This is the first study establishing LMS-based continuous pediatric reference percentiles for sRANKL, OPG and sRANKL/OPG ratio, which were derived from the HARP cohort. This allows the calculation of standardized patient z-scores to improve assessment and monitoring of bone modeling in children in clinical practice and studies.

In the present study, LMS percentiles for serum sRANKL, OPG and sRANKL/OPG ratio were negatively associated with age, while sRANKL and sRANKL/OPG ratio also associated with sex. Boys, but not girls, showed a second although lower peak for sRANKL and sRANKL/OPG ratio during ages 12–13 years. The strong age-dependence of all parameters assessed, with highest values during infancy, is striking. This most likely represents the physiologically highest growth rates and thus higher bone modeling in infancy compared to childhood and adolescence [3]. A second peak for sRANKL and the sRANKL/OPG ratio was observed in boys at the ages of 12–13, the point of physiological onset of pubertal growth spurt, indicating a high bone modulation with relatively increased bone resorption at this age. This further supports the concept, that increased bone modeling in early puberty, together with the strongly increased gains of height and weight but lag of bone mineral accrual, contributes to a more filigree long bone and explains the observed increased fracture rate in early puberty [27]. In addition, it has been demonstrated that sex hormones regulate RANK and sRANKL expression, possibly leading to an increase in their concentrations during puberty [28]. The absence of a second peak for sRANKL and the sRANKL/OPG ratio during puberty in girls may, at least partly, be due to the fact that girls show less bone mass accrual during puberty and consequently have less bone remodeling than boys during this period [29].

The previously largest pediatric cross-sectional study reporting on sRANKL, OPG and sRANKL/OPG ratio included 259 healthy children aged 1 to 20 years [5]. The authors noted significant associations between sRANKL and categorized values for age, Tanner stage, and BMI z-score. In addition, OPG values were inversely associated with standardized BMI. The comparison of this report with the present study is hampered, since only median and IQR, but no upper and lower limits (97.5th and 2.5th percentiles), are given in this study. In general, however, median and IQR for sRANKL/OPG appeared to be somewhat higher in the present study when compared to the 4 available age cohorts reported by Akhtar Ali et al. whereas median and IQR values for the sRANKL/OPG ratio were comparable. These discrepancies may be due, at least in part, to differences in cohort compositions and/or methodology. For example, Akhtar Ali et al. did not include infants and used very wide age ranges instead of continuous LMS percentiles, as well as a different assay, to assess OPG compared to the present study. Overall, the LMS percentiles for sRANKL, OPG and sRANKL/OPG ratio show a smoother variation with age and splitting between boys and girls, likely reflecting the physiological differences in bone modeling during puberty in boys compared to girls, when compared to the study of Akhtar Ali et al.

Wasilewska et al. investigated sRANKL and OPG values in a cohort of 70 healthy children [1]. They noted significantly higher median sRANKL values in boys compared to girls, irrespective of age, lower values in younger (age < 9 years) compared to older (> 9 years) children, while OPG levels were not associated with age, which is in contrast to the considerably larger-sized studies performed by Akhtar Ali et al. and us. Also in this study, the medians and standard deviations for sRANKL and OPG are somewhat lower compared with the present study, although the same assay for sRANKL was used in both studies. This could be due, at least in part, to the fact that sRANKL levels were undetectable in some patients and/or to the small number of participants included.

Serum sRANKL concentrations were significantly associated with OPG values, irrespective of sex, which supports the concept of strong interrelations within the sRANKL/RANKL/OPG system, which was noted in smaller-sized previous studies [1, 5, 6, 30]. In addition, sRANKL was positively associated with standardized serum phosphate and OPG was inversely associated with standardized urinary phosphate to creatinine ratio in both sexes, suggesting that both high sRANKL and low OPG levels stimulate bone resorption, thereby increasing serum phosphate levels and urinary phosphate excretion, respectively.

We identified an inverse correlation between OPG plasma concentrations and standardized values for body weight and BMI, which is in line with previous studies in healthy as well as obese children and adults [5, 7, 10, 11, 31]. Dimitri et al. investigated OPG plasma levels in healthy lean and obese children and noted that OPG levels were lowest in obese children with a prior fracture, suggesting increased bone resorption in relation to formation in obese children [7]. It has been proposed that obesity may be aggravated by a lack of physical activity, which results in low bone turnover and thus low OPG concentrations. Alternatively, obesity itself may promote osteoclast activity via secretion of adipokines like leptin, resulting in reduced OPG secretion by activation of osteoblast leptin receptors [7].

This study should be considered in the context of its limitations. Firstly, bone marker levels may differ in cohorts of different ethnic background. Due to the composition of the general population in Germany, predominantly Caucasian children were enrolled in HARP. This must be taken into account when using our reference values for children with other ethnic backgrounds. Secondly, RANKL and OPG act at the paracrine level. The determination of serum sRANKL and plasma OPG concentrations was performed using ELISA, which was satisfactory, concerning reproducibility and handling qualities. RANKL concentrations have to be differentiated into total RANKL and freely soluble RANKL. As in most other studies, free soluble RANKL levels were measured [5,6,7, 32]. Another study investigated the total RANKL levels, but specified that it is unknown whether the detected levels and activities of sRANKL are correlated to the membrane-bound protein [30]. Both free soluble and total RANKL levels may be inaccurate because of the lack of information on the tissue source of the measured RANKL concentrations and because of the uncertainty whether circulating RANKL levels represent overall levels or concentrations in specific regions of interest. Moreover, the stability of RANKL and its diurnal fluctuation were not evaluated and it is unclear whether there is an optimal point for sample collection [2]. OPG is present as a free and bound form as RANKL/OPG complexes. The ELISA kit used detects all forms of circulating OPG [30]. Thirdly, bone mass accrual can persist for up to seven years after peak height growth velocity [33]. Thus, the age range used in the present study of 0.1 to 18 years may not be sufficient to represent the entire age-related dynamic of these parameters. Fourthly, we did not evaluate the impact of combined oral contraceptives in female adolescents as they were shown to interact with growth hormone and gonadal steroid hormones [34]. Fifthly, we did not assess Tanner stages in this cross-sectional study and therefore, we could not evaluate the impact of adrenarche and pubarche on the presented reference values in our population.

In conclusion, here we present LMS-based continuous pediatric reference percentiles for sRANKL, OPG and sRANKL/OPG ratio derived from the HARP cohort, that allow calculation of standardized patient z-scores to assess bone modeling in children and adolescents in clinical practice and studies. The observed associations between sRANKL, OPG, and the sRANKL/OPG ratio with age, sex, anthropometric and mineral metabolism parameters underscore the close relationship between bone modeling, growth and maturation in children.