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Differential microvascular endothelial cell responses in the retina in diabetes compared to the heart and kidneys, a spatial transcriptomic analysis
Endothelial cells and high glucose-induced endothelial dysfunction are the common origin of chronic diabetic complications such as retinopathy, nephropathy, and cardiomyopathy. Yet their common origins, the vascular manifestations of such complications are different. We examined the basal heterogeneity between microvascular endothelial cells(MECs) from the retina, kidneys, and heart, as well as their differential responses to hyperglycemia in diabetes. To this extent, we used a spatial transcriptomic approach to investigate gene expression differences across retinal, renal, and cardiac MECs in diabetic and non-diabetic mouse models. We validated MEC heterogeneity in vitro using human retinal and cardiac MECs. The spatial transcriptomic approach was also used to explore potential similarities in retinal MECs and neuronal cells in response to hyperglycemia. We found that MECs from different target organs of major diabetic complications were transcriptomically distinct at the ba sal state and respond differently to hyperglycemia. These findings were recapitulated in cell culture, with selected analytes. We found minimal similarities between retinal MECs and neuronal cells. Our findings show considerable heterogeneity across retinal, renal, and cardiac MECs, both at the basal state and in their responses to hyperglycemia in diabetes. These findings show that organ specific MEC heterogeneity can influence differential development of pathological changes across various target organs of chronic diabetic complications, and suggest that MEC heterogeneity may influence treatment target(s) and drug development. © 2024 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Authors : Wang E.; Feng B.; Chen S.; Su Z.; Chakrabarti S.
Source : Public Library of Science
Article Information
| Year | 2024 |
| Type | Article |
| DOI | 10.1371/journal.pone.0310949 |
| ISSN | 19326203 |
| Volume | 19 |
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