{"doi":"10.1002/hbm.70407","title":"Investigating Disruptions in Information Flow due to Sickle Cell Disease Using Granger Causality","abstract":"ABSTRACT Sickle cell disease (SCD) is an inherited blood disorder caused by a mutation in the beta‐globin gene, resulting in chronic complications, including cognitive decline—particularly in executive functions. Neuroimaging studies have identified structural and functional abnormalities associated with SCD; however, the directionality of information flow between brain networks and how disruptions in these interactions contribute to cognitive deficits remains poorly understood. This study employed Granger causality (GC) analysis to investigate effective connectivity and information flow between brain regions and resting‐state networks using ultra‐high‐field 7T MRI in adult patients with SCD ( n = 51) and age‐, sex‐, and race‐matched controls ( n = 44). We first performed a whole‐brain network analysis, followed by an examination of specific brain regions within the default mode network (DMN), executive control network (ECN), dorsal attention network (DAN), and ventral attention network (VAN). For each analysis, we computed both the magnitude and directionality of information flow to capture the strength and directional influence of connectivity between brain regions. While patients with SCD exhibited a higher magnitude of information flow compared to controls, this difference was only statistically significant when computed at the brain region level, not at the resting‐state network level. In terms of directionality, afferent flow from DAN and VAN to ECN was significantly greater in patients with SCD than in controls. Subtype analysis revealed that patients with severe SCD demonstrated significantly higher magnitude of information flow than those with mild SCD and controls. We also observed subtype‐specific differences in afferent flow to ECN: mild SCD patients showed significant flow from VAN, while severe SCD patients showed significant flow from DAN. Additionally, multiple regression analyzes assessing correlations between information flow and cognitive performance showed that controls had higher R 2 values than patients with SCD, suggesting reduced network efficiency in SCD. This study is the first to apply GC‐based effective connectivity analysis in SCD, revealing unique pathways of information exchange in patients with SCD, potentially as compensatory mechanisms for disease‐related structural and functional disruptions. These findings provide novel insights into how SCD impacts brain network organization and cognitive function, emphasizing the importance of investigating network‐level dynamics in this population.","journal":"Human Brain Mapping","year":2025,"id":580240,"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":0.9534,"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":652063,"name":"Helmet T. Karim","orcid":"0000-0002-9286-0694","position":1,"is_corresponding":false},{"id":528818,"name":"Nadim Farhat","orcid":"0000-0002-6443-9165","position":2,"is_corresponding":false},{"id":528816,"name":"Tales Santini","orcid":"0000-0003-4533-9190","position":3,"is_corresponding":false},{"id":379109,"name":"Enrico M. Novelli","orcid":"0000-0003-3010-8285","position":4,"is_corresponding":false},{"id":1396046,"name":"Tamer S. Ibrahim","orcid":"0000-0001-5338-5635","position":5,"is_corresponding":false},{"id":528815,"name":"Sossena Wood","orcid":"0000-0003-3079-1096","position":6,"is_corresponding":false},{"id":809807,"name":"Nahom Mossazghi","orcid":null,"position":0,"is_corresponding":true}],"reference_count":41,"raw_metadata":null,"created_at":"2026-07-19T02:58:38.868285Z","pmid":"41195759","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":[]}