Inflammasome Blood Biomarkers for Metabolic Health in Chronic Spinal Cord Injury

Introduction: Chronic spinal cord injury (cSCI) is associated with systemic inflammation and metabolic dysregulation. The inflammasome is implicated in inflammation, and its role in cSCI remains underexplored. This study aimed to evaluate changes in inflammasome biomarkers and metabolic measurements in paraplegics and healthy controls, with the hypothesis that metabolic dysfunction in cSCI may result in an abnormal inflammatory response.

Methods: A prospective case-control study was conducted involving five cSCI patients and five healthy controls. Blood samples were collected at baseline, 80 minutes, and 400 minutes post-feeding. The specific biomarkers measured included both inflammasome and metabolic markers. Analyzed inflammasome biomarkers included apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC), interleukin-18 (IL-18), and caspase-1 (CASP-1), as well as the marker of disease associated microglia/macrophages (DAM) triggering receptor expressed on myeloid cell-1 (TREM-1). Metabolic biomarkers included glucose, insulin, triglycerides, non-esterified fatty acids (NEFA), and glycerol.

Results: cSCI patients showed consistently elevated levels of all inflammasome markers, including ASC, CASP-1, IL-18, and TREM-1, as compared to the healthy controls at every timepoint. Additionally, metabolic biomarkers such as insulin and triglycerides were elevated in cSCI patients at each timepoint. cSCI patients exhibited a lack of NEFA and glucose change in response to feeding.

Conclusion : This study demonstrates elevated inflammasome biomarkers and disrupted metabolic responses in cSCI patients compared to controls. Higher levels of ASC, CASP-1, IL-18, and TREM-1 suggest sustained inflammation, while altered metabolic responses imply underlying dysregulation in cSCI. These findings support exploring inflammasome-targeted therapies for managing inflammation and metabolic dysfunction in cSCI. Future research should expand the sample size to strengthen evidence and enhance generalizability.