Daniel Hanson

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

BackgroundA 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.ResultsWe 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.ConclusionsSimilar 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.

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.

Identifying biological pathways that underlie primordial short stature using network analysis.

Mutations in CUL7, OBSL1 and CCDC8, leading to disordered ubiquitination, cause one of the commonest primordial growth disorders, 3-M syndrome. This condition is associated with i) abnormal p53 function, ii) GH and/or IGF1 resistance, which may relate to failure to recycle signalling molecules, and iii) cellular IGF2 deficiency. However the exact molecular mechanisms that may link these abnormalities generating growth restriction remain undefined. In this study, we have used immunoprecipitation/mass spectrometry and transcriptomic studies to generate a 3-M ‘interactome’, to define key cellular pathways and biological functions associated with growth failure seen in 3-M. We identified 189 proteins which interacted with CUL7, OBSL1 and CCDC8, from which a network including 176 of these proteins was generated. To strengthen the association to 3-M syndrome, these proteins were compared with an inferred network generated from the genes that were differentially expressed in 3-M fibroblasts compared with controls. This resulted in a final 3-M network of 131 proteins, with the most significant biological pathway within the network being mRNA splicing/processing. We have shown using an exogenous insulin receptor (INSR) minigene system that alternative splicing of exon 11 is significantly changed in HEK293 cells with altered expression of CUL7, OBSL1 and CCDC8 and in 3-M fibroblasts. The net result is a reduction in the expression of the mitogenic INSR isoform in 3-M syndrome. From these preliminary data, we hypothesise that disordered ubiquitination could result in aberrant mRNA splicing in 3-M; however, further investigation is required to determine whether this contributes to growth failure.

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

IntroductionOur 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).MethodsJIA 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.ResultsA 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.ConclusionsThis 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.

Pediatric perspective on pharmacogenomics

The advances in high-throughput genomic technologies have improved the understanding of disease pathophysiology and have allowed a better characterization of drug response and toxicity based on individual genetic make up. Pharmacogenomics is being recognized as a valid approach used to identify patients who are more likely to respond to medication, or those in whom there is a high probability of developing severe adverse drug reactions. An increasing number of pharmacogenomic studies are being published, most include only adults. A few studies have shown the impact of pharmacogenomics in pediatrics, highlighting a key difference between children and adults, which is the contribution of developmental changes to therapeutic responses across different age groups. This review focuses on pharmacogenomic research in pediatrics, providing examples from common pediatric conditions and emphasizing their developmental context.

Constitutional delay of growth and puberty is not commonly associated with mutations in the acid labile subunit gene

OBJECTIVES Constitutional delay of growth and puberty (CDGP) is a common clinical condition that may be inherited as an autosomal dominant, recessive or X-linked trait. However, single-gene defects underlying CDGP have not yet been identified. A small number of children (to date 10) with modest growth failure and in the majority delayed puberty, a phenotype similar to that of CDGP, have been reported to carry mutations in the IGF acid labile subunit (IGFALS) gene which encodes the ALS, a part of the ternary complex carrying IGF-I in the circulation. The aim of our study was to screen a well-characterised CDGP cohort exhibiting a range of growth retardation and pubertal delay for pathogenic sequence variants in IGFALS. DESIGN AND METHODS We used denaturing high performance liquid chromatography (dHPLC) to screen for IGFALS mutations in DNA samples from 90 children (80 males) with CDGP of predominantly White European origin. DNA fragments generating abnormal waveforms were directly sequenced. RESULTS No IGFALS mutation was identified in the coding sequences or exon-intron boundaries in our CDGP cohort. One abnormal waveform pattern in dHPLC in 15 children with CDGP was found to represent a recognised synonymous single-nucleotide polymorphism of the coding transcript in the second exon in residue 210 of IGFALS. CONCLUSIONS IGFALS sequence variants are unlikely to be a common association with pubertal delay in children with CDGP.

EVI1 expression in childhood acute lymphoblastic leukaemia is not restricted to MLL and BCR/ABL rearrangements and is influenced by age.

EVI1 expression in childhood acute lymphoblastic leukaemia is not restricted to MLL and BCR/ABL rearrangements and is influenced by age

Metabolites involved in Glycolysis and Amino Acid Metabolism are Altered in Short Children Born Small for Gestational Age

Background:Later life metabolic dysfunction is a well-recognized consequence of being born small for gestational age (SGA). This study has applied metabolomics to identify whether there are changes in these pathways in prepubertal short SGA children and aimed to compare the intracellular and extracellular metabolome in fibroblasts derived from healthy children and SGA children with postnatal growth impairment.Methods:Skin fibroblast cell lines were established from eight SGA children (age 1.8–10.3 y) with failure of catch-up growth and from three healthy control children. Confluent cells were incubated in serum-free media and the spent growth medium (metabolic footprint), and intracellular metabolome (metabolic fingerprint) were analyzed by gas-chromatography mass spectrometry.Results:Nineteen metabolites were significantly altered between SGA and control cell lines. The greatest fold difference (FD) was seen for alanine (fingerprint FD, SGA: control 0.3, P = 0.01 and footprint FD = 0.19, P = 0.01), aspartic acid (fingerprint FD = 5.21, P = 0.01), and cystine (footprint FD = 1.66, P = 0.02). Network analysis of the differentially expressed metabolites predicted inhibition of insulin as well as growth (ERK) signaling in SGA cells.Conclusion:This study indicates that changes in cellular metabolism associated with both growth failure and insulin insensitivity are present in prepubertal short children born SGA.

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 childs 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.

The in vitro functional analysis of single-nucleotide polymorphisms associated with growth hormone (GH) response in children with GH deficiency

Response to recombinant human growth hormone (r-hGH) in the first year of therapy has been associated with single-nucleotide polymorphisms (SNPs) in children with GH deficiency (GHD). Associated SNPs were screened for regulatory function using a combination of in silico techniques. Four SNPs in regulatory sequences were selected for the analysis of in vitro transcriptional activity (TA). There was an additive effect of the alleles in the four genes associated with good growth response. For rs3110697 within IGFBP3, rs1045992 in CYP19A1 and rs2888586 in SOS1, the variant associated with better growth response showed higher TA with r-hGH treatment. For rs1024531 in GRB10, a negative regulator of IGF-I signalling and growth, the variant associated with better growth response had a significantly lower TA on r-hGH stimulation. These results indicate that specific SNP variants have effects on TA that provide a rationale for their clinical impact on growth response to r-hGH therapy.