Sendotypes predict worsening renal function in chronic kidney disease patients

• Published in: Clinical and translational medicine Vol. 15; no. 4; pp. e70279 - n/a
• Main Authors: McLarnon, Thomas, Watterson, Steven, McCallion, Sean, Cooper, Eamonn, English, Andrew R., Kuan, Ying, Gibson, David S., Murray, Elaine K., McCarroll, Frank, Zhang, Shu‐Dong, Bjourson, Anthony J., Rai, Taranjit Singh
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.04.2025; John Wiley and Sons Inc; Wiley
• Subjects: Adult; Aged; biomarker; Cellular Senescence - physiology; CKD; Disease Progression; Female; Humans; Kidney diseases; Kinases; machine learning; Male; Middle Aged; Patients; Phenotype; Proteins; Proteomics - methods; Renal Insufficiency, Chronic - physiopathology; sendotype; Senescence; senescence; sendotype; biomarker; machine learning; CKD

Background Senescence associated secretory phenotype (SASP) contributes to age‐related pathology, however the role of SASP in Chronic Kidney Disease (CKD) is unclear. Here, we employ a variety of omic techniques to show that senescence signatures can separate CKD patients into distinct senescence en...