Routinely Measured Hematological Markers Can Help to Predict American Spinal Injury Association Impairment Scale Scores after Spinal Cord Injury

Data-driven prediction of spinal cord injury recovery: An exploration of current status and future perspectives

Spinal Cord Injury (SCI) presents a significant challenge in rehabilitation medicine, with recovery outcomes varying widely among individuals. Machine learning (ML) is a promising approach to enhance the prediction of recovery trajectories, but its integration into clinical practice requires a thorough understanding of its efficacy and applicability. We systematically reviewed the current literature on data-driven models of SCI recovery prediction. The included studies were evaluated based on a range of criteria assessing the approach, implementation, input data preferences, and the clinical outcomes aimed to forecast. We observe a tendency to utilize routinely acquired data, such as International Standards for Neurological Classification of SCI (ISNCSCI), imaging, and demographics, for the prediction of functional outcomes derived from the Spinal Cord Independence Measure (SCIM) III and Functional Independence Measure (FIM) scores with a focus on motor ability. Although there has been an increasing interest in data-driven studies over time, traditional machine learning architectures, such as linear regression and tree-based approaches, remained the overwhelmingly popular choices for implementation. This implies ample opportunities for exploring architectures addressing the challenges of predicting SCI recovery, including techniques for learning from limited longitudinal data, improving generalizability, and enhancing reproducibility. We conclude with a perspective, highlighting possible future directions for data-driven SCI recovery prediction and drawing parallels to other application fields in terms of diverse data types (imaging, tabular, sequential, multimodal), data challenges (limited, missing, longitudinal data), and algorithmic needs (causal inference, robustness).

Profiling Immunological Phenotypes in Individuals During the First Year After Traumatic Spinal Cord Injury: A Longitudinal Analysis

Abstract Individuals with SCI are severely affected by immune system changes, resulting in increased risk of infections and persistent systemic inflammation. While recent data support that immunological changes after SCI differ in the acute and chronic phases of living with SCI, only limited immunological phenotyping in humans is available. To characterize dynamic molecular and cellular immune phenotypes over the first year, we assess RNA (bulk-RNA sequencing), protein, and flow cytometry (FACS) profiles of blood samples from 12 individuals with SCI at 0-3 days and at 3, 6, and 12 months post injury (MPI) compared to 23 uninjured individuals (controls). We identified 967 differentially expressed (DE) genes in individuals with SCI (FDR <0.001) compared to controls. Within the first 6 MPI we detected a reduced expression of NK cell genes, consistent with reduced frequencies of CD56bright, CD56dim NK cells present at 12 MPI. Over 6MPI, we observed increased and prolonged expression of genes associated with inflammation (e.g. HMGB1, Toll-like receptor signaling) and expanded frequencies of monocytes acutely. Canonical T-cell related DE genes (e.g. FOXP3, TCF7, CD4) were upregulated during the first 6 MPI and increased frequencies of activated T cells at 3-12 MPI. Neurological injury severity was reflected in distinct whole blood gene expression profiles at any time after SCI, verifying a persistent 'neurogenic' imprint. Overall, 2876 DE genes emerge when comparing motor complete to motor incomplete SCI (ANOVA, FDR <0.05), including those related to neutrophils, inflammation, and infection. In summary, we identify a dynamic immunological phenotype in humans, including molecular and cellular changes which may provide potential targets to reduce inflammation, improve immunity, or serve as candidate biomarkers of injury severity.

Proteomic Analyses of Autologous Chondrocyte Implantation Plasma Highlight Cartilage Acidic Protein 1 as a Candidate for Preclinical Screening

BACKGROUND

Stratification is required to ensure that only patients likely to benefit receive autologous chondrocyte implantation (ACI). It would be advantageous to identify biomarkers to predict ACI outcome that are measurable in blood, avoiding the need for an invasive synovial fluid harvest.

PURPOSE

To assess if proteomic analyses can be used to identify novel candidate blood biomarkers in individuals who respond well or poorly to ACI.

STUDY DESIGN

Controlled laboratory study.

METHODS

Isobaric tagging for relative and absolute quantitation (iTRAQ) mass spectrometry was used to assess the proteome in plasma pooled from ACI responders (mean Lysholm improvement after ACI, 33; n = 10) or nonresponders (mean, -13; n = 10), collected at the time of surgery for cartilage harvest (stage 1) or implantation of culture-expanded chondrocytes (stage 2). An alternative proteomic method, label-free quantitation liquid chromatography-tandem mass spectrometry, was used to analyze plasma samples (majority matched to iTRAQ) individually. Differentially abundant proteins (±2.0-fold) were analyzed from both proteomic data sets, and markers of interest identified via pooled iTRAQ were validated via immunoassay of individual samples.

RESULTS

Protein differences could be detected in the plasma preoperatively between ACI responders and nonresponders (16 proteins; ≥±2.0-fold change; P < .05) using iTRAQ proteomics. The most pronounced plasma proteome shift was evident in response to stage 1 surgery in ACI nonresponders, with 48 proteins being differentially abundant between the procedures. Label-free quantitation liquid chromatography-tandem mass spectrometry analysis of these same plasma samples (nonpooled) resulted in very few proteins being identified that were significantly differentially abundant. However, this work highlighted cartilage acidic protein 1 as being increased preoperatively in nonresponders as compared with responders.

CONCLUSIONS

This study is the first to use proteomic techniques to profile the plasma of individuals treated with ACI. Despite iTRAQ analysis of pooled plasmas indicating that there are differences in the plasma proteome between responders and nonresponders to ACI, these findings were not replicated when assessed using an alternative nonpooled technique. This study highlights some of the difficulties in profiling the plasma proteome in an attempt to identify novel biomarkers. Regardless, cartilage acidic protein 1 has been identified as a protein candidate, which is detectable in plasma and can predict outcome to ACI before treatment.

CLINICAL RELEVANCE

Candidate plasma protein biomarkers identified in this study have the potential to help determine which patients will be best suited to treatment with ACI.

Cognitive and physical impairment in spinal cord injury: A scoping review and call for new understanding

Study Design: Scoping review.Objective: To examine potential underlying mechanisms of cognitive and physical impairment in patients with spinal cord injury and identify current research gaps.Methods: A scoping review of the literature was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews to identify primary studies that explored mechanisms of cognitive and/or physical impairment after spinal cord injury. The databases searched were PubMed/MEDLINE, EMBASE (OVID), Cumulative Index to Nursing and Allied Health Literature (CINAHL; EBSCO), Web of Science, Scopus, and PsycInfo. These databases were searched from inception through December 20, 2021.Results: Accumulating research suggests that neuroinflammation and neurodegeneration after a traumatic event may be possible mechanisms for cognitive impairment among patients with SCI. In addition, lack of physical activity due to impaired mobility is associated with an increased risk of cognitive impairment.Conclusion: While the results establish a foundation for understanding how cognitive impairment, mental health, and physical function independently affect patients with SCI, further research is warranted to understand how these factors systemically impact the patient and discover refined targets for future rehabilitation therapies. Studies should also explore potential predisposing factors for the relationship between cognitive and physical impairment among patients with SCI.

Glial fibrillary acidic protein is a robust biomarker in cerebrospinal fluid and peripheral blood after traumatic spinal cord injury: a prospective pilot study

PURPOSE

Biochemical biomarkers to determine the injury severity and the potential for functional recovery of traumatic spinal cord injury (TSCI) are highly warranted; however, it remains to be clarified whether cerebrospinal fluid (CSF) or peripheral blood (PB) is the ideal sample media. This study aims to measure and compare biomarker concentrations in CSF and PB and to explore associations between biomarker concentrations and injury severity, i.e., American Spinal Injury Association (ASIA) Impairment Scale (AIS) grade, and biomarker concentrations and clinical outcome, i.e., AIS grade improvement and Spinal Cord Independent Measure version III (SCIM-III) score.

METHODS

From 2018 to 2020, we conducted a single-center prospective pilot study of TSCI patients (n=15) and healthy controls (n=15). Sample collection and clinical outcome assessment were performed at median 13 h [IQR: 19], 9 days [IQR: 2], and 148 days [IQR: 49] after TSCI. Concentrations of neuron-specific enolase (NSE); glial fibrillary acid protein (GFAP); neurofilament light chain (NfL); interferon-γ (IFN-γ); interleukin (IL)-1ß, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, and IL-13; and tumor necrosis factor α (TNF-α) were measured and associated to clinical outcomes.

RESULTS

The biomarker concentrations were higher in CSF than PB. CSF concentrations of GFAP, NSE, IFN-y, TNF-a, IL-2, IL-12p70, IL-4, IL-10, and IL-13 and PB concentrations of GFAP and IFN-y were significantly associated with AIS grade, but not with AIS grade improvement or SCIM-III score.

CONCLUSIONS

Our results support GFAP as a potential diagnostic biomarker that may be measured in CSF as well as PB.

Comparison of the Levels of Hematological Parameters at Rest and after Maximum Exercise between Physically Active People with Spinal Cord Injury and Able-Bodied People

The aim of the study was to reveal the difference in the hematological reaction to the applied exercise-induced workload between the able-bodied and physically active people with cervical spinal cord injury. The study covered 11 males with spinal cord injury and 11 able-bodied persons. An incremental stress test was carried out until the maximum individual workloads were achieved. The peak oxygen uptake was measured with the use of the ergospirometric method. Venous blood test results at rest and after finishing the maximal exercise showed hemoglobin (Hb) concentration, hematocrit (HCT) value, erythrocytes (RBC), leukocytes (WBC) and platelets (PLT) counts as well as the relative percentage of granulocytes (GRA), lymphocytes (LYM), and monocytes (MON). RBC, HCT as well as Hb and PLT among people with the injury were statistically lower (p < 0.001) large effect size, than in the control group. Statistically significant difference between the test and control group, subjected to the maximal exercise stress test, was observed in the exercise induced change of the PLT [p < 0.001, (ES: 2.631)] WBC [p < 0.05, (ES: 1.429)] and the percentage of LYM and GRA [p < 0.05, (ES: 1.447) for LYM and (ES: 1.332) for GRA] between both groups, subjected to the maximal cardiac stress test on the manual cycloergometer. The analysis of the obtained results indicates that people with spinal cord injury are much more vulnerable to the occurrence of microcytic anemia compared to able-bodied people. The after-exercise percentage shift of selected subpopulations of leukocytes in both groups indicates a delayed post-exercise recovery among people with spinal cord injury.

The potential of prediction models of functioning remains to be fully exploited: A scoping review in the field of spinal cord injury rehabilitation

OBJECTIVE

The study aimed to explore existing prediction models of functioning in spinal cord injury (SCI).

STUDY DESIGN AND SETTING

The databases PubMed, EBSCOhost CINAHL Complete, and IEEE Xplore were searched for relevant literature. The search strategy included published search filters for prediction model and impact studies, index terms and keywords for SCI, and relevant outcome measures able to assess functioning as reflected in the International Classification of Functioning, Disability and Health (ICF). The search was completed in October 2020.

RESULTS

We identified seven prediction model studies reporting twelve prediction models of functioning. The identified prediction models were mainly envisioned to be used for rehabilitation planning, however, also other possible applications were stated. The method predominantly used was regression analysis and the investigated predictors covered mainly the ICF-components of body functions and activities and participation, next to characteristics of the health condition and health interventions.

CONCLUSION

Findings suggest that the development of prediction models of functioning for use in clinical practice remains to be fully exploited. By providing a comprehensive overview of what has been done, this review informs future research on prediction models of functioning in SCI and contributes to an efficient use of research evidence.

Improving Diagnostic Workup Following Traumatic Spinal Cord Injury: Advances in Biomarkers

PURPOSE OF REVIEW

Traumatic spinal cord injury (SCI) is a life-changing event with drastic implications for patients due to sensorimotor impairment and autonomous dysfunction. Current clinical evaluations focus on the assessment of injury level and severity using standardized neurological examinations. However, they fail to predict individual trajectories of recovery, which highlights the need for the development of advanced diagnostics. This narrative review identifies recent advances in the search of clinically relevant biomarkers in the field of SCI.

RECENT FINDINGS

Advanced neuroimaging and molecular biomarkers sensitive to the disease processes initiated by the SCI have been identified. These biomarkers range from advanced neuroimaging techniques, neurophysiological readouts, and molecular biomarkers identifying the concentrations of several proteins in blood and CSF samples. Some of these biomarkers improve current prediction models based on clinical readouts. Validation with larger patient cohorts is warranted. Several biomarkers have been identified-ranging from imaging to molecular markers-that could serve as advanced diagnostic and hence supplement current clinical assessments.