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

Altered contractility of skeletal muscle in mice deficient in titin's M-Band region

We investigated the contractile phenotype of skeletal muscle deficient in the titin's M-band exons MEx1 and MEx2 (KO) by using the cre-lox recombination system and a multidisciplinary physiological approach to study skeletal muscle contractile performance. At a maximal tetanic stimulation frequency, intact KO EDL muscle was able to produce wildtype levels of force. However, at submaximal stimulation frequency force was reduced in KO mice giving rise to a rightward shift of the force-frequency curve. This rightward shift of the force-frequency curve could not be explained by altered sarcoplasmic reticulum Ca(2+)handling as indicated by analysis of Ca(2+)transients in intact myofibers and expression of Ca(2+)handling proteins, but can be explained by the reduced myofilament Ca(2+)sensitivity of force generation that we found. Western blotting experiments suggested that the excision of titin exons MEx1 and MEx2 did not result in major changes in expression of titin M-band binding proteins or phosphorylation level of the thin filament regulatory proteins, but rather in a shift towards expression of slow isoforms of the thick filament-associated protein myosin binding protein-C (MyBP-C). Extraction of MyBP-C from skinned muscle normalized myofilament Ca(2+)sensitivity of KO EDL muscle. Thus, our data suggest that the M-band region of titin affects the expression of genes involved in the regulation of skeletal muscle contraction

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press