{"doi":"10.1101/2025.06.05.658079","title":"Comprehensive molecular impact mapping of common and rare variants at GWAS loci","abstract":", a deep learning model that predicts the effects of genetic variants across diverse biological contexts-including those not directly measured. DNACipher takes 196 kb of genome sequences as input and imputes variant effects across 38,582 cell type-assay combinations. DNACipher generates predictions for >7 times as many contexts as Enformer, which allows for better detection of variant effects at expression quantitative trait loci (eQTLs). We also introduce DNACipher Deep Variant Impact Mapping (DVIM), a method to identify variants with molecular effects at genome-wide association study (GWAS) loci. Application of DVIM to type 1 diabetes (T1D) reduced the mean fine-mapping credible set size from 24 to 1.4 variants per signal. DVIM variants had significantly higher fine-mapping posterior probabilities, and their predicted effects were supported by single-nucleus ATAC-seq and luciferase assays. DVIM also detected 6547 rare variants with molecular effects at 96% of GWAS T1D loci, and these were enriched for associations with immune traits. In summary, DNACipher DVIM prioritises common and rare variants at GWAS loci by predicting molecular effects across a broad range of contexts.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":558180,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8011,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1458638,"name":"Sanjana Tule","orcid":"0000-0001-5630-5792","position":1,"is_corresponding":false},{"id":617299,"name":"Mei-Lin Okino","orcid":null,"position":2,"is_corresponding":false},{"id":1459087,"name":"William JF Rieger","orcid":null,"position":3,"is_corresponding":false},{"id":810609,"name":"Sierra Corban","orcid":null,"position":4,"is_corresponding":false},{"id":378704,"name":"Jeff Jaureguy","orcid":"0000-0002-6303-422X","position":5,"is_corresponding":false},{"id":56525,"name":"Nathan J. Palpant","orcid":"0000-0002-9334-8107","position":6,"is_corresponding":false},{"id":16068,"name":"Kyle J. Gaulton","orcid":"0000-0003-1318-7161","position":7,"is_corresponding":false},{"id":29557,"name":"Mikael Bodén","orcid":"0000-0003-3548-268X","position":8,"is_corresponding":false},{"id":43077,"name":"Graham McVicker","orcid":"0000-0003-0991-0951","position":9,"is_corresponding":false},{"id":56517,"name":"Brad Balderson","orcid":"0000-0002-5153-6601","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:55:25.969263Z","pmid":"40501721","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}