IMPRESS: Improved methylation profiling using restriction enzymes and smMIP sequencing, combined with a new biomarker panel, creating a multi-cancer detection assay.

BACKGROUND: Despite the worldwide progress in cancer diagnostics, more sensitive diagnostic biomarkers are needed. The methylome has been extensively investigated in the last decades, but a low-cost, bisulfite-free detection method for multiplex analysis is still lacking. METHODS: We developed a methylation detection technique called IMPRESS, which combines methylation-sensitive restriction enzymes and single-molecule Molecular Inversion Probes. We used this technique for the development of a multi-cancer detection assay for eight of the most lethal cancer types worldwide. We selected 1791 CpG sites that can distinguish tumor from normal tissue based on DNA methylation. These sites were analysed with IMPRESS in 35 blood, 111 tumor and 114 normal samples. Finally, a classifier model was built. RESULTS: We present the successful development of IMPRESS and validated it with ddPCR. The final classifier model discriminating tumor from normal samples was built with 358 CpG target sites and reached a sensitivity of 0.95 and a specificity of 0.91. Moreover, we provide data that highlight IMPRESS's potential for liquid biopsies. CONCLUSIONS: We successfully created an innovative DNA methylation detection technique. By combining this method with a new multi-cancer biomarker panel, we developed a sensitive and specific multi-cancer assay, with potential use in liquid biopsies.

Lack of functional TCR-epitope interaction is associated with herpes zoster through reduced downstream T cell activation.

The role of T cell receptor (TCR) diversity in infectious disease susceptibility is not well understood. We use a systems immunology approach on three cohorts of herpes zoster (HZ) patients and controls to investigate whether TCR diversity against varicella-zoster virus (VZV) influences the risk of HZ. We show that CD4+ T cell TCR diversity against VZV glycoprotein E (gE) and immediate early 63 protein (IE63) after 1-week culture is more restricted in HZ patients. Single-cell RNA and TCR sequencing of VZV-specific T cells shows that T cell activation pathways are significantly decreased after stimulation with VZV peptides in convalescent HZ patients. TCR clustering indicates that TCRs from HZ patients co-cluster more often together than TCRs from controls. Collectively, our results suggest that not only lower VZV-specific TCR diversity but also reduced functional TCR affinity for VZV-specific proteins in HZ patients leads to lower T cell activation and consequently affects the susceptibility for viral reactivation.

Unraveling the Immune Signature of Herpes Zoster: Insights Into the Pathophysiology and Human Leukocyte Antigen Risk Profile.

The varicella-zoster virus (VZV) infects >95% of the population. VZV reactivation causes herpes zoster (HZ), known as shingles, primarily affecting the elderly and individuals who are immunocompromised. However, HZ can occur in otherwise healthy individuals. We analyzed the immune signature and risk profile in patients with HZ using a genome-wide association study across different UK Biobank HZ cohorts. Additionally, we conducted one of the largest HZ human leukocyte antigen association studies to date, coupled with transcriptomic analysis of pathways underlying HZ susceptibility. Our findings highlight the significance of the major histocompatibility complex locus for HZ development, identifying 5 protective and 4 risk human leukocyte antigen alleles. This demonstrates that HZ susceptibility is largely governed by variations in the major histocompatibility complex. Furthermore, functional analyses revealed the upregulation of type I interferon and adaptive immune responses. These findings provide fresh molecular insights into the pathophysiology and activation of innate and adaptive immune responses triggered by symptomatic VZV reactivation.

Blood transcriptomics to facilitate diagnosis and stratification in pediatric rheumatic diseases - a proof of concept study.

BACKGROUND: Transcriptome profiling of blood cells is an efficient tool to study the gene expression signatures of rheumatic diseases. This study aims to improve the early diagnosis of pediatric rheumatic diseases by investigating patients' blood gene expression and applying machine learning on the transcriptome data to develop predictive models. METHODS: RNA sequencing was performed on whole blood collected from children with rheumatic diseases. Random Forest classification models were developed based on the transcriptome data of 48 rheumatic patients, 46 children with viral infection, and 35 controls to classify different disease groups. The performance of these classifiers was evaluated by leave-one-out cross-validation. Analyses of differentially expressed genes (DEG), gene ontology (GO), and interferon-stimulated gene (ISG) score were also conducted. RESULTS: Our first classifier could differentiate pediatric rheumatic patients from controls and infection cases with high area-under-the-curve (AUC) values (AUC = 0.8 ± 0.1 and 0.7 ± 0.1, respectively). Three other classifiers could distinguish chronic recurrent multifocal osteomyelitis (CRMO), juvenile idiopathic arthritis (JIA), and interferonopathies (IFN) from control and infection cases with AUC ≥ 0.8. DEG and GO analyses reveal that the pathophysiology of CRMO, IFN, and JIA involves innate immune responses including myeloid leukocyte and granulocyte activation, neutrophil activation and degranulation. IFN is specifically mediated by antibacterial and antifungal defense responses, CRMO by cellular response to cytokine, and JIA by cellular response to chemical stimulus. IFN patients particularly had the highest mean ISG score among all disease groups. CONCLUSION: Our data show that blood transcriptomics combined with machine learning is a promising diagnostic tool for pediatric rheumatic diseases and may assist physicians in making data-driven and patient-specific decisions in clinical practice.

Preexisting memory CD4 T cells in naïve individuals confer robust immunity upon hepatitis B vaccination.

Antigen recognition through the T cell receptor (TCR) αß heterodimer is one of the primary determinants of the adaptive immune response. Vaccines activate naïve T cells with high specificity to expand and differentiate into memory T cells. However, antigen-specific memory CD4 T cells exist in unexposed antigen-naïve hosts. In this study, we use high-throughput sequencing of memory CD4 TCRß repertoire and machine learning to show that individuals with preexisting vaccine-reactive memory CD4 T cell clonotypes elicited earlier and higher antibody titers and mounted a more robust CD4 T cell response to hepatitis B vaccine. In addition, integration of TCRß sequence patterns into a hepatitis B epitope-specific annotation model can predict which individuals will have an early and more vigorous vaccine-elicited immunity. Thus, the presence of preexisting memory T cell clonotypes has a significant impact on immunity and can be used to predict immune responses to vaccination.

Immune cells called CD4 T cells help the body build immunity to infections caused by bacteria and viruses, or after vaccination. Receptor proteins on the outside of the cells recognize pathogens, foreign molecules called antigens, or vaccine antigens. Vaccine antigens are usually inactivated bacteria or viruses, or fragments of these pathogens. After recognizing an antigen, CD4 T cells develop into memory CD4 T cells ready to defend against future infections with the pathogen. People who have never been exposed to a pathogen, or have never been vaccinated against it, may nevertheless have preexisting memory cells ready to defend against it. This happens because CD4 T cells can recognize multiple targets, which enables the immune system to be ready to defend against both new and familiar pathogens. Elias, Meysman, Bartholomeus et al. wanted to find out whether having preexisting memory CD4 T cells confers an advantage for vaccine-induced immunity. Thirty-four people who were never exposed to hepatitis B or vaccinated against it participated in the study. These individuals provided blood samples before vaccination, with 2 doses of the hepatitis B vaccine, and at 3 time points afterward. Using next generation immune sequencing and machine learning techniques, Elias et al. analyzed the individuals' memory CD4 T cells before and after vaccination. The experiments showed that preexisting memory CD4 T cells may determine vaccination outcomes, and people with more preexisting memory cells develop quicker and stronger immunity after vaccination against hepatitis B. This information may help scientists to better understand how people develop immunity to pathogens. It may guide them develop better vaccines or predict who will develop immunity after vaccination.

Transcriptomic profiling of different responder types in adults after a Priorix® vaccination.

Thanks to the recommendation of a combined Measles/Mumps/Rubella (MMR) vaccine, like Priorix®, these childhood diseases are less common now. This is beneficial to limit the spread of these diseases and work towards their elimination. However, the measles, mumps and rubella antibody titers show a large variability in short- and long-term immunity. The recent outbreaks worldwide of measles and mumps and previous studies, which mostly focused on only one of the three virus responses, illustrate that there is a clear need for better understanding the immune responses after vaccination. Our healthy cohort was already primed with the MMR antigens in their childhood. In this study, the adult volunteers received one Priorix® vaccine dose at day 0. First, we defined 4 different groups of responders, based on their antibody titers' evolution over 4 time points (Day 0, 21, 150 and 365). This showed a high variability within and between individuals. Second, we determined transcriptome profiles using 3'mRNA sequencing at day 0, 3 and 7. Using two analytical approaches, "one response group per time point" and "a time comparison per response group", we correlated the short-term gene expression profiles to the different response groups. In general, the list of differentially expressed genes is limited, however, most of them are clearly immune-related and upregulated at day 3 and 7, compared to the baseline day 0. Depending on the specific response group there are overlapping signatures for two of the three viruses. Antibody titers and transcriptomics data showed that an additional Priorix vaccination does not facilitate an equal immune response against the 3 viruses or among different vaccine recipients.

Diagnosing enterovirus meningitis via blood transcriptomics: an alternative for lumbar puncture?

BACKGROUND: Meningitis can be caused by several viruses and bacteria. Identifying the causative pathogen as quickly as possible is crucial to initiate the most optimal therapy, as acute bacterial meningitis is associated with a significant morbidity and mortality. Bacterial meningitis requires antibiotics, as opposed to enteroviral meningitis, which only requires supportive therapy. Clinical presentation is usually not sufficient to differentiate between viral and bacterial meningitis, thereby necessitating cerebrospinal fluid (CSF) analysis by PCR and/or time-consuming bacterial cultures. However, collecting CSF in children is not always feasible and a rather invasive procedure. METHODS: In 12 Belgian hospitals, we obtained acute blood samples from children with signs of meningitis (49 viral and 7 bacterial cases) (aged between 3 months and 16 years). After pathogen confirmation on CSF, the patient was asked to give a convalescent sample after recovery. 3' mRNA sequencing was performed to determine differentially expressed genes (DEGs) to create a host transcriptomic profile. RESULTS: Enteroviral meningitis cases displayed the largest upregulated fold change enrichment in type I interferon production, response and signaling pathways. Patients with bacterial meningitis showed a significant upregulation of genes related to macrophage and neutrophil activation. We found several significantly DEGs between enteroviral and bacterial meningitis. Random forest classification showed that we were able to differentiate enteroviral from bacterial meningitis with an AUC of 0.982 on held-out samples. CONCLUSIONS: Enteroviral meningitis has an innate immunity signature with type 1 interferons as key players. Our classifier, based on blood host transcriptomic profiles of different meningitis cases, is a possible strong alternative for diagnosing enteroviral meningitis.

Methylation analysis of Gasdermin E shows great promise as a biomarker for colorectal cancer.

In addition to its implication in hereditary hearing loss, the Gasdermin E (GSDME) gene is also a tumor suppressor involved in cancer progression through programmed cell death. GSDME epigenetic silencing through methylation has been shown in some cancer types, but studies are yet to fully explore its diagnostic/prognostic potential in colorectal cancer on a large-scale. We used public data from The Cancer Genome Atlas (TCGA) to investigate differences in GSDME methylation and expression between colorectal cancer and normal colorectal tissue, and between left- and right-sided colorectal cancers in 432 samples. We also explored GSDME's diagnostic capacity as a biomarker for colorectal cancer. We observed differential methylation in all 22 GSDME CpGs between tumor and normal tissues, and in 18 CpGs between the left- and right-sided groups. In the cancer tissue, putative promoter probes were hypermethylated and gene body probes were hypomethylated, while this pattern was inversed in normal tissues. Both putative promoter and gene body CpGs correlated well together but formed distinct methylation patterns with the putative promoter exhibiting the most pronounced methylation differences between tumor and normal tissues. Clinicopathological parameters, excluding age, did not show any effect on CpG methylation. Although the methylation of 5 distinct probes was a good predictor of gene expression, we could not identify an association between GSDME methylation and expression in general. Survival analysis showed no association between GSDME methylation and expression on 5-year patient survival. Through logistic regression, we identified a combination of 2 CpGs, that can discriminate between cancer and normal tissue with high accuracy (AUC = 0.95) irrespective of age and tumor stage. We also validated our model in 3 external methylation datasets, from the Gene Expression Omnibus database, and similar results were reached. Our results suggest that GSDME is a promising biomarker for the detection of colorectal cancer.

Memory CD4+ T cell receptor repertoire data mining as a tool for identifying cytomegalovirus serostatus.

Pathogens of past and current infections have been identified directly by means of PCR or indirectly by measuring a specific immune response (e.g., antibody titration). Using a novel approach, Emerson and colleagues showed that the cytomegalovirus serostatus can also be accurately determined by using a T cell receptor repertoire data mining approach. In this study, we have sequenced the CD4+ memory T cell receptor repertoire of a Belgian cohort with known cytomegalovirus serostatus. A random forest classifier was trained on the CMV specific T cell receptor repertoire signature and used to classify individuals in the Belgian cohort. This study shows that the novel approach can be reliably replicated with an equivalent performance as that reported by Emerson and colleagues. Additionally, it provides evidence that the T cell receptor repertoire signature is to a large extent present in the CD4+ memory repertoire.

Transcriptome profiling in blood before and after hepatitis B vaccination shows significant differences in gene expression between responders and non-responders.

INTRODUCTION: As the hepatitis B virus is widely spread and responsible for considerable morbidity and mortality, WHO recommends vaccination from infancy to reduce acute infection and chronic carriers. However, current subunit vaccines are not 100% efficacious and leave 5-10% of recipients unprotected. METHODS: To evaluate immune responses after Engerix-B vaccination, we determined, using mRNA-sequencing, whole blood early gene expression signatures before, at day 3 and day 7 after the first dose and correlated this with the resulting antibody titer after two vaccine doses. RESULTS: Our results indicate that immune related genes are differentially expressed in responders mostly at day 3 and in non-responders mostly at day 7. The most remarkable difference between responders and non-responders were the differentially expressed genes before vaccination. The granulin precursor gene (GRN) was significantly downregulated in responders while upregulated in non-responders at day 0. Furthermore, absolute granulocytes numbers were significantly higher in non-responders at day 0. CONCLUSION: The non-responders already showed an activated state of the immune system before vaccination. Furthermore, after vaccination, they exhibited a delayed and partial immune response in comparison to the responders. Our data may indicate that the baseline and untriggered immune system can influence the response upon hepatitis B vaccination.

Large-scale analysis of DFNA5 methylation reveals its potential as biomarker for breast cancer.

Background: Breast cancer is the most frequent cancer among women worldwide. Biomarkers for early detection and prognosis of these patients are needed. We hypothesized that deafness, autosomal dominant 5 (DFNA5) may be a valuable biomarker, based upon strong indications for its role as tumor suppressor gene and its function in regulated cell death. In this study, we aimed to analyze DFNA5 methylation and expression in the largest breast cancer cohort to date using publicly available data from TCGA, in order to further unravel the role of DFNA5 as detection and/or prognostic marker in breast cancer. We analyzed Infinium HumanMethylation450k data, covering 22 different CpGs in the DFNA5 gene (668 breast adenocarcinomas and 85 normal breast samples) and DFNA5 expression (Agilent 244K Custom Gene Expression: 476 breast adenocarcinomas and 56 normal breast samples; RNA-sequencing: 666 breast adenocarcinomas and 71 normal breast samples). Results: DFNA5 methylation and expression were significantly different between breast cancer and normal breast samples. Overall, breast cancer samples showed higher DFNA5 methylation in the putative gene promoter compared to normal breast samples, whereas in the gene body and upstream of the putative gene promoter, the opposite is true. Furthermore, DFNA5 methylation, in 10 out of 22 CpGs, and expression were significantly higher in lobular compared to ductal breast cancers. An important result of this study was the identification of a combination of one CpG in the gene promoter (CpG07504598) and one CpG in the gene body (CpG12922093) of DFNA5, which was able to discriminate between breast cancer and normal breast samples (AUC = 0.93). This model was externally validated in three independent datasets. Moreover, we showed that estrogen receptor state is associated with DFNA5 methylation and expression. Finally, we were able to find a significant effect of DFNA5 gene body methylation on a 5-year overall survival time. Conclusions: We conclude that DFNA5 methylation shows strong potential as detection and prognostic biomarker for breast cancer.

Increased herpes zoster risk associated with poor HLA-A immediate early 62 protein (IE62) affinity.

Around 30% of individuals will develop herpes zoster (HZ), caused by the varicella zoster virus (VZV), during their life. While several risk factors for HZ, such as immunosuppressive therapy, are well known, the genetic and molecular components that determine the risk of otherwise healthy individuals to develop HZ are still poorly understood. We created a computational model for the Human Leukocyte Antigen (HLA-A, -B, and -C) presentation capacity of peptides derived from the VZV Immediate Early 62 (IE62) protein. This model could then be applied to a HZ cohort with known HLA molecules. We found that HLA-A molecules with poor VZV IE62 presentation capabilities were more common in a cohort of 50 individuals with a history of HZ compared to a nationwide control group, which equated to a HZ risk increase of 60%. This tendency was most pronounced for cases of HZ at a young age, where other risk factors are less prevalent. These findings provide new molecular insights into the development of HZ and reveal a genetic predisposition in those individuals most at risk to develop HZ.

On the feasibility of mining CD8+ T cell receptor patterns underlying immunogenic peptide recognition.

Current T cell epitope prediction tools are a valuable resource in designing targeted immunogenicity experiments. They typically focus on, and are able to, accurately predict peptide binding and presentation by major histocompatibility complex (MHC) molecules on the surface of antigen-presenting cells. However, recognition of the peptide-MHC complex by a T cell receptor (TCR) is often not included in these tools. We developed a classification approach based on random forest classifiers to predict recognition of a peptide by a T cell receptor and discover patterns that contribute to recognition. We considered two approaches to solve this problem: (1) distinguishing between two sets of TCRs that each bind to a known peptide and (2) retrieving TCRs that bind to a given peptide from a large pool of TCRs. Evaluation of the models on two HIV-1, B*08-restricted epitopes reveals good performance and hints towards structural CDR3 features that can determine peptide immunogenicity. These results are of particular importance as they show that prediction of T cell epitope and T cell epitope recognition based on sequence data is a feasible approach. In addition, the validity of our models not only serves as a proof of concept for the prediction of immunogenic T cell epitopes but also paves the way for more general and high-performing models.

Inborn errors in RNA polymerase III underlie severe varicella zoster virus infections.

Varicella zoster virus (VZV) typically causes chickenpox upon primary infection. In rare cases, VZV can give rise to life-threatening disease in otherwise healthy people, but the immunological basis for this remains unexplained. We report 4 cases of acute severe VZV infection affecting the central nervous system or the lungs in unrelated, otherwise healthy children who are heterozygous for rare missense mutations in POLR3A (one patient), POLR3C (one patient), or both (two patients). POLR3A and POLR3C encode subunits of RNA polymerase III. Leukocytes from all 4 patients tested exhibited poor IFN induction in response to synthetic or VZV-derived DNA. Moreover, leukocytes from 3 of the patients displayed defective IFN production upon VZV infection and reduced control of VZV replication. These phenotypes were rescued by transduction with relevant WT alleles. This work demonstrates that monogenic or digenic POLR3A and POLR3C deficiencies confer increased susceptibility to severe VZV disease in otherwise healthy children, providing evidence for an essential role of a DNA sensor in human immunity.

Recessive mutations in SLC35A3 cause early onset epileptic encephalopathy with skeletal defects.

We describe the clinical and whole genome sequencing (WGS) study of a non-consanguineous Italian family in which two siblings, a boy and a girl, manifesting a severe epileptic encephalopathy (EE) with skeletal abnormalities, carried novel SLC35A3 compound heterozygous mutations. Both siblings exhibited infantile spasms, associated with focal, and tonic vibratory seizures from early infancy. EEG recordings showed a suppression-burst (SB) pattern and multifocal paroxysmal activity in both. In addition both had quadriplegia, acquired microcephaly, and severe intellectual disability. General examination showed distal arthrogryposis predominant in the hands in both siblings and severe left dorso-lumbar convex scoliosis in one. WGS of the siblings-parents quartet identified novel compound heterozygous mutations in SLC35A3 in both children. SLC35A3 encodes the major Golgi uridine diphosphate N-acetylglucosamine transporter. With this study, we add SLC35A3 to the gene list of epilepsies. Neurological symptoms and skeletal abnormalities might result from impaired glycosylation of proteins involved in normal development and function of the central nervous system and skeletal apparatus.

Large-scale copy number analysis reveals variations in genes not previously associated with malignant pleural mesothelioma.

Malignant pleural mesothelioma (MPM) is an aggressive tumor that is often causally associated with asbestos exposure. Comparative genomic hybridization techniques and arrays demonstrated a complex set of copy number variations (CNVs) in the MPM-genome. These techniques however have a limited resolution, throughput and flexibility compared to next-generation sequencing platforms. In this study, the presence of CNVs in the MPM-genome was investigated using an MPM-cohort (N = 85) for which genomic microarray data are available through 'The Cancer Genome Atlas' (TCGA). To validate these results, the genomes of MPMs and matched normal samples (N = 21) were analyzed using low-pass whole genome sequencing on an 'Illumina HiSeq' platform. CNVs were detected using in-house developed analysis pipelines and frequencies of copy number loss and gain were calculated. In both datasets, losses on chromosomes 1, 3, 4, 6, 9, 13 and 22 and gains on chromosomes 1, 5, 7 and 17 were found in at least 25% and 15% of MPMs, respectively. Besides the well-known MPM-associated genes, CDKN2A, NF2 and BAP1, other interesting cancer-associated genes were listed as frequently involved in a copy number loss (e.g. EP300, SETD2 and PBRM1). Moreover, four cancer-associated genes showed a high frequency of copy number gain in both datasets (i.e. TERT, FCGR2B, CD79B and PRKAR1A). A statistically significant association between overall survival and the presence of copy number loss in the CDKN2A-containing region was observed in the TCGA-set. In conclusion, recurrent CNVs were detected in both datasets, occurring in regions harboring known MPM-associated genes and genes not previously linked to MPM.

Targeted sequencing of 351 candidate genes for epileptic encephalopathy in a large cohort of patients.

BACKGROUND: Many genes are candidates for involvement in epileptic encephalopathy (EE) because one or a few possibly pathogenic variants have been found in patients, but insufficient genetic or functional evidence exists for a definite annotation. METHODS: To increase the number of validated EE genes, we sequenced 26 known and 351 candidate genes for EE in 360 patients. Variants in 25 genes known to be involved in EE or related phenotypes were followed up in 41 patients. We prioritized the candidate genes, and followed up 31 variants in this prioritized subset of candidate genes. RESULTS: Twenty-nine genotypes in known genes for EE (19) or related diseases (10), dominant as well as recessive or X-linked, were classified as likely pathogenic variants. Among those, likely pathogenic de novo variants were found in EE genes that act dominantly, including the recently identified genes EEF1A2, KCNB1 and the X-linked gene IQSEC2. A de novo frameshift variant in candidate gene HNRNPU was the only de novo variant found among the followed-up candidate genes, and the patient's phenotype was similar to a few recent publications. CONCLUSION: Mutations in genes described in OMIM as, for example, intellectual disability gene can lead to phenotypes that get classified as EE in the clinic. We confirmed existing literature reports that de novo loss-of-function HNRNPUmutations lead to severe developmental delay and febrile seizures in the first year of life.

Phenotypic spectrum of GABRA1: From generalized epilepsies to severe epileptic encephalopathies.

OBJECTIVE: To delineate phenotypic heterogeneity, we describe the clinical features of a cohort of patients with GABRA1 gene mutations. METHODS: Patients with GABRA1 mutations were ascertained through an international collaboration. Clinical, EEG, and genetic data were collected. Functional analysis of 4 selected mutations was performed using the Xenopus laevis oocyte expression system. RESULTS: The study included 16 novel probands and 3 additional family members with a disease-causing mutation in the GABRA1 gene. The phenotypic spectrum varied from unspecified epilepsy (1), juvenile myoclonic epilepsy (2), photosensitive idiopathic generalized epilepsy (1), and generalized epilepsy with febrile seizures plus (1) to severe epileptic encephalopathies (11). In the epileptic encephalopathy group, the patients had seizures beginning between the first day of life and 15 months, with a mean of 7 months. Predominant seizure types in all patients were tonic-clonic in 9 participants (56%) and myoclonic seizures in 5 (31%). EEG showed a generalized photoparoxysmal response in 6 patients (37%). Four selected mutations studied functionally revealed a loss of function, without a clear genotype-phenotype correlation. CONCLUSIONS: GABRA1 mutations make a significant contribution to the genetic etiology of both benign and severe epilepsy syndromes. Myoclonic and tonic-clonic seizures with pathologic response to photic stimulation are common and shared features in both mild and severe phenotypes.

Pitfalls in genetic testing: the story of missed SCN1A mutations.

BACKGROUND: Sanger sequencing, still the standard technique for genetic testing in most diagnostic laboratories and until recently widely used in research, is gradually being complemented by next-generation sequencing (NGS). No single mutation detection technique is however perfect in identifying all mutations. Therefore, we wondered to what extent inconsistencies between Sanger sequencing and NGS affect the molecular diagnosis of patients. Since mutations in SCN1A, the major gene implicated in epilepsy, are found in the majority of Dravet syndrome (DS) patients, we focused on missed SCN1A mutations. METHODS: We sent out a survey to 16 genetic centers performing SCN1A testing. RESULTS: We collected data on 28 mutations initially missed using Sanger sequencing. All patients were falsely reported as SCN1A mutation-negative, both due to technical limitations and human errors. CONCLUSION: We illustrate the pitfalls of Sanger sequencing and most importantly provide evidence that SCN1A mutations are an even more frequent cause of DS than already anticipated.