Topological data analysis for discovery in preclinical spinal cord injury and traumatic brain injury

Jessica L. Nielson; Jesse Paquette; Aiwen W. Liu; Cristian F. Guandique; C. Amy Tovar; Tomoo Inoue; Karen Amanda Irvine; John C. Gensel; Jennifer Kloke; Tanya C. Petrossian; Pek Y. Lum; Gunnar E. Carlsson; Geoffrey T. Manley; Wise Young; Michael S. Beattie; Jacqueline C. Bresnahan; Adam R. Ferguson

doi:10.1038/ncomms9581

Topological data analysis for discovery in preclinical spinal cord injury and traumatic brain injury

Jessica L. Nielson, Jesse Paquette, Aiwen W. Liu, Cristian F. Guandique, C. Amy Tovar, Tomoo Inoue, Karen Amanda Irvine, John C. Gensel, Jennifer Kloke, Tanya C. Petrossian, Pek Y. Lum, Gunnar E. Carlsson, Geoffrey T. Manley, Wise Young, Michael S. Beattie, Jacqueline C. Bresnahan, Adam R. Ferguson

Producción científica: Article › revisión exhaustiva

166 Citas (Scopus)

Resumen

Data-driven discovery in complex neurological disorders has potential to extract meaningful syndromic knowledge from large, heterogeneous data sets to enhance potential for precision medicine. Here we describe the application of topological data analysis (TDA) for data-driven discovery in preclinical traumatic brain injury (TBI) and spinal cord injury (SCI) data sets mined from the Visualized Syndromic Information and Outcomes for Neurotrauma-SCI (VISION-SCI) repository. Through direct visualization of inter-related histopathological, functional and health outcomes, TDA detected novel patterns across the syndromic network, uncovering interactions between SCI and co-occurring TBI, as well as detrimental drug effects in unpublished multicentre preclinical drug trial data in SCI. TDA also revealed that perioperative hypertension predicted long-term recovery better than any tested drug after thoracic SCI in rats. TDA-based data-driven discovery has great potential application for decision-support for basic research and clinical problems such as outcome assessment, neurocritical care, treatment planning and rapid, precision-diagnosis.

Idioma original	English
Número de artículo	8581
Publicación	Nature Communications
Volumen	6
DOI	https://doi.org/10.1038/ncomms9581
Estado	Published - oct 14 2015

Nota bibliográfica

Publisher Copyright:
© 2015 Macmillan Publishers Limited.

Financiación

This work was funded by the Craig H. Neilsen Foundation Grant 224308, the National Institutes of Health (NIH) NS067092 (A.R.F.), NS069537 (A.R.F), NS038079 (J.C.B. and M.S.B.), NS031193 and AG032518 (M.S.B. and J.C.B.), NS079030 (J.L.N.), NS032000 (W.Y.; M.S.B. site PI, multicentre study); NYSCoRE CO19772 (M.S.B. and J.C.B.), the Department of Defense (DoD) grants W81XWH-10-1-0910 (M.S.B.) and W81XWH-13-1-0297 (M.S.B.), and Wings for Life Foundation grants WFLUS008/12 and WFLUS006/ 14 (A.R.F.). We thank J.R. Huie and J. Haefeli for useful comments, and A. Lin and S. Visuthikraisee for technical support.

Financiadores	Número del financiador
National Institutes of Health (NIH)	NS038079, NS067092, AG032518, NS069537, NYSCoRE CO19772, NS032000, NS031193
National Institutes of Health (NIH)
U.S. Department of Defense	W81XWH-13-1-0297, W81XWH-10-1-0910
U.S. Department of Defense
Institute of Neurological Disorders and Stroke National Advisory Neurological Disorders and Stroke Council	F32NS079030
Institute of Neurological Disorders and Stroke National Advisory Neurological Disorders and Stroke Council
Craig H. Neilsen Foundation	224308
Craig H. Neilsen Foundation
Wings for Life Spinal Cord Research Foundation	WFLUS006/ 14, WFLUS008/12
Wings for Life Spinal Cord Research Foundation

ASJC Scopus subject areas

General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy

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10.1038/ncomms9581

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Nielson, J. L., Paquette, J., Liu, A. W., Guandique, C. F., Tovar, C. A., Inoue, T., Irvine, K. A., Gensel, J. C., Kloke, J., Petrossian, T. C., Lum, P. Y., Carlsson, G. E., Manley, G. T., Young, W., Beattie, M. S., Bresnahan, J. C., & Ferguson, A. R. (2015). Topological data analysis for discovery in preclinical spinal cord injury and traumatic brain injury. Nature Communications, 6, Artículo 8581. https://doi.org/10.1038/ncomms9581

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abstract = "Data-driven discovery in complex neurological disorders has potential to extract meaningful syndromic knowledge from large, heterogeneous data sets to enhance potential for precision medicine. Here we describe the application of topological data analysis (TDA) for data-driven discovery in preclinical traumatic brain injury (TBI) and spinal cord injury (SCI) data sets mined from the Visualized Syndromic Information and Outcomes for Neurotrauma-SCI (VISION-SCI) repository. Through direct visualization of inter-related histopathological, functional and health outcomes, TDA detected novel patterns across the syndromic network, uncovering interactions between SCI and co-occurring TBI, as well as detrimental drug effects in unpublished multicentre preclinical drug trial data in SCI. TDA also revealed that perioperative hypertension predicted long-term recovery better than any tested drug after thoracic SCI in rats. TDA-based data-driven discovery has great potential application for decision-support for basic research and clinical problems such as outcome assessment, neurocritical care, treatment planning and rapid, precision-diagnosis.",

author = "Nielson, \{Jessica L.\} and Jesse Paquette and Liu, \{Aiwen W.\} and Guandique, \{Cristian F.\} and Tovar, \{C. Amy\} and Tomoo Inoue and Irvine, \{Karen Amanda\} and Gensel, \{John C.\} and Jennifer Kloke and Petrossian, \{Tanya C.\} and Lum, \{Pek Y.\} and Carlsson, \{Gunnar E.\} and Manley, \{Geoffrey T.\} and Wise Young and Beattie, \{Michael S.\} and Bresnahan, \{Jacqueline C.\} and Ferguson, \{Adam R.\}",

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Nielson, JL, Paquette, J, Liu, AW, Guandique, CF, Tovar, CA, Inoue, T, Irvine, KA, Gensel, JC, Kloke, J, Petrossian, TC, Lum, PY, Carlsson, GE, Manley, GT, Young, W, Beattie, MS, Bresnahan, JC & Ferguson, AR 2015, 'Topological data analysis for discovery in preclinical spinal cord injury and traumatic brain injury', Nature Communications, vol. 6, 8581. https://doi.org/10.1038/ncomms9581

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AU - Manley, Geoffrey T.

AU - Young, Wise

AU - Beattie, Michael S.

AU - Bresnahan, Jacqueline C.

AU - Ferguson, Adam R.

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N2 - Data-driven discovery in complex neurological disorders has potential to extract meaningful syndromic knowledge from large, heterogeneous data sets to enhance potential for precision medicine. Here we describe the application of topological data analysis (TDA) for data-driven discovery in preclinical traumatic brain injury (TBI) and spinal cord injury (SCI) data sets mined from the Visualized Syndromic Information and Outcomes for Neurotrauma-SCI (VISION-SCI) repository. Through direct visualization of inter-related histopathological, functional and health outcomes, TDA detected novel patterns across the syndromic network, uncovering interactions between SCI and co-occurring TBI, as well as detrimental drug effects in unpublished multicentre preclinical drug trial data in SCI. TDA also revealed that perioperative hypertension predicted long-term recovery better than any tested drug after thoracic SCI in rats. TDA-based data-driven discovery has great potential application for decision-support for basic research and clinical problems such as outcome assessment, neurocritical care, treatment planning and rapid, precision-diagnosis.

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Topological data analysis for discovery in preclinical spinal cord injury and traumatic brain injury

Resumen

Nota bibliográfica

Financiación

ASJC Scopus subject areas

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