Reanalyzing the Genome: The Diagnostic Power of Ongoing Discovery

As a patient's clinical journey evolves, genomic science advances, and analytical methodologies improve, reanalysis of existing whole-genome data can turn yesterday’s uncertain or nondiagnostic findings into tomorrow’s clinical breakthroughs. Because new information is constantly emerging, genomic testing is far from a one-and-done event— periodic reanalysis has repeatedly been shown to uncover new diagnoses, reclassify variants, and strengthen clinical management.^1-3

In this blog, we explore why reanalyzing genomic data is becoming an increasingly essential part of rare disease diagnosis, management, and care decisions.

 The Dynamic Nature of Variant Interpretation

The American College of Medical Genetics (ACMG) emphasizes that new gene-disease research, new clinical information, updated population resources, and improved laboratory methods continually alter how variants are interpreted.³ As an illustrative example, in a study published by the MedSeq project, 22% of patients had new or updated clinical results within 6-23 months after initial genomic analysis.¹ The value of reanalysis is driven by constantly shifting factors: the patient’s evolving clinical journey, the advancing global body of scientific knowledge, and improvements in analytical technologies.

1. Evolving Clinical Journey

Most genome and exome analyses rely heavily on phenotypic data - the observable physical or biochemical characteristics of a patient. As a patient’s clinical picture evolves, newly observed symptoms, updated phenotypic data, or recent laboratory results can offer critical information that helps laboratory analysts identify variants corresponding to the latest clinical findings.

2. Advancing Genomic Science

Science moves faster than a single test report. In a pediatric whole-genome sequencing (WGS) cohort study, reanalyzing data approximately two years after the initial analysis identified new diagnostic variants in 10.9% of previously unsolved cases, increasing the overall diagnostic yield of WGS to 41%.² Notably, no other clinical tests performed during that interval produced additional diagnoses, highlighting the distinct value of genome reanalysis. As new evidence emerges, scientists gain the ability to better interpret genomic information in two ways:

• Variant Resolution: As more individuals are tested, scientific understanding of the impact of specific genetic changes and their impact on disease is greatly improved. As variant databases expand, new data can help resolve variants of uncertain significance (VUS) - allowing for categorization into benign or pathogenic categories with clearer impacts on clinical next steps.

• New Gene-Disease Relationships: Researchers are constantly discovering new genes linked to specific rare or common health conditions. This allows laboratory analysts to revisit existing genomic data for a growing set of indications, or report on genetic variants that were previously thought to be unrelated to the condition at hand. A large review of reanalysis studies found that new gene–disease discoveries were responsible for additional diagnoses in 93% of cohorts examined, with more than half of studies increasing diagnostic yield from updates to databases such as OMIM and ClinVar.³

Many individuals receive clearer genomic insights over time—not because their DNA changed, but because the world’s collective scientific knowledge expanded. The ACMG recommends that labs have policies in place for re-evaluating previously classified variants and communicating clinically significant changes clearly.⁴

3. Analytical Improvements

In addition to new clinical insights and advancing genomic knowledge, improvements in bioinformatics and variant filtration methods can also drive new insights from reanalysis. In one meta-analysis, updated analysis pipelines contributed to increased diagnostic yield in 44% of reanalysis studies.³

MyOme's Platform was Designed for Reanalysis

Grounded in emerging reanalysis recommendations^2,4 and the growing body of evidence, MyOme has built reanalysis directly into our testing platform. Because every MyOme test begins with whole-genome sequencing, each patient’s secure data acts as a living resource—continuously available for reanalysis as clinical profiles evolve, genomic knowledge advances, and analytical methods improve. 

For Rare Disease Exome and Genome tests, MyOme offers complimentary reanalysis one year after initial testing to help uncover new diagnoses or clarify prior findings. Importantly, reanalyzing the existing whole-genome dataset does not require additional sampling or re-sequencing, making it a seamless and patient-friendly process.

Because every MyOme test is built on a whole-genome backbone, all current and future test offerings can be run from the same underlying dataset—eliminating the need to restart the testing process as new test menus or indications are introduced. In addition, as new genomic discoveries are made and gene–disease databases are updated, our bioinformatics pipelines automatically incorporate those updates during reanalysis to ensure the latest genomic knowledge is reflected in each interpretation. Further, as our analytical capabilities continue to advance, improved bioinformatic methods may identify variants that were previously undetected—further increasing the potential clinical value of the existing genomic dataset. Finally, MyOme is spearheading several initiatives that harness the power of AI to integrate EHR data with genetic testing, enabling automatic reanalysis as clinical insights evolve to shift healthcare from a reactive model to a proactive one.^5,6

Conclusion

The evidence is clear: genomic reanalysis increases diagnostic yield, improves the accuracy of variant interpretation, and preserves the long-term clinical value of genomic data. At MyOme, we ensure that a patient’s genome is not just a static report, but rather a dynamic and enduring asset that tailors diagnosis and care.

References

1. Machini, K., Ceyhan-Birsoy, O., Azzariti, D. R., Sharma, H., Rossetti, P., Mahanta, L., Hutchinson, L., McLaughlin, H., MedSeq Project, Green, R. C., Lebo, M., & Rehm, H. L. (2019). Analyzing and Reanalyzing the Genome: Findings from the MedSeq Project. American journal of human genetics, 105(1), 177–188. https://doi.org/10.1016/j.ajhg.2019.05.017

2. Costain, G., Jobling, R., Walker, S., Reuter, M. S., Snell, M., Bowdin, S., Cohn, R. D., Dupuis, L., Hewson, S., Mercimek-Andrews, S., Shuman, C., Sondheimer, N., Weksberg, R., Yoon, G., Meyn, M. S., Stavropoulos, D. J., Scherer, S. W., Mendoza-Londono, R., & Marshall, C. R. (2018). Periodic reanalysis of whole-genome sequencing data enhances the diagnostic advantage over standard clinical genetic testing. European journal of human genetics : EJHG, 26(5), 740–744. https://doi.org/10.1038/s41431-018-0114-6

3. Robertson, A. J., Tan, N. B., Spurdle, A. B., Metke-Jimenez, A., Sullivan, C., & Waddell, N. (2022). Re-analysis of genomic data: An overview of the mechanisms and complexities of clinical adoption. Genetics in medicine : official journal of the American College of Medical Genetics, 24(4), 798–810. https://doi.org/10.1016/j.gim.2021.12.011

4. Deignan, J. L., Chung, W. K., Kearney, H. M., Monaghan, K. G., Rehder, C. W., Chao, E. C., & ACMG Laboratory Quality Assurance Committee (2019). Points to consider in the reevaluation and reanalysis of genomic test results: a statement of the American College of Medical Genetics and Genomics (ACMG). Genetics in medicine : official journal of the American College of Medical Genetics, 21(6), 1267–1270. https://doi.org/10.1038/s41436-019-0478-1

5. MyOme, Inc. MyOme joins Mayo Clinic Platform_Accelerate cohort to advance preventative care [press release]. PR Newswire. Published August 12, 2025.  Menlo Park, CA.