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

Deep multiple-instance learning accurately predicts gene haploinsufficiency and deletion pathogenicity

Copy number losses (deletions) are a major contributor to the etiology of severe genetic disorders. Although haploinsufficient genes play a critical role in deletion pathogenicity, current methods for deletion pathogenicity prediction fail to integrate multiple lines of evidence for haploinsufficiency at the gene level, limiting their power to pinpoint deleterious deletions associated with genetic disorders. Here we introduce DosaCNV, a deep multiple-instance learning framework that, for the first time, models deletion pathogenicity jointly with gene haploinsufficiency. By integrating over 30 gene-level features potentially predictive of haploinsufficiency, DosaCNV shows unmatched performance in prioritizing pathogenic deletions associated with a broad spectrum of genetic disorders. Furthermore, DosaCNV outperforms existing methods in predicting gene haploinsufficiency even though it is not trained on known haploinsufficient genes. Finally, DosaCNV leverages a state-of-the-art technique to quantify the contributions of individual gene-level features to haploinsufficiency, allowing for human-understandable explanations of model predictions. Altogether, DosaCNV is a powerful computational tool for both fundamental and translational research.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Further delineation of EBF3-related syndromic neurodevelopmental disorder in twelve Chinese patients

Neurodevelopmental disorders (NDDs) have heterogeneity in both clinical characteristics and genetic factors. EBF3 is a recently discovered gene associated with a syndromic form of NDDs characterized by hypotonia, ataxia and facial features. In this study, we report twelve unrelated individuals with EBF3 variants using next-generation sequencing. Five missense variants (four novel variants and one known variant) and seven copy number variations (CNVs) of EBF3 gene were identified. All of these patients exhibited developmental delay/intellectual disability. Ataxia was observed in 33% (6/9) of the patients, and abnormal muscle tone was observed in 55% (6/11) of the patients. Aberrant MRI reports were noted in 64% (7/11) of the patients. Four novel missense variants were all located in the DNA-binding domain. The pathogenicity of these variants was validated by in vitro experiments. We found that the subcellular protein localization of the R152C and F211L mutants was changed, and the distribution pattern of the R163G mutant was changed from even to granular. Luciferase assay results showed that the four EBF3 mutants' transcriptional activities were all significantly decreased (p < 0.01). Our study further expanded the gene mutation spectrum of EBF3-related NDD.

Using coding and non-coding rare variants to target candidate genes in patients with severe tinnitus

Tinnitus is the phantom percept of an internal non-verbal set of noises and tones. It is reported by 15% of the population and it is usually associated with hearing and/or brain disorders. The role of structural variants (SVs) in coding and non-coding regions has not been investigated in patients with severe tinnitus. In this study, we performed whole-genome sequencing in 97 unrelated Swedish individuals with chronic tinnitus (TIGER cohort). Rare single nucleotide variants (SNV), large structural variants (LSV), and copy number variations (CNV) were retrieved to perform a gene enrichment analysis in TIGER and in a subgroup of patients with severe tinnitus (SEVTIN, n = 34), according to the tinnitus handicap inventory (THI) scores. An independent exome sequencing dataset of 147 Swedish tinnitus patients was used as a replication cohort (JAGUAR cohort) and population-specific datasets from Sweden (SweGen) and Non-Finish Europeans (NFE) from gnomAD were used as control groups. SEVTIN patients showed a higher prevalence of hyperacusis, hearing loss, and anxiety when they were compared to individuals in the TIGER cohort. We found an enrichment of rare missense variants in 6 and 8 high-constraint genes in SEVTIN and TIGER cohorts, respectively. Of note, an enrichment of missense variants was found in the CACNA1E gene in both SEVTIN and TIGER. We replicated the burden of missense variants in 9 high-constrained genes in the JAGUAR cohort, including the gene NAV2, when data were compared with NFE. Moreover, LSVs in constrained regions overlapping CACNA1E, NAV2, and TMEM132D genes were observed in TIGER and SEVTIN.

A cross-disorder dosage sensitivity map of the human genome

Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics.

The Gene Curation Coalition: A global effort to harmonize gene-disease evidence resources

PURPOSE

Several groups and resources provide information that pertains to the validity of gene-disease relationships used in genomic medicine and research; however, universal standards and terminologies to define the evidence base for the role of a gene in disease and a single harmonized resource were lacking. To tackle this issue, the Gene Curation Coalition (GenCC) was formed.

METHODS

The GenCC drafted harmonized definitions for differing levels of gene-disease validity on the basis of existing resources, and performed a modified Delphi survey with 3 rounds to narrow the list of terms. The GenCC also developed a unified database to display curated gene-disease validity assertions from its members.

RESULTS

On the basis of 241 survey responses from the genetics community, a consensus term set was chosen for grading gene-disease validity and database submissions. As of December 2021, the database contained 15,241 gene-disease assertions on 4569 unique genes from 12 submitters. When comparing submissions to the database from distinct sources, conflicts in assertions of gene-disease validity ranged from 5.3% to 13.4%.

CONCLUSION

Terminology standardization, sharing of gene-disease validity classifications, and resolution of curation conflicts will facilitate collaborations across international curation efforts and in turn, improve consistency in genetic testing and variant interpretation.

Variant Interpretation: UCSC Genome Browser Recommended Track Sets

The UCSC Genome Browser has been an important tool for genomics and clinical genetics since the sequence of the human genome was first released in 2000. As it has grown in scope to display more types of data it has also grown more complicated. The data, which are dispersed at many locations worldwide, are collected into one view on the Browser, where the graphical interface presents the data in one location. This supports the expertise of the researcher to interpret variants in the genome. Because the analysis of Single Nucleotide Variants (SNVs) and Copy Number Variants (CNVs) require interpretation of data at very different genomic scales, different data resources are required. We present here several Recommended Track Sets designed to facilitate the interpretation of variants in the clinic, offering quick access to datasets relevant to the appropriate scale. This article is protected by copyright. All rights reserved.

A patient with compound heterozygosity of SMPD4: Another example of utility of exome-based copy number analysis in autosomal recessive disorders

For the efficient diagnosis of rare and undiagnosed diseases, the parallel detection of copy number variants (CNVs) and single nucleotide variants using exome analysis is required. Recently, our group reported the usefulness of a program called EXCAVATOR2, which screens for CNVs from aligned exome data in bam format. This method is expected to contribute to the identification of structural variants and to improve the diagnosis rate, especially for the diagnosis of autosomal recessive disease, when a conventional exome analysis identifies a pathogenic variant in one allele but not the other. Here we report a 2-year-old Japanese boy with an undiagnosed disease. He had severe neonatal asphyxia, severe intellectual disability, intractable seizures, cerebellar and brainstem hypoplasia and dysmorphic features including a prominent supraorbital ridge, thin upper lip, and prominent antihelix. An exome analysis reinforced with a copy number analysis using the EXCAVATOR2 method revealed that the patient had a hemizygous variant in chr2(GRCh37):g.130925108G>A, NM_017951.4 c.832C>T, p.(Arg278*) in SMPD4 that was derived from his father and a deletion of SMPD4 derived from his mother. The presence of the deletion spanning SMPD4 was confirmed by short-read and long-read whole-genome sequencing. The successful diagnosis of this reported patient demonstrates the diagnostic utility of EXCAVATOR2 and overcomes the weakness of exome analysis for the detection of autosomal recessive diseases in nonconsanguineous families, significantly impacting genetic counseling for family planning.

AutoCNV: a semiautomatic CNV interpretation system based on the 2019 ACMG/ClinGen Technical Standards for CNVs

Background

The American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen) presented technical standards for interpretation and reporting of constitutional copy-number variants in 2019 (the standards). Although ClinGen developed a web-based CNV classification calculator based on scoring metrics, it can only track and tally points that have been assigned based on observed evidence. Here, we developed AutoCNV (a semiautomatic automated CNV interpretation system) based on the standards, which can automatically generate predictions on 18 and 16 criteria for copy number loss and gain, respectively.

Results

We assessed the performance of AutoCNV using 72 CNVs evaluated by external independent reviewers and 20 illustrative case examples. Using AutoCNV, it showed that 100 % (72/72) and 95 % (19/20) of CNVs were consistent with the reviewers’ and ClinGen-verified classifications, respectively. AutoCNV only required an average of less than 5 milliseconds to obtain the result for one CNV with automated scoring. We also applied AutoCNV for the interpretation of CNVs from the ClinVar database and the dbVar database. We also developed a web-based version of AutoCNV (wAutoCNV).

Conclusions

AutoCNV may serve to assist users in conducting in-depth CNV interpretation, to accelerate and facilitate the interpretation process of CNVs and to improve the consistency and reliability of CNV interpretation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08011-4.

Characterising the loss-of-function impact of 5' untranslated region variants in 15,708 individuals

Upstream open reading frames (uORFs) are tissue-specific cis-regulators of protein translation. Isolated reports have shown that variants that create or disrupt uORFs can cause disease. Here, in a systematic genome-wide study using 15,708 whole genome sequences, we show that variants that create new upstream start codons, and variants disrupting stop sites of existing uORFs, are under strong negative selection. This selection signal is significantly stronger for variants arising upstream of genes intolerant to loss-of-function variants. Furthermore, variants creating uORFs that overlap the coding sequence show signals of selection equivalent to coding missense variants. Finally, we identify specific genes where modification of uORFs likely represents an important disease mechanism, and report a novel uORF frameshift variant upstream of NF2 in neurofibromatosis. Our results highlight uORF-perturbing variants as an under-recognised functional class that contribute to penetrant human disease, and demonstrate the power of large-scale population sequencing data in studying non-coding variant classes.

Transcript expression-aware annotation improves rare variant interpretation

The acceleration of DNA sequencing in samples from patients and population studies has resulted in extensive catalogues of human genetic variation, but the interpretation of rare genetic variants remains problematic. A notable example of this challenge is the existence of disruptive variants in dosage-sensitive disease genes, even in apparently healthy individuals. Here, by manual curation of putative loss-of-function (pLoF) variants in haploinsufficient disease genes in the Genome Aggregation Database (gnomAD)1, we show that one explanation for this paradox involves alternative splicing of mRNA, which allows exons of a gene to be expressed at varying levels across different cell types. Currently, no existing annotation tool systematically incorporates information about exon expression into the interpretation of variants. We develop a transcript-level annotation metric known as the 'proportion expressed across transcripts', which quantifies isoform expression for variants. We calculate this metric using 11,706 tissue samples from the Genotype Tissue Expression (GTEx) project2 and show that it can differentiate between weakly and highly evolutionarily conserved exons, a proxy for functional importance. We demonstrate that expression-based annotation selectively filters 22.8% of falsely annotated pLoF variants found in haploinsufficient disease genes in gnomAD, while removing less than 4% of high-confidence pathogenic variants in the same genes. Finally, we apply our expression filter to the analysis of de novo variants in patients with autism spectrum disorder and intellectual disability or developmental disorders to show that pLoF variants in weakly expressed regions have similar effect sizes to those of synonymous variants, whereas pLoF variants in highly expressed exons are most strongly enriched among cases. Our annotation is fast, flexible and generalizable, making it possible for any variant file to be annotated with any isoform expression dataset, and will be valuable for the genetic diagnosis of rare diseases, the analysis of rare variant burden in complex disorders, and the curation and prioritization of variants in recall-by-genotype studies.

Haploinsufficiency of the basic helix-loop-helix transcription factor HAND2 causes congenital heart defects

Congenital heart defects (CHDs) are caused by a disruption in heart morphogenesis, which is dependent, in part, on a network of transcription factors (TFs) that regulate myocardial development. Heterozygous sequence variants in the basic helix-loop-helix TF gene heart and neural crest derivatives expressed 2 (HAND2) have been reported among some patients with CHDs; however, HAND2 has not yet been established as a Mendelian disease gene. We report a 31-month-old male with unicommissural unicuspid aortic valve, moderate aortic stenosis, and mild pulmonic stenosis. Chromosome analysis revealed a normal 46,XY karyotype, and a CHD sequencing panel was negative for pathogenic variants in NKX2.5, GATA4, TBX5, and CHD7. However, chromosomal microarray (CMA) testing identified a heterozygous 546.0-kb deletion on chromosome 4q34.1 (174364195_174910239[GRCh37/hg19]) that included exons 1 and 2 of SCRG1, HAND2, and HAND2-AS1. Familial CMA testing determined that the deletion was paternally inherited, which supported a likely pathogenic classification as the proband's father had previously undergone surgery for Tetralogy of Fallot. The family history was also notable for a paternal uncle who had previously died from complications related to an unknown heart defect. Taken together, this first report of a HAND2 and HAND2-AS1 deletion in a family with CHDs strongly supports haploinsufficiency of HAND2 as an autosomal dominant cause of CHD.

Genome sequencing of human in vitro fertilisation embryos for pathogenic variation screening

Whole-genome sequencing of preimplantation human embryos to detect and screen for genetic diseases is a technically challenging extension to preconception screening. Combining preconception genetic screening with preimplantation testing of human embryos facilitates the detection of de novo mutations and self-validates transmitted variant detection in both the reproductive couple and the embryo’s samples. Here we describe a trio testing workflow that involves whole-genome sequencing of amplified DNA from biopsied embryo trophectoderm cells and genomic DNA from both parents. Variant prediction software and annotation databases were used to assess variants of unknown significance and previously not described de novo variants in five single-gene preimplantation genetic testing couples and eleven of their embryos. Pathogenic variation, tandem repeat, copy number and structural variations were examined against variant calls for compound heterozygosity and predicted disease status was ascertained. Multiple trio testing showed complete concordance with known variants ascertained by single-nucleotide polymorphism array and uncovered de novo and transmitted pathogenic variants. This pilot study describes a method of whole-genome sequencing and analysis for embryo selection in high-risk couples to prevent early life fatal genetic conditions that adversely affect the quality of life of the individual and families.

Challenges in the clinical interpretation of small de novo copy number variants in neurodevelopmental disorders

In clinical genetics, the need to discriminate between benign and pathogenic variants identified in patients with neurodevelopmental disorders is an absolute necessity. Copy number variants (CNVs) of small size can enable the identification of genes that are critical for neurologic development. However, assigning a definite association with a specific disorder is a difficult task. Among 328 trios analyzed over seven years of activity in a single laboratory, we identified 19 unrelated patients (5.8%) who carried a small (<500 kb) de novo CNV. Four patients had an additional independent de novo CNV. Nine had a variant that could be assigned as definitely pathogenic, whereas the remaining CNVs were considered as variants of unknown significance (VUS). We report clinical and molecular findings of patients harboring VUS. We reviewed the medical literature available for genes impacted by CNVs, obtained the probability of truncating loss-of-function intolerance, and compared overlapping CNVs reported in databases. The classification of small non-recurrent CNVs remains difficult but, among our findings, we provide support for a role of SND1 in the susceptibility of autism, describe a new case of the rare 17p13.1 microduplication syndrome, and report an X-linked duplication involving KIF4A and DLG3 as a likely cause of epilepsy.

Genomic variant sharing: a position statement

Sharing de-identified genetic variant data is essential for the practice of genomic medicine and is demonstrably beneficial to patients. Robust genetic diagnoses that inform medical management cannot be made accurately without reference to genetic test results from other patients, as well as population controls. Errors in this process can result in delayed, missed or erroneous diagnoses, leading to inappropriate or missed medical interventions for the patient and their family. The benefits of sharing individual genetic variants, and the harms of not sharing them, are numerous and well-established. Databases and mechanisms already exist to facilitate deposition and sharing of pseudonomised genetic variants, but clarity and transparency around best practice is needed to encourage widespread use, prevent inconsistencies between different communities, maximise individual privacy and ensure public trust. We therefore recommend that widespread sharing of a small number of individual genetic variants associated with limited clinical information should become standard practice in genomic medicine. Information robustly linking genetic variants with specific conditions is fundamental biological knowledge, not personal information, and therefore should not require consent to share. For additional case-level detail about individual patients or more extensive genomic information, which is often essential for clinical interpretation, it may be more appropriate to use a controlled-access model for data sharing, with the ultimate aim of making as much information as open and de-identified as possible with appropriate consent.