Meta-Analyses of Auditory Evoked Potentials as Alzheimer Biomarkers.

OBJECTIVES

Alterations in auditory evoked potential (AEP) parameters have been associated with sensory memory deficits and may serve as biomarkers for cognitive decline. This systematic review and meta-analysis aimed to evaluate the effectiveness of AEPs in the early detection of Alzheimer disease (AD).

DESIGN

The systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. A comprehensive search was performed across five electronic databases (EMBASE, Scopus, Cochrane Library, Web of Science, PubMed, and CINAHL) from their inception until August 2024, without restrictions on date or language. The methodological quality of evidence was assessed using the Crew Critical Appraisal Tool. Data were extracted on the latency and amplitude of five AEP components, including auditory P50 gating, mismatch negativity, and late-latency responses (N100, N200, P300), comparing patients with AD to age-matched control peers.

RESULTS

Out of 437 publications, 54 articles were selected for review, with most rated as having high methodological quality. The analysis revealed a significantly larger P50 gating amplitude ( p < 0.001) in patients with AD. Furthermore, patients with AD demonstrated significantly prolonged latencies and reduced amplitudes for N100, N200, and P300 components ( p ≤ 0.001) compared with controls. Among all AEPs, P300 latency exhibited the largest effect size. Funnel plot analysis and Egger's regression test showed no evidence of publication bias.

CONCLUSIONS

Our findings support the clinical utility of AEPs in early AD detection, with the P300 response identified as the most accurate electrophysiological measure for distinguishing patients with AD from the control group. These results highlight the value of incorporating AEPs into clinical assessment protocols to enhance early-stage AD diagnosis and monitoring, thereby facilitating timely interventions and the development of personalized treatment strategies.