眼部检查或可提前数年揭示阿尔茨海默病预警信号Eye exams may uncover Alzheimer's warning signs years before memory loss appears

环球医讯 / 认知障碍来源:www.msn.com美国 - 英语2025-09-08 18:54:39 - 阅读时长4分钟 - 1841字
最新研究显示视网膜变薄可作为阿尔茨海默病早期生物标志物,通过眼底扫描可在出现记忆丧失症状前6-7年检测疾病风险,该非侵入性检测方法为大规模筛查提供了新可能
阿尔茨海默病眼部检查视网膜变薄早期预警信号认知症状早期干预淀粉样蛋白斑块医疗检查疾病诊断机器学习应用
眼部检查或可提前数年揭示阿尔茨海默病预警信号

In a new study published today in JCI Insight, researchers from Cedars-Sinai Medical Center have demonstrated that thinning of the retina – the light-sensitive tissue in the back of the eye – may serve as an early indicator of Alzheimer's disease up to seven years before cognitive symptoms manifest.

This groundbreaking research builds on existing evidence linking neurodegenerative processes in the brain to observable changes in ocular anatomy. Using advanced optical coherence tomography (OCT) scans on 70 participants with confirmed Alzheimer's diagnoses and 70 cognitively healthy controls, scientists found consistent patterns of retinal layer thinning in disease-associated regions among those who later developed dementia.

The study's lead author, Dr. Maya Koronyo-Hamaoui, noted that the findings could revolutionize early intervention strategies: "The ability to detect Alzheimer's pathology through a simple, non-invasive eye exam represents a paradigm shift in our approach to this devastating disease. Current diagnostic methods require expensive brain imaging or lumbar punctures, which are impractical for widespread screening."

Researchers emphasized the correlation between specific retinal layers affected and the accumulation of amyloid-beta plaques – hallmark pathological features of Alzheimer's. The technology's potential for integration into routine medical check-ups could enable population-level monitoring and facilitate enrollment in preventive clinical trials at earlier stages.

While further validation with larger, diverse cohorts is needed, this research marks significant progress toward affordable, accessible Alzheimer's diagnostics. The team is now exploring machine learning applications to enhance OCT scan analysis and improve predictive accuracy across different demographic groups.

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