Isolated GnRH deficiency: a disease model serving as a unique prism into the systems biology of the GnRH neuronal network.
Ontology highlight
ABSTRACT:
SUBMITTER: Balasubramanian R
PROVIDER: S-EPMC3226734 | biostudies-literature | 2011 Oct
REPOSITORIES: biostudies-literature
Publications
Isolated GnRH deficiency: a disease model serving as a unique prism into the systems biology of the GnRH neuronal network.
Balasubramanian Ravikumar R Crowley William F WF
Molecular and cellular endocrinology 20110712 1-2
Similar Datasets
Project description:Evolutionary survival of a species is largely a function of its reproductive fitness. In mammals, a sparsely populated and widely dispersed network of hypothalamic neurons, the gonadotropin-releasing hormone (GnRH) neurons, serve as the pilot light of reproduction via coordinated secretion of GnRH. Since it first description, human GnRH deficiency has been recognized both clinically and genetically as a heterogeneous disease. A spectrum of different reproductive phenotypes comprised of congenital GnRH deficiency with anosmia (Kallmann syndrome), congenital GnRH deficiency with normal olfaction (normosmic idiopathic hypogonadotropic hypogonadism), and adult-onset hypogonadotropic hypogonadism has been described. In the last two decades, several genes and pathways which govern GnRH ontogeny have been discovered by studying humans with GnRH deficiency. More importantly, detailed study of these patients has highlighted the emerging theme of oligogenicity and genotypic synergism, and also expanded the phenotypic diversity with the documentation of reversal of GnRH deficiency later in adulthood in some patients. The underlying genetic defect has also helped understand the associated nonreproductive phenotypes seen in some of these patients. These insights now provide practicing clinicians with targeted genetic diagnostic strategies and also impact on clinical management.
| S-EPMC3214927 | biostudies-literature
Project description:Inactivating mutations in chromodomain helicase DNA binding protein 7 (CHD7) cause CHARGE syndrome, a severe multiorgan system disorder of which Isolated gonadotropin-releasing hormone (GnRH) deficiency (IGD) is a minor feature. Recent reports have described predominantly missense CHD7 alleles in IGD patients, but it is unclear if these alleles are relevant to causality or overall genetic burden of Kallmann syndrome (KS) and normosmic form of IGD. To address this question, we sequenced CHD7 in 783 well-phenotyped IGD patients lacking full CHARGE features; we identified nonsynonymous rare sequence variants in 5.2% of the IGD cohort (73% missense and 27% splice variants). Functional analyses in zebrafish using a surrogate otolith assay of a representative set of these CHD7 alleles showed that rare sequence variants observed in controls showed no altered function. In contrast, 75% of the IGD-associated alleles were deleterious and resulted in both KS and normosmic IGD. In two families, pathogenic mutations in CHD7 coexisted with mutations in other known IGD genes. Taken together, our data suggest that rare deleterious CHD7 alleles contribute to the mutational burden of patients with both KS and normosmic forms of IGD in the absence of full CHARGE syndrome. These findings (i) implicate a unique role or preferential sensitivity for CHD7 in the ontogeny of GnRH neurons, (ii) reiterate the emerging genetic complexity of this family of IGD disorders, and (iii) demonstrate how the coordinated use of well-phenotyped cohorts, families, and functional studies can inform genetic architecture and provide insights into the developmental biology of cellular systems.
| S-EPMC4273325 | biostudies-literature
Project description: Not available
| S-EPMC5881574 | biostudies-literature
Project description:This Teaching Resource provides lecture notes, slides, and a problem set for a set of three lectures from a course entitled "Systems Biology: Biomedical Modeling." The materials are from three separate lectures introducing applications of graph theory and network analysis in systems biology. The first lecture describes different types of intracellular networks, methods for constructing biological networks, and different types of graphs used to represent regulatory intracellular networks. The second lecture surveys milestones and key concepts in network analysis by introducing topological measures, random networks, growing network models, and topological observations from molecular biological systems abstracted to networks. The third lecture discusses methods for analyzing lists of genes and experimental data in the context of prior knowledge networks to make predictions.
| S-EPMC3196357 | biostudies-literature
Project description:BackgroundA goal of systems biology is the quantitative modelling of biochemical networks. Yet for many biochemical systems, parameter values and even the existence of interactions between some chemical species are unknown. It is therefore important to be able to easily investigate the effects of adding or removing reactions and to easily perform a bifurcation analysis, which shows the qualitative dynamics of a model for a range of parameter values.ResultsWe present Facile, a Perl command-line tool for analysing the dynamics of a systems biology model. Facile implements the law of mass action to automatically compile a biochemical network (written as, for example, E + S <-> C) into scripts for analytical analysis (Mathematica and Maple), for simulation (XPP and Matlab), and for bifurcation analysis (AUTO). Facile automatically identifies mass conservations and generates the reduced form of a model with the minimum number of independent variables. This form is essential for bifurcation analysis, and Facile produces a C version of the reduced model for AUTO.ConclusionFacile is a simple, yet powerful, tool that greatly accelerates analysis of the dynamics of a biochemical network. By acting at the command-line and because of its intuitive, text-based input, Facile is quick to learn and can be incorporated into larger programs or into automated tasks.
| S-EPMC1976619 | biostudies-literature
Project description:Evidence suggests that psychosexuality in humans is modulated by both organizational effects of prenatal and peripubertal sex steroid hormones, and by activational effects of circulating hormones in adulthood. Experimental work in male rodents indicates that sensitivity to androgen-driven organization of sexual motivation decreases across the pubertal window, such that earlier puberty leads to greater sex-typicality. We test this hypothesis in typically developing men (n = 231) and women (n = 648), and in men (n = 72) and women (n = 32) with isolated GnRH deficiency (IGD), in whom the precise timing of peripubertal hormone exposure can be ascertained via the age at which hormone replacement therapy (HRT) was initiated. Psychosexuality was measured with the Sexual Desire Inventory-2 (SDI-2) and Sociosexual Orientation Inventory-Revised (SOI-R). In both sexes, earlier recalled absolute pubertal timing predicted higher psychosexuality in adulthood, although the magnitude of these associations varied with psychosexuality type and group (i.e., typically developing and IGD). Results were robust when controlling for circulating steroid hormones in typically developing participants. Age of initiation of HRT in men with IGD negatively predicted SOI-R. We discuss the clinical implications of our findings for conditions in which pubertal timing is medically altered.
| S-EPMC8938930 | biostudies-literature
Project description:One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1) network visualization tools, (2) pathway analyses, (3) genome-scale metabolic reconstruction, and (4) the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms.
| S-EPMC4219401 | biostudies-literature
Project description:A major challenge in human genetics is the validation of pathogenicity of heterozygous missense variants. This problem is well-illustrated by PROKR2 variants associated with Isolated GnRH Deficiency (IGD). Homozygous, loss of function variants in PROKR2 was initially implicated in autosomal recessive IGD; however, most IGD-associated PROKR2 variants are heterozygous. Moreover, while IGD patient cohorts are enriched for PROKR2 missense variants similar rare variants are also found in normal individuals. To elucidate the pathogenic mechanisms distinguishing IGD-associated PROKR2 variants from rare variants in controls, we assessed 59 variants using three approaches: (i) in silico prediction, (ii) traditional in vitro functional assays across three signaling pathways with mutant-alone transfections, and (iii) modified in vitro assays with mutant and wild-type expression constructs co-transfected to model in vivo heterozygosity. We found that neither in silico analyses nor traditional in vitro assessments of mutants transfected alone could distinguish IGD variants from control variants. However, in vitro co-transfections revealed that 15/34 IGD variants caused loss-of-function (LoF), including 3 novel dominant-negatives, while only 4/25 control variants caused LoF. Surprisingly, 19 IGD-associated variants were benign or exhibited LoF that could be rescued by WT co-transfection. Overall, variants that were LoF in ≥ 2 signaling assays under co-transfection conditions were more likely to be disease-associated than benign or 'rescuable' variants. Our findings suggest that in vitro modeling of WT/Mutant interactions increases the resolution for identifying causal variants, uncovers novel dominant negative mutations, and provides new insights into the pathogenic mechanisms underlying heterozygous PROKR2 variants.
| S-EPMC5886255 | biostudies-literature
Project description:β-Peptoids are peptidomimetics based on N-alkylated β-aminopropionic acid residues (or N-alkyl-β-alanines). This type of peptide mimic has previously been incorporated in biologically active ligands and has been hypothesized to be able to exhibit foldamer properties. Here we show, for the first time, that β-peptoids can be tuned to fold into stable helical structures. We provide high-resolution X-ray crystal structures of homomeric β-peptoid hexamers, which reveal right-handed helical conformations with exactly three residues per turn and a helical pitch of 9.6-9.8 Å between turns. The presence of folded conformations in solution is supported by circular dichroism spectroscopy showing length- and solvent dependency, and molecular dynamics simulations provide further support for a stabilized helical secondary structure in organic solvent. We thus outline a framework for future design of novel biomimetics that display functional groups with high accuracy in three dimensions, which has potential for development of new functional materials.
| S-EPMC4432622 | biostudies-literature
Project description:In this work, we integrated prior knowledge from gene signatures and protein interactions with gene set enrichment analysis (GSEA), and gene/protein network modeling together to identify gene network signatures from gene expression microarray data. We demonstrated how to apply this approach into discovering gene network signatures for colorectal cancer (CRC) from microarray datasets. First, we used GSEA to analyze the microarray data through enriching differential genes in different CRC-related gene sets from two publicly available up-to-date gene set databases - Molecular Signatures Database (MSigDB) and Gene Signatures Database (GeneSigDB). Second, we compared the enriched gene sets through enrichment score, false-discovery rate, and nominal p-value. Third, we constructed an integrated protein-protein interaction (PPI) network through connecting these enriched genes by high-quality interactions from a human annotated and predicted protein interaction database, with a confidence score labeled for each interaction. Finally, we mapped differential gene expressions onto the constructed network to build a comprehensive network model containing visualized transcriptome and proteome data. The results show that although MSigDB has more CRC-relevant gene sets than GeneSigDB, the integrated PPI network connecting the enriched genes from both MSigDB and GeneSigDB can provide a more complete view for discovering gene network signatures. We also found several important sub-network signatures for CRC, such as TP53 sub-network, PCNA sub-network, and IL8 sub-network, corresponding to apoptosis, DNA repair, and immune response, respectively.
| S-EPMC3354560 | biostudies-literature