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Usage Information

Targeting HSPA1A with geranylgeranylacetone alleviates ADTKD-UMOD via suppression of endoplasmic reticulum stress and ferroptosis
Wen Shi, Yan Yang, Xianli Wen, Qianqian Wu, Jinxuan Wei, Xin-Lu Wang, Junyuan Shen, Siqi Peng, Xiaoliang Zhang, Bi-Cheng Liu, Bin Wang
Wen Shi, Yan Yang, Xianli Wen, Qianqian Wu, Jinxuan Wei, Xin-Lu Wang, Junyuan Shen, Siqi Peng, Xiaoliang Zhang, Bi-Cheng Liu, Bin Wang
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Research In-Press Preview Genetics Nephrology

Targeting HSPA1A with geranylgeranylacetone alleviates ADTKD-UMOD via suppression of endoplasmic reticulum stress and ferroptosis

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Abstract

Missense mutations in the UMOD gene are a well-established genetic cause of autosomal dominant tubulointerstitial kidney disease (ADTKD). Here, we report two ADTKD pedigrees carrying de novo UMOD mutations, p.His36Tyr (H36Y) and p.Trp31Cys (W31C). To elucidate the underlying pathogenic mechanisms and explore targeted therapeutic strategies, we generated a UMODH36Y/+ knock-in mouse model using CRISPR/Cas9 technology, which recapitulated the major clinical manifestations observed in patients. Through single-cell RNA sequencing and experimental validation, we demonstrated that uromodulin mutations triggered endoplasmic reticulum (ER) stress and the unfolded protein response, with ferroptosis identified as the predominant mode of cell death in this disease. These findings were further confirmed in plasmid-transfected cell models expressing UMODH36Y and UMODW31C. Moreover, the molecular chaperone HSPA1A was identified as a potential therapeutic target. Geranylgeranylacetone, targeting HSPA1A as a chaperone drug, effectively mitigated endoplasmic reticulum stress, alleviated ferroptosis, and delayed the progression of renal dysfunction. Based on novel uromodulin mutations, our study reveals a pathogenic ER-ferroptosis axis in ADTKD-UMOD, deepens the insight into the pathogenesis of ADTKD-UMOD, and provides a promising strategy for developing chaperone therapy with drug repurposing in genetic kidney diseases.

Authors

Wen Shi, Yan Yang, Xianli Wen, Qianqian Wu, Jinxuan Wei, Xin-Lu Wang, Junyuan Shen, Siqi Peng, Xiaoliang Zhang, Bi-Cheng Liu, Bin Wang

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Usage data is cumulative from October 2026 through October 2026.

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