Clinical Utility of Reinterpreting Previously Reported Genomic Epilepsy Test Results for Pediatric Patients | Epilepsy and Seizures | JAMA Pediatrics | JAMA Network
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Figure 1.  Patients With Diagnostic Changes Based on Variant Classification
Patients With Diagnostic Changes Based on Variant Classification

A, Patients with reclassification of gene variants from each of the categories. There were patients with both a variant of uncertain significance (VUS) and a pathogenic or likely pathogenic (P-LP) variant reclassified; these patients are represented only once in this figure. B, Reclassification rate plotted as the fraction of reclassified variants for each year testing was performed. Solid lines indicate the fraction of patients with a reclassified variant; dotted lines, the extrapolated slopes for the change in VUS classification (9% per year) and P-LP variant classification (6% per year). The R2 and slope values were calculated using linear regression. B-LB indicates benign or likely benign.

Figure 2.  Variants Reinterpreted in the Study
Variants Reinterpreted in the Study

Number of downgraded pathogenic or likely pathogenic (P-LP) variants (A) and evidence for downgrade (B) and number of changed variant of uncertain significance (VUS) types (C) and evidence for change (D). The most frequently downgraded P-LP variant type was missense (n = 13) followed by protein truncating variants (structural, n = 3; stop-loss, n = 2) and duplications (n = 1). For VUS types that changed, the most frequent type was missense (n = 62) followed by synonymous (n = 2) and deletions (n = 1). The dominant category of protein consequence was missense variants in the P-LP variant (68.4%) and VUS (95.4%). The evidence used to reclassify the variants was as follows: ClinVar, information posted to the ClinVar database; lack of data, no evidence in the ClinVar database or the Human Gene Mutation Database; HGMD, population frequency in the Human Gene Mutation Database; 1000Gen, population frequency in the 1000 Genomes database; ExAC, population frequency information in the Exome Aggregation Consortium database; and manual, determined when variant was synonymous or a protein-truncating variant.

Table.  Reclassified Clinically Significant P-LP Variants and VUSsa
Reclassified Clinically Significant P-LP Variants and VUSsa
1.
Berg  AT, Coryell  J, Saneto  RP,  et al.  Early-life epilepsies and the emerging role of genetic testing.  JAMA Pediatr. 2017;171(9):863-871. doi:10.1001/jamapediatrics.2017.1743PubMedGoogle ScholarCrossref
2.
Comprehensive Epilepsy Panel. GeneDx. https://www.genedx.com/test-catalog/available-tests/comprehensive-epilepsy-panel/. Updated December 2016. Accessed May 2018.
3.
College of American Pathologists. Sequence variants—interpretation and reporting. In:  Molecular Pathology Checklist: CAP Accreditation Program. Northfield, IL: College of American Pathologists; July 28, 2015.
4.
Richards  S, Aziz  N, Bale  S,  et al; ACMG Laboratory Quality Assurance Committee.  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.  Genet Med. 2015;17(5):405-424. doi:10.1038/gim.2015.30PubMedGoogle ScholarCrossref
5.
Nambot  S, Thevenon  J, Kuentz  P,  et al; Orphanomix Physicians’ Group.  Clinical whole-exome sequencing for the diagnosis of rare disorders with congenital anomalies and/or intellectual disability: substantial interest of prospective annual reanalysis.  Genet Med. 2018;20(6):645-654. doi:10.1038/gim.2017.162PubMedGoogle ScholarCrossref
6.
Costain  G, Jobling  R, Walker  S,  et al.  Periodic reanalysis of whole-genome sequencing data enhances the diagnostic advantage over standard clinical genetic testing.  Eur J Hum Genet. 2018;26(5):740-744. doi:10.1038/s41431-018-0114-6PubMedGoogle ScholarCrossref
7.
Walsh  R, Thomson  KL, Ware  JS,  et al; Exome Aggregation Consortium.  Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples.  Genet Med. 2017;19(2):192-203. doi:10.1038/gim.2016.90PubMedGoogle ScholarCrossref
8.
Hiatt  SM, Amaral  MD, Bowling  KM,  et al.  Systematic reanalysis of genomic data improves quality of variant interpretation.  Clin Genet. 2018;94(1):174-178. doi:10.1111/cge.13259PubMedGoogle ScholarCrossref
9.
Aronson  SJ, Clark  EH, Varugheese  M, Baxter  S, Babb  LJ, Rehm  HL.  Communicating new knowledge on previously reported genetic variants.  Genet Med. 2012;14(8):713-719. doi:10.1038/gim.2012.19PubMedGoogle ScholarCrossref
10.
Harrison  SM, Dolinsky  JS, Knight Johnson  AE,  et al.  Clinical laboratories collaborate to resolve differences in variant interpretations submitted to ClinVar.  Genet Med. 2017;19(10):1096-1104. doi:10.1038/gim.2017.14PubMedGoogle ScholarCrossref
11.
Wright  CF, McRae  JF, Clayton  S,  et al.  Making new genetic diagnoses with old data: iterative reanalysis and reporting from genome-wide data in 1,133 families with developmental disorders.  [published online January 11, 2018].  Genet Med. 2018. doi:10.1038/gim.2017.246PubMedGoogle Scholar
12.
Mudigoudar  B, Weatherspoon  S, Wheless  JW.  Emerging antiepileptic drugs for severe pediatric epilepsies.  Semin Pediatr Neurol. 2016;23(2):167-179. doi:10.1016/j.spen.2016.06.003PubMedGoogle ScholarCrossref
13.
Hani  AJ, Mikati  MA.  Current and emerging therapies of severe epileptic encephalopathies.  Semin Pediatr Neurol. 2016;23(2):180-186. doi:10.1016/j.spen.2016.06.001PubMedGoogle ScholarCrossref
14.
Lek  M, Karczewski  KJ, Minikel  EV,  et al; Exome Aggregation Consortium.  Analysis of protein-coding genetic variation in 60,706 humans.  Nature. 2016;536(7616):285-291. doi:10.1038/nature19057PubMedGoogle ScholarCrossref
15.
The 1000 Genomes Project Consortium; Auton  A, Brooks  LD, Durbin  RM,  et al.  A global reference for human genetic variation.  Nature. 2015;526(7571):68-74. doi:10.1038/nature15393Google ScholarCrossref
16.
ClinVar Database. https://www.ncbi.nlm.nih.gov/clinvar/. Accessed May 2018.
Original Investigation
January 7, 2019

Clinical Utility of Reinterpreting Previously Reported Genomic Epilepsy Test Results for Pediatric Patients

Author Affiliations
  • 1Department of Pathology, University of Texas Southwestern Medical Center, Dallas
  • 2Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas
  • 3Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas
  • 4Eugene McDermott Center for Human Growth & Development, University of Texas Southwestern Medical Center, Dallas
  • 5Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas
JAMA Pediatr. 2019;173(1):e182302. doi:10.1001/jamapediatrics.2018.2302
Key Points

Question  How often do genomic test result interpretations change?

Findings  In this study of reported genetic variants from clinical genomic epilepsy tests, 67 of 185 pediatric patients (36.2%) had variants reclassified. A clinically significant change in the interpretation occurred in 19 of 61 patients (31.1%) with a genetic diagnosis during the 5-year study.

Meaning  The findings of this study suggest that pediatric patients with epilepsy and previous genomic test results should have their test results reinterpreted at least every 2 years and before further genetic testing.

Abstract

Importance  Clinical genomic tests that examine the DNA sequence of large numbers of genes are commonly used in the diagnosis and management of epilepsy in pediatric patients. The permanence of genomic test result interpretations is not known.

Objective  To investigate the value of reinterpreting previously reported genomic test results.

Design, Setting, and Participants  This study retrospectively reviewed and reinterpreted genomic test results from July 1, 2012, to August 31, 2015, for pediatric patients who previously underwent genomic epilepsy testing at a single tertiary care pediatric health care facility. Reinterpretation of previously reported variants was conducted in May 2017.

Main Outcomes and Measures  Patient reports from clinical genomic epilepsy tests were reviewed, and all reported genetic variants were reinterpreted using 2015 consensus standards and guidelines for interpreting hereditary genetic variants. Three classification tiers were used in the reinterpretation: pathogenic or likely pathogenic variant, variant of uncertain significance (VUS), or benign or likely benign variant.

Results  A total of 309 patients had genomic epilepsy tests performed (mean [SD] age, 5.6 [0.8] years; 163 [52.8%] male), and 185 patients had a genetic variant reported. The reported variants resulted in 61 patients with and 124 patients without a genetic diagnosis (VUS variants only). On reinterpretation of all reported variants, 67 of the 185 patients (36.2%) had a change in variant classification. Of the 67 patients with a genetic variant change in interpretation, 21 (31.3%) experienced a change in diagnosis. During the 5 years of the study, 19 of 61 patients (31.1%) with a genetic diagnosis and 48 of 124 patients (38.7%) with undiagnosed conditions (VUS only) had their results reclassified. Review of genomic reports issued during the final 2 years of the study identified reclassification of variants in 4 of 16 patients (25.0%) with a pathogenic or likely pathogenic variant and 11 of 41 patients (26.8%) with a VUS.

Conclusions and Relevance  The identified high rate of reinterpretation in this study suggests that interpretation of genomic test results has rapidly evolved during the past 5 years. These findings suggest that reinterpretation of genomic test results should be performed at least every 2 years.

Introduction

Genomic testing is used to evaluate many pediatric neurologic diseases, including intractable epilepsy and neuromuscular disorders. A recent study1 recommended broad genetic sequencing in the routine evaluation of early childhood epilepsies. Although it is technically feasible to analyze hundreds of genes in a single genomic test,2 the interpretation and clinical significance of genetic variants are evolving. Laboratory guidelines (College of American Pathologists and American College of Medical Genetics and Genomics [ACMG]) recommend periodic review of reported genetic variants.3,4 However, no clear recommendations guide the frequency of review of previously issued laboratory diagnoses.

Current clinical genomic tests include disease-specific panels, whole exome sequencing, and whole genome sequencing, which are powerful tools when used in combination with clinical knowledge.5 Recent reports6,7 have focused on the discovery and identification of new disease associations by reanalysis of genomic data. Only a few genomic studies8-11 have expanded the scope of reanalysis to include all gene variants previously reported. In a recent genomic reanalysis study8 of 494 patients with intellectual disability and/or developmental delay, the disease significance of a gene variant was upgraded in 23 patients and downgraded in 7 patients. Another previous study9 examining the reinterpretation of small panels of genes associated with hypertrophic cardiomyopathy found frequent changes in genetic interpretation. Similarly, periodic reinterpretation may apply new therapeutic associations to previously reported gene variants.12,13 Advances in publicly available databases and standardized interpretation criteria have improved the clinical interpretation of gene variants.4,14-16 In this study, we examined the frequency and significance of gene variant reclassification from previously interpreted epilepsy genomic test results.

Methods

This retrospective study included patients from a tertiary care pediatric health system (Children's Health Dallas, Dallas, Texas) with clinical genomic tests performed using next-generation sequencing epilepsy gene panels (July 1, 2012, to August 31, 2015). A single clinical laboratory (GeneDx) performed the tests and the initial interpretation of all the results. Initial genetic test results provided by the laboratory included interpretations equivalent to pathogenic variant, likely pathogenic variant, variant of uncertain significance, or negative test with no clinically significant variants. No benign or likely benign (B-LB) variants were initially reported. The laboratory in this study has a practice of routinely reclassifying variants and providing updated reports. In addition, this same laboratory routinely reinterprets variants and updates the significance of variants within the public database ClinVar and provides updated patient reports. This study was approved by the University of Texas Southwestern Medical Center Institutional Review Board with waiver of informed consent. Data were deidentified on collection and subsequently analyzed.

Reinterpretation of previously reported variants was conducted in May 2017 in 2 stages. First, variants were screened for new information in population frequency (Exome Aggregation Consortium, 1000 Genomes phase 315) (>1%) or clinical association (Human Gene Mutation Database, ClinVar16) databases. Second, identified variants were reinterpreted using the 2015 ACMG variant classification criteria4 and then compared with ClinVar updates from the original laboratory.

A clinically significant change of diagnosis was defined as P-LP variant downgraded to a VUS or B-LB variant or VUS upgraded to P-LP. Variant reinterpretation was performed by consensus among a clinical geneticist (G.G.), a clinical neurologist (D.M.T.), and a clinical genomics laboratory director (J.Y.P.).

Linear regression statistical analysis was performed using GraphPad Prism, version 7 (GraphPad Software). Statistical tests included R2, nonzero slope test, and comparison of the slopes (P < .05 was considered to be statistically significant).

Results

Genomic epilepsy tests were performed for 309 patients (mean [SD] age, 5.6 [0.8] years; 163 [52.8%] male), and 185 patients had a reported genetic variant. A laboratory diagnosis of at least 1 VUS (124 of 185 [67.0%]) and/or P-LP (61 of 185 [33.0%]) variant was initially reported. Thirty-five patients had both a VUS and a P-LP variant reported. After reanalyzing all cases with reported variants from the past 5 years, 67 of the 185 patients (36.2%) with a reported gene variant had a revised classification. A clinically significant change in diagnosis occurred in 21 of the 185 patients (11.4%) (Figure 1). Nineteen P-LP variants were downgraded in pathogenicity (14 to VUS and 5 to B-LB), and 2 VUSs were upgraded to P-LP (Table). Nine of these 21 reclassified variants were in concordance with the original laboratory data in upgraded or downgraded significance as reported in ClinVar and/or the patient's updated medical record.

Next, we examined the likelihood of reclassification over time. The reclassification rates for patients with P-LP variants and VUSs were similar, with nonsignificant differences in slope (P-LP, 6% change per year; VUS, 9% change per year; P = .24) (Figure 1). In total, 19 of 61 patients (31.1%) had a change in genetic diagnosis. Examination of a subset of the most recent 2 years of data identified 4 of 16 P-LP variants (25.0%) and 11 of 41 VUSs (26.8%) as reclassified.

The most frequently downgraded P-LP variants were missense (n = 13) (Figure 2). In most cases, protein-truncating variants were downgraded because of new population database information that indicated a high frequency of loss-of-function variants in healthy individuals. Overall, P-LP variants were reclassified because of new information in clinical databases (10 of 19 [52.6%]), population databases (1 of 19 [5.3%]), or a combination of both (4 of 19 [21.1%]) or the absence of data in either (4 of 19 [21.1%]) (Figure 2). Many of the downgraded P-LP variants or VUSs were similarly downgraded by the original reporting laboratory as observed in the laboratory’s ClinVar and/or medical record updates.

Of the 124 patients with no definitive diagnosis (VUS only), 2 (1.6%) had a VUS upgraded to P-LP (Table); however, 46 of 124 patients (37.1%) had their variants downgraded to B-LB. Most reclassified VUSs were missense variants (n = 62) followed by synonymous or deletion variants (Figure 2). In reviewing VUSs, new information in clinical databases (20 of 65 [30.8%]), population databases (7 of 65 [10.8%]), or a combination of both (34 of 65 [52.3%]) provided the basis for revising the VUS classification (Figure 2).

Discussion

On the basis of our single institution experience, 67 of 185 patients (36.2%) had revised gene variant interpretations. A clinically significant change in diagnosis occurred for 21 patients (11.4%). During the 5-year study period, patients with P-LP variants had a yearly reclassification rate of 5.5% and patients with VUSs had a yearly reclassification rate of 8.7%. This change in reclassification affected 19 of 61 patients (31.1%) with a P-LP variant and 48 of 124 patients (38.7%) with a VUS. In the final 2 years of the study, 4 of 16 patients (25.0%) with a P-LP variant and 11 of 41 patients (26.8%) with a VUS were affected.

Compared with the 36.2% variant reclassification rate observed in this study, another recent study8 that examined changes to P-LP variants and VUSs found a lower rate of reclassification (6%; 23 patients with variants upgraded in significance and 6 patients with variants downgraded in significance). The difference in the rate of reclassification may be because of the longer period of review in our study (5 years) compared with the previous study8 (2 years). Of more importance, the previous study8 examined patients with intellectual disability and/or developmental delay, whereas our study was focused on pediatric patients with epilepsy. We anticipate that both the patient’s disease and the passage of time will influence the degree to which reinterpretation will occur.

We recommend that reinterpretation of genetic test results for pediatric patients with epilepsy be performed at a minimum frequency of every 2 years. The reinterpretation should not be limited to genomic tests but should include all previously reported genetic tests. Before the initiation of the study, we had anticipated that the variants requiring reclassification might decrease after the publication of the 2015 ACMG guidelines4 or the release of population databases in 2014.15 On the contrary, the pattern of reclassifications was unchanged.

Limitations

This study was limited by an absence of an analysis of B-LB variants that may be upgraded to P-LP variants or VUSs; these variants were unavailable for examination. In addition, we used a consensus interpretation approach and did not examine variations in interpretation among health care professionals; however, this was mitigated by our frequent positive correlation (9 of 21), with upgraded and downgraded interpretations posted by the original laboratory to ClinVar and/or patient’s medical record (Table). Also, it is possible that our reinterpretation of variants in this study may not have included all of the evidence available in the literature.

Conclusions

This study suggests that clinical laboratories should commit to reinterpretation of P-LP variants and VUSs, and corrected laboratory reports should be communicated to treating physicians. Furthermore, physicians should understand and communicate to patients that medical knowledge is dynamic and genetic test interpretations may change over time. In summary, patients with previous epilepsy genomic test results should have their test results reinterpreted at least every 2 years and before further genetic testing. Applying these recommendations to other genomic tests is worth considering and should be investigated in future studies.

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Article Information

Accepted for Publication: June 4, 2018.

Corresponding Author: Jason Y. Park, MD, PhD, Department of Pathology, University of Texas Southwestern Medical Center, 1935 Medical District Dr, Dallas, TX 75235 (jason.park@childrens.com).

Published Online: November 5, 2018. doi:10.1001/jamapediatrics.2018.2302

Author Contributions: Drs Thodeson and Park had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: SoRelle, Thodeson, Park.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: SoRelle, Park.

Administrative, technical, or material support: Thodeson, Park.

Supervision: Thodeson, Arnold, Park.

Conflict of Interest Disclosures: Dr Park reported serving as a scientific advisory board member of Miraca Holdings, which has subsidiaries that provide generic testing services, including Baylor Genetics (Houston TX); serving as clinical director of the Advanced Diagnostics Laboratory at Children's Health Dallas, which provides genomic epilepsy testing and interpretation services; having patents for cancer diagnostics (gene patents) and therapeutics, which are assigned to Thomas Jefferson University or the University of Pennsylvania, and receiving patent royalty payments; having patent applications pending for cancer diagnostics and therapeutics; and having served as a consultant and scientific advisory board member for Targeted Diagnostics and Therapeutics, and holding stock in this company. No other disclosures were reported.

Funding/Support: This study was funded by award UL1TR001105 from the National Center for Advancing Translational Sciences, National Institutes of Health (Dr Thodeson).

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

References
1.
Berg  AT, Coryell  J, Saneto  RP,  et al.  Early-life epilepsies and the emerging role of genetic testing.  JAMA Pediatr. 2017;171(9):863-871. doi:10.1001/jamapediatrics.2017.1743PubMedGoogle ScholarCrossref
2.
Comprehensive Epilepsy Panel. GeneDx. https://www.genedx.com/test-catalog/available-tests/comprehensive-epilepsy-panel/. Updated December 2016. Accessed May 2018.
3.
College of American Pathologists. Sequence variants—interpretation and reporting. In:  Molecular Pathology Checklist: CAP Accreditation Program. Northfield, IL: College of American Pathologists; July 28, 2015.
4.
Richards  S, Aziz  N, Bale  S,  et al; ACMG Laboratory Quality Assurance Committee.  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.  Genet Med. 2015;17(5):405-424. doi:10.1038/gim.2015.30PubMedGoogle ScholarCrossref
5.
Nambot  S, Thevenon  J, Kuentz  P,  et al; Orphanomix Physicians’ Group.  Clinical whole-exome sequencing for the diagnosis of rare disorders with congenital anomalies and/or intellectual disability: substantial interest of prospective annual reanalysis.  Genet Med. 2018;20(6):645-654. doi:10.1038/gim.2017.162PubMedGoogle ScholarCrossref
6.
Costain  G, Jobling  R, Walker  S,  et al.  Periodic reanalysis of whole-genome sequencing data enhances the diagnostic advantage over standard clinical genetic testing.  Eur J Hum Genet. 2018;26(5):740-744. doi:10.1038/s41431-018-0114-6PubMedGoogle ScholarCrossref
7.
Walsh  R, Thomson  KL, Ware  JS,  et al; Exome Aggregation Consortium.  Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples.  Genet Med. 2017;19(2):192-203. doi:10.1038/gim.2016.90PubMedGoogle ScholarCrossref
8.
Hiatt  SM, Amaral  MD, Bowling  KM,  et al.  Systematic reanalysis of genomic data improves quality of variant interpretation.  Clin Genet. 2018;94(1):174-178. doi:10.1111/cge.13259PubMedGoogle ScholarCrossref
9.
Aronson  SJ, Clark  EH, Varugheese  M, Baxter  S, Babb  LJ, Rehm  HL.  Communicating new knowledge on previously reported genetic variants.  Genet Med. 2012;14(8):713-719. doi:10.1038/gim.2012.19PubMedGoogle ScholarCrossref
10.
Harrison  SM, Dolinsky  JS, Knight Johnson  AE,  et al.  Clinical laboratories collaborate to resolve differences in variant interpretations submitted to ClinVar.  Genet Med. 2017;19(10):1096-1104. doi:10.1038/gim.2017.14PubMedGoogle ScholarCrossref
11.
Wright  CF, McRae  JF, Clayton  S,  et al.  Making new genetic diagnoses with old data: iterative reanalysis and reporting from genome-wide data in 1,133 families with developmental disorders.  [published online January 11, 2018].  Genet Med. 2018. doi:10.1038/gim.2017.246PubMedGoogle Scholar
12.
Mudigoudar  B, Weatherspoon  S, Wheless  JW.  Emerging antiepileptic drugs for severe pediatric epilepsies.  Semin Pediatr Neurol. 2016;23(2):167-179. doi:10.1016/j.spen.2016.06.003PubMedGoogle ScholarCrossref
13.
Hani  AJ, Mikati  MA.  Current and emerging therapies of severe epileptic encephalopathies.  Semin Pediatr Neurol. 2016;23(2):180-186. doi:10.1016/j.spen.2016.06.001PubMedGoogle ScholarCrossref
14.
Lek  M, Karczewski  KJ, Minikel  EV,  et al; Exome Aggregation Consortium.  Analysis of protein-coding genetic variation in 60,706 humans.  Nature. 2016;536(7616):285-291. doi:10.1038/nature19057PubMedGoogle ScholarCrossref
15.
The 1000 Genomes Project Consortium; Auton  A, Brooks  LD, Durbin  RM,  et al.  A global reference for human genetic variation.  Nature. 2015;526(7571):68-74. doi:10.1038/nature15393Google ScholarCrossref
16.
ClinVar Database. https://www.ncbi.nlm.nih.gov/clinvar/. Accessed May 2018.
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