Assessing the necessity of confirmatory testing for exome-sequencing results in a clinical molecular diagnostic laboratory

Inconsistencies between prenatal diagnostic and genetic testing laboratories on variant validation of rare monogenic diseases

BACKGROUND

The advent of next-generation sequencing (NGS) has enhanced the diagnostic efficacy for monogenic diseases, while presenting challenges in achieving consistent diagnoses.

METHOD

We retrospectively analyzed the concordance rate and reasons for the inconsistency between the original diagnostic result from the genetic testing laboratory and the variant validation result from the prenatal diagnostic center. The validation procedure comprised three stages: validation of variant detection, reevaluation of variant classification, and assessment of recurrence risk, which involved verifying the mode of inheritance and parental carriage.

RESULT

In total, 17 (6%) of the 286 families affected by rare monogenic diseases showed different results during the variant validation procedure. These cases comprised four (23.5%) with variant detection errors, 12 (70.5%) with inconsistent interpretation, and one (6%) with non-Mendelian inheritance patterns. False-positive NGS results confirmed by Sanger sequencing were related to pseudogenes and GC-rich regions. The classification of the 17 variants was altered in the 12 cases owing to various factors. The case with an atypical inheritance pattern was originally considered autosomal recessive inheritance, but was diagnosed as maternal uniparental disomy after additional genetic analysis.

CONCLUSION

We underscored the significance of variant validation by prenatal diagnostic centers. Families affected by monogenic diseases with reproductive plans should be referred to prenatal genetic centers as early as possible to avoid different results that may postpone subsequent prenatal diagnosis.

Incorporating CNV analysis improves the yield of exome sequencing for rare monogenic disorders-an important consideration for resource-constrained settings

Exome sequencing (ES) is a recommended first-tier diagnostic test for many rare monogenic diseases. It allows for the detection of both single-nucleotide variants (SNVs) and copy number variants (CNVs) in coding exonic regions of the genome in a single test, and this dual analysis is a valuable approach, especially in limited resource settings. Single-nucleotide variants are well studied; however, the incorporation of copy number variant analysis tools into variant calling pipelines has not been implemented yet as a routine diagnostic test, and chromosomal microarray is still more widely used to detect copy number variants. Research shows that combined single and copy number variant analysis can lead to a diagnostic yield of up to 58%, increasing the yield with as much as 18% from the single-nucleotide variant only pipeline. Importantly, this is achieved with the consideration of computational costs only, without incurring any additional sequencing costs. This mini review provides an overview of copy number variant analysis from exome data and what the current recommendations are for this type of analysis. We also present an overview on rare monogenic disease research standard practices in resource-limited settings. We present evidence that integrating copy number variant detection tools into a standard exome sequencing analysis pipeline improves diagnostic yield and should be considered a significantly beneficial addition, with relatively low-cost implications. Routine implementation in underrepresented populations and limited resource settings will promote generation and sharing of CNV datasets and provide momentum to build core centers for this niche within genomic medicine.

Improving the filtering of false positive single nucleotide variations by combining genomic features with quality metrics

MOTIVATION

Technical errors in sequencing or bioinformatics steps and difficulties in alignment at some genomic sites result in false positive (FP) variants. Filtering based on quality metrics is a common method for detecting FP variants, but setting thresholds to reduce FP rates may reduce the number of true positive variants by overlooking the more complex relationships between features. The goal of this study is to develop a machine learning-based model for identifying FPs that integrates quality metrics with genomic features and with the feature interpretability property to provide insights into model results.

RESULTS

We propose a random forest-based model that utilizes genomic features to improve identification of FPs. Further examination of the features shows that the newly introduced features have an important impact on the prediction of variants misclassified by VEF, GATK-CNN, and GARFIELD, recently introduced FP detection systems. We applied cost-sensitive training to avoid errors in misclassification of true variants and developed a model that provides a robust mechanism against misclassification of true variants while increasing the prediction rate of FP variants. This model can be easily re-trained when factors such as experimental protocols might alter the FP distribution. In addition, it has an interpretability mechanism that allows users to understand the impact of features on the model's predictions.

AVAILABILITY AND IMPLEMENTATION

The software implementation can be found at https://github.com/ideateknoloji/FPDetect.

Confirmation of Insertion, Deletion, and Deletion-Insertion Variants Detected by Next-Generation Sequencing

BACKGROUND

Despite clinically demonstrated accuracy in next generation sequencing (NGS) data, many clinical laboratories continue to confirm variants with Sanger sequencing, which increases cost of testing and turnaround time. Several studies have assessed the accuracy of NGS in detecting single nucleotide variants; however, less has been reported about insertion, deletion, and deletion-insertion variants (indels).

METHODS

We performed a retrospective analysis from 2015-2022 of indel results from a subset of NGS targeted gene panel tests offered through the Mayo Clinic Genomics Laboratories. We compared results from NGS and Sanger sequencing of indels observed in clinical runs and during the intra-assay validation of the tests.

RESULTS

Results demonstrated 100% concordance between NGS and Sanger sequencing for over 490 indels (217 unique), ranging in size from 1 to 68 basepairs (bp). The majority of indels were deletions (77%) and 1 to 5 bp in length (90%). Variant frequencies ranged from 11.4% to 67.4% and 85.1% to 100% for heterozygous and homozygous variants, respectively, with a median depth of coverage of 2562×. A subset of indels (7%) were located in complex regions of the genome, and these were accurately detected by NGS. We also demonstrated 100% reproducibility of indel detection (n = 179) during intra-assay validation.

CONCLUSIONS

Together this data demonstrates that reportable indel variants up to 68 bp can be accurately assessed using NGS, even when they occur in complex regions. Depending on the complexity of the region or variant, Sanger sequence confirmation of indels is usually not necessary if the variants meet appropriate coverage and allele frequency thresholds.

Recommendations for Next-Generation Sequencing Germline Variant Confirmation: A Joint Report of the Association for Molecular Pathology and National Society of Genetic Counselors

Clinical laboratory implementation of next-generation sequencing (NGS)-based constitutional genetic testing has been rapid and widespread. In the absence of widely adopted comprehensive guidance, there remains substantial variability among laboratories in the practice of NGS. One issue of sustained discussion in the field is whether and to what extent orthogonal confirmation of genetic variants identified by NGS is necessary or helpful. The Association for Molecular Pathology Clinical Practice Committee convened the NGS Germline Variant Confirmation Working Group to assess current evidence regarding orthogonal confirmation and to establish recommendations for standardizing orthogonal confirmation practices to support quality patient care. On the basis of the results of a survey of the literature, a survey of laboratory practices, and subject expert matter consensus, eight recommendations are presented, providing a common framework for clinical laboratory professionals to develop or refine individualized laboratory policies and procedures regarding orthogonal confirmation of germline variants detected by NGS.

Identification of Compound Heterozygous EVC2 Gene Variants in Two Mexican Families with Ellis-van Creveld Syndrome

BACKGROUND

Ellis-van Creveld syndrome (EvCS) is an autosomal recessive ciliopathy with a disproportionate short stature, polydactyly, dystrophic nails, oral defects, and cardiac anomalies. It is caused by pathogenic variants in the EVC or EVC2 genes. To obtain further insight into the genetics of EvCS, we identified the genetic defect for the EVC2 gene in two Mexican patients.

METHODS

Two Mexican families were enrolled in this study. Exome sequencing was applied in the probands to screen potential genetic variant(s), and then Sanger sequencing was used to identify the variant in the parents. Finally, a prediction of the three-dimensional structure of the mutant proteins was made.

RESULTS

One patient has a compound heterozygous EVC2 mutation: a novel heterozygous variant c.519_519 + 1delinsT inherited from her mother, and a heterozygous variant c.2161delC (p.L721fs) inherited from her father. The second patient has a previously reported compound heterozygous EVC2 mutation: nonsense mutation c.645G > A (p.W215*) in exon 5 inherited from her mother, and c.273dup (p.K92fs) in exon 2 inherited from her father. In both cases, the diagnostic was Ellis-van Creveld syndrome. Three-dimensional modeling of the EVC2 protein showed that truncated proteins are produced in both patients due to the generation of premature stop codons.

CONCLUSION

The identified novel heterozygous EVC2 variants, c.2161delC and c.519_519 + 1delinsT, were responsible for the Ellis-van Creveld syndrome in one of the Mexican patients. In the second Mexican patient, we identified a compound heterozygous variant, c.645G > A and c.273dup, responsible for EvCS. The findings in this study extend the EVC2 mutation spectrum and may provide new insights into the EVC2 causation and diagnosis with implications for genetic counseling and clinical management.

Inconsistency between non-invasive prenatal testing (NIPT) and conventional prenatal diagnosis due to confined placental and fetal mosaicism: Two case reports

We aimed to identify the causes of inconsistent results between non-invasive prenatal testing (NIPT) and invasive testing methods for trisomy 21. In the first case, NIPT was performed at 11 weeks of pregnancy, and the result showed a high risk of trisomy 21 [fetal fraction (FF) = 6.98%, 21 chromosome Z-score = 3.6]. The patient underwent quantitative fluorescent (QF)-PCR and karyotyping at 14 + 0 weeks of pregnancy through CVS showing mosaicism of 47, XX, + 21[11] and 46, XX [39] in karyotyping. The patient underwent amniocentesis at 15 + 6 weeks, showing a normal pattern in QF-PCR and 46, XX karyotyping in long term culture. The second case underwent NIPT at 16 + 5 weeks of pregnancy (FF = 7.52%, 21 chromosome Z-score = 2.503). She underwent an invasive test at 19 weeks through amniotic fluid sampling. As a result, trisomy 21 was detected by QF-PCR, and mosaicism of XX, +21[22]/46, XX [4] was identified by karyotyping. Despite significant advances in fetal chromosome analysis using NIPT, invasive testing is still needed as placenta-derived DNA does not reflect 100% fetal genetic information. Placental mosaicism can be detected by NIPT, but more research is needed to increase its sensitivity. Therefore, if the NIPT result is positive, an invasive test can confirm the result, and continuous monitoring is required even if the NIPT result is negative.

A Rare Phenotype of Uncommon Charcot–Marie–Tooth Genotypes Complicated With Inflammation Evaluated by Genetics and Magnetic Resonance Neurography

The pathogenesis of Charcot–Marie–Tooth (CMT) disease, an inherited peripheral neuropathy, is associated with more than 60 nuclear genes. We reported a rare phenotype of the uncommon CMT genotype complicated with neuroinflammation, that is, an MPZ mutation, NC_000001.11 (NM_000530.6): c.308G > C detected by next-generation sequencing. Moreover, we present a case of the CMT type 1B, with atypical presentation as two patterns of hypertrophy in the brachial and lumbosacral plexus, as well as enhancement in the cauda equina and nerve roots on multimodal magnetic resonance neurography (MRN). MRN assessment facilitated the identification of coexisting neuroinflammation and provided more evidence, especially for patients with atypical symptoms in hereditary sensory and motor neuropathy, who could benefit from immunotherapy.

Whole Exome Sequencing in South Africa: Stakeholder Views on Return of Individual Research Results and Incidental Findings

The use of whole exome sequencing (WES) in medical research is increasing in South Africa (SA), raising important questions about whether and which individual genetic research results, particularly incidental findings, should be returned to patients. Whilst some commentaries and opinions related to the topic have been published in SA, there is no qualitative data on the views of professional stakeholders on this topic. Seventeen participants including clinicians, genomics researchers, and genetic counsellors (GCs) were recruited from the Western Cape in SA. Semi-structured interviews were conducted, and the transcripts analysed using the framework approach for data analysis. Current roadblocks for the clinical adoption of WES in SA include a lack of standardised guidelines; complexities relating to variant interpretation due to lack of functional studies and underrepresentation of people of African ancestry in the reference genome, population and variant databases; lack of resources and skilled personnel for variant confirmation and follow-up. Suggestions to overcome these barriers include obtaining funding and buy-in from the private and public sectors and medical insurance companies; the generation of a locally relevant reference genome; training of health professionals in the field of genomics and bioinformatics; and multidisciplinary collaboration. Participants emphasised the importance of upscaling the accessibility to and training of GCs, as well as upskilling of clinicians and genetic nurses for return of genetic data in collaboration with GCs and medical geneticists. Future research could focus on exploring the development of stakeholder partnerships for increased access to trained specialists as well as community engagement and education, alongside the development of guidelines for result disclosure.

Addressing ethical and laboratory challenges for initiation of a rapid whole genome sequencing program

Rapid whole genome sequencing (rapid WGS) is a powerful diagnostic tool that is becoming increasingly practical for widespread clinical use. However, protocols for its use are challenging to implement. A significant obstacle to clinical adoption is that laboratory certification requires an initial research development phase, which is constrained by regulations from returning results. Regulations preventing return of results have ethical implications in cases which might impact patient outcomes. Here, we describe our experience with the development of a rapid WGS research protocol, that balanced the requirements for laboratory-validated test development with the ethical needs of clinically relevant return of results.

A graphical, interactive and GPU-enabled workflow to process long-read sequencing data

Background

Long-read sequencing has great promise in enabling portable, rapid molecular-assisted cancer diagnoses. A key challenge in democratizing long-read sequencing technology in the biomedical and clinical community is the lack of graphical bioinformatics software tools which can efficiently process the raw nanopore reads, support graphical output and interactive visualizations for interpretations of results. Another obstacle is that high performance software tools for long-read sequencing data analyses often leverage graphics processing units (GPU), which is challenging and time-consuming to configure, especially on the cloud.

Results

We present a graphical cloud-enabled workflow for fast, interactive analysis of nanopore sequencing data using GPUs. Users customize parameters, monitor execution and visualize results through an accessible graphical interface. The workflow and its components are completely containerized to ensure reproducibility and facilitate installation of the GPU-enabled software. We also provide an Amazon Machine Image (AMI) with all software and drivers pre-installed for GPU computing on the cloud. Most importantly, we demonstrate the potential of applying our software tools to reduce the turnaround time of cancer diagnostics by generating blood cancer (NB4, K562, ME1, 238 MV4;11) cell line Nanopore data using the Flongle adapter. We observe a 29x speedup and a 93x reduction in costs for the rate-limiting basecalling step in the analysis of blood cancer cell line data.

Conclusions

Our interactive and efficient software tools will make analyses of Nanopore data using GPU and cloud computing accessible to biomedical and clinical scientists, thus facilitating the adoption of cost effective, fast, portable and real-time long-read sequencing.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07927-1.

Approach to genetic diagnosis of inborn errors of immunity through next-generation sequencing

Patients with inborn errors of immunity (IEI) present with a heterogeneous clinical and immunological phenotype, therefore a correct molecular diagnosis is crucial for the classification and subsequent therapeutic management. On the other hand, IEI are a group of rare congenital diseases with highly diverse features and, in most cases, an as yet unknown genetic etiology. Next generation sequencing has facilitated genetic examinations of rare inherited disorders during the recent years, thus allowing a suitable molecular diagnosis in the IEI patients. This review aimed to investigate the current findings about these techniques in the field of IEI, suggesting an efficient stepwise approach to molecular diagnosis of inborn errors of immunity.

Diagnostic yield of exome sequencing in myopathies: Experience of a Slovenian tertiary centre

BACKGROUND

Our aim was to present the experience of systematic, routine use of next generation sequencing (NGS) in clinical diagnostics of myopathies.

METHODS

Exome sequencing was performed on patients with high risk for inherited myopathy, which were selected based on the history of the disease, family history, clinical presentation, and diagnostic workup. Exome target capture was performed, followed by sequencing on HiSeq 2500 or MiSeq platforms. Data analysis was performed using internally developed bioinformatic pipeline.

RESULTS

The study comprised 86 patients, including 22 paediatric cases (26%). The largest group were patients referred with an unspecified myopathy (47%), due to non-specific or incomplete clinical and laboratory findings, followed by congenital myopathies (22%) and muscular dystrophies (22%), congenital myotonias (6%), and mitochondrial myopathies (3%). Altogether, a diagnostic yield was 52%; a high diagnostic rate was present in paediatric patients (64%), while in patients with unspecified myopathies the rate was 35%. We found 51 pathogenic/likely pathogenic variants in 23 genes and two pathogenic copy number variations.

CONCLUSION

Our results provide evidence that phenotype driven exome analysis diagnostic approach facilitates the diagnostic rate of complex, heterogeneous disorders, such as myopathies, particularly in paediatric patients and patients with unspecified myopathies.

Reducing Sanger confirmation testing through false positive prediction algorithms

Purpose

Clinical genome sequencing (cGS) followed by orthogonal confirmatory testing is standard practice. While orthogonal testing significantly improves specificity, it also results in increased turnaround time and cost of testing. The purpose of this study is to evaluate machine learning models trained to identify false positive variants in cGS data to reduce the need for orthogonal testing.

Methods

We sequenced five reference human genome samples characterized by the Genome in a Bottle Consortium (GIAB) and compared the results with an established set of variants for each genome referred to as a truth set. We then trained machine learning models to identify variants that were labeled as false positives.

Results

After training, the models identified 99.5% of the false positive heterozygous single-nucleotide variants (SNVs) and heterozygous insertions/deletions variants (indels) while reducing confirmatory testing of nonactionable, nonprimary SNVs by 85% and indels by 75%. Employing the algorithm in clinical practice reduced overall orthogonal testing using dideoxynucleotide (Sanger) sequencing by 71%.

Conclusion

Our results indicate that a low false positive call rate can be maintained while significantly reducing the need for confirmatory testing. The framework that generated our models and results is publicly available at https://github.com/HudsonAlpha/STEVE.

Sanger sequencing is no longer always necessary based on a single-center validation of 1109 NGS variants in 825 clinical exomes

Despite the improved accuracy of next-generation sequencing (NGS), it is widely accepted that variants need to be validated using Sanger sequencing before reporting. Validation of all NGS variants considerably increases the turnaround time and costs of clinical diagnosis. We comprehensively assessed this need in 1109 variants from 825 clinical exomes, the largest sample set to date assessed using Illumina chemistry reported. With a concordance of 100%, we conclude that Sanger sequencing can be very useful as an internal quality control, but not so much as a verification method for high-quality single-nucleotide and small insertion/deletions variants. Laboratories might validate and establish their own thresholds before discontinuing Sanger confirmation studies. We also expand and validate 23 copy number variations detected by exome sequencing in 20 samples, observing a concordance of 95.65% (22/23).

Utility of droplet digital PCR and NGS-based CNV clinical assays in hearing loss diagnostics: current status and future prospects

Introduction: Genetic variants in over 100 genes can cause non-syndromic hearing loss (NSHL). Comprehensive diagnostic testing of these genes requires detecting pathogenic sequence and copy number alterations with economical, scalable and sensitive assays. Here we discuss best practices and effective testing algorithms for hearing-loss-related genes with special emphasis on detection of copy number variants.Areas covered: We review studies that used next-generation sequencing (NGS), chromosomal microarrays, droplet digital PCR (ddPCR), and multiplex ligation-dependent probe amplification (MLPA) for the diagnosis of NSHL. We specifically focus on unique and recurrent copy number changes that affect the GJB2 and STRC genes, two of the most common causes of NSHL.Expert opinion: NGS panels and exome sequencing can detect most pathogenic sequence and copy number variants that cause NSHL; however, GJB2 and STRC currently require additional assays to capture all pathogenic copy number variants. Adoption of genome sequencing may simplify diagnostic workflows, but further investigational studies will be required to evaluate its clinical efficacy.

Mining Grapevine Downy Mildew Susceptibility Genes: A Resource for Genomics-Based Breeding and Tailored Gene Editing

Several pathogens continuously threaten viticulture worldwide. Until now, the investigation on resistance loci has been the main trend to understand the interaction between grapevine and the mildew causal agents. Dominantly inherited gene-based resistance has shown to be race-specific in some cases, to confer partial immunity, and to be potentially overcome within a few years since its introgression. Recently, on the footprint of research conducted in Arabidopsis, putative genes associated with downy mildew susceptibility have been discovered also in the grapevine genome. In this work, we deep-sequenced four putative susceptibility genes-namely VvDMR6.1, VvDMR6.2, VvDLO1, VvDLO2-in 190 genetically diverse grapevine genotypes to discover new sources of broad-spectrum and recessively inherited resistance. Identified Single Nucleotide Polymorphisms were screened in a bottleneck analysis from the genetic sequence to their impact on protein structure. Fifty-five genotypes showed at least one impacting mutation in one or more of the scouted genes. Haplotypes were inferred for each gene and two of them at the VvDMR6.2 gene were found significantly more represented in downy mildew resistant genotypes. The current results provide a resource for grapevine and plant genetics and could corroborate genomic-assisted breeding programs as well as tailored gene editing approaches for resistance to biotic stresses.

Bioinformatics workflows for clinical applications in precision oncology

High-throughput molecular profiling of tumors is a fundamental aspect of precision oncology, enabling the identification of genomic alterations that can be targeted therapeutically. In this context, a patient is matched to a specific drug or therapy based on the tumor's underlying genetic driver events rather than the histologic classification. This approach requires extensive bioinformatics methodology and workflows, including raw sequencing data processing and quality control, variant calling and annotation, integration of different molecular data types, visualization and finally reporting the data to physicians, cancer researchers and pharmacologists in a format that is readily interpretable for clinical decision making. This review comprises a broad overview of these bioinformatics aspects and discusses the multiple analytical, technical and interpretational challenges that remain to efficiently translate molecular findings into personalized treatment recommendations.

Sanger Validation of High-Throughput Sequencing in Genetic Diagnosis: Still the Best Practice?

Next-generation sequencing (NGS)'s crucial role in supporting genetic diagnosis and personalized medicine leads to the definition of Guidelines for Diagnostic NGS by the European Society of Human Genetics. Factors of different nature producing false-positive/negative NGS data together with the paucity of internationally accepted guidelines providing specified NGS quality metrics to be followed for diagnostics purpose made the Sanger validation of NGS variants still mandatory. We reported the analysis of three cases of discrepancy between NGS and Sanger sequencing in a cohort of 218 patients. NGS was performed by Illumina MiSeq^® and Haloplex/SureSelect protocols targeting 97 or 57 or 10 gene panels usually applied for diagnostics. Variants called following guidelines suggested by the Broad Institute and identified according to MAF <0.01 and allele balance >0.2 were Sanger validated. Three out of 945 validated variants showed a discrepancy between NGS and Sanger. In all three cases, a deep evaluation of the discrepant gene variant results and methodological approach allowed to confirm the NGS datum. Allelic dropout (ADO) occurrence during polymerase chain or sequencing reaction was observed, mainly related to incorrect variant zygosity. Our study extends literature data in which almost 100% "high quality" NGS variants are confirmed by Sanger; moreover, it demonstrates that in case of discrepancy between a high-quality NGS variant and Sanger validation, NGS call should not be a priori assumed to represent the source of the error. Actually, difficulties (i.e., ADO, unpredictable presence of private variants on primer-binding regions) of the so-called gold standard direct sequencing should be considered especially in light of the constantly implemented and accurate high-throughput technologies. Our data along with literature raise a discussion on the opportunity to establish a standardized quality threshold by International Guidelines for clinical NGS in order to limit Sanger confirmation to borderline conditions of variant quality parameters and verification of correct gene variant call/patient coupling on a different blood sample aliquot.

Molecular diagnosis methods in familial hypercholesterolemia

Familial hypercholesterolemia (FH) is considered the genetic cause of coronary heart disease and ischemic stroke. FH is mainly an autosomal codominant pattern-based disorder and is primarily determined by point mutations within the low-density lipoprotein receptor, apolipoprotein B, and proprotein convertase subtilisin/kexin type 9 genes, causing increased low-density lipoprotein cholesterol levels in the serum of untreated individuals. The accumulation will eventually lead to atherosclerotic cardiovascular disease. Although clinical criteria comprising several prognosis scores, such as the Simon Broome, Dutch Lipid Clinic Network, Make Early Diagnosis to Prevent Early Death, and the recently proposed Montreal-FH-SCORE, are the conventional basis of diagnosing FH, the genetic diagnosis made by single nucleotide polymorphism genotyping, multiplex ligation-dependent probe amplification analysis, and sequencing (both Sanger and Next-Generation sequencing) offers unequivocal diagnosis. Given the heterogeneity of known mutations, the genetic diagnosis of FH is often difficult to establish, despite the growing evidence of the causative mutations, as well as the polygenic aspect of this pathology and the importance of cascade screening of the FH patient’s healthy family members. This review article details different genetic techniques that can be used in FH identification when there is a clinical FH suspicion based on criteria comprised in prognosis scores, knowing that none of these are exhaustive in the diagnosis, yet they efficaciously overlap and complement each other for confirming the disease at the molecular level.

Best practices for variant calling in clinical sequencing

Next-generation sequencing technologies have enabled a dramatic expansion of clinical genetic testing both for inherited conditions and diseases such as cancer. Accurate variant calling in NGS data is a critical step upon which virtually all downstream analysis and interpretation processes rely. Just as NGS technologies have evolved considerably over the past 10 years, so too have the software tools and approaches for detecting sequence variants in clinical samples. In this review, I discuss the current best practices for variant calling in clinical sequencing studies, with a particular emphasis on trio sequencing for inherited disorders and somatic mutation detection in cancer patients. I describe the relative strengths and weaknesses of panel, exome, and whole-genome sequencing for variant detection. Recommended tools and strategies for calling variants of different classes are also provided, along with guidance on variant review, validation, and benchmarking to ensure optimal performance. Although NGS technologies are continually evolving, and new capabilities (such as long-read single-molecule sequencing) are emerging, the “best practice” principles in this review should be relevant to clinical variant calling in the long term.

Familial hypercholesterolemia: A single-nucleotide variant (SNV) in mosaic at the low density lipoprotein receptor (LDLR)

BACKGROUND AND AIMS

Familial hypercholesterolemia is most frequently caused by genetic variants in the LDLR gene. Most of LDLR pathogenic variants are missense, followed by splicing and deletion/insertions variants. Mosaicism is a genetic condition in which an individual shows more than one clone of cells with different genotypes. The objective of this article was the molecular characterization of a patient with hypercholesterolemia.

METHODS AND RESULTS

Genetic analysis of DNA from peripheral blood and saliva was performed by NGS, Sanger sequencing and pyrosequencing technologies. NGS analysis detected the pathogenic variant LDLR:c.1951G > T:p.(Asp651Tyr) in 9%-12% of reads. The presence of the variant was confirmed by pyrosequencing analysis. The variant found was functional characterized using an in vitro model (CHO-ldlA7 cells). Activity and expression of cell surface LDLR were measured by flow cytometry. Colocalization LDLR-Dil-LDL was detected by immunofluorescence. The LDLR activity showed 80% uptake, 50% binding and 53% expression of cell surface LDLR regarding wild type.

CONCLUSIONS

Herein, we report the first case of a mosaic single nucleotide variant affecting the LDLR gene in a patient with familial hypercholesterolemia. As it has been described for other pathologies, mosaicism could be underestimated in FH and its detection will improve with the introduction of NGS technologies in the diagnostic routine.

A preliminary computational outputs versus experimental results: Application of sTRAP, a biophysical tool for the analysis of SNPs of transcription factor-binding sites

BACKGROUND

In the human genome, the transcription factors (TFs) and transcription factor-binding sites (TFBSs) network has a great regulatory function in the biological pathways. Such crosstalk might be affected by the single-nucleotide polymorphisms (SNPs), which could create or disrupt a TFBS, leading to either a disease or a phenotypic defect. Many computational resources have been introduced to predict the TFs binding variations due to SNPs inside TFBSs, sTRAP being one of them.

METHODS

A literature review was performed and the experimental data for 18 TFBSs located in 12 genes was provided. The sequences of TFBS motifs were extracted using two different strategies; in the size similar with synthetic target sites used in the experimental techniques, and with 60 bp upstream and downstream of the SNPs. The sTRAP (http://trap.molgen.mpg.de/cgi-bin/trap_two_seq_form.cgi) was applied to compute the binding affinity scores of their cognate TFs in the context of reference and mutant sequences of TFBSs. The alternative bioinformatics model used in this study was regulatory analysis of variation in enhancers (RAVEN; http://www.cisreg.ca/cgi-bin/RAVEN/a). The bioinformatics outputs of our study were compared with experimental data, electrophoretic mobility shift assay (EMSA).

RESULTS

In 6 out of 18 TFBSs in the following genes COL1A1, Hb ḉᴪ, TF, FIX, MBL2, NOS2A, the outputs of sTRAP were inconsistent with the results of EMSA. Furthermore, no p value of the difference between the two scores of binding affinity under the wild and mutant conditions of TFBSs was presented. Nor, were any criteria for preference or selection of any of the measurements of different matrices used for the same analysis.

CONCLUSION

Our preliminary study indicated some paradoxical results between sTRAP and experimental data. However, to link the data of sTRAP to the biological functions, its optimization via experimental procedures with the integration of expanded data and applying several other bioinformatics tools might be required.

The NGS technology for the identification of genes associated with the ALS. A systematic review

BACKGROUND

More than 30 causative genes have been identified in familial and sporadic amyotrophic lateral sclerosis (ALS). The next-generation sequencing (NGS) is a powerful and groundbreaking tool to identify disease-associated variants. Despite documented advantages of NGS, its diagnostic reliability needs to be addressed in order to use this technology for specific routine diagnosis.

MATERIAL AND METHODS

Literature database was explored to identify studies comparing NGS and Sanger sequencing for the detection of variants causing ALS. We collected data about patients' characteristics, disease type and duration, NGS and Sanger properties.

RESULTS

More than 200 bibliographic references were identified, of which only 14 studies matching our inclusion criteria. Only 2 out of 14 studies compared results of NGS analysis with the Sanger sequencing. Twelve studies screened causative genes associated to ALS using NGS technologies and confirmed the identified variants with Sanger sequencing. Overall, data about more 2,000 patients were analysed. The number of genes that were investigated in each study ranged from 1 to 32, the most frequent being FUS, OPTN, SETX and VCP. NGS identified already known mutations in 21 genes, and new or rare variants in 27 genes.

CONCLUSIONS

NGS seems to be a promising tool for the diagnosis of ALS in routine clinical practice. Its advantages are represented by an increased speed and a lowest sequencing cost, but patients' counselling could be problematic due to the discovery of frequent variants of unknown significance.

Secuenciación de nueva generación (NGS) de ADN: presente y futuro en la práctica clínica

Introducción: el término secuenciación de nueva generación (NGS) hace referencia a las tecnologías diseñadas para analizar gran cantidad de ADN de forma masiva y paralela. Abordamos en esta revisión los conceptos básicos de estas tecnologías, las consideraciones de su uso clínico actual y perspectivas a futuro. Desarrollo: las pruebas basadas en NGS han revolucionado el estudio de los genomas pues permiten la lectura de millones de secuencias de ADN de forma masiva y paralela en un menor lapso de tiempo y a menor costo por base. Estas pruebas incluyen la secuenciación de panel de genes, la secuenciación completa del exoma y la secuenciación completa del genoma. El análisis de sus resultados es complejo y requiere de un proceso bioinformático y clínico exhaustivo para su adecuada interpretación. Las limitaciones de las pruebas NGS incluyen aspectos técnicos como la cobertura, profundidad y longitud de las secuencias, las cuales se pueden solventar implementando buenas prácticas de laboratorio. Conclusiones: las pruebas basadas en la secuenciación por NGS son herramientas diagnósticas que deben partir de una aproximación clínica adecuada para su uso razonado, correcta interpretación y toma de decisiones acertadas. Es de gran trascendencia que los médicos tengan la información básica para poder solicitar e interpretar estas pruebas dada su relevancia clínica actual.

Genetic Predisposition to Breast and Ovarian Cancers: How Many and Which Genes to Test?

Breast and ovarian cancers are some of the most common tumors in females, and the genetic predisposition is emerging as one of the key risk factors in the development of these two malignancies. BRCA1 and BRCA2 are the best-known genes associated with hereditary breast and ovarian cancer. However, recent advances in molecular techniques, Next-Generation Sequencing in particular, have led to the identification of many new genes involved in the predisposition to breast and/or ovarian cancer, with different penetrance estimates. TP53, PTEN, STK11, and CDH1 have been identified as high penetrance genes for the risk of breast/ovarian cancers. Besides them, PALB2, BRIP1, ATM, CHEK2, BARD1, NBN, NF1, RAD51C, RAD51D and mismatch repair genes have been recognized as moderate and low penetrance genes, along with other genes encoding proteins involved in the same pathways, possibly associated with breast/ovarian cancer risk. In this review, we summarize the past and more recent findings in the field of cancer predisposition genes, with insights into the role of the encoded proteins and the associated genetic disorders. Furthermore, we discuss the possible clinical utility of genetic testing in terms of prevention protocols and therapeutic approaches.

Diagnostic and Clinical Utility of Clinical Exome Sequencing in Children With Moderate and Severe Global Developmental Delay / Intellectual Disability

Clinical exome sequencing is currently being used in diagnostics of various genetic disorders, but studies supporting its application in clinical setting are scarce. The aim of this study was to establish diagnostic and clinical utility of clinical exome sequencing in patients with moderate and severe global developmental delay/intellectual disability. Clinical diagnosis was made in 49 of 88 investigated patients, with overall diagnostic yield of 55.7%. Molecular findings are characterized in detail, including the impact of newly made diagnosis on clinical management. Several previously unreported genotype-phenotype correlations and 33 novel variants are described. Genetic and clinical data were shared through publicly available database. In conclusion, clinical exome sequencing allows identification of causative variants in a significant proportion of patients in investigated clinical subgroup. Compared to whole exome sequencing, it shows similar diagnostic and clinical utility with reduced costs, which could be of particular importance for institutions with limited resources.

FDA oversight of NSIGHT genomic research: the need for an integrated systems approach to regulation

The National Institutes of Health (NIH) funded the Newborn Sequencing In Genomic medicine and public HealTh (NSIGHT) Consortium to investigate the implications, challenges, and opportunities associated with the possible use of genomic sequence information in the newborn period. Following announcement of the NSIGHT awardees in 2013, the Food and Drug Administration (FDA) contacted investigators and requested that pre-submissions to investigational device exemptions (IDE) be submitted for the use of genomic sequencing under Title 21 of the Code of Federal Regulations (21 CFR) part 812. IDE regulation permits clinical investigation of medical devices that have not been approved by the FDA. To our knowledge, this marked the first time the FDA determined that NIH-funded clinical genomic research projects are subject to IDE regulation. Here, we review the history of and rationale behind FDA oversight of clinical research and the NSIGHT Consortium's experiences in navigating the IDE process. Overall, NSIGHT investigators found that FDA's application of existing IDE regulations and medical device definitions aligned imprecisely with the aims of publicly funded exploratory clinical research protocols. IDE risk assessments by the FDA were similar to, but distinct from, protocol risk assessments conducted by local Institutional Review Boards (IRBs), and had the potential to reflect novel oversight of emerging genomic technologies. However, the pre-IDE and IDE process delayed the start of NSIGHT research studies by an average of 10 months, and significantly limited the scope of investigation in two of the four NIH approved projects. Based on the experience of the NSIGHT Consortium, we conclude that policies and practices governing the development and use of novel genomic technologies in clinical research urgently need clarification in order to mitigate potentially conflicting or redundant oversight by IRBs, NIH, FDA, and state authorities.

A diagnostic ceiling for exome sequencing in cerebellar ataxia and related neurological disorders

Genetic ataxias are associated with mutations in hundreds of genes with high phenotypic overlap complicating the clinical diagnosis. Whole-exome sequencing (WES) has increased the overall diagnostic rate considerably. However, the upper limit of this method remains ill-defined, hindering efforts to address the remaining diagnostic gap. To further assess the role of rare coding variation in ataxic disorders, we reanalyzed our previously published exome cohort of 76 predominantly adult and sporadic-onset patients, expanded the total number of cases to 260, and introduced analyses for copy number variation and repeat expansion in a representative subset. For new cases (n = 184), our resulting clinically relevant detection rate remained stable at 47% with 24% classified as pathogenic. Reanalysis of the previously sequenced 76 patients modestly improved the pathogenic rate by 7%. For the combined cohort (n = 260), the total observed clinical detection rate was 52% with 25% classified as pathogenic. Published studies of similar neurological phenotypes report comparable rates. This consistency across multiple cohorts suggests that, despite continued technical and analytical advancements, an approximately 50% diagnostic rate marks a relative ceiling for current WES-based methods and a more comprehensive genome-wide assessment is needed to identify the missing causative genetic etiologies for cerebellar ataxia and related neurodegenerative diseases.

Misannotation of multiple-nucleotide variants risks misdiagnosis

Multiple Nucleotide Variants (MNVs) are miscalled by the most widely utilised next generation sequencing analysis (NGS) pipelines, presenting the potential for missing diagnoses that would previously have been made by standard Sanger (dideoxy) sequencing. These variants, which should be treated as a single insertion-deletion mutation event, are commonly called as separate single nucleotide variants. This can result in misannotation, incorrect amino acid predictions and potentially false positive and false negative diagnostic results. This risk will be increased as confirmatory Sanger sequencing of Single Nucleotide variants (SNVs) ceases to be standard practice. Using simulated data and re-analysis of sequencing data from a diagnostic targeted gene panel, we demonstrate that the widely adopted pipeline, GATK best practices, results in miscalling of MNVs and that alternative tools can call these variants correctly. The adoption of calling methods that annotate MNVs correctly would present a solution for individual laboratories, however GATK best practices are the basis for important public resources such as the gnomAD database. We suggest integrating a solution into these guidelines would be the optimal approach.

Genomic testing in pediatric epilepsy

Genomic testing has become routine in the diagnosis and management of pediatric patients with epilepsy. In a single test, hundreds to thousands of genes are examined for DNA changes that may not only explain the etiology of the patient's condition but may also inform management and seizure control. Clinical genomic testing has been in clinical practice for less than a decade, and because of this short period of time, the appropriate clinical use and interpretation of genomic testing is still evolving. Compared to the previous era of single-gene testing in epilepsy, which yielded a diagnosis in <5% of cases, many clinical genomic studies of epilepsy have demonstrated a clinically significant diagnosis in 30% or more of patients tested. This review will examine key studies of the past decade and indicate the clinical scenarios in which genomic testing should be considered standard of care.

A comprehensive assessment of Next-Generation Sequencing variants validation using a secondary technology

BACKGROUND

Recently, increasing innovations improved the accuracy of next generation sequencing (NGS) data. However, the validation of all NGS variants increased the cost and turn-around time of clinical diagnosis, and therefore limited the further development of clinical applications. We aimed to comprehensively assess the necessity of validating NGS variants.

METHODS

Validation data of 7,601 NGS variants involving 1,045 genes were collected from 5,190 clinical samples and sequenced by one of five targeted capture panels and two NGS chemistries, respectively. These genes and variants were widely distributed in 24 human chromosomes and mitochondrial genome. Variants validation was firstly processed by Sanger sequencing. If validation results were unavailable or inconsistent with NGS calls, another validation test would be performed by mass spectrometry genotyping.

RESULTS

A total of 6,939 high quality NGS variants with ≥35 × depth coverage and ≥35% heterozygous ratio were 100% confirmed by a secondary methodology. 5,775 heterozygous variants were separated from 760 homozygous variants and 404 hemizygous variants by 80% heterozygous ratio. A total of 1.5% (98/6,939) of NGS variants were validated by mass spectrometry genotyping.

CONCLUSION

Considering of the above comprehensive assessment, a new variant with high quality from a well-validated capture-based NGS workflow can be reported directly without validation.

Multi-gene testing in neurological disorders showed an improved diagnostic yield: data from over 1000 Indian patients

BACKGROUND

Neurological disorders are clinically heterogeneous group of disorders and are major causes of disability and death. Several of these disorders are caused due to genetic aberration. A precise and confirmatory diagnosis in the patients in a timely manner is essential for appropriate therapeutic and management strategies. Due to the complexity of the clinical presentations across various neurological disorders, arriving at an accurate diagnosis remains a challenge.

METHODS

We sequenced 1012 unrelated patients from India with suspected neurological disorders, using TruSight One panel. Genetic variations were identified using the Strand NGS software and interpreted using the StrandOmics platform.

RESULTS

We were able to detect mutations in 197 genes in 405 (40%) cases and 178 mutations were novel. The highest diagnostic rate was observed among patients with muscular dystrophy (64%) followed by leukodystrophy and ataxia (43%, each). In our cohort, 26% of the patients who received definitive diagnosis were primarily referred with complex neurological phenotypes with no suggestive diagnosis. In terms of mutations types, 62.8% were truncating and in addition, 13.4% were structural variants, which are also likely to cause loss of function.

CONCLUSION

In our study, we observed an improved performance of multi-gene panel testing, with an overall diagnostic yield of 40%. Furthermore, we show that NGS (next-generation sequencing)-based testing is comprehensive and can detect all types of variants including structural variants. It can be considered as a single-platform genetic test for neurological disorders that can provide a swift and definitive diagnosis in a cost-effective manner.

On the critical evaluation and confirmation of germline sequence variants identified using massively parallel sequencing

Although massively parallel sequencing (MPS) is becoming common practice in both research and routine clinical care, confirmation requirements of identified DNA variants using alternative methods are still topics of debate. When evaluating variants directly from MPS data, different read depth statistics, together with specialized genotype quality scores are, therefore, of high relevance. Here we report results of our validation study performed in two different ways: 1) confirmation of MPS identified variants using Sanger sequencing; and 2) simultaneous Sanger and MPS analysis of exons of selected genes. Detailed examination of false-positive and false-negative findings revealed typical error sources connected to low read depth/coverage, incomplete reference genome, indel realignment problems, as well as microsatellite associated amplification errors leading to base miss-calling. However, all these error types were identifiable with thorough manual revision of aligned reads according to specific patterns of distributions of variants and their corresponding reads. Moreover, our results point to dependence of both basic quantitative metrics (such as total read counts, alternative allele read counts and allelic balance) together with specific genotype quality scores on the used bioinformatics pipeline, stressing thus the need for establishing of specific thresholds for these metrics in each laboratory and for each involved pipeline independently.

A Rigorous Interlaboratory Examination of the Need to Confirm Next-Generation Sequencing-Detected Variants with an Orthogonal Method in Clinical Genetic Testing

Orthogonal confirmation of next-generation sequencing (NGS)-detected germline variants is standard practice, although published studies have suggested that confirmation of the highest-quality calls may not always be necessary. The key question is how laboratories can establish criteria that consistently identify those NGS calls that require confirmation. Most prior studies addressing this question have had limitations: they have been generally of small scale, omitted statistical justification, and explored limited aspects of underlying data. The rigorous definition of criteria that separate high-accuracy NGS calls from those that may or may not be true remains a crucial issue. We analyzed five reference samples and over 80,000 patient specimens from two laboratories. Quality metrics were examined for approximately 200,000 NGS calls with orthogonal data, including 1662 false positives. A classification algorithm used these data to identify a battery of criteria that flag 100% of false positives as requiring confirmation (CI lower bound, 98.5% to 99.8%, depending on variant type) while minimizing the number of flagged true positives. These criteria identify false positives that the previously published criteria miss. Sampling analysis showed that smaller data sets resulted in less effective criteria. Our methodology for determining test- and laboratory-specific criteria can be generalized into a practical approach that can be used by laboratories to reduce the cost and time burdens of confirmation without affecting clinical accuracy.

Genetic Diagnostic Testing for Inherited Cardiomyopathies: Considerations for Offering Multi-Gene Tests in a Health Care Setting

Inherited cardiomyopathies (ICs) are a major cause of heart disease. Given their marked clinical and genetic heterogeneity, the content and clinical utility of IC multi-gene panels has been the topic of continuous debate. Our genetics diagnostic laboratory has been providing clinical diagnostic testing for ICs since 2012. We began by testing nine genes and expanded our panel by fivefold in 2015. Here, we describe the implementation of a cost-effective next-generation sequencing (NGS)-based assay for testing of IC genes, including a protocol that minimizes the amount of Sanger sequencing required to confirm variants identified by NGS, which reduces the cost and time of testing. The NGS assay was developed for the simultaneous analysis of 45 IC genes and was assessed for the impact of panel expansion on variant detection, turnaround time, and cost of testing in a cohort of 993 patients. The assay led to a considerable reduction in test cost and turnaround time. However, only a marginal increase was observed in the diagnostic yield, whereas the rate of inconclusive findings increased considerably. These findings suggest that the ongoing evaluation of gene content and monitoring of clinical utility for multi-gene tests are essential to achieve maximum clinical utility of multi-gene tests in a publicly funded health care setting.

Genome-wide sequencing in acutely ill infants: genomic medicine's critical application?

Diagnostic genome-wide sequencing (exome or genome sequencing and data analysis for high-penetrance disease-causing variants) in acutely ill infants appears to be clinically useful, but the value of this diagnostic test should be rigorously demonstrated before it is accepted as a standard of care. This white paper was developed by the Paediatric Task Team of the Global Alliance for Genomics and Health's Regulatory and Ethics Work Stream to address the question of how we can determine the clinical value of genome-wide sequencing in infants in an intensive care setting. After reviewing available clinical and ethics literature on this question, we conclude that evaluating diagnostic genome-wide sequencing as a comprehensive scan for major genetic disease (rather than as a large panel of single-gene tests) provides a practical approach to assessing its clinical value in acutely ill infants. Comparing the clinical value of diagnostic genome-wide sequencing to chromosomal microarray analysis, the current evidence-based standard of care, per case of serious genetic disease diagnosed provides a practical means of assessing clinical value. Scientifically rigorous studies of this kind are needed to determine if clinical genome-wide sequencing should be established as a standard of care supported by healthcare systems and insurers for diagnosis of genetic disease in seriously ill newborn infants.

Glucocorticoid resistance syndrome caused by a novel NR3C1 point mutation

Glucocorticoid resistance syndrome (GRS) is a rare genetic disorder caused by inactivating mutations of the NR3C1 gene which encodes the glucocorticoid receptor. The phenotypic spectrum is broad but typically include symptoms of adrenal insufficiency, mineralocorticoid excess and hyperandrogenism. We report a new case associated with a novel NR3C1 mutation. A 55-year-old woman with lifelong history of low body weight, hyperandrogenism and anxiety was seen at the endocrine clinic after left adrenalectomy and salpingoophorectomy for lesions suspicious of ovarian cancer and adrenal metastasis. The tumors turned out to be a 3.5 cm benign ovarian serous adenofibroma and a 3.5 cm multinodular adrenal mass. She complained of worsened fatigue and inability to recover weight lost with surgery. Pre-operative serum and urinary cortisol were elevated, but she had no stigma of Cushing's syndrome. Plasma ACTH was elevated and a 1-mcg cosyntropin stimulation test was normal. Her fatigue persisted over ensuing years and ACTH-dependent hypercortisolemia remained stable. Low dose oral dexamethasone failed to suppress endogenous cortisol. A pituitary MRI was normal but revealed incidental brain aneurysms. Bone densitometry showed profound osteoporosis. On the bases of this contradictory clinical picture, glucocorticoid resistance syndrome (GRS) was suspected. Using next generation sequencing technology, a novel heterozygous pathogenic variant in the NR3C1 gene was detected. We speculate that vascular malformations and profound osteoporosis, findings associated to cortisol excess, reflect in our patient a variable tissue sensitivity to glucocorticoids. In conclusion, in patients with clinically unexpected ACTH-dependent hypercortisolemia, primary glucocorticoid resistance (GRS) should be considered.

Variant in human POFUT1 reduces enzymatic activity and likely causes a recessive microcephaly, global developmental delay with cardiac and vascular features

Protein O-fucosyltransferase-1 (POFUT1) adds O-fucose monosaccharides to epidermal growth factor-like (EGF) repeats found on approximately 100 mammalian proteins, including Notch receptors. Haploinsufficiency of POFUT1 has been linked to adult-onset Dowling Degos Disease (DDD) with hyperpigmentation defects. Homozygous deletion of mouse Pofut1 results in embryonic lethality with severe Notch-like phenotypes including defects in somitogenesis, cardiogenesis, vasculogenesis and neurogenesis, but the extent to which POFUT1 is required for normal human development is not yet understood. Here we report a patient with a congenital syndrome consisting of severe global developmental delay, microcephaly, heart defects, failure to thrive and liver disease with a previously unreported homozygous NM_015352.1: c.485C>T variant (p.Ser162Leu) in POFUT1 detected by exome sequencing. Both parents are heterozygotes and neither manifests any signs of DDD. No other detected variant explained the phenotype. This variant eliminated a conserved N-glycosylation sequon at Asn160 in POFUT1 and profoundly decreased POFUT1 activity in patient fibroblasts compared to control fibroblasts. Purified p.Ser162Leu mutant protein also showed much lower POFUT1 activity with a lower affinity for EGF acceptor substrate than wild type POFUT1. Eliminating the N-glycan sequon by replacing Asn160 with Gln had little effect on POFUT1 activity, suggesting that loss of the glycan is not responsible for the defect. Furthermore, the p.Ser162Leu mutant showed weaker ability to rescue Notch activity in cell-based assays. These results suggest that this N-glycan of POFUT1 is not required for its proper enzymatic function, and that the p.Ser162Leu mutation of POFUT1 likely causes global developmental delay, microcephaly with vascular and cardiac defects.

Validating Comprehensive Next-Generation Sequencing Results for Precision Oncology: The NCT/DKTK Molecularly Aided Stratification for Tumor Eradication Research Experience

Purpose

Rapidly evolving genomics technologies, in particular comprehensive next-generation sequencing (NGS), have led to exponential growth in the understanding of cancer biology, shifting oncology toward personalized treatment strategies. However, comprehensive NGS approaches, such as whole-exome sequencing, have limitations that are related to the technology itself as well as to the input source. Hence, clinical implementation of comprehensive NGS in a quality-controlled diagnostic workflow requires both the standardization of sequencing procedures and continuous validation of sequencing results by orthogonal methods in an ongoing program to enable the determination of key test parameters and continuous improvement of NGS and bioinformatics pipelines.

Patients and Methods

We present validation data on 220 patients who were enrolled between 2013 and 2016 in a multi-institutional, genomics-guided precision oncology program (Molecularly Aided Stratification for Tumor Eradication Research) of the National Center for Tumor Diseases Heidelberg and the German Cancer Consortium.

Results

More than 90% of clinically actionable genomic alterations identified by combined whole-exome sequencing and transcriptome sequencing were successfully validated, with varying frequencies of discordant results across different types of alterations (fusions, 3.7%; single-nucleotide variants, 2.6%; amplifications, 1.1%; overexpression, 0.9%; deletions, 0.6%). The implementation of new computational methods for NGS data analysis led to a substantial improvement of gene fusion calling over time.

Conclusion

Collectively, these data demonstrate the value of a rigorous validation program that partners with comprehensive NGS to successfully implement and continuously improve cancer precision medicine in a clinical setting.

Validation of differentially methylated microRNAs identified from an epigenome-wide association study; Sanger and next generation sequencing approaches

Objectives

Altered DNA methylation and microRNA profiles are associated with diabetic kidney disease. This study compared different sequencing approaches to define the genetic and epigenetic architecture of sequences surrounding microRNAs associated with diabetic kidney disease.

Results

We compared Sanger and next generation sequencing to validate microRNAs associated with diabetic kidney disease identified from an epigenome-wide association study (EWAS). These microRNAs demonstrated differential methylation levels in cases with diabetic kidney disease compared to controls with long duration of type 1 diabetes and no evidence of kidney disease (P_adjusted < 10⁻⁵). Targeted next generation sequencing analysis of genomic DNA and matched cell-line transformed DNA samples identified four genomic variants within the microRNAs, two within miR-329-2 and two within miR-429. Sanger sequencing of genomic DNA replicated these findings and confirmed the altered methylation status of the CpG sites identified by the EWAS in bisulphite-treated DNA. This investigation successfully fine-mapped the genetic sequence around key microRNAs. Variants have been detected which may affect their methylation status and methylated CpG sites have been confirmed. Additionally, we explored both the fidelity of next generation sequencing analysis and the potential efficacy of cell-line transformed DNA samples in place of finite patient samples in discovery genetic and epigenetic research.

Electronic supplementary material

The online version of this article (10.1186/s13104-018-3872-x) contains supplementary material, which is available to authorized users.

SwissMTB: establishing comprehensive molecular cancer diagnostics in Swiss clinics

Background

Molecular precision oncology is an emerging practice to improve cancer therapy by decreasing the risk of choosing treatments that lack efficacy or cause adverse events. However, the challenges of integrating molecular profiling into routine clinical care are manifold. From a computational perspective these include the importance of a short analysis turnaround time, the interpretation of complex drug-gene and gene-gene interactions, and the necessity of standardized high-quality workflows. In addition, difficulties faced when integrating molecular diagnostics into clinical practice are ethical concerns, legal requirements, and limited availability of treatment options beyond standard of care as well as the overall lack of awareness of their existence.

Methods

To the best of our knowledge, we are the first group in Switzerland that established a workflow for personalized diagnostics based on comprehensive high-throughput sequencing of tumors at the clinic. Our workflow, named SwissMTB (Swiss Molecular Tumor Board), links genetic tumor alterations and gene expression to therapeutic options and clinical trial opportunities. The resulting treatment recommendations are summarized in a clinical report and discussed in a molecular tumor board at the clinic to support therapy decisions.

Results

Here we present results from an observational pilot study including 22 late-stage cancer patients. In this study we were able to identify actionable variants and corresponding therapies for 19 patients. Half of the patients were analyzed retrospectively. In two patients we identified resistance-associated variants explaining lack of therapy response. For five out of eleven patients analyzed before treatment the SwissMTB diagnostic influenced treatment decision.

Conclusions

SwissMTB enables the analysis and clinical interpretation of large numbers of potentially actionable molecular targets. Thus, our workflow paves the way towards a more frequent use of comprehensive molecular diagnostics in Swiss hospitals.

Electronic supplementary material

The online version of this article (10.1186/s12911-018-0680-0) contains supplementary material, which is available to authorized users.

1 in 38 individuals at risk of a dominant medically actionable disease

Clinical genomic sequencing can identify pathogenic variants unrelated to the initial clinical question, but of medical relevance to the patients and their families. With ongoing discussions on the utility of disclosing or searching for such variants, it is of crucial importance to obtain unbiased insight in the prevalence of these incidental or secondary findings, in order to better weigh potential risks and benefits. Previous studies have reported a broad range of secondary findings ranging from 1 to 9%, merely attributable to differences in study design, cohorts tested, sequence technology used and genes analyzed. Here, we analyzed WES data of 1640 anonymized healthy Dutch individuals to establish the frequency of medically actionable disease alleles in an outbred population of European descent. Our study shows that 1 in 38 healthy individuals (2.7%) has a (likely) pathogenic variant in one of 59 medically actionable dominant disease genes for which the American College of Medical Genetics and Genomics (ACMG) recommends disclosure. Additionally, we identified 36 individuals (2.2%) to be a carrier of a recessive pathogenic disease allele. Whereas these frequencies of secondary findings are in line with what has been reported in the East-Asian population, the pathogenic variants are differently distributed across the 59 ACMG genes. Our results contribute to the debate on genetic risk factor screening in healthy individuals and the discussion whether the potential benefits of this knowledge and related preventive options, outweigh the risk of the emotional impact of the test result and possible stigmatization.

Valection: design optimization for validation and verification studies

Background

Platform-specific error profiles necessitate confirmatory studies where predictions made on data generated using one technology are additionally verified by processing the same samples on an orthogonal technology. However, verifying all predictions can be costly and redundant, and testing a subset of findings is often used to estimate the true error profile.

Results

To determine how to create subsets of predictions for validation that maximize accuracy of global error profile inference, we developed Valection, a software program that implements multiple strategies for the selection of verification candidates. We evaluated these selection strategies on one simulated and two experimental datasets.

Conclusions

Valection is implemented in multiple programming languages, available at: http://labs.oicr.on.ca/boutros-lab/software/valection

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2391-z) contains supplementary material, which is available to authorized users.

Cost Analyses of Genomic Sequencing: Lessons Learned from the MedSeq Project

OBJECTIVE

To summarize lessons learned while analyzing the costs of integrating whole genome sequencing into the care of cardiology and primary care patients in the MedSeq Project by conducting the first randomized controlled trial of whole genome sequencing in general and specialty medicine.

METHODS

Case study that describes key methodological and data challenges that were encountered or are likely to emerge in future work, describes the pros and cons of approaches considered by the study team, and summarizes the solutions that were implemented.

RESULTS

Major methodological challenges included defining whole genome sequencing, structuring an appropriate comparator, measuring downstream costs, and examining clinical outcomes. Discussions about solutions addressed conceptual and practical issues that arose because of definitions and analyses around the cost of genomic sequencing in trial-based studies.

CONCLUSIONS

The MedSeq Project provides an instructive example of how to conduct a cost analysis of whole genome sequencing that feasibly incorporates best practices while being sensitive to the varied applications and diversity of results it may produce. Findings provide guidance for researchers to consider when conducting or analyzing economic analyses of whole genome sequencing and other next-generation sequencing tests, particularly regarding costs.

Development of an evidence-based algorithm that optimizes sensitivity and specificity in ES-based diagnostics of a clinically heterogeneous patient population

Purpose

Next-generation sequencing (NGS) is rapidly replacing Sanger sequencing in genetic diagnostics. Sensitivity and specificity of NGS approaches are not well-defined, but can be estimated from applying NGS and Sanger sequencing in parallel. Utilizing this strategy, we aimed at optimizing exome sequencing (ES)–based diagnostics of a clinically diverse patient population.

Methods

Consecutive DNA samples from unrelated patients with suspected genetic disease were exome-sequenced; comparatively nonstringent criteria were applied in variant calling. One thousand forty-eight variants in genes compatible with the clinical diagnosis were followed up by Sanger sequencing. Based on a set of variant-specific features, predictors for true positives and true negatives were developed.

Results

Sanger sequencing confirmed 81.9% of ES-derived variants. Calls from the lower end of stringency accounted for the majority of the false positives, but also contained ~5% of the true positives. A predictor incorporating three variant-specific features classified 91.7% of variants with 100% specificity and 99.75% sensitivity. Confirmation status of the remaining variants (8.3%) was not predictable.

Conclusions

Criteria for variant calling in ES-based diagnostics impact on specificity and sensitivity. Confirmatory sequencing for a proportion of variants, therefore, remains a necessity. Our study exemplifies how these variants can be defined on an empirical basis.