Amino acid patterns predict white matter integrity measures in the brain in patients across the Alzheimer's disease continuum

Abstract

Alzheimer's disease (AD), the leading cause of dementia, poses a growing global health challenge due to its rising prevalence and socioeconomic impact. Investigating metabolic alterations associated with white matter integrity (WMI) could provide critical insights into AD pathogenesis and identify potential therapeutic targets. This cross-sectional study explored the associations between amino acid (AA) profiles, assessed via ultra-high-performance liquid chromatography (UHPLC), and WMI metrics derived from diffusion tensor imaging (DTI) in individuals across the AD continuum. A total of 176 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were included and grouped into cognitively normal (CN) individuals (n = 54), patients with mild cognitive impairment (MCI, n = 88), and AD patients (n = 34). WMI was evaluated using DTI-derived metrics, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD). AA profiling was conducted using an appropriate panel. Regression analyses, adjusted for age, gender, and education, was used to identify significant associations between AA levels and WMI. Distinct AA alterations were associated with white matter microstructural integrity across study groups. In CN individuals, higher levels of arginine, glycine, and threonine correlated with decreased FA and increased MD, indicating reduced white matter integrity. Conversely, in AD patients, aspartate, glutamate, and histidine exhibited opposite associations, showing positive correlations with FA and negative correlations with MD, suggesting potential neuroprotective or compensatory mechanisms. These findings underscore the associations between AA patterns and white matter integrity and their potential role as AD progression markers. Further investigations into these AA metabolism pathways may identify novel biomarkers for early diagnosis and targets for therapeutic interventions.