<p>Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the two most common age-related neurodegenerative disorders. Allen Human Brain Atlas (AHBA) provides high-resolution transcriptomic data across 102 brain regions with multi-site sampling from healthy controls, promoting the use of brain-wide transcriptomic data for imaging transcriptomics and cross-modal model construction. Increasingly, researchers are utilizing brain-wide transcriptomic datasets to investigate the transcriptome correlates of the neuroimage phenotypes in AD and PD. Leveraging the AHBA, researchers have analyzed the transcriptomic correlations of regional susceptibility to Aβ deposition, tau deposition, α-synuclein propagation, and disease-related multiple-dominal neuroimage phenotypes. These studies revealed that transcriptomic pathways related to metabolism, immunity, neurotransmission, and synaptic function play critical roles in the neuroimage phenotype of AD and PD. By incorporating transcriptomic data modeling, subsequent analyses further confirmed that transcriptomic differences provide the molecular basis for the varying susceptibility observed across brain regions. The analytical approaches of imaging transcriptomics, multimodal data integration strategies, and model construction methods used in AD and PD provide a novel perspective for exploration and can be extended to other neurodegenerative diseases. Future research is expected to utilize brain-wide transcriptomic data to uncover the gene expression mechanisms driving neurodegenerative disease phenotypes.</p>

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Application of the Allen Human Brain Atlas in Alzheimer’s disease and Parkinson’s disease

  • Yi Xiao,
  • Shichan Wang,
  • Yanbing Hou,
  • Huifang Shang

摘要

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the two most common age-related neurodegenerative disorders. Allen Human Brain Atlas (AHBA) provides high-resolution transcriptomic data across 102 brain regions with multi-site sampling from healthy controls, promoting the use of brain-wide transcriptomic data for imaging transcriptomics and cross-modal model construction. Increasingly, researchers are utilizing brain-wide transcriptomic datasets to investigate the transcriptome correlates of the neuroimage phenotypes in AD and PD. Leveraging the AHBA, researchers have analyzed the transcriptomic correlations of regional susceptibility to Aβ deposition, tau deposition, α-synuclein propagation, and disease-related multiple-dominal neuroimage phenotypes. These studies revealed that transcriptomic pathways related to metabolism, immunity, neurotransmission, and synaptic function play critical roles in the neuroimage phenotype of AD and PD. By incorporating transcriptomic data modeling, subsequent analyses further confirmed that transcriptomic differences provide the molecular basis for the varying susceptibility observed across brain regions. The analytical approaches of imaging transcriptomics, multimodal data integration strategies, and model construction methods used in AD and PD provide a novel perspective for exploration and can be extended to other neurodegenerative diseases. Future research is expected to utilize brain-wide transcriptomic data to uncover the gene expression mechanisms driving neurodegenerative disease phenotypes.