Clinical application of next-generation sequencing for Mendelian diseases

Diverse biophysical mechanisms in voltage-gated sodium channel Nav1.4 variants associated with myotonia

Mutations in SCN4A gene encoding Nav1.4 channel α-subunit, are known to cause neuromuscular disorders such as myotonia or paralysis. Here, we study the effect of two amino acid replacements, K1302Q and G1306E, in the DIII-IV loop of the channel, corresponding to mutations found in patients with myotonia. We combine clinical, electrophysiological, and molecular modeling data to provide a holistic picture of the molecular mechanisms operating in mutant channels and eventually leading to pathology. We analyze the existing clinical data for patients with the K1302Q substitution, which was reported for adults with or without myotonia phenotypes, and report two new unrelated patients with the G1306E substitution, who presented with severe neonatal episodic laryngospasm and childhood-onset myotonia. We provide a functional analysis of the mutant channels by expressing Nav1.4 α-subunit in Xenopus oocytes in combination with β1 subunit and recording sodium currents using two-electrode voltage clamp. The K1302Q variant exhibits abnormal voltage dependence of steady-state fast inactivation, being the likely cause of pathology. K1302Q does not lead to decelerated fast inactivation, unlike several other myotonic mutations such as G1306E. For both mutants, we observe increased window currents corresponding to a larger population of channels available for activation. To elaborate the structural rationale for our experimental data, we explore the contacts involving K/Q1302 and E1306 in the AlphaFold2 model of wild-type Nav1.4 and Monte Carlo-minimized models of mutant channels. Our data provide the missing evidence to support the classification of K1302Q variant as likely pathogenic and may be used by clinicians.

Genomic Landscape of Branchio-Oto-Renal Syndrome through Whole-Genome Sequencing: A Single Rare Disease Center Experience in South Korea

Branchio-oto-renal (BOR) and branchio-otic (BO) syndromes are characterized by anomalies affecting the ears, often accompanied by hearing loss, as well as abnormalities in the branchial arches and renal system. These syndromes exhibit a broad spectrum of phenotypes and a complex genomic landscape, with significant contributions from the EYA1 gene and the SIX gene family, including SIX1 and SIX5. Due to their diverse phenotypic presentations, which can overlap with other genetic syndromes, molecular genetic confirmation is essential. As sequencing technologies advance, whole-genome sequencing (WGS) is increasingly used in rare disease diagnostics. We explored the genomic landscape of 23 unrelated Korean families with typical or atypical BOR/BO syndrome using a stepwise approach: targeted panel sequencing and exome sequencing (Step 1), multiplex ligation-dependent probe amplification (MLPA) with copy number variation screening (Step 2), and WGS (Step 3). Integrating WGS into our diagnostic pipeline detected structure variations, including cryptic inversion and complex genomic rearrangement, eventually enhancing the diagnostic yield to 91%. Our findings expand the genomic architecture of BOR/BO syndrome and highlight the need for WGS to address the genetic diagnosis of clinically heterogeneous rare diseases.

Detection of PTCH1 Copy-Number Variants in Mosaic Basal Cell Nevus Syndrome

Basal cell nevus syndrome (BCNS) is an inherited disorder characterized mainly by the development of basal cell carcinomas (BCCs) at an early age. BCNS is caused by heterozygous small-nucleotide variants (SNVs) and copy-number variants (CNVs) in the Patched1 (PTCH1) gene. Genetic diagnosis may be complicated in mosaic BCNS patients, as accurate SNV and CNV analysis requires high-sensitivity methods due to possible low variant allele frequencies. We compared test outcomes for PTCH1 CNV detection using multiplex ligation-probe amplification (MLPA) and digital droplet PCR (ddPCR) with samples from a BCNS patient heterozygous for a PTCH1 CNV duplication and the patient's father, suspected to have a mosaic form of BCNS. ddPCR detected a significantly increased PTCH1 copy-number ratio in the index patient's blood, and the father's blood and tissues, indicating that the father was postzygotic mosaic and the index patient inherited the CNV from him. MLPA only detected the PTCH1 duplication in the index patient's blood and in hair and saliva from the mosaic father. Our data indicate that ddPCR more accurately detects CNVs, even in low-grade mosaic BCNS patients, which may be missed by MLPA. In general, quantitative ddPCR can be of added value in the genetic diagnosis of mosaic BCNS patients and in estimating the recurrence risk for offspring.

The Impact of Artificial Intelligence on Optimizing Diagnosis and Treatment Plans for Rare Genetic Disorders

Rare genetic disorders (RDs), characterized by their low prevalence and diagnostic complexities, present significant challenges to healthcare systems. This article explores the transformative impact of artificial intelligence (AI) and machine learning (ML) in addressing these challenges. It emphasizes the need for accurate and early diagnosis of RDs, often hindered by genetic and clinical heterogeneity. This article discusses how AI and ML are reshaping healthcare, providing examples of their effectiveness in disease diagnosis, prognosis, image analysis, and drug repurposing. It highlights AI's ability to efficiently analyze extensive datasets and expedite diagnosis, showcasing case studies like Face2Gene. Furthermore, the article explores how AI tailors treatment plans for RDs, leveraging ML and deep learning (DL) to create personalized therapeutic regimens. It emphasizes AI's role in drug discovery, including the identification of potential candidates for rare disease treatments. Challenges and limitations related to AI in healthcare, including ethical, legal, technical, and human aspects, are addressed. This article underscores the importance of data ethics, privacy, and algorithmic fairness, as well as the need for standardized evaluation techniques and transparency in AI research. It highlights second-generation AI systems that prioritize patient-centric care, efficient patient recruitment for clinical trials, and the significance of high-quality data. The integration of AI with telemedicine, the growth of health databases, and the potential for personalized therapeutic recommendations are identified as promising directions for the field. In summary, this article provides a comprehensive exploration of how AI and ML are revolutionizing the diagnosis and treatment of RDs, addressing challenges while considering ethical implications in this rapidly evolving healthcare landscape.

eyeVarP: A computational framework for the identification of pathogenic variants specific to eye disease

PURPOSE

Disease-specific pathogenic variant prediction tools that differentiate pathogenic variants from benign have been improved through disease specificity recently. However, they have not been evaluated on disease-specific pathogenic variants compared with other diseases, which would help to prioritize disease-specific variants from several genes or novel genes. Thus, we hypothesize that features of pathogenic variants alone would provide a better model.

METHODS

We developed an eye disease-specific variant prioritization tool (eyeVarP), which applied the random forest algorithm to the data set of pathogenic variants of eye diseases and other diseases. We also developed the VarP tool and generalized pipeline to filter missense and insertion-deletion variants and predict their pathogenicity from exome or genome sequencing data, thus we provide a complete computational procedure.

RESULTS

eyeVarP outperformed pan disease-specific tools in identifying eye disease-specific pathogenic variants under the top 10. VarP outperformed 12 pathogenicity prediction tools with an accuracy of 95% in correctly identifying the pathogenicity of missense and insertion-deletion variants. The complete pipeline would help to develop disease-specific tools for other genetic disorders.

CONCLUSION

eyeVarP performs better in identifying eye disease-specific pathogenic variants using pathogenic variant features and gene features. Implementing such complete computational procedure would significantly improve the clinical variant interpretation for specific diseases.

The Genetics of Intellectual Disability

Intellectual disability (ID) has a prevalence of ~2-3% in the general population, having a large societal impact. The underlying cause of ID is largely of genetic origin; however, identifying this genetic cause has in the past often led to long diagnostic Odysseys. Over the past decades, improvements in genetic diagnostic technologies and strategies have led to these causes being more and more detectable: from cytogenetic analysis in 1959, we moved in the first decade of the 21st century from genomic microarrays with a diagnostic yield of ~20% to next-generation sequencing platforms with a yield of up to 60%. In this review, we discuss these various developments, as well as their associated challenges and implications for the field of ID, which highlight the revolutionizing shift in clinical practice from a phenotype-first into genotype-first approach.

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.

Genetic data sharing and artificial intelligence in the era of personalized medicine based on a cross-sectional analysis of the Saudi human genome program

The success of the Saudi Human Genome Program (SHGP), one of the top ten genomic programs worldwide, is highly dependent on the Saudi population embracing the concept of participating in genetic testing. However, genetic data sharing and artificial intelligence (AI) in genomics are critical public issues in medical care and scientific research. The present study was aimed to examine the awareness, knowledge, and attitude of the Saudi society towards the SHGP, the sharing and privacy of genetic data resulting from the SHGP, and the role of AI in genetic data analysis and regulations. Results of a questionnaire survey with 804 respondents revealed moderate awareness and attitude towards the SHGP and minimal knowledge regarding its benefits and applications. Respondents demonstrated a low level of knowledge regarding the privacy of genetic data. A generally positive attitude was found towards the outcomes of the SHGP and genetic data sharing for medical and scientific research. The highest level of knowledge was detected regarding AI use in genetic data analysis and privacy regulation. We recommend that the SHGP’s regulators launch awareness campaigns and educational programs to increase and improve public awareness and knowledge regarding the SHGP’s benefits and applications. Furthermore, we propose a strategy for genetic data sharing which will facilitate genetic data sharing between institutions and advance Personalized Medicine in genetic diseases’ diagnosis and treatment.

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.

Psychosocial Effect of Newborn Genomic Sequencing on Families in the BabySeq Project: A Randomized Clinical Trial

IMPORTANCE

Newborn genomic sequencing (nGS) may provide health benefits throughout the life span, but there are concerns that it could also have an unfavorable (ie, negative) psychosocial effect on families.

OBJECTIVE

To assess the psychosocial effect of nGS on families from the BabySeq Project, a randomized clinical trial evaluating the effect of nGS on the clinical care of newborns from well-baby nurseries and intensive care units.

DESIGN, SETTING, AND PARTICIPANTS

In this randomized clinical trial conducted from May 14, 2015, to May 21, 2019, at well-baby nurseries and intensive care units at 3 Boston, Massachusetts, area hospitals, 519 parents of 325 infants completed surveys at enrollment, immediately after disclosure of nGS results, and 3 and 10 months after results disclosure. Statistical analysis was performed on a per-protocol basis from January 16, 2019, to December 1, 2019.

INTERVENTION

Newborns were randomized to receive either standard newborn screening and a family history report (control group) or the same plus an nGS report of childhood-onset conditions and highly actionable adult-onset conditions (nGS group).

MAIN OUTCOMES AND MEASURES

Mean responses were compared between groups and, within the nGS group, between parents of children who received a monogenic disease risk finding and those who did not in 3 domains of psychosocial impact: parent-child relationship (Mother-to-Infant Bonding Scale), parents' relationship (Kansas Marital Satisfaction Scale), and parents' psychological distress (Edinburgh Postnatal Depression Scale anxiety subscale).

RESULTS

A total of 519 parents (275 women [53.0%]; mean [SD] age, 35.1 [4.5] years) were included in this study. Although mean scores differed for some outcomes at singular time points, generalized estimating equations models did not show meaningful differences in parent-child relationship (between-group difference in adjusted mean [SE] Mother-to-Infant Bonding Scale scores: postdisclosure, 0.04 [0.15]; 3 months, -0.18 [0.18]; 10 months, -0.07 [0.20]; joint P = .57) or parents' psychological distress (between-group ratio of adjusted mean [SE] Edinburgh Postnatal Depression Scale anxiety subscale scores: postdisclosure, 1.04 [0.08]; 3 months, 1.07 [0.11]; joint P = .80) response patterns between study groups over time for any measures analyzed in these 2 domains. Response patterns on one parents' relationship measure differed between groups over time (between-group difference in adjusted mean [SE] Kansas Marital Satisfaction Scale scores: postdisclosure, -0.19 [0.07]; 3 months, -0.04 [0.07]; and 10 months, -0.01 [0.08]; joint P = .02), but the effect decreased over time and no difference was observed on the conflict measure responses over time. We found no evidence of persistent negative psychosocial effect in any domain.

CONCLUSIONS AND RELEVANCE

In this randomized clinical trial of nGS, there was no persistent negative psychosocial effect on families among those who received nGS nor among those who received a monogenic disease risk finding for their infant.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02422511.

The diagnostic protocol for hereditary spherocytosis-2021 update

Background

Hereditary spherocytosis (HS), a commonly encountered hereditary hemolytic disease, is mostly inherited in an autosomal dominant manner. The clinical manifestations in patients with HS show obvious heterogeneity. Moreover, the sensitivity or specificity of some HS diagnostic tests are not ideal and may easily result in misdiagnosis or missed diagnosis in some patients. The objective of this study was to propose a simple and practical diagnostic protocol, which can contribute to the diagnosis of HS and its differential diagnosis with different types of hemolytic anemia such as thalassemia (THAL), autoimmune hemolytic anemia (AIHA), and glucose‐6‐phosphate dehydrogenase (G6PD) deficiency, thus, to provide an alternative simple and reliable method for better clinical diagnosis of HS.

Methods

Through combing our research with existing experimental technologies and studies, we propose a simple and practical protocol for HS diagnosis, which will help clinicians to improve HS diagnosis.

Results

Compared with the existing HS diagnostic protocols, the HS diagnostic protocol we proposed is simpler. In this new protocol, some experimental tests with ideal diagnostic efficiency are added, such as mean reticulocyte volume (MRV), mean sphered cell volume (MSCV), mean corpuscular volume (MCV), in combination with the observation of clinical manifestations, family investigation, routine tests for hemolytic anemia, genetic testing, and other screening tests.

Conclusion

The HS diagnostic protocol we proposed could improve the clinical practice and efficiency of HS diagnosis.

Current status of use of high throughput nucleotide sequencing in rheumatology

OBJECTIVE

Here, we assess the usage of high throughput sequencing (HTS) in rheumatic research and the availability of public HTS data of rheumatic samples.

METHODS

We performed a semiautomated literature review on PubMed, consisting of an R-script and manual curation as well as a manual search on the Sequence Read Archive for public available HTS data.

RESULTS

Of the 699 identified articles, rheumatoid arthritis (n=182 publications, 26%), systemic lupus erythematous (n=161, 23%) and osteoarthritis (n=152, 22%) are among the rheumatic diseases with the most reported use of HTS assays. The most represented assay is RNA-Seq (n=457, 65%) for the identification of biomarkers in blood or synovial tissue. We also find, that the quality of accompanying clinical characterisation of the sequenced patients differs dramatically and we propose a minimal set of clinical data necessary to accompany rheumatological-relevant HTS data.

CONCLUSION

HTS allows the analysis of a broad spectrum of molecular features in many samples at the same time. It offers enormous potential in novel personalised diagnosis and treatment strategies for patients with rheumatic diseases. Being established in cancer research and in the field of Mendelian diseases, rheumatic diseases are about to become the third disease domain for HTS, especially the RNA-Seq assay. However, we need to start a discussion about reporting of clinical characterisation accompany rheumatological-relevant HTS data to make clinical meaningful use of this data.

Congenital limb deficiency: Genetic investigation of 44 individuals presenting mainly longitudinal defects in isolated or syndromic forms

Congenital limb deficiency (CLD), one of the most common congenital anomalies, is characterized by hypoplasia/aplasia of one or more limb bones and can be isolated or syndromic. The etiology in CLD is heterogeneous, including environmental and genetic factors. A fraction remains with no etiological factor identified. We report the study of 44 Brazilian individuals presenting isolated or syndromic CLD, mainly with longitudinal defects. Genetic investigation included particularly next-generation sequencing (NGS) and/or chromosomal microarray. The overall diagnostic yield was 45.7%, ranging from 60.9% in the syndromic to 16.7% in the non-syndromic group. In TAR syndrome, a common variant in 3´UTR of RBM8A, in trans with 1q21.1 microdeletion, was detected, corroborating the importance of this recently reported variant in individuals of African ancestry. NGS established a diagnosis in three individuals in syndromes recently reported or still under delineation (an acrofacial dysostosis, Coats plus and Verheij syndromes), suggesting a broader phenotypic spectrum in these disorders. Although a low rate of molecular detection in non-syndromic forms was observed, it is still possible that variants in non-coding regions and small CNVs, not detected by the techniques applied in this study, could play a role in the etiology of CLD.

Clinical application of whole-exome sequencing: A retrospective, single-center study

The aim of the present study was to assess the practical diagnostic value of whole-exome sequencing (WES) in patients with different phenotypes and to explore possible strategies to increase the capability of WES in identifying disease-causing genes. A total of 1,360 patients (aged from 1 day to 42 years old) with manifestations of genetic diseases were genotyped using WES and statistical analysis was performed on the results obtained. Within this cohort, the overall positive rate of identification of a disease-causing gene alteration was 44.41%. The positive identification rate where trio-samples were used (from the proband and both parents) was higher than that where a single proband sample was used (50.00 vs. 43.71%), and 604 positive cases with 150 genetic syndromes, 510 genes and 718 mutations were detected. Missense mutations were the most common variations (n=335, 45.27%) and visual or auditory abnormalities (58.51%) had the highest rate of association with a genetic abnormality. The positive detection rate of WES was elevated with the increase in the number of clinical symptoms from 1 to 8. The present study indicated that WES may be used as a valuable tool in the clinic and the positive rate depends more on the professional experience of clinicians rather than on the analytical capabilities of the data analyst. At the same time, particular attention must be paid to certain possible factors (such as the age of the patients as well as possible exon deletions), which may affect the diagnostic rate while applying this process.

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.

Next-generation sequencing technologies: An overview

Since the days of Sanger sequencing, next-generation sequencing technologies have significantly evolved to provide increased data output, efficiencies, and applications. These next generations of technologies can be categorized based on read length. This review provides an overview of these technologies as two paradigms: short-read, or "second-generation," technologies, and long-read, or "third-generation," technologies. Herein, short-read sequencing approaches are represented by the most prevalent technologies, Illumina and Ion Torrent, and long-read sequencing approaches are represented by Pacific Biosciences and Oxford Nanopore technologies. All technologies are reviewed along with reported advantages and disadvantages. Until recently, short-read sequencing was thought to provide high accuracy limited by read-length, while long-read technologies afforded much longer read-lengths at the expense of accuracy. Emerging developments for third-generation technologies hold promise for the next wave of sequencing evolution, with the co-existence of longer read lengths and high accuracy.

Genetic factors contributing to skeletal class III malocclusion: a systematic review and meta-analysis

OBJECTIVES

The present systematic review aims to report and critically assess the findings of the available scientific evidence from genetic association studies examining the genetic variants underlying skeletal class III malocclusion and its sub-phenotypes.

MATERIAL AND METHODS

A pre-piloted protocol was registered and followed. The PubMed, Scopus, WOS, Cochrane Library, Gray Open literature, and CADTH databases were explored for genetic association studies following PICOS-based selection criteria. The research was reported in accordance with PRISMA statement and HuGE guidelines. The Q-genie tool was applied to assess the quality of genetic studies. Meta-analysis of genetic association studies was done by means of Meta-Genyo tool.

RESULTS

A total of 8258 articles were retrieved, of which 22 were selected for in-depth analysis. Most of the studies did not differentiate between sub-phenotypes, and the cohorts were heterogeneous regarding ethnicity. Four to five principal components of class III malocclusion explained the phenotypic variation, and gene variants at MYO1H(rs10850110), BMP3(rs1390319), GHR (rs2973015,rs6184, rs2973015), FGF7(rs372127537), FGF10(rs593307), and SNAI3(rs4287555) (p < .05) explained most of the variation across the studies, associated to vertical, horizontal, or combined skeletal discrepancies. Meta-analysis results identified a statistically significant association between risk of class III malocclusion of A allele of the FBN3 rs7351083 [OR 2.13; 95% CI 1.1-4.1; p 0.02; recessive model].

CONCLUSION

Skeletal class III is a polygenic trait substantially modulated by ethnicity. A multicentric approach should be considered in future studies to increase sample sizes, applying multivariate analysis such as PCA and cluster analysis to characterize existing sub-phenotypes warranting a deeper analysis of genetic variants contributing to skeletal class III craniofacial disharmony.

CLINICAL RELEVANCE

Grasping the underlying mechanisms of this pathology is critical for a fuller understanding of its etiology, allowing generation of preventive strategies, new individualized therapeutic approaches and more accurate treatment planification strategies.

A Multi-Strategy Sequencing Workflow in Inherited Retinal Dystrophies: Routine Diagnosis, Addressing Unsolved Cases and Candidate Genes Identification

The management of unsolved inherited retinal dystrophies (IRD) cases is challenging since no standard pipelines have been established. This study aimed to define a diagnostic algorithm useful for the diagnostic routine and to address unsolved cases. Here, we applied a Next-Generation Sequencing-based workflow, including a first step of panel sequencing (PS) followed by clinical-exome sequencing (CES) and whole-exome sequencing (WES), in 46 IRD patients belonging to 42 families. Twenty-six likely causal variants in retinal genes were found by PS and CES. CES and WES allowed proposing two novel candidate loci (WDFY3 and a X-linked region including CITED1), both abundantly expressed in human retina according to RT-PCR and immunohistochemistry. After comparison studies, PS showed the best quality and cost values, CES and WES involved similar analytical efforts and WES presented the highest diagnostic yield. These results reinforce the relevance of panels as a first step in the diagnostic routine and suggest WES as the next strategy for unsolved cases, reserving CES for the simultaneous study of multiple conditions. Standardizing this algorithm would enhance the efficiency and equity of clinical genetics practice. Furthermore, the identified candidate genes could contribute to increase the diagnostic yield and expand the mutational spectrum in these disorders.

Next Generation Sequencing and Bioinformatics Analysis of Family Genetic Inheritance

Mendelian and complex genetic trait diseases continue to burden and affect society both socially and economically. The lack of effective tests has hampered diagnosis thus, the affected lack proper prognosis. Mendelian diseases are caused by genetic mutations in a singular gene while complex trait diseases are caused by the accumulation of mutations in either linked or unlinked genomic regions. Significant advances have been made in identifying novel diseases associated mutations especially with the introduction of next generation and third generation sequencing. Regardless, some diseases are still without diagnosis as most tests rely on SNP genotyping panels developed from population based genetic analyses. Analysis of family genetic inheritance using whole genomes, whole exomes or a panel of genes has been shown to be effective in identifying disease-causing mutations. In this review, we discuss next generation and third generation sequencing platforms, bioinformatic tools and genetic resources commonly used to analyze family based genomic data with a focus on identifying inherited or novel disease-causing mutations. Additionally, we also highlight the analytical, ethical and regulatory challenges associated with analyzing personal genomes which constitute the data used for family genetic inheritance.

Contemporary Insights Into the Genetics of Hypertrophic Cardiomyopathy: Toward a New Era in Clinical Testing?

Genetic testing for hypertrophic cardiomyopathy (HCM) is an established clinical technique, supported by 30 years of research into its genetic etiology. Although pathogenic variants are often detected in patients and used to identify at-risk relatives, the effectiveness of genetic testing has been hampered by ambiguous genetic associations (yielding uncertain and potentially false-positive results), difficulties in classifying variants, and uncertainty about genotype-negative patients. Recent case-control studies on rare variation, improved data sharing, and meta-analysis of case cohorts contributed to new insights into the genetic basis of HCM. In particular, although research into new genes and mechanisms remains essential, reassessment of Mendelian genetic associations in HCM argues that current clinical genetic testing should be limited to a small number of validated disease genes that yield informative and interpretable results. Accurate and consistent variant interpretation has benefited from new standardized variant interpretation guidelines and innovative approaches to improve classification. Most cases lacking a pathogenic variant are now believed to indicate non-Mendelian HCM, with more benign prognosis and minimal risk to relatives. Here, we discuss recent advances in the genetics of HCM and their application to clinical genetic testing together with practical issues regarding implementation. Although this review focuses on HCM, many of the issues discussed are also relevant to other inherited cardiac diseases.

Exploring the Molecular Aetiology of Preeclampsia by Massive Parallel Sequencing of DNA

PURPOSE OF REVIEW

This manuscript aims to review (for the first time) studies describing NGS sequencing of preeclampsia (PE) women's DNA.

RECENT FINDINGS

Describing markers for the early detection of PE is an essential task because, although associated molecular dysfunction begins early on during pregnancy, the disease's clinical signs usually appear late in pregnancy. Although several biochemical biomarkers have been proposed, their use in clinical environments is still limited, thereby encouraging research into PE's genetic origin. Hundreds of genes involved in numerous implantation- and placentation-related biological processes may be coherent candidates for PE aetiology. Next-generation sequencing (NGS) offers new technical possibilities for PE studying, as it enables large genomic regions to be analysed at affordable cost. This technique has facilitated the description of genes contributing to the molecular origin of a significant amount of monogenic and complex diseases. Regarding PE, NGS of DNA has been used in familial and isolated cases, thereby enabling new genes potentially related to the phenotype to be proposed. For a better understanding of NGS, technical aspects, applications and limitations are presented initially. Thereafter, NGS studies of DNA in familial and non-familial cases are described, including pitfalls and positive findings. The information given here should enable scientists and clinicians to analyse and design new studies permitting the identification of novel clinically useful molecular PE markers.

Cell-cycle dependence of transcriptome gene modules: comparison of regression lines

The transcriptome consists of various gene modules that can be mutually dependent, and ignoring these dependencies may lead to misinterpretation. The most important problem is module dependence on cell-cycle activity. Using meta-analysis of over 30 000 single-cell transcriptomes, we show gene module dependencies on cell-cycle signature, which can be consistently observed in various normal and cancer cells. Transcript levels of receptors, plasma membrane, and differentiation-related genes are negatively regressed on cell-cycle signature. Pluripotency, stress response, DNA repair, chromatin remodeling, proteasomal protein degradation, protein network connectivity, and unicellular evolutionary origin are regressed positively. These effects cannot be explained by partial overlap of corresponding gene sets because they remain if the overlapped genes were removed. We propose a visual analysis of gene module-specific regression lines as complement to an uncurated enrichment analysis. The different lines for a same gene module indicate different cell conditions. The approach is tested on several problems (polyploidy, pluripotency, cancer, phylostratigraphy). Intriguingly, we found variation in cell-cycle activity, which is independent of cell progression through the cycle. The upregulation of G2/M checkpoint genes with downregulation of G2/M transition and cytokinesis is revealed in polyploid cells. A temporal increase in cell-cycle activity at transition from pluripotent to more differentiated state is found in human embryonic stem cells. The upregulation of unicellular interactome cluster in human cancers is shown in single cells with control for cell-cycle activity. The greater scatter around regression line in cancer cells suggests greater heterogeneity caused by deviation from a line of normal cells.

Unveiling the genetic etiology of primary ciliary dyskinesia: When standard genetic approach is not enough

PURPOSE

Primary ciliary dyskinesia (PCD) is a ciliopathy caused by dysfunction of motile cilia. As there is still no standard PCD diagnostics, the final diagnosis requires a combination of several tests. The genetic screening is a hallmark for the final diagnosis and requires high-throughput techniques, such as whole-exome sequencing (WES). Nevertheless, WES has limitations that may prevent a definitive genetic diagnosis. Here we present a case that demonstrates how the PCD genetic diagnosis may not be trivial.

MATERIALS/METHODS

A child with PCD and situs inversus totalis (designated as Kartagener syndrome (KS)) was subjected to clinical assessments, ultrastructural analysis of motile cilia, extensive genetic evaluation by WES and chromosomal array analysis, bioinformatic analysis, gene expression analysis and immunofluorescence to identify the genetic etiology. His parents and sister, as well as healthy controls were also evaluated.

RESULTS

Here we show that a disease-causing variant in the USP11 gene and copy number variations in CRHR1 and KRT34 genes may be involved in the patient PCD phenotype. None of these genes were previously reported in PCD patients and here we firstly show its presence and immunolocalization in respiratory cells.

CONCLUSIONS

This work highlights how the genetic diagnosis can turn to be rather complex and that combining several approaches may be needed. Overall, our results contribute to increase the understanding of the genetic factors involved in the pathophysiology of PCD/KS, which is of paramount importance to assist the current diagnosis and future development of newer therapies.

Setup and Validation of a Targeted Next-Generation Sequencing Approach for the Diagnosis of Lysosomal Storage Disorders

Lysosomal storage disorders (LSDs) are monogenic diseases, due to accumulation of specific undegraded substrates into lysosomes. LSD diagnosis could take several years because of both poor knowledge of these diseases and shared clinical features. The diagnostic approach includes clinical evaluations, biochemical tests, and genetic analysis of the suspected gene. In this study, we evaluated an LSD targeted sequencing panel as a tool capable to potentially reverse this classic diagnostic route. The panel includes 50 LSD genes and 230 intronic sequences conserved among 33 placental mammals. For the validation phase, 56 positive controls, 13 biochemically diagnosed patients, and nine undiagnosed patients were analyzed. Disease-causing variants were identified in 66% of the positive control alleles and in 62% of the biochemically diagnosed patients. Three undiagnosed patients were diagnosed. Eight patients undiagnosed by the panel were analyzed by whole exome sequencing: for two of them, the disease-causing variants were identified. Five patients, undiagnosed by both panel and exome analyses, were investigated through array comparative genomic hybridization: one of them was diagnosed. Conserved intronic fragment analysis, performed in cases unresolved by the first-level analysis, evidenced no candidate intronic variants. Targeted sequencing has low sequencing costs and short sequencing time. However, a coverage >60× to 80× must be ensured and/or Sanger validation should be performed. Moreover, it must be supported by a thorough clinical phenotyping.

Genome Editing for the Understanding and Treatment of Inherited Cardiomyopathies

Cardiomyopathies are diseases of heart muscle, a significant percentage of which are genetic in origin. Cardiomyopathies can be classified as dilated, hypertrophic, restrictive, arrhythmogenic right ventricular or left ventricular non-compaction, although mixed morphologies are possible. A subset of neuromuscular disorders, notably Duchenne and Becker muscular dystrophies, are also characterized by cardiomyopathy aside from skeletal myopathy. The global burden of cardiomyopathies is certainly high, necessitating further research and novel therapies. Genome editing tools, which include zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) and clustered regularly interspaced short palindromic repeats (CRISPR) systems have emerged as increasingly important technologies in studying this group of cardiovascular disorders. In this review, we discuss the applications of genome editing in the understanding and treatment of cardiomyopathy. We also describe recent advances in genome editing that may help improve these applications, and some future prospects for genome editing in cardiomyopathy treatment.

A fast, reliable and easy method to detect within-species DNA contamination

BACKGROUND AND AIM

Next generation sequencing (ngs) is becoming the standard for clinical diagnosis. Different steps of NGS, such as DNA extraction, fragmentation, library preparation and amplification, require handling of samples, making the process susceptible to contamination. In diagnostic environments, sample contamination with DNA from the same species can lead to errors in diagnosis. Here we propose a simple method to detect within-sample contamination based on analysis of the heterozygous single nucleotide polymorphisms allele ratio (AR).

METHODS

A dataset of 38000 heterozygous snps was used to estimate the ar distribution. The parameters of the reference distribution were then used to estimate the contamination probability of a sample. Validation was performed using 12 samples contaminated to different levels.

RESULTS

Results show that the method easily detects contamination of 20% or more. The method has a limit of detection of about 10%, threshold below which the number of false positives increases significantly.

CONCLUSIONS

The method can be applied to any type of ngs analysis and is useful for quality control. Being fast and easy to implement makes it ideal for inclusion in NGS pipelines to improve quality control of data and make results more robust.

Practical guide to genetic screening for inherited eye diseases

Genetic eye diseases affect around one in 1000 people worldwide for which the molecular aetiology remains unknown in the majority. The identification of disease-causing gene variant(s) allows a better understanding of the disorder and its inheritance. There is now an approved retinal gene therapy for autosomal recessive RPE65-retinopathy, and numerous ocular gene/mutation-targeted clinical trials underway, highlighting the importance of establishing a genetic diagnosis so patients can fully access the latest research developments and treatment options. In this review, we will provide a practical guide to managing patients with these conditions including an overview of inheritance patterns, required pre- and post-test genetic counselling, different types of cytogenetic and genetic testing available, with a focus on next generation sequencing using targeted gene panels, whole exome and genome sequencing. We will expand on the pros and cons of each modality, variant interpretation and options for family planning for the patient and their family. With the advent of genomic medicine, genetic screening will soon become mainstream within all ophthalmology subspecialties for prevention of disease and provision of precision therapeutics.

Novel bioinformatics quality control metric for next-generation sequencing experiments in the clinical context

As the use of next-generation sequencing (NGS) for the Mendelian diseases diagnosis is expanding, the performance of this method has to be improved in order to achieve higher quality. Typically, performance measures are considered to be designed in the context of each application and, therefore, account for a spectrum of clinically relevant variants. We present EphaGen, a new computational methodology for bioinformatics quality control (QC). Given a single NGS dataset in BAM format and a pre-compiled VCF-file of targeted clinically relevant variants it associates this dataset with a single arbiter parameter. Intrinsically, EphaGen estimates the probability to miss any variant from the defined spectrum within a particular NGS dataset. Such performance measure virtually resembles the diagnostic sensitivity of given NGS dataset. Here we present case studies of the use of EphaGen in context of BRCA1/2 and CFTR sequencing in a series of 14 runs across 43 blood samples and 504 publically available NGS datasets. EphaGen is superior to conventional bioinformatics metrics such as coverage depth and coverage uniformity. We recommend using this software as a QC step in NGS studies in the clinical context. Availability: https://github.com/m4merg/EphaGen or https://hub.docker.com/r/m4merg/ephagen.

Personalised analytics for rare disease diagnostics

Whole genome and exome sequencing is a standard tool for the diagnosis of patients suffering from rare and other genetic disorders. The interpretation of the tens of thousands of variants returned from such tests remains a major challenge. Here we focus on the problem of prioritising variants with respect to the observed disease phenotype. We hypothesise that linking patterns of gene expression across multiple tissues to the phenotypes will aid in discovering disease causing variants. To test this, we construct classifiers that learn associations between tissue-specific gene expression and disease phenotypes. We find that using Genotype-Tissue Expression project (GTEx) expression data in conjunction with disease agnostic variant prioritisation methods (CADD or MetaSVM) results in consistent improvements in classification accuracy. Our method represents a previously overlooked avenue of utilising existing expression data for clinical diagnostics, and also opens the door to use of other functional genomic data sets in the same manner.

Recent trends in molecular diagnostics of yeast infections: from PCR to NGS

The incidence of opportunistic yeast infections in humans has been increasing over recent years. These infections are difficult to treat and diagnose, in part due to the large number and broad diversity of species that can underlie the infection. In addition, resistance to one or several antifungal drugs in infecting strains is increasingly being reported, severely limiting therapeutic options and showcasing the need for rapid detection of the infecting agent and its drug susceptibility profile. Current methods for species and resistance identification lack satisfactory sensitivity and specificity, and often require prior culturing of the infecting agent, which delays diagnosis. Recently developed high-throughput technologies such as next generation sequencing or proteomics are opening completely new avenues for more sensitive, accurate and fast diagnosis of yeast pathogens. These approaches are the focus of intensive research, but translation into the clinics requires overcoming important challenges. In this review, we provide an overview of existing and recently emerged approaches that can be used in the identification of yeast pathogens and their drug resistance profiles. Throughout the text we highlight the advantages and disadvantages of each methodology and discuss the most promising developments in their path from bench to bedside.

GenePy - a score for estimating gene pathogenicity in individuals using next-generation sequencing data

BACKGROUND

Next-generation sequencing is revolutionising diagnosis and treatment of rare diseases, however its application to understanding common disease aetiology is limited. Rare disease applications binarily attribute genetic change(s) at a single locus to a specific phenotype. In common diseases, where multiple genetic variants within and across genes contribute to disease, binary modelling cannot capture the burden of pathogenicity harboured by an individual across a given gene/pathway. We present GenePy, a novel gene-level scoring system for integration and analysis of next-generation sequencing data on a per-individual basis that transforms NGS data interpretation from variant-level to gene-level. This simple and flexible scoring system is intuitive and amenable to integration for machine learning, network and topological approaches, facilitating the investigation of complex phenotypes.

RESULTS

Whole-exome sequencing data from 508 individuals were used to generate GenePy scores. For each variant a score is calculated incorporating: i) population allele frequency estimates; ii) individual zygosity, determined through standard variant calling pipelines and; iii) any user defined deleteriousness metric to inform on functional impact. GenePy then combines scores generated for all variants observed into a single gene score for each individual. We generated a matrix of ~ 14,000 GenePy scores for all individuals for each of sixteen popular deleteriousness metrics. All per-gene scores are corrected for gene length. The majority of genes generate GenePy scores < 0.01 although individuals harbouring multiple rare highly deleterious mutations can accumulate extremely high GenePy scores. In the absence of a comparator metric, we examine GenePy performance in discriminating genes known to be associated with three common, complex diseases. A Mann-Whitney U test conducted on GenePy scores for this positive control gene in cases versus controls demonstrates markedly more significant results (p = 1.37 × 10- 4) compared to the most commonly applied association tool that combines common and rare variation (p = 0.003).

CONCLUSIONS

Per-gene per-individual GenePy scores are intuitive when assessing genetic variation in individual patients or comparing scores between groups. GenePy outperforms the currently accepted best practice tools for combining common and rare variation. GenePy scores are suitable for downstream data integration with transcriptomic and proteomic data that also report at the gene level.

Comparative Analysis for the Performance of Variant Calling Pipelines on Detecting the de novo Mutations in Humans

Despite of the low occurrence rate in the entire genomes, de novo mutation is proved to be deleterious and will lead to severe genetic diseases via impacting on the gene function. Considering the fact that the traditional family based linkage approaches and the genome-wide association studies are unsuitable for identifying the de novo mutations, in recent years, several pipelines have been proposed to detect them based on the whole-genome or whole-exome sequencing data and were used for calling them in the rare diseases. However, how the performance of these variant calling pipelines on detecting the de novo mutations is still unexplored. For the purpose of facilitating the appropriate choice of the pipelines and reducing the false positive rate, in this study, we thoroughly evaluated the performance of the commonly used trio calling methods on the detection of the de novo single-nucleotide variants (DNSNVs) by conducting a comparative analysis for the calling results. Our results exhibited that different pipelines have a specific tendency to detect the DNSNVs in the genomic regions with different GC contents. Additionally, to refine the calling results for a single pipeline, our proposed filter achieved satisfied results, indicating that the read coverage at the mutation positions can be used as an effective index to identify the high-confidence DNSNVs. Our findings should be good support for the committees to choose an appropriate way to explore the de novo mutations for the rare diseases.

PhenoPro: a novel toolkit for assisting in the diagnosis of Mendelian disease

Motivation

Whole-exome sequencing (WES) is now being used in clinical practice for the diagnosis of the causal genes of Mendelian diseases. In order to make the diagnosis, however, the clinical phenotypes [e.g. Human Phenotype Ontology (HPO) terms] of a patient are needed for prioritizing the variants called from the WES data of the patient. Computational tools are therefore needed to standardize and accelerate this process.

Results

Here, we introduce a tool named PhenoPro for prioritizing the causal gene of Mendelian disease given both the HPO terms assigned to and the variants called from the WES data of a patient. PhenoPro has been benchmarked using both simulated patients and 287 real diagnosed patients of Chinese ancestry, and shows significant improvements over five previous tools. Moreover, the addition of an internal variant data of Chinese ancestry and the variant data from the patients’ parents can further improve PhenoPro’s performance. To make PhenoPro a fully automated tool, we also include a natural language processing component for automated HPO term assignment from clinical reports, and demonstrate that the natural language processing is as effective as manual HPO assignment using real clinical reports. In conclusion, PhenoPro can be used as a pre-screening tool to assist in the diagnosis of Mendelian disease genes.

Availability and implementation

The web server of PhenoPro is freely available at http://app.tianlab.cn.

Supplementary information

Supplementary data are available at Bioinformatics online.

Application of next-generation sequencing technology to precision medicine in cancer: joint consensus of the Tumor Biomarker Committee of the Chinese Society of Clinical Oncology

Next-generation sequencing (NGS) technology is capable of sequencing millions or billions of DNA molecules simultaneously. Therefore, it represents a promising tool for the analysis of molecular targets for the initial diagnosis of disease, monitoring of disease progression, and identifying the mechanism of drug resistance. On behalf of the Tumor Biomarker Committee of the Chinese Society of Clinical Oncology (CSCO) and the China Actionable Genome Consortium (CAGC), the present expert group hereby proposes advisory guidelines on clinical applications of NGS technology for the analysis of cancer driver genes for precision cancer therapy. This group comprises an assembly of laboratory cancer geneticists, clinical oncologists, bioinformaticians, pathologists, and other professionals. After multiple rounds of discussions and revisions, the expert group has reached a preliminary consensus on the need of NGS in clinical diagnosis, its regulation, and compliance standards in clinical sample collection. Moreover, it has prepared NGS criteria, the sequencing standard operation procedure (SOP), data analysis, report, and NGS platform certification and validation.

An exonic splicing enhancer mutation in DUOX2 causes aberrant alternative splicing and severe congenital hypothyroidism in Bama pigs

Pigs share many similarities with humans in terms of anatomy, physiology and genetics, and have long been recognized as important experimental animals in biomedical research. Using an N-ethyl-N-nitrosourea (ENU) mutagenesis screen, we previously identified a large number of pig mutants, which could be further established as human disease models. However, the identification of causative mutations in large animals with great heterogeneity remains a challenging endeavor. Here, we select one pig mutant, showing congenital nude skin and thyroid deficiency in a recessive inheritance pattern. We were able to efficiently map the causative mutation using family-based genome-wide association studies combined with whole-exome sequencing and a small sample size. A loss-of-function variant (c.1226 A>G) that resulted in a highly conserved amino acid substitution (D409G) was identified in the DUOX2 gene. This mutation, located within an exonic splicing enhancer motif, caused aberrant splicing of DUOX2 transcripts and resulted in lower H₂O₂ production, which might cause a severe defect in thyroid hormone production. Our findings suggest that exome sequencing is an efficient way to map causative mutations and that DUOX2^D409G/D409G mutant pigs could be a potential large animal model for human congenital hypothyroidism.

Summary: Here, we show that an exonic splicing enhancer variant in DUOX2 (c.1226 A>G) causes aberrant splicing of DUOX2 transcripts, resulting in lower H₂O₂ production, to cause severe congenital hypothyroidism in Bama pigs.

Transcriptome Sequencing Approaches to Elucidate Host-Microbe Interactions in Opportunistic Human Fungal Pathogens

Infections caused by opportunistic human fungal pathogens are a source of increasing medical concern, due to their growing incidence, the emergence of novel pathogenic species, and the lack of effective diagnostics tools. Fungal pathogens are phylogenetically diverse, and their virulence mechanisms can differ widely across species. Despite extensive efforts, the molecular bases of virulence in pathogenic fungi and their interactions with the human host remain poorly understood for most species. In this context, next-generation sequencing approaches hold the promise of helping to close this knowledge gap. In particular, high-throughput transcriptome sequencing (RNA-Seq) enables monitoring the transcriptional profile of both host and microbes to elucidate their interactions and discover molecular mechanisms of virulence and host defense. Here, we provide an overview of transcriptome sequencing techniques and approaches, and survey their application in studying the interplay between humans and fungal pathogens. Finally, we discuss novel RNA-Seq approaches in studying host-pathogen interactions and their potential role in advancing the clinical diagnostics of fungal infections.

Comparing complex variants in family trios

Motivation

Several tools exist to count Mendelian violations in family trios by comparing variants at the same genomic positions. This naive variant comparison, however, fails to assess regions where multiple variants need to be examined together, resulting in reduced accuracy of existing Mendelian violation checking tools.

Results

We introduce VBT, a trio concordance analysis tool, which identifies Mendelian violations by approximately solving the 3-way variant matching problem to resolve variant representation differences in family trios. We show that VBT outperforms previous trio comparison methods by accuracy.

Availability and implementation

VBT is implemented in C++ and source code is available under GNU GPLv3 license at the following URL: https://github.com/sbg/VBT-TrioAnalysis.git.

Supplementary information

Supplementary data are available at Bioinformatics online.

BRCA-analyzer: Automatic workflow for processing NGS reads of BRCA1 and BRCA2 genes

The use of targeted next-generation sequencing (NGS) provides great new opportunities for molecular and medical genetics. However, in order to take advantage of these opportunities, we need to have reliable tools for extracting the necessary information from the huge amount of data generated by NGS. Here we present our automatic multithreaded workflow for processing NGS data of BRCA1 and BRCA2 genes obtained with NGS technology named BRCA-analyzer. Optimizing it on the sequencing data of 899 samples from 693 patients, we were able to find the most reliable tools and adjust their parameters in such a way that all pathogenic variants found were confirmed by Sanger's sequencing. For 82 and 24 DNA samples from blood and formalin-fixed paraffin-embedded blocks, NGS libraries were prepared with GeneRead BRCA panel v2 (Qiagen). The reads obtained were processed with BRCA-analyzer and Qiagen GeneRead Data analysis workflow. In total 27 pathogenic variants were found and confirmed by Sanger's sequencing, with all of them determined with BRCA-analyzer. Qiagen GeneRead Data analysis discarded 5 true pathogenic variants due to their location in homopolymeric sequence stretches. For other 793 samples, libraries were prepared by the in-house method, and NGS data were analyzed by BRCA-analyzer in comparison to another free automatic amplicon NGS workflow Canary. From total 137 pathogenic variations, BRCA-analyzer found 135 and Canary 123. Mutations were missed by BRCA-analyzer due to the trimming primer sequences from reads before mapping to be fixed in the next version. On the freely available NGS data, we showed that BRCA-analyzer could also be used for hybrid capture gene panels, although it needs more extensive testing on such library preparation methods. Thus, BRCA-analyzer is an automatic workflow for processing NGS data of BRCA1/2 genes with variant filters adapted to amplicon-based targeted NGS data. BRCA-analyzer can be used to identify germline as well as somatic mutations. BRCA-analyzer is freely available at https://github.com/aakechin/BRCA-analyzer.

Next Generation Sequencing: From Research Area to Clinical Practice

Translating the power of high-throughput sequencing technologies from research area into clinical medicine is one of the major goal for several researchers and health-care providers. One of the important advantages of these technologies is that they can be successfully used in a numerous range of clinical applications. The efficiency of sequencing, that can now be achieved, is leading impressive progress in the diagnostics of common and rare genetic disorders, inherited forms of cancer, prenatal testing or infectious diseases, to cite some examples. Despite several challenges and limitations still remain to overcome, the high-throughput sequencing technologies are leading to real and unprecedented benefits for the medical care of patients.

Expanded carrier screening: A current perspective

Prenatal carrier screening has expanded to include a large number of genes offered to all couples considering pregnancy or with an ongoing pregnancy. Expanded carrier screening refers to identification of carriers of single-gene disorders outside of traditional screening guidelines. Expanded carrier screening panels include numerous autosomal recessive and X-linked genetic conditions, including those with a very low carrier frequency, as well as those with mild or incompletely penetrant phenotype. Therefore, the clinical utility of these panels is still subject of debate. Priority should be given to carrier screening panels that include a comprehensive set of severe childhood-onset disorders. Psychosocial support and genetic couseling should be available prior to screening and for the return of positive results. Systems are needed to reduce the risk of misinterpreting results. Finally, attention should be paid on the impact of expanded carrier screening on health care organizations and burden of cost.

Next-generation sequencing as a second-tier diagnostic test for newborn screening

Background Tandem mass spectrometry (MS/MS) has been used for newborn screening (NBS) of inherited metabolic diseases (IMDs) for decades. However, the traditional approach can yield false-positive or false-negative results and is affected by biochemical substrate-level fluctuations. To overcome the current limitations, we explored the possibility of using next-generation sequencing (NGS) as a second-tier diagnostic test to detect gene mutations in samples with abnormal MS/MS results. Methods Genomic DNA was extracted from dried blood spots and we designed a multigene panel, comprising 77 genes related to over 40 IMDs, for NBS. The prepared libraries were sequenced on the Ion Personal Genome Machine (PGM) platform. Thirty-eight samples identified as abnormal by MS/MS were tested for the diagnostic accuracy of NGS compared with Sanger sequencing. Results The concentration of DNA extracted from the 38 dried blood spots was sufficient for library preparation. The coverage and depth of the sequencing data were sufficient for the analysis. For all samples, the NGS results were consistent with the Sanger sequencing results. Conclusions The genomic DNA extracted from dried blood spots could be used for NGS, generating reliable sequencing results, and NGS may function as a second-tier diagnostic test for NBS. Ion PGM could facilitate the molecular diagnosis of IMDs with appropriate primers designed for candidate genes.

Contemporary genetic testing in inherited cardiac disease: tools, ethical issues, and clinical applications

Inherited cardiac diseases comprise a wide and heterogeneous spectrum of diseases of the heart, including the cardiomyopathies and the arrhythmic diseases in structurally normal hearts, that is, channelopathies. With a combined estimated prevalence of 3% in the general population, these conditions represent a relevant epidemiological entity worldwide, and are a major cause of cardiac morbidity and mortality in the young. The extraordinary progress achieved in molecular genetics over the last three decades has unveiled the complex molecular basis of many familial cardiac conditions, paving the way for routine use of gene testing in clinical practice. In current practice, genetic testing can be used in a clinically affected patient to confirm diagnosis, or to formulate a differential diagnosis among overlapping phenotypes or between hereditary and acquired (nongenetic) forms of disease. Although genotype–phenotype correlations are generally unpredictable, a precise molecular diagnosis can help predict prognosis in specific patient subsets and may guide management. In clinically unaffected relatives, genetic cascade testing is recommended, after the initial identification of a pathogenic variation, with the aim of identifying asymptomatic relatives who might be at risk of disease-related complications, including unexpected sudden cardiac death. Future implications include the identification of novel therapeutic targets and development of tailored treatments including gene therapy. This document reflects the multidisciplinary, ‘real-world’ experience required when implementing genetic testing in cardiomyopathies and arrhythmic syndromes, along the recommendations of various guidelines.

Concurrent somatic KRAS mutation and germline 10q22.3-q23.2 deletion in a patient with juvenile myelomonocytic leukemia, developmental delay, and multiple malformations: a case report

Background

The proto-oncogene KRAS performs an essential function in normal tissue signaling, and the mutation of KRAS gene is a key step in the development of many cancers. Somatic KRAS mutations are often detected in patients with solid and non-solid tumors, whereas germline KRAS mutations are implicated in patients with the Noonan syndrome, cardio-facio-cutaneous (CFC) syndrome and Costello syndrome. The deletion of chromosome 10q22.3-q23.2 is a rare cytogenetic abnormality, which often leads to distinct facial appearance and delays in speech and global development.

Case presentation

Herein, we report the case of a 4-year-old boy diagnosed with juvenile myelomonocytic leukemia. The boy also had syndromic features, such as speech and motor developmental delay, multiple congenital malformations, including distinct facial features, club feet, and cryptorchidism. Using whole-exome sequencing, we identified a pathogenic mutation in KRAS [c.34G > A, p.Gly12Ser] isolated from peripheral blood DNA. Sanger sequencing confirmed the wild-type sequence in the parents and patient’s salivary cell DNA indicating its somatic state. A 7311-kb deletion in 10q22.3-q23.2 was also revealed by chromosomal microarray analysis, which was later proved as a germline de novo variant.

Conclusion

Juvenile myelomonocytic leukemia in the patient was attributed to a somatic KRAS mutation, whereas the syndromic features of the patient were considered a consequence of germline chromosome 10q22.3-q23.2 deletion. Genetic testing for patients with complicated phenotypes can be valuable in detecting multiple pathogenic variants.

The BabySeq project: implementing genomic sequencing in newborns

BACKGROUND

The greatest opportunity for lifelong impact of genomic sequencing is during the newborn period. The "BabySeq Project" is a randomized trial that explores the medical, behavioral, and economic impacts of integrating genomic sequencing into the care of healthy and sick newborns.

METHODS

Families of newborns are enrolled from Boston Children's Hospital and Brigham and Women's Hospital nurseries, and half are randomized to receive genomic sequencing and a report that includes monogenic disease variants, recessive carrier variants for childhood onset or actionable disorders, and pharmacogenomic variants. All families participate in a disclosure session, which includes the return of results for those in the sequencing arm. Outcomes are collected through review of medical records and surveys of parents and health care providers and include the rationale for choice of genes and variants to report; what genomic data adds to the medical management of sick and healthy babies; and the medical, behavioral, and economic impacts of integrating genomic sequencing into the care of healthy and sick newborns.

DISCUSSION

The BabySeq Project will provide empirical data about the risks, benefits and costs of newborn genomic sequencing and will inform policy decisions related to universal genomic screening of newborns.

TRIAL REGISTRATION

The study is registered in ClinicalTrials.gov Identifier: NCT02422511 . Registration date: 10 April 2015.

Assessing the Accuracy of Variant Detection in Cost-Effective Gene Panel Testing by Next-Generation Sequencing

There is significant debate within the diagnostics community regarding the accuracy of variant identification by next-generation sequencing and the necessity of confirmatory testing of detected variants. Because the quality threshold to discriminate false positives depends on the workflow, no regulatory standard regarding this matter has yet been published. The goal of this study was to empirically determine the threshold to perform additional Sanger sequencing and to reduce the experimental cost to a practical level. Using 278 model genes, a hybridization capture-based protocol was examined to meet the clinical requirements of low cost, high efficiency, and high-quality data. To reduce excessive false-positive detection, filtering processes were introduced to remove mismapped reads and strand-biased detection to a published best-practices pipeline. With seven samples from the 1000 Genomes Project, 2750 single-nucleotide polymorphisms and 142 insertions/deletions were identified by our designed workflow. Compared with variants registered in the single nucleotide polymorphism database (dbSNP), a zero false-positive threshold value was determined (quality score > 1000). The variants satisfying these criteria accounted for 95.6% of single-nucleotide polymorphisms and 50.7% of insertions/deletions. Except for deletions located within the highly repeated sequences, the workflow achieved 100% sensitivity. The established threshold allowed us to discriminate between convincing variants and those requiring validation, a design that reconciles the competing objectives of cost minimization and quality maximization of clinical gene panel testing.

A Next-Generation Sequencing Primer-How Does It Work and What Can It Do?

Next-generation sequencing refers to a high-throughput technology that determines the nucleic acid sequences and identifies variants in a sample. The technology has been introduced into clinical laboratory testing and produces test results for precision medicine. Since next-generation sequencing is relatively new, graduate students, medical students, pathology residents, and other physicians may benefit from a primer to provide a foundation about basic next-generation sequencing methods and applications, as well as specific examples where it has had diagnostic and prognostic utility. Next-generation sequencing technology grew out of advances in multiple fields to produce a sophisticated laboratory test with tremendous potential. Next-generation sequencing may be used in the clinical setting to look for specific genetic alterations in patients with cancer, diagnose inherited conditions such as cystic fibrosis, and detect and profile microbial organisms. This primer will review DNA sequencing technology, the commercialization of next-generation sequencing, and clinical uses of next-generation sequencing. Specific applications where next-generation sequencing has demonstrated utility in oncology are provided.

Exome sequencing has higher diagnostic yield compared to simulated disease-specific panels in children with suspected monogenic disorders

As test costs decline, whole-exome sequencing (WES) has become increasingly used for clinical diagnosis, and now represents the primary alternative to gene panel testing for patients with a suspected genetic disorder. We sought to compare the diagnostic yield of singleton-WES with simulated application of commercial gene panels in children suspected of having a genetically heterogeneous condition. Recruitment, singleton-WES and phenotype-driven variant analysis was completed for 145 paediatric patients. At recruitment, clinicians were required to propose commercial gene panel tests as an alternative to WES and nominate a phenotype-driven candidate gene list. In WES-diagnosed children, three commercial options for each proposed panel were identified and evaluated for hypothetical diagnostic yield assuming 100% analytical sensitivity and specificity. We compared the price of WES with the least costly panel in WES-diagnosed children. In WES-undiagnosed children, we evaluated the exonic coverage of their phenotype-driven gene list using aggregate data. WES diagnoses were made in genes not included in at least one-of-three commercial panels in 42% of cases. Had a panel been selected instead, 23% of WES-diagnosed children would not have been diagnosed. In 26% of cases, the least costly panel option would have been more expensive than WES. Evaluation of WES coverage found that at the most stringent level of 20× coverage, the likelihood of missing a clinically relevant variant in a candidate gene list was maximally 8%. The broader coverage of WES makes it a superior alternative to gene panel testing at similar financial cost for children with suspected complex monogenic phenotypes.