Comprehensive reanalysis for CNVs in ES data from unsolved rare disease cases results in new diagnoses

\ua9 The Author(s) 2024.We report the results of a comprehensive copy number variant (CNV) reanalysis of 9171 exome sequencing datasets from 5757 families affected by a rare disease (RD). The data reanalysed was extremely heterogeneous, having been generated using 28 different enrichment kits by 42 different research groups across Europe partnering in the Solve-RD project. Each research group had previously undertaken their own analysis of the data but failed to identify disease-causing variants. We applied three CNV calling algorithms to maximise sensitivity, and rare CNVs overlapping genes of interest, provided by four partner European Reference Networks, were taken forward for interpretation by clinical experts. This reanalysis has resulted in a molecular diagnosis being provided to 51 families in this sample, with ClinCNV performing the best of the three algorithms. We also identified partially explanatory pathogenic CNVs in a further 34 individuals. This work illustrates the value of reanalysing ES cold cases for CNVs

Muscle Biopsy Findings in Valosin-Containing Protein Multisystem Proteinopathy

Background and Objectives Valosin Containing Protein-associated multisystem proteinopathy (VCP-MSP) is a progressive, autosomal dominant disorder caused by pathogenic variants in the VCP gene, resulting in a heterogeneous clinical presentation. Muscle biopsy findings are characteristic but not pathognomonic. This study aimed to comprehensively analyse VCP-related myopathology and explore correlations with clinical phenotypes, genetic variants, and disease progression. Methods Muscle biopsy images and data were collected retrospectively from adults (>= 18 years) with pathogenic or likely pathogenic VCP variants enrolled in the VCP Multicentre International Study. Biopsy data were standardized using the Common Data Elements for Muscle Biopsy Reporting. Variations in biopsy findings were analysed by biopsy site, time from disease onset, the four most common VCP variants, and clinical phenotypes. Result A total of 112 muscle biopsies were included. Most individuals were male (66.0%). The mean age at biopsy was 53.3 years (SD 10.0), with a mean disease duration of 6.5 years (SD 4.5). The most frequent VCP variant was c.464G>A (p.Arg155His) (18.8%). The top clinical phenotypes were isolated myopathy (37.5%), myopathy with Paget disease of bone (17.9%), and myopathy with motor neuron involvement (13.4%). The vastus lateralis was the most common biopsy site (34.8%), and 91% were open biopsies. Histopathologic findings included atrophic fibres (87.5%), rimmed vacuoles (72.3%), endomysial fibrosis (58.0%), and protein aggregates (51.8%), primarily p62 (60.3%) and VCP (36.2%). Degeneration niches with fibrofatty replacement and atrophic fibres were seen in 33.3% of biopsies without frequency differences by clinical phenotypes. There were no differences in biopsy findings among the 4 most common VCP gene variants, except for the absence of degeneration niches in muscle biopsies of 12 patients with c.277C>T (p.Arg93Cys). MRI data from 30 patients showed fat pockets corresponding to these niches and STIR hyperintensity correlated with inflammatory infiltrates in 42.9%. Concordance between clinical phenotype, biopsy, and neurophysiology was observed in only 49.4% of cases, indicating significant heterogeneity. Discussion VCP-MSP muscle biopsies consistently show myopathic or mixed patterns with rimmed vacuoles and p62/VCP-positive inclusions, regardless of clinical phenotype, age, or progression. Some lack vacuoles, challenging diagnosis. Discrepancies between clinical, neurophysiology, and biopsy findings should prompt consideration of VCP-MSP to improve detection and management

Correction to: Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases

In the original publication of the article, consortium author list was missing in the article

Correction to: Solving patients with rare diseases through programmatic reanalysis of genome-phenome data

In the original publication of the article, consortium author lists were missing in the articl

Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases.

For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient's data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe

Solving unsolved rare neurological diseases-a Solve-RD viewpoint.

Funder: Durch Princess Beatrix Muscle Fund Durch Speeren voor Spieren Muscle FundFunder: University of Tübingen Medical Faculty PATE programFunder: European Reference Network for Rare Neurological Diseases | 739510Funder: European Joint Program on Rare Diseases (EJP-RD COFUND-EJP) | 44140962

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