Detecting missed diagnoses of spinal muscular atrophy in genome, exome, and panel sequencing datasets

Spinal muscular atrophy (SMA) is a genetic disorder that causes progressive degeneration of lower motor neurons and the subsequent loss of muscle function throughout the body. It is the second most common recessive disorder in individuals of European descent and is present in all populations. Accurate tools exist for diagnosing SMA from short read and long read genome sequencing data. However, there are no publicly available tools for GRCh38-aligned data from panel or exome sequencing assays which continue to be used as first line tests for neuromuscular disorders. We therefore developed and extensively validated a new tool - SMA Finder - that can diagnose SMA not only in genome, but also exome and targeted sequencing samples aligned to GRCh37, GRCh38, or T2T-CHM13. It works by evaluating aligned reads that overlap the c.840 position of SMN1 and SMN2 in order to detect the most common molecular causes of SMA. We applied SMA Finder to 16,626 exomes and 3,911 genomes from heterogeneous rare disease cohorts sequenced at the Broad Institute Center for Mendelian Genomics as well as 1,157 exomes and 8,762 targeted sequencing samples from Tartu University Hospital. SMA Finder correctly identified all 16 known SMA cases and reported nine novel diagnoses which have since been confirmed by clinical testing, with another four novel diagnoses undergoing validation. Notably, out of the 29 total SMA positive cases, 21 had an initial clinical diagnosis of muscular dystrophy, congenital myasthenic syndrome, or congenital myopathy. This underscored the frequency with which SMA can be misdiagnosed as other neuromuscular disorders and confirmed the utility of using SMA Finder to reanalyze phenotypically diverse neuromuscular disease cohorts. Finally, we evaluated SMA Finder on 198,868 individuals that had both exome and genome sequencing data within the UK Biobank (UKBB) and found that SMA Finder's overall false positive rate was less than 1 / 200,000 exome samples, and its positive predictive value (PPV) was 96%. We also observed 100% concordance between UKBB exome and genome calls. This analysis showed that, even though it is located within a segmental duplication, the most common causal variant for SMA can be detected with comparable accuracy to monogenic disease variants in non-repetitive regions. Additionally, the high PPV demonstrated by SMA Finder, the existence of treatment options for SMA in which early diagnosis is imperative for therapeutic benefit, as well as widespread availability of clinical confirmatory testing for SMA, may warrant the addition of SMN1 to the ACMG list of genes with reportable secondary findings after genome and exome sequencing.

Exome copy number variant detection, analysis and classification in a large cohort of families with undiagnosed rare genetic disease

Copy number variants (CNVs) are significant contributors to the pathogenicity of rare genetic diseases and with new innovative methods can now reliably be identified from exome sequencing. Challenges still remain in accurate classification of CNV pathogenicity. CNV calling using GATK-gCNV was performed on exomes from a cohort of 6,633 families (15,759 individuals) with heterogeneous phenotypes and variable prior genetic testing collected at the Broad Institute Center for Mendelian Genomics of the GREGoR consortium. Each family's CNV data was analyzed using the seqr platform and candidate CNVs classified using the 2020 ACMG/ClinGen CNV interpretation standards. We developed additional evidence criteria to address situations not covered by the current standards. The addition of CNV calling to exome analysis identified causal CNVs for 173 families (2.6%). The estimated sizes of CNVs ranged from 293 bp to 80 Mb with estimates that 44% would not have been detected by standard chromosomal microarrays. The causal CNVs consisted of 141 deletions, 15 duplications, 4 suspected complex structural variants (SVs), 3 insertions and 10 complex SVs, the latter two groups being identified by orthogonal validation methods. We interpreted 153 CNVs as likely pathogenic/pathogenic and 20 CNVs as high interest variants of uncertain significance. Calling CNVs from existing exome data increases the diagnostic yield for individuals undiagnosed after standard testing approaches, providing a higher resolution alternative to arrays at a fraction of the cost of genome sequencing. Our improvements to the classification approach advances the systematic framework to assess the pathogenicity of CNVs.

Critical assessment of variant prioritization methods for rare disease diagnosis within the Rare Genomes Project

Background

A major obstacle faced by rare disease families is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years, and causal variants are identified in under 50%. The Rare Genomes Project (RGP) is a direct-to-participant research study on the utility of genome sequencing (GS) for diagnosis and gene discovery. Families are consented for sharing of sequence and phenotype data with researchers, allowing development of a Critical Assessment of Genome Interpretation (CAGI) community challenge, placing variant prioritization models head-to-head in a real-life clinical diagnostic setting.

Methods

Predictors were provided a dataset of phenotype terms and variant calls from GS of 175 RGP individuals (65 families), including 35 solved training set families, with causal variants specified, and 30 test set families (14 solved, 16 unsolved). The challenge tasked teams with identifying the causal variants in as many test set families as possible. Ranked variant predictions were submitted with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on rank position of true positive causal variants and maximum F-measure, based on precision and recall of causal variants across EPCR thresholds.

Results

Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performing teams recalled the causal variants in up to 13 of 14 solved families by prioritizing high quality variant calls that were rare, predicted deleterious, segregating correctly, and consistent with reported phenotype. In unsolved families, newly discovered diagnostic variants were returned to two families following confirmatory RNA sequencing, and two prioritized novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant, in an unsolved proband with phenotype overlap with asparagine synthetase deficiency.

Conclusions

By objective assessment of variant predictions, we provide insights into current state-of-the-art algorithms and platforms for genome sequencing analysis for rare disease diagnosis and explore areas for future optimization. Identification of diagnostic variants in unsolved families promotes synergy between researchers with clinical and computational expertise as a means of advancing the field of clinical genome interpretation.

Wide range of phenotypic severity in individuals with late truncations unique to the predominant CDKL5 transcript in the brain

Cyclin-dependent kinase-like 5 (CDKL5) deficiency disorder (CDD) is caused by heterozygous or hemizygous variants in CDKL5 and is characterized by refractory epilepsy, cognitive and motor impairments, and cerebral visual impairment. CDKL5 has multiple transcripts, of which the longest transcripts, NM_003159 and NM_001037343, have been used historically in clinical laboratory testing. However, the transcript NM_001323289 is the most highly expressed in brain and contains 170 nucleotides at the 3' end of its last exon that are noncoding in other transcripts. Two truncating variants in this region have been reported in association with a CDD phenotype. To clarify the significance and range of phenotypes associated with late truncating variants in this region of the predominant transcript in the brain, we report detailed information on two individuals, updated clinical information on a third individual, and a summary of published and unpublished individuals reported in ClinVar. The two new individuals (one male and one female) each had a relatively mild clinical presentation including periods of pharmaco-responsive epilepsy, independent walking and limited purposeful communication skills. A previously reported male continued to have a severe phenotype. Overall, variants in this region demonstrate a range of clinical severity consistent with reports in CDD but with the potential for milder presentation.

De novo coding variants in the AGO1 gene cause a neurodevelopmental disorder with intellectual disability

BACKGROUND

High-impact pathogenic variants in more than a thousand genes are involved in Mendelian forms of neurodevelopmental disorders (NDD).

METHODS

This study describes the molecular and clinical characterisation of 28 probands with NDD harbouring heterozygous AGO1 coding variants, occurring de novo for all those whose transmission could have been verified (26/28).

RESULTS

A total of 15 unique variants leading to amino acid changes or deletions were identified: 12 missense variants, two in-frame deletions of one codon, and one canonical splice variant leading to a deletion of two amino acid residues. Recurrently identified variants were present in several unrelated individuals: p.(Phe180del), p.(Leu190Pro), p.(Leu190Arg), p.(Gly199Ser), p.(Val254Ile) and p.(Glu376del). AGO1 encodes the Argonaute 1 protein, which functions in gene-silencing pathways mediated by small non-coding RNAs. Three-dimensional protein structure predictions suggest that these variants might alter the flexibility of the AGO1 linker domains, which likely would impair its function in mRNA processing. Affected individuals present with intellectual disability of varying severity, as well as speech and motor delay, autistic behaviour and additional behavioural manifestations.

CONCLUSION

Our study establishes that de novo coding variants in AGO1 are involved in a novel monogenic form of NDD, highly similar to the recently reported AGO2-related NDD.

seqr: A web-based analysis and collaboration tool for rare disease genomics

Exome and genome sequencing have become the tools of choice for rare disease diagnosis, leading to large amounts of data available for analyses. To identify causal variants in these datasets, powerful filtering and decision support tools that can be efficiently used by clinicians and researchers are required. To address this need, we developed seqr - an open-source, web-based tool for family-based monogenic disease analysis that allows researchers to work collaboratively to search and annotate genomic callsets. To date, seqr is being used in several research pipelines and one clinical diagnostic lab. In our own experience through the Broad Institute Center for Mendelian Genomics, seqr has enabled analyses of over 10,000 families, supporting the diagnosis of more than 3,800 individuals with rare disease and discovery of over 300 novel disease genes. Here, we describe a framework for genomic analysis in rare disease that leverages seqr's capabilities for variant filtration, annotation, and causal variant identification, as well as support for research collaboration and data sharing. The seqr platform is available as open source software, allowing low-cost participation in rare disease research, and a community effort to support diagnosis and gene discovery in rare disease.

De novo variants in CACNA1E found in patients with intellectual disability, developmental regression and social cognition deficit but no seizures

BACKGROUND

De novo variants in the voltage-gated calcium channel subunit α1 E gene (CACNA1E) have been described as causative of epileptic encephalopathy with contractures, macrocephaly and dyskinesias.

METHODS

Following the observation of an index patient with developmental delay and autism spectrum disorder (ASD) without seizures who had a de novo deleterious CACNA1E variant, we screened GeneMatcher for other individuals with CACNA1E variants and neurodevelopmental phenotypes without epilepsy. The spectrum of pathogenic CACNA1E variants was compared to the mutational landscape of variants in the gnomAD control population database.

RESULTS

We identified seven unrelated individuals with intellectual disability, developmental regression and ASD-like behavioral profile, and notably without epilepsy, who had de novo heterozygous putatively pathogenic variants in CACNA1E. Age of onset of clinical manifestation, presence or absence of regression and degree of severity were variable, and no clear-cut genotype-phenotype association could be recognized. The analysis of disease-associated variants and their comparison to benign variants from the control population allowed for the identification of regions in the CACNA1E protein that seem to be intolerant to substitutions and thus more likely to harbor pathogenic variants. As in a few reported cases with CACNA1E variants and epilepsy, one patient showed a positive clinical behavioral response to topiramate, a specific calcium channel modulator.

LIMITATIONS

The significance of our study is limited by the absence of functional experiments of the effect of identified variants, the small sample size and the lack of systematic ASD assessment in all participants. Moreover, topiramate was given to one patient only and for a short period of time.

CONCLUSIONS

Our results indicate that CACNA1E variants may result in neurodevelopmental disorders without epilepsy and expand the mutational and phenotypic spectrum of this gene. CACNA1E deserves to be included in gene panels for non-specific developmental disorders, including ASD, and not limited to patients with seizures, to improve diagnostic recognition and explore the possible efficacy of topiramate.