| Literature DB >> 35715588 |
Abhinav Srinath1, Ying Li1,2, Romuald Girard1, Issam A Awad3, Sharbel G Romanos1, Bingqing Xie4, Chang Chen1,5, Yan Li1,5, Thomas Moore1, Dehua Bi1,6, Je Yeong Sone1, Rhonda Lightle1, Nick Hobson1, Dongdong Zhang1, Janne Koskimäki1, Le Shen7, Sara McCurdy8, Catherine Chinhchu Lai8, Agnieszka Stadnik1, Kristina Piedad1, Julián Carrión-Penagos1, Abdallah Shkoukani1, Daniel Snellings9, Robert Shenkar1, Dinanath Sulakhe5, Yuan Ji1,6, Miguel A Lopez-Ramirez8,10, Mark L Kahn11, Douglas A Marchuk9, Mark H Ginsberg8.
Abstract
Patients with familial cerebral cavernous malformation (CCM) inherit germline loss of function mutations and are susceptible to progressive development of brain lesions and neurological sequelae during their lifetime. To date, no homologous circulating molecules have been identified that can reflect the presence of germ line pathogenetic CCM mutations, either in animal models or patients. We hypothesize that homologous differentially expressed (DE) plasma miRNAs can reflect the CCM germline mutation in preclinical murine models and patients. Herein, homologous DE plasma miRNAs with mechanistic putative gene targets within the transcriptome of preclinical and human CCM lesions were identified. Several of these gene targets were additionally found to be associated with CCM-enriched pathways identified using the Kyoto Encyclopedia of Genes and Genomes. DE miRNAs were also identified in familial-CCM patients who developed new brain lesions within the year following blood sample collection. The miRNome results were then validated in an independent cohort of human subjects with real-time-qPCR quantification, a technique facilitating plasma assays. Finally, a Bayesian-informed machine learning approach showed that a combination of plasma levels of miRNAs and circulating proteins improves the association with familial-CCM disease in human subjects to 95% accuracy. These findings act as an important proof of concept for the future development of translatable circulating biomarkers to be tested in preclinical studies and human trials aimed at monitoring and restoring gene function in CCM and other diseases.Entities:
Keywords: Cerebral cavernous malformations; Genotype; Machine learning; MicroRNA
Year: 2022 PMID: 35715588 DOI: 10.1007/s12975-022-01050-3
Source DB: PubMed Journal: Transl Stroke Res ISSN: 1868-4483 Impact factor: 6.829