide (NO), endothelin (ET), and others.34, 35 Patients were classified into groups of either normal endothelial function (NEF) or ED, based on their reactive hyperemic index (RHI) score. RHI was measured with peripheral arterial tonometry (PAT) (study 1) or with time of peak reperfusion (Tmax) after occlusion of arteries (studies 3 and 4). Condition of epithelium of patients in study 2 was inspected using levels of intercellular adhesion molecule 1 (ICAM-1), vascular cell adhesion molecule 1 (VCAM-1), and E-selectin.36-38 Patients' characteristics are presented in Table 2.

TABLE 2. Articles concerning the differences of miRNA levels in endothelial dysfunction and physiology Article Group Number of patients Age (years) Sex (% of male) BMI-z *BMI 1. CGa n = 10 12–18 100 Pre *23.05 ± 0.46 Post *23.01 ± 0.50 EGa n = 37 12–18 100 Pre *33.48 ± 3.54 Post *29.63 ± 3.16 2. DG n = 20 12.05 ± 2.28 65 Pre *29.33 ± 1.11 Post *28.63 ± 0.94 EG n = 40 12.30 ± 2.61 70 Pre *29.33 ± 1.29 Post *26.09 ± 1.05 3. NEF n = 25 7.59 ± 1.26 70.4 1.69 ± 0.62 ED n = 35 8.41 ± 1.20 63.8 2.00 ± 0.68 4. OBNEF n = 23 7.6 ± 2.6 56.5 1.74 ± 0.28 OBED n = 20 7.7 ± 2.8 60 1.76 ± 0.31 CG n = 26 7.3 ± 2.2 58 1.08 ± 0.21 Abbreviations: BMI, body mass index; BMI-z, body mass index Z-score; CG, control group; DG, dietary group; ED, endothelial dysfunction; EG, experimental group; NEF, normal endothelial function; OBED, subjects with obesity and endothelial dysfunction; OBNEF, subjects with obesity and normal endothelial function. 3.2 Non-alcoholic fatty liver disease

NAFLD is a disease comprising of two main clinical features – steatosis and inflammation of liver. It is a condition resulting from factors other than alcohol consumption.39 Studies 5 and 6 examined the correlations of miRNAs levels (miR-199a-5p, miR-122-5p, and others) with serum levels of clinically approved markers of hepatic steatosis: aspartate-aminotransferase, alanine-aminotransferase (both articles), glutamate-pyruvate-transaminase (only study 6) (respectively: AST, ALT, and GGT); as well as with BMI and BMI-z scores of children with obesity (BMI >95th percentile) and NAFLD (NAFLD) in comparison to the ones without obesity and NAFLD (CG) (study 5), or in three paediatric cohorts of children with overweight, recruited from hospitals in Germany (GC), Italy (IC), and Slovenia (SC) (study 6). Additional marker used in study 6 was cytokeratin 18 (CK18) measured in serum or plasma using enzyme-linked immunosorbent assay (ELISA). In both studies, severity of liver steatosis was graded using ultrasonography (USG) into scales: undetectable/mild/diffuse (study 5) or no-steatosis/grade I/grade II/grade III (study 6).

3.3 Type 2 diabetes mellitus

The goal of study 7 was the comparative analysis of miRNA levels in paediatric groups of children with (OB) or without obesity (CG) and children who were overweight (OW); adult groups of patients with type 2 diabetes/normal glucose tolerance (T2DM/NGT) (total of 352 subjects) and animal model groups of mice with obesity/diabetes (ob/db). First stage was miRNA profiling of nine patients from OB and CG groups each, validated further in full-size final paediatric groups (study 2) and in groups of adults with T2DM/NGT. MiRNAs which were chosen according to the results of the experiment (miR-15b, miR-146b, and miR-486) were then transfected using lentivirus into human preadipocyte, murine beta-cell (MIN6), and myoblast (C2C12) cultures in order to examine their influence on respectively: adipocytes cell proliferation, insulin secretion, and glucose intake. Obesity and overweight in children were measured with BMI standard deviations (SDs), according to WHO Child Growth Standards (CGS) – children under 60 months: obesity >3 SDs, overweight >2 SDs; children over 60 months: obesity >2 SDs, overweight >1 SDs. Measure of T2DM was fasting plasma glucose (FPG) >7.0 mmol/L. Information on FPG as well as age, serum triglyceride, and cholesterol levels of subjects were collected from hospitals.

Study 8 was conducted as a response to the results of study 7. Serum levels of three selected miRNAs (miR-15b, miR-146b, and miR-486), as well as of the betatrophin, were measured and compared between the groups of children with (>95th BMI percentile) or without (5th to 85th BMI percentile) obesity, and children suffering from diabetes (classification based on previous results of FPG, blood glucose, oral glucose tolerance test, or glycated haemoglobin [HbA1c]). Venous blood samples intended for measurement of percentage of HbA1c (HbA1c%), betatrophin, cholesterol, glucose, and miRNAs relative expression levels were collected after overnight fasting. Correlations of miRNAs expression, betatrophin, and other parameters were tested by Pearson correlations coefficient (significance: p < 0.05). ROC of miRNAs and serum betatrophin were created in order to assess the potential of differentiating between the groups.

These two studies presented, though to a different extent, a profile of three miRNAs (namely miR-486-5p, miR-146a-5p, and miR-15b) potentially useful in detection of T2DM development in children. Results of study 8 are less satisfactory than those of study 7, showing lower AUC score values. However, it should be pointed out, that in study 7 the cumulative effect of simultaneous measurement of two or three of aforementioned molecules was not examined.

Another two miRNAs (miR-29a, miR-122) were examined in study 9 in terms of differences of their levels in children without obesity, with obesity but without T2DM, and in those with obesity and T2DM. Two hundred and ninety eight patients, aged 9–15 years, were divided into above groups based on their BMI and WC (obesity vs. non-obesity) and glucose levels (fasting ≥126 mg/dl, random ≥200 mg/dl, OGTT ≥126 mg/dl 2 h post-ingestion), or HbA1c% >6.5%. The groups were significantly different in terms of diabetes parameters (glucose, insulin, homeostatic model assessment IR [HOMA-IR]), whereas children with obesity and without T2DM did not differ significantly in WC and BMI percentiles from children with obesity and T2DM.

3.4 Metabolic syndrome

Similarly to the obesity, we can observe the increasing metabolic syndrome (MetS) prevalence worldwide. This term represents the cluster of metabolic changes, which stem directly from long-term positive energy balance. These alterations include obesity, followed by hypertension, and atherogenic dyslipidemia.40 Recently the study on 250 adolescents (study 10) investigated the relation between miRNAs and adipokines, specifically adiponectin and leptin. The latter are known to play important role in regulating and maintaining the metabolic homeostasis,41 therefore their dysregulation is a strong evidence of developing metabolic disorders. Patients were categorized based on their obesity scores into three groups: without obesity (NW; 50 subjects), suffering from overweight (OW; 100 subjects), and from obesity (OB; 100 subjects).

A potential of miR-24-3p molecule in differentiating children with obesity (BMI ≥95th centile according to Working Group on Obesity in China) from children without obesity, as well as children with MetS from ones without MetS, was examined in study 11. The population of study consisted of three groups: children without obesity (n = 50); with obesity but without MetS (n = 45); with obesity and MetS (n = 52). Cut-off points of metabolic parameters for the MetS were as follows: FBG ≥5.6 mmol/L or type 2 diabetes; SBP ≥130 mmHg and/or DBP ≥85 mmHg; TG ≥1.7 mmol/L; HDL-c <1.03 mmol/L.

In study 12, a group of 109 children with severe obesity and its complications (hypertonia, T2DM, and MS) were examined in terms of panel of 16 circulating miRNAs (including miR-122, -192, -34a), hepatic transaminases, anthropometric, and blood metabolic parameters. Similar to study 10, the associations between the miRNA profile and adiponectin, as well as obesity-related inflammatory markers levels were investigated. The population of the study varied in age (9–18 years, mean 13.1 ± 2.7 years) with a disproportion for sex (37 male/72 female), therefore the results were adjusted for age and sex, which led to differences between the sexes in significance of correlation of some miRNAs with studied parameters.

3.5 Insulin resistance

Three studies (studies 13, 14, and 15) concentrated on the correlation between miRNAs and insulin resistance (IR). In study 13, the children and adolescents aged 10–17 years were divided into two groups: children with obesity (OB; 9 patients) and children with obesity and IR (OB-IR; 21 patients), based on the HOMA-IR score (threshold value: >4.00). Their anthropometric parameters and biomarkers values (fasting glucose, leptin, adiponectin, adiponectin/leptin ratio, FFA, HDL-C, systolic, and diastolic blood pressure) were measured and compared between groups. Forty miRNAs were measured in serum of patients and compared with values of biomarkers and anthropometric parameters.

Study 14 in turn examined the role of miRNA-27a in the development of IR. For that purpose, group of 45 children with obesity (OB) and group of 45 age-matched children without obesity (CG) were examined in terms of serum levels of miR-27a and biochemical parameters: fasting blood glucose, adiponectin, leptin, resistin, subfatin, visfatin, and TNF-α, IL-6. The correlations between miRNA-27a and above biomarkers were calculated. Further research was conducted on animal model, comparing the influence of high-fat and low-fat diet, as well as knocking-out gene for miRNA-27a on mRNA expressions of IRS-1 and GLUT4 in skeletal muscle tissue.

Analysis of glucose metabolism parameters and their association with miRNA profile in a group of 58 children with overweight or obesity was conducted in study 15. There was no statistical difference in mean age or insulin levels and HOMA-IR between the sexes, though the latter parameters were insignificantly higher in girls. Two examined miRNAs: miR-191-3p and miR-375, were also further analysed in terms of interactions with their respective pathway targets.

3.6 Atherosclerosis

Relations between BMI, miRNA levels (both circulatory molecules transported in EVs, as well as levels in visceral adipose tissue [VAT]) and cholesterol efflux capacity of THP-1 derived macrophages were examined in study 16, which was based on population of adolescents (12–19 years) with (all subjects were >99th percentile for age-adjusted BMI) and without obesity (BMI ≤25 kg/m2). Cholesterol efflux capacity reduction leads to creation of foam cells, thus being crucial for the development of atherosclerosis.42 Lipoprotein concentrations were measured using nuclear magnetic resonance, followed by calculation of the lipoprotein IR index based on HOMA-IR data from Multi-Ethnic Study of Atherosclerosis. Adipocyte-derived EVs were obtained from serum of female subgroup (chosen as representative for cohort) with further extraction of total ribonucleic acid (RNA). Each participant underwent the bariatric surgery after 2 weeks of protein-saving diet (1000 kcal/day, 50–60 g protein) and pre-intervention overnight fasting. VAT collected during this process served as the miRNA source. EVs were applied on THP-1 macrophages to examine its effect on THP-1 cholesterol intake. THP-1 macrophages were also treated with 1 or 3 μg/ml solutions of adipocyte-derived EVs and separately supplemented RPMI 1640 medium in order to assess the cholesterol efflux. These cells were then used for total RNA isolation, and after reverse transcription and PCR amplification of acquired complementary deoxyribonucleic acid, quantitative analysis of expressed genes was conducted.

4 DISCUSSION

Facing the newest progress in techniques of isolation, sequencing, and quantification of nucleic acids (in that case miRNA) from various biological materials, we begin to recognize an important role of miRNAs in modulation of nearly every process in human body. Observing changes of miRNA levels and profiles in various physiological and pathological conditions creates the possibilities to establish new ways of disease diagnosis, treatment, as well as the prediction of their comorbidities and complications. Comparison of miRNA profiles in groups of adults and children with obesity and/or its comorbidities is an important issue for critical assessment of miRNAs as markers reflecting the development of obesity and its comorbidities. These molecules modulate expression of genes involved in metabolic pathways common for both age groups. Dysregulation of given molecule, associated with a comorbidity in one group, should also be observed in the other, with differences in its extent attributable to entering further stages of disease and its associated alterations. Such comparison would be a valid method of evaluating the findings for both age groups (adults and children), nonetheless it exceeds the scope of this review, which concentrated solely on studies conducted in the paediatric population.

Examined miRNAs, their level changes, as well as their significance and AUC score are presented in Table 3. Studies 12 and 15 were not applicable for the purpose of this table, and as such were not included.

TABLE 3. Summary of results Article no. Comorbidity Molecule Compared groups Status (fold change) Significance (p-value*) AUC 1. ED miR-126 Pre-CG versus Pre-EG −1.73 <0.01 - Pre-EG versus Post-EG 0.31 <0.01 - 2. ED miR-320a Post-EG versus Post-DG 1.00 <0.001 - Post-EG versus Pre-EG 1.00 <0.001 - 3. ED miR-125a-5p ED versus NEF −1.33 ± 0.11b (−1.27 ± 0.12)c 0.02 (0.01)c - miR-342-3p −1.41 ± 0.08b (−1.22 ± 0.06)c 0.03 (0.02)c - miR-365b-3p 1.41 ± 0.14b (1.52 ± 0.23)c 0.004 (0.001)c - 4. ED miR-630 ED versus NEF −0.11 <0.0001 - 5. NAFLD miR-199a-5p NAFLD versus CG 17.18 <0.0001 0.9750a miR-122-5p 12.48 <0.0001 0.9833a 6. NAFLD miR-122 NAFLD versus NN (GC) 2.25 <0.05 0.77 NAFLD versus NN (IC) 0.20 >0.05 0.54 7. T2DM miR-15b OB versus CG > 6.00 <0.01 - T2DM versus NGT 6.67 <0.01 0.969