Amita Bansal, Soon Wei Wong, Wilson K M Wong, Giles Best, Steven James, Sarah Glastras, Alexia Pena, Cheng Xue Qin, Sih Min Tan, Devy Deliyanti, Darling M Rojas-Canales, Mugdha V Joglekar, Elif I Ekinci
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引用次数: 0
Abstract
Background: Diabetic kidney disease (DKD) is a common complication of type 1 diabetes (T1D). T1D and some kidney disorders are often associated with abnormalities in regulatory T cells (Tregs). However, it is unknown if Treg subsets, and their molecular architecture are altered during the onset and progression of DKD in T1D.
Methods: We addressed this critical knowledge gap by characterising changes in Tregs isolated from 31 participants (10 control, 13 with T1D, and 8 T1D with albuminuria) using flow cytometry, RNA-sequencing, and microRNA profiling.
Results: We identified that the effector and central memory Tregs were significantly different between groups. Similarly, multiple gene transcripts were also significantly different between groups that also overlapped with other publicly available datasets. Machine-learning based data analyses discovered a set of important microRNAs associated with clinical eGFR values.
Conclusions: Importantly, our analyses identified two differentially expressed Treg ligand genes (LRRC4B, TGM2), which interacted with the receptors on kidney cells (PTPRD/F/S, ADGRG1) in silico, providing potential mechanistic insights into the role of Tregs in DKD progression. Together, our work supports the yet unappreciated role of Tregs in DKD and opens new research avenues to further consolidate their causal relationship.