ABSTRACT BACKGROUND: We investigated the association between path-integration (PI) errors related to entorhinal cortex function detectable using a 3D virtual reality (VR) navigation system and various biomarkers to explore its potential as an early AD indicator. METHODS: The PI capabilities of 111 healthy adults were assessed using a head-mounted 3D VR system. Demographic and cognitive assessments, AD-related plasma biomarkers, and apolipoprotein E genotypes were also evaluated. Predictive factors for PI errors were identified using multivariate linear regression, logistic regression, and random forest. RESULTS: PI errors positively correlated with age, plasma levels of glial fibrillary acidic protein [GFAP], neurofilament light, and p-tau181. Multivariate analysis identified plasma GFAP and p-tau181 levels as significant predictors. Random forest analysis and receiver operating characteristic curves underscored plasma p-tau181 levels as the most substantial predictor. DISCUSSION: PI errors, particularly in conjunction with plasma p-tau181 levels, could reflect early AD pathophysiology, highlighting their potential as early biomarkers.

The authors have declared no competing interest.

This work was supported by the Japan Agency for Medical Research and Development (AMED) under grant number JP21wm0425016

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