ACSS2 gene variants determine kidney disease risk by controlling de novo lipogenesis in kidney tubules.

Chronic kidney disease Fibrosis Genetics Nephrology

Journal

The Journal of clinical investigation
ISSN: 1558-8238
Titre abrégé: J Clin Invest
Pays: United States
ID NLM: 7802877

Informations de publication

Date de publication:
05 Dec 2023
Historique:
medline: 6 12 2023
pubmed: 6 12 2023
entrez: 5 12 2023
Statut: aheadofprint

Résumé

Worldwide, over 800 million people are affected by kidney disease, yet its pathogenesis remains elusive, hindering the development of novel therapeutics. In this study, we employed kidney-specific expression of quantitative traits and single-nuclear open chromatin analysis to show that genetic variants linked to kidney dysfunction on chromosome 20 target the acyl-CoA synthetase short-chain family 2 (ACSS2). By generating ACSS2 knock-out mice, we demonstrated their protection from kidney fibrosis in multiple disease models. Our analysis of primary tubular cells revealed that ACSS2 regulates de novo lipogenesis (DNL), causing NADPH depletion and increasing ROS levels, ultimately leading to NLRP3-dependent pyroptosis. Additionally, we discovered that pharmacological inhibition or genetic ablation of fatty acid synthase safeguarded kidney cells against profibrotic gene expression and prevented kidney disease in mice. Lipid accumulation and the expression of genes related to DNL were elevated in the kidneys of patients with fibrosis. Our findings pinpoint ACSS2 as a critical kidney disease gene and reveal the role of DNL in kidney disease.

Identifiants

pubmed: 38051585
pii: 172963
doi: 10.1172/JCI172963
doi:
pii:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Dhanunjay Mukhi (D)

Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, United States of America.

Lingzhi Li (L)

Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, United States of America.

Hongbo Liu (H)

Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, United States of America.

Tomohito Doke (T)

Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, United States of America.

Lakshmi P Kolligundla (LP)

Department of Medicine, University of Pennsylvania, Philadelphia, United States of America.

Eunji Ha (E)

Department of Medicine, University of Pennsylvania, Philadelphia, United States of America.

Konstantin A Klötzer (KA)

Department of Medicine, University of Pennsylvania, Philadelphia, United States of America.

Amin Abedini (A)

Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, United States of America.

Sarmistha Mukherjee (S)

Department of Physiology, University of Pennsylvania, Philadelphia, United States of America.

Junnan Wu (J)

Department of Medicine, University of Pennsylvania, Philadelphia, United States of America.

Poonam Dhillon (P)

Department of Medicine, University of Pennsylvania, Philadelphia, United States of America.

Hailong Hu (H)

Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, United States of America.

Dongyin Guan (D)

Division of Endocrinology, Baylor College of Medicine, Houston, United States of America.

Katsuhiko Funai (K)

Diabetes & Metabolism Research Center, University of Utah, Salt Lake City, United States of America.

Kahealani Uehara (K)

Institutes for Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, United States of America.

Paul M Titchenell (PM)

Department of Physiology, University of Pennsylvania, Philadelphia, United States of America.

Joseph A Baur (JA)

Department of Physiology, University of Pennsylvania, Philadelphia, United States of America.

Kathryn E Wellen (KE)

Department of Cancer Biology, University of Pennsylvania, Philadelphia, United States of America.

Katalin Susztak (K)

Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, United States of America.

Classifications MeSH