Accelerating biomedical discoveries in brain health through transformative neuropathology of aging and neurodegeneration

IF 14.7 1区 医学 Q1 NEUROSCIENCES
Melissa E. Murray, Colin Smith, Vilas Menon, C. Dirk Keene, Ed Lein, Michael Hawrylycz, Adriano Aguzzi, Brett Benedetti, Katja Brose, Kelsey Caetano-Anolles, Maria Inmaculada Cobos Sillero, John F. Crary, Philip L. De Jager, Arline Faustin, Margaret E. Flanagan, Ozgun Gokce, Seth G.N. Grant, Lea T. Grinberg, David A. Gutman, Elizabeth M.C. Hillman, Zhi Huang, David J. Irwin, David T. Jones, Alifiya Kapasi, Celeste M. Karch, Walter T. Kukull, Tammaryn Lashley, Edward B. Lee, Thomas Lehner, Laura Parkkinen, Maria Pedersen, Dominique Pritchett, Matthew H. Rutledge, Julie A. Schneider, William W. Seeley, Claire E. Shepherd, Tara L. Spires-Jones, Judith A. Steen, Margaret Sutherland, Sanja Vickovic, Bin Zhang, David J. Stewart, Michael J. Keiser, Jacob W. Vogel, Brittany N. Dugger, Hemali Phatnani
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引用次数: 0

Abstract

Transformative neuropathology is redefining human brain research by integrating foundational descriptive pathology with advanced methodologies. These approaches, spanning multi-omics studies and machine learning applications, will drive discovery for the identification of biomarkers, therapeutic targets, and complex disease patterns through comprehensive analyses of postmortem human brain tissue. Yet critical challenges remain, including the sustainability of brain banks, expanding donor participation, strengthening training pipelines, enabling rapid autopsies, supporting collaborative platforms, and integrating data across modalities. Innovations in digital pathology, tissue quality enhancement, harmonization of data standards, and machine learning integration offer opportunities to accelerate tissue-level “pathomics” research in brain health through cross-disciplinary collaborations. Lessons from neuroimaging, particularly in establishing common data frameworks and multi-site collaborations, offer a valuable roadmap for streamlining innovations. In this perspective, we outline actionable solutions for leveraging existing resources and strengthening collaboration -where we envision future opportunities to drive translational discoveries stemming from transformative neuropathology.
通过衰老和神经变性的变革性神经病理学加速脑健康的生物医学发现
转化神经病理学通过整合基础描述病理学和先进的方法重新定义了人类大脑的研究。这些方法跨越多组学研究和机器学习应用,将通过对死后人类脑组织的综合分析,推动生物标志物、治疗靶点和复杂疾病模式的发现。然而,严峻的挑战依然存在,包括脑库的可持续性、扩大捐赠者参与、加强培训渠道、实现快速尸检、支持协作平台以及跨模式整合数据。数字病理学、组织质量增强、数据标准统一和机器学习集成方面的创新为通过跨学科合作加速组织层面的脑健康“病理学”研究提供了机会。神经影像学的经验教训,特别是在建立通用数据框架和多站点合作方面,为简化创新提供了宝贵的路线图。从这个角度来看,我们概述了利用现有资源和加强合作的可行解决方案-我们展望了未来的机会,以推动源于变革性神经病理学的转化发现。
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来源期刊
Neuron
Neuron 医学-神经科学
CiteScore
24.50
自引率
3.10%
发文量
382
审稿时长
1 months
期刊介绍: Established as a highly influential journal in neuroscience, Neuron is widely relied upon in the field. The editors adopt interdisciplinary strategies, integrating biophysical, cellular, developmental, and molecular approaches alongside a systems approach to sensory, motor, and higher-order cognitive functions. Serving as a premier intellectual forum, Neuron holds a prominent position in the entire neuroscience community.
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