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bioRxiv · 10.1101/2020.07.22.216572

Machine intelligence identifies soluble TNFa as a therapeutic target for spinal cord injury

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 repair1,2. Here, we used big-data integration and large-scale analytics to examine a large dataset of preclinical efficacy tests combining 5 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 analysis3 (TDA) and principal components analysis (PCA) revealed that only one showed consistent multidimensional syndromic benefit: intrathecal application of recombinant soluble TNF 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 hrs 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 TNF signaling as a therapeutic target.

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BibTeXRIS

Huie, J. R., Ferguson, A. R., Kyritsis, N., Pan, J., Irvine, K.-A., Nielson, J. L., Schupp, P., Oldham, M. C., Gensel, J. C., Lin, A., Segal, M. R., Ratan, R., Bresnahan, J. C., Beattie, M.. 2020-07-24. Machine intelligence identifies soluble TNFa as a therapeutic target for spinal cord injury. https://doi.org/10.1101/2020.07.22.216572

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