Highlights
· In boys with premature adrenarche, obesity was independently associated with advanced bone age progression. Although dehydroepiandrosterone sulfate levels were elevated in this population, they did not mediate the relationship between obesity and bone age advancement. This suggests that obesity appears to directly contribute to bone maturation through mechanisms independent of adrenal androgen levels.
Introduction
Premature adrenarche (PA) is characterized by adrenal activation in girls less than 8-years-old and boys less than 9-years-old. PA is classified as either biochemical adrenarche or clinical adrenarche [1,2]. Biochemical adrenarche refers to the midchildhood increase in adrenal androgen precursor levels such as those of dehydroepiandrosterone (DHEA) and DHEA sulfate (DHEA-S). A serum DHEA-S level above 40 μg/dL is the usual cutoff value for a diagnosis of biochemical adrenarche [1]. Clinical adrenarche is diagnosed from the presence of visible signs of androgenic activity and elevated adrenal androgen secretion on physical examination. These signs include the presence of pubic or axillary hair, the detection of a body odor of an adult, and the onset of acne. Typical pubertal signs like breast development in girls and testicular enlargement in boys are, however, generally absent [2,3]. Children with PA may experience adverse long-term health outcomes, including the development of metabolic syndrome, insulin resistance, and functional ovarian hyperandrogenism [1,4-7]. Although most affected children achieve midparental height, some fail to achieve their target adult height owing to the advancement of bone age (BA) [8].
The prevalence of childhood obesity is currently increasing, and this condition is a significant factor in the association of androgen regulation with BA progression [9-13]. Accelerated bone aging occurs in obese children and in children with PA. The cause of the accelerated bone aging is not fully understood, but one theory posits a role for obesity- and PA-associated adrenal androgen level elevations and the conversion of these androgens to estrogens either peripherally or at the growth plate [14-16]. Sopher et al. [14] demonstrated that even after adjusting for weight, the BA/chronological age (CA) ratio was higher in the group of children with PA compared to that of children in the control group. This finding suggests that the presence of obesity and/or PA may involve additional hormonal factors that affect BA. However, experimental data from tests of the possible mediation of the obesity and accelerated bone aging association by either adrenal androgens or other hormones are limited.
PA is substantially more common in girls than in boys; approximately 90% of PA cases occur in girls [17]. The higher prevalence of PA in girls is likely due to the greater adiposity and peripheral conversion of DHEA-S to active androgens in women than in men [1,18,19]. While several studies have examined the relationship between PA and obesity in girls, relatively few studies have examined this in boys [6,13,19].
Therefore, our study aimed to test for an association between obesity and BA progression in boys with PA and for evidence of a role for elevated concentrations of adrenal androgens in any identified obesity-PA association.
Materials and methods
We retrospectively reviewed the medical records of boys diagnosed with PA among those who visited the Pediatric Endocrinology Clinic of Hanyang University Hospital between March 2021 and May 2023. PA was defined as the appearance of clinical signs of androgen activity, such as the presence of acne or comedones, oily hair and skin, body odor of individuals of a greater CA, and pubic and/or axillary hair, in boys less than 9-years-old. No testicular enlargement was observed in these patients, and their serum DHEA-S levels were≥40 μg/dL [1,2,20]. Patients with chronic diseases, endocrine disorders requiring hormonal treatment, idiopathic short stature, precocious puberty, and genetic disorders were excluded from our assessments as were those diagnosed as being small for gestational age.
1. Pubertal and clinical assessments
Pubertal and clinical assessments of the participants were performed by a trained pediatric endocrinologist (SY). Testicular volume was evaluated by palpation, and these evaluations were compared with those of the orchidometer of Prader [21] for assessment of accuracy. The presence or absence of pubic hair was determined through visual inspection using the Marshall and Tanner rating scales [22].
Height (cm) was measured with a Harpenden stadiometer (Holtain Ltd., UK), and body weight (kg) was measured using a digital scale (GL-310C; G-Tech International Co. Ltd., Korea). Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared (kg/m²). Age- and sex-standardized z-scores for height, weight, and BMI were determined using the 2017 Korean National Growth Charts [23]. Normal weight was defined as having a BMI below the 85th percentile for age and sex, and being overweight or obese was defined as having a BMI equal to or above the 85th or 95th percentiles for age and sex, respectively.
2. BA assessment
We obtained radiographs of the left hand and wrist, and 2 pediatric endocrinologists assessed BA using the Greulich and Pyle standards [24]. The difference between BA and CA was calculated as BA–CA, and a BA–CA≥1 was defined as significant skeletal maturation.
3. Laboratory evaluation
We collected venous blood samples to measure hormonal and metabolic marker levels, including those of DHEA-S, adrenocorticotropic hormone (ACTH), cortisol, 17-hydroxyprogesterone (17α-OHP), insulin-like growth factor-1 (IGF-1), insulin-like growth factor binding protein-3 (IGFBP-3), and 25-hydroxyvitamin D (25-(OH) vitamin D). Samples for ACTH, cortisol, and 17α-OHP measurements were obtained in the morning, between 08:00 and 10:00, following an overnight fast. DHEA-S, ACTH, cortisol, IGF-1, IGFBP-3, and 25-(OH) vitamin D levels were analyzed using electrochemiluminescence immunoassay, and 17α-OHP levels were assessed using a radioimmunoassay. DHEA-S levels were converted to z-scores using age-specific reference data from Elmlinger et al. [25] for standardized comparisons.
4. Statistical analysis
Statistical analysis was performed using IBM SPSS Statistics ver. 26.0 (IBM Co., USA). Continuous variable data are presented as means±standard deviations or as medians and ranges, and categorical variable data are presented as frequencies (percentages). The chi-squared test was used to compare categorical variable data between groups. For continuous variables, analysis of variance was used for comparisons between multiple groups, and the Student t-test was employed for data comparisons between the 2 groups. The Shapiro-Wilk test was used to test the normality of data distribution. Pearson correlation analysis was performed to test for relationships among clinical factors. To identify clinical factors predicting BA–CA>1, a multivariate logistic regression analysis was performed. This analysis incorporated variables with P-values <0.05 in the univariate analyses. The PROCESS macro for SPSS was used to test for mediation of the identified BMI z-score and BA–CA association by adrenal androgens. Our study used model 4 from Hayes' PROCESS macro [26] to test for this mediation effect. This mediation model is simple and evaluates the influences of an independent variable on a dependent one through a mediator variable. Indirect effect bootstrap confidence intervals (CIs) were estimated using 5,000 bootstrap samples with bias-corrected results. A P-value of less than 0.05 was considered statistically significant.
Results
1. Clinical characteristics of the participants
Initially, data from 82 boys less than 9-years-old presenting with clinical signs of androgen activity but no testicular enlargement were considered for inclusion in this study's analyses. Of these, 5 children were excluded due to having DHEA-S levels below 40 μg/dL, and 10 additional boys were excluded because of failure to meet all inclusion criteria. Therefore, data from 67 boys were included in the final analyses. The participants were divided into 2 groups according to their BA–CA values. Forty participants were classified in the BA–CA<1 group, and the other 27 were assigned to the BA–CA≥1 group (Fig. 1).
Table 1 presents the clinical characteristics of the study population. The mean age of the participants was 8.2±0.7 years, and no significant age difference between the 2 groups existed. However, participants in the BA–CA≥1 group were significantly taller, 0.8±1.0 versus 0.4±0.8 with P<0.001, and heavier, 1.7±0.9 versus 0.9±1.1 with P=0.002; had higher BMI z-scores, 1.7±0.9 versus 1.0±1.3 with P=0.022; and had more advanced BA, 10.2±1.0 years versus 8.2±0.9 years with P<0.001, than those in the BA–CA<1 group. Additionally, in the BA–CA≥1 group, a significantly higher proportion of participants were obese, 55.6%; only 30.0% of BA–CA<1 group participants were obese. Also, the proportion of participants with weights in the normal range was substantially lower in the BA–CA≥1 group, 18.5%, compared to 55.0% of those in the BA–CA<1 group, P=0.012. No significant prenatal history or family-related factor differences, including maternal age at menarche and midparental height, were observed between the groups (Table 1). Among the hormonal and metabolic markers analyzed, only DHEA-S levels and DHEA-S z-scores showed significant differences between the 2 groups; the BA–CA≥1 group had higher DHEA-S levels, 113.1±54.1 versus 86.5±39.4 μg/dL with P=0.023, and DHEA-S z-scores, 1.7±1.3 versus 1.1±0.7 with P=0.020, than those of participants in the BA–CA<1 group. No significant differences were observed in ACTH, cortisol, 17α-OHP, IGF-1, IGFBP-3, and 25-(OH) vitamin D levels between the 2 groups.
We also classified the study population into subgroups based on BMI, comparing the data among normal weight, overweight, and obese groups (Supplementary Table 1). BA–CA was significantly higher in the overweight and obese groups, 0.3±0.8, 0.9±0.8, and 1.2±1.4 years, respectively, with P=0.017. However, no significant difference was observed in DHEA-S z-scores among these groups, 1.2±0.8, 1.0±0.6, and 1.6±1.2 μg/dL, respectively, with P=0.196.
2. Factors affecting BA progression: regression and correlation analyses
Table 2 presents the results of the univariate and multivariate logistic regression analyses that were conducted to identify factors associated with BA progression (BA–CA≥1). In the univariate analyses, BA, height, weight, BMI, and DHEA-S z-scores were significantly associated with BA–CA≥1. However, due to their significant correlations with BMI z-score, height and weight z-scores were not analyzed simultaneously to avoid multicollinearity. BA was also excluded, due to its strong influence on BA–CA, in the assessments of the independent effects of other variables. In multivariate analyses, the BMI z-score remained significantly associated with BA–CA≥1 after adjusting for DHEA-S z-score, odds ratio [OR]=1.605 with a 95% CI of 1.003–2.567 and a P=0.048. However, DHEA-S z-score was not significantly associated with BA–CA≥1 after adjusting for BMI z-score, Or=1.804 with a 95% CI of 0.981–3.319 and a P=0.058 (Table 2).
In correlation analyses, BA–CA positively correlated with BMI z-score, r=0.285 with P=0.019, and DHEA-S z-score, r=0.412 with P=0.001. However, BMI z-score and DHEA-S z-score were not significantly correlated, r=0.136 and P=0.273 (Supplementary Table 2).
3. Associations between BMI z-score and BA-CA: a mediation analysis
Table 3 show the results of mediation analyses testing for the existence of a DHEA-S z-score mediating effect on the identified BMI z-score and bone aging association. The analyses indicated a statistically significant direct effect of BMI z-score on BA–CA, P=0.039, and a DHEA-S z-score and BA–CA association, P=0.001. However, the indirect effect of BMI z-score on BA–CA via DHEA-S z-score mediation was not significant.
Discussion
In this study, BMI z-score was independently associated with advanced BA in boys with PA, even after adjusting for DHEA-S z-score. BMI z-score and DHEA-S level showed no significant correlation, and DHEA-S z-score did not mediate the relationship between obesity and advanced BA.
Our study identified a positive correlation between BMI z-score and BA–CA, suggesting that higher BMI z-scores are associated with more rapid skeletal maturation relative to CA. This finding is consistent with existing reports of similar associations in obese children without PA. Therefore, these findings suggest the presence of a universal mechanism by which excess adiposity contributes to advanced BA [10,27]. Obesity induces a cascade of metabolic changes, primarily through increased insulin resistance and altered secretion of cytokines and adipokines [11,28]. Elevated insulin resistance in obesity raises IGF-1 levels, further accelerating bone aging by stimulating growth plate activity [11,14]. Additionally, obesity-related cytokine secretion, such as that of tumor necrosis factor-alpha, and secretion of hormones like leptin are associated with inflammatory responses in adipose tissue that may influence adrenal function [29,30]. In obese individuals, lower adiponectin levels lead to insulin resistance and accelerate bone aging. This interplay illustrates the obesity-driven metabolic factor impacts on both adrenal androgen levels and skeletal maturation [11,14,27,28,30]. Obesity may accelerate bone aging by increasing the conversion of androgens into estrogen within adipose tissue. This process results from higher aromatase activity due to increased body fat. These estrogens then stimulate the growth plate, thereby leading to early skeletal maturation [14-16].
Notably, while DHEA-S z-scores were significantly higher in boys with BA–CA≥1 than in those with BA–CA<1, multivariate analysis revealed that DHEA-S z-score did not independently predict BA progression after adjusting for BMI z-score. This suggests that although adrenal androgens are crucial in the pathophysiology of PA, their role in skeletal maturation might be mediated or usurped by other factors associated with adiposity. Previous studies [14,31] have indicated that obese children with PA tend to have higher adrenal androgen levels and that obesity is associated with BA progression. Additionally, some reports have even suggested that increased DHEA-S levels serve as an independent predictor of and play a central role in advanced bone aging in obese children [32]. However, we specifically tested for an association between obesity and BA progression in boys with PA and for mediation of any identified association between these by the presence of increased adrenal androgen levels. We found that DHEA-S levels did not independently predict BA progression, a result that differs from previous research findings. We suggest that in obese boys with PA, obesity alone, not DHEA-S levels, is the primary factor contributing to rapid skeletal maturation.
Our mediation analysis examined the relationship between BMI, DHEA-S z-score, and BA–CA and revealed a significant direct effect of BMI z-score on BA progression. However, the indirect effect through DHEA-S z-score was not significant. Therefore, obesity affects skeletal maturation through mechanisms other than adrenal androgen levels. Although DHEA-S level was associated with BA progression in our study, this level was not an independent predictor in multivariate analysis. Also, no significant indirect effect was identified in the mediation analysis. This inconsistency with previous findings regarding the role of DHEA-S levels may be due to our specific focus on boys with PA who had already undergone biochemical adrenarche. In contrast, previous studies generally included prepubertal children without considering adrenarche status [2,17]. Children with PA may have a unique metabolic environment; in this population, obesity may accelerate bone maturation through metabolic pathways other than DHEA-S level alone [15].
Obesity might directly influence skeletal maturation through increased insulin resistance, altered growth hormone secretion, and enhanced estrogen synthesis from peripheral androgens [12,27,33,34]. These findings highlight the complex interplay between obesity, adrenal androgen secretion, and skeletal maturation in boys with PA. Future longitudinal studies are warranted to elucidate the pathway alterations that underlie these associations and to test potential interventions that target modifiable risk factors like obesity. These interventions will mitigate accelerated bone aging and its potential long-term consequences on growth and development.
This study has some limitations. First, its cross-sectional and retrospective design limited our ability to assess causal relationships in the pathogenesis of BA progression. Second, our sample size was relatively small. This may have restricted our ability to detect an influence of DHEA-S levels on skeletal maturation. Future studies with larger samples will provide clearer insight into the role of DHEA-S levels in BA progression. Third, the subjective nature of BA assessment may have introduced variability across studies and thereby influenced the differences in results. Fourth, the assessment of adrenal androgen activity focused primarily on DHEA-S measurements. Including other androgen measurements, such as those of androstenedione, may improve our understanding of the hormonal dynamics in PA. Fifth, our study predominantly relied on BMI as a measure of obesity and did not include additional metrics such as waist circumference and total body fat; and including obesity-related parameters such as fasting insulin level, the homeostatic model assessment for insulin resistance, or leptin level may have provided a more comprehensive understanding of related factors. Also, owing to limited Korean percentile data, we analyzed DHEA-S levels using European references for z-scores.
Our study's strength was its focus on an under-studied population, boys with PA [6,19]; and, to the best of our knowledge, this study was the first to investigate the mediating effect of adrenal androgen levels on the association between obesity and BA progression in prepubertal boys with PA. Future studies with a larger number of participants will provide a more comprehensive evaluation of obesity in relation to adrenal androgens in the pathophysiology of PA.
In conclusion, our study provides evidence that obesity is independently associated with accelerated BA progression in boys with PA. These findings highlight the importance of early recognition and management of obesity in this population to potentially mitigate adverse skeletal outcomes associated with accelerated bone aging.
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