Genomic reanalysis of a pan-European rare-disease resource yields new diagnoses
Bibliographic record
Abstract
Funder: The Solve-RD consortium is grateful to all involved rare disease patients and their families as well as other contributors to Solve-RD. The Solve-RD project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257 (to all authors). This research is supported (not financially) by four ERNs: (1) The ERN for Intellectual Disability, Telehealth and Congenital Anomalies (ERN ITHACA)—Project ID No 101085231; (2) The ERN on Rare Neurological Diseases (ERN RND)—Project ID No 101155994; (3) The ERN for Neuromuscular Diseases (ERN Euro-NMD)—Project ID No 101156434; (4) The ERN on Genetic Tumour Risk Syndromes (ERN GENTURIS)—Project ID No 101155809. The ERNs are co-funded by the European Union within the framework of the Third Health Programme. The RD-Connect Genome-Phenome Analysis platform developed under FP7/2007–2013 funded project (grant agreement n° 305444) and ongoing funding from EJP-RD (grant numbers H2020 779257, H2020 825575), Instituto de Salud Carlos III (Grant numbers PT13/0001/0044, PT17/0009/0019; Instituto Nacional de Bioinformática, INB), ELIXIR-EXCELERATE (Grant number EU H2020 #676559) and ELIXIR Implementation Studies (Remote real-time visualisation of human rare disease genomics data (RD-Connect) stored at the EGA ELIXIR. 2017-2018; ELIXIR IT-2017-INTEGRATION, Rare Disease Infrastructure ELIXIR, 2019-2020 and the Beacon ELIXIR, 2019-2021). The RD-Connect GPAP has leveraged developments funded through project VEIS (001-P-001647 co-financed by the European Regional Development Fund of the European Union in the framework of the Operational Program FEDER of Catalonia 2014-2020 with the support of the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya) and URD-Cat (PERIS SLT002/16/00174, Departament de Salut, Generalitat de Catalunya). The Spanish academic and research network RedIris (https://www.rediris.es/) provided the Aspera service used for uploading raw data for processing to the RD-Connect GPAP, and for transferring data between centres. Netherlands Science Organisations (NWO VIDI 917.164.55 to C.G.). Ministero della Salute (Genoma mEdiciNa pERsonalizzatA, T3-AN-04, to V.N., A.R., and M.T.). The “Network for Italian Genomes - NIG”, “Cell lines and DNA bank of Rett Syndrome, X-linked mental retardation and other genetic diseases”, member of the Telethon Network of Genetic Biobanks (project no. GTB12001), and EuroBioBank network. H.L. receives support from the Canadian Institutes of Health Research (CIHR) for Foundation Grant FDN-167281 (Precision Health for Neuromuscular Diseases), Transnational Team Grant ERT-174211 (ProDGNE) and Network Grant OR2-189333 (NMD4C), from the Canada Foundation for Innovation (CFI-JELF 38412), the Canada Research Chairs program (Canada Research Chair in Neuromuscular Genomics and Health, 950-232279), the European Commission (grant number 101080249) and the Canada Research Coordinating Committee New Frontiers in Research Fund (NFRFG-2022-00033) for SIMPATHIC, and from the Government of Canada Canada First Research Excellence Fund (CFREF) for the Brain-Heart Interconnectome (CFREF-2022-00007). K.P. is a recipient of a Canadian Institutes of Health Research (CIHR) postdoctoral fellowship award under award no: MFE-491707 This work was furthermore supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) No 441409627, as part of the PROSPAX consortium under the frame of EJP RD, the European Joint Programme on Rare Diseases, under the EJP RD COFUND-EJP N° 825575 (to M.Sy., R.S., and R.H.,) and the Clinician Scientist programme "PRECISE.net" funded by the Else Kröner-Fresenius-Stiftung (to C.W., M.K., R.S. and M.Sy.). J.P.S. was financed by Programme EXCELES, (ID Project No. LX22NPO5107) - Funded by the European Union – Next Generation EU. B.v.d.W. is supported by ZonMW, the Gossweiler Foundation, and the ‘Hersenstichting’. The work of F.Mun. was also supported by Muscular Dystrophy UK, and Muscular Dystrophy USA. H.G. and T.B.H. are supported by the European Union’s Horizon 2020 research and innovation program project Recon4IMD (grant number 101080997). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".