Project description: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.

Project description:More humans have died of tuberculosis (TB) than any other infectious disease and millions still die each year. Experts advocate for blood-based, protein biomarkers to help diagnosis TB, which is critical in high-burden countries. However, the protein biomarker pipeline is small. Here, we used the Diversity Outbred (DO) mouse population to address this gap, identifying five protein biomarker candidates. One biomarker, serum CXCL1, met the World Health Organization’s Targeted Product Profile for a triage test to diagnose active TB from latent M.tb infection (LTBI), non-TB lung disease, and normal sera in HIV-negative, adults from South Africa and Vietnam. To find the biomarker candidates, we quantified seven immune mediators and four proteins corresponding to a subset of highly expressed genes unique to progressor DO mice. Next, we applied statistical and machine learning methods to the data, i.e., 11 proteins in lungs from 453 infected and 29 non-infected mice. After searching all combinations of five algorithms and 239 protein subsets, validating, and testing the findings on independent data, two combinations accurately diagnosed progressor DO mice: Logistic Regression using MMP8; and Gradient Tree Boosting using a panel of 4: CXCL1, CXCL2, TNF, IL-10. Of those five protein biomarker candidates, two (MMP8 and CXCL1) were crucial for classifying DO mice; were above the limit of detection in most human serum samples; and had not been widely assessed for diagnostic performance in humans before. In patient sera, CXCL1 exceeded the triage diagnostic test criteria (>90% sensitivity; >70% specificity), while MMP8 did not. Using Area Under the Curve analyses, CXCL1 averaged 94.5% sensitivity and 88.8% specificity for active pulmonary TB (ATB) vs LTBI; 90.9% sensitivity and 71.4% specificity for ATB vs non-TB; and 100.0% sensitivity and 98.4% specificity for ATB vs normal sera. Our findings overall show that the DO mouse population can discover diagnostic-quality, serum protein biomarkers of human TB.

Dataset Information

Biomarkers of Cavernous Angioma with Symptomatic Hemorrhage (CASH) [small RNA-seq]

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets