Frontiers in Cellular Neuroscience (Nov 2022)

Improving translatability of spinal cord injury research by including age as a demographic variable

  • Andrew N. Stewart,
  • Andrew N. Stewart,
  • Linda A. T. Jones,
  • John C. Gensel,
  • John C. Gensel

DOI
https://doi.org/10.3389/fncel.2022.1017153
Journal volume & issue
Vol. 16

Abstract

Read online

Pre-clinical and clinical spinal cord injury (SCI) studies differ in study design, particularly in the demographic characteristics of the chosen population. In clinical study design, criteria such as such as motor scores, neurological level, and severity of injury are often key determinants for participant inclusion. Further, demographic variables in clinical trials often include individuals from a wide age range and typically include both sexes, albeit historically most cases of SCI occur in males. In contrast, pre-clinical SCI models predominately utilize young adult rodents and typically use only females. While it is often not feasible to power SCI clinical trials to test multi-variable designs such as contrasting different ages, recent pre-clinical findings in SCI animal models have emphasized the importance of considering age as a biological variable prior to human experiments. Emerging pre-clinical data have identified case examples of treatments that diverge in efficacy across different demographic variables and have elucidated several age-dependent effects in SCI. The extent to which these differing or diverging treatment responses manifest clinically can not only complicate statistical findings and trial interpretations but also may be predictive of worse outcomes in select clinical populations. This review highlights recent literature including age as a biological variable in pre-clinical studies and articulates the results with respect to implications for clinical trials. Based on emerging unpredictable treatment outcomes in older rodents, we argue for the importance of including age as a biological variable in pre-clinical animal models prior to clinical testing. We believe that careful analyses of how age interacts with SCI treatments and pathophysiology will help guide clinical trial design and may improve both the safety and outcomes of such important efforts.

Keywords