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BACKGROUND The QEPS-growth-model, developed and validated in GrowUp-Gothenburg cohorts, used for developing growth references and investigating healthy/pathological growth, lacks external validation from other longitudinal cohorts of healthy individuals. AIM To investigate if the QEPS-model can fit the longitudinal Edinburgh growth study of another design than GrowUp-Gothenburg cohorts, and to compare growth patterns in the individuals born in mid-1970s in North-Western Europe. METHODS Longitudinal growth data were obtained from the Edinburgh and the GrowUp1974Gothenburg cohorts. The QEPS-model was used to describe length/height from birth to adult height with confidence interval, and the multivariable regression model for estimating the contribution of the different QEPS-functions to adult height. RESULTS The QEPS-model fitted the Edinburgh cohort well, with high accuracy, and low confidence intervals indicating high precision. Despite 3 cm shorter stature (less QE-function growth) in Scottish children, the growth patterns of the cohorts were similar, especially for specific pubertal growth. The contribution to adult height from different QEPS functions was similar. CONCLUSION The QEPS-model is validated for the first time in a longitudinal study of healthy individuals of another design and found to fit with high accuracy and precision. The Scottish and Western-Swedish cohorts born in mid-1970s showed similar growth patterns for both sexes, especially pubertal growth. IMPACT For the first time, the QEPS height model was used and found to fit another longitudinal cohort of healthy individuals other than the Swedish longitudinal cohorts. With large numbers of individual measurements in each growth phase, the QEPS model calculates growth estimates with narrow confidence intervals (high precision) and high accuracy. The two different cohorts born in the mid-1970s from Scotland and Western Sweden have similar growth patterns, despite a 3 cm difference in adult height.

AIM To update the Swedish references for weight, weight-for-height and body mass index (BMI) considering the secular trend for height but not including that for weight. METHODS Longitudinal measures of height and weight were obtained (0-18 years) from 1418 (698 girls) healthy children from the GrowUp 1990 Gothenburg cohort born at term to non-smoking mothers and Nordic parents. A total of 145 individuals with extreme BMI value vs GrowUp 1974 BMI SDS reference were excluded (0-2 years: ±4SDS, 2

Aim We aimed to develop up‐to‐date references with standard deviation scores (SDS) for prepubertal and total height. Methods Longitudinal length/height measures from 1572 healthy children (51.5% boys) born at term in 1989‐1991 to non‐smoking mothers and Nordic parents were obtained from the GrowUp 1990 Gothenburg cohort. A total height SDS reference from birth to adult height was constructed from Quadratic‐Exponential‐Pubertal‐Stop (QEPS) function estimated heights based on individual growth curves. A prepubertal height SDS reference, showing growth trajectory in the absence of puberty, was constructed using the QE functions. Results The total height reference showed taller prepubertal mean heights (for boys 1‐2 cm; for girls 0.5‐1.0 cm) with a narrower normal within ± 2SDS range vs the GrowUp 1974 Gothenburg reference. Adult height was increased by + 0.9 cm for women (168.6 cm) and by + 1.6 cm for men (182.0 cm). Height in children growing at −2SDS (the cut‐off used for referrals) differed up to 2 cm vs the GrowUp 1974 Gothenburg reference, 3 cm vs Swedish 1981 references and World Health Organisation (WHO) 0‐5 years standard, and 6‐8 cm vs the WHO 5‐19 years reference. Conclusion Up‐to‐date total and prepubertal height references offer promise of improved growth monitoring compared with the references used in Sweden today.

Background Growth references are traditionally constructed relative to chronological age, despite inter-individual variations in pubertal timing. A new type of height reference was recently developed allowing growth to be aligned based on onset of pubertal height growth. We here aim to develop a corresponding reference for pubertal weight. Methods To model QEPS-weight, 3595 subjects (1779 girls) from GrowUp1974Gothenburg and GrowUp1990Gothenburg were used. The QEPS-height-model was transformed to a corresponding QEPS-weight-model; thereafter, QEPS-weight was modified by an individual, constitutional weight-height-factor. Longitudinal weight and length/height measurements from 1418 individuals (698 girls) from GrowUp1990Gothenburg were then used to create weight references aligned for height at pubertal onset (the age at 5% of P-function growth, AgeP5). GrowUp1974Gothenburg subgroups based on pubertal timing, stature at pubertal onset, and childhood body composition were assessed using the references. Results References (median, SDS) for total weight (QEPS-functions), weight specific to puberty (P-function), and weight gain in the absence of specific pubertal growth (basic weight, QES-functions), allowing alignment of individual growth based on age at pubertal onset. For both sexes, basic weight was greater than average for late maturing, tall and high-BMI subgroups. The P-function-related weight was greater than average in short and lower than average in tall children, in those with high BMI, and in girls but not boys with low BMI. Conclusions New pubertal weight references allow individual variations in pubertal timing to be taken into consideration when evaluating growth. When used together with the comparable pubertal height reference, this will improve growth monitoring in clinical practice for identifying abnormal growth and serve as a valuable research tool providing insight into human growth.

Over the past 150 years, humans have become taller, and puberty has begun earlier. It is unclear if these changes are continuing in Sweden, and how longitudinal growth patterns are involved. We aimed to evaluate the underlying changes in growth patterns from birth to adulthood by QEPS estimates in two Swedish cohorts born in 1974 and 1990. Growth characteristics of the longitudinal 1974 and 1990-birth cohorts (n = 4181) were compared using the QEPS model together with adult heights. There was more rapid fetal/infancy growth in girls/boys born in 1990 compared to 1974, as shown by a faster Etimescale and they were heavier at birth. The laterborn were taller also in childhood as shown by a higher Q-function. Girls born in 1990 had earlier and more pronounced growth during puberty than girls born in 1974. Individuals in the 1990 cohort attained greater adult heights than those in the 1974 cohort; 6 mm taller for females and 10 mm for males. A positive change in adult height was attributed to more growth during childhood in both sexes and during puberty for girls. The QEPS model proved to be effective detecting small changes of growth patterns, between two longitudinal growth cohorts born only 16 years apart.

Computerized mathematical models describing absolute and relative individual growth during puberty in both cm and standard deviation (SD)-scores are lacking. The present study aimed to fill this gap, by applying the QEPS-model that delineates mathematically the specific pubertal functions of the total growth curve. Study population used was the individual growth curves of the longitudinally followed cohort GrowUp1974 Gothenburg (n = 2280). The QEPS-model describes total height as (T)otal-function: a combination of four shape-invariant growth functions, modified by time-scale and height-scale parameters: a (Q)uadratic-function for the continuous growth from fetal life to adulthood; a negative (E)xponential-function adds the rapid, declining fetal/infancy growth; a (P)ubertal-function the specific pubertal growth spurt; a (S)top-function the declining growth until adult height. A constructed variable, MathSelect, was developed for assessing data-quality. CIs and SD-scores for growth estimates were calculated for each individual. QEPS-model estimates used for pubertal growth; from the T-function: onset of puberty as minimal height velocity (AgeT ONSET ); mid-puberty as peak height velocity (AgeT PHV ); end of puberty as height velocity decreased to 1 cm/year (AgeT END ); duration of different intervals and gain (AgeT ONSET–END and Tpubgain); from the P-function: onset of puberty, estimated as growth at 1% or 5% (AgeP1 , AgeP5); mid-puberty as 50% (AgeP50) and PHV (AgeP PHV ); end of pubertal growth at 95 or 99% (AgeP95, AgeP99); duration of different intervals and pubertal gain (Ppubgain; P max ); from the QES-function: gain (QESpubgain) . Application of these mathematical estimates for onset, middle and end of puberty of P-function, QES-function, and T-function during puberty showed: the later the onset of puberty, the greater the adult height; pubertal gain due to the P-function growth was independent of age at onset of puberty; boys had higher total gain during puberty due to P-function growth than to QES-function growth; for girls it was reversed. QEPS is the first growth model to provide individualized estimates of both the specific pubertal growth function and the total growth during puberty, with accompanying SD-scores and Cis for each individual. These QEPS-derived estimates enable more in-depth analysis of different aspects of pubertal growth than previously possible.

Childhood BMI may influence subsequent growth in height as well as the timing of puberty. The aim of the present study was to investigate associations between BMI in childhood and subsequent height gain/pubertal growth. Longitudinal growth data were used (GrowUp1990Gothenburg cohort, n = 1,901). The QEPS growth-model was used to characterize height gain in relation to the highest BMISDS value between 3.5 and 8 y of age. Children were defined as overweight/obese (OwOb) or normal weight/underweight (NwUw), using the 2012 International Obesity Task Force criteria. A negative association between childhood BMISDS and pubertal height gain was observed. Already at birth, OwOb children were heavier than NwUw children, and had a greater height velocity during childhood. Onset of puberty was 3.5/3.0 mo earlier in OwOb girls/boys, and they had 2.3/3.1 cm less pubertal height gain from the QEPS-models specific P-function than NwUw children. Adult height was not related to childhood BMI. We found that pubertal height gain was inversely related to peak BMI in childhood. Higher childhood BMISDS was associated with more growth before onset of puberty, earlier puberty, and less pubertal height gain, resulting in similar adult heights for OwOb and NwUw children.

Context Few studies have evaluated the metabolic outcomes of growth hormone (GH) treatment in idiopathic short stature (ISS). Moreover, children with ISS appear to need higher GH doses than childr ...

The aim of the study was to develop and validate models that could predict the growth responses to GH therapy of individual children. Models for prediction of the initial one and 2-y growth response were constructed from a cohort of 269 prepubertal children (Model group) with isolated GH deficiency or idiopathic short stature, using a nonlinear multivariate data fitting technique. Five sets of clinical information were used. The "Basic model" was created using auxological data from the year before the start of GH treatment and parental heights. In addition to Basic model data, the other four models included growth data from the first 2 y of life, or IGF-I, or GH secretion estimated during a provocation test (AITT) or a spontaneous GH secretion profile. The performance of the models was validated by calculating the differences between predicted and observed growth responses in 149 new GH treated children (Validation group) who fulfilled the inclusion criteria used in the original cohort. The SD of these differences (SD(res)) in the validation group was compared with the SD(res) for the model group. For the 1st y, the SD(res) for the Basic model was 0.28 SDscores. The lowest SD(res) (0.19 SDscores), giving the most narrow prediction interval, was achieved adding the 24h GH profile and data on growth from the first 2 y of life to the Basic model. The models presented permit estimation of GH responsiveness in children over a broad range in GH secretion, and with an accuracy of the models substantially better than when using maximal GH response during an provocation test. The predicted individual growth response, calculated using a computer program, can serve as a guide for evidence-based decisions when selecting children to GH treatment.

BACKGROUND: In addition to stimulating linear growth in children, growth hormone (GH) influences metabolism and body composition. These effects should be considered when individualizing GH treatment as dose-dependent changes in metabolic markers have been reported. Hypothesis: There are different dose-dependent thresholds for metabolic effects in response to GH treatment. METHOD: A randomized, prospective, multicentre trial TRN 98-0198-003 was performed for a 2-year catch-up growth period, with two treatment regimens (a) individualized GH dose including six different dose groups ranging from 17--100 mug/kg/day (n=87) and (b) fixed GH dose of 43 mug/kg/day (n=41). The individualized GH dose group was used for finding dose--response effects, where the effective GH dose (ED 50%) required to achieve 50% Delta effect was calculated with piecewise linear regressions. RESULTS: Different thresholds for the GH dose were found for the metabolic effects. The GH dose to achieve half of a given effect (ED 50%, with 90% confidence interval) was calculated as 33(+/-24.4) mug/kg/day for [increment] left ventricular diastolic diameter (cm), 39(+/-24.5) mug/kg/day for [increment] alkaline phosphatase (mukat/L), 47(+/-43.5) mug/kg/day for [increment] lean soft tissue (SDS), 48(+/-35.7) mug/kg/day for [increment] insulin (mU/L), 51(+/-47.6) mug/kg/day for [increment] height (SDS), and 57(+/-52.7) mug/kg/day for [increment] insulin-like growth factor I (IGF-I) SDS. Even though lipolysis was seen in all subjects, there was no dose--response effect for Delta fat mass (SDS) or Delta leptin ng/ml in the dose range studied. None of the metabolic effects presented here were related to the dose selection procedure in the trial. CONCLUSIONS: Dose-dependent thresholds were observed for different GH effects, with cardiac tissue being the most responsive and level of IGF-I the least responsive. The level of insulin was more responsive than that of IGF-I, with the threshold effect for height in the interval between.

This paper examined the effects of the combined product,Citrus e fructibus/Cydonia e fructibus(Citrus/Cydonia; Citrus and Cydonia: each 0.01 g/mL), and separate products of Citrus (0.01 g/mL) and Cydonia (0.01 g/mL) on the immunological pathways involved in seasonal allergic rhinitis (SAR). Peripheral blood mononuclear cells (PBMCs) from five healthy and five grass pollen-allergic donors were isolated and analyzedin vitroafter polyclonal and allergen-specific stimulation of T cells in the presence of the three extracts. The analyses demonstrated acceptable cell survival with no signs of toxicity. Citrus mainly had a selective effect on reducing allergen-specific chronic inflammatory (TNF-α; Citrus compared to Cydonia and Citrus/Cydonia: −87.4 (P<0.001) and −68.0 (P<0.05), resp.) and Th2 pathway activity (IL-5; Citrus compared to Cydonia: −217.8 (P<0.01); while, both Cydonia and Citrus/Cydonia mainly affected the induction of the allergen-specific Th1 pathway (IFN-γ; Cydonia and Citrus/Cydonia compared to Citrus: 3.8 (P<0.01) and 3.0 (P<0.01), resp.). Citrus and Cydonia demonstrated different working mechanisms in the treatment of SAR and the combination product did not demonstrate larger effects than the separate preparations. Further effectiveness and efficacy studies comparing the effects of the products on SARin vivoare indicated.

Background. Clinical experiences in vitro and clinical studies have demonstrated the curative potency and safety of Citrus/Cydonia compositum in seasonal allergic rhinitis treatment. Objectives. To compare the efficacy and safety of two routes of administration (nasal spray versus subcutaneous injections). Methodology: Design. a national, randomised, comparative clinical trial with two parallel groups. Participants. 23 patients fulfilled the study requirements. Intervention. after a one- or two-week wash-out period, 23 patients were randomized, to a 6-week treatment period. Outcomes. immunological and symptom severity changes and safety. Immunologic outcome assessments were blinded to group assignment. 23 patients were randomized and from 22/23 patients (11 in each group) blood samples were analyzed before and after treatment. Conclusion. Both routes of administration demonstrate immunological and clinical effects, with larger inflammatory and innate immunological effects of the nasal spray route and larger allergen-specific clinical effects of the subcutaneous route, and are safe.

Background Pretreatment auxological variables, such as birth size and parental heights, are important predictors of the growth response to GH treatment. For children with missing pretreatment data, published prediction models cannot be used. The objective was to construct and validate a prediction model for children with missing background data based on the observed first-year growth response to GH. The accuracy and reliability of the model should be comparable with our previously published prediction model relying on pretreatment data. The design used was mathematical curve fitting on observed growth response data from children treated with a GH dose of 33 μg/kg/d. Methods Growth response data from 162 prepubertal children born at term were used to construct the model; the group comprised of 19% girls, 80% GH-deficient and 23% born SGA. For validation, data from 205 other children fulfilling the same inclusion and treatment criteria as the model group were used. The model was also tested on data from children born prematurely, children from other continents and children receiving a GH dose of 67 μg/kg/d. Results The GH response curve was similar for all children, but with an individual amplitude. The curve SD score depends on an individual factor combining the effect of dose and growth, the 'Response Score', and time on treatment, making prediction possible when the first-year growth response is known. The prediction interval (± 2 SDres) was ± 0.34 SDS for the second treatment year growth response, corresponding to ± 1.2 cm for a 3-year-old child and ± 1.8 cm for a 7-year-old child. For the 1–4-year prediction, the SDres was 0.13 SDS/year and for the 1–7-year prediction it was 0.57 SDS (i.e. < 0.1 SDS/year). Conclusion The model based on the observed first-year growth response on GH is valid worldwide for the prediction of up to 7 years of prepubertal growth in children with GHD/ISS, born AGA/SGA and born preterm/term, and can be used as an aid in medical decision making.

Background Mathematical models can be used to predict individual growth responses to growth hormone (GH) therapy. The aim of this study was to construct and validate high-precision models to predict the growth response to GH treatment of short children, independent of their GH status, birth size and gestational age. As the GH doses are included, these models can be used to individualize treatment. Methods Growth data from 415 short prepubertal children were used to construct models for predicting the growth response during the first years of GH therapy. The performance of the models was validated with data from a separate cohort of 112 children using the same inclusion criteria. Results Using only auxological data, the model had a standard error of the residuals (SDres), of 0.23 SDS. The model was improved when endocrine data (GHmax profile, IGF-I and leptin) collected before starting GH treatment were included. Inclusion of these data resulted in a decrease of the SDres to 0.15 SDS (corresponding to 1.1 cm in a 3-year-old child and 1.6 cm in a 7-year old). Validation of these models with a separate cohort, showed similar SDres for both types of models. Preterm children were not included in the Model group, but predictions for this group were within the expected range. Conclusion These prediction models can with high accuracy be used to identify short children who will benefit from GH treatment. They are clinically useful as they are constructed using data from short children with a broad range of GH secretory status, birth size and gestational age.

Background The broad range in growth observed in short prepubertal children receiving the same growth hormone (GH) dose is due to individual variation in GH responsiveness. This study used a pharmaco-proteomic approach in order to identify novel biomarkers that discriminate between short non-GH-deficient (GHD) children who show a good or poor growth response to GH treatment. A group of 32 prepubertal children with idiopathic short stature (ISS) were included in the study. Children were classified on the basis of their first year growth velocity as either good (high responders, n = 13; range, 0.9–1.3 standard deviation score (SDS) or poor (low responders, n = 19; range, 0.3–0.5 SDS) responders to GH treatment (33 μg/kg daily). Serum protein expression profiles before, and after 1 year of GH treatment, were analyzed on a weak cationic exchange array (CM10) using surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF-MS). Results Changes in the intensity of two protein peaks (13.788 kDa and 17.139 kD) during the study period allowed the correct classification of 82% of children as high and low responders, respectively. The 13.788 kD peak, transthyretin, decreased in the high-responder group and increased in the low-responder group during 1 year of GH treatment, whereas the 17.139 kDa peak, apolipoprotein A-II (Apo A-II) decreased in the high-responder group and remained unchanged in the low-responder group. These peaks were identified by the consistency of peak pattern in the spectra, serum depletion experiments using specific antibodies and mass spectrometry. Conclusion Our results suggest that transthyretin and apolipoprotein A-II may have a role in GH sensitivity and could be used as markers to predict which short prepubertal children with ISS will show a good or poor response to GH treatment.

Background The broad range in growth observed in response to growth hormone (GH) treatment is mainly caused by individual variations in both GH secretion and GH sensitivity. Individual GH responsiveness can be estimated using evidence-based models that predict the response to GH treatment; however, these models can be improved. High-throughput proteomics techniques can be used to identify proteins that may potentially be used as variables in such models in order to improve their predictive ability. Previously we have reported that proteomic analyses can identify biomarkers that discriminate between short prepubertal children with idiopathic short stature (ISS) who show good or poor growth in response to GH treatment. In this study we used a pharmaco-proteomic approach to identify novel factors that correlate with the growth response to GH treatment in prepubertal children who are short due to GH deficiency or ISS. The study included 128 short prepubertal children receiving GH treatment, of whom 39 were GH-deficient and 89 had ISS. Serum protein expression profiles at study start and after 1 year of GH treatment were analyzed using SELDI-TOF. Cross-validated regression and random permutation analyses were performed to identify significant correlations between protein expression patterns and the 2-year growth response to GH treatment. Results At start of treatment we identified a combination of seven protein peaks that correlated with the 2-year growth response in the GH-deficient group (R2 = 0.73). After 1 year of treatment, a combination of four peaks in the GH-deficient group (R2 = 0.64), eight peaks in the ISS group R2 = 0.47) and eight peaks in the total study group correlated with the 2-year growth response R2 = 0.38). The peaks identified corresponded to apolipoproteins A-I, A-II, C-I, C-III, transthyretin and serum amyloid A 4, which are all part of the high-density lipoprotein. Conclusion Using a proteomic approach we identified biomarkers related to the lipoprotein profile that could be used to predict growth response to GH treatment in prepubertal children who are short as a result of GH-deficiency or who have ISS. These results support our previous findings that apolipoproteins and transthyretin may have a role in GH sensitivity.