Alterations in microbial composition of the gut and urine are associated with many seemingly diverse disorders, affecting the immune system and correspondingly influence the composition of the microbiome (i.e. reciprocal signaling). Individuals with spinal cord injury (SCI) are prone to infections and this could be reflected by changes in the microbiome. Given the paucity in the current literature, there is a need to track changes in human urinary tract (UT) and gastrointestinal (GI) microbiota after acute SCI.

The aim of this exploratory, feasibility study was to track longitudinal changes of UT and GI microbiota across the first year following acute human SCI. The study was registered at clinicaltrials.gov (NCT02903472) and approved by the local ethics boards of all participating centers, i.e. Calgary (Canada), Barcelona (Spain), and Ankara (Turkey).
Main inclusion criterion: Individuals with an acute tetraplegic or paraplegic motor complete (American Spinal Injury Association impairment scale [AIS] A, B) or motor incomplete (AIS C, D) single non-penetrating SCI to the C2-S1 spinal cord were recruited. Urine and stool samples were scheduled to be obtained at baseline (i.e. visit, V0, within the first week after SCI) and then, when available, longitudinally at approximately 1, 3, 6, and 12 months (i.e. V1 to V4) after SCI.
DNA sequencing: 16Sv4 amplicons generated from the samples were sequenced, quality-filtered and clustered into 97% similarity operational taxonomic unit (OTUs). Any sample with a read count <1000 was removed the analysis. OTUs were aggregated into each taxonomic rank, and plotted the relative abundance of the most abundant ones. Alpha diversity (Shannon index) was computed and compared between visits using a linear mixed model. Microbiome composition similarity among samples (Beta diversity) was assessed using permutational ANOVA (PermANOVA). Thus far, we conducted analysis of the urine samples only.

Overall 24 individuals (3 women, 12.5%, median age 34 years [Q1: 24; Q3: 46]) with an acute SCI were enrolled. Alpha diversity (i.e. Shannon indices shown as mean [SD]) were V0=1.364 [1.364], V1=1.363 [1.1.83], V2=1.719 [1.205], V3=1.080 [1.165], V4=0.605 [0.365], respectively. The linear mixed model revealed no significant differences in Alpha diversity over time. PermANOVA determined no significant differences in Beta diversity (R2=0.0867, P=0.216) over time.

Group-level analysis revealed no significant Alpha and Beta diversity differences among urine samples over time.

To gain more in-depth knowledge about temporal changes of the microbiome during the first year following SCI, we will conduct additional group-level analysis, i.e. differential abundance testing. Thereafter, we will investigate intra-individual changes of the urine samples. The same analyses will be conducted for the participants’ corresponding stool samples.