MiRseq-PRT1D
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB58187 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR10682109.fastq.gz | Fastqsanger.gz | |||
| ERR10682110.fastq.gz | Fastqsanger.gz | |||
| ERR10682111.fastq.gz | Fastqsanger.gz | |||
| ERR10682112.fastq.gz | Fastqsanger.gz | |||
| ERR10682113.fastq.gz | Fastqsanger.gz |
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Project description:Type 1 diabetes is a progressive autoimmune disease with unknown etiology. Although the destruction of β-cells is recognized as an irreversible process, many type 1 diabetes patients experience the partial remission stage characterized by spontaneous and transient recovery of β-cell function. However, a comprehensive understanding of immune disturbances in the progression of type 1 diabetes as well as the immunological mechanisms responsible for the partial remission stage remains to be elucidated.
2024-01-18 | GSE221297 | GEO
Project description:Partial remission (PR) occurs in only half of patients with new-onset type 1 diabetes (T1D) and correspond to a transient period characterized by low daily insulin needs, low glycemic fluctuations and increased endogenous insulin secretion. While identification of newly-onset T1D patients with significant residual beta-cell function may foster patient-specific interventions, reliable predictive biomarkers of PR occurrence currently lack. We analyzed the plasma of children with new-onset T1D to identify biomarkers present at diagnosis that predicted PR at 3 months post-diagnosis. We first performed an extensive shotgun proteomic analysis using Liquid Chromatography-Tandem-Mass-Spectrometry (LCMS/MS) on the plasma of 16 children with new-onset T1D and quantified nearly 1500 unique proteins with 98 significantly correlating with Insulin-Dose Adjusted glycated hemoglobin A1c score (IDAA1C). We next applied a series of both qualitative and statistical filters that yielded to the selection of 26 protein candidates that were associated to pathophysiological mechanisms related to T1D. Finally, we translationally validated several of the candidates using single-shot targeted proteomic (PRM method) on raw plasma. Taken together, we identified plasmatic biomarkers present at diagnosis that may predict the occurrence of PR in a single mass-spectrometry run. We believe that the identification of new predictive biomarkers of PR and β-cell function is key to stratify patients with new-onset T1D for β-cell preservation therapies
2024-04-05 | PXD049795 | Pride
Project description:Biomarkers are needed to accurately predict and monitor type 1 diabetes progression during the substantially heterogeneous presymptomatic period of the disease development. To address this concern, we studied temporal changes in the plasma and serum proteomes of < 5-year-old children with HLA-conferred risk for type 1 diabetes by analysing longitudinal sample series that were collected at regular intervals between birth and diagnosis. Using mass spectrometry-based discovery proteomics, longitudinal plasma sample series from multiple autoantibody positive children who had rapidly progressed to type 1 diabetes before 4 years of age were analysed and compared with similar measurements from age and gender matched children who were either single autoantibody positive or autoantibody negative. Following analysis of the data with an additive Gaussian process regression model (LonGP), targeted proteomics was used to verify 11 biomarker candidates in a larger independent yet similar cohort of children with more frequent sampling points. The data reiterated extensive age related trends for protein levels in young children. Further, by combining the utility of LonGP together with the targeted analysis in an extended cohort, these analyses demonstrated that the serum levels of two peptides unique for apolipoprotein C1 (APOC1) were decreased after the appearance of the first autoantibody and remained relatively less abundant in children who progressed to type 1 diabetes in comparison to autoantibody negative children.
2023-09-26 | PXD033744 | Pride
Project description:OBJECTIVE: Novel biomarkers of disease progression after type 1 diabetes onset are needed. RESEARCH DESIGN AND METHODS: We profiled peripheral blood (PB) monocyte gene expression in 6 healthy subjects and 16 children with type 1 diabetes diagnosed ~3 months previously, and analyzed clinical features from diagnosis to 1 year. RESULTS: Monocyte expression profiles clustered into two distinct subgroups, representing mild and severe deviation from healthy controls, along the same continuum. Patients with strongly divergent monocyte gene expression had significantly higher insulin dose-adjusted HbA1c levels during the first year, compared to patients with mild deviation. The diabetes-associated expression signature identified multiple perturbations in pathways controlling cellular metabolism and survival, including endoplasmic reticulum and oxidative stress (e.g. induction of HIF1A, DDIT3, DDIT4 and GRP78). qPCR quantitation of a 9-gene panel correlated with glycaemic control in 12 additional recent-onset patients. The qPCR signature was also detected in PB from healthy first-degree relatives. CONCLUSIONS: A PB gene expression signature correlates with glycaemic control in the first year after diabetes diagnosis, and is present in at-risk subjects. These findings implicate monocyte phenotype as a candidate biomarker for disease progression pre- and post-onset, and systemic stresses as contributors to innate immune function in type 1 diabetes. CD14+ monocytes from a total of 16 children with recent-onset type 1 diabetes and 6 adult healthy controls were profiled in 2 independent microarrays.
2012-05-31 | E-GEOD-33440 | biostudies-arrayexpress
Project description:Aims/hypothesis: Biomarkers are needed to accurately predict and monitor type 1 diabetes progression during the substantially heterogeneous presymptomatic period of the disease development. To address this concern, we studied temporal changes in the plasma and serum proteomes of < 5-year-old children with HLA-conferred risk for type 1 diabetes, by analysing longitudinal sample series that were collected at regular intervals between birth and diagnosis.
Methods: Using mass spectrometry-based discovery proteomics, longitudinal sample series from children positive for multiple autoantibodies who had rapidly progressed to type 1 diabetes before 4 years of age (n=10) were analysed and compared with similar measurements from children, matched from age and gender who were either positive for single autoantibody (n=10) or autoantibody negative (n=10). Following analysis of the data with an additive Gaussian process regression model (LonGP), targeted proteomics was used to verify 11 biomarker candidates in a similar yet independent cohort of children who progressed to the disease within 5 years of age (n=31) and matched autoantibody negative children (n=31).
Results: These data reiterated extensive age related trends for protein levels in young children. Further, by combining the utility of LonGP together with the targeted analysis in an extended cohort with more frequent sampling points, these analysis demonstrated that the serum levels of two peptides unique for apolipoprotein C1 (APOC1) were decreased after the appearance of the first islet autoantibody and remained relatively less abundant in children who later progressed to type 1 diabetes, in comparison to autoantibody negative children.
Conclusions/interpretation: Through the comparative analysis of prospectively collected samples, our data indicate that the serum/plasma levels of APOC1 are decreased in islet autoantibody positive children who develop type 1 diabetes at a young age. In future studies, APOC1 could be used as an additional measurement to improve early prediction of type 1 diabetes and selection of subjects for intervention studies.
2023-10-02 | PXD033946 | panorama
Project description:Neutrophils in children with the polyarticular form of juvenile idiopathic arthritis (JIA) display abnormal transcriptional patterns linked to fundamental metabolic derangements. These abnormalities include re-ordering of miRNA-RNA expression networks. In this study, we sought to determine the effects of therapy on miRNA-RNA networks in polyarticular JIA. We studied children with active JIA disease on therapy (ADM), children with inactive disease also on therapy (ID), and children with clinical remission on medication (CRM) using exon and miRNA microarrays and compared results to findings from healthy control (HC) children. We found substantial re-ordering of miRNA-RNA networks after the initiation of therapy. Each disease state was associated with a distinct transcriptional profile.
2017-02-01 | GSE94354 | GEO
Project description:<h4><strong>AIMS/HYPOTHESIS: </strong>Metabolic dysregulation may precede the onset of type 1 diabetes. However, these metabolic disturbances and their specific role in disease initiation remain poorly understood. In this study, we examined whether children who progress to type 1 diabetes have a circulatory polar metabolite profile distinct from that of children who later progress to islet autoimmunity but not type 1 diabetes and a matched control group.</h4><h4><strong>METHODS: </strong>We analysed polar metabolites from 415 longitudinal plasma samples in a prospective cohort of children in three study groups: those who progressed to type 1 diabetes; those who seroconverted to one islet autoantibody but not to type 1 diabetes; and an antibody-negative control group. Metabolites were measured using two-dimensional GC high-speed time of flight MS.</h4><h4><strong>RESULTS: </strong>In early infancy, progression to type 1 diabetes was associated with downregulated amino acids, sugar derivatives and fatty acids, including catabolites of microbial origin, compared with the control group. Methionine remained persistently upregulated in those progressing to type 1 diabetes compared with the control group and those who seroconverted to one islet autoantibody. The appearance of islet autoantibodies was associated with decreased glutamic and aspartic acids.</h4><h4><strong>CONCLUSIONS/INTERPRETATION: </strong>Our findings suggest that children who progress to type 1 diabetes have a unique metabolic profile, which is, however, altered with the appearance of islet autoantibodies. Our findings may assist with early prediction of the disease.</h4>
2022-01-19 | MTBLS802 | MetaboLights
Project description:OBJECTIVE: Novel biomarkers of disease progression after type 1 diabetes onset are needed. RESEARCH DESIGN AND METHODS: We profiled peripheral blood (PB) monocyte gene expression in 6 healthy subjects and 16 children with type 1 diabetes diagnosed ~3 months previously, and analyzed clinical features from diagnosis to 1 year. RESULTS: Monocyte expression profiles clustered into two distinct subgroups, representing mild and severe deviation from healthy controls, along the same continuum. Patients with strongly divergent monocyte gene expression had significantly higher insulin dose-adjusted HbA1c levels during the first year, compared to patients with mild deviation. The diabetes-associated expression signature identified multiple perturbations in pathways controlling cellular metabolism and survival, including endoplasmic reticulum and oxidative stress (e.g. induction of HIF1A, DDIT3, DDIT4 and GRP78). qPCR quantitation of a 9-gene panel correlated with glycaemic control in 12 additional recent-onset patients. The qPCR signature was also detected in PB from healthy first-degree relatives. CONCLUSIONS: A PB gene expression signature correlates with glycaemic control in the first year after diabetes diagnosis, and is present in at-risk subjects. These findings implicate monocyte phenotype as a candidate biomarker for disease progression pre- and post-onset, and systemic stresses as contributors to innate immune function in type 1 diabetes.
2012-06-01 | GSE33440 | GEO
Project description:Children with newly diagnosed ITP that after 12 month enter remission, shows molecular separate entities. The molecular basis for remission and tolerance induction is characterized by gene transcriptional profiling Global gene expression profile in isolated T-cells from 6 children with newly diagnosed ITP and after 12 month when they enter remission
2016-02-06 | E-GEOD-56232 | biostudies-arrayexpress
Project description:Sleeve gastrectomy (SG) could improve diabetes mellitus dramatically. However, the mechanisms remain largely undetermined. With the advancement of in-depth bioinformatic analysis, non-coding RNAs especially long non-coding RNAs(lncRNAs), have been implicated in many biological processes. To explore whether lncRNAs mediate the amelioration of diabetes mellitus condition after SG, we subjected liver samples of diabetic rats after SG and shame operations for RNA sequencing. Further, interaction network between lncRNAs and mRNAs/microRNAs(miRNAs) were constructed to infer the function of lncRNAs in diabetic remission, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Through RNA sequencing, we identified more than 9000 lncRNAs with a dramatically differentially expressed profile of 147 lncRNAs. Some of these specific lncRNAs were only expressed in diabetic rats after SG, which may be promising biological markers of diabetic remission and SG prognosis. Through co-analysis between lncRNAs and mRNAs, 20 potential target genes of lncRNAs were screened out. Further bioinformatic analysis indicated the differentially expressed lncRNAs harbored various miRNAs binding sites and three representative lncRNA-miRNA networks of lnc50 and lnc136 were constructed. The KEGG analysis revealed that differential expressed lncRNAs were mainly related to mitogen-activated protein kinase (MAPK) pathway. These results demonstrated that SG dramatically altered expression profile of lncRNAs on diabetes mellitus, and altered lncRNAs expression may contribute to the improvement on diabetic remission through MAPK pathway by interaction with mRNA/miRNA. Our findings provide valuable resources for molecular mechanism of diabetic remission after SG and is benefit for development of lncRNAs-based diagnostic and therapeutic interventions of diabetes mellitus.
2023-11-23 | GSE162018 | GEO