1,720,963 research outputs found
Correction to: Genomic reanalysis of a pan-European rare-disease resource yields new diagnoses (Nature Medicine, (2025), 31, 2, (478-489), 10.1038/s41591-024-03420-w)
Full text link\ua9 The Author(s) 2025. Correction to: Nature Medicinehttps://doi.org/10.1038/s41591-024-03420-w, published online 17 January 2025. In the version of this article initially published, collaborators in the Solve-RD DITF-GENTURIS, Solve-RD DITF-ITHACA, Solve-RD DITF-EURO-NMD, Solve-RD DITF-RND and Solve-RD consortia were not listed correctly as authors in the metadata associated with this paper, as is now amended in the HTML and PDF versions of the article
Publisher Correction: Genomic reanalysis of a pan-European rare-disease resource yields new diagnoses
No full textIn the version of this article initially published, collaborators in the Solve-RD DITF-GENTURIS, Solve-RD DITF-ITHACA, Solve-RD DITF-EURO-NMD, Solve-RD DITF-RND and Solve-RD consortia were not listed correctly as authors in the metadata associated with this paper, as is now amended in the HTML and PDF versions of the article
Genomic reanalysis of a pan-European rare-disease resource yields new diagnoses
No full textAbstract: Genetic diagnosis of rare diseases requires accurate identification and interpretation of genomic variants. Clinical and molecular scientists from 37 expert centers across Europe created the Solve-Rare Diseases Consortium (Solve-RD) resource, encompassing clinical, pedigree and genomic rare-disease data (94.5% exomes, 5.5% genomes), and performed systematic reanalysis for 6,447 individuals (3,592 male, 2,855 female) with previously undiagnosed rare diseases from 6,004 families. We established a collaborative, two-level expert review infrastructure that allowed a genetic diagnosis in 506 (8.4%) families. Of 552disease-causing variants identified, 464 (84.1%) were single-nucleotide variants or short insertions/deletions. These variants were either located in recently published novel disease genes (n=67), recently reclassified in ClinVar (n=187) or reclassified by consensus expert decision within Solve-RD (n=210). Bespoke bioinformatics analyses identified the remaining 15.9% of causative variants (n=88). Ad hoc expert review, parallel to the systematic reanalysis, diagnosed 249 (4.1%) additional families for an overall diagnostic yield of 12.6%. The infrastructure and collaborative networks set up by Solve-RD can serve as a blueprint for future further scalable international efforts. The resource is open to the global rare-disease community, allowing phenotype, variant and gene queries, as well as genome-wide discoveries
Unraveling undiagnosed rare disease cases by HiFi long-read genome sequencing
No full textAbstract: Solve-RD is a pan-European rare disease (RD) research program that aims to identify disease-causing genetic variants in previously undiagnosed RD families. We utilized 10-fold coverage HiFi long-read sequencing (LRS) for detecting causative structural variants (SVs), single-nucleotide variants (SNVs), insertion-deletions (indels), and short tandem repeat (STR) expansions in previously studied RD families without a clear molecular diagnosis. Our cohort includes 293 individuals from 114 genetically undiagnosed RD families selected by European Reference Network (ERN) experts. Of these, 21 families were affected by so-called \u201cunsolvable\u201d syndromes for which genetic causes remain unknown and for which prior testing was not a prerequisite. The remaining 93 families had at least one individual affected by a rare neurological, neuromuscular, or epilepsy disorder without a genetic diagnosis despite extensive prior testing. Clinical interpretation and orthogonal validation of variants in known disease genes yielded 12 novel genetic diagnoses due to de novo and rare inherited SNVs, indels, SVs, and STR expansions. In an additional five families, we identified a candidate disease-causing variant, including an MCF2/FGF13 fusion and a PSMA3 deletion. However, no common genetic cause was identified in any of the \u201cunsolvable\u201d syndromes. Taken together, we found (likely) disease-causing genetic variants in 11.8% of previously unsolved families and additional candidate disease-causing SVs in another 5.4% of these families. In conclusion, our results demonstrate the potential added value of HiFi long-read genome sequencing in undiagnosed rare diseases
Publisher Correction: Genomic reanalysis of a pan-European rare-disease resource yields new diagnoses
No full textCorrection to: Nature Medicinehttps://doi.org/10.1038/s41591-024-03420-w, published online 17 January 2025. In the version of this article initially published, collaborators in the Solve-RD DITF-GENTURIS, Solve-RD DITF-ITHACA, Solve-RD DITF-EURO-NMD, Solve-RD DITF-RND and Solve-RD consortia were not listed correctly as authors in the metadata associated with this paper, as is now amended in the HTML and PDF versions of the article.</p
Correction to: The Solve-RD Solvathons as a pan-European interdisciplinary collaboration to diagnose patients with rare disease (Nature Genetics, (2025), 57, 10, (2361-2370), 10.1038/s41588-025-02290-3)
No full text\ua9 Springer Nature America, Inc. 2026.Correction to: Nature Geneticshttps://doi.org/10.1038/s41588-025-02290-3, published online 9 September 2025. In the version of the article initially published, the Supplementary Information did not include the members of the Solve-RD DITF-EPICARE, Solve-RD DITF-ITHACA, Solve-RD DITF-EURO-NMD, Solve-RD DITF-RITA, Solve-RD DITF-RND and Solve-RD consortia. The Supplementary Information has now been corrected to include these lists
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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