Perinatal asphyxia leads to acute kidney damage and increased renal susceptibility in adulthood

Lakat, Tamás and Fekete, Andrea and Demeter, Kornél and Tóth, Ákos Roland and Varga, Zoltán Kristóf and Patonai, Attila and Kelemen, Hanga and Budai, András and Szabó, Miklós and Szabó, Attila and Kai, Kaila and Dénes, Ádám and Mikics, Éva and Hosszú, Ádám (2024) Perinatal asphyxia leads to acute kidney damage and increased renal susceptibility in adulthood. AMERICAN JOURNAL OF PHYSIOLOGY: RENAL PHYSIOLOGY, 327 (2). F314-F326. ISSN 1931-857X

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Abstract

Perinatal asphyxia (PA) poses a significant threat to multiple organs, particularly the kidneys. Diagnosing PA-associated kidney injury remains challenging and treatment options are inadequate. Furthermore, there is a lack of long-term follow-up data regarding the renal implications of PA. In this study, 7-day-old male Wistar rats were exposed to PA using a gas mixture (4% O2; 20% CO2 in N2 for 15 minutes) to investigate molecular pathways linked to renal tubular damage, hypoxia, angiogenesis, heat-shock response, inflammation, and fibrosis in the kidney. In a second experiment, adult rats with a history of PA were subjected to moderate renal ischemia-reperfusion (IR) injury to test the hypothesis that PA exacerbates renal susceptibility. Our results revealed an increased gene expression of renal injury markers (KIM-1, NGAL), hypoxic- and heat shock factors (HIF-1α, HSF-1, HSP-27), pro-inflammatory cytokines (IL-1ß, IL-6, TNF-α, MCP-1), and fibrotic markers (TGF-ß, CTGF, Fibronectin) promptly after PA. Moreover, a machine learning model was identified through Random Forest analysis, demonstrating an impressive classification accuracy (95.5%) for PA. Post-PA rats showed exacerbated functional decline and tubular injury and more intense hypoxic-, heat-shock-, pro-inflammatory-, and pro-fibrotic response after renal IRI compared to controls. In conclusion, PA leads to subclinical kidney injury, which may increase the susceptibility to subsequent renal damage later in life. Additionally, the parameters identified through Random Forest analysis provide a robust foundation for future biomarker research in the context of PA.

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