{"doi":"10.64898/2026.02.03.702791","title":"Federated cross-biobank conditional analysis identifies LDL-C lowering effects of\n                  <i>DNAJC13</i>\n                  haploinsufficiency and\n                  <i>LDLR</i>\n                  regulation","abstract":"<jats:title>Abstract</jats:title>\n                <jats:p>\n                  Whole genome sequencing in diverse population-scale biobanks offers new insights into the genetic architecture of complex traits from rare and non-coding variants. However, rare single variant and aggregate associations are often confounded by linkage disequilibrium and haplotype structure, resulting in large numbers of false-positive associations. Previous methods that rely on reference panels or linkage disequilibrium-matrices to determine conditional independence in meta-analyses do not scale to very rare variants, which may be observed in only one biobank and can exhibit long-range haplotypes. Here, we implement a federated approach to perform iterative conditional meta-analysis on individual-level genotype and phenotype data across biobanks while adhering to data sharing policies. We applied our methodology to a meta-analysis of LDL-C in 614,375 individuals from UK Biobank and All of Us, encompassing six genetic ancestry groups. After conditioning, only 4.3% of significantly associated rare single variants and 6.9% of aggregates remained statistically independent. The proportion of significant aggregates that remained independent after conditioning was higher for coding-based tests than non-coding. We further validate that our approach effectively suppresses false-positive associations using simulations centred on the\n                  <jats:italic>LDLR</jats:italic>\n                  locus. We identify allelic series of variants associated with reduced LDL-C, including loss-of-function variants in\n                  <jats:italic>DNAJC13</jats:italic>\n                  and variants in the 3-prime untranslated region of\n                  <jats:italic>LDLR</jats:italic>\n                  . Our results highlight that federated conditioning can distinguish independent rare variant signals from linkage and haplotype structure artifacts in multi-ancestry meta-analyses across separate biobanks.\n                </jats:p>","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2026,"id":2185,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0572,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2026-02-05","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":25374,"name":"Liza Darrous","orcid":"0000-0002-0056-4127","position":1,"is_corresponding":false},{"id":25375,"name":"Lauric Ferrat","orcid":"0000-0002-3166-9685","position":2,"is_corresponding":false},{"id":25376,"name":"V. Kartik Chundru","orcid":"0000-0002-6348-5565","position":3,"is_corresponding":false},{"id":25377,"name":"Aurelie Kamoun","orcid":null,"position":4,"is_corresponding":false},{"id":5328,"name":"Katharina Domschke","orcid":"0000-0002-2550-9132","position":5,"is_corresponding":false},{"id":25378,"name":"Caroline F. Wright","orcid":"0000-0003-2958-5076","position":6,"is_corresponding":false},{"id":25379,"name":"Kashyap A. Patel","orcid":"0000-0002-9240-8104","position":7,"is_corresponding":false},{"id":16114,"name":"Timothy M. Frayling","orcid":"0000-0001-8362-2603","position":8,"is_corresponding":false},{"id":22004,"name":"Michael N. Weedon","orcid":"0000-0002-6174-6135","position":9,"is_corresponding":false},{"id":25380,"name":"Robin N. Beaumont","orcid":null,"position":10,"is_corresponding":false},{"id":25381,"name":"Gareth Hawkes","orcid":"0000-0002-3367-789X","position":11,"is_corresponding":false},{"id":25382,"name":"Wood Ar","orcid":null,"position":12,"is_corresponding":false},{"id":25383,"name":"C David Wright","orcid":null,"position":13,"is_corresponding":false},{"id":25373,"name":"Harrison I.W. Wright","orcid":"0009-0009-1900-163X","position":0,"is_corresponding":true}],"reference_count":47,"raw_metadata":null,"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"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":[]}