Next generation sequencing for clinical diagnostics: Five year experience of an academic laboratory

Clinical application of prospective whole-exome sequencing in the diagnosis of genetic disease: Experience of a regional disease center in South Korea

INTRODUCTION

Next-generation sequencing helps clinicians diagnose patients with suspected genetic disorders. The current study aimed to investigate the diagnostic yield and clinical utility of prospective whole-exome sequencing (WES) in rare diseases.

METHODS

WES was performed in 92 patients who presented with clinical symptoms suggestive of genetic disorders. The WES data were analyzed using an in-house developed software. The patients' phenotypic characteristics were classified according to the human phenotype ontology.

RESULTS

WES detected 64 variants, 13 were classified as pathogenic, 26 as likely pathogenic, and 25 as variants of uncertain significance. In 57 patients with these variants, 30 were identified as causal variants. The diagnostic yield was higher in patients with abnormalities in joint mobility and skin morphology than in those with cerebellar hypoplasia/atrophy, epilepsy, global developmental delay, dysmorphic features/facial dysmorphisms, and chronic kidney disease/abnormal renal morphology.

CONCLUSION

In this study, a WES-based variant interpretation system was employed to provide a definitive diagnosis for 28.3% of the patients suspected of having genetic disorders. WES is particularly useful for diagnosing rare diseases with symptoms that affect more than one system, when targeted genetic panels are difficult to employ.

Clinical application of next generation sequencing for Mendelian disease diagnosis in the Iranian population

Next-generation sequencing (NGS) has been proven to be one of the most powerful diagnostic tools for rare Mendelian disorders. Several studies on the clinical application of NGS in unselected cohorts of Middle Eastern patients have reported a high diagnostic yield of up to 48%, correlated with a high level of consanguinity in these populations. We evaluated the diagnostic utility of NGS-based testing across different clinical indications in 1436 patients from Iran, representing the first study of its kind in this highly consanguineous population. A total of 1075 exome sequencing and 361 targeted gene panel sequencing were performed over 8 years at a single clinical genetics laboratory, with the majority of cases tested as proband-only (91.6%). The overall diagnostic rate was 46.7%, ranging from 24% in patients with an abnormality of prenatal development to over 67% in patients with an abnormality of the skin. We identified 660 pathogenic or likely pathogenic variants, including 241 novel variants, associated with over 342 known genetic conditions. The highly consanguineous nature of this cohort led to the diagnosis of autosomal recessive disorders in the majority of patients (79.1%) and allowed us to determine the shared carrier status of couples for suspected recessive phenotypes in their deceased child(ren) when direct testing was not possible. We also highlight the observations of recessive inheritance of genes previously associated only with dominant disorders and provide an expanded genotype-phenotype spectrum for multiple less-characterized genes. We present the largest mutational spectrum of known Mendelian disease, including possible founder variants, throughout the Iranian population, which can serve as a unique resource for clinical genomic studies locally and beyond.

Next-generation sequencing in dermatology

Over the past decade, Next-Generation Sequencing (NGS) has advanced our understanding, diagnosis, and management of several areas within dermatology. NGS has emerged as a powerful tool for diagnosing genetic diseases of the skin, improving upon traditional PCR-based techniques limited by significant genetic heterogeneity associated with these disorders. Epidermolysis bullosa and ichthyosis are two of the most extensively studied genetic diseases of the skin, with a well-characterized spectrum of genetic changes occurring in these conditions. NGS has also played a critical role in expanding the mutational landscape of cutaneous squamous cell carcinoma, enhancing our understanding of its molecular pathogenesis. Similarly, genetic testing has greatly benefited melanoma diagnosis and treatment, primarily due to the high prevalence of BRAF hot spot mutations and other well-characterized genetic alterations. Additionally, NGS provides a valuable tool for measuring tumor mutational burden, which can aid in management of melanoma. Lastly, NGS demonstrates promise in improving the sensitivity of diagnosing cutaneous T-cell lymphoma. This article provides a comprehensive summary of NGS applications in the diagnosis and management of genodermatoses, cutaneous squamous cell carcinoma, melanoma, and cutaneous T-cell lymphoma, highlighting the impact of NGS on the field of dermatology.

Cross-platform comparisons for targeted bisulfite sequencing of MGISEQ-2000 and NovaSeq6000

BACKGROUND

An accurate and reproducible next-generation sequencing platform is essential to identify malignancy-related abnormal DNA methylation changes and translate them into clinical applications including cancer detection, prognosis, and surveillance. However, high-quality DNA methylation sequencing has been challenging because poor sequence diversity of the bisulfite-converted libraries severely impairs sequencing quality and yield. In this study, we tested MGISEQ-2000 Sequencer's capability of DNA methylation sequencing with a published non-invasive pancreatic cancer detection assay, using NovaSeq6000 as the benchmark.

RESULTS

We sequenced a series of synthetic cell-free DNA (cfDNA) samples with different tumor fractions and found MGISEQ-2000 yielded data with similar quality as NovaSeq6000. The methylation levels measured by MGISEQ-2000 demonstrated high consistency with NovaSeq6000. Moreover, MGISEQ-2000 showed a comparable analytic sensitivity with NovaSeq6000, suggesting its potential for clinical detection. As to evaluate the clinical performance of MGISEQ-2000, we sequenced 24 clinical samples and predicted the pathology of the samples with a clinical diagnosis model, PDACatch classifier. The clinical model performance of MGISEQ-2000's data was highly consistent with that of NovaSeq6000's data, with the area under the curve of 1. We also tested the model's robustness with MGISEQ-2000's data when reducing the sequencing depth. The results showed that MGISEQ-2000's data showed matching robustness of the PDACatch classifier with NovaSeq6000's data.

CONCLUSIONS

Taken together, MGISEQ-2000 demonstrated similar data quality, consistency of the methylation levels, comparable analytic sensitivity, and matching clinical performance, supporting its application in future non-invasive early cancer detection investigations by detecting distinct methylation patterns of cfDNAs.

Role of non-coding variants in cardiovascular disease

Cardiovascular diseases (CVDs) constitute one of the significant causes of death worldwide. Different pathological states are linked to CVDs, which despite interventions and treatments, still have poor prognoses. The genetic component, as a beneficial tool in the risk stratification of CVD development, plays a role in the pathogenesis of this group of diseases. The emergence of genome-wide association studies (GWAS) have led to the identification of non-coding parts associated with cardiovascular traits and disorders. Variants located in functional non-coding regions, including promoters/enhancers, introns, miRNAs and 5'/3' UTRs, account for 90% of all identified single-nucleotide polymorphisms associated with CVDs. Here, for the first time, we conducted a comprehensive review on the reported non-coding variants for different CVDs, including hypercholesterolemia, cardiomyopathies, congenital heart diseases, thoracic aortic aneurysms/dissections and coronary artery diseases. Additionally, we present the most commonly reported genes involved in each CVD. In total, 1469 non-coding variants constitute most reports on familial hypercholesterolemia, hypertrophic cardiomyopathy and dilated cardiomyopathy. The application and identification of non-coding variants are beneficial for the genetic diagnosis and better therapeutic management of CVDs.

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

BACKGROUND

Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques.

RESULTS

We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection.

CONCLUSION

We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques.

Implementation of Exome Sequencing in Clinical Practice for Neurological Disorders

Neurological disorders (ND) are diseases that affect the brain and the central and autonomic nervous systems, such as neurodevelopmental disorders, cerebellar ataxias, Parkinson’s disease, or epilepsies. Nowadays, recommendations of the American College of Medical Genetics and Genomics strongly recommend applying next generation sequencing (NGS) as a first-line test in patients with these disorders. Whole exome sequencing (WES) is widely regarded as the current technology of choice for diagnosing monogenic ND. The introduction of NGS allows for rapid and inexpensive large-scale genomic analysis and has led to enormous progress in deciphering monogenic forms of various genetic diseases. The simultaneous analysis of several potentially mutated genes improves the diagnostic process, making it faster and more efficient. The main aim of this report is to discuss the impact and advantages of the implementation of WES into the clinical diagnosis and management of ND. Therefore, we have performed a retrospective evaluation of WES application in 209 cases referred to the Department of Biochemistry and Molecular Genetics of the Hospital Clinic of Barcelona for WES sequencing derived from neurologists or clinical geneticists. In addition, we have further discussed some important facts regarding classification criteria for pathogenicity of rare variants, variants of unknown significance, deleterious variants, different clinical phenotypes, or frequency of actionable secondary findings. Different studies have shown that WES implementation establish diagnostic rate around 32% in ND and the continuous molecular diagnosis is essential to solve the remaining cases.

Five years' experience of the clinical exome sequencing in a Spanish single center

Nowadays, exome sequencing is a robust and cost-efficient genetic diagnostic tool already implemented in many clinical laboratories. Despite it has undoubtedly improved our diagnostic capacity and has allowed the discovery of many new Mendelian-disease genes, it only provides a molecular diagnosis in up to 25-30% of cases. Here, we comprehensively evaluate the results of a large sample set of 4974 clinical exomes performed in our laboratory over a period of 5 years, showing a global diagnostic rate of 24.62% (1391/4974). For the evaluation we establish different groups of diseases and demonstrate how the diagnostic rate is not only dependent on the analyzed group of diseases (43.12% in ophthalmological cases vs 16.61% in neurological cases) but on the specific disorder (47.49% in retinal dystrophies vs 24.02% in optic atrophy; 18.88% in neuropathies/paraparesias vs 11.43% in dementias). We also detail the most frequent mutated genes within each group of disorders and discuss, on our experience, further investigations and directions needed for the benefit of patients.

Human Retrotransposons and Effective Computational Detection Methods for Next-Generation Sequencing Data

Transposable elements (TEs) are classified into two classes according to their mobilization mechanism. Compared to DNA transposons that move by the "cut and paste" mechanism, retrotransposons mobilize via the "copy and paste" method. They have been an essential research topic because some of the active elements, such as Long interspersed element 1 (LINE-1), Alu, and SVA elements, have contributed to the genetic diversity of primates beyond humans. In addition, they can cause genetic disorders by altering gene expression and generating structural variations (SVs). The development and rapid technological advances in next-generation sequencing (NGS) have led to new perspectives on detecting retrotransposon-mediated SVs, especially insertions. Moreover, various computational methods have been developed based on NGS data to precisely detect the insertions and deletions in the human genome. Therefore, this review discusses details about the recently studied and utilized NGS technologies and the effective computational approaches for discovering retrotransposons through it. The final part covers a diverse range of computational methods for detecting retrotransposon insertions with human NGS data. This review will give researchers insights into understanding the TEs and how to investigate them and find connections with research interests.

AnFiSA: An open-source computational platform for the analysis of sequencing data for rare genetic disease

Despite genomic sequencing rapidly transforming from being a bench-side tool to a routine procedure in a hospital, there is a noticeable lack of genomic analysis software that supports both clinical and research workflows as well as crowdsourcing. Furthermore, most existing software packages are not forward-compatible in regards to supporting ever-changing diagnostic rules adopted by the genetics community. Regular updates of genomics databases pose challenges for reproducible and traceable automated genetic diagnostics tools. Lastly, most of the software tools score low on explainability amongst clinicians. We have created a fully open-source variant curation tool, AnFiSA, with the intention to invite and accept contributions from clinicians, researchers, and professional software developers. The design of AnFiSA addresses the aforementioned issues via the following architectural principles: using a multidimensional database management system (DBMS) for genomic data to address reproducibility, curated decision trees adaptable to changing clinical rules, and a crowdsourcing-friendly interface to address difficult-to-diagnose cases. We discuss how we have chosen our technology stack and describe the design and implementation of the software. Finally, we show in detail how selected workflows can be implemented using the current version of AnFiSA by a medical geneticist.

Phenotypic Variation in Two Siblings Affected with Shwachman-Diamond Syndrome: The Use of Expert Variant Interpreter (eVai) Suggests Clinical Relevance of a Variant in the KMT2A Gene

Introduction. Shwachman-Diamond Syndrome (SDS) is an autosomal-recessive disorder characterized by neutropenia, pancreatic exocrine insufficiency, skeletal dysplasia, and an increased risk for leukemic transformation. Biallelic mutations in the SBDS gene have been found in about 90% of patients. The clinical spectrum of SDS in patients is wide, and variability has been noticed between different patients, siblings, and even within the same patient over time. Herein, we present two SDS siblings (UPN42 and UPN43) carrying the same SBDS mutations and showing relevant differences in their phenotypic presentation. Study aim. We attempted to understand whether other germline variants, in addition to SBDS, could explain some of the clinical variability noticed between the siblings. Methods. Whole-exome sequencing (WES) was performed. Human Phenotype Ontology (HPO) terms were defined for each patient, and the WES data were analyzed using the eVai and DIVAs platforms. Results. In UPN43, we found and confirmed, using Sanger sequencing, a novel de novo variant (c.10663G > A, p.Gly3555Ser) in the KMT2A gene that is associated with autosomal-dominant Wiedemann−Steiner Syndrome. The variant is classified as pathogenic according to different in silico prediction tools. Interestingly, it was found to be related to some of the HPO terms that describe UPN43. Conclusions. We postulate that the KMT2A variant found in UPN43 has a concomitant and co-occurring clinical effect, in addition to SBDS mutation. This dual molecular effect, supported by in silico prediction, could help to understand some of the clinical variations found among the siblings. In the future, these new data are likely to be useful for personalized medicine and therapy for selected cases.

Detection of respiratory viruses directly from clinical samples using next-generation sequencing: A literature review of recent advances and potential for routine clinical use

Acute respiratory infection is the third most frequent cause of mortality worldwide, causing over 4.25 million deaths annually. Although most diagnosed acute respiratory infections are thought to be of viral origin, the aetiology often remains unclear. The advent of next‐generation sequencing (NGS) has revolutionised the field of virus discovery and identification, particularly in the detection of unknown respiratory viruses. We systematically reviewed the application of NGS technologies for detecting respiratory viruses from clinical samples and outline potential barriers to the routine clinical introduction of NGS. The five databases searched for studies published in English from 01 January 2010 to 01 February 2021, which led to the inclusion of 52 studies. A total of 14 different models of NGS platforms were summarised from included studies. Among these models, second‐generation sequencing platforms (e.g., Illumina sequencers) were used in the majority of studies (41/52, 79%). Moreover, NGS platforms have proven successful in detecting a variety of respiratory viruses, including influenza A/B viruses (9/52, 17%), SARS‐CoV‐2 (21/52, 40%), parainfluenza virus (3/52, 6%), respiratory syncytial virus (1/52, 2%), human metapneumovirus (2/52, 4%), or a viral panel including other respiratory viruses (16/52, 31%). The review of NGS technologies used in previous studies indicates the advantages of NGS technologies in novel virus detection, virus typing, mutation identification, and infection cluster assessment. Although there remain some technical and ethical challenges associated with NGS use in clinical laboratories, NGS is a promising future tool to improve understanding of respiratory viruses and provide a more accurate diagnosis with simultaneous virus characterisation.

Poly(A) capture full length cDNA sequencing improves the accuracy and detection ability of transcript quantification and alternative splicing events

The full-length double-strand cDNA sequencing, one of the RNA-Seq methods, is a powerful method used to investigate the transcriptome status of a gene of interest, such as its transcription level and alternative splicing variants. Furthermore, full-length double-strand cDNA sequencing has the advantage that it can create a library from a small amount of sample and the library can be applied to long-read sequencers in addition to short-read sequencers. Nevertheless, one of our previous studies indicated that the full-length double-strand cDNA sequencing yields non-specific genomic DNA amplification, affecting transcriptome analysis, such as transcript quantification and alternative splicing analysis. In this study, it was confirmed that it is possible to produce the RNA-Seq library from only genomic DNA and that the full-length double-strand cDNA sequencing of genomic DNA yielded non-specific genomic DNA amplification. To avoid non-specific genomic DNA amplification, two methods were examined, which are the DNase I-treated full-length double-strand cDNA sequencing and poly(A) capture full-length double-strand cDNA sequencing. Contrary to expectations, the non-specific genomic DNA amplification was increased and the number of the detected expressing genes was reduced in DNase I-treated full-length double-strand cDNA sequencing. On the other hand, in the poly(A) capture full-length double-strand cDNA sequencing, the non-specific genomic DNA amplification was significantly reduced, accordingly the accuracy and the number of detected expressing genes and splicing events were increased. The expression pattern and percentage spliced in index of splicing events were highly correlated. Our results indicate that the poly(A) capture full-length double-strand cDNA sequencing improves transcript quantification accuracy and the detection ability of alternative splicing events. It is also expected to contribute to the determination of the significance of DNA variants to splicing events.

Determining Mitochondrial 3243A>G Heteroplasmy Using an ARMS-ddPCR Strategy

OBJECTIVES

Determining mitochondrial DNA (mtDNA) A-to-G substitution at nucleotide 3243 (m.3243A>G) heteroplasmy is essential for both precision diagnosis of m.3243A>G-associated mitochondrial disease and genetic counseling. Precise determination of m.3243A>G heteroplasmy is challenging, however, without appropriate strategies to accommodate heteroplasmic levels ranging from 1% to 100% in samples carrying thousands to millions of mtDNA copies.

METHODS

We used a combined strategy of amplification-refractory mutation system-quantitative polymerase chain reaction (ARMS-qPCR) and droplet digital PCR (ddPCR) to determine m.3243A>G heteroplasmy. Primers were specifically designed and screened for both ARMS-qPCR and ddPCR to determine m.3243A>G heteroplasmy. An optimized ARMS-qPCR-ddPCR-based strategy was established using artificial standards, with different mixtures of m.3243A-containing and m.3243G-containing plasmids and further tested using clinical samples containing the m.3243A>G mutation.

RESULTS

One of 20 primer pairs designed in the study was omitted for ARMS-qPCR-ddPCR strategy application according to criteria of 85% to 110%, R2> 0.98 amplification efficiency, melt curve with a single clear peak, and specificity for m.3243A and m.3243G artificial standards (|CtWt-CtMut|max). Using plasmid standards with various m.3243A>G heteroplasmy (1%-100%) at low, mid, and high copy numbers (3,000, 104, and 105-107, respectively) and DNA from the blood of 20 patients carrying m.3243A>G with mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes, we found that ARMS-qPCR was reliable for determining m.3243A>G at 3% to 100% for low copy number and 1% to 100% for mid to high copy number samples. Meanwhile, ddPCR was reliable for determining m.3243A>G at 1% to 100% at low to mid copy number samples.

CONCLUSIONS

An ARMS-qPCR-ddPCR-based strategy was successfully established for precise determination of m.3243A>G heteroplasmy in complex clinical samples.

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.

Copy number variants calling from WES data through eXome hidden Markov model (XHMM) identifies additional 2.5% pathogenic genomic imbalances smaller than 30 kb undetected by array-CGH

It has been estimated that Copy Number Variants (CNVs) account for 10%-20% of patients affected by Developmental Disorder (DD)/Intellectual Disability (ID). Although array comparative genomic hybridization (array-CGH) represents the gold-standard for the detection of genomic imbalances, common Agilent array-CGH 4 × 180 kb arrays fail to detect CNVs smaller than 30 kb. Whole Exome sequencing (WES) is becoming the reference application for the detection of gene variants and makes it possible also to infer genomic imbalances at single exon resolution. However, the contribution of small CNVs in DD/ID is still underinvestigated. We made use of the eXome Hidden Markov Model (XHMM) software, a tool utilized by the ExAC consortium, to detect CNVs from whole exome sequencing data, in a cohort of 200 unsolved DD/DI patients after array-CGH and WES-based single nucleotide/indel variant analyses. In five out of 200 patients (2.5%), we identified pathogenic CNV(s) smaller than 30 kb, ranging from one to six exons. They included two heterozygous deletions in TCF4 and STXBP1 and three homozygous deletions in PPT1, CLCN2, and PIGN. After reverse phenotyping, all variants were reported as causative. This study shows the interest in applying sequencing-based CNV detection, from available WES data, to reduce the diagnostic odyssey of additional patients unsolved DD/DI patients and compare the CNV-detection yield of Agilent array-CGH 4 × 180kb versus whole exome sequencing.

Genetic variants in eleven central and peripheral chemoreceptor genes in sudden infant death syndrome

BACKGROUND

Sudden infant death syndrome (SIDS) is still one of the leading causes of postnatal infant death in developed countries. The occurrence of SIDS is described by a multifactorial etiology that involves the respiratory control system including chemoreception. It is still unclear whether genetic variants in genes involved in respiratory chemoreception might play a role in SIDS.

METHODS

The exome data of 155 SIDS cases were screened for variants within 11 genes described in chemoreception. Pathogenicity of variants was assigned based on the assessment of variant types and in silico protein predictions according to the current recommendations of the American College of Medical Genetics and Genomics.

RESULTS

Potential pathogenic variants in genes encoding proteins involved in respiratory chemoreception could be identified in 5 (3%) SIDS cases. Two of the variants (R137S/A188S) were found in the KNCJ16 gene, which encodes for the potassium channel Kir5.1, presumably involved in central chemoreception. Electrophysiologic analysis of these KCNJ16 variants revealed a loss-of-function for the R137S variant but no obvious impairment for the A188S variant.

CONCLUSIONS

Genetic variants in genes involved in respiratory chemoreception may be a risk factor in a fraction of SIDS cases and may thereby contribute to the multifactorial etiology of SIDS.

IMPACT

What is the key message of your article? Gene variants encoding proteins involved in respiratory chemoreception may play a role in a minority of SIDS cases. What does it add to the existing literature? Although impaired respiratory chemoreception has been suggested as an important risk factor for SIDS, genetic variants in single genes seem to play a minor role. What is the impact? This study supports previous findings, which indicate that genetic variants in single genes involved in respiratory control do not have a dominant role in SIDS.

Phenotype-driven variant filtration strategy in exome sequencing toward a high diagnostic yield and identification of 85 novel variants in 400 patients with rare Mendelian disorders

About 6000 to 7000 different rare disorders with suspected genetic etiologies have been described and almost 4500 causative gene(s) have been identified. The advent of next-generation sequencing (NGS) technologies has revolutionized genomic research and diagnostics, representing a major advance in the identification of pathogenic genetic variations. This study presents a 3-year experience from an academic genetics center, where 400 patients were referred for genetic analysis of disorders with unknown etiology. A phenotype-driven proband-only exome sequencing (ES) strategy was applied for the investigation of rare disorders, in the context of optimizing ES diagnostic yield and minimizing costs and time to definitive diagnosis. Overall molecular diagnostic yield reached 53% and characterized 243 pathogenic variants in 210 cases, 85 of which were novel and 148 known, contributing information to the community of disease and variant databases. ES provides an opportunity to resolve the genetic etiology of disorders and support appropriate medical management and genetic counseling. In cases with complex phenotypes, the identification of complex genotypes may contribute to more comprehensive clinical management. In the context of effective multidisciplinary collaboration between clinicians and laboratories, ES provides an efficient and appropriate tool for first-tier genomic analysis.

Improving diagnostics of rare genetic diseases with NGS approaches

According to a rough estimate, one in fifteen people worldwide is affected by a rare disease. Rare diseases are therefore common in clinical practice; however, timely diagnosis of rare diseases is still challenging. Introduction of novel methods based on next-generation sequencing (NGS) technology offers a successful diagnosis of genetically heterogeneous disorders, even in case of unclear clinical diagnostic hypothesis. However, the application of novel technology differs among the centres and health systems significantly. Our goal is to discuss the impact of the implementation of NGS in the diagnosis of rare diseases and present advantages along with challenges of diagnostic approach. Systematic implementation of NGS in health systems can significantly improve the access of patients with rare diseases to diagnosis and reduce the dependence of national health systems for cross-border collaboration.

Targeted Double-Stranded cDNA Sequencing-Based Phase Analysis to Identify Compound Heterozygous Mutations and Differential Allelic Expression

Simple Summary

Phase analysis to distinguish between in cis and in trans heterozygous mutations is important for clinical diagnosis because in trans compound heterozygous mutations cause autosomal recessive diseases. However, conventional phase analysis is limited because of the large target size of genomic DNA. Here, we performed a targeted double-stranded cDNA sequencing-based phase analysis to resolve the limitation of distance using direct adapter ligation library preparation and paired-end sequencing; we elucidated that two heterozygous mutations on a patient with Wilson disease are in trans compound heterozygous mutations. Furthermore, we detected the differential allelic expression. Our results indicate that a targeted double-stranded cDNA sequencing-based phase analysis is useful for determining compound heterozygous mutations and confers information on allelic expression.

Abstract

There are two combinations of heterozygous mutation, i.e., in trans, which carries mutations on different alleles, and in cis, which carries mutations on the same allele. Because only in trans compound heterozygous mutations have been implicated in autosomal recessive diseases, it is important to distinguish them for clinical diagnosis. However, conventional phase analysis is limited because of the large target size of genomic DNA. Here, we performed a genetic analysis on a patient with Wilson disease, and we detected two heterozygous mutations chr13:51958362;G>GG (NM_000053.4:c.2304dup r.2304dup p.Met769HisfsTer26) and chr13:51964900;C>T (NM_000053.4:c.1841G>A r.1841g>a p.Gly614Asp) in the causative gene ATP7B. The distance between the two mutations was 6.5 kb in genomic DNA but 464 bp in mRNA. Targeted double-stranded cDNA sequencing-based phase analysis was performed using direct adapter ligation library preparation and paired-end sequencing, and we elucidated they are in trans compound heterozygous mutations. Trio analysis showed that the mutation (chr13:51964900;C>T) derived from the father and the other mutation from the mother, validating that the mutations are in trans composition. Furthermore, targeted double-stranded cDNA sequencing-based phase analysis detected the differential allelic expression, suggesting that the mutation (chr13:51958362;G>GG) caused downregulation of expression by nonsense-mediated mRNA decay. Our results indicate that targeted double-stranded cDNA sequencing-based phase analysis is useful for determining compound heterozygous mutations and confers information on allelic expression.

Prioritizing variants of uncertain significance for reclassification using a rule-based algorithm in inherited retinal dystrophies

Inherited retinal dystrophies (IRD) are a highly heterogeneous group of rare diseases with a molecular diagnostic rate of >50%. Reclassification of variants of uncertain significance (VUS) poses a challenge for IRD diagnosis. We collected 668 IRD cases analyzed by our geneticists using two different clinical exome-sequencing tests. We identified 114 unsolved cases pending reclassification of 125 VUS and studied their genomic, functional, and laboratory-specific features, comparing them to pathogenic and likely pathogenic variants from the same cohort (N = 390). While the clinical exome used did not show differences in diagnostic rate, the more IRD-experienced geneticist reported more VUS (p = 4.07e-04). Significantly fewer VUS were reported in recessive cases (p = 2.14e-04) compared to other inheritance patterns, and of all the genes analyzed, ABCA4 and IMPG2 had the lowest and highest VUS frequencies, respectively (p = 3.89e-04, p = 6.93e-03). Moreover, few frameshift and stop-gain variants were found to be informed VUS (p = 6.73e-08 and p = 2.93e-06). Last, we applied five pathogenicity predictors and found there is a significant proof of deleteriousness when all score for pathogenicity in missense variants. Altogether, these results provided input for a set of rules that correctly reclassified ~70% of VUS as pathogenic in validation datasets. Disease- and setting-specific features influence VUS reporting. Comparison with pathogenic and likely pathogenic variants can prioritize VUS more likely to be reclassified as causal.

Ocular Phenotype Associated with DYRK1A Variants

Dual-specificity tyrosine phosphorylation-regulated kinase 1A or DYRK1A, contributes to central nervous system development in a dose-sensitive manner. Triallelic DYRK1A is implicated in the neuropathology of Down syndrome, whereas haploinsufficiency causes the rare DYRK1A-related intellectual disability syndrome (also known as mental retardation 7). It is characterised by intellectual disability, autism spectrum disorder and microcephaly with a typical facial gestalt. Preclinical studies elucidate a role for DYRK1A in eye development and case studies have reported associated ocular pathology. In this study families of the DYRK1A Syndrome International Association were asked to self-report any co-existing ocular abnormalities. Twenty-six patients responded but only 14 had molecular confirmation of a DYRK1A pathogenic variant. A further nineteen patients from the UK Genomics England 100,000 Genomes Project were identified and combined with 112 patients reported in the literature for further analysis. Ninety out of 145 patients (62.1%) with heterozygous DYRK1A variants revealed ocular features, these ranged from optic nerve hypoplasia (13%, 12/90), refractive error (35.6%, 32/90) and strabismus (21.1%, 19/90). Patients with DYRK1A variants should be referred to ophthalmology as part of their management care pathway to prevent amblyopia in children and reduce visual comorbidity, which may further impact on learning, behaviour, and quality of life.

Expediting rare disease diagnosis: a call to bridge the gap between clinical and functional genomics

Approximately 400 million people throughout the world suffer from a rare disease. Although advances in whole exome and whole genome sequencing have greatly facilitated rare disease diagnosis, overall diagnostic rates remain below 50%. Furthermore, in cases where accurate diagnosis is achieved the process requires an average of 4.8 years. Reducing the time required for disease diagnosis is among the most critical needs of patients impacted by a rare disease. In this perspective we describe current challenges associated with rare disease diagnosis and discuss several cutting-edge functional genomic screening technologies that have the potential to rapidly accelerate the process of distinguishing pathogenic variants that lead to disease.

Functional characterisation guides classification of novel BAP1 germline variants

We have identified six patients harbouring distinct germline BAP1 mutations. In this study, we functionally characterise known BAP1 pathogenic and likely benign germline variants out of these six patients to aid in the evaluation and classification of unknown BAP1 germline variants. We found that pathogenic germline variants tend to encode truncated proteins, show diminished expression of epithelial-mesenchymal transition (EMT) markers, are localised in the cytosol and have reduced deubiquitinase capabilities. We show that these functional assays are useful for BAP1 variant curation and may be added in the American College of Medical Genetics and Genomics (ACMG) criteria for BAP1 variant classification. This will allow clinicians to distinguish between BAP1 pathogenic and likely benign variants reliably and may aid to quickly benchmark newly identified BAP1 germline variants. Classification of novel BAP1 germline variants allows clinicians to inform predisposed patients and relevant family members regarding potential cancer risks, with appropriate clinical interventions implemented if required.

Genetic Variants as Sudden-Death Risk Markers in Inherited Arrhythmogenic Syndromes: Personalized Genetic Interpretation

Inherited arrhythmogenic syndromes are the primary cause of unexpected lethal cardiac episodes in young people. It is possible that the first sign of the condition may be sudden death. Inherited arrhythmogenic syndromes are caused by genetic defects that may be analyzed using different technical approaches. A genetic alteration may be used as a marker of risk for families who carry the genetic alterations. Therefore, the early identification of the responsible genetic defect may help the adoption of preventive therapeutic measures focused on reducing the risk of lethal arrhythmias. Here, we describe the use of massive sequencing technologies and the interpretation of genetic analyses in inherited arrhythmogenic syndromes.

Neonatal respiratory failure due to novel compound heterozygous mutations in the ABCA3 lipid transporter

The ATP-binding cassette transporter member A3 (ABCA3) is a lipid transporter with a critical function in pulmonary surfactant biogenesis. Biallelic loss-of-function mutations in ABCA3 result in severe surfactant deficiency leading to neonatal respiratory failure with death in the first year of life. Herein, we describe a newborn with severe respiratory distress at birth progressing to respiratory failure requiring transplant. This patient was found to have a maternally inherited frameshift loss-of-function ABCA3 mutation and a paternally inherited synonymous variant in ABCA3 predicted to create a cryptic splice site. Additional studies showed reduced ABCA3 expression in hyperplastic alveolar epithelial type II cells and lamellar body alterations characteristic of ABCA3 deficiency, leading to a diagnosis of autosomal recessive ABCA3-related pulmonary surfactant dysfunction. This case highlights the need for an integrated, comprehensive approach for the diagnosis of inherited diseases when in silico modeling is utilized in the interpretation of key novel genetic mutations.

Review of current status of molecular diagnosis and characterization of monogenic diabetes mellitus: a focus on next-generation sequencing

Introduction: Monogenic diabetes is a subset of diabetes characterized by the presence of single-gene mutations and includes neonatal diabetes mellitus and maturity-onset diabetes of the young. Due to the genetic etiology of monogenic diabetes, molecular genetic testing can be used for diagnosis and classification.Areas covered: In addition to first-generation molecular analyses, many large clinical laboratories are transitioning to multiplexed next-generation sequencing panels to simultaneously assess patients for several of the most common genetic mutations seen in monogenic diabetes. With expanded development and adoption of next-generation sequencing panels, particularly in reference to laboratory settings, diagnostic testing for monogenic diabetes has the potential to be more accessible to the patient population.Expert opinion: Although molecular diagnostic testing is becoming increasingly prevalent, it is crucial to identify patients most likely to benefit from molecular testing versus those whose disease can be diagnosed and characterized with more traditional, less costly laboratory analyses. The continuous evolution of clinical molecular testing will be echoed in the clinical laboratory analysis of monogenic diabetes and continue to improve the diagnostic capabilities for monogenic diabetes mellitus.

From cytogenetics to cytogenomics: whole-genome sequencing as a first-line test comprehensively captures the diverse spectrum of disease-causing genetic variation underlying intellectual disability

Background

Since different types of genetic variants, from single nucleotide variants (SNVs) to large chromosomal rearrangements, underlie intellectual disability, we evaluated the use of whole-genome sequencing (WGS) rather than chromosomal microarray analysis (CMA) as a first-line genetic diagnostic test.

Methods

We analyzed three cohorts with short-read WGS: (i) a retrospective cohort with validated copy number variants (CNVs) (cohort 1, n = 68), (ii) individuals referred for monogenic multi-gene panels (cohort 2, n = 156), and (iii) 100 prospective, consecutive cases referred to our center for CMA (cohort 3). Bioinformatic tools developed include FindSV, SVDB, Rhocall, Rhoviz, and vcf2cytosure.

Results

First, we validated our structural variant (SV)-calling pipeline on cohort 1, consisting of three trisomies and 79 deletions and duplications with a median size of 850 kb (min 500 bp, max 155 Mb). All variants were detected. Second, we utilized the same pipeline in cohort 2 and analyzed with monogenic WGS panels, increasing the diagnostic yield to 8%. Next, cohort 3 was analyzed by both CMA and WGS. The WGS data was processed for large (> 10 kb) SVs genome-wide and for exonic SVs and SNVs in a panel of 887 genes linked to intellectual disability as well as genes matched to patient-specific Human Phenotype Ontology (HPO) phenotypes. This yielded a total of 25 pathogenic variants (SNVs or SVs), of which 12 were detected by CMA as well. We also applied short tandem repeat (STR) expansion detection and discovered one pathologic expansion in ATXN7. Finally, a case of Prader-Willi syndrome with uniparental disomy (UPD) was validated in the WGS data.

Important positional information was obtained in all cohorts. Remarkably, 7% of the analyzed cases harbored complex structural variants, as exemplified by a ring chromosome and two duplications found to be an insertional translocation and part of a cryptic unbalanced translocation, respectively.

Conclusion

The overall diagnostic rate of 27% was more than doubled compared to clinical microarray (12%). Using WGS, we detected a wide range of SVs with high accuracy. Since the WGS data also allowed for analysis of SNVs, UPD, and STRs, it represents a powerful comprehensive genetic test in a clinical diagnostic laboratory setting.

Copy number of 8q24.3 drives HSF1 expression and patient outcome in cancer: an individual patient data meta-analysis

Background

The heat-shock transcription factor 1 (HSF1) has been linked to cell proliferation and survival in cancer and has been proposed as a biomarker for poor prognosis. Here, we assessed the role of HSF1 expression in relation to copy number alteration (CNA) and cancer prognosis.

Methods

Using 10,287 cancer genomes from The Cancer Genome Atlas and Cbioportal databases, we assessed the association of HSF1 expression with CNA and cancer prognosis. CNA of 8q24.3 was categorized as diploid (reference), deletion (fewer copies), gain (+ 1 copy) and amplification (≥ + 2 copies). Multivariate logistic regression modeling was used to assess 5-year survival among those with a first cancer diagnosis and complete follow-up data (N = 9568), categorized per anatomical location and histology, assessing interaction with tumor stage, and expressed as odds ratios and 95% confidence intervals.

Results

We found that only 54.1% of all tumors have a normal predicted 8q24.3 copy number and that 8q24.3 located genes including HSF1 are mainly overexpressed due to increased copies number of 8q24.3 in different cancers. The tumor of patients having respectively gain (+ 1 copy) and amplification (≥ + 2 copies) of 8q24.3 display a global increase of 5-year mortality (odds ratio = 1.98, 95% CI 1.22–3.21) and (OR = 2.19, 1.13–4.26) after full adjustment. For separate cancer types, tumor patients with 8q24.3 deletion showed a marked increase of 5-year mortality in uterine (OR = 4.84, [2.75–8.51]), colorectal (OR = 4.12, [1.15–14.82]), and ovarian (OR = 1.83, [1.39–2.41]) cancers; and decreased mortality in kidney cancer (OR = 0.41, [0.21–0.82]). Gain of 8q24.3 resulted in significant mortality changes in 5-year mortality for cancer of the uterus (OR = 3.67, [2.03–6.66]), lung (OR = 1.76, [1.24–2.51]), colorectal (OR = 1.75, [1.32–2.31]) cancers; and amplification for uterine (OR = 4.58, [1.43–14.65]), prostate (OR = 4.41 [3.41–5.71]), head and neck (OR = 2.68, [2.17–3.30]), and stomach (OR = 0.56, [0.36–0.87]) cancers.

Conclusions

Here, we show that CNAs of 8q24.3 genes, including HSF1, are tightly linked to 8q24.3 copy number in tumor patients and can affect patient outcome. Our results indicate that the integration of 8q24.3 CNA detection may be a useful predictor for cancer prognosis.