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. 2026 Jul 24;86(5):e70162. doi: 10.1002/jdn.70162

Effects of NR3C1 and COMT Genes on Attention‐Deficit/Hyperactivity Disorder and Accompanying Aggressiveness: A Cross‐Sectional Study in a Clinical Sample

Mert Kaan Kale 1, Öznur Bilaç 2,✉, Muhammet Burak Batır 3, Fethi Sırrı Çam 4
PMCID: PMC13400752  PMID: 42498977

ABSTRACT

Introduction

Attention‐deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition characterized by developmentally inappropriate inattention, hyperactivity–impulsivity, increased distractibility and impairments in executive functioning and behavioural self‐regulation. Aggressive behaviours and anger dysregulation are frequently observed across a range of psychiatric conditions, including ADHD and disruptive behaviour disorders, and have been hypothesized to reflect, in part, shared biological and genetic mechanisms. In this study, we investigated whether genetic variation in COMT and NR3C1 is associated with aggression‐related phenotypes in youth with ADHD, including physical aggression, verbal aggression and hostility/resentment.

Methods

The case group comprised 69 children and adolescents with ADHD and comorbid aggression, and the control group comprised 111 children and adolescents with ADHD without comorbid aggression. Parents completed a sociodemographic form, the LEVEL 2—Anger Scale (ages 6–17), and the Turgay DSM‐IV Disruptive Behaviour Disorders Rating Scale. To evaluate psychiatric comorbidity and cognitive functioning, participants were assessed using the Schedule for Affective Disorders and Schizophrenia for School‐Age Children—Present and Lifetime Version and the Wechsler Intelligence Scale for Children–Revised. Peripheral blood samples were obtained and analysed for COMT and NR3C1 genotype and allele frequencies.

Results

Hostility/resentment was significantly associated with COMT genotypes (p = 0.037) and COMT allele distribution (p = 0.015). In addition, the presence of aggression was significantly associated with COMT allele distribution (p = 0.024). However, these statistically significant findings were no longer significant after advanced statistical analysis. In addition, no statistically significant associations were observed between NR3C1 variation and any aggression phenotype or hostility/resentment.

Conclusion

These findings suggest that COMT‐related genetic variation may be associated with aggression‐related features in youth with ADHD, whereas no such association was observed for both COMT and NR3C1 in this sample with advanced statistical analysis. Further studies with larger samples and more refined phenotyping are warranted to clarify the genetic architecture underlying aggression in ADHD.

Keywords: ADHD, aggression, attention deficit hyperactivity disorder, COMT, NR3C1

Examining COMT and NR3C1 gene variations in youth with ADHD, this study found initial nominal associations between COMT and aggression‐related phenotypes, including hostility. However, advanced statistical analyses nullified these effects, emphasising the complexity of the genetic architecture underlying comorbid aggression in ADHD.

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1. Introduction

Attention deficit/hyperactivity disorder (ADHD) is characterized by significant motor restlessness (hyperactivity), concentration deficits that impair performance (inattention and increased distractibility) and considerable limitations in planning and controlling one's behaviour (impulse control disorder). ADHD is a globally prevalent disorder, with a 2007 meta‐analysis identifying its prevalence in children and adolescents at 5.3% (Polanczyk et al. 2007). Despite differing rates among studies, the prevalence is thought to be relatively consistent worldwide (Polanczyk et al. 2014). National studies in our country have demonstrated an ADHD prevalence ranging between 3.8% and 12.7% (Ercan et al. 2013; Zorlu et al. 2020). The diagnosis is clinical, serving as a prerequisite for a thorough differential diagnosis and pharmacological treatment.

ADHD is a disorder with multiple aetiologies. A combination of genetic, neurological and environmental factors contributes to its heterogeneous phenotype (Akutagava‐Martins et al. 2016). Evidence from family, twin and adoption studies strongly suggests that ADHD is a highly heritable, polygenic disorder (Faraone et al. 2005). Genetic variants that predict ADHD risk are crucial for brain development, cell migration and the coding of catecholamine receptors and transporters (Faraone et al. 2005; Gizer et al. 2009). The identification of gene sequences affecting neurotransmitter pathways in the brain suggests that the accumulation of rare copy number variants or larger deletions and duplications affecting gene transcription is more commonly found in individuals with ADHD (Stergiakouli et al. 2012; Williams et al. 2012).

Aggression has been defined as destructive behaviour, motivated by anger, rage or hatred, with the intent of harming others physically or mentally. Hostile aggression is described as a response to situations where an individual perceives themselves to be insulted or deliberately provoked. Violence, the extreme form of aggression, involves physically harming others with the intent to injure or destroy (Abay and Tuğlu 2000). Although the DSM's subdivision of aggressive conduct disorder into socialised and under socialised forms was not retained in subsequent revisions, various research reports support the existence of qualitatively distinct forms of aggression in children. Aggression issues affect between 10% and 25% of adolescents and are among the most common reasons for referrals to children and adolescent psychiatrists (Vitiello and Stoff 1997). Children and adolescents exhibiting aggressive behaviour often experience profound impairments across several functional domains, including academic and occupational success, social and familial relationships and psychological development. Although aggression is a behavioural construct present to some degree in all humans and can be adaptive for survival, it is highly detrimental when pathological and persistent. Consequently, aggression is often a target for both psychosocial and pharmacological treatment.

Aggression is a common symptom of numerous psychiatric disorders, including ADHD, oppositional defiant disorder (ODD), conduct disorder (CD), tourette syndrome, bipolar disorder, alcohol‐related disorders, intellectual disability, intermittent explosive disorder and personality disorders. It is also observed in many cases of organic brain damage. Aggression is common in patients with epilepsy and may also be seen in some endocrine disorders (Loeber and Farrington 2001). A study by Turgay et al. on 129 children and adolescents found aggression rates to be 93% in ODD, 88% in ADHD, 38% in CD, 21% in major depressive disorder, 14% in dysthymia and 8% in anxiety disorders (Turgay et al. 2000). Other studies have shown that aggression frequently co‐occurs with various clinical disorders, such as ADHD, mood disorders (particularly bipolar disorder and paediatric mania), schizophrenia, intellectual disability, ODD, CD and autism spectrum disorders, which are often characterized by aggressive behaviours (Barkley and Benton 1998; Barkley 2003). In children and adolescents with ADHD who do not have comorbid diagnoses, aggression can manifest as behavioural disinhibition or impulsivity, which may be explained by difficulties in inhibiting, delaying or extinguishing responses to environmental stimuli or considering the potential consequences of their actions (Barkley and Benton 1998). Additionally, studies have shown that even when comorbid conditions such as ODD or CD are considered, children with ADHD remain at a higher risk of engaging in aggressive behaviour (Waschbusch 2002; Pelham et al. 1991; Hinshaw et al. 1989).

Laboratory‐based studies using controlled behavioural observation paradigms and computerized peer‐provocation tasks have provided important insights into aggression subtypes among children with ADHD. For example, Waschbusch et al. examined behavioural, physiological and affective responses to experimentally induced peer provocation in boys with ADHD, ADHD combined with ODD/CD, ODD/CD only, and typically developing controls. In this study, participants completed a structured reaction‐time task involving standardised verbal and behavioural provocation, allowing researchers to experimentally elicit and measure reactive aggression. Findings demonstrated that although all groups displayed aggressive responses under conditions of high provocation, boys with comorbid ADHD and ODD/CD uniquely exhibited elevated reactive aggression under low‐provocation conditions. These children also showed greater anger reactivity, physiological arousal and a tendency to maintain aggressive responses for longer periods following provocation (Waschbusch et al. 2002). Similarly, studies investigating social information processing in ADHD have employed structured vignette‐based and naturalistic observational paradigms to assess aggression‐related cognitive biases. For instance, Mikami et al. examined associations between overt and relational aggression and maladaptive social information processing biases in adolescent girls with and without ADHD. Their findings indicated that the relationship between aggression and hostile or maladaptive social information processing was stronger in the comparison group than in girls with ADHD, suggesting potential differences in the cognitive mechanisms underlying aggressive behaviour in ADHD populations (Mikami et al. 2008).

Research into the pathophysiology of ADHD and aggression has focused on the role of dopamine. ADHD has been associated with dopamine dysfunction in the mesocortical, mesolimbic and nigrostriatal pathways (Sonuga‐Barke 2005; Del Campo et al. 2011). Alterations in the dopamine system have also been linked to aggression. Similar to findings in patients with ADHD, the nine‐repeat allele of the DAT1 gene and the seven‐repeat allele of the DRD4 gene have been associated with an increased risk of aggression. Children carrying at least one nine‐repeat allele of the DAT1 gene are at significantly higher risk for externalising behaviours (Young et al. 2002) and exhibit tenfold higher rates of CD and ODD symptoms (Lee et al. 2007). The seven‐repeat allele of the DRD4 gene has been shown to increase the risk of aggression in adulthood and CD symptoms (Buchmann et al. 2014; Rowe et al. 2001). Additionally, children with the seven‐repeat allele of the DRD4 gene who are exposed to high maternal stress prenatally are at greater risk for CD or ODD symptoms and display more externalising behaviours (Zohsel et al. 2014). One study has suggested that interactions between the DRD2 and DRD4 genes predict variability in adolescent CD and adult antisocial behaviour (Beaver et al. 2007). Catechol‐O‐methyltransferase (COMT), the enzyme responsible for the breakdown of dopamine, has also been shown to regulate aggression. COMT exhibits a functional polymorphism in which valine (Val) is substituted by methionine (Met) at codon 158 of the COMT gene (the Val158Met polymorphism). Met carriers have been found to have lower COMT activity compared to Val homozygotes, and in samples of children and adolescents with problem behaviours, met carriers have been shown to exhibit higher levels of aggression than Val homozygotes (Albaugh et al. 2010). Another study has reported that a single nucleotide polymorphism (SNP) in the COMT promoter is associated with higher levels of aggression (Hirata et al. 2013). Additionally, other research has shown that aggression is associated with increased dopamine release in the ‘reward’ pathway during the act of aggression (Mogavero et al. 2018). A 2008 study demonstrated that the substitution of valine for methionine at codon 158 is associated with CD ADHD and increased aggression (Caspi et al. 2008).

Recent findings indicate that dopaminergic neurotransmission and stress‐response systems may play a role in the neurobiological mechanisms underlying impulsivity and aggression in ADHD. In this context, the COMT and glucocorticoid receptor (NR3C1) genes have attracted significant attention. The functional COMT rs4680 (Val158Met) polymorphism has been associated with dopaminergic activity, impulsivity, emotional dysregulation and aggressive behaviours. Despite the absence of a consistent direct association between COMT Val158Met and ADHD susceptibility, as demonstrated by recent meta‐analyses, COMT‐related genetic variability may contribute to aggression‐related behavioural phenotypes in ADHD (Kang et al. 2020).

In a similar manner, NR3C1, a pivotal regulator of the hypothalamic–pituitary–adrenal (HPA) axis, has been implicated in stress responsivity and emotional regulation. Recent reviews indicate that NR3C1‐related epigenetic alterations may be associated with externalising behaviours, ADHD symptoms and aggression (Cecil et al. 2018). A review of the literature also indicates that the NR3C1 gene is significantly associated with cortisol concentration, adrenal body weight and aggressive behaviour in both humans and animals (Muráni et al. 2010; Li et al. 2017). Methylation primarily occurs in CpG regions, where a cytosine nucleotide is followed by a guanine nucleotide. CpG regions, particularly those in CpG islands, are highly sensitive to methylation. In the context of the NR3C1 gene, an increased frequency of cytosine in CpG regions may increase the likelihood of methylation, which can subsequently affect gene expression. The methylation of NR3C1 has been associated with a decrease in gene expression. When methylation occurs at the binding site for the nerve growth factor‐induced protein A (NGFI‐A) transcription factor, it interferes with gene transcription; methylation at other CpG sites can inhibit transcription through different mechanisms (Armstrong et al. 2014; Turner et al. 2008). Methylation of this region of the Nr3c1 gene and the associated decrease in glucocorticoid receptor numbers and glucocorticoid receptor‐mediated negative feedback have been linked to increased glucocorticoid secretion and behavioural problems (Zhang et al. 2013). In a 2014 study, individuals with the NR3C1 rs6198 C/C genotype were found to score higher on a measure of general externalisation traits as reported by parents, compared to T‐carriers (Bryushkova 2014). Similarly, a 2020 study in adults identified multiple CpG regions within the NR3C1 gene as being significantly associated with aggressive behaviour, suggesting that epigenetic alterations in NR3C1 may be associated with aggressive behaviour, potentially mediated by epigenetic processes that affect HPA axis activity (Liu et al. 2020). In a study examining methylation levels within the NR3C1 gene, individuals with methylation demonstrated higher lifetime externalising disorders and depression diagnoses, as well as greater early psychosocial adversity compared to healthy controls (Heinrich et al. 2015).

The present study was based on the priori hypothesis that COMT variants may be associated with increased aggression through dopaminergic dysregulation, whereas NR3C1‐related alterations may influence aggression phenotypes via stress‐response mechanisms. In our knowledge, there is no research examining aggression, aggression subtypes and hostility/resentment in children and adolescents diagnosed with ADHD without comorbid conditions in conjunction with the genes mentioned. This is what differentiates our study from other publications in the field.

2. Materials and Methods

This study was designed as a single‐centre, case–control, cross‐sectional investigation. Ethical approval was obtained from the Ethics Committee of the Faculty of Medicine at Manisa Celal Bayar University on 15.06.2022 with Decision Number 20.478.486/1483. The study was supported by the Scientific Research Projects Commission of Manisa Celal Bayar University Faculty of Medicine under Project Number 2023‐021. In our study, we examined 180 children and adolescents with respect to the NR3C1 and COMT genes, regardless of whether they had received psychostimulant or nonstimulant treatment, who met no diagnostic criteria for any psychiatric disorder other than ADHD and who either did or did not exhibit physical aggression, verbal aggression and/or hostility and resentment. A total of 180 children and adolescents diagnosed with ADHD and having a total intelligence score of 90 or above were included in the study.

A sociodemographic data form, developed in our clinic, was completed by one of the parents during the child's initial consultation. The sociodemographic data collected included the age of both the parent and the child, and the gender of the parent filling out the form. Aggression was classified into two categories: physical and verbal aggression. Physical aggression was further subdivided into three subcategories: ‘physical fights,’ ‘object throwing’ and ‘use of sharp instruments.’ Verbal aggression was similarly divided into ‘swearing,’ ‘insults’ and ‘degrading remarks.’ Hostility and resentment were recorded as binary responses: ‘yes’ or ‘no.’ Additionally, parents completed the Anger Scale for Ages 6–17 and the Turgay DSM‐IV Disruptive Behaviour Disorders Assessment Scale. To exclude comorbid diagnoses of CD, ODD and other psychiatric disorders, all children and adolescents were assessed using the Schedule for Affective Disorders and Schizophrenia for School‐Age Children‐Present and Lifetime Version (K‐SADS‐PL‐DSM‐5‐Turkish Adaptation). Psychometric assessments included the Wechsler Intelligence Scale for Children–Revised (WISC‐R).

A total of 69 children and adolescents diagnosed with ADHD and concurrent aggression were included in the case group, while 111 children and adolescents with ADHD and without concurrent aggression were included as the control group. Among the 111 cases, the T‐score on the DSM‐5 anger scale was below 55. The exclusion criteria for both the case and control groups included substance use disorder, autism spectrum disorder, intellectual disability, psychosis and related disorders, as well as mood disorders. No exclusion criteria were set for the parents.

2.1. Measures

2.1.1. DSM‐5 Level 2 Anger Scale (Ages 6–17)

The scale is a standardised self‐report measure developed to evaluate the frequency and severity of anger symptoms during the previous 7 days. It consists of five items rated on a 5‐point Likert scale ranging from 0 (‘never’) to 4 (‘almost always’), with higher scores indicating greater anger severity. The Turkish validity and reliability study conducted by Sapmaz et al. demonstrated satisfactory psychometric properties, including good internal consistency and construct validity in Turkish children and adolescents (Yalın Sapmaz et al. 2017).

2.1.2. Turgay DSM‐IV Disruptive Behaviour Disorders Assessment Scale

The scale assesses symptoms of attention‐deficit/hyperactivity disorder, ODD and CD according to DSM‐IV diagnostic criteria. Items are scored on a 4‐point Likert scale ranging from 0 (‘not at all’) to 3 (‘very much’). Higher scores indicate greater symptom severity. The Turkish adaptation study reported satisfactory validity and reliability findings, including good internal consistency coefficients for Turkish child and adolescent populations (Ercan et al. 2001).

2.1.3. K‐SADS‐PL‐DSM‐5‐TR

This semistructured diagnostic interview assesses current and lifetime psychiatric disorders in children and adolescents according to DSM criteria. The Turkish adaptation demonstrated adequate validity and reliability for clinical use in Turkish populations (Kaufman et al. 1997; Ünal et al. 2019).

2.1.4. Wechsler Intelligence Scale for Children–Revised (WISC‐R)

The WISC‐R is a standardised intelligence assessment tool designed for children and adolescents and provides verbal, performance and full‐scale intelligence quotient (IQ) scores. The Turkish standardisation and adaptation study conducted by Savaşır and Şahin established the reliability and validity of the instrument for Turkish children (Petrosko 1975; Savaşır and Şahin 1984).

2.2. AI Assistance Statement

The free version of OpenAI ChatGPT was used as a language editing tool in the preparation of this article. No content generation, data analysis or scientific decision‐making was performed by the AI system. The authors take full responsibility for the content of the manuscript.

2.3. DNA Isolation

DNA isolation was performed by taking 200 μL of blood from 2 mL peripheral venous blood samples collected from the cases using the spin column method according to the relevant protocol of the Invitrogen Purelink Genomic DNA mini kit. The amount and purity of the DNA in the samples were determined by measuring it with the Maestro ND2000 nanodrop device. The isolated genomic DNA samples exhibited a high‐quality purity profile, with the A 260/A 280 absorbance ratio ranging between 1.8 and 2.0, and concentrations were adjusted to a standard working dilution of 50 ng/μL for subsequent applications.

2.4. PCR Amplification and Sanger Sequence Analysis of the COMT (rs4680) and NR3C1 (rs10052957) Gene Region

COMTF1 5′‐ CAAGTTCCCCTCTCTCCACC ‐3′ and COMTR1 5′‐ CAGTGAACGTGGTGTGAACA ‐3′ primer pair was designed to amplify the rs4680 gene region of the COMT gene. In addition, NR3C1F2 5′‐ TTGTTGGGTGCCTGCTATGT ‐3′ and NR3C1R2 5′‐ CACTCTTCTGCTGCCCACTT ‐3′ primer pair was designed to amplify the rs10052957 gene region of the NR3C1 gene. The PCR reaction was set up with 2X PCR Dye Taq polymerase master mix (GeneMark), genomic DNA, COMTF1/R1 or NR3C1F2/R2 primer pairs and ddH20 in 20 μL total volume for each DNA sample separately. The prepared PCR reactions were amplified in a SensoQuest GmbH thermal cycler with a 5 min 95°C initial denaturation step followed by 45 s of 95°C denaturation, 45 s of 60°C annealing and a 1 min 72°C extension cycle (35 cycles), which ended with a 5 min 72°C final extension step. After the end of the PCR amplification, PCR reactions that were obtained to use in this study were exposed to an electrophoretic process for 1 h, under 100 V current in 1.0% agarose gel containing 0.05 μL/mL Safeview (GeneMark) agarose gel dye and were then, these gels were checked with a UV imaging system for the validation of the amplified gene region. The PCR reactions of each DNA sample were sequenced with a Big Dye cycle sequencing kit (Applied Biosystems, Foster City, California, USA) using an ABI 3130 XL genetic analyser (Applied Biosystems). In addition, to ensure high reliability and reproducibility in genotyping, several quality control procedures were implemented. A final sample call rate of 100% was achieved for both SNPs, and 10% of the samples were randomly selected for duplicate genotyping, resulting in 100% concordance with no errors. Postsequencing genotype calling was performed by two independent researchers, who visually inspected and verified the sequencing chromatograms using ABI Sequencing Analysis Software to address any potential ambiguities. Additionally, all laboratory personnel and researchers involved in genotyping and sequence analysis were strictly blinded to the clinical group status of the subjects (presence or absence of aggression).

2.5. Statistical Analysis

A post hoc power analysis was conducted using G*Power 3.1 software to evaluate the achieved statistical power based on the final sample size. The study included 180 children and adolescents diagnosed with ADHD, of whom 69 exhibited aggression symptoms and 111 did not. The analyses were performed within a clinical sample comparing two independent groups (aggression present vs. absent). For genetic association analyses, allele and genotype distributions between groups were compared using chi‐square (χ2) tests. The post hoc power analysis was performed for categorical comparisons between two independent groups, assuming a medium effect size (w = 0.30) and a significance level of α = 0.05. The achieved statistical power (1–β) was calculated as 0.91, indicating adequate power to detect medium‐sized effects and a low probability of Type II error.

Statistical analyses were performed using IBM SPSS Statistics Version 23. Normality of continuous variables was assessed using both the Shapiro–Wilk and Kolmogorov–Smirnov tests. For group comparisons, independent samples t‐tests were used for normally distributed variables, while the Mann–Whitney U test was applied for nonnormally distributed variables. Categorical variables were analysed using the chi‐square test. When appropriate, Fisher's exact test, Yates' continuity correction and the Fisher–Freeman–Halton test were also applied depending on expected cell counts and table structure. Data were presented as mean ± standard deviation for normally distributed continuous variables, median (minimum–maximum) for nonnormally distributed variables and frequency (percentage) for categorical variables. All statistical tests were two‐tailed, and an initial significance level of p < 0.05 was used prior to multiple comparison correction.

To control for Type I error inflation due to multiple comparisons across genotypes, alleles and behavioural phenotypes, a false discovery rate (FDR) correction using the Benjamini–Hochberg procedure was applied. Adjusted p values were calculated, and results with FDR‐corrected p < 0.05 were considered statistically significant. In addition, Hardy–Weinberg equilibrium (HWE) analysis was performed to evaluate whether the observed genotype frequencies in the control and case groups conformed to the expected theoretical proportions (p > 0.05 indicated adherence to HWE).

3. Results

Our sample consisted of 180 individuals. The gender distribution of the group with physical aggression was examined, the proportion of girls was 22.5%, while the proportion of boys was 77.6%. In the group without physical aggression, the proportion of girls was 31.3%, whereas the proportion of boys was 68.7%. When the association between sex and the presence of physical aggression was analysed, no statistically significant relationship was found (p = 0.327). When the sex distribution of the group with verbal aggression was examined, the proportion of girls was 34%, while the proportion of boys was 66%. In the group without verbal aggression, the proportion of girls was 27.1%, whereas the proportion of boys was 72.9%. When the association between sex and the presence of verbal aggression was analysed, no statistically significant relationship was found (p = 0.472). Aggression was detected in 69 participants, while 111 participants showed no signs of aggression, with an overall aggression prevalence of 38%. Among those exhibiting aggression, 49 participants demonstrated physical aggression; of these, 10 exhibited solely physical aggression. Additionally, 47 individuals exhibited verbal aggression, with 10 showing only verbal aggression. A total of 41 participants exhibited hostility and resentment, with only 6 showing exclusively these traits. The number of individuals exhibiting physical, verbal and hostile/resentful aggression was 25 (Table 1).

TABLE 1.

Sex distribution according to the presence of physical and verbal aggression in the study sample (N = 180).

Aggression type Girls, n (%) Boys, n (%) p
Physical aggression + 22.5% 77.6% 0.327
− 31.3% 68.7%
Verbal aggression + 34.0% 66.0% 0.472
− 27.1% 72.9%
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In addition, NR3C1 rs10052957 (C>T) and COMT rs4680 (A>G) polymorphism sites of 180 DNA samples were amplified by PCR, and these gene regions were analysed by Sanger sequencing. As a result of the analysis among these case samples, homozygous wild type NR3C1 rs10052957 (C/C), heterozygous polymorphism NR3C1 rs10052957 (C/T), homozygous polymorphism NR3C1 rs10052957 (T/T), homozygous wild type COMT rs4680 (A/A), heterozygous polymorphism COMT rs4680 (A/G) and homozygous polymorphism COMT rs4680 (G/G) were found (Figure 1).

FIGURE 1.

FIGURE 1

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Chromatograms of NR3C1 rs10052957 (C>T) and COMT rs4680 (A>G) polymorphism sites. Chromatograms of case samples of the PCR products demonstrate rs10052957 related heterozygous or homozygous nucleotide polymorphism signals (A). Chromatograms of case samples of the PCR products demonstrate rs4680 related heterozygous or homozygous nucleotide polymorphism signals (B).

As shown in Table 2, in the group characterized by physical aggression, no statistically significant difference in the distribution of NR3C1 gene genotypes was observed between the presence and absence of physical aggression groups. Specifically, in the presence of physical aggression, the genotypes were distributed as follows: C/C: 55.1%, C/T: 34.7% and T/T: 10.2%. In contrast, in the absence of physical aggression, the distributions were C/C: 58.0%, C/T: 28.2% and T/T: 13.7%. The χ2 statistic was 0.896 (df = 2, p = 0.639). Additionally, there were no significant differences between the groups in allele frequencies, with an odds ratio (OR) of 1.02 (95% CI = 0.60–1.71, p = 0.953).

TABLE 2.

Comparison of genotypes and allele frequencies according to the presence of physical aggression.

Gene Variant level Physical aggression χ2 p Odds ratio (95% CI) HWE (p) a
Present Absent
NR3C1 Genotype χ2 = 0.896, df = 2

0.639 b

* 0.852

 —
C/C 27 (55.1) 76 (58.0) Case: 0.359
C/T 17 (34.7) 37 (28.2) Control: 0.087
T/T 5 (10.2) 18 (13.7)
Allele χ2 = 0.003, df = 1

0.953 c

* 1.000

 1.02 (0.60–1.71) —
C 71 (0.724) 189 (0.721)
T 27 (0.276) 73 (0.279)
COMT Genotype χ2 = 2.065, df = 2

0.356 b

* 0.639

 —
A/A 16 (0.327) 54 (0.412) Case: 0.337
A/G 21 (0.429) 56 (0.427) Control: 0.319
G/G 12 (0.245) 21 (0.160)
Allele χ2 = 2.159, df = 1

0.142 c

* 0.379

 0.70 (0.44–1.13) —
A 53 (0.541) 164 (0.626) 0.70 (0.44–1.13)
G 45 (0.459) 98 (0.374)
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Abbreviations: CI, confidence interval; df, degrees of freedom.

a

HWE (p): Hardy–Weinberg equilibrium test Pearson p value.

b

Evaluated using the Pearson chi‐square test for genotype distribution.

c

Evaluated using the Pearson chi‐square test for allele distribution.

*

Benjamini–Hochberg procedure, false discovery rate (FDR) p value.

Similarly, no statistically significant difference was found in the distribution of COMT gene alleles between ADHD cases who exhibited physical aggression and those who did not (χ2 = 2.159, df = 1, p = 0.142) (Table 1). The frequency of the A allele was 62.6% in the absence of physical aggression group, compared with 54.1% in the presence of physical aggression group. Furthermore, the risk analysis suggested that the A allele did not show a statistically significant protective effect against the development of aggression in individuals with ADHD, yielding an OR of 0.70 (95% CI = 0.44–1.13, p = 0.142). Overall genotype analysis also indicated no significant differences between the groups (χ2 = 2.065, df = 2, p = 0.356), with genotype frequencies of A/A, A/G and G/G being 32.7%, 42.9% and 24.5% in the physical aggressive group, and 41.2%, 42.7% and 16.0% in the nonaggressive group, respectively.

In the group characterized by verbal aggression, no statistically significant difference in the distribution of NR3C1 gene genotypes was observed between groups (Table 3). Specifically, in the presence of verbal aggression, the genotypes were distributed as follows: C/C: 63.8%, C/T: 29.8% and T/T: 6.4%. In contrast, in the absence of verbal aggression, the distributions were C/C: 54.9%, C/T: 30.1% and T/T: 15.0%. The χ2 statistic was 2.522 (df = 2, p = 0.283). Additionally, there were no significant differences between the groups in allele frequencies, with an OR of 1.59 (95% CI = 0.91–2.78, p = 0.102).

TABLE 3.

Comparison of genotypes and allele frequencies according to the presence of verbal aggression.

Gene Variant level Verbal aggression χ2 p Odds ratio (95% CI) HWE (p) a
Present Absent
NR3C1 Genotype χ2 = 2.522, df = 2

0.283 b

* 0.566

 —
C/C 30 (63.8) 73 (54.9) Case: 0.447
C/T 14 (29.8) 40 (30.1) Control: 0.102
T/T 3 (6.4) 20 (15.0)
Allele χ2 = 2.680, df = 1

0.102c

* 0.326

 1.59 (0.91–2.78) —
C 74 (78.7) 186 (69.9)
T 24 (21.3) 80 (30.1)
COMT Genotype χ2 = 2.594, df = 2

0.273 b

0.566

 —
A/A 15 (31.9) 55 (41.4) Case: 0.319
A/G 20 (42.6) 57 (42.9) Control: 0.339
G/G 12 (25.5) 21 (15.8)
Allele χ2 = 2.668, df = 1

0.102 c

* 0326

 0.67 (0.42–1.08) —
A 50 (53.2) 167 (62.8) 0.67 (0.42–1.08)
G 44 (46.8) 99 (37.2)
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Abbreviations: CI, confidence interval; df, degrees of freedom.

a

HWE (p): Hardy–Weinberg equilibrium test Pearson p value.

b

Evaluated using the Pearson chi‐square test for genotype distribution.

c

Evaluated using the Pearson chi‐square test for allele distribution.

*

Benjamini–Hochberg procedure, false discovery rate (FDR) p value.

Similarly, no statistically significant difference was observed in the COMT gene allele distribution between ADHD cases who exhibited verbal aggression and those who did not (χ2 = 2.668, df = 1, p = 0.102) (Table 3). The frequency of the A allele was 62.8% in the group without verbal aggression compared to 53.2% in the group with verbal aggression. Additionally, the risk analysis indicated that the A allele did not demonstrate a statistically significant protective effect against the development of verbal aggression in individuals with ADHD, with an OR of 0.67 (95% CI = 0.42–1.08, p = 0.102). The overall genotype analysis also revealed no significant difference between the groups (χ2 = 2.594, df = 2, p = 0.273), with the frequencies of the A/A, A/G and G/G genotypes being 31.9%, 42.6% and 25.5% in the verbal aggression group and 41.4%, 42.9% and 15.8% in the group without verbal aggression, respectively.

Regarding the phenotypic subgroup characterized by resentment and hostility, no statistically significant difference was observed between the groups in the distribution of NR3C1 genotypes (Table 4). Specifically, in the presence of resentment and hostility, the genotypes were distributed as follows: C/C: 56.1%, C/T: 31.7% and T/T: 12.2%. In comparison, in the absence of resentment and hostility, the corresponding distributions were C/C: 57.6%, C/T: 29.5% and T/T: 12.9% (χ2 = 0.077, df = 2, p = 0.962). Additionally, allele frequencies did not differ significantly between the groups, yielding an OR of 0.98 (95% CI = 0.57–1.70, p = 0.950), which confirms a neutral allelic effect on this specific phenotype.

TABLE 4.

Comparison of genotypes and allele frequencies according to the state of resentment and hostility.

Gene Variant level Resentment and hostility χ2 p Odds ratio (95% CI) HWE (p) a
Present Absent
NR3C1 Genotype χ2 = 0.077, df = 2

0.962 b

* 1.000

 —
C/C 23 (56.1) 80 (57.6) Case: 0.170
C/T 13 (31.7) 41 (29.5) Control: 0.152
T/T 5 (12.2) 18 (12.9)
Allele χ2 = 0.004, df = 1

0.950 c

* 1.000

 0.98 (0.57–1.70) —
C 59 (72.0) 201 (72.3)
T 23 (28.0) 77 (27.7)
COMT Genotype χ2 = 6.618, df = 2

0.037 b

* 0.148

 —
A/A 12 (29.3) 58 (41.7) Case: 0.161
A/G 16 (39.0) 61 (43.9) Control: 0.544
G/G 13 (31.7) 20 (14.4)
Allele χ2 = 5.862, df = 1

0.015 c

* 0.120

 0.54 (0.33–0.89) —
A 40 (48.8) 177 (63.7) 0.54 (0.33–0.89)
G 42 (51.2) 101 (36.3)
Open in a new tab

Abbreviations: CI, confidence interval; df, degrees of freedom.

a

HWE (p): Hardy–Weinberg equilibrium test Pearson p value.

b

Evaluated using the Pearson chi‐square test for genotype distribution.

c

Evaluated using the Pearson chi‐square test for allele distribution.

*

Benjamini–Hochberg procedure, false discovery rate (FDR) p value.

In clear contrast, a statistically significant difference was detected in the COMT gene allele distribution between ADHD cases who exhibited resentment and hostility and those who did not (χ2 = 5.862, df = 1, p = 0.015) (Table 4). The frequency of the A allele was notably higher in the nonaggressive group (63.7%) than in the group with presentation of resentment and hostility (48.8%). Allelic risk analysis indicated that the A allele exerts a significant protective effect against the development of resentment and hostility in individuals with ADHD (OR = 0.54, 95% CI = 0.33–0.89, p = 0.015). Furthermore, the overall genotype analysis corroborated this association, revealing a significant variance between the clinical groups (χ2 = 6.618, df = 2, p = 0.037). This difference highlights that the frequency of the risky variant—the G/G homozygous genotype—was more than twice as prevalent in patients exhibiting resentment and hostility (31.7%) compared to those without such aggressive tendencies (14.4%). Although nominal significance was observed for COMT genotype distribution in the hostility/resentment subgroup (raw p = 0.037) and COMT allele distribution in both hostility/resentment (raw p = 0.015), these findings did not retain significance after FDR adjustment.

In the group characterised by aggression (including physical and/or verbal aggression, as well as grudges and hostility), no statistically significant difference was observed between groups in the distribution of NR3C1 gene genotypes (Table 5). Specifically, in the presence of aggression, the genotypes were distributed as follows: C/C: 56.5%, C/T: 33.3% and T/T: 10.1%. In contrast, in the absence of aggression, the distributions were C/C: 57.7%, C/T: 27.9% and T/T: 14.4%. The χ2 statistic was 1.031 (df = 2, p = 0.597). Additionally, there were no significant differences between the groups in allele frequencies, with an OR of 1.08 (95% CI = 0.67–1.74, p = 0.747).

TABLE 5.

Comparison of genotypes and allele frequencies according to the presence of aggression.

Gene Variant level Aggression χ2 p Odds ratio (95% CI) HWE (p) a
Present Absent
NR3C1 Genotype χ2 = 1.031, df = 2

0.597 b

*0.852

 —
C/C 39 (56.5) 64 (57.7) Case: 0.211
C/T 23 (33.3) 31 (27.9) Control: 0.098
T/T 7 (10.1) 16 (14.4)
Allele χ2 = 0.104, df = 1

0.747 c

*0.920

 1.08 (0.67–1.74) —
C 101 (73.2) 159 (71.6)
T 37 (26.8) 63 (28.4)
COMT Genotype χ2 = 5.096, df = 2

0.078 b

0.208

 —
A/A 22 (31.9) 48 (43.2) Case: 0.193
A/G 29 (42.0) 48 (43.2) Control: 0.589
G/G 18 (26.1) 15 (13.5)
Allele χ2 = 5.089, df = 1

0.024 c

0.128

 0.61 (0.39–0.94) —
A 73 (52.9) 144 (64.9) 0.61 (0.39–0.94)
G 65 (47.1) 78 (35.1)
Open in a new tab

Abbreviations: CI, confidence interval; df, degrees of freedom.

a

HWE (p): Hardy–Weinberg equilibrium test Pearson p value.

b

Evaluated using the Pearson chi‐square test for genotype distribution.

c

Evaluated using the Pearson chi‐square test for allele distribution.

**

Benjamini–Hochberg procedure, false discovery rate (FDR) p value.

In contrast, a significant difference was observed in the allele distributions of the COMT gene when comparing ADHD cases that exhibited aggression (physical and/or verbal, as well as grudge and hostility) to those that did not (χ2 = 5.089, df = 1, p = 0.024) (Table 5). The frequency of the A allele was notably higher in the nonaggressive group (64.9%) compared to the aggressive group (52.9%). Additionally, the risk analysis indicated that the A allele has a significantly protective effect against the development of aggression in individuals with ADHD, with an OR of 0.61 (95% CI = 0.39–0.94, p = 0.747). Although the overall genotype analysis showed a trend towards borderline significance (χ2 = 5.096, df = 2, p = 0.078), it is important to highlight that the frequency of the risky variant, the G/G homozygous genotype, was approximately twice as prevalent in cases exhibiting aggression (26.1%) compared to those without aggressive tendencies (13.5%). Although nominal significance was observed for COMT allele distribution in the overall aggression analyses (raw p = 0.024), this finding did not retain significance after FDR adjustment.

4. Discussion

In this study, we examined independent main effects of the NR3C1 and COMT genes in 180 children and adolescents who did not meet the criteria for any psychiatric diagnosis other than ADHD, irrespective of whether they had undergone psychostimulant treatment, and who exhibited either physical aggression, verbal aggression or hostility or did not. Of the 180 participants, 69 demonstrated some form of aggression (physical and/or verbal aggression and/or hostility), while 111 showed no signs of aggression. A strength of the present study is that participants with psychiatric disorders that could potentially accompany the primary diagnosis were carefully screened during the assessment process and excluded according to the predefined exclusion criteria, thereby increasing the homogeneity of the sample. One of the key distinctions of our study, which sets it apart from others in the literature, is the individual and parallel assessment of the NR3C1 and COMT genes in relation to physical aggression, verbal aggression and hostility.

Our primary findings indicated a statistically significant relationship between the presence of hostility and the COMT gene genotypes as well as the distribution of COMT alleles. These first statistical findings are in line with previous research linking variations in the COMT gene with aggressive behaviour (Sheikh et al. 2013). Although an initial association was observed between the COMT Val158Met polymorphism and aggression in children with ADHD, this association was no longer significant after adjustment for relevant clinical covariates. Notably, our study identified that 38% of the children and adolescents in our sample exhibited some form of aggression, a rate that differs from those reported in other studies (Jensen et al. 2007; Saylor and Amann 2016). The variability in these rates across studies could be attributed to the absence of a gold‐standard method for assessing aggression and the nosological differences in classifying aggression, as highlighted in previous literature (Connor et al. 2004). Differences in reported aggression prevalence across studies may also reflect variations in sampling strategies, such as recruitment from tertiary psychiatric centres versus community‐based populations, as well as differences in concurrent psychopharmacological treatments that may influence aggressive behaviour.

The COMT gene rs4680 polymorphism is a G→A single nucleotide polymorphism in exon 4, which leads to the substitution of valine by methionine, commonly known as the Val158Met polymorphism (Saylor and Amann 2016). This polymorphism causes the Val (valine) allele to exhibit higher activity and the Met (methionine) allele to exhibit lower activity. Variations in the gene coding for COMT have been linked to aggressive behaviours (Sheikh et al. 2013). A study demonstrated an association between the valine‐to‐methionine substitution at codon 158 of the COMT gene, CD, ADHD and increased aggression (Caspi et al. 2008). Another study showed that the COMT Val (108/158) Met polymorphism modulates task‐oriented behaviour but does not affect the behavioural response to MPH treatment (Sengupta et al. 2008). In our study, a significant association was identified between the COMT gene and the presence of resentment and hostility, with the adenine (A) and guanine (G) allele frequencies in the COMT gene also showing significant associations with resentment and hostility However, these statistically significant findings were no longer significant after advanced statistical analysis. Phenotypic heterogeneity is a major factor contributing to inconsistent findings across studies, as aggression, CD, ODD, irritability and antisocial behaviour are not considered to represent the same underlying biological construct (Langevin et al. 2016). Developmental stage and sex may also moderate the effect of COMT; several reviews have suggested that the direction of the association may vary across developmental periods and have emphasised the limited evidence available for females (Hosák 2007; Langevin et al. 2016). Furthermore, gene–environment interaction appears to play an important role. Increased aggression has been reported among children homozygous for the Val allele only in the presence of severe adverse life events, whereas this association may not be observed in the absence of relevant environmental stressors (Del Puerto‐Golzarri et al. 2023; Sadeh et al. 2023). These findings support the notion that COMT may function as a susceptibility rather than a deterministic gene. Overall, our findings are consistent with the current literature, suggesting that COMT may represent a potential biomarker of aggression in individuals with ADHD, although its independent contribution appears modest and lacks robustness. The disappearance of the initial association after adjustment for relevant clinical and demographic covariates may reflect the small effect size of COMT, as well as the substantial heterogeneity of aggressive phenotypes and the influence of developmental and environmental moderators. Given that ADHD is a highly polygenic disorder, it is unlikely that a single functional polymorphism can adequately explain variability in aggressive behaviour. Future studies integrating polygenic risk scores, longitudinal developmental trajectories and gene–environment interactions may better clarify the contribution of COMT to aggression in ADHD. A review of the literature also indicates that the NR3C1 gene is significantly associated with cortisol concentration, adrenal body weight and aggressive behaviour in both humans and animals (Muráni et al. 2010; Li et al. 2017). Methylation primarily occurs in CpG regions, where a cytosine nucleotide is followed by a guanine nucleotide. CpG regions, particularly those in CpG islands, are highly sensitive to methylation. In the context of the NR3C1 gene, an increased frequency of cytosine in CpG regions may increase the likelihood of methylation, which can subsequently affect gene expression. The methylation of NR3C1 has been associated with a decrease in gene expression. When methylation occurs at the binding site for the nerve growth factor‐induced protein A (NGFI‐A) transcription factor, it interferes with gene transcription; methylation at other CpG sites can inhibit transcription through different mechanisms (Armstrong et al. 2014; Turner et al. 2008). Methylation of this region of the Nr3c1 gene and the associated decrease in glucocorticoid receptor numbers and glucocorticoid receptor‐mediated negative feedback have been linked to increased glucocorticoid secretion and behavioural problems (Zhang et al. 2013). In a 2014 study, individuals with the NR3C1 rs6198 C/C genotype were found to score higher on a measure of general externalisation traits as reported by parents, compared to T‐carriers (Bryushkova 2014). Similarly, a 2020 study in adults identified multiple CpG regions within the NR3C1 gene as being significantly associated with aggressive behaviour, suggesting that epigenetic alterations in NR3C1 may be associated with aggressive behaviour, potentially mediated by epigenetic processes that affect HPA axis activity (Liu et al. 2020). In a study examining methylation levels within the NR3C1 gene, individuals with methylation demonstrated higher lifetime externalising disorders and depression diagnoses, as well as greater early psychosocial adversity compared to healthy controls (Heinrich et al. 2015). Our study found no statistically significant relationship between the NR3C1 gene and types of aggression. While a systematic review revealed that a significant number of studies reported an association between increased NR3C1 methylation and psychopathology/externalising symptoms, some studies found no association, indicating a heterogeneous literature and the need for further research (Wadji et al. 2021). In addition, the absence of a significant association between NR3C1 and aggression in the present ADHD sample should be interpreted within recent epigenetic frameworks emphasising the context‐dependent regulation of HPA‐axis genes in externalising behaviours. Current evidence suggests that the effects of NR3C1 are primarily mediated through environmentally sensitive epigenetic mechanisms (e.g., DNA methylation) rather than stable genetic main effects. Variability is strongly influenced by early‐life stress and developmental timing (Cecil and Nigg 2022; Zannas and Binder 2019). In the context of ADHD‐related aggression, recent epigenetic findings suggest that genes involved in stress regulation, such as NR3C1, FKBP5 and CRHR1, play a role in individual differences in emotional and behavioural dysregulation. These genes appear to exert small, heterogeneous and context‐dependent effects, which are often only observable under specific environmental conditions (Dunn et al. 2023). Within this theoretical framework, aggression is better conceptualised as a multifactorial externalising phenotype shaped by interacting epigenetic and neurobiological systems, rather than as the result of single‐gene effects. Consequently, the absence of a significant finding in this study is likely indicative of the developmental and environmental specificity of NR3C1 epigenetic effects, as well as methodological limitations characteristic of peripheral epigenetic research, rather than an absence of biological relevance in ADHD‐related aggression.

The present sample, which encompasses a relatively broad age range (7–18 years), signifies a significant developmental limitation that ought to be taken into account during the interpretation of the findings. Recent literature in developmental psychopathology and epigenetics indicates that HPA‐axis–related gene expression, including NR3C1 methylation and transcriptional activity, shows marked developmental variability across childhood and adolescence, particularly during pubertal transition periods when stress‐response systems undergo significant recalibration (Romens et al. 2021; McEwen and Akil 2020). Conversely, aggression and other externalising behaviours exhibit pronounced developmental shifts, with evidence indicating that reactive and impulsive forms of aggression are more prevalent in childhood, whereas regulatory and context‐dependent forms become more differentiated in adolescence (Smeets et al. 2017; Alsem et al. 2022). In the context of ADHD, recent developmental models underscore the notion that neurobiological and behavioural phenotypes are not static across the lifespan but rather represent dynamic interactions between the maturation of prefrontal regulatory systems and stress‐related limbic reactivity. These interactions may also moderate the expression of genetic and epigenetic influences (Shaw et al. 2013; Nigg et al. 2022). Consequently, the integration of children and adolescents within a uniform analytical framework might have led to the introduction of developmental heterogeneity, which could have resulted in the obscuring of age‐specific associations between NR3C1‐related mechanisms and aggression. Contemporary epigenetic research lends further support to the hypothesis that DNA methylation patterns in stress‐related genes are developmentally dynamic and sensitive to both age and pubertal status. This suggests that NR3C1‐related effects may differ substantially across developmental stages, rather than remaining stable across childhood and adolescence (Zannas and Binder 2019; Cecil and Nigg 2022). Consequently, the absence of age stratification in the present study may have constrained the capacity to discern developmental stage‐specific effects, and future studies should contemplate age‐ or puberty‐stratified analyses to more effectively capture these dynamic biological processes.

In conclusion, the study did not find a statistically significant association between the NR3C1 and COMT gene and the presence of aggression in ADHD. Our study distinguishes itself from others by jointly parallel evaluating the NR3C1 and COMT genes in children and adolescents diagnosed with ADHD who have no comorbid conditions. In our study, the inclusion of only children diagnosed with ADHD represents a strength. On the other hand, the use of a structured scale for the assessment of anger is a notable strength of the study.

Differences in the reported prevalence of aggression across studies should also be interpreted in light of methodological factors. Variations in sample selection, including recruitment from tertiary referral clinics versus community‐based populations, may influence the clinical severity and comorbidity profiles of participants. In addition, differences in concurrent psychopharmacological treatment status may affect the expression of aggressive behaviours and contribute to inconsistent findings across studies. These methodological considerations, together with phenotypic heterogeneity, developmental factors and environmental influences, may also partly explain the lack of robust associations observed for both COMT and NR3C1 polymorphisms in the present study. Therefore, the genetic contribution to aggression in ADHD is likely multifactorial and should be interpreted within the broader context of clinical and environmental variability.

However, several limitations must be noted. One of these is that aggression was assessed based on reports obtained from both the parents and the child. In addition, the small sample size, the relative underrepresentation of female participants, the reliance on information provided by only one parent and the inclusion of participants who were on medication are limitations. Additionally, information from teachers or other third‐party sources could not be obtained, which may have provided a more comprehensive understanding, and we were unable to examine potential genetic differences between genders. Another limitation of the present study is that environmental factors potentially associated with aggression phenotypes, such as family adversity and psychosocial stressors, were not controlled for in the analyses and its cross‐sectional design, which limits the ability to draw causal inferences regarding the relationship between genetic variations and aggression‐related phenotypes. Therefore, the findings should be interpreted with consideration of the possible influence of unmeasured environmental variables. The present study has the relatively limited sample size, which may have reduced the ability to detect small genetic effects. Therefore, the absence of a significant association for NR3C1 should not necessarily be interpreted as evidence of a true negative finding, as small effect sizes may not have been detectable despite the reported statistical power. Certain demographic variables such as medication use, age and sex were not statistically controlled for or matched in the analyses. It is acknowledged that medication use, age and sex may potentially influence phenotypic aggression levels and complex genetic associations; consequently, the lack of control over these variables constitutes a limitation of the present study. While the present study provides a valuable contribution to the extant literature, further research with larger sample sizes and age‐ and sex‐matched cohorts is essential. The integration of more structured genetic designs in future studies will facilitate the comprehensive elucidation of the genetic basis of aggression and the validation of our findings.

Author Contributions

Öznur Bilaç and Mert Kaan Kale have constructed the conception and design of the study. Öznur Bilaç and Mert Kaan Kale have arranged/edited the material and method section and the study instruments. The article was written by Mert Kaan Kale, Öznur Bilaç. Mert Kaan Kale has done the analysis and evaluation of the data with Muhammet Burak Batır and Fethi Sırrı Çam in the results section. Mert Kaan Kale collected the study data. Muhammet Burak Batır and Fethi Sırrı Çam conducted the genetic analyses of the study, writing the genetic methodology section, interpreting the genetic results and managing the genetic analyses. Öznur Bilaç, Mert Kaan Kale and Fethi Sırrı Çam reviewed and proofread the study.

Funding

This work was supported by the Manisa Celal Bayar Üniversitesi (Unit. Project Number: 2023‐021).

Disclosure

The free version of OpenAI ChatGPT was used as a language editing tool in the preparation of this article. No content generation, data analysis or scientific decision‐making was performed by the AI system. The authors take full responsibility for the content of the manuscript.

Ethics Statement

Ethical approval for this study was obtained from the Ethics Committee of the Faculty of Medicine at Manisa Celal Bayar University on 15.06.2022 approval date and approval/reference number: 20.478.486/1483. Written informed consent was obtained from all participants. For participants under the age of 18, written informed consent was obtained from their parents or legal guardians, and assent was obtained from the children/adolescents where appropriate. The study was conducted in accordance with the ethical standards of the Declaration of Helsinki.

Acknowledgements

The authors thank the participating children, adolescents and parents for their cooperation and support.

Data Availability Statement

The datasets analysed during the current study are available from the corresponding author upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The datasets analysed during the current study are available from the corresponding author upon reasonable request.

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