Implications of serum liver enzymes for brain amyloidopathy and cognition

Author:

Han Sang-Won1,Lee Sang-Hwa1,Kim Jong Ho1,Lee Jae-Jun1,Park Young Ho2,Kim SangYun2,Nho Kwangsik3,Sohn Jong-Hee1

Affiliation:

1. Chuncheon Sacred Heart Hospital

2. Seoul National University Bundang Hospital

3. Indiana University School of Medicine

Abstract

Abstract Background 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 peripheral organs, particularly the liver, in regulating Aβ homeostasis. This study aimed to investigate the association of serum liver enzymes with brain amyloidopathy and cognitive performance as the precise relationship remains unclear. Methods This retrospective study analyzed data collected between November 2015 and June 2023 using a clinical big data analytic solution called the Smart Clinical Data Warehouse (CDW). A total of 1,036 patients with subjective cognitive decline (SCD), mild cognitive impairment (MCI), AD dementia, and other neurodegenerative diseases were included in the study. Amyloid positron emission tomography (PET) imaging, comprehensive neuropsychological evaluations, and measurements of liver enzymes, including aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), total bilirubin, and albumin, were assessed. 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 status. Results Lower ALT levels (OR, 0.976; 95% CI, 0.957–0.994; P = 0.031) and higher AST-to-ALT ratios (OR, 1.862; 95% CI, 1.397–2.521; P < 0.001) were significantly associated with amyloid PET positivity. The AST-to-ALT ratio wasalsosignificantly associated with poor memory function. Machine learning analysis revealed that the classification performance of amyloid status (area under the curve (AUC) = 0.642) for age, sex, and apolipoprotein E ε4 carrier status significantly improved by 6.2% by integrating the AST-to-ALT ratio. Conclusions The association of lower ALT levels and a higher AST-to-ALT ratio with amyloid status in the brain suggests potential implications of liver function in the Aβ pathogenesis of AD. Moreover, the AST-to-ALT ratio showed promising associations with memory function, and its integration with clinical information improved the classification performance of amyloid status in the brain.

Publisher

Research Square Platform LLC

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