Flype: Software for enabling personalized medicine

The advent of next generation DNA sequencing (NGS) has revolutionized clinical medicine by enabling wide‐spread testing for genomic anomalies and polymorphisms. With that explosion in testing, however, come several informatics challenges including managing large amounts of data, interpreting the results and providing clinical decision support. We present Flype, a web‐based bioinformatics platform built by a small group of bioinformaticians working in a community hospital setting, to address these challenges by allowing us to: (a) securely accept data from a variety of sources, (b) send orders to a variety of destinations, (c) perform secondary analysis and annotation of NGS data, (d) provide a central repository for all genomic variants, (e) assist with tertiary analysis and clinical interpretation, (f) send signed out data to our EHR as both PDF and discrete data elements, (g) allow population frequency analysis and (h) update variant annotation when literature knowledge evolves. We discuss the multiple use cases Flype supports such as (a) in‐house NGS tests, (b) in‐house pharmacogenomics (PGX) tests, (c) dramatic scale‐up of genomic testing using an external lab, (d) consumer genomics using two external partners, and (e) a variety of reporting tools. The source code for Flype is available upon request to the authors.     

Diagnosis of monogenic liver diseases in childhood by next‐generation sequencing

Next‐generation sequencing (NGS) has opened up novel diagnostic opportunities for children with unidentified, but suspected inherited diseases. We describe our single‐center experience with NGS diagnostics in standard clinical scenarios in pediatric hepatology. We investigated 135 children with suspected inherited hepatopathies, where initially no causative pathogenic variant had been identified, with an amplicon‐based NGS panel of 21 genes associated with acute and chronic hepatopathies. In 23 of these patients, we detected pathogenic or likely pathogenic variants in 10 different genes. We present 6 novel variants. A total of 14 of these patients presented with the characteristic phenotype of the related hepatopathy. Nine patients showed only few or atypical clinical symptoms or presented with additional signs. In another 13 out of 135 cases, we detected variants of unknown significance (VUS) in 9 different genes. Only 2 of these patients showed characteristic phenotypes conclusive with the detected variants, whereas 11 patients showed unspecific or atypical phenotypes. Our multi‐gene panel is a fast and comprehensive tool to diagnose inherited pediatric hepatopathies. We also illustrate the challenge of dealing with genetic variants and highlight arising clinical questions, especially in patients with atypical phenotypes.     

Insights into genetics,human biology and disease gleaned from family based genomic studies

Identifying genes and variants contributing to rare disease phenotypes and Mendelian conditions informs biology and medicine, yet potential phenotypic consequences for variation of >75% of the ~20,000 annotated genes in the human genome are lacking. Technical advances to assess rare variation genome-wide, particularly exome sequencing (ES), enabled establishment in the United States of the National Institutes of Health (NIH)-supported Centers for Mendelian Genomics (CMGs) and have facilitated collaborative studies resulting in novel “disease gene” discoveries. Pedigree-based genomic studies and rare variant analyses in families with suspected Mendelian conditions have led to the elucidation of hundreds of novel disease genes and highlighted the impact of de novo mutational events, somatic variation underlying nononcologic traits, incompletely penetrant alleles, phenotypes with high locus heterogeneity, and multilocus pathogenic variation. Herein, we highlight CMG collaborative discoveries that have contributed to understanding both rare and common diseases and discuss opportunities for future discovery in single-locus Mendelian disorder genomics. Phenotypic annotation of all human genes; development of bioinformatic tools and analytic methods; exploration of non-Mendelian modes of inheritance including reduced penetrance, multilocus variation, and oligogenic inheritance; construction of allelic series at a locus; enhanced data sharing worldwide; and integration with clinical genomics are explored. Realizing the full contribution of rare disease research to functional annotation of the human genome, and further illuminating human biology and health, will lay the foundation for the Precision Medicine Initiative.     

eDiVA—Classification and prioritization of pathogenic variants for clinical diagnostics

Mendelian diseases have shown to be an and efficient model for connecting genotypes to phenotypes and for elucidating the function of genes. Whole‐exome sequencing (WES) accelerated the study of rare Mendelian diseases in families, allowing for directly pinpointing rare causal mutations in genic regions without the need for linkage analysis. However, the low diagnostic rates of 20–30% reported for multiple WES disease studies point to the need for improved variant pathogenicity classification and causal variant prioritization methods. Here, we present the exome Disease Variant Analysis (eDiVA; http://ediva.crg.eu ), an automated computational framework for identification of causal genetic variants (coding/splicing single‐nucleotide variants and small insertions and deletions) for rare diseases using WES of families or parent–child trios. eDiVA combines next‐generation sequencing data analysis, comprehensive functional annotation, and causal variant prioritization optimized for familial genetic disease studies. eDiVA features a machine learning‐based variant pathogenicity predictor combining various genomic and evolutionary signatures. Clinical information, such as disease phenotype or mode of inheritance, is incorporated to improve the precision of the prioritization algorithm. Benchmarking against state‐of‐the‐art competitors demonstrates that eDiVA consistently performed as a good or better than existing approach in terms of detection rate and precision. Moreover, we applied eDiVA to several familial disease cases to demonstrate its clinical applicability.     

Targeted next‐generation sequencing and parental genotyping in sporadic Chinese Han deaf patients

The interpretation of the targeted next‐generation sequencing (NGS) results can be challenging for variants identified in the sporadic deaf patients. In this study, we performed targeted NGS of 143 deafness‐associated genes in 44 sporadic deaf patients and use parental genotyping to test whether the candidate pathogenic variants complied with recessive or de novo pattern. Of 29 recessive candidate variants with minor allele frequencies (MAFs) less than 0.005, 3 pairs of apparent compound heterozygous variants were inherited from the same parental allele, ruling out their pathogenic roles. In addition, non‐segregation of an OTOA p.Gln293Arg variant led to the discovery of a genomic microdeletion of OTOA on the opposite allele by copy number variation analysis. Overall, 13 pairs of recessive candidate variants were deemed causative in 13 patients. Of the 28 dominant candidate variants with MAFs less than 0.0005, none occurred de novo, suggesting that they were not disease causing. Our results revealed that targeted NGS in sporadic deaf patients may generate a significant false‐positive rate. Parental genotyping is a simple but effective step toward minimizing the false‐positive results. Our study also showed that de novo variants in dominant deafness genes may not be a common cause for sporadic deafness.     

mit‐o‐matic: A Comprehensive Computational Pipeline for Clinical Evaluation of Mitochondrial Variations from Next‐Generation Sequencing Datasets

The human mitochondrial genome has been reported to have a very high mutation rate as compared with the nuclear genome. A large number of mitochondrial mutations show significant phenotypic association and are involved in a broad spectrum of diseases. In recent years, there has been a remarkable progress in the understanding of mitochondrial genetics. The availability of next‐generation sequencing (NGS) technologies have not only reduced sequencing cost by orders of magnitude but has also provided us good quality mitochondrial genome sequences with high coverage, thereby enabling decoding of a number of human mitochondrial diseases. In this study, we report a computational and experimental pipeline to decipher the human mitochondrial DNA variations and examine them for their clinical correlation. As a proof of principle, we also present a clinical study of a patient with Leigh disease and confirmed maternal inheritance of the causative allele. The pipeline is made available as a user‐friendly online tool to annotate variants and find haplogroup, disease association, and heteroplasmic sites. The “mit‐o‐matic” computational pipeline represents a comprehensive cloud‐based tool for clinical evaluation of mitochondrial genomic variations from NGS datasets. The tool is freely available at http://genome.igib.res.in/mitomatic/ .     

The Clinical Next‐Generation Sequencing Database: A Tool for the Unified Management of Clinical Information and Genetic Variants to Accelerate Variant Pathogenicity Classification

Recent advances in next‐generation sequencing (NGS) have given rise to new challenges due to the difficulties in variant pathogenicity interpretation and large dataset management, including many kinds of public population databases as well as public or commercial disease‐specific databases. Here, we report a new database development tool, named the “Clinical NGS Database,” for improving clinical NGS workflow through the unified management of variant information and clinical information. This database software offers a two‐feature approach to variant pathogenicity classification. The first of these approaches is a phenotype similarity‐based approach. This database allows the easy comparison of the detailed phenotype of each patient with the average phenotype of the same gene mutation at the variant or gene level. It is also possible to browse patients with the same gene mutation quickly. The other approach is a statistical approach to variant pathogenicity classification based on the use of the odds ratio for comparisons between the case and the control for each inheritance mode (families with apparently autosomal dominant inheritance vs. control, and families with apparently autosomal recessive inheritance vs. control). A number of case studies are also presented to illustrate the utility of this database.     

Diagnostic exome sequencing of syndromic epilepsy patients in clinical practice

Although genetic revolution of recent years has vastly expanded a list of genes implicated in epilepsies, complex architecture of epilepsy genetics is still largely unknown, consequently, universally accepted workflows for epilepsy genetic testing in a clinical practice are missing. We present a comprehensive NGS‐based diagnostic approach addressing both the clinical and genetic heterogeneity of disorders involving epilepsy or seizures. A bioinformatic panel of 862 epilepsy‐ or seizure‐associated genes was applied to Mendeliome (4813 genes) or whole‐exome sequencing data as a first stage, while the second stage included untargeted variant interpretation. Eighty‐six consecutive patients with epilepsy or seizures associated with neurodevelopmental disorders and/or congenital malformations were investigated. Of the 86 probands, 42 harbored pathogenic and likely pathogenic variants, giving a diagnostic yield of 49%. Two patients were diagnosed with pathogenic copy number variations and 2 had causative mitochondrial DNA variants. Eleven patients (13%) were diagnosed with diseases with specific treatments. Besides, genomic approach in diagnostics had multiple additional benefits due to mostly non‐specific, overlapping, not full‐blown phenotypes and abilities to diagnose novel and ultra rare epilepsy‐associated diseases. Likely pathogenic variants were identified in SOX5 gene, not previously associated with epilepsy, and UBA5, a recently associated with epilepsy gene.     

Muscular dystrophies and myopathies: the spectrum of mutated genes in the Czech Republic

Inherited neuromuscular disorder (NMD) is a wide term covering different genetic disorders affecting muscles, nerves, and neuromuscular junctions. Genetic and clinical heterogeneity is the main drawback in a routine gene‐by‐gene diagnostics. We present Czech NMD patients with a genetic cause identified using targeted next‐generation sequencing (NGS) and the spectrum of these causes. Overall 167 unrelated patients presenting NMD falling into categories of muscular dystrophies, congenital muscular dystrophies, congenital myopathies, distal myopathies, and other myopathies were tested by targeted NGS of 42 known NMD‐related genes. Pathogenic or probably pathogenic sequence changes were identified in 79 patients (47.3%). In total, 37 novel and 51 known disease‐causing variants were detected in 23 genes. In addition, variants of uncertain significance were suspected in 7 cases (4.2%), and in 81 cases (48.5%) sequence changes associated with NMD were not found. Our results strongly indicate that for molecular diagnostics of heterogeneous disorders such as NMDs, targeted panel testing has a high‐clinical yield and should therefore be the preferred first‐tier approach. Further, we show that in the genetic diagnostic practice of NMDs, it is necessary to take into account different types of inheritance including the occurrence of an autosomal recessive disorder in two generations of one family.     

Reclassification of a frequent African‐origin variant from PMS2 to the pseudogene PMS2CL

Genomic analysis has become a mainstay in the investigation of cancer patients, especially for those suspected of harboring a heritable cancer predisposition syndrome. With ubiquitous short‐read next‐generation sequencing (NGS) technologies, these analyses can be complicated by the inappropriate alignment of variants to homologous genomic regions or pseudogenes. Using distinct primer sets specific to the gene and pseudogene, a nonspecific primer set, and a highly gene‐specific long‐range polymerase chain reaction primer set, we have shown that in at least a subset of patients, the common African PMS2 variant NM_000535.5:c.2182_2184delACTinsG, classified as pathogenic in ClinVar, has been incorrectly assigned to PMS2 from its well‐documented pseudogene, PMS2CL. This result is not only important for patients but also highlights a weakness in short‐read NGS technologies and the racial inequity in genomic analysis.     

NGS testing for cardiomyopathy: Utility of adding RASopathy‐associated genes

RASopathies include a group of syndromes caused by pathogenic germline variants in RAS‐MAPK pathway genes and typically present with facial dysmorphology, cardiovascular disease, and musculoskeletal anomalies. Recently, variants in RASopathy‐associated genes have been reported in individuals with apparently nonsyndromic cardiomyopathy, suggesting that subtle features may be overlooked. To determine the utility and burden of adding RASopathy‐associated genes to cardiomyopathy panels, we tested 11 RASopathy‐associated genes by next‐generation sequencing (NGS), including NGS‐based copy number variant assessment, in 1,111 individuals referred for genetic testing for hypertrophic cardiomyopathy (HCM) or dilated cardiomyopathy (DCM). Disease‐causing variants were identified in 0.6% (four of 692) of individuals with HCM, including three missense variants in the PTPN11, SOS1, and BRAF genes. Overall, 36 variants of uncertain significance (VUSs) were identified, averaging ～3VUSs/100 cases. This study demonstrates that adding a subset of the RASopathy‐associated genes to cardiomyopathy panels will increase clinical diagnoses without significantly increasing the number of VUSs/case.     

Caution in interpretation of disease causality for heterozygous loss-of-function variants in the MYH8 gene associated with autosomal dominant disorder

To date, the NM_002472.2(MYH8):c.2021G>A (p.Arg674Gln) missense variant in the MYH8 gene is the only known genetic change in individuals with autosomal dominant trismus-pseudocamptodactyly syndrome with unknown molecular mechanism. Next-generation sequencing (NGS), including targeted gene panels and whole-exome sequencing, is routinely performed in many clinical diagnostic laboratories as standard-of-care testing aimed at identifying disease-causing genomic variants. Whole-exome sequencing has revealed loss-of-function variants in the MYH8 gene. To properly classify the MYH8 loss-of-function variants, we either retrieved them from public databases or retrospectively collected them from individuals genetically tested by custom NGS panels or by whole-exome sequencing and confirmed using Sanger sequencing. We further evaluated the respective clinical presentations of these individuals with the MYH8 loss-of-function variants. Heterozygous loss-of-function variants in the MYH8 gene were detected in 16 individuals without trismus-pseudocamptodactyly syndrome. Four of these 16 individuals had a pathogenic or likely pathogenic variant detected in another gene that could explain their clinical presentation. Moreover, there are ∼100 MYH8 heterozygous protein-truncating and splice site variants in the ExAC database in different populations. Our results, combined with the population data, indicate that loss-of-function variants in the MYH8 gene do not cause autosomal dominant trismus-pseudocamptodactyly syndrome, and the clinical significance of these variants remains unknown at present. This result highlights the importance of considering the molecular mechanism of disease, variants published in the medical literature, and population genomic data for the correct interpretation of loss-of-function variants in genes associated with autosomal dominant diseases.     

Results of next‐generation sequencing gene panel diagnostics including copy‐number variation analysis in 810 patients suspected of heritable thoracic aortic disorders

Simultaneous analysis of multiple genes using next‐generation sequencing (NGS) technology has become widely available. Copy‐number variations (CNVs) in disease‐associated genes have emerged as a cause for several hereditary disorders. CNVs are, however, not routinely detected using NGS analysis. The aim of this study was to assess the diagnostic yield and the prevalence of CNVs using our panel of Hereditary Thoracic Aortic Disease (H‐TAD)‐associated genes. Eight hundred ten patients suspected of H‐TAD were analyzed by targeted NGS analysis of 21 H‐TAD associated genes. In addition, the eXome hidden Markov model (XHMM; an algorithm to identify CNVs in targeted NGS data) was used to detect CNVs in these genes. A pathogenic or likely pathogenic variant was found in 66 of 810 patients (8.1%). Of these 66 pathogenic or likely pathogenic variants, six (9.1%) were CNVs not detectable by routine NGS analysis. These CNVs were four intragenic (multi‐)exon deletions in MYLK, TGFB2, SMAD3, and PRKG1, respectively. In addition, a large duplication including NOTCH1 and a large deletion encompassing SCARF2 were detected. As confirmed by additional analyses, both CNVs indicated larger chromosomal abnormalities, which could explain the phenotype in both patients. Given the clinical relevance of the identification of a genetic cause, CNV analysis using a method such as XHMM should be incorporated into the clinical diagnostic care for H‐TAD patients.     

NEUROINFORMATICS IN MODEL ORGANISMS

Since its first availability in 2009, the next-generation sequencing (NGS) has been proved to be a powerful tool in identifying disease-associated variants in many neurological diseases, such as spinocerebellar ataxias, Charcot–Marie–Tooth disease, hereditary spastic paraplegia, and amyotrophic lateral sclerosis. Whole exome sequencing and whole genome sequencing are efficient for identifying variants in novel or unexpected genes responsible for inherited diseases, whereas targeted sequencing is useful in detecting variants in previously known disease-associated genes. The trove of genetic data yielded by NGS has made a significant impact on the clinical diagnoses while contributing hugely on the discovery of molecular pathomechanisms underlying these diseases. Nonetheless, elucidation of the pathogenic roles of the variants identified by NGS is challenging. Establishment of consensus guidelines and development of public genomic/phenotypic databases are thus vital to facilitate data sharing and validation.     

Reanalysis and optimisation of bioinformatic pipelines is critical for mutation detection

Rapid advances in genomic technologies have facilitated the identification pathogenic variants causing human disease. We report siblings with developmental and epileptic encephalopathy due to a novel, shared heterozygous pathogenic 13 bp duplication in SYNGAP1 (c.435_447dup, p.(L150Vfs*6)) that was identified by whole genome sequencing (WGS). The pathogenic variant had escaped earlier detection via two methodologies: whole exome sequencing and high‐depth targeted sequencing. Both technologies had produced reads carrying the variant, however, they were either not aligned due to the size of the insertion or aligned to multiple major histocompatibility complex (MHC) regions in the hg19 reference genome, making the critical reads unavailable for variant calling. The WGS pipeline followed different protocols, including alignment of reads to the GRCh37 reference genome, which lacks the additional MHC contigs. Our findings highlight the benefit of using orthogonal clinical bioinformatic pipelines and all relevant inheritance patterns to re‐analyze genomic data in undiagnosed patients.     

Next-generation sequencing for inborn errors of immunity

Inborn errors of immunity (IEIs) include several hundred gene defects affecting various components of the immune system. As with other constitutional disorders, next-generation sequencing (NGS) is a powerful tool for the diagnosis of these diseases. While NGS can provide molecular confirmation of disease in a patient with a suspected or classic phenotype, it can also identify new molecular defects of the immune system, expand gene-disease phenotypes, clarify mechanism of disease, pattern of inheritance or identify new gene-disease associations. Multiple clinical specialties are involved in the diagnosis and management of patients with IEI, and most have no formal genetic training or expertise. To effectively utilize NGS tools and data in clinical practice, it is relevant and pragmatic to obtain a modicum of knowledge about genetic terminology, the variety of platforms and tools available for high-throughput genomic analysis, the interpretation and implementation of such data in clinical practice. There is considerable variability not only in the technologies and analytical tools used for NGS but in the bioinformatics approach to variant identification and interpretation. The ability to provide a molecular basis for disease has the potential to alter therapeutic management and longer-term treatment of the disease, including developing personalized approaches with molecularly targeted therapies. This review is intended for the clinical specialist or diagnostic immunologist who works in the area of inborn errors of immunity, and provides an overview of the need for genetic testing in these patients (the “why” aspect), the various technologies and analytical approaches, bioinformatics tools, resources, and challenges (the “how” aspect), and the clinical evidence for identifying which patients might be best served by such testing (the “when” aspect).     

UniProt genomic mapping for deciphering functional effects of missense variants

Understanding the association of genetic variation with its functional consequences in proteins is essential for the interpretation of genomic data and identifying causal variants in diseases. Integration of protein function knowledge with genome annotation can assist in rapidly comprehending genetic variation within complex biological processes. Here, we describe mapping UniProtKB human sequences and positional annotations, such as active sites, binding sites, and variants to the human genome (GRCh38) and the release of a public genome track hub for genome browsers. To demonstrate the power of combining protein annotations with genome annotations for functional interpretation of variants, we present specific biological examples in disease‐related genes and proteins. Computational comparisons of UniProtKB annotations and protein variants with ClinVar clinically annotated single nucleotide polymorphism (SNP) data show that 32% of UniProtKB variants colocate with 8% of ClinVar SNPs. The majority of colocated UniProtKB disease‐associated variants (86%) map to 'pathogenic' ClinVar SNPs. UniProt and ClinVar are collaborating to provide a unified clinical variant annotation for genomic, protein, and clinical researchers. The genome track hubs, and related UniProtKB files, are downloadable from the UniProt FTP site and discoverable as public track hubs at the UCSC and Ensembl genome browsers.     

Simple and Efficient Identification of Rare Recessive Pathologically Important Sequence Variants from Next Generation Exome Sequence Data

Massively parallel (“next generation”) DNA sequencing (NGS) has quickly become the method of choice for seeking pathogenic mutations in rare uncharacterized monogenic diseases. Typically, before DNA sequencing, protein‐coding regions are enriched from patient genomic DNA, representing either the entire genome (“exome sequencing”) or selected mapped candidate loci. Sequence variants, identified as differences between the patient's and the human genome reference sequences, are then filtered according to various quality parameters. Changes are screened against datasets of known polymorphisms, such as dbSNP and the 1000 Genomes Project, in the effort to narrow the list of candidate causative variants. An increasing number of commercial services now offer to both generate and align NGS data to a reference genome. This potentially allows small groups with limited computing infrastructure and informatics skills to utilize this technology. However, the capability to effectively filter and assess sequence variants is still an important bottleneck in the identification of deleterious sequence variants in both research and diagnostic settings. We have developed an approach to this problem comprising a user‐friendly suite of programs that can interactively analyze, filter and screen data from enrichment‐capture NGS data. These programs (“Agile Suite”) are particularly suitable for small‐scale gene discovery or for diagnostic analysis.     

MT‐ATP6 mitochondrial disease variants: Phenotypic and biochemical features analysis in 218 published cases and cohort of 14 new cases

Mitochondrial complex V (CV) generates cellular energy as adenosine triphosphate (ATP). Mitochondrial disease caused by the m.8993T>G pathogenic variant in the CV subunit gene MT‐ATP6 was among the first described human mitochondrial DNA diseases. Due to a lack of clinically available functional assays, validating the definitive pathogenicity of additional MT‐ATP6 variants remains challenging. We reviewed all reportedMT‐ATP6 disease cases ( n = 218) to date, to assess for MT‐ATP6 variants, heteroplasmy levels, and inheritance correlation with clinical presentation and biochemical findings. We further describe the clinical and biochemical features of a new cohort of 14 kindreds with MT‐ATP6 variants of uncertain significance. Despite extensive overlap in the heteroplasmy levels of MT‐ATP6 variant carriers with and without a wide range of clinical symptoms, previously reported symptomatic subjects had significantly higher heteroplasmy load (p = 2.2 x 10^‐16). Pathogenic MT‐ATP6 variants resulted in diverse biochemical features. The most common findings were reduced ATP synthesis rate, preserved ATP hydrolysis capacity, and abnormally increased mitochondrial membrane potential. However, no single biochemical feature was universally observed. Extensive heterogeneity exists among both clinical and biochemical features of distinct MT‐ATP6 variants. Improved mechanistic understanding and development of consistent biochemical diagnostic analyses are needed to permit accurate pathogenicity assessment of variants of uncertain significance in MT‐ATP6.     

Lake Louise Mutation Detection Meeting 2013: Clinical Translation of Next‐Generation Sequencing Requires Optimization of Workflows and Interpretation of Variants

With the exponential reduction of the cost of next‐generation sequencing (NGS), it is no longer the generation of data but the analysis and interpretation of massive amounts of sequencing data that are seen as key challenges for the effective integration of these technologies into clinical practice. Clinical geneticists, informaticians, and scientists from 17 countries gathered for the 12th International Symposium on Mutation in the Genome at the Fairmont Chateau Lake Louise (Canada) to discuss technological advances and applications of NGS and consider possible approaches to the challenges of clinical translation. Here, we provide an overview of the main themes of the meeting that included development of innovative solutions for variant sharing, tools and resources for NGS analysis, novel technology and methodology development, NGS‐based discovery of disease pathogenesis, development of multigene NGS sequencing panels for clinical use, exploring diagnostic utility of whole‐exome and whole‐genome sequencing, and, finally, integration of genomic sequencing into the clinic.