{"id":"W4412707941","doi":"10.1038/s41587-025-02725-6","title":"Single-cell polygenic risk scores dissect cellular and molecular heterogeneity of complex human diseases","year":2025,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Servier; Eisai; Wellcome Trust; Janssen Alzheimer Immunotherapy Research And Development; Helmholtz Zentrum München; Northern California Institute for Research and Education; F. Hoffmann-La Roche; Bristol-Myers Squibb; Eli Lilly and Company; Biogen; BioClinica; Pfizer; Meso Scale Diagnostics; Genentech; IXICO; Office of Research and Development; Alzheimer's Association","keywords":"Biology; Polygenic risk score; Computational biology; Genetics; Evolutionary biology; Gene; Genotype; Single-nucleotide polymorphism","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":[0.0004046475,0.0003815583,0.0004070307,0.0008294999,0.0001501128,0.000672315,0.0002780927,0.0003394008,0.0009703444],"category_scores_gemma":[0.001266833,0.0002148873,0.0003461617,0.000654735,0.000430576,0.0005654793,0.0006143551,0.0004193312,0.0001340864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003465631,"about_ca_system_score_gemma":0.0002838869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003263383,"about_ca_topic_score_gemma":0.005005824,"domain_scores_codex":[0.9998877,0.00002789492,0.000005558208,0.00004775192,0.0000180221,0.00001308093],"domain_scores_gemma":[0.9995895,0.0002380455,0.00007604866,0.00004133444,0.00002302955,0.00003206111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003972102,0.00008620392,0.1796524,0.0002084148,0.0005196985,0.000506679,0.0003551447,0.5630826,0.111403,0.02801737,0.001389509,0.1143818],"study_design_scores_gemma":[0.00001369894,0.00006150263,0.05805687,0.00001270764,0.00007785687,0.0001873969,0.00008084076,0.8858172,0.007086107,0.04758556,0.000991919,0.00002832948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6655938,0.0004506122,0.3304847,0.0002077574,0.00001652758,0.00002239306,0.001087598,0.000507895,0.001628693],"genre_scores_gemma":[0.9777676,0.0001986321,0.02114387,0.00003660964,0.000009468368,0.00001422358,0.000438822,0.00004101168,0.0003498302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003263383,"threshold_uncertainty_score":0.0064888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006929992674318174,"score_gpt":0.2388961679714069,"score_spread":0.2319661752970887,"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."}}