Abstract
BACKGROUND: The relationship between plasma chaperone-related autophagy proteins and white matter hyperintensity (WMH) in Alzheimer's disease (AD) remains unclear. METHODS: We employed 4D-DIA proteomics to identify plasma protein changes, and evaluated the clinical relevance of the chaperone-mediated autophagy (CMA)-related protein HSPA8. Additionally, using ITK-SNAP software to assess WMH volume's role in AD. We analyzed the ROC curves for both HSPA8 and WMH in the AD spectrum. Among which, using One-Anova, Kruskal-Wallis, and multivariable logistic analyses to detect the population data. Moreover, the impact of age on WMH volume changes between the AD group and the CN group will be assessed using sensitivity analysis and testing the age-diagnosis interaction. RESULTS: Significant factors in the AD population included age, MMSE score, MoCA score, and WMH volumes. The OR for age in MCI and for WMH volume in AD patients were significant. The expression of HSPA8 was decline in the AD disease spectrum, but it had no statistical difference. Importantly, HSPA8 protein had the highest AUC value for distinguishing between cognitively normal (CN)/mild cognitive impairment (MCI) and MCI/AD groups. Meanwhile, WMH was significant in the AD disease spectrum. And the influence of age on WMH is comparable in cognitively normal elderly individuals and those with AD. Combining HSPA8 with WMH improved the AUC value, which was further enhanced by including age and gender. CONCLUSION: We found that the level of CMA-related protein HSPA8 is decline in the AD disease continuum, and WMH volume may help differentiate the AD spectrum. Moreover, Age is the primary factor influencing WMH changes in both CN and AD groups, with AD status having no significant effect on WMH levels or their progression. Thus, age should be carefully considered when evaluating elevated WMH in AD patients. It is noteworthy that the integration of HSPA8 and WMH may function as a potential early biomarker for AD, thereby enhancing the accuracy of its early diagnosis. Including age and gender increases the diagnostic model's AUC value, indicating HSPA8 and WMH are crucial for early AD diagnosis.