{"id":"W3128672366","doi":"10.1186/s13073-021-00838-6","title":"Improved prediction of fracture risk leveraging a genome-wide polygenic risk score","year":2021,"lang":"en","type":"article","venue":"Genome Medicine","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill Genome Centre; McGill University Health Centre; University of Manitoba; McGill University; Jewish General Hospital","funders":"Medical Research Council; Fonds de Recherche du Québec - Santé; Department of Epidemiology, Biostatistics and Occupational Health, McGill University; Skånes universitetssjukhus; King's College London; Oxford University Hospitals NHS Foundation Trust; NIHR Oxford Biomedical Research Centre; Wellcome Trust; Sahlgrenska Universitetssjukhuset; Australian Catholic University; Lunds Universitet; Novo Nordisk Fonden; Peking University; National Institute for Health and Care Research; University of Oxford; Canadian Institutes of Health Research; Compute Canada; McGill University","keywords":"Medicine; Confidence interval; Odds ratio; Osteoporosis; Polygenic risk score; Osteoporotic fracture; Demography; Odds; Internal medicine; Risk assessment; Statistics; Physical therapy; Bone mineral; Single-nucleotide polymorphism; Logistic regression; Genetics; Biology; Computer science; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003532729,0.0009120587,0.0005844652,0.001601445,0.0003263253,0.001034356,0.0005323262,0.0006352827,0.001085736],"category_scores_gemma":[0.007227917,0.0002411739,0.001063497,0.001419675,0.0004200776,0.0004505625,0.0008372287,0.0008955022,0.0002782585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002634349,"about_ca_system_score_gemma":0.0004386954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008277956,"about_ca_topic_score_gemma":0.01065445,"domain_scores_codex":[0.9986688,0.0006331964,0.00007023021,0.0003636462,0.0001708248,0.00009324536],"domain_scores_gemma":[0.9960914,0.002176947,0.000812005,0.0004453005,0.000283874,0.0001904208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001344534,0.00003969042,0.9808872,0.00002025495,0.0005106378,0.00006750396,0.00004567111,0.006529777,0.0007498516,0.0001475246,0.0002336162,0.01063369],"study_design_scores_gemma":[0.00003066724,0.0002879618,0.9237448,0.00002565163,0.0005891029,0.0003159886,0.00005616463,0.07243158,0.0004780937,0.001397603,0.0006084723,0.00003378851],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821,0.0004869219,0.01509141,0.0002919202,0.00002370588,0.00002701694,0.001023248,0.0001020658,0.0008538166],"genre_scores_gemma":[0.9945044,0.0001319337,0.004576581,0.00004077321,0.00002599649,0.00001038604,0.0005661307,0.000008346463,0.0001353767],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008277956,"threshold_uncertainty_score":0.01868302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01124584018403255,"score_gpt":0.2336112779811237,"score_spread":0.2223654377970911,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}