Biomarkers Of Spinal Cord Injury Research Articles

SCIseg: Automatic Segmentation of Intramedullary Lesions in Spinal Cord Injury on T2-weighted MRI Scans.

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To develop a deep learning tool for the automatic segmentation of the spinal cord and intramedullary lesions in spinal cord injury (SCI) on T2-weighted MRI scans. Materials and Methods This retrospective study included MRI data acquired between July 2002 and February 2023 from 191 patients with SCI (mean age, 48.1 years ± 17.9 [SD]; 142 males). The data consisted of T2-weighted MRI acquired using different scanner manufacturers with various image resolutions (isotropic and anisotropic) and orientations (axial and sagittal). Patients had different lesion etiologies (traumatic, ischemic, and hemorrhagic) and lesion locations across the cervical, thoracic and lumbar spine. A deep learning model, SCIseg, was trained in a three-phase process involving active learning for the automatic segmentation of intramedullary SCI lesions and the spinal cord. The segmentations from the proposed model were visually and quantitatively compared with those from three other open-source methods (PropSeg, DeepSeg and contrast-agnostic, all part of the Spinal Cord Toolbox). Wilcoxon signed-rank test was used to compare quantitative MRI biomarkers of SCI (lesion volume, lesion length, and maximal axial damage ratio) derived from the manual reference standard lesion masks and biomarkers obtained automatically with SCIseg segmentations. Results SCIseg achieved a Dice score of 0.92 ± 0.07 (mean ± SD) and 0.61 ± 0.27 for spinal cord and SCI lesion segmentation, respectively. There was no evidence of a difference between lesion length (P = .42) and maximal axial damage ratio (P = .16) computed from manually annotated lesions and the lesion segmentations obtained using SCIseg. Conclusion SCIseg accurately segmented intramedullary lesions on a diverse dataset of T2-weighted MRI scans and extracted relevant lesion biomarkers (namely, lesion volume, lesion length, and maximal axial damage ratio). SCIseg is open-source and accessible through the Spinal Cord Toolbox (v6.2 and above). Published under a CC BY 4.0 license.

Identification of coagulation diagnostic biomarkers related to the severity of spinal cord injury

BackgroundBlood always shows coagulation changes after spinal cord injury (SCI), and identifying these blood changes may be helpful for diagnosis and treatment of SCI. Nevertheless, studies to date on blood coagulation changes after SCI in humans are not comprehensive. Therefore, this study aims to identify blood coagulation diagnostic biomarkers and immune changes related to SCI and its severity levels. MethodsHuman blood sequencing datasets were obtained from public databases. Differentially expressed coagulation-related genes were analyzed (DECRGs). Enrichment analysis and assessment of immune changes were conducted. Weighted gene co-expression network analysis, least absolute shrinkage and selection operator logistic regression were used to identify biomarkers. Validation for these biomarkers was performed. The correlation between biomarkers and immune cells was evaluated. Transcription factors, miRNA, lncRNA, and drugs that can regulate biomarkers were analyzed. ResultsDECRGs associated with SCI and its different grades were identified, showing enrichment in altered coagulation and immune-related signaling pathways. ADAM9, CD55, and STAT4 were identified as coagulation diagnostic biomarkers for SCI. IRF4 and PABPC4 were identified as coagulation diagnostic biomarkers for American Spinal Injury Association Impairment Scale (AIS) A grade of SCI. GP9 was designated as a diagnostic biomarker for AIS D grade of SCI. Immune changes in blood of SCI and its different grades were observed. Correlation between diagnostic biomarkers and immune cells were identified. Transcription factors, miRNA, lncRNA, and drugs that can regulate diagnostic biomarker expression were discovered. ConclusionTherefore, detecting the expression of these putative diagnostic biomarkers and related immune changes may be helpful for predicting the severity of SCI. Uncovering potential regulatory mechanisms for biomarkers may be beneficial for further research.

Promising Biomarkers for Spinal Cord Injury: A Brief Review

Mechanical trauma to the spinal cord leads to neural and molecular pathophysiological responses. Biomarkers are emerging as a promising unbiased tool that can assess the pathophysiological processes following spinal cord injury (SCI). In this concise review, we provide details of role and expression of structural, including Neurofilament Proteins (NF), Glial Fibrillary Acidic Protein (GFAP), Cleaved Tau (C-Tau), S100-β, Neuron Specific Enolase (NSE), Myelin Basic Protein (MBP), and inflammatory, including Transforming Growth Factor Beta (TGF-β), Tumor Necrosis Factor (TNF), Interleukins (ILs), Soluble CD95 Ligand (sCD95L) biomarkers in reported human and animal SCI studies.

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

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

High resolution terahertz ATR frequency-domain spectroscopy for monitoring spinal cord injury in rats.

Traumatic spinal cord injury (SCI) can lead to permanent neurological impairment, underscoring the urgency of regular therapeutic intervention and monitoring. In this study, we propose a new strategy for monitoring spinal cord injury through serum based on high-resolution THz attenuated total reflection frequency domain spectroscopy (THz-ATR-FDS). We demonstrated serum spectral differences at different time points after experimental SCI in rats. We also studied the relationship between serum lipid concentration and the time of SCI, which revealed the potential of lipid molecules as biomarkers of SCI. In addition, based on the principal component analysis (PCA) and least squares regression (LSR) models, the quantitative relationship between the refractive index spectrum and lipid concentration in serum was automatically analyzed. This work highlights terahertz spectroscopy as a promising tool for label-free, periodic, and efficient monitoring of SCI.

Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning.

JOURNAL/nrgr/04.03/01300535-202412000-00028/figure1/v/2024-04-08T165401Z/r/image-tiff Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal cord injury. They can greatly affect nerve regeneration and functional recovery. However, there is still limited understanding of the peripheral immune inflammatory response in spinal cord injury. In this study, we obtained microRNA expression profiles from the peripheral blood of patients with spinal cord injury using high-throughput sequencing. We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus (GEO) database (GSE151371). We identified 54 differentially expressed microRNAs and 1656 differentially expressed genes using bioinformatics approaches. Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways, such as neutrophil extracellular trap formation pathway, T cell receptor signaling pathway, and nuclear factor-κB signal pathway, were abnormally activated or inhibited in spinal cord injury patient samples. We applied an integrated strategy that combines weighted gene co-expression network analysis, LASSO logistic regression, and SVM-RFE algorithm and identified three biomarkers associated with spinal cord injury: ANO10, BST1, and ZFP36L2. We verified the expression levels and diagnostic performance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve. Quantitative polymerase chain reaction results showed that ANO10 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients. We also constructed a small RNA-mRNA interaction network using Cytoscape. Additionally, we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal cord injury patients using the CIBERSORT tool. The proportions of naïve B cells, plasma cells, monocytes, and neutrophils were increased while the proportions of memory B cells, CD8+ T cells, resting natural killer cells, resting dendritic cells, and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects, and ANO10, BST1 and ZFP26L2 were closely related to the proportion of certain immune cell types. The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal cord injury and suggest that ANO10, BST1, and ZFP36L2 are potential biomarkers for spinal cord injury. The study was registered in the Chinese Clinical Trial Registry (registration No. ChiCTR2200066985, December 12, 2022).

Identification of age-specific biomarkers of spinal cord injury: A bioinformatics analysis of young and aged mice models.

Spinal cord injury (SCI) is a debilitating event that often results in long-term physical damage, disability, and a significant impact on a patient's quality of life. Past research has noted an age-dependent decline in regeneration post-SCI. This study seeks to identify potential biomarkers and enriched pathways in young and aged SCI mouse models. We retrieved the microarray data of spinal cord samples from SCI mice and control mice from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the R software and the Linear Models for Microarray Data (limma) package. The Gene Set Enrichment Analysis (GSEA) determined enrichment differences among gene sets. The Weighted Gene Co-expression Network Analysis (WGCNA) pinpointed clinically significant modules and hub genes in SCI. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was employed to uncover significantly related pathways of crucial genes in SCI. We found 2560 DEGs in the young SCI group, comprised of 1733 upregulated RNAs and 827 downregulated RNAs. In the aged SCI group, 3048 DEGs were revealed including 1856 upregulated and 1192 downregulated genes. The GSEA revealed 12 enriched signaling pathways in the young SCI group, such as IL6/JAK/STAT3 signaling, interferon alpha response, and interferon gamma response, and 21 signaling pathways in the aged SCI group such as IL6/JAK/STAT3 signaling, E2F targets, and angiogenesis-related pathways. The WGCNA identified the turquoise module as significantly associated with the clinical traits of both young and aged SCI, and revealed 3181 hub genes. Ultimately, 1858 significant genes in SCI were found, with associated signaling pathways including epithelial-mesenchymal transition (EMT), interferon gamma response, and KARS signaling. Our study explored the RNA expression patterns and enriched signaling pathways in young and aged SCI mice. These findings may provide potential biomarkers for targeted SCI therapy.

Biomarkers of Spinal Cord Injury in Patients Undergoing Complex Endovascular Aortic Repair Procedures-A Narrative Review of Current Literature.

Complex endovascular aortic repair (coEVAR) of thoracoabdominal aortic aneurysms (TAAA) has greatly evolved in the past decades. Despite substantial improvements of postoperative care, spinal cord injury (SCI) remains the most devastating complication of coEVAR being associated with impaired patient outcome and having an impact on long-term survival. The rising number of challenges of coEVAR, essentially associated with an extensive coverage of critical blood vessels supplying the spinal cord, resulted in the implementation of dedicated SCI prevention protocols. In addition to maintenance of adequate spinal cord perfusion pressure (SCPP), early detection of SCI plays an integral role in intra- and postoperative patient care. However, this is challenging due to difficulties with clinical neurological examinations during patient sedation in the postoperative setting. There is a rising amount of evidence, suggesting that subclinical forms of SCI might be accompanied by an elevation of biochemical markers, specific to neuronal tissue damage. Addressing this hypothesis, several studies have attempted to assess the potential of selected biomarkers with regard to early SCI diagnosis. In this review, we discuss biomarkers measured in patients undergoing coEVAR. Once validated in future prospective clinical studies, biomarkers of neuronal tissue damage may potentially add to the armamentarium of modalities for early SCI diagnosis and risk stratification.

Identification of immunodiagnostic blood biomarkers associated with spinal cord injury severity.

Blood always shows some immune changes after spinal cord injury (SCI), and detection of such changes in blood may be helpful for diagnosis and treatment of SCI. However, studies to date on blood immune changes after SCI in humans are not comprehensive. Therefore, to obtain the characteristics of blood immune changes and immunodiagnostic blood biomarkers of SCI and its different grades, a human blood transcriptome sequencing dataset was downloaded and analyzed to obtain differentially expressed immune-related genes (DEIGs), related functions and signaling pathways related to SCI and its various grades. Characteristic biomarkers of SCI and its different grades were identified by using weighted gene coexpression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) logistic regression. Expression of biomarkers was verified through experiments. The area under the curve (AUC) of biomarkers was calculated to evaluate their diagnostic value, and differences in immune cell content were examined. In this study, 17 kinds of immune cells with different contents between the SCI group and healthy control (HC) group were identified, with 7 immune cell types being significantly increased. Differences in the content of immune cells between different grades of SCI and the HC group were also discovered. DEIGs were identified, with alteration in some immune-related signaling pathways, vascular endothelial growth factor signaling pathways, and axon guidance signaling pathways. The SCI biomarkers identified and those of American Spinal Injury Society Impairment Scale (AIS) A and AIS D of SCI have certain diagnostic sensitivity. Analysis of the correlation of immune cells and biomarkers showed that biomarkers of SCI, AIS A grade and AIS D grade correlated positively or negatively with some immune cells. CKLF, EDNRB, FCER1G, SORT1, and TNFSF13B can be used as immune biomarkers for SCI. Additionally, GDF11and HSPA1L can be used as biomarkers of SCI AIS A grade; PRKCA and CMTM2 can be used as biomarkers of the SCI AIS D grade. Detecting expression of these putative biomarkers and changes in related immune cells may be helpful for predicting the severity of SCI.

Trajectory of Serum Levels of Glial Fibrillary Acidic Protein Within Four Weeks Post-Injury Is Related to Neurological Recovery During the Transition from Acute to Chronic Spinal Cord Injury.

The use of biomarkers in spinal cord injury (SCI) research has evolved rapidly in recent years whereby most studies focused on the acute post-injury phase. Since SCI is characterized by persisting neurological impairments, the question arises whether blood biomarkers remain altered during the subacute post-injury time. Sample collection in the subacute phase might provide a better insight in the ongoing SCI specific molecular mechanism with fewer confounding factors compared with the acute phase where, amongst other complications, individuals receive a substantial amount of medication. This study aimed to determine if the temporal dynamics of serum biomarkers of neurodegeneration differ between individuals depending on their extent of neurological recovery in the transition phase between acute and chronic SCI. We performed a secondary analysis of biomarkers in patients with SCI (n = 41) who were treated at a level I trauma center in Germany. Patients with cervical or thoracic SCI regardless of injury severity were included. Blood samples were collected in the acute phase (1-4 days post-injury), and after 30 and 120 days post-injury. Serum protein levels of glial fibrillary acidic protein (GFAP) and neurofilament light protein (NfL) were determined for each time-point of sample collection using R-Plex Assays (Meso Scale Discovery). Linear mixed models were used to evaluate the trajectory of GFAP and NfL over time. Fixed effects of time, neurological recovery, and injury severity, along with the recovery-by-time interaction, were included in models with random slopes and intercepts. GFAP levels increase during the first days after SCI and decrease in subacute to chronic stages. Notably, the trajectory of GFAP over time is significantly associated with the extent of neurological recovery during the transition from acute to chronic SCI with a steeper decline in individuals who recovered better. Serum levels of NfL continue to rise significantly until Day 30 followed by a decrease afterwards, independent of neurological recovery. The trajectory of serum GFAP levels qualifies as a prognostic biomarker for neurological recovery, and facilitates monitoring of disease progression in the sub-acute post-injury phase.

MiR-30b-5p attenuates the inflammatory response and facilitates the functional recovery of spinal cord injury by targeting the NEFL/mTOR pathway.

Neurofilament light chain (NEFL) has been identified as a biomarker for spinal cord injury (SCI), but its effect and underlying mechanism in SCI remain unclear. SCI rat models were established for in vivo studies. Lipopolysaccharide (LPS)-induced cell models were used for in vitro studies. The protein and mRNA expression levels of genes were evaluated by western blotting and reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The pathological changes in rats after SCI were subjected to histological examinations. The interaction of NEFL and upstream miRNAs was explored using dual-luciferase reporter gene assays. NEFL was highly expressed in SCI rat spinal cord tissues and LPS-stimulated PC12 cells. NEFL silencing showed an inhibitory effect on the morphological changes of SCI rats and the secretion of inflammatory factors and facilitated functional recovery of SCI rats. MiR-30b-5p was demonstrated to target NEFL and negatively regulate NEFL mRNA and protein levels. Downregulation of miR-30b-5p in SCI cell and rat models was demonstrated. MiR-30b-5p alleviated the inflammatory response in SCI rat models and LPS-stimulated PC12 cells and promoted functional recovery in rats by targeting NEFL. NEFL activated mTOR signaling. MiR-30b-5p inactivated mTOR signaling by negatively regulating NEFL. MiR-30b-5p alleviated the inflammatory response and facilitated the functional recovery of SCI rats by targeting NEFL to inactivate the mTOR pathway.

Extracellular Vesicles in the Pathogenesis, Treatment, and Diagnosis of Spinal Cord Injury: A Mini-Review.

Benefiting from in-depth research into stem cells, extracellular vesicles (EVs), which are byproducts of cells and membrane-wrapped microvesicles (30-120 nm) containing lipids, proteins, and nucleic acids, may cast light on the research and development of therapeutics capable of improving the neurological recovery of spinal cord injury (SCI) animals. However, the mechanistic modes of action for EVs in alleviating the lesion size of SCI remain to be solved, thus presenting a tremendous gap existing in translation from the laboratory to the clinic. The purpose of this minireview was to cover a wide range of basic views on EVs involved in SCI treatment, including the effects of EVs on the pathogenesis, treatment, and diagnosis of spinal cord injury. We searched databases (i.e., PubMed, Web of Science, Scopus, Medline, and EMBASE) and acquired all accessible articles published in the English language within five years. Studies reporting laboratory applications of EVs in the treatment of SCI were included and screened to include studies presenting relevant molecular mechanisms. This review first summarized the basic role of EVs in cell communication, cell death, inflammatory cascades, scar formation, neuronal regrowth, and angiogenesis after SCI, thereby providing insights into neuroprotection and consolidated theories for future clinical application of EVs. EVs participate in an extremely wide range of cell activities, play a critical role in cell communication centring neurons, and are considered potential therapies and biomarkers for SCI. miRNAs are the most abundant nucleic acids shipped by EVs and effluent cytokines, and they may represent important messengers of EVs and important factors in SCI treatment.

A Subdural Bioelectronic Implant to Record Electrical Activity from the Spinal Cord in Freely Moving Rats

Bioelectronic devices have found use at the interface with neural tissue to investigate and treat nervous system disorders. Here, the development and characterization of a very thin flexible bioelectronic implant inserted along the thoracic spinal cord in rats directly in contact with and conformable to the dorsal surface of the spinal cord are presented. There is no negative impact on hind‐limb functionality nor any change in the volume or shape of the spinal cord. The bioelectronic implant is maintained in rats for a period of 12 weeks. The first subdural recordings of spinal cord activity in freely moving animals are presented; rats are plugged in via a recording cable and allowed to freely behave and move around on a raised platform. Recordings contained multiple distinct voltage waveforms spatially localize to individual electrodes. This device has great potential to monitor electrical signaling in the spinal cord after an injury and in the future, this implant will facilitate the identification of biomarkers in spinal cord injury and recovery, while enabling the delivery of localized electroceutical and chemical treatments.

The Study of Cerebrospinal Fluid microRNAs in Spinal Cord Injury and Neurodegenerative Diseases: Methodological Problems and Possible Solutions.

Despite extensive research on neurological disorders, unanswered questions remain regarding the molecular mechanisms underpinning the course of these diseases, and the search continues for effective biomarkers for early diagnosis, prognosis, or therapeutic intervention. These questions are especially acute in the study of spinal cord injury (SCI) and neurodegenerative diseases. It is believed that the changes in gene expression associated with processes triggered by neurological disorders are the result of post-transcriptional gene regulation. microRNAs (miRNAs) are key regulators of post-transcriptional gene expression and, as such, are often looked to in the search for effective biomarkers. We propose that cerebrospinal fluid (CSF) is potentially a source of biomarkers since it is in direct contact with the central nervous system and therefore may contain biomarkers indicating neurodegeneration or damage to the brain and spinal cord. However, since the abundance of miRNAs in CSF is low, their isolation and detection is technically difficult. In this review, we evaluate the findings of recent studies of CSF miRNAs as biomarkers of spinal cord injury (SCI) and neurodegenerative diseases. We also summarize the current knowledge concerning the methods of studying miRNA in CSF, including RNA isolation and normalization of the data, highlighting the caveats of these approaches and possible solutions.

Dynamics of biomarkers across the stages of traumatic spinal cord injury - implications for neural plasticity and repair.

Traumatic spinal cord injury (SCI) is a complex medical condition causing significant physical disability and psychological distress. While the adult spinal cord is characterized by poor regenerative potential, some recovery of neurological function is still possible through activation of neural plasticity mechanisms. We still have limited knowledge about the activation of these mechanisms in the different stages after human SCI. In this review, we discuss the potential role of biomarkers of SCI as indicators of the plasticity mechanisms at work during the different phases of SCI. An extensive review of literature related to SCI pathophysiology, neural plasticity and humoral biomarkers was conducted by consulting the PubMed database. Research and review articles from SCI animal models and SCI clinical trials published in English until January 2021 were reviewed. The selection of candidates for humoral biomarkers of plasticity after SCI was based on the following criteria: 1) strong evidence supporting involvement in neural plasticity (mandatory); 2) evidence supporting altered expression after SCI (optional). Based on selected findings, we identified two main groups of potential humoral biomarkers of neural plasticity after SCI: 1) neurotrophic factors including: Brain derived neurotrophic factor (BDNF), Nerve growth factor (NGF), Neurotrofin-3 (NT-3), and Insulin-like growth factor 1 (IGF-1); 2) other factors including: Tumor necrosis factor-alpha (TNF-α), Matrix Metalloproteinases (MMPs), and MicroRNAs (miRNAs). Plasticity changes associated with these biomarkers often can be both adaptive (promoting functional improvement) and maladaptive. This dual role seems to be influenced by their concentrations and time-window during SCI. Further studies of dynamics of biomarkers across the stages of SCI are necessary to elucidate the way in which they reflect the remodeling of neural pathways. A better knowledge about the mechanisms underlying plasticity could guide the selection of more appropriate therapeutic strategies to enhance positive spinal network reorganization.

Parallel Metabolomic Profiling of Cerebrospinal Fluid, Plasma, and Spinal Cord to Identify Biomarkers for Spinal Cord Injury

Loss of physical and emotional health due to spinal cord injury (SCI) has been rapidly increasing worldwide. Effective evaluation of the severity of SCI is crucial to its prognosis. Herein, we constructed rat models of SCI with four different degrees of injury (sham group, light injury group, moderate injury group, and heavy injury group), using the surgical approach. Cerebrospinal fluid (CSF), plasma, and spinal cord were sampled at the sub-acute spinal cord (72 h post-injury) from each rat. The LC–MS-based metabolic profiling of these samples was performed according to a universal metabolome standard (UMS). The results demonstrated that 130, 104, and 128 metabolites were significantly altered within the CSF, plasma, and spinal cord samples, respectively. Among them, there were four differential metabolites, including uric acid, phosphorycholine, pyridoxine, and guanidoacetic acid, which were commonly identified within the CSF, plasma, and spinal cord samples. Further pathway analysis of these differential metabolites demonstrated a disturbance in the metabolism of glyoxylate and dicarboxylate and glycine, serine, and threonine which were associated with pathophysiologic consequence of spinal cord injury. In particular, phosphorycholine, pyridoxine, and guanidoacetic acid demonstrated a relationship with SCI severity. Thus, they could be utilized as potential metabolite biomarkers for SCI severity assessment.

Biomarkers mining for spinal cord injury based on integrated multi-transcriptome expression profile data

BackgroundThis study was aimed to discover more biomarkers associated with spinal cord injury (SCI) by constructing a competing endogenous RNA (ceRNA) network.MethodsThe transcriptome expression profile data related to SCI (GSE45006 GSE20907) were downloaded from GEO database. The differentially expressed RNAs (DERs), including lncRNAs, miRNAs, and mRNAs, between SCI and control groups were selected, which were then performed function enrichment analyses. Following that, a SCI-related ceRNA regulatory network was constructed. PCA analysis was performed on the genes constituting the ceRNA regulatory network directly related to SCI.ResultsIn GSE45006 and GSE20907 datasets, there were respectively 3336 and 1453 DERs. Venn analysis showed that there were 429 DERs which had consistent differential expression direction. RGD1564534-miR-29b-5p relation pair and 103 miRNA-target regulatory pairs were integrated to construct the ceRNA regulatory network. Then a SCI-related ceRNA regulatory network including 8 mRNAs of IFNGR1, STAT2, CYBB, NFATC1, FCGR2B, HMOX1, TLR4, and HK2, a lncRNA of RGD1564534, and a miRNA of miR-29b-5p was constructed. Additionally, two pathways, osteoclast differentiation, and HIF-1 signaling pathway, were involved in this network. PCA indicated the samples before and after injury can be significantly distinguished based on the genes in the ceRNA network.ConclusionA total of 8 SCI-related mRNAs have been identified in the ceRNA network, including IFNGR1, STAT2, CYBB, NFATC1, FCGR2B, HMOX1, TLR4, and HK2. Moreover, RGD1564534 may serve as ceRNA by competitively binding to miR-29b-5p to regulate the expression of 8 SCI-related mRNAs. Therefore, these genes may serve as key biomarkers of SCI.

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.

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

Neurological outcomes following spinal cord injury (SCI) are currently difficult to predict. While the initial American Spinal Injury Association Impairment Scale (AIS) grade can give an estimate of outcome, the high remaining degree of uncertainty has stoked recent interest in biomarkers for SCI. This study aimed to assess the prognostic value of routinely measured blood biomarkers by developing prognostic models of AIS scores at discharge and 12 months post-injury. Routine blood and clinical data were collected from SCI patients (n = 417), and blood measures that had been assessed in less than 50% of patients were excluded. Outcome neurology was obtained from AIS and Spinal Cord Independence Measure III (SCIM-III) scores at discharge and 12 months post-injury, with motor (AIS) and sensory (AIS, touch and prick) abilities being assessed individually. Linear regression models with and without elastic net penalization were created for all outcome measures. Blood measures associated with liver function, such as alanine transaminase, were found to add value to predictions of SCIM-III at discharge and 12 months post-injury. Further, components of a total blood count, including hemoglobin, were found to add value to predictions of AIS motor and sensory scores at discharge and 12 months post-injury. These findings corroborate the results of our previous preliminary study and thus provide further evidence that routine blood measures can add prognostic value in SCI and that markers of liver function are of particular interest.

Identification of potential oxidative stress biomarkers for spinal cord injury in erythrocytes using mass spectrometry.

Oxidative stress is a hallmark of secondary injury associated with spinal cord injury. Identifying stable and specific oxidative biomarkers is of important significance for studying spinal cord injury-associated secondary injury. Mature erythrocytes do not contain nuclei and mitochondria and cannot be transcribed and translated. Therefore, mature erythrocytes are highly sensitive to oxidative stress and may become a valuable biomarker. In the present study, we revealed the proteome dynamics of protein expression in erythrocytes of beagle dogs in the acute and subacute phases of spinal cord injury using mass spectrometry-based approaches. We found 26 proteins that were differentially expressed in the acute (0-3 days) and subacute (7-21 days) phases of spinal cord injury. Bioinformatics analysis revealed that these differentially expressed proteins were involved in glutathione metabolism, lipid metabolism, and pentose phosphate and other oxidative stress pathways. Western blot assays validated the differential expression of glutathione synthetase, transaldolase, and myeloperoxidase. This result was consistent with mass spectrometry results, suggesting that erythrocytes can be used as a novel sample source of biological markers of oxidative stress in spinal cord injury. Glutathione synthetase, transaldolase, and myeloperoxidase sourced from erythrocytes are potential biomarkers of oxidative stress after spinal cord injury. This study was approved by the Experimental Animal Centre of Ningxia Medical University, China (approval No. 2017-073) on February 13, 2017.