Molecular Determinants of Spinal Cord Injury Rehabilitation

BACKGROUND:

Spinal cord injury (SCI) is a devastating condition with no effective cure, that hinders motor, sensory and autonomic functions. Besides affecting the spinal cord parenchyma, SCI has various systemic impacts including altered metabolic states, chronic inflammation, gastrointestinal alterations like gut dysbiosis, and urinary dysfunctions. Given these systemic pathophysiological effects, and the physiological drainage of molecules from the cerebrospinal fluid into the bloodstream, SCI biomarkers may also be identified in the blood/serum, urine and feces.

This study hypothesizes that alterations in proteins, metabolites and gut bacteria from blood/serum, urine and/or feces, reflect and influence neurological and/or functional recovery of SCI patients. Thus, using high-throughput omics analyses, the investigators here aim to identify molecular determinants and microbiota taxa that correlate with clinical recovery measures (the motor scores assessed by the International Standards for Neurological Classification of Spinal Cord Injury - ISNCSCI, the American Spinal Injury Association (ASIA) Impairment Scale - AIS grades, the Spinal Cord Independence Measure - SCIM-IV, and the Functional Independence Measure - FIM). In parallel, the investigators also aim to monitor potential neuroregeneration-associated molecules identified in pre-clinical studies led by the investigators, such as project GoBack (New therapeutic targets for spinal cord injury regeneration - PTDC/CVT-CVT/32261/2017), project pAGE (Protein aggregation across the lifespan - CENTRO-01-0145-FEDER-000003), project MEDISIS (CENTRO-01-0246-FEDER-000018), and project ReConnect (Developing innovative therapies for spinal cord injury - COMPETE2030-FEDER-00891600).

STUDY OBJECTIVES:

This research work has the following main objectives:

1. To perform broad-spectrum omics analyses, including metabolomics, proteomics, microbiome, in samples from patients with SCI at different phases post-injury, including pre- and post-rehabilitation;
2. Correlate the levels of relevant molecules and microbiota taxa identified in the omics analyses with relevant clinical data (including vital data and outcome measures like AIS grades, ISNCSCI motor scores, and functional scales SCIM-IV and FIM), in a Systems Medicine approach to SCI;
3. To monitor potential biomarkers of spinal cord injury and neuroregeneration, discovered within the scope of the investigators' previous and ongoing pre-clinical projects in cell and animal models of SCI, and search for associations between these molecules and relevant clinical data.

EXPLORATORY OBJECTIVE:

To identify biomarkers that may help in prognosis, stratification and pharmacological adjustments, and/or serve as therapeutic targets, with the main aim to improve the quality of life of spinal cord injury patients, particularly by improving their functional competences and attenuate commorbidities.

STUDY DESIGN AND METHODOLOGY:

Observational, longitudinal, prospective cohort study involving 66 patients with subacute SCI (28 patients with A and B classification in ASIA Impairment Scale - AIS and 38 patients with C and D classification in AIS) and 40 able-bodied control participants, recruited from familiars, hospital personnel and the community.

PARTICIPANT RECRUITMENT:

Participants were recruited when admitted for hospitalization at the rehabilitation center "Centro de Reabilitação do Norte (CRN, ULSGE)". Inclusion and exclusion criteria were clearly defined to ensure a homogenous and representative study population.

DATA COLLECTION:

Clinical data, including neurological assessments (e.g., ASIA Impairment Scale), functional outcome measures (e.g. SCIM, FIM), and demographic information, were collected at three time points (T): T1: Admission to the rehabilitation unit (subacute phase, around 2 months post-injury). T2: Discharge from the rehabilitation unit (around 4 months post-injury). T3: One-year post-injury follow-up. Biological samples (blood, feces, and urine) were collected at each time point (T1, T2, and T3). The same biological samples were collected from controls at a single time point.

LABORATORY ANALYSES:

Metabolomics and Lipidomics analyses: Serum samples were analysed by Attenuated Total Reflection Fourier-Transform Infrared (ATR-FTIR) spectroscopy, fecal and serum samples by Nuclear Magnetic Resonance (NMR); serum samples will be analysed by Mass-spectrometry-based lipidomics.

Microbiome Analysis: Fecal samples undergone 16S rRNA gene sequencing to determine gut microbiota composition and diversity.

Immune Biomarker Quantification: Serum samples were analyzed by citometry multiplex array.

Proteomic analyses: Serum samples were analysed by Mass-spectrometry.

STATISTICAL ANALYSES:

Descriptive statistics (mean/median) were calculated for all outcome measures. Data association studies will be performed between molecular data (levels of microbiota taxa and/or molecules at a given time point, or their variation between time points) and continuous (e.g. ISNCSCI motor scores; SCIM-IV and FIM scores) and categorical clinical data (e.g. stratification by severity using AIS grades; medication intake).

Potential confounders (age, gender, injury level, time post-injury, etc.) and biases are being accounted for. Independent group comparisons (e.g., T1 cytokine levels) used t-tests or Mann-Whitney U-tests, while dependent group comparisons (e.g., cytokine changes within AIS groups) used paired t-tests or Wilcoxon tests. ANOVA, multivariate analyses, and generalized linear models (regression, mixed-model repeated measures) assessed inter-group data and associations between omics datasets and clinical measures. Multiomics analyses will be performed using prediction models.