Sex-Stratified Single-Cell RNA-Seq Analysis Identifies Sex-Specific and Cell Type-Specific Transcriptional Responses in Alzheimer's Disease Across Two Brain Regions

Stella A Belonwu^#^{1

2}, Yaqiao Li^#^{1

2}, Daniel Bunis^{1

3

4}, Arjun Arkal Rao^{3

4

5}, Caroline Warly Solsberg^{1

2}, Alice Tang^{1

6}, Gabriela K Fragiadakis^{3

4

7}, Dena B Dubal^{8

9

10}, Tomiko Oskotsky^{1

11}, Marina Sirota^{12

13}

Affiliations

¹ Bakar Computational Health Sciences Institute, University of California San Francisco, 490 Illinois St, San Francisco, CA, 94143, USA.
² Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California San Francisco, San Francisco, CA, USA.
³ CoLabs, University of California, San Francisco, San Francisco, CA, USA.
⁴ Bakar ImmunoX Initiative, University of California, San Francisco, San Francisco, CA, USA.
⁵ Department of Pathology, University of California San Francisco, San Francisco, CA, USA.
⁶ Bioengineering Graduate Program, University of California San Francisco, San Francisco, CA, USA.
⁷ Department of Medicine, Division of Rheumatology, University of California, San Francisco, San Francisco, CA, USA.
⁸ Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
⁹ Neurosciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
¹⁰ Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA.
¹¹ Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA.
¹² Bakar Computational Health Sciences Institute, University of California San Francisco, 490 Illinois St, San Francisco, CA, 94143, USA. marina.sirota@ucsf.edu.
¹³ Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA. marina.sirota@ucsf.edu.

^# Contributed equally.

PMID: 34669146
PMCID: PMC8786804
DOI: 10.1007/s12035-021-02591-8

Sex-Stratified Single-Cell RNA-Seq Analysis Identifies Sex-Specific and Cell Type-Specific Transcriptional Responses in Alzheimer's Disease Across Two Brain Regions

Stella A Belonwu et al. Mol Neurobiol. 2022 Jan.

. 2022 Jan;59(1):276-293.

doi: 10.1007/s12035-021-02591-8. Epub 2021 Oct 20.

Authors

Affiliations

¹ Bakar Computational Health Sciences Institute, University of California San Francisco, 490 Illinois St, San Francisco, CA, 94143, USA.
² Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California San Francisco, San Francisco, CA, USA.
³ CoLabs, University of California, San Francisco, San Francisco, CA, USA.
⁴ Bakar ImmunoX Initiative, University of California, San Francisco, San Francisco, CA, USA.
⁵ Department of Pathology, University of California San Francisco, San Francisco, CA, USA.
⁶ Bioengineering Graduate Program, University of California San Francisco, San Francisco, CA, USA.
⁷ Department of Medicine, Division of Rheumatology, University of California, San Francisco, San Francisco, CA, USA.
⁸ Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
⁹ Neurosciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
¹⁰ Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA.
¹¹ Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA.
¹² Bakar Computational Health Sciences Institute, University of California San Francisco, 490 Illinois St, San Francisco, CA, 94143, USA. marina.sirota@ucsf.edu.
¹³ Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA. marina.sirota@ucsf.edu.

^# Contributed equally.

PMID: 34669146
PMCID: PMC8786804
DOI: 10.1007/s12035-021-02591-8

Abstract

Alzheimer's disease (AD) is a pervasive neurodegenerative disorder that disproportionately affects women. Since neural anatomy and disease pathophysiology differ by sex, investigating sex-specific mechanisms in AD pathophysiology can inform new therapeutic approaches for both sexes. Previous bulk human brain RNA sequencing studies have revealed sex differences in dysregulated molecular pathways related to energy production, neuronal function, and immune response; however, the sex differences in disease mechanisms are yet to be examined comprehensively on a single-cell level. We leveraged nearly 74,000 cells from human prefrontal and entorhinal cortex samples from the first two publicly available single-cell RNA sequencing AD datasets to perform a case versus control sex-stratified differential gene expression analysis and pathway network enrichment in a cell type-specific manner for each brain region. Our examination at the single-cell level revealed sex differences in AD prominently in glial cells of the prefrontal cortex. In the entorhinal cortex, we observed the same genes and networks to be perturbed in opposing directions between sexes in AD relative to healthy state. Our findings contribute to growing evidence of sex differences in AD-related transcriptomic changes, which can fuel the development of therapies that may prove more effective at reversing AD pathophysiology.

Keywords: Alzheimer’s disease; RNA sequencing; Sex differences; Single-cell.

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Conflict of interest statement

MS is on the advisory board of twoXAR. Other authors declare no competing financial interests.

Figures

**Fig. 1**
Workflow for cohort sample definition and sex-stratified cell type-specific differential gene expression and functional enrichment. AD and non-AD cells were determined based on tau (Braak) and amyloid-β plaque (CERAD) burdens. Cell types were identified, and AD versus non-AD differential expression and pathway network enrichment analyses were performed separately for each sex in each cell type

**Fig. 2**
Sex-stratified cell type-specific differential gene expression signatures in the prefrontal cortex. a. Upset plots indicating intersections of AD versus non-AD DEGs (BH-adjusted p value < 0.05 and absolute LFC > 0.25) across cell types. Rows correspond to cell types. The bar chart shows the number of single and common sets of DEGs across cell types. Single filled dots represent a unique set of DEGs for the corresponding cell type. Multiple filled black dots connected by vertical lines represent common sets of DEGs across cell types. b. LFC scores of all genes in the DE analysis clustered by cell type and sex. c. *LINGO1*, *PLXDC2*, *SPP1*, *RBFOX1*, and *ERBB21P* expressions. Asterisks represent meeting both significance and absolute LFC thresholds. Colors correspond to sex and AD status. d. Pairwise DEG plots of DEGs in male and female samples using LFC scores. Genes shown are significant and have a LFC > 0.25 in at least one sex. Colors indicate significance level of DEGs and whether DEGs are unique or shared by both sexes

**Fig. 3**
Sex-stratified cell type-specific differential gene expression signatures in the entorhinal cortex. a. Upset plots indicating intersections of AD versus non-AD DEGs (BH-adjusted p value < 0.05 and absolute LFC > 0.25) across cell types. Rows correspond to cell types. The bar chart shows the number of single and common sets of DEGs across cell types. Single filled dots represent a unique set of DEGs for the corresponding cell type. Multiple filled black dots connected by vertical lines represent common sets of DEGs across cell types. b. LFC scores of all genes in the DE analysis clustered by cell type and sex. c. *LINGO1*, *GPM6A*, *CST3*, and *LINC00486* expressions. Asterisks represent meeting both significance and absolute LFC thresholds. Colors correspond to sex and AD status. d. Pairwise DEG plots of DEGs in male and female samples using LFC scores. Genes shown are significant and have a LFC > 0.25 in at least one sex. Colors indicate significance level of DEGs and whether DEGs are unique or shared by both sexes

**Fig. 4**
Sex-stratified cell type-specific disease signatures across brain regions. a. Upset plots indicating intersections of AD versus non-AD DEGs (BH-adjusted p value < 0.05 and absolute LFC > 0.25) within cell types across brain region and sex. Rows correspond to brain region and sex pairings. The bar chart shows the number of single and common sets of DEGs across brain regions and sex. Single filled dots represent a unique set of DEGs for the corresponding brain region and sex. Multiple filled black dots connected by vertical lines represent common sets of DEGs across brain region and sex. Bar chart colors correspond to whether DEGs are shared by brain regions or sex using the bottom right key. b. LFC scores of all genes in the DE analysis of both brain regions clustered by cell type, brain region, and sex

**Fig. 5**
Enriched disease pathway networks in female and male neurons and microglia. AD compared to non-AD functionally enriched pathways with a BH-adjusted p value < 0.05 clustered into biological themes for a. excitatory and b. inhibitory neurons from the prefrontal cortex; c. neurons from the entorhinal cortex; and microglia from the d. prefrontal and e. entorhinal cortices. Lines represent gene set overlaps with magnitude showed by thickness

See this image and copyright information in PMC

References

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Sex-Stratified Single-Cell RNA-Seq Analysis Identifies Sex-Specific and Cell Type-Specific Transcriptional Responses in Alzheimer's Disease Across Two Brain Regions

Affiliations

Sex-Stratified Single-Cell RNA-Seq Analysis Identifies Sex-Specific and Cell Type-Specific Transcriptional Responses in Alzheimer's Disease Across Two Brain Regions

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Medical