Re-evaluation of a Fibrillin-1 Gene Variant of Uncertain Significance Using the ClinGen Guidelines

Background

Marfan syndrome (MFS) is caused by fibrillin-1 gene (FBN1) variants. Mutational hotspots and/or well-established critical functional domains of FBN1 include cysteine residues, calcium-binding consensus sequences, and amino acids related to interdomain packaging. Previous guidelines for variant interpretation do not reflect the features of genes or related diseases. Using the Clinical Genome Resource (ClinGen) FBN1 variant curation expert panel (VCEP), we re-evaluated FBN1 germline variants reported as variants of uncertain significance (VUSs).

Methods

We re-evaluated 26 VUSs in FBN1 reported in 161 patients with MFS. We checked the variants in the Human Genome Mutation Database, ClinVar, and VarSome databases and assessed their allele frequencies using the gnomAD database. Patients' clinical information was reviewed.

Results

Four missense variants affecting cysteines (c.460T>C, c.1006T>C, c.5330G>C, and c.8020T>C) were reclassified as likely pathogenic and were assigned PM1_strong or PM1. Two intronic variants were reclassified as benign by granting BA1 (stand-alone). Four missense variants were reclassified as likely benign. BP5 criteria were applied in cases with an alternate molecular basis for disease, one of which (c.7231G>A) was discovered alongside a pathogenic de novo COL3A1 variant (c.1988G>T, p.Gly633Val).

Conclusions

Considering the high penetrance of FBN1 variants and clinical variability of MFS, the detection of pathogenic variants is important. The ClinGen FBN1 VCEP encompasses mutational hotspots and/or well-established critical functional domains and adjusts the criteria specifically for MFS; therefore, it is beneficial not only for identifying pathogenic FBN1 variants but also for distinguishing these variants from those that cause other connective tissue disorders with overlapping clinical features.

Functional Analysis of G6PD Variants Associated With Low G6PD Activity in the All of Us Research Program

Glucose-6-phosphate dehydrogenase (G6PD) protects red blood cells against oxidative damage through regeneration of NADPH. Individuals with G6PD polymorphisms (variants) that produce an impaired G6PD enzyme are usually asymptomatic, but at risk of hemolytic anemia from oxidative stressors, including certain drugs and foods. Prevention of G6PD deficiency-related hemolytic anemia is achievable through G6PD genetic testing or whole-genome sequencing (WGS) to identify affected individuals who should avoid hemolytic triggers. However, accurately predicting the clinical consequence of G6PD variants is limited by over 800 G6PD variants which remain of uncertain significance. There also remains significant variability in which deficiency-causing variants are included in pharmacogenomic testing arrays across institutions: many panels only include c.202G>A, even though dozens of other variants can also cause G6PD deficiency. Here, we seek to improve G6PD genotype interpretation using data available in the All of Us Research Program and using a yeast functional assay. We confirm that G6PD coding variants are the main contributor to decreased G6PD activity, and that 13% of individuals in the All of Us data with deficiency-causing variants would be missed if only the c.202G>A variant were tested for. We expand clinical interpretation for G6PD variants of uncertain significance; reporting that c.595A>G, known as G6PD Dagua or G6PD Açores, and the newly identified variant c.430C>G, reduce activity sufficiently to lead to G6PD deficiency. We also provide evidence that five missense variants of uncertain significance are unlikely to lead to G6PD deficiency, since they were seen in hemi- or homozygous individuals without a reduction in G6PD activity. We also applied the new WHO guidelines and were able to classify two synonymous variants as WHO class C. We anticipate these results will improve the accuracy, and prompt increased use, of G6PD genetic tests through a more complete clinical interpretation of G6PD variants. As the All of Us data increases from 245,000 to 1 million participants, and additional functional assays are carried out, we expect this research to serve as a template to enable complete characterization of G6PD deficiency genotypes. With an increased number of interpreted variants, genetic testing of G6PD will be more informative for preemptively identifying individuals at risk for drug- or food-induced hemolytic anemia.

Expansion of the Genotypic and Phenotypic Spectrum of ASH1L-Related Syndromic Neurodevelopmental Disorder

Pathogenic ASH1L variants have been reported in probands with broad phenotypic presentations, including intellectual disability, autism spectrum disorder, attention deficit hyperactivity disorder, seizures, congenital anomalies, and other skeletal, muscular, and sleep differences. Here, we review previously published individuals with pathogenic ASH1L variants and report three further probands with novel ASH1L variants and previously unreported phenotypic features, including mixed receptive language disorder and gait disturbances. These novel data from the Brain Gene Registry, an accessible repository of clinically derived genotypic and phenotypic data, have allowed for the expansion of the phenotypic and genotypic spectrum of this condition.

Gene-specific ACMG/AMP classification criteria for germline APC variants: Recommendations from the ClinGen InSiGHT Hereditary Colorectal Cancer/Polyposis Variant Curation Expert Panel

PURPOSE

The Hereditary Colorectal Cancer/Polyposis Variant Curation Expert Panel (VCEP) was established by the International Society for Gastrointestinal Hereditary Tumours and the Clinical Genome Resource, who set out to develop recommendations for the interpretation of germline APC variants underlying Familial Adenomatous Polyposis, the most frequent hereditary polyposis syndrome.

METHODS

Through a rigorous process of database analysis, literature review, and expert elicitation, the APC VCEP derived gene-specific modifications to the ACMG/AMP (American College of Medical Genetics and Genomics and Association for Molecular Pathology) variant classification guidelines and validated such criteria through the pilot classification of 58 variants.

RESULTS

The APC-specific criteria represented gene- and disease-informed specifications, including a quantitative approach to allele frequency thresholds, a stepwise decision tool for truncating variants, and semiquantitative evaluations of experimental and clinical data. Using the APC-specific criteria, 47% (27/58) of pilot variants were reclassified including 14 previous variants of uncertain significance (VUS).

CONCLUSION

The APC-specific ACMG/AMP criteria preserved the classification of well-characterized variants on ClinVar while substantially reducing the number of VUS by 56% (14/25). Moving forward, the APC VCEP will continue to interpret prioritized lists of VUS, the results of which will represent the most authoritative variant classification for widespread clinical use.

Specifications of the ACMG/AMP guidelines for ACADVL variant interpretation

Very long-chain acyl-CoA dehydrogenase (VLCAD) deficiency (VLCADD) is a relatively common inborn error of metabolism, but due to difficulty in accurately predicting affected status through newborn screening, molecular confirmation of the causative variants by sequencing of the ACADVL gene is necessary. Although the ACMG/AMP guidelines have helped standardize variant classification, ACADVL variant classification remains disparate due to a phenotype that can be nonspecific, the possibility of variants that produce late-onset disease, and relatively high carrier frequency, amongst other challenges. Therefore, an ACADVL-specific variant curation expert panel (VCEP) was created to facilitate the specification of the ACMG/AMP guidelines for VLCADD. We expect these guidelines to help streamline, increase concordance, and expedite the classification of ACADVL variants.

Using the ACMG/AMP framework to capture evidence related to predicted and observed impact on splicing: Recommendations from the ClinGen SVI Splicing Subgroup

The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1, PS3, PP3, BS3, BP4, and BP7. However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. We utilized empirically derived splicing evidence to (1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, (2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and (3) exemplify methodology to calibrate splice prediction tools. We propose repurposing the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely, BP7 may be used to capture RNA results demonstrating no splicing impact for intronic and synonymous variants. We propose that the PS3/BS3 codes are applied only for well-established assays that measure functional impact not directly captured by RNA-splicing assays. We recommend the application of PS1 based on similarity of predicted RNA-splicing effects for a variant under assessment in comparison with a known pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA-assay evidence described aim to help standardize variant pathogenicity classification processes when interpreting splicing-based evidence.

Evidence-Based Assessment of Congenital Heart Disease Genes to Enable Returning Results in a Genomic Study

BACKGROUND

Congenital heart disease (CHD) is the most common major congenital anomaly and causes significant morbidity and mortality. Epidemiologic evidence supports a role of genetics in the development of CHD. Genetic diagnoses can inform prognosis and clinical management. However, genetic testing is not standardized among individuals with CHD. We sought to develop a list of validated CHD genes using established methods and to evaluate the process of returning genetic results to research participants in a large genomic study.

METHODS

Two-hundred ninety-five candidate CHD genes were evaluated using a ClinGen framework. Sequence and copy number variants involving genes in the CHD gene list were analyzed in Pediatric Cardiac Genomics Consortium participants. Pathogenic/likely pathogenic results were confirmed on a new sample in a clinical laboratory improvement amendments-certified laboratory and disclosed to eligible participants. Adult probands and parents of probands who received results were asked to complete a post-disclosure survey.

RESULTS

A total of 99 genes had a strong or definitive clinical validity classification. Diagnostic yields for copy number variants and exome sequencing were 1.8% and 3.8%, respectively. Thirty-one probands completed clinical laboratory improvement amendments-confirmation and received results. Participants who completed postdisclosure surveys reported high personal utility and no decision regret after receiving genetic results.

CONCLUSIONS

The application of ClinGen criteria to CHD candidate genes yielded a list that can be used to interpret clinical genetic testing for CHD. Applying this gene list to one of the largest research cohorts of CHD participants provides a lower bound for the yield of genetic testing in CHD.

Specifications of the ACMG/AMP Variant Classification Guidelines for Germline DICER1 Variant Curation

Germline pathogenic variants in DICER1 predispose individuals to develop a variety of benign and malignant tumors. Accurate variant curation and classification is essential for reliable diagnosis of DICER1-related tumor predisposition and identification of individuals who may benefit from surveillance. Since 2015, most labs have followed the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) sequence variant classification guidelines for DICER1 germline variant curation. However, these general guidelines lack gene-specific nuances and leave room for subjectivity. Consequently, a group of DICER1 experts joined ClinGen to form the DICER1 and miRNA-Processing Genes Variant Curation Expert Panel (VCEP), to create DICER1- specific ACMG/AMP guidelines for germline variant curation. The VCEP followed the FDA-approved ClinGen protocol for adapting and piloting these guidelines. A diverse set of 40 DICER1 variants were selected for piloting, including 14 known Pathogenic/Likely Pathogenic (P/LP) variants, 12 known Benign/Likely Benign (B/LB) variants, and 14 variants classified as variants of uncertain significance (VUS) or with conflicting interpretations in ClinVar. Clinically meaningful classifications (i.e., P, LP, LB, or B) were achieved for 82.5% (33/40) of the pilot variants, with 100% concordance among the known P/LP and known B/LB variants. Half of the VUS or conflicting variants were resolved with four variants classified as LB and three as LP. These results demonstrate that the DICER1-specific guidelines for germline variant curation effectively classify known pathogenic and benign variants while reducing the frequency of uncertain classifications. Individuals and labs curating DICER1 variants should consider adopting this classification framework to encourage consistency and improve objectivity.

Reactive gene curation to support interpretation and reporting of a clinical genome test for rare disease: Experience from over 1,000 cases

Current standards in clinical genetics recognize the need to establish the validity of gene-disease relationships as a first step in the interpretation of sequence variants. We describe our experience incorporating the ClinGen Gene-Disease Clinical Validity framework in our interpretation and reporting workflow for a clinical genome sequencing (cGS) test for individuals with rare and undiagnosed genetic diseases. This "reactive" gene curation is completed upon identification of candidate variants during active case analysis and within the test turn-around time by focusing on the most impactful evidence and taking advantage of the broad applicability of the framework to cover a wide range of disease areas. We demonstrate that reactive gene curation can be successfully implemented in support of cGS in a clinical laboratory environment, enabling robust clinical decision making and allowing all variants to be fully and appropriately considered and their clinical significance confidently interpreted.

Clinical validity assessment of genes frequently tested on intellectual disability/autism sequencing panels

PURPOSE

Neurodevelopmental disorders (NDDs), such as intellectual disability (ID) and autism spectrum disorder (ASD), exhibit genetic and phenotypic heterogeneity, making them difficult to differentiate without a molecular diagnosis. The Clinical Genome Resource Intellectual Disability/Autism Gene Curation Expert Panel (GCEP) uses systematic curation to distinguish ID/ASD genes that are appropriate for clinical testing (ie, with substantial evidence supporting their relationship to disease) from those that are not.

METHODS

Using the Clinical Genome Resource gene-disease validity curation framework, the ID/Autism GCEP classified genes frequently included on clinical ID/ASD testing panels as Definitive, Strong, Moderate, Limited, Disputed, Refuted, or No Known Disease Relationship.

RESULTS

As of September 2021, 156 gene-disease pairs have been evaluated. Although most (75%) were determined to have definitive roles in NDDs, 22 (14%) genes evaluated had either Limited or Disputed evidence. Such genes are currently not recommended for use in clinical testing owing to the limited ability to assess the effect of identified variants.

CONCLUSION

Our understanding of gene-disease relationships evolves over time; new relationships are discovered and previously-held conclusions may be questioned. Without periodic re-examination, inaccurate gene-disease claims may be perpetuated. The ID/Autism GCEP will continue to evaluate these claims to improve diagnosis and clinical care for NDDs.

Genetic Architecture of Azoospermia-Time to Advance the Standard of Care

BACKGROUND

Crypto- and azoospermia (very few/no sperm in the semen) are main contributors to male factor infertility. Genetic causes for spermatogenic failure (SPGF) include Klinefelter syndrome and Y-chromosomal azoospermia factor microdeletions, and CFTR mutations for obstructive azoospermia (OA). However, the majority of cases remain unexplained because monogenic causes are not analysed.

OBJECTIVE

To elucidate the monogenic contribution to azoospermia by prospective exome sequencing and strict application of recent clinical guidelines.

DESIGN, SETTING, AND PARTICIPANTS

Since January 2017, we studied crypto- and azoospermic men without chromosomal aberrations and Y-chromosomal microdeletions attending the Centre of Reproductive Medicine and Andrology, Münster.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

We performed exome sequencing in 647 men, analysed 60 genes having at least previous limited clinical validity, and strictly assessed variants according to clinical guidelines.

RESULTS AND LIMITATIONS

Overall, 55 patients (8.5%) with diagnostic genetic variants were identified. Of these patients, 20 (3.1%) carried mutations in CFTR or ADGRG2, and were diagnosed with OA. In 35 patients (5.4%) with SPGF, mutations in 20 different genes were identified. According to ClinGen criteria, 19 of the SPGF genes now reach at least moderate clinical validity. As limitations, only one transcript per gene was considered, and the list of genes is increasing rapidly so cannot be exhaustive.

CONCLUSIONS

The number of diagnostic genes in crypto-/azoospermia was almost doubled to 21 using exome-based analyses and clinical guidelines. Application of this procedure in routine diagnostics will significantly improve the diagnostic yield and clinical workup as the results indicate the success rate of testicular sperm extraction.

PATIENT SUMMARY

When no sperm are found in the semen, a man cannot conceive naturally. The causes are often unknown, but genetics play a major role. We searched for genetic variants in a large group of patients and found causal mutations for one in 12 men; these predict the chances for fatherhood.

Evaluating the impact of in silico predictors on clinical variant classification

PURPOSE

According 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.

METHODS

A 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).

RESULTS

The 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.

CONCLUSION

We 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.

The Clinical Genome Resource (ClinGen) Familial Hypercholesterolemia Variant Curation Expert Panel consensus guidelines for LDLR variant classification

PURPOSE

In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published consensus standardized guidelines for sequence-level variant classification in Mendelian disorders. To increase accuracy and consistency, the Clinical Genome Resource Familial Hypercholesterolemia (FH) Variant Curation Expert Panel was tasked with optimizing the existing ACMG/AMP framework for disease-specific classification in FH. In this study, we provide consensus recommendations for the most common FH-associated gene, LDLR, where >2300 unique FH-associated variants have been identified.

METHODS

The multidisciplinary FH Variant Curation Expert Panel met in person and through frequent emails and conference calls to develop LDLR-specific modifications of ACMG/AMP guidelines. Through iteration, pilot testing, debate, and commentary, consensus among experts was reached.

RESULTS

The consensus LDLR variant modifications to existing ACMG/AMP guidelines include (1) alteration of population frequency thresholds, (2) delineation of loss-of-function variant types, (3) functional study criteria specifications, (4) cosegregation criteria specifications, and (5) specific use and thresholds for in silico prediction tools, among others.

CONCLUSION

Establishment of these guidelines as the new standard in the clinical laboratory setting will result in a more evidence-based, harmonized method for LDLR variant classification worldwide, thereby improving the care of patients with FH.

Clinical Genetics Lacks Standard Definitions and Protocols for the Collection and Use of Diversity Measures

Genetics researchers and clinical professionals rely on diversity measures such as race, ethnicity, and ancestry (REA) to stratify study participants and patients for a variety of applications in research and precision medicine. However, there are no comprehensive, widely accepted standards or guidelines for collecting and using such data in clinical genetics practice. Two NIH-funded research consortia, the Clinical Genome Resource (ClinGen) and Clinical Sequencing Evidence-generating Research (CSER), have partnered to address this issue and report how REA are currently collected, conceptualized, and used. Surveying clinical genetics professionals and researchers (n = 448), we found heterogeneity in the way REA are perceived, defined, and measured, with variation in the perceived importance of REA in both clinical and research settings. The majority of respondents (>55%) felt that REA are at least somewhat important for clinical variant interpretation, ordering genetic tests, and communicating results to patients. However, there was no consensus on the relevance of REA, including how each of these measures should be used in different scenarios and what information they can convey in the context of human genetics. A lack of common definitions and applications of REA across the precision medicine pipeline may contribute to inconsistencies in data collection, missing or inaccurate classifications, and misleading or inconclusive results. Thus, our findings support the need for standardization and harmonization of REA data collection and use in clinical genetics and precision health research.

AutoPVS1: An automatic classification tool for PVS1 interpretation of null variants

Null variants are prevalent within the human genome, and their accurate interpretation is critical for clinical management. In 2018, the ClinGen Sequence Variant Interpretation (SVI) Working Group refined the only criterion with a very strong pathogenicity rating (PVS1). To streamline PVS1 interpretation, we have developed an automatic classification tool with a graphical user interface called AutoPVS1. The performance of AutoPVS1 was assessed using 56 variants manually curated by the ClinGen's SVI Working Group; it achieved an interpretation concordance of 93% (52/56). A further analysis of 28,586 putative loss-of-function variants by AutoPVS1 demonstrated that at least 27.7% of them do not reach a very strong strength level, 17.5% because of variant-specific issues and 10.2% due to disease mechanism considerations. Notably, 41.0% (1,936/4,717) of splicing variants were assigned a decreased preliminary PVS1 strength level, a significantly greater fraction than in frameshift variants (13.2%) and nonsense variants (10.8%). Our results reinforce the necessity of considering variant-specific issues and disease mechanisms in variant interpretation and demonstrate that AutoPVS1 meets an urgent need by enabling biocurators to easily assign accurate, reliable and reproducible PVS1 strength levels in the process of variant interpretation. AutoPVS1 is publicly available at http://autopvs1.genetics.bgi.com/.

Clinical Interpretation of Sequence Variants

Clinical interpretation of DNA sequence variants is a critical step in reporting clinical genetic testing results. Application of next-generation sequencing technology in molecular genetic testing has facilitated diagnoses of genetic disorders in clinical practice. However, the large number of DNA sequence variants detected in clinical specimens, many of which have never been seen before, make clinical interpretation challenging. Recommendations by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) have been widely adopted by clinical laboratories around the world to guide clinical interpretation of sequence variants. The ClinGen Sequence Variant Interpretation Working Group and various disease-specific variant curation expert panels have also developed specifications for the ACMG/AMP recommendations. Despite these efforts to standardize variant interpretation in clinical practice, different laboratories may subjectively use professional judgment to determine which criteria are applicable when classifying a variant. In addition, clinicians and researchers who are not familiar with the variant interpretation process may have difficulty understanding clinical genetic reports and communicating the clinical significance of genetic testing results. Here we provide a step-by-step protocol for clinical interpretation of sequence variants, including practical examples. By following this protocol, clinical laboratory geneticists can interpret the clinical significance of sequence variants according to the ACMG/AMP recommendations and ClinGen framework. Furthermore, this article will help clinicians and researchers to understand variant classification in clinical genetic testing reports and evaluate the quality of the reports. © 2020 by John Wiley & Sons, Inc. Basic Protocol: Interpreting the clinical significance of sequence variants Support Protocol: Reevaluating the clinical significance of sequence variants.

An International, Multicentered, Evidence-Based Reappraisal of Genes Reported to Cause Congenital Long QT Syndrome

Supplemental Digital Content is available in the text.

Background:

Long QT syndrome (LQTS) is the first described and most common inherited arrhythmia. Over the last 25 years, multiple genes have been reported to cause this condition and are routinely tested in patients. Because of dramatic changes in our understanding of human genetic variation, reappraisal of reported genetic causes for LQTS is required.

Methods:

Utilizing an evidence-based framework, 3 gene curation teams blinded to each other’s work scored the level of evidence for 17 genes reported to cause LQTS. A Clinical Domain Channelopathy Working Group provided a final classification of these genes for causation of LQTS after assessment of the evidence scored by the independent curation teams.

Results:

Of 17 genes reported as being causative for LQTS, 9 (AKAP9, ANK2, CAV3, KCNE1, KCNE2, KCNJ2, KCNJ5, SCN4B, SNTA1) were classified as having limited or disputed evidence as LQTS-causative genes. Only 3 genes (KCNQ1, KCNH2, SCN5A) were curated as definitive genes for typical LQTS. Another 4 genes (CALM1, CALM2, CALM3, TRDN) were found to have strong or definitive evidence for causality in LQTS with atypical features, including neonatal atrioventricular block. The remaining gene (CACNA1C) had moderate level evidence for causing LQTS.

Conclusions:

More than half of the genes reported as causing LQTS have limited or disputed evidence to support their disease causation. Genetic variants in these genes should not be used for clinical decision-making, unless accompanied by new and sufficient genetic evidence. The findings of insufficient evidence to support gene-disease associations may extend to other disciplines of medicine and warrants a contemporary evidence-based evaluation for previously reported disease-causing genes to ensure their appropriate use in precision medicine.

Genetic Testing: Consent and Result Disclosure for Primary Care Providers

Historically, both pretest and posttest genetic counseling has been standard of care for genetic testing. This model should be adapted for primary care providers (PCPs) willing to learn critical information about the test and key concepts that patients need to make an informed testing decision. It is helpful for PCPs to discuss a few initial patients with a genetic counselor to prepare for the key concepts of pretest and posttest counseling. This article provides guidance about the recommended level of involvement of PCPs based on the test indication, test complexity, disorder management, and the potential for psychosocial sequela.

Consensus interpretation of the p.Met34Thr and p.Val37Ile variants in GJB2 by the ClinGen Hearing Loss Expert Panel

PURPOSE

Pathogenic variants in GJB2 are the most common cause of autosomal recessive sensorineural hearing loss. The classification of c.101T>C/p.Met34Thr and c.109G>A/p.Val37Ile in GJB2 are controversial. Therefore, an expert consensus is required for the interpretation of these two variants.

METHODS

The ClinGen Hearing Loss Expert Panel collected published data and shared unpublished information from contributing laboratories and clinics regarding the two variants. Functional, computational, allelic, and segregation data were also obtained. Case-control statistical analyses were performed.

RESULTS

The panel reviewed the synthesized information, and classified the p.Met34Thr and p.Val37Ile variants utilizing professional variant interpretation guidelines and professional judgment. We found that p.Met34Thr and p.Val37Ile are significantly overrepresented in hearing loss patients, compared with population controls. Individuals homozygous or compound heterozygous for p.Met34Thr or p.Val37Ile typically manifest mild to moderate hearing loss. Several other types of evidence also support pathogenic roles for these two variants.

CONCLUSION

Resolving controversies in variant classification requires coordinated effort among a panel of international multi-institutional experts to share data, standardize classification guidelines, review evidence, and reach a consensus. We concluded that p.Met34Thr and p.Val37Ile variants in GJB2 are pathogenic for autosomal recessive nonsyndromic hearing loss with variable expressivity and incomplete penetrance.

Clinical Validity of Genes for Heritable Thoracic Aortic Aneurysm and Dissection

BACKGROUND

Thoracic aortic aneurysms progressively enlarge and predispose to acute aortic dissections. Up to 25% of individuals with thoracic aortic disease harbor an underlying Mendelian pathogenic variant. An evidence-based strategy for selection of genes to test in hereditary thoracic aortic aneurysm and dissection (HTAAD) helps inform family screening and intervention to prevent life-threatening thoracic aortic events.

OBJECTIVES

The purpose of this study was to accurately identify genes that predispose to HTAAD using the Clinical Genome Resource (ClinGen) framework.

METHODS

We applied the semiquantitative ClinGen framework to assess presumed gene-disease relationships between 53 candidate genes and HTAAD. Genes were classified as causative for HTAAD if they were associated with isolated thoracic aortic disease and were clinically actionable, triggering routine aortic surveillance, intervention, and family cascade screening. All gene-disease assertions were evaluated by a pre-defined curator-expert pair and subsequently discussed with an expert panel.

RESULTS

Genes were classified based on the strength of association with HTAAD into 5 categories: definitive (n = 9), strong (n = 2), moderate (n = 4), limited (n = 15), and no reported evidence (n = 23). They were further categorized by severity of associated aortic disease and risk of progression. Eleven genes in the definitive and strong groups were designated as "HTAAD genes" (category A). Eight genes were classified as unlikely to be progressive (category B) and 4 as low risk (category C). The remaining genes were recent genes with an uncertain classification or genes with no evidence of association with HTAAD.

CONCLUSIONS

The ClinGen framework is useful to semiquantitatively assess the strength of gene-disease relationships for HTAAD. Gene categories resulting from the curation may inform clinical laboratories in the development, interpretation, and subsequent clinical implications of genetic testing for patients with aortic disease.

Copy number variant discrepancy resolution using the ClinGen dosage sensitivity map results in updated clinical interpretations in ClinVar

Conflict resolution in genomic variant interpretation is a critical step toward improving patient care. Evaluating interpretation discrepancies in copy number variants (CNVs) typically involves assessing overlapping genomic content with focus on genes/regions that may be subject to dosage sensitivity (haploinsufficiency (HI) and/or triplosensitivity (TS)). CNVs containing dosage sensitive genes/regions are generally interpreted as "likely pathogenic" (LP) or "pathogenic" (P), and CNVs involving the same known dosage sensitive gene(s) should receive the same clinical interpretation. We compared the Clinical Genome Resource (ClinGen) Dosage Map, a publicly available resource documenting known HI and TS genes/regions, against germline, clinical CNV interpretations within the ClinVar database. We identified 251 CNVs overlapping known dosage sensitive genes/regions but not classified as LP or P; these were sent back to their original submitting laboratories for re-evaluation. Of 246 CNVs re-evaluated, an updated clinical classification was warranted in 157 cases (63.8%); no change was made to the current classification in 79 cases (32.1%); and 10 cases (4.1%) resulted in other types of updates to ClinVar records. This effort will add curated interpretation data into the public domain and allow laboratories to focus attention on more complex discrepancies.

Gene-specific criteria for PTEN variant curation: Recommendations from the ClinGen PTEN Expert Panel

The ClinGen PTEN Expert Panel was organized by the ClinGen Hereditary Cancer Clinical Domain Working Group to assemble clinicians, researchers, and molecular diagnosticians with PTEN expertise to develop specifications to the 2015 ACMG/AMP Sequence Variant Interpretation Guidelines for PTEN variant interpretation. We describe finalized PTEN-specific variant classification criteria and outcomes from pilot testing of 42 variants with benign/likely benign (BEN/LBEN), pathogenic/likely pathogenic (PATH/LPATH), uncertain significance (VUS), and conflicting (CONF) ClinVar assertions. Utilizing these rules, classifications concordant with ClinVar assertions were achieved for 14/15 (93.3%) BEN/LBEN and 16/16 (100%) PATH/LPATH ClinVar consensus variants for an overall concordance of 96.8% (30/31). The variant where agreement was not reached was a synonymous variant near a splice donor with noncanonical sequence for which in silico models cannot predict the native site. Applying these rules to six VUS and five CONF variants, adding shared internal laboratory data enabled one VUS to be classified as LBEN and two CONF variants to be as classified as PATH and LPATH. This study highlights the benefit of gene-specific criteria and the value of sharing internal laboratory data for variant interpretation. Our PTEN-specific criteria and expertly reviewed assertions should prove helpful for laboratories and others curating PTEN variants.

Assessing the gene-disease association of 19 genes with the RASopathies using the ClinGen gene curation framework

The RASopathies are a complex group of conditions regarding phenotype and genetic etiology. The ClinGen RASopathy Expert Panel (RAS EP) assessed published and other publicly available evidence supporting the association of 19 genes with RASopathy conditions. Using the semiquantitative literature curation method developed by the ClinGen Gene Curation Working Group, evidence for each gene was curated and scored for Noonan syndrome (NS), Costello syndrome, cardiofaciocutaneous syndrome, NS with multiple lentigines, and Noonan-like syndrome with loose anagen hair. The curated evidence supporting each gene-disease relationship was then discussed and approved by the ClinGen RASopathy Expert Panel. Each association's strength was classified as definitive, strong, moderate, limited, disputed, or no evidence. Eleven genes were classified as definitively associated with at least one RASopathy condition. Two genes classified as strong for association with at least one RASopathy condition while one gene was moderate and three were limited. The RAS EP also disputed the association of two genes for all RASopathy conditions. Overall, our results provide a greater understanding of the different gene-disease relationships within the RASopathies and can help in guiding and directing clinicians, patients, and researchers who are identifying variants in individuals with a suspected RASopathy.

Expert specification of the ACMG/AMP variant interpretation guidelines for genetic hearing loss

Due to the high genetic heterogeneity of hearing loss (HL), current clinical testing includes sequencing large numbers of genes, which often yields a significant number of novel variants. Therefore, the standardization of variant interpretation is crucial to provide consistent and accurate diagnoses. The Hearing Loss Variant Curation Expert Panel was created within the Clinical Genome Resource to provide expert guidance for standardized genomic interpretation in the context of HL. As one of its major tasks, our Expert Panel has adapted the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for the interpretation of sequence variants in HL genes. Here, we provide a comprehensive illustration of the newly specified ACMG/AMP HL rules. Three rules remained unchanged, four rules were removed, and the remaining 21 rules were specified. These rules were further validated and refined using a pilot set of 51 variants assessed by curators and disease experts. Of the 51 variants evaluated in the pilot, 37% (19/51) changed category based upon application of the expert panel specified rules and/or aggregation of evidence across laboratories. These HL-specific ACMG/AMP rules will help standardize variant interpretation, ultimately leading to better care for individuals with HL.

ClinGen's GenomeConnect registry enables patient-centered data sharing

GenomeConnect, the NIH-funded Clinical Genome Resource (ClinGen) patient registry, engages patients in data sharing to support the goal of creating a genomic knowledge base to inform clinical care and research. Participant self-reported health information and genomic variants from genetic testing reports are curated and shared with public databases, such as ClinVar. There are four primary benefits of GenomeConnect: (1) sharing novel genomic data-47.9% of variants were new to ClinVar, highlighting patients as a genomic data source; (2) contributing additional phenotypic information-of the 52.1% of variants already in ClinVar, GenomeConnect provided enhanced case-level data; (3) providing a way for patients to receive variant classification updates if the reporting laboratory submits to ClinVar-97.3% of responding participants opted to receive such information and 13 updates have been identified; and (4) supporting connections with others, including other participants, clinicians, and researchers to enable the exchange of information and support-60.4% of participants have opted to partake in participant matching. Moving forward, ClinGen plans to increase patient-centric data sharing by partnering with other existing patient groups. By engaging patients, more information is contributed to the public knowledge base, benefiting both patients and the genomics community.

Unique aspects of sequence variant interpretation for inborn errors of metabolism (IEM): The ClinGen IEM Working Group and the Phenylalanine Hydroxylase Gene

The ClinGen Inborn Errors of Metabolism Working Group was tasked with creating a comprehensive, standardized knowledge base of genes and variants for metabolic diseases. Phenylalanine hydroxylase (PAH) deficiency was chosen to pilot development of the Working Group's standards and guidelines. A PAH variant curation expert panel (VCEP) was created to facilitate this process. Following ACMG-AMP variant interpretation guidelines, we present the development of these standards in the context of PAH variant curation and interpretation. Existing ACMG-AMP rules were adjusted based on disease (6) or strength (5) or both (2). Disease adjustments include allele frequency thresholds, functional assay thresholds, and phenotype-specific guidelines. Our validation of PAH-specific variant interpretation guidelines is presented using 85 variants. The PAH VCEP interpretations were concordant with existing interpretations in ClinVar for 69 variants (81%). Development of biocurator tools and standards are also described. Using the PAH-specific ACMG-AMP guidelines, 714 PAH variants have been curated and will be submitted to ClinVar. We also discuss strategies and challenges in applying ACMG-AMP guidelines to autosomal recessive metabolic disease, and the curation of variants in these genes.

The progression of the ClinGen gene clinical validity classification over time

In order for ClinGen to maintain up-to-date gene-disease clinical validity classifications for use by clinicians and clinical laboratories, an appropriate timeline for reevaluating curated gene-disease associations will need to be determined. To provide guidance on how often a gene-disease association should be recurated, a retrospective analysis of 30 gene curations was performed. Curations were simulated at one-year intervals starting with the year of the first publication to assert disease-causing variants in the gene to observe trends in the classification over time, as well as factors that influenced changes in classification. On average, gene-disease associations spent the least amount of time in the "Moderate" classification before progressing to "Strong" or "Definitive." In contrast, gene-disease associations that spent five or more years in the "Limited" classification were most likely to remain "Limited" or become "Disputed/Refuted." Large population datasets contributed to the reclassification of several gene-disease associations from "Limited" to "Disputed/Refuted." Finally, recent advancements in sequencing technology correlated with an increase in the quantity of case-level evidence that was curated per paper. This study provided a number of key points to consider when determining how often to recurate a gene-disease association.

ClinGen Variant Curation Expert Panel experiences and standardized processes for disease and gene-level specification of the ACMG/AMP guidelines for sequence variant interpretation

Genome-scale sequencing creates vast amounts of genomic data, increasing the challenge of clinical sequence variant interpretation. The demand for high-quality interpretation requires multiple specialties to join forces to accelerate the interpretation of sequence variant pathogenicity. With over 600 international members including clinicians, researchers, and laboratory diagnosticians, the Clinical Genome Resource (ClinGen), funded by the National Institutes of Health, is forming expert groups to systematically evaluate variants in clinically relevant genes. Here, we describe the first ClinGen variant curation expert panels (VCEPs), development of consistent and streamlined processes for establishing new VCEPs, and creation of standard operating procedures for VCEPs to define application of the ACMG/AMP guidelines for sequence variant interpretation in specific genes or diseases. Additionally, ClinGen has created user interfaces to enhance reliability of curation and a Sequence Variant Interpretation Working Group (SVI WG) to harmonize guideline specifications and ensure consistency between groups. The expansion of VCEPs represents the primary mechanism by which curation of a substantial fraction of genomic variants can be accelerated and ultimately undertaken systematically and comprehensively. We welcome groups to utilize our resources and become involved in our effort to create a publicly accessible, centralized resource for clinically relevant genes and variants.

Clinical validity assessment of genes frequently tested on hereditary breast and ovarian cancer susceptibility sequencing panels

PURPOSE

Several genes on hereditary breast and ovarian cancer susceptibility test panels have not been systematically examined for strength of association with disease. We employed the Clinical Genome Resource (ClinGen) clinical validity framework to assess the strength of evidence between selected genes and breast or ovarian cancer.

METHODS

Thirty-one genes offered on cancer panel testing were selected for evaluation. The strength of gene-disease relationship was systematically evaluated and a clinical validity classification of either Definitive, Strong, Moderate, Limited, Refuted, Disputed, or No Reported Evidence was assigned.

RESULTS

Definitive clinical validity classifications were made for 10/31 and 10/32 gene-disease pairs for breast and ovarian cancer respectively. Two genes had a Moderate classification whereas, 6/31 and 6/32 genes had Limited classifications for breast and ovarian cancer respectively. Contradictory evidence resulted in Disputed or Refuted assertions for 9/31 genes for breast and 4/32 genes for ovarian cancer. No Reported Evidence of disease association was asserted for 5/31 genes for breast and 11/32 for ovarian cancer.

CONCLUSION

Evaluation of gene-disease association using the ClinGen clinical validity framework revealed a wide range of classifications. This information should aid laboratories in tailoring appropriate gene panels and assist health-care providers in interpreting results from panel testing.

ClinGen expert clinical validity curation of 164 hearing loss gene-disease pairs

PURPOSE

Proper interpretation of genomic variants is critical to successful medical decision making based on genetic testing results. A fundamental prerequisite to accurate variant interpretation is the clear understanding of the clinical validity of gene-disease relationships. The Clinical Genome Resource (ClinGen) has developed a semiquantitative framework to assign clinical validity to gene-disease relationships.

METHODS

The ClinGen Hearing Loss Gene Curation Expert Panel (HL GCEP) uses this framework to perform evidence-based curations of genes present on testing panels from 17 clinical laboratories in the Genetic Testing Registry. The HL GCEP curated and reviewed 142 genes and 164 gene-disease pairs, including 105 nonsyndromic and 59 syndromic forms of hearing loss.

RESULTS

The final outcome included 82 Definitive (50%), 12 Strong (7%), 25 Moderate (15%), 32 Limited (20%), 10 Disputed (6%), and 3 Refuted (2%) classifications. The summary of each curation is date stamped with the HL GCEP approval, is live, and will be kept up-to-date on the ClinGen website ( https://search.clinicalgenome.org/kb/gene-validity ).

CONCLUSION

This gene curation approach serves to optimize the clinical sensitivity of genetic testing while reducing the rate of uncertain or ambiguous test results caused by the interrogation of genes with insufficient evidence of a disease link.

Determining the clinical validity of hereditary colorectal cancer and polyposis susceptibility genes using the Clinical Genome Resource Clinical Validity Framework. Genet Med. 2019;21:1507-1516. [PMID: 30523343 PMCID: PMC6579719 DOI: 10.1038/s41436-018-0373-1]

Purpose:

Gene-disease associations implicated in hereditary colorectal cancer and polyposis susceptibility were evaluated using the ClinGen Clinical Validity framework.

Methods:

Forty-two gene-disease pairs were assessed for strength of evidence supporting an association with hereditary colorectal cancer and/or polyposis. Genetic and experimental evidence supporting each gene-disease relationship was curated independently by two trained biocurators. Evidence was reviewed with experts and assigned a final clinical validity classification.

Results:

Of all gene-disease pairs evaluated, 14/42 (33.3%) were Definitive, 1/42 (2.4%) were Strong, 6/42 (14.3%) were Moderate, 18/42 (42.9%) were Limited, and 3/42 (7.1%) were either No Reported Evidence, Disputed, or Refuted. Of panels in the NIH Genetic Testing Registry, 4/26 (~15.4%) contain genes with Limited clinical evidence.

Conclusion:

Clinicians and laboratory diagnosticians should note that <60% of the genes on clinically available panels have Strong or Definitive evidence of association with hereditary colon cancer or polyposis, and >40% have only Moderate, Limited, Disputed, or Refuted evidence. Continuing to expand the structured assessment of the clinical relevance of genes listed on hereditary cancer testing panels will help clinicians and diagnostic laboratories focus the communication of genetic testing results on clinically significant genes.

Adapting crowdsourced clinical cancer curation in CIViC to the ClinGen minimum variant level data community-driven standards

Harmonization of cancer variant representation, efficient communication, and free distribution of clinical variant-associated knowledge are central problems that arise with increased usage of clinical next-generation sequencing. The Clinical Genome Resource (ClinGen) Somatic Working Group (WG) developed a minimal variant level data (MVLD) representation of cancer variants, and has an ongoing collaboration with Clinical Interpretations of Variants in Cancer (CIViC), an open-source platform supporting crowdsourced and expert-moderated cancer variant curation. Harmonization between MVLD and CIViC variant formats was assessed by formal field-by-field analysis. Adjustments to the CIViC format were made to harmonize with MVLD and support ClinGen Somatic WG curation activities, including four new features in CIViC: (1) introduction of an assertions feature for clinical variant assessment following the Association of Molecular Pathologists (AMP) guidelines, (2) group-level curation tracking for organizations, enabling member transparency, and curation effort summaries, (3) introduction of ClinGen Allele Registry IDs to CIViC, and (4) mapping of CIViC assertions into ClinVar submission with automated submissions. A generalizable workflow utilizing MVLD and new CIViC features is outlined for use by ClinGen Somatic WG task teams for curation and submission to ClinVar, and provides a model for promoting harmonization of cancer variant representation and efficient distribution of this information.

Specifications of the ACMG/AMP variant curation guidelines for the analysis of germline CDH1 sequence variants

The variant curation guidelines published in 2015 by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) provided the genetics community with a framework to assess variant pathogenicity; however, these rules are not gene specific. Germline pathogenic variants in the CDH1 gene cause hereditary diffuse gastric cancer and lobular breast cancer, a clinically challenging cancer predisposition syndrome that often requires a multidisciplinary team of experts to be properly managed. Given this challenge, the Clinical Genome Resource (ClinGen) Hereditary Cancer Domain prioritized the development of the CDH1 variant curation expert panel (VCEP) to develop and implement rules for CDH1 variant classifications. Here, we describe the CDH1 specifications of the ACMG/AMP guidelines, which were developed and validated after a systematic evaluation of variants obtained from a cohort of clinical laboratory data encompassing ∼827,000 CDH1 sequenced alleles. Comparing previously reported germline variants that were classified using the 2015 ACMG/AMP guidelines to the CDH1 VCEP recommendations resulted in reduced variants of uncertain significance and facilitated resolution of variants with conflicted assertions in ClinVar. The ClinGen CDH1 VCEP recommends the use of these CDH1-specific guidelines for the assessment and classification of variants identified in this clinically actionable gene.

Recommendations for interpreting the loss of function PVS1 ACMG/AMP variant criterion

The 2015 ACMG/AMP sequence variant interpretation guideline provided a framework for classifying variants based on several benign and pathogenic evidence criteria, including a pathogenic criterion (PVS1) for predicted loss of function variants. However, the guideline did not elaborate on specific considerations for the different types of loss of function variants, nor did it provide decision-making pathways assimilating information about variant type, its location, or any additional evidence for the likelihood of a true null effect. Furthermore, this guideline did not take into account the relative strengths for each evidence type and the final outcome of their combinations with respect to PVS1 strength. Finally, criteria specifying the genes for which PVS1 can be applied are still missing. Here, as part of the ClinGen Sequence Variant Interpretation (SVI) Workgroup's goal of refining ACMG/AMP criteria, we provide recommendations for applying the PVS1 criterion using detailed guidance addressing the above-mentioned gaps. Evaluation of the refined criterion by seven disease-specific groups using heterogeneous types of loss of function variants (n = 56) showed 89% agreement with the new recommendation, while discrepancies in six variants (11%) were appropriately due to disease-specific refinements. Our recommendations will facilitate consistent and accurate interpretation of predicted loss of function variants.

Development of Clinical Domain Working Groups for the Clinical Genome Resource (ClinGen): lessons learned and plans for the future

The Clinical Genome Resource (ClinGen) is supported by the National Institutes of Health (NIH) to develop expertly curated and freely accessible resources defining the clinical relevance of genes and variants for use in precision medicine and research. To facilitate expert input, ClinGen has formed Clinical Domain Working Groups (CDWGs) to leverage the collective knowledge of clinicians, laboratory diagnosticians, and researchers. In the initial phase of ClinGen, CDWGs were launched in the cardiovascular, hereditary cancer, and inborn errors of metabolism clinical fields. These early CDWGs established the infrastructure necessary to implement standardized processes developed or adopted by ClinGen working groups for the interpretation of gene-disease associations and variant pathogenicity, and provided a sustainable model for the formation of future disease-focused curation groups.

The establishment of CDWGs requires recruitment of international experts to broadly represent the interests of their field and ensure that assertions made are reliable and widely accepted. Building on the successes, challenges, and trade-offs made in establishing the original CDWGs, ClinGen has developed standard operating procedures for the development of CDWGs in new clinical domains, while maximizing efforts to scale up curation and facilitate involvement of external groups who wish to utilize ClinGen methods and infrastructure for expert curation.

Harmonizing Outcomes for Genomic Medicine: Comparison of eMERGE Outcomes to ClinGen Outcome/Intervention Pairs

Genomic medicine is moving from research to the clinic. There is a lack of evidence about the impact of genomic medicine interventions on health outcomes. This is due in part to a lack of standardized outcome measures that can be used across different programs to evaluate the impact of interventions targeted to specific genetic conditions. The eMERGE Outcomes working group (OWG) developed measures to collect information on outcomes following the return of genomic results to participants for several genetic disorders. These outcomes were compared to outcome intervention pairs for genetic disorders developed independently by the ClinGen Actionability working group (AWG). In general, there was concordance between the defined outcomes between the two groups. The ClinGen outcomes tended to be from a higher level and the AWG scored outcomes represented a subset of outcomes referenced in the accompanying AWG evidence review. eMERGE OWG outcomes were more detailed and discrete, facilitating a collection of relevant information from the health records. This paper demonstrates that common outcomes for genomic medicine interventions can be identified. Further work is needed to standardize outcomes across genomic medicine implementation projects and to make these publicly available to enhance dissemination and assist in making precision public health a reality.

Development of a consent resource for genomic data sharing in the clinical setting

PURPOSE

Data sharing between clinicians, laboratories, and patients is essential for improvements in genomic medicine, but obtaining consent for individual-level data sharing is often hindered by a lack of time and resources. To address this issue, the Clinical Genome Resource (ClinGen) developed tools to facilitate consent, including a one-page consent form and online supplemental video with information on key topics, such as risks and benefits of data sharing.

METHODS

To determine whether the consent form and video accurately conveyed key data sharing concepts, we surveyed 5,162 members of the general public. We measured comprehension at baseline, after reading the form and watching the video. Additionally, we assessed participants' attitudes toward genomic data sharing.

RESULTS

Participants' performance on comprehension questions significantly improved over baseline after reading the form and continued to improve after watching the video.

CONCLUSION

Results suggest reading the form alone provided participants with important knowledge regarding broad data sharing, and watching the video allowed for broader comprehension. These materials are now available at http://www.clinicalgenome.org/share . These resources will provide patients a straightforward way to share their genetic and health information, and improve the scientific community's access to data generated through routine healthcare.

ClinGen's RASopathy Expert Panel consensus methods for variant interpretation

Purpose

Standardized and accurate variant assessment is essential for effective medical care. To that end, Clinical Genome (ClinGen) Resource clinical domain working groups (CDWG) are systematically reviewing disease-associated genes for sufficient evidence to support disease causality and creating disease-specific specifications of ACMG-AMP guidelines for consistent and accurate variant classification.

Methods

The ClinGen RASopathy CDWG established an expert panel (EP) to curate gene information and generate gene and disease-specific specifications to ACMG-AMP variant classification framework. These specifications were tested by classifying 37 exemplar pathogenic variants plus an additional 66 variants in ClinVar distributed across nine RASopathy genes.

Results

RASopathy-related specifications were applied to sixteen ACMG-AMP criteria, with five also having adjustable strength with availability of additional evidence. Another five criteria were deemed not applicable. Key adjustments to minor allele frequency thresholds, multiple de novo occurrence events and/or segregation, and strength adjustments impacted 60% of variant classifications. Unpublished case-level data from participating laboratories impacted 45% of classifications supporting the need for data sharing.

Conclusions

RAS-specific ACMG-AMP specifications optimized the utility of available clinical evidence and Ras/MAPK pathway-specific characteristics to consistently classify RASopathy-associated variants. These specifications highlight how grouping genes by shared features promotes rapid multi-genic variant assessment without sacrificing specificity and accuracy.

Distinguishing pathogenic mutations from background genetic noise in cardiology: The use of large genome databases for genetic interpretation

Advances in clinical genetic testing have led to increased insight into the human genome, including how challenging it is to interpret rare genetic variation. In some cases, the ability to detect genetic mutations exceeds the ability to understand their clinical impact, limiting the advantage of these technologies. Obstacles in genomic medicine are many and include: understanding the level of certainty/uncertainty behind pathogenicity determination, the numerous different variant interpretation-guidelines used by clinical laboratories, delivering the certain or uncertain result to the patient, helping patients evaluate medical decisions in light of uncertainty regarding the consequence of the findings. Through publication of large publicly available exome/genome databases, researchers and physicians are now able to highlight dubious variants previously associated with different cardiac traits. Also, continuous efforts through data sharing, international collaborative efforts to develop disease-gene-specific guidelines, and computational analyses using large data, will indubitably assist in better variant interpretation and classification. This article discusses the current, and quickly changing, state of variant interpretation resources within cardiovascular genetic research, e.g., publicly available databases and ways of how cardiovascular genetic counselors and geneticists can aid in improving variant interpretation in cardiology.

ClinGen Pathogenicity Calculator: a configurable system for assessing pathogenicity of genetic variants

BACKGROUND

The success of the clinical use of sequencing based tests (from single gene to genomes) depends on the accuracy and consistency of variant interpretation. Aiming to improve the interpretation process through practice guidelines, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) have published standards and guidelines for the interpretation of sequence variants. However, manual application of the guidelines is tedious and prone to human error. Web-based tools and software systems may not only address this problem but also document reasoning and supporting evidence, thus enabling transparency of evidence-based reasoning and resolution of discordant interpretations.

RESULTS

In this report, we describe the design, implementation, and initial testing of the Clinical Genome Resource (ClinGen) Pathogenicity Calculator, a configurable system and web service for the assessment of pathogenicity of Mendelian germline sequence variants. The system allows users to enter the applicable ACMG/AMP-style evidence tags for a specific allele with links to supporting data for each tag and generate guideline-based pathogenicity assessment for the allele. Through automation and comprehensive documentation of evidence codes, the system facilitates more accurate application of the ACMG/AMP guidelines, improves standardization in variant classification, and facilitates collaborative resolution of discordances. The rules of reasoning are configurable with gene-specific or disease-specific guideline variations (e.g. cardiomyopathy-specific frequency thresholds and functional assays). The software is modular, equipped with robust application program interfaces (APIs), and available under a free open source license and as a cloud-hosted web service, thus facilitating both stand-alone use and integration with existing variant curation and interpretation systems. The Pathogenicity Calculator is accessible at http://calculator.clinicalgenome.org .

CONCLUSIONS

By enabling evidence-based reasoning about the pathogenicity of genetic variants and by documenting supporting evidence, the Calculator contributes toward the creation of a knowledge commons and more accurate interpretation of sequence variants in research and clinical care.