bioRxiv : the preprint server for biology · 2026
Circulating miRNA-Protein Signatures Predict Outcomes in Pediatric Dilated Cardiomyopathy.
СтатьяПрепринтНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Vicentino Amanda R, Karimpour-Fard Anis, Hamza Taye, Stauffer Brian L, Lavine Kory J, Miyamoto Shelley D, Lipshultz Steven, Sucharov Carmen C, Pediatric Cardiomyopathy Registry Investigators
Аннотация
BACKGROUND: Pediatric dilated cardiomyopathy (DCM) is a rare, progressive heart disease with variable outcomes that range from recovery to heart transplantation. To date, there are no prognostic biomarkers for children with DCM. Identifying circulating biomarkers that are associated with clinical outcomes is critical for personalized management.
METHODS: miRNAs were identified by RNA-seq, whereas proteins were identified by SomaScan®. Machine learning methodologies were used to explore the predictive ability of circulating factors identified from serum samples collected at the time of presentation with acute heart failure.
RESULTS: Thirty patients experienced poor outcomes (cardiac transplantation, mechanical circulatory support, or death) and 19 patients recovered left ventricular function. Distinct miRNA and protein signatures differentiated outcomes groups. Top candidate proteins (COL2A1, CXCL12, and ADGRF5) and miRNAs (miR-874-3p, miR-335-3p, miR-323a-3p) demonstrated strong discriminatory performance within the study cohort (recovered vs poor outcomes; Area Under the Curve of 0.92). Ingenuity Pathway Analysis implicates cardiac remodeling, fibrosis, and inflammatory signaling as central pathways differentiating patient outcomes.
CONCLUSIONS: Circulating miRNA and protein signatures at presentation identify a circulating molecular signature associated with divergent clinical trajectories in pediatric DCM. These findings support the potential utility of multi-omic biomarkers for early risk stratification and provide insight into mechanisms underlying divergent outcomes.
METHODS: miRNAs were identified by RNA-seq, whereas proteins were identified by SomaScan®. Machine learning methodologies were used to explore the predictive ability of circulating factors identified from serum samples collected at the time of presentation with acute heart failure.
RESULTS: Thirty patients experienced poor outcomes (cardiac transplantation, mechanical circulatory support, or death) and 19 patients recovered left ventricular function. Distinct miRNA and protein signatures differentiated outcomes groups. Top candidate proteins (COL2A1, CXCL12, and ADGRF5) and miRNAs (miR-874-3p, miR-335-3p, miR-323a-3p) demonstrated strong discriminatory performance within the study cohort (recovered vs poor outcomes; Area Under the Curve of 0.92). Ingenuity Pathway Analysis implicates cardiac remodeling, fibrosis, and inflammatory signaling as central pathways differentiating patient outcomes.
CONCLUSIONS: Circulating miRNA and protein signatures at presentation identify a circulating molecular signature associated with divergent clinical trajectories in pediatric DCM. These findings support the potential utility of multi-omic biomarkers for early risk stratification and provide insight into mechanisms underlying divergent outcomes.