A practical guide to data management and sharing for biomedical laboratory researchers

Effective data management and sharing have become increasingly crucial in biomedical research; however, many laboratory researchers lack the necessary tools and knowledge to address this challenge. This article provides an introductory guide into research data management (RDM), and the importance of FAIR (Findable, Accessible, Interoperable, and Reusable) data-sharing principles for laboratory researchers produced by practicing scientists. We explore the advantages of implementing organized data management strategies and introduce key concepts such as data standards, data documentation, and the distinction between machine and human-readable data formats. Furthermore, we offer practical guidance for creating a data management plan and establishing efficient data workflows within the laboratory setting, suitable for labs of all sizes. This includes an examination of requirements analysis, the development of a data dictionary for routine data elements, the implementation of unique subject identifiers, and the formulation of standard operating procedures (SOPs) for seamless data flow. To aid researchers in implementing these practices, we present a simple organizational system as an illustrative example, which can be tailored to suit individual needs and research requirements. By presenting a user-friendly approach, this guide serves as an introduction to the field of RDM and offers practical tips to help researchers effortlessly meet the common data management and sharing mandates rapidly becoming prevalent in biomedical research.

ATF3 is a neuron-specific biomarker for spinal cord injury and ischaemic stroke

BACKGROUND

Although many molecules have been investigated as biomarkers for spinal cord injury (SCI) or ischemic stroke, none of them are specifically induced in central nervous system (CNS) neurons following injuries with low baseline expression. However, neuronal injury constitutes a major pathology associated with SCI or stroke and strongly correlates with neurological outcomes. Biomarkers characterized by low baseline expression and specific induction in neurons post-injury are likely to better correlate with injury severity and recovery, demonstrating higher sensitivity and specificity for CNS injuries compared to non-neuronal markers or pan-neuronal markers with constitutive expressions.

METHODS

In animal studies, young adult wildtype and global Atf3 knockout mice underwent unilateral cervical 5 (C5) SCI or permanent distal middle cerebral artery occlusion (pMCAO). Gene expression was assessed using RNA-sequencing and qRT-PCR, while protein expression was detected through immunostaining. Serum ATF3 levels in animal models and clinical human samples were measured using commercially available enzyme-linked immune-sorbent assay (ELISA) kits.

RESULTS

Activating transcription factor 3 (ATF3), a molecular marker for injured dorsal root ganglion sensory neurons in the peripheral nervous system, was not expressed in spinal cord or cortex of naïve mice but was induced specifically in neurons of the spinal cord or cortex within 1 day after SCI or ischemic stroke, respectively. Additionally, ATF3 protein levels in mouse blood significantly increased 1 day after SCI or ischemic stroke. Importantly, ATF3 protein levels in human serum were elevated in clinical patients within 24 hours after SCI or ischemic stroke. Moreover, Atf3 knockout mice, compared to the wildtype mice, exhibited worse neurological outcomes and larger damage regions after SCI or ischemic stroke, indicating that ATF3 has a neuroprotective function.

CONCLUSIONS

ATF3 is an easily measurable, neuron-specific biomarker for clinical SCI and ischemic stroke, with neuroprotective properties.

HIGHLIGHTS

ATF3 was induced specifically in neurons of the spinal cord or cortex within 1 day after SCI or ischemic stroke, respectively. Serum ATF3 protein levels are elevated in clinical patients within 24 hours after SCI or ischemic stroke. ATF3 exhibits neuroprotective properties, as evidenced by the worse neurological outcomes and larger damage regions observed in Atf3 knockout mice compared to wildtype mice following SCI or ischemic stroke.

Correction: Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome

[This corrects the article DOI: 10.1371/journal.pone.0265254.].

Safety and comparative efficacy of initiating low-molecular-weight heparin within 24 hours of injury or surgery for venous thromboembolism prophylaxis in patients with spinal cord injury: a prospective TRACK-SCI registry study

OBJECTIVE

Venous thromboembolism (VTE) following traumatic spinal cord injury (SCI) is a significant clinical concern. This study sought to determine the incidence of VTE and hemorrhagic complications among patients with SCI who received low-molecular-weight heparin (LMWH) within 24 hours of injury or surgery and identify variables that predict VTE using the prospective Transforming Research and Clinical Knowledge in SCI (TRACK-SCI) database.

METHODS

The TRACK-SCI database was queried for individuals with traumatic SCI from 2015 to 2022. Primary outcomes of interest included rates of VTE (including deep vein thrombosis [DVT] and pulmonary embolism [PE]) and in-hospital hemorrhagic complications that occurred after LWMH administration. Secondary outcomes included intensive care unit and hospital length of stay, discharge location type, and in-hospital mortality.

RESULTS

The study cohort consisted of 162 patients with SCI. Fifteen of the 162 patients withdrew from the study, leading to loss of data for certain variables for these patients. One hundred thirty patients (87.8%) underwent decompression and/or fusion surgery for SCI. DVT occurred in 11 (7.4%) of 148 patients, PE in 9 (6.1%) of 148, and any VTE in 18 (12.2%) of 148 patients. The analysis showed that admission lower-extremity motor score (p = 0.0408), injury at the thoracic level (p = 0.0086), admission American Spinal Injury Association grade (p = 0.0070), and younger age (p = 0.0372) were significantly associated with VTE. There were 3 instances of postoperative spine surgery-related bleeding (2.4%) in the 127 patients who had spine surgery with bleeding complication data available, with one requiring return to surgery (0.8%). Thirteen (8.8%) of 147 patients had a bleeding complication not related to spine surgery. There were 2 gastrointestinal bleeds associated with nasogastric tube placement, 3 cases of postoperative non-spine-related surgery bleeding, and 8 cases of other bleeding complications (5.4%) not related to any surgery.

CONCLUSIONS

Initiation of LMWH within 24 hours was associated with a low rate of spine surgery-related bleeding. Bleeding complications unrelated to SCI surgery still occur with LMWH administration. Because neurosurgical intervention is typically the limiting factor in initializing chemical DVT prophylaxis, many of these bleeding complications would have likely occurred regardless of the protocol.

Longitudinal Recovery Following Repetitive Traumatic Brain Injury

Importance

One traumatic brain injury (TBI) increases the risk of subsequent TBIs. Research on longitudinal outcomes of civilian repetitive TBIs is limited.

Objective

To investigate associations between sustaining 1 or more TBIs (ie, postindex TBIs) after study enrollment (ie, index TBIs) and multidimensional outcomes at 1 year and 3 to 7 years.

Design, Setting, and Participants

This cohort study included participants presenting to emergency departments enrolled within 24 hours of TBI in the prospective, 18-center Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study (enrollment years, February 2014 to July 2020). Participants who completed outcome assessments at 1 year and 3 to 7 years were included. Data were analyzed from September 2022 to August 2023.

Exposures

Postindex TBI(s).

Main Outcomes and Measures

Demographic and clinical factors, prior TBI (ie, preindex TBI), and functional (Glasgow Outcome Scale-Extended [GOSE]), postconcussive (Rivermead Post-Concussion Symptoms Questionnaire [RPQ]), psychological distress (Brief Symptom Inventory-18 [BSI-18]), depressive (Patient Health Questionnaire-9 [PHQ-9]), posttraumatic stress disorder (PTSD; PTSD Checklist for DSM-5 [PCL-5]), and health-related quality-of-life (Quality of Life After Brain Injury-Overall Scale [QOLIBRI-OS]) outcomes were assessed. Adjusted mean differences (aMDs) and adjusted relative risks are reported with 95% CIs.

Results

Of 2417 TRACK-TBI participants, 1572 completed the outcomes assessment at 1 year (1049 [66.7%] male; mean [SD] age, 41.6 [17.5] years) and 1084 completed the outcomes assessment at 3 to 7 years (714 [65.9%] male; mean [SD] age, 40.6 [17.0] years). At 1 year, a total of 60 participants (4%) were Asian, 255 (16%) were Black, 1213 (77%) were White, 39 (2%) were another race, and 5 (0.3%) had unknown race. At 3 to 7 years, 39 (4%) were Asian, 149 (14%) were Black, 868 (80%) were White, 26 (2%) had another race, and 2 (0.2%) had unknown race. A total of 50 (3.2%) and 132 (12.2%) reported 1 or more postindex TBIs at 1 year and 3 to 7 years, respectively. Risk factors for postindex TBI were psychiatric history, preindex TBI, and extracranial injury severity. At 1 year, compared with those without postindex TBI, participants with postindex TBI had worse functional recovery (GOSE score of 8: adjusted relative risk, 0.57; 95% CI, 0.34-0.96) and health-related quality of life (QOLIBRI-OS: aMD, -15.9; 95% CI, -22.6 to -9.1), and greater postconcussive symptoms (RPQ: aMD, 8.1; 95% CI, 4.2-11.9), psychological distress symptoms (BSI-18: aMD, 5.3; 95% CI, 2.1-8.6), depression symptoms (PHQ-9: aMD, 3.0; 95% CI, 1.5-4.4), and PTSD symptoms (PCL-5: aMD, 7.8; 95% CI, 3.2-12.4). At 3 to 7 years, these associations remained statistically significant. Multiple (2 or more) postindex TBIs were associated with poorer outcomes across all domains.

Conclusions and Relevance

In this cohort study of patients with acute TBI, postindex TBI was associated with worse symptomatology across outcome domains at 1 year and 3 to 7 years postinjury, and there was a dose-dependent response with multiple postindex TBIs. These results underscore the critical need to provide TBI prevention, education, counseling, and follow-up care to at-risk patients.

Improving rigor and reproducibility in western blot experiments with the blotRig analysis software

Western blot is a popular biomolecular analysis method for measuring the relative quantities of independent proteins in complex biological samples. However, variability in quantitative western blot data analysis poses a challenge in designing reproducible experiments. The lack of rigorous quantitative approaches in current western blot statistical methodology may result in irreproducible inferences. Here we describe best practices for the design and analysis of western blot experiments, with examples and demonstrations of how different analytical approaches can lead to widely varying outcomes. To facilitate best practices, we have developed the blotRig tool for designing and analyzing western blot experiments to improve their rigor and reproducibility. The blotRig application includes functions for counterbalancing experimental design by lane position, batch management across gels, and analytics with covariates and random effects.

Associations of Microvascular Injury-Related Biomarkers With Traumatic Brain Injury Severity and Outcomes: A Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Pilot Study

Traumatic brain injury (TBI) is characterized by heterogeneity in terms of injury severity, mechanism, outcome, and pathophysiology. A single biomarker alone is unlikely to capture the heterogeneity of even one injury subtype, necessitating the use of panels of biomarkers. Herein, we focus on traumatic cerebrovascular injury and investigate associations of a panel of 16 vascular injury-related biomarkers with indices of TBI severity and outcomes using data from 159 participants in the Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) Pilot Study. Associations of individual biomarkers and clusters of biomarkers identified using non-linear principal components analysis with TBI severity and outcomes were assessed using logistic regression models and Spearman's correlations. As individual biomarkers, higher levels of thrombomodulin, angiopoietin (Ang)-2, von Willebrand factor, and P-selectin were associated with more severe injury; higher levels of Ang-1, Tie2, vascular endothelial growth factor (VEGF)-C, and basic fibroblast growth factor (bFGF) were associated with less severe injury (all p < 0.05 in age-adjusted models). After false discovery rate correction for multiple comparisons, higher levels of Ang-2 remained associated with more severe injury and higher levels of Ang-1, Tie2, and bFGF remained associated with less severe injury at a p < 0.05 level. In principal components analysis, principal component (PC)1, comprised of Ang1, bFGF, P-selectin, VEGF-C, VEGF-A, and Tie2, was associated with less severe injury (age-adjusted odds ratio [OR]: 0.63, 95% confidence interval [CI]: 0.44-0.88 for head computer tomography [CT] positive vs. negative) and PC2 (Ang-2, E-selectin, Flt-1, placental growth factor, thrombomodulin, and vascular cell adhesion protein 1) was associated with greater injury severity (age-adjusted OR: 2.29, 95% CI: 1.49-3.69 for Glasgow Coma Scale [GCS] 3-12 vs. 13-15 and age-adjusted OR 1.59, 95% CI: 1.11-2.32 for head CT positive vs. negative). Neither individual biomarkers nor PCs were associated with outcomes in adjusted models (all p > 0.05). In conclusion, in this trauma-center based population of acute TBI patients, biomarkers of microvascular injury were associated with TBI severity.

Toward a causal model of chronic back pain: Challenges and opportunities

Chronic low back pain (cLBP) afflicts 8. 2% of adults in the United States, and is the leading global cause of disability. Neuropsychiatric co-morbidities including anxiety, depression, and substance abuse- are common in cLBP patients. In particular, cLBP is a risk factor for opioid addiction, as more than 50% of opioid prescriptions in the United States are for cLBP. Misuse of these prescriptions is a common precursor to addiction. While associations between cLBP and neuropsychiatric disorders are well established, causal relationships for the most part are unknown. Developing effective treatments for cLBP, and associated co-morbidities, requires identifying and understanding causal relationships. Rigorous methods for causal inference, a process for quantifying causal effects from observational data, have been developed over the past 30 years. In this review we first discuss the conceptual model of cLBP that current treatments are based on, and how gaps in causal knowledge contribute to poor clinical outcomes. We then present cLBP as a "Big Data" problem and identify how advanced analytic techniques may close knowledge gaps and improve clinical outcomes. We will focus on causal discovery, which is a data-driven method that uses artificial intelligence (AI) and high dimensional datasets to identify causal structures, discussing both constraint-based (PC and Fast Causal Inference) and score-based (Fast Greedy Equivalent Search) algorithms.

Data-driven approach to integrating genomic and behavioral preclinical traumatic brain injury research

Understanding recovery from TBI is complex, involving multiple systems and modalities. The current study applied modern data science tools to manage this complexity and harmonize large-scale data to understand relationships between gene expression and behavioral outcomes in a preclinical model of chronic TBI (cTBI). Data collected by the Moody Project for Translational TBI Research included rats with no injury (naïve animals with similar amounts of anesthetic exposure to TBI and sham-injured animals), sham injury, or lateral fluid percussion TBI, followed by recovery periods up to 12 months. Behavioral measures included locomotor coordination (beam balance neuroscore) and memory and cognition assessments (Morris water maze: MWM) at multiple timepoints. Gene arrays were performed using hippocampal and cortical samples to probe 45,610 genes. To reduce the high dimensionality of molecular and behavioral domains and uncover gene-behavior associations, we performed non-linear principal components analyses (NL-PCA), which de-noised the data. Genomic NL-PCA unveiled three interpretable eigengene components (PC2, PC3, and PC4). Ingenuity pathway analysis (IPA) identified the PCs as an integrated stress response (PC2; EIF2-mTOR, corticotropin signaling, etc.), inflammatory factor translation (PC3; PI3K-p70S6K signaling), and neurite growth inhibition (PC4; Rho pathways). Behavioral PCA revealed three principal components reflecting the contribution of MWM overall speed and distance, neuroscore/beam walk, and MWM platform measures. Integrating the genomic and behavioral domains, we then performed a 'meta-PCA' on individual PC scores for each rat from genomic and behavioral PCAs. This meta-PCA uncovered three unique multimodal PCs, characterized by robust associations between inflammatory/stress response and neuroscore/beam walk performance (meta-PC1), stress response and MWM performance (meta-PC2), and stress response and neuroscore/beam walk performance (meta-PC3). Multivariate analysis of variance (MANOVA) on genomic-behavioral meta-PC scores tested separately on cortex and hippocampal samples revealed the main effects of TBI and recovery time. These findings are a proof of concept for the integration of disparate data domains for translational knowledge discovery, harnessing the full syndromic space of TBI.

Neuroinflammatory Biomarkers for Traumatic Brain Injury Diagnosis and Prognosis: A TRACK-TBI Pilot Study

The relationship between systemic inflammation and secondary injury in traumatic brain injury (TBI) is complex. We investigated associations between inflammatory markers and clinical confirmation of TBI diagnosis and prognosis. The prospective TRACK-TBI Pilot (Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot) study enrolled TBI patients triaged to head computed tomography (CT) and received blood draw within 24 h of injury. Healthy controls (HCs) and orthopedic controls (OCs) were included. Thirty-one inflammatory markers were analyzed from plasma. Area under the receiver operating characteristic curve (AUC) was used to evaluate discriminatory ability. AUC >0.7 was considered acceptable. Criteria included: TBI diagnosis (vs. OC/HC); moderate/severe vs. mild TBI (Glasgow Coma Scale; GCS); radiographic TBI (CT positive vs. CT negative); 3- and 6-month Glasgow Outcome Scale-Extended (GOSE) dichotomized to death/greater relative disability versus less relative disability (GOSE 1-4/5-8); and incomplete versus full recovery (GOSE <8/ = 8). One-hundred sixty TBI subjects, 28 OCs, and 18 HCs were included. Markers discriminating TBI/OC: HMGB-1 (AUC = 0.835), IL-1b (0.795), IL-16 (0.784), IL-7 (0.742), and TARC (0.731). Markers discriminating GCS 3-12/13-15: IL-6 (AUC = 0.747), CRP (0.726), IL-15 (0.720), and SAA (0.716). Markers discriminating CT positive/CT negative: SAA (AUC = 0.767), IL-6 (0.757), CRP (0.733), and IL-15 (0.724). At 3 months, IL-15 (AUC = 0.738) and IL-2 (0.705) discriminated GOSE 5-8/1-4. At 6 months, IL-15 discriminated GOSE 1-4/5-8 (AUC = 0.704) and GOSE <8/ = 8 (0.711); SAA discriminated GOSE 1-4/5-8 (0.704). We identified a profile of acute circulating inflammatory proteins with potential relevance for TBI diagnosis, severity differentiation, and prognosis. IL-15 and serum amyloid A are priority markers with acceptable discrimination across multiple diagnostic and outcome categories. Validation in larger prospective cohorts is needed. ClinicalTrials.gov Registration: NCT01565551.

Rehabilitation combined with neural progenitor cell grafts enables functional recovery in chronic spinal cord injury

We reported previously that neural progenitor cell (NPC) grafts form neural relays across sites of subacute spinal cord injury (SCI) and support functional recovery. Here, we examine whether NPC grafts after chronic delays also support recovery and whether intensive rehabilitation further enhances recovery. One month after severe bilateral cervical contusion, rats received daily intensive rehabilitation, NPC grafts, or both rehabilitation and grafts. Notably, only the combination of rehabilitation and grafting significantly improved functional recovery. Moreover, improved functional outcomes were associated with a rehabilitation-induced increase in host corticospinal axon regeneration into grafts. These findings identify a critical and synergistic role of rehabilitation and neural stem cell therapy in driving neural plasticity to support functional recovery after chronic and severe SCI.

Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome

Artificial intelligence and machine learning (AI/ML) is becoming increasingly more accessible to biomedical researchers with significant potential to transform biomedicine through optimization of highly-accurate predictive models and enabling better understanding of disease biology. Automated machine learning (AutoML) in particular is positioned to democratize artificial intelligence (AI) by reducing the amount of human input and ML expertise needed. However, successful translation of AI/ML in biomedicine requires moving beyond optimizing only for prediction accuracy and towards establishing reproducible clinical and biological inferences. This is especially challenging for clinical studies on rare disorders where the smaller patient cohorts and corresponding sample size is an obstacle for reproducible modeling results. Here, we present a model-agnostic framework to reinforce AutoML using strategies and tools of explainable and reproducible AI, including novel metrics to assess model reproducibility. The framework enables clinicians to interpret AutoML-generated models for clinical and biological verifiability and consequently integrate domain expertise during model development. We applied the framework towards spinal cord injury prognostication to optimize the intraoperative hemodynamic range during injury-related surgery and additionally identified a strong detrimental relationship between intraoperative hypertension and patient outcome. Furthermore, our analysis captured how evolving clinical practices such as faster time-to-surgery and blood pressure management affect clinical model development. Altogether, we illustrate how expert-augmented AutoML improves inferential reproducibility for biomedical discovery and can ultimately build trust in AI processes towards effective clinical integration.

Empowering Data Sharing and Analytics through the Open Data Commons for Traumatic Brain Injury Research

Traumatic brain injury (TBI) is a major public health problem. Despite considerable research deciphering injury pathophysiology, precision therapies remain elusive. Here, we present large-scale data sharing and machine intelligence approaches to leverage TBI complexity. The Open Data Commons for TBI (ODC-TBI) is a community-centered repository emphasizing Findable, Accessible, Interoperable, and Reusable data sharing and publication with persistent identifiers. Importantly, the ODC-TBI implements data sharing of individual subject data, enabling pooling for high-sample-size, feature-rich data sets for machine learning analytics. We demonstrate pooled ODC-TBI data analyses, starting with descriptive analytics of subject-level data from 11 previously published articles (N = 1250 subjects) representing six distinct pre-clinical TBI models. Second, we perform unsupervised machine learning on multi-cohort data to identify persistent inflammatory patterns across different studies, improving experimental sensitivity for pro- versus anti-inflammation effects. As funders and journals increasingly mandate open data practices, ODC-TBI will create new scientific opportunities for researchers and facilitate multi-data-set, multi-dimensional analytics toward effective translation.

Cognitive Outcome 1 Year After Mild Traumatic Brain Injury: Results From the TRACK-TBI Study

BACKGROUND AND OBJECTIVES

The objectives of this study were to develop and establish concurrent validity of a clinically relevant definition of poor cognitive outcome 1 year after mild traumatic brain injury (mTBI), to compare baseline characteristics across cognitive outcome groups, and to determine whether poor 1-year cognitive outcome can be predicted by routinely available baseline clinical variables.

METHODS

Prospective cohort study included 656 participants ≥17 years of age presenting to level 1 trauma centers within 24 hours of mTBI (Glasgow Coma Scale score 13-15) and 156 demographically similar healthy controls enrolled in the Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study. Poor 1-year cognitive outcome was defined as cognitive impairment (below the ninth percentile of normative data on ≥2 cognitive tests), cognitive decline (change score [1-year score minus best 2-week or 6-month score] exceeding the 90% reliable change index on ≥2 cognitive tests), or both. Associations of poor 1-year cognitive outcome with 1-year neurobehavioral outcomes were performed to establish concurrent validity. Baseline characteristics were compared across cognitive outcome groups, and backward elimination logistic regression was used to build a prediction model.

RESULTS

Mean age of participants with mTBI was 40.2 years; 36.6% were female; 76.6% were White. Poor 1-year cognitive outcome was associated with worse 1-year functional outcome, more neurobehavioral symptoms, greater psychological distress, and lower satisfaction with life (all p < 0.05), establishing concurrent validity. At 1 year, 13.5% of participants with mTBI had a poor cognitive outcome vs 4.5% of controls (p = 0.003). In univariable analyses, poor 1-year cognitive outcome was associated with non-White race, lower education, lower income, lack of health insurance, hyperglycemia, preinjury depression, and greater injury severity (all p < 0.05). The final multivariable prediction model included education, health insurance, preinjury depression, hyperglycemia, and Rotterdam CT score ≥3 and achieved an area under the curve of 0.69 (95% CI 0.62-0.75) for the prediction of a poor 1-year cognitive outcome, with each variable associated with >2-fold increased odds of poor 1-year cognitive outcome.

DISCUSSION

Poor 1-year cognitive outcome is common, affecting 13.5% of patients with mTBI vs 4.5% of controls. These results highlight the need for better understanding of mechanisms underlying poor cognitive outcome after mTBI to inform interventions to optimize cognitive recovery.

Appendicular fracture and polytrauma correlate with outcome of spinal cord injury (SCI): A TRACK-SCI study

Spinal cord injuries (SCIs) frequently occur in combination with other major organ injuries, such as traumatic brain injury (TBI) and injuries to the chest, abdomen, and musculoskeletal system (e.g., extremity, pelvic, and spine fractures). However, the effects of appendicular fractures on SCI recovery are poorly understood. We investigated whether the presence of SCI-concurrent appendicular fractures is predictive of a less robust SCI recovery. Patients enrolled in the Transforming Research And Clinical Knowledge in SCI (TRACK-SCI) prospective cohort study were identified and included in this secondary analysis study. Inclusion criteria resulted in 147 patients consisting of 120 isolated SCIs and 27 with concomitant appendicular fracture. The primary outcome was ASIA Impairment Scale (AIS) neurological grades at hospital discharge. Secondary outcomes included hospital length of stay, ICU length of stay, and AIS grade improvement during hospitalization. Multivariable binomial logistic regression analyses assessed whether SCI-concomitant appendicular fractures associate with SCI function and secondary outcomes. These analyses were adjusted for age, gender, injury severity, and non-fracture polytrauma. Appendicular fractures were associated with more severe AIS grades at hospital discharge, though covariate adjustments diminished statistical significance of this effect. Notably, non-fracture injuries to the chest and abdomen were influential covariates. Secondary analyses suggested that appendicular fractures also increased hospital length of stay. Our study indicated that SCI-associated polytrauma is important for predicting SCI functional outcomes. Further statistical evaluation is required to disentangle the effects of appendicular fractures, non-fracture solid organ injury, and SCI physiology to improve health outcomes amongst SCI patients.

Mixture Model Framework for Traumatic Brain Injury Prognosis Using Heterogeneous Clinical and Outcome Data

Prognoses of Traumatic Brain Injury (TBI) outcomes are neither easily nor accurately determined from clinical indicators. This is due in part to the heterogeneity of damage inflicted to the brain, ultimately resulting in diverse and complex outcomes. Using a data-driven approach on many distinct data elements may be necessary to describe this large set of outcomes and thereby robustly depict the nuanced differences among TBI patients' recovery. In this work, we develop a method for modeling large heterogeneous data types relevant to TBI. Our approach is geared toward the probabilistic representation of mixed continuous and discrete variables with missing values. The model is trained on a dataset encompassing a variety of data types, including demographics, blood-based biomarkers, and imaging findings. In addition, it includes a set of clinical outcome assessments at 3, 6, and 12 months post-injury. The model is used to stratify patients into distinct groups in an unsupervised learning setting. We use the model to infer outcomes using input data, and show that the collection of input data reduces uncertainty of outcomes over a baseline approach. In addition, we quantify the performance of a likelihood scoring technique that can be used to self-evaluate the extrapolation risk of prognosis on unseen patients.

Promoting FAIR Data Through Community-driven Agile Design: the Open Data Commons for Spinal Cord Injury (odc-sci.org)

The past decade has seen accelerating movement from data protectionism in publishing toward open data sharing to improve reproducibility and translation of biomedical research. Developing data sharing infrastructures to meet these new demands remains a challenge. One model for data sharing involves simply attaching data, irrespective of its type, to publisher websites or general use repositories. However, some argue this creates a 'data dump' that does not promote the goals of making data Findable, Accessible, Interoperable and Reusable (FAIR). Specialized data sharing communities offer an alternative model where data are curated by domain experts to make it both open and FAIR. We report on our experiences developing one such data-sharing ecosystem focusing on 'long-tail' preclinical data, the Open Data Commons for Spinal Cord Injury (odc-sci.org). ODC-SCI was developed with community-based agile design requirements directly pulled from a series of workshops with multiple stakeholders (researchers, consumers, non-profit funders, governmental agencies, journals, and industry members). ODC-SCI focuses on heterogeneous tabular data collected by preclinical researchers including bio-behaviour, histopathology findings and molecular endpoints. This has led to an example of a specialized neurocommons that is well-embraced by the community it aims to serve. In the present paper, we provide a review of the community-based design template and describe the adoption by the community including a high-level review of current data assets, publicly released datasets, and web analytics. Although odc-sci.org is in its late beta stage of development, it represents a successful example of a specialized data commons that may serve as a model for other fields.

Excavating FAIR Data: the Case of the Multicenter Animal Spinal Cord Injury Study (MASCIS), Blood Pressure, and Neuro-Recovery

Meta-analyses suggest that the published literature represents only a small minority of the total data collected in biomedical research, with most becoming 'dark data' unreported in the literature. Dark data is due to publication bias toward novel results that confirm investigator hypotheses and omission of data that do not. Publication bias contributes to scientific irreproducibility and failures in bench-to-bedside translation. Sharing dark data by making it Findable, Accessible, Interoperable, and Reusable (FAIR) may reduce the burden of irreproducible science by increasing transparency and support data-driven discoveries beyond the lifecycle of the original study. We illustrate feasibility of dark data sharing by recovering original raw data from the Multicenter Animal Spinal Cord Injury Study (MASCIS), an NIH-funded multi-site preclinical drug trial conducted in the 1990s that tested efficacy of several therapies after a spinal cord injury (SCI). The original drug treatments did not produce clear positive results and MASCIS data were stored in boxes for more than two decades. The goal of the present study was to independently confirm published machine learning findings that perioperative blood pressure is a major predictor of SCI neuromotor outcome (Nielson et al., 2015). We recovered, digitized, and curated the data from 1125 rats from MASCIS. Analyses indicated that high perioperative blood pressure at the time of SCI is associated with poorer health and worse neuromotor outcomes in more severe SCI, whereas low perioperative blood pressure is associated with poorer health and worse neuromotor outcome in moderate SCI. These findings confirm and expand prior results that a narrow window of blood-pressure control optimizes outcome, and demonstrate the value of recovering dark data for assessing reproducibility of findings with implications for precision therapeutic approaches.

The Relationship of Fear-Potentiated Startle and Polysomnography-Measured Sleep in Trauma-Exposed Men and Women with and without PTSD: Testing REM Sleep Effects and Exploring the Roles of an Integrative Measure of Sleep, PTSD Symptoms, and Biological Sex

STUDY OBJECTIVES

Published research indicates that sleep is involved in emotional information processing. Using a fear-potentiated startle (FPS) and nap sleep protocol, we examined the relationship of emotional learning with REM sleep (REMS) in trauma-exposed participants. We also explored the roles of PTSD symptoms, biological sex, and an integrative measure of polysomnography-measured (PSG) sleep in the learning-sleep relationship.

METHODS

After an adaptation nap, participants (N=46) completed 2 more visits (counterbalanced): a stress-condition visit, which included FPS conditioning procedures prior to a nap and assessment of learning retention and fear extinction training after the nap, and a control visit, which included a nap opportunity without stressful procedures. FPS conditioning included a "fear" visual stimulus paired with an air blast to the neck and a "safety" visual stimulus never paired with an air blast. Retention and extinction involved presentation of the visual stimuli without the air blast. Primary analyses examined the relationship between FPS responses pre- and post- sleep with stress-condition REMS duration, controlling for control-nap REMS duration.

RESULTS

Higher safety learning predicted increased REMS and increased REMS predicted more rapid extinction learning. Similar relationships were observed with an integrative PSG sleep measure. They also showed unexpected effects of PTSD symptoms on learning and showed biological sex effects on learning-sleep relationships.

CONCLUSIONS

Findings support evidence of a relationship between adaptive emotional learning and REMS. They underscore the importance of examining sex effects in sleep-learning relationships. They introduce an integrative PSG sleep measure with potential relevance to studies of sleep and subjective and biological outcomes.

Topological network analysis of patient similarity for precision management of acute blood pressure in spinal cord injury

Background:

Predicting neurological recovery after spinal cord injury (SCI) is challenging. Using topological data analysis, we have previously shown that mean arterial pressure (MAP) during SCI surgery predicts long-term functional recovery in rodent models, motivating the present multicenter study in patients.

Methods:

Intra-operative monitoring records and neurological outcome data were extracted (n = 118 patients). We built a similarity network of patients from a low-dimensional space embedded using a non-linear algorithm, Isomap, and ensured topological extraction using persistent homology metrics. Confirmatory analysis was conducted through regression methods.

Results:

Network analysis suggested that time outside of an optimum MAP range (hypotension or hypertension) during surgery was associated with lower likelihood of neurological recovery at hospital discharge. Logistic and LASSO (least absolute shrinkage and selection operator) regression confirmed these findings, revealing an optimal MAP range of 76–[104-117] mmHg associated with neurological recovery.

Conclusions:

We show that deviation from this optimal MAP range during SCI surgery predicts lower probability of neurological recovery and suggest new targets for therapeutic intervention.

Funding:

NIH/NINDS: R01NS088475 (ARF); R01NS122888 (ARF); UH3NS106899 (ARF); Department of Veterans Affairs: 1I01RX002245 (ARF), I01RX002787 (ARF); Wings for Life Foundation (ATE, ARF); Craig H. Neilsen Foundation (ARF); and DOD: SC150198 (MSB); SC190233 (MSB); DOE: DE-AC02-05CH11231 (DM).

Spinal cord injury is a devastating condition that involves damage to the nerve fibers connecting the brain with the spinal cord, often leading to permanent changes in strength, sensation and body functions, and in severe cases paralysis. Scientists around the world work hard to find ways to treat or even repair spinal cord injuries but few patients with complete immediate paralysis recover fully.

Immediate paralysis is caused by direct damage to neurons and their extension in the spinal cord. Previous research has shown that blood pressure regulation may be key in saving these damaged neurons, as spinal cord injuries can break the communication between nerves that is involved in controlling blood pressure. This can lead to a vicious cycle of dysregulation of blood pressure and limit the supply of blood and oxygen to the damaged spinal cord tissue, exacerbating the death of spinal neurons. Management of blood pressure is therefore a key target for spinal cord injury care, but so far, the precise thresholds to enable neurons to recover are poorly understood.

To find out more, Torres-Espin, Haefeli et al. used machine learning software to analyze previously recorded blood pressure and heart rate data obtained from 118 patients that underwent spinal cord surgery after acute spinal cord injury.

The analyses revealed that patients who suffered from either low or high blood pressure during surgery had poorer prospects of recovery. Statistical models confirming these findings showed that the optimal blood pressure range to ensure recovery lies between 76 to 104-117 mmHg. Any deviation from this narrow window would dramatically worsen the ability to recover.

These findings suggests that dysregulated blood pressure during surgery affects to odds of recovery in patients with a spinal cord injury. Torres-Espin, Haefeli et al. provide specific information that could improve current clinical practice in trauma centers. In the future, such machine learning tools and models could help develop real-time models that could predict the likelihood of a patient’s recovery following spinal cord injury and related neurological conditions.

FAIR Data Reuse in Traumatic Brain Injury: Exploring Inflammation and Age as Moderators of Recovery in the TRACK-TBI Pilot

The guiding principle for data stewardship dictates that data be FAIR: findable, accessible, interoperable, and reusable. Data reuse allows researchers to probe data that may have been originally collected for other scientific purposes in order to gain novel insights. The current study reuses the Transforming Research and Clinical Knowledge for Traumatic Brain Injury (TRACK-TBI) Pilot dataset to build upon prior findings and ask new scientific questions. Specifically, we have previously used a multivariate analytics approach to multianalyte serum protein data from the TRACK-TBI Pilot dataset to show that an inflammatory ensemble of biomarkers can predict functional outcome at 3 and 6 months post-TBI. We and others have shown that there are quantitative and qualitative changes in inflammation that come with age, but little is known about how this interaction affects recovery from TBI. Here we replicate the prior proteomics findings with improved missing value analyses and non-linear principal component analysis and then expand upon this work to determine whether age moderates the effect of inflammation on recovery. We show that increased age correlates with worse functional recovery on the Glasgow Outcome Scale-Extended (GOS-E) as well as increased inflammatory signature. We then explore the interaction between age and inflammation on recovery, which suggests that inflammation has a more detrimental effect on recovery for older TBI patients.

Biomarkers for Traumatic Brain Injury: Data Standards and Statistical Considerations

Recent biomarker innovations hold potential for transforming diagnosis, prognostic modeling, and precision therapeutic targeting of traumatic brain injury (TBI). However, many biomarkers, including brain imaging, genomics, and proteomics, involve vast quantities of high-throughput and high-content data. Management, curation, analysis, and evidence synthesis of these data are not trivial tasks. In this review, we discuss data management concepts and statistical and data sharing strategies when dealing with biomarker data in the context of TBI research. We propose that application of biomarkers involves three distinct steps-discovery, evaluation, and evidence synthesis. First, complex/big data has to be reduced to useful data elements at the stage of biomarker discovery. Second, inferential statistical approaches must be applied to these biomarker data elements for assessment of biomarker clinical utility and validity. Last, synthesis of relevant research is required to support practice guidelines and enable health decisions informed by the highest quality, up-to-date evidence available. We focus our discussion around recent experiences from the International Traumatic Brain Injury Research (InTBIR) initiative, with a specific focus on four major clinical projects (Transforming Research and Clinical Knowledge in TBI, Collaborative European NeuroTrauma Effectiveness Research in TBI, Collaborative Research on Acute Traumatic Brain Injury in Intensive Care Medicine in Europe, and Approaches and Decisions in Acute Pediatric TBI Trial), which are currently enrolling subjects in North America and Europe. We discuss common data elements, data collection efforts, data-sharing opportunities, and challenges, as well as examine the statistical techniques required to realize successful adoption and use of biomarkers in the clinic as a foundation for precision medicine in TBI.

Pre-Clinical Common Data Elements for Traumatic Brain Injury Research: Progress and Use Cases

Traumatic brain injury (TBI) is an extremely complex condition due to heterogeneity in injury mechanism, underlying conditions, and secondary injury. Pre-clinical and clinical researchers face challenges with reproducibility that negatively impact translation and therapeutic development for improved TBI patient outcomes. To address this challenge, TBI Pre-clinical Working Groups expanded upon previous efforts and developed common data elements (CDEs) to describe the most frequently used experimental parameters. The working groups created 913 CDEs to describe study metadata, animal characteristics, animal history, injury models, and behavioral tests. Use cases applied a set of commonly used CDEs to address and evaluate the degree of missing data resulting from combining legacy data from different laboratories for two different outcome measures (Morris water maze [MWM]; RotorRod/Rotarod). Data were cleaned and harmonized to Form Structures containing the relevant CDEs and subjected to missing value analysis. For the MWM dataset (358 animals from five studies, 44 CDEs), 50% of the CDEs contained at least one missing value, while for the Rotarod dataset (97 animals from three studies, 48 CDEs), over 60% of CDEs contained at least one missing value. Overall, 35% of values were missing across the MWM dataset, and 33% of values were missing for the Rotarod dataset, demonstrating both the feasibility and the challenge of combining legacy datasets using CDEs. The CDEs and the associated forms created here are available to the broader pre-clinical research community to promote consistent and comprehensive data acquisition, as well as to facilitate data sharing and formation of data repositories. In addition to addressing the challenge of standardization in TBI pre-clinical studies, this effort is intended to bring attention to the discrepancies in assessment and outcome metrics among pre-clinical laboratories and ultimately accelerate translation to clinical research.

047 Fear-Potentiated Startle and Sleep in Trauma-Exposed Men and Women with and without PTSD

Introduction

Animal and human studies indicate that fear conditioning disrupts subsequent sleep, including REM sleep (REMS). REMS is thought to be central to fear information processing. We utilized an afternoon nap protocol to examine the effects of fear-potentiated startle (FPS), a variant of fear conditioning, on subsequent sleep integrity and REMS in trauma-exposed participants with varying levels of PTSD. We also examined the effects of changes in sleep integrity and REMS on subsequent retention and extinction of pre-sleep learning.

Methods

Participants (N=47) participated in 3 nap visits. The first was an adaptation nap. The second and third nap visits were counterbalanced: a stress-condition nap, during which participants underwent FPS procedures prior to a nap and assessment of retention of fear and safety signal learning and fear extinction after the nap, and a control visit during which participants had a nap opportunity without stressful procedures. Canonical correlation analysis assessed the relationship between FPS responses and change in subsequent sleep relative to a control nap, as well as the relationship between change in sleep from control to stress condition and both subsequent fear and safety learning retention, and subsequent extinction.

Results

Results demonstrated a relationship between fear learning and change in sleep and supported a relationship between safety signal learning and subsequent REMS, as well as differential conditioning and wake after sleep onset. Sleep did not predict measures of fear retention or extinction. PTSD symptoms did not predict fear learning or sleep measures.

Conclusion

These findings replicate prior work showing a relationship between safety learning and REMS, suggesting that this is a core mechanism through which stress impacts fear processing. Further research is critical to further understand this effect, and to examine how different aspects of fear learning impact different components of sleep. This study also demonstrates that nap studies can be a valuable approach for studying the stress-sleep relationship.

Support (if any)

VA Career Development Award to Dr. Richards (5IK2CX000871-05)

Transforming Research and Clinical Knowledge in Spinal Cord Injury (TRACK-SCI): an overview of initial enrollment and demographics

OBJECTIVE

Traumatic spinal cord injury (SCI) is a dreaded condition that can lead to paralysis and severe disability. With few treatment options available for patients who have suffered from SCI, it is important to develop prospective databases to standardize data collection in order to develop new therapeutic approaches and guidelines. Here, the authors present an overview of their multicenter, prospective, observational patient registry, Transforming Research and Clinical Knowledge in SCI (TRACK-SCI).

METHODS

Data were collected using the National Institute of Neurological Disorders and Stroke (NINDS) common data elements (CDEs). Highly granular clinical information, in addition to standardized imaging, biospecimen, and follow-up data, were included in the registry. Surgical approaches were determined by the surgeon treating each patient; however, they were carefully documented and compared within and across study sites. Follow-up visits were scheduled for 6 and 12 months after injury.

RESULTS

One hundred sixty patients were enrolled in the TRACK-SCI study. In this overview, basic clinical, imaging, neurological severity, and follow-up data on these patients are presented. Overall, 78.8% of the patients were determined to be surgical candidates and underwent spinal decompression and/or stabilization. Follow-up rates to date at 6 and 12 months are 45% and 36.3%, respectively. Overall resources required for clinical research coordination are also discussed.

CONCLUSIONS

The authors established the feasibility of SCI CDE implementation in a multicenter, prospective observational study. Through the application of standardized SCI CDEs and expansion of future multicenter collaborations, they hope to advance SCI research and improve treatment.

Analysis of Normal High-Frequency Intracranial Pressure Values and Treatment Threshold in Neurocritical Care Patients: Insights into Normal Values and a Potential Treatment Threshold

Importance

Intracranial pressure (ICP) elevation is a compartment syndrome that impairs blood flow to the brain. Despite the importance of ICP values in neurocritical care, normal ICP values and the precise ICP threshold at which treatment should be initiated remain uncertain.

Objective

To refine our understanding of normal ICP values and determine the ICP threshold most strongly associated with outcome.

Design, Setting, and Participants

Prospective observational study (2004-2010), with outcomes determined at hospital discharge. The study included neurocritical care patients from a single level I trauma center, San Francisco General Hospital. Three hundred eighty-three patients had a traumatic brain injury with or without craniectomy; 140 patients had another indication for ICP monitoring. Consecutive patients were studied. Data analyses were completed between March 2015 and December 2019.

Exposures

Five hundred twenty-three ICP-monitored patients.

Main Outcomes and Measures

A computer system prospectively and automatically collected 1-minute physiologic data from patients in the intensive care unit during a 6-year period. Mean ICP was calculated, as was the proportion of ICP values greater than thresholds from 1 to 80 mm Hg in 1-mm Hg increments. The association between these measures and outcome was explored for various epochs up to 30 days from the time of injury. A principal component analysis was used to explore physiologic changes at various ICP thresholds, and elastic net regression was used to identify ICP thresholds most strongly associated with Glasgow Outcome Scale score at discharge.

Results

Of the 523 studied patients, 70.7% of studied patients were men (n = 370) and 72.1% had a traumatic brain injury (n = 377). A total of 4 090 964 1-minute ICP measurements were recorded for the included patients (7.78 years of recordings). Intracranial pressure values of 8 to 9 mm Hg were most commonly recorded and could possibly reflect normal values. The principal component analysis suggested state shifts in the physiome occurred at ICPs greater than 19 mm Hg and 24 mm Hg. Elastic net regression identified an ICP threshold of 19 mm Hg as most robustly associated with outcome when considering all neurocritical care patients, patients with TBI, and patients with TBI who underwent craniectomy. Intracranial pressure values greater than 19 mm Hg were associated with mortality, while lower values were associated with outcome in surviving patients.

Conclusions and Relevance

This study provides insight into what normal ICP values could be. An ICP threshold of 19 mm Hg was robustly associated with outcome in studied patients, although lower ICP values were associated with outcome in surviving patients.

Modeling and Bioinformatics Identify Responders to G-CSF in Patients With Amyotrophic Lateral Sclerosis

Objective: Developing an integrative approach to early treatment response classification using survival modeling and bioinformatics with various biomarkers for early assessment of filgrastim (granulocyte colony stimulating factor) treatment effects in amyotrophic lateral sclerosis (ALS) patients. Filgrastim, a hematopoietic growth factor with excellent safety, routinely applied in oncology and stem cell mobilization, had shown preliminary efficacy in ALS. Methods: We conducted individualized long-term filgrastim treatment in 36 ALS patients. The PRO-ACT database, with outcome data from 23 international clinical ALS trials, served as historical control and mathematical reference for survival modeling. Imaging data as well as cytokine and cellular data from stem cell analysis were processed as biomarkers in a non-linear principal component analysis (NLPCA) to identify individual response. Results: Cox proportional hazard and matched-pair analyses revealed a significant survival benefit for filgrastim-treated patients over PRO-ACT comparators. We generated a model for survival estimation based on patients in the PRO-ACT database and then applied the model to filgrastim-treated patients. Model-identified filgrastim responders displayed less functional decline and impressively longer survival than non-responders. Multimodal biomarkers were then analyzed by PCA in the context of model-defined treatment response, allowing identification of subsequent treatment response as early as within 3 months of therapy. Strong treatment response with a median survival of 3.8 years after start of therapy was associated with younger age, increased hematopoietic stem cell mobilization, less aggressive inflammatory cytokine plasma profiles, and preserved pattern of fractional anisotropy as determined by magnetic resonance diffusion tensor imaging (DTI-MRI). Conclusion: Long-term filgrastim is safe, is well-tolerated, and has significant positive effects on disease progression and survival in a small cohort of ALS patients. Developing and applying a model-based biomarker response classification allows use of multimodal biomarker patterns in full potential. This can identify strong individual treatment responders (here: filgrastim) at a very early stage of therapy and may pave the way to an effective individualized treatment option.

Diagnostic blood RNA profiles for human acute spinal cord injury

Diagnosis of spinal cord injury (SCI) severity at the ultra-acute stage is of great importance for emergency clinical care of patients as well as for potential enrollment into clinical trials. The lack of a diagnostic biomarker for SCI has played a major role in the poor results of clinical trials. We analyzed global gene expression in peripheral white blood cells during the acute injury phase and identified 197 genes whose expression changed after SCI compared with healthy and trauma controls and in direct relation to SCI severity. Unsupervised coexpression network analysis identified several gene modules that predicted injury severity (AIS grades) with an overall accuracy of 72.7% and included signatures of immune cell subtypes. Specifically, for complete SCIs (AIS A), ROC analysis showed impressive specificity and sensitivity (AUC: 0.865). Similar precision was also shown for AIS D SCIs (AUC: 0.938). Our findings indicate that global transcriptomic changes in peripheral blood cells have diagnostic and potentially prognostic value for SCI severity.

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

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.

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.

Injury volume extracted from MRI predicts neurologic outcome in acute spinal cord injury: A prospective TRACK-SCI pilot study

Conventional MRI measures of traumatic spinal cord injury severity largely rely on 2-dimensional injury characteristics such as intramedullary lesion length and cord compression. Recent advances in spinal cord (SC) analysis have led to the development of a robust anatomic atlas incorporated into an open-source platform called the Spinal Cord Toolbox (SCT) that allows for quantitative volumetric injury analysis. In the current study, we evaluate the prognostic value of volumetric measures of spinal cord injury on MRI following registration of T2-weighted (T2w) images and segmented lesions from acute SCI patients with a standardized atlas. This IRB-approved prospective cohort study involved the image analysis of 60 blunt cervical SCI patients enrolled in the TRACK-SCI clinical research protocol. Axial T2w MRI data obtained within 24 h of injury were processed using the SCT. Briefly, SC MRIs were automatically segmented using the sct_deepseg_sc tool in the SCT and segmentations were manually corrected by a neuro-radiologist. Lesion volume data were used as predictor variables for correlation with lower extremity motor scores at discharge. Volumetric MRI measures of T2w signal abnormality comprising the SCI lesion accurately predict lower extremity motor scores at time of patient discharge. Similarly, MRI measures of injury volume significantly correlated with motor scores to a greater degree than conventional 2-D metrics of lesion size. The volume of total injury and of injured spinal cord motor regions on T2w MRI is significantly and independently associated with neurologic outcome at discharge after injury.

Evidence That the Central Nervous System Can Induce a Modification at the Neuromuscular Junction That Contributes to the Maintenance of a Behavioral Response

Neurons within the spinal cord are sensitive to environmental relations and can bring about a behavioral modification without input from the brain. For example, rats that have undergone a thoracic (T2) transection can learn to maintain a hind leg in a flexed position to minimize exposure to a noxious electrical stimulation (shock). Inactivating neurons within the spinal cord with lidocaine, or cutting communication between the spinal cord and the periphery (sciatic transection), eliminates the capacity to learn, which implies that it depends on spinal neurons. Here we show that these manipulations have no effect on the maintenance of the learned response, which implicates a peripheral process. EMG showed that learning augments the muscular response evoked by motoneuron output and that this effect survives a sciatic transection. Quantitative fluorescent imaging revealed that training brings about an increase in the area and intensity of ACh receptor labeling at the neuromuscular junction (NMJ). It is hypothesized that efferent motoneuron output, in conjunction with electrical stimulation of the tibialis anterior muscle, strengthens the connection at the NMJ in a Hebbian manner. Supporting this, paired stimulation of the efferent nerve and tibialis anterior generated an increase in flexion duration and augmented the evoked electrical response without input from the spinal cord. Evidence is presented that glutamatergic signaling contributes to plasticity at the NMJ. Labeling for vesicular glutamate transporter is evident at the motor endplate. Intramuscular application of an NMDAR antagonist blocked the acquisition/maintenance of the learned response and the strengthening of the evoked electrical response.SIGNIFICANCE STATEMENT The neuromuscular junction (NMJ) is designed to faithfully elicit a muscular contraction in response to neural input. From this perspective, encoding environmental relations (learning) and the maintenance of a behavioral modification over time (memory) are assumed to reflect only modifications upstream from the NMJ, within the CNS. The current results challenge this view. Rats were trained to maintain a hind leg in a flexed position to avoid noxious stimulation. As expected, treatments that inhibit activity within the CNS, or disrupt peripheral communication, prevented learning. These manipulations did not affect the maintenance of the acquired response. The results imply that a peripheral modification at the NMJ contributes to the maintenance of the learned response.

Polytrauma Is Associated with Increased Three- and Six-Month Disability after Traumatic Brain Injury: A TRACK-TBI Pilot Study

Polytrauma and traumatic brain injury (TBI) frequently co-occur and outcomes are routinely measured by the Glasgow Outcome Scale-Extended (GOSE). Polytrauma may confound GOSE measurement of TBI-specific outcomes. Adult patients with TBI from the prospective Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study had presented to a Level 1 trauma center after injury, received head computed tomography (CT) within 24 h, and completed the GOSE at 3 months and 6 months post-injury. Polytrauma was defined as an Abbreviated Injury Score (AIS) ≥3 in any extracranial region.

Univariate regressions were performed using known GOSE clinical cutoffs. Multi-variable regressions were performed for the 3- and 6-month GOSE, controlling for known demographic and injury predictors. Of 361 subjects (age 44.9 ± 18.9 years, 69.8% male), 69 (19.1%) suffered polytrauma. By Glasgow Coma Scale (GCS) assessment, 80.1% had mild, 5.8% moderate, and 14.1% severe TBI. On univariate logistic regression, polytrauma was associated with increased odds of moderate disability or worse (GOSE ≤6; 3 month odds ratio [OR] = 2.57 [95% confidence interval (CI): 1.50-4.41; 6 month OR = 1.70 [95% CI: 1.01-2.88]) and death/severe disability (GOSE ≤4; 3 month OR = 3.80 [95% CI: 2.03-7.11]; 6 month OR = 3.33 [95% CI: 1.71-6.46]). Compared with patients with isolated TBI, more polytrauma patients experienced a decline in GOSE from 3 to 6 months (37.7 vs. 24.7%), and fewer improved (11.6 vs. 22.6%). Polytrauma was associated with greater univariate ordinal odds for poorer GOSE (3 month OR = 2.79 [95% CI: 1.73-4.49]; 6 month OR = 1.73 [95% CI: 1.07-2.79]), which was conserved on multi-variable ordinal regression (3 month OR = 3.05 [95% CI: 1.76-5.26]; 6 month OR = 2.04 [95% CI: 1.18-3.42]). Patients with TBI with polytrauma are at greater risk for 3- and 6-month disability compared with those with isolated TBI. Methodological improvements in assessing TBI-specific disability, versus disability attributable to all systemic injuries, will generate better TBI outcomes assessment tools.

Clinical Implementation of Novel Spinal Cord Perfusion Pressure Protocol in Acute Traumatic Spinal Cord Injury at U.S. Level I Trauma Center: TRACK-SCI Study

OBJECTIVE

We sought to report the safety of implementation of a novel standard of care protocol using spinal cord perfusion pressure (SCPP) maintenance for managing traumatic spinal cord injury (SCI) in lieu of mean arterial pressure goals at a U.S. Level I trauma center.

METHODS

Starting in December 2017, blunt SCI patients presenting <24 hours after injury with admission American Spinal Injury Association Impairment Scale (AIS) A-C (or AIS D at neurosurgeon discretion) received lumbar subarachnoid drain (LSAD) placement for SCPP monitoring in the intensive care unit and were included in the TRACK-SCI (Transforming Research and Clinical Knowledge in Spinal Cord Injury) data registry. This SCPP protocol comprises standard care at our institution. SCPPs were monitored for 5 days (goal ≥65 mm Hg) achieved through intravenous fluids and vasopressor support. AISs were assessed at admission and day 7.

RESULTS

Fifteen patients enrolled to date were aged 60.5 ± 17 years. Injury levels were 93.3% (cervical) and 6.7% (thoracic). Admission AIS was 20.0%/20.0%/26.7%/33.3% for A/B/C/D. All patients maintained mean SCPP ≥65 mm Hg during monitoring. Fourteen of 15 cases required surgical decompression and stabilization with time to surgery 8.8 ± 7.1 hours (71.4% <12 hours). At day 7, 33.3% overall and 50% of initial AIS A-C had an improved AIS. Length of stay was 14.7 ± 8.3 days. None had LSAD-related complications. There were 7 respiratory complications. One patient expired after transfer to comfort care.

CONCLUSIONS

In our initial experience of 15 patients with acute SCI, standardized SCPP goal-directed care based on LSAD monitoring for 5 days was feasible. There were no SCPP-related complications. This is the first report of SCPP implementation as clinical standard of care in acute SCI.

Chondroitinase improves anatomical and functional outcomes after primate spinal cord injury

Inhibitory extracellular matrices form around mature neurons as perineuronal nets containing chondroitin sulfate proteoglycans (CSPGs) that limit axonal sprouting after CNS injury. The enzyme chondroitinase (Chase) degrades the inhibitory CSPGs and improves axonal sprouting and functional recovery after spinal cord injury (SCI) in rodents. We evaluated the effects of Chase in Rhesus monkeys that had undergone C7 spinal cord hemisection. Four weeks after hemisection, multiple intraparenchymal Chase injections targeted spinal cord circuits controlling hand function below the lesion. Hand function improved significantly in Chase-treated monkeys relative to vehicle-injected controls. Moreover, Chase significantly increased corticospinal axon growth and the number of synapses formed by corticospinal terminals in gray matter caudal to the lesion. No detrimental effects were detected. This approach appears to merit clinical translation in SCI.

Origins of Neural Progenitor Cell-Derived Axons Projecting Caudally after Spinal Cord Injury

Neural progenitor cells (NPCs) transplanted into sites of spinal cord injury (SCI) extend large numbers of axons into the caudal host spinal cord. We determined the precise locations of neurons in the graft that extend axons into the caudal host spinal cord using AAV9-Cre-initiated retrograde tracing into floxed-TdTomato-expressing NPC grafts. 7,640 ± 630 grafted neurons extended axons to a single caudal host spinal cord site located 2 mm beyond the lesion, 5 weeks post injury. While caudally projecting axons arose from neurons located in all regions of the graft, the majority of caudally projecting graft neurons (53%) were located within the caudal one-third of the graft. Numerous host corticospinal axons formed monosynaptic projections onto caudally projecting graft neurons; however, we find that the majority of host axonal neuronal projections formed by neural progenitor cell interneuronal "relays" across sites of SCI are likely polysynaptic in nature.

Data Dissemination: Shortening the Long Tail of Traumatic Brain Injury Dark Data

Translation of traumatic brain injury (TBI) research findings from bench to bedside involves aligning multi-species data across diverse data types including imaging and molecular biomarkers, histopathology, behavior, and functional outcomes. In this review we argue that TBI translation should be acknowledged for what it is: a problem of big data that can be addressed using modern data science approaches. We review the history of the term big data, tracing its origins in Internet technology as data that are "big" according to the "4Vs" of volume, velocity, variety, veracity and discuss how the term has transitioned into the mainstream of biomedical research. We argue that the problem of TBI translation fundamentally centers around data variety and that solutions to this problem can be found in modern machine learning and other cutting-edge analytical approaches. Throughout our discussion we highlight the need to pull data from diverse sources including unpublished data ("dark data") and "long-tail data" (small, specialty TBI datasets undergirding the published literature). We review a few early examples of published articles in both the pre-clinical and clinical TBI research literature to demonstrate how data reuse can drive new discoveries leading into translational therapies. Making TBI data resources more Findable, Accessible, Interoperable, and Reusable (FAIR) through better data stewardship has great potential to accelerate discovery and translation for the silent epidemic of TBI.

Testing a Multivariate Proteomic Panel for Traumatic Brain Injury Biomarker Discovery: A TRACK-TBI Pilot Study

The complex and heterogeneous nature of traumatic brain injury (TBI) has rendered the identification of diagnostic and prognostic biomarkers elusive. A single acute biomarker may not be sufficient to categorize injury severity and/or predict outcome. Using multivariate dimension reduction analyses, we tested the sensitivity and specificity of a multi-analyte panel of proteins as an ensemble biomarker for TBI. Serum was collected within 24 h of injury in a cohort of 130 patients enrolled in the multi-center prospective Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study and run on an array that measured 72 proteins. Using unsupervised principal components analysis, we first identified the subset of protein changes accounting for the most variance across patients. This yielded a group of 21 proteins that reflected an inverse relationship between inflammatory cytokines and regulators of anti-inflammation, and generated an individual inflammatory profile score for each patient. We then tested the association between these scores and computed tomography (CT) findings at hospital admission, as well as their prognostic association with functional recovery at 3 and 6 months (Glasgow Outcome Scale-Extended), and cognitive recovery at 6 months (California Verbal Learning Test, Second Edition) after injury. Inflammatory signatures were significantly increased in patients with positive CT findings, as well as in those who showed poor or incomplete recovery. Inflammation biomarker scores also showed significant sensitivity and specificity as a discriminator of these outcome measures (all areas under the curve [AUCs] >0.62). This proof of concept for the feasibility of multivariate biomarker identification demonstrates the prognostic validity of using a proteomic panel as a potential biomarker for TBI.

Neurotrauma as a big-data problem

PURPOSE OF REVIEW

The field of neurotrauma research faces a reproducibility crisis. In response, research leaders in traumatic brain injury (TBI) and spinal cord injury (SCI) are leveraging data curation and analytics methods to encourage transparency, and improve the rigor and reproducibility. Here we review the current challenges and opportunities that come from efforts to transform neurotrauma's big data to knowledge.

RECENT FINDINGS

Three parallel movements are driving data-driven-discovery in neurotrauma. First, large multicenter consortia are collecting large quantities of neurotrauma data, refining common data elements (CDEs) that can be used across studies. Investigators are now testing the validity of CDEs in diverse research settings. Second, data sharing initiatives are working to make neurotrauma data findable, accessible, interoperable, and reusable (FAIR). These efforts are reflected by recent open data repository projects for preclinical and clinical neurotrauma. Third, machine learning analytics are allowing researchers to uncover novel data-driven-hypotheses and test new therapeutics in multidimensional outcome space.

SUMMARY

We are on the threshold of a new era in data collection, curation, and analysis. The next phase of big data in neurotrauma research will require responsible data stewardship, a culture of data-sharing, and the illumination of 'dark data'.

Analysis of high-frequency PbtO2 measures in traumatic brain injury: insights into the treatment threshold

OBJECTIVE

Brain tissue hypoxia is common after traumatic brain injury (TBI). Technology now exists that can detect brain hypoxia and guide corrective therapy. Current guidelines for the management of severe TBI recommend maintaining partial pressure of brain tissue oxygen (PbtO2) > 15-20 mm Hg; however, uncertainty persists as to the optimal treatment threshold. The object of this study was to better inform the relationship between PbtO2 values and outcome for patients with TBI.

METHODS

PbtO2 measurements were prospectively and automatically collected every minute from consecutive patients admitted to the San Francisco General Hospital neurological ICU during a 6-year period. Mean PbtO2 values in TBI patients as well as the proportion of PbtO2 values below each of 75 thresholds between 0 mm Hg and 75 mm Hg over various epochs up to 30 days from the time of admission were analyzed. Patient outcomes were determined using the Glasgow Outcome Scale. The authors explored putative treatment thresholds by generating 675 separate receiver operating characteristic curves and 675 generalized linear models to examine each 1-mm Hg threshold for various epochs.

RESULTS

A total of 1,380,841 PbtO2 values were recorded in 190 TBI patients. A high proportion of PbtO2 measures were below 20 mm Hg irrespective of the examined epoch. Time below treatment thresholds was more strongly associated with outcome than mean PbtO2. A treatment window was suggested: a threshold of 19 mm Hg most robustly distinguished patients by outcome, especially from days 3-5; however, benefit was suggested from maintaining values at least as high as 33 mm Hg.

CONCLUSIONS

This analysis of high-frequency physiological data substantially informs the relationship between PbtO2 values and outcome. The results suggest a therapeutic window for PbtO2 in TBI patients along with minimum and preferred PbtO2 treatment thresholds, which may be examined in future studies. Traditional treatment thresholds that have the strongest association with outcome may not be optimal.

Restorative effects of human neural stem cell grafts on the primate spinal cord

We grafted human spinal cord-derived neural progenitor cells (NPCs) into sites of cervical spinal cord injury in rhesus monkeys (Macaca mulatta). Under three-drug immunosuppression, grafts survived at least 9 months postinjury and expressed both neuronal and glial markers. Monkey axons regenerated into grafts and formed synapses. Hundreds of thousands of human axons extended out from grafts through monkey white matter and synapsed in distal gray matter. Grafts gradually matured over 9 months and improved forelimb function beginning several months after grafting. These findings in a 'preclinical trial' support translation of NPC graft therapy to humans with the objective of reconstituting both a neuronal and glial milieu in the site of spinal cord injury.

Inflammation-induced GluA1 trafficking and membrane insertion of Ca2+ permeable AMPA receptors in dorsal horn neurons is dependent on spinal tumor necrosis factor, PI3 kinase and protein kinase A

Peripheral inflammation induces sensitization of nociceptive spinal cord neurons. Both spinal tumor necrosis factor (TNF) and neuronal membrane insertion of Ca²⁺ permeable AMPA receptor (AMPAr) contribute to spinal sensitization and resultant pain behavior, molecular mechanisms connecting these two events have not been studied in detail. Intrathecal (i.t.) injection of TNF-blockers attenuated paw carrageenan-induced mechanical and thermal hypersensitivity. Levels of GluA1 and GluA4 from dorsal spinal membrane fractions increased in carrageenan-injected rats compared to controls. In the same tissue, GluA2 levels were not altered. Inflammation-induced increases in membrane GluA1 were prevented by i.t. pre-treatment with antagonists to TNF, PI3K, PKA and NMDA. Interestingly, administration of TNF or PI3K inhibitors followed by carrageenan caused a marked reduction in plasma membrane GluA2 levels, despite the fact that membrane GluA2 levels were stable following inhibitor administration in the absence of carrageenan. TNF pre-incubation induced increased numbers of Co²⁺ labeled dorsal horn neurons, indicating more neurons with Ca²⁺ permeable AMPAr. In parallel to Western blot results, this increase was blocked by antagonism of PI3K and PKA. In addition, spinal slices from GluA1 transgenic mice, which had a single alanine replacement at GluA1 ser 845 or ser 831 that prevented phosphorylation, were resistant to TNF-induced increases in Co²⁺ labeling. However, behavioral responses following intraplantar carrageenan and formalin in the mutant mice were no different from littermate controls, suggesting a more complex regulation of nociception. Co-localization of GluA1, GluA2 and GluA4 with synaptophysin on identified spinoparabrachial neurons and their relative ratios were used to assess inflammation-induced trafficking of AMPAr to synapses. Inflammation induced an increase in synaptic GluA1, but not GluA2. Although total GluA4 also increased with inflammation, co-localization of GluA4 with synaptophysin, fell short of significance. Taken together these data suggest that peripheral inflammation induces a PI3K and PKA dependent TNFR1 activated pathway that culminates with trafficking of calcium permeable AMPAr into synapses of nociceptive dorsal horn projection neurons.

What Is Being Trained? How Divergent Forms of Plasticity Compete To Shape Locomotor Recovery after Spinal Cord Injury

Spinal cord injury (SCI) is a devastating syndrome that produces dysfunction in motor and sensory systems, manifesting as chronic paralysis, sensory changes, and pain disorders. The multi-faceted and heterogeneous nature of SCI has made effective rehabilitative strategies challenging. Work over the last 40 years has aimed to overcome these obstacles by harnessing the intrinsic plasticity of the spinal cord to improve functional locomotor recovery. Intensive training after SCI facilitates lower extremity function and has shown promise as a tool for retraining the spinal cord by engaging innate locomotor circuitry in the lumbar cord. As new training paradigms evolve, the importance of appropriate afferent input has emerged as a requirement for adaptive plasticity. The integration of kinematic, sensory, and loading force information must be closely monitored and carefully manipulated to optimize training outcomes. Inappropriate peripheral input may produce lasting maladaptive sensory and motor effects, such as central pain and spasticity. Thus, it is important to closely consider the type of afferent input the injured spinal cord receives. Here we review preclinical and clinical input parameters fostering adaptive plasticity, as well as those producing maladaptive plasticity that may undermine neurorehabilitative efforts. We differentiate between passive (hindlimb unloading [HU], limb immobilization) and active (peripheral nociception) forms of aberrant input. Furthermore, we discuss the timing of initiating exposure to afferent input after SCI for promoting functional locomotor recovery. We conclude by presenting a candidate rapid synaptic mechanism for maladaptive plasticity after SCI, offering a pharmacological target for restoring the capacity for adaptive spinal plasticity in real time.

Assessments of sensory plasticity after spinal cord injury across species

Spinal cord injury (SCI) is a multifaceted phenomenon associated with alterations in both motor function and sensory function. A majority of patients with SCI report sensory disturbances, including not only loss of sensation, but in many cases enhanced abnormal sensation, dysesthesia and pain. Development of therapeutics to treat these abnormal sensory changes require common measurement tools that can enable cross-species translation from animal models to human patients. We review the current literature on translational nociception/pain measurement in SCI and discuss areas for further development. Although a number of tools exist for measuring both segmental and affective sensory changes, we conclude that there is a pressing need for better, integrative measurement of nociception/pain outcomes across species to enhance precise therapeutic innovation for sensory dysfunction in SCI.

Diffusion-Weighted Magnetic Resonance Imaging Characterization of White Matter Injury Produced by Axon-Sparing Demyelination and Severe Contusion Spinal Cord Injury in Rats

Alterations in magnetic resonance imaging (MRI)-derived measurements of water diffusion parallel (D∥) and perpendicular (D⊥) to white matter tracts have been specifically attributed to pathology of axons and myelin, respectively. We test the hypothesis that directional diffusion measurements can distinguish between axon-sparing chemical demyelination and severe contusion spinal cord white matter injury. Adult rats received either unilateral ethidium bromide (EB) microinjections (chemical demyelination) into the lateral funiculus of the spinal cord at C5 or were subjected to unilateral severe contusion spinal cord injury (SCI). Diffusion MRI metrics in the lateral funiculus were analyzed at early and late time-points following injury and correlated with histology. Early EB-demyelination resulted in a significant elevation in D⊥ and significant reduction in D∥ at the injury epicenter, with histological evidence of uniform axon preservation. Alterations in D⊥ and D∥ at the epicenter of early EB-demyelination were not significantly different from those observed with severe contusion at the epicenter, where histology demonstrated severe combined axonal and myelin injury. Diffusion abnormalities away from the injury epicenter were seen with contusion injury, but not with EB-demyelination. Chronic EB lesions underwent endogenous remyelination with normalization of diffusion metrics, whereas chronic contusion resulted in persistently altered diffusivities. In the early setting, directional diffusion measurements at the injury epicenter associated with chemical demyelination are indistinguishable from those seen with severe contusive SCI, despite dramatic pathologic differences between injury models. Caution is advised in interpretation of diffusion metrics with respect to specific white matter structural alterations. Diffusion analysis should not be limited to the epicenter of focal spinal lesions as alterations marginal to the epicenter are useful for assessing the nature of focal white matter injury.