眼组学在神经退行性疾病中的研究进展

Research progress of oculomics in neurodegenerative diseases

神经退行性疾病会损害大脑和神经系统的结构和功能,导致认知和行为能力逐渐下降,因此,早期诊断神经系统疾病可以促进预防、监测和治疗,从而改善患者的预后。眼与脑在结构和胚胎学上的相似之处为评估中枢神经系统的神经和微血管变化提供了潜在可能。眼组学是眼科学、遗传学和生物信息学的交叉学科,目标是开发快速、无创、具有成本效益的生物标志物,用于全身性疾病的筛查、诊断和风险分层。随着诊断和眼科成像技术的进步,用于检测眼的结构、功能和视觉变化的各项技术得到了快速发展。眼部生物标志物成为评估神经退行性疾病进展有前景的工具。文章采用眼部影像学(例如光学相干断层扫描(optical coherence tomography,OCT)和OCT血管成像(OCT angiography,OCTA))和电生理学(例如视觉诱发电位(visual evoked cortical potentials,VEP)、视网膜电图(electroretinogram,ERG))等筛查方法检测眼部异常神经退行性疾病,总结了眼组学在神经退行性疾病的应用,包括阿尔茨海默病、帕金森病、额颞叶痴呆、肌萎缩侧索硬化症和亨廷顿病,旨在为神经退行性疾病的诊断和治疗提供新的思路。尽管并非所有生物标志物都是疾病特异性的,但未来大数据、人工智能和眼组学的融合,有可能进一步深入了解这些神经退行性疾病。

Neurodegenerative diseases can damage the structure and function of the brain and nervous system,leading to a gradual decline in cognitive and behavioral abilities.Therefore,early diagnosis of neurological diseases can promote prevention,monitoring,and treatment,thereby improving the prognosis of patients.The structural and embryological similarities between the eyes and the brain provide potential for evaluating neurological and microvascular changes in the central nervous system.oculomics is an interdisciplinary field that combines ophthalmology,genetics,and bioinformatics,with the goal of developing rapid,non-invasive,and cost-effective biomarkers for screening,diagnosis,and risk stratification of systemic diseases.With the advancement of diagnostic and ophthalmic imaging technologies,various techniques for detecting the structure,function,and visual changes of the eye have been rapidly developed.Eye biomarkers have become promising tools for assessing the progression of neurodegenerative diseases.The article uses screening methods such as eye imaging(such as OCT,OCTA)and electrophysiology(such as VEP,ERG)to detect abnormal neurodegenerative diseases in the eyes.It summarizes the application of oculomics in neurodegenerative diseases,including Alzheimer's disease,Parkinson's disease,frontotemporal dementia,amyotrophic lateral sclerosis,and Huntington's disease,aiming to provide new ideas for the diagnosis and treatment of neurodegenerative diseases.Although not all biomarkers are disease-specific,the integration of big data,artificial intelligence,and oculomics in the future may further deepen our understanding of these neurodegenerative diseases.