{"doi":"10.3390/jdad2030024","title":"Gray Matter Volume Associations with Montreal Cognitive Assessment Domains in an ADNI Cohort of Early-Onset Mild Cognitive Impairment and Alzheimer’s Disease","abstract":"Background/Objectives: T1-weighted magnetic resonance imaging (MRI) and the Montreal Cognitive Assessment are standard, efficient, and swift clinical and research tools used when interrogating cognitively impairing (CI) conditions, such as Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD). However, the associations between gross cognitive impairment (CI) as compared to domain-specific functioning and underlying neuroanatomical correlates have not been investigated among individuals with early-onset Mild Cognitive Impairment (MCI) or Alzheimer’s disease (EOAD), who can benefit greatly from early diagnosis and intervention strategies. Methods: We analyzed T1-weighted MRIs and Montreal Cognitive Assessment (MoCA) scores from the ADNI database in individuals < 65 years old who were either cognitively normal (CN) or had MCI or EOAD. Gray matter volume (GMV) was estimated in voxel-based morphometry (VBM) and ROI-parcellation general linear models examining associations with individual MoCA scores after adjusting for demographic covariates. Results: Results from 120 subjects (44 CN, 62 MCI, and 14 EOAD), identified significant global but also individually distinct domain-specific topographical signatures spanning the temporal, parietal, limbic, occipital, frontal lobes, and cingulate gyri. Conclusions: The results highlight neural correlates of cognitive functioning in a sample of young patients representative of the AD continuum, in addition to studying the structural MRI and functional cognitive difference.","journal":"Journal of dementia and Alzheimer's disease","year":2025,"id":537170,"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":0.9571,"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":1422971,"name":"Taulant Rama","orcid":"0009-0005-4501-585X","position":1,"is_corresponding":false},{"id":1423436,"name":"Vania Zubair","orcid":null,"position":2,"is_corresponding":false},{"id":290753,"name":"Chuan Huang","orcid":"0000-0001-6052-0663","position":3,"is_corresponding":false},{"id":607052,"name":"Christopher Christodoulou","orcid":"0000-0003-1826-1711","position":4,"is_corresponding":false},{"id":658823,"name":"Allen P. F. Chen","orcid":"0000-0002-6990-7044","position":5,"is_corresponding":false},{"id":343005,"name":"Roman Kotov","orcid":"0000-0001-9569-8381","position":6,"is_corresponding":false},{"id":315310,"name":"Frank D. Mann","orcid":"0000-0002-5450-0620","position":7,"is_corresponding":false},{"id":253335,"name":"on behalf of the Alzheimer’s Disease Neuroimaging Initiative","orcid":null,"position":8,"is_corresponding":false},{"id":476521,"name":"Minos Kritikos","orcid":"0000-0003-2710-0717","position":0,"is_corresponding":true}],"reference_count":58,"raw_metadata":null,"created_at":"2026-07-19T02:52:12.997494Z","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":[]}