{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006710951,0.0002390282,0.0002952741,0.0001658213,0.0001152165,0.000014917,0.0003404605,0.001115669,0.000005945595],"category_scores_gemma":[0.00007850768,0.0002303166,0.0001519648,0.0002030482,0.0004116617,0.000002677663,0.0001910943,0.0004026239,6.674701e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001489016,"about_ca_system_score_gemma":0.00004072997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004426153,"about_ca_topic_score_gemma":0.00007645327,"domain_scores_codex":[0.9987809,0.00006983803,0.0002592001,0.0005280128,0.00009526401,0.0002668041],"domain_scores_gemma":[0.9991825,0.00001573812,0.0001233039,0.0005604853,0.0000600301,0.00005792816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000816259,0.0001738338,0.01697731,0.00007691133,0.00009835171,0.00000597614,0.000004243246,0.000002991628,0.9790671,0.001623949,0.000173819,0.0017139],"study_design_scores_gemma":[0.0006856871,0.0003653916,0.004924913,0.00001910455,0.0001085006,0.000003810097,0.00001510946,0.00003046295,0.9883757,0.0004670042,0.004800112,0.000204264],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808841,0.01619597,0.001923406,0.0002281083,0.0001496158,0.0001998466,0.0001130828,0.00005362813,0.0002522607],"genre_scores_gemma":[0.9984617,0.0003145708,0.0007114406,0.0002238246,0.00003687553,0.000006761626,0.0001560241,0.00002332113,0.00006549748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0175776,"threshold_uncertainty_score":0.9392039,"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."}}