Abstract
High-cervical spinal cord injury (SCI) often disrupts respiratory motor pathways and disables breathing in the affected population. Moreover, cervically injured individuals are at risk for developing acute lung injury (ALI), which predicts substantial mortality rates. While the correlation between ALI and SCI has been found in the clinical setting, the field lacks an animal model to interrogate the fundamental biology of this relationship. To begin to address this gap, we performed an experimental cervical SCI and assessed lung injury in adult rats. We demonstrate that animals display signs of ALI two weeks post-SCI. We also observed aberrant N-glycan metabolism determined by matrix-assisted laser desorption/ionization mass spectrometry imaging. Collectively, we establish for the first time a model of ALI after SCI at an acute time point that can be used to monitor the progression of lung damage, as well as identify potential targets to ameliorate ALI.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Author Contribution Statement EEH and WJA conceived of and designed the work for this project. EEH acquired, analyzed, and interpreted its data, drafted, and revised this manuscript. BED and CMW were integral in the interpretation of data and training for this work. DBA provided assessment of the lung pathology. HAC, LEAY, and RCS provided the metabolomic work and analysis for this project. All authors assisted in editing this manuscript.
Impact statement This research establishes a model of cervical spinal cord injury-induced lung injury that can be used to study the progression of lung injury after SCI. This approach demonstrates the physiological consequences of SCI that contribute to acute lung injury.
Funding Information This publication was financially supported by NIH R01 NS101105 (WJA). NIH R01 HL131526 (CMW), NIH R01 HL151419 (CMW), NIH R01 AG066653 (RCS), and 1R21NS121966-01 (WJA).
This publication was supported by the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant UL1TR001998. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Research reported in this publication was supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under grant number P20GM103527.