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.
Project description:Diabetes-resistant and diabetes-prone female New Zealand Obese mice were classified based on liver fat content and early blood glucose concentrations at 10 weeks of age before the onset of T2D. By using transcriptome and DNA methylome analysis of Langerhans islets, we identified early epigenetic alteration in mice and humans which could serve as putative epigenetic biomarkers
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.
Project description:To further examine the mechanisms of urate in islet β-cell death, we have employed whole genome microarray expression profiling as a discovery platform to identify genes with the potential to distinguish primacy of streptozotocin (STZ) vs. urate. Islets were isolated from Uox-KO and WT mice with and without multiple low-dose STZ. Differentially expressed genes (DEGs) in islets of the hyperuricemic and/or diabetic mice in comparison to their respective controls represented specific Gene Ontology (GO) pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional meanings.
Project description:Single cell RNA-sequencing analysis allows for a more complete cell-by-cell analysis of the effects of SGLT2 inhibitors on the kidneys of patients with youth onset type 2 diabetes.
Project description:New measures are needed to predict type 1 diabetes disease trajectory. We have developed a sensitive array-based bioassay whereby patient plasma is used to induce transcription in healthy “reporter” leukocytes. Here we report a refined gene ontology-based inflammatory index (I.I.359) that is based upon expression levels of 359 transcripts identified in cross-sectional studies of new onset Type 1 diabetes patients and controls, where higher scores reflect greater inflammatory bias. We examined the relationship between I.I.359 measured at onset and the post-onset disease course in local patients as well as participants of the TrialNet CTLA4-Ig trial. In untreated patients, I.I.359 at baseline was highly variable and exhibited a significant inverse relationship with stimulated C-peptide AUC at 3, 6, 12, 18 and 24 months post-onset. Further, duration of the post-onset partial remission was negatively related to baseline I.I.359 and positively associated with the peripheral abundance of activated regulatory T cells (CD4+/CD45RA-/FoxP3high).
Project description:The pathophysiology underlying the autoimmune disease type 1 diabetes (T1D) is poorly understood. Obtaining an accurate proteomic profile of the T helper cell population is essential for understanding the pathogenesis of T1D. Here, we performed in-depth proteomic profiling of peripheral CD4+ T cells in a pediatric cohort in order to identify cellular signatures associated with the onset of T1D. Using only 250,000 CD4+ T cells per patient, isolated from biobanked PBMC samples, we identified nearly 6,000 proteins using deep-proteome profiling with LC-MS/MS data-independent acquisition. Our analysis revealed an inflammatory signature in patients with T1D; this signature is characterized by circulating mediators of neutrophils, platelets, and the complement system. This signature likely reflects the inflammatory extracellular milieu, suggesting that activation of the innate immune system plays an important role in disease onset. Our results emphasize the potential value of using high-resolution LC-MS/MS to investigate limited quantities of biobanked samples in order to identify disease-relevant proteomic patterns.