GenIA, the Genetic Immunology Advisor database for inborn errors of immunity.

BACKGROUND: To date, no publicly accessible platform has captured and synthesized all of the layered dimensions of genotypic, phenotypic, and mechanistic information published in the field of inborn errors of immunity (IEIs). Such a platform would represent the extensive and complex landscape of IEIs and could increase the rate of diagnosis in patients with a suspected IEI, which remains unacceptably low. OBJECTIVE: Our aim was to create an expertly curated, patient-centered, multidimensional IEI database that enables aggregation and sophisticated data interrogation and promotes involvement from diverse stakeholders across the community. METHODS: The database structure was designed following a subject-centered model and written in Structured Query Language (SQL). The web application is written in Hypertext Preprocessor (PHP), Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), and JavaScript. All data stored in the Genetic Immunology Advisor (GenIA) are extracted by manually reviewing published research articles. RESULTS: We completed data collection and curation for 24 pilot genes. Using these data, we have exemplified how GenIA can provide quick access to structured, longitudinal, more thorough, comprehensive, and up-to-date IEI knowledge than do currently existing databases, such as ClinGen, Human Phenotype Ontology (HPO), ClinVar, or Online Mendelian Inheritance in Man (OMIM), with which GenIA intends to dovetail. CONCLUSIONS: GenIA strives to accurately capture the extensive genetic, mechanistic, and phenotypic heterogeneity found across IEIs, as well as genetic paradigms and diagnostic pitfalls associated with individual genes and conditions. The IEI community's involvement will help promote GenIA as an enduring resource that supports and improves knowledge sharing, research, diagnosis, and care for patients with genetic immune disease.

Exome sequencing as a first-tier test for copy number variant detection: retrospective evaluation and prospective screening in 2418 cases.

BACKGROUND: Despite the availability of whole exome (WES) and genome sequencing (WGS), chromosomal microarray (CMA) remains the first-line diagnostic test in most rare disorders diagnostic workup, looking for copy number variations (CNVs), with a diagnostic yield of 10%-20%. The question of the equivalence of CMA and WES in CNV calling is an organisational and economic question, especially when ordering a WGS after a negative CMA and/or WES. METHODS: This study measures the equivalence between CMA and GATK4 exome sequencing depth of coverage method in detecting coding CNVs on a retrospective cohort of 615 unrelated individuals. A prospective detection of WES-CNV on a cohort of 2418 unrelated individuals, including the 615 individuals from the validation cohort, was performed. RESULTS: On the retrospective validation cohort, every CNV detectable by the method (ie, a CNV with at least one exon not in a dark zone) was accurately called (64/64 events). In the prospective cohort, 32 diagnoses were performed among the 2418 individuals with CNVs ranging from 704 bp to aneuploidy. An incidental finding was reported. The overall increase in diagnostic yield was of 1.7%, varying from 1.2% in individuals with multiple congenital anomalies to 1.9% in individuals with chronic kidney failure. CONCLUSION: Combining single-nucleotide variant (SNV) and CNV detection increases the suitability of exome sequencing as a first-tier diagnostic test for suspected rare Mendelian disorders. Before considering the prescription of a WGS after a negative WES, a careful reanalysis with updated CNV calling and SNV annotation should be considered.

Evaluating the Transition from Targeted to Exome Sequencing: A Guide for Clinical Laboratories.

The transition from targeted to exome or genome sequencing in clinical contexts requires quality standards, such as targeted sequencing, in order to be fully adopted. However, no clear recommendations or methodology have emerged for evaluating this technological evolution. We developed a structured method based on four run-specific sequencing metrics and seven sample-specific sequencing metrics for evaluating the performance of exome sequencing strategies to replace targeted strategies. The indicators include quality metrics and coverage performance on gene panels and OMIM morbid genes. We applied this general strategy to three different exome kits and compared them with a myopathy-targeted sequencing method. After having achieved 80 million reads, all-tested exome kits generated data suitable for clinical diagnosis. However, significant differences in the coverage and PCR duplicates were observed between the kits. These are two main criteria to consider for the initial implementation with high-quality assurance. This study aims to assist molecular diagnostic laboratories in adopting and evaluating exome sequencing kits in a diagnostic context compared to the strategy used previously. A similar strategy could be used to implement whole-genome sequencing for diagnostic purposes.

Genome Alert!: A standardized procedure for genomic variant reinterpretation and automated gene-phenotype reassessment in clinical routine.

PURPOSE: Retrospective interpretation of sequenced data in light of the current literature is a major concern of the field. Such reinterpretation is manual and both human resources and variable operating procedures are the main bottlenecks. METHODS: Genome Alert! method automatically reports changes with potential clinical significance in variant classification between releases of the ClinVar database. Using ClinVar submissions across time, this method assigns validity category to gene-disease associations. RESULTS: Between July 2017 and December 2019, the retrospective analysis of ClinVar submissions revealed a monthly median of 1247 changes in variant classification with potential clinical significance and 23 new gene-disease associations. Re-examination of 4929 targeted sequencing files highlighted 45 changes in variant classification, and of these classifications, 89% were expert validated, leading to 4 additional diagnoses. Genome Alert! gene-disease association catalog provided 75 high-confidence associations not available in the OMIM morbid list; of which, 20% became available in OMIM morbid list For more than 356 negative exome sequencing data that were reannotated for variants in these 75 genes, this elective approach led to a new diagnosis. CONCLUSION: Genome Alert! (https://genomealert.univ-grenoble-alpes.fr/) enables systematic and reproducible reinterpretation of acquired sequencing data in a clinical routine with limited human resource effect.

Accurate detection of clinically relevant uniparental disomy from exome sequencing data.

PURPOSE: Uniparental disomy (UPD) is the rare occurrence of two homologous chromosomes originating from the same parent and is typically identified by marker analysis or single-nucleotide polymorphism (SNP)-based microarrays. UPDs may lead to disease due to imprinting effects, underlying homozygous pathogenic variants, or low-level mosaic aneuploidies. In this study we detected clinically relevant UPD events in both trio and single exome sequencing (ES) data. METHODS: UPD was detected by applying a method based on Mendelian inheritance errors to a cohort of 4912 ES trios (all UPD types) and by using median absolute deviation-scaled regions of homozygosity to a cohort of 29,723 single ES samples (isodisomy only). RESULTS: As positive controls, we accurately identified three mixed UPD, three isodisomy, as well as two segmental UPD events that were all previously reported by SNP-based microarrays. In addition, we identified three segmental UPD and 11 isodisomy events. This resulted in a novel diagnosis based on imprinting for one patient, and adjusted genetic counseling for another patient. CONCLUSION: UPD can easily be identified using both single and trio ES and may be clinically relevant to patients. UPD analysis should become routine in clinical ES, because it increases the diagnostic yield and could affect genetic counseling.

Ovarian Clear Cell Carcinoma in Cowden Syndrome.

Cowden syndrome (CS) is an autosomal dominant mendelian disease related to germline pathogenic variants affecting the PTEN-gene. CS is characterized by macrocephaly, mucocutaneous lesions, and an increased risk of breast and thyroid cancers. Rare ovarian cancer cases (mostly embryonic tumors) associated with PTEN have been described in the literature, but no current CS guidelines are available for ovarian cancer risk management. We report on a woman diagnosed with ovarian clear cell carcinoma (OCCC) at 28 years of age. The patient displayed macrocephaly, trichilemmomas, oral papillomatosis, and acral keratosis. A family history of multiple cancer cases within the PTEN-related tumor spectrum was identified. In addition, PET scan and fine-needle biopsy results led to a diagnosis of thyroid follicular neoplasia. PTEN sequencing revealed that she carried a germline inherited pathogenic variant in exon 5 c.388C>T, p.(Arg130*) (NM_000314). Somatic mismatch repair immunohistochemistry analysis showed normal expression, and germline BRCA1/2 sequencing did not reveal pathogenic or likely pathogenic variants. An ovarian cell immunohistochemistry analysis reported total loss of PTEN expression, which strongly suggested the role of PTEN in the oncogenesis of this cancer. Hence, a total thyroid resection was performed instead of thyroid lobectomy and a risk-reducing bilateral mastectomy was discussed. Co-occurrence of this pathogenic germline mutation in PTEN in this patient, early development of OCCC at age 28 years, and total loss of PTEN expression in the tumor might support the involvement of PTEN in the carcinogenesis of her ovarian cancer. We describe a new ovarian cancer case with an atypical histologic type-clear cell carcinoma-in CS. This observation might be the first indication of the need to expand the PTEN-related tumor spectrum to incorporate OCCC. The CS diagnosis significantly changed the therapeutic outcome of this patient.

B3GAT3-related disorder with craniosynostosis and bone fragility due to a unique mutation.

PurposeBased on prenatal suspicion of the combination of radioulnar or radiohumeral synostosis and a peculiar shape of the skull suggestive of craniosynostosis, we report on six patients from four unrelated consanguineous families in whom Antley-Bixler syndrome was suspected during the prenatal period without mutation in genes known to be associated with the syndrome.MethodsMolecular diagnosis involved whole-exome and gene-panel sequencing. RESULTS: All sequenced patients showed a unique homozygous mutation of c.667G>A, p.Gly223Ser (NM_012200) in the beta-1,3-glucuronyltransferase 3 (B3GAT3) gene known to be involved in linkeropathy syndrome. Linkeropathies correspond to a recently identified group of heterogeneous genetic syndromes along a spectrum of skeletal and connective tissue disorders. These patients featured mainly craniosynostosis, midface hypoplasia, bilateral radioulnar synostosis, multiple neonatal fractures, dislocated joints, joint contracture, long fingers, foot deformity, and cardiovascular abnormalities. All died before 1 year of age.ConclusionWe identified a novel B3GAT3-related disorder with craniosynostosis and bone fragility, due to a unique homozygous mutation in B3GAT3. This syndrome should be considered in the prenatal period in light of the severe outcome and as an alternative diagnosis to Antley-Bixler or Shprintzen-Goldberg syndrome.

Next generation phenotyping for diagnosis and phenotype-genotype correlations in Kabuki syndrome.

The field of dysmorphology has been changed by the use Artificial Intelligence (AI) and the development of Next Generation Phenotyping (NGP). The aim of this study was to propose a new NGP model for predicting KS (Kabuki Syndrome) on 2D facial photographs and distinguish KS1 (KS type 1, KMT2D-related) from KS2 (KS type 2, KDM6A-related). We included retrospectively and prospectively, from 1998 to 2023, all frontal and lateral pictures of patients with a molecular confirmation of KS. After automatic preprocessing, we extracted geometric and textural features. After incorporation of age, gender, and ethnicity, we used XGboost (eXtreme Gradient Boosting), a supervised machine learning classifier. The model was tested on an independent validation set. Finally, we compared the performances of our model with DeepGestalt (Face2Gene). The study included 1448 frontal and lateral facial photographs from 6 centers, corresponding to 634 patients (527 controls, 107 KS); 82 (78%) of KS patients had a variation in the KMT2D gene (KS1) and 23 (22%) in the KDM6A gene (KS2). We were able to distinguish KS from controls in the independent validation group with an accuracy of 95.8% (78.9-99.9%, p < 0.001) and distinguish KS1 from KS2 with an empirical Area Under the Curve (AUC) of 0.805 (0.729-0.880, p < 0.001). We report an automatic detection model for KS with high performances (AUC 0.993 and accuracy 95.8%). We were able to distinguish patients with KS1 from KS2, with an AUC of 0.805. These results outperform the current commercial AI-based solutions and expert clinicians.

Predominance of BRCA2 Mutation and Estrogen Receptor Positivity in Unselected Breast Cancer with BRCA1 or BRCA2 Mutation.

BACKGROUND: Poly(ADP-ribose) polymerase 1 inhibitor (PARPi) agents can improve progression-free survival of patients with breast cancer who carry a germline BRCA1 or BRCA2 pathogenic or likely pathogenic variant (gBRCA) in both the metastatic and adjuvant setting. Therefore, we need to reassess the frequency of gBRCA1 and gBRCA2 in order to redefine the criteria for women and tumor phenotype that should be tested. OBJECTIVE: We studied the relative distribution of gBRCA1 and gBRCA2 in unselected populations of women with breast cancer and in unaffected individuals. We also analyzed the proportion of estrogen receptor (ER)-positive (ER+) tumors in unselected breast cancer patients with gBRCA. DESIGN: We performed a meta-analysis of studies of unselected breast cancer that analyzed the relative contribution of gBRCA1 versus gBRCA2 among unselected breast cancer cases in gBRCA carriers. We then performed a meta-analysis of gBRCA carriage in unaffected individuals from genome-wide population studies, the gnomAD databank, and case-control studies. RESULTS: The BRCA2 gene was involved in 54% of breast cancer cases in unselected patients with gBRCA (n = 108,699) and 60% of unaffected individuals (n = 238,973) as compared with 38% of the largest gBRCA family cohort (n = 29,700). The meta-analysis showed that 1.66% (95% CI 1.08-2.54) and 1.71% (95% CI 1.33-2.2) of unselected breast cancer patients carried gBRCA1 and gBRCA2, respectively. In a population of unaffected individuals, the frequency of heterozygosity for gBRCA1 and gBRCA2 was estimated at 1/434 and 1/288, respectively. Nearly 0.5% of unaffected individuals in the studied populations carried a gBRCA. Carriage of a gBRCA was 2.5% for patients with ER+ tumors (95% CI 1.5-4.1) and 5.7% (95% CI 5.1-6.2) for those with ER- tumors. Overall, 58% of breast tumors occurring in women carrying a gBRCA were ER+ (n = 86,870). CONCLUSIONS: This meta-analysis showed that gBRCA2 carriage is predominant in unselected breast cancer patients and unaffected individuals. ER+ tumors among women with gBRCA-related breast cancer are predominant and have been underestimated. Because PARPi agents improve progression-free survival with ER+ gBRCA breast cancer in most clinical trials, breast cancer should be considered, regardless of ER status, for BRCA1/2 screening for therapeutic purposes.

Rapid exome sequencing in critically ill infants: implementation in routine care from French regional hospital's perspective.

This monocentric study included fifteen children under a year old in intensive care with suspected monogenic conditions for rapid trio exome sequencing (rES) between April 2019 and April 2021. The primary outcome was the time from blood sampling to rapid exome sequencing report to parents. All results were available within 16 days and were reported to parents in or under 16 days in 13 of the 15 individuals (86%). Six individuals (40%) received a diagnosis with rES, two had a genetic condition not diagnosed by rES. Eight individuals had their care impacted by their rES results, four were discharged or died before the results. This small-scale study shows that rES can be implemented in a regional University hospital with rapid impactful diagnosis to improve care in critically ill infants.

Using deep-neural-network-driven facial recognition to identify distinct Kabuki syndrome 1 and 2 gestalt.

Kabuki syndrome (KS) is a rare genetic disorder caused by mutations in two major genes, KMT2D and KDM6A, that are responsible for Kabuki syndrome 1 (KS1, OMIM147920) and Kabuki syndrome 2 (KS2, OMIM300867), respectively. We lack a description of clinical signs to distinguish KS1 and KS2. We used facial morphology analysis to detect any facial morphological differences between the two KS types. We used a facial-recognition algorithm to explore any facial morphologic differences between the two types of KS. We compared several image series of KS1 and KS2 individuals, then compared images of those of Caucasian origin only (12 individuals for each gene) because this was the main ethnicity in this series. We also collected 32 images from the literature to amass a large series. We externally validated results obtained by the algorithm with evaluations by trained clinical geneticists using the same set of pictures. Use of the algorithm revealed a statistically significant difference between each group for our series of images, demonstrating a different facial morphotype between KS1 and KS2 individuals (mean area under the receiver operating characteristic curve = 0.85 [p = 0.027] between KS1 and KS2). The algorithm was better at discriminating between the two types of KS with images from our series than those from the literature (p = 0.0007). Clinical geneticists trained to distinguished KS1 and KS2 significantly recognised a unique facial morphotype, which validated algorithm findings (p = 1.6e-11). Our deep-neural-network-driven facial-recognition algorithm can reveal specific composite gestalt images for KS1 and KS2 individuals.

An Integrated Clinical-Biological Approach to Identify Interindividual Variability and Atypical Phenotype-Genotype Correlations in Myopathies: Experience on A Cohort of 156 Families.

Diagnosis of myopathies is challenged by the high genetic heterogeneity and clinical overlap of the various etiologies. We previously reported a Next-Generation Sequencing strategy to identify genetic etiology in patients with undiagnosed Limb-Girdle Muscular Dystrophies, Congenital Myopathies, Congenital Muscular Dystrophies, Distal Myopathies, Myofibrillar Myopathies, and hyperCKemia or effort intolerance, using a large gene panel including genes classically associated with other entry diagnostic categories. In this study, we report the comprehensive clinical-biological strategy used to interpret NGS data in a cohort of 156 pediatric and adult patients, that included Copy Number Variants search, variants filtering and interpretation according to ACMG guidelines, segregation studies, deep phenotyping of patients and relatives, transcripts and protein studies, and multidisciplinary meetings. Genetic etiology was identified in 74 patients, a diagnostic yield (47.4%) similar to previous studies. We identified 18 patients (10%) with causative variants in different genes (ACTA1, RYR1, NEB, TTN, TRIP4, CACNA1S, FLNC, TNNT1, and PAPBN1) that resulted in milder and/or atypical phenotypes, with high intrafamilial variability in some cases. Mild phenotypes could mostly be explained by a less deleterious effect of variants on the protein. Detection of inter-individual variability and atypical phenotype-genotype associations is essential for precision medicine, patient care, and to progress in the understanding of the molecular mechanisms of myopathies.

Clinical and Molecular Spectrum of Nonsyndromic Early-Onset Osteoarthritis.

OBJECTIVE: Osteoarthritis (OA) is the most common joint disease worldwide. The etiology of OA is varied, ranging from multifactorial to environmental to monogenic. In a condition called early-onset OA, OA occurs at an earlier age than is typical in the general population. To our knowledge, there have been no large-scale genetic studies of individuals with early-onset OA. The present study was undertaken to investigate causes of monogenic OA in individuals with nonsyndromic early-onset OA. METHODS: The study probands were 45 patients with nonsyndromic early-onset OA who were referred to our skeletal disease center by skeletal dysplasia experts between 2013 and 2019. Criteria for early-onset OA included radiographic evidence, body mass index ≤30 kg/m2 , age at onset ≤50 years, and involvement of ≥1 joint site. Molecular analysis was performed with a next-generation sequencing panel. RESULTS: We identified a genetic variant in 13 probands (29%); the affected gene was COL2A1 in 11, ACAN in 1, and SLC26A2 in 1. After familial segregation analysis, 20 additional individuals were identified. The mean ± SD age at onset of joint pain was 19.5 ± 3.9 years (95% confidence interval 3-47). Eighteen of 33 subjects (55%) with nonsyndromic early-onset OA and a genetic variant had had at least 1 joint replacement (mean ± SD age at first joint replacement 41 ± 4.2 years; mean number of joint replacements 2.6 per individual), and 21 (45%) of the joint replacement surgeries were performed when the patient was <45 years old. Of the 20 patients age >40 years, 17 (85%) had had at least 1 joint replacement. CONCLUSION: We confirmed that COL2A1 is the main monogenic cause of nonsyndromic early-onset OA. However, on the basis of genetic heterogeneity of early-onset OA, we recommend next-generation sequencing for all individuals who undergo joint replacement prior to the age of 45 years. Lifestyle recommendations for prevention should be implemented.

Disruption of chromatin organisation causes MEF2C gene overexpression in intellectual disability: a case report.

BACKGROUND: Balanced structural variants are mostly described in disease with gene disruption or subtle rearrangement at breakpoints. CASE PRESENTATION: Here we report a patient with mild intellectual deficiency who carries a de novo balanced translocation t(3;5). Breakpoints were fully explored by microarray, Array Painting and Sanger sequencing. No gene disruption was found but the chromosome 5 breakpoint was localized 228-kb upstream of the MEF2C gene. The predicted Topologically Associated Domains analysis shows that it contains only the MEF2C gene and a long non-coding RNA LINC01226. RNA studies looking for MEF2C gene expression revealed an overexpression of MEF2C in the lymphoblastoid cell line of the patient. CONCLUSIONS: Pathogenicity of MEF2C overexpression is still unclear as only four patients with mild intellectual deficiency carrying 5q14.3 microduplications containing MEF2C are described in the literature. The microduplications in these individuals also contain other genes expressed in the brain. The patient presented the same phenotype as 5q14.3 microduplication patients. We report the first case of a balanced translocation leading to an overexpression of MEF2C similar to a functional duplication.

Looking for Broken TAD Boundaries and Changes on DNA Interactions: Clinical Guide to 3D Chromatin Change Analysis in Complex Chromosomal Rearrangements and Chromothripsis.

Apparition of next-generation sequencing (NGS) was a breakthrough on knowledge of genome structure. Bioinformatic tools are a key point to analyze this huge amount of data from NGS and characterize the three-dimensional organization of chromosomes. This chapter describes usage of different browsers to explore publicly available online data and to search for possible 3D chromatin changes involved during complex chromosomal rearrangements as chromothripsis. Their pathogenic impact on clinical phenotype and gene misexpression can also be evaluated with annotated databases.

Role of the general practitioner in the care of BRCA1 and BRCA2 mutation carriers: General practitioner and patient perspectives.

BACKGROUND: General practitioners (GPs) have an increasing role in referring patients with putative mutation in BRCA1/2 genes for genetics consultation and for long-term follow-up of mutation carriers. METHODS: We compared the expectations of the GPs' role according to BRCA1/2 mutation carriers and to GPs themselves. RESULTS: Overall, 38% (58/152) of eligible GPs and 70% (176/252) of eligible patients were surveyed. Although 81% of GPs collected the family history, only 24% considered that they know criteria indicating genetics consultation and 39% sufficient knowledge of BRCA1/2 guidelines to answer patients' questions. Twelve% of GPs were aware of the French national guidelines. Among unsatisfied patients, 40% felt that their GP was able to answer (moderately, sufficiently, or completely) specific questions about BRCA1/2 care as compared with 81% in satisfied patients. Only 33% of GPs reported being informed directly by the geneticist about the patients' results. GPs' main expectations for their role in BRCA1/2 carrier care were psychological support and informing relatives about screening (72% and 71%, respectively), which contrasts with the perceptions of patients, who mainly requested medical advice for BRCA1/2-related care (51%). CONCLUSION: There is an important need for GP training and enhancing interactions between GPs and geneticists to improve the GP's role in BRCA1/2 screening and management.

MoBiDiC Prioritization Algorithm, a Free, Accessible, and Efficient Pipeline for Single-Nucleotide Variant Annotation and Prioritization for Next-Generation Sequencing Routine Molecular Diagnosis.

Interpretation of next-generation sequencing constitutes the main limitation of molecular diagnostics. In diagnosing myopathies and muscular dystrophies, another issue is efficiency in predicting the pathogenicity of variants identified in large genes, especially TTN; current in silico prediction tools show limitations in predicting and ranking the numerous variants of such genes. We propose a variant-prioritization tool, the MoBiDiCprioritization algorithm (MPA). MPA is based on curated interpretation of data on previously reported variants, biological assumptions, and splice and missense predictors, and is used to prioritize all types of single-nucleotide variants. MPA was validated by comparing its sensitivity and specificity to those of dbNSFP database prediction tools, using a data set composed of DYSF, DMD, LMNA, NEB, and TTN variants extracted from expert-reviewed and ExAC databases. MPA obtained the best annotation rates for missense and splice variants. As MPA aggregates the results from several predictors, individual predictor errors are counterweighted, improving the sensitivity and specificity of missense and splice variant predictions. We propose a sequential use of MPA, beginning with the selection of variants with higher scores and followed by, in the absence of candidate pathologic variants, consideration of variants with lower scores. We provide scripts and documentation for free academic use and a validated annotation pipeline scaled for panel and exome sequencing to prioritize single-nucleotide variants from a VCF file.

A Reliable Targeted Next-Generation Sequencing Strategy for Diagnosis of Myopathies and Muscular Dystrophies, Especially for the Giant Titin and Nebulin Genes.

Myopathies and muscular dystrophies (M-MDs) are genetically heterogeneous diseases, with >100 identified genes, including the giant and complex titin (TTN) and nebulin (NEB) genes. Next-generation sequencing technology revolutionized M-MD diagnosis and revealed high frequency of TTN and NEB variants. We developed a next-generation sequencing diagnostic strategy targeted to the coding sequences of 135 M-MD genes. Comparison of two targeted capture technologies (SeqCap EZ Choice library capture kit and Nextera Rapid Capture Custom Enrichment kit) and of two whole-exome sequencing kits (SureSelect V5 and TruSeq RapidExome capture) revealed best coverage with the SeqCap EZ Choice protocol. A marked decrease in coverage was observed with the other kits, affecting mostly the first exons of genes and the repeated regions of TTN and NEB. Bioinformatics analysis strategy was fine-tuned to achieve optimal detection of variants, including small insertions/deletions (INDELs) and copy number variants (CNVs). Analysis of a cohort of 128 patients allowed the detection of 52 substitutions, 13 INDELs (including a trinucleotide repeat expansion), and 3 CNVs. Two INDELs were localized in the repeated regions of NEB, suggesting that these mutations may be frequent but underestimated. A large deletion was also identified in TTN that is, to our knowledge, the first published CNV in this gene.