Biomarkers – Cornell Center for Enervating NeuroImmune Disease

Center Graduate Student Researcher Wins Award at International Conference

Anne Gardella, a graduate student researcher in the Cornell Center for Enervating NeuroImmune Disease, has been awarded the Research Insight prize at the 2025 ME Research UK Virtual Poster Competition hosted by IACFS/ME. Gardella’s winning poster focused on cell-free RNA research in ME/CFS at the International Association for Chronic Fatigue Syndrome/Myalgic Encephalomyelitis’s virtual conference held October 22-25, 2025. This recognition highlights the cutting-edge ME/CFS research being conducted at Cornell and demonstrates the Center’s commitment to advancing our understanding of ME/CFS through innovative biomarker discovery and molecular research approaches.

Interested in viewing the poster? Click here to see the poster in full detail.

Center Investigator Anne Gardella Featured in Discover Magazine for ME/CFS Biomarker Research

We’re excited to share that a graduate student within the Center, Anne Gardella, has been featured in Discover Magazine for her recent publication in the Proceedings of the National Academy of Sciences on cell-free RNA biomarkers for ME/CFS. Gardella’s work developed machine-learning models to identify molecular fingerprints in blood samples that achieved 77% accuracy in detecting ME/CFS, representing what she calls “a promising start to a non-invasive test” for this complex condition affecting over 3 million Americans. While acknowledging that clinical diagnostic tools typically require above 90% accuracy, Gardella remains optimistic about the potential for this approach to contribute to both reliable diagnosis and deeper understanding of ME/CFS, stating, “we hope this work not only contributes to a reliable diagnostic tool and a deeper understanding of ME/CFS but also continues to bring understanding of the biological problems that result in the lived experiences of these patients.”

Cell-free RNA may help us understand and diagnose ME/CFS

Great work by Center member and lead author Anne Gardella (doctoral student, De Vlaminck Lab) on demonstrating how cell-free RNA (cfRNA) in blood could help us understand—and possibly diagnose—ME/CFS. This Center-led project highlights our cross-lab collaboration, with cfRNA expertise from the De Vlaminck Lab, guidance and materials from our Center’s Administrative Core, and immune profiling resources from our Center’s Grimson Lab.

What the study did:

Our team analyzed cfRNA from plasma samples from 93 people with ME/CFS and 75 sedentary healthy controls, drawn from our Center’s prior cardiopulmonary exercise testing (CPET) study.

What the study found:

Using a machine-learning approach, the study uncovered 21 cfRNA signals that, together, identified ME/CFS cases versus controls with 0.81 AUC and 77% accuracy in a held-out test set. This is promising research, but not yet a clinical test.

By using an immune cell “atlas” from our Center’s Grimson Lab, the team estimated where the cfRNA signals likely came from. They found differences in the relative contributions of several cell types, including plasmacytoid dendritic cells, monocytes, naive CD8 T cells, MAIT cells, and platelets.

Gene-level analyses in ME/CFS point to broad changes in immune function, extracellular matrix organization, and mitochondrial function, consistent with prior studies.

When looking at circulating viral signals, the study did not find a significant difference in overall viral burden between groups.

Why this matters:

This work advances our understanding of the biology of ME/CFS and supports the search for blood-based biomarkers. It is part of our NIH-funded U54 research program.

What’s next:

We are now studying cfRNA before and after CPET to better understand post-exertional malaise, and we are exploring how cfRNA patterns may relate to muscle and cellular function. Stay tuned for updates.

Want to read more?

The Cornell Chronicle has published a press release about this study. The full paper appears in PNAS. The Chronicle article provides background, explains the approach, and highlights key findings.