Association of Serum Liver Enzymes with Brain Amyloidopathy and Cognitive Performance

dc.contributor.authorHan, Sang-Won
dc.contributor.authorLee, Sang-Hwa
dc.contributor.authorKim, Jong Ho
dc.contributor.authorLee, Jae-Jun
dc.contributor.authorPark, Young Ho
dc.contributor.authorKim, SangYun
dc.contributor.authorNho, Kwangsik
dc.contributor.authorSohn, Jong-Hee
dc.contributor.departmentRadiology and Imaging Sciences, School of Medicine
dc.date.accessioned2024-05-28T11:48:26Z
dc.date.available2024-05-28T11:48:26Z
dc.date.issued2023-12-29
dc.description.abstractBackground: Alzheimer's disease (AD) is characterized by amyloid-β (Aβ) plaque accumulation and neurofibrillary tangles in the brain. Emerging evidence has suggested potential interactions between the brain and periphery, particularly the liver, in regulating Aβ homeostasis. Objective: This study aimed to investigate the association of serum liver enzymes with brain amyloidopathy and cognitive performance in patients with complaints of cognitive decline. Methods: A total of 1,036 patients (mean age 74 years, 66.2% female) with subjective cognitive decline, mild cognitive impairment, AD dementia, and other neurodegenerative diseases were included using the Smart Clinical Data Warehouse. Amyloid positron emission tomography (PET) imaging, comprehensive neuropsychological evaluations, and measurements of liver enzymes, including aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase, total bilirubin, and albumin, were assessed. After propensity score matching, logistic and linear regression analyses were used to investigate the associations between liver enzymes, amyloid status, and cognitive performance. Additionally, a machine learning approach was used to assess the classification performance of liver enzymes in predicting amyloid PET positivity. Results: Lower ALT levels and higher AST-to-ALT ratios were significantly associated with amyloid PET positivity and AD diagnosis. The AST-to-ALT ratio was also significantly associated with poor memory function. Machine learning analysis revealed that the classification performance of amyloid status (AUC = 0.642) for age, sex, and apolipoprotein E ɛ4 carrier status significantly improved by 6.2% by integrating the AST-to-ALT ratio. Conclusions: These findings highlight the potential association of liver function on AD and its potential as a diagnostic and therapeutic implications.
dc.eprint.versionFinal published version
dc.identifier.citationHan SW, Lee SH, Kim JH, et al. Association of Serum Liver Enzymes with Brain Amyloidopathy and Cognitive Performance. J Alzheimers Dis Rep. 2023;7(1):1465-1474. Published 2023 Dec 29. doi:10.3233/ADR-230148
dc.identifier.urihttps://hdl.handle.net/1805/41043
dc.language.isoen_US
dc.publisherIOS Press
dc.relation.isversionof10.3233/ADR-230148
dc.relation.journalJournal of Alzheimer's Disease Reports
dc.rightsAttribution-NonCommercial 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.sourcePMC
dc.subjectAlzheimer’s disease
dc.subjectAmyloid PET
dc.subjectCognition
dc.subjectLiver enzymes
dc.subjectMachine learning
dc.titleAssociation of Serum Liver Enzymes with Brain Amyloidopathy and Cognitive Performance
dc.typeArticle
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