Re-analysis of genomic data: An overview of the mechanisms and complexities of clinical adoption
- PMID: 35065883
- DOI: 10.1016/j.gim.2021.12.011
Re-analysis of genomic data: An overview of the mechanisms and complexities of clinical adoption
Abstract
Re-analyzing genomic information from a patient suspected of having an underlying genetic condition can improve the diagnostic yield of sequencing tests, potentially providing significant benefits to the patient and to the health care system. Although a significant number of studies have shown the clinical potential of re-analysis, less work has been performed to characterize the mechanisms responsible for driving the increases in diagnostic yield. Complexities surrounding re-analysis have also emerged. The terminology itself represents a challenge because "re-analysis" can refer to a range of different concepts. Other challenges include the increased workload that re-analysis demands of curators, adequate reimbursement pathways for clinical and diagnostic services, and the development of systems to handle large volumes of data. Re-analysis also raises ethical implications for patients and families, most notably when re-classification of a variant alters diagnosis, treatment, and prognosis. This review highlights the possibilities and complexities associated with the re-analysis of existing clinical genomic data. We propose a terminology that builds on the foundation presented in a recent statement from the American College of Medical Genetics and Genomics and describes each re-analysis process. We identify mechanisms for increasing diagnostic yield and provide perspectives on the range of challenges that must be addressed by health care systems and individual patients.
Keywords: Clinical genomics; Curation; Genomics; Re-analysis; Sequence analysis.
Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.
Conflict of interest statement
Conflict of Interest A.J.R. is the founder and director of ClearSKY Genomics. N.W. is a founder and board member of genomiQa.
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