Extending the clinical utility of exome sequencing: reanalysis, variant reclassification, and dynamic reporting in molecular diagnosis
Lupeng Ji, Xue Zhou, Jiong Gao, Lin Zhu, Hui Zhang, Yilong Tu, Shun Ge, Chao YuanAbstract
Introduction
Clinical exome sequencing (ES), commonly referred to as whole-exome sequencing (WES), is widely used to diagnose suspected Mendelian and rare diseases. However, many patients remain undiagnosed after initial analysis. A negative or non-diagnostic result does not necessarily exclude a genetic etiology, as genomic knowledge and patient phenotypes evolve over time. This review examines post-test strategies for extending the clinical utility of ES.
Methods
We conducted a narrative review of the literature identified through PubMed/MEDLINE, Web of Science Core Collection, and Google Scholar, with searches performed on August 5, 2026. The review synthesized evidence and practical considerations concerning exome reanalysis, variant reclassification, dynamic reporting, and complementary diagnostic approaches.
Results
Non-diagnostic ES results may reflect technical and bioinformatics limitations, incomplete clinical or family information, evolving gene–disease knowledge, uncertain variant evidence, or genetic mechanisms beyond the detection scope of conventional ES. Structured reanalysis incorporating updated phenotype information, databases, analytical methods, and family evidence may identify additional diagnoses. Variant reclassification and dynamic report updating support longitudinal interpretation, while secondary findings and artificial intelligence-assisted workflows require appropriate oversight. When reanalysis is insufficient, mechanism-guided escalation to genome sequencing, RNA sequencing, long-read sequencing, methylation testing, biochemical testing, or functional assays may be appropriate.
Discussion
Structured reanalysis and dynamic reporting can transform ES from a one-time molecular test into a longitudinal diagnostic process. Their implementation requires transparent reanalysis criteria, traceable interpretation, appropriate communication of uncertainty, and sustainable laboratory workflows to support clinical decision-making and precision medicine.