Blood Test Identifies Multiple Biomarkers for Rapid Diagnosis of Spinal Cord Injury

The National Institutes of Health estimates that 18,000 individuals in the United States sustain spinal cord injuries (SCIs) annually, resulting in a staggering financial burden of over USD 9.7 billion each year. SCI imposes significant emotional and financial strain on both patients and caregivers. Diagnosing SCI and determining the potential for recovery necessitate extensive clinical evaluations and advanced imaging, which is both time-consuming and costly, especially for those with SCI-related complications. Clinicians have long been in search of a rapid, minimally invasive method that can reliably confirm the injury, assess its severity, and predict the potential for recovery. A new blood test, detailed in The Journal of Clinical Investigation, may offer a solution to this pressing need in patient care.

Researchers at Johns Hopkins University School of Medicine (Baltimore, MD, USA) have developed an innovative blood test that could quickly predict the severity of SCI and the likelihood of sensory and motor recovery within six months. This test presents a cost-effective alternative to traditional diagnostic methods. Historically, blood tests have not been seen as reliable for assessing spinal conditions due to the blood-brain barrier—a protective layer that shields the brain from harmful substances, such as viruses and bacteria, found in the blood. However, researchers speculated that SCI could disrupt this barrier, potentially allowing for detectable biomarkers in the bloodstream. Drawing on advancements in cancer biomarker research, particularly the use of liquid biopsies to detect cell-free DNA (cfDNA) and proteins, the team applied similar techniques to SCI, offering a method to guide treatment and monitor recovery progress.

The researchers analyzed blood samples from 50 individuals with acute SCI and 25 without, with 68% of the participants being male and 32% female. They observed that cfDNA levels in the blood corresponded with the American Spinal Injury Association (ASIA) scale, a standard tool for assessing SCI severity based on motor and sensory functions. The study found higher cfDNA concentrations in patients in the ASIA A group, which represents the most severe cases with no sensation or motor function. This was in contrast to less severe injuries in ASIA groups B, C, and D, indicating that greater spinal cord damage leads to more cfDNA being released into the bloodstream. To enhance the accuracy of the blood test, the researchers identified four specific plasma proteins—FABP3, REST, IL-6, and NF-H—that were elevated in patients with SCI. They combined these markers into what they termed the Spinal Cord Injury Index (SCII).

When the SCII was compared with ASIA groups, it accurately reflected the severity of injury and aligned with MRI scans and physical evaluations. Patients were monitored for six months to assess any improvements in their ASIA grade. The SCII successfully predicted with 77% accuracy which patients would experience neurological improvements. This suggests that the new blood test can potentially predict long-term recovery for most patients, addressing a central concern for those with SCI and their caregivers. The researchers believe that using the SCII to track biomarkers over time could help measure treatment effectiveness and facilitate personalized care, similar to the use of liquid biopsies in cancer patients. This multi-analyte blood test represents a promising advancement in SCI diagnostics and personalized treatment for traumatic injuries. However, additional studies are needed, and the research team plans to conduct multi-center clinical trials to further evaluate and refine the performance of this test.

“If you have a spinal cord injury, your main question is simple: Am I going to walk again?” said lead study author and neurosurgery chief resident Tej D. Azad, M.D., M.S. “With the new blood test, we are trying to bring a precision medicine framework to spinal cord injury with something that tells you about injury severity and can hopefully predict neurological recovery.”