When a genetic test reveals a variant of uncertain significance (VUS), patients and clinicians are left in limbo. Is the variant harmless? Is it disease-causing? Without clarity, treatment decisions stall, families are left without answers, and payers hesitate to cover therapies 1.
Variant reclassification is one of the areas where real-world evidence (RWE) can have the most immediate and meaningful impact. By systematically collecting and interpreting data from multiple real-world sources - functional studies, case series, literature-based follow-ups, and patient registries - uncertain variants can be reclassified as either pathogenic or benign, giving patients and providers the clarity they need 2.
RWE as the Missing Piece
Traditional variant interpretation follows the ACMG/AMP guidelines, which weigh multiple lines of evidence: population frequency data, computational predictions, functional assays, segregation studies, and published literature. Yet, in many cases, the available evidence is incomplete. Functional data may be missing, clinical observations limited, and population datasets too small to provide clarity. As a result, many variants remain classified as uncertain 3.
This is where real-world evidence (RWE) makes a critical difference. By incorporating data generated outside of controlled trial settings, RWE provides the context needed to resolve those uncertainties:
- Functional studies: Patient-derived samples and in vitro assays measure the actual biological effect of a variant, such as enzyme activity thresholds.
- Case series and literature follow-ups: Longitudinal reports reveal how a variant presents across diverse patients, capturing disease course, treatment response, and outcomes over time.
- Registries and observational data: Larger cohorts uncover genotype–phenotype correlations, refine penetrance estimates, and highlight demographic patterns.
Together, these real-world insights supply the missing evidence that can shift a variant from uncertain to pathogenic or benign - turning ambiguity into actionable knowledge.
The Fabry Example: GLA Variant Reclassification
Fabry disease shows how powerful real-world evidence can be in variant interpretation. This rare, X-linked disorder is caused by pathogenic variants in the GLA gene, yet many variants have long been labeled uncertain - leaving patients without clear diagnostic or therapeutic options.
To address this, Genomenon conducted a systematic literature review of 1,600+ publications, uncovering 1,677 unique GLA variants, including 802 not previously reported in ClinVar. Most newly identified variants were supported by clinical or functional evidence.
A key innovation was the creation of functional thresholds for α-Gal A enzyme activity (<5.5% in vitro, <3.0% in vivo). Applying these cutoffs enabled the reclassification of 71 of 126 GLA VUS (56%) as pathogenic - turning uncertainty into actionable knowledge. 4
Why Reclassification Matters
Variant reclassification is more than an academic exercise - it carries weight across the healthcare ecosystem:
- For clinicians: A definitive classification informs diagnosis, prognosis, and eligibility for therapies or clinical trials.
- For payers: RWE-backed reclassifications justify coverage decisions, ensuring that patients receive therapies aligned with the latest evidence.
- For regulators: Literature-based evidence and real-world cohorts strengthen submissions, support label expansions, and align with evolving standards for genomic medicine.
In all cases, reclassification driven by RWE turns uncertainty into clarity - with direct consequences for patients.
From Uncertain to Actionable
Every reclassified variant represents a patient who now has a clearer path forward. By leveraging real-world evidence - from functional thresholds to decades of published clinical data - we can move beyond uncertainty and deliver answers that guide care, inform policy, and accelerate therapeutic development.
Variant reclassification shows the true value of RWE: not just collecting data, but turning it into evidence that changes lives.
References:
- Hoffman-Andrews, L. (2017). The known unknown: The challenges of genetic variants of uncertain significance in clinical practice. Journal of Law and the Biosciences, 4(3), 648–657. https://doi.org/10.1093/jlb/lsx038
- Richards, S., Aziz, N., Bale, S., Bick, D., Das, S., Gastier-Foster, J., Grody, W. W., Hegde, M., Lyon, E., Spector, E., Voelkerding, K., Rehm, H. L., & ACMG Laboratory Quality Assurance Committee. (2015). Standards and guidelines for the interpretation of sequence variants: A joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genetics in Medicine, 17(5), 405–424. https://doi.org/10.1038/gim.2015.30
- McEwen, A. E., Tejura, M., Fayer, S., Starita, L. M., & Fowler, D. M. (2025). Multiplexed assays of variant effect for clinical variant interpretation. Nature Reviews Genetics. https://doi.org/10.1038/s41576-025-00870-x
- Bisonnette, J., Veleva-Rotse, B. O., Giuliano, J. D., Kerawala, R., Timm, D., Syverud, N., Kozaric, A., & Kiel, M. J. (2025, March). Uncovering pathogenic GLA variants in Fabry disease: A systematic literature review using real-world evidence [Conference presentation]. American College of Medical Genetics and Genomics (ACMG) Annual Meeting, Salt Lake City, UT, United States. https://www.genomenon.com/resource/uncovering-pathogenic-gla-variants-fabry-disease-systematic-literature-review-real-world-evidence
