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<p>Spinal cord injury (SCI) is a devastating condition that leads to motor, sensory, and autonomic dysfunction. Current therapeutic options remain limited, emphasizing the need for a comprehensive understanding of the underlying SCI-associated molecular mechanisms. This study characterized distinct SCI phases and severities at the gene and functional levels, focusing on biomarker gene identification. Our approach involved a systematic review, individual transcriptomic analysis, gene meta-analysis, and functional characterization. We compiled a total of fourteen studies with 273 samples, leading to the identification of severity- and phase-specific biomarker genes that allow the precise classification of transcriptomic profiles. We investigated the potential transferability of severity-specific biomarkers and identified a twelve-gene signature that predicted injury prognosis from human blood samples. We also report the development of MetaSCI-app - an interactive web application designed for researchers - that allows the exploration and visualization of all generated results (<a href="https://metasci-cbl.shinyapps.io/metaSCI">https://metasci-cbl.shinyapps.io/metaSCI</a>). Overall, we present a transcriptomic reference and provide a comprehensive framework for assessing SCI considering severity and time perspectives, all integrated into a user-friendly tool.</p> Graphical abstract <p></p>

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A comprehensive transcriptional reference for severity and progression in spinal cord injury reveals novel translational biomarker genes

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月4日

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  • Rubén Grillo-Risco,
  • Marta R. Hidalgo,
  • Beatriz Martínez-Rojas,
  • Victoria Moreno-Manzano,
  • Francisco García-García

摘要

Spinal cord injury (SCI) is a devastating condition that leads to motor, sensory, and autonomic dysfunction. Current therapeutic options remain limited, emphasizing the need for a comprehensive understanding of the underlying SCI-associated molecular mechanisms. This study characterized distinct SCI phases and severities at the gene and functional levels, focusing on biomarker gene identification. Our approach involved a systematic review, individual transcriptomic analysis, gene meta-analysis, and functional characterization. We compiled a total of fourteen studies with 273 samples, leading to the identification of severity- and phase-specific biomarker genes that allow the precise classification of transcriptomic profiles. We investigated the potential transferability of severity-specific biomarkers and identified a twelve-gene signature that predicted injury prognosis from human blood samples. We also report the development of MetaSCI-app - an interactive web application designed for researchers - that allows the exploration and visualization of all generated results (https://metasci-cbl.shinyapps.io/metaSCI). Overall, we present a transcriptomic reference and provide a comprehensive framework for assessing SCI considering severity and time perspectives, all integrated into a user-friendly tool.

Graphical abstract