{"id":"W4399631066","doi":"10.1016/j.psychres.2024.116030","title":"Neurodevelopmental signature of a transcriptome-based polygenic risk score for depression","year":2024,"lang":"en","type":"article","venue":"Psychiatry Research","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; Centre for Addiction and Mental Health Foundation; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Polygenic risk score; Transcriptome; Signature (topology); Depression (economics); Computational biology; Medicine; Biology; Psychology; Genetics; Gene; Mathematics; Single-nucleotide polymorphism; Genotype; Gene expression","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":[0.0001822397,0.0002559932,0.0002445989,0.0004903229,0.0002416824,0.0004526245,0.0001647302,0.0002817108,0.001421885],"category_scores_gemma":[0.0006352167,0.00009977586,0.000260647,0.0005221333,0.0001407476,0.0001354867,0.0002956892,0.0003834228,0.0001578751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001821096,"about_ca_system_score_gemma":0.0002177179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002123902,"about_ca_topic_score_gemma":0.003424562,"domain_scores_codex":[0.9998562,0.00002653848,0.000008933684,0.00005688169,0.00002146763,0.00002988754],"domain_scores_gemma":[0.9996916,0.00005898939,0.0001443237,0.00002502799,0.00003109068,0.00004899093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001090947,0.0001121975,0.847847,0.00006032661,0.0007196615,0.0008176233,0.0002640175,0.0008190745,0.1330328,0.0004728157,0.0007838703,0.01397969],"study_design_scores_gemma":[0.000003141756,0.00005333602,0.9980298,0.000004723752,0.00006252482,0.0002373651,0.00005269649,0.0004387734,0.0008479918,0.0001465279,0.0001194155,0.000003706206],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976488,0.0001289065,0.0005805914,0.00006742353,0.000006128865,0.000004511925,0.001077307,0.00001023097,0.0004761054],"genre_scores_gemma":[0.9985138,0.00008228633,0.0003595748,0.00003174509,0.000006375837,0.000008844445,0.0007263413,0.000006864335,0.0002641694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002123902,"threshold_uncertainty_score":0.004756749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0881753762474309,"score_gpt":0.3684106894466219,"score_spread":0.280235313199191,"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."}}