Topological Data Analysis for Discovery in Preclinical Spinal Cord Injury and Traumatic Brain Injury

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the syndromic network, uncovering interactions between SCI and co-occurring TBI, as well as detrimental drug effects in unpublished multicentre preclinical drug trial data in SCI.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

Hyperparathyroidism and parathyroidectomy in X-linked hypophosphatemia patients

Background X-linked hypophosphatemia (XLH) causes rickets, osteomalacia, skeletal deformities and growth impairment, due to elevated fibroblast growth factor 23 and hypophosphatemia. Conventional therapy requires high doses of phosphate salts combined with active vitamin D analogues. Risks of this regimen include nephrocalcinosis and secondary hyperparathyroidism or progression to tertiary (hypercalcemic) hyperparathyroidism. Methods The primary goals were to estimate the prevalence of hyperparathyroidism and to characterize parathyroidectomy outcomes regarding hypercalcemia among XLH patients. XLH patients attending our center from 1/2000 to 12/2017 were included in a retrospective chart review. Prevalence of nephrocalcinosis and eGFR<60 mL/min/1.732 was also assessed. Results Of 104 patients with XLH, 84 had concurrent measurements of calcium and PTH (40 adults and 44 children). Of these, 70/84 (83.3%), had secondary or tertiary hyperparathyroidism at any time point. Secondary hyperparathyroidism was persistent in 62.2% of those with data at multiple timepoints. Tertiary hyperparathyroidism had an overall prevalence of 14/84 (16.7%) patients. Parathyroidectomy was performed in 8/84 (9.5%) of the total population. After parathyroidectomy, persistent or recurrent tertiary hyperparathyroidism was detected in 6/8 (75%) patients at a median of 6 years (from 0 to 29 years). One patient had chronic postoperative hypoparathyroidism and one patient remained normocalcemic 4 years after surgery. Nephrocalcinosis was more prevalent in patients with tertiary hyperparathyroidism than those without (60.0% vs 18.6%). Chronic kidney disease (eGFR<60 mL/min/1.732) was also more prevalent in patients with tertiary hyperparathyroidism than those without (35.7% vs 1.5%). Conclusion The majority of patients with XLH develop secondary hyperparathyroidism during treatment with phosphate and active vitamin D. A significant proportion develops tertiary hyperparathyroidism and most have recurrence or persistence of hypercalcemia after surgery

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

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

Leveraging biomedical informatics for assessing plasticity and repair in primate spinal cord injury

Recent preclinical advances highlight the therapeutic potential of treatments aimed at boosting regeneration and plasticity of spinal circuitry damaged by spinal cord injury (SCI). With several promising candidates being considered for translation into clinical trials, the SCI community has called for a non-human primate model as a crucial validation step to test efficacy and validity of these therapies prior to human testing. The present paper reviews the previous and ongoing efforts of the California Spinal Cord Consortium (CSCC), a multi-disciplinary team of experts from 5 University of California medical and research centers, to develop this crucial translational SCI model. We focus on the growing volumes of high resolution data collected by the CSCC, and our efforts to develop a biomedical informatics framework aimed at leveraging multidimensional data to monitor plasticity and repair targeting recovery of hand and arm function. Although the main focus of many researchers is the restoration of voluntary motor control, we also describe our ongoing efforts to add assessments of sensory function, including pain, vital signs during surgery, and recovery of bladder and bowel function. By pooling our multidimensional data resources and building a unified database infrastructure for this clinically relevant translational model of SCI, we are now in a unique position to test promising therapeutic strategies' efficacy on the entire syndrome of SCI. We review analyses highlighting the intersection between motor, sensory, autonomic and pathological contributions to the overall restoration of function. This article is part of a Special Issue entitled SI: Spinal cord injury. (C) 2014 Elsevier B.V. All rights reserved

Leveraging biomedical informatics for assessing plasticity and repair in primate spinal cord injury

Recent preclinical advances highlight the therapeutic potential of treatments aimed at boosting regeneration and plasticity of spinal circuitry damaged by spinal cord injury (SCI). With several promising candidates being considered for translation into clinical trials, the SCI community has called for a non-human primate model as a crucial validation step to test efficacy and validity of these therapies prior to human testing. The present paper reviews the previous and ongoing efforts of the California Spinal Cord Consortium (CSCC), a multidisciplinary team of experts from 5 University of California medical and research centers, to develop this crucial translational SCI model. We focus on the growing volumes of high resolution data collected by the CSCC, and our efforts to develop a biomedical informatics framework aimed at leveraging multidimensional data to monitor plasticity and repair targeting recovery of hand and arm function. Although the main focus of many researchers is the restoration of voluntary motor control, we also describe our ongoing efforts to add assessments of sensory function, including pain, vital signs during surgery, and recovery of bladder and bowel function. By pooling our multidimensional data resources and building a unified database infrastructure for this clinically relevant translational model of SCI, we are now in a unique position to test promising therapeutic strategies' efficacy on the entire syndrome of SCI. We review analyses highlighting the intersection between motor, sensory, autonomic and pathological contributions to the overall restoration of function. This article is part of a Special Issue entitled SI: Spinal cord injury

Development of a Database for Translational Spinal Cord Injury Research

Efforts to understand spinal cord injury (SCI) and other complex neurotrauma disorders at the pre-clinical level have shown progress in recent years. However, successful translation of basic research into clinical practice has been slow, partly because of the large, heterogeneous data sets involved. In this sense, translational neurological research represents a "big data" problem. In an effort to expedite translation of pre-clinical knowledge into standards of patient care for SCI, we describe the development of a novel database for translational neurotrauma research known as Visualized Syndromic Information and Outcomes for Neurotrauma-SCI (VISION-SCI). We present demographics, descriptive statistics, and translational syndromic outcomes derived from our ongoing efforts to build a multi-center, multi-species pre-clinical database for SCI models. We leveraged archived surgical records, postoperative care logs, behavioral outcome measures, and histopathology from approximately 3000 mice, rats, and monkeys from pre-clinical SCI studies published between 1993 and 2013. The majority of animals in the database have measures collected for health monitoring, such as weight loss/gain, heart rate, blood pressure, postoperative monitoring of bladder function and drug/fluid administration, behavioral outcome measures of locomotion, and tissue sparing postmortem. Attempts to align these variables with currently accepted common data elements highlighted the need for more translational outcomes to be identified as clinical endpoints for therapeutic testing. Last, we use syndromic analysis to identify conserved biological mechanisms of recovery after cervical SCI between rats and monkeys that will allow for more-efficient testing of therapeutics that will need to be translated toward future clinical trials