Suspected clonal hematopoiesis as a natural functional assay of TP53 germline variant pathogenicity

PurposeSome variants identified by multigene panel testing of DNA from blood present with low variant allele fraction (VAF), often a manifestation of clonal hematopoiesis. Research has shown that the proportion of variants with low VAF is especially high in TP53, the Li-Fraumeni syndrome gene. Based on the hypothesis that variants with low VAF are positively selected as drivers of clonal hematopoiesis, we investigated the use of VAF as a predictor of TP53 germline variant pathogenicity.MethodsWe used data from 260,681 TP53 variants identified at 2 laboratories to compare the distribution of pathogenic and benign variants at different VAF intervals.ResultsLikelihood ratios toward pathogenicity associated with a VAF < 26% equated to the American College of Medical Genetics/Association of Molecular Pathology strong strength level and were applicable for 1 in 5 variants of unknown significance.ConclusionIn conclusion, detection of variants with low VAF in blood can be considered an in vivo functional assay to aid assessment of TP53 variant pathogenicity.     

Reanalysis of eMERGE phase III sequence variants in 10,500 participants and infrastructure to support the automated return of knowledge updates

PurposeThe clinical genomics knowledgebase is dynamic with variant classifications changing as newly identified cases, additional population data, and other evidence become available. This is a challenge for the clinical laboratory because of limited resource availability for variant reassessment.MethodsThroughout the Electronic Medical Records and Genomics phase III program, clinical sites associated with the Mass General Brigham/Broad sequencing center received automated, real-time notifications when reported variants were reclassified. In this study, we summarized the nature of these reclassifications and described the proactive reassessment framework we used for the Electronic Medical Records and Genomics program data set to identify variants most likely to undergo reclassification.ResultsReanalysis of 1855 variants led to the reclassification of 2% (n = 45) of variants, affecting 0.6% (n = 67) of participants. Of these reclassifications, 78% (n = 35) were high-impact changes affecting reportability, with 8 variants downgraded from likely pathogenic/pathogenic to variants of uncertain significance (VUS) and 27 variants upgraded from VUS to likely pathogenic/pathogenic. Most upgraded variants (67%) were initially classified as VUS–Favor Pathogenic, highlighting the benefit of VUS subcategorization. The most common reason for reclassification was new published case data and/or functional evidence.ConclusionOur results highlight the importance of periodic sequence variant reevaluation and the need for automated approaches to advance routine implementation of variant reevaluations in clinical practice.     

CardioClassifier: disease- and gene-specific computational decision support for clinical genome interpretation

PurposeInternationally adopted variant interpretation guidelines from the American College of Medical Genetics and Genomics (ACMG) are generic and require disease-specific refinement. Here we developed CardioClassifier (http://www.cardioclassifier.org), a semiautomated decision-support tool for inherited cardiac conditions (ICCs).MethodsCardioClassifier integrates data retrieved from multiple sources with user-input case-specific information, through an interactive interface, to support variant interpretation. Combining disease- and gene-specific knowledge with variant observations in large cohorts of cases and controls, we refined 14 computational ACMG criteria and created three ICC-specific rules.ResultsWe benchmarked CardioClassifier on 57 expertly curated variants and show full retrieval of all computational data, concordantly activating 87.3% of rules. A generic annotation tool identified fewer than half as many clinically actionable variants (64/219 vs. 156/219, Fisher’s P = 1.1 × 10⁻¹⁸), with important false positives, illustrating the critical importance of disease and gene-specific annotations. CardioClassifier identified putatively disease-causing variants in 33.7% of 327 cardiomyopathy cases, comparable with leading ICC laboratories. Through addition of manually curated data, variants found in over 40% of cardiomyopathy cases are fully annotated, without requiring additional user-input data.ConclusionCardioClassifier is an ICC-specific decision-support tool that integrates expertly curated computational annotations with case-specific data to generate fast, reproducible, and interactive variant pathogenicity reports, according to best practice guidelines.     

eyeVarP: A computational framework for the identification of pathogenic variants specific to eye disease

PurposeDisease-specific pathogenic variant prediction tools that differentiate pathogenic variants from benign have been improved through disease specificity recently. However, they have not been evaluated on disease-specific pathogenic variants compared with other diseases, which would help to prioritize disease-specific variants from several genes or novel genes. Thus, we hypothesize that features of pathogenic variants alone would provide a better model.MethodsWe developed an eye disease–specific variant prioritization tool (eyeVarP), which applied the random forest algorithm to the data set of pathogenic variants of eye diseases and other diseases. We also developed the VarP tool and generalized pipeline to filter missense and insertion-deletion variants and predict their pathogenicity from exome or genome sequencing data, thus we provide a complete computational procedure.ResultseyeVarP outperformed pan disease–specific tools in identifying eye disease–specific pathogenic variants under the top 10. VarP outperformed 12 pathogenicity prediction tools with an accuracy of 95% in correctly identifying the pathogenicity of missense and insertion-deletion variants. The complete pipeline would help to develop disease-specific tools for other genetic disorders.ConclusioneyeVarP performs better in identifying eye disease–specific pathogenic variants using pathogenic variant features and gene features. Implementing such complete computational procedure would significantly improve the clinical variant interpretation for specific diseases.     

Evaluating the impact of in silico predictors on clinical variant classification

PurposeAccording to the American College of Medical Genetics and Genomics/Association of Medical Pathology (ACMG/AMP) guidelines, in silico evidence is applied at the supporting strength level for pathogenic (PP3) and benign (BP4) evidence. Although PP3 is commonly used, less is known about the effect of these criteria on variant classification outcomes.MethodsA total of 727 missense variants curated by Clinical Genome Resource expert groups were analyzed to determine how often PP3 and BP4 were applied and their impact on variant classification. The ACMG/AMP categorical system of variant classification was compared with a quantitative point-based system. The pathogenicity likelihood ratios of REVEL, VEST, FATHMM, and MPC were calibrated using a gold standard set of 237 pathogenic and benign variants (classified independent of the PP3/BP4 criteria).ResultsThe PP3 and BP4 criteria were applied by Variant Curation Expert Panels to 55% of missense variants. Application of those criteria changed the classification of 15% of missense variants for which either criterion was applied. The point-based system resolved borderline classifications. REVEL and VEST performed best at a strength level consistent with moderate evidence.ConclusionWe show that in silico criteria are commonly applied and often affect the final variant classifications. When appropriate thresholds for in silico predictors are established, our results show that PP3 and BP4 can be used at a moderate strength.     

Toward automation of germline variant curation in clinical cancer genetics

PurposeCancer care professionals are confronted with interpreting results from multiplexed gene sequencing of patients at hereditary risk for cancer. Assessments for variant classification now require orthogonal data searches and aggregation of multiple lines of evidence from diverse resources. The clinical genetics community needs a fast algorithm that automates American College of Medical Genetics and Genomics (ACMG) based variant classification and provides uniform results.MethodsPathogenicity of Mutation Analyzer (PathoMAN) automates germline genomic variant curation from clinical sequencing based on ACMG guidelines. PathoMAN aggregates multiple tracks of genomic, protein, and disease specific information from public sources. We compared expertly curated variant data from clinical laboratories to assess performance.ResultsPathoMAN achieved a high overall concordance of 94.4% for pathogenic and 81.1% for benign variants. We observed negligible discordance (0.3% pathogenic, 0% benign) when contrasted against expert curated variants. Some loss of resolution (5.3% pathogenic, 18.9% benign) and gain of resolution (1.6% pathogenic, 3.8% benign) were also observed.ConclusionAutomation of variant curation enables unbiased, fast, efficient delivery of results in both clinical and laboratory research. We highlight the advantages and weaknesses related to the programmable automation of variant classification. PathoMAN will aid in rapid variant classification by generating robust models using a knowledgebase of diverse genetic data (https://pathoman.mskcc.org).     

Systematic misclassification of missense variants in BRCA1 and BRCA2 “coldspots”

PurposeGuidelines for variant interpretation incorporate variant hotspots in critical functional domains as evidence for pathogenicity (e.g., PM1 and PP2), but do not use “coldspots,” that is, regions without essential functions that tolerate variation, as evidence a variant is benign. To improve variant classification we evaluated BRCA1 and BRCA2 missense variants reported in ClinVar to identify regions where pathogenic missenses are extremely infrequent, defined as coldspots.MethodsWe used Bayesian approaches to model variant classification in these regions.ResultsBRCA1 exon 11 (~60% of the coding sequence), and BRCA2 exons 10 and 11 (~65% of the coding sequence), are coldspots. Of 89 pathogenic (P) or likely pathogenic (LP) missense variants in BRCA1, none are in exon 11 (odds <0.01, 95% confidence interval [CI] 0.0–0.01). Of 34 P or LP missense variants in BRCA2, none are in exons 10–11 (odds <0.01, 95% CI 0.0–0.01). More than half of reported missense variants of uncertain significance (VUS) in BRCA1 and BRCA2 are in coldspots (3115/5301 = 58.8%). Reclassifying these 3115 VUS as likely benign would substantially improve variant classification.ConclusionIn BRCA1 and BRCA2 coldspots, missense variants are very unlikely to be pathogenic. Classification schemes that incorporate coldspots can reduce the number of VUS and mitigate risks from reporting benign variation as VUS.     

Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework

PurposeWe evaluated the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) variant pathogenicity guidelines for internal consistency and compatibility with Bayesian statistical reasoning.MethodsThe ACMG/AMP criteria were translated into a naive Bayesian classifier, assuming four levels of evidence and exponentially scaled odds of pathogenicity. We tested this framework with a range of prior probabilities and odds of pathogenicity.ResultsWe modeled the ACMG/AMP guidelines using biologically plausible assumptions. Most ACMG/AMP combining criteria were compatible. One ACMG/AMP likely pathogenic combination was mathematically equivalent to pathogenic and one ACMG/AMP pathogenic combination was actually likely pathogenic. We modeled combinations that include evidence for and against pathogenicity, showing that our approach scored some combinations as pathogenic or likely pathogenic that ACMG/AMP would designate as variant of uncertain significance (VUS).ConclusionBy transforming the ACMG/AMP guidelines into a Bayesian framework, we provide a mathematical foundation for what was a qualitative heuristic. Only 2 of the 18 existing ACMG/AMP evidence combinations were mathematically inconsistent with the overall framework. Mixed combinations of pathogenic and benign evidence could yield a likely pathogenic, likely benign, or VUS result. This quantitative framework validates the approach adopted by the ACMG/AMP, provides opportunities to further refine evidence categories and combining rules, and supports efforts to automate components of variant pathogenicity assessments.     

Genetic heterogeneity of heritable ectopic mineralization disorders in a large international cohort

PurposeHeritable ectopic mineralization disorders comprise a group of conditions with a broad range of clinical manifestations in nonskeletal connective tissues. We report the genetic findings from a large international cohort of 478 patients afflicted with ectopic mineralization.MethodsSequence variations were identified using a next-generation sequencing panel consisting of 29 genes reported in association with ectopic mineralization. The pathogenicity of select splicing and missense variants was analyzed in experimental systems in vitro and in vivo.ResultsA total of 872 variants of unknown significance as well as likely pathogenic and pathogenic variants were disclosed in 25 genes. A total of 159 distinct variants were identified in 425 patients in ABCC6, the gene responsible for pseudoxanthoma elasticum, a heritable multisystem ectopic mineralization disorder. The interpretation of variant pathogenicity relying on bioinformatic predictions did not provide a consensus. Our in vitro and in vivo functional assessment of 14 ABCC6 variants highlighted this dilemma and provided unambiguous interpretations to their pathogenicity.ConclusionThe results expand the ABCC6 variant repertoire, shed new light on the genetic heterogeneity of heritable ectopic mineralization disorders, and provide evidence that functional characterization in appropriate experimental systems is necessary to determine the pathogenicity of genetic variants.     

Assessment of the ExAC data set for the presence of individuals with pathogenic genotypes implicated in severe Mendelian pediatric disorders

PurposeWe analyzed the Exome Aggregation Consortium (ExAC) data set for the presence of individuals with pathogenic genotypes implicated in Mendelian pediatric disorders.MethodsClinVar likely/pathogenic variants supported by at least one peer-reviewed publication were assessed within the ExAC database to identify individuals expected to exhibit a childhood disorder based on concordance with disease inheritance modes: heterozygous (for dominant), homozygous (for recessive) or hemizygous (for X-linked recessive conditions). Variants from 924 genes reported to cause Mendelian childhood disorders were considered.ResultsWe identified ExAC individuals with candidate pathogenic genotypes for 190 previously published likely/pathogenic variants in 128 genes. After curation, we determined that 113 of the variants have sufficient support for pathogenicity and identified 1,717 ExAC individuals (~2.8% of the ExAC population) with corresponding possible/disease-associated genotypes implicated in rare Mendelian disorders, ranging from mild (e.g., due to SCN2A deficiency) to severe pediatric conditions (e.g., due to FGFR1 deficiency).ConclusionLarge-scale sequencing projects and data aggregation consortia provide unprecedented opportunities to determine the prevalence of pathogenic genotypes in unselected populations. This knowledge is crucial for understanding the penetrance of disease-associated variants, phenotypic variability, somatic mosaicism, as well as published literature curation for variant classification procedures and predicted clinical outcomes.     

A functional assay–based procedure to classify mismatch repair gene variants in Lynch syndrome

PurposeTo enhance classification of variants of uncertain significance (VUS) in the DNA mismatch repair (MMR) genes in the cancer predisposition Lynch syndrome, we developed the cell-free in vitro MMR activity (CIMRA) assay. Here, we calibrate and validate the assay, enabling its integration with in silico and clinical data.MethodsTwo sets of previously classified MLH1 and MSH2 variants were selected from a curated MMR gene database, and their biochemical activity determined by the CIMRA assay. The assay was calibrated by regression analysis followed by symmetric cross-validation and Bayesian integration with in silico predictions of pathogenicity. CIMRA assay reproducibility was assessed in four laboratories.ResultsConcordance between the training runs met our prespecified validation criterion. The CIMRA assay alone correctly classified 65% of variants, with only 3% discordant classification. Bayesian integration with in silico predictions of pathogenicity increased the proportion of correctly classified variants to 87%, without changing the discordance rate. Interlaboratory results were highly reproducible.ConclusionThe CIMRA assay accurately predicts pathogenic and benign MMR gene variants. Quantitative combination of assay results with in silico analysis correctly classified the majority of variants. Using this calibration, CIMRA assay results can be integrated into the diagnostic algorithm for MMR gene variants.     

Integration of functional assay data results provides strong evidence for classification of hundreds of BRCA1 variants of uncertain significance

PurposeBRCA1 pathogenic variant heterozygotes are at a substantially increased risk for breast and ovarian cancer. The widespread uptake of testing has led to a significant increase in the detection of missense variants in BRCA1, the vast majority of which are variants of uncertain clinical significance (VUS), posing a challenge to genetic counseling. Here, we harness a wealth of functional data for thousands of variants to aid in variant classification.MethodsWe have collected, curated, and harmonized functional data for 2701 missense variants representing 24.5% of possible missense variants in BRCA1. Results were harmonized across studies by converting data into binary categorical variables (functional impact versus no functional impact). Using a panel of reference variants we identified a subset of assays with high sensitivity and specificity (≥80%) and apply the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) variant interpretation guidelines to assign evidence criteria for classification.ResultsIntegration of data from validated assays provided ACMG/AMP evidence criteria in favor of pathogenicity for 297 variants or against pathogenicity for 2058 representing 96.2% of current VUS functionally assessed. We also explore discordant results and identify limitations in the approach.ConclusionHigh quality functional data are available for BRCA1 missense variants and provide evidence for classification of 2355 VUS according to their pathogenicity.     

Rare variants found in clinical gene panels illuminate the genetic and allelic architecture of orofacial clefting

PurposeOrofacial clefts (OFCs) are common birth defects including cleft lip, cleft lip and palate, and cleft palate. OFCs have heterogeneous etiologies, complicating clinical diagnostics because it is not always apparent if the cause is Mendelian, environmental, or multifactorial. Sequencing is not currently performed for isolated or sporadic OFCs; therefore, we estimated the diagnostic yield for 418 genes in 841 cases and 294 controls.MethodsWe evaluated 418 genes using genome sequencing and curated variants to assess their pathogenicity using American College of Medical Genetics criteria.Results9.04% of cases and 1.02% of controls had “likely pathogenic” variants (P < .0001), which was almost exclusively driven by heterozygous variants in autosomal genes. Cleft palate (17.6%) and cleft lip and palate (9.09%) cases had the highest yield, whereas cleft lip cases had a 2.80% yield. Out of 39 genes with likely pathogenic variants, 9 genes, including CTNND1 and IRF6, accounted for more than half of the yield (4.64% of cases). Most variants (61.8%) were “variants of uncertain significance”, occurring more frequently in cases (P = .004), but no individual gene showed a significant excess of variants of uncertain significance.ConclusionThese results underscore the etiological heterogeneity of OFCs and suggest sequencing could reduce the diagnostic gap in OFCs.     

Targeted mutation screening panels expose systematic population bias in detection of cystic fibrosis risk

PurposeCarrier screening for mutations contributing to cystic fibrosis (CF) is typically accomplished with panels composed of variants that are clinically validated primarily in patients of European descent. This approach has created a static genetic and phenotypic profile for CF. An opportunity now exists to reevaluate the disease profile of CFTR at a global population level.MethodsCFTR allele and genotype frequencies were obtained from a nonpatient cohort with more than 60,000 unrelated personal genomes collected by the Exome Aggregation Consortium. Likely disease-contributing mutations were identified with the use of public database annotations and computational tools.ResultsWe identified 131 previously described and likely pathogenic variants and another 210 untested variants with a high probability of causing protein damage. None of the current genetic screening panels or existing CFTR mutation databases covered a majority of deleterious variants in any geographical population outside of Europe.ConclusionsBoth clinical annotation and mutation coverage by commercially available targeted screening panels for CF are strongly biased toward detection of reproductive risk in persons of European descent. South and East Asian populations are severely underrepresented, in part because of a definition of disease that preferences the phenotype associated with European-typical CFTR alleles.     

Variant curation expert panel recommendations for RYR1 pathogenicity classifications in malignant hyperthermia susceptibility

PurposeAs a ClinGen Expert Panel (EP) we set out to adapt the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) pathogenicity criteria for classification of RYR1 variants as related to autosomal dominantly inherited malignant hyperthermia (MH).MethodsWe specified ACMG/AMP criteria for variant classification for RYR1 and MH. Proposed rules were piloted on 84 variants. We applied quantitative evidence calibration for several criteria using likelihood ratios based on the Bayesian framework.ResultsSeven ACMG/AMP criteria were adopted without changes, nine were adopted with RYR1-specific modifications, and ten were dropped. The in silico (PP3 and BP4) and hotspot criteria (PM1) were evaluated quantitatively. REVEL gave an odds ratio (OR) of 23:1 for PP3 and 14:1 for BP4 using trichotomized cutoffs of ≥0.85 (pathogenic) and ≤0.5 (benign). The PM1 hotspot criterion had an OR of 24:1. PP3 and PM1 were implemented at moderate strength. Applying the revised ACMG/AMP criteria to 44 recognized MH variants, 29 were classified as pathogenic, 13 as likely pathogenic, and 2 as variants of uncertain significance.ConclusionCuration of these variants will facilitate classification of RYR1/MH genomic testing results, which is especially important for secondary findings analyses. Our approach to quantitatively calibrating criteria is generalizable to other variant curation expert panels.     

Clinical implications of conflicting variant interpretations in the cancer genetics clinic

PurposeThe aim of this study was to describe the clinical impact of commercial laboratories issuing conflicting classifications of genetic variants.MethodsResults from 2000 patients undergoing a multigene hereditary cancer panel by a single laboratory were analyzed. Clinically significant discrepancies between the laboratory-provided test reports and other major commercial laboratories were identified, including differences between pathogenic/likely pathogenic and variant of uncertain significance (VUS) classifications, via review of ClinVar archives. For patients carrying a VUS, clinical documentation was assessed for evidence of provider awareness of the conflict.ResultsFifty of 975 (5.1%) patients with non-negative results carried a variant with a clinically significant conflict, 19 with a pathogenic/likely pathogenic variant reported in APC or MUTYH, and 31 with a VUS reported in CDKN2A, CHEK2, MLH1, MSH2, MUTYH, RAD51C, or TP53. Only 10 of 28 (36%) patients with a VUS with a clinically significant conflict had a documented discussion by a provider about the conflict. Discrepant counseling strategies were used for different patients with the same variant. Among patients with a CDKN2A variant or a monoallelic MUTYH variant, providers were significantly more likely to make recommendations based on the laboratory-reported classification.ConclusionOur findings highlight the frequency of variant interpretation discrepancies and importance of clinician awareness. Guidance is needed on managing patients with discrepant variants to support accurate risk assessment.     

Cancer Risk C (CR-C), a functional genomics test is a sensitive and rapid test for germline mismatch repair deficiency

PurposeHeritable pathogenic variants in the DNA mismatch repair (MMR) pathway cause Lynch syndrome, a condition that significantly increases risk of colorectal and other cancers. At least half of individuals tested using gene panel sequencing have a variant of uncertain significance or no variant identified leading to no diagnosis. To fill this diagnostic gap, we developed Cancer Risk C (CR-C), a flow variant assay test.MethodsIn response to treatment with an alkylating agent, individual assays of the nuclear translocation of MLH1, MSH2, BARD1, PMS2, and BRCA2 proteins and the nuclear phosphorylation of the ATM and ATR proteins distinguished pathogenic/likely pathogenic (P/LP) from benign/likely benign variants in MMR genes.ResultsA risk classification score based on MLH1, MSH2, and ATR assays was 100% sensitive and 98% specific. Causality of MMR P/LP variants was shown through gene editing and rescue. In individuals with suspected Lynch syndrome but no P/LP, CR-C identified most (73%) as having germline MMR defects. Direct comparison of CR-C on matched blood samples and lymphoblastoid cell lines yielded comparable results (r² > 0.9).ConclusionFor identifying germline MMR defects, CR-C provides augmentation to traditional panel sequencing through greater accuracy, shorter turnaround time (48 hours), and performance on blood with minimal sample handling.     

Homozygosity mapping provides supporting evidence of pathogenicity in recessive Mendelian disease

PurposeOne of the greatest challenges currently facing those studying Mendelian disease is identifying the pathogenic variant from the long list produced by a next-generation sequencing test. We investigate the predictive ability of homozygosity mapping for identifying the regions likely to contain the causative variant.MethodsWe use 179 homozygous pathogenic variants from three independent cohorts to investigate the predictive power of homozygosity mapping.ResultsWe demonstrate that homozygous pathogenic variants in our cohorts are disproportionately likely to be found within one of the largest regions of homozygosity: 80% of pathogenic variants are found in a homozygous region that is in the ten largest regions in a sample. The maximal predictive power is achieved in patients with <8% homozygosity and variants >3 Mb from a telomere; this gives an area under the curve (AUC) of 0.735 and results in 92% of the causative variants being in one of the ten largest homozygous regions.ConclusionThis predictive power can be used to prioritize the list of candidate variants in gene discovery studies. When classifying a homozygous variant the size and rank of the region of homozygosity in which the candidate variant is located can also be considered as supporting evidence for pathogenicity.     

DNA variant classification–reconsidering “allele rarity” and “phenotype” criteria in ACMG/AMP guidelines

Recent guidance suggested modified DNA variant pathogenicity assignments based on genome-wide allele rarity. Different a priori probabilities of pathogenicity operate where patients already have clinical diagnoses, and are found to have a very rare variant in a gene known to cause their disease, compared to predictive testing of a clinically unaffected individual. We tested new recommendations from the ClinGen Sequence Variant Interpretation Working Group for ClinVar-listed, loss-of-function variants meeting the very strong evidence of pathogenicity criterion [PVS1] in genes for 3 specific diseases where causal gene identification can modify clinical care of an individual- Von Willebrand disease, cystic fibrosis and hereditary haemorrhagic telangiectasia. Across these diseases, current rules leave 20/1,278 (1.6%) of loss-of-function variants as variants of uncertain significance (VUS that may not be reported to clinicians), and 207/1,278 (17.2%) as likely pathogenic. Applying the new ClinGen rule enabling PVS1 and the allele rarity criterion PM2 to delineate likely pathogenicity still left 8/1,278 (0.9%) as VUS (reflecting non-PVS1 calls by the submitters), and the majority of null alleles meeting PVS1 as merely likely pathogenic. We favour an approach whereby, for PVS1 variants in patients who personally meet the phenotypic PP4 criterion for a disease where casual variants are commonly family-specific, that PM2 is upgraded to permit a pathogenic call. Of 1,278 ClinVar-listed frameshift, nonsense and canonical splice site variants that met PVS1 in the 3 conditions, 16.0% (204/1,278) would be newly designated as pathogenic, avoiding misinterpretation outside of clinical genetics communities. We suggest further discussion around variant assessment across different clinical applications, potentially guided by PP4 alerts to distinguish personal versus family phenotypic history.