Clinical Utility and Long-Term Feasibility of Exome and Genome Reanalysis: From the Perspectives of a Clinical Laboratory

Exome and genome reanalysis involves the evaluation of previously generated genomic data. Unlike many other clinical tests, clinical exome sequencing (ES) or genome sequencing (GS) is often viewed as a “once-in-a-lifetime” diagnostic test as the germline genome is presumed to be invariant over time (1). However, changes in the interpretation of sequencing data from these complex clinical genomic tests are inevitable. By leveraging updated bioinformatics pipelines and published data, as well as the latest population and disease databases, ES and GS reanalysis enable the unveiling of molecular diagnosis in patients whose initial clinical ES or GS testing were not informative. Through reanalysis of genomic data, it is also possible to identify novel genetic variants that can improve our understanding of underlying pathogenesis of the disease. The clinical utilities and significance of routine reanalyses for patients with suspected rare genetic disease have been acknowledged by the American College of Medical Genetics and Genomics (2). The increase in diagnostic yield achieved through reanalysis can be attributed to several factors. Newly published literature with functional data is instrumental in describing novel variant-gene-disease associations that are otherwise not available during the initial analysis. The inclusion of additional family members in the analysis allows for the establishment of disease segregation. Patients’ evolving clinical presentations may provide information that contributes to variant interpretation. The availability of large-scale disease and population genetic databases enhances the accuracy of variant interpretation. Updated informatics pipelines, e.g., structural variant detection software tools, may become available and may not have existed at the time of initial analysis (1, 3). While data on GS reanalysis are limited, early published findings suggest that exome reanalysis leads to an approximate 10% increase in diagnostic yield (4–7). However, the diagnostic yield from reanalysis can vary and may even decline over the time. This variability could potentially be attributed to reasons such as a slower pace of variant-gene-disease discovery, improved quality of initial ES or GS analysis, greater emphasis on family-based analysis rather than singleton-based analysis in recent years, and potentially increased reanalysis referrals. Ultimately, the success of reanalysis depends on whether the molecular diagnosis lies within the exome or genome data, the detection capabilities of current tools for specific variant types, and the sufficiency of existing knowledge to interpret the identified variant. These determinants significantly influence the overall diagnostic yield of reanalysis (1). As the field of reanalysis of genomic data continues to evolve, it raises questions that warrant consideration from a laboratory perspective (Table 1). (a) What would be the optimal time interval between the initial analysis and reanalysis, considering the pace of gene-disease and variant-disease discoveries, updated bioinformatic tools, and clinical databases? Although the reported time intervals between initial analysis and reanalysis range from 6 months to 7 years across studies, reanalyses are typically performed after 1 to 2 years for the majority of studies (8). Larger studies may be helpful for establishing a standardized timeframe for reanalysis. It is reasonable to expect that frequent reanalyses would have increased costs and labor. (b) Is reanalysis the most suitable approach for a specific case, and who should initiate the ES or GS reanalysis? Given limited reanalysis resources, should we consider whether reanalysis might be of greater benefit to specific patient populations? For example, patients with specific phenotypes may have a higher likelihood of receiving a genetic diagnosis after reanalysis. Currently, data reanalysis is considered a shared responsibility among the healthcare provider, the clinical testing laboratory, and the patient. Typically, reanalysis is initiated on a case-by-case basis by the clinician or on a cohort level by a clinical laboratory (1, 9, 10). For the former, laboratories may rely on the expertise of the ordering clinician to determine the necessity of ES or GS reanalysis. However, without a systematic and comprehensive strategy for reevaluating all previously tested negative cases, there is a potential risk of “hidden diagnosis” cases remaining in the clinical laboratory's internal data set without reanalysis orders, while reanalysis may be excessively ordered for other cases. (c) When a clinician requests a reanalysis, is a new consent form required, particularly for case-level reanalysis, considering that the initial consent may not have addressed data reanalysis? Is a formal requisition form with updated clinical information mandatory for reanalysis, including requests that focused solely on reviewing variants from the initial report? Who should be responsible for verifying whether the bioinformatics pipeline, annotation resources, and variant filter settings used for the initial analysis have been updated? Should a laboratory issue an addendum, amendment, or accession as a new case? The response to these inquiries may differ among clinical laboratories; nevertheless, it is generally advisable to have an established standard operating procedure in place, as it adheres to the principle of “doing what you say.” (d) What would be the appropriate type of reanalysis? The requested type of reanalysis can vary significantly, including the reanalysis of variants in the previous ES or GS report, comprehensive whole-case reanalysis, transitioning from singleton to trio ES or GS reanalysis, expanding analysis from a focused exome or genome testing (also referred to as exome or genome slice) to the entire exome or genome, or even focusing on the reanalysis of a specific set of clinically relevant genes. In rare scenarios, there may be a need to explore a second pathogenic variant for recessive conditions, which could involve copy number variants analysis when a heterozygous sequence variant was previously detected. (e) Do laboratories use the same reporting criteria for reanalysis cases? The reporting of additional variants of uncertain significance during reanalysis may not yield additional diagnostic information, thereby making it challenging to assess the relevance of such additional information and determine its utilization in informing clinical management decisions. All of these scenarios require clinical laboratories to establish an standard operating procedure to ensure accuracy and consistency. (f) Has the entire process of reanalysis been validated, including the chemistry, bioinformatics, and analysis procedure? If the laboratory has changed its chemistry since the original sequencing was performed, it may or may not have a clinically valid bioinformatics pipeline for some aspects of reinterpretation. Clinical laboratories need to ensure that their data reanalysis practices meet all relevant regulatory requirements, such as those set by CLIA and College of American Pathologists, to ensure patient safety and accurate results. General considerations of exome and genome reanalysis. What would be the optimal time interval between the initial analysis and reanalysis? The pace of gene-disease and variant-disease discoveries Updated bioinformatic tools Updated clinical databases Updated clinical and family history Is reanalysis the most suitable approach for a specific case, and who should initiate reanalysis? Data reanalysis is considered a shared responsibility among the healthcare provider, the clinical testing laboratory, and the patient. Reanalysis on a case-by-case basis by the clinician may result in bias. Reanalysis on a cohort level by a clinical laboratory exists. Reanalysis might be of greater benefit to specific patient populations. Is a new consent form required for reanalysis when a clinician requests it, especially for case-level reanalysis where the initial consent may not have covered data reanalysis? Is a formal requisition form with updated clinical information mandatory for reanalysis, even for requests focused solely on reviewing variants from the initial report? Who is responsible for verifying whether the bioinformatics pipeline, annotation resources, and variant filter settings used for the initial analysis have been updated? Should a laboratory issue an addendum, amendment, or accession as a new case for reanalysis? To establish SOP What would be the appropriate type of reanalysis? Reanalysis of variants in the previous ES or GS report Comprehensive whole-case reanalysis Transitioning from singleton to trio ES or GS reanalysis Expanding analysis from a focused exome or genome testing (also referred to as exome or genome slice) to the entire exome or genome, or focusing on the reanalysis of a specific set of clinically relevant genes Other, e.g., exploring a second pathogenic variant for recessive conditions, which could involve copy number variants analysis when a heterozygous sequence variant was previously detected Do laboratories use the same reporting criteria for reanalysis cases? To establish SOP on reanalysis reporting Has the entire reanalysis process been validated altogether? To ensure that their data reanalysis practices meet all relevant regulatory requirements SOP, standard operating procedure. As genomic testing becomes more widely used, it is crucial to contemplate the long-term sustainability of ES and GS reanalyses from the laboratory's standpoint. One of the major challenges facing ES and GS reanalyses is the exponentially increasing volume of data that needs to be stored and analyzed. This necessitates significant investments in computing infrastructure and data management systems (11), which can be both costly and challenging to maintain. As sequencing technology advances and new data is generated, the demand for more sophisticated and scalable systems will continue to rise. Given the large amount of sensitive genomic data, it is also important to ensure its protection and security (12). As the cost of ES and whole exome sequencing continues to decline, and testing volume and data storage needs continue to expand, the notion of reanalyzing previously generated genomic data may evolve over time, with the possibility of opting for resequencing instead of reanalysis. Another challenge is the need for highly trained personnel proficient in performing such tasks as it involves complex processes. The complexities of reanalysis demand a specialized workforce with expertise in clinical genetics, bioinformatics, and laboratory medicine; the types of reanalysis include reclassifying single or multiple variants previously reported as variants of uncertain significance, analyzing specific genes of interest using existing ES or GS data, or reanalyzing the entire ES or GS data set requiring reprocessing initial data from FASTQ files, and potentially performing additional analyses such as copy number variants analysis. The challenges of reanalysis interpretation (such as reclassifying variants of uncertain significance) remain significant. Ensuring the continued availability of these skilled genetics professionals is vital for the long-term sustainability of ES and GS reanalysis. There is a need to increase the use of automation in the reanalysis process. Although challenges remain, an automated or semi-automated reanalysis model could alleviate some of the burden. This model involves automatically flagging patients’ variants when new information becomes available, facilitating updated curation. Despite the potential benefits of data reanalysis, reimbursement for ES and GS reanalysis remains a challenge. Even during the initial analysis, reimbursement for whole genome sequencing analysis can be less available compared to ES analysis. The process of ES and GS reanalysis is complex, labor-intensive, and costly, particularly when specialized bioinformatics expertise and computing resources are required, which adds to the overall analysis cost. The establishment of best practices for such analysis in the clinical setting is still ongoing. The cost of ES and GS reanalysis can be substantial, and the question of whether insurance companies should reimburse for it has sparked debate. The argument for reimbursement may ultimately depend on various factors, such as the medical necessity of the test, the benefits it offers to the patient, and the cost-effectiveness of the reanalysis. Currently, research on reimbursement for ES and GS reanalysis is limited, and the reimbursement landscape for ES and GS reanalysis is still evolving (13–15). Future studies on coverage policies regarding reanalysis using ES and GS may provide information on how reanalysis can be utilized to enhance the diagnostic yield. In summary, the clinical utility of ES and GS reanalysis is a multifaceted matter that requires continuous refinement. While these tests hold promise for enhancing overall diagnostic yield, it is crucial to consider the complexities of the process and its long-term sustainability. This calls for a collaborative effort among all stakeholders to ensure the responsible and effective utilization of data reanalysis while tackling the technical, personnel, and regulatory challenges they pose. Nonstandard Abbreviations: ES, exome sequencing; GS, genome sequencing. Author Contributions:The corresponding author takes full responsibility that all authors on this publication have met the following required criteria of eligibility for authorship: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; (c) final approval of the published article; and (d) agreement to be accountable for all aspects of the article thus ensuring that questions related to the accuracy or integrity of any part of the article are appropriately investigated and resolved. Nobody who qualifies for authorship has been omitted from the list. Authors’ Disclosures or Potential Conflicts of Interest:No authors declared any potential conflicts of interest. Acknowledgments: The authors would like to thank Dr. Gordana Raca for the careful review and helpful comments on the manuscript.