{"doi":"10.31234/osf.io/tcuhd","title":"Partial Least Squares analysis of Alzheimer’s disease biomarkers, modifiable health variables, and cognition in older adults with Mild Cognitive Impairment","abstract":"Objective: To identify novel associations between modifiable physical and health variables, Alzheimer’s disease (AD) biomarkers, and cognitive function in a cohort of older adults with Mild Cognitive Impairment (MCI).Method: Metrics of cardiometabolic risk, stress, inflammation, neurotrophic/growth factors, AD, and cognition were assessed in 155 MCI participants (Mean age = 74.2 years) from theAlzheimer’s Disease Neuroimaging Initiative. Partial Least Squares analysis was employed to examine associations among these physiological variables and cognition.Results: Latent variable 1 revealed a unique combination of AD biomarkers, neurotrophic/growth factors, including brain-derived neurotrophic factor, and education that were significantly associated with specific domains of cognitive function, including episodic memory, executive function, and processing speed, representing 47.9% of the covariance in thedata. Age, BMI, and metrics tapping working memory, language or premorbid IQ were not significant.Conclusions: Our data-driven analysis highlights the significant relationships between metrics associated with AD-pathology, neuroprotection, and neuroplasticity with tasks requiring fluid (episodic memory and executive function) rather than crystallized (premorbid IQ and language) ability. These data also indicate that biological metrics are more strongly associated with episodic memory, executive function, and processing speed than chronological age in older adults with MCI.","journal":"PsyArXiv (OSF Preprints)","year":2020,"id":132737,"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":0.5682,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":493522,"name":"Daniela J. Palombo","orcid":"0000-0001-8082-3522","position":1,"is_corresponding":false},{"id":278647,"name":"Jasmeet P. Hayes","orcid":"0000-0002-5157-0666","position":2,"is_corresponding":false},{"id":588750,"name":"Kelly J. Hiersche","orcid":"0000-0003-2609-4298","position":3,"is_corresponding":false},{"id":588751,"name":"Alexander N. Hasselbach","orcid":"0000-0001-5801-741X","position":4,"is_corresponding":false},{"id":431615,"name":"Scott M. Hayes","orcid":"0000-0002-1185-5149","position":5,"is_corresponding":false},{"id":577438,"name":"Jessica Stark","orcid":"0000-0003-3258-7494","position":0,"is_corresponding":true}],"reference_count":19,"raw_metadata":null,"created_at":"2026-07-18T23:16:14.071209Z","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":[]}