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Temporal Expression Profiling of Plasma Proteins in Type 1 Diabetes Progression

ABSTRACT: A longitudinal proteomic profiling of human plasma using TMT-10plex-based LC-MS/MS analysis was performed to track temporal proteomic changes of T1D patients (n = 11) across 9 serial time points, spanning the period of T1D natural progression, in comparison with those of the matching healthy controls (n = 10). Longitudinal expression profiles of >2000 human plasma proteins in T1D natural progression were presented in the current study.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Qibin Zhang

PROVIDER: MSV000084341 | MassIVE |

SECONDARY ACCESSION(S): PXD007884

REPOSITORIES: MassIVE

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Publications

Temporal expression profiling of plasma proteins reveals oxidative stress in early stages of Type 1 Diabetes progression.

Liu Chih-Wei CW Bramer Lisa L Webb-Robertson Bobbie-Jo BJ Waugh Kathleen K Rewers Marian J MJ Zhang Qibin Q

Journal of proteomics 20171007

Blood markers other than islet autoantibodies are greatly needed to indicate the pancreatic beta cell destruction process as early as possible, and more accurately reflect the progression of Type 1 Diabetes Mellitus (T1D). To this end, a longitudinal proteomic profiling of human plasma using TMT-10plex-based LC-MS/MS analysis was performed to track temporal proteomic changes of T1D patients (n=11) across 9 serial time points, spanning the period of T1D natural progression, in comparison with tho ...[more]

PMID: 28993202

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Temporal Expression Profiling of Plasma Proteins in Type 1 Diabetes Progression

Project description:A longitudinal proteomic profiling of human plasma using TMT-10plex-based LC-MS/MS analysis was performed to track temporal proteomic changes of T1D patients (n = 11) across 9 serial time points, spanning the period of T1D natural progression, in comparison with those of the matching healthy controls (n = 10). Longitudinal expression profiles of >2000 human plasma proteins in T1D natural progression were presented in the current study.

2018-03-08 | PXD007884 | Pride

Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [T1D_114]

Project description:The complex milieu of inflammatory mediators associated with many diseases is often too dilute to directly measure in the periphery, necessitating development of more sensitive measurements suitable for mechanistic studies, earlier diagnosis, guiding selection of therapy, and monitoring interventions. Previously, we determined that plasma of recent-onset (RO) Type 1 diabetes (T1D) patients induce a proinflammatory transcriptional signature in fresh peripheral blood mononuclear cells (PBMC) relative to that of unrelated healthy controls (HC). Here, using an optimized cryopreserved PBMC-based protocol, we analyzed larger RO T1D and HC cohorts. In addition, we examined T1D progression by looking at longitudinal, pre-onset and longstanding T1D samples. UPN727 cells were stimulated with autologous plasma (n=7), unrelated healthy control plasma (n=44), recent onset T1D plasma (n=46), longstanding T1D plasma (n=11), or longitudinal series plasma (n=6 time points) from pre/post onset. Gene expression analysis was performed in order to evaluate the transcriptional signature associated with T1D.

2012-09-01 | E-GEOD-35725 | biostudies-arrayexpress

Molecular signatures differentiate immune states in Type 1 Diabetes families

Project description:The complex milieu of inflammatory mediators associated with many diseases is often too dilute to directly measure in the periphery, necessitating development of more sensitive measurements suitable for mechanistic studies, earlier diagnosis, guiding selection of therapy, and monitoring interventions. Previously, we determined that plasma of recent-onset (RO) Type 1 diabetes (T1D) patients induce a proinflammatory transcriptional signature in fresh peripheral blood mononuclear cells (PBMC) relative to that of unrelated healthy controls (HC). Here, using an optimized cryopreserved PBMC-based protocol, we analyzed larger RO T1D, HC, and healthy T1D sibling cohorts. In addition, we examined T1D progression by looking at longitudinal samples. UPN727 cells were stimulated with Auto-antibody-negative (AA-) High HLA Risk Siblings plasma (n=30), Auto-antibody-negative (AA-) Low HLA Risk Siblings plasma (n=42), Recent onset T1DM plasma cultured with IL1RA (n=42), or longitudinal series plasma on T1DM progressor (n=27 chips, 5 series), on auto-antibody-positive (AA+) High HLA Risk Siblings (n=54 chips, 9 series), on auto-antibody-negative (AA-) High HLA Risk Siblings (n=60 chips, 12 series), on auto-antibody-negative (AA-) Low HLA Risk Siblings (n=31 chips, 6 series). Gene expression analysis was perfromed in order to evaluate the transcriptional signature associated with T1D.

2014-05-13 | E-GEOD-52724 | biostudies-arrayexpress

Molecular signatures differentiate immune states in Type 1 Diabetes families

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2-year Longitudinal Analyses of Peripheral Blood RNA in Huntington's Disease gene-positive and control subjects

Project description:Samples collected in the course of the TRACK HD study and used to analyse association between gene expression in blood and symptomatic progression of Huntington's disease Longitudinal analysis of UHDRS TMS versus gene expression in individual subjects followed by cross-sectional comparisons across phenotype groups at each timepoint

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Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [T1D_114]

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The temporal dynamics of proinflammatory and immuno-regulatory processes during progression to type 1 diabetes in the BioBreeding rat [human]

Project description:A need exists for biomarkers in T1D that can 1) sensitively and specifically detect disease-related immune activity prior to, and independent of, measurement of auto-antibodies towards islet cell antigens; 2) define immunopathological mechanisms; and 3) monitor changes in the inflammatory state associated with disease progression or response to therapeutic intervention. In an effort to fill this gap, we have applied a novel bioassay to both human and BB rat T1D whereby the complex milieu of inflammatory mediators present in plasma can be indirectly detected through their ability to drive transcription in peripheral blood mononuclear cells drawn from healthy, unrelated donors. The resultant gene expressions are comprehensively measured with a microarray. In our human studies, we find that plasma of recent-onset T1D patients induces expression of a pro-inflammatory signature consisting in part of many interleukin-1 (IL-1) regulated genes related to immunological activation and immunocyte chemotaxis compared to unrelated healthy controls. This signature has been found to resolve in long-standing T1D subjects (>10 years post-onset), thus associating it with active autoimmunity. Importantly, this signature has been detected in pre-onset samples of progressors to T1D years prior to onset and prior to development of auto-antibodies directed towards islet antigens. Fresh PBMCs of a healthy control donor were isolated by density gradient centrifugation. These cells were then stimulated with 20% plasma from a longitudinally monitored sibling of a T1D patient that progressed to T1D (n= 6 timepoints) at 37C in 5% CO2. Gene expression analysis was perfromed in order to evaluate the transcriptional signature associated with T1D pathogenesis.

2013-06-01 | E-GEOD-40496 | biostudies-arrayexpress

Serum APOC1 levels are decreased in seroconverted children who progress to type 1 diabetes at a young age

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

Transcriptomic Profiling of Plasma Extracellular Vesicles Enables Reliable Annotation of the Cancer-specific Transcriptome and Molecular Subtype (plasma_cancer)

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