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

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

Development and validation of a Type 1 and Type 2 diabetes-specific patient-reported experience measure e-questionnaire: Diabetes reported experience measures (DREMS)

Introduction: Successful diabetes management is associated with an effective partnership between People with Diabetes (PwD) and healthcare professionals. Though possible to measure using Patient-Reported Experience Measures (PREMs), none are specific to Type 1 or Type 2 Diabetes (T1D/T2D) and validated in French. Thus, we developed and validated the DREMS (Diabetes Reported Experience MeasureS) e-questionnaire. Methodology: DREMS is comprised of 18 items evaluating 5 different factors. Validation for use by PwT1D and PwT2D (recruited online) was performed using: Exploratory Factor Analysis (EFA); Confirmatory Factor Analysis (CFA) and Cronbach's Alpha. Test-retest reliability was evaluated through Intraclass Correlation Coefficients (ICC) in a subsample. Results: DREMS was tested by 2,513 respondents, including 942 PwT1D and 1,571 PwT2D. For both groups, EFA results indicated 18 items loaded substantially onto 5 clear factors. CFA showed all coefficients were significant in their respective factors. Goodness-of-fit, assessed using the Comparative Fit Index was >0.90 and by the RMSEA was <0.080. Cronbach's α for the entire DREMS e-questionnaire was ≥0.90. ICC was 0.87 for PwT1D (n = 136) and 0.74 for PwT2D (n = 169). Innovation: DREMS is the first validated French-language diabetes-specific PREM for both PwT1D and PwT2D and can be useful to evaluate and improve health care management and patient health

Large-scale migration into Britain during the Middle to Late Bronze Age

Present-day people from England and Wales harbour more ancestry derived from Early European Farmers (EEF) than people of the Early Bronze Age . To understand this, we generated genome-wide data from 793 individuals, increasing data from the Middle to Late Bronze and Iron Age in Britain by 12-fold, and Western and Central Europe by 3.5-fold. Between 1000 and 875 BC, EEF ancestry increased in southern Britain (England and Wales) but not northern Britain (Scotland) due to incorporation of migrants who arrived at this time and over previous centuries, and who were genetically most similar to ancient individuals from France. These migrants contributed about half the ancestry of Iron Age people of England and Wales, thereby creating a plausible vector for the spread of early Celtic languages into Britain. These patterns are part of a broader trend of EEF ancestry becoming more similar across central and western Europe in the Middle to Late Bronze Age, coincident with archaeological evidence of intensified cultural exchange . There was comparatively less gene flow from continental Europe during the Iron Age, and Britain's independent genetic trajectory is also reflected in the rise of the allele conferring lactase persistence to ~50% by this time compared to ~7% in central Europe where it rose rapidly in frequency only a millennium later. This suggests that dairy products were used in qualitatively different ways in Britain and in central Europe over this period. [Abstract copyright: © 2021. The Author(s), under exclusive licence to Springer Nature Limited.

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

: 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