Increased CD69 and Human Leukocyte Antigen-DR Expression on T Lymphocytes in Insulin-Dependent Diabetes Mellitus of Long Standing

Gessl, Alois; Waldhäusl, W.

doi:10.1210/jcem.83.6.4889

Cited by 16 publications

(2 citation statements)

References 46 publications

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“…Pathways include metabolism [42], transport of small molecules [43] and immune system [44] are linked with progression of FSGS. PDK4 [45], ALB (albumin) [46], EGR1 [47], RYR3 [48], APOH (apolipoprotein H) [49], CYP27B1 [50], ESM1 [51], GATA6 [52], PCK1 [53], TET2 [54], AFP (alpha fetoprotein) [55], CACNA1D [56], ATF3 [57], EGF (epidermal growth factor) [58], LPL (lipoprotein lipase) [59], PPARGC1A [60], PLG (plasminogen) [61], NR4A1 [62], STRA6 [63], MLXIPL (MLX interacting protein like) [64], PLA2G6 [65], RGS2 [66], GPS2 [67], SOX5 [68], GLUL (glutamate-ammonia ligase) [69], RYK (receptor like tyrosine kinase) [70], NFKBIA (NFKB inhibitor alpha) [71], LGR4 [72], SPRY2 [73], TRPC1 [74], KL (klotho) [75], GCLC (glutamate-cysteine ligase catalytic subunit) [76], NOX4 [77], CD69 [78], SLC19A2 [79], S100A12 [80], MT1A [81], SORCS1 [82], FKBP5 [83], AFM (afamin) [84], CA3 [85], MAOA (monoamine oxidase A) [86], ND1 [87], ATP6 [88], CHGA (chromogranin A) [89], ICOS (inducible T cell costimulator) [90], DBH (dopamine beta-hydroxylase) [91], CD5 [92], LTA (lymphotoxin alpha) [93], IFNG (interferon gamma) [94], MPO (myeloperoxidase) [95], CD70 [96], CD300E [97], COLEC12 [98], TLR10 [99], LCN2 [100], SLAMF7 [101], TREM2 [102], ITGAL (integrin subunit alpha L) [103], CD27 [104], JAK3 [105], CCR5 [106], FCN1 [107], IL1RN [108], CX3CR1 [109], PDCD1 [110], TRPM2 [111], PLEK (pleckstrin) [112], CD101 [113],...…”

Section: Discussionmentioning

confidence: 99%

Identification of biomarkers and pathways for focal segmental glomerulosclerosis using next generation sequencing data and bioinformatics analysis

Vastrad¹,

Vastrad²

2022

Preprint

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Focal segmental glomerulosclerosis (FSGS) is a renal disease leading threat to human health around the world. Here we aimed to explore novel molecular and potential therapeutic targets in FSGS through adopting integrated bioinformatics tools. Next generation sequencing (NGS) data of GSE197307 was available from Gene Expression Omnibus (GEO) database. Furthermore, differentially expressed genes (DEGs) were screened using the DESeq2 package in R software. Gene ontology (GO) and REACTOME pathway enrichment analyses of DEGs were performed via g:Profiler. Then, the protein-protein interaction (PPI) network, miRNA- hub gene regulatory network and TF-hub gene regulatory network were constructed using the HIPPIE, miRNet and NetworkAnalyst databases. Hub genes were validated using the receiver operating characteristic curve (ROC) analysis. By performing DEGs analysis, 488 up regulated genes and 488 down regulated genes were successfully identified from GSE197307, respectively. And they were mainly enriched in the terms of multicellular organismal process, cell periphery, protein binding, metabolism, immune system process, signaling receptor binding and immune system. Based on the data of protein-protein interaction (PPI), miRNA-hub gene regulatory network and TF-hub gene regulatory network, the top hub genes were ranked, including ILK, DDX5, MATR3, ALB, FOS, MKI67, PLK1, TNF, LCK and GTSE1. Bioinformatics analysis of NGS data identified signaling pathways and hub genes, potentially representing molecular mechanisms for the occurrence, progression, and risk prediction in FSGS.

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Section: Discussionmentioning

confidence: 99%

Identification of biomarkers and pathways for focal segmental glomerulosclerosis using next generation sequencing data and bioinformatics analysis

Vastrad¹,

Vastrad²

2022

Preprint

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“…T2D is characterized by hyperglycemia, especially when inadequately treated, and some studies report that hyperglycemia promotes aberrant activation and higher responsiveness of peripheral CD4 + T-cells [21,22]. Some studies have associated hyperglycemia with higher numbers of peripheral CD4 + T-cells, and higher Th1 and Th17 subset frequencies [23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Fasting and Glucose Metabolism Differentially Impact Peripheral Inflammation in Human Type 2 Diabetes

Kalantar,

Saraswat,

SantaCruz-Calvo

et al. 2024

Nutrients

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Cytokines produced by peripheral T-helper 1/17 cells disproportionately contribute to the inflammation (i.e., metaflammation) that fuels type 2 diabetes (T2D) pathogenesis. Shifts in the nutrient milieu could influence inflammation through changes in T-cell metabolism. We aimed to determine whether changes in glucose utilization alter cytokine profiles in T2D. Peripheral blood mononuclear cells (PBMCs), CD4+ T-cells, and CD4+CD25- T-effector (Teff) cells were isolated from age-matched humans classified by glycemic control and BMI. Cytokines secreted by CD3/CD28-stimulated PBMCs and Teff were measured in supernatants with multiplex cytokine assays and a FLEXMAP-3D. Metabolic activity of stimulated CD4+ T-cells was measured by a Seahorse XFe96 analyzer. In this study, we demonstrated that T-cell stimulated PBMCs from non-fasted people with T2D produced higher amounts of cytokines compared to fasting. Although dysglycemia characterizes T2D, cytokine production by PBMCs or CD4+ T-cells in T2D was unaltered by hyperglycemic media. Moreover, pharmacological suppression of mitochondrial glucose oxidation did not change T-cell metabolism in T2D, yet enhanced cytokine competency. In conclusion, fasting and glucose metabolism differentially impact peripheral inflammation in human T2D, suggesting that glucose, along with fatty acid metabolites per our previous work, partner to regulate metaflammation. These data expose a major disconnect in the use of glycemic control drugs to target T2D-associated metaflammation.

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CD 69

Vance

2002

Wiley Encyclopedia of Molecular Medicine

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Increased CD69 and Human Leukocyte Antigen-DR Expression on T Lymphocytes in Insulin-Dependent Diabetes Mellitus of Long Standing

Cited by 16 publications

References 46 publications

Identification of biomarkers and pathways for focal segmental glomerulosclerosis using next generation sequencing data and bioinformatics analysis

Identification of biomarkers and pathways for focal segmental glomerulosclerosis using next generation sequencing data and bioinformatics analysis

Fasting and Glucose Metabolism Differentially Impact Peripheral Inflammation in Human Type 2 Diabetes

CD 69

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