Abstract

Traumatic spinal cord injury (SCI) produces a complex syndrome that is expressed across multiple endpoints ranging from molecular and cellular changes to functional behavioral deficits. Effective therapeutic strategies for CNS injury are therefore likely to manifest multi-factorial effects across a broad range of biological and functional outcome measures. Thus, multivariate analytic approaches are needed to capture the linkage between biological and neurobehavioral outcomes. Injury-induced neuroinflammation (NI) presents a particularly challenging therapeutic target, since NI is involved in both degeneration and repair. Here, we used big-data integration and large-scale analytics to examine a large dataset of preclinical efficacy tests combining five different blinded, fully counter-balanced treatment trials for different acute anti-inflammatory treatments for cervical spinal cord injury in rats. Multi-dimensional discovery, using topological data analysis (TDA) and principal components analysis (PCA) revealed that only one showed consistent multidimensional syndromic benefit: intrathecal application of recombinant soluble TNFα receptor 1 (sTNFR1), which showed an inverse-U dose response efficacy. Using the optimal acute dose, we showed that clinically-relevant 90 min delayed treatment profoundly affected multiple biological indices of NI in the first 48 h after injury, including reduction in pro-inflammatory cytokines and gene expression of a coherent complex of acute inflammatory mediators and receptors. Further, a 90 min delayed bolus dose of sTNFR1 reduced the expression of NI markers in the chronic perilesional spinal cord, and consistently improved neurological function over 6 weeks post SCI. These results provide validation of a novel strategy for precision preclinical drug discovery that is likely to improve translation in the difficult landscape of CNS trauma, and confirm the importance of TNFα signaling as a therapeutic target.

Details

Title
Machine intelligence identifies soluble TNFa as a therapeutic target for spinal cord injury
Author
Huie, J R 1 ; Ferguson, A R 2 ; Kyritsis, N 1 ; Pan, J Z 3 ; K-A, Irvine 4 ; Nielson, J L 5 ; Schupp, P G 6 ; Oldham, M C 6 ; Gensel, J C 7 ; Lin, A 1 ; Segal, M R 8 ; Ratan, R R 9 ; Bresnahan, J C 1 ; Beattie, M S 1 

 University of California, Department of Neurological Surgery, Brain and Spinal Injury Center (BASIC), San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811) 
 University of California, Department of Neurological Surgery, Brain and Spinal Injury Center (BASIC), San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811); San Francisco Veterans Affairs Medical Center, San Francisco, USA (GRID:grid.410372.3) (ISNI:0000 0004 0419 2775) 
 University of California San Francisco, Department of Anesthesiology, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811) 
 Veterans Affairs Palo Alto Health Care System, Department of Anesthesiology, Palo Alto, USA (GRID:grid.280747.e) (ISNI:0000 0004 0419 2556); Stanford University, Department of Anesthesia, Perioperative Medicine and Pain, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956) 
 University of Minnesota, Department of Psychiatry and Behavioral Sciences, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000000419368657); University of Minnesota, Institute for Health Informatics, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000000419368657) 
 University of California, Brain Tumor Research Center, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811) 
 SCoBIRC, University of Kentucky, Lexington, USA (GRID:grid.266539.d) (ISNI:0000 0004 1936 8438) 
 University of California San Francisco, Department of Epidemiology and Biostatistics, Center for Bioinformatics and Molecular Biostatistics, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811) 
 Weill Medical College of Cornell University, Department of Neurology and Neuroscience, Burke-Cornell Medical Research Institute, New York, USA (GRID:grid.5386.8) (ISNI:000000041936877X) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2487663166
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.