Identification of Misclassified ClinVar Variants via Disease Population Prevalence

Development of multiplexed orthogonal base editor (MOBE) systems

Base editors (BEs) enable efficient, programmable installation of point mutations while avoiding the use of double-strand breaks. Simultaneous application of two or more different BEs, such as an adenine BE (which converts A·T base pairs to G·C) and a cytosine BE (which converts C·G base pairs to T·A), is not feasible because guide RNA crosstalk results in non-orthogonal editing, with all BEs modifying all target loci. Here we engineer both adenine BEs and cytosine BEs that can be orthogonally multiplexed by using RNA aptamer-coat protein systems to recruit the DNA-modifying enzymes directly to the guide RNAs. We generate four multiplexed orthogonal BE systems that enable rates of precise co-occurring edits of up to 7.1% in the same DNA strand without enrichment or selection strategies. The addition of a fluorescent enrichment strategy increases co-occurring edit rates up to 24.8% in human cells. These systems are compatible with expanded protospacer adjacent motif and high-fidelity Cas9 variants, function well in multiple cell types, have equivalent or reduced off-target propensities compared with their parental systems and can model disease-relevant point mutation combinations.

Clinical Features of Brugada Syndrome Patients With SCN5A Variants

BACKGROUND

SCN5A is the most common susceptibility gene in patients with Brugada syndrome (BrS); however, the interpretation and management of benign or variants of unknown clinical significance (VUS) in SCN5A remains a challenge despite the availability of genetic testing.

OBJECTIVE

This study aimed to investigate the relationship between the SCN5A variants and clinical symptoms of BrS patients.

METHODS

We resequenced the SCN5A gene in 239 patients diagnosed with BrS at Hiroshima University Hospital and analyzed the association between the SCN5A variants and clinical features, 12-lead electrocardiography (ECG) parameters, and signal-averaged ECG.

RESULTS

Overall, 84 SCN5A variants were identified: 55 benign, 7 pathogenic, and 22 VUS. No significant difference in the incidence of previous cardiac events was observed between patients with and without SCA5A benign variants. The female proportion was higher in BrS patients with SCN5A VUS or pathogenic variants. Moreover, the symptomatic proportion was higher in BrS patients with SCN5A VUS or pathogenic variants than in those without SCN5A variants. Multivariate analyses revealed that the presence of SCN5A pathogenic variants, longer r-J intervals in lead V1, and the presence of fragmented QRS were independently associated with cardiac events in BrS patients, and that positive late potentials, longer LAS40, and lower RMS40 were significantly associated with symptomatic BrS in patients carrying SCN5A VUS.

CONCLUSIONS

SCN5A pathogenic variants were found to be independent risk factors for cardiac events in BrS patients. Although SCN5A VUS was not an independent risk factor for cardiac events, proportion of symptomatic patients was higher in BrS patients with SCN5A VUS than in those without SCN5A variants. In BrS patients with SCN5A VUS, the signal-averaged ECG was the key to the risk stratification for cardiac events.

Insights for variant clinical interpretation based on a benchmark of 65 variant effect predictors

Single amino acid substitutions in protein sequences are generally harmless, but a certain number of these changes can lead to disease. Accurately predicting the effect of genetic variants is crucial for clinicians as it accelerates the diagnosis of patients with missense variants associated with health problems. Many computational tools have been developed to predict the pathogenicity of genetic variants with various approaches. Analysing the performance of these different computational tools is crucial to provide guidance to both future users and especially clinicians. In this study, a large-scale investigation of 65 tools was conducted. Variants from both clinical and functional contexts were used, incorporating data from the ClinVar database and bibliographic sources. The analysis showed that AlphaMissense often performed very well and was in fact one of the best options among the existing tools. In addition, as expected, meta-predictors perform well on average. Tools using evolutionary information showed the best performance for functional variants. These results also highlighted some heterogeneity in the difficulty of predicting some specific variants while others are always well categorized. Strikingly, the majority of variants from the ClinVar database appear to be easy to predict, while variants from other sources of data are more challenging. This raises questions about the use of ClinVar and the dataset used to validate tools accuracy. In addition, these results show that this variant predictability can be divided into three distinct classes: easy, moderate and hard to predict. We analyzed the parameters leading to these differences and showed that the classes are related to structural and functional information.

Uncovering ASO-Targetable Deep Intronic AIRE Variants: Insights and Therapeutic Implications

High-throughput DNA sequencing has accelerated the discovery of disease-causing genetic variants, yet only in 10-40% of cases yield a genetic diagnosis. Increased implementation of genome sequencing has enabled a deeper exploration of the noncoding genome and recognition of noncoding variants as major contributors to disease. In a recent study, we identified a deep intronic variant in the AutoImmune REgulator (AIRE) gene (c.1504-818 G>A) as the cause of autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED), a life-threatening monogenic autoimmune disorder most often caused by biallelic AIRE defects. This deep intronic variant disrupts normal splicing AIRE , causing pseudoexon inclusion and altered protein function. By developing an antisense oligonucleotide (ASO) targeting the pseudoexon sequence, we restored normal AIRE transcript in vitro, thereby revealing a potential genotype-specific candidate treatment. Our study illustrates key aspects of intronic variant detection, validation, and candidate ASO development. Herein, we briefly highlight the growing potential of ASO-based therapies for deep intronic variants, addressing the unmet need of personalized, genotype-specific therapies in diseases lacking curative options.

Ensemble and consensus approaches to prediction of recessive inheritance for missense variants in human disease

Mode of inheritance (MOI) is necessary for clinical interpretation of pathogenic variants; however, the majority of variants lack this information. Furthermore, variant effect predictors are fundamentally insensitive to recessive-acting diseases. Here, we present MOI-Pred, a variant pathogenicity prediction tool that accounts for MOI, and ConMOI, a consensus method that integrates variant MOI predictions from three independent tools. MOI-Pred integrates evolutionary and functional annotations to produce variant-level predictions that are sensitive to both dominant-acting and recessive-acting pathogenic variants. Both MOI-Pred and ConMOI show state-of-the-art performance on standard benchmarks. Importantly, dominant and recessive predictions from both tools are enriched in individuals with pathogenic variants for dominant- and recessive-acting diseases, respectively, in a real-world electronic health record (EHR)-based validation approach of 29,981 individuals. ConMOI outperforms its component methods in benchmarking and validation, demonstrating the value of consensus among multiple prediction methods. Predictions for all possible missense variants are provided in the "Data and code availability" section.

Genetic disease risks of under-represented founder populations in New York City

The detection of founder pathogenic variants, those observed in high frequency only in a group of individuals with increased inter-relatedness, can help improve delivery of health care for that community. We identified 16 groups with shared ancestry, based on genomic segments that are shared through identity by descent (IBD), in New York City using the genomic data of 25,366 residents from the All Of Us Research Program and the Mount Sinai BioMe biobank. From these groups we defined 8 as founder populations, mostly communities currently under-represented in medical genomics research, such as Puerto Rican, Garifuna and Filipino/Pacific Islanders. The enrichment analysis of ClinVar pathogenic or likely pathogenic (P/LP) variants in each group identified 202 of these damaging variants across the 8 founder populations. We confirmed disease-causing variants previously reported to occur at increased frequencies in Ashkenazi Jewish and Puerto Rican genetic ancestry groups, but most of the damaging variants identified have not been previously associated with any such founder populations, and most of these founder populations have not been described to have increased prevalence of the associated rare disease. Twenty-five of 51 variants meeting Tier 2 clinical screening criteria (1/100 carrier frequency within these founder groups) have never previously been reported. We show how population structure studies can provide insights into rare diseases disproportionately affecting under-represented founder populations, delivering a health care benefit but also a potential source of stigmatization of these communities, who should be part of the decision-making about implementation into health care delivery.

Guidance for estimating penetrance of monogenic disease-causing variants in population cohorts

Penetrance is the probability that an individual with a pathogenic genetic variant develops a specific disease. Knowing the penetrance of variants for monogenic disorders is important for counseling of individuals. Until recently, estimates of penetrance have largely relied on affected individuals and their at-risk family members being clinically referred for genetic testing, a 'phenotype-first' approach. This approach substantially overestimates the penetrance of variants because of ascertainment bias. The recent availability of whole-genome sequencing data in individuals from very-large-scale population-based cohorts now allows 'genotype-first' estimates of penetrance for many conditions. Although this type of population-based study can underestimate penetrance owing to recruitment biases, it provides more accurate estimates of penetrance for secondary or incidental findings. Here, we provide guidance for the conduct of penetrance studies to ensure that robust genotypes and phenotypes are used to accurately estimate penetrance of variants and groups of similarly annotated variants from population-based studies.

Estimating cancer risk in carriers of Lynch syndrome variants in UK Biobank

BackgroundLynch syndrome (LS) is an inherited cancer predisposition syndrome caused by genetic variants affecting DNA mismatch repair (MMR) genes MLH1, MSH2, MSH6 and PMS2 Cancer risk in LS is estimated from cohorts of individuals ascertained by individual or family history of cancer, which may upwardly bias estimates.

METHODS

830 carriers of pathogenic or likely pathogenic (path_MMR) MMR gene variants classified by InSiGHT were identified in 454 756 UK Biobank (UKB) participants using whole-exome sequence. Nelson-Aalen survival analysis was used to estimate cumulative incidence of colorectal, endometrial and breast cancer (BC).

RESULTS

Cumulative incidence of colorectal and endometrial cancer (EC) by age 70 years was elevated in path_MMR carriers compared with non-carriers (colorectal: 11.8% (95% confidence interval (CI): 9.5% to 14.6%) vs 1.7% (95% CI: 1.6% to 1.7%), endometrial: 13.4% (95% CI: 10.2% to 17.6%) vs 1.0% (95% CI: 0.9% to 1.0%)), but the magnitude of this increase differed between genes. Cumulative BC incidence by age 70 years was not elevated in path_MMR carriers compared with non-carriers (8.9% (95% CI: 6.3% to 12.4%) vs 7.5% (95% CI: 7.4% to 7.6%)). Cumulative cancer incidence estimates in UKB were similar to estimates from the Prospective Lynch Syndrome Database for all genes and cancers, except there was no evidence for elevated EC risk in carriers of pathogenic PMS2 variants in UKB.

CONCLUSION

These results support offering incidentally identified carriers of any path_MMR surveillance to manage colorectal cancer risk. Incidentally identified carriers of pathogenic variants in MLH1, MSH2 and MSH6 would also benefit from interventions to reduce EC risk. The results suggest that BC is not an LS-related cancer.

Two Japanese families with familial pancreatic cancer with suspected pathogenic variants of CDKN2A: a case report

BACKGROUND

Germline mutations in CDKN2A result in Familial Atypical Multiple Mole Melanoma Syndrome (FAMMM) (OMIM #155,601), which is associated with an increased risk of pancreatic ductal adenocarcinoma and melanoma. FAMMM has been reported globally, but it is quite rare in Japan. We report two families with familial pancreatic cancer with suspected pathogenic variants of CDKN2A that were incidentally identified through comprehensive genomic profiling.

CASE PRESENTATION

The first case is a 74-year-old woman with a diagnosis of pancreatic carcinoma with multiple liver metastases. She had family histories of pancreatic cancer, but no personal or family history of malignant melanoma. Whole exon sequencing detected a germline CDKN2A variant evaluated as likely pathogenic. The results were disclosed to her daughters after she died, and the same CDKN2A variant was detected in one of the daughter. The daughter was referred to a nearby hospital for her clinical management. The second case is a 65-year-old man with pancreatic ductal adenocarcinoma. He had family histories of pancreatic cancer, but no personal or family history of malignant melanoma. He underwent a comprehensive genomic profiling test using pancreatic cancer tissue, and detected a presumed germline pathogenic variant of CDKN2A. Germline testing confirmed the same CDKN2A variant. Genetic analysis of his relatives produced negative results. Other blood relatives are scheduled for genetic analysis in the future. We report two families with familial pancreatic cancer with suspected pathogenic variants of CDKN2A that were incidentally identified through comprehensive genomic profiling.

CONCLUSIONS

In current Japanese precision medicine, comprehensive genetic analysis can reveal rare genetic syndromes and offer us the opportunity to provide health management for patients and their relatives. However, gene-specific issues are raised in terms of the evaluation of a variant's pathogenicity and the extent of surveillance of the at-risk organs due to a lack of genetic and clinical data concerning CDKN2A variant carriers in Japan.

Variant Effect Prediction in the Age of Machine Learning

Over the years, many computational methods have been created for the analysis of the impact of single amino acid substitutions resulting from single-nucleotide variants in genome coding regions. Historically, all methods have been supervised and thus limited by the inadequate sizes of experimentally curated data sets and by the lack of a standardized definition of variant effect. The emergence of unsupervised, deep learning (DL)-based methods raised an important question: Can machines learn the language of life from the unannotated protein sequence data well enough to identify significant errors in the protein "sentences"? Our analysis suggests that some unsupervised methods perform as well or better than existing supervised methods. Unsupervised methods are also faster and can, thus, be useful in large-scale variant evaluations. For all other methods, however, their performance varies by both evaluation metrics and by the type of variant effect being predicted. We also note that the evaluation of method performance is still lacking on less-studied, nonhuman proteins where unsupervised methods hold the most promise.

SwissGenVar: A Platform for Clinical-Grade Interpretation of Genetic Variants to Foster Personalized Healthcare in Switzerland

Large-scale next-generation sequencing (NGS) germline testing is technically feasible today, but variant interpretation represents a major bottleneck in analysis workflows. This includes extensive variant prioritization, annotation, and time-consuming evidence curation. The scale of the interpretation problem is massive, and variants of uncertain significance (VUSs) are a challenge to personalized medicine. This challenge is further compounded by the complexity and heterogeneity of the standards used to describe genetic variants and the associated phenotypes when searching for relevant information to support clinical decision making. To address this, all five Swiss academic institutions for Medical Genetics joined forces with the Swiss Institute of Bioinformatics (SIB) to create SwissGenVar as a user-friendly nationwide repository and sharing platform for genetic variant data generated during routine diagnostic procedures and research sequencing projects. Its aim is to provide a protected environment for expert evidence sharing about individual variants to harmonize and upscale their significance interpretation at the clinical grade according to international standards. To corroborate the clinical assessment, the variant-related data will be combined with consented high-quality clinical information. Broader visibility will be achieved by interfacing with international databases, thus supporting global initiatives in personalized healthcare.

Underrepresentation of Diverse Ancestries Drives Uncertainty in Genetic Variants Found in Cardiomyopathy-Associated Genes

BACKGROUND

Thousands of genetic variants have been identified in cardiomyopathy-associated genes. Diagnostic genetic testing is key for evaluation of individuals with suspected cardiomyopathy. While accurate variant pathogenicity assignment is important for diagnosis, the frequency of and factors associated with clinically relevant assessment changes are unclear.

OBJECTIVES

The authors aimed to characterize pathogenicity assignment change in cardiomyopathy-associated genes and to identify factors associated with this change.

METHODS

We identified 10 sarcomeric and 6 desmosomal genetic cardiomyopathy-associated genes along with comparison gene sets. We analyzed clinically meaningful changes in pathogenicity assignment between any of the following: pathogenic/likely pathogenic (P/LP), conflicting interpretations of pathogenicity or variant of unknown significance (C/VUS), and benign/likely benign. We explored association of minor allele frequency (MAF) differences between well, and traditionally poorly, represented ancestries in genetic studies with assessment stability. Analyses were performed using ClinVar and GnomAD data.

RESULTS

Of the 30,975 cardiomyopathy-associated gene variants in ClinVar, 2,276 of them (7.3%) had a clinically meaningful change in pathogenicity assignment over the study period, 2011 to 2021. Sixty-seven percent of variants that underwent a clinically significant change moved from P/LP or benign/likely benign to C/VUS. Among cardiomyopathy variants downgraded from P/LP, 35% had a MAF above 1 × 10 -4 in non-Europeans and below 1 × 10 -4 in Europeans.

CONCLUSIONS

Over the past 10 years, 7.3% of cardiomyopathy gene variants underwent a clinically meaningful change in pathogenicity assignment. Over 30% of downgrades from P/LP may be attributable to higher MAF in Non-Europeans than Europeans. This finding suggests that low ancestral diversity in genetic studies has increased diagnostic uncertainty in cardiomyopathy gene variants.

Genetics and Pathogenesis of Dystonia

Dystonia is a clinically and genetically highly heterogeneous neurological disorder characterized by abnormal movements and postures caused by involuntary sustained or intermittent muscle contractions. A number of groundbreaking genetic and molecular insights have recently been gained. While they enable genetic testing and counseling, their translation into new therapies is still limited. However, we are beginning to understand shared pathophysiological pathways and molecular mechanisms. It has become clear that dystonia results from a dysfunctional network involving the basal ganglia, cerebellum, thalamus, and cortex. On the molecular level, more than a handful of, often intertwined, pathways have been linked to pathogenic variants in dystonia genes, including gene transcription during neurodevelopment (e.g., KMT2B, THAP1), calcium homeostasis (e.g., ANO3, HPCA), striatal dopamine signaling (e.g., GNAL), endoplasmic reticulum stress response (e.g., EIF2AK2, PRKRA, TOR1A), autophagy (e.g., VPS16), and others. Thus, different forms of dystonia can be molecularly grouped, which may facilitate treatment development in the future.

Evaluating the association of biallelic OGDHL variants with significant phenotypic heterogeneity

BACKGROUND

Biallelic variants in OGDHL, encoding part of the α-ketoglutarate dehydrogenase complex, have been associated with highly heterogeneous neurological and neurodevelopmental disorders. However, the validity of this association remains to be confirmed. A second OGDHL patient cohort was recruited to carefully assess the gene-disease relationship.

METHODS

Using an unbiased genotype-first approach, we screened large, multiethnic aggregated sequencing datasets worldwide for biallelic OGDHL variants. We used CRISPR/Cas9 to generate zebrafish knockouts of ogdhl, ogdh paralogs, and dhtkd1 to investigate functional relationships and impact during development. Functional complementation with patient variant transcripts was conducted to systematically assess protein functionality as a readout for pathogenicity.

RESULTS

A cohort of 14 individuals from 12 unrelated families exhibited highly variable clinical phenotypes, with the majority of them presenting at least one additional variant, potentially accounting for a blended phenotype and complicating phenotypic understanding. We also uncovered extreme clinical heterogeneity and high allele frequencies, occasionally incompatible with a fully penetrant recessive disorder. Human cDNA of previously described and new variants were tested in an ogdhl zebrafish knockout model, adding functional evidence for variant reclassification. We disclosed evidence of hypomorphic alleles as well as a loss-of-function variant without deleterious effects in zebrafish variant testing also showing discordant familial segregation, challenging the relationship of OGDHL as a conventional Mendelian gene. Going further, we uncovered evidence for a complex compensatory relationship among OGDH, OGDHL, and DHTKD1 isoenzymes that are associated with neurodevelopmental disorders and exhibit complex transcriptional compensation patterns with partial functional redundancy.

CONCLUSIONS

Based on the results of genetic, clinical, and functional studies, we formed three hypotheses in which to frame observations: biallelic OGDHL variants lead to a highly variable monogenic disorder, variants in OGDHL are following a complex pattern of inheritance, or they may not be causative at all. Our study further highlights the continuing challenges of assessing the validity of reported disease-gene associations and effects of variants identified in these genes. This is particularly more complicated in making genetic diagnoses based on identification of variants in genes presenting a highly heterogenous phenotype such as "OGDHL-related disorders".

Is there a duty to routinely reinterpret genomic variant classifications?

Multiple studies show that periodic reanalysis of genomic test results held by clinical laboratories delivers significant increases in overall diagnostic yield. However, while there is a widespread consensus that implementing routine reanalysis procedures is highly desirable, there is an equally widespread understanding that routine reanalysis of individual patient results is not presently feasible to perform for all patients. Instead, researchers, geneticists and ethicists are beginning to turn their attention to one part of reanalysis-reinterpretation of previously classified variants-as a means of achieving similar ends to large-scale individual reanalysis but in a more sustainable manner. This has led some to ask whether the responsible implementation of genomics in healthcare requires that diagnostic laboratories routinely reinterpret their genomic variant classifications and reissue patient reports in the case of materially relevant changes. In this paper, we set out the nature and scope of any such obligation, and analyse some of the main ethical considerations pertaining to a putative duty to reinterpret. We discern and assess three potential outcomes of reinterpretation-upgrades, downgrades and regrades-in light of ongoing duties of care, systemic error risks and diagnostic equity. We argue against the existence of any general duty to reinterpret genomic variant classifications, yet we contend that a suitably restricted duty to reinterpret ought to be recognised, and that the responsible implementation of genomics into healthcare must take this into account.

A curated census of pathogenic and likely pathogenic UTR variants and evaluation of deep learning models for variant effect prediction

Introduction: Variants in 5' and 3' untranslated regions (UTR) contribute to rare disease. While predictive algorithms to assist in classifying pathogenicity can potentially be highly valuable, the utility of these tools is often unclear, as it depends on carefully selected training and validation conditions. To address this, we developed a high confidence set of pathogenic (P) and likely pathogenic (LP) variants and assessed deep learning (DL) models for predicting their molecular effects. Methods: 3' and 5' UTR variants documented as P or LP (P/LP) were obtained from ClinVar and refined by reviewing the annotated variant effect and reassessing evidence of pathogenicity following published guidelines. Prediction scores from sequence-based DL models were compared between three groups: P/LP variants acting though the mechanism for which the model was designed (model-matched), those operating through other mechanisms (model-mismatched), and putative benign variants. PhyloP was used to compare conservation scores between P/LP and putative benign variants. Results: 295 3' and 188 5' UTR variants were obtained from ClinVar, of which 26 3' and 68 5' UTR variants were classified as P/LP. Predictions by DL models achieved statistically significant differences when comparing modelmatched P/LP variants to both putative benign variants and modelmismatched P/LP variants, as well as when comparing all P/LP variants to putative benign variants. PhyloP conservation scores were significantly higher among P/LP compared to putative benign variants for both the 3' and 5' UTR. Discussion: In conclusion, we present a high-confidence set of P/LP 3' and 5' UTR variants spanning a range of mechanisms and supported by detailed pathogenicity and molecular mechanism evidence curation. Predictions from DL models further substantiate these classifications. These datasets will support further development and validation of DL algorithms designed to predict the functional impact of variants that may be implicated in rare disease.

Clinical risk management of breast, ovarian, pancreatic, and prostatic cancers for BRCA1/2 variant carriers in Japan

Opportunities for genetic counseling and germline BRCA1/2 (BRCA) testing are increasing in Japan owing to cancer genomic profiling testing and companion diagnostics being covered by national health insurance for patients with BRCA-related cancers. These tests are useful not only to judge whether platinum agents and PARP inhibitors are indicated but also to reveal an autosomal-dominant inherited cancer syndrome: hereditary breast and ovarian cancer. In individuals with germline BRCA variants, risk of cancers of the breast, ovary, pancreas, and prostate is significantly increased at various ages of onset, but the stomach, uterus, biliary tract, and skin might also be at risk. For women with pathogenic BRCA variants, breast awareness and image analyses should be initiated in their 20s, and risk-reducing procedures such as mastectomy are recommended starting in their 30s, with salpingo-oophorectomy in their late 30s. For male BRCA pathogenic variant carriers, prostatic surveillance should be applied using serum prostate-specific antigen starting in their 40s. For both sexes, image examinations ideally using endoscopic ultrasound and magnetic resonance cholangiopancreatography and blood testing should begin in their 50s for pancreatic surveillance. Homologous recombination pathway-associated genes are also causative candidates. Variant pathogenicity needs to be evaluated every 6-12 months when results are uncertain for clinical significance. Genetic counseling needs to be offered to the blood relatives of the pathogenic variant carriers with suitable timing. We review the recommended cross-organ BRCA risk management in Japan.

In vivo versus in silico assessment of potentially pathogenic missense variants in human reproductive genes

Infertility is a heterogeneous condition, with genetic causes thought to underlie a substantial fraction of cases. Genome sequencing is becoming increasingly important for genetic diagnosis of diseases including idiopathic infertility; however, most rare or minor alleles identified in patients are variants of uncertain significance (VUS). Interpreting the functional impacts of VUS is challenging but profoundly important for clinical management and genetic counseling. To determine the consequences of these variants in key fertility genes, we functionally evaluated 11 missense variants in the genes ANKRD31, BRDT, DMC1, EXO1, FKBP6, MCM9, M1AP, MEI1, MSH4 and SEPT12 by generating genome-edited mouse models. Nine variants were classified as deleterious by most functional prediction algorithms, and two disrupted a protein-protein interaction (PPI) in the yeast two hybrid (Y2H) assay. Though these genes are essential for normal meiosis or spermiogenesis in mice, only one variant, observed in the MCM9 gene of a male infertility patient, compromised fertility or gametogenesis in the mouse models. To explore the disconnect between predictions and outcomes, we compared pathogenicity calls of missense variants made by ten widely used algorithms to 1) those annotated in ClinVar and 2) those evaluated in mice. All the algorithms performed poorly in terms of predicting the effects of human missense variants modeled in mice. These studies emphasize caution in the genetic diagnoses of infertile patients based primarily on pathogenicity prediction algorithms and emphasize the need for alternative and efficient in vitro or in vivo functional validation models for more effective and accurate VUS description to either pathogenic or benign categories.

ClinVar and HGMD genomic variant classification accuracy has improved over time, as measured by implied disease burden

BACKGROUND

Curated databases of genetic variants assist clinicians and researchers in interpreting genetic variation. Yet, these databases contain some misclassified variants. It is unclear whether variant misclassification is abating as these databases rapidly grow and implement new guidelines.

METHODS

Using archives of ClinVar and HGMD, we investigated how variant misclassification has changed over 6 years, across different ancestry groups. We considered inborn errors of metabolism (IEMs) screened in newborns as a model system because these disorders are often highly penetrant with neonatal phenotypes. We used samples from the 1000 Genomes Project (1KGP) to identify individuals with genotypes that were classified by the databases as pathogenic. Due to the rarity of IEMs, nearly all such classified pathogenic genotypes indicate likely variant misclassification in ClinVar or HGMD.

RESULTS

While the false-positive rates of both ClinVar and HGMD have improved over time, HGMD variants currently imply two orders of magnitude more affected individuals in 1KGP than ClinVar variants. We observed that African ancestry individuals have a significantly increased chance of being incorrectly indicated to be affected by a screened IEM when HGMD variants are used. However, this bias affecting genomes of African ancestry was no longer significant once common variants were removed in accordance with recent variant classification guidelines. We discovered that ClinVar variants classified as Pathogenic or Likely Pathogenic are reclassified sixfold more often than DM or DM? variants in HGMD, which has likely resulted in ClinVar's lower false-positive rate.

CONCLUSIONS

Considering misclassified variants that have since been reclassified reveals our increasing understanding of rare genetic variation. We found that variant classification guidelines and allele frequency databases comprising genetically diverse samples are important factors in reclassification. We also discovered that ClinVar variants common in European and South Asian individuals were more likely to be reclassified to a lower confidence category, perhaps due to an increased chance of these variants being classified by multiple submitters. We discuss features for variant classification databases that would support their continued improvement.

Rare penetrant mutations confer severe risk of common diseases

We examined 454,712 exomes for genes associated with a wide spectrum of complex traits and common diseases and observed that rare, penetrant mutations in genes implicated by genome-wide association studies confer ~10-fold larger effects than common variants in the same genes. Consequently, an individual at the phenotypic extreme and at the greatest risk for severe, early-onset disease is better identified by a few rare penetrant variants than by the collective action of many common variants with weak effects. By combining rare variants across phenotype-associated genes into a unified genetic risk model, we demonstrate superior portability across diverse global populations compared with common-variant polygenic risk scores, greatly improving the clinical utility of genetic-based risk prediction.

The landscape of tolerated genetic variation in humans and primates

Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole-genome sequencing data for 809 individuals from 233 primate species and identified 4.3 million common protein-altering variants with orthologs in humans. We show that these variants can be inferred to have nondeleterious effects in humans based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases.

Rare penetrant mutations confer severe risk of common diseases

We examined 454,712 exomes for genes associated with a wide spectrum of complex traits and common diseases and observed that rare, penetrant mutations in genes implicated by genome-wide association studies confer ∼10-fold larger effects than common variants in the same genes. Consequently, an individual at the phenotypic extreme and at the greatest risk for severe, early-onset disease is better identified by a few rare penetrant variants than by the collective action of many common variants with weak effects. By combining rare variants across phenotype-associated genes into a unified genetic risk model, we demonstrate superior portability across diverse global populations compared to common variant polygenic risk scores, greatly improving the clinical utility of genetic-based risk prediction.

One sentence summary

Rare variant polygenic risk scores identify individuals with outlier phenotypes in common human diseases and complex traits.

The landscape of tolerated genetic variation in humans and primates

Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole genome sequencing data for 809 individuals from 233 primate species, and identified 4.3 million common protein-altering variants with orthologs in human. We show that these variants can be inferred to have non-deleterious effects in human based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases.

One Sentence Summary

Deep learning classifier trained on 4.3 million common primate missense variants predicts variant pathogenicity in humans.

Hemizygosity can reveal variant pathogenicity on the X-chromosome

Pathogenic variants on the X-chromosome can have more severe consequences for hemizygous males, while heterozygote females can avoid severe consequences due to diploidy and the capacity for nonrandom expression. Thus, when an allele is more common in females this could indicate that it increases the probability of early death in the male hemizygous state, which can be considered a measure of pathogenicity. Importantly, large-scale genomic data now makes it possible to compare allele proportions between the sexes. To discover pathogenic variants on the X-chromosome, we analyzed exome data from 125,748 ancestrally diverse participants in the Genome Aggregation Database (gnomAD). After filtering out duplicates and extremely rare variants, 44,606 of the original 348,221 remained for analysis. We divided the proportion of variant alleles in females by the proportion in males for all variant sites, and then placed each variant into one of three a priori categories: (1) Reference (Primarily synonymous and intronic), (2) Unlikely-to-be-tolerated (Primarily missense), and (3) Least-likely-to-be-tolerated (Primarily frameshift). To assess the impact of ploidy, we compared the distribution of these ratios between pseudoautosomal and non-pseudoautosomal regions. In the non-pseudoautosomal regions, mean female-to-male ratios were lowest among Reference (2.40), greater for Unlikely-to-be-tolerated (2.77) and highest for Least-likely-to-be-tolerated (3.28) variants. Corresponding ratios were lower in the pseudoautosomal regions (1.52, 1.57, and 1.68, respectively), with the most extreme ratio being just below 11. Because pathogenic effects in the pseudoautosomal regions should not drive ratio increases, this maximum ratio provides an upper bound for baseline noise. In the non-pseudoautosomal regions, 319 variants had a ratio over 11. In sum, we identified a measure with a dataset specific threshold for identifying pathogenicity in non-pseudoautosomal X-chromosome variants: the female-to-male allele proportion ratio.

Comprehensive interpretation of single-nucleotide substitutions in GJB2 reveals the genetic and phenotypic landscape of GJB2-related hearing loss

Genetic variants in GJB2 are the most frequent cause of congenital and childhood hearing loss worldwide. The purpose of this study was to delineate the genetic and phenotypic landscape of GJB2 SNV variants. All possible single-nucleotide substitution variants of the coding region of GJB2 (N = 2043) were manually curated following the ACMG/AMP hearing loss guidelines. As a result, 60 (2.9%), 177 (8.7%), 1499 (73.4%), 301 (14.7%) and 6 (0.3%) of the variants were classified as pathogenic, likely pathogenic, variant of uncertain significance, likely benign, and benign, respectively. 53% (84/158) of the pathogenic/likely pathogenic missense variants were not present in ClinVar. The second transmembrane domain and the 3₁₀ helix were highly enriched for pathogenic missense variants, while the intracellular loops were tolerant to variation. The N-terminal tail and the extracellular loop showed high clustering of variants that are associated with syndromic or dominant non-syndromic hearing loss. In conclusion, our study interpreted all possible single-nucleotide substitution coding variants, characterized novel clinically significant variants in GJB2, and revealed significant genotype-phenotype correlations at this common hearing loss locus. Our work provides a prototype for other genes with similarly high genetic and phenotypic heterogeneity.

Using gene panels in the diagnosis of neuromuscular disorders: A mini-review

The diagnosis of inherited neuromuscular disorders is challenging due to their genetic and phenotypic variability. Traditionally, neurophysiology and histopathology were primarily used in the initial diagnostic approach to these conditions. Sanger sequencing for molecular diagnosis was less frequently utilized as its application was a time-consuming and cost-intensive process. The advent and accessibility of next-generation sequencing (NGS) has revolutionized the evaluation process of genetically heterogenous neuromuscular disorders. Current NGS diagnostic testing approaches include gene panels, whole exome sequencing (WES), and whole genome sequencing (WGS). Gene panels are often the most widely used, being more accessible due to availability and affordability. In this mini-review, we describe the benefits and risks of clinical genetic testing. We also discuss the utility, benefits, challenges, and limitations of using gene panels in the evaluation of neuromuscular disorders.

Approach to genetic testing to optimize the safety of living donor transplantation in Alport syndrome spectrum

Alport syndrome spectrum can be considered as a group of genetic diseases affecting the major basement membrane collagen type IV network in various organs including the ear, eye, and kidney. The living donor candidate evaluation is an ever-changing landscape. Recently, next-generation sequence (NGS) panels have become readily available and provide opportunities to genetically screen recipient and donor candidates for collagen network gene variants. In this review, our aim is to provide a comprehensive update on the role of genetic testing for the evaluation of potential living kidney donors to kidney candidates with Alport syndrome spectrum. We examine the utility of genetic testing in the evaluation of potential donors for recipients with Alport syndrome spectrum, and discuss risks and unresolved challenges. Suggested algorithms in the context of related and unrelated donation are offered. In contemporary practice, an approach to the evaluation of living donor candidates for transplant candidates with Alport syndrome spectrum can incorporate genetic testing in algorithms tailored for donor-recipient relationship status. Ongoing research is needed to inform optimal practice.

Genomic testing in premature ovarian insufficiency: proceed with caution

Genomic testing has potential to transform outcomes for women with infertility conditions, such as premature ovarian insufficiency (POI), with growing calls for widespread diagnostic use. The current research literature, however, often uses poor variant curation leading to inflated diagnostic claims and fails to address the complexities of genomic testing for this condition. Without careful execution of the transition from research to the clinic, there is danger of inaccurate diagnoses and poor appreciation of broader implications of testing. This Forum outlines the benefits of genomic testing for POI and raises often-overlooked concerns.

Increasing African genomic data generation and sharing to resolve rare and undiagnosed diseases in Africa: a call-to-action by the H3Africa rare diseases working group

The rich and diverse genomics of African populations is significantly underrepresented in reference and in disease-associated databases. This renders interpreting the Next Generation Sequencing (NGS) data and reaching a diagnostic more difficult in Africa and for the African diaspora. It increases chances for false positives with variants being misclassified as pathogenic due to their novelty or rarity. We can increase African genomic data by (1) making consent for sharing aggregate frequency data an essential component of research toolkit; (2) encouraging investigators with African data to share available data through public resources such as gnomAD, AVGD, ClinVar, DECIPHER and to use MatchMaker Exchange; (3) educating African research participants on the meaning and value of sharing aggregate frequency data; and (4) increasing funding to scale-up the production of African genomic data that will be more representative of the geographical and ethno-linguistic variation on the continent. The RDWG of H3Africa is hereby calling to action because this underrepresentation accentuates the health disparities. Applying the NGS to shorten the diagnostic odyssey or to guide therapeutic options for rare diseases will fully work for Africans only when public repositories include sufficient data from African subjects.

Pathogenicity Assignment of Variants in Genes Associated With Cardiac Channelopathies Evolve Toward Diagnostic Uncertainty

BACKGROUND

Accurately determining variant pathogenicity is critical in the diagnosis of cardiac channelopathies; however, it remains unknown how variant pathogenicity status changes over time. Our aim is to use a comprehensive analysis of ClinVar to understand the mutability of variant evaluation in channelopathy-associated genes to inform clinical decision-making around variant calling.

METHODS

We identified 10 genes (RYR2, CASQ2, KCNQ1, KCNH2, SCN5A, CACNA1C, CALM1, CALM2, CALM3, TRDN) strongly associated with cardiac channelopathies, as well as 3 comparison gene sets (disputed long QT syndrome, sudden unexpected death in epilepsy, and all ClinVar). We comprehensively analyzed variant pathogenicity calls over time using the ClinVar database with Rstudio. Analyses focused on the frequency and directionality of clinically meaningful changes in disease association, defined as a change from one of the following three categories to another: likely benign/benign, conflicting evidence of pathogenicity/variant of uncertain significance, and likely pathogenic/pathogenic.

RESULTS

In total, among channelopathy-associated genes, there were 9975 variants in ClinVar and 8.4% had a clinically meaningful change in disease association at least once over the past 10 years, as opposed to 4.9% of all ClinVar variants. The 3 channelopathy-associated genes with the most variants undergoing a clinically significant change were KCNQ1 (20.9%), SCN5A (11.2%), and KCNH2 (10.1%). Ten of the 12 included genes had variant evaluations that trended toward diagnostic uncertainty over time. Specifically, channelopathy-associated gene variants with either pathogenic/likely pathogenic or benign/likely benign assignments were 5.6× and 2×, respectively, as likely to be reevaluated to conflicting/variant of uncertain significance compared to the converse.

CONCLUSIONS

Over the past 10 years, 8.4% of variants in channelopathy-associated genes have changed pathogenicity status with a decline in overall diagnostic certainty. Ongoing clinical and genetic variant follow-up is needed to account for presence of clinically meaningful change in variant pathogenicity assignment over time.

Present status of germline findings in precision medicine for Japanese cancer patients: issues in the current system

OBJECTIVE

Since 2019, precision cancer medicine has been covered by national insurance in Japan; however, to date, germline findings have not been fully reported. The aim of this study was to evaluate the current status and raise a problem of germline finding analysis and disclosure in Japanese precision cancer medicine.

METHODS

Germline findings of 52 genes were examined in 296 cases with advanced cancer by a case series study.

RESULTS

Six (2.0%) cases were examined by the Oncoguide™ NCC Oncopanel with germline testing, but no germline findings were reported. The remaining 290 (98.0%) cases were analyzed by FoundationOne® CDx (tumor-only testing), which recognized 404 pathogenic variants; those of BRCA1/2 were recognized in 16 (5.5%) tumors. Our institutional algorithm suggested 39 candidate germline findings in 34 cases, while the public algorithm listed at least 91 candidate germline findings. Four germline findings had been previously identified (BRCA1: 3 and ATM: 1). Nine of 30 cases with candidate germline findings excluding these known germline findings refused or deferred germline testing. Only 4 of 16 cases that received counseling underwent germline testing, and those 4 revealed 3 germline findings (BRCA2, CDK4 and RAD51C); in total, 8 (2.7%) germline findings were revealed. Reasons for refusing genetic counseling and/or germline testing included extra hospital visits, added expense for germline testing due to limited national insurance coverage, poor patient physical condition and no known family members associated with the possible germline finding.

CONCLUSIONS

In current Japanese precision cancer medicine, only a small fraction of the patients undergoes germline testing and demonstrated germline finding. The current results suggested a need for earlier indications for precision cancer medicine, broader insurance coverage and more efficient germline finding prediction algorithms, to increase the number of germline testings and to improve the following managements.

Computational and experimental methods for classifying variants of unknown clinical significance

The increase in sequencing capacity, reduction in costs, and national and international coordinated efforts have led to the widespread introduction of next-generation sequencing (NGS) technologies in patient care. More generally, human genetics and genomic medicine are gaining importance for more and more patients. Some communities are already discussing the prospect of sequencing each individual's genome at time of birth. Together with digital health records, this shall enable individualized treatments and preventive measures, so-called precision medicine. A central step in this process is the identification of disease causal mutations or variant combinations that make us more susceptible for diseases. Although various technological advances have improved the identification of genetic alterations, the interpretation and ranking of the identified variants remains a major challenge. Based on our knowledge of molecular processes or previously identified disease variants, we can identify potentially functional genetic variants and, using different lines of evidence, we are sometimes able to demonstrate their pathogenicity directly. However, the vast majority of variants are classified as variants of uncertain clinical significance (VUSs) with not enough experimental evidence to determine their pathogenicity. In these cases, computational methods may be used to improve the prioritization and an increasing toolbox of experimental methods is emerging that can be used to assay the molecular effects of VUSs. Here, we discuss how computational and experimental methods can be used to create catalogs of variant effects for a variety of molecular and cellular phenotypes. We discuss the prospects of integrating large-scale functional data with machine learning and clinical knowledge for the development of accurate pathogenicity predictions for clinical applications.

Evaluation of Genetic Kidney Diseases in Living Donor Kidney Transplantation: Towards Precision Genomic Medicine in Donor Risk Assessment

Purpose of Review

To provide a comprehensive update on the role of genetic testing for the evaluation of kidney transplant recipient and living donor candidates.

Recent Findings

The evaluation of candidates for living donor transplantation and their potential donors occurs within an ever-changing landscape impacted by new evidence and risk assessment techniques. Criteria that were once considered contraindications to living kidney donation are now viewed as standard of care, while new tools identify novel risk markers that were unrecognized in past decades. Recent work suggests that nearly 10% of a cohort of patients with chronic/end-stage kidney disease had an identifiable genetic etiology, many whose original cause of renal disease was either unknown or misdiagnosed. Some also had an incidentally found genetic variant, unrelated to their nephropathy, but medically actionable. These patterns illustrate the substantial potential for genetic testing to better guide the selection of living donors and recipients, but guidance on the proper application and interpretation of novel technologies is in its infancy. In this review, we examine the utility of genetic testing in various kidney conditions, and discuss risks and unresolved challenges. Suggested algorithms in the context of related and unrelated donation are offered.

Summary

Genetic testing is a rapidly evolving strategy for the evaluation of candidates for living donor transplantation and their potential donors that has potential to improve risk assessment and optimize the safety of donation.

Whole-genome sequencing of 1,171 elderly admixed individuals from São Paulo, Brazil

As whole-genome sequencing (WGS) becomes the gold standard tool for studying population genomics and medical applications, data on diverse non-European and admixed individuals are still scarce. Here, we present a high-coverage WGS dataset of 1,171 highly admixed elderly Brazilians from a census-based cohort, providing over 76 million variants, of which ~2 million are absent from large public databases. WGS enables identification of ~2,000 previously undescribed mobile element insertions without previous description, nearly 5 Mb of genomic segments absent from the human genome reference, and over 140 alleles from HLA genes absent from public resources. We reclassify and curate pathogenicity assertions for nearly four hundred variants in genes associated with dominantly-inherited Mendelian disorders and calculate the incidence for selected recessive disorders, demonstrating the clinical usefulness of the present study. Finally, we observe that whole-genome and HLA imputation could be significantly improved compared to available datasets since rare variation represents the largest proportion of input from WGS. These results demonstrate that even smaller sample sizes of underrepresented populations bring relevant data for genomic studies, especially when exploring analyses allowed only by WGS.

Whole genome sequencing (WGS) data on non-European and admixed individuals remains scarce. Here, the authors analyse WGS data from 1,171 admixed elderly Brazilians from a census cohort, characterising population-specific genetic variation and exploring the clinical utility of this expanded dataset.

StrVCTVRE: A supervised learning method to predict the pathogenicity of human genome structural variants

Whole-genome sequencing resolves many clinical cases where standard diagnostic methods have failed. However, at least half of these cases remain unresolved after whole-genome sequencing. Structural variants (SVs; genomic variants larger than 50 base pairs) of uncertain significance are the genetic cause of a portion of these unresolved cases. As sequencing methods using long or linked reads become more accessible and SV detection algorithms improve, clinicians and researchers are gaining access to thousands of reliable SVs of unknown disease relevance. Methods to predict the pathogenicity of these SVs are required to realize the full diagnostic potential of long-read sequencing. To address this emerging need, we developed StrVCTVRE to distinguish pathogenic SVs from benign SVs that overlap exons. In a random forest classifier, we integrated features that capture gene importance, coding region, conservation, expression, and exon structure. We found that features such as expression and conservation are important but are absent from SV classification guidelines. We leveraged multiple resources to construct a size-matched training set of rare, putatively benign and pathogenic SVs. StrVCTVRE performs accurately across a wide SV size range on independent test sets, which will allow clinicians and researchers to eliminate about half of SVs from consideration while retaining a 90% sensitivity. We anticipate clinicians and researchers will use StrVCTVRE to prioritize SVs in probands where no SV is immediately compelling, empowering deeper investigation into novel SVs to resolve cases and understand new mechanisms of disease. StrVCTVRE runs rapidly and is publicly available.

Population-Based Penetrance of Deleterious Clinical Variants

IMPORTANCE

Population-based assessment of disease risk associated with gene variants informs clinical decisions and risk stratification approaches.

OBJECTIVE

To evaluate the population-based disease risk of clinical variants in known disease predisposition genes.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included 72 434 individuals with 37 780 clinical variants who were enrolled in the BioMe Biobank from 2007 onwards with follow-up until December 2020 and the UK Biobank from 2006 to 2010 with follow-up until June 2020. Participants had linked exome and electronic health record data, were older than 20 years, and were of diverse ancestral backgrounds.

EXPOSURES

Variants previously reported as pathogenic or predicted to cause a loss of protein function by bioinformatic algorithms (pathogenic/loss-of-function variants).

MAIN OUTCOMES AND MEASURES

The primary outcome was the disease risk associated with clinical variants. The risk difference (RD) between the prevalence of disease in individuals with a variant allele (penetrance) vs in individuals with a normal allele was measured.

RESULTS

Among 72 434 study participants, 43 395 were from the UK Biobank (mean [SD] age, 57 [8.0] years; 24 065 [55%] women; 2948 [7%] non-European) and 29 039 were from the BioMe Biobank (mean [SD] age, 56 [16] years; 17 355 [60%] women; 19 663 [68%] non-European). Of 5360 pathogenic/loss-of-function variants, 4795 (89%) were associated with an RD less than or equal to 0.05. Mean penetrance was 6.9% (95% CI, 6.0%-7.8%) for pathogenic variants and 0.85% (95% CI, 0.76%-0.95%) for benign variants reported in ClinVar (difference, 6.0 [95% CI, 5.6-6.4] percentage points), with a median of 0% for both groups due to large numbers of nonpenetrant variants. Penetrance of pathogenic/loss-of-function variants for late-onset diseases was modified by age: mean penetrance was 10.3% (95% CI, 9.0%-11.6%) in individuals 70 years or older and 8.5% (95% CI, 7.9%-9.1%) in individuals 20 years or older (difference, 1.8 [95% CI, 0.40-3.3] percentage points). Penetrance of pathogenic/loss-of-function variants was heterogeneous even in known disease predisposition genes, including BRCA1 (mean [range], 38% [0%-100%]), BRCA2 (mean [range], 38% [0%-100%]), and PALB2 (mean [range], 26% [0%-100%]).

CONCLUSIONS AND RELEVANCE

In 2 large biobank cohorts, the estimated penetrance of pathogenic/loss-of-function variants was variable but generally low. Further research of population-based penetrance is needed to refine variant interpretation and clinical evaluation of individuals with these variant alleles.

Low frequency of treatable pediatric disease alleles in gnomAD: An opportunity for future genomic screening of newborns

Hematopoietic stem cell transplant (HSCT) can prevent progression of several genetic disorders. Although a subset of these disorders are identified on newborn screening panels, others are not identified until irreversible symptoms develop. Genetic testing is an efficient methodology to ascertain pre-symptomatic children, but the penetrance of risk-associated variants in the general population is not well understood. We developed a list of 127 genes associated with disorders treatable with HSCT. We identified likely pathogenic or pathogenic (LP/P) and loss-of-function (LoF) variants in these genes in the Genome Aggregation Database (gnomAD), a dataset containing exome and genome sequencing data from 141,456 healthy adults. Within gnomAD, we identified 59 individuals with a LP/P or LoF variant in 15 genes. Genes were associated with bone marrow failure syndromes, bleeding disorders, primary immunodeficiencies, osteopetrosis, metabolic disorders, and epidermolysis bullosa. In conclusion, few ostensibly healthy adults had genotypes associated with pediatric disorders treatable with HSCTs. Given that most of these disorders do not have biomarkers that could be cheaply and universally assessed on a standard newborn screen, our data suggest that genetic testing may be a complementary approach to traditional newborn screening methodology that has the potential to improve mortality and is not expected to lead to a high burden of false-positive results.

Challenges in variant interpretation in prenatal exome sequencing

The use of exome sequencing (ES) in the prenatal setting improves the diagnostic yield of genetic testing for fetuses with ultrasound anomalies. However, while the purpose of ES is to explain the fetal phenotype, secondary or incidental findings unrelated to the observed abnormalities might be detected. Recently, requests for ES in fetuses with no sonographic abnormalities have been increasing, raising serious ethical and medico-legal concerns. Variant interpretation is complex even in the postnatal setting and performing broad genomic data analyses in the prenatal setting presents additional dilemmas. This article discusses challenges and questions related to prenatal ES, including variant interpretation of incidental findings in cases of indicated prenatal ES, as well as in situations where ES is performed in asymptomatic fetuses.

VIP-HL: Semi-automated ACMG/AMP variant interpretation platform for genetic hearing loss

The American College of Medical Genetics and Genomics, and the Association for Molecular Pathology (ACMG/AMP) have proposed a set of evidence-based guidelines to support sequence variant interpretation. The ClinGen hearing loss expert panel (HL-EP) introduced further specifications into the ACMG/AMP framework for genetic hearing loss. This study developed a tool named Variant Interpretation Platform for genetic Hearing Loss (VIP-HL), aiming to semi-automate the HL ACMG/AMP rules. VIP-HL aggregates information from external databases to automate 13 out of 24 ACMG/AMP rules specified by HL-EP, namely PVS1, PS1, PM1, PM2, PM4, PM5, PP3, BA1, BS1, BS2, BP3, BP4, and BP7. We benchmarked VIP-HL using 50 variants in which 82 rules were activated by the ClinGen HL-EP. VIP-HL concordantly activated 93% (76/82) rules, significantly higher than that of by InterVar (48%; 39/82). VIP-HL is an integrated online tool for reliable automated variant classification in hearing loss genes. It assists curators in variant interpretation and provides a platform for users to share classifications with each other. VIP-HL is available with a user-friendly web interface at http://hearing.genetics.bgi.com/.

Targeted Sequencing of 242 Clinically Important Genes in the Russian Population From the Ivanovo Region

We performed a targeted sequencing of 242 clinically important genes mostly associated with cardiovascular diseases in a representative population sample of 1,658 individuals from the Ivanovo region northeast of Moscow. Approximately 11% of 11,876 detected variants were not found in the Single Nucleotide Polymorphism Database (dbSNP) or reported earlier in the Russian population. Most novel variants were singletons and doubletons in our sample, and virtually no novel alleles presumably specific for the Russian population were able to reach the frequencies above 0.1-0.2%. The overwhelming majority (99.3%) of variants detected in this study in three or more copies were shared with other populations. We found two dominant and seven recessive known pathogenic variants with allele frequencies significantly increased compared to those in the gnomAD non-Finnish Europeans. Of the 242 targeted genes, 28 were in the list of 59 genes for which the American College of Medical Genetics and Genomics (ACMG) recommended the reporting of incidental findings. Based on the number of variants detected in the sequenced subset of ACMG59 genes, we approximated the prevalence of known pathogenic and novel or rare protein-truncating variants in the complete set of ACMG59 genes in the Ivanovo population at 1.4 and 2.8%, respectively. We analyzed the available clinical data and observed the incomplete penetrance of known pathogenic variants in the 28 ACMG59 genes: only 1 individual out of 12 with such variants had the phenotype most likely related to the variant. When known pathogenic and novel or rare protein-truncating variants were considered together, the overall rate of confirmed phenotypes was about 19%, with maximum in the subset of novel protein-truncating variants. We report three novel protein truncating variants in APOB and one in MYH7 observed in individuals with hypobetalipoproteinemia and hypertrophic cardiomyopathy, respectively. Our results provide a valuable reference for the clinical interpretation of gene sequencing in Russian and other populations.

Current Developments in Detection of Identity-by-Descent Methods and Applications

Identity-by-descent (IBD), the detection of shared segments inherited from a common ancestor, is a fundamental concept in genomics with broad applications in the characterization and analysis of genomes. While historically the concept of IBD was extensively utilized through linkage analyses and in studies of founder populations, applications of IBD-based methods subsided during the genome-wide association study era. This was primarily due to the computational expense of IBD detection, which becomes increasingly relevant as the field moves toward the analysis of biobank-scale datasets that encompass individuals from highly diverse backgrounds. To address these computational barriers, the past several years have seen new methodological advances enabling IBD detection for datasets in the hundreds of thousands to millions of individuals, enabling novel analyses at an unprecedented scale. Here, we describe the latest innovations in IBD detection and describe opportunities for the application of IBD-based methods across a broad range of questions in the field of genomics.

Identification of incompletely penetrant variants and interallelic interactions in autosomal recessive disorders by a population-genetic approach

We aimed to identify incompletely penetrant (IP) variants and interallelic interactions in autosomal recessive disorders by a population-genetic approach. Genotype and clinical data were collected from 9038 patients of European origin with ASL, ATP7B, CAPN3, CFTR, CTNS, DHCR7, GAA, GALNS, GALT, IDUA, MUT, NPHS1, NPHS2, PAH, PKHD1, PMM2, or SLC26A4-related disorders. We calculated the relative allele frequency of each pathogenic variant (n = 1936) to the loss-of-function (LOF) variants of the corresponding gene in the patient ( A C p t V / A C p t L O F ) and the general population ( AC gnomAD V / AC gnomAD LOF ) and estimated the penetrance of each variant by calculating their ratio: ( A C p t V / A C p t L O F ) ( A C g n o m A D V / A C g n o m A D L O F ) (V/LOF ratio). We classified all variants as null or hypomorphic based on the associated clinical phenotype. We found 25 variants, 29% of the frequent 85 variants, to be underrepresented in the patient population (V/LOF ratio <30% with p < 7.22 × 10^-5 ), including 22 novel ones in the ASL, CAPN3, CFTR, GAA, GALNS, PAH, and PKHD1 genes. In contrast to the completely penetrant variants (CP), the majority of the IP variants were hypomorphic (IP: 16/18, 88%; CP: 177/933, 19.0%; p = 5.12 × 10^-10 ). Among them, only the NPHS2 R229Q variant was subject to interallelic interactions. The proposed algorithm identifies frequent IP variants and estimates their penetrance and interallelic interactions in large patient cohorts.

Frequency and management of medically actionable incidental findings from genome and exome sequencing data; A systematic review

The application of whole genome/exome sequencing technologies in clinical genetics and research has resulted in the discovery of incidental findings unrelated to the primary purpose of genetic testing. The American College of Medical Genetics and Genomics published guidelines for reporting pathogenic and likely pathogenic variants that are deemed to be medically actionable, which allowed us to learn about the epidemiology of incidental findings in different populations. However, consensus guidelines for variant reporting and classification are still lacking. We conducted a systematic literature review of incidental findings in whole genome/exome sequencing studies to obtain a comprehensive understanding of variable reporting and classification methods for variants that are deemed to be medically actionable across different populations. The review highlights the elements that demand further consideration or adjustment.

Penetrance and outcomes at 1-year following return of actionable variants identified by genome sequencing

PURPOSE

We estimated penetrance of actionable genetic variants and assessed near-term outcomes following return of results (RoR).

METHODS

Participants (n = 2,535) with hypercholesterolemia and/or colon polyps underwent targeted sequencing of 68 genes and 14 single-nucleotide variants. Penetrance was estimated based on presence of relevant traits in the electronic health record (EHR). Outcomes occurring within 1-year of RoR were ascertained by EHR review. Analyses were stratified by tier 1 and non-tier 1 disorders.

RESULTS

Actionable findings were present in 122 individuals and results were disclosed to 98. The average penetrance for tier 1 disorder variants (67%; n = 58 individuals) was higher than in non-tier 1 variants (46.5%; n = 58 individuals). After excluding 45 individuals (decedents, nonresponders, known genetic diagnoses, mosaicism), ≥1 outcomes were noted in 83% of 77 participants following RoR; 78% had a process outcome (referral to a specialist, new testing, surveillance initiated); 68% had an intermediate outcome (new test finding or diagnosis); 19% had a clinical outcome (therapy modified, risk reduction surgery). Risk reduction surgery occurred more often in participants with tier 1 than those with non-tier 1 variants.

CONCLUSION

Relevant phenotypic traits were observed in 57% whereas a clinical outcome occurred in 19% of participants with actionable genomic variants in the year following RoR.

Biased pathogenic assertions of loss of function variants challenge molecular diagnosis of admixed individuals

Diagnosis of individuals affected by monogenic disorders was significantly improved by next-generation sequencing targeting clinically relevant genes. Whole exomes yield a large number of variants that require several filtering steps, prioritization, and pathogenicity classification. Among the criteria recommended by ACMG, those that rely on population databases critically affect analyses of individuals with underrepresented ancestries. Population-specific allelic frequencies need consideration when characterizing potential deleteriousness of variants. An orthogonal input for classification is annotation of variants previously classified as pathogenic as a criterion that provide supporting evidence widely sourced at ClinVar. We used a whole-genome dataset from a census-based cohort of 1,171 elderly individuals from São Paulo, Brazil, highly admixed, and unaffected by severe monogenic disorders, to investigate if pathogenic assertions in ClinVar are enriched with higher proportions of European ancestry, indicating bias. Potential loss of function (pLOF) variants were filtered from 4,250 genes associated with Mendelian disorders and annotated with ClinVar assertions. Over 1,800 single nucleotide pLOF variants were included, 381 had non-benign assertions. Among carriers (N = 463), average European ancestry was significantly higher than noncarriers (N = 708; p = .011). pLOFs in genomic contexts of non-European local ancestries were nearly three times less likely to have any ClinVar entry (OR = 0.353; p <.0001). Independent pathogenicity assertions are useful for variant classification in molecular diagnosis. However, European overrepresentation of assertions can promote distortions when classifying variants in non-European individuals, even in admixed samples with a relatively high proportion of European ancestry. The investigation and deposit of clinically relevant findings of diverse populations is fundamental improve this scenario.

Challenges in the diagnosis and discovery of rare genetic disorders using contemporary sequencing technologies

Next generation sequencing (NGS) has revolutionised rare disease diagnostics. Concomitant with advancing technologies has been a rise in the number of new gene disorders discovered and diagnoses made for patients and their families. However, despite the trend towards whole exome and whole genome sequencing, diagnostic rates remain suboptimal. On average, only ~30% of patients receive a molecular diagnosis. National sequencing projects launched in the last 5 years are integrating clinical diagnostic testing with research avenues to widen the spectrum of known genetic disorders. Consequently, efforts to diagnose genetic disorders in a clinical setting are now often shared with efforts to prioritise candidate variants for the detection of new disease genes. Herein we discuss some of the biggest obstacles precluding molecular diagnosis and discovery of new gene disorders. We consider bioinformatic and analytical challenges faced when interpreting next generation sequencing data and showcase some of the newest tools available to mitigate these issues. We consider how incomplete penetrance, non-coding variation and structural variants are likely to impact diagnostic rates, and we further discuss methods for uplifting novel gene discovery by adopting a gene-to-patient-based approach.

Sub-genic intolerance, ClinVar, and the epilepsies: A whole-exome sequencing study of 29,165 individuals

Both mild and severe epilepsies are influenced by variants in the same genes, yet an explanation for the resulting phenotypic variation is unknown. As part of the ongoing Epi25 Collaboration, we performed a whole-exome sequencing analysis of 13,487 epilepsy-affected individuals and 15,678 control individuals. While prior Epi25 studies focused on gene-based collapsing analyses, we asked how the pattern of variation within genes differs by epilepsy type. Specifically, we compared the genetic architectures of severe developmental and epileptic encephalopathies (DEEs) and two generally less severe epilepsies, genetic generalized epilepsy and non-acquired focal epilepsy (NAFE). Our gene-based rare variant collapsing analysis used geographic ancestry-based clustering that included broader ancestries than previously possible and revealed novel associations. Using the missense intolerance ratio (MTR), we found that variants in DEE-affected individuals are in significantly more intolerant genic sub-regions than those in NAFE-affected individuals. Only previously reported pathogenic variants absent in available genomic datasets showed a significant burden in epilepsy-affected individuals compared with control individuals, and the ultra-rare pathogenic variants associated with DEE were located in more intolerant genic sub-regions than variants associated with non-DEE epilepsies. MTR filtering improved the yield of ultra-rare pathogenic variants in affected individuals compared with control individuals. Finally, analysis of variants in genes without a disease association revealed a significant burden of loss-of-function variants in the genes most intolerant to such variation, indicating additional epilepsy-risk genes yet to be discovered. Taken together, our study suggests that genic and sub-genic intolerance are critical characteristics for interpreting the effects of variation in genes that influence epilepsy.

The prevalence, genetic complexity and population-specific founder effects of human autosomal recessive disorders

Autosomal recessive (AR) disorders pose a significant burden for public health. However, despite their clinical importance, epidemiology and molecular genetics of many AR diseases remain poorly characterized. Here, we analyzed the genetic variability of 508 genes associated with AR disorders based on sequencing data from 141,456 individuals across seven ethnogeographic groups by integrating variants with documented pathogenicity from ClinVar, with stringent functionality predictions for variants with unknown pathogenicity. We first validated our model using 85 diseases for which population-specific prevalence data were available and found that our estimates strongly correlated with the respective clinically observed disease frequencies (r = 0.68; p < 0.0001). We found striking differences in population-specific disease prevalence with 101 AR diseases (27%) being limited to specific populations, while an additional 305 diseases (68%) differed more than tenfold across major ethnogeographic groups. Furthermore, by analyzing genetic AR disease complexity, we confirm founder effects for cystic fibrosis and Stargardt disease, and provide strong evidences for >25 additional population-specific founder mutations. The presented analyses reveal the molecular genetics of AR diseases with unprecedented resolution and provide insights into epidemiology, complexity, and population-specific founder effects. These data can serve as a powerful resource for clinical geneticists to inform population-adjusted genetic screening programs, particularly in otherwise understudied ethnogeographic groups.

The Science and Art of Clinical Genetic Variant Classification and Its Impact on Test Accuracy

Clinical genetic variant classification science is a growing subspecialty of clinical genetics and genomics. The field's continued improvement is essential for the success of precision medicine in both germline (hereditary) and somatic (oncology) contexts. This review focuses on variant classification for DNA next-generation sequencing tests. We first summarize current limitations in variant discovery and definition, and then describe the current five- and four-tier classification systems outlined in dominant standards and guideline publications for germline and somatic tests, respectively. We then discuss measures of variant classification discordance and the field's bias for positive results, as well as considerations for panel size and population screening in the context of estimates of positive predictive value thatincorporate estimated variant classification imperfections. Finally, we share opinions on the current state of variant classification from some of the authors of the most widely used standards and guideline publications and from other domain experts.