Eye-brain coupling-mediated eye movement abnormalities as non-invasive biomarkers for mild cognitive impairment: A
Yi Li1, Jiaxin Feng1, Yanhong Xie2
1College of Teacher Education, Ningbo University, Ningbo, China.
Abstract:
BackgroundEye movement abnormalities have emerged as promising non-invasive candidate biomarkers for the early detection, progression monitoring, and differential diagnosis of Alzheimer's disease (AD), with preliminary clinical evidence supporting their translational potential. Current AD diagnostic methods are limited by subjectivity, high cost, and complexity-making non-invasive biomarkers critical, especially for mild cognitive impairment (MCI). The tight functional link between the eye and brain underscores eye movement abnormalities as a window into AD-related pathology.ObjectiveThis systematic review summarizes AD-associated multi-modal eye movement dysfunctions (focusing on saccades, fixation, and smooth pursuit), clarifies their pathological mechanisms, clinical value, and translational feasibility, providing a basis for constructing an AD biomarker system.MethodsLiterature searches were conducted in PubMed, Web of Science, and Google Scholar using ("Alzheimer's disease" OR "mild cognitive impairment" AND "eye movements" OR "saccades" OR "smooth pursuit" OR "fixation") with a search cutoff date of September 30, 2025. Studies deemed irrelevant or lacking sufficient data were excluded.ResultsAD/MCI patients exhibit eye movement abnormalities: prolonged saccadic latency, increased antisaccade errors, reduced fixation stability, and attenuated smooth pursuit gain, which are closely linked to core AD pathologies, detectable in AD/MCI stages, and can, to a certain extent, distinguish AD from Parkinson's disease and frontotemporal dementia, and have value for MCI-to-AD conversion prediction.ConclusionsEye movement abnormalities hold promise as non-invasive biomarkers for AD, with potential for preclinical screening and differential diagnosis. To advance translation, future research should prioritize AI-driven multi-modal integration, standardized detection protocols, portable device development, and preclinical longitudinal validation.
