Metabolomics Approach to Identify Molecules and Pathways Involved in the Development of Atherosclerotic Coronary Artery Disease
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ABSTRACT:
ORGANISM(S): Homo Sapiens
TISSUE(S): Blood
PROVIDER: ST000306 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
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Project description:BackgroundThe mesenchymal compartment plays a key role in organogenesis, and cells within the mesenchyme/stroma are a source of potent molecules that control epithelia during development and tumorigenesis. We used serial analysis of gene expression (SAGE) to profile a key subset of prostatic mesenchyme that regulates prostate development and is enriched for growth-regulatory molecules.ResultsSAGE libraries were constructed from prostatic inductive mesenchyme and from the complete prostatic rudiment (including inductive mesenchyme, epithelium, and smooth muscle). By comparing these two SAGE libraries, we generated a list of 219 transcripts that were enriched or specific to inductive mesenchyme and that may act as mesenchymal regulators of organogenesis and tumorigenesis. We identified Scube1 as enriched in inductive mesenchyme from the list of 219 transcripts; also, quantitative RT-PCR and whole-mount in situ hybridization revealed Scube1 to exhibit a highly restricted expression pattern. The expression of Scube1 in a subset of mesenchymal cells suggests a role in prostatic induction and branching morphogenesis. Additionally, Scube1 transcripts were expressed in prostate cancer stromal cells, and were less abundant in cancer associated fibroblasts relative to matched normal prostate fibroblasts.ConclusionThe use of a precisely defined subset of cells and a back-comparison approach allowed us to identify rare mRNAs that could be overlooked using other approaches. We propose that Scube1 encodes a novel stromal molecule that is involved in prostate development and tumorigenesis.
| S-EPMC2246287 | biostudies-literature
Project description:Erythrocytosis is a blood disorder characterised by an increased red blood cell mass. The most common causes of erythrocytosis are acquired and caused by diseases and conditions that are accompanied by hypoxaemia or overproduction of erythropoietin. More rarely, erythrocytosis has a known genetic background, such as for polycythaemia vera and familial erythrocytosis. The majority of cases of polycythaemia vera are associated with acquired variants in JAK2, while familial erythrocytosis is a group of congenital disorders. Familial erythrocytosis type 1 is associated with hypersensitivity to erythropoietin (variants in EPOR), types 2-5 with defects in oxygen-sensing pathways (variants in VHL, EGLN1, EPAS1, EPO), and types 6-8 with an increased affinity of haemoglobin for oxygen (variants in HBB, HBA1, HBA2, BPGM). Due to a heterogenic genetic background, the causes of disease are not fully discovered and in more than 70% of patients the condition remains labelled idiopathic.The transfer of next-generation sequencing into clinical practice is becoming a reality enabling detection of various variants in a single rapid test. In this review, we describe the current research on erythrocytosis gene variants and the mechanisms associated with disease development, along with the currently used diagnostic tests.
| S-EPMC8580782 | biostudies-literature
Project description:BackgroundWe have made use of publicly available gene expression data to identify transcription factors and transcriptional modules (regulons) associated with leaf development in Populus. Different tissue types were compared to identify genes informative in the discrimination of leaf and non-leaf tissues. Transcriptional modules within this set of genes were identified in a much wider set of microarray data collected from leaves in a number of developmental, biotic, abiotic and transgenic experiments.ResultsTranscription factors that were over represented in leaf EST libraries and that were useful for discriminating leaves from other tissues were identified, revealing that the C2C2-YABBY, CCAAT-HAP3 and 5, MYB, and ZF-HD families are particularly important in leaves. The expression of transcriptional modules and transcription factors was examined across a number of experiments to select those that were particularly active during the early stages of leaf development. Two transcription factors were found to collocate to previously published Quantitative Trait Loci (QTL) for leaf length. We also found that miRNA family 396 may be important in the control of leaf development, with three members of the family collocating with clusters of leaf development QTL.ConclusionThis work provides a set of candidate genes involved in the control and processes of leaf development. This resource can be used for a wide variety of purposes such as informing the selection of candidate genes for association mapping or for the selection of targets for reverse genetics studies to further understanding of the genetic control of leaf size and shape.
| S-EPMC2621207 | biostudies-literature
Project description:Background Field observations and a few physiological studies pointed out that peach embryogenesis and fruit development are strictly related. In fact, attempts to stimulate parthenocarpic fruit development by means of external tools failed. Moreover, physiological disturbances during the early embryo development lead to seed abortion and fruitlet abscission. Later on, the interactions between seed and fruit development become less stringent. Genetic and molecular information about seed and fruit development in peach is limited. Results The isolation of 455 genes differentially expressed in seed and fruit was done by means of a comparative analysis of the transcription profiles carried out in peach (Prunus persica, cv Fantasia) seed and mesocarp throughout development by means of µPEACH 1.0, the first peach microarray. Genes differentially expressed in the two organs and specific of developmental stages had been identified, and some were validated as markers. Genes representative of the main functional categories are present, among which several transcription factors such as MADS-box, bZIP, Aux/IAA, AP2, WRKY, and HD. Some of these showed a similar transcription profile in the two organs, while others displayed an opposite pattern, being more expressed in embryo at early development and in mesocarp at ripening. Conclusions The µPEACH1.0, although developed from ripe fruit ESTs, resulted in being suitable for studying seed/mesocarp interactions. Among the differentially expressed genes, marker genes specific for organ and stage of development have been selected.
2011-06-27 | GSE22582 | GEO
Project description:BackgroundField observations and a few physiological studies have demonstrated that peach embryogenesis and fruit development are tightly coupled. In fact, attempts to stimulate parthenocarpic fruit development by means of external tools have failed. Moreover, physiological disturbances during early embryo development lead to seed abortion and fruitlet abscission. Later in embryo development, the interactions between seed and fruit development become less strict. As there is limited genetic and molecular information about seed-pericarp cross-talk and development in peach, a massive gene approach based on the use of the μPEACH 1.0 array platform and quantitative real time RT-PCR (qRT-PCR) was used to study this process.ResultsA comparative analysis of the transcription profiles conducted in seed and mesocarp (cv Fantasia) throughout different developmental stages (S1, S2, S3 and S4) evidenced that 455 genes are differentially expressed in seed and fruit. Among differentially expressed genes some were validated as markers in two subsequent years and in three different genotypes. Seed markers were a LTP1 (lipid transfer protein), a PR (pathogenesis-related) protein, a prunin and LEA (Late Embryogenesis Abundant) protein, for S1, S2, S3 and S4, respectively. Mesocarp markers were a RD22-like protein, a serin-carboxypeptidase, a senescence related protein and an Aux/IAA, for S1, S2, S3 and S4, respectively.The microarray data, analyzed by using the HORMONOMETER platform, allowed the identification of hormone-responsive genes, some of them putatively involved in seed-pericarp crosstalk. Results indicated that auxin, cytokinins, and gibberellins are good candidates, acting either directly (auxin) or indirectly as signals during early development, when the cross-talk is more active and vital for fruit set, whereas abscisic acid and ethylene may be involved later on.ConclusionsIn this research, genes were identified marking different phases of seed and mesocarp development. The selected genes behaved as good seed markers, while for mesocarp their reliability appeared to be dependent upon developmental and ripening traits. Regarding the cross-talk between seed and pericarp, possible candidate signals were identified among hormones.Further investigations relying upon the availability of whole genome platforms will allow the enrichment of a marker genes repertoire and the elucidation of players other than hormones that are involved in seed-pericarp cross-talk (i.e. hormone peptides and microRNAs).
| S-EPMC3141638 | biostudies-literature
Project description:BackgroundCoronary artery disease (CAD) is one of the most common causes of sudden death with high morbidity in recent years. This paper is aimed at exploring the early peripheral blood biomarkers of sudden death and providing a new perspective for clinical diagnosis and forensic pathology identification by integrated bioinformatics analysis.MethodsTwo microarray expression profiling datasets (GSE113079 and GSE31568) were downloaded from the Gene Expression Omnibus (GEO) database, and we identified differentially expressed lncRNAs, miRNAs, and mRNAs in CAD. Gene Ontology (GO) and KEGG pathway analyses of DEmRNAs were executed. A protein-protein interaction (PPI) network was constructed, and hub genes were identified. Finally, we constructed a competitive endogenous RNA (ceRNA) regulation network among lncRNAs, miRNAs, and mRNAs. Also, the 5 miRNAs of the ceRNA network were verified by RT-PCR.ResultsIn total, 86 DElncRNAs, 148 DEmiRNAs, and 294 DEmRNAs were dysregulated in CAD. We received 12 GO terms and 5 pathways of DEmRNAs. 31 nodes and 78 edges were revealed in the PPI network. The top 10 genes calculated by degree method were identified as hub genes. Moreover, there were a total of 26 DElncRNAs, 5 DEmiRNAs, and 13 DEmRNAs in the ceRNA regulation network. We validated the 5 miRNAs of the ceRNA network by RT-PCR, which were consistent with the results of the microarray.ConclusionsIn this paper, a CAD-specific ceRNA network was successfully constructed, contributing to the understanding of the relationship among lncRNAs, miRNAs, and mRNAs. We identified potential peripheral blood biomarkers in CAD and provided novel insights into the development and progress of CAD.
| S-EPMC7822659 | biostudies-literature
Project description:Huntington disease (HD) is a degenerative brain disease caused by the expansion of CAG (cytosine-adenine-guanine) repeats, which is inherited as a dominant trait and progressively worsens over time possessing threat. Although HD is monogenetic, the specific pathophysiology and biomarkers are yet unknown specifically, also, complex to diagnose at an early stage, and identification is restricted in accuracy and precision. This study combined bioinformatics analysis and network-based system biology approaches to discover the biomarker, pathways, and drug targets related to molecular mechanism of HD etiology. The gene expression profile data sets GSE64810 and GSE95343 were analyzed to predict the molecular markers in HD where 162 mutual differentially expressed genes (DEGs) were detected. Ten hub genes among them (DUSP1, NKX2-5, GLI1, KLF4, SCNN1B, NPHS1, SGK2, PITX2, S100A4, and MSX1) were identified from protein-protein interaction (PPI) network which were mostly expressed as down-regulated. Following that, transcription factors (TFs)-DEGs interactions (FOXC1, GATA2, etc), TF-microRNA (miRNA) interactions (hsa-miR-340, hsa-miR-34a, etc), protein-drug interactions, and disorders associated with DEGs were predicted. Furthermore, we used gene set enrichment analysis (GSEA) to emphasize relevant gene ontology terms (eg, TF activity, sequence-specific DNA binding) linked to DEGs in HD. Disease interactions revealed the diseases that are linked to HD, and the prospective small drug molecules like cytarabine and arsenite was predicted against HD. This study reveals molecular biomarkers at the RNA and protein levels that may be beneficial to improve the understanding of molecular mechanisms, early diagnosis, as well as prospective pharmacologic targets for designing beneficial HD treatment.
| S-EPMC10683407 | biostudies-literature
Project description:BackgroundMany reptiles exhibit temperature-dependent sex determination (TSD). The initial cue in TSD is incubation temperature, unlike genotypic sex determination (GSD) where it is determined by the presence of specific alleles (or genetic loci). We used patterns of gene expression to identify candidates for genes with a role in TSD and other developmental processes without making a priori assumptions about the identity of these genes (ortholog-based approach). We identified genes with sexually dimorphic mRNA accumulation during the temperature sensitive period of development in the Red-eared slider turtle (Trachemys scripta), a turtle with TSD. Genes with differential mRNA accumulation in response to estrogen (estradiol-17β; E(2)) exposure and developmental stages were also identified.ResultsSequencing 767 clones from three suppression-subtractive hybridization libraries yielded a total of 581 unique sequences. Screening a macroarray with a subset of those sequences revealed a total of 26 genes that exhibited differential mRNA accumulation: 16 female biased and 10 male biased. Additional analyses revealed that C16ORF62 (an unknown gene) and MALAT1 (a long noncoding RNA) exhibited increased mRNA accumulation at the male producing temperature relative to the female producing temperature during embryonic sexual development. Finally, we identified four genes (C16ORF62, CCT3, MMP2, and NFIB) that exhibited a stage effect and five genes (C16ORF62, CCT3, MMP2, NFIB and NOTCH2) showed a response to E(2) exposure.ConclusionsHere we report a survey of genes identified using patterns of mRNA accumulation during embryonic development in a turtle with TSD. Many previous studies have focused on examining the turtle orthologs of genes involved in mammalian development. Although valuable, the limitations of this approach are exemplified by our identification of two genes (MALAT1 and C16ORF62) that are sexually dimorphic during embryonic development. MALAT1 is a noncoding RNA that has not been implicated in sexual differentiation in other vertebrates and C16ORF62 has an unknown function. Our results revealed genes that are candidates for having roles in turtle embryonic development, including TSD, and highlight the need to expand our search parameters beyond protein-coding genes.
| S-EPMC3434017 | biostudies-literature
Project description:IntroductionMultiple trials have demonstrated broad performance ranges for tests attempting to detect coronary artery disease. The most common test, SPECT, requires capital-intensive equipment, the use of radionuclides, induction of stress, and time off work and/or travel. Presented here are the development and clinical validation of an office-based machine learned algorithm to identify functionally significant coronary artery disease without radiation, expensive equipment or induced patient stress.Materials and methodsThe IDENTIFY trial (NCT03864081) is a prospective, multicenter, non-randomized, selectively blinded, repository study to collect acquired signals paired with subject meta-data, including outcomes, from subjects with symptoms of coronary artery disease. Time synchronized orthogonal voltage gradient and photoplethysmographic signals were collected for 230 seconds from recumbent subjects at rest within seven days of either left heart catheterization or coronary computed tomography angiography. Following machine learning on a proportion of these data (N = 2,522), a final algorithm was selected, along with a pre-specified cut point on the receiver operating characteristic curve for clinical validation. An unseen set of subject signals (N = 965) was used to validate the algorithm.ResultsAt the pre-specified cut point, the sensitivity for detecting functionally significant coronary artery disease was 0.73 (95% CI: 0.68-0.78), and the specificity was 0.68 (0.62-0.74). There exists a point on the receiver operating characteristic curve at which the negative predictive value is the same as coronary computed tomographic angiography, 0.99, assuming a disease incidence of 0.04, yielding sensitivity of 0.89 and specificity of 0.42. Selecting a point at which the positive predictive value is maximized, 0.12, yields sensitivity of 0.39 and specificity of 0.88.ConclusionThe performance of the machine learned algorithm presented here is comparable to common tertiary center testing for coronary artery disease. Employing multiple cut points on the receiver operating characteristic curve can yield the negative predictive value of coronary computed tomographic angiography and a positive predictive value approaching that of myocardial perfusion imaging. As such, a system employing this algorithm may address the need for a non-invasive, no radiation, no stress, front line test, and hence offer significant advantages to the patient, their physician, and healthcare system.
| S-EPMC9481304 | biostudies-literature
Project description:Background Field observations and a few physiological studies pointed out that peach embryogenesis and fruit development are strictly related. In fact, attempts to stimulate parthenocarpic fruit development by means of external tools failed. Moreover, physiological disturbances during the early embryo development lead to seed abortion and fruitlet abscission. Later on, the interactions between seed and fruit development become less stringent. Genetic and molecular information about seed and fruit development in peach is limited. Results The isolation of 455 genes differentially expressed in seed and fruit was done by means of a comparative analysis of the transcription profiles carried out in peach (Prunus persica, cv Fantasia) seed and mesocarp throughout development by means of µPEACH 1.0, the first peach microarray. Genes differentially expressed in the two organs and specific of developmental stages had been identified, and some were validated as markers. Genes representative of the main functional categories are present, among which several transcription factors such as MADS-box, bZIP, Aux/IAA, AP2, WRKY, and HD. Some of these showed a similar transcription profile in the two organs, while others displayed an opposite pattern, being more expressed in embryo at early development and in mesocarp at ripening. Conclusions The µPEACH1.0, although developed from ripe fruit ESTs, resulted in being suitable for studying seed/mesocarp interactions. Among the differentially expressed genes, marker genes specific for organ and stage of development have been selected. Comparisons were carried out by pooling stage 1 and 2 (named early development, e) and stage 3 and 4 (named late development, l), separately for mesocarp (M) and seed (S) of cultivar Fantasia, and using a simple loop experimental design. RNA has been extracted from fruit harvest at above-mentioned stages of development. At least four hybridizations have been conducted for a total of four technical replicates (with dye-swap).
2011-06-27 | E-GEOD-22582 | biostudies-arrayexpress