Single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease

Area of Science:

• Neuroscience
• Genetics
• Immunology

Background:

• Single nucleus RNA sequencing (snRNA-seq) is a powerful tool for studying complex diseases like Alzheimer's disease (AD).
• Integrating multiomics data (genetics, proteomics, clinical) with transcriptomics enhances understanding of disease mechanisms.
• The superior frontal gyrus is a critical brain region for cognitive functions affected by AD.

Purpose of the Study:

• To investigate Alzheimer's disease (AD) at the single-cell level using snRNA-seq.
• To integrate genetic and transcriptomic data to identify AD-associated molecular pathways.
• To explore the role of specific cell types and molecular networks in AD pathogenesis.

Main Methods:

• snRNA-seq profiling of superior frontal gyrus samples from 101 well-characterized individuals.
• Whole genome sequencing to identify common AD risk variants.
• Bioinformatic analysis to link genetic variants with gene expression and identify cell subtypes.
• Replication of key findings in two independent snRNA-seq datasets.

Main Results:

• Common AD risk variants were associated with CR1 expression in oligodendrocytes.
• Alterations in hematological parameters were observed in AD subjects.
• A distinct CD83(+) microglial subtype associated with AD was identified, exhibiting unique molecular networks and linked to immunoglobulin IgG4 production.
• Key findings were validated in independent datasets, confirming robustness.

Conclusions:

• Multi-tissue molecular profiling effectively contextualizes brain transcriptomics in AD.
• snRNA-seq combined with multiomics data reveals novel AD-associated cell subpopulations and molecular mechanisms.
• The identified microglial subtype and its link to immune responses offer new avenues for AD research.