ClinGen Variant Curation Interface: a variant classification platform for the application of evidence criteria from ACMG/AMP guidelines

Online Mendelian Inheritance in Animals (OMIA): a genetic resource for vertebrate animals

Online Mendelian Inheritance in Animals (OMIA) is a freely available curated knowledgebase that contains information and facilitates research on inherited traits and diseases in animals. For the past 29 years, OMIA has been used by animal geneticists, breeders, and veterinarians worldwide as a definitive source of information. Recent increases in curation capacity and funding for software engineering support have resulted in software upgrades and commencement of several initiatives, which include the enhancement of variant information and links to human data resources, and the introduction of ontology-based breed information and categories. We provide an overview of current information and recent enhancements to OMIA and discuss how we are expanding the integration of OMIA into other resources and databases via the use of ontologies and the adaptation of tools used in human genetics.

Exploring novel MYH7 gene variants using in silico analyses in Korean patients with cardiomyopathy

BACKGROUND

Pathogenic variants of MYH7, which encodes the beta-myosin heavy chain protein, are major causes of dilated and hypertrophic cardiomyopathy.

METHODS

In this study, we used whole-genome sequencing data to identify MYH7 variants in 397 patients with various cardiomyopathy subtypes who were participating in the National Project of Bio Big Data pilot study in Korea. We also performed in silico analyses to predict the pathogenicity of the novel variants, comparing them to known pathogenic missense variants.

RESULTS

We identified 27 MYH7 variants in 41 unrelated patients with cardiomyopathy, consisting of 20 previously known pathogenic/likely pathogenic variants, 2 variants of uncertain significance, and 5 novel variants. Notably, the pathogenic variants predominantly clustered within the myosin motor domain of MYH7. We confirmed that the novel identified variants could be pathogenic, as indicated by high prediction scores in the in silico analyses, including SIFT, Mutation Assessor, PROVEAN, PolyPhen-2, CADD, REVEL, MetaLR, MetaRNN, and MetaSVM. Furthermore, we assessed their damaging effects on protein dynamics and stability using DynaMut2 and Missense3D tools.

CONCLUSIONS

Overall, our study identified the distribution of MYH7 variants among patients with cardiomyopathy in Korea, offering new insights for improved diagnosis by enriching the data on the pathogenicity of novel variants using in silico tools and evaluating the function and structural stability of the MYH7 protein.

Evidence-based recommendations for gene-specific ACMG/AMP variant classification from the ClinGen ENIGMA BRCA1 and BRCA2 Variant Curation Expert Panel

The ENIGMA research consortium develops and applies methods to determine clinical significance of variants in hereditary breast and ovarian cancer genes. An ENIGMA BRCA1/2 classification sub-group, formed in 2015 as a ClinGen external expert panel, evolved into a ClinGen internal Variant Curation Expert Panel (VCEP) to align with Food and Drug Administration recognized processes for ClinVar contributions. The VCEP reviewed American College of Medical Genetics and Genomics/Association of Molecular Pathology (ACMG/AMP) classification criteria for relevance to interpreting BRCA1 and BRCA2 variants. Statistical methods were used to calibrate evidence strength for different data types. Pilot specifications were tested on 40 variants and documentation revised for clarity and ease of use. The original criterion descriptions for 13 evidence codes were considered non-applicable or overlapping with other criteria. Scenario of use was extended or re-purposed for eight codes. Extensive analysis and/or data review informed specification descriptions and weights for all codes. Specifications were applied to pilot variants with pre-existing ClinVar classification as follows: 13 uncertain significance or conflicting, 14 pathogenic and/or likely pathogenic, and 13 benign and/or likely benign. Review resolved classification for 11/13 uncertain significance or conflicting variants and retained or improved confidence in classification for the remaining variants. Alignment of pre-existing ENIGMA research classification processes with ACMG/AMP classification guidelines highlighted several gaps in the research processes and the baseline ACMG/AMP criteria. Calibration of evidence strength was key to justify utility and strength of different data types for gene-specific application. The gene-specific criteria demonstrated value for improving ACMG/AMP-aligned classification of BRCA1 and BRCA2 variants.

Generating Clinical-Grade Gene-Disease Validity Classifications Through the ClinGen Data Platforms

Clinical genetic laboratories must have access to clinically validated biomedical data for precision medicine. A lack of accessibility, normalized structure, and consistency in evaluation complicates interpretation of disease causality, resulting in confusion in assessing the clinical validity of genes and genetic variants for diagnosis. A key goal of the Clinical Genome Resource (ClinGen) is to fill the knowledge gap concerning the strength of evidence supporting the role of a gene in a monogenic disease, which is achieved through a process known as Gene-Disease Validity curation. Here we review the work of ClinGen in developing a curation infrastructure that supports the standardization, harmonization, and dissemination of Gene-Disease Validity data through the creation of frameworks and the utilization of common data standards. This infrastructure is based on several applications, including the ClinGen GeneTracker, Gene Curation Interface, Data Exchange, GeneGraph, and website.

Accuracy of renovo predictions on variants reclassified over time

BACKGROUND

Interpreting the clinical consequences of genetic variants is the central problem in modern clinical genomics, for both hereditary diseases and oncology. However, clinical validation lags behind the pace of discovery, leading to distressing uncertainty for patients, physicians and researchers. This "interpretation gap" changes over time as evidence accumulates, and variants initially deemed of uncertain (VUS) significance may be subsequently reclassified in pathogenic/benign. We previously developed RENOVO, a random forest-based tool able to predict variant pathogenicity based on publicly available information from GnomAD and dbNFSP, and tested on variants that have changed their classification status over time. Here, we comprehensively evaluated the accuracy of RENOVO predictions on variants that have been reclassified over the last four years.

METHODS

we retrieved 16 retrospective instances of the ClinVar database, every 3 months since March 2020 to March 2024, and analyzed time trends of variant classifications. We identified variants that changed their status over time and compared RENOVO predictions generated in 2020 with the actual reclassifications.

RESULTS

VUS have become the most represented class in ClinVar (44.97% vs. 9.75% (likely) pathogenic and 40,33% (likely) benign). The rate of VUS reclassification is linear and slow compared to the rate of VUS reporting, exponential and currently ~ 30x faster, creating a growing divide between what can be sequenced vs. what can be interpreted. Out of 10,196 VUS variants in January 2020 that have undergone a clinically meaningful reclassification to march 2024, RENOVO correctly classified 82.6% in 2020. In addition, RENOVO correctly identified the majority of the few variants that switched clinically meaningful classes (e.g., from benign to pathogenic and vice versa). We highlight variant classes and clinically relevant genes for which RENOVO provides particularly accurate estimates. In particularly, genes characterized by large prevalence of high- or low-impact variants (e.g., POLE, NOTCH1, FANCM etc.). Suboptimal RENOVO predictions mostly concern genes validated through dedicated consortia (e.g., BRCA1/2), in which RENOVO would anyway have a limited impact.

CONCLUSIONS

Time trend analysis demonstrates that the current model of variant interpretation cannot keep up with variant discovery. Machine learning-based tools like RENOVO confirm high accuracy that can aid in clinical practice and research.

Variant classification changes over time in the clinical molecular diagnostic laboratory setting

BACKGROUND

Variant classification in the setting of germline genetic testing is necessary for patients and their families to receive proper care. Variants are classified as pathogenic (P), likely pathogenic (LP), uncertain significance (VUS), likely benign (LB) and benign (B) using the standards and guidelines recommended by the American College of Medical Genetics and the Association for Molecular Pathology, with modifications for specific genes. As the literature continues to rapidly expand, and evidence continues to accumulate, prior classifications can be updated accordingly. In this study, we aim to characterise variant reclassifications in Ontario.

METHODS

DNA samples from patients seen at hereditary cancer clinics in Ontario from January 2012 to April 2022 were submitted for testing. Patients met provincial eligibility criteria for testing for hereditary cancer syndromes or polycystic kidney disease. Reclassification events were determined to be within their broader category of significance (B to LB or vice versa, or P to LP or vice versa) or outside of their broader category as significance (ie, significant reclassifications from B/LB or VUS or P/LP, from P/LP to VUS or B/LB, or from VUS to any other category).

RESULTS

Of the 8075 unique variants included in this study, 23.7% (1912) of variants were reassessed, and 7.2% (578) of variants were reclassified. Of these, 351 (60.7%) variants were reclassified outside of their broader category of significance. Overall, the final classification was significantly different for 336 (58.1%) variants. Importantly, most reclassified variants were downgraded to a more benign classification (n=245; 72.9%). Of note, most reclassified VUS was downgraded to B/LB (n=233; 84.7%).

CONCLUSIONS

The likelihood for reclassification of variants on reassessment is high. Most reclassified variants were downgraded to a more benign classification. Our findings highlight the importance of periodic variant reassessment to ensure timely and appropriate care for patients and their families.

Advancing Genetic Testing in Kidney Diseases: Report From a National Kidney Foundation Working Group

About 37 million people in the United States have chronic kidney disease, a disease that encompasses multiple causes. About 10% or more of kidney diseases in adults and as many as 70% of selected chronic kidney diseases in children are expected to be explained by genetic causes. Despite the advances in genetic testing and an increasing understanding of the genetic bases of certain kidney diseases, genetic testing in nephrology lags behind other medical fields. More understanding of the benefits and logistics of genetic testing is needed to advance the implementation of genetic testing in chronic kidney diseases. Accordingly, the National Kidney Foundation convened a Working Group of experts with diverse expertise in genetics, nephrology, and allied fields to develop recommendations for genetic testing for monogenic disorders and to identify genetic risk factors for oligogenic and polygenic causes of kidney diseases. Algorithms for clinical decision making on genetic testing and a road map for advancing genetic testing in kidney diseases were generated. An important aspect of this initiative was the use of a modified Delphi process to reach group consensus on the recommendations. The recommendations and resources described herein provide support to nephrologists and allied health professionals to advance the use of genetic testing for diagnosis and screening of kidney diseases.

Pathway-based, reaction-specific annotation of disease variants for elucidation of molecular phenotypes

Germline and somatic mutations can give rise to proteins with altered activity, including both gain and loss-of-function. The effects of these variants can be captured in disease-specific reactions and pathways that highlight the resulting changes to normal biology. A disease reaction is defined as an aberrant reaction in which a variant protein participates. A disease pathway is defined as a pathway that contains a disease reaction. Annotation of disease variants as participants of disease reactions and disease pathways can provide a standardized overview of molecular phenotypes of pathogenic variants that is amenable to computational mining and mathematical modeling. Reactome (https://reactome.org/), an open source, manually curated, peer-reviewed database of human biological pathways, in addition to providing annotations for >11 000 unique human proteins in the context of ∼15 000 wild-type reactions within more than 2000 wild-type pathways, also provides annotations for >4000 disease variants of close to 400 genes as participants of ∼800 disease reactions in the context of ∼400 disease pathways. Functional annotation of disease variants proceeds from normal gene functions, described in wild-type reactions and pathways, through disease variants whose divergence from normal molecular behaviors has been experimentally verified, to extrapolation from molecular phenotypes of characterized variants to variants of unknown significance using criteria of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Reactome's data model enables mapping of disease variant datasets to specific disease reactions within disease pathways, providing a platform to infer pathway output impacts of numerous human disease variants and model organism orthologs, complementing computational predictions of variant pathogenicity. Database URL: https://reactome.org/.

ClinGen variant curation expert panel recommendations for classification of variants in GAMT, GATM and SLC6A8 for cerebral creatine deficiency syndromes

Cerebral creatine deficiency syndromes (CCDS) are inherited metabolic phenotypes of creatine synthesis and transport. There are two enzyme deficiencies, guanidinoacetate methyltransferase (GAMT), encoded by GAMT and arginine-glycine amidinotransferase (AGAT), encoded by GATM, which are involved in the synthesis of creatine. After synthesis, creatine is taken up by a sodium-dependent membrane bound creatine transporter (CRTR), encoded by SLC6A8, into all organs. Creatine uptake is very important especially in high energy demanding organs such as the brain, and muscle. To classify the pathogenicity of variants in GAMT, GATM, and SLC6A8, we developed the CCDS Variant Curation Expert Panel (VCEP) in 2018, supported by The Clinical Genome Resource (ClinGen), a National Institutes of Health (NIH)-funded resource. We developed disease-specific variant classification guidelines for GAMT-, GATM-, and SLC6A8-related CCDS, adapted from the American College of Medical Genetics/Association of Molecular Pathology (ACMG/AMP) variant interpretation guidelines. We applied specific variant classification guidelines to 30 pilot variants in each of the three genes that have variants associated with CCDS. Our CCDS VCEP was approved by the ClinGen Sequence Variant Interpretation Working Group (SVI WG) and Clinical Domain Oversight Committee in July 2022. We curated 181 variants including 72 variants in GAMT, 45 variants in GATM, and 64 variants in SLC6A8 and submitted these classifications to ClinVar, a public variant database supported by the National Center for Biotechnology Information. Missense variants were the most common variant type in all three genes. We submitted 32 new variants and reclassified 34 variants with conflicting interpretations. We report specific phenotype (PP4) using a points system based on the urine and plasma guanidinoacetate and creatine levels, brain magnetic resonance spectroscopy (MRS) creatine level, and enzyme activity or creatine uptake in fibroblasts ranging from PP4, PP4_Moderate and PP4_Strong. Our CCDS VCEP is one of the first panels applying disease specific variant classification algorithms for an X-linked disease. The availability of these guidelines and classifications can guide molecular genetics and genomic laboratories and health care providers to assess the molecular diagnosis of individuals with a CCDS phenotype.

Standards of NGS Data Sharing and Analysis in Ataxias: Recommendations by the NGS Working Group of the Ataxia Global Initiative

The Ataxia Global Initiative (AGI) is a worldwide multi-stakeholder research platform to systematically enhance trial-readiness in degenerative ataxias. The next-generation sequencing (NGS) working group of the AGI aims to improve methods, platforms, and international standards for ataxia NGS analysis and data sharing, ultimately allowing to increase the number of genetically ataxia patients amenable for natural history and treatment trials. Despite extensive implementation of NGS for ataxia patients in clinical and research settings, the diagnostic gap remains sizeable, as approximately 50% of patients with hereditary ataxia remain genetically undiagnosed. One current shortcoming is the fragmentation of patients and NGS datasets on different analysis platforms and databases around the world. The AGI NGS working group in collaboration with the AGI associated research platforms-CAGC, GENESIS, and RD-Connect GPAP-provides clinicians and scientists access to user-friendly and adaptable interfaces to analyze genome-scale patient data. These platforms also foster collaboration within the ataxia community. These efforts and tools have led to the diagnosis of > 500 ataxia patients and the discovery of > 30 novel ataxia genes. Here, the AGI NGS working group presents their consensus recommendations for NGS data sharing initiatives in the ataxia field, focusing on harmonized NGS variant analysis and standardized clinical and metadata collection, combined with collaborative data and analysis tool sharing across platforms.

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.

The effects of pathogenic and likely pathogenic variants for inherited hemostasis disorders in 140 214 UK Biobank participants

Rare genetic diseases affect millions, and identifying causal DNA variants is essential for patient care. Therefore, it is imperative to estimate the effect of each independent variant and improve their pathogenicity classification. Our study of 140 214 unrelated UK Biobank (UKB) participants found that each of them carries a median of 7 variants previously reported as pathogenic or likely pathogenic. We focused on 967 diagnostic-grade gene (DGG) variants for rare bleeding, thrombotic, and platelet disorders (BTPDs) observed in 12 367 UKB participants. By association analysis, for a subset of these variants, we estimated effect sizes for platelet count and volume, and odds ratios for bleeding and thrombosis. Variants causal of some autosomal recessive platelet disorders revealed phenotypic consequences in carriers. Loss-of-function variants in MPL, which cause chronic amegakaryocytic thrombocytopenia if biallelic, were unexpectedly associated with increased platelet counts in carriers. We also demonstrated that common variants identified by genome-wide association studies (GWAS) for platelet count or thrombosis risk may influence the penetrance of rare variants in BTPD DGGs on their associated hemostasis disorders. Network-propagation analysis applied to an interactome of 18 410 nodes and 571 917 edges showed that GWAS variants with large effect sizes are enriched in DGGs and their first-order interactors. Finally, we illustrate the modifying effect of polygenic scores for platelet count and thrombosis risk on disease severity in participants carrying rare variants in TUBB1 or PROC and PROS1, respectively. Our findings demonstrate the power of association analyses using large population datasets in improving pathogenicity classifications of rare variants.

Pathway-based, reaction-specific annotation of disease variants for elucidation of molecular phenotypes

Disease variant annotation in the context of biological reactions and pathways can provide a standardized overview of molecular phenotypes of pathogenic mutations that is amenable to computational mining and mathematical modeling. Reactome, an open source, manually curated, peer-reviewed database of human biological pathways, provides annotations for over 4000 disease variants of close to 400 genes in the context of ∼800 disease reactions constituting ∼400 disease pathways. Functional annotation of disease variants proceeds from normal gene functions, through disease variants whose divergence from normal molecular behaviors has been experimentally verified, to extrapolation from molecular phenotypes of characterized variants to variants of unknown significance using criteria of the American College of Medical Genetics and Genomics (ACMG). Reactome's pathway-based, reaction-specific disease variant dataset and data model provide a platform to infer pathway output impacts of numerous human disease variants and model organism orthologs, complementing computational predictions of variant pathogenicity.

In silico Analysis of Two Novel Variants in the Pyruvate Carboxylase (PC) Gene Associated with the Severe Form of PC Deficiency

Background

Inborne errors of metabolism are a common cause of neonatal death. This study evaluated the acute early-onset metabolic derangement and death in two unrelated neonates.

Methods

Whole-exome sequencing (WES), Sanger sequencing, homology modeling, and in silico bioinformatics analysis were employed to assess the effects of variants on protein structure and function.

Results

WES revealed a novel homozygous variant, p.G303Afs*40 and p.R156P, in the pyruvate carboxylase (PC) gene of each neonate, which both were confirmed by Sanger sequencing. Based on the American College of Medical Genetics and Genomics guidelines, the p.G303Afs*40 was likely pathogenic, and the p.R156P was a variant of uncertain significance (VUS). Nevertheless, a known variant at position 156, the p.R156Q, was also a VUS. Protein secondary structure prediction showed changes in p.R156P and p.R156Q variants compared to the wild-type protein. However, p.G303Afs*40 depicted significant changes at C-terminal. Furthermore, comparing the interaction of wild-type and variant proteins with the ATP ligand during simulations, revealed a decreased affinity to the ATP in all the variants. Moreover, analysis of Single nucleotide polymorphism impacts on PC protein using Polyphen-2, SNAP2, FATHMM, and SNPs&GO servers predicted both R156P and R156Q as damaging variants. Likewise, free energy calculations demonstrated the destabilizing effect of both variants on PC.

Conclusion

This study confirmed the pathogenicity of both variants and suggested them as a cause of type B Pyruvate carboxylase deficiency. The results of this study would provide the family with prenatal diagnosis and expand the variant spectrum in the PC gene,which is beneficial for geneticists and endocrinologists.

Variant Classification for Pompe disease; ACMG/AMP specifications from the ClinGen Lysosomal Diseases Variant Curation Expert Panel

Accurate determination of the clinical significance of genetic variants is critical to the integration of genomics in medicine. To facilitate this process, the NIH-funded Clinical Genome Resource (ClinGen) has assembled Variant Curation Expert Panels (VCEPs), groups of experts and biocurators which provide gene- and disease- specifications to the American College of Medical Genetics & Genomics and Association for Molecular Pathology's (ACMG/AMP) variation classification guidelines. With the goal of classifying the clinical significance of GAA variants in Pompe disease (Glycogen storage disease, type II), the ClinGen Lysosomal Diseases (LD) VCEP has specified the ACMG/AMP criteria for GAA. Variant classification can play an important role in confirming the diagnosis of Pompe disease as well as in the identification of carriers. Furthermore, since the inclusion of Pompe disease on the Recommended Uniform Screening Panel (RUSP) for newborns in the USA in 2015, the addition of molecular genetic testing has become an important component in the interpretation of newborn screening results, particularly for asymptomatic individuals. To date, the LD VCEP has submitted classifications and supporting data on 243 GAA variants to public databases, specifically ClinVar and the ClinGen Evidence Repository. Here, we describe the ACMG/AMP criteria specification process for GAA, an update of the GAA-specific variant classification guidelines, and comparison of the ClinGen LD VCEP's GAA variant classifications with variant classifications submitted to ClinVar. The LD VCEP has added to the publicly available knowledge on the pathogenicity of variants in GAA by increasing the number of expert-curated GAA variants present in ClinVar, and aids in resolving conflicting classifications and variants of uncertain clinical significance.

The mutational profile in a South African cohort with inherited neuropathies and spastic paraplegia

Introduction

Limited diagnostics are available for inherited neuromuscular diseases (NMD) in South Africa and (excluding muscle disease) are mainly aimed at the most frequent genes underlying genetic neuropathy (GN) and spastic ataxias in Europeans. In this study, we used next-generation sequencing to screen 61 probands with GN, hereditary spastic paraplegia (HSP), and spastic ataxias for a genetic diagnosis.

Methods

After identifying four GN probands with PMP22 duplication and one spastic ataxia proband with SCA1, the remaining probands underwent whole exome (n = 26) or genome sequencing (n = 30). The curation of coding/splice region variants using gene panels was guided by allele frequencies from internal African-ancestry control genomes (n = 537) and the Clinical Genome Resource's Sequence Variant Interpretation guidelines.

Results

Of 32 GN probands, 50% had African-genetic ancestry, and 44% were solved: PMP22 (n = 4); MFN2 (n = 3); one each of MORC2, ATP1A1, ADPRHL2, GJB1, GAN, MPZ, and ATM. Of 29 HSP probands (six with predominant ataxia), 66% had African-genetic ancestry, and 48% were solved: SPG11 (n = 3); KIF1A (n = 2); and one each of SPAST, ATL1, SPG7, PCYT2, PSEN1, ATXN1, ALDH18A1, CYP7B1, and RFT1. Structural variants in SPAST, SPG11, SPG7, MFN2, MPZ, KIF5A, and GJB1 were excluded by computational prediction and manual visualisation.

Discussion

In this preliminary cohort screening panel of disease genes using WES/WGS data, we solved ~50% of cases, which is similar to diagnostic yields reported for global cohorts. However, the mutational profile among South Africans with GN and HSP differs substantially from that in the Global North.

MAGI-ACMG: Algorithm for the Classification of Variants According to ACMG and ACGS Recommendations

We have developed MAGI-ACMG, a classification algorithm that allows the classification of sequencing variants (single nucleotide or small indels) according to the recommendations of the American College of Medical Genetics (ACMG) and the Association for Clinical Genomic Science (ACGS). The MAGI-ACMG classification algorithm uses information retrieved through the VarSome Application Programming Interface (API), integrates the AutoPVS1 tool in order to evaluate more precisely the attribution of the PVS1 criterion, and performs the customized assignment of specific criteria. In addition, we propose a sub-classification scheme for variants of uncertain significance (VUS) according to their proximity either towards the "likely pathogenic" or "likely benign" classes. We also conceived a pathogenicity potential criterion (P_POT) as a proxy for segregation criteria that might be added to a VUS after posterior testing, thus allowing it to upgrade its clinical significance in a diagnostic reporting setting. Finally, we have developed a user-friendly web application based on the MAGI-ACMG algorithm, available to geneticists for variant interpretation.

Utility of Exome Sequencing for Diagnosis in Unexplained Pediatric-Onset Epilepsy

Importance

Genomic advances inform our understanding of epilepsy and can be translated to patients as precision diagnoses that influence clinical treatment, prognosis, and counseling.

Objective

To delineate the genetic landscape of pediatric epilepsy and clinical utility of genetic diagnoses for patients with epilepsy.

Design, Setting, and Participants

This cohort study used phenotypic data from medical records and treating clinicians at a pediatric hospital to identify patients with unexplained pediatric-onset epilepsy. Exome sequencing was performed for 522 patients and available biological parents, and sequencing data were analyzed for single nucleotide variants (SNVs) and copy number variants (CNVs). Variant pathogenicity was assessed, patients were provided with their diagnostic results, and clinical utility was evaluated. Patients were enrolled from August 2018 to October 2021, and data were analyzed through December 2022.

Exposures

Phenotypic features associated with diagnostic genetic results.

Main Outcomes and Measures

Main outcomes included diagnostic yield and clinical utility. Diagnostic findings included variants curated as pathogenic, likely pathogenic (PLP), or diagnostic variants of uncertain significance (VUS) with clinical features consistent with the involved gene's associated phenotype. The proportion of the cohort with diagnostic findings, the genes involved, and their clinical utility, defined as impact on clinical treatment, prognosis, or surveillance, are reported.

Results

A total of 522 children (269 [51.5%] male; mean [SD] age at seizure onset, 1.2 [1.4] years) were enrolled, including 142 children (27%) with developmental epileptic encephalopathy and 263 children (50.4%) with intellectual disability. Of these, 100 participants (19.2%) had identifiable genetic explanations for their seizures: 89 participants had SNVs (87 germline, 2 somatic mosaic) involving 69 genes, and 11 participants had CNVs. The likelihood of identifying a genetic diagnosis was highest in patients with intellectual disability (adjusted odds ratio [aOR], 2.44; 95% CI, 1.40-4.26), early onset seizures (aOR, 0.93; 95% CI, 0.88-0.98), and motor impairment (aOR, 2.19; 95% CI 1.34-3.58). Among 43 patients with apparently de novo variants, 2 were subsequently determined to have asymptomatic parents harboring mosaic variants. Of 71 patients who received diagnostic results and were followed clinically, 29 (41%) had documented clinical utility resulting from their genetic diagnoses.

Conclusions and Relevance

These findings suggest that pediatric-onset epilepsy is genetically heterogeneous and that some patients with previously unexplained pediatric-onset epilepsy had genetic diagnoses with direct clinical implications.

Clinical utility of periodic reinterpretation of CNVs of uncertain significance: an 8-year retrospective study

BACKGROUND

Array-CGH is the first-tier genetic test both in pre- and postnatal developmental disorders worldwide. Variants of uncertain significance (VUS) represent around 10~15% of reported copy number variants (CNVs). Even though VUS reanalysis has become usual in practice, no long-term study regarding CNV reinterpretation has been reported.

METHODS

This retrospective study examined 1641 CGH arrays performed over 8 years (2010-2017) to demonstrate the contribution of periodically re-analyzing CNVs of uncertain significance. CNVs were classified using AnnotSV on the one hand and manually curated on the other hand. The classification was based on the 2020 American College of Medical Genetics (ACMG) criteria.

RESULTS

Of the 1641 array-CGH analyzed, 259 (15.7%) showed at least one CNV initially reported as of uncertain significance. After reinterpretation, 106 of the 259 patients (40.9%) changed categories, and 12 of 259 (4.6%) had a VUS reclassified to likely pathogenic or pathogenic. Six were predisposing factors for neurodevelopmental disorder/autism spectrum disorder (ASD). CNV type (gain or loss) does not seem to impact the reclassification rate, unlike the length of the CNV: 75% of CNVs downgraded to benign or likely benign are less than 500 kb in size.

CONCLUSIONS

This study's high rate of reinterpretation suggests that CNV interpretation has rapidly evolved since 2010, thanks to the continuous enrichment of available databases. The reinterpreted CNV explained the phenotype for ten patients, leading to optimal genetic counseling. These findings suggest that CNVs should be reinterpreted at least every 2 years.

The functional impact of 1,570 individual amino acid substitutions in human OTC

Deleterious mutations in the X-linked gene encoding ornithine transcarbamylase (OTC) cause the most common urea cycle disorder, OTC deficiency. This rare but highly actionable disease can present with severe neonatal onset in males or with later onset in either sex. Individuals with neonatal onset appear normal at birth but rapidly develop hyperammonemia, which can progress to cerebral edema, coma, and death, outcomes ameliorated by rapid diagnosis and treatment. Here, we develop a high-throughput functional assay for human OTC and individually measure the impact of 1,570 variants, 84% of all SNV-accessible missense mutations. Comparison to existing clinical significance calls, demonstrated that our assay distinguishes known benign from pathogenic variants and variants with neonatal onset from late-onset disease presentation. This functional stratification allowed us to identify score ranges corresponding to clinically relevant levels of impairment of OTC activity. Examining the results of our assay in the context of protein structure further allowed us to identify a 13 amino acid domain, the SMG loop, whose function appears to be required in human cells but not in yeast. Finally, inclusion of our data as PS3 evidence under the current ACMG guidelines, in a pilot reclassification of 34 variants with complete loss of activity, would change the classification of 22 from variants of unknown significance to clinically actionable likely pathogenic variants. These results illustrate how large-scale functional assays are especially powerful when applied to rare genetic diseases.

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.

Schmidtea mediterranea as a Model Organism to Study the Molecular Background of Human Motile Ciliopathies

Cilia and flagella are evolutionarily conserved organelles that form protrusions on the surface of many growth-arrested or differentiated eukaryotic cells. Due to the structural and functional differences, cilia can be roughly classified as motile and non-motile (primary). Genetically determined dysfunction of motile cilia is the basis of primary ciliary dyskinesia (PCD), a heterogeneous ciliopathy affecting respiratory airways, fertility, and laterality. In the face of the still incomplete knowledge of PCD genetics and phenotype-genotype relations in PCD and the spectrum of PCD-like diseases, a continuous search for new causative genes is required. The use of model organisms has been a great part of the advances in understanding molecular mechanisms and the genetic basis of human diseases; the PCD spectrum is not different in this respect. The planarian model (Schmidtea mediterranea) has been intensely used to study regeneration processes, and-in the context of cilia-their evolution, assembly, and role in cell signaling. However, relatively little attention has been paid to the use of this simple and accessible model for studying the genetics of PCD and related diseases. The recent rapid development of the available planarian databases with detailed genomic and functional annotations prompted us to review the potential of the S. mediterranea model for studying human motile ciliopathies.

CIViCdb 2022: evolution of an open-access cancer variant interpretation knowledgebase

CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is a crowd-sourced, public domain knowledgebase composed of literature-derived evidence characterizing the clinical utility of cancer variants. As clinical sequencing becomes more prevalent in cancer management, the need for cancer variant interpretation has grown beyond the capability of any single institution. CIViC contains peer-reviewed, published literature curated and expertly-moderated into structured data units (Evidence Items) that can be accessed globally and in real time, reducing barriers to clinical variant knowledge sharing. We have extended CIViC's functionality to support emergent variant interpretation guidelines, increase interoperability with other variant resources, and promote widespread dissemination of structured curated data. To support the full breadth of variant interpretation from basic to translational, including integration of somatic and germline variant knowledge and inference of drug response, we have enabled curation of three new Evidence Types (Predisposing, Oncogenic and Functional). The growing CIViC knowledgebase has over 300 contributors and distributes clinically-relevant cancer variant data currently representing >3200 variants in >470 genes from >3100 publications.

Developing a disease-specific annotation protocol for VHL gene curation using Hypothes.is

Von Hippel-Lindau (VHL) disease is a rare, autosomal dominant disorder that predisposes individuals to developing tumors in many organs. There is significant phenotypic variability and genetic variants encountered within this syndrome, posing a considerable challenge to patient care. The lack of VHL variant data sharing paired with the absence of aggregated genotype-phenotype information results in an arduous process, when characterizing genetic variants and predicting patient prognosis. To address these gaps in knowledge, the Clinical Genome Resource (ClinGen) VHL Variant Curation Expert Panel (VCEP) has been resolving a list of variants of uncertain significance within the VHL gene. Through community curation, we crowdsourced the laborious task of variant annotation by modifying the ClinGen Community Curation (C3)-developed Baseline Annotation protocol and annotating all published VHL cases with the reported genotype-phenotype information in Hypothes.is, an open-access web annotation tool. This process, incorporated into the ClinGen VCEP's workflow, will aid in their curation efforts. To facilitate the curation at all levels of genetics expertise, our team developed a 4-day biocuration training protocol and resource guide. To date, 91.3% of annotations have been completed by undergraduate and high-school students without formal academic genetics specialization. Here, we present our VHL-specific annotation protocol utilizing Hypothes.is, which offers a standardized method to present case-resolution data, and our biocuration training protocol, which can be adapted for other rare disease platforms. By facilitating training for community curation of VHL disease, we increased student engagement with clinical genetics while enhancing knowledge translation in the field of hereditary cancer. Database URL: https://hypothes.is/groups/dKymJJpZ/vhl-hypothesis-annotation.

The global prevalence and ethnic heterogeneity of iron-refractory iron deficiency anaemia

BACKGROUND

Iron-refractory iron deficiency anaemia (IRIDA) is an autosomal recessive iron deficiency anaemia caused by mutations in the TMPRSS6 gene. Iron deficiency anaemia is common, whereas IRIDA is rare. The prevalence of IRIDA is unclear. This study aimed to estimate the carrier frequency and genetic prevalence of IRIDA using Genome Aggregation Database (gnomAD) data.

METHODS

The pathogenicity of TMPRSS6 variants was interpreted according to the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) standards and guidelines. The minor allele frequency (MAF) of TMPRSS6 gene disease-causing variants in 141,456 unique individuals was examined to estimate the global prevalence of IRIDA in seven ethnicities: African/African American (afr), American Admixed/Latino (amr), Ashkenazi Jewish (asj), East Asian (eas), Finnish (fin), Non-Finnish European (nfe) and South Asian (sas). The global and population-specific carrier frequencies and genetic prevalence of IRIDA were calculated using the Hardy-Weinberg equation.

RESULTS

In total, 86 pathogenic/likely pathogenic variants (PV/LPV) were identified according to ACMG/AMP guideline. The global carrier frequency and genetic prevalence of IRIDA were 2.02 per thousand and 1.02 per million, respectively.

CONCLUSIONS

The prevalence of IRIDA is greater than previous estimates.

The advantages and pitfalls of genetic analysis in the diagnosis and management of lipid disorders

The increasing affordability of and access to next-generation DNA sequencing has increased the feasibility of incorporating genetic analysis into the diagnostic pathway for dyslipidaemia. But should genetic diagnosis be used routinely? DNA testing for any medical condition has potential benefits and pitfalls. For dyslipidaemias, the overall balance of advantages versus drawbacks differs according to the main lipid disturbance. For instance, some patients with severely elevated low-density lipoprotein cholesterol levels have a monogenic disorder, namely heterozygous familial hypercholesterolaemia. In these patients, DNA diagnosis can be definitive, in turn yielding several benefits for patient care that tend to outweigh any potential disadvantages. In contrast, hypertriglyceridaemia is almost always a polygenic condition without a discrete monogenic basis, except for ultrarare monogenic familial chylomicronaemia syndrome. Genetic testing in patients with hypertriglyceridaemia is therefore predominantly non-definitive and evidence for benefit is presently lacking. Here we consider advantages and limitations of genetic testing in dyslipidaemias.

Genetic testing in dyslipidaemia: An approach based on clinical experience

We have used DNA sequencing in our lipid clinic for >20 years. Dyslipidaemia is typically ascertained biochemically. For moderate deviations in the lipid profile, the etiology is often a combination of a polygenic susceptibility component plus secondary non-genetic factors. For severe dyslipidaemia, a monogenic etiology is more likely, although a discrete single-gene cause is frequently not found. A severe phenotype can also result from strong polygenic predisposition that is aggravated by secondary factors. A young age of onset plus a family history of dyslipidaemia or atherosclerotic cardiovascular disease can suggest a monogenic etiology. With severe dyslipidaemia, clinical examination focuses on detecting manifestations of monogenic syndromic conditions. For all patients with dyslipidaemia, secondary causes must be ruled out. Here we describe an experience-based practical approach to genetic testing of patients with severe deviations of low-density lipoprotein, triglycerides, high-density lipoprotein and also combined hyperlipidaemia and dysbetalipoproteinemia.

Approach to the patient with a variant of uncertain significance on genetic testing

Establishing a genetic diagnosis may lead to major health benefits for the patient and their wider family, but is dependent on the accurate interpretation of test results. The processes of variant interpretation are by their nature imprecise such that the potential for uncertain test results (i.e., variant(s) of uncertain significance [VUS]) are an inevitable consequence of genomic testing. With an increased responsibility for diagnostic testing in the hands of the specialty physician (e.g., endocrinologist) rather than clinical geneticist, it is essential that they are familiar with the possible outcomes of testing including an understanding of the VUS category. While uncertainty is endemic to many aspects of clinical medicine, receiving a VUS result may pose a considerable challenge to both the clinician and the patient. In this article, a framework to support decision-making when confronted with a VUS variant is provided, focusing on the key components of the genetic testing pathway. This highlights the importance of assessing the VUS result in the context of the clinical presentation and genetic testing strategy, the value of multidisciplinary team working and ensuring good communication with the patient.

Updated variant curation expert panel criteria and pathogenicity classifications for 251 variants for RYR1-related malignant hyperthermia susceptibility

The ClinGen malignant hyperthermia susceptibility (MHS) variant curation expert panel specified the American College of Medical Genetics and Genomics/Association of Molecular Pathologists (ACMG/AMP) criteria for RYR1-related MHS and a pilot analysis of 84 variants was published. We have now classified an additional 251 variants for RYR1-related MHS according to current ClinGen standards and updated the criteria where necessary. Criterion PS4 was modified such that individuals with multiple RYR1 variants classified as pathogenic (P), likely pathogenic (LP), or variant of uncertain significance (VUS) were not considered as providing evidence for pathogenicity. Criteria PS1 and PM5 were revised to consider LP variants at the same amino-acid residue as providing evidence for pathogenicity at reduced strength. Finally, PM1 was revised such that if PS1 or PM5 are used PM1, if applicable, should be downgraded to supporting. Of the 251 RYR1 variants, 42 were classified as P/LP, 16 as B/LB, and 193 as VUS. The primary driver of 175 VUS classifications was insufficient evidence supporting pathogenicity, rather than evidence against pathogenicity. Functional data supporting PS3/BS3 was identified for only 13 variants. Based on the posterior probabilities of pathogenicity and variant frequencies in gnomAD, we estimated the prevalence of individuals with RYR1-related MHS pathogenic variants to be between 1/300 and 1/1075, considerably higher than current estimates. We have updated ACMG/AMP criteria for RYR1-related MHS and classified 251 variants. We suggest that prioritization of functional studies is needed to resolve the large number of VUS classifications and allow for appropriate risk assessment. RYR1-related MHS pathogenic variants are likely to be more common than currently appreciated.

Global Globin Network Consensus Paper: Classification and Stratified Roadmaps for Improved Thalassaemia Care and Prevention in 32 Countries

The Global Globin Network (GGN) is a project-wide initiative of the Human Variome/Global Variome Project (HVP) focusing on haemoglobinopathies to build the capacity for genomic diagnosis, clinical services, and research in low- and middle-income countries. At present, there is no framework to evaluate the improvement of care, treatment, and prevention of thalassaemia and other haemoglobinopathies globally, despite thalassaemia being one of the most common monogenic diseases worldwide. Here, we propose a universally applicable system for evaluating and grouping countries based on qualitative indicators according to the quality of care, treatment, and prevention of haemoglobinopathies. We also apply this system to GGN countries as proof of principle. To this end, qualitative indicators were extracted from the IthaMaps database of the ITHANET portal, which allowed four groups of countries (A, B, C, and D) to be defined based on major qualitative indicators, supported by minor qualitative indicators for countries with limited resource settings and by the overall haemoglobinopathy carrier frequency for the target countries of immigration. The proposed rubrics and accumulative scores will help analyse the performance and improvement of care, treatment, and prevention of haemoglobinopathies in the GGN and beyond. Our proposed criteria complement future data collection from GGN countries to help monitor the quality of services for haemoglobinopathies, provide ongoing estimates for services and epidemiology in GGN countries, and note the contribution of the GGN to a local and global reduction of disease burden.

Evaluation of in silico predictors on short nucleotide variants in HBA1, HBA2, and HBB associated with haemoglobinopathies

Haemoglobinopathies are the commonest monogenic diseases worldwide and are caused by variants in the globin gene clusters. With over 2400 variants detected to date, their interpretation using the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) guidelines is challenging and computational evidence can provide valuable input about their functional annotation. While many in silico predictors have already been developed, their performance varies for different genes and diseases. In this study, we evaluate 31 in silico predictors using a dataset of 1627 variants in HBA1, HBA2, and HBB. By varying the decision threshold for each tool, we analyse their performance (a) as binary classifiers of pathogenicity and (b) by using different non-overlapping pathogenic and benign thresholds for their optimal use in the ACMG/AMP framework. Our results show that CADD, Eigen-PC, and REVEL are the overall top performers, with the former reaching moderate strength level for pathogenic prediction. Eigen-PC and REVEL achieve the highest accuracies for missense variants, while CADD is also a reliable predictor of non-missense variants. Moreover, SpliceAI is the top performing splicing predictor, reaching strong level of evidence, while GERP++ and phyloP are the most accurate conservation tools. This study provides evidence about the optimal use of computational tools in globin gene clusters under the ACMG/AMP framework.