A semiautomated whole-exome sequencing workflow leads to increased diagnostic yield and identification of novel candidate variants

Exome sequencing (ES) of a pediatric cohort with chronic endocrine diseases: a single-center study (within the framework of the TRANSLATE-NAMSE project)

BACKGROUND

Endocrine disorders are heterogeneous and include a significant number of rare monogenic diseases.

METHODS

We performed exome sequencing (ES) in 106 children recruited from a single center within the TRANSLATE‑NAMSE project. They were categorized into subgroups: proportionate short stature (PSS), disproportionate short stature (DSS), hypopituitarism (H), differences in sexual development (DSD), syndromic diseases (SD) and others.

RESULTS

The overall diagnostic yield was 34.9% (n = 37/106), including 5 patients with variants in candidate genes, which have contributed to collaborations to identify gene-disease associations. The diagnostic yield varied significantly between subgroups: PSS: 16.6% (1/6); DSS: 18.8% (3/16); H: 17.1% (6/35); DSD: 37.5% (3/8); SD: 66.6% (22/33); others: 25% (2/8). Confirmed diagnoses included 75% ultrarare diseases. Three patients harbored more than one disease-causing variant, resulting in dual diagnoses.

CONCLUSIONS

ES is an effective tool for genetic diagnosis in pediatric patients with complex endocrine diseases. An accurate phenotypic description, including comprehensive endocrine diagnostics, as well as the evaluation of variants in multidisciplinary case conferences involving geneticists, are necessary for personalized diagnostic care. Here, we illustrate the broad spectrum of genetic endocrinopathies that have led to the initiation of specific treatment, surveillance, and family counseling.

Significance Associated with Phenotype Score Aids in Variant Prioritization for Exome Sequencing Analysis

Several in silico annotation-based methods have been developed to prioritize variants in exome sequencing analysis. This study introduced a novel metric Significance Associated with Phenotypes (SAP) score, which generates a statistical score by comparing an individual's observed phenotypes against existing gene-phenotype associations. To evaluate the SAP score, a retrospective analysis was performed on 219 exomes. Among them, 82 family-based and 35 singleton exomes had at least one disease-causing variant that explained the patient's clinical features. SAP scores were calculated, and the rank of the disease-causing variant was compared with a known method, Exomiser. Using the SAP score, the known causative variant was ranked in the top 10 retained variants for 94% (77 of 82) of the family-based exomes and in first place for 73% of these cases. For singleton exomes, the SAP score analysis ranked the known pathogenic variants within the top 10 for 80% (28 of 35) of cases. The SAP score, which is independent of detected variants, demonstrates comparable performance with Exomiser, which considers both phenotype and variant-level evidence simultaneously. Among 102 cases with negative results or variants of uncertain significance, SAP score analysis revealed two cases with a potential new diagnosis based on rank. The SAP score, a phenotypic quantitative metric, can be used in conjunction with standard variant filtration and annotation to enhance variant prioritization in exome analysis.

Clinical phenotype and genetic characteristics of SZT2 related diseases: A case report and literature review

PURPOSE

Seizure threshold 2 protein homolog gene (SZT2, MIM: 615463) related diseases are extremely rare autosomal recessive disorders with a wide spectrum of clinical phenotypes ranging from mild intellectual impairment to severe developmental epileptic encephalopathy (DEE). Most SZT2 related diseases are accompanied by craniofacial malformation and corpus callosum malformation. This study attempts to analyze and summarize the clinical phenotype and genetic characteristics of SZT2 related diseases, providing a basis for early diagnosis, treatment, and prognosis.

METHOD

We analyzed the clinical characteristics of a Chinese child with pathogenic variants of SZT2. We also performed whole-exome sequencing (WES) on the patient. In addition, we conducted a literature review of previously reported patients with pathogenic mutations in the SZT2 gene.

RESULT

The proband was a boy aged 1 year and 9 months with severe global developmental delay, transient drug-controlled focal epilepsy, cluster epilepsy, autism spectrum disorder, craniofacial deformity, hypotonia, focal EEG discharge, corpus callosum malformation, and persistent cavum septum pellucidum. WES revealed that the patient carried the SZT2 gene c.7584dupA and c.6302A>C complex heterozygous variants; the former being Likely Pathogenic (LP) and the latter Uncertain Significance (VUS) according to ACMG classification guidelines. According to our literature review, 43 cases of SZT2 related diseases have been reported so far; these include 15 cases with homozygous variations and 28 cases with complex heterozygous variations. A total of 57 types of variation were found, including 47 genetic variants, 2 de novo variants, and 8 unknown genetic modes. In addition, 2 high-frequency variants were found (c.5949_5951delTGT and c.6553C>T). The main clinical manifestations of the 40 patients were global developmental delay (GDD) of varying degrees (38/40, 95.00 %), seizures (36/40, 90.00 %), cranial deformity (27/40, 67.50 %), facial deformity (22/40, 55.00 %), hypotonia (22/40, 55.00 %), abnormal interseizure EEG discharge (26/40, 65.00 %), slow background activity (20/40, 50.00 %), corpus callosum deformity (18/40, 45.00 %). There was also one case of sudden unexpected death in epilepsy (SUDEP) and 3 cases of death from infection. In addition, three fetuses with the same variant had hydrocephalus and encephalocele.

CONCLUSION

The compound heterozygous mutation of c.7584dupA and c.6302A>C in the SZT2 gene is the genetic etiology of this patient, expanding the mutation spectrum of SZT2 related diseases. Early genetic testing is the best choice for clear diagnosis, treatment, and prognosis.

MSeqDR Quick-Mitome (QM): Combining Phenotype-Guided Variant Interpretation and Machine Learning Classifiers to Aid Primary Mitochondrial Disease Genetic Diagnosis

The international Mitochondrial Disease Sequence Data Resource Consortium (MSeqDR) Quick-Mitome (QM) is a web-based platform enabling automated variant interpretation of whole-exome sequencing (WES) datasets for the genetic diagnosis of primary mitochondrial diseases (PMD). Designed specifically to address the unique dual genome nature of PMD etiologies, QM includes features for both nuclear and mitochondrial DNA (mtDNA) genome analysis. QM requires VCF variant lists, HPO ID clinical phenotypes, and pedigree files for multiple-sample VCF inputs. QM maps phenotypes to HPO terms before analysis. QM analysis requires 2 to 20 min for 100,000 variants on an 8-vCPU AWS server using Exomiser's "PASS_ONLY" mode for nuclear variants. QM ranks variants based on allele frequency, phenotype-gene association, functional impact, and inheritance mode. Variants are further annotated with multiple data sources such as OMIM, ClinVar, dbNSFP, gnoMAD, MITOMAP, and MSeqDR. In addition to standard Exomiser results, QM generates an Analysis Report and QM Integrated Report with add-on mtDNA-specific analyses, including haplogroup prediction with Phy-Mer, heteroplasmy calculation, and mvTool annotations. We developed the Mitochondrial Disease Variant (MDV) classifier using XGBoost to predict variant pathogenicity for PMD. The MDV classifier was trained on >120 features and performance benchmarking showed that it correctly classified >98% of nuclear gene variants as being pathogenic or benign, and predicted PMD-causing variants with 94% precision. The MSeqDR QM server is an open-access resource for phenotype-driven dual-genome analyses for PMD diagnosis by the global mitochondrial disease community. It is publicly available for non-commercial, non-clinical research use at https://mseqdr.org/quickmitome.php. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Standardizing clinical phenotypes into human phenotype ontology (HPO) terms as the phenotype input for Quick-Mitome (QM) Basic Protocol 2: Prepare the pedigree input for multiple-sample VCF Basic Protocol 3: Quick-Mitome (QM) analysis Basic Protocol 4: Reviewing and understanding the QM Integrated Report and Analysis Report.

Accurate long-read sequencing identified GBA1 as major risk factor in the Luxembourgish Parkinson's study

Heterozygous variants in the glucocerebrosidase GBA1 gene are an increasingly recognized risk factor for Parkinson's disease (PD). Due to the GBAP1 pseudogene, which shares 96% sequence homology with the GBA1 coding region, accurate variant calling by array-based or short-read sequencing methods remains a major challenge in understanding the genetic landscape of GBA1-associated PD. We analyzed 660 patients with PD, 100 patients with Parkinsonism and 808 healthy controls from the Luxembourg Parkinson's study, sequenced using amplicon-based long-read DNA sequencing technology. We found that 12.1% (77/637) of PD patients carried GBA1 variants, with 10.5% (67/637) of them carrying known pathogenic variants (including severe, mild, risk variants). In comparison, 5% (34/675) of the healthy controls carried GBA1 variants, and among them, 4.3% (29/675) were identified as pathogenic variant carriers. We found four GBA1 variants in patients with atypical parkinsonism. Pathogenic GBA1 variants were 2.6-fold more frequently observed in PD patients compared to controls (OR = 2.6; CI = [1.6,4.1]). Three novel variants of unknown significance (VUS) were identified. Using a structure-based approach, we defined a potential risk prediction method for VUS. This study describes the full landscape of GBA1-related parkinsonism in Luxembourg, showing a high prevalence of GBA1 variants as the major genetic risk for PD. Although the long-read DNA sequencing technique used in our study may be limited in its effectiveness to detect potential structural variants, our approach provides an important advancement for highly accurate GBA1 variant calling, which is essential for providing access to emerging causative therapies for GBA1 carriers.

Molecular Diagnostic Yield of Exome Sequencing and Chromosomal Microarray in Short Stature: A Systematic Review and Meta-Analysis

Importance

Currently, the diagnostic yield of exome sequencing (ES) and chromosomal microarray analysis (CMA) for short stature cohorts is uncertain. Despite previous studies reporting the widespread use of ES and CMA, a definitive diagnostic yield has not been established.

Objective

To investigate the diagnostic yield of ES and CMA in short stature.

Data Sources

A systematic literature search was conducted using relevant keywords in 3 databases (PubMed, Embase, and Web of Science) in February 2023.

Study Selection

Eligible studies for meta-analysis were those that had at least 10 participants with short stature who were diagnosed using either ES or CMA and the number of diagnosed patients was reported. Of 5222 identified studies, 20 were eventually included in the study.

Data Extraction and Synthesis

Two independent investigators extracted relevant information from each study, which was then synthesized using proportional meta-analysis to obtain the overall diagnostic yield of ES and CMA.

Main Outcomes and Measures

The primary outcome measure was to determine the overall diagnostic yield of ES and CMA. A subgroup meta-analysis was also performed to assess if the diagnostic yield varied depending on whether ES was used as a first-tier or last-resort test. Additionally, a meta-regression was carried out to investigate how the diagnostic yield varied over time.

Results

Twenty studies were included, comprising 1350 patients with short stature who underwent ES and 1070 patients who completed CMA. The overall diagnostic yield of ES among the cohorts and CMA among the cohorts was found to be 27.1% (95% CI, 18.1%-37.2%) and 13.6% (95% CI, 9.2%-18.7%), respectively. No statistically significant difference was observed between the first-tier (27.8%; 95% CI, 15.7%-41.8%) and last-resort groups (25.6%; 95% CI, 13.6%-39.6%) (P = .83) or in the percentage of positively diagnosed patients over time. No statistically significant difference was observed between the first-tier (27.8%; 95% CI, 15.7%-41.8%) and last-resort groups (25.6%; 95% CI, 13.6%-39.6%) (P = .83) or in the percentage of positively diagnosed patients over time.

Conclusion and Relevance

This systematic review and meta-analysis provides high-level evidence supporting the diagnostic efficacy of ES and CMA in patients with short stature. The findings serve as a solid reference for clinicians when making informed decisions about recommending these genetic tests.

The Application of Optical Genome Mapping (OGM) in Severe Short Stature Caused by Duplication of 15q14q21.3

(1) Background: Optical genome mapping (OGM) is a novel approach to identifying genomic structural variations with high accuracy and resolution. We report a proband with severe short stature caused by 46, XY, der (16) ins (16;15) (q23; q21.3q14) that was detected by OGM combined with other tests and review the clinical features of patients with duplication within 15q14q21.3; (2) Methods: OGM, whole exon sequencing (WES), copy number variation sequencing (CNV-seq), and karyotyping were used; (3) Results: The proband was a 10.7-year-old boy with a complaint of severe short stature (-3.41SDS) and abnormal gait. He had growth hormone deficiency, lumbar lordosis, and epiphyseal dysplasia of both femurs. WES and CNV-seq showed a 17.27 Mb duplication of chromosome 15, and there was an insertion in chromosome 16 found by karyotyping. Furthermore, OGM revealed that duplication of 15q14q21.3 was inversely inserted into 16q23.1, resulting in two fusion genes. A total of fourteen patients carried the duplication of 15q14q21.3, with thirteen previously reported and one from our center, 42.9% of which were de novo. In addition, neurologic symptoms (71.4%,10/14) were the most common phenotypes; (4) Conclusions: OGM combined with other genetic methods can reveal the genetic etiology of patients with the clinical syndrome, presenting great potential for use in properly diagnosing in the genetic cause of the clinical syndrome.

DNAJC21-related thrombocytopenia in a young adult female

Bone marrow failure type 3 (BMFS3) (MIM:617052) is a subtype of inherited bone marrow failure syndromes (IBMFS) caused by homozygous pathogenic variants in DNAJC21. It was first defined in 2016, and to date, 19 patients have been reported. Here we report the first adult patient; a 20-year-old female with a novel frameshift variant in DNAJC21 presents with thrombocytopenia, dysmorphic findings, and ovarian agenesis. Our patient expands the clinical spectrum to the milder end and suggests that DNAJC21-related disorders can have relatively mild presentations. Investigation of DNAJC21 variants in both childhood and adult patients with persistent, non-progressive thrombocytopenia will allow to broaden the gene-related phenotypic and genotypic spectrum and elucidate the pathophysiology. Therefore, we encourage revisiting undiagnosed patients to offer whole exome sequencing (WES) in adulthood.

Improving variant prioritization in exome analysis by entropy-weighted ensemble of multiple tools

Variant prioritization is a crucial step in the analysis of exome and genome sequencing. Multiple phenotype-driven tools have been developed to automate the variant prioritization process, but the efficacy of these tools in clinical setting with fuzzy phenotypic information and whether ensemble of these tools could outperform single algorithm remains to be assessed. A large rare disease cohort with heterogeneous phenotypic information, including a primary cohort of 1614 patients and a replication cohort of 1904 patients referred to exome sequencing, were recruited to assess the efficacy of variant prioritization and their ensemble. Three freely available tools-Exomiser, Xrare, and DeepPVP-and their ensemble were evaluated. The performance of all three tools was influenced by the attributes of phenotypic input. When combining these three tools by weighted-sum entropy method (EWE3), the ensemble outperformed any single algorithm, achieving a rate of 78% diagnostic variants in top 3 (13% improvement over current best performer, compared to Exomiser: 63%, Xrare: 65%, and DeepPVP: 51%), 88% in top 10 and 96% in top 30. The results were replicated in another independent cohort. Our study supports using entropy-weighted ensemble of multiple tools to improve variant prioritization and accelerate molecular diagnosis in exome/genome sequencing.

Detection of a de novo heterozygous ANK2 variant in a child with autism spectrum disorder and epilepsy: a case report

Background

The pathogenesis of autism spectrum disorder (ASD) is not fully clarified. Next-generation sequencing technologies have greatly enhanced the identification of new genes associated with ASD. Variants in ANK2 gene are known to correlate with a broad spectrum of clinical cardiac phenotypes, but, more recently, it has also been pointed out as a candidate gene for the etiology of ASD.

Case presentation

We report the case of a female patient with ASD and epilepsy in whom clinical exome sequencing was performed for etiological enlightenment. A heterozygous variant of uncertain significance was identified in the ANK2 gene: c.3412C > T p.(Arg1138Ter). The child was submitted to a formal cardiac evaluation, ruling out cardiovascular abnormalities. The genetic variant was searched in her parents and was negative in both, suggesting a de novo variant, which favors its pathogenicity.

Conclusions

We recognize the challenge of assessing variant pathogenicity in candidate genes for ASD, and ANK2 gene is currently not associated with neurodevelopmental disorders in the Online Mendelian Inheritance in Man database. Nonetheless, our case can be added to other published reports of de novo ANK2 variants in children with ASD and neurological phenotypes (including seizures), some without cardiac impairment. Hopefully, this study provides a more detailed phenotypical description that is often lacking, and it may contribute to a better understanding of the association between ANK2 and ASD.

Emerging bone marrow failure syndromes- new pieces to an unsolved puzzle

Inherited bone marrow failure (BMF) syndromes are genetically diverse - more than 100 genes have been associated with those syndromes and the list is rapidly expanding. Risk assessment and genetic counseling of patients with recently discovered BMF syndromes is inherently difficult as disease mechanisms, penetrance, genotype-phenotype associations, phenotypic heterogeneity, risk of hematologic malignancies and clonal markers of disease progression are unknown or unclear. This review aims to shed light on recently described BMF syndromes with sparse concise data and with an emphasis on those associated with germline variants in ADH5/ALDH2, DNAJC21, ERCC6L2 and MECOM. This will provide important data that may help to individualize and improve care for these patients.

Phenotype-driven approaches to enhance variant prioritization and diagnosis of rare disease

Rare disease diagnostics and disease gene discovery have been revolutionized by whole-exome and genome sequencing but identifying the causative variant(s) from the millions in each individual remains challenging. The use of deep phenotyping of patients and reference genotype-phenotype knowledge, alongside variant data such as allele frequency, segregation, and predicted pathogenicity, has proved an effective strategy to tackle this issue. Here we review the numerous tools that have been developed to automate this approach and demonstrate the power of such an approach on several thousand diagnosed cases from the 100,000 Genomes Project. Finally, we discuss the challenges that need to be overcome if we are going to improve detection rates and help the majority of patients that still remain without a molecular diagnosis after state-of-the-art genomic interpretation.

Case Report: Identification of Two Variants of ALG13 in Families With or Without Seizure and Binocular Strabismus: Phenotypic Spectrum Analysis

Background: Genetic causes in most affected children with intellectual disability and/or development delay remain unknown. Methods: To identify potential variants responsible for these disorders, we recruited 161 affected families and performed whole-exome sequencing and associated bioinformatics analysis. Results: In the present study, we report the identification of variants in the ALG13 gene in two of the families. In family 1, a known pathogenic missense variant (c.23T > C; p.V8A) of ALG13 was identified in a boy and his mother. In family 2, a novel missense variant (c.862C > G; p.L288V) of the same gene was identified in the affected boy and his phenotypically normal mother. Genotype-phenotype correlation analysis by comparing reported 28 different variants (HGMD) showed that three major phenotypes, including various seizures/epilepsy, intellectual disability, and development delay (such as growth, speech, motor, etc.), are present in most affected individuals. However, other phenotypes, such as strabismus and absence of seizure in our second patient, are not reported if any, which may represent a unique case of X-linked recessive nonsyndromic disorder caused by a mutation in ALG13. Conclusion: We identified two missense variants in ALG13 in a cohort of 161 families with affected individuals diagnosed as intellectual disability and/or development delay. A novel c.862C > G mutation may represent a case of X-linked recessive.

Genomic answers for children: Dynamic analyses of >1000 pediatric rare disease genomes

PURPOSE

This study aimed to provide comprehensive diagnostic and candidate analyses in a pediatric rare disease cohort through the Genomic Answers for Kids program.

METHODS

Extensive analyses of 960 families with suspected genetic disorders included short-read exome sequencing and short-read genome sequencing (srGS); PacBio HiFi long-read genome sequencing (HiFi-GS); variant calling for single nucleotide variants (SNV), structural variant (SV), and repeat variants; and machine-learning variant prioritization. Structured phenotypes, prioritized variants, and pedigrees were stored in PhenoTips database, with data sharing through controlled access the database of Genotypes and Phenotypes.

RESULTS

Diagnostic rates ranged from 11% in patients with prior negative genetic testing to 34.5% in naive patients. Incorporating SVs from genome sequencing added up to 13% of new diagnoses in previously unsolved cases. HiFi-GS yielded increased discovery rate with >4-fold more rare coding SVs compared with srGS. Variants and genes of unknown significance remain the most common finding (58% of nondiagnostic cases).

CONCLUSION

Computational prioritization is efficient for diagnostic SNVs. Thorough identification of non-SNVs remains challenging and is partly mitigated using HiFi-GS sequencing. Importantly, community research is supported by sharing real-time data to accelerate gene validation and by providing HiFi variant (SNV/SV) resources from >1000 human alleles to facilitate implementation of new sequencing platforms for rare disease diagnoses.

Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases

Yuan et al. recently described an independent evaluation of several phenotype-driven gene prioritization methods for Mendelian disease on two separate, clinical datasets. Although they attempted to use default settings for each tool, we describe three key differences from those we currently recommend for our Exomiser and PhenIX tools. These influence how variant frequency, quality and predicted pathogenicity are used for filtering and prioritization. We propose that these differences account for much of the discrepancy in performance between that reported by them (15–26% diagnoses ranked top by Exomiser) and previously published reports by us and others (72–77%). On a set of 161 singleton samples, we show using these settings increases performance from 34% to 72% and suggest a reassessment of Exomiser and PhenIX on their datasets using these would show a similar uplift.

Best practices for the interpretation and reporting of clinical whole genome sequencing

Whole genome sequencing (WGS) shows promise as a first-tier diagnostic test for patients with rare genetic disorders. However, standards addressing the definition and deployment practice of a best-in-class test are lacking. To address these gaps, the Medical Genome Initiative, a consortium of leading health care and research organizations in the US and Canada, was formed to expand access to high quality clinical WGS by convening experts and publishing best practices. Here, we present best practice recommendations for the interpretation and reporting of clinical diagnostic WGS, including discussion of challenges and emerging approaches that will be critical to harness the full potential of this comprehensive test.

Case Report: Novel Biallelic Variants in DNAJC21 Causing an Inherited Bone Marrow Failure Spectrum Phenotype: An Odyssey to Diagnosis

Bone marrow failure represents an umbrella diagnosis for several life-threatening disorders. In many people, the etiology remains unknown for a long time, leading to an odyssey to diagnosis, with numerous tests performed and sometimes inappropriate treatment. Biallelic pathogenic variants in the DNAJC21 gene were recently discovered to cause bone marrow failure syndrome type 3, having phenotypic overlap with Fanconi anemia, dyskeratosis congenita, Shwachman–Diamond syndrome, and Diamond–Blackfan anemia. Herein, we report an 8-year-old boy, with normal intellect, presenting bone marrow failure; growth retardation; failure to thrive; recurrent infections (including sepsis); cryptorchidia; skeletal, skin, teeth, and hair abnormalities; joint hypermobility; eczema; palpebral ptosis; high myopia; rod–cone retinal dystrophy; and short telomeres. He underwent several tests and evaluations, including genetic investigations (panel and exome sequencing), before the DNAJC21 gene was known to cause disease. Whole-genome sequencing performed at the age of 7 years, identified two novel, pathogenic, and compound heterozygous variants in the DNAJC21 gene: NM_001012339.3:c.148C>T (stopgain-maternal origin), p.Gln50∗ and c.643_644delinsTTT (frameshift paternal origin), and p.Lys215Phefs∗71. He received aggressive treatments for his multisystem disease: blood cell transfusions, high-dose corticosteroids, immunoglobulins, multiple antibiotics, vitamins, growth hormone, and others. However, allogeneic hematopoietic stem cell transplantation was avoided. The clinical evolution of bone marrow failure and recurrent infections stabilized with age, yet the myopia progressed. Exocrine pancreatic insufficiency was not detected. This report widens the molecular and clinical understanding of bone marrow failure syndrome type 3. Genome sequencing directed a precise diagnosis that improved patient management and enabled family genetic counseling.

Methods to Improve Molecular Diagnosis in Genomic Cold Cases in Pediatric Neurology

During the last decade, genetic testing has emerged as an important etiological diagnostic tool for Mendelian diseases, including pediatric neurological conditions. A genetic diagnosis has a considerable impact on disease management and treatment; however, many cases remain undiagnosed after applying standard diagnostic sequencing techniques. This review discusses various methods to improve the molecular diagnostic rates in these genomic cold cases. We discuss extended analysis methods to consider, non-Mendelian inheritance models, mosaicism, dual/multiple diagnoses, periodic re-analysis, artificial intelligence tools, and deep phenotyping, in addition to integrating various omics methods to improve variant prioritization. Last, novel genomic technologies, including long-read sequencing, artificial long-read sequencing, and optical genome mapping are discussed. In conclusion, a more comprehensive molecular analysis and a timely re-analysis of unsolved cases are imperative to improve diagnostic rates. In addition, our current understanding of the human genome is still limited due to restrictions in technologies. Novel technologies are now available that improve upon some of these limitations and can capture all human genomic variation more accurately. Last, we recommend a more routine implementation of high molecular weight DNA extraction methods that is coherent with the ability to use and/or optimally benefit from these novel genomic methods.

Genetic etiology of hearing loss in Iran

Hearing loss (HL) is an etiologically heterogeneous disorder that affects around 5% of the world's population. There has been an exponential increase in the identification of genes and variants responsible for hereditary HL over recent years. Iran, a country located in the Middle East, has a high prevalence of consanguineous marriages, so heterogeneous diseases such as HL are more common. Comprehensive studies using different strategies from linkage analysis to next-generation sequencing, especially exome-sequencing, have achieved significant success in identifying possible pathogens in deaf Iranian families. About 12% of non-syndromic autosomal recessive HL genes investigated to date, were first identified in families from Iran. Variations of 56 genes have been observed in families with NSHL in Iran. Variants in GJB2, SLC26A4, MYO15A, MYO7A, CDH23, and TMC1 account for 16.5%, 16.25%, 13.5%, 9.35%, 6.9% and 4.92%, cases of NSHL, respectively. In summary, there are also different diagnostic rates between studies conducted in Iran. In the comprehensive investigations conducted by the Genetic Research Center of the University of Social Welfare and Rehabilitation Sciences over the past 20 years, the overall diagnosis rate is about 80% while there are other studies with lower diagnostic rates which could reflect differences in project designs, sampling, and accuracy and validity of the methods used. Furthermore, there are several syndromic HHLs in Iran including, Waardenburg syndrome, BOR syndrome, Brown-Vialetto-Van Laere syndrome, Wolfram syndrome, among which Pendred and Usher syndromes are well-studied. These results are of importance for further investigation and elucidation of the molecular basis of HHL in Iran.

The importance of automation in genetic diagnosis: Lessons from analyzing an inherited retinal degeneration cohort with the Mendelian Analysis Toolkit (MATK)

PURPOSE

In Mendelian disease diagnosis, variant analysis is a repetitive, error-prone, and time consuming process. To address this, we have developed the Mendelian Analysis Toolkit (MATK), a configurable, automated variant ranking program.

METHODS

MATK aggregates variant information from multiple annotation sources and uses expert-designed rules with parameterized weights to produce a ranked list of potentially causal solutions. MATK performance was measured by a comparison between MATK-aided and human-domain expert analyses of 1060 families with inherited retinal degeneration (IRD), analyzed using an IRD-specific gene panel (589 individuals) and exome sequencing (471 families).

RESULTS

When comparing MATK-assisted analysis with expert curation in both the IRD-specific gene panel and exome sequencing (1060 subjects), 97.3% of potential solutions found by experts were also identified by the MATK-assisted analysis (541 solutions identified with MATK of 556 solutions found by conventional analysis). Furthermore, MATK-assisted analysis identified 114 additional potential solutions from the 504 cases unsolved by conventional analysis.

CONCLUSION

MATK expedites the process of identification of likely solving variants in Mendelian traits, and reduces variability stemming from human error and researcher bias. MATK facilitates data reanalysis to keep up with the constantly improving annotation sources and next-generation sequencing processing pipelines. The software is open source and available at https://gitlab.com/matthew_maher/mendelanalysis.

Somatic Variation as an Incidental Finding in the Pediatric Next Generation Sequencing Era

The methodologic approach used in next-generation sequencing (NGS) affords a high depth of coverage in genomic analysis. Inherent in the nature of genomic testing, there exists potential for identifying genomic findings that are incidental or secondary to the indication for clinical testing, with the frequency dependent on the breadth of analysis and the tissue sample under study. The interpretation and management of clinically meaningful incidental genomic findings is a pressing issue particularly in the pediatric population. Our study describes a 16-mo-old male who presented with profound global delays, brain abnormality, progressive microcephaly, and growth deficiency, as well as metopic craniosynostosis. Clinical exome sequencing (ES) trio analysis revealed the presence of two variants in the proband. The first was a de novo variant in the PPP2R1A gene (c.773G > A, p.Arg258His), which is associated with autosomal dominant (AD) intellectual disability, accounting for the proband's clinical phenotype. The second was a recurrent hotspot variant in the CBL gene (c.1111T > C, p.Tyr371His), which was present at a variant allele fraction of 11%, consistent with somatic variation in the peripheral blood sample. Germline pathogenic variants in CBL are associated with AD Noonan syndrome–like disorder with or without juvenile myelomonocytic leukemia. Molecular analyses using a different tissue source, buccal epithelial cells, suggest that the CBL alteration may represent a clonal population of cells restricted to leukocytes. This report highlights the laboratory methodologic and interpretative processes and clinical considerations in the setting of acquired variation detected during clinical ES in a pediatric patient.

The clinical utility of exome and genome sequencing across clinical indications: a systematic review

Exome sequencing and genome sequencing have the potential to improve clinical utility for patients undergoing genetic investigations. However, evidence of clinical utility is limited to pediatric populations; we aimed to fill this gap by conducting a systematic review of the literature on the clinical utility of exome/genome sequencing across disease indications in pediatric and adult populations. MEDLINE, EMBASE and Cochrane Library were searched between 2016 and 2020. Quantitative studies evaluating diagnostic yield were included; other measures of clinical utility such as changes to clinical management were documented if reported. Two reviewers screened, extracted data, and appraised risk of bias. Fifty studies met our inclusion criteria. All studies reported diagnostic yield, which ranged from 3 to 70%, with higher range of yields reported for neurological indications and acute illness ranging from 22 to 68% and 37-70%, respectively. Diagnoses triggered a range of clinical management changes including surveillance, reproductive-risk counseling, and identifying at-risk relatives in 4-100% of patients, with higher frequencies reported for acute illness ranging from 67 to 95%. The frequency of variants of uncertain significance ranged from 5 to 85% across studies with a potential trend of decreasing frequency over time and higher rates identified in patients of non-European ancestry. This review provides evidence for a higher range of diagnostic yield of exome/genome sequencing compared to standard genetic tests, particularly in neurological and acute indications. However, we identified significant heterogeneity in study procedures and outcomes, precluding a meaningful meta-analysis and certainty in the evidence available for decision-making. Future research that incorporates a comprehensive and consistent approach in capturing clinical utility of exome/genome sequencing across broader ancestral groups is necessary to improve diagnostic accuracy and yield and allow for analysis of trends over time.Prospero registration CRD42019094101.

Genetic evaluation in children with short stature

PURPOSE OF REVIEW

Short stature is a common clinical manifestation in children. Yet, a cause is often unidentifiable in the majority of children with short stature by a routine screening approach. The purpose of this review is to describe the optimal genetic approach for evaluating short stature, challenges of genetic testing, and recent advances in genetic testing for short stature.

RECENT FINDINGS

Genetic testing, such as karyotype, chromosomal microarray, targeted gene sequencing, or exome sequencing, has served to identify the underlying genetic causes of short stature. When determining which short stature patient would benefit from genetic evaluation, it is important to consider whether the patient would have a single identifiable genetic cause. Specific diagnoses permit clinicians to predict responses to growth hormone treatment, to understand the phenotypic spectrum, and to understand any associated co-morbidities.

SUMMARY

The continued progress in the field of genetics and enhanced capabilities provided by genetic testing methods expands the ability of physicians to evaluate children with short stature for underlying genetic defects. Continued effort is needed to elaborate new genetic causes of linear growth disorders, therefore, we expand the list of known genes for short stature, which will subsequently increase the rate of genetic diagnosis for children with short stature.

Clinically Responsive Genomic Analysis Pipelines: Elements to Improve Detection Rate and Efficiency

Massively parallel sequencing has markedly improved mendelian diagnostic rates. This study assessed the effects of custom alterations to a diagnostic genomic bioinformatic pipeline in response to clinical need and derived practice recommendations relative to diagnostic rates and efficiency. The Genomic Annotation and Interpretation Application (GAIA) bioinformatics pipeline was designed to detect panel, exome, and genome sample integrity and prioritize gene variants in mendelian disorders. Reanalysis of selected negative cases was performed after improvements to the pipeline. GAIA improvements and their effect on sensitivity are described, including addition of a PubMed search for gene-disease associations not in the Online Mendelian Inheritance of Man database, inclusion of a process for calling low-quality variants (known as QPatch), and gene symbol nomenclature consistency checking. The new pipeline increased the diagnostic rate and reduced staff costs, resulting in a saving of US$844.34 per additional diagnosis. Recommendations for genomic analysis pipeline requirements are summarized. Clinically responsive bioinformatics pipeline improvements increase diagnostic sensitivity and increase cost-effectiveness.

Impact of integrated translational research on clinical exome sequencing

PURPOSE

Exome sequencing often identifies pathogenic genetic variants in patients with undiagnosed diseases. Nevertheless, frequent findings of variants of uncertain significance necessitate additional efforts to establish causality before reaching a conclusive diagnosis. To provide comprehensive genomic testing to patients with undiagnosed disease, we established an Individualized Medicine Clinic, which offered clinical exome testing and included a Translational Omics Program (TOP) that provided variant curation, research activities, or research exome sequencing.

METHODS

From 2012 to 2018, 1101 unselected patients with undiagnosed diseases received exome testing. Outcomes were reviewed to assess impact of the TOP and patient characteristics on diagnostic rates through descriptive and multivariate analyses.

RESULTS

The overall diagnostic yield was 24.9% (274 of 1101 patients), with 174 (15.8% of 1101) diagnosed on the basis of clinical exome sequencing alone. Four hundred twenty-three patients with nondiagnostic or without access to clinical exome sequencing were evaluated by the TOP, with 100 (9% of 1101) patients receiving a diagnosis, accounting for 36.5% of the diagnostic yield. The identification of a genetic diagnosis was influenced by the age at time of testing and the disease phenotype of the patient.

CONCLUSION

Integration of translational research activities into clinical practice of a tertiary medical center can significantly increase the diagnostic yield of patients with undiagnosed disease.

Dilated cardiomyopathy in a patient with autosomal dominant EEF1A2-related neurodevelopmental disorder

The EEF1A2 gene encodes eukaryotic translation elongation factor 1α2, an integral component of the elongation factor complex. Heterozygous pathogenic variants in EEF1A2 are associated with neurodevelopmental disorders characterized by epilepsy, global developmental delay, and autism. To date, dilated cardiomyopathy has only been reported in two siblings with neurodevelopmental phenotypes and a homozygous missense variant in EEF1A2. This report describes a nine-year-old female patient who presented with neurodevelopmental phenotypes and dilated cardiomyopathy. Analysis of 193 epilepsy genes by focused exome sequencing revealed a novel heterozygous variant c.46G > C (p.Val16Leu; NM_001958.3) in EEF1A2. The variant was not detected in either parent, confirming its de novo origin. No additional variants that explain the patient's phenotypes were found by subsequent whole exome analysis. Copy number analysis of the exome data and exon-level microarray excluded a deletion in the other allele of EEF1A2. We present the first patient with a heterozygous pathogenic EEF1A2 variant who had dilated cardiomyopathy as well as neurodevelopmental phenotypes, suggesting that this cardiac phenotype may be associated with the autosomal dominant form of the EEF1A2-related disorder.

A Next-Generation Sequencing Test for Severe Congenital Neutropenia: Utility in a Broader Clinicopathologic Spectrum of Disease

Severe congenital neutropenia (SCN) is a collection of diverse disorders characterized by chronically low absolute neutrophil count in the peripheral blood, increased susceptibility to infection, and a significant predisposition to the development of myeloid malignancies. SCN can be acquired or inherited. Inherited forms have been linked to variants in a group of diverse genes involved in the neutrophil-differentiation process. Variants that promote resistance to treatment have also been identified. Thus, genetic testing is important for the diagnosis, prognosis, and management of SCN. Herein we describe clinically validated assay developed for assessing patients with suspected SCN. The assay is performed from a whole-exome backbone. Variants are called across all coding exons, and results are filtered to focus on 48 genes that are clinically relevant to SCN. Validation results indicated 100% analytical sensitivity and specificity for the detection of constitutional variants among the 48 reportable genes. To date, 34 individuals have been referred for testing (age range: birth to 67 years). Several pathogenic and likely pathogenic variants have been identified, including one in a patient with late-onset disease. The pattern of cases referred for testing suggests that this assay has clinical utility in a broader spectrum of patients beyond those in the pediatric population who have classic early-onset symptoms characteristic of SCN.

Novel progressive acrodysostosis-like skeletal dysplasia, cerebellar atrophy, and ichthyosis

Acrodysostosis refers to a rare heterogeneous group of bone dysplasias that share skeletal features, hormone resistance, and intellectual disability. Two genes have been associated with acrodysostosis with or without hormone resistance (PRKAR1A and PDE4D). Severe intellectual disability has been reported with acrodysostosis but brain malformations and ichthyosis have not been reported in these syndromes. Here we describe a female patient with acrodysostosis, intellectual disability, cerebellar hypoplasia, and lamellar ichthyosis. The patient has an evolving distinctive facial phenotype and childhood onset ataxia. X-rays showed generalized osteopenia, shortening of middle and distal phalanges, and abnormal distal epiphysis of the ulna and radius. Brain magnetic resonance imaging showed cerebellar atrophy without other brainstem abnormalities. Genetic workup included nondiagnostic chromosomal microarray and skeletal dysplasia molecular panels. These clinical findings are different from any recognized form of acrodysostosis syndrome. Whole exome sequencing did not identify rare or predicted pathogenic variants in genes associated with known acrodysostosis, lamellar ichthyosis, and other overlapping disorders. A broader search for rare alleles absent in healthy population databases and controls identified two heterozygous truncating alleles in FBNL7 and PPM1M genes, and one missense allele in the NPEPPS gene. Identification of additional patients is required to delineate the mechanism of this unique disorder.

Synonymous GATA2 mutations result in selective loss of mutated RNA and are common in patients with GATA2 deficiency

Deficiency of the transcription factor GATA2 is a highly penetrant genetic disorder predisposing to myelodysplastic syndromes (MDS) and immunodeficiency. It has been recognized as the most common cause underlying primary MDS in children. Triggered by the discovery of a recurrent synonymous GATA2 variant, we systematically investigated 911 patients with phenotype of pediatric MDS or cellular deficiencies for the presence of synonymous alterations in GATA2. In total, we identified nine individuals with five heterozygous synonymous mutations: c.351C>G, p.T117T (N = 4); c.649C>T, p.L217L; c.981G>A, p.G327G; c.1023C>T, p.A341A; and c.1416G>A, p.P472P (N = 2). They accounted for 8.2% (9/110) of cases with GATA2 deficiency in our cohort and resulted in selective loss of mutant RNA. While for the hotspot mutation (c.351C>G) a splicing error leading to RNA and protein reduction was identified, severe, likely late stage RNA loss without splicing disruption was found for other mutations. Finally, the synonymous mutations did not alter protein function or stability. In summary, synonymous GATA2 substitutions are a new common cause of GATA2 deficiency. These findings have broad implications for genetic counseling and pathogenic variant discovery in Mendelian disorders.

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

An Improved Phenotype-Driven Tool for Rare Mendelian Variant Prioritization: Benchmarking Exomiser on Real Patient Whole-Exome Data

Next-generation sequencing has revolutionized rare disease diagnostics, but many patients remain without a molecular diagnosis, particularly because many candidate variants usually survive despite strict filtering. Exomiser was launched in 2014 as a Java tool that performs an integrative analysis of patients' sequencing data and their phenotypes encoded with Human Phenotype Ontology (HPO) terms. It prioritizes variants by leveraging information on variant frequency, predicted pathogenicity, and gene-phenotype associations derived from human diseases, model organisms, and protein-protein interactions. Early published releases of Exomiser were able to prioritize disease-causative variants as top candidates in up to 97% of simulated whole-exomes. The size of the tested real patient datasets published so far are very limited. Here, we present the latest Exomiser version 12.0.1 with many new features. We assessed the performance using a set of 134 whole-exomes from patients with a range of rare retinal diseases and known molecular diagnosis. Using default settings, Exomiser ranked the correct diagnosed variants as the top candidate in 74% of the dataset and top 5 in 94%; not using the patients' HPO profiles (i.e., variant-only analysis) decreased the performance to 3% and 27%, respectively. In conclusion, Exomiser is an effective support tool for rare Mendelian phenotype-driven variant prioritization.

Detection of mitochondrial DNA variants at low level heteroplasmy in pediatric CNS and extra-CNS solid tumors with three different enrichment methods

The mitochondrial genome is small, 16.5 kb, and yet complex to study due to an abundance of mitochondria in any given cell or tissue. Mitochondrial DNA (mtDNA) mutations have been previously described in cancer, many of which were detected at low heteroplasmy. In this study we enriched the mitochondrial genome in primary pediatric tumors for detection of mtDNA variants. We completed mtDNA enrichment using REPLI-g, Agilent SureSelect, and long-range polymerase chain reaction (LRPCR) followed by next generation sequencing (NGS) on Illumina platforms. Primary tumor and germline genomic DNA from a variety of pediatric central nervous system (CNS) and extra-CNS solid tumors were analyzed by the three different methods. Although all three methods performed equally well for detecting variants at high heteroplasmy or homoplasmy, only LRPCR and SureSelect-based enrichment methods provided consistent results for variants that were present at less than five percent heteroplasmy. We then applied both LRPCR and SureSelect to three successive samples from a patient with multiply-recurrent gliofibroma and detected a low-level novel mutation as well as a change in heteroplasmy levels of a synonymous variant that was correlated with progression of disease. IMPLICATION: This study demonstrates that LRPCR and SureSelect enrichment, but not REPLI-g, followed by NGS are accurate methods for studying the mtDNA variations at low heteroplasmy, which may be applied to studying mtDNA mutations in cancer.