{"doi":"10.1093/jamia/ocab050","title":"Finding commonalities in rare diseases through the undiagnosed diseases network","abstract":"OBJECTIVE: When studying any specific rare disease, heterogeneity and scarcity of affected individuals has historically hindered investigators from discerning on what to focus to understand and diagnose a disease. New nongenomic methodologies must be developed that identify similarities in seemingly dissimilar conditions. MATERIALS AND METHODS: This observational study analyzes 1042 patients from the Undiagnosed Diseases Network (2015-2019), a multicenter, nationwide research study using phenotypic data annotated by specialized staff using Human Phenotype Ontology terms. We used Louvain community detection to cluster patients linked by Jaccard pairwise similarity and 2 support vector classifier to assign new cases. We further validated the clusters' most representative comorbidities using a national claims database (67 million patients). RESULTS: Patients were divided into 2 groups: those with symptom onset before 18 years of age (n = 810) and at 18 years of age or older (n = 232) (average symptom onset age: 10 [interquartile range, 0-14] years). For 810 pediatric patients, we identified 4 statistically significant clusters. Two clusters were characterized by growth disorders, and developmental delay enriched for hypotonia presented a higher likelihood of diagnosis. Support vector classifier showed 0.89 balanced accuracy (0.83 for Human Phenotype Ontology terms only) on test data. DISCUSSIONS: To set the framework for future discovery, we chose as our endpoint the successful grouping of patients by phenotypic similarity and provide a classification tool to assign new patients to those clusters. CONCLUSION: This study shows that despite the scarcity and heterogeneity of patients, we can still find commonalities that can potentially be harnessed to uncover new insights and targets for therapy.","journal":"Journal of the American Medical Informatics Association","year":2021,"id":200033,"datarank":0.7153557136152485,"base_score":2.1972245773362196,"endowment":2.1972245773362196,"self_citation_contribution":0.32958368660043297,"citation_network_contribution":0.38577202701481556,"self_endowment_contribution":0.32958368660043297,"citer_contribution":0.38577202701481556,"corpus_percentile":71.9579175369382,"corpus_rank":3626,"citation_count":8,"citer_count":8,"citers_with_citation_signal":5,"citers_with_endowment":5,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.8009,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":22.9167,"fair_percentile":40.53806175481504,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":488860,"name":"Alba Gutiérrez‐Sacristán","orcid":"0000-0002-1245-198X","position":1,"is_corresponding":false},{"id":554592,"name":"Vianney Jouhet","orcid":"0000-0001-5272-2265","position":2,"is_corresponding":false},{"id":514626,"name":"Kimberly LeBlanc","orcid":"0000-0003-3828-9447","position":3,"is_corresponding":false},{"id":464474,"name":"Cecilia Esteves","orcid":null,"position":4,"is_corresponding":false},{"id":276384,"name":"Undiagnosed Diseases Network","orcid":null,"position":5,"is_corresponding":false},{"id":777703,"name":"Thomas DeSain","orcid":null,"position":6,"is_corresponding":false},{"id":777704,"name":"Nick Benik","orcid":null,"position":7,"is_corresponding":false},{"id":427687,"name":"Jason Stedman","orcid":"0000-0002-0718-5648","position":8,"is_corresponding":false},{"id":249689,"name":"Nathan Palmer","orcid":"0000-0002-4361-207X","position":9,"is_corresponding":false},{"id":477755,"name":"Guillaume Mellon","orcid":"0000-0002-7009-7253","position":10,"is_corresponding":false},{"id":3527,"name":"Isaac S. Kohane","orcid":"0000-0003-2192-5160","position":11,"is_corresponding":false},{"id":74694,"name":"Paul Avillach","orcid":"0000-0002-0235-7543","position":12,"is_corresponding":false},{"id":777146,"name":"Josephine Yates","orcid":"0000-0001-8346-4502","position":0,"is_corresponding":true}],"reference_count":39,"raw_metadata":null,"created_at":"2026-07-18T23:50:44.479665Z","pmid":"34009343","pmcid":"PMC8324228","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":22.2222,"fair_a":37.5,"fair_i":40.0,"fair_r":45.8333,"fair_zscore":-0.4565,"fair_rationale":{"fair_score":22.92,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":22.22,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No persistent identifier (DOI, Handle, ARK, or repository accession) is provided for the study's own dataset.","anchors":["RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit","RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier'","FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"UDN data are available to approved researchers only.","grounded":true,"rationale":"The Undiagnosed Diseases Network is named as the holder, but it is not a data repository in the class 1 list. 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[majority verdict 'no' (3/5 passes agreed)]","anchors":["RDA-I3-01M — '(meta)data include references to other (meta)data'","RDA-I3-03M — 'metadata includes qualified references to other metadata'","FsF-I3-01M — F-UJI: 'Metadata includes links between the data and its related entities'"],"scored":false,"signal":null}]},"R":{"name":"Reusable","score":45.83,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No license is attached to the data; the CC BY license applies to the article only, not the data.","anchors":["RDA-R1.1-01M — 'Metadata includes information about the licence under which the data can be reu","RDA-R1.1-02M — 'Metadata refers to a standard reuse licence'","RDA-R1.1-03M — 'Metadata refers to a machine-understandable reuse licence'"],"scored":true,"signal":null},{"key":"r_provenance_methods","label":"Provenance of the data","kind":"llm","weight":1.0,"fraction":0.5,"verdict":"partial","evidence":"This observational study analyzes 1042 patients from the Undiagnosed Diseases Network (2015-2019), a multicenter, nationwide research study using phenotypic data annotated by specialized staff using Human Phenotype Ontology terms.","grounded":true,"rationale":"The data collection is described in generic terms (annotated by staff) without naming specific instruments, kits, or software versions. 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A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For clinical / human-subjects data, deposit in dbGaP or the European Genome-phenome Archive (EGA).","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No persistent identifier (DOI, Handle, ARK, or repository accession) is provided for the study's own dataset.","gain":16.67,"priority":"essential","scored":true},{"key":"a_data_openly_accessible","dimension":"A","label":"Access route free of preconditions","action":"Remove the precondition or justify it. Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it. 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