{"doi":"10.1101/2025.09.25.674923","title":"From Correlation to Causation: Cell-Type-Specific Gene Regulatory Networks in Alzheimer’s Disease","abstract":"INTRODUCTION: Alzheimer's disease (AD) involves complex regulatory disruptions across multiple brain cell types, yet a comprehensive understanding of the intracellular causal mechanisms remains unclear. METHODS: We presented an integrative analysis framework using single-nucleus transcriptomic with matched subject-level genotype data from 272 human AD in the Religious Orders Study and the Rush Memory and Aging Project (ROSMAP) study, and constructed causality-based, cell-type-specific gene regulatory networks (GRNs). RESULTS: Our method identifies regulatory genes from both transcription factors (TFs) and non-TFs, thereby capturing a complete and accurate causal regulatory map across different brain cell types. This work revealed both established and novel regulations, pathways, and cell-type-unique hub genes in AD. Beyond constructing transcriptome-wide GRNs, we quantitatively assessed hub genes and distinguished those with regulatory or responsive roles. DISCUSSION: Our study provides a comprehensive mapping of cell-type-specific causal GRNs in AD, providing a powerful resource for dynamic pathway exploration, hypothesis generation, and functional interpretation.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":576000,"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":0.0,"corpus_rank":10062,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.6376,"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":1097026,"name":"Zhongli Jiang","orcid":"0000-0002-7989-6502","position":1,"is_corresponding":false},{"id":675225,"name":"Hyunjin Kim","orcid":"0000-0003-1674-623X","position":2,"is_corresponding":false},{"id":663762,"name":"Anke M. Tukker","orcid":"0000-0001-8973-4809","position":3,"is_corresponding":false},{"id":1484573,"name":"Ashish Dalvi","orcid":null,"position":4,"is_corresponding":false},{"id":663763,"name":"Junkai Xie","orcid":"0009-0001-8758-3741","position":5,"is_corresponding":false},{"id":1484132,"name":"Yan Li","orcid":"0000-0003-3170-2198","position":6,"is_corresponding":false},{"id":631786,"name":"Chongli Yuan","orcid":"0000-0003-3765-0931","position":7,"is_corresponding":false},{"id":426794,"name":"Aaron B. Bowman","orcid":"0000-0001-8728-3346","position":8,"is_corresponding":false},{"id":434589,"name":"Dabao Zhang","orcid":"0000-0003-0629-8672","position":9,"is_corresponding":false},{"id":1097028,"name":"Min Zhang","orcid":"0009-0004-4883-8379","position":10,"is_corresponding":false},{"id":1295694,"name":"D. Liu","orcid":"0000-0002-2863-0288","position":0,"is_corresponding":true}],"reference_count":43,"raw_metadata":null,"created_at":"2026-07-19T02:57:52.712371Z","pmid":"41040299","pmcid":"PMC12485798","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":[]}