Year: 2025
Type: article
Abstract: Early and accurate diagnosis of Alzheimer's disease (AD) will be key for effective personalized treatment plans ( Cummings, 2023). Significant difficulties in auditory processing have been frequently reported in many patients with mild cognitive impairment, the prodromal form of AD ( Tarawneh et al., 2022), making it an outstanding candidate as AD diagnostic biomarker. However, the efficiency of diagnosis with this parameter has not been explored. Here we show that when male mice with amyloidosis begin to show memory decline, changes in the auditory brainstem response (ABR) to clicks enable the reliable diagnosis of disease using a machine learning algorithm. Interpretation of the machine learning diagnosis revealed that the upper levels of the auditory pathway, including the inferior colliculus, were the probable sources of the defects. Histological analyses show that in these locations, neuroinflammation and plaque deposition temporally correlate with behavioral changes consistent with memory loss. While these findings are tempered by the caveat that they derive from amyloidosis mice, we propose that ABR measurements be evaluated as an additional rapid, low-cost, noninvasive biomarker to assist the diagnostic testing of early-stage AD.
Source: eNeuro
Authors: Daxiang Na, Yidan Yang, Li Xie, Dorota Piekna-Przybylska, Dominic Bunn, Maleelo Shamambo, Patricia White
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,925
OpenAlex ID: W4409261386