Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Unexpected relevant role of gene mosaicism in patients with primary immunodeficiency diseases

BACKGROUND: Postzygotic de novo mutations lead to the phenomenon of gene mosaicism. The 3 main types are called somatic, gonadal, and gonosomal mosaicism, which differ in terms of the body distribution of postzygotic mutations. Mosaicism has been reported occasionally in patients with primary immunodeficiency diseases (PIDs) since the early 1990s, but its real involvement has not been systematically addressed. OBJECTIVE: We sought to investigate the incidence of gene mosaicism in patients with PIDs. METHODS: The amplicon-based deep sequencing method was used in the 3 parts of the study that establish (1) the allele frequency of germline variants (n = 100), (2) the incidence of parental gonosomal mosaicism in families with PIDs with de novo mutations (n = 92), and (3) the incidence of mosaicism in families with PIDs with moderate-to-high suspicion of gene mosaicism (n = 36). Additional investigations evaluated body distribution of postzygotic mutations, their stability over time, and their characteristics. RESULTS: The range of allele frequency (44.1% to 55.6%) was established for germline variants. Those with minor allele frequencies of less than 44.1% were assumed to be postzygotic. Mosaicism was detected in 30 (23.4%) of 128 families with PIDs, with a variable minor allele frequency (0.8% to 40.5%). Parental gonosomal mosaicism was detected in 6 (6.5%) of 92 families with de novo mutations, and a high incidence of mosaicism (63.9%) was detected among families with moderate-to-high suspicion of gene mosaicism. In most analyzed cases mosaicism was found to be both uniformly distributed and stable over time. CONCLUSION: This study represents the largest performed to date to investigate mosaicism in patients with PIDs, revealing that it affects approximately 25% of enrolled families. Our results might have serious consequences regarding treatment and genetic counseling and reinforce the use of next-generation sequencing-based methods in the routine analyses of PIDs

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose: Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods: Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results: We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion: The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Ankylosing spondylitis: an autoimmune or autoinflammatory disease?

Ankylosing spondylitis (AS) is a chronic inflammatory disorder of unknown aetiology. Unlike other systemic autoimmune diseases, in AS, the innate immune system has a dominant role characterized by aberrant activity of innate and innate-like immune cells, including γδ T cells, group 3 innate lymphoid cells, neutrophils, mucosal-associated invariant T cells and mast cells, at sites predisposed to the disease. The intestine is involved in disease manifestations, as it is at the forefront of the interaction between the mucosal-associated immune cells and the intestinal microbiota. Similarly, biomechanical factors, such as entheseal micro-trauma, might also be involved in the pathogenesis of the articular manifestation of AS, and sentinel immune cells located in the entheses could provide links between local damage, genetic predisposition and the development of chronic inflammation. Although these elements might support the autoinflammatory nature of AS, studies demonstrating the presence of autoantibodies (such as anti-CD74, anti-sclerostin and anti-noggin antibodies) and evidence of activation and clonal expansion of T cell populations support an autoimmune component to the disease. This Review presents the evidence for autoinflammation and the evidence for autoimmunity in AS and, by discussing the pathophysiological factors associated with each, aims to reconcile the two hypotheses.</p