bioRxivBioengineeringPreprint
In Search for Biomarkers Reflecting Neural Implant-Induced Tissue Response Dynamics
Ali SharbatianiD, Kevin JosephiD, Ulrich HofmanniD, VA CoeneniD, Thomas StieglitziD, Danesh Ashouri VajariiD
Abstract
Extracellular matrix (ECM) remodeling is a fundamental determinant of neural tissue repair and implant integration, yet its conserved regulatory architecture remains undefined. While transcriptomic alterations following neural injury and implantation have been described, the ECM-centered programs that unify traumatic injury and neural implant responses remain unclear. Here, integrative systems-level transcriptomic analysis identifies a dominant and conserved ECM regulatory axis linking traumatic brain injury (BI), spinal cord injury (SCI), and neural implant-induced injury. By integrating transcriptomic datasets from brain and spinal cord injury models using weighted gene co-expression network analysis (WGCNA), six conserved ECM-associated gene modules are identified, with hyaluronan (HA)-centered networks emerging as the dominant and conserved regulatory axis across both injury types. Modules enriched for low-molecular-weight HA (LMW-HA) are linked to Toll-like receptor signaling and pro-inflammatory cytokine expression, whereas high-molecular-weight HA (HMW-HA)-associated modules correlate with Cd44 signaling, tissue stabilization and repair. Furthermore, independent validation in thin-film intracortical microelectrode datasets confirms robust activation of HA damage-associated molecular pattern (HA-DAMP) signaling following implantation, with 9/10 injury-derived modules preserved and 88% of transcripts exhibiting resolving temporal dynamics. These findings indicate that neural implants engage conserved trauma-associated ECM programs rather than a conventional foreign-body response, highlighting HA-related metabolisms. Given that HA fragments and HA-modifying enzymes are detectable in cerebrospinal fluid and peripheral circulation, HA-associated signatures may serve as minimally invasive biomarkers of neural injury and implant biocompatibility, enabling longitudinal monitoring and informing next-generation neural interface design.
- organism: mouse
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
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