{"doi":"10.3233/jad-220608","title":"Associations Between Insulin-Like Growth Factor-1 and Resting-State Functional Connectivity in Cognitively Unimpaired Midlife Adults","abstract":"BACKGROUND: Insulin-like growth factor (IGF)-1 plays an important role in Alzheimer's disease (AD) pathogenesis and increases disease risk. However, prior research examining IGF-1 levels and brain neural network activity is mixed. OBJECTIVE: The present study investigated the relationship between IGF-1 levels and 21 neural networks, as measured by functional magnetic resonance imaging (fMRI) in 13,235 UK Biobank participants. METHODS: Linear mixed models were used to regress IGF-1 against the intrinsic functional connectivity (i.e., degree of network activity) for each neural network. Interactions between IGF-1 and AD risk factors such as Apolipoprotein E4 (APOE4) genotype, sex, AD family history, and age were also tested. RESULTS: Higher IGF-1 was associated with more network activity in the right Executive Function neural network. IGF-1 interactions with APOE4 or sex implicated motor, primary/extrastriate visual, and executive function related neural networks. Neural network activity trends with increasing IGF-1 were different in different age groups. Higher IGF-1 levels relate to much more network activity in the Sensorimotor Network and Cerebellum Network in early-life participants (40-52 years old), compared with mid-life (52-59 years old) and late-life (59-70 years old) participants. CONCLUSION: These findings suggest that sex and APOE4 genotype may modify the relationship between IGF-1 and brain network activities related to visual, motor, and cognitive processing. Additionally, IGF-1 may have an age-dependent effect on neural network connectivity.","journal":"Journal of Alzheimer s Disease","year":2023,"id":361618,"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":8,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9562,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":447573,"name":"Colleen Pappas","orcid":"0000-0001-9140-3558","position":1,"is_corresponding":false},{"id":447566,"name":"Brandon S. Klinedinst","orcid":"0000-0003-2697-1852","position":2,"is_corresponding":false},{"id":447572,"name":"Amy Pollpeter","orcid":"0000-0001-5122-7174","position":3,"is_corresponding":false},{"id":447568,"name":"Brittany Larsen","orcid":"0000-0002-6088-5176","position":4,"is_corresponding":false},{"id":583959,"name":"Nathan Hoth","orcid":null,"position":5,"is_corresponding":false},{"id":1114877,"name":"Faith Anton","orcid":null,"position":6,"is_corresponding":false},{"id":447574,"name":"Qian Wang","orcid":"0000-0003-4250-4744","position":7,"is_corresponding":false},{"id":447577,"name":"Auriel A. Willette","orcid":"0000-0001-5131-8199","position":8,"is_corresponding":false},{"id":558765,"name":"Tianqi Li","orcid":"0000-0001-7215-2546","position":0,"is_corresponding":true}],"reference_count":57,"raw_metadata":null,"created_at":"2026-07-19T01:14:15.063476Z","pmid":"36710671","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":[]}