Best Practices for Clinical Whole Genome Sequencing (PDF)

www.nature.com/npjgenmed REVIEW ARTICLE OPEN Best practices for the interpretation and reporting of clinical whole genome sequencing Christina A. Austin-Tse 1,2,3,16 ✉, Vaidehi Jobanputra 4,5,16, Deni...

www.nature.com/npjgenmed REVIEW ARTICLE OPEN Best practices for the interpretation and reporting of clinical whole genome sequencing Christina A. Austin-Tse 1,2,3,16 ✉, Vaidehi Jobanputra 4,5,16, Denise L. Perry6, David Bick 7, Ryan J. Taft6, Eric Venner8, Richard A. Gibbs8, Ted Young 9, Sarah Barnett10, John W. Belmont 6, Nicole Boczek10,11, Shimul Chowdhury12, Katarzyna A. Ellsworth12, Saurav Guha 4, Shashikant Kulkarni13,14, Cherisse Marcou10, Linyan Meng13,14, David R. Murdock8,14, Atteeq U. Rehman4, Elizabeth Spiteri15, Amanda Thomas-Wilson4, Hutton M. Kearney 10,16, Heidi L. Rehm1,3,16 and Medical Genome Initiative* Whole genome sequencing (WGS) shows promise as a first-tier diagnostic test for patients with rare genetic disorders. However, standards addressing the definition and deployment practice of a best-in-class test are lacking. To address these gaps, the Medical Genome Initiative, a consortium of leading health care and research organizations in the US and Canada, was formed to expand access to high quality clinical WGS by convening experts and publishing best practices. Here, we present best practice recommendations for the interpretation and reporting of clinical diagnostic WGS, including discussion of challenges and emerging approaches that will be critical to harness the full potential of this comprehensive test. npj Genomic Medicine (2022)7:27 ; https://doi.org/10.1038/s41525-022-00295-z 1234567890():,; INTRODUCTION are appropriately and accurately interpreted, validated, and Whole genome sequencing (WGS) is emerging as a first-tier reported, laboratories must carefully consider additional steps in diagnostic test for rare genetic diseases1,2. Compared to whole the testing process, including test ordering and orthogonal exome sequencing (WES) and other molecular diagnostic tests confirmation. (e.g. sequencing panels, microarrays), WGS is more comprehensive To facilitate more widespread adoption of whole genome for two reasons: (i) it allows detection of a broad range of variant sequencing, the Medical Genome Initiative16 (MGI) formed a types in a single assay, including single nucleotide variants (SNV), working group to establish best practice recommendations for the small insertions and deletions, mitochondrial variants (MT), repeat interpretation and reporting of clinical diagnostic WGS as a expansions (RE), copy number variants (CNV) and other structural comprehensive test. Teleconference meetings were held over a variants (SV); and (ii) it is untargeted, resulting in more uniform 12-month period. Informal polling (Supplementary Note 1) was coverage of exonic regions3–5 and added coverage of intronic, used to gain insight into the current practices of each member intergenic and regulatory regions. institution related to a multitude of topics including requisition/ Multiple publications have demonstrated the diagnostic super- consent, data annotation, analysis, triage and variant curation, iority of WGS as compared to chromosomal microarray (CMA), reporting, and reanalysis. Information obtained was used to guide karyotyping, or other targeted sequencing assays2,6–10. While a the discussion and development of recommendations based on recent meta-analysis11 found no significant difference in yields consensus among the participating laboratories. The discussions between WES and WGS, comparisons across cohorts, such as this also allowed identification of areas lacking consensus and key one, have limited utility given the variability introduced by unmet needs that, if addressed, would enable increased adoption differing patient age groups, clinical indications, family structures, of WGS in routine practice. and variant types analyzed12. In contrast, studies comparing yields within the same cohort support diagnostic or analytical superiority of WGS2,6,13–15. As a result, WGS has the potential to replace most OVERVIEW other forms of DNA-based testing. Clinical diagnostic genomic sequencing tests can be separated Genome test interpretation and reporting represents a chal- into three phases of analysis: primary, secondary, and tertiary (Fig. lenge to laboratories seeking to implement, or maximize the 1). Primary analysis encompasses the technical components of the diagnostic potential of, clinical WGS. For instance, laboratories assay, including DNA extraction, library preparation, sequence must design analytical strategies capable of efficiently prioritizing generation, and preliminary data quality control (QC). Secondary clinically relevant variation across all variant types captured by analysis involves bioinformatic processes such as alignment of the WGS (Table 1). Furthermore, to ensure that the prioritized variants raw sequence data to a genome reference, variant calling, and 1 Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA. 2Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA, USA. 3Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. 4Molecular Diagnostics Laboratory, New York Genome Center, New York, NY, USA. 5Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA. 6Illumina Inc., San Diego, CA, USA. 7 HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA. 8Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA. 9Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, ON, Canada. 10Division of Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA. 11Center for Individualized Medicine, College of Medicine, Mayo Clinic, Rochester, MN, USA. 12Rady Children’s Institute for Genomic Medicine, San Diego, CA, USA. 13Baylor Genetics and Baylor College of Medicine, Houston, TX, USA. 14Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA. 15Department of Pathology, Stanford Medicine, Stanford University, Stanford, CA, USA. 16These authors contributed equally: Christina A. Austin-Tse, Vaidehi Jobanputra, Hutton M. Kearney, Heidi L. Rehm. *A list of members and their affiliations appears in the Supplementary Information. ✉email: [email protected] Published in partnership with CEGMR, King Abdulaziz University  1234567890():,; 2 Table 1. Interpretation and reporting considerations for clinically relevant variant types detectable by clinical WGS. Variant type or category Key interpretation and reporting considerations Diagnostic potentiala Exome platform Genome platform maturityb maturityb Single nucleotide variants (SNV) Represents the largest number of variants for review, requiring phenotype-driven and High High High genotype-driven filtering strategies (Fig. 2). All possible consequences should be considered (e.g. review of splicing annotations, transcript-specific impacts, MNVs). Some positions may have more than one alternate allele (multi-allelic variant) Small (1%) to ensure known pathogenic high of an unbiased analysis approach. This strategy facilitates the frequency variants will be reviewed. Resources for identifying detection of: (1) unanticipated genetic diagnoses that may explain these types of variants are being assembled through ClinGen48 all or a portion of the patient phenotype; (2) patients with unusual and the Genetic Testing Reference Materials Coordination presentations of established disorders (phenotypic expansion); (3) Program (GeT-RM, https://www.cdc.gov/labquality/get-rm/index. multiple genetic diagnoses in a single individual; (4) variants html). To supplement these resources, we have also provided relevant to a secondary phenotype or family history of disease; (5) examples of low penetrance, risk, and other high frequency variants in novel disease genes; and (6) clinically significant variants of interest in Supplementary Data 4. incidental or secondary findings. Beyond the identification of variants in well-established disease Genotype-driven analyses should aim to capture all variants genes that match the patient phenotype, genotype-driven that might have sufficient evidence to be classified as pathogenic analysis can also be tailored to the discovery of novel disease or likely pathogenic, including: previously reported disease- genes. Given the rapid pace at which new genotype-phenotype causing variants, predicted loss of function (pLOF) variants (e.g. correlations are discovered, reporting these findings may aid in nonsense, frameshift, and essential splice sites) and, when building evidence for disease causality in a time period relevant to multiple family members are sequenced, variants that are the patient’s care. As a result, clinical laboratories are encouraged suspicious based on their inheritance pattern (e.g. de novo to include analysis of genes not yet linked to disease with variants or biallelic rare variants in a gene associated with a judicious reporting. Gene discovery analyses may prioritize de recessive disorder). Automated prioritization of previously novo and/or pLOF variants in highly constrained genes based on reported pathogenic variants can be challenging given the gnomAD constraint scores as well as biallelic pLOF variants in unstructured nature of the scientific literature. To aid analysts in genes that are devoid of homozygous LOF variants in gnomAD. identifying variants with known or suspected disease association, software tools may identify variants previously reported in Phenotype-driven analysis association with any phenotype based on incorporated literature In most cases, the genotype-driven analysis should be supple- searches or database entries. ClinVar is a critical database for this mented with additional “phenotype-driven” analyses, particularly purpose44. While variant classifications in ClinVar should not be if there are specific genes that are highly relevant to the patient’s assumed to be correct, they represent a useful tool to efficiently phenotype. Phenotype-driven analyses allow for the comprehen- identify candidate variants and publications that warrant further review. In addition to freely accessible and downloadable sive review of potentially relevant variants that may not meet the databases like ClinVar, laboratories may choose to supplement criteria defined in the genotype-driven analysis approach their annotations with gene or variant-disease relationships from described above (e.g. novel missense variants in dominant genes). additional sources including subscription-based databases (see Variants identified exclusively by phenotype-driven analyses are Supplementary Data 3 for databases in use at participating more likely to be classified as benign or variants of uncertain institutions). significance given that they have no prior reports of pathogeni- In order to reduce the number of variants requiring expert city, no de novo occurrence, and no predicted LOF impact, all of review and to target variants most likely to cause genetic disease, which would surface through genotype-driven analyses. Never- additional filters are typically applied to genotype-driven analyses. theless, they may still meet criteria for reporting if located in a For example, expert review may be focused on variants in or near gene strongly associated with the patient’s phenotype (see genes that have a reported link to human disease, such as those reporting section below). Some nonspecific or highly genetically curated by OMIM and other gene-level resources, most of which heterogeneous phenotypes (e.g. developmental delay and autism) have been aggregated by the Gene Curation Coalition (thegencc. are less likely to benefit from phenotype-driven analysis strategies. org). To further reduce the interpretive burden, laboratories also Therefore, the decision regarding the appropriateness of this employ allele frequency cutoffs, which make use of population approach is at the discretion of the analysis team. frequency data from reference databases such as the Genome When performing phenotype-driven analyses, laboratories must Aggregation Database (gnomAD; https://gnomad.broadinstitute. have a mechanism for defining the genes of interest for a given org/) to exclude variants that are too common to cause rare phenotype. Automated phenotype-driven analyses, such as those genetic disease. Caution must be exercised as some cohorts in integrated into commercially available genomic analysis plat- gnomAD do not represent the general population and were not forms, typically depend on structured patient phenotype data (e.g. screened to exclude all individuals with a genetic disease. HPO terms) to prioritize variants found in genes relevant to the Additionally, variants that arise from clonal hematopoiesis of patient’s phenotype. While automated methods have clear indeterminate potential (CHIP)45,46 may falsely elevate population benefits in terms of efficiency, their performance varies depending allele frequencies in several genes associated with germline on the algorithms and gene-phenotype association sources used. genetic syndromes (e.g. DNMT3A, ASXL1, and TP53)47. Alternatively, laboratories may manually curate a list of relevant While reducing the number of variants requiring review is genes that can be used to prioritize variants for downstream critical to the efficiency of WGS analysis, filtering criteria must analysis. There are multiple available sources of gene-disease ensure true pathogenic variation is not missed. For example, association information (see Supplementary Data 5). Of note, there pathogenic founder variants, variants with reduced penetrance, or is no single source from which all relevant genes can reliably be variants in genes associated with a disease of varying clinical mined. As a result, the curation of gene-disease associations from severity may be more common in the population than the applied multiple databases is likely to produce a more comprehensive list. frequency cutoff, yet still be clinically relevant to the patient. Furthermore, caution should be exercised as idiosyncrasies in Laboratories must design filtering approaches to account for this search functionality and gene-disease annotations can lead to circumstance. For example, laboratories could review all variants missing critical genes (e.g. if a database associates the GJB2 gene classified as likely pathogenic/pathogenic in ClinVar and the exclusively with “hearing loss”, a query using the term “deafness” laboratory’s internal knowledge base with no additional filtering may not return the gene). Given multiple potential sources of error criteria, or implement more permissive criteria (e.g. 500 kb for deletions and WGS reporting policies should maximize the test’s diagnostic >1 Mb for duplications) or gene content threshold (e.g. more than potential while minimizing the number of variants that may cause 25 deleted genes), should be curated and classified per published unnecessary clinician follow-up or patient stress or anxiety. guidelines77, and reported according to laboratory policy. Policies should be available to patients and ordering providers to ensure the patient is appropriately consented prior to the In-depth variant assessment initiation of testing. Finally, laboratories are strongly encouraged When variants of interest are identified during triage, in-depth to engage ordering providers in reporting decisions when there is gene and variant analysis should be performed prior to making uncertainty as to whether a variant aligns with the patient’s reporting decisions. Such analyses should follow existing guide- phenotype or the family’s preferences. This communication and lines on the interpretation of sequence variants78,79, copy number the factors considered in the decision to return a result should be variants77, low penetrance/risk alleles (https://www. documented in the laboratory’s record. clinicalgenome.org/working-groups/low-penetrance-risk-allele- working-group/), mitochondrial variants58,80,81, and evaluating Result summary gene-disease relationships82. While it is common practice for targeted panel results to be classified as “Positive”, “Negative”, or “Inconclusive” based on the Secondary review variants identified, the definition of these categories becomes Given the large amount of information processed by analysts more complex in genomic testing, which may identify variants during triage steps, it is recommended that all triage decisions be relevant to the primary indication for testing, variants that explain agreed upon by at least two trained staff members. This QC step non-primary phenotypes, secondary findings, or other variant increases the accuracy of genome interpretations and aims to types. We support current ACMG recommendations49, which state identify potentially missed candidate variants. Dual review that “Primary findings in a diagnostic test should appear as a increases the time and cost of the test, but the laboratory may succinct interpretive result at the beginning of the report efficiently design the review step in consideration of the type of indicating the presence or absence of variants consistent with personnel completing each step and the depth of review required the phenotype.” Laboratories may find terms such as “Positive” or to achieve high quality genome interpretation. “Negative” useful for straightforward WGS results, but a descrip- tive statement defining those terms (e.g. “Positive: Findings Orthogonal confirmation or characterization of reportable explain indication for testing”) should also be considered. When variants the interpretive result is more complex, descriptive statements that speak to the relevance of the result to the patient phenotype The decision to pursue orthogonal testing depends on the extent are essential. The integration of WGS results into the medical of the laboratory’s validation for a particular variant type, quality record should be considered when drafting interpretive result metrics for a specific variant and requirements from regulatory summaries, since the summary may influence whether or not a bodies83–85. For example, a laboratory may conduct orthogonal provider chooses to review the report in detail. It is also possible testing on the same specimen to confirm a variant with low that future clinical informatics standards (e.g. HL7) may dictate quality metrics, confirm the result with a new specimen, clarify the that each indication for testing has a separate and distinct result. exact repeat size for a locus with an expanded STR call using a Therefore, considering report structure in light of these evolving targeted assay, deeply sequence (via a separate NGS test) an SNV standards may be prudent. to investigate potential of mosaicism, or determine levels of heteroplasmy in additional tissues from the affected individual. Technical limitations Reporting practices for technical limitations should be consistent REPORTING with other NGS-based testing standards49. In addition to listing Report contents should conform to existing guidelines for key components of the bioinformatics pipeline, the description of reporting from the ACMG49. Additional considerations particularly the analysis strategy should define all filtering and/or prioritization relevant to WGS reporting are presented below, including variants approaches used. The known limitations of the testing methodol- and genes of uncertain significance, STRs, and variants unrelated ogy as well as any variant types not interrogated should be to the primary indication for testing. described. Any known technically challenging regions or coverage Variants identified in established disease genes (as defined by issues in genes that are likely to be highly relevant to the patient current standards82) that are relevant to the primary indication for (e.g. limited sensitivity for F8 inversions in a patient with Published in partnership with CEGMR, King Abdulaziz University npj Genomic Medicine (2022) 27  C.A. Austin-Tse et al. 10 Table 2. Suggested steps of reanalysis based on events that have occurred since initial analysis. Tertiary analysis Change since initial analysis Primary analysis (sample/ Secondary analysis (mapping, Annotation Variant Variant and Reporting library prep and sequencing) alignment, variant calling, QC) stratification gene assessment Significant improvements in library ✔ ✔ ✔ ✔ ✔ ✔ prep/sequencing technology Bioinformatics improvements ✔ ✔ ✔ ✔ ✔ >1 year lapsed since initial analysis ✔ ✔ ✔ ✔ Additional patient phenotypes or ✔ ✔ ✔ family history Improved understanding of the ✔ ✔ ✔ genetic etiology of patient condition New methodology or resource for ✔ ✔ variant assessment hemophilia86) should be specifically called out as a potential Furthermore, given the differing approaches, algorithms, and source of reduced sensitivity. Several tools for calculating region- professional opinion inherent to WGS analysis, laboratories should specific coverage are freely available87–89. support the sharing of raw sequencing data and other file types to enable analysis by other laboratories or research programs if requested by the patient or ordering provider. MGI laboratories REANALYSIS are currently providing this data through encrypted hard drives or Periodic case reanalysis has been demonstrated to improve access through a portal. diagnostic yield90–93. It is therefore recommended that labora- tories provide an option for reanalysis of finalized WGS cases. Ideally, reanalysis policies should be developed in advance of test KEY RECOMMENDATIONS launch and communicated to providers at the time the test is Key recommendations are summarized below. Given our goal to ordered. The ACMG has recently produced two “points to provide a complete reference for WGS, this list includes consider” documents relevant to reanalysis policies and proce- recommendations that are also relevant to WES. dures94,95. Of note, procedures for variant-level reevaluation are not substantially different from other genetic testing methods and Requisition/Consent have been addressed elsewhere78,94. While the use of structured phenotype ontologies is important Robust reanalysis may necessitate re-running multiple steps of for the automation and scalability of WGS, laboratories are the test (Table 2). Given the significant role that the patient cautioned against requiring ordering providers to submit phenotype plays in the analysis process, laboratories should information in the primary structured form given the potential request updates to the patient’s medical and family history prior for loss of detailed and nuanced phenotypic information to initiating reanalysis. Phenotype- and genotype-driven analyses The test ordering process should enable physicians to specify should be reviewed and adjusted in light of the updated patient the primary clinical question of interest information. Test requisition forms and any laboratory provided consent Even in the absence of new phenotype information, newly forms should clearly indicate that genetic variants relevant to published variant or gene-level evidence may allow a previously any phenotype provided to the laboratory may be returned unreviewed variant to meet criteria for expert review or a unless specific reporting instructions are provided by the previously reviewed variant to meet criteria for reporting. ordering clinician Laboratories may consider suggesting a minimum time period For trio or other multiple-family member sequencing (e.g. one year) to have elapsed since the initial analysis to conduct approaches, requisition and/or consent forms should clarify this type of case review. Alternatively, reanalysis may be initiated how the data from auxiliary family members will be used and by new publications, updated transcripts and new gene models, reported or changes to the WGS test definition that may impact a set Phenotypic data submitted with the test order should of cases. undergo review by laboratory staff prior to the initiation of The initiation of reanalysis may be either reactive (i.e., when testing and laboratories should seek clarification of unclear or requested by the ordering provider/patient) or proactive (inde- conflicting information pendently triggered by the lab). As of the time of this publication, Policies for secondary findings analysis and secondary and the majority of laboratories currently offering WGS analysis are incidental findings reporting should be developed in advance performing reactive reanalysis. However, proactive reanalysis, of launching a WGS test and clearly defined on the including the acquisition of updated clinical information, is laboratory’s requisition and any provided consent form recognized as an important step towards maximizing the clinical Annotation utility of the WGS test. Several key issues stand in the way of this ideal, including the personnel effort required to conduct analysis, In the absence of infrastructure that can support continuous lack of reimbursement, limited tools to enable tracking of cases in updates, we recommend that data sources used in annotation need of follow-up, and limited tools to automatically identify new pipelines be updated at least quarterly. scientific literature relevant to variants and genes reviewed in past Until noncoding regions of the genome can be system- cases. Improved systems to address these issues will be critical to atically interrogated and interpreted, laboratories should the future implementation of proactive reanalysis. ensure that their pipelines are able to capture all known Given the substantial effort required for case reanalysis, pathogenic variants in ClinVar, including those that fall laboratories may need to charge a fee for this service. outside of coding sequence and flanking intronic regions. npj Genomic Medicine (2022) 27 Published in partnership with CEGMR, King Abdulaziz University  C.A. Austin-Tse et al. 11 Analysis variants that affect exonic splice enhancers, and databases cataloguing structural variation within large populations). The overall analysis approach should incorporate both genotype-driven and phenotype-driven strategies. Analysis The complete set of variants meeting the genotype- and Routine deposition of variant data in structured format into phenotype-centric filtering criteria should be reviewed for centralized databases (e.g. ClinVar) and scientific literature to every case, even when a likely explanatory variant is identified improve identification of previously reported variants. early in the triage process. Improved tools for calling, filtering, and interpretation of SVs If the interpretive tool in use does not readily identify and STRs. compound heterozygous calls across variant classes (e.g. Maturation and validation of AI/machine learning tools will be SNV and CNV), re-examination of calls across all relevant needed to scale analysis. variant classes should be performed when a compelling monoallelic variant is found in an autosomal recessive gene Reporting associated with the patient’s phenotype. Structured integration of WGS results into the medical record Given the large amount of information processed by analysts or connected platforms. during triage steps, it is recommended that all variants identified by genotype- and phenotype-centric filtering Reanalysis criteria be reviewed by at least two trained staff members. Tools to support systematic proactive reanalysis (i.e., tools to The sensitivity and specificity of automated analysis tools automatically identify new scientific literature relevant to remain insufficient to replace the role of a human analyst. variants and genes reviewed in past cases). Results from automated analyses should be carefully assessed Reimbursement for reanalysis. by a human analyst prior to consideration for reporting. Reporting Reporting summary The laboratory should establish policies defining the types of Further information on research design is available in the Nature findings that are considered for return, and these policies Research Reporting Summary linked to this article. should be available to patients and providers. Variant-level evidence, gene-level evidence, and the DATA AVAILABILITY correlation between the patient’s phenotype and the All structured data generated or analyzed during this study are included in this gene should be addressed. published article (and its supplementary information files). The goal of reporting policies should be to maximize the test’s diagnostic potential while minimizing the number of Received: 4 August 2021; Accepted: 17 February 2022; VUS reported. 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