The genomic landscape of rare disorders in the Middle East.

BACKGROUND: Rare diseases collectively impose a significant burden on healthcare systems, especially in underserved regions, like the Middle East, which lack access to genomic diagnostic services and the associated personalized management plans. METHODS: We established a clinical genomics and genetic counseling facility, within a multidisciplinary tertiary pediatric center, in the United Arab Emirates to locally diagnose and manage patients with rare diseases. Clinical genomic investigations included exome-based sequencing, chromosomal microarrays, and/or targeted testing. We assessed the diagnostic yield and implications for clinical management among this population. Variables were compared using the Fisher exact test. Tests were 2-tailed, and P < .05 was considered statistically significant. RESULTS: We present data on 1000 patients with rare diseases (46.2% females; average age, 4.6 years) representing 47 countries primarily from the Arabian Peninsula, the Levant, Africa, and Asia. The cumulative diagnostic yield was 32.5% (95% CI, 29.7-35.5%) and was higher for genomic sequencing-based testing than chromosomal microarrays (37.9% versus 17.2%, P = 0.0001) across all indications, consistent with the higher burden of single gene disorders. Of the 221 Mendelian disorders identified in this cohort, the majority (N = 184) were encountered only once, and those with recessive inheritance accounted for ~ 62% of sequencing diagnoses. Of patients with positive genetic findings (N = 325), 67.7% were less than 5 years of age, and 60% were offered modified management and/or intervention plans. Interestingly, 24% of patients with positive genetic findings received delayed diagnoses (average age, 12.4 years; range 7-37 years), most likely due to a lack of access to genomic investigations in this region. One such genetic finding ended a 15-year-long diagnostic odyssey, leading to a life-threatening diagnosis in one patient, who was then successfully treated using an experimental allogenic bone marrow transplant. Finally, we present cases with candidate genes within regions of homozygosity, likely underlying novel recessive disorders. CONCLUSIONS: Early access to genomic diagnostics for patients with suspected rare disorders in the Middle East is likely to improve clinical outcomes while driving gene discovery in this genetically underrepresented population.

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

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

Super-enhancer associated core regulatory circuits mediate susceptibility to retinoic acid in neuroblastoma cells.

Neuroblastoma is a pediatric tumour that accounts for more than 15% of cancer-related deaths in children. High-risk tumours are often difficult to treat, and patients' survival chances are less than 50%. Retinoic acid treatment is part of the maintenance therapy given to neuroblastoma patients; however, not all tumours differentiate in response to retinoic acid. Within neuroblastoma tumors, two phenotypically distinct cell types have been identified based on their super-enhancer landscape and transcriptional core regulatory circuitries: adrenergic (ADRN) and mesenchymal (MES). We hypothesized that the distinct super-enhancers in these different tumour cells mediate differential response to retinoic acid. To this end, three different neuroblastoma cell lines, ADRN (MYCN amplified and non-amplified) and MES cells, were treated with retinoic acid, and changes in the super-enhancer landscape upon treatment and after subsequent removal of retinoic acid was studied. Using ChIP-seq for the active histone mark H3K27ac, paired with RNA-seq, we compared the super-enhancer landscape in cells that undergo neuronal differentiation in response to retinoic acid versus those that fail to differentiate and identified unique super-enhancers associated with neuronal differentiation. Among the ADRN cells that respond to treatment, MYCN-amplified cells remain differentiated upon removal of retinoic acid, whereas MYCN non-amplified cells revert to an undifferentiated state, allowing for the identification of super-enhancers responsible for maintaining differentiation. This study identifies key super-enhancers that are crucial for retinoic acid-mediated differentiation.

Rapid whole genome sequencing of critically ill pediatric patients from genetically underrepresented populations.

We describe a case series of five infants (age range: 1-90 days; 4 females and 1 male) who presented to Al Jalila Children's intensive care units (ICU) with complex multisystem disorders. Patients were Emirati, Kenyan, Jordanian, Filipino, or Pakistani. Trio rapid whole genome sequencing (rWGS) was performed on all five patients and their parents within the hospital's genomics facility. Results were returned within ~37 h from blood sample draws and were diagnostic in 3 out of 5 patients. Positive findings were a homozygous pathogenic variant in POMT1 gene causing muscular dystrophydystroglycanopathy, a mosaic tetrasomy of the short arm of chromosome 12 (12p13.33p11.1) causing Pallister-Killian syndrome, and compound heterozygous pathogenic variants in the LIPA gene causing lysosomal acid lipase deficiency and Wolman disease. The rWGS analysis provided fast and precise diagnostic findings in those 3 patients and also aided in devising better management plans for them in the intensive care setting. For example, the 3-month-old infant with pathogenic variants in the LIPA gene is now a candidate for an FDA-approved, potentially lifesaving enzyme replacement therapy (sebelipase alfa). Our case series emphasize the feasibility and utility of rWGS in pediatric intensive care setting, in a diverse population that has long been underserved in genomic services. Significant investments in local healthcare infrastructure are needed, globally, for more equitable access of genomic medicine among vulnerable patients.

Evaluating the impact of in silico predictors on clinical variant classification.

PURPOSE: According to the American College of Medical Genetics and Genomics/Association of Medical Pathology (ACMG/AMP) guidelines, in silico evidence is applied at the supporting strength level for pathogenic (PP3) and benign (BP4) evidence. Although PP3 is commonly used, less is known about the effect of these criteria on variant classification outcomes. METHODS: A total of 727 missense variants curated by Clinical Genome Resource expert groups were analyzed to determine how often PP3 and BP4 were applied and their impact on variant classification. The ACMG/AMP categorical system of variant classification was compared with a quantitative point-based system. The pathogenicity likelihood ratios of REVEL, VEST, FATHMM, and MPC were calibrated using a gold standard set of 237 pathogenic and benign variants (classified independent of the PP3/BP4 criteria). RESULTS: The PP3 and BP4 criteria were applied by Variant Curation Expert Panels to 55% of missense variants. Application of those criteria changed the classification of 15% of missense variants for which either criterion was applied. The point-based system resolved borderline classifications. REVEL and VEST performed best at a strength level consistent with moderate evidence. CONCLUSION: We show that in silico criteria are commonly applied and often affect the final variant classifications. When appropriate thresholds for in silico predictors are established, our results show that PP3 and BP4 can be used at a moderate strength.

Genomic medicine in the Middle East.

We discuss the current state of genomic medicine in Arab countries of the Middle East, a region with outsized contribution to Mendelian genetics due to inbreeding yet has poor representation in global variome datasets. We focus on genomic testing, clinical genetics, and genetic counseling services along with associated training and research programs. Finally, we highlight opportunities for improvement in genomic medicine services in this region.

Genetic variation in the Middle East-an opportunity to advance the human genetics field.

We highlight the current lack of representation of the Middle East from large genomic studies and emphasize the expected high impact of cataloging its variation. We discuss the limiting factors and possible solutions to generating and accessing research and clinical sequencing data from this part of the world.

Genetic variant pathogenicity prediction trained using disease-specific clinical sequencing data sets.

Recent advances in DNA sequencing have expanded our understanding of the molecular basis of genetic disorders and increased the utilization of clinical genomic tests. Given the paucity of evidence to accurately classify each variant and the difficulty of experimentally evaluating its clinical significance, a large number of variants generated by clinical tests are reported as variants of unknown clinical significance. Population-scale variant databases can improve clinical interpretation. Specifically, pathogenicity prediction for novel missense variants can use features describing regional variant constraint. Constrained genomic regions are those that have an unusually low variant count in the general population. Computational methods have been introduced to capture these regions and incorporate them into pathogenicity classifiers, but these methods have yet to be compared on an independent clinical variant data set. Here, we introduce one variant data set derived from clinical sequencing panels and use it to compare the ability of different genomic constraint metrics to determine missense variant pathogenicity. This data set is compiled from 17,071 patients surveyed with clinical genomic sequencing for cardiomyopathy, epilepsy, or RASopathies. We further use this data set to demonstrate the necessity of disease-specific classifiers and to train PathoPredictor, a disease-specific ensemble classifier of pathogenicity based on regional constraint and variant-level features. PathoPredictor achieves an average precision >90% for variants from all 99 tested disease genes while approaching 100% accuracy for some genes. The accumulation of larger clinical variant training data sets can significantly enhance their performance in a disease- and gene-specific manner.

Consensus interpretation of the p.Met34Thr and p.Val37Ile variants in GJB2 by the ClinGen Hearing Loss Expert Panel.

PURPOSE: Pathogenic variants in GJB2 are the most common cause of autosomal recessive sensorineural hearing loss. The classification of c.101T>C/p.Met34Thr and c.109G>A/p.Val37Ile in GJB2 are controversial. Therefore, an expert consensus is required for the interpretation of these two variants. METHODS: The ClinGen Hearing Loss Expert Panel collected published data and shared unpublished information from contributing laboratories and clinics regarding the two variants. Functional, computational, allelic, and segregation data were also obtained. Case-control statistical analyses were performed. RESULTS: The panel reviewed the synthesized information, and classified the p.Met34Thr and p.Val37Ile variants utilizing professional variant interpretation guidelines and professional judgment. We found that p.Met34Thr and p.Val37Ile are significantly overrepresented in hearing loss patients, compared with population controls. Individuals homozygous or compound heterozygous for p.Met34Thr or p.Val37Ile typically manifest mild to moderate hearing loss. Several other types of evidence also support pathogenic roles for these two variants. CONCLUSION: Resolving controversies in variant classification requires coordinated effort among a panel of international multi-institutional experts to share data, standardize classification guidelines, review evidence, and reach a consensus. We concluded that p.Met34Thr and p.Val37Ile variants in GJB2 are pathogenic for autosomal recessive nonsyndromic hearing loss with variable expressivity and incomplete penetrance.

A mutation update for the PCDH19 gene causing early-onset epilepsy in females with an unusual expression pattern.

The PCDH19 gene consists of six exons encoding a 1,148 amino acid transmembrane protein, Protocadherin 19, which is involved in brain development. Heterozygous pathogenic variants in this gene are inherited in an unusual X-linked dominant pattern in which heterozygous females are affected, while hemizygous males are typically unaffected, although they pass on the pathogenic variant to each affected daughter. PCDH19-related disorder is known to cause early-onset epilepsy in females characterized by seizure clusters exacerbated by fever and in most cases, onset is within the first year of life. This condition was initially described in 1971 and in 2008 PCDH19 was identified as the underlying genetic etiology. This condition is the result of pathogenic loss-of-function variants that may be de novo or inherited from an affected mother or unaffected father and cellular interference has been hypothesized to be the culprit. Heterozygous females are symptomatic because of the presence of both wild-type and mutant cells that interfere with one another due to the production of different surface proteins, whereas nonmosaic hemizygous males produce a homogenous population of cells. Here, we review novel pathogenic variants in the PCDH19 gene since 2012 to date, and summarize any genotype-phenotype correlations.

Automated Clinical Exome Reanalysis Reveals Novel Diagnoses.

Clinical exome sequencing (CES) has a reported diagnostic yield of 20% to 30% for most clinical indications. The ongoing discovery of novel gene-disease and variant-disease associations are expected to increase the diagnostic yield of CES. Performing systematic reanalysis of previously nondiagnostic CES samples represents a significant challenge for clinical laboratories. Here, we present the results of a novel automated reanalysis methodology applied to 300 CES samples initially analyzed between June 2014 and September 2016. Application of our reanalysis methodology reduced reanalysis variant analysis burden by >93% and correctly captured 70 of 70 previously identified diagnostic variants among 60 samples with previously identified diagnoses. Notably, reanalysis of 240 initially nondiagnostic samples using information available on July 1, 2017, revealed 38 novel diagnoses, representing a 15.8% increase in diagnostic yield. Modeling monthly iterative reanalysis of 240 nondiagnostic samples revealed a diagnostic rate of 0.57% of samples per month. Modeling the workload required for monthly iterative reanalysis of nondiagnostic samples revealed a variant analysis burden of approximately 5 variants/month for proband-only and approximately 0.5 variants/month for trio samples. Approximately 45% of samples required evaluation during each monthly interval, and 61.3% of samples were reevaluated across three consecutive reanalyses. In sum, automated reanalysis methods can facilitate efficient reevaluation of nondiagnostic samples using up-to-date literature and can provide significant value to clinical laboratories.

Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework.

BACKGROUND: The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) clinical variant interpretation guidelines established criteria for different types of evidence. This includes the strong evidence codes PS3 and BS3 for "well-established" functional assays demonstrating a variant has abnormal or normal gene/protein function, respectively. However, they did not provide detailed guidance on how functional evidence should be evaluated, and differences in the application of the PS3/BS3 codes are a contributor to variant interpretation discordance between laboratories. This recommendation seeks to provide a more structured approach to the assessment of functional assays for variant interpretation and guidance on the use of various levels of strength based on assay validation. METHODS: The Clinical Genome Resource (ClinGen) Sequence Variant Interpretation (SVI) Working Group used curated functional evidence from ClinGen Variant Curation Expert Panel-developed rule specifications and expert opinions to refine the PS3/BS3 criteria over multiple in-person and virtual meetings. We estimated the odds of pathogenicity for assays using various numbers of variant controls to determine the minimum controls required to reach moderate level evidence. Feedback from the ClinGen Steering Committee and outside experts were incorporated into the recommendations at multiple stages of development. RESULTS: The SVI Working Group developed recommendations for evaluators regarding the assessment of the clinical validity of functional data and a four-step provisional framework to determine the appropriate strength of evidence that can be applied in clinical variant interpretation. These steps are as follows: (1) define the disease mechanism, (2) evaluate the applicability of general classes of assays used in the field, (3) evaluate the validity of specific instances of assays, and (4) apply evidence to individual variant interpretation. We found that a minimum of 11 total pathogenic and benign variant controls are required to reach moderate-level evidence in the absence of rigorous statistical analysis. CONCLUSIONS: The recommendations and approach to functional evidence evaluation described here should help clarify the clinical variant interpretation process for functional assays. Further, we hope that these recommendations will help develop productive partnerships with basic scientists who have developed functional assays that are useful for interrogating the function of a variety of genes.

Expert specification of the ACMG/AMP variant interpretation guidelines for genetic hearing loss.

Due to the high genetic heterogeneity of hearing loss (HL), current clinical testing includes sequencing large numbers of genes, which often yields a significant number of novel variants. Therefore, the standardization of variant interpretation is crucial to provide consistent and accurate diagnoses. The Hearing Loss Variant Curation Expert Panel was created within the Clinical Genome Resource to provide expert guidance for standardized genomic interpretation in the context of HL. As one of its major tasks, our Expert Panel has adapted the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for the interpretation of sequence variants in HL genes. Here, we provide a comprehensive illustration of the newly specified ACMG/AMP HL rules. Three rules remained unchanged, four rules were removed, and the remaining 21 rules were specified. These rules were further validated and refined using a pilot set of 51 variants assessed by curators and disease experts. Of the 51 variants evaluated in the pilot, 37% (19/51) changed category based upon application of the expert panel specified rules and/or aggregation of evidence across laboratories. These HL-specific ACMG/AMP rules will help standardize variant interpretation, ultimately leading to better care for individuals with HL.

Recommendations for interpreting the loss of function PVS1 ACMG/AMP variant criterion.

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.

Curating Clinically Relevant Transcripts for the Interpretation of Sequence Variants.

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.

The Development and Validation of Clinical Exome-Based Panels Using ExomeSlicer: Considerations and Proof of Concept Using an Epilepsy Panel.

Exome-based panels are becoming the preferred diagnostic strategy in clinical laboratories. This approach enables dynamic gene content update and, if needed, cost-effective reflex to whole-exome sequencing. Currently, no guidelines or appropriate resources are available to support the clinical implementation of exome-based panels. Here, we highlight principles and important considerations for the clinical development and validation of exome-based panels. In addition, we developed ExomeSlicer, a novel, web-based resource, which uses empirical exon-level next-generation sequencing quality metrics to predict and visualize technically challenging exome-wide regions in any gene or genes of interest. Exome sequencing data from 100 clinical epilepsy cases were used to illustrate the clinical utility of ExomeSlicer in predicting poor-quality regions and its impact on streamlining the ad hoc Sanger sequencing fill in burden. With the use of ExomeSlicer, >2100 low complexity and/or high-homology regions affecting >1615 genes across the exome were also characterized. These regions can be a source of false-positive or false-negative variant calls, which can lead to misdiagnoses in tested patients and/or inaccurate functional annotations. We provide important considerations and a novel resource for the clinical development of exome-based panels.

AUDIOME: a tiered exome sequencing-based comprehensive gene panel for the diagnosis of heterogeneous nonsyndromic sensorineural hearing loss.

PURPOSE: Hereditary hearing loss is highly heterogeneous. To keep up with rapidly emerging disease-causing genes, we developed the AUDIOME test for nonsyndromic hearing loss (NSHL) using an exome sequencing (ES) platform and targeted analysis for the curated genes. METHODS: A tiered strategy was implemented for this test. Tier 1 includes combined Sanger and targeted deletion analyses of the two most common NSHL genes and two mitochondrial genes. Nondiagnostic tier 1 cases are subjected to ES and array followed by targeted analysis of the remaining AUDIOME genes. RESULTS: ES resulted in good coverage of the selected genes with 98.24% of targeted bases at >15 ×. A fill-in strategy was developed for the poorly covered regions, which generally fell within GC-rich or highly homologous regions. Prospective testing of 33 patients with NSHL revealed a diagnosis in 11 (33%) and a possible diagnosis in 8 cases (24.2%). Among those, 10 individuals had variants in tier 1 genes. The ES data in the remaining nondiagnostic cases are readily available for further analysis. CONCLUSION: The tiered and ES-based test provides an efficient and cost-effective diagnostic strategy for NSHL, with the potential to reflex to full exome to identify causal changes outside of the AUDIOME test.