Genomics

Dataset Information

0

Common and Distinct Circulating MicroRNAs Across Four Neurovascular Disorders


ABSTRACT: Background: Familial cerebral cavernous malformations (FCCM), Sturge-Weber Syndrome (SWS), and hereditary hemorrhagic telangiectasia with brain arteriovenous malformations (HHT) are neurovascular disorders driven by genetic mutations. Cerebral microbleeds (CMBs) are primarily associated with the aging process with less known about genetic drivers. This study hypothesizes that common and distinct circulating microribonucleic acids (miRNAs) reflect shared and different pathobiology and can serve as potential diagnostic and mechanistic biomarkers. Methods: Common and unique differentially expressed (DE) plasma miRNAs (p<0.05, FDR corrected, absolute fold change [|FC|]>1.5]) were identified between patients with FCCM, SWS, HHT and CMB, compared to age- and sex-propensity-matched healthy subjects. Ingenuity Pathway Analysis as well as transcriptome integration analyses were performed to identify gene targets and their associated pathways. Preselected miRNAs were finally validated using ddPCR. Results: Eleven DE miRNAs were identified in FCCM, 40 in SWS, 41 in HHT, and 26 in CMB (p<0.05, FDR-corrected, [|FC|]>1.5]). Further analyses showed that 18 DE miRNAs were commonly dysregulated in any two of the studied neurovascular disorders. The PI3K-Akt and ROBO SLIT signaling pathways were identified across all four disorders. The plasma levels of four of the 18 miRNAs were further validated (p<0.05) using ddPCR. Conclusion: The common dysregulated miRNAs across neurovascular disorders reflect shared pathophysiological pathways, underscoring their potential as biomarkers and therapeutic targets. These findings pave the way for further exploration of these miRNAs, aiming at the clinical application for disease monitoring and therapeutic intervention.

ORGANISM(S): Homo sapiens

PROVIDER: GSE287906 | GEO | 2025/08/07

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2022-10-31 | GSE189023 | GEO
2021-09-28 | GSE179382 | GEO
2014-12-19 | E-GEOD-53515 | biostudies-arrayexpress
2024-07-31 | GSE252666 | GEO
2025-02-12 | GSE242741 | GEO
2025-02-12 | GSE269174 | GEO
2023-04-06 | GSE184747 | GEO
2023-04-06 | GSE184746 | GEO
2014-12-19 | GSE53515 | GEO
2022-07-28 | GSE199978 | GEO