<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>15(1)</volume><submitter>Inaba S</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>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 miRNAs among patients with CKD.&lt;h4>Methods&lt;/h4>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.&lt;h4>Results&lt;/h4>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-&lt;i>hsa-let-7d-5p&lt;/i>, &lt;i>hsa-miR-24-3p&lt;/i>, and &lt;i>hsa-miR-126-3p&lt;/i>-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.&lt;h4>Conclusions&lt;/h4>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.</pubmed_abstract><journal>Journal of the American Heart Association</journal><pagination>e045148</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12909002</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Circulating Extracellular Vesicle MicroRNAs as Predictive Biomarkers for Kidney and Cardiovascular Events.</pubmed_title><pmcid>PMC12909002</pmcid><pubmed_authors>Mori Y</pubmed_authors><pubmed_authors>Uchida S</pubmed_authors><pubmed_authors>Fujiki T</pubmed_authors><pubmed_authors>Hasegawa T</pubmed_authors><pubmed_authors>Koide T</pubmed_authors><pubmed_authors>Kikuchi H</pubmed_authors><pubmed_authors>Suzukawa R</pubmed_authors><pubmed_authors>Sekiya H</pubmed_authors><pubmed_authors>Arai Y</pubmed_authors><pubmed_authors>Inaba S</pubmed_authors><pubmed_authors>Naito S</pubmed_authors><pubmed_authors>Sohara E</pubmed_authors><pubmed_authors>Matsuki H</pubmed_authors><pubmed_authors>Susa K</pubmed_authors><pubmed_authors>Ando F</pubmed_authors><pubmed_authors>Iimori S</pubmed_authors><pubmed_authors>Nakano Y</pubmed_authors><pubmed_authors>Mori T</pubmed_authors><pubmed_authors>Mandai S</pubmed_authors></additional><is_claimable>false</is_claimable><name>Circulating Extracellular Vesicle MicroRNAs as Predictive Biomarkers for Kidney and Cardiovascular Events.</name><description>&lt;h4>Background&lt;/h4>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 miRNAs among patients with CKD.&lt;h4>Methods&lt;/h4>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.&lt;h4>Results&lt;/h4>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-&lt;i>hsa-let-7d-5p&lt;/i>, &lt;i>hsa-miR-24-3p&lt;/i>, and &lt;i>hsa-miR-126-3p&lt;/i>-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.&lt;h4>Conclusions&lt;/h4>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.</description><dates><release>2026-01-01T00:00:00Z</release><publication>2026 Jan</publication><modification>2026-07-07T03:08:56.619Z</modification><creation>2026-07-07T03:08:04.059Z</creation></dates><accession>S-EPMC12909002</accession><cross_references><pubmed>41369156</pubmed><doi>10.1161/JAHA.125.045148</doi></cross_references></HashMap>