Table 2.

Studies analyzing previously published AAA scRNA-Seq data and databases.

Author	Year	Model/tissue	Cells/clusters	Major findings by scRNA-seq
Liu et al. (16)	2020	Re-analysis of Ang II-induced murine AAA scRNA-seq database compared to a human AAA mRNA microarray dataset	•Clusters: 5	•Analysis of human AAA mRNA microarray dataset identified DEGs, which were then used to construct a PPI network revealing 3 genes previously reported to be associated with AAA, and 3 novel genes. The Ang II murine AAA scRNA-seq database was analyzed for these results, revealing 4 AAA-linked genes in common—CANX, CD44, STAT1, and DAXX
Yang et al. (17)	2022	Comparison of CaCl2-, elastase-, or Ang II-induced murine AAA and human AAA scRNA-seq datasets evaluating cell-cell communication	CaCl2 • Cells: 3896 • Sham: 2,537 • AAA: 1,359 •Clusters: 12 Elastase •Clusters: 16 Ang II •Clusters: 9 Human •Clusters: 14	•Intercellular communication networks were evaluated in murine and human AAA scRNA-seq databases using CellChat analysis •CaCl2 database analysis showed 8,799 ligand-receptor interactions in the sham group, compared to 8,601 in AAA. Outgoing and ingoing signals were highest in the SMC and Fib-1 cell populations. AAA induction increased signaling from Maph-2 to SMC-1 and from DC to SMC-2. Seven signaling pathways were unique to sham, while three pathways were unique to AAA. •Elastase database analysis showed 7,233 interactions in the control group, 10,453 in the Day 7 post-surgery group, and 9,343 in the Day 14 group. AAA increased the communication probability compared to controls, with SMCs as the major signal source and fibroblasts the target. Five signaling pathways were exclusive to controls, while 21 pathways were only expressed in the elastase treatment groups •Ang II database analysis showed fibroblasts and SMC populations were the major signal source while SMC-1 was the major receiver •Human AAA database analysis showed 52 total interactions in the control group, compared to 972 interactions in AAA. Interaction strength was nearly undetectable in the control group. In the AAA group, the SMC and fibroblast populations were the major signal senders, while the NK cell population was the major receiver. Most signaling pathways were expressed in AAA •Eight signaling pathways were altered in all murine models and human AAA. MIF signaling was upregulated in all AAA groups.
Li Y. et al. (18)	2022	Analysis of human AAA scRNA-seq database, GSE166676, compared to transcriptomic data of hypertension and intracranial aneurysm datasets	•Cells: 9,796 •Clusters: 21	•Reanalysis of human AAA database produced 21 cell clusters. The Mo/Mø cluster of 2,102 cells was used for differential analysis between controls and AAA tissues. DESeq2 and FindMarker of Mo/Mø identified 869 DEGs, which were then were utilized to further analyze bulk RNA-seq data of hypertension and intracranial aneurysm datasets
Xiong et al. (19)	2022	Comparison of human AAA scRNA-seq database, GSE166676, to 4 human AAA RNA chip datasets	•Clusters: 20	•DEGs identified in the scRNA-seq dataset were aggregated with DEGs identified by weighted co-expression network analysis (WGCNA) of the RNA chip datasets •G0S2 was identified as a diagnostic biomarker for early AAA and HPSE correlated with rupture risk in large AAAs •Immune infiltration analysis of AAA and normal samples using the CIBERSORT algorithm showed T follicular helper (Tfh) cells were overexpressed in AAA, especially in larger sized aneurysms
Davis et al. (20)	2022	Reanalysis of scRNA-seq data from human infrarenal AAA and control tissues	•Cells: 9,290 •Clusters: 17	•8 major cell types in were identified in infrarenal AAA: endothelial cells, SMCs, fibroblasts, myeloid cells, T cells, NK, B cells, and plasma cells •The SMC cluster showed high expression of contractile proteins encoded by TAGLN, ACTA2, and MYL9; 3 fibroblast clusters were identified, 2 displaying inflammation activation while one demonstrated high extracellular matrix organization •The majority of the immune cell population was comprised of T lymphocytes •5 of 8 AAA cell types showed >300 DEGs; SMCs showed the greatest number of DEGs, with upregulated genes involving cell migration/proliferation and TGFß receptor signaling •Comparison of DEGs with GWAS results from AAA patient peripheral blood showed the aneurysm-associated SNP, SORT1, to be elevated in AAA SMCs compared to control
Cheng et al. (21)	2022	Analysis of murine elastase- and CaCl2-induced AAA, and human AAA scRNA-seq databases, compared to mRNA microarray expression datasets	CaCl2 •Clusters: 15 Elastase •Clusters: 17	•Murine scRNA-seq datasets show the majority of infiltrating immune cells to be monocytes/macrophages •Functional enrichment, PPI analysis, and WGCNA of monocyte/macrophages pseudocells was performed on murine AAA scRNA-seq datasets to identify key functional pathways of Mo/Mø •DEG analysis of the two murine AAA datasets identified elevated expression of Thbs1, Il1b, and Clec4e, particularly within Mo/Mø. In the human AAA scRNA-seq database, these genes were also found to colocalize with CD68, a common macrophage marker
Ruan et al. (22)	2022	Re-analysis of human AAA scRNA-seq database, GSE166676	•Clusters: 11	•PTPN22, the gene encoding for protein tyrosine phosphatase non-receptor type 22, was identified as a potential AAA biomarker during cross-comparisons of GO public datasets. Analysis of the GSE166676 scRNA-seq database demonstrated upregulation of PTPN22 within AAA tissues. Re-clustering using lineage-specific biomarkers identified the cells expressing higher PTPN22 as immune cell origin. Subpopulation analysis defined these cells as T cells, NK cells, and B cells •Analysis of VSMCs via ACTA2 expression showed AAA VSMCs to have higher expression of PTPN22

Ang II, angiotensin II; DC, dendritic cell; DEG, differentially expressed gene; EC, endothelial cell; Fib, fibroblast; GO, gene ontology; Maph or Mø, macrophage; Mo, monocytes; PPI, protein-protein interaction; SMC, smooth muscle; VSMC, vascular smooth muscle cell.