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Updated: Sep 14, 2026

Biomarker Identification for Gender Specificity of Alzheimer's Disease Based on the Glial Transcriptome Profiles
Published on: May 20, 2024
Cellular transcriptomic signatures underpinning the heterogeneity of depression in Alzheimer's disease
Michael W Lutz1, Zhaohui Man1, Ornit Chiba-Falek1,2
1Division of Translational Brain Sciences, Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA.
Introduction:
Late-onset Alzheimer's disease (LOAD) and major depressive disorder (MDD) share genetic etiologies. Here, we investigated brain transcriptomic landscapes to gain insights into shared and divergent molecular and biological etiologies across LOAD and MDD.
Methods:
Brain single-nucleus RNA sequencing (snRNA-seq) datasets from cognitively normal older and young individuals and LOAD patients stratified by comorbid MDD were analyzed to identify differential expressed genes (DEGs). Using cell type-specific DEGs we performed biological pathway and intercellular-communication networks analyses. We investigated shared DEGs across MDD and LOAD cohorts and sex-specific DEGs. Results were validated by comparison with four transcriptomic and proteomic studies of MDD and depression.
Results:
MDD-associated dysregulated genes and pathways were shared between LOAD and cognitive-normal individuals, including JUNB and DUSP1 in glutamatergic neurons, and PRAM1 and SNX9 in microglia. DEGs shared between the MDD and LOAD cohorts included HSPA1A and NDUFB7 in glutamatergic neurons. Sex interaction analysis identified numerous new DEGs in the MDD cohorts, whereas there were ≈5 to 10 times more DEGs in female than in male individuals. LOAD and MDD common microglial pathways included neuronal injury, stress, peroxisome proliferator-activated receptor (PPAR) signaling and interferon alpha/beta signaling.
Discussion:
LOAD and MDD exhibited common molecular profiles, dysregulated pathways, and cellular communication changes. MDD develops earlier in life, thus, our findings provide a window into early molecular and biological processes preceding LOAD-onset.
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