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

Warming during embryogenesis induces a lasting transcriptomic signature in fishes

Exposure to elevated temperatures during embryogenesis can influence the plasticity of tissues in later life. Despite these long-term changes in plasticity, few differentially expressed genes are ever identified, suggesting that the developmental programming of later life plasticity may occur through the modulation of other aspects of transcriptomic architecture, such as gene network organisation. Here, we use network modelling approaches to demonstrate that warm temperatures during embryonic development (developmental warming) have consistent effects in later life on the organisation of transcriptomic networks across four diverse species of fishes: Scyliorhinus canicula, Danio rerio, Dicentrarchus labrax, and Gasterosteus aculeatus. The transcriptomes of developmentally warmed fishes are characterised by an increased entropy of their pairwise gene interaction networks, implying a less structured, more 'random' set of gene interactions. We also show that, in zebrafish subject to developmental warming, the entropy of an individual gene within a network is associated with that gene's probability of expression change during temperature acclimation in later life. However, this association is absent in animals reared under 'control' conditions. Thus, the thermal environment experienced during embryogenesis can alter transcriptomic organisation in later life, and these changes may influence an individual's responsiveness to future temperature challenges.

Evidence for adolescent length growth spurts in bonobos and other primates highlights the importance of scaling laws

Adolescent growth spurts (GSs) in body length seem to be absent in non-human primates and are considered a distinct human trait. However, this distinction between present and absent length-GSs may reflect a mathematical artefact that makes it arbitrary. We first outline how scaling issues and inappropriate comparisons between length (linear) and weight (volume) growth rates result in misleading interpretations like the absence of length-GSs in non-human primates despite pronounced weight-GSs, or temporal delays between length- and weight-GSs. We then apply a scale-corrected approach to a comprehensive dataset on 258 zoo-housed bonobos that includes weight and length growth as well as several physiological markers related to growth and adolescence. We found pronounced GSs in body weight and length in both sexes. Weight and length growth trajectories corresponded with each other and with patterns of testosterone and insulin-like growth factor-binding protein 3 levels, resembling adolescent GSs in humans. We further re-interpreted published data of non-human primates, which showed that aligned GSs in weight and length exist not only in bonobos. Altogether, our results emphasize the importance of considering scaling laws when interpreting growth curves in general, and further show that pronounced, human-like adolescent length-GSs exist in bonobos and probably also many other non-human primates.

Similar hypothyroid and sepsis circulating mRNA expression could be useful as a biomarker in onthyroidal illness syndrome: a pilot study

Objective

Based on hypothetical hypothyroidism and nonthyroidal illness syndrome (NTIS) gene expression similarities, we decided to compare the patterns of expression of both as models of NTIS. The concordant profile between them may enlighten new biomarkers for NTIS challenging scenarios.

Materials and methods

We used Ion Proton System next-generation sequencing to build the hypothyroidism transcriptome. We selected two databanks in GEO2 platform datasets to find the differentially expressed genes (DEGs) in adults and children with sepsis. The ROC curve was constructed to calculate the area under the curve (AUC). The AUC, chi-square, sensitivity, specificity, accuracy, kappa and likelihood were calculated. We performed Cox regression and Kaplan-Meier analyses for the survival analysis.

Results

Concerning hypothyroidism DEGs, 70.42% were shared with sepsis survivors and 61.94% with sepsis nonsurvivors. Some of them were mitochondrial gene types (mitGenes), and 95 and 88 were related to sepsis survivors and nonsurvivors, respectively. BLOC1S1, ROMO1, SLIRP and TIMM8B mitGenes showed the capability to distinguish sepsis survivors and nonsurvivors.

Conclusion

We matched our hypothyroidism DEGs with those in adults and children with sepsis. Additionally, we observed different patterns of hypothyroid-related genes among sepsis survivors and nonsurvivors. Finally, we demonstrated that ROMO1, SLIRP and TIMM8B could be predictive biomarkers in children´s sepsis.

Pharmacogenetic Aspects of Drug Metabolizing Enzymes and Transporters in Pediatric Medicine: Study Progress, Clinical Practice and Future Perspectives

As the activity of certain drug metabolizing enzymes or transporter proteins can vary with age, the effect of ontogenetic and genetic variation on the activity of these enzymes is critical for the accurate prediction of treatment outcomes and toxicity in children. This makes pharmacogenetic research in pediatrics particularly important and urgently needed, but also challenging. This review summarizes pharmacogenetic studies on the effects of genetic polymorphisms on pharmacokinetic parameters and clinical outcomes in pediatric populations for certain drugs, which are commonly prescribed by clinicians across multiple therapeutic areas in a general hospital, organized from those with the most to the least pediatric evidence among each drug category. We also further discuss the research status of the gene-guided dosing regimens and clinical implementation of pediatric pharmacogenetics. More and more drug-gene interactions are demonstrated to have clinical validity for children, and pharmacogenomics in pediatrics have shown evidence-based benefits to enhance the efficacy and precision of existing drug dosing regimens in several therapeutic areas. However, the most important limitation to the implementation is the lack of high-quality, rigorous pediatric prospective clinical studies, so adequately powered interventional clinical trials that support incorporation of pharmacogenetics into the care of children are still needed.

A database of pediatric drug effects to evaluate ontogenic mechanisms from child growth and development

BACKGROUND

Adverse drug effects (ADEs) in children are common and may result in disability and death, necessitating post-marketing monitoring of their use. Evaluating drug safety is especially challenging in children due to the processes of growth and maturation, which can alter how children respond to treatment. Current drug safety-signal-detection methods do not account for these dynamics.

METHODS

We recently developed a method called disproportionality generalized additive models (dGAMs) to better identify safety signals for drugs across child-development stages.

FINDINGS

We used dGAMs on a database of 264,453 pediatric adverse-event reports and found 19,438 ADEs signals associated with development and validated these signals against a small reference set of pediatric ADEs. Using our approach, we can hypothesize on the ontogenic dynamics of ADE signals, such as that montelukast-induced psychiatric disorders appear most significant in the second year of life. Additionally, we integrated pediatric enzyme expression data and found that pharmacogenes with dynamic childhood expression, such as CYP2C18 and CYP27B1, are associated with pediatric ADEs.

CONCLUSIONS

We curated KidSIDES, a database of pediatric drug safety signals, for the research community and developed the Pediatric Drug Safety portal (PDSportal) to facilitate evaluation of drug safety signals across childhood growth and development.

FUNDING

This study was supported by grants from the National Institutes of Health (NIH).

Role of ZBTB38 Genotype and Expression in Growth and Response to Recombinant Human Growth Hormone Treatment

CONTEXT

Single-nucleotide polymorphisms (SNPs) in ZBTB38 have been associated with idiopathic short stature (ISS) and adult height.

OBJECTIVE

This study sought to (a) characterize the phenotype of ISS patients and their response to recombinant human growth hormone (rhGH) by ZBTB38 SNP genotype; (b) describe the relationship of ZBTB38 expression with normal growth; and (c) describe the in vitro effects of ZBTB38 knockdown on cell proliferation and MCM10 expression.

METHODS

The genotype-phenotype relationship of rs6764769 and rs724016 were explored in 261 ISS patients and effects of genotype on response to rhGH were assessed in 93 patients treated with rhGH. The relationship between age and ZBTB38 expression was assessed in 87 normal children and young adults. Knockdown of ZBTB38 in SiHA cells was achieved with siRNAs and cell proliferation assessed with a WST-8 assay.

RESULTS

We found that rs6764769 and rs724016 are in linkage disequilibrium. The rs724016 GG genotype was associated with lower birth length (P = 0.01) and a lower change in height SDS over the first year of treatment (P = 0.02). ZBTB38 expression was positively correlated with age (P < 0.001). siRNA-mediated knockdown of ZBTB38 resulted in increased cell proliferation at 72 and 96 hours posttransfection but did not alter expression of MCM10.

CONCLUSIONS

SNPs within ZBTB38 associated with ISS are linked to higher birth size within a cohort of ISS patients and a better response to rhGH therapy while ZBTB38 expression is positively related to age.

Pharmacogenomics in Children

Historically genetics has not been considered when prescribing drugs for children. However, it is clear that genetics are not only an important determinant of disease in children but also of drug response for many important drugs that are core agents used in the therapy of common problems in children. Advances in therapy and in the ethical construct of children's research have made pharmacogenomic assessment for children much easier to pursue. It is likely that pharmacogenomics will become part of the therapeutic decision-making process for children, notably in areas such as childhood cancer where weighing benefits and risks of therapy is crucial.

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.

No population left behind: Improving paediatric drug safety using informatics and systems biology

Adverse drugs effects (ADEs) in children are common and may result in disability and death. The current paediatric drug safety landscape, including clinical trials, is limited as it rarely includes children and relies on extrapolation from adults. Children are not small adults but go through an evolutionarily conserved and physiologically dynamic process of growth and maturation. Novel quantitative approaches, integrating observations from clinical trials and drug safety databases with dynamic mechanisms, can be used to systematically identify ADEs unique to childhood. In this perspective, we discuss three critical research directions using systems biology methodologies and novel informatics to improve paediatric drug safety, namely child versus adult drug safety profiles, age-dependent drug toxicities and genetic susceptibility of ADEs across childhood. We argue that a data-driven framework that leverages observational data, biomedical knowledge and systems biology modelling will reveal previously unknown mechanisms of pediatric adverse drug events and lead to improved paediatric drug safety.

Pharmacogenomics in Pediatric Oncology: Mitigating Adverse Drug Reactions While Preserving Efficacy

Cancer is the leading cause of death in American children older than 1 year of age. Major developments in drugs such as thiopurines and optimization in clinical trial protocols for treating cancer in children have led to a remarkable improvement in survival, from approximately 30% in the 1960s to more than 80% today. Short-term and long-term adverse effects of chemotherapy still affect most survivors of childhood cancer. Pharmacogenetics plays a major role in predicting the safety of cancer chemotherapy and, in the future, its effectiveness. Treatment failure in childhood cancer-due to either serious adverse effects that limit therapy or the failure of conventional dosing to induce remission-warrants development of new strategies for treatment. Here, we summarize the current knowledge of the pharmacogenomics of cancer drug treatment in children and of statistically and clinically relevant drug-gene associations and the mechanistic understandings that underscore their therapeutic value in the treatment of childhood cancer.

Physiological mechanisms underlying children's circannual growth patterns and their contributions to the obesity epidemic in elementary school age children

Several studies since the 1990s have demonstrated that children increase their body mass index at a faster rate during summer months compared with the school year, leading some to conclude that the out-of-school summer environment is responsible. Other studies, however, have suggested that seasonality may play a role in children's height and weight changes across the year. This article reviews evidence for seasonal differences in the rate of children's height and weight gain and proposes potential physiological mechanisms that may explain these seasonal variations.

Exercise-associated prevention of adult cardiovascular disease in children and adolescents: monocytes, molecular mechanisms, and a call for discovery

Atherosclerosis originates in childhood and adolescence. The goal of this review is to highlight how exercise and physical activity during childhood and adolescence, critical periods of growth and development, can prevent adult cardiovascular disease (CVD), particularly through molecular mechanisms of monocytes, a key cell of the innate immune system. Monocytes are heterogeneous and pluripotential cells that can, paradoxically, play a role in both the instigation and prevention of atherosclerosis. Recent discoveries in young adults reveal that brief exercise affects monocyte gene pathways promoting a cell phenotype that patrols the vascular system and repairs injuries. Concurrently, exercise inhibits pro-inflammatory monocytes, cells that contribute to vascular damage and plaque formation. Because CVD is typically asymptomatic in youth, minimally invasive techniques must be honed to study the subtle anatomic and physiologic evidence of vascular dysfunction. Exercise gas exchange and heart rate measures can be combined with ultrasound assessments of vascular anatomy and reactivity, and near-infrared spectroscopy to quantify impaired O2 transport that is often hidden at rest. Combined with functional, transcriptomic, and epigenetic monocyte expression and measures of monocyte-endothelium interaction, molecular mechanisms of early CVD can be formulated, and then translated into effective physical activity-based strategies in youth to prevent adult-onset CVD.

The Pediatric Cell Atlas: Defining the Growth Phase of Human Development at Single-Cell Resolution

Single-cell gene expression analyses of mammalian tissues have uncovered profound stage-specific molecular regulatory phenomena that have changed the understanding of unique cell types and signaling pathways critical for lineage determination, morphogenesis, and growth. We discuss here the case for a Pediatric Cell Atlas as part of the Human Cell Atlas consortium to provide single-cell profiles and spatial characterization of gene expression across human tissues and organs. Such data will complement adult and developmentally focused HCA projects to provide a rich cytogenomic framework for understanding not only pediatric health and disease but also environmental and genetic impacts across the human lifespan.

Systems based analysis of human embryos and gene networks involved in cell lineage allocation

BACKGROUND

Little is understood of the molecular mechanisms involved in the earliest cell fate decision in human development, leading to the establishment of the trophectoderm (TE) and inner cell mass (ICM) stem cell population. Notably, there is a lack of understanding of how transcriptional networks arise during reorganisation of the embryonic genome post-fertilisation.

RESULTS

We identified a hierarchical structure of preimplantation gene network modules around the time of embryonic genome activation (EGA). Using network models along with eukaryotic initiation factor (EIF) and epigenetic-associated gene expression we defined two sets of blastomeres that exhibited diverging tendencies towards ICM or TE. Analysis of the developmental networks demonstrated stage specific EIF expression and revealed that histone modifications may be an important epigenetic regulatory mechanism in preimplantation human embryos. Comparison to published RNAseq data confirmed that during EGA the individual 8-cell blastomeres are transcriptionally primed for the first lineage decision in development towards ICM or TE.

CONCLUSIONS

Using multiple systems biology approaches to compare developmental stages in the early human embryo with single cell transcript data from blastomeres, we have shown that blastomeres considered to be totipotent are not transcriptionally equivalent. Furthermore we have linked the developmental interactome to individual blastomeres and to later cell lineage. This has clinical implications for understanding the impact of fertility treatments and developmental programming of long term health.

Evolutionary conserved networks of human height identify multiple Mendelian causes of short stature

Height is a heritable and highly heterogeneous trait. Short stature affects 3% of the population and in most cases is genetic in origin. After excluding known causes, 67% of affected individuals remain without diagnosis. To identify novel candidate genes for short stature, we performed exome sequencing in 254 unrelated families with short stature of unknown cause and identified variants in 63 candidate genes in 92 (36%) independent families. Based on systematic characterization of variants and functional analysis including expression in chondrocytes, we classified 13 genes as strong candidates. Whereas variants in at least two families were detected for all 13 candidates, two genes had variants in 6 (UBR4) and 8 (LAMA5) families, respectively. To facilitate their characterization, we established a clustered network of 1025 known growth and short stature genes, which yielded 29 significantly enriched clusters, including skeletal system development, appendage development, metabolic processes, and ciliopathy. Eleven of the candidate genes mapped to 21 of these clusters, including CPZ, EDEM3, FBRS, IFT81, KCND1, PLXNA3, RASA3, SLC7A8, UBR4, USP45, and ZFHX3. Fifty additional growth-related candidates we identified await confirmation in other affected families. Our study identifies Mendelian forms of growth retardation as an important component of idiopathic short stature.

Hypoalbuminemia: Pathogenesis and Clinical Significance

Hypoalbuminemia is associated with inflammation. Despite being addressed repeatedly in the literature, there is still confusion regarding its pathogenesis and clinical significance. Inflammation increases capillary permeability and escape of serum albumin, leading to expansion of interstitial space and increasing the distribution volume of albumin. The half‐life of albumin has been shown to shorten, decreasing total albumin mass. These 2 factors lead to hypoalbuminemia despite increased fractional synthesis rates in plasma. Hypoalbuminemia, therefore, results from and reflects the inflammatory state, which interferes with adequate responses to events like surgery or chemotherapy, and is associated with poor quality of life and reduced longevity. Increasing or decreasing serum albumin levels are adequate indicators, respectively, of improvement or deterioration of the clinical state. In the interstitium, albumin acts as the main extracellular scavenger, antioxidative agent, and as supplier of amino acids for cell and matrix synthesis. Albumin infusion has not been shown to diminish fluid requirements, infection rates, and mortality in the intensive care unit, which may imply that there is no body deficit or that the quality of albumin “from the shelf” is unsuitable to play scavenging and antioxidative roles. Management of hypoalbuminaemia should be based on correcting the causes of ongoing inflammation rather than infusion of albumin. After the age of 30 years, muscle mass and function slowly decrease, but this loss is accelerated by comorbidity and associated with decreasing serum albumin levels. Nutrition support cannot fully prevent, but slows down, this chain of events, especially when combined with physical exercise.

Pharmacogenetics: Applications to Pediatric Patients

Individual genomic differences may affect drug disposition and effects of many drugs, and identification of biomarkers are crucial to personalize dosage and optimize response. In children, developmental changes associated with growth and maturation translate into different relationships between genotype and phenotype and different responses to treatment compared to adults. This review aims to summarize some developmental aspects of pharmacogenetics, based on practical examples.

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).

Pharmacogenetics and application in pediatrics

Identification of markers involved in drug disposition is crucial for drugs with a narrow therapeutic index. Individual genomic differences can affect the pharmacology of some drugs and participate to inter-individual variability in drug response. Pharmacogenetics is a useful tool in clinical practice for dosage adjustment and to limit drug toxicities. In pediatrics, physiological changes can also influence the disposition of drugs in infants, children and adolescents. The importance of ontogeny translates into different responses to the same drug in children and adults. Thus, interactions between the maturation of metabolism enzymes or transporters and genetics have a major impact on drug exposure leading to age-specific dosage requirements. This review aims to describe implementation of pharmacogenetics in personalized medicine and specifies pediatric characteristics with ethical considerations.

A high-quality annotated transcriptome of swine peripheral blood

Background

High throughput gene expression profiling assays of peripheral blood are widely used in biomedicine, as well as in animal genetics and physiology research. Accurate, comprehensive, and precise interpretation of such high throughput assays relies on well-characterized reference genomes and/or transcriptomes. However, neither the reference genome nor the peripheral blood transcriptome of the pig have been sufficiently assembled and annotated to support such profiling assays in this emerging biomedical model organism. We aimed to assemble published and novel RNA-seq data to provide a comprehensive, well-annotated blood transcriptome for pigs by integrating a de novo assembly with a genome-guided assembly.

Results

A de novo and a genome-guided transcriptome of porcine whole peripheral blood was assembled with ~162 million pairs of paired-end and ~183 million single-end, trimmed and normalized Illumina RNA-seq reads (~6 billion initial reads from 146 RNA-seq libraries) from five independent studies by using the Trinity and Cufflinks software, respectively. We then removed putative transcripts (PTs) of low confidence from both assemblies and merged the remaining PTs into an integrated transcriptome consisting of 132,928 PTs, with 126,225 (~95%) PTs from the de novo assembly and more than 91% of PTs spliced. In the integrated transcriptome, ~90% and 63% of PTs had significant sequence similarity to sequences in the NCBI NT and NR databases, respectively; 68,754 (~52%) PTs were annotated with 15,965 unique gene ontology (GO) terms; and 7618 PTs annotated with Enzyme Commission codes were assigned to 134 pathways curated by the Kyoto Encyclopedia of Genes and Genomes (KEGG). Full exon-intron junctions of 17,528 PTs were validated by PacBio IsoSeq full-length cDNA reads from 3 other porcine tissues, NCBI pig RefSeq mRNAs and transcripts from Ensembl Sscrofa10.2 annotation. Completeness of the 5’ termini of 37,569 PTs was validated by public cap analysis of gene expression (CAGE) data. By comparison to the Ensembl transcripts, we found that (1) the deduced precursors of 54,402 PTs shared at least one intron or exon with those of 18,437 Ensembl transcripts; (2) 12,262 PTs had both longer 5’ and 3’ termini than their maximally overlapping Ensembl transcripts; and (3) 41,838 spliced PTs were totally missing from the Sscrofa10.2 annotation. Similar results were obtained when the PTs were compared to the pig NCBI RefSeq mRNA collection.

Conclusions

We built, validated and annotated a comprehensive porcine blood transcriptome with significant improvement over the annotation of Ensembl Sscrofa10.2 and the pig NCBI RefSeq mRNAs, and laid a foundation for blood-based high throughput transcriptomic assays in pigs and for advancing annotation of the pig genome.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3863-7) contains supplementary material, which is available to authorized users.

A systematic SNP selection approach to identify mechanisms underlying disease aetiology: linking height to post-menopausal breast and colorectal cancer risk

Data from GWAS suggest that SNPs associated with complex diseases or traits tend to co-segregate in regions of low recombination, harbouring functionally linked gene clusters. This phenomenon allows for selecting a limited number of SNPs from GWAS repositories for large-scale studies investigating shared mechanisms between diseases. For example, we were interested in shared mechanisms between adult-attained height and post-menopausal breast cancer (BC) and colorectal cancer (CRC) risk, because height is a risk factor for these cancers, though likely not a causal factor. Using SNPs from public GWAS repositories at p-values < 1 × 10⁻⁵ and a genomic sliding window of 1 mega base pair, we identified SNP clusters including at least one SNP associated with height and one SNP associated with either post-menopausal BC or CRC risk (or both). SNPs were annotated to genes using HapMap and GRAIL and analysed for significantly overrepresented pathways using ConsensuspathDB. Twelve clusters including 56 SNPs annotated to 26 genes were prioritised because these included at least one height- and one BC risk- or CRC risk-associated SNP annotated to the same gene. Annotated genes were involved in Indian hedgehog signalling (p-value = 7.78 × 10⁻⁷) and several cancer site-specific pathways. This systematic approach identified a limited number of clustered SNPs, which pinpoint potential shared mechanisms linking together the complex phenotypes height, post-menopausal BC and CRC.

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.

Pharmacogenomics in Pediatric Oncology: Review of Gene-Drug Associations for Clinical Use

During the 3rd congress of the European Society of Pharmacogenomics and Personalised Therapy (ESPT) in Budapest in 2015, a preliminary meeting was held aimed at establishing a pediatric individualized treatment in oncology and hematology committees. The main purpose was to facilitate the transfer and harmonization of pharmacogenetic testing from research into clinics, to bring together basic and translational research and to educate health professionals throughout Europe. The objective of this review was to provide the attendees of the meeting as well as the larger scientific community an insight into the compiled evidence regarding current pharmacogenomics knowledge in pediatric oncology. This preliminary evaluation will help steer the committee’s work and should give the reader an idea at which stage researchers and clinicians are, in terms of personalizing medicine for children with cancer. From the evidence presented here, future recommendations to achieve this goal will also be suggested.

Characterization of GPR101 transcript structure and expression patterns

We recently showed that Xq26.3 microduplications cause X-linked acrogigantism (X-LAG). X-LAG patients mainly present with growth hormone and prolactin-secreting adenomas and share a minimal duplicated region containing at least four genes. GPR101 was the only gene highly expressed in their pituitary lesions, but little is known about its expression patterns. In this work, GPR101 transcripts were characterized in human tissues by 5'-Rapid Amplification of cDNA Ends (RACE) and RNAseq, while the putative promoter was bioinformatically predicted. We investigated GPR101 mRNA and protein expression by RT-quantitative PCR (qPCR), whole-mount in situ hybridization, and immunostaining, in human, rhesus monkey, rat and zebrafish. We identified four GPR101 isoforms characterized by different 5'-untranslated regions (UTRs) and a common 6.1kb long 3'UTR. GPR101 expression was very low or absent in almost all adult human tissues examined, except for specific brain regions. Strong GPR101 staining was observed in human fetal pituitary and during adolescence, whereas very weak/absent expression was detected during childhood and adult life. In contrast to humans, adult monkey and rat pituitaries expressed GPR101, but in different cell types. Gpr101 is expressed in the brain and pituitary during rat and zebrafish development; in rat pituitary, Gpr101 is expressed only after birth and shows sexual dimorphism. This study shows that different GPR101 transcripts exist and that the brain is the major site of GPR101 expression across different species, although divergent species- and temporal-specific expression patterns are evident. These findings suggest an important role for GPR101 in brain and pituitary development and likely reflect the very different growth, development and maturation patterns among species.

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.

Bridging the Gaps: the Promise of Omics Studies in Pediatric Exercise Research

In this review, we highlight promising new discoveries that may generate useful and clinically relevant insights into the mechanisms that link exercise with growth during critical periods of development. Growth in childhood and adolescence is unique among mammals and is a dynamic process regulated by an evolution of hormonal and inflammatory mediators, age-dependent progression of gene expression, and environmentally modulated epigenetic mechanisms. Many of these same processes likely affect molecular transducers of physical activity. How the molecular signaling associated with growth is synchronized with signaling associated with exercise is poorly understood. Recent advances in "omics"-namely genomics and epigenetics, metabolomics, and proteomics-now provide exciting approaches and tools that can be used for the first time to address this gap. A biologic definition of "healthy" exercise that links the metabolic transducers of physical activity with parallel processes that regulate growth will transform health policy and guidelines that promote optimal use of physical activity.

Nonlinear transcriptomic response to dietary fat intake in the small intestine of C57BL/6J mice

BACKGROUND

A high caloric diet, in conjunction with low levels of physical activity, promotes obesity. Many studies are available regarding the relation between dietary saturated fats and the etiology of obesity, but most focus on liver, muscle and white adipose tissue. Furthermore, the majority of transcriptomic studies seek to identify linear effects of an external stimulus on gene expression, although such an assumption does not necessarily hold. Our work assesses the dose-dependent effects of dietary fat intake on differential gene expression in the proximal, middle and distal sections of the small intestine in C57BL/6J mice. Gene expression is analyzed in terms of either linear or nonlinear responses to fat intake.

RESULTS

The highest number of differentially expressed genes was observed in the middle section. In all intestine sections, most of the identified processes exhibited a linear response to increasing fat intake. The relative importance of logarithmic and exponential responses was higher in the proximal and distal sections, respectively. Functional enrichment analysis highlighted a constantly linear regulation of acute-phase response along the whole small intestine, with up-regulation of Serpina1b. The study of gene expression showed that exponential down-regulation of cholesterol transport in the middle section is coupled with logarithmic up-regulation of cholesterol homeostasis. A shift from linear to exponential response was observed in genes involved in the negative regulation of caspase activity, from middle to distal section (e.g., Birc5, up-regulated).

CONCLUSIONS

The transcriptomic signature associated with inflammatory processes preserved a linear response in the whole small intestine (e.g., up-regulation of Serpina1b). Processes related to cholesterol homeostasis were particularly active in the middle small intestine and only the highest fat intake down-regulated cholesterol transport and efflux (with a key role played by the down-regulation of ATP binding cassette transporters). Characterization of nonlinear patterns of gene expression triggered by different levels of dietary fat is an absolute novelty in intestinal studies. This approach helps identifying which processes are overloaded (i.e., positive, logarithmic regulation) or arrested (i.e., negative, exponential regulation) in response to excessive fat intake, and can shed light on the relationships linking lipid intake to obesity and its associated molecular disturbances.

Post-weaning blood transcriptomic differences between Yorkshire pigs divergently selected for residual feed intake

Background

Improving feed efficiency (FE) of pigs by genetic selection is of economic and environmental significance. An increasingly accepted measure of feed efficiency is residual feed intake (RFI). Currently, the molecular mechanisms underlying RFI are largely unknown. Additionally, to incorporate RFI into animal breeding programs, feed intake must be recorded on individual pigs, which is costly and time-consuming. Thus, convenient and predictive biomarkers for RFI that can be measured at an early age are greatly desired. In this study, we aimed to explore whether differences exist in the global gene expression profiles of peripheral blood of 35 to 42 day-old pigs with extremely low (more efficient) and high RFI (less efficient) values from two lines that were divergently selected for RFI during the grow-finish phase, to use such information to explore the potential molecular basis of RFI differences, and to initiate development of predictive biomarkers for RFI.

Results

We identified 1972 differentially expressed genes (DEGs) (q ≤ 0.15) between the low (n = 15) and high (n = 16) RFI groups of animals by using RNA sequencing technology. We validated 24 of 37 selected DEGs by reverse transcription-quantitative PCR (RT-qPCR) in a joint analysis of 24 (12 per line) of the 31 samples already used for RNA-seq plus 24 (12 per line) novel samples from the same contemporary group of pigs. Using an analysis of the 24 novel samples alone, only nine of the 37 selected DEGs were validated. Genes involved in small molecule biosynthetic process, antigen processing and presentation of peptide antigen via major histocompatibility complex (MHC) class I, and steroid biosynthetic process were overrepresented among DEGs that had higher expression in the low versus high RFI animals. Genes known to function in the proteasome complex or mitochondrion were also significantly enriched among genes with higher expression in the low versus high RFI animals. Alternatively, genes involved in signal transduction, bone mineralization and regulation of phosphorylation were overrepresented among DEGs with lower expression in the low versus high RFI animals. The DEGs significantly overlapped with genes associated with disease, including hyperphagia, eating disorders and mitochondrial diseases (q < 1E-05). A weighted gene co-expression network analysis (WGCNA) identified four co-expression modules that were differentially expressed between the low and high RFI groups. Genes involved in lipid metabolism, regulation of bone mineralization, cellular immunity and response to stimulus were overrepresented within the two modules that were most significantly differentially expressed between the low and high RFI groups. We also found five of the DEGs and one of the co-expression modules were significantly associated with the RFI phenotype of individual animals (q < 0.05).

Conclusions

The post-weaning blood transcriptome was clearly different between the low and high RFI groups. The identified DEGs suggested potential differences in mitochondrial and proteasomal activities, small molecule biosynthetic process, and signal transduction between the two RFI groups and provided potential new insights into the molecular basis of RFI in pigs, although the observed relationship between the post-weaning blood gene expression and RFI phenotype measured during the grow-finish phase was not strong. DEGs and representative genes in co-expression modules that were associated with RFI phenotype provide a preliminary list for developing predictive biomarkers for RFI in pigs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2395-x) contains supplementary material, which is available to authorized users.

Combinatorial PX-866 and Raloxifene Decrease Rb Phosphorylation, Cyclin E2 Transcription, and Proliferation of MCF-7 Breast Cancer Cells

As a potential means to reduce proliferation of breast cancer cells, a multiple-pathway approach with no effect on control cells was explored. The human interactome being constructed by the Center for Cancer Systems Biology will prove indispensable to understanding composite effects of multiple pathways, but its discovered protein-protein interactions require characterization. Accordingly, we explored the effects of regulators of one protein on downstream targets of the other protein. MCF-7 estrogen receptor-positive (ER+) breast cancer cells were treated with raloxifene to upregulate the TGF-β pathway and PX-866 to down-regulate the PI3K/Akt pathway. This resulted in highly significant downstream reduction of cell cycle proliferation in breast cancer cells with no significant proliferation reduction following similar treatment of noncancerous MCF10A breast epithelial cells. Reduced phosphorylation of p107 and substantial reduction of Rb phosphorylation were observed in response. The effects of reduced Rb and p107 phosphorylation were reflected in significant decline in E2F-1 transcriptional activity, which is dependent on pocket protein phosphorylation status. The reduced proliferation was related to decreased expression of cyclins, including E2F-1-regulated Cyclin E2, which was also in response to raloxifene and PX-866. All combinations of raloxifene and PX-866 produced significant or highly significant results for reduced MCF-7 cell proliferation, reduced Cyclin E2 transcription, and reduced Rb phosphorylation. These studies demonstrated that uncontrolled proliferation of ER+ breast cancer cells can be significantly reduced by combinational targeting of two relevant pathways. J. Cell. Biochem. 117: 1688-1696, 2016. © 2015 Wiley Periodicals, Inc.

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.

The oncogenic FIP1L1-PDGFRα fusion protein displays skewed signaling properties compared to its wild-type PDGFRα counterpart

Aberrant activation of oncogenic kinases is frequently observed in human cancers, but the underlying mechanism and resulting effects on global signaling are incompletely understood. Here, we demonstrate that the oncogenic FIP1L1-PDGFRα kinase exhibits a significantly different signaling pattern compared to its PDGFRα wild type counterpart. Interestingly, the activation of primarily membrane-based signal transduction processes (such as PI3-kinase- and MAP-kinase- pathways) is remarkably shifted toward a prominent activation of STAT factors. This diverging signaling pattern compared to classical PDGF-receptor signaling is partially coupled to the aberrant cytoplasmic localization of the oncogene, since membrane targeting of FIP1L1-PDGFRα restores activation of MAPK- and PI3K-pathways. In stark contrast to the classical cytokine-induced STAT activation process, STAT activation by FIP1L1-PDGFRα does neither require Janus kinase activity nor Src kinase activity. Furthermore, we investigated the mechanism of STAT5 activation via FIP1L1-PDGFRα in more detail and found that STAT5 activation does not involve an SH2-domain-mediated binding mechanism. We thus demonstrate that STAT5 activation occurs via a non-canonical activation mechanism in which STAT5 may be subject to a direct phosphorylation by FIP1L1-PDGFRα.

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.

A co-association network analysis of the genetic determination of pig conformation, growth and fatness

BACKGROUND

Several QTLs have been identified for major economically relevant traits in livestock, such as growth and meat quality, revealing the complex genetic architecture of these traits. The use of network approaches considering the interactions of multiple molecules and traits provides useful insights into the molecular underpinnings of complex traits. Here, a network based methodology, named Association Weight Matrix, was applied to study gene interactions and pathways affecting pig conformation, growth and fatness traits.

RESULTS

The co-association network analysis underpinned three transcription factors, PPARγ, ELF1, and PRDM16 involved in mesoderm tissue differentiation. Fifty-four genes in the network belonged to growth-related ontologies and 46 of them were common with a similar study for growth in cattle supporting our results. The functional analysis uncovered the lipid metabolism and the corticotrophin and gonadotrophin release hormone pathways among the most important pathways influencing these traits. Our results suggest that the genes and pathways here identified are important determining either the total body weight of the animal and the fat content. For instance, a switch in the mesoderm tissue differentiation may determinate the age-related preferred pathways being in the puberty stage those related with the miogenic and osteogenic lineages; on the contrary, in the maturity stage cells may be more prone to the adipocyte fate. Hence, our results demonstrate that an integrative genomic co-association analysis is a powerful approach for identifying new connections and interactions among genes.

CONCLUSIONS

This work provides insights about pathways and key regulators which may be important determining the animal growth, conformation and body proportions and fatness traits. Molecular information concerning genes and pathways here described may be crucial for the improvement of genetic breeding programs applied to pork meat production.

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.

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.

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.

Network analysis: a new approach to study endocrine disorders

Systems biology is the study of the interactions that occur between the components of individual cells - including genes, proteins, transcription factors, small molecules, and metabolites, and their relationships to complex physiological and pathological processes. The application of systems biology to medicine promises rapid advances in both our understanding of disease and the development of novel treatment options. Network biology has emerged as the primary tool for studying systems biology as it utilises the mathematical analysis of the relationships between connected objects in a biological system and allows the integration of varied 'omic' datasets (including genomics, metabolomics, proteomics, etc.). Analysis of network biology generates interactome models to infer and assess function; to understand mechanisms, and to prioritise candidates for further investigation. This review provides an overview of network methods used to support this research and an insight into current applications of network analysis applied to endocrinology. A wide spectrum of endocrine disorders are included ranging from congenital hyperinsulinism in infancy, through childhood developmental and growth disorders, to the development of metabolic diseases in early and late adulthood, such as obesity and obesity-related pathologies. In addition to providing a deeper understanding of diseases processes, network biology is also central to the development of personalised treatment strategies which will integrate pharmacogenomics with systems biology of the individual.