Comparison of the performance of two targeted metagenomic virus capture probe-based methods using reference control materials and clinical samples.

Viral enrichment by probe hybridization has been reported to significantly increase the sensitivity of viral metagenomics. This study compares the analytical performance of two targeted metagenomic virus capture probe-based methods: (i) SeqCap EZ HyperCap by Roche (ViroCap) and (ii) Twist Comprehensive Viral Research Panel workflow, for diagnostic use. Sensitivity, specificity, and limit of detection were analyzed using 25 synthetic viral sequences spiked in increasing proportions of human background DNA, eight clinical samples, and American Type Culture Collection (ATCC) Virome Virus Mix. Sensitivity and specificity were 95% and higher for both methods using the synthetic and reference controls as gold standard. Combining thresholds for viral sequence read counts and genome coverage [respectively 500 reads per million (RPM) and 10% coverage] resulted in optimal prediction of true positive results. Limits of detection were approximately 50-500 copies/mL for both methods as determined by ddPCR. Increasing proportions of spike-in cell-free human background sequences up to 99.999% (50 ng/mL) did not negatively affect viral detection, suggesting effective capture of viral sequences. These data show analytical performances in ranges applicable to clinical samples, for both probe hybridization metagenomic approaches. This study supports further steps toward more widespread use of viral metagenomics for pathogen detection, in clinical and surveillance settings using low biomass samples. IMPORTANCE: Viral metagenomics has been gradually applied for broad-spectrum pathogen detection of infectious diseases, surveillance of emerging diseases, and pathogen discovery. Viral enrichment by probe hybridization methods has been reported to significantly increase the sensitivity of viral metagenomics. During the past years, a specific hybridization panel distributed by Roche has been adopted in a broad range of different clinical and zoonotic settings. Recently, Twist Bioscience has released a new hybridization panel targeting human and animal viruses. This is the first report comparing the performance of viral metagenomic hybridization panels.

No Remdesivir Resistance Observed in the Phase 3 Severe and Moderate COVID-19 SIMPLE Trials.

Remdesivir (RDV) is a broad-spectrum nucleotide analog prodrug approved for the treatment of COVID-19 in hospitalized and non-hospitalized patients with clinical benefit demonstrated in multiple Phase 3 trials. Here we present SARS-CoV-2 resistance analyses from the Phase 3 SIMPLE clinical studies evaluating RDV in hospitalized participants with severe or moderate COVID-19 disease. The severe and moderate studies enrolled participants with radiologic evidence of pneumonia and a room-air oxygen saturation of ≤94% or >94%, respectively. Virology sample collection was optional in the study protocols. Sequencing and related viral load data were obtained retrospectively from participants at a subset of study sites with local sequencing capabilities (10 of 183 sites) at timepoints with detectable viral load. Among participants with both baseline and post-baseline sequencing data treated with RDV, emergent Nsp12 substitutions were observed in 4 of 19 (21%) participants in the severe study and none of the 2 participants in the moderate study. The following 5 substitutions emerged: T76I, A526V, A554V, E665K, and C697F. The substitutions T76I, A526V, A554V, and C697F had an EC50 fold change of ≤1.5 relative to the wildtype reference using a SARS-CoV-2 subgenomic replicon system, indicating no significant change in the susceptibility to RDV. The phenotyping of E665K could not be determined due to a lack of replication. These data reveal no evidence of relevant resistance emergence and further confirm the established efficacy profile of RDV with a high resistance barrier in COVID-19 patients.

A comparison of five Illumina, Ion Torrent, and nanopore sequencing technology-based approaches for whole genome sequencing of SARS-CoV-2.

Rapid identification of the rise and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern remains critical for monitoring of the efficacy of diagnostics, therapeutics, vaccines, and control strategies. A wide range of SARS-CoV-2 next-generation sequencing (NGS) methods have been developed over the last years, but cross-sequence technology benchmarking studies have been scarce. In the current study, 26 clinical samples were sequenced using five protocols: AmpliSeq SARS-CoV-2 (Illumina), EasySeq RC-PCR SARS-CoV-2 (Illumina/NimaGen), Ion AmpliSeq SARS-CoV-2 (Thermo Fisher), custom primer sets (Oxford Nanopore Technologies (ONT)), and capture probe-based viral metagenomics (Roche/Illumina). Studied parameters included genome coverage, depth of coverage, amplicon distribution, and variant calling. The median SARS-CoV-2 genome coverage of samples with cycle threshold (Ct) values of 30 and lower ranged from 81.6 to 99.8% for, respectively, the ONT protocol and Illumina AmpliSeq protocol. Correlation of coverage with PCR Ct values varied per protocol. Amplicon distribution signatures differed across the methods, with peak differences of up to 4 log10 at disbalanced positions in samples with high viral loads (Ct values ≤ 23). Phylogenetic analyses of consensus sequences showed clustering independent of the workflow used. The proportion of SARS-CoV-2 reads in relation to background sequences, as a (cost-)efficiency metric, was the highest for the EasySeq protocol. The hands-on time was the lowest when using EasySeq and ONT protocols, with the latter additionally having the shortest sequence runtime. In conclusion, the studied protocols differed on a variety of the studied metrics. This study provides data that assist laboratories when selecting protocols for their specific setting.

Performance of Five Metagenomic Classifiers for Virus Pathogen Detection Using Respiratory Samples from a Clinical Cohort.

Viral metagenomics is increasingly applied in clinical diagnostic settings for detection of pathogenic viruses. While several benchmarking studies have been published on the use of metagenomic classifiers for abundance and diversity profiling of bacterial populations, studies on the comparative performance of the classifiers for virus pathogen detection are scarce. In this study, metagenomic data sets (n = 88) from a clinical cohort of patients with respiratory complaints were used for comparison of the performance of five taxonomic classifiers: Centrifuge, Clark, Kaiju, Kraken2, and Genome Detective. A total of 1144 positive and negative PCR results for a total of 13 respiratory viruses were used as gold standard. Sensitivity and specificity of these classifiers ranged from 83 to 100% and 90 to 99%, respectively, and was dependent on the classification level and data pre-processing. Exclusion of human reads generally resulted in increased specificity. Normalization of read counts for genome length resulted in a minor effect on overall performance, however it negatively affected the detection of targets with read counts around detection level. Correlation of sequence read counts with PCR Ct-values varied per classifier, data pre-processing (R2 range 15.1-63.4%), and per virus, with outliers up to 3 log10 reads magnitude beyond the predicted read count for viruses with high sequence diversity. In this benchmarking study, sensitivity and specificity were within the ranges of use for diagnostic practice when the cut-off for defining a positive result was considered per classifier.

Longitudinal Monitoring of DNA Viral Loads in Transplant Patients Using Quantitative Metagenomic Next-Generation Sequencing.

INTRODUCTION: Immunocompromised patients are prone to reactivations and (re-)infections of multiple DNA viruses. Viral load monitoring by single-target quantitative PCRs (qPCR) is the current cornerstone for virus quantification. In this study, a metagenomic next-generation sequencing (mNGS) approach was used for the identification and load monitoring of transplantation-related DNA viruses. METHODS: Longitudinal plasma samples from six patients that were qPCR-positive for cytomegalovirus (CMV), Epstein-Barr virus (EBV), BK polyomavirus (BKV), adenovirus (ADV), parvovirus B19 (B19V), and torque teno-virus (TTV) were sequenced using the quantitative metagenomic Galileo Viral Panel Solution (Arc Bio, LLC, Cambridge, MA, USA) reagents and bioinformatics pipeline combination. Qualitative and quantitative performance was analysed with a focus on viral load ranges relevant for clinical decision making. RESULTS: All pathogens identified by qPCR were also identified by mNGS. BKV, CMV, and HHV6B were additionally detected by mNGS, and could be confirmed by qPCR or auxiliary bioinformatic analysis. Viral loads determined by mNGS correlated with the qPCR results, with inter-method differences in viral load per virus ranging from 0.19 log10 IU/mL for EBV to 0.90 log10 copies/mL for ADV. TTV, analysed by mNGS in a semi-quantitative way, demonstrated a mean difference of 3.0 log10 copies/mL. Trends over time in viral load determined by mNGS and qPCR were comparable, and clinical thresholds for initiation of treatment were equally identified by mNGS. CONCLUSIONS: The Galileo Viral Panel for quantitative mNGS performed comparably to qPCR concerning detection and viral load determination, within clinically relevant ranges of patient management algorithms.

Viral metagenomic sequencing in the diagnosis of meningoencephalitis: a review of technical advances and diagnostic yield.

INTRODUCTION: Meningoencephalitis patients are often severely impaired and benefit from early etiological diagnosis, though many cases remain without identified cause. Metagenomics as pathogen agnostic approach can result in additional etiological findings; however, the exact diagnostic yield when used as a secondary test remains unknown. AREAS COVERED: This review aims to highlight recent advances with regard to wet and dry lab methodologies of metagenomic testing and technical milestones that have been achieved. A selection of procedures currently applied in accredited diagnostic laboratories is described in more detail to illustrate best practices. Furthermore, a meta-analysis was performed to assess the additional diagnostic yield utilizing metagenomic sequencing in meningoencephalitis patients. Finally, the remaining challenges for successful widespread implementation of metagenomic sequencing for the diagnosis of meningoencephalitis are addressed in a future perspective. EXPERT OPINION: The last decade has shown major advances in technical possibilities for using mNGS in diagnostic settings including cloud-based analysis. An additional advance may be the current established infrastructure of platforms for bioinformatic analysis of SARS-CoV-2, which may assist to pave the way for global use of clinical metagenomics.

Viral metagenomic sequencing in a cohort of international travellers returning with febrile illness.

BACKGROUND: Diagnosis of infections in returning international travellers can be challenging because of the broad spectrum of potential infectious etiologies potentially involved. Viral metagenomic next-generation sequencing (mNGS) has the potential to detect any virus present in a patient sample and is increasingly being used for difficult to diagnose cases. The aim of this study was to analyze the performance of mNGS for viral pathogen detection in the clinical setting of international travellers returning with febrile illness. METHODS: Thirty-eight serum samples from international travellers returning with febrile illness and presenting at the outpatient clinic of the Leiden University Medical Center in the Netherlands in the time period 2015-2016 were selected retrospectively. Samples were processed for viral metagenomic sequencing using a probe panel capturing all known vertebrate viruses. Bioinformatic analysis was performed using Genome Detective software for metagenomic virus detection. Metagenomic virus findings were compared with viral pathogen detection using conventional methods. RESULTS: In 8 out of the 38 patients (21%), a pathogenic virus was detected by mNGS. All viral pathogens detected by conventional assays were also detected by mNGS: dengue virus (n=4 patients), Epstein-Barr virus (n=2), hepatitis B virus (n=1). In addition, mNGS resulted in additional pathogenic findings in 2 patients (5%): dengue virus (n=1), and hepatitis C virus (n=1). Non-pathogenic viruses detected were: GB virus C (n=1) and torque teno viruses (n=3). High genome coverage and depth using capture probes enabled typing of the dengue viruses detected. CONCLUSIONS: Viral metagenomics has the potential to assist the detection of viral pathogens and co-infections in one step in international travellers with a febrile syndrome. Furthermore, viral enrichment by probes resulted in high genome coverage and depth which enabled dengue virus typing.

Recommendations for the introduction of metagenomic next-generation sequencing in clinical virology, part II: bioinformatic analysis and reporting.

Metagenomic next-generation sequencing (mNGS) is an untargeted technique for determination of microbial DNA/RNA sequences in a variety of sample types from patients with infectious syndromes. mNGS is still in its early stages of broader translation into clinical applications. To further support the development, implementation, optimization and standardization of mNGS procedures for virus diagnostics, the European Society for Clinical Virology (ESCV) Network on Next-Generation Sequencing (ENNGS) has been established. The aim of ENNGS is to bring together professionals involved in mNGS for viral diagnostics to share methodologies and experiences, and to develop application guidelines. Following the ENNGS publication Recommendations for the introduction of mNGS in clinical virology, part I: wet lab procedure in this journal, the current manuscript aims to provide practical recommendations for the bioinformatic analysis of mNGS data and reporting of results to clinicians.

Coronavirus discovery by metagenomic sequencing: a tool for pandemic preparedness.

INTRODUCTION: The SARS-CoV-2 pandemic of 2020 is a prime example of the omnipresent threat of emerging viruses that can infect humans. A protocol for the identification of novel coronaviruses by viral metagenomic sequencing in diagnostic laboratories may contribute to pandemic preparedness. AIM: The aim of this study is to validate a metagenomic virus discovery protocol as a tool for coronavirus pandemic preparedness. METHODS: The performance of a viral metagenomic protocol in a clinical setting for the identification of novel coronaviruses was tested using clinical samples containing SARS-CoV-2, SARS-CoV, and MERS-CoV, in combination with databases generated to contain only viruses of before the discovery dates of these coronaviruses, to mimic virus discovery. RESULTS: Classification of NGS reads using Centrifuge and Genome Detective resulted in assignment of the reads to the closest relatives of the emerging coronaviruses. Low nucleotide and amino acid identity (81% and 84%, respectively, for SARS-CoV-2) in combination with up to 98% genome coverage were indicative for a related, novel coronavirus. Capture probes targeting vertebrate viruses, designed in 2015, enhanced both sequencing depth and coverage of the SARS-CoV-2 genome, the latter increasing from 71% to 98%. CONCLUSION: The model used for simulation of virus discovery enabled validation of the metagenomic sequencing protocol. The metagenomic protocol with virus probes designed before the pandemic, can assist the detection and identification of novel coronaviruses directly in clinical samples.

Improved diagnosis of viral encephalitis in adult and pediatric hematological patients using viral metagenomics.

Metagenomic sequencing is a powerful technique that enables detection of the full spectrum of pathogens present in any specimen in a single test. Hence, metagenomics is increasingly being applied for detection of viruses in clinical cases with suspected infections of unknown etiology and a large number of relevant potential causes. This is typically the case in patients presenting with encephalitis, in particular when immunity is impaired by underlying disorders. In this study, viral metagenomics has been applied to a cohort of hematological patients with encephalitis of unknown origin. Because viral loads in cerebrospinal fluid of patients with encephalitis are generally low, the technical performance of a metagenomic sequencing protocol with viral enrichment by capture probes targeting all known vertebrate viral sequences was studied. Subsequently, the optimized viral metagenomics protocol was applied to a cohort of hematological patients with encephalitis of unknown origin. Viral enrichment by capture probes increased the viral sequence read count of metagenomics on cerebrospinal fluid samples 100 - 10.000 fold, compared to unenriched metagenomic sequencing. In five out of 41 (12%) hematological patients with encephalitis, a virus was detected by viral metagenomics which had not been detected by current routine diagnostics. BK polyomavirus, hepatitis E virus, human herpes virus-6 and Epstein Barr virus were identified by this unbiased metagenomic approach. This study demonstrated that hematological patients with encephalitis of unknown origin may benefit from early viral metagenomics testing as a single step approach.

STROBE-metagenomics: a STROBE extension statement to guide the reporting of metagenomics studies.

The term metagenomics refers to the use of sequencing methods to simultaneously identify genomic material from all organisms present in a sample, with the advantage of greater taxonomic resolution than culture or other methods. Applications include pathogen detection and discovery, species characterisation, antimicrobial resistance detection, virulence profiling, and study of the microbiome and microecological factors affecting health. However, metagenomics involves complex and multistep processes and there are important technical and methodological challenges that require careful consideration to support valid inference. We co-ordinated a multidisciplinary, international expert group to establish reporting guidelines that address specimen processing, nucleic acid extraction, sequencing platforms, bioinformatics considerations, quality assurance, limits of detection, power and sample size, confirmatory testing, causality criteria, cost, and ethical issues. The guidance recognises that metagenomics research requires pragmatism and caution in interpretation, and that this field is rapidly evolving.

Retrospective Validation of a Metagenomic Sequencing Protocol for Combined Detection of RNA and DNA Viruses Using Respiratory Samples from Pediatric Patients.

Viruses are the main cause of respiratory tract infections. Metagenomic next-generation sequencing (mNGS) enables unbiased detection of all potential pathogens. To apply mNGS in viral diagnostics, sensitive and simultaneous detection of RNA and DNA viruses is needed. Herein, were studied the performance of an in-house mNGS protocol for routine diagnostics of viral respiratory infections with potential for automated pan-pathogen detection. The sequencing protocol and bioinformatics analysis were designed and optimized, including exogenous internal controls. Subsequently, the protocol was retrospectively validated using 25 clinical respiratory samples. The developed protocol using Illumina NextSeq 500 sequencing showed high repeatability. Use of the National Center for Biotechnology Information's RefSeq database as opposed to the National Center for Biotechnology Information's nucleotide database led to enhanced specificity of classification of viral pathogens. A correlation was established between read counts and PCR cycle threshold value. Sensitivity of mNGS, compared with PCR, varied up to 83%, with specificity of 94%, dependent on the cutoff for defining positive mNGS results. Viral pathogens only detected by mNGS, not present in the routine diagnostic workflow, were influenza C, KI polyomavirus, cytomegalovirus, and enterovirus. Sensitivity and analytical specificity of this mNGS protocol were comparable to PCR and higher when considering off-PCR target viral pathogens. One single test detected all potential viral pathogens and simultaneously obtained detailed information on detected viruses.

The respiratory virome and exacerbations in patients with chronic obstructive pulmonary disease.

INTRODUCTION: Exacerbations are major contributors to morbidity and mortality in patients with chronic obstructive pulmonary disease (COPD), and respiratory bacterial and viral infections are an important trigger. However, using conventional diagnostic techniques, a causative agent is not always found. Metagenomic next-generation sequencing (mNGS) allows analysis of the complete virome, but has not yet been applied in COPD exacerbations. OBJECTIVES: To study the respiratory virome in nasopharyngeal samples during COPD exacerbations using mNGS. STUDY DESIGN: 88 nasopharyngeal swabs from 63 patients from the Bergen COPD Exacerbation Study (2006-2010) were analysed by mNGS and in-house qPCR for respiratory viruses. Both DNA and RNA were sequenced simultaneously using an Illumina library preparation protocol with in-house adaptations. RESULTS: By mNGS, 24/88 samples tested positive. Sensitivity and specificity, as compared with PCR, were 96% and 98% for diagnostic targets (23/24 and 1093/1120, respectively). Additional viral pathogens detected by mNGS were herpes simplex virus type 1 and coronavirus OC43. A positive correlation was found between Cq value and mNGS viral normalized species reads (log value) (p = 0.002). Patients with viral pathogens had lower percentages of bacteriophages (p<0.001). No correlation was found between viral reads and clinical markers. CONCLUSIONS: The mNGS protocol used was highly sensitive and specific for semi-quantitative detection of respiratory viruses. Excellent negative predictive value implicates the power of mNGS to exclude any pathogenic respiratory viral infectious cause in one test, with consequences for clinical decision making. Reduced abundance of bacteriophages in COPD patients with viral pathogens implicates skewing of the virome during infection, with potential consequences for the bacterial populations, during infection.

Gene Mosaicism Screening Using Single-Molecule Molecular Inversion Probes in Routine Diagnostics for Systemic Autoinflammatory Diseases.

Diagnosis of systemic autoinflammatory diseases (SAIDs) is often difficult to achieve and can delay the start of proper treatments and result in irreversible organ damage. In several patients with dominantly inherited SAID, postzygotic mutations have been detected as the disease-causing gene defects. Mutations with allele frequencies <5% have been detected, even in patients with severe phenotypes. Next-generation sequencing techniques are currently used to detect mutations in SAID-associated genes. However, even if the genomic region is highly covered, this approach is usually not able to distinguish low-grade postzygotic variants from background noise. We, therefore, developed a sensitive deep sequencing assay for mosaicism detection in SAID-associated genes using single-molecule molecular inversion probes. Our results show the accurate detection of postzygotic variants with allele frequencies as low as 1%. The probability of calling mutations with allele frequencies ≥3% exceeds 99.9%. To date, we have detected three patients with mosaicism, two carrying likely pathogenic NLRP3 variants and one carrying a likely pathogenic TNFRSF1A variant with an allele frequency of 1.3%, confirming the relevance of the technology. The assay shown herein is a flexible, robust, fast, cost-effective, and highly reliable method for mosaicism detection; therefore, it is well suited for routine diagnostics.

Assessment of parental mosaicism in SCN1A-related epilepsy by single-molecule molecular inversion probes and next-generation sequencing.

BACKGROUND: Dravet syndrome is a severe genetic encephalopathy, caused by pathogenic variants in SCN1A. Low-grade parental mosaicism occurs in a substantial proportion of families (7%-13%) and has important implications for recurrence risks. However, parental mosaicism can remain undetected by methods regularly used in diagnostics. In this study, we use single-molecule molecular inversion probes (smMIP), a technique with high sensitivity for detecting low-grade mosaic variants and high cost-effectiveness, to investigate the incidence of parental mosaicism of SCN1A variants in a cohort of 90 families and assess the feasibility of this technique. METHODS: Deep sequencing of SCN1A was performed using smMIPs. False positive rates for each of the proband's pathogenic variants were determined in 145 unrelated samples. If parents showed corresponding variant alleles at a significantly higher rate than the established noise ratio, mosaicism was confirmed by droplet digital PCR (ddPCR). RESULTS: Sequence coverage of at least 100× at the location of the corresponding pathogenic variant was reached for 80 parent couples. The variant ratio was significantly higher than the established noise ratio in eight parent couples, of which four (5%) were regarded as true mosaics, based on ddPCR results. The false positive rate of smMIP analysis without ddPCR was therefore 50%. Three of these variants had previously been considered de novo in the proband by Sanger sequencing. CONCLUSION: smMIP technology combined withnext generation sequencing (NGS) performs better than Sanger sequencing in the detection of parental mosaicism. Because parental mosaicism has important implications for genetic counselling and recurrence risks, we stress the importance of implementing high-sensitivity NGS-based assays in standard diagnostics.

New workflow for classification of genetic variants' pathogenicity applied to hereditary recurrent fevers by the International Study Group for Systemic Autoinflammatory Diseases (INSAID).

BACKGROUND: Hereditary recurrent fevers (HRFs) are rare inflammatory diseases sharing similar clinical symptoms and effectively treated with anti-inflammatory biological drugs. Accurate diagnosis of HRF relies heavily on genetic testing. OBJECTIVES: This study aimed to obtain an experts' consensus on the clinical significance of gene variants in four well-known HRF genes: MEFV, TNFRSF1A, NLRP3 and MVK. METHODS: We configured a MOLGENIS web platform to share and analyse pathogenicity classifications of the variants and to manage a consensus-based classification process. Four experts in HRF genetics submitted independent classifications of 858 variants. Classifications were driven to consensus by recruiting four more expert opinions and by targeting discordant classifications in five iterative rounds. RESULTS: Consensus classification was reached for 804/858 variants (94%). None of the unsolved variants (6%) remained with opposite classifications (eg, pathogenic vs benign). New mutational hotspots were found in all genes. We noted a lower pathogenic variant load and a higher fraction of variants with unknown or unsolved clinical significance in the MEFV gene. CONCLUSION: Applying a consensus-driven process on the pathogenicity assessment of experts yielded rapid classification of almost all variants of four HRF genes. The high-throughput database will profoundly assist clinicians and geneticists in the diagnosis of HRFs. The configured MOLGENIS platform and consensus evolution protocol are usable for assembly of other variant pathogenicity databases. The MOLGENIS software is available for reuse at http://github.com/molgenis/molgenis; the specific HRF configuration is available at http://molgenis.org/said/. The HRF pathogenicity classifications will be published on the INFEVERS database at https://fmf.igh.cnrs.fr/ISSAID/infevers/.

Mosaicism of de novo pathogenic SCN1A variants in epilepsy is a frequent phenomenon that correlates with variable phenotypes.

OBJECTIVE: Phenotypes caused by de novo SCN1A pathogenic variants are very variable, ranging from severely affected patients with Dravet syndrome to much milder genetic epilepsy febrile seizures plus cases. The most important determinant of disease severity is the type of variant, with variants that cause a complete loss of function of the SCN1A protein (α-subunit of the neuronal sodium channel Nav1.1) being detected almost exclusively in Dravet syndrome patients. However, even within Dravet syndrome disease severity ranges greatly, and consequently other disease modifiers must exist. A better prediction of disease severity is very much needed in daily practice to improve counseling, stressing the importance of identifying modifying factors in this patient group. We evaluated 128 participants with de novo, pathogenic SCN1A variants to investigate whether mosaicism, caused by postzygotic mutation, is a major modifier in SCN1A-related epilepsy. METHODS: Mosaicism was investigated by reanalysis of the pathogenic SCN1A variants using single molecule molecular inversion probes and next generation sequencing with high coverage. Allelic ratios of pathogenic variants were used to determine whether mosaicism was likely. Selected mosaic variants were confirmed by droplet digital polymerase chain reaction and sequencing of different tissues. Developmental outcome was classified based on available data on intelligence quotient and school functioning/education. RESULTS: Mosaicism was present for 7.5% of de novo pathogenic SCN1A variants in symptomatic patients. Mosaic participants were less severely affected than nonmosaic participants if only participants with truncating variants are considered (distribution of developmental outcome scores, Mann-Whitney U, P = .023). SIGNIFICANCE: Postzygotic mutation is a common phenomenon in SCN1A-related epilepsies. Participants with mosaicism have on average milder phenotypes, suggesting that mosaicism can be a major modifier of SCN1A-related diseases. Detection of mosaicism has important implications for genetic counseling and can be achieved by deep sequencing of unique reads.

Effectiveness of whole-exome sequencing and costs of the traditional diagnostic trajectory in children with intellectual disability.

PURPOSE: This study investigated whole-exome sequencing (WES) yield in a subset of intellectually disabled patients referred to our clinical diagnostic center and calculated the total costs of these patients' diagnostic trajectory in order to evaluate early WES implementation. METHODS: We compared 17 patients' trio-WES yield with the retrospective costs of diagnostic procedures by comprehensively examining patient records and collecting resource use information for each patient, beginning with patient admittance and concluding with WES initiation. We calculated cost savings using scenario analyses to evaluate the costs replaced by WES when used as a first diagnostic tool. RESULTS: WES resulted in diagnostically useful outcomes in 29.4% of patients. The entire traditional diagnostic trajectory average cost was $16,409 per patient, substantially higher than the $3,972 trio-WES cost. WES resulted in average cost savings of $3,547 for genetic and metabolic investigations in diagnosed patients and $1,727 for genetic investigations in undiagnosed patients. CONCLUSION: The increased causal variant detection yield by WES and the relatively high costs of the entire traditional diagnostic trajectory suggest that early implementation of WES is a relevant and cost-efficient option in patient diagnostics. This information is crucial for centers considering implementation of WES and serves as input for future value-based research into diagnostics.Genet Med 18 9, 949-956.