{"id":"W4285728547","doi":"10.1186/s13073-022-01077-z","title":"Adipose methylome integrative-omic analyses reveal genetic and dietary metabolic health drivers and insulin resistance classifiers","year":2022,"lang":"en","type":"article","venue":"Genome Medicine","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Vetenskapsrådet; Agence Nationale de la Recherche; National Institute for Health and Care Research; Biotechnology and Biological Sciences Research Council; Joint Programming Initiative A healthy diet for a healthy life; Wellcome Trust; Medical Research Council; Wellcome","keywords":"Epigenetics; DNA methylation; Insulin resistance; Biology; Epigenome; Adipose tissue; Body mass index; Methylation; Metabolic syndrome; Bioinformatics; Metabolomics; Genetics; Phenotype; Endocrinology; Internal medicine; Medicine; Obesity; Gene; Gene expression","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001394904,0.0005938986,0.0007583743,0.001360962,0.0004077758,0.001095166,0.0004163657,0.0004353444,0.002683034],"category_scores_gemma":[0.001916818,0.0002733985,0.001243705,0.001560492,0.0002276069,0.0003674287,0.001176822,0.0006800907,0.0005475278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003196135,"about_ca_system_score_gemma":0.0005029284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00280195,"about_ca_topic_score_gemma":0.006352463,"domain_scores_codex":[0.9994165,0.0001143899,0.00003899204,0.0002724855,0.00008680678,0.00007091845],"domain_scores_gemma":[0.9992278,0.0002438183,0.0002160343,0.0001412218,0.000111188,0.00005996906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001833528,0.00009917512,0.6254426,0.00105965,0.006409117,0.0005646354,0.0006076661,0.003337993,0.2720725,0.001722301,0.002618758,0.08423211],"study_design_scores_gemma":[0.00006970302,0.0002595413,0.9548395,0.0001743911,0.003063101,0.0007927557,0.000333792,0.007380098,0.01844472,0.003641154,0.0109525,0.00004877465],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9230013,0.009329982,0.03680944,0.0007246022,0.00007883516,0.00008030714,0.02559724,0.0005045792,0.003873742],"genre_scores_gemma":[0.962977,0.00198156,0.01866855,0.0004260197,0.00005175653,0.00009161358,0.01414213,0.0001682369,0.001493114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00280195,"threshold_uncertainty_score":0.008975685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03224243439984201,"score_gpt":0.3161876950520858,"score_spread":0.2839452606522438,"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."}}