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

Longitudinal multiparametric MRI of traumatic spinal cord injury in animal models

Multi-parametric MRI (mpMRI) technology enables non-invasive and quantitative assessments of the structural, molecular, and functional characteristics of various neurological diseases. Despite the recognized importance of studying spinal cord pathology, mpMRI applications in spinal cord research have been somewhat limited, partly due to technical challenges associated with spine imaging. However, advances in imaging techniques and improved image quality now allow longitudinal investigations of a comprehensive range of spinal cord pathological features by exploiting different endogenous MRI contrasts. This review summarizes the use of mpMRI techniques including blood oxygenation level-dependent (BOLD) functional MRI (fMRI), diffusion tensor imaging (DTI), quantitative magnetization transfer (qMT), and chemical exchange saturation transfer (CEST) MRI in monitoring different aspects of spinal cord pathology. These aspects include cyst formation and axonal disruption, demyelination and remyelination, changes in the excitability of spinal grey matter and the integrity of intrinsic functional circuits, and non-specific molecular changes associated with secondary injury and neuroinflammation. These approaches are illustrated with reference to a nonhuman primate (NHP) model of traumatic cervical spinal cord injuries (SCI). We highlight the benefits of using NHP SCI models to guide future studies of human spinal cord pathology, and demonstrate how mpMRI can capture distinctive features of spinal cord pathology that were previously inaccessible. Furthermore, the development of mechanism-based MRI biomarkers from mpMRI studies can provide clinically useful imaging indices for understanding the mechanisms by which injured spinal cords progress and repair. These biomarkers can assist in the diagnosis, prognosis, and evaluation of therapies for SCI patients, potentially leading to improved outcomes.

A biocompatible gelatin sponge scaffold confers robust tissue remodeling after spinal cord injury in a non-human primate model

We previously constructed a three-dimensional gelatin sponge (3D-GS) scaffold as a delivery vehicle for therapeutic cells and trophic factors in the treatment of spinal cord injury (SCI), and this study aimed to assess the biosafety and efficacy of the scaffold in a non-human primate SCI model. However, because it has only been tested in rodent and canine models, the biosafety and efficacy of the scaffold should ideally be assessed in a non-human primate SCI model before its use in the clinic. No adverse reactions were observed over 8 weeks following 3D-GS scaffold implantation into in a Macaca fascicularis with hemisected SCI. Scaffold implantation also did not add to neuroinflammatory or astroglial responses already present at the injured site, suggesting good biocompatibility. Notably, there was a significant reduction in α-smooth muscle actin (αSMA)-positive cells at the injury/implantation interface, leading to alleviation of fibrotic compression of the residual spinal cord tissue. The regenerating tissue in the scaffold showed numerous cells migrating into the implant secreting abundant extracellular matrix, resulting in a pro-regenerative microenvironment. Consequently, nerve fiber regeneration, myelination, vascularization, neurogenesis, and electrophysiological improvements were achieved. These results indicated that the 3D-GS scaffold had good histocompatibility and effectiveness in the structural repair of injured spinal cord tissue in a non-human primate and is suitable for use in the treatment of patients with SCI.

Harmonization-Information Trade-Offs for Sharing Individual Participant Data in Biomedicine

Biomedical practice is evidence-based. Peer-reviewed papers are the primary medium to present evidence and data-supported results to drive clinical practice. However, it could be argued that scientific literature does not contain data, but rather narratives about and summaries of data. Meta-analyses of published literature may produce biased conclusions due to the lack of transparency in data collection, publication bias, and inaccessibility to the data underlying a publication ('dark data'). Co-analysis of pooled data at the level of individual research participants can offer higher levels of evidence, but this requires that researchers share raw individual participant data (IPD). FAIR (findable, accessible, interoperable, and reusable) data governance principles aim to guide data lifecycle management by providing a framework for actionable data sharing. Here we discuss the implications of FAIR for data harmonization, an essential step for pooling data for IPD analysis. We describe the harmonization-information trade-off, which states that the level of granularity in harmonizing data determines the amount of information lost. Finally, we discuss a framework for managing the trade-off and the levels of harmonization. In the coming era of funder mandates for data sharing, research communities that effectively manage data harmonization will be empowered to harness big data and advanced analytics such as machine learning and artificial intelligence tools, leading to stunning new discoveries that augment our understanding of diseases and their treatments. By elevating scientific data to the status of a first-class citizen of the scientific enterprise, there is strong potential for biomedicine to transition from a narrative publication product orientation to a modern data-driven enterprise where data itself is viewed as a primary work product of biomedical research.

Reproducible analysis of disease space via principal components using the novel R package syndRomics

Biomedical data are usually analyzed at the univariate level, focused on a single primary outcome measure to provide insight into systems biology, complex disease states, and precision medicine opportunities. More broadly, these complex biological and disease states can be detected as common factors emerging from the relationships among measured variables using multivariate approaches. ‘Syndromics’ refers to an analytical framework for measuring disease states using principal component analysis and related multivariate statistics as primary tools for extracting underlying disease patterns. A key part of the syndromic workflow is the interpretation, the visualization, and the study of robustness of the main components that characterize the disease space. We present a new software package, syndRomics, an open-source R package with utility for component visualization, interpretation, and stability for syndromic analysis. We document the implementation of syndRomics and illustrate the use of the package in case studies of neurological trauma data.

Neuroregeneration and plasticity: a review of the physiological mechanisms for achieving functional recovery postinjury

Neuronal networks, especially those in the central nervous system (CNS), evolved to support extensive functional capabilities while ensuring stability. Several physiological "brakes" that maintain the stability of the neuronal networks in a healthy state quickly become a hinderance postinjury. These "brakes" include inhibition from the extracellular environment, intrinsic factors of neurons and the control of neuronal plasticity. There are distinct differences between the neuronal networks in the peripheral nervous system (PNS) and the CNS. Underpinning these differences is the trade-off between reduced functional capabilities with increased adaptability through the formation of new connections and new neurons. The PNS has "facilitators" that stimulate neuroregeneration and plasticity, while the CNS has "brakes" that limit them. By studying how these "facilitators" and "brakes" work and identifying the key processes and molecules involved, we can attempt to apply these theories to the neuronal networks of the CNS to increase its adaptability. The difference in adaptability between the CNS and PNS leads to a difference in neuroregenerative properties and plasticity. Plasticity ensures quick functional recovery of abilities in the short and medium term. Neuroregeneration involves synthesizing new neurons and connections, providing extra resources in the long term to replace those damaged by the injury, and achieving a lasting functional recovery. Therefore, by understanding the factors that affect neuroregeneration and plasticity, we can combine their advantages and develop rehabilitation techniques. Rehabilitation training methods, coordinated with pharmacological interventions and/or electrical stimulation, contributes to a precise, holistic treatment plan that achieves functional recovery from nervous system injuries. Furthermore, these techniques are not limited to limb movement, as other functions lost as a result of brain injury, such as speech, can also be recovered with an appropriate training program.

Applying univariate vs. multivariate statistics to investigate therapeutic efficacy in (pre)clinical trials: A Monte Carlo simulation study on the example of a controlled preclinical neurotrauma trial

BACKGROUND

Small sample sizes combined with multiple correlated endpoints pose a major challenge in the statistical analysis of preclinical neurotrauma studies. The standard approach of applying univariate tests on individual response variables has the advantage of simplicity of interpretation, but it fails to account for the covariance/correlation in the data. In contrast, multivariate statistical techniques might more adequately capture the multi-dimensional pathophysiological pattern of neurotrauma and therefore provide increased sensitivity to detect treatment effects.

RESULTS

We systematically evaluated the performance of univariate ANOVA, Welch's ANOVA and linear mixed effects models versus the multivariate techniques, ANOVA on principal component scores and MANOVA tests by manipulating factors such as sample and effect size, normality and homogeneity of variance in computer simulations. Linear mixed effects models demonstrated the highest power when variance between groups was equal or variance ratio was 1:2. In contrast, Welch's ANOVA outperformed the remaining methods with extreme variance heterogeneity. However, power only reached acceptable levels of 80% in the case of large simulated effect sizes and at least 20 measurements per group or moderate effects with at least 40 replicates per group. In addition, we evaluated the capacity of the ordination techniques, principal component analysis (PCA), redundancy analysis (RDA), linear discriminant analysis (LDA), and partial least squares discriminant analysis (PLS-DA) to capture patterns of treatment effects without formal hypothesis testing. While LDA suffered from a high false positive rate due to multicollinearity, PCA, RDA, and PLS-DA were robust and PLS-DA outperformed PCA and RDA in capturing a true treatment effect pattern.

CONCLUSIONS

Multivariate tests do not provide an appreciable increase in power compared to univariate techniques to detect group differences in preclinical studies. However, PLS-DA seems to be a useful ordination technique to explore treatment effect patterns without formal hypothesis testing.

FAIR SCI Ahead: The Evolution of the Open Data Commons for Pre-Clinical Spinal Cord Injury Research

Over the last 5 years, multiple stakeholders in the field of spinal cord injury (SCI) research have initiated efforts to promote publications standards and enable sharing of experimental data. In 2016, the National Institutes of Health/National Institute of Neurological Disorders and Stroke hosted representatives from the SCI community to streamline these efforts and discuss the future of data sharing in the field according to the FAIR (Findable, Accessible, Interoperable and Reusable) data stewardship principles. As a next step, a multi-stakeholder group hosted a 2017 symposium in Washington, DC entitled "FAIR SCI Ahead: the Evolution of the Open Data Commons for Spinal Cord Injury research." The goal of this meeting was to receive feedback from the community regarding infrastructure, policies, and organization of a community-governed Open Data Commons (ODC) for pre-clinical SCI research. Here, we summarize the policy outcomes of this meeting and report on progress implementing these policies in the form of a digital ecosystem: the Open Data Commons for Spinal Cord Injury (ODC-SCI.org). ODC-SCI enables data management, harmonization, and controlled sharing of data in a manner consistent with the well-established norms of scholarly publication. Specifically, ODC-SCI is organized around virtual "laboratories" with the ability to share data within each of three distinct data-sharing spaces: within the laboratory, across verified laboratories, or publicly under a creative commons license (CC-BY 4.0) with a digital object identifier that enables data citation. The ODC-SCI implements FAIR data sharing and enables pooled data-driven discovery while crediting the generators of valuable SCI data.

Accuracy of image-guided percutaneous injection into a phantom spinal cord utilizing flat panel detector CT with MR fusion and integrated navigational software

PURPOSE

To evaluate the accuracy of percutaneous fluoroscopic injection into the spinal cord of a spine phantom utilizing integrated navigational guidance from fused flat panel detector CT (FDCT) and MR datasets. Conventional and convection-enhanced delivery (CED) techniques were evaluated.

MATERIALS AND METHODS

FDCT and MR datasets of a swine thoracic spine phantom were co-registered using an integrated guidance system and surface to spinal cord target trajectory planning was performed on the fused images. Under real-time fluoroscopic guidance with pre-planned trajectory overlay, spinal cord targets were accessed via a coaxial technique. Final needle tip position was compared with a pre-determined target on 10 independent passes. In a subset of cases, contrast was injected into the central spinal cord with a 25G spinal needle or customized 200 µm inner diameter step design cannula for CED.

RESULTS

Average needle tip deviation from target measured 0.92±0.5 mm in the transverse, 0.47±0.4 mm in the anterior-posterior, and 1.67±1.2 mm in the craniocaudal dimension for an absolute distance error of 2.12±1.12 mm. CED resulted in elliptical intramedullary diffusion of contrast compared with primary reflux observed with standard needle injection.

CONCLUSIONS

These phantom feasibility data demonstrate a minimally invasive percutaneous approach for targeted injection into the spinal cord utilizing real-time fluoroscopy aided by overlay trajectories derived from fused MRI and FDCT data sets with a target error of 2.1 mm. Intramedullary diffusion of injectate in the spinal cord is facilitated with CED compared with standard injection technique. Pre-clinical studies in large animal models are warranted.

Developing a data sharing community for spinal cord injury research

The rapid growth in data sharing presents new opportunities across the spectrum of biomedical research. Global efforts are underway to develop practical guidance for implementation of data sharing and open data resources. These include the recent recommendation of 'FAIR Data Principles', which assert that if data is to have broad scientific value, then digital representations of that data should be Findable, Accessible, Interoperable and Reusable (FAIR). The spinal cord injury (SCI) research field has a long history of collaborative initiatives that include sharing of preclinical research models and outcome measures. In addition, new tools and resources are being developed by the SCI research community to enhance opportunities for data sharing and access. With this in mind, the National Institute of Neurological Disorders and Stroke (NINDS) at the National Institutes of Health (NIH) hosted a workshop on October 5-6, 2016 in Bethesda, MD, in collaboration with the Open Data Commons for Spinal Cord Injury (ODC-SCI) titled "Preclinical SCI Data: Creating a FAIR Share Community". Workshop invitees were nominated by the workshop steering committee (co-chairs: ARF and VPL; members: AC, KDA, MSB, KF, LBJ, PGP, JMS), to bring together junior and senior level experts including preclinical and basic SCI researchers from academia and industry, data science and bioinformatics experts, investigators with expertise in other neurological disease fields, clinical researchers, members of the SCI community, and program staff representing federal and private funding agencies. The workshop and ODC-SCI efforts were sponsored by the International Spinal Research Trust (ISRT), the Rick Hansen Institute, Wings for Life, the Craig H. Neilsen Foundation and NINDS. The number of attendees was limited to ensure active participation and feedback in small groups. The goals were to examine the current landscape for data sharing in SCI research and provide a path to its future. Below are highlights from the workshop, including perspectives on the value of data sharing in SCI research, workshop participant perspectives and concerns, descriptions of existing resources and actionable directions for further engaging the SCI research community in a model that may be applicable to many other areas of neuroscience. This manuscript is intended to share these initial findings with the broader research community, and to provide talking points for continued feedback from the SCI field, as it continues to move forward in the age of data sharing.

A ventral root avulsion injury model for neurogenic underactive bladder studies

Detrusor underactivity (DU) is defined as a contraction of reduced strength and/or duration during bladder emptying and results in incomplete and prolonged bladder emptying. The clinical diagnosis of DU is challenging when present alone or in association with other bladder conditions such as detrusor overactivity, urinary retention, detrusor hyperactivity with impaired contractility, aging, and neurological injuries. Several etiologies may be responsible for DU or the development of an underactive bladder (UAB), but the pathobiology of DU or UAB is not well understood. Therefore, new clinically relevant and interpretable models for studies of UAB are much needed in order to make progress towards new treatments and preventative strategies. Here, we review a neuropathic cause of DU in the form of traumatic injuries to the cauda equina (CE) and conus medullaris (CM) portions of the spinal cord. Lumbosacral ventral root avulsion (VRA) injury models in rats mimic the clinical phenotype of CM/CE injuries. Bilateral VRA injuries result in bladder areflexia, whereas a unilateral lesion results in partial impairment of lower urinary tract and visceromotor reflexes. Surgical re-implantation of avulsed ventral roots into the spinal cord and pharmacological strategies can augment micturition reflexes. The translational research need for the development of a large animal model for UAB studies is also presented, and early studies of lumbosacral VRA injuries in rhesus macaques are discussed.

Radiographic and Magnetic Resonance Imaging Identification of Thoracolumbar Spine Variants with Implications for the Positioning of the Conus Medullaris in Rhesus Macaques

The anatomy of the vertebral column in mammals may differ between species and between subjects of the same species, especially with regards to the composition of the thoracolumbar spine. We investigated, using several noninvasive imaging techniques, the thoracolumbar spine of a total of 44 adult rhesus macaques of both genders. Radiographic examination of the vertebral column showed a predominant spine phenotype with 12 rib-bearing thoracic vertebrae and 7 lumbar vertebrae without ribs in 82% of subjects, whereas a subset of subjects demonstrated 13 rib-bearing thoracic vertebrae and 6 lumbar vertebrae without ribs. Computer tomography studies of the thoraco-lumbar spine in two cases with a pair of supernumerary ribs showed facet joints between the most caudal pair of ribs and the associated vertebra, supporting a thoracic phenotype. Magnetic resonance imaging (MRI) studies were used to determine the relationship between the lumbosacral spinal cord and the vertebral column. The length of the conus medullaris portion of the spinal cord was 1.5 ± 0.3 vertebral units, and its rostral and caudal positions in the spinal canal were at 2.0 ± 0.3 and 3.6 ± 0.4 vertebral units below the thoracolumbar junction, respectively (n = 44). The presence of a set of supernumerary ribs did not affect the length or craniocaudal position of the conus medullaris, and subjects with13 rib-bearing vertebrae may from a functional or spine surgical perspective be considered as exhibiting12 thoracic vertebrae and an L1 vertebra with ribs. Anat Rec, 300:300-308, 2017. © 2016 Wiley Periodicals, Inc.

Plasticity and Recovery After Dorsal Column Spinal Cord Injury in Nonhuman Primates

Here, we review recent work on plasticity and recovery after dorsal column spinal cord injury in nonhuman primates. Plasticity in the adult central nervous system has been established and studied for the past several decades; however, capacities and limits of plasticity are still under investigation. Studies of plasticity include assessing multiple measures before and after injury in animal models. Such studies are particularly important for improving recovery after injury in patients. In summarizing work by our research team and others, we suggest how the findings from plasticity studies in nonhuman primate models may affect therapeutic interventions for conditions involving sensory loss due to spinal cord injury.

A Unilateral Cervical Spinal Cord Contusion Injury Model in Non-Human Primates (Macaca mulatta)

The development of a non-human primate (NHP) model of spinal cord injury (SCI) based on mechanical and computational modeling is described. We scaled up from a rodent model to a larger primate model using a highly controllable, friction-free, electronically-driven actuator to generate unilateral C6-C7 spinal cord injuries. Graded contusion lesions with varying degrees of functional recovery, depending upon pre-set impact parameters, were produced in nine NHPs. Protocols and pre-operative magnetic resonance imaging (MRI) were used to optimize the predictability of outcomes by matching impact protocols to the size of each animal's spinal canal, cord, and cerebrospinal fluid space. Post-operative MRI confirmed lesion placement and provided information on lesion volume and spread for comparison with histological measures. We evaluated the relationships between impact parameters, lesion measures, and behavioral outcomes, and confirmed that these relationships were consistent with our previous studies in the rat. In addition to providing multiple univariate outcome measures, we also developed an integrated outcome metric describing the multivariate cervical SCI syndrome. Impacts at the higher ranges of peak force produced highly lateralized and enduring deficits in multiple measures of forelimb and hand function, while lower energy impacts produced early weakness followed by substantial recovery but enduring deficits in fine digital control (e.g., pincer grasp). This model provides a clinically relevant system in which to evaluate the safety and, potentially, the efficacy of candidate translational therapies.