{"id":"W4376132263","doi":"10.1002/alz.13069","title":"Alzheimer's disease heterogeneity explained by polygenic risk scores derived from brain transcriptomic profiles","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; CurePSP; Servier; Eisai; Northern California Institute for Research and Education; H. Lundbeck A/S; Rush University; Eli Lilly and Company; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Mayo Foundation for Medical Education and Research; University of Pennsylvania; University of Southern California; Biogen; Pfizer; BioClinica; Translational Genomics Research Institute; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb","keywords":"Senile plaques; Disease; Transcriptome; Alzheimer's disease; Atrophy; Cognition; Neuroimaging; Dementia; Neuroscience; Psychology; Biology; Medicine; Gene; Pathology; Genetics; Gene expression","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007205142,0.0004559961,0.0005681122,0.001604639,0.0003059822,0.0007192314,0.0002095494,0.0002527042,0.001008238],"category_scores_gemma":[0.00196052,0.0001521814,0.0007304184,0.001576383,0.0003117138,0.0003898591,0.0005307053,0.0002932039,0.0001492466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002961318,"about_ca_system_score_gemma":0.0002443355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002021522,"about_ca_topic_score_gemma":0.001938464,"domain_scores_codex":[0.9995214,0.0001132064,0.00002869283,0.0002168737,0.00005224971,0.00006757103],"domain_scores_gemma":[0.9988995,0.000470066,0.0003767908,0.0001093623,0.00007647126,0.00006788399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004791038,0.00004764136,0.9281106,0.0001507986,0.001387764,0.0002474296,0.0002572502,0.008603776,0.04197426,0.0008344506,0.0004449862,0.01746201],"study_design_scores_gemma":[0.000009268035,0.0000614266,0.9686055,0.00001857625,0.0003593664,0.0002319965,0.00008068964,0.02511453,0.001435549,0.003675046,0.0003855597,0.00002248948],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896108,0.000446688,0.007933553,0.00005878623,0.000004165316,0.00001240582,0.001534461,0.0000432667,0.0003559503],"genre_scores_gemma":[0.9972005,0.0001113352,0.001341946,0.00001726648,0.000006817285,0.00001494752,0.001213035,0.000008316213,0.00008578182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002021522,"threshold_uncertainty_score":0.004019558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02944654353984587,"score_gpt":0.3036451101487129,"score_spread":0.274198566608867,"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."}}