Gut Dysbiosis in Spinal Cord Injury Rehabilitation

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Background: Spinal cord injury (SCI) is a devastating condition with no effective cure. Gut dysbiosis and chronic immune dysfunction are common complications that may hinder recovery. This study aims to investigate the role of gut microbiota and related immune biomarkers and metabolites in the functional recovery of SCI patients during the subacute phase. This study hypothesizes that alterations in the gut microbiota and associated immune responses are critical factors influencing recovery trajectories in patients during the subacute phase of SCI. Therefore, we aim to investigate the intricate relationship between gut microbiota composition, immune biomarkers, and functional outcomes in this population, to develop a probiotic-based therapeutic intervention. Study Objectives: * To characterize gut microbiota changes in subacute SCI patients; * To identify microbiota-based biomarkers for prognosis; * To correlate gut dysbiosis with systemic inflammation and functional recovery. Exploratory objective: - To assess the potential of probiotic-based approaches for therapeutic intervention. Study Design and Methodology: This is an 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. Participant Recruitment and Enrollment: Participants admitted for hospitalization at Centro de Reabilitação do Norte (CRN)/Unidade Local de Saúde de Gaia e Espinho (ULSGE) were recruited. Inclusion and exclusion criteria were clearly defined to ensure a homogenous study population. Data Collection: Clinical data, including neurological assessments, functional outcome measures (e.g., ASIA Impairment Scale, Functional Independence Measure), and demographic information, were collected at three time points: T1: Admission to the rehabilitation unit (subacute phase). T2: Discharge from the rehabilitation unit. T3: One-year post-injury follow-up. Biological samples, including fecal samples and blood samples, were collected at each time point (T1, T2, and T3). Laboratory Analyses: Microbiome Analysis: Fecal samples undergone 16S rRNA gene sequencing to determine gut microbiota composition and diversity. Immune Biomarker Quantification: Blood samples were analyzed to quantify levels of key inflammatory cytokines, chemokines, and other immune markers. Metabolite Profiling: Fecal samples, and/or blood samples will be analyzed using metabolomics techniques to identify gut-derived metabolites that may influence recovery. Statistical Analysis: Descriptive statistics (means) were calculated for all outcome measures. Data association studies included gut microbiota composition, AIS-based rehabilitation outcomes (percentage improvement), comorbidities (e.g., UTIs), immune biomarkers, and metabolites at T1-T3, with focus on microbiota linked to SCI. Potential confounders (age, gender, injury level, etc.) and biases were 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 gut microbiota changes and functional/immunological outcomes.