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Purpose An efficient framework to identify disease associated genes is needed to evaluate genomic data for both individuals with an unknown disease etiology and those undergoing genomic screening. Here, we propose a framework for gene selection used in genomic analyses, including applications limited to genes with strong or established evidence levels and applications including genes with less or emerging evidence of disease association. Methods We extracted genes with evidence for gene-disease association from the Human Gene Mutation Database, Online Mendelian Inheritance in Man, and ClinVar to build a comprehensive gene list of 6,145 genes. Next, we applied stringent filters in conjunction with computationally curated evidence (DisGeNET) to create a restrictive list limited to 3,929 genes with stronger disease associations. Results When compared to manual gene curation efforts, including the Clinical Genome Resource, genes with strong or definitive disease associations are included in both gene lists at high percentages, while genes with limited evidence are largely removed. We further confirmed the utility of this approach in identifying pathogenic and likely pathogenic variants in 45 genomes. Conclusion Our approach efficiently creates highly sensitive gene lists for genomic applications, while remaining dynamic and updatable, enabling time savings in genomic applications.

Focal segmental glomerulosclerosis (FSGS) is the main pathology underlying steroid-resistant nephrotic syndrome (SRNS) and a leading cause of chronic kidney disease. Monogenic forms of pediatric SRNS are predominantly caused by recessive mutations, while the contribution of de novo variants (DNVs) to this trait is poorly understood. Using exome sequencing (ES) in a proband with FSGS/SRNS, developmental delay, and epilepsy, we discovered a nonsense DNV in TRIM8, which encodes the E3 ubiquitin ligase tripartite motif containing 8. To establish whether TRIM8 variants represent a cause of FSGS, we aggregated exome/genome-sequencing data for 2,501 pediatric FSGS/SRNS-affected individuals and 48,556 control subjects, detecting eight heterozygous TRIM8 truncating variants in affected subjects but none in control subjects (p = 3.28 × 10(−11)). In all six cases with available parental DNA, we demonstrated de novo inheritance (p = 2.21 × 10(−15)). Reverse phenotyping revealed neurodevelopmental disease in all eight families. We next analyzed ES from 9,067 individuals with epilepsy, yielding three additional families with truncating TRIM8 variants. Clinical review revealed FSGS in all. All TRIM8 variants cause protein truncation clustering within the last exon between residues 390 and 487 of the 551 amino acid protein, indicating a correlation between this syndrome and loss of the TRIM8 C-terminal region. Wild-type TRIM8 overexpressed in immortalized human podocytes and neuronal cells localized to nuclear bodies, while constructs harboring patient-specific variants mislocalized diffusely to the nucleoplasm. Co-localization studies demonstrated that Gemini and Cajal bodies frequently abut a TRIM8 nuclear body. Truncating TRIM8 DNVs cause a neuro-renal syndrome via aberrant TRIM8 localization, implicating nuclear bodies in FSGS and developmental brain disease.

Nonsyndromic hearing loss is genetically heterogeneous. Despite comprehensive genetic testing, many cases remain unsolved because the clinical significance of identified variants is uncertain or because biallelic pathogenic variants are not identified for presumed autosomal recessive cases. Common synonymous variants are often disregarded. Determining the pathogenicity of synonymous variants may improve genetic diagnosis. We report a synonymous variant c.9861 C > T/p.(Gly3287=) in MYO15A in homozygosity or compound heterozygosity with another pathogenic or likely pathogenic MYO15A variant in 10 unrelated families with nonsyndromic sensorineural hearing loss. Biallelic variants in MYO15A were identified in 21 affected and were absent in 22 unaffected siblings. A mini-gene assay confirms that the synonymous variant leads to abnormal splicing. The variant is enriched in the Ashkenazi Jewish population. Individuals carrying biallelic variants involving c.9861 C > T often exhibit progressive post-lingual hearing loss distinct from the congenital profound deafness typically associated with biallelic loss-of-function MYO15A variants. This study establishes the pathogenicity of the c.9861 C > T variant in MYO15A and expands the phenotypic spectrum of MYO15A-related hearing loss. Our work also highlights the importance of multicenter collaboration and data sharing to establish the pathogenicity of a relatively common synonymous variant for improved diagnosis and management of hearing loss.

International audience; Congenital anomalies of the kidney and urinary tract (CAKUT) constitute one of the most frequent birth defects and represent the most common cause of chronic kidney disease in the first three decades of life. Despite the discovery of dozens of monogenic causes of CA-KUT, most pathogenic pathways remain elusive. We performed whole-exome sequencing (WES) in 551 individuals with CAKUT and identified a heterozygous de novo stop-gain variant in ZMYM2 in two different families with CAKUT. Through collaboration, we identified in total 14 different heterozygous loss-of-function mutations in ZMYM2 in 15 unrelated families. Most mutations occurred de novo, indicating possible interference with reproductive function. Human disease features are replicated in X. tropicalis larvae with morpho-lino knockdowns, in which expression of truncated ZMYM2 proteins, based on individual mutations, failed to rescue renal and cranio-facial defects. Moreover, heterozygous Zmym2-deficient mice recapitulated features of CAKUT with high penetrance. The ZMYM2 protein is a component of a transcriptional corepressor complex recently linked to the silencing of developmentally regulated endoge-nous retrovirus elements. Using protein-protein interaction assays, we show that ZMYM2 interacts with additional epigenetic silencing complexes, as well as confirming that it binds to FOXP1, a transcription factor that has also been linked to CAKUT. In summary, our findings establish that loss-of-function mutations of ZMYM2, and potentially that of other proteins in its interactome, as causes of human CAKUT, offering new routes for studying the pathogenesis of the disorder.

Here, we report on six unrelated individuals, all presenting with early-onset global developmental delay, associated with impaired motor, speech and cognitive development, partly with developmental epileptic encephalopathy and physical dysmorphisms. All individuals carry heterozygous missense variants of KCND2, which encodes the voltage-gated potassium (Kv) channel α-subunit Kv4.2. The amino acid substitutions associated with the variants, p.(Glu323Lys) (E323K), p.(Pro403Ala) (P403A), p.(Val404Leu) (V404L) and p.(Val404Met) (V404M), affect sites known to be critical for channel gating. To unravel their likely pathogenicity, recombinant mutant channels were studied in the absence and presence of auxiliary β-subunits under two-electrode voltage clamp in Xenopus oocytes. All channel mutants exhibited slowed and incomplete macroscopic inactivation, and the P403A variant in addition slowed activation. Co-expression of KChIP2 or DPP6 augmented the functional expression of both wild-type and mutant channels; however, the auxiliary β-subunit-mediated gating modifications differed from wild type and among mutants. To simulate the putative setting in the affected individuals, heteromeric Kv4.2 channels (wild type + mutant) were studied as ternary complexes (containing both KChIP2 and DPP6). In the heteromeric ternary configuration, the E323K variant exhibited only marginal functional alterations compared to homomeric wild-type ternary, compatible with mild loss-of-function. By contrast, the P403A, V404L and V404M variants displayed strong gating impairment in the heteromeric ternary configuration, compatible with loss-of-function or gain-of-function. Our results support the etiological involvement of Kv4.2 channel gating impairment in early-onset monogenic global developmental delay. In addition, they suggest that gain-of-function mechanisms associated with a substitution of V404 increase epileptic seizure susceptibility.

Identifying Mendelian diseases with recessive inheritance is challenging as the majority of cases are caused by compound heterozygous genotypes which require sequencing data in families to definitively identify. Bottleneck events, such as in the Finnish population, enrich specific homozygous variants to higher frequencies and thus facilitate identification of disease associations through easily recognized homozygous genotypes. Here, we study homozygous and heterozygous effects of 82,516 coding variants on 2,444 disease endpoints using nationwide electronic health record (EHR) data of 176,899 Finns. We find known and novel associations to homozygous genotypes across a broad spectrum of phenotypes such as retinal dystrophy, adult-onset cataract and female infertility (13/20 of which would have been missed by the traditional additive GWAS model). With these results, and supporting simulations, we demonstrate the added benefit of homozygous scans in GWAS. We further use these results to explore inheritance patterns of known Mendelian variants. We find many Mendelian variants whose inheritance cannot be adequately described with the traditional definition of dominant or recessive. In particular, we find disease risk in heterozygous carriers of variants known to cause disease with recessive inheritance, as well as for variants labeled benign in ClinVar. Our results demonstrate how biobank efforts, particularly in founder populations, can broaden our understanding of the impact of genetic variants.

We promote a shared vision and guide for how and when to federate genomic and health-related data sharing, enabling connections and insights across independent, secure databases. The GA4GH encourages a federated approach wherein data providers have the mandate and resources to share, but where data cannot move for legal or technical reasons. We recommend a federated approach to connect national genomics initiatives into a global network and precision medicine resource. Funding: A.T. acknowledges funding support from Genome Canada, Genome Quebec, and the Canadian Institutes of Health Research. H.L.R. and A.J.H.P. acknowledge funding under NIH U41HG006834 and U24HG011025. M. Baudis acknowledges funding under the Bio-MedIT Network project of Swiss Institute of Bioinformatics (SIB) and Swiss Personalized Health Network (SPHN). M.L. acknowledges funding from the CINECA project (H2020 No 825775). M.S.C. acknowledges funding under NIH/NCI U01CA242954, NIH/NHLBI Fellowship 5118777. M. Brudno is a CIFAR Canada AI Chair. P.G. acknowledges funding from CIHR, Genome Canada, Wellcome Trust, and NIH. T.H.N. was funded by the Academy of Finland grant no 319968 and ELIXIR Europe 2019–2023 program

Understanding whether there is enough evidence to implicate a gene's role in a given disease, as well as the mechanisms by which variants in this gene might cause this disease, are essential in order to determine clinical relevance. The National Institutes of Health-funded Clinical Genome Resource (ClinGen) has developed evaluation frameworks to assess both the strength of evidence supporting a relationship between a gene and disease (gene-disease validity), and whether loss (haploinsufficiency) or gain (triplosensitivity) of individual genes or genomic regions is a mechanism for disease (dosage sensitivity). ClinGen actively applies these frameworks across multiple disease domains, and makes this information publicly available via its website (www.clinicalgenome.org) for use in multiple applications, including clinical variant classification. Here we describe how the results of these curation processes can be utilized to inform proper application of pathogenicity criteria for both sequence and copy number variants, as well as to guide test development and inform genomic filtering pipelines. This article is protected by copyright. All rights reserved.

BackgroundIn silicoevidence is important to consider when interpreting genetic variants. According to the ACMG/AMP,in silicoevidence is applied at the supporting strength level using the PP3 and BP4 criteria, for pathogenic and benign evidence, respectively. While PP3 has been determined to be one of the most commonly applied criteria, less is known about the effect of these two criteria on variant classification outcomes.MethodsIn this study, a total of 727 missense variants curated by Clinical Genome Resource (ClinGen) Variant Curation Expert Panels (VCEPs) were analyzed to determine how often PP3 and BP4 were applied and how often they influenced final variant classifications. The current categorical system of variant classification was compared with a point-based system being developed by the ClinGen Sequence Variant Interpretation Working Group. In addition, the performance of fourin silicotools (REVEL, VEST, FATHMM, and MPC) was assessed by using a gold set of 237 variants (classified as benign or pathogenic independent of PP3 or BP4) to calculate pathogenicity likelihood ratios.ResultsCollectively, the PP3 and BP4 criteria were applied by ClinGen VCEPs to 55% of missense variants in this data set. Removingin silicocriteria from variants where they were originally applied caused variants to change classification from pathogenic to likely pathogenic (14%), likely pathogenic to variant of uncertain significance (VUS) (24%), or likely benign to VUS (64%). The proportion of downgrades with the categorical classification system was similar to that of the point-based system, though the latter resolved borderline classifications. REVEL and VEST performed at a level consistent with moderate strength towards either benign or pathogenic evidence, while FATHMM performed at the supporting level.ConclusionsOverall, this study demonstrates thatin silicocriteria PP3 and BP4 are commonly applied in variant classification and often affect the final classification. Our results suggest that when sufficient thresholds forin silicopredictors are established, PP3 and BP4 may be appropriate to use at a moderate strength. However, further calibration with larger datasets is needed to optimize the performance of currentin silicotools given the impact they have on clinical variant classification.

Databases of allele frequency are extremely helpful for evaluating clinical variants of unknown significance; however, until now, genetic databases such as the Genome Aggregation Database (gnomAD) have ignored the mitochondrial genome (mtDNA). Here we present a pipeline to call mtDNA variants that addresses three technical challenges: (i) detecting homoplasmic and heteroplasmic variants, present respectively in all or a fraction of mtDNA molecules, (ii) circular mtDNA genome, and (iii) misalignment of nuclear sequences of mitochondrial origin (NUMTs). We observed that mtDNA copy number per cell varied across gnomAD cohorts and influenced the fraction of NUMT-derived false-positive variant calls, which can account for the majority of putative heteroplasmies. To avoid false positives, we excluded samples prone to NUMT misalignment (few mtDNA copies per cell), cell line artifacts (many mtDNA copies per cell), or with contamination and we reported variants with heteroplasmy greater than 10%. We applied this pipeline to 56,434 whole genome sequences in the gnomAD v3.1 database that includes individuals of European (58%), African (25%), Latino (10%), and Asian (5%) ancestry. Our gnomAD v3.1 release contains population frequencies for 10,850 unique mtDNA variants at more than half of all mtDNA bases. Importantly, we report frequencies within each nuclear ancestral population and mitochondrial haplogroup. Homoplasmic variants account for most variant calls (98%) and unique variants (85%). We observed that 1/250 individuals carry a pathogenic mtDNA variant with heteroplasmy above 10%. These mitochondrial population allele frequencies are publicly available at gnomad.broadinstitute.org and will aid in diagnostic interpretation and research studies.

Summary Over 100 million research participants around the world have had research array-based genotyping (GT) or genome sequencing (GS), but only a small fraction of these have been offered return of actionable genomic findings (gRoR). Between 2017 and 2021, we analyzed genomic results from 36,417 participants in the Mass General Brigham Biobank and offered to confirm and return pathogenic and likely pathogenic variants (PLPVs) in 59 genes. Variant verification prior to participant recontact revealed that GT falsely identified PLPVs in 44.9% of samples, and GT failed to identify 72.0% of PLPVs detected in a subset of samples that were also sequenced. GT and GS detected verified PLPVs in 1% and 2.5% of the cohort, respectively. Of 256 participants who were alerted that they carried actionable PLPVs, 37.5% actively or passively declined further disclosure. 76.3% of those carrying PLPVs were unaware that they were carrying the variant, and over half of those met published professional criteria for genetic testing but had never been tested. This gRoR protocol cost approximately $129,000 USD per year in laboratory testing and research staff support, representing $14 per participant whose DNA was analyzed or $3,224 per participant in whom a PLPV was confirmed and disclosed. These data provide logistical details around gRoR that could help other investigators planning to return genomic results.

PurposeWe aimed to gain insight into frequencies of genetic variants in genes implicated in neurodevelopmental disorder with epilepsy (NDD+E) by investigating large cohorts of patients in a diagnostic setting.MethodsWe analyzed variants in NDD+E using epilepsy gene panel sequencing performed between 2013 and 2017 by two large diagnostic companies. We compared variant frequencies in 6,994 panels to other 8,588 recently published panels as well as exome-widede novovariants in 1,942 individuals with NDD+E and 10,937 controls.ResultsGenes with highest frequencies of ultra-rare variants in NDD+E comprisedSCN1A, KCNQ2, SCN2A, CDKL5, SCN8AandSTXBP1, concordant with the two other epilepsy cohorts we investigated. Only 46% of the analysed 262 dominant and X-linked panel genes contained ultra-rare variants in patients. Among genes with contradictory evidence of association with epilepsyCACNB4, CLCN2, EFHC1, GABRD, MAGI2andSRPX2showed equal frequencies in cases and controls.ConclusionWe show that improvement of panel design increased diagnostic yield over time, but panels still display genes with low or no diagnostic yield. With our data, we hope to improve current diagnostic NDD+E panel design and provide a resource of ultra-rare variants in individuals with NDD+E to the community.

Rare genetic disorders, while individually rare, are collectively common. They represent some of the most severe disorders affecting patients worldwide with significant morbidity and mortality. Over the last decade, advances in genomic methods have significantly uplifted diagnostic rates for patients and facilitated novel and targeted therapies. However, many patients with rare genetic disorders still remain undiagnosed as the genetic etiology of only a proportion of Mendelian conditions has been discovered to date. This article explores existing strategies to identify novel Mendelian genes and how these discoveries impact clinical care and therapeutics. We discuss the importance of data sharing, phenotype-driven approaches, patient-led approaches, utilization of large-scale genomic sequencing projects, constraint-based methods, integration of multi-omics data, and gene-to-patient methods. We further consider the health economic advantages of novel gene discovery and speculate on potential future methods for improved clinical outcomes.

Autosomal-recessive cerebellar hypoplasia and ataxia constitute a group of heterogeneous brain disorders caused by disruption of several fundamental cellular processes. Here, we identified 10 families showing a neurodegenerative condition involving pontocerebellar hypoplasia with microcephaly (PCHM). Patients harbored biallelic mutations in genes encoding the spliceosome components Peptidyl-Prolyl Isomerase Like-1 (PPIL1) or Pre-RNA Processing-17 (PRP17). Mouse knockouts of either gene were lethal in early embryogenesis, whereas PPIL1 patient mutation knockin mice showed neuron-specific apoptosis. Loss of either protein affected splicing integrity, predominantly affecting short and high GC-content introns and genes involved in brain disorders. PPIL1 and PRP17 form an active isomerase-substrate interaction, but we found that isomerase activity is not critical for function. Thus, we establish disrupted splicing integrity and "major spliceosome-opathies" as a new mechanism underlying PCHM and neurodegeneration and uncover a non-enzymatic function of a spliceosomal proline isomerase.

Phosphoinositides are lipids that play a critical role in processes such as cellular signalling, ion channel activity and membrane trafficking. When mutated, several genes that encode proteins that participate in the metabolism of these lipids give rise to neurological or developmental phenotypes. PI4KA is a phosphoinositide kinase that is highly expressed in the brain and is essential for life. Here we used whole exome or genome sequencing to identify 10 unrelated patients harbouring biallelic variants in PI4KA that caused a spectrum of conditions ranging from severe global neurodevelopmental delay with hypomyelination and developmental brain abnormalities to pure spastic paraplegia. Some patients presented immunological deficits or genito-urinary abnormalities. Functional analyses by western blotting and immunofluorescence showed decreased PI4KA levels in the patients’ fibroblasts. Immunofluorescence and targeted lipidomics indicated that PI4KA activity was diminished in fibroblasts and peripheral blood mononuclear cells. In conclusion, we report a novel severe metabolic disorder caused by PI4KA malfunction, highlighting the importance of phosphoinositide signalling in human brain development and the myelin sheath., Verdura et al. report a novel rare brain metabolic disorder caused by recessive mutations in PI4KA, which encodes an enzyme with a pivotal role in phosphoinositide metabolism at the cell membrane. The description of this syndrome will simplify the identification of undiagnosed cases with similar clinical features.

An efficient framework to identify disease-causing genes is needed to evaluate genomic data for both individuals with an unknown disease etiology and those undergoing genomic screening. Here, we propose a framework for gene selection used in genomic analyses, including screening applications limited to genes with strong or established evidence levels and diagnostic applications that includes genes with less or emerging evidence of disease association. We extracted genes with evidence for gene-disease association from the Human Gene Mutation Database, Online Mendelian Inheritance in Man, and ClinVar to build a diagnostic gene list of 5,973 genes. Next, we applied stringent filters in conjunction with computationally curated evidence (DisGeNET) to create a list limited to 3,600 genes with stronger levels of evidence for disease association. When compared to manual gene curation efforts, including the Clinical Genome Resource, genes with strong or definitive disease associations are included in both gene lists at high percentages, while genes with limited evidence are largely removed. We further confirmed the utility of this approach in the screening of 45 ostensibly healthy genomes. Our approach efficiently creates highly sensitive gene lists for genomic applications, while remaining dynamic and updatable, enabling time savings in gene curation and review.

Documenting variation in our genomes is important for research and clinical care. Accuracy in the description of DNA variants is therefore essential. To address this issue, the Human Variome Project convened a committee to evaluate the feasibility of requiring authors to verify that all variants submitted for publication complied with a widely accepted standard for description. After a pilot study at two journals, the committee agreed that requiring authors to verify that variants complied with Human Genome Variation Society nomenclature is a reasonable step toward standardizing the worldwide inventory of human variation. This article is protected by copyright. All rights reserved.

Current clinical guidelines recommend three genetic tests for the assessment of fetal structural anomalies: karyotype to detect microscopically-visible balanced and unbalanced chromosomal rearrangements, chromosomal microarray (CMA) to detect sub-microscopic copy number variants (CNVs), and exome sequencing (ES) to identify individual nucleotide changes in coding sequence. Advances in genome sequencing (GS) analysis suggest that it is poised to displace the sequential application of all three conventional tests to become a single diagnostic approach for the assessment of fetal structural anomalies. However, systematic benchmarking is required to assure that GS can capture the full mutational spectrum associated with fetal structural anomalies and to accurately quantify the added diagnostic yield of GS. We applied a novel GS analytic framework that included the discovery, filtration, and interpretation of nine classes of genomic variation to 7,195 individuals. We assessed the sensitivity of GS to detect diagnostic variants (pathogenic or likely pathogenic) from three standard-of-care tests using 1,612 autism spectrum disorder quartet families (ASD; n=6,448) with matched GS, ES, and CMA data, and validated these findings in 46 fetuses with a clinically reportable variant originally identified by karyotype, CMA, or ES. We then assessed the added diagnostic yield of GS in 249 trios (n=747) comprising a fetus with a structural anomaly detected by ultrasound and two unaffected parents that were pre-screened with a combination of all three standard-of-care tests. Across both cohorts, our GS analytic framework identified 98.2% of all diagnostic variants detected by standard-of-care tests, including 100% of those originally detected by CMA (n=88) and ES (n=61), as well as 78.6% (n=11/14) of the chromosomal rearrangements identified by karyotype. The diagnostic yield from GS was 7.8% across all 1,612 ASD probands, almost two-fold more than CMA (4.4%) and three-fold more than ES (3.0%). We also demonstrated that the yield of ES can approach that of GS when CNVs are captured with high sensitivity from exome data (7.4% vs. 7.8%, respectively). In 249 pre-screened fetuses with structural anomalies, GS provided an additional diagnostic yield of 0.4% beyond the combination of all three tests (karyotype, CMA, and ES). Applying our benchmarking results to existing data indicates that GS can achieve an overall diagnostic yield of 46.1% in unselected fetuses with fetal structural anomalies, providing an estimated 17.2% increase in diagnostic yield over karyotype, 14.1% over CMA, and 36.1% over ES when sequence variants are assessed, and 4.1% when CNVs are also identified from exome data. In this study we demonstrate that GS is sensitive to the detection of almost all pathogenic variation captured by karyotype, CMA, and ES, provides a superior diagnostic yield than any individual test by a wide margin, and contributes a modest increase in diagnostic yield beyond the combination of all three tests. We also outline several strategies to aid the interpretation of GS variants that are cryptic to conventional technologies, which we anticipate will be increasingly encountered as comprehensive variant identification from GS is performed. Taken together, these data suggest GS warrants consideration as a first-tier diagnostic approach for fetal structural anomalies.

The Clinical Genome Resource (ClinGen) Sequence Variant Interpretation Working Group set out to refine the American College of Medical Genetics and Genomics and the Association of Molecular Pathologists (ACMG/AMP) variant pathogenicity recommendations for stand-alone rule BA1 (a variant with minor allele frequency [MAF] > 0.05 is benign), by clarifying how it should be used and specifying a set of variants that should be exempted from this rule. We cross-referenced ClinVar and Exome Aggregation Consortium data to identify variants for which there was a plausible argument for pathogenicity and the variant exists in one or more population data sets at MAF > 0.05. We identified nine such variants that were present in these data sets that may not be benign. The ACMG/AMP criteria were applied to these variants that resulted in four pathogenic and five variants of uncertain significance. We have refined benign rule BA1 by clarifying terms used to describe its use, which databases we recommend using, and assumptions made about this rule. We also recognized an initial list of nine variants for which there was some evidence of pathogenicity even though the MAF was high for these variants. We specify processes whereby individuals can petition ClinGen for amendments to our variant-specific assertions and the criteria experts should use when setting a numerically lower threshold for BA1 for specific genes.

ClinVar provides open access to variant classifications shared from many clinical laboratories. While most classifications are consistent across laboratories, classification differences exist. To facilitate resolution of classification differences on a large scale, clinical laboratories were encouraged to reassess outlier classifications of variants with medically significant differences. Outliers were identified by first comparing ClinVar submissions from 41 clinical laboratories to detect variants with medically significant differences between the laboratories (650 variants). Next, medically significant differences were filtered for variants with ≥3 classifications (244 variants), of which 87.6% (213 variants) had a majority consensus in ClinVar, thus allowing for identification of outlier classifications in need of reassessment. Laboratories with outlier classifications were sent a custom report and encouraged to reassess variants. Results were returned for 204 (96%) variants, of which 62.3% (127) were resolved. Of those 127, 64.6% (82) were resolved due to reassessment prompted by this study and 35.4% (45) resolved by a previously completed reassessment. This study demonstrates a scalable approach to classification resolution and capitalizes on the value of data sharing within ClinVar. These activities will help the community move toward more consistent variant classifications which will improve the care of patients with, or at risk for, genetic disorders.

Rare disease investigators constantly face challenges in identifying additional cases to build evidence for gene‐disease causality. The Matchmaker Exchange (MME) addresses this limitation by providing a mechanism for matching patients across genomic centers via a federated network. The MME has revolutionized searching for additional cases by making it possible to query across institutional boundaries, so that what was once a laborious and manual process of contacting researchers is now automated and computable. However, while the MME network is beginning to scale, the growth of additional nodes is limited by the lack of easy‐to‐use solutions that can be implemented by any rare disease database owner, even one without significant software engineering resources. Here we describe matchbox, which is an open‐source, platform‐independent, portable bridge between any given rare disease genomic center and the MME network, which has already led to novel gene discoveries. We also describe how matchbox greatly reduces the barrier to participation by overcoming challenges for new databases to join the MME. Refereed/Peer-reviewed

Given that all forms of Usher syndrome (USH) present with hearing loss in advance of retinal disease, the syndromic nature of the disorder is rarely appreciated when critical management decisions are being made. As a result, molecular diagnostics are crucial in guiding the management of USH patients. While 11 genes have been associated with USH, the USH2A gene is one of the largest contributors. Approximately 20% of suspected USH probands that undergo USH2A sequencing at our laboratory receive an inconclusive result due to the identification of a monoallelic disease-causing variant in USH2A. Many studies suggest that intragenic deletions and duplications represent an important USH2A variant type that can be missed by sequencing assays if supplemental algorithms or testing methods are not applied. To gain a comprehensive view of the contribution of USH2A CNVs to USH, we conducted prospective and retrospective screening in 700 hearing loss probands. Fourteen individuals with 11 unique USH2A CNVs are reported, including one pathogenic multi-exon duplication. Additionally, we mapped deletion breakpoints and performed a meta-analysis of USH2A CNVs to evaluate recurrence and underlying mechanisms. This analysis revealed breakpoint grouping within three introns, raising the possibility of CNV-susceptible regions within the gene. Overall, our data highlight the diversity of pathogenic CNVs in this gene, demonstrating that the comprehensive, high-resolution USH2A CNV analysis methods employed here are essential components of clinical genetic testing for USH.

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

Background Steroid-resistant nephrotic syndrome (SRNS) is a frequent cause of CKD. The discovery of monogenic causes of SRNS has revealed specific pathogenetic pathways, but these monogenic causes do not explain all cases of SRNS. Methods To identify novel monogenic causes of SRNS, we screened 665 patients by whole-exome sequencing. We then evaluated the in vitro functional significance of two genes and the mutations therein that we discovered through this sequencing and conducted complementary studies in podocyte-like Drosophila nephrocytes. Results We identified conserved, homozygous missense mutations of GAPVD1 in two families with early-onset NS and a homozygous missense mutation of ANKFY1 in two siblings with SRNS. GAPVD1 and ANKFY1 interact with the endosomal regulator RAB5. Coimmunoprecipitation assays indicated interaction between GAPVD1 and ANKFY1 proteins, which also colocalized when expressed in HEK293T cells. Silencing either protein diminished the podocyte migration rate. Compared with wild-type GAPVD1 and ANKFY1, the mutated proteins produced upon ectopic expression of GAPVD1 or ANKFY1 bearing the patient-derived mutations exhibited altered binding affinity for active RAB5 and reduced ability to rescue the knockout-induced defect in podocyte migration. Coimmunoprecipitation assays further demonstrated a physical interaction between nephrin and GAPVD1, and immunofluorescence revealed partial colocalization of these proteins in rat glomeruli. The patient-derived GAPVD1 mutations reduced nephrin-GAPVD1 binding affinity. In Drosophila , silencing Gapvd1 impaired endocytosis and caused mistrafficking of the nephrin ortholog. Conclusions Mutations in GAPVD1 and probably in ANKFY1 are novel monogenic causes of NS. The discovery of these genes implicates RAB5 regulation in the pathogenesis of human NS.

Item does not contain fulltext BACKGROUND: Congenital anomalies of the kidney and urinary tract (CAKUT) are the most prevalent cause of kidney disease in the first three decades of life. Previous gene panel studies showed monogenic causation in up to 12% of patients with CAKUT. METHODS: We applied whole-exome sequencing to analyze the genotypes of individuals from 232 families with CAKUT, evaluating for mutations in single genes known to cause human CAKUT and genes known to cause CAKUT in mice. In consanguineous or multiplex families, we additionally performed a search for novel monogenic causes of CAKUT. RESULTS: In 29 families (13%), we detected a causative mutation in a known gene for isolated or syndromic CAKUT that sufficiently explained the patient's CAKUT phenotype. In three families (1%), we detected a mutation in a gene reported to cause a phenocopy of CAKUT. In 15 of 155 families with isolated CAKUT, we detected deleterious mutations in syndromic CAKUT genes. Our additional search for novel monogenic causes of CAKUT in consanguineous and multiplex families revealed a potential single, novel monogenic CAKUT gene in 19 of 232 families (8%). CONCLUSIONS: We identified monogenic mutations in a known human CAKUT gene or CAKUT phenocopy gene as the cause of disease in 14% of the CAKUT families in this study. Whole-exome sequencing provides an etiologic diagnosis in a high fraction of patients with CAKUT and will provide a new basis for the mechanistic understanding of CAKUT. 01 september 2018

The Matchmaker Exchange (MME) connects rare disease clinicians and researchers to facilitate the sharing of data from undiagnosed patients for the purpose of novel gene discovery. Such sharing raises the odds that two or more similar patients with candidate genes in common may be found, thereby allowing their condition to be more readily studied and understood. Consent considerations for data sharing in MME included both the ethical and legal differences between clinical and research settings and the level of privacy risk involved in sharing varying amounts of rare disease patient data to enable patient matches. In this commentary, we discuss these consent considerations and the resulting MME Consent Policy as they may be relevant to other international data sharing initiatives.

While the diagnostic success of genomic sequencing expands, the complexity of this testing should not be overlooked. Numerous laboratory processes are required to support the identification, interpretation, and reporting of clinically significant variants. This study aimed to examine the workflow and reporting procedures among US laboratories to highlight shared practices and identify areas in need of standardization. Surveys and follow-up interviews were conducted with laboratories offering exome and/or genome sequencing to support a research program or for routine clinical services. The 73-item survey elicited multiple choice and free-text responses that were later clarified with phone interviews. Twenty-one laboratories participated. Practices highly concordant across all groups included consent documentation, multiperson case review, and enabling patient opt-out of incidental or secondary findings analysis. Noted divergence included use of phenotypic data to inform case analysis and interpretation and reporting of case-specific quality metrics and methods. Few laboratory policies detailed procedures for data reanalysis, data sharing, or patient access to data. This study provides an overview of practices and policies of experienced exome and genome sequencing laboratories. The results enable broader consideration of which practices are becoming standard approaches, where divergence remains, and areas of development in best practice guidelines that may be helpful.Genet Med advance online publication 03 Novemeber 2016.

Classification of novel variants is a major challenge facing the widespread adoption of comprehensive clinical genomic sequencing and the field of personalized medicine in general. This is largely because most novel variants do not have functional, genetic, or population data to support their clinical classification.To improve variant interpretation, we leveraged the Exome Aggregation Consortium (ExAC) data set (N = ~60,000) as well as 7,000 clinically curated variants in 132 genes identified in more than 11,000 probands clinically tested for cardiomyopathies, rasopathies, hearing loss, or connective tissue disorders to perform a systematic evaluation of domain level disease associations.We statistically identify regions that are most sensitive to functional variation in the general population and also most commonly impacted in symptomatic individuals. Our data show that a significant number of exons and domains in genes strongly associated with disease can be defined as disease-sensitive or disease-tolerant, leading to potential reclassification of at least 26% (450 out of 1,742) of variants of uncertain clinical significance in the 132 genes.This approach leverages domain functional annotation and associated disease in each gene to prioritize candidate disease variants, increasing the sensitivity and specificity of novel variant assessment within these genes.Genet Med advance online publication 22 September 2016.

With the rapid evolution of next-generation DNA sequencing technologies, the cost of sequencing a human genome has plummeted, and genomics has started to pervade health care across all stages of life - from preconception to adult medicine. Challenges to fully embracing genomics in a clinical setting remain, but some approaches are starting to overcome these barriers, such as community-driven data sharing to improve the accuracy and efficiency of applying genomics to patient care.

In 2015, professional guidelines defined the term ‘likely pathogenic’ to mean with a 90% chance of pathogenicity. To determine whether current practice reflects this definition, ClinVar classifications were tracked from 2016 to 2019. During that period, between 83.8 and 99.1% of likely pathogenic classifications were reclassified as pathogenic, depending on whether LP to VUS reclassifications are included and on how these classifications are categorized.

PurposeProper interpretation of genomic variants is critical to successful medical decision making based on genetic testing results. A fundamental prerequisite to accurate variant interpretation is the clear understanding of the clinical validity of gene-disease relationships. The Clinical Genome Resource (ClinGen) has developed a semi-quantitative framework to assign clinical validity to gene-disease relationships.MethodsThe ClinGen Hearing Loss Gene Curation Expert Panel (HL GCEP) uses this framework to perform evidence-based curations of genes present on testing panels from 17 clinical laboratories in the Genetic Testing Registry. The HL GCEP curated and reviewed 142 genes and 164 gene-disease pairs, including 105 nonsyndromic and 59 syndromic forms of hearing loss.ResultsThe final outcome included 82 Definitive (50%), 12 Strong (7%), 25 Moderate (15%), 32 Limited (20%), 10 Disputed (6%), and 3 Refuted (2%) classifications. The summary of each curation is date stamped with the HL GCEP approval, is live, and will be kept up-to-date on the ClinGen website (https://search.clinicalgenome.org/kb/gene-validity).ConclusionThis gene curation approach serves to optimize the clinical sensitivity of genetic testing while reducing the rate of uncertain or ambiguous test results caused by the interrogation of genes with insufficient evidence of a disease link.

Identifying genes and variants contributing to rare disease phenotypes and Mendelian conditions informs biology and medicine, yet potential phenotypic consequences for variation of >75% of the ~20,000 annotated genes in the human genome are lacking. Technical advances to assess rare variation genome-wide, particularly exome sequencing (ES), enabled establishment in the United States of the National Institutes of Health (NIH)-supported Centers for Mendelian Genomics (CMGs) and have facilitated collaborative studies resulting in novel “disease gene” discoveries. Pedigree-based genomic studies and rare variant analyses in families with suspected Mendelian conditions have led to the elucidation of hundreds of novel disease genes and highlighted the impact of de novo mutational events, somatic variation underlying nononcologic traits, incompletely penetrant alleles, phenotypes with high locus heterogeneity, and multilocus pathogenic variation. Herein, we highlight CMG collaborative discoveries that have contributed to understanding both rare and common diseases and discuss opportunities for future discovery in single-locus Mendelian disorder genomics. Phenotypic annotation of all human genes; development of bioinformatic tools and analytic methods; exploration of non-Mendelian modes of inheritance including reduced penetrance, multilocus variation, and oligogenic inheritance; construction of allelic series at a locus; enhanced data sharing worldwide; and integration with clinical genomics are explored. Realizing the full contribution of rare disease research to functional annotation of the human genome, and further illuminating human biology and health, will lay the foundation for the Precision Medicine Initiative.

Hermle, Tobias/0000-0002-0441-7749, WOS: 000508269600010, PubMed: 31732614, Background Mutations in about 50 genes have been identified as monogenic causes of nephrotic syndrome, a frequent cause of CKD. These genes delineated the pathogenetic pathways and rendered significant insight into podocyte biology. Methods We used whole-exome sequencing to identify novel monogenic causes of steroid-resistant nephrotic syndrome (SRNS). We analyzed the functional significance of an SRNS-associated gene in vitro and in podocyte-like Drosophila nephrocytes. Results We identified hemizygous missense mutations in the gene TBC1D8B in five families with nephrotic syndrome. Coimmunoprecipitation assays indicated interactions between TBC1D8B and active forms of RAB11. Silencing TBC1D8B in HEK293T cells increased basal autophagy and exocytosis, two cellular functions that are independently regulated by RAB11. This suggests that TBC1D8B plays a regulatory role by inhibiting endogenous RAB11. Coimmunoprecipitation assays showed TBC1D8B also interacts with the slit diaphragm protein nephrin, and colocalizes with it in immortalized cell lines. Overexpressed murine Tbc1d8b with patient-derived mutations had lower affinity for endogenous RAB11 and nephrin compared with wild-type Tbc1d8b protein. Knockdown of Tbc1d8b in Drosophila impaired function of the podocyte-like nephrocytes, and caused mistrafficking of Sns, the Drosophila ortholog of nephrin. Expression of Rab11 RNAi in nephrocytes entailed defective delivery of slit diaphragm protein to the membrane, whereas RAB11 overexpression revealed a partial phenotypic overlap to Tbc1d8b loss of function. Conclusions Novel mutations in TBC1D8B are monogenic causes of SRNS. This gene inhibits RAB11. Our findings suggest that RAB11-dependent vesicular nephrin trafficking plays a role in the pathogenesis of nephrotic syndrome., Deutsche ForschungsgemeinschaftGerman Research Foundation (DFG) [HE 7456/3-1]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [DK076683, U54HG006504]; MOTI-VATE program of the Medical Faculty of theUniversity of Freiburg; National Human Genome Research InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Human Genome Research Institute (NHGRI) [UM1HG008900]; National Eye InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Eye Institute (NEI); National Heart, Lung, and Blood InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI); T32 Ruth L. Kirschstein Institutional National Research Service AwardUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [DK007527]; Charite-Universitatsmedizin Berlin; Berlin Institute of Health; German Research FoundationGerman Research Foundation (DFG) [RO4341/2-1]; Excellence Initiative of the German Research FoundationGerman Research Foundation (DFG) [EXC 294]; Ministry of Science, Research and the Arts of Baden-Wurttemberg [Az: 33-7532.20]; Deutsche Forschungsgemeinschaft Collaborative Research CentreGerman Research Foundation (DFG) [KIDGEM1140]; Federal Ministry of Education and ResearchFederal Ministry of Education & Research (BMBF) [01GM1515C]; NATIONAL HUMAN GENOME RESEARCH INSTITUTEUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Human Genome Research Institute (NHGRI) [UM1HG008900, UM1HG008900, UM1HG008900, UM1HG008900, UM1HG008900] Funding Source: NIH RePORTER; NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASESUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Diabetes & Digestive & Kidney Diseases (NIDDK) [T32DK007527, T32DK007527, T32DK007527, T32DK007527, T32DK007527] Funding Source: NIH RePORTER, This research was supported by grants from the Deutsche Forschungsgemeinschaft to Dr. Hermle (HE 7456/3-1) and the National Institutes of Health to Dr. Hildebrandt (DK076683), and to the Yale Center for Mendelian Genomics (U54HG006504). Ms. Kampf was supported by the MOTI-VATE program of the Medical Faculty of theUniversity of Freiburg. the Broad CMG was funded by a grant from the National Human Genome Research Institute (UM1HG008900), the National Eye Institute, and the National Heart, Lung, and Blood Institute. A. Onuchic-Whitford acknowledges support from the T32 Ruth L. Kirschstein Institutional National Research Service Award (DK007527). Dr. Schrezenmeier is participant in the BIH-Charite Clinician Scientist Program funded by the Charite-Universitatsmedizin Berlin and the Berlin Institute of Health. Dr. Romer acknowledges the support by the German Research Foundation (grant RO4341/2-1), the Excellence Initiative of the German Research Foundation (EXC 294), and the Ministry of Science, Research and the Arts of Baden-Wurttemberg (Az: 33-7532.20). Dr. Bergmann acknowledges support from the Deutsche Forschungsgemeinschaft Collaborative Research Centre (KIDGEM1140) and the Federal Ministry of Education and Research (01GM1515C).

Mucin-1 kidney disease, previously described as medullary cystic kidney disease type 1 (MCKD1, OMIM 174000), is an autosomal dominant tubulointerstitial kidney disease recently shown to be caused by a single-base insertion within the variable number tandem repeat region of the MUC1 gene. Because of variable age of disease onset and often subtle signs and symptoms, clinical diagnosis of mucin-1 kidney disease and differentiation from other forms of hereditary kidney disease have been difficult. The causal insertion resides in a variable number tandem repeat region with high GC content, which has made detection by standard next-generation sequencing impossible to date. The inherently difficult nature of this mutation required an alternative method for routine detection and clinical diagnosis of the disease. We therefore developed and validated a mass spectrometry–based probe extension assay with a series of internal controls to detect the insertion event using 24 previously characterized positive samples from patients with mucin-1 kidney disease and 24 control samples known to be wild type for the variant. Validation results indicate an accurate and reliable test for clinically establishing the molecular diagnosis of mucin-1 kidney disease with 100% sensitivity and specificity across 275 tests called., Carlos Slim Foundation. Slim Initiative for Genomic Medicine

With next generation sequencing technology improvement and cost reductions, it has become technically feasible to sequence a large number of genes in one diagnostic test. This is especially relevant for diseases with large genetic and/or phenotypic heterogeneity, such as hearing loss. However, variant interpretation remains the major bottleneck. This is further exacerbated by the lack in the clinical genetics community of consensus criteria for defining the evidence necessary to include genes on targeted disease panels or in genomic reports, and the consequent risk of reporting variants in genes with no relevance to disease. We describe a systematic evidence-based approach for assessing gene–disease associations and for curating relevant genes for different disease aspects, including mode of inheritance, phenotypic severity, and mutation spectrum. By applying this approach to clinically available hearing loss gene panels with a total of 163 genes, we show that a significant number (45%) of genes lack sufficient evidence of association with disease and thus are expected to increase uncertainty and patient anxiety, in addition to intensifying the interpretation burden. Information about all curated genes is summarized. Our retrospective analysis of 539 hearing loss cases tested by our previous OtoGenomeV2 panel demonstrates the impact of including genes with weak disease association in laboratory wet-bench and interpretation processes. Our study is, to our knowledge, the first to highlight the urgent need for defining the clinical validity of gene–disease relationships for more efficient and accurate clinical testing and reporting. Genet Med 18 6, 545–553.

BACKGROUND There are 346 serologically defined red blood cell (RBC) antigens and 33 serologically defined platelet (PLT) antigens, most of which have known genetic changes in 45 RBC or six PLT genes that correlate with antigen expression. Polymorphic sites associated with antigen expression in the primary literature and reference databases are annotated according to nucleotide positions in cDNA. This makes antigen prediction from next-generation sequencing data challenging, since it uses genomic coordinates. STUDY DESIGN AND METHODS The conventional cDNA reference sequences for all known RBC and PLT genes that correlate with antigen expression were aligned to the human reference genome. The alignments allowed conversion of conventional cDNA nucleotide positions to the corresponding genomic coordinates. RBC and PLT antigen prediction was then performed using the human reference genome and whole genome sequencing (WGS) data with serologic confirmation. RESULTS Some major differences and alignment issues were found when attempting to convert the conventional cDNA to human reference genome sequences for the following genes: ABO, A4GALT, RHD, RHCE, FUT3, ACKR1 (previously DARC), ACHE, FUT2, CR1, GCNT2, and RHAG. However, it was possible to create usable alignments, which facilitated the prediction of all RBC and PLT antigens with a known molecular basis from WGS data. Traditional serologic typing for 18 RBC antigens were in agreement with the WGS-based antigen predictions, providing proof of principle for this approach. CONCLUSION Detailed mapping of conventional cDNA annotated RBC and PLT alleles can enable accurate prediction of RBC and PLT antigens from whole genomic sequencing data.

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

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

The Clinical Genome Resource (ClinGen)’s work to develop a knowledge base to support the understanding of genes and variants for use in precision medicine and research depends on robust, broadly-applicable, and adaptable technical standards for sharing data and information. To forward these goals, ClinGen has joined with the Global Alliance for Genomics and Health (GA4GH) to support the development of open, freely-available technical standards and regulatory frameworks for secure and responsible sharing of genomic and health-related data. In its capacity as one of 15 inaugural GA4GH “Driver Projects”, ClinGen is providing input on the key standards needs of the global genomics community, and has committed to participating on GA4GH Work Streams to support the development of: i) a standard model for computer-readable variant representation; ii) a data model for linking variant data to annotations; iii) a specification to enable sharing of genomic variant knowledge and associated clinical interpretations, and; iv) a set of best practices for use of phenotype and disease ontologies. ClinGen’s participation as a GA4GH Driver Project will provide a robust environment to test drive emerging genomic knowledge sharing standards and prove their utility among the community, while accelerating the construction of the ClinGen evidence base.

Precision medicine is predicted to revolutionize the clinical practice of medicine, in part by using molecular biomarkers to assess patients' risk, prognosis, and therapeutic response more precisely. However, reliance on biomarkers could present challenges for diverse populations that are not equitably represented in precision medicine research. We examined the populations included in genomic studies whose data were available in the following two public databases: the Genome-Wide Association Study Catalog and the database of Genotypes and Phenotypes. We found significantly fewer studies of African, Latin American, and Asian ancestral populations in comparison to European populations. These patterns were consistent across both data types and disease areas. While the number of genomic research studies that include non-European populations is modestly improving, the overall numbers are still low, and decisive action is needed now to implement the changes necessary for realizing the promise of precision medicine for all.

Variant interpretation depends on accurate annotations using biologically relevant transcripts. We have developed a systematic strategy for designating primary transcripts, and applied it to 109 hearing loss-associated genes that were divided into 3 categories. Category 1 genes (n=38) had a single transcript, Category 2 genes (n=32) had multiple transcripts, but a single transcript was sufficient to represent all exons, and Category 3 genes (n=38) had multiple transcripts with unique exons. Transcripts were curated with respect to gene expression reported in the literature and the Genotype-Tissue Expression Project. In addition, high frequency loss of function variants in the Genome Aggregation Database, and disease-causing variants in ClinVar and the Human Gene Mutation Database across the 109 genes were queried. These data were used to classify exons as "clinically relevant", "uncertain significance", or "clinically insignificant". Interestingly, 7% of all exons, containing >124 "clinically significant" variants, were of “uncertain significance”. Finally, we used exon-level next generation sequencing quality metrics generated at two clinical labs, and identified a total of 43 technically challenging exons in 20 different genes that had inadequate coverage and/or homology issues which might lead to false variant calls. We have demonstrated that transcript analysis plays a critical role in accurate clinical variant interpretation.

Variant interpretation depends on accurate annotations using biologically relevant transcripts. We have developed a systematic strategy for designating primary transcripts and have applied it to 109 hearing loss–associated genes that were divided into three categories. Category 1 genes (n = 38) had a single transcript; category 2 genes (n = 33) had multiple transcripts, but a single transcript was sufficient to represent all exons; and category 3 genes (n = 38) had multiple transcripts with unique exons. Transcripts were curated with respect to gene expression reported in the literature and the Genotype-Tissue Expression Project. In addition, high-frequency loss-of-function variants in the Genome Aggregation Database and disease-causing variants in ClinVar and the Human Gene Mutation Database across the 109 genes were queried. These data were used to classify exons as clinically significant, insignificant, or of uncertain significance. Interestingly, 6% of all exons, containing 124 reportedly disease-causing variants, were of uncertain significance. Finally, we used exon-level next-generation sequencing quality metrics generated at two clinical laboratories and identified a total of 43 technically challenging exons in 20 different genes that had inadequate coverage and/or homology issues that might lead to false-variant calls. We have demonstrated that transcript analysis plays a critical role in accurate clinical variant interpretation.

ClinVar Miner is a Web-based suite that utilizes the data held in the National Center for Biotechnology Information's ClinVar archive. The goal is to render the data more accessible to processes pertaining to conflict resolution of variant interpretation as well as tracking details of data submission and data management for detailed variant curation. Here, we establish the use of these tools to address three separate use cases and to perform analyses across submissions. We demonstrate that the ClinVar Miner tools are an effective means to browse and consolidate data for variant submitters, curation groups, and general oversight. These tools are also relevant to the variant interpretation community in general.

Pathogenic variants at the DFNB1 locus encompassing the GJB2 and GJB6 genes account for 50% of autosomal-recessive, congenital nonsyndromic hearing loss in the United States. Most cases are caused by sequence variants within the GJB2 gene, but a significant number of DFNB1 patients carry a large deletion (GJB6-D13S1830) in trans with a GJB2 variant. This deletion lies upstream of GJB2 and was shown to reduce GJB2 expression by disrupting unidentified regulatory elements. First-tier genetic testing for hearing loss includes GJB2 sequence and GJB6-D13S1830 deletion analysis; however, several other deletions in this locus, each with distinct breakpoints, have been reported in DFNB1 patients and are missed by current panels. Here, we report the development of a targeted droplet digital polymerase chain reaction-based assay for comprehensive copy-number analysis at the DFNB1 locus that detects all deletions reported to date. This assay increased detection rates in a multiethnic cohort of 87 hearing loss patients with only one identified pathogenic GJB2 variant. We identify two deletions, one of which is novel, in two patients (2/87 or 2.3%), suggesting that other pathogenic deletions at the DFNB1 locus may be missed. Mapping the assayed DFNB1 deletions also revealed a ∼ 95 kb critical region, which may harbor the GJB2 regulatory element(s).