Background Chronic kidney disease ( CKD ) leads to premature mortality from cardiovascular events before kidney replacement therapy. Despite recognition of syndromes like cardiorenal anemia and cardiovascular‐kidney‐metabolic, predictive models for kidney and cardiovascular outcomes remain inadequate. This study aimed to develop a minimally invasive, risk model using circulating small extracellular vesicle‐derived mi RNAs among patients with CKD . Methods A derivation cohort (n=36) underwent microarray‐based miRNA profiling, and a least absolute shrinkage and selection operator‐penalized Cox proportional hazards model was constructed. Validation was performed using TaqMan quantitative polymerase chain reaction in a cohort of 234 patients with CKD without kidney replacement therapy. The primary outcome was a ≥30% reduction in estimated glomerular filtration rate or progression to kidney replacement therapy. The secondary outcome included all‐cause mortality, kidney replacement therapy initiation, and major adverse cardiovascular events. Results In the derivation cohort, 36% of patients had hypertensive glomerulosclerosis as the underlying CKD cause, increasing to 48% in the validation cohort. Twenty‐three miRNAs were significantly downregulated in advanced CKD , associated with cellular senescence, FOXO (forkhead box, class O) signaling, and cell cycle pathways. From these, 3 miRNAs — hsa‐let‐7d‐5p , hsa‐ miR ‐24‐3p , and hsa‐ miR ‐126‐3p —were selected and integrated into the final risk score with cystatin C and urinary protein levels, following optimization in the validation cohort. Lower miRNA levels were linked to cardiovascular comorbidities and cardiorenal anemia syndrome. Over a median follow‐up of 39 and 59 months, 108 kidney events and 70 composite outcomes occurred. The model effectively predicted adverse outcomes across CKD causes, further stratifying risk within cardiovascular‐kidney‐metabolic stage classifications. Conclusions Circulating small extracellular vesicle‐derived miRNA profiles enable a noninvasive, longitudinally predictive model for adverse kidney and cardiovascular outcomes in CKD . This approach may improve early risk identification and clinical decision‐making.
Inaba et al. (Wed,) studied this question.