The present cross-sectional observational study was conducted on 80 healthy subjects of North-Indian origin, with the aim to evaluate the salivary level of biomarkers namely salivary Insulin Like growth factor − 1 (sIGF-1) and salivary Alkaline Phosphatase (sALP) as the indicators of circumpubertal stages in growing individuals for the assessment of skeletal maturation as well as to find associations with chronological age, mandibular base length and maxillary base length. The variables were also studied in males and females. These subjects ought to be healthy individuals, free from any systemic disorders or pregnancy. Clinically healthy subjects who fulfilled the inclusion and exclusion criteria as to rule out any confounding variable. Those undergoing treatment were excluded to avoid confounding bias because variation and fluctuation in levels of markers are predominantly present during orthodontic treatment which could result in false quantifications of proposed parameters. This way standardization of sample collection was achieved. Assessment of cervical vertebral maturation stages using method described by Hassel and Farman offers convenient assessment by looking at the shape and concavities in inferior body of CV2, CV3, and CV4 observed in lateral cephalogram.
Saliva has been preferred as a sample because it mirrors serum levels and can be used as a possible tool for calibration of skeletal age. It is easy to collect, present in sufficient quantities and far less invasive than GCF and serum [14, 18, 19, 20, 21].
Correlation has been observed between growth spurt and biomarker levels peaking at the same time. Radiation exposure can be avoided when biomarkers are used and they are involved directly in bone growth and remodelling [22, 23]. The proposed biomarkers were quantified by Enzyme Linked Immunosorbent Assay. This immunological test is highly sensitive and is considered as gold standard of immunoassays. [24].
The correlation between chronological age and cervical vertebrae skeletal maturation has been established [25]. Significant difference is observed between chronological age and skeletal age assessed using CVMI [26]. Insulin like growth factor-1 (IGF-1) that controls the effects of growth biomarkers and was initially identified to be a liver derived “sulphation factors” [27]. IGF-1 mediates growth hormone function and plays a prime role in systemic and local regulation of both prenatal and postnatal longitudinal bone growth. Liver, bone and intestine to some extents are the main sources of sALP in serum (> 80%). It is disputed that sIGF-1 has an effect on bone therefore in our study including sALP seemed appropriate to advance present knowledge [28]. ALP is more bone specific and can also withstand multiple freeze-thaw cycles and prolonged frozen storage [29]. Studies have provided evidence that mandibular growth continues even after skeletal maturity observed upon radiographs [16]. Similar evaluation of maxillary growth and its association across CVMI stages is taken up in this study.
sIGF-1 activity is at peak at stage 3 which is showing a pattern similar to previous studies [32, 33, 43, 35]. In our study, [Table 1 & Fig. 3A] females had higher mean sIGF-1 values than males at stage 3 (297.92 ± 136.88 pg/ml and 245.41 ± 135.63 pg/ml respectively) which is found to be consistent with previous study [34]. A high standard deviation was observed in our study at stage 3. This could be a reflection of great individual variation with regard to skeletal maturation and similar has been concluded by other authors [36, 37], and as well as found in previous studies [6, 9]. It is also observed that the increase in mean value of sIGF-1 in males in stage 6 could be a marker of residual mandibular growth as well as their prolonged growth spurt [6]. Here sexual dimorphism is well appreciated as well. The mean value of sIGF-1 in both subgroups is found to increase during the pubertal growth phase and similar was reported by previous studies [9, 38, 39].
The mean salivary sALP [Table 1 & Fig. 3B] was found to be the highest at Stage 3 (2.96 ± 1.81 ng/ml) followed by stage 4 (2.08 ± 0.54 ng/ml) for Group A (Male) whereas in Group B (Female) the highest mean value was observed at stage 4, (2.33 ± 0.71 ng/ml) followed by stage 3 (2.09 ± 0.61ng/ml). This pattern is evident of peak concentration attained at pubertal phase and at the same time sexual dimorphism is observed. The pattern observed in Group B (Female) is in accordance with overall findings of previous studies [30]. The pattern observed with Group A (Male) is in accordance with previous studies [16]. The results of our study supported findings stating higher sALP activity in the pubertal phase of skeletal maturation as compared to pre-pubertal and post-pubertal phases, which was also found in previous studies [14, 16, 22, 40, 41, 42, 43, 44, 45]. There is insignificant difference in sALP levels between males and females in stage 3 and stage 4 demonstrated that no difference exists in sALP values at the threshold of pubertal growth spurt. Such a finding has been reported [16]. The mean values of sALP levels do not show statistically significant difference (p > 0.05) between pre-pubertal and pubertal phase which is consistent with previous studies [46].
Table 3 shows statistically significant difference in mean values of sIGF-1 among all the Stages. Our data shows the pattern that second highest overall mean value of sIGF-1 is observed at stage 4 and in stage 5 and stage 6 there is a drastic decline found similarly in other studies [9] and statistically significant with p value (0.003). Similar pattern was noted in other works as well [22, 30] with respect to GCF ALP .
The post-pubertal activity of sALP was found to be least followed by pre-pubertal similar to findings of previous study [16]. The mean values of Group A (Male) and Group B (Female) amongst CVM Stages are not found to be statistically significant (p > 0.05).
Association has been found using linear regression analysis with sALP dependant on chronological age in males but more studies are needed to confirm this [Table 4]. Out of the 6 multinomial models [Table 5], although CA + sALP + sIGF-1is the best model for CVMS prediction, the second best fit model CA + sALP will be more convenient for a clinician per se. Along with traditional techniques, skeletal assessment can be enhanced using new tools such as biomarkers. This study is consistent with previous works [30, 31].
sALP is found to be weakly correlated with mandibular length. A positive correlation is found between sALP and mandibular base length [Table 6] at stage 3, stage 4 and stage 5 consistent with previous studies [16]. Not much correlation was found with maxillary base length growth changes. There is negative correlation between mandibular base length and sIGF-1 in stage 4 with the correlation coefficient of -0.317 which is weakly correlated but in stage 3 and stage 5 there was no correlation observed which is consistent with previous studies [6]. Since no correlation observed between stage 3, stage 4 and stage 5 with sIGF-1 activity, such a finding is in accordance with previous study [28].
sALP is found to be moderately correlated to chronological age range. The present finding is consistent with previous studies [12, 15]. sIGF-1 is not found to be correlated with chronological age range [Table 7].
The findings are factual that recruitment of a specific population is a tedious task and a larger sample number is required while conducting further studies. Since sIGF-1 represents only one percent quantification than that of serum or blood, further studies could be conducted taking blood or serum as specimens and expect to find more correlations one can also include more number of biomarkers to find correlations which could hypothesize clinically relevant. Since saliva as a sample is non-invasive, the findings can be correlated with invasive analysis using blood as a sample.