Comprehensive transcriptome analysis of cerebral cavernous malformation across multiple species and genotypes

Koskimäki, Janne; Girard, Romuald; Li, Yan; Saadat, Laleh; Zeineddine, Hussein A.; Lightle, Rhonda; Moore, Thomas; Lyne, Seán B.; Avner, Kenneth; Shenkar, Robert; Cao, Ying; Shi, Changbin; Polster, Sean P.; Zhang, Dongdong; Carrión‐Penagos, Julián; Romanos, Sharbel; Fonseca, Gregory J.; Lopez-Ramirez, Miguel Alejandro; Chapman, Eric Michael; Popiel, Evelyn; Tang, Alan T.; Akers, Amy; Faber, Pieter; Andrade, Jorge; Ginsberg, Mark H.; Derry, W. Brent; Kahn, Mark L.; Marchuk, Douglas A.; Awad, Issam A.

doi:10.1172/jci.insight.126167

Cited by 49 publications

(63 citation statements)

References 48 publications

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“…Five of the 6 molecules composing the prognostic and diagnostic biomarkers were significantly related (P < 0. (Table 3) (13)(14)(15). IL10RA (log 2 FC = 1.68) was also identified in the CASH transcriptome (as well as in the non-CASH transcriptome).…”

Section: L I N I C a L M E D I C I N Ementioning

confidence: 91%

“…Transcriptomic analyses were performed in order to both validate the current biomarkers and identify new candidate biomarkers for future study (Supplemental Figure 4 and Supplemental Table 4). A total of 1027 and 866 differently expressed genes (DEGs) were identified (P < 0.05, FDR corrected) in, respectively, the CASH and non-CASH compared with healthy NVUs harvested from brains at autopsy brain (13). Among the 1027 DEGs, 398 were only dysregulated in the CASH transcriptome.…”

Section: L I N I C a L M E D I C I N Ementioning

confidence: 99%

“…Our transcriptomic lesional mRNA and plasma miRNA databanks may serve as an important resource for identifying new mechanistic targets involved in CASH pathogenesis, as well as possible biomarker exploration in the future (13). Network analysis of the DEGs identified only in the CASH transcriptome showed 17 highly interconnected genes, such as BTRC, COL6A1, and ITGB5 (Supplemental Figure 5), which may be considered as additional candidate biomarkers or undergo mechanistic studies in the future (Supplemental Figure 4).…”

Section: L I N I C a L M E D I C I N Ementioning

confidence: 99%

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Biomarkers of cavernous angioma with symptomatic hemorrhage

Lyne¹,

Girard²,

Koskimäki³

et al. 2019

JCI Insight

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BACKGROUND. Cerebral cavernous angiomas (CAs) with a symptomatic hemorrhage (CASH) have a high risk of recurrent hemorrhage and serious morbidity. METHODS. Eighteen plasma molecules with mechanistic roles in CA pathobiology were investigated in 114 patients and 12 healthy subjects. The diagnostic biomarker of a CASH in the prior year was derived as that minimizing the Akaike information criterion and validated using machine learning, and was compared with the prognostic CASH biomarker predicting bleeding in the subsequent year. Biomarkers were longitudinally followed in a subset of cases. The biomarkers were queried in the lesional neurovascular unit (NVU) transcriptome and in plasma miRNAs from CASH and non-CASH patients. RESULTS. The diagnostic CASH biomarker included a weighted combination of soluble CD14 (sCD14), VEGF, C-reactive protein (CRP), and IL-10 distinguishing CASH patients with 76% sensitivity and 80% specificity (P = 0.0003). The prognostic CASH biomarker (sCD14, VEGF, IL-1β, and sROBO-4) was confirmed to predict a bleed in the subsequent year with 83% sensitivity and 93% specificity (P = 0.001). Genes associated with diagnostic and prognostic CASH biomarkers were differentially expressed in CASH lesional NVUs. Thirteen plasma miRNAs were differentially expressed between CASH and non-CASH patients. CONCLUSION. Shared and unique biomarkers of recent symptomatic hemorrhage and of future bleeding in CA are mechanistically linked to lesional transcriptome and miRNA. The biomarkers may be applied for risk stratification in clinical trials and developed as a tool in clinical practice.

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Section: L I N I C a L M E D I C I N Ementioning

confidence: 91%

Section: L I N I C a L M E D I C I N Ementioning

confidence: 99%

Section: L I N I C a L M E D I C I N Ementioning

confidence: 99%

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Biomarkers of cavernous angioma with symptomatic hemorrhage

Lyne¹,

Girard²,

Koskimäki³

et al. 2019

JCI Insight

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“…It has been demonstrated that the three CCM proteins form the CSC, which plays an essential role in the pathogenesis of CCMs when disrupted [26]. Efforts to dissect CSC signaling cascades have been made (Additional file 11) [8,10,[20][21][22][23][24][25][26], but with some contradicting outcomes. It is essential to establish comparative omics methods to assess similarities among those independent studies, which can aid in identification of potential biomarker candidates for prognostic and diagnostic applications.…”

Section: Discussionmentioning

confidence: 99%

“…A comparative database in excel (Additional files 1 and 2) was set up for the nine total available CCM cohorts that were analyzed for our comparative omics studies [8,10,[19][20][21][22][23][24][25] (Fig. 1).…”

Section: Data Acquisitionmentioning

confidence: 99%

Comparative omics of CCM signaling complex (CSC)

et al. 2020

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Background: Cerebral cavernous malformations (CCMs), a major neurosurgical condition, characterized by abnormally dilated intracranial capillaries, result in increased susceptibility to stroke. KRIT1 (CCM1), MGC4607 (CCM2), and PDCD10 (CCM3) have been identified as causes of CCMs in which at least one of them is disrupted in most familial cases. Our goal is to identify potential biomarkers and genetic modifiers of CCMs, using a global comparative omics approach across several in vitro studies and multiple in vivo animal models. We hypothesize that through analysis of the CSC utilizing various omics, we can identify potential biomarkers and genetic modifiers, by systemically evaluating effectors and binding partners of the CSC as well as second layer interactors. Methods: We utilize a comparative omics approach analyzing multiple CCMs deficient animal models across nine independent studies at the genomic, transcriptomic, and proteomic levels to dissect alterations in various signaling cascades. Results: Our analysis revealed a large set of genes that were validated across multiple independent studies, suggesting an important role for these identified genes in CCM pathogenesis. Conclusion: This is currently one of the largest comparative omics analysis of CCM deficiencies across multiple models, allowing us to investigate global alterations among multiple signaling cascades involved in both angiogenic and non-angiogenic events and to also identify potential biomarker candidates of CCMs, which can be used for new therapeutic strategies.

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