Transcriptome clarifies mechanisms of lesion genesis versus progression in models of Ccm3 cerebral cavernous malformations.

Published online

Journal Article

Cerebral cavernous malformations (CCMs) are dilated capillaries causing epilepsy and stroke. Inheritance of a heterozygous mutation in CCM3/PDCD10 is responsible for the most aggressive familial form of the disease. Here we studied the differences and commonalities between the transcriptomes of microdissected lesional neurovascular units (NVUs) from acute and chronic in vivo Ccm3/Pdcd10ECKO mice, and cultured brain microvascular endothelial cells (BMECs) Ccm3/Pdcd10ECKO.We identified 2409 differentially expressed genes (DEGs) in acute and 2962 in chronic in vivo NVUs compared to microdissected brain capillaries, as well as 121 in in vitro BMECs with and without Ccm3/Pdcd10 loss (fold change ≥ |2.0|; p < 0.05, false discovery rate corrected). A functional clustered dendrogram generated using the Euclidean distance showed that the DEGs identified only in acute in vivo NVUs were clustered in cellular proliferation gene ontology functions. The DEGs only identified in chronic in vivo NVUs were clustered in inflammation and immune response, permeability, and adhesion functions. In addition, 1225 DEGs were only identified in the in vivo NVUs but not in vitro BMECs, and these clustered within neuronal and glial functions. One miRNA mmu-miR-3472a was differentially expressed (FC = - 5.98; p = 0.07, FDR corrected) in the serum of Ccm3/Pdcd10+/- when compared to wild type mice, and this was functionally related as a putative target to Cand2 (cullin associated and neddylation dissociated 2), a DEG in acute and chronic lesional NVUs and in vitro BMECs. Our results suggest that the acute model is characterized by cell proliferation, while the chronic model showed inflammatory, adhesion and permeability processes. In addition, we highlight the importance of extra-endothelial structures in CCM disease, and potential role of circulating miRNAs as biomarkers of disease, interacting with DEGs. The extensive DEGs library of each model will serve as a validation tool for potential mechanistic, biomarker, and therapeutic targets.

Full Text

Duke Authors

Cited Authors

  • Koskimäki, J; Zhang, D; Li, Y; Saadat, L; Moore, T; Lightle, R; Polster, SP; Carrión-Penagos, J; Lyne, SB; Zeineddine, HA; Shi, C; Shenkar, R; Romanos, S; Avner, K; Srinath, A; Shen, L; Detter, MR; Snellings, D; Cao, Y; Lopez-Ramirez, MA; Fonseca, G; Tang, AT; Faber, P; Andrade, J; Ginsberg, M; Kahn, ML; Marchuk, DA; Girard, R; Awad, IA

Published Date

  • August 19, 2019

Published In

Volume / Issue

  • 7 / 1

Start / End Page

  • 132 -

PubMed ID

  • 31426861

Pubmed Central ID

  • 31426861

Electronic International Standard Serial Number (EISSN)

  • 2051-5960

Digital Object Identifier (DOI)

  • 10.1186/s40478-019-0789-0

Language

  • eng

Conference Location

  • England