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Sendotypes predict worsening renal function in chronic kidney disease patients
Thomas McLarnon1, Steven Watterson1, Sean McCallion1
1School of Medicine, Personalised Medicine Centre, Ulster University, Londonderry, UK.
Senescence signatures identify distinct patient groups in Chronic Kidney Disease (CKD). This discovery may help predict disease progression and improve patient care pathways for CKD.
Area of Science:
- Gerontology
- Nephrology
- Proteomics
Background:
- Senescence-associated secretory phenotype (SASP) is implicated in aging, but its role in Chronic Kidney Disease (CKD) remains undefined.
- This study investigates the potential of SASP to classify CKD patients into distinct endotypes.
Purpose of the Study:
- To determine if senescence signatures can stratify CKD patients into distinct endotypes.
- To explore the clinical and molecular differences between these identified endotypes.
Main Methods:
- Utilized omic techniques to analyze senescent protein expression in CKD patients.
- Employed clustering algorithms to group patients into distinct senescence endotypes (Sendotypes).
- Performed differential expression analysis to identify key molecular pathways between Sendotypes.
Main Results:
- CKD patients were successfully stratified into two distinct Sendotypes based on proteomic data.
- Each Sendotype exhibited unique clinical profiles, with higher senescent protein expression correlating with more severe disease.
- Differential enrichment of pathways like TNF, JAK-STAT, and NFKB was observed between Sendotypes.
Conclusions:
- Senescence signatures, combined with clinical data, can accurately stratify CKD patients.
- This stratification may predict renal trajectory, aiding in personalized CKD management.
- The findings offer potential for improved clinical care pathways and accurate patient stratification in CKD.
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