Precision Neuroscience: Harnessing AI and Multi-Omics to Bridge Lab Discoveries and Clinical Solutions for Neurodegenerative Disorders
核心洞察
Frontiers (搜索) launches a multidisciplinary Research Topic aimed at accelerating the translation of laboratory discoveries into personalized clinical interventions for neurodegenerative diseases.
The initiative emphasizes integration of AI, multi-omics, digital biomarkers, and advanced neuroimaging to define disease heterogeneity and identify biologically meaningful patient subgroups.
A parallel Research Topic addresses persistent challenges in data sharing, harmonization, and interoperability that currently limit the impact of precision medicine in Alzheimer's and Parkinson's research.
The translation of fundamental neuroscience discoveries into effective clinical interventions for neurodegenerative disorders remains one of the most pressing challenges in modern medicine. Two newly launched Research Topics from Frontiers (搜索) seek to address this gap by fostering multidisciplinary collaboration that bridges laboratory science with clinical application, while simultaneously tackling the data-sharing and interoperability barriers that have hindered progress in precision medicine.
Integrating Multi-Omics, AI, and Digital Biomarkers
The Research Topic "Precision Neuroscience: Bridging Lab Discoveries to Clinical Solutions for Neurodegenerative Disorders" aims to provide a platform for research that advances both mechanistic understanding and the development of personalized diagnostic, prognostic, and therapeutic strategies. The initiative spans a broad spectrum of neurodegenerative conditions, including amyotrophic lateral sclerosis (搜索), frontotemporal dementia (搜索), Alzheimer's disease (搜索) and other dementias, Parkinson's disease (搜索), Huntington's disease (搜索), and atypical parkinsonisms.
Recent years have witnessed major progress in identifying the molecular and cellular mechanisms underlying neurodegeneration. These include protein misfolding and aggregation, neuroinflammation, synaptic dysfunction, mitochondrial impairment, altered RNA metabolism, vascular contributions, and gut-brain interactions. Concurrently, novel biomarkers derived from cerebrospinal fluid, blood, neuroimaging, genetics, transcriptomics, proteomics, metabolomics, and digital health technologies are reshaping how diseases are characterized and how patients are stratified.
The concept of precision neuroscience, as articulated by the Research Topic editors, seeks to integrate these diverse sources of information to better define disease heterogeneity, identify biologically meaningful subgroups, predict disease trajectories, and tailor therapeutic interventions. The collection welcomes original research articles, reviews, systematic reviews, meta-analyses, perspectives, and methodological papers across areas including biomarkers for diagnosis and treatment response, multi-omics approaches and systems biology, neuroimaging and computational neuroscience, artificial intelligence and machine learning applications, digital biomarkers and remote monitoring technologies, and precision clinical trials.
Confronting the Data-Sharing Bottleneck
A companion Research Topic, "Empowering Precision Medicine in Neurodegenerative Diseases via Data Sharing Strategies and AI Innovations," developed in collaboration with Dr. Ornit Chiba-Falek and Dr. Ara Khachaturian's podcast series on empowering proteomics and transcriptomics in Alzheimer's drug discovery, confronts a critical obstacle: despite advances in AI and machine learning coupled with large-scale multi-omics datasets, the impact of precision medicine in neurodegenerative research remains limited by persistent challenges in data sharing, harmonization, and integration across diverse data modalities.
Several major data-sharing initiatives are already operational, including the AD Knowledge Portal, the AMP-PD Knowledge Platform, and the Seattle Alzheimer's Disease (搜索) Brain Cell Atlas, alongside repositories for analytical code. Complementary harmonization efforts such as the Alzheimer's Disease Sequencing Project Phenotype Harmonization Consortium and the RNA-seq Harmonization Study have further strengthened the field's infrastructure. Funding agencies and scientific journals have also issued guidelines promoting transparency and reproducibility.
Yet fragmentation in policy frameworks and inconsistencies in data standards continue to impede the development of a cohesive and interoperable data-sharing ecosystem. The Research Topic calls for innovative technical, regulatory, and social strategies that promote interoperability, protect privacy, and engage the public. By leveraging emerging technologies and strengthening collaborative data infrastructures, the research community can accelerate the translation of precision medicine approaches from bench to bedside.
This collection, hosted by Dr. Michael Lutz and Jean-Marie Bouteiller, welcomes submissions addressing novel data-sharing platforms, AI-driven methods for early diagnosis and personalized therapeutic strategies, integration of genomic and real-world data, ethical and legal considerations, and case studies illustrating successful clinical applications of AI-enabled approaches.
A Unified Vision for Neurodegenerative Disease Research
Together, these two Research Topics represent a concerted effort to move beyond fragmented research paradigms. By bringing together researchers, clinicians, data scientists, translational investigators, and policymakers, the collections aim to highlight emerging discoveries that can accelerate the transition from mechanistic understanding to meaningful clinical benefit. As global populations age and the prevalence of disorders such as Alzheimer's disease (搜索) and Parkinson's disease (搜索) continues to rise, the urgency for more effective and personalized therapeutic strategies has never been greater.