Advancing Alzheimer’s Understanding through Single-Cell Sequencing Data Analysis

Dear Colleagues,

Alzheimer's disease (AD) is a chronic degenerative disease of the brain and it is the most common cause of dementia. In the absence of conscious impairment, there are barriers to memory, thinking, analytical judgment, visuospatial discrimination, and mood, thus seriously affecting the social lives of patients.

At present, the exact etiology and pathogenesis of AD have not yet been elucidated, and effective treatment options are lacking. A new technology is urgently needed to analyze the molecular mechanism of AD pathogenesis at a deeper level, to provide a theoretical basis for the search for early diagnosis, differential diagnosis, and early prediction of the efficacy of biomarkers, and the development of specific targeted drugs. Previous studies have confirmed that the pathology of Alzheimer's disease varies according to different brain regions and cell types. The integration of large-scale data is needed to provide technical support.

Single-cell sequencing is an emerging cutting-edge technology, and a full suite of single-cell and spatial multi-omics technologies including single-cell transcriptome (scRNA-seq), single-cell ATAC (sc-ATAC-seq), and spatial transcriptome have been developed. Compared with traditional conventional genomics technologies, single-cell sequencing allows for independent sequencing and analysis at the single-cell level to reflect the heterogeneity between different cell types, thereby providing new technical support for elucidating pathogenesis and discovering new therapeutic targets.

We invite experts to share their valuable insights, new data, and comprehensive systematic evaluations in this emerging and critical field.

Dr. Aristidis G. Vrahatis
Guest Editor

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• Alzheimer’s disease
• single-cell sequencing
• machine learning
• molecular biomarkers
• single-cell RNA-seq
• single-cell ATAC-seq
• spatial transcriptomics