Breakthrough: WFIRM Discovers New Gene Expression Pattern for Faster Ebola Diagnoses

Researchers at the Wake Forest Institute for Regenerative Medicine (WFIRM) have identified a new gene expression pattern that could enable faster and more accurate diagnoses of the Ebola virus. The discovery provides a potential biomarker to help medical professionals differentiate Ebola infections from other illnesses that trigger similar immune responses in the body.

The findings, published April 19, 2026, in the journal Frontiers in Genetics, address a significant challenge in treating viral hemorrhagic fevers. Because the body’s immune system reacts vigorously to many different pathogens, the early symptoms and genetic signals of Ebola often overlap with those of other infectious diseases, complicating early detection.

Identifying a Genetic Fingerprint

To isolate a signature unique to the Ebola virus, the WFIRM team analyzed blood-derived RNA-Seq data from human cohorts and nonhuman primates. The researchers compared these samples against data from patients suffering from other illnesses, including mpox, influenza, COVID-19, bacterial pneumonia, and HIV.

By systematically removing genes that were shared across these various infections—such as common interferon-stimulated genes—the team pinpointed 281 genes that appeared to be specific to Ebola. From this group, they optimized a top-50 gene set that serves as a specific genetic fingerprint for the virus.

Many infections trigger very similar immune responses in the body, making it difficult to distinguish one disease from another based on gene expression alone. Our approach goes beyond traditional analysis by systematically removing these shared signals, allowing us to identify what is truly specific to Ebola virus infection.

Mostafa Rezapour, Ph.D., lead author and researcher at WFIRM

The effectiveness of this targeted approach was evident in the study’s independent test cohort. When using all genes for classification, the F1 score—a measure of a test’s accuracy—was 37.5%. However, after applying the top-50 gene set, the classification performance increased to 95.0%.

Clinical and Public Health Implications

Accurate and rapid diagnosis is critical for the containment of Ebola, as early intervention is essential for both patient survival and the prevention of wider outbreaks. The identified gene pattern is significantly associated with secretory, metabolic, vascular, and coagulation pathways, offering deeper insight into how the virus interacts with the host’s biological systems.

These findings demonstrate how advanced computational genomics can uncover disease‑specific biological signals that traditional approaches often miss. This work strengthens our ability to distinguish highly dangerous pathogens using host responses and advances the development of more precise diagnostic strategies.

Anthony Atala, M.D., director of WFIRM and senior author of the study

The research suggests that this genetic fingerprint could lead to the development of more precise diagnostic tests, which would be particularly valuable in outbreak settings where resources are limited and quick detection is necessary to save lives.

The study was conducted using previously collected data and was funded by a grant from the State of North Carolina.