{"id":"W3182648508","doi":"10.1007/s00125-021-05491-7","title":"Polygenic risk scores predict diabetes complications and their response to intensive blood pressure and glucose control","year":2021,"lang":"en","type":"article","venue":"Diabetologia","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec; Montreal Heart Institute; Public Health Ontario; Ontario Institute for Cancer Research; Université de Montréal","funders":"Fonds de Recherche du Québec - Santé; Université de Montréal; Canada Research Chairs; Ministère de l'Économie, de l’Innovation et des Exportations du Québec; British Heart Foundation; Canadian Institutes of Health Research; National Institute for Health and Care Research; Québec Consortium for Drug Discovery; Institut de Valorisation des Données; Medical Research Council; Institut de Cardiologie de Montréal; Servier","keywords":"Medicine; Diabetes mellitus; Internal medicine; Logistic regression; Type 2 diabetes; Blood pressure; Biobank; Framingham Risk Score; Bioinformatics; Endocrinology; Disease; Biology","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":[0.00237036,0.0009773206,0.000570367,0.0008859535,0.0002015794,0.0007759501,0.0004478532,0.0006446443,0.002416562],"category_scores_gemma":[0.007947064,0.0002620584,0.00140258,0.0009001159,0.0003333938,0.0003250972,0.0007859977,0.0007948754,0.0002645772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001684578,"about_ca_system_score_gemma":0.0003044434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003545501,"about_ca_topic_score_gemma":0.002461564,"domain_scores_codex":[0.998464,0.0008585125,0.0001076777,0.000318485,0.0001282504,0.0001231688],"domain_scores_gemma":[0.9943165,0.003086815,0.001501256,0.000520483,0.0002421472,0.000332843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004655509,0.00007324154,0.988014,0.00001477297,0.0006862146,0.0000838722,0.000021421,0.005088763,0.0005426764,0.0001017535,0.000178983,0.00472871],"study_design_scores_gemma":[0.0000446403,0.0003721223,0.9321994,0.00001314699,0.0004880987,0.0002816214,0.00004500956,0.06528371,0.0003454035,0.0007488442,0.0001564146,0.00002158911],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942905,0.0001721988,0.004446871,0.0001174641,0.00001094052,0.00001676854,0.0005644907,0.00004684956,0.0003338633],"genre_scores_gemma":[0.9982559,0.00003196854,0.001188854,0.00002004937,0.0000106004,0.000009885098,0.0003663215,0.000005138744,0.0001112253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003545501,"threshold_uncertainty_score":0.01253581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00633542172268734,"score_gpt":0.2263784593796591,"score_spread":0.2200430376569718,"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."}}