Alternative transcripts in variant interpretation: the potential for missed diagnoses and misdiagnoses

CDKL5 deficiency disorder and other infantile-onset genetic epilepsies

AIM

To differentiate phenotypic features of individuals with CDKL5 deficiency disorder (CDD) from those of individuals with other infantile-onset epilepsies.

METHOD

We performed a retrospective cohort study and ascertained individuals with CDD and comparison individuals with infantile-onset epilepsy who had epilepsy gene panel testing. We reviewed records, updated variant classifications, and compared phenotypic features. Wilcoxon rank-sum tests and χ2 or Fisher's exact tests were performed for between-cohort comparisons.

RESULTS

We identified 137 individuals with CDD (110 females, 80.3%; median age at last follow-up 3 year 11 months) and 313 individuals with infantile-onset epilepsies (156 females, 49.8%; median age at last follow-up 5 years 2 months; 35% with genetic diagnosis). Features reported significantly more frequently in the CDD group than in the comparison cohort included developmental and epileptic encephalopathy (81% vs 66%), treatment-resistant epilepsy (95% vs 71%), sequential seizures (46% vs 6%), epileptic spasms (66% vs 42%, with hypsarrhythmia in 30% vs 48%), regression (52% vs 29%), evolution to Lennox-Gastaut syndrome (23% vs 5%), diffuse hypotonia (72% vs 36%), stereotypies (69% vs 11%), paroxysmal movement disorders (29% vs 17%), cerebral visual impairment (94% vs 28%), and failure to thrive (38% vs 22%).

INTERPRETATION

CDD, compared with other suspected or confirmed genetic epilepsies presenting in the first year of life, is more often characterized by a combination of treatment-resistant epilepsy, developmental and epileptic encephalopathy, sequential seizures, spasms without hypsarrhythmia, diffuse hypotonia, paroxysmal movement disorders, cerebral visual impairment, and failure to thrive. Defining core phenotypic characteristics will improve precision diagnosis and treatment.

Novel germline variants in KMT2C in Chinese patients with Kleefstra syndrome-2

Kleefstra syndrome (KLEFS) refers to a rare inherited neurodevelopmental disorder characterized by intellectual disability (ID), language and motor delays, behavioral abnormalities, abnormal facial appearance, and other variable clinical features. KLEFS is subdivided into two subtypes: Kleefstra syndrome-1 (KLEFS1, OMIM: 610253), caused by a heterozygous microdeletion encompassing the Euchromatic Histone Lysine Methyltransferase 1 (EHMT1) gene on chromosome 9q34.3 or pathogenic variants in the EHMT1 gene, and Kleefstra syndrome-2 (KLEFS2, OMIM: 617768), caused by pathogenic variants in the KMT2C gene. More than 100 cases of KLEFS1 have been reported with pathogenic variants in the EHMT1 gene. However, only 13 patients with KLEFS2 have been reported to date. In the present study, five unrelated Chinese patients were diagnosed with KLEFS2 caused by KMT2C variants through whole-exome sequencing (WES). We identified five different variants of the KMT2C gene in these patients: c.9166C>T (p.Gln3056*), c.9232_9247delCAGCGATCAGAACCGT (p.Gln3078fs*13), c.5068dupA (p.Arg1690fs*10), c.10815_10819delAAGAA (p.Lys3605fs*7), and c.6911_6912insA (p.Met2304fs*8). All five patients had a clinical profile similar to that of patients with KLEFS2. To analyze the correlation between the genotype and phenotype of KLEFS2, we examined 18 variants and their associated phenotypes in 18 patients with KLEFS2. Patients carrying KMT2C variants presented with a wide range of phenotypic defects and an extremely variable phenotype. We concluded that the core phenotypes associated with KMT2C variants were intellectual disability, facial dysmorphisms, language and motor delays, behavioral abnormalities, hypotonia, short stature, and weight loss. Additionally, sex may be one factor influencing the outcome. Our findings expand the phenotypic and genetic spectrum of KLEFS2 and help to clarify the genotype-phenotype correlation.

Bioinformatics of germline variant discovery for rare disease diagnostics: current approaches and remaining challenges

Next-generation sequencing (NGS) has revolutionized the field of rare disease diagnostics. Whole exome and whole genome sequencing are now routinely used for diagnostic purposes; however, the overall diagnosis rate remains lower than expected. In this work, we review current approaches used for calling and interpretation of germline genetic variants in the human genome, and discuss the most important challenges that persist in the bioinformatic analysis of NGS data in medical genetics. We describe and attempt to quantitatively assess the remaining problems, such as the quality of the reference genome sequence, reproducible coverage biases, or variant calling accuracy in complex regions of the genome. We also discuss the prospects of switching to the complete human genome assembly or the human pan-genome and important caveats associated with such a switch. We touch on arguably the hardest problem of NGS data analysis for medical genomics, namely, the annotation of genetic variants and their subsequent interpretation. We highlight the most challenging aspects of annotation and prioritization of both coding and non-coding variants. Finally, we demonstrate the persistent prevalence of pathogenic variants in the coding genome, and outline research directions that may enhance the efficiency of NGS-based disease diagnostics.

Implementing precision oncology for sarcoma patients: the CCCLMUmolecular tumor board experience

PURPOSE

Due to poor outcomes and limited treatment options, patients with advanced bone and soft tissue sarcomas (BS/STS) may undergo comprehensive molecular profiling of tumor samples to identify possible therapeutic targets. The aim of this study was to determine the impact of routine molecular profiling in the setting of a dedicated precision oncology program in patients with BS/STS in a German large-volume sarcoma center.

METHODS

92 BS/STS patients who received comprehensive genomic profiling (CGP) and were subsequently discussed in our molecular tumor board (MTB) between 2016 and 2022 were included. Patient records were retrospectively reviewed, and the clinical impact of NGS-related findings was analyzed.

RESULTS

89.1% of patients had received at least one treatment line before NGS testing. At least one molecular alteration was found in 71 patients (82.6%). The most common alterations were mutations in TP53 (23.3% of patients), followed by PIK3CA and MDM2 mutations (9.3% each). Druggable alterations were identified, and treatment recommended in 32 patients (37.2%). Of those patients with actionable alterations, ten patients (31.2%) received personalized treatment and six patients did benefit from molecular-based therapy in terms of a progression-free survival ratio (PFSr) > 1.3.

CONCLUSION

Our single-center experience shows an increasing uptake of next-generation sequencing (NGS) and highlights current challenges of implementing precision oncology in the management of patients with BS/STS. A relevant number of patients were diagnosed with clinically actionable alterations. Our results highlight the potential benefit of NGS in patients with rare cancers and currently limited therapeutic options.

The status of the human gene catalogue

Scientists have been trying to identify every gene in the human genome since the initial draft was published in 2001. In the years since, much progress has been made in identifying protein-coding genes, currently estimated to number fewer than 20,000, with an ever-expanding number of distinct protein-coding isoforms. Here we review the status of the human gene catalogue and the efforts to complete it in recent years. Beside the ongoing annotation of protein-coding genes, their isoforms and pseudogenes, the invention of high-throughput RNA sequencing and other technological breakthroughs have led to a rapid growth in the number of reported non-coding RNA genes. For most of these non-coding RNAs, the functional relevance is currently unclear; we look at recent advances that offer paths forward to identifying their functions and towards eventually completing the human gene catalogue. Finally, we examine the need for a universal annotation standard that includes all medically significant genes and maintains their relationships with different reference genomes for the use of the human gene catalogue in clinical settings.

Advanced variant classification framework reduces the false positive rate of predicted loss-of-function variants in population sequencing data

Predicted loss of function (pLoF) variants are often highly deleterious and play an important role in disease biology, but many pLoF variants may not result in loss of function (LoF). Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines' PVS1 criterion. Applying this framework to all high-confidence pLoF variants in 22 genes associated with autosomal-recessive disease from the Genome Aggregation Database (gnomAD v.2.1.1) revealed predicted LoF evasion or potential artifacts in 27.3% (304/1,113) of variants. The major reasons were location in the last exon, in a homopolymer repeat, in a low proportion expressed across transcripts (pext) scored region, or the presence of cryptic in-frame splice rescues. Variants predicted to evade LoF or to be potential artifacts were enriched for ClinVar benign variants. PVS1 was downgraded in 99.4% (162/163) of pLoF variants predicted as likely not LoF/not LoF, with 17.2% (28/163) downgraded as a result of our framework, adding to previous guidelines. Variant pathogenicity was affected (mostly from likely pathogenic to VUS) in 20 (71.4%) of these 28 variants. This framework guides assessment of pLoF variants beyond standard annotation pipelines and substantially reduces false positive rates, which is key to ensure accurate LoF variant prediction in both a research and clinical setting.

Using the ACMG/AMP framework to capture evidence related to predicted and observed impact on splicing: Recommendations from the ClinGen SVI Splicing Subgroup

The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1, PS3, PP3, BS3, BP4, and BP7. However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. We utilized empirically derived splicing evidence to (1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, (2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and (3) exemplify methodology to calibrate splice prediction tools. We propose repurposing the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely, BP7 may be used to capture RNA results demonstrating no splicing impact for intronic and synonymous variants. We propose that the PS3/BS3 codes are applied only for well-established assays that measure functional impact not directly captured by RNA-splicing assays. We recommend the application of PS1 based on similarity of predicted RNA-splicing effects for a variant under assessment in comparison with a known pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA-assay evidence described aim to help standardize variant pathogenicity classification processes when interpreting splicing-based evidence.

A concurrent dual analysis of genomic data augments diagnoses: Experiences of 2 clinical sites in the Undiagnosed Diseases Network

PURPOSE

Next-generation sequencing (NGS) has revolutionized the diagnostic process for rare/ultrarare conditions. However, diagnosis rates differ between analytical pipelines. In the National Institutes of Health-Undiagnosed Diseases Network (UDN) study, each individual's NGS data are concurrently analyzed by the UDN sequencing core laboratory and the clinical sites. We examined the outcomes of this practice.

METHODS

A retrospective review was performed at 2 UDN clinical sites to compare the variants and diagnoses/candidate genes identified with the dual analyses of the NGS data.

RESULTS

In total, 95 individuals had 100 diagnoses/candidate genes. There was 59% concordance between the UDN sequencing core laboratories and the clinical sites in identifying diagnoses/candidate genes. The core laboratory provided more diagnoses, whereas the clinical sites prioritized more research variants/candidate genes (P < .001). The clinical sites solely identified 15% of the diagnoses/candidate genes. The differences between the 2 pipelines were more often because of variant prioritization disparities than variant detection.

CONCLUSION

The unique dual analysis of NGS data in the UDN synergistically enhances outcomes. The core laboratory provided a clinical analysis with more diagnoses and the clinical sites prioritized more research variants/candidate genes. Implementing such concurrent dual analyses in other genomic research studies and clinical settings can improve both variant detection and prioritization.

The status of the human gene catalogue

Scientists have been trying to identify all of the genes in the human genome since the initial draft of the genome was published in 2001. Over the intervening years, much progress has been made in identifying protein-coding genes, and the estimated number has shrunk to fewer than 20,000, although the number of distinct protein-coding isoforms has expanded dramatically. The invention of high-throughput RNA sequencing and other technological breakthroughs have led to an explosion in the number of reported non-coding RNA genes, although most of them do not yet have any known function. A combination of recent advances offers a path forward to identifying these functions and towards eventually completing the human gene catalogue. However, much work remains to be done before we have a universal annotation standard that includes all medically significant genes, maintains their relationships with different reference genomes, and describes clinically relevant genetic variants.

Advanced variant classification framework reduces the false positive rate of predicted loss of function (pLoF) variants in population sequencing data

Predicted loss of function (pLoF) variants are highly deleterious and play an important role in disease biology, but many of these variants may not actually result in loss-of-function. Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines's PVS1 criterion. Applying this framework to all high-confidence pLoF variants in 22 autosomal recessive disease-genes from the Genome Aggregation Database (gnomAD, v2.1.1) revealed predicted LoF evasion or potential artifacts in 27.3% (304/1,113) of variants. The major reasons were location in the last exon, in a homopolymer repeat, in low per-base expression (pext) score regions, or the presence of cryptic splice rescues. Variants predicted to be potential artifacts or to evade LoF were enriched for ClinVar benign variants. PVS1 was downgraded in 99.4% (162/163) of LoF evading variants assessed, with 17.2% (28/163) downgraded as a result of our framework, adding to previous guidelines. Variant pathogenicity was affected (mostly from likely pathogenic to VUS) in 20 (71.4%) of these 28 variants. This framework guides assessment of pLoF variants beyond standard annotation pipelines, and substantially reduces false positive rates, which is key to ensure accurate LoF variant prediction in both a research and clinical setting.

APPLICATION OF THE ACMG/AMP FRAMEWORK TO CAPTURE EVIDENCE RELEVANT TO PREDICTED AND OBSERVED IMPACT ON SPLICING: RECOMMENDATIONS FROM THE CLINGEN SVI SPLICING SUBGROUP

The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1 (null variant in a gene where loss-of-function is the mechanism of disease), PS3 (functional assays show damaging effect on splicing), PP3 (computational evidence supports a splicing effect), BS3 (functional assays show no damaging effect on splicing), BP4 (computational evidence suggests no splicing impact), and BP7 (silent change with no predicted impact on splicing). However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation (SVI) Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. Our study utilised empirically derived splicing evidence to: 1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, 2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and 3) exemplify methodology to calibrate bioinformatic splice prediction tools. We propose repurposing of the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely BP7 may be used to capture RNA results demonstrating no impact on splicing for both intronic and synonymous variants, and for missense variants if protein functional impact has been excluded. Furthermore, we propose that the PS3 and BS3 codes are applied only for well-established assays that measure functional impact that is not directly captured by RNA splicing assays. We recommend the application of PS1 based on similarity of predicted RNA splicing effects for a variant under assessment in comparison to a known Pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA assay evidence described aim to help standardise variant pathogenicity classification processes and result in greater consistency when interpreting splicing-based evidence.

From tuberculosis bedside to bench: UBE2B splicing as a potential biomarker and its regulatory mechanism

Alternative splicing (AS) is an important approach for pathogens and hosts to remodel transcriptome. However, tuberculosis (TB)-related AS has not been sufficiently explored. Here we presented the first landscape of TB-related AS by long-read sequencing, and screened four AS events (S100A8-intron1-retention intron, RPS20-exon1-alternaitve promoter, KIF13B-exon4-skipping exon (SE) and UBE2B-exon7-SE) as potential biomarkers in an in-house cohort-1. The validations in an in-house cohort-2 (2274 samples) and public datasets (1557 samples) indicated that the latter three AS events are potential promising biomarkers for TB diagnosis, but not for TB progression and prognosis. The excellent performance of classifiers further underscored the diagnostic value of these three biomarkers. Subgroup analyses indicated that UBE2B-exon7-SE splicing was not affected by confounding factors and thus had relatively stable performance. The splicing of UBE2B-exon7-SE can be changed by heat-killed mycobacterium tuberculosis through inhibiting SRSF1 expression. After heat-killed mycobacterium tuberculosis stimulation, 231 ubiquitination proteins in macrophages were differentially expressed, and most of them are apoptosis-related proteins. Taken together, we depicted a global TB-associated splicing profile, developed TB-related AS biomarkers, demonstrated an optimal application scope of target biomarkers and preliminarily elucidated mycobacterium tuberculosis-host interaction from the perspective of splicing, offering a novel insight into the pathophysiology of TB.

Exome/Genome Sequencing in Undiagnosed Syndromes

Exome sequencing (ES) and genome sequencing (GS) have radically transformed the diagnostic approach to undiagnosed rare/ultrarare Mendelian diseases. Next-generation sequencing (NGS), the technology integral for ES, GS, and most large (100+) gene panels, has enabled previously unimaginable diagnoses, changes in medical management, new treatments, and accurate reproductive risk assessments for patients, as well as new disease gene discoveries. Yet, challenges remain, as most individuals remain undiagnosed with current NGS. Improved NGS technology has resulted in long-read sequencing, which may resolve diagnoses in some patients who do not obtain a diagnosis with current short-read ES and GS, but its effectiveness is unclear, and it is expensive. Other challenges that persist include the resolution of variants of uncertain significance, the urgent need for patients with ultrarare disorders to have access to therapeutics, the need for equity in patient access to NGS-based testing, and the study of ethical concerns. However, the outlook for undiagnosed disease resolution is bright, due to continual advancements in the field.

Computational prediction of human deep intronic variation

BACKGROUND

The adoption of whole-genome sequencing in genetic screens has facilitated the detection of genetic variation in the intronic regions of genes, far from annotated splice sites. However, selecting an appropriate computational tool to discriminate functionally relevant genetic variants from those with no effect is challenging, particularly for deep intronic regions where independent benchmarks are scarce.

RESULTS

In this study, we have provided an overview of the computational methods available and the extent to which they can be used to analyze deep intronic variation. We leveraged diverse datasets to extensively evaluate tool performance across different intronic regions, distinguishing between variants that are expected to disrupt splicing through different molecular mechanisms. Notably, we compared the performance of SpliceAI, a widely used sequence-based deep learning model, with that of more recent methods that extend its original implementation. We observed considerable differences in tool performance depending on the region considered, with variants generating cryptic splice sites being better predicted than those that potentially affect splicing regulatory elements. Finally, we devised a novel quantitative assessment of tool interpretability and found that tools providing mechanistic explanations of their predictions are often correct with respect to the ground - information, but the use of these tools results in decreased predictive power when compared to black box methods.

CONCLUSIONS

Our findings translate into practical recommendations for tool usage and provide a reference framework for applying prediction tools in deep intronic regions, enabling more informed decision-making by practitioners.

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 Mutation in KMT2C Manifesting as Kleefstra Syndrome 2: Case Report and Literature Review

Diagnosis of pediatric intellectual disability (ID) can be difficult because it is due to a vast number of established and novel causes. Here, we described a full-term female infant affected by Kleefstra syndrome-2 presenting with neurodevelopmental disorder, a history of hypotonia and minor face anomalies. A systematic literature review was also performed. The patient was a 6-year-old Caucasian female. In the family history there was no intellectual disability or genetic conditions. Auxological parameters at birth were adequate for gestational age. Clinical evaluation at 6 months revealed hypotonia and, successively, delay in the acquisition of the stages of psychomotor development. Auditory, visual, somatosensory, and motor-evoked potentials were normal. A brain MRI, performed at 9 months, showed minimal gliotic changes in bilateral occipital periventricular white matter. Neuropsychiatric control, performed at 5 years, established a definitive diagnosis of childhood autism and developmental delay. Molecular analysis of the exome revealed a novel KMT2C missense variant: c.9244C > T (p.Pro3082Ser) at a heterozygous state, giving her a diagnosis of Kleefstra syndrome 2. Parents did not show the variant. Literature review (four retrieved eligible studies, 10 patients) showed that all individuals had mild, moderate, or severe ID; language and motor delay; and autism. Short stature, microcephaly, childhood hypotonia and plagiocephaly were also present. Conclusion. Kleefstra syndrome 2 is a difficult diagnosis of a rare condition with a high clinical phenotypic heterogeneity. This study suggests that it must be taken in account in the work-up of an orphan diagnosis of intellectual disability and/or autism spectrum disorder.

OFD1: One gene, several disorders

The OFD1 protein is necessary for the formation of primary cilia and left–right asymmetry establishment but additional functions have also been ascribed to this multitask protein. When mutated, this protein results in a variety of phenotypes ranging from multiorgan involvement, such as OFD type I (OFDI) and Joubert syndromes (JBS10), and Primary ciliary dyskinesia (PCD), to the engagement of single tissues such as in the case of retinitis pigmentosa (RP23). The inheritance pattern of these condition differs from X‐linked dominant male‐lethal (OFDI) to X‐linked recessive (JBS10, PCD, and RP23). Distinctive biological peculiarities of the protein, which can contribute to explain the extreme clinical variability and the genetic mechanisms underlying the different disorders are discussed. The extensive spectrum of clinical manifestations observed in OFD1‐mutated patients represents a paradigmatic example of the complexity of genetic diseases. The elucidation of the mechanisms underlying this complexity will expand our comprehension of inherited disorders and will improve the clinical management of patients.

Clinical exome sequencing - mistakes and caveats

Massive parallel sequencing technology has become the predominant technique for genetic diagnostics and research. Many genetic laboratories have wrestled with the challenges of setting up genetic testing workflows based on a completely new technology. The learning curve we went through as a laboratory was accompanied by growing pains while we gained new knowledge and expertise. Here we discuss some important mistakes that have been made in our laboratory through 10 years of clinical exome sequencing but that have given us important new insights on how to adapt our working methods. We provide these examples and the lessons that we learned to help other laboratories avoid to make the same mistakes.

The splicing effect of variants at branchpoint elements in cancer genes

PURPOSE

Branchpoint elements are required for intron removal, and variants at these elements can result in aberrant splicing. We aimed to assess the value of branchpoint annotations generated from recent large-scale studies to select branchpoint-abrogating variants, using hereditary cancer genes as model.

METHODS

We identified branchpoint elements in 119 genes associated with hereditary cancer from 3 genome-wide experimentally-inferred and 2 predicted branchpoint data sets. We then identified variants that occur within branchpoint elements from public databases. We compared conservation, unique variant observations, and population frequencies at different nucleotides within branchpoint motifs. Finally, selected minigene assays were performed to assess the splicing effect of variants at branchpoint elements within mismatch repair genes.

RESULTS

There was poor overlap between predicted and experimentally-inferred branchpoints. Our analysis of cancer genes suggested that variants at -2 nucleotide, -1 nucleotide, and branchpoint positions in experimentally-inferred canonical motifs are more likely to be clinically relevant. Minigene assay data showed the -2 nucleotide to be more important to branchpoint motif integrity but also showed fluidity in branchpoint usage.

CONCLUSION

Data from cancer gene analysis suggest that there are few high-risk alleles that severely impact function via branchpoint abrogation. Results of this study inform a general scheme to prioritize branchpoint motif variants for further study.

Case Report: Long-Term Treatment and Follow-Up of Kleefstra Syndrome-2

BACKGROUND

Mutations in the KMT2C gene can cause Kleefstra syndrome-2 (KLEFS2).

CASE

In this study, we analyzed the clinical, genetic testing, and 10-year follow-up data of a child with KLEFS2 treated at the Child Healthcare Department, Children's Hospital of Nanjing Medical University, Nanjing. The case of KLEFS2 presented feeding difficulty and developmental delay, both intervened by nutritional support and family rehabilitation. Obvious attention deficit hyperactivity disorder (ADHD) occurred in preschool and school-age children and was managed by behavioral and pharmaceutical interventions.

CONCLUSION

Features of KLEFS2 include feeding difficulty and developmental delays in an early age, as well as ADHD in preschool and school age. Satisfactory outcomes are not achieved in early nutritional support for correcting malnutrition and pharmaceutical intervention for relieving ADHD, but both measures can counter developmental delay.

Challenges in variant interpretation in prenatal exome sequencing

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

Variations in Nomenclature of Clinical Variants between Annotation Tools

BACKGROUND

Accurate nomenclature of variants is an essential element for genetic diagnosis and patient care.

OBJECTIVE

To investigate annotation differences of clinical variants between annotation tools.

METHODS

We analyzed 218,156 clinical variants from the Human Gene Mutation Database. Multiple nomenclatures based on RefSeq transcripts were provided using ANNOVAR and snpEff.

RESULTS

The concordance rate between ANNOVAR and snpEff was approximately 85%. Based on the Human Genome Variation Society (HGVS) nomenclature, snpEff was more accurate than ANNOVAR (coding variants, 99.3% vs 84.9%; protein variants, 94.3% vs 79.8%). When annotating each variant with ANNOVAR and snpEff, the accuracy of nomenclature was 99.5%.

CONCLUSIONS

There were substantial differences between ANNOVAR and snpEff annotations. The findings of this study suggest that simultaneous use of multiple annotation tools could decrease nomenclature errors and contribute to providing standardized clinical reporting.

Spectrum of splicing variants in disease genes and the ability of RNA analysis to reduce uncertainty in clinical interpretation

The complexities of gene expression pose challenges for the clinical interpretation of splicing variants. To better understand splicing variants and their contribution to hereditary disease, we evaluated their prevalence, clinical classifications, and associations with diseases, inheritance, and functional characteristics in a 689,321-person clinical cohort and two large public datasets. In the clinical cohort, splicing variants represented 13% of all variants classified as pathogenic (P), likely pathogenic (LP), or variants of uncertain significance (VUSs). Most splicing variants were outside essential splice sites and were classified as VUSs. Among all individuals tested, 5.4% had a splicing VUS. If RNA analysis were to contribute supporting evidence to variant interpretation, we estimated that splicing VUSs would be reclassified in 1.7% of individuals in our cohort. This would result in a clinically significant result (i.e., P/LP) in 0.1% of individuals overall because most reclassifications would change VUSs to likely benign. In ClinVar, splicing VUSs were 4.8% of reported variants and could benefit from RNA analysis. In the Genome Aggregation Database (gnomAD), splicing variants comprised 9.4% of variants in protein-coding genes; most were rare, precluding unambiguous classification as benign. Splicing variants were depleted in genes associated with dominant inheritance and haploinsufficiency, although some genes had rare variants at essential splice sites or had common splicing variants that were most likely compatible with normal gene function. Overall, we describe the contribution of splicing variants to hereditary disease, the potential utility of RNA analysis for reclassifying splicing VUSs, and how natural variation may confound clinical interpretation of splicing variants.

Clinical sites of the Undiagnosed Diseases Network: unique contributions to genomic medicine and science

PURPOSE

The NIH Undiagnosed Diseases Network (UDN) evaluates participants with disorders that have defied diagnosis, applying personalized clinical and genomic evaluations and innovative research. The clinical sites of the UDN are essential to advancing the UDN mission; this study assesses their contributions relative to standard clinical practices.

METHODS

We analyzed retrospective data from four UDN clinical sites, from July 2015 to September 2019, for diagnoses, new disease gene discoveries and the underlying investigative methods.

RESULTS

Of 791 evaluated individuals, 231 received 240 diagnoses and 17 new disease-gene associations were recognized. Straightforward diagnoses on UDN exome and genome sequencing occurred in 35% (84/240). We considered these tractable in standard clinical practice, although genome sequencing is not yet widely available clinically. The majority (156/240, 65%) required additional UDN-driven investigations, including 90 diagnoses that occurred after prior nondiagnostic exome sequencing and 45 diagnoses (19%) that were nongenetic. The UDN-driven investigations included complementary/supplementary phenotyping, innovative analyses of genomic variants, and collaborative science for functional assays and animal modeling.

CONCLUSION

Investigations driven by the clinical sites identified diagnostic and research paradigms that surpass standard diagnostic processes. The new diagnoses, disease gene discoveries, and delineation of novel disorders represent a model for genomic medicine and science.

Missense variants in the N-terminal domain of the A isoform of FHF2/FGF13 cause an X-linked developmental and epileptic encephalopathy

Fibroblast growth factor homologous factors (FHFs) are intracellular proteins which regulate voltage-gated sodium (Nav) channels in the brain and other tissues. FHF dysfunction has been linked to neurological disorders including epilepsy. Here, we describe two sibling pairs and three unrelated males who presented in infancy with intractable focal seizures and severe developmental delay. Whole-exome sequencing identified hemi- and heterozygous variants in the N-terminal domain of the A isoform of FHF2 (FHF2A). The X-linked FHF2 gene (also known as FGF13) has alternative first exons which produce multiple protein isoforms that differ in their N-terminal sequence. The variants were located at highly conserved residues in the FHF2A inactivation particle that competes with the intrinsic fast inactivation mechanism of Nav channels. Functional characterization of mutant FHF2A co-expressed with wild-type Nav1.6 (SCN8A) revealed that mutant FHF2A proteins lost the ability to induce rapid-onset, long-term blockade of the channel while retaining pro-excitatory properties. These gain-of-function effects are likely to increase neuronal excitability consistent with the epileptic potential of FHF2 variants. Our findings demonstrate that FHF2 variants are a cause of infantile-onset developmental and epileptic encephalopathy and underline the critical role of the FHF2A isoform in regulating Nav channel function.