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Reference Values for Insulin-Like Growth Factor-Binding Protein-3 (IGFBP-3) and the Ratio of Insulin-Like Growth Factor-I to IGFBP-3 throughout Childhood and Adolescence

Göteborg Pediatric Growth Research Center (C.L., L.G., S.R., K.A.W.), Institute for the Health of Women and Children, Department of Clinical Nutrition (L.H.), The Sahlgrenska Academy at Göteborg University, and Department of Statistics (E.A.), University of Göteborg, S-416 85 Göteborg, Sweden; and University Children’s Hospital (W.F.B.), 35392 Giessen, Germany

Address all correspondence and requests for reprints to: Chatarina Löfqvist, The Sahlgrenska Academy at Göteborg University, Institute for the Health of Women and Children, Göteborg Pediatric Growth Research Center, The Queen Silvia Children’s Hospital, S-416 85 Göteborg, Sweden. E-mail: chatarina.lofqvist{at}vgregion.se.

	Abstract

Top Abstract Introduction Subjects and Methods Results Discussion References

 
To facilitate the diagnosis of GH deficiency and monitor GH therapy, we constructed two reference models to allow comparison of serum IGF binding protein (IGFBP)-3 concentrations and IGF-I to IGFBP-3 ratios among children throughout childhood and adolescence. This report presents equations for determining the SD score of IGFBP-3 and IGF-I to IGFBP-3 measurements for individual patients. The data set contains serum values from 468 healthy children and adolescents (232 males, 236 females; ages 1.1–18.3 yr) whose height, weight, and body mass index were within ± 3 SD of means. Puberty was classified according to breast development (B) and testicular volume into pre-, early, mid-, and late puberty. The values of IGFBP-3 and IGF-I to IGFBP-3 ratios were log transformed, and multiple linear regression analysis was used to identify models for converting serum concentrations into SD scores. The models include the variables of age, gender, and puberty and take into account the interactions among these variables. The best linear models explain 42% of the variation in serum IGFBP-3 concentrations and 50% of the variation in serum IGF-I to IGFBP-3 concentrations.

The relationship between age and log(IGFBP-3) was positive for boys in pre-, early, and midpuberty. In late puberty, values were higher than earlier in puberty, and there was a negative relationship with age. For girls the relationship between age and log(IGFBP-3) also was positive in pre- and early puberty, with larger effect for girls older than 8 yr. Values for girls in midpuberty were relatively constant, and in late puberty values were higher than earlier in puberty, and there was a negative relationship with age.

The relationship between age and log(IGF-I to IGFBP-3 ratio) was positive for boys in pre-, early, and early midpuberty (volume = 9–14 ml). In late midpuberty (volume = 15–19 ml), the relationship between age and IGF-I to IGFBP-3 ratio was negative. In late puberty, values were relatively constant and higher than earlier in puberty. For girls in prepuberty, the relationship with age was positive, with a larger effect in girls older than 8 yr. In early puberty, the girls’ values were relatively constant. In early midpuberty (B = 3), log(IGF-I to IGFBP-3 ratio) values were higher for girls than boys of the same age. In late midpuberty (B = 4), the relationship with age was negative, and in late puberty values were relatively constant and higher than earlier in puberty.

	Introduction

Top Abstract Introduction Subjects and Methods Results Discussion References

 
THE CLINICAL USE of IGF-I and IGF binding protein (IGFBP)-3 measurements in children has focused primarily on diagnosing GH deficiency (GHD) and monitoring GH therapy. It has been reported that maximum GH levels in serum reached during provocative testing correlate with IGF-I SD scores (1, 2). Although measurements of IGF-I are useful for diagnosis and follow-up of patients with acromegaly (3), there is controversy about the sensitivity and specificity of IGF-I and of IGFBP-3 in the diagnosis of GHD in children (4, 5). Because the liver is the principal source of IGF-I and IGFBP-3 in the circulation (6) and hepatic production of IGF-I is influenced by nutritional factors (7), it is likely that decrements in IGF-I expected with GHD are modified by nutritional status. Other factors also may produce variations of IGF-I and IGFBP-3 independent of GHD, as exemplified by the wide variation of concentrations of these peptides among healthy children (8). Moreover, a polymorphism in the IGFBP-3 promoter alters serum IGFBP-3 concentrations (9), which leads to differences in absolute IGF-I and IGFBP-3 concentrations. To differentiate among pathologies of the GH-IGF-I-axis associated with growth disorders, there is a need to measure both IGF-I and IGFBP-3 and consider their ratio (10, 11).

Numerous reports (12, 13, 14, 15, 16, 17, 18) indicate that serum concentrations of IGF-I and IGFBP-3 increase through childhood. Also, puberty produces significant increases in IGFBP-3 and IGF-I (19, 20, 21, 22, 23, 24, 25), possibly as a result of increased GH secretion mediated by sex steroids (26, 27, 28, 29, 30).

The objective of our study was to develop a childhood and adolescent model for converting serum concentrations of IGFBP-3 and IGF-I to IGFBP-3 ratio to SD scores. We set out to develop a model that would explain a large part of the variation in IGFBP-3 and IGF-I to IGFBP-3 ratio, based on the variables that are known to have a significant effect on IGF-I concentrations. The variables selected were those shown to affect IGF-I concentration in a preliminary exploratory study and a study reported previously (19).

	Subjects and Methods

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Subjects

The cross-sectional data used for estimating and validating the reference model were obtained from 468 children (236 girls, 232 boys) from a cohort of 969 serum samples (Table 1). The aim was to construct a reference model for a normal population. Therefore, only children with height and weight within ± 3 SD of the population mean were included (31).

The data used consist of children involved in three different studies, denoted here as groups A, B, and C.

Group A. The group consisted of subjects 1–18 yr of age (n = 176), mainly relatives or friends of employees at our research center. Some were siblings of children with short stature or children of normal height and growth seen in pediatric endocrine outpatient clinics and subsequently regarded as healthy.

Group B. This group consisted of subjects 8–13 yr of age (n = 80), children from a single primary school who had participated in a study to determine the mean intraindividual monthly coefficient of variation (CV) of serum IGF-I concentrations (8).

Group C. The group consisted of subjects 15–18 yr of age (n = 212), children from several schools in Göteborg who had participated in a follow-up assessment of a study of iron supplementation in flour.

To avoid bias in the reference model, each child was required to have the same number of measurements. We used one measurement per subject because over 40% of the children had only one measurement. In a preliminary analysis, we determined whether any systematic differences in either IGFBP-3 or IGF-I to IGFBP-3 ratio could be detected between the children with one measurement and those with several measurements. No such difference was observed (data not shown).

When data from several studies are combined, i.e. groups A, B, and C, the results sometimes produce biased estimates. Therefore, tests were performed to uncover systematic differences among groups. No evidence of such deviations was found (data not shown).

A preliminary exploratory study was performed to ascertain the optimal variables that might be related to IGFBP-3 and the ratio IGF-I to IGFBP-3. One aim for our model was that the explanatory variables, among them puberty, should have a significant effect. In the preliminary study, the children were distributed in several ways. We began by using Tanner stages and found that this did not produce models with significant effect, whereas the use of breast stage for girls and testicular volume for boys did.

Because puberty is an important explanatory variable for the levels of IGF-I and for IGFBP-3 and the total number of measurements available within each pubertal stage differed considerably, we selected observations in such a way as to provide sufficient information for each pubertal stage. The selection process was as follows.

Girls. The pubertal stage having the smallest number of subjects was early puberty (24 girls). If these girls had any measurements in pre-, mid-, or late puberty, these measurements were omitted. The same procedure was thereafter applied to midpuberty; that is, those girls who had a measurement in midpuberty were omitted from pre- and late puberty. Thereafter this procedure was applied to the prepubertal stage.

Boys. The omission procedure described above was applied to data from the boys, in the following order for the pubertal stages: mid-, early, and late. If a child had several measurements in the chosen pubertal stage, the sample was chosen in a randomized manner.

Pubertal stage. Puberty was classified originally into five stages according to breast development and testicular volume: breast stage 1 and testis 1–3 ml; breast stage 2 and testis 4–8 ml; breast stage 3 and testis 9–14 ml; breast stage 4 and testis 15–19 ml; and breast stage 5 and testis 20 ml or more.

Because the IGFBP-3 values were similar among some pubertal stages, a robust model for IGFBP-3 was created by combining stages 1 and 2 for both girls and boys and also combining stages 3 and 4, according to Löfqvist et al. (19), thus resulting in three pubertal stages: pre-/early, mid, and late puberty. For the IGF-I to IGFBP-3 ratio model, the original five stages were kept for both boys and girls, thereby resulting in the stages pre, early, mid-early, mid-late, and late.

Cross-sectional validation group

More than 50% of the 468 children whose samples were used in the reference model had more than one measurement. For these children, one of their serum samples that was not used in the reference model was selected randomly (n = 244) and used to validate the reference model.

Hormone measurements

It is important for IGF-I assays to avoid reassociation of the analyte with IGFBPs. It was reported recently that sera of persons with diabetes contain IGFBP fragments that cannot be removed by physical separation methods and have the potential to interfere with the IGF-I assays, leading to falsely low results. This problem can be overcome by adding excess IGF-II.

Serum IGF-I and IGFBP-3 levels were measured using an IGFBP-blocked RIA with a large excess of IGF-II for determination of IGF-I and a specific RIA for IGFBP-3 (Mediagnost GmbH, Tübingen, Germany). The intraassay CVs for the IGF-I assay were 11.1, 7.2, and 7.4% at concentrations of 36, 204, and 545 µg/liter, respectively, and the interassay CVs were 13.5, 8.8, and 9.9%. For the IGFBP-3 assay, the intraassay CVs were 7.1, 7.3, and 7.9% at concentrations of 1800, 3790, and 5776 µg/liter, respectively, and the interassay CVs were 13.4, 10.5, and 14.1%.

Auxology

Heights and weights were transformed into SD scores for sex and age according to Swedish reference values (31).

Statistical evaluation

Multiple linear regression analysis was used to construct the reference models. The model fit in regression analysis is often evaluated using the coefficient of determination, R²; the value of R² is highly associated with the absolute value of the correlation between the observed and fitted values. R² measures the proportion of the variation in outcome that is explained by the combination of the explanatory variables in the model. In multiple regression analysis, an adjusted R² is used, with a correction for degrees of freedom. The model allows for different age effects for boys and girls within each pubertal stage. When selecting which variables to include in the reference models, the significance and variables found to be biologically relevant in our exploratory study and in earlier studies were taken into account. Only variables that are significant (gender, age, and pubertal stage) were included in the final model. Residual analysis was performed to check the assumptions of normality (nonskewness) and homoscedasticity, i.e. constant variance of the residuals. The statistical package SPSS (SPSS, Inc., Chicago, IL) was used for the analysis.

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
The analysis was performed after logarithmic transformation of the IGFBP-3 and IGF-I to IGFBP-3 ratio values (Fig. 1, A and B, upper and lower panels). A measure of fit in a multiple regression model is the coefficient of determination, R²; the closer R² is to 1.00, the better is the fit of the model. In multiple regression analysis, an adjusted R² is used. The adjusted R² was 0.42 for log(IGFBP-3) and 0.50 for the log(IGF-I to IGFBP-3 ratio). The P values for each of the explanatory variables showed that all the variables included had a significant relationship with the response variable [log(IGFBP-3) and log(IGF-I to IGFBP-3 ratio), respectively]. The estimated regression model for the normal reference for log(IGFBP-3) is presented in Table 2 and Fig. 2, and the corresponding results for log(IGF-I to IGFBP-3 ratio) are presented in Table 2 and Fig. 3.

View larger version (44K): [in this window] [in a new window]   FIG. 1. Cross-sectional measurements of IGFBP-3 (A, top panel) and the IGF-I to IGFBP-3 ratio (B, top panel) in 468 children (boys, , and girls, ) whose heights and weights were within ± 3 SD score of Swedish norms. The logarithmic transformation of IGFBP-3 (A, lower panel) and the IGF-I to IGFBP-3 ratio (B, lower panel) are shown with the mean values given at 2-yr intervals for boys () and girls (•).

View larger version (36K): [in this window] [in a new window]   FIG. 2. IGFBP-3. The reference model is illustrated using in-sample data, segregated by gender and pubertal stage, pre, early, mid, and late (girls, top panel, and boys, bottom panel). The five reference lines indicate regression line ± 1 SD and ± 2 SD.

View larger version (30K): [in this window] [in a new window]   FIG. 3. IGF-I/IGFBP-3 ratio. The reference model is illustrated using in-sample data, segregated by gender and pubertal stage: pre, early, mid-early, mid-late, and late (girls, top panel, and boys, bottom panel). The five reference lines indicate regression line ± 1 SD and ± 2 SD.

Interpretation of the coefficients in Table 2 log(IGF-I to IGFBP-3 ratio) for prepubertal boys reveals that the relationship between age and log(IGF-I to IGFBP-3 ratio) is positive, with the regression coefficient of 0.0181 (b_{Age * Pre} = 0.0181, P < 0.001). In early and mid-early puberty, the relationship between age and log(IGF-I to IGFBP-3 ratio) is positive (b_{Age * Early * Boy} = 0.0243, P < 0.001; b_{Age * Mid-early} = 0.0284, P < 0.001). In mid-late puberty, there is a negative relationship between age and log(IGF-I to IGFBP-3 ratio) with b_{Age * Mid-late} = –0.0301 (P < 0.005). Finally, in late puberty there is no age effect in boys. For prepubertal girls the relationship between age and log(IGF-I to IGFBP-3 ratio) is positive, with the regression coefficient of 0.0181, the same as for boys. For prepubertal girls above 8 yr of age, the relationship between age and log(IGF-I to IGFBP-3 ratio) is somewhat more pronounced (b_{Girl * Age * Pre (>8 yr)} = 0.0068, P < 0.001) than that observed in boys of the same age. In early puberty we observed a positive relationship between age and log(IGF-I to IGFBP-3 ratio) for boys, whereas no age effect was observed in girls. In mid-early puberty, the relationship between age and log(IGF-I to IGFBP-3 ratio) is similar for girls and boys, but the log(IGF-I to IGFBP-3 ratio) values are higher for girls. In mid-late puberty, there is a negative relationship between age and log(IGF-I to IGFBP-3 ratio), b_{Age * Mid-late} = –0.0301, the same as for boys. Finally, in girls in late puberty, there is a small negative relationship between age and log(IGF-I to IGFBP-3 ratio), b_{Girl * Age * Late} = –0.0036 (P < 0.005).

Estimated regression models

The regression models in Table 2 can be used to predict the value of log(IGFBP-3) and log(IGF-I to IGFBP-3 ratio), respectively, given age, sex, and pubertal status. When we estimated the two multiple regression models, the effect of all of the explanatory variables included was taken into account simultaneously. However, presentation and use is facilitated by presenting the regression equation for each subgroup of gender and puberty, which is done in Table 3. The reference ranges for each gender and pubertal stage are displayed in Figs. 2 and 3.

The following illustrates how to calculate SD score, using the reference models: a 9-yr-old prepubertal girl has an IGF-I of 219 µg/liter and an IGFBP-3 of 3560 µg/liter. Her SD scores are 0.6 and 0.9 for IGFBP-3 and IGF-I to IGFBP-3 ratio, respectively. These values are calculated using the following formula:

IGFBP-3 SD score

y is the logarithmic value of her IGFBP-3 measurement, i.e. y = log (3560) = 3.55145.

is calculated from the estimated regression equations: i.e. = 3.32 + 0.0173 _* 9 + 0.0027 _* 9, simplified; = 3.32 + 0.02 _* 9 = 3.50; and the SD score is (3.55145–3.50)/0.0878, where the mean SE value (0.0878) is used.

IGF-I to IGFBP-3 ratio SD score

y is the logarithmic value of her (IGF-I to IGFBP-3 ratio) measurement, i.e. y = log (219/3560) = –1.21101.

is calculated from the estimated regression equations, i.e. = –1.545 + 0.0181 _* 9 + 0.0068 _* 9, simplified; = –1.545 + 0.0249 _* 9 = –1.3209; and the SD score is [–1.21101 – (–1.3209)]/0.1176, where the mean SE value (0.1176) is used.

Validation of the model

Distribution of SD scores. The distribution of SD scores for log(IGFBP-3) for the reference group is compared in Fig. 4 with the distribution for the validation group. The graph shows that the reference model works very well also on an out-of-sample group, i.e. the distribution of SD scores is the same for the validation group as for the reference group, which was used in the construction of the model. The same holds for the log(IGF-I to IGFBP-3 ratio) (figure not shown).

View larger version (16K): [in this window] [in a new window]   FIG. 4. Histogram of the distribution of SD scores for IGFBP-3 for the reference group (n = 468, top panel) and the validation group (n = 244, bottom panel). The graphs show that the distribution of SD scores is the same for the validation group as for the reference group.

Evaluation of influence of body composition on the models

Influence of height and weight. We found that there is a strong positive linear association between age and height and that age and weight also have a positive association but in a nonlinear manner. We concluded that inclusion of height or weight would not increase the explanatory power of the models because the age variable already is included in each pubertal stage.

Influence of body mass index (BMI). There is an association between BMI and log(IGF-I), log(IGFBP-3), and log(IGF-I to IGFBP-3 ratio), respectively. Including BMI in the respective models showed that the BMI variable is significant but that the R² value is unchanged. There is no gender difference in BMI. The relation between log(IGF-I to IGFBP-3 ratio) and BMI is not the same over the age span we examined. We found that for children in pre- and early puberty (all children younger than 10 yr), there is a positive relationship between the ratio and BMI, whereas for older children and children in later puberty, there is no relationship (Fig. 5).

View larger version (31K): [in this window] [in a new window]   FIG. 5. The relationship between the log(IGF-I to IGFBP-3 ratio) and BMI. Filled squares, Children in pre- and early puberty; open circles, children in later puberty stages. The regression line shows the positive relationship for pre- and early and the constant relation for later puberty.

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

IGF-I and IGFBP-3 concentrations are low during early childhood, rise progressively through childhood, and increase during sexual maturation, with the typical pubertal peak around 12 and 14 yr of age for girls and boys, respectively. The increased GH secretion that is provoked by the increased production of gonadal steroids most likely initiates the pubertal increase (26, 27, 28, 29, 30). After puberty, IGF-I and IGFBP-3 concentrations decrease sharply, reaching a plateau in early adulthood.

Our results confirm previous studies (16, 17, 18, 19, 20, 21, 22) showing that the relationship between age and serum IGFBP-3 levels is positive in prepubertal and early pubertal children and that the relationship between age and IGFBP-3 concentrations is negative in late puberty. For children in puberty, no reference values have been available. With the exception of girls in Tanner stage 5, Juul et al. (21) did not report a prediction range for children in Tanner stages 2–5. Our study shows that in midpuberty the relationship between age and IGFBP-3 was different for girls than boys, with a positive age effect in boys and a constant level for girls. The IGFBP-3 values were higher for midpubertal girls, compared with boys. These gender differences agree with the observation that girls have peak height velocity and concurrent elevation of serum IGF-I earlier than boys (21).

No reference model has been available for the IGF-I to IGFBP-3 ratio for either prepubertal or pubertal children. Our results show that the relationship between age and serum IGF-I to IGFBP-3 levels is positive in prepubertal and early midpubertal children and that the relationship between age and IGF-I to IGFBP-3 concentrations is negative in late midpuberty and constant in late puberty. Our study shows that in early puberty the relationship between age and IGF-I to IGFBP-3 ratio was different for girls and boys, with a positive age effect in boys and a fairly constant effect in girls. The IGF-I to IGFBP-3 values were higher for midpubertal girls, compared with boys. These gender differences are in line with the observation that girls have peak height velocity and concurrent elevation of serum IGF-I earlier than boys (20). A girl who has reached final height and/or had menarche more than 2 yr previously should be classified as being in late puberty, even if she has not reached stage 5 of breast development.

In our study, one regression model fits all observations. The advantage of using one model is that it permits simultaneous estimation of all explanatory variables and uses all observations in the estimation process. Generally, the variance of an estimate decreases as the number of observations increases, thereby making it easier to obtain significance.

The reference model presented in this report was constructed from cross-sectional data. In a longitudinal study, it would be possible to estimate the variation between children as well as the variation within each child over time. In normal children, repeated measurements of IGF-I and IGFBP-3 have been shown to cluster around a level dependent on the size of the child, although the mean intraindividual monthly CV for IGF-I was found to be 16% (8). Constructing longitudinal reference models would require repeated blood sampling from the same healthy children over a prolonged interval, for as long as 20 yr.

The advantage of this type of modeling is that it produces robust reference ranges for boys and girls for each pubertal stage. There are also some benefits not available previously. These include reference ranges for each pubertal stage for both boys and girls and illustrates that there is a gender difference within each pubertal stage for both IGFBP-3 and IGF-I to IGFBP-3 ratio. The results of the study provide a tool to optimize the evaluation of IGF-I and IGFBP-3 in the diagnosis of GH insufficiency and follow-up of patients receiving GH during treatment.

	Acknowledgments

 
The authors wish to extend their appreciation to all the children who volunteered, to Lisbeth Larsson for her help with the IGF-I measurements, and to the staff at ward 335.

	Footnotes

 
The Swedish Research Council, The Swedish Foundation for Health Care Sciences and Allergy Research, and The Medical Faculty at Göteborg University supported the study.

First Published Online December 14, 2004

Abbreviations: BMI, Body mass index; CV, coefficient of variation; GHD, GH deficiency; IGFBP, IGF binding protein.

Received May 11, 2004.

Accepted December 2, 2004.

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