A team led by scientists at St. Jude Children's Research Hospital announced on Mar. 23 the development of a comprehensive protein atlas, called the pan-neurodegeneration atlas (PanNDA), designed to help understand and diagnose neurodegenerative diseases. The findings were published in Cell.
The PanNDA resource aims to provide researchers and clinicians with a broad overview of the molecular changes underlying major neurodegenerative conditions, which could improve diagnosis and inform treatment strategies for these complex disorders.
The research team, including Junmin Peng, PhD, from St. Jude's Departments of Structural Biology and Developmental Neurobiology, and Bin Zhang, PhD, from the Icahn School of Medicine at Mount Sinai, created PanNDA by analyzing proteomes—the complete set of proteins—from 2,279 individuals affected by one of six major neurodegenerative diseases: Alzheimer's disease, Parkinson's disease, vascular dementia, Lewy body dementia, progressive supranuclear palsy and frontotemporal degeneration with TDP-43 pathology. Their analysis revealed both shared and unique alterations among these diseases as well as distinct subtypes within each condition.
Zhang said: "Protein network analysis revealed not only the global landscape of protein–protein interactions in each disease, but also local interaction subnetworks and key candidate driver proteins." He added: "Highly predictive protein subnetworks and driver proteins may play causal roles in disease pathogenesis and therefore represent promising targets for therapeutic intervention."
Peng said: "We identified all the major aggregated proteins previously known, but with our data we could correlate these with other proteins that change alongside them." He described it as "the first really large-scale, deep analysis of its kind," noting that it covers more than 10,000 brain proteins.
Peng emphasized PanNDA's value for future research: "The project was a huge undertaking...we want the results to serve the whole neurodegenerative disease research community." He noted that many newly identified proteins had not been studied before in this context. The dataset is available online for public use.
Looking ahead at clinical applications Peng said: "Subtype information can be combined with biomarkers to stratify patients and predict who will benefit from which treatment...by following certain pathways and identifying protein functions we hope to provide a deeper understanding of disease mechanisms and point to new treatment strategies."
