Menendez-Gonzalez Manuel
Departamento de Medicina, Universidad de Oviedo, Oviedo, Spain.
Servicio de Neurología, Hospital Universitario Central de Asturias, Oviedo, Spain.
Alzheimers Dement. 2025 Feb;21(2):e14591. doi: 10.1002/alz.14591.
Neurodegenerative diseases (NDDs) pose a significant challenge in modern medicine due to their clinical heterogeneity, multifactorial etiologies, and frequent co-pathologies. Traditional diagnostic systems, based on clinical symptoms and post mortem findings, are limited in capturing the complex interactions among genetic, molecular, and neuroanatomical factors. This manuscript introduces a novel tridimensional diagnostic framework that integrates these factors across three key axes: etiology (genetic and environmental influences), molecular markers (primary and secondary biomarkers), and neuroanatomoclinical correlations. Through case studies, we demonstrate the framework's ability to synthesize incomplete datasets, stratify patients, and guide precision medicine. By incorporating omics technologies, neuroimaging, and AI-driven probabilistic modeling, the framework enhances diagnostic accuracy and clinical relevance. This approach may contribute to overcoming the limitations of traditional nosologies, offering a scalable and adaptable tool for both clinical practice and research and advancing the field of precision medicine in NDD management. HIGHLIGHTS: Tridimensional diagnostic system: We propose a new framework that incorporates three axes - etiology, molecular markers, and neuroanatomical-clinical correlations - to enhance diagnostic accuracy for NDDs. Personalized medicine: The tridimensional system enables the integration of genetic, molecular, and clinical data, allowing for highly personalized treatment strategies tailored to individual patients. Proteinopathies as key biomarkers: This diagnostic system emphasizes the use of primary proteinopathies (amyloid, tau, synuclein) and secondary biomarkers (eg, NfL, GFAP) to monitor disease progression and treatment efficacy. Addressing clinical heterogeneity: The framework accommodates the complexity and heterogeneity of NDDs, offering an adaptable diagnostic approach for classical conditions like Alzheimer's disease, Parkinson's disease, frontotemporal dementia, and ALS. Case studies and real-world application: Practical case studies illustrate how this system can be implemented in clinical practice, enabling the combination of DMTs with symptomatic treatments.
神经退行性疾病（NDDs）在现代医学中构成了重大挑战，因为它们具有临床异质性、多因素病因以及常见的合并病理情况。基于临床症状和尸检结果的传统诊断系统，在捕捉遗传、分子和神经解剖因素之间的复杂相互作用方面存在局限性。本手稿介绍了一种新颖的三维诊断框架，该框架在三个关键轴上整合了这些因素：病因（遗传和环境影响）、分子标志物（主要和次要生物标志物）以及神经解剖临床相关性。通过案例研究，我们展示了该框架整合不完整数据集、对患者进行分层以及指导精准医学的能力。通过纳入组学技术、神经影像学和人工智能驱动的概率模型，该框架提高了诊断准确性和临床相关性。这种方法可能有助于克服传统疾病分类学的局限性，为临床实践和研究提供一种可扩展且适应性强的工具，并推动神经退行性疾病管理领域的精准医学发展。
三维诊断系统：我们提出了一个新的框架，该框架纳入了三个轴——病因、分子标志物和神经解剖临床相关性——以提高神经退行性疾病的诊断准确性。
个性化医疗：三维系统能够整合遗传、分子和临床数据，从而为个体患者制定高度个性化的治疗策略。
蛋白病作为关键生物标志物：这种诊断系统强调使用主要蛋白病（淀粉样蛋白、tau蛋白、突触核蛋白）和次要生物标志物（例如，神经丝轻链蛋白、胶质纤维酸性蛋白）来监测疾病进展和治疗效果。
应对临床异质性：该框架适应神经退行性疾病的复杂性和异质性，为阿尔茨海默病、帕金森病、额颞叶痴呆和肌萎缩侧索硬化症等经典病症提供了一种适应性诊断方法。
案例研究与实际应用：实际案例研究说明了该系统如何在临床实践中实施，使疾病修饰治疗与对症治疗相结合。
