Pharmacogenomics of insulin-like growth factor-I generation during GH treatment in children with GH deficiency or Turner syndrome

Gene Expression Signatures Predict First-Year Response to Somapacitan Treatment in Children With Growth Hormone Deficiency

CONTEXT

The pretreatment blood transcriptome predicts growth response to daily growth hormone (GH) therapy with high accuracy.

OBJECTIVE

Investigate response prediction using pretreatment transcriptome in children with GH deficiency (GHD) treated with once-weekly somapacitan, a novel long-acting GH.

METHODS

REAL4 is a randomized, multinational, open-label, active-controlled parallel group phase 3 trial, comprising a 52-week main phase and an ongoing 3-year safety extension (NCT03811535). A total of 128/200 treatment-naïve prepubertal children with GHD consented to baseline blood transcriptome profiling. They were randomized 2:1 to subcutaneous somapacitan (0.16 mg/kg/week) or daily GH (0.034 mg/kg/day). Differential RNA-seq analysis and machine learning were used to predict therapy response.

RESULTS

121/128 samples passed quality control. Children treated with somapacitan (n = 76) or daily GH (n = 45) were categorized based on fastest and slowest growing quartiles at week 52. Prediction of height velocity (HV; cm/year) was excellent for both treatments (out of bag [OOB] area under curve [AUC]: 0.98-0.99; validation AUC: 0.83-0.84), as was prediction of secondary markers of growth response: HV standard deviation score (SDS) (0.99-1.0; 0.75-0.78), change from baseline height SDS (ΔHSDS) (0.98-1.0; 0.61-0.75), and change from baseline insulin-like growth factor-I SDS (ΔIGF-I SDS) (0.96-1.0; 0.85-0.88). Genes previously identified as predictive of GH therapy response were consistently better at predicting the fastest growers in both treatments in this study (OOB AUC: 0.93-0.97) than the slowest (0.67-0.85).

CONCLUSION

Pretreatment transcriptome predicts first-year growth response in somapacitan-treated children with GHD. A common set of genes can predict the treatment response to both once-weekly somapacitan and conventional daily GH. This approach could potentially be developed into a clinically applicable pretreatment test to improve clinical management.

Molecular diagnosis is an important indicator for response to growth hormone therapy in children with short stature

BACKGROUND

Significant differences have been observed in the efficacy of recombinant human growth hormone (rhGH) treatment for short children. The present study aimed to identify the genetic etiology of short stature and to assess the role of molecular diagnosis in predicting responses to rhGH treatment.

METHODS

A total of 407 short children were included in the present study, 226 of whom received rhGH treatment. Whole-exome sequencing (WES) was conducted on short children to identify the underlying genetic etiology. Correlations between molecular diagnosis and the efficacy of rhGH treatment were examined.

RESULTS

Pathogenic or likely pathogenic mutations were identified in 86 of the 407 patients (21.1%), including 36 (41.9%) novel variants. Among the multiple pathways affecting short stature, genes involved in fundamental cellular processes (38.7%) play a larger role, especially the RAS-MAPK pathway. In general, patients without pathogenic mutations responded better to rhGH than those with mutations. Furthermore, patients with hormone signaling pathway mutations had a better response to rhGH, while those with paracrine factor mutations had a worse response to rhGH.

CONCLUSIONS

This study highlights the utility of WES in identifying genetic etiology in children with short stature. Identifying likely causal mutations is an important factor in predicting rhGH response.

Diagnosis of childhood and adolescent growth hormone deficiency using transcriptomic data

BACKGROUND

Gene expression (GE) data have shown promise as a novel tool to aid in the diagnosis of childhood growth hormone deficiency (GHD) when comparing GHD children to normal children. The aim of this study was to assess the utility of GE data in the diagnosis of GHD in childhood and adolescence using non-GHD short stature children as a control group.

METHODS

GE data was obtained from patients undergoing growth hormone stimulation testing. Data were taken for the 271 genes whose expression was utilized in our previous study. The synthetic minority oversampling technique was used to balance the dataset and a random forest algorithm applied to predict GHD status.

RESULTS

24 patients were recruited to the study and eight subsequently diagnosed with GHD. There were no significant differences in gender, age, auxology (height SDS, weight SDS, BMI SDS) or biochemistry (IGF-I SDS, IGFBP-3 SDS) between the GHD and non-GHD subjects. A random forest algorithm gave an AUC of 0.97 (95% CI 0.93 - 1.0) for the diagnosis of GHD.

CONCLUSION

This study demonstrates highly accurate diagnosis of childhood GHD using a combination of GE data and random forest analysis.

First Clinical Study on Long-Acting Growth Hormone Therapy in Children with Turner Sydrome

Study on long-acting growth hormone (LAGH) therapy in Turner syndrome (TS) is a 2-year retrospective study including patients diagnosed with TS from 2018-2021. Patients were divided into four groups: Group 1 to 4 were low dose (0.1 mg/kg/ w), high-dose (0.2 mg/kg/w) LAGH, daily GH (0.38 mg/kg/w), and untreated control. The efficacy and safety data were analyzed. Seventy-five TS cases with the age 7.9±2.9 years and the bone age 6.8±2.8 years were recruited. In year 1: The change of height standard deviation score (ΔHtSDS) and height velocity (HV) in Group 2 were comparable to Group 3, both two groups were higher than Group 1. ΔHtSDS and HV in all GH treatment group were higher than untreated group. IGF1 increased in all treatment groups, only 4 cases had IGF1>3 SD. In year 2: ΔHtSDS and HV in Group 2 and 3 were comparable. Five cases had IGF1>3 SD. Correlation analysis for LAGH efficacy at year 1 indicated that baseline variables correlated with ΔHtSDS include: GH dose, CA (chronological age), and bone age (BA). The HV was positively correlated with baseline GH dose, HtSDS, IGF-1SDS and negatively correlated with baseline CA, BA, and BMI. No GH-related serious adverse effects were observed. The high-dose LAGH treatment in TS patients is effective and safe as daily GH for 2 years. The favorable prognosis factors include sufficient GH dose and early treatment. IGF1 monitoring and weight control are important.

Gene expression signatures predict response to therapy with growth hormone

Recombinant human growth hormone (r-hGH) is used as a therapeutic agent for disorders of growth including growth hormone deficiency (GHD) and Turner syndrome (TS). Treatment is costly and current methods to model response are inexact. GHD (n = 71) and TS patients (n = 43) were recruited to study response to r-hGH over 5 years. Analysis was performed using 1219 genetic markers and baseline (pre-treatment) blood transcriptome. Random forest was used to determine predictive value of transcriptomic data associated with growth response. No genetic marker passed the stringency criteria for prediction. However, we identified an identical set of genes in both GHD and TS whose expression could be used to classify therapeutic response to r-hGH with a high accuracy (AUC > 0.9). Combining transcriptomic markers with clinical phenotype was shown to significantly reduce predictive error. This work could be translated into a single genomic test linked to a prediction algorithm to improve clinical management. Trial registration numbers: NCT00256126 and NCT00699855.

Pharmacogenomics applied to recombinant human growth hormone responses in children with short stature

We present current knowledge concerning the pharmacogenomics of growth hormone therapy in children with short stature. We consider the evidence now emerging for the polygenic nature of response to recombinant human growth hormone (r-hGH). These data are related predominantly to the use of transcriptomic data for prediction. The impact of the complex interactions of developmental phenotype over childhood on response to r-hGH are discussed. Finally, the issues that need to be addressed in order to develop a clinical test are described.

A Genome-Wide Pharmacogenetic Study of Growth Hormone Responsiveness

CONTEXT

Individual patients vary in their response to growth hormone (GH). No large-scale genome-wide studies have looked for genetic predictors of GH responsiveness.

OBJECTIVE

To identify genetic variants associated with GH responsiveness.

DESIGN

Genome-wide association study (GWAS).

SETTING

Cohorts from multiple academic centers and a clinical trial.

PATIENTS

A total of 614 individuals from 5 short stature cohorts receiving GH: 297 with idiopathic short stature, 276 with isolated GH deficiency, and 65 born small for gestational age.

INTERVENTION

Association of more than 2 million variants was tested.

MAIN OUTCOME MEASURES

Primary analysis: individual single nucleotide polymorphism (SNP) association with first-year change in height standard deviation scores. Secondary analyses: SNP associations in clinical subgroups adjusted for clinical variables; association of polygenic score calculated from 697 genome-wide significant height SNPs with GH responsiveness.

RESULTS

No common variant associations reached genome-wide significance in the primary analysis. The strongest suggestive signals were found near the B4GALT4 and TBCE genes. After meta-analysis including replication data, signals at several loci reached or retained genome-wide significance in secondary analyses, including variants near ST3GAL6. There was no significant association with variants previously reported to be associated with GH response nor with a polygenic predicted height score.

CONCLUSIONS

We performed the largest GWAS of GH responsiveness to date. We identified 2 loci with a suggestive effect on GH responsiveness in our primary analysis and several genome-wide significant associations in secondary analyses that require further replication. Our results are consistent with a polygenic component to GH responsiveness, likely distinct from the genetic regulators of adult height.

Transcriptomics and machine learning predict diagnosis and severity of growth hormone deficiency

BACKGROUND

The effect of gene expression data on diagnosis remains limited. Here, we show how diagnosis and classification of growth hormone deficiency (GHD) can be achieved from a single blood sample using a combination of transcriptomics and random forest analysis.

METHODS

Prepubertal treatment-naive children with GHD (n = 98) were enrolled from the PREDICT study, and controls (n = 26) were acquired from online data sets. Whole blood gene expression was correlated with peak growth hormone (GH) using rank regression and a random forest algorithm tested for prediction of the presence of GHD and in classification of GHD as severe (peak GH <4 μg/l) and nonsevere (peak ≥4 μg/l). Performance was assessed using area under the receiver operating characteristic curve (AUC-ROC).

RESULTS

Rank regression identified 347 probe sets in which gene expression correlated with peak GH concentrations (r = ± 0.28, P < 0.01). These 347 probe sets yielded an AUC-ROC of 0.95 for prediction of GHD status versus controls and an AUC-ROC of 0.93 for prediction of GHD severity.

CONCLUSION

This study demonstrates highly accurate diagnosis and disease classification for GHD using a combination of transcriptomics and random forest analysis.

TRIAL REGISTRATION

NCT00256126 and NCT00699855.

FUNDING

Merck and the National Institute for Health Research (CL-2012-06-005).

Validating genetic markers of response to recombinant human growth hormone in children with growth hormone deficiency and Turner syndrome: the PREDICT validation study

OBJECTIVE

Single-nucleotide polymorphisms (SNPs) associated with the response to recombinant human growth hormone (r-hGH) have previously been identified in growth hormone deficiency (GHD) and Turner syndrome (TS) children in the PREDICT long-term follow-up (LTFU) study (Nbib699855). Here, we describe the PREDICT validation (VAL) study (Nbib1419249), which aimed to confirm these genetic associations.

DESIGN AND METHODS

Children with GHD (n = 293) or TS (n = 132) were recruited retrospectively from 29 sites in nine countries. All children had completed 1 year of r-hGH therapy. 48 SNPs previously identified as associated with first year growth response to r-hGH were genotyped. Regression analysis was used to assess the association between genotype and growth response using clinical/auxological variables as covariates. Further analysis was undertaken using random forest classification.

RESULTS

The children were younger, and the growth response was higher in VAL study. Direct genotype analysis did not replicate what was found in the LTFU study. However, using exploratory regression models with covariates, a consistent relationship with growth response in both VAL and LTFU was shown for four genes - SOS1 and INPPL1 in GHD and ESR1 and PTPN1 in TS. The random forest analysis demonstrated that only clinical covariates were important in the prediction of growth response in mild GHD (>4 to <10 μg/L on GH stimulation test), however, in severe GHD (≤4 μg/L) several SNPs contributed (in IGF2, GRB10, FOS, IGFBP3 and GHRHR).

CONCLUSIONS

The PREDICT validation study supports, in an independent cohort, the association of four of 48 genetic markers with growth response to r-hGH treatment in both pre-pubertal GHD and TS children after controlling for clinical/auxological covariates. However, the contribution of these SNPs in a prediction model of first-year response is not sufficient for routine clinical use.

Network analysis and juvenile idiopathic arthritis (JIA): a new horizon for the understanding of disease pathogenesis and therapeutic target identification

Juvenile idiopathic arthritis (JIA) is a clinically diverse and genetically complex autoimmune disease. Currently, there is very limited understanding of the potential underlying mechanisms that result in the range of phenotypes which constitute JIA.The elucidation of the functional relevance of genetic associations with phenotypic traits is a fundamental problem that hampers the translation of genetic observations to plausible medical interventions. Genome wide association studies, and subsequent fine-mapping studies in JIA patients, have identified many genetic variants associated with disease. Such approaches rely on 'tag' single nucleotide polymorphisms (SNPs). The associated SNPs are rarely functional variants, so the extrapolation of genetic association data to the identification of biologically meaningful findings can be a protracted undertaking. Integrative genomics aims to bridge the gap between genotype and phenotype.Systems biology, principally through network analysis, is emerging as a valuable way to identify biological pathways of relevance to complex genetic diseases. This review aims to highlight recent findings in systems biology related to JIA in an attempt to assist in the understanding of JIA pathogenesis and therapeutic target identification.

GH deficiency status combined with GH receptor polymorphism affects response to GH in children

Meta-analysis has shown a modest improvement in first-year growth response to recombinant human GH (r-hGH) for carriers of the exon 3-deleted GH receptor (GHRd3) polymorphism but with significant interstudy variability. The associations between GHRd3 and growth response to r-hGH over 3 years in relation to severity of GH deficiency (GHD) were investigated in patients from 14 countries. Treatment-naïve pre-pubertal children with GHD were enrolled from the PREDICT studies (NCT00256126 and NCT00699855), categorized by peak GH level (peak GH) during provocation test: ≤4 μg/l (severe GHD; n=45) and >4 to <10 μg/l mild GHD; n=49) and genotyped for the GHRd3 polymorphism (full length (fl/fl, fl/d3, d3/d3). Gene expression (GE) profiles were characterized at baseline. Changes in growth (height (cm) and SDS) over 3 years were measured. There was a dichotomous influence of GHRd3 polymorphism on response to r-hGH, dependent on peak GH level. GH peak level (higher vs lower) and GHRd3 (fl/fl vs d3 carriers) combined status was associated with height change over 3 years (P<0.05). GHRd3 carriers with lower peak GH had lower growth than subjects with fl/fl (median difference after 3 years -3.3 cm; -0.3 SDS). Conversely, GHRd3 carriers with higher peak GH had better growth (+2.7 cm; +0.2 SDS). Similar patterns were observed for GH-dependent biomarkers. GE profiles were significantly different between the groups, indicating that the interaction between GH status and GHRd3 carriage can be identified at a transcriptomic level. This study demonstrates that responses to r-hGH depend on the interaction between GHD severity and GHRd3 carriage.

Effect of summer daylight exposure and genetic background on growth in growth hormone-deficient children

The response to growth hormone in humans is dependent on phenotypic, genetic and environmental factors. The present study in children with growth hormone deficiency (GHD) collected worldwide characterised gene–environment interactions on growth response to recombinant human growth hormone (r-hGH). Growth responses in children are linked to latitude, and we found that a correlate of latitude, summer daylight exposure (SDE), was a key environmental factor related to growth response to r-hGH. In turn growth response was determined by an interaction between both SDE and genes known to affect growth response to r-hGH. In addition, analysis of associated networks of gene expression implicated a role for circadian clock pathways and specifically the developmental transcription factor NANOG. This work provides the first observation of gene–environment interactions in children treated with r-hGH.

Effects of growth hormone therapeutic supplementation on hematopoietic stem/progenitor cells in children with growth hormone deficiency: focus on proliferation and differentiation capabilities

We investigated the direct effects of growth hormone (GH) replacement therapy (GH-RT) on hematopoiesis in children with GH deficiency (GHD) with the special emphasis on proliferation and cell cycle regulation. Peripheral blood (PB) was collected from sixty control individuals and forty GHD children before GH-RT and in 3rd and 6th month of GH-RT to measure hematological parameters and isolate CD34(+)-enriched hematopoietic progenitor cells (HPCs). Selected parameters of PB were analyzed by hematological analyzer. Moreover, collected HPCs were used to analyze GH receptor (GHR) and IGF1 expression, clonogenicity, and cell cycle activity. Finally, global gene expression profile of collected HPCs was analyzed using genome-wide RNA microarrays. GHD resulted in a decrease in several hematological parameters related to RBCs and significantly diminished clonogenicity of erythroid progenies. In contrast, GH-RT stimulated increases in clonogenic growth of erythroid lineage and RBC counts as well as significant up-regulation of cell cycle-propagating genes, including MAP2K1, cyclins D1/E1, PCNA, and IGF1. Likewise, GH-RT significantly modified GHR expression in isolated HPCs and augmented systemic IGF1 levels. Global gene expression analysis revealed significantly higher expression of genes associated with cell cycle, proliferation, and differentiation in HPCs from GH-treated subjects. (i) GH-RT significantly augments cell cycle progression in HPCs and increases clonogenicity of erythroid progenitors; (ii) GHR expression in HPCs is modulated by GH status; (iii) molecular mechanisms by which GH influences hematopoiesis might provide a basis for designing therapeutic interventions for hematological complications related to GHD.

Developmental variations in environmental influences including endocrine disruptors on pubertal timing and neuroendocrine control: Revision of human observations and mechanistic insight from rodents

Puberty presents remarkable individual differences in timing reaching over 5 years in humans. We put emphasis on the two edges of the age distribution of pubertal signs in humans and point to an extended distribution towards earliness for initial pubertal stages and towards lateness for final pubertal stages. Such distortion of distribution is a recent phenomenon. This suggests changing environmental influences including the possible role of nutrition, stress and endocrine disruptors. Our ability to assess neuroendocrine effects and mechanisms is very limited in humans. Using the rodent as a model, we examine the impact of environmental factors on the individual variations in pubertal timing and the possible underlying mechanisms. The capacity of environmental factors to shape functioning of the neuroendocrine system is thought to be maximal during fetal and early postnatal life and possibly less important when approaching the time of onset of puberty.

Sex, Sport, IGF-1 and the Community Effect in Height Hypothesis

We test the hypothesis that differences in social status between groups of people within a population may induce variation in insulin-like growth factor-1(IGF-1) levels and, by extension, growth in height. This is called the community effect in height hypothesis. The relationship between IGF-1, assessed via finger-prick dried blood spot, and elite level sport competition outcomes were analysed for a sample of 116 undergraduate men and women. There was a statistically significant difference between winners and losers of a competition. Winners, as a group, had higher average pre-game and post-game IGF-1 levels than losers. We proposed this type of difference as a proxy for social dominance. We found no evidence that winners increased in IGF-1 levels over losers or that members of the same team were more similar in IGF-1 levels than they were to players from other teams. These findings provide limited support toward the community effect in height hypothesis. The findings are discussed in relation to the action of the growth hormone/IGF-1 axis as a transducer of multiple bio-social influences into a coherent signal which allows the growing human to adjust and adapt to local ecological conditions.

[Turner syndrome and genetic polymorphism: a systematic review]

Objective:

To present the main results of the literature on genetic polymorphisms in Turner syndrome and their association with the clinical signs and the etiology of this chromosomal disorder.

Data sources:

The review was conducted in the PubMed database without any time limit, using the terms Turner syndrome and genetic polymorphism. A total of 116 articles were found, and based on the established inclusion and exclusion criteria 17 were selected for the review.

Data synthesis:

The polymorphisms investigated in patients with Turner syndrome were associated with growth deficit, causing short stature, low bone mineral density, autoimmunity and cardiac abnormalities, which are frequently found in patients with Turner syndrome. The role of single nucleotide polymorphisms in the etiology of Turner syndrome, i.e., in chromosomal nondisjunction, was also confirmed.

Conclusions:

Genetic polymorphisms appear to be associated with Turner syndrome. However, in view of the small number of published studies and their contradictory findings, further studies in different populations are needed in order to clarify the role of genetic variants in the clinical signs and etiology of the Turner syndrome.

Pharmacogenomics related to growth disorders

Growth disorders resulting in short stature are caused by a wide range of underlying pathophysiological processes. To improve height many of these conditions are treated with recombinant human growth hormone (rhGH). However, substantial inter-individual variability in growth response both in the short and long-term is recognised. Over the last decade, disease-specific growth prediction models have been developed that the clinician can use to define a child's potential response to rhGH and to optimise starting and maintenance doses of rhGH. These models, however, are not able to predict all the variations in treatment response. There has, therefore, been recent interest in using genetic information to contribute to the evaluation of responses to rhGH, including high-throughput technologies for assessing DNA markers (genome) and mRNA transcripts (transcriptome) as pharmacogenomic tools. This review will focus on how these pharmacogenomic approaches are being applied to growth disorders.

Genetic predictors of long-term response to growth hormone (GH) therapy in children with GH deficiency and Turner syndrome: the influence of a SOCS2 polymorphism

BACKGROUND

There is great interindividual variability in the response to GH therapy. Ascertaining genetic factors can improve the accuracy of growth response predictions. Suppressor of cytokine signaling (SOCS)-2 is an intracellular negative regulator of GH receptor (GHR) signaling.

OBJECTIVE

The objective of the study was to assess the influence of a SOCS2 polymorphism (rs3782415) and its interactive effect with GHR exon 3 and -202 A/C IGFBP3 (rs2854744) polymorphisms on adult height of patients treated with recombinant human GH (rhGH).

DESIGN AND PATIENTS

Genotypes were correlated with adult height data of 65 Turner syndrome (TS) and 47 GH deficiency (GHD) patients treated with rhGH, by multiple linear regressions. Generalized multifactor dimensionality reduction was used to evaluate gene-gene interactions.

RESULTS

Baseline clinical data were indistinguishable among patients with different genotypes. Adult height SD scores of patients with at least one SOCS2 single-nucleotide polymorphism rs3782415-C were 0.7 higher than those homozygous for the T allele (P < .001). SOCS2 (P = .003), GHR-exon 3 (P= .016) and -202 A/C IGFBP3 (P = .013) polymorphisms, together with clinical factors accounted for 58% of the variability in adult height and 82% of the total height SD score gain. Patients harboring any two negative genotypes in these three different loci (homozygosity for SOCS2 T allele; the GHR exon 3 full-length allele and/or the -202C-IGFBP3 allele) were more likely to achieve an adult height at the lower quartile (odds ratio of 13.3; 95% confidence interval of 3.2-54.2, P = .0001).

CONCLUSION

The SOCS2 polymorphism (rs3782415) has an influence on the adult height of children with TS and GHD after long-term rhGH therapy. Polymorphisms located in GHR, IGFBP3, and SOCS2 loci have an influence on the growth outcomes of TS and GHD patients treated with rhGH. The use of these genetic markers could identify among rhGH-treated patients those who are genetically predisposed to have less favorable outcomes.

Isolated growth hormone deficiency (GHD) in childhood and adolescence: recent advances

The diagnosis of GH deficiency (GHD) in childhood is a multistep process involving clinical history, examination with detailed auxology, biochemical testing, and pituitary imaging, with an increasing contribution from genetics in patients with congenital GHD. Our increasing understanding of the factors involved in the development of somatotropes and the dynamic function of the somatotrope network may explain, at least in part, the development and progression of childhood GHD in different age groups. With respect to the genetic etiology of isolated GHD (IGHD), mutations in known genes such as those encoding GH (GH1), GHRH receptor (GHRHR), or transcription factors involved in pituitary development, are identified in a relatively small percentage of patients suggesting the involvement of other, yet unidentified, factors. Genome-wide association studies point toward an increasing number of genes involved in the control of growth, but their role in the etiology of IGHD remains unknown. Despite the many years of research in the area of GHD, there are still controversies on the etiology, diagnosis, and management of IGHD in children. Recent data suggest that childhood IGHD may have a wider impact on the health and neurodevelopment of children, but it is yet unknown to what extent treatment with recombinant human GH can reverse this effect. Finally, the safety of recombinant human GH is currently the subject of much debate and research, and it is clear that long-term controlled studies are needed to clarify the consequences of childhood IGHD and the long-term safety of its treatment.

Network analysis identifies protein clusters of functional importance in juvenile idiopathic arthritis

Introduction

Our objective was to utilise network analysis to identify protein clusters of greatest potential functional relevance in the pathogenesis of oligoarticular and rheumatoid factor negative (RF-ve) polyarticular juvenile idiopathic arthritis (JIA).

Methods

JIA genetic association data were used to build an interactome network model in BioGRID 3.2.99. The top 10% of this protein:protein JIA Interactome was used to generate a minimal essential network (MEN). Reactome FI Cytoscape 2.83 Plugin and the Disease Association Protein-Protein Link Evaluator (Dapple) algorithm were used to assess the functionality of the biological pathways within the MEN and to statistically rank the proteins. JIA gene expression data were integrated with the MEN and clusters of functionally important proteins derived using MCODE.

Results

A JIA interactome of 2,479 proteins was built from 348 JIA associated genes. The MEN, representing the most functionally related components of the network, comprised of seven clusters, with distinct functional characteristics. Four gene expression datasets from peripheral blood mononuclear cells (PBMC), neutrophils and synovial fluid monocytes, were mapped onto the MEN and a list of genes enriched for functional significance identified. This analysis revealed the genes of greatest potential functional importance to be PTPN2 and STAT1 for oligoarticular JIA and KSR1 for RF-ve polyarticular JIA. Clusters of 23 and 14 related proteins were derived for oligoarticular and RF-ve polyarticular JIA respectively.

Conclusions

This first report of the application of network biology to JIA, integrating genetic association findings and gene expression data, has prioritised protein clusters for functional validation and identified new pathways for targeted pharmacological intervention.

Insights into the pathophysiology of catch-up compared with non-catch-up growth in children born small for gestational age: an integrated analysis of metabolic and transcriptomic data

Small for gestational age (SGA) children exhibiting catch-up (CU) growth have a greater risk of cardiometabolic diseases in later life compared with non-catch-up (NCU) SGA children. The aim of this study was to establish differences in metabolism and gene expression profiles between CU and NCU at age 4-9 years. CU children (n=22) had greater height, weight and body mass index standard deviation scores along with insulin-like growth factor-I (IGF-I) and fasting glucose levels but lower adiponectin values than NCU children (n=11; all P<0.05). Metabolic profiling demonstrated a fourfold decrease of urine myo-inositol in CU compared with NCU (P<0.05). There were 1558 genes differentially expressed in peripheral blood mononuclear cells between the groups (P<0.05). Integrated analysis of data identified myo-inositol related to gene clusters associated with an increase in insulin, growth factor and IGF-I signalling in CU children (P<0.05). Metabolic and transcriptomic profiles in CU SGA children showed changes that may relate to cardiometabolic risk.

Personalized approach to growth hormone treatment: clinical use of growth prediction models

The goal of growth hormone (GH) treatment in a short child is to attain a fast catch-up growth toward the target height (TH) standard deviation score (SDS), followed by a maintenance phase, a proper pubertal height gain, and an adult height close to TH. The short-term response variable of GH treatment, first-year height velocity (HV) (cm/year or change in height SDS), can either be compared with GH response charts for diagnosis, age and gender, or with predicted HV based on prediction models. Three types of prediction models have been described: the Kabi International Growth Hormone Study models, the Gothenburg models and the Cologne model. With these models, 50-80% of the variance could be explained. When used prospectively, individualized dosing reduces the variation in growth response in comparison with a fixed dose per body weight. Insulin-like growth factor-I-based dose titration also led to a decrease in the variation. It is uncertain whether adding biochemical, genetic or proteomic markers may improve the accuracy of the prediction. Prediction models may lead to a more evidence-based approach to determine the GH dose regimen and may reduce the drug costs for GH treatment. There is a need for user-friendly software programs to make prediction models easily available in the clinic.

Human growth is associated with distinct patterns of gene expression in evolutionarily conserved networks

Background

A co-ordinated tissue-independent gene expression profile associated with growth is present in rodent models and this is hypothesised to extend to all mammals. Growth in humans has similarities to other mammals but the return to active long bone growth in the pubertal growth spurt is a distinctly human growth event. The aim of this study was to describe gene expression and biological pathways associated with stages of growth in children and to assess tissue-independent expression patterns in relation to human growth.

Results

We conducted gene expression analysis on a library of datasets from normal children with age annotation, collated from the NCBI Gene Expression Omnibus (GEO) and EBI Arrayexpress databases. A primary data set was generated using cells of lymphoid origin from normal children; the expression of 688 genes (ANOVA false discovery rate modified p-value, q < 0.1) was associated with age, and subsets of these genes formed clusters that correlated with the phases of growth – infancy, childhood, puberty and final height. Network analysis on these clusters identified evolutionarily conserved growth pathways (NOTCH, VEGF, TGFB, WNT and glucocorticoid receptor – Hyper-geometric test, q < 0.05). The greatest degree of network ‘connectivity’ and hence functional significance was present in infancy (Wilcoxon test, p < 0.05), which then decreased through to adulthood. These observations were confirmed in a separate validation data set from lymphoid tissue. Similar biological pathways were observed to be associated with development-related gene expression in other tissues (conjunctival epithelia, temporal lobe brain tissue and bone marrow) suggesting the existence of a tissue-independent genetic program for human growth and maturation.

Conclusions

Similar evolutionarily conserved pathways have been associated with gene expression and child growth in multiple tissues. These expression profiles associate with the developmental phases of growth including the return to active long bone growth in puberty, a distinctly human event. These observations also have direct medical relevance to pathological changes that induce disease in children. Taking into account development-dependent gene expression profiles for normal children will be key to the appropriate selection of genes and pathways as potential biomarkers of disease or as drug targets.