bioRxivGenomicsPreprint
Blood prognostic biomarker signatures for hemorrhagic cerebral cavernous malformations (CCMs)
Jacob CroftiD, Brian I. GrajedaiD, Johnathan Abou‐FadeliD, Cameron C. EllisiD, Igor L. EstevaoiD, Igor Correia de AlmeidaiD, Jun ZhangiD
Abstract
BackgroundCerebral cavernous malformations (CCMs) is a neurological disorder that causes enlarged intracranial capillaries in the brain, leading to an increased risk of hemorrhagic strokes, which is a leading cause of death and disability worldwide. ObjectivesThe current treatment options for CCMs are limited, highlighting the need for prognostic biomarkers to predict the risk of hemorrhagic events to better inform treatment decisions and identify future pharmacological targets. Eligibility CriteriaThe study is centered on a comparative proteomic analysis between hemorrhagic CCMs (HCs) and healthy controls, while excluding patients with non-hemorrhagic CCMs (NHCs) from the analysis due to the experimental design. Sources of EvidenceRecent research has identified several serum biomarkers and blood circulating biomarkers in a selected cohort of homogeneous CCM patients and animal models. MethodProteomic profiles from both human and mouse CCM models were examined, and pathway enrichment analyses were performed using three approaches (GO, KEGG, and DOSE). To account for multiple comparisons, t-tests were employed to evaluate differences. A p-value below 0.05 was deemed statistically significant. ResultsThe authors have developed the first panel of candidate biomarker signatures, featuring both etiological and prognostic markers in two distinct pathways. This panel of biomarker signatures demonstrates a robust correlation with the likelihood of hemorrhagic CCMs. ConclusionsThis groundbreaking biomarker panel paves the way for further investigation of potential blood biomarkers to determine the risk of hemorrhagic CCMs.
- organism: human
- organism: mouse
- assay: proteomics
- research focus: differential expression
- approach: statistical model
- Citations
- 3
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