Transcriptomic datasets of human and mouse aortic diseases and VSMCs available in the public accessible NIH-NCBI Geodatasets database (https://www.ncbi.nlm.nih.gov/gds) were collected and organized. The transcription data analysis tool GEO2R in the NCBI-Geodatasets database was used for analysis. The datasets used for this study were the following: GSE10000 dataset: microarrays analysis of mouse aortic atherosclerotic lesions and adventitia in WT and apoE^–/– mice; GSE83500 dataset: microarray analysis of VSMCs isolated from human aortic wall atherosclerotic lesions in patients with myocardial infarction (MI); GSE57691 dataset: microarray analysis of aortic specimens obtained from aortic occlusive disease (AOD) patients and AAA patients; GSE17901 dataset: microarray analysis of suprarenal aorta of ApoE^–/– mice after ang II infusion for 7 days, 14 days, and 28 days. GSE147078 dataset: microarray analysis of mouse aorta after β-aminopropionitrile (BAPN) and Ang II infusion for 3 days; GSE51227 dataset: microarray analysis of infrarenal aortic tissue of a porcine pancreatic elastase (PPE)-induced AAA mouse model; GSE66280 dataset: microarray analysis of mouse aortic smooth muscle cells cultured with 4.5 g/l glucose; GSE47744 dataset: microarray analysis of mouse aortic VSMCs treated with 10 μg/mL cholesterol; GSE49519 dataset: microarray analysis of mouse aortic VSMCs from C57BL/6 and Signal Transducer and Activator of Transcription (STAT) 1 knockout mice with or without LPS stimulation; GSE9490 dataset: microarray analysis of human aortic VSMC treated with 0, 10 and 100 μmol/L DL-homocysteine; GSE11367 dataset: microarray analysis of human aortic VSMCs treated with 100 ng/ml IL-17 for 6 hours; GSE142417 dataset: microarray analysis of primary human aortic VSMCs stimulated with 5 ng/ml recombinant human transforming growth factor beta-1 (TGFβ1) for 24 hour; GSE30004 dataset: microarray analysis of human VSMCs treated with 1 ng/ml TGF-β; GSE180761 dataset: RNA-sequencing of human peripheral blood mononuclear cells (PBMCs) differentiated dendritic cells (DC) treated with Aryl hydrocarbon receptor (AHR) antagonist CH-223191-20 μM; GSE162015 dataset: RNA-sequencing of WT and NFKB1^–/– human macrophage induced THP-1 cell line either unstimulated or LPS-stimulated; GSE100671 dataset: microarray analysis of WT and NAPDH oxidase-2 deficient (NOX2)^–/– human myelomonoblastic cell line PLB-985; GSE29929 dataset: microarray analysis of liver tissue of WT and liver specific PERK knock-out (lsPERK^–/–) mice with and without tunicamycin injection for 6 hours; GSE53038 dataset: microarray analysis of human embryonic stem cells (hESCs) treated with SET7 siRNA; GSE7810 dataset: microarray analysis of lungs type II cells from both NRF2^+/+ and NRF2^–/– mice.

Ingenuity pathway analysis (IPA, Qiagen, Redwood City, CA) was used to characterize the clinical relevance and molecular and cellular functions related to the genes in our RNA-seq data. Differentially expressed genes were collected and uploaded to IPA for further analysis. For the short upregulated gene lists that cannot be analyzed with IPA, the gene lists were analyzed with the Metascape website (https://metascape.org/gp/index.html#/main/step1) ( Figure 1A ).

The data processing involves using the Pandas library in Python to convert the data into DataFrame format, filter genes based on specified conditions (e.g., p-value < 0.05, log2FC ≥ 1), and subsequently organize the resulting screened data into separate Excel files for subsequent statistical analysis ( Figure 1B ). Using Python to process data improves work efficiency and prevents potential errors in manual processing. Of note, it is essential to consider potential duplicate genes in certain datasets, where only data from the first occurrence of duplicates is considered valid.

Our previous papers reported that the upregulated innate immune response genes play significant roles in endothelial cell activation and inflammation in response to viral infections such as COVID-19 homologous MERS-CoV, influenza virus, and sterile endogenous DAMPs such as oxidized low-density lipoprotein (oxLDL) (11) ( Figures 2A, B ), which verified our new working model that endothelial cells are innate immune cells (2, 3, 49). We also reported that the aorta in pathologies functions as an immune organ by upregulating a large number of secretomic genes (22). A complete list of innate immune genes (innatome) (11, 70) has never been examined to determine whether they are significantly upregulated in aortic diseases such as atherosclerosis and aortic aneurysms, with the exception of a short list of well-characterized cytokines and chemokines in aortic diseases (71, 72). We hypothesized that innate immune genes are significantly upregulated in aortic diseases. To examine this hypothesis, we collected 1226 genes out of 2308 innate immune genes after removing duplicated genes from the comprehensive innate immune database (InnateDB, https://www.innatedb.com/annotatedGenes.do?type=innatedb). The results in Figure 2C showed that: a) 1.4%, 11.0%, and 17.7% of innate immune genes were significantly upregulated in atherogenic ApoE^–/– aorta with HFD for 6 weeks, 32 weeks, 78 weeks, respectively; b) 6.7% and 29.0% of innate immune genes were upregulated in two aneurysm mouse models, including β-aminopropionitrile monofumarate (BAPN, an irreversible inhibitor of lysyl oxidase) (73)-Ang II-induced AAA and porcine pancreatic elastase (PPE)-induced AAA (74), respectively, suggesting that PPE-induced AAA induced the highest innate immune responses; c) upregulations of innate immune genes in ApoE^–/– Ang II-induced AAA model in three time points, including 7 days (17.8%), 14 days (2.4%), and 28 days (10.2%), which were in a twin-peak pattern; and d) By comparison, 0.3% to 1.4% of innate immune genes were upregulated in human atherosclerotic aorta and human aneurysm aorta, which were much lower than that in mouse models of aortic diseases;, suggesting that chronic vascular inflammation, such as atherosclerosis, displayed a distinct pattern of chronic innate immune responses with a continuous increase throughout 78 weeks, similar to what we reported in patients with CKD and end-stage renal disease (23), demonstrating that newly defined chronic innate immune responses may not be in remission as prototypic acute innate immune responses ( Figure 2B ).

Of note, since there were a lot of data throughout the analyses that cannot be included in a limited space in the manuscript, our attention was focused on identifying the differences between: i) the time course of atherosclerosis; ii) the time course of AAA; iii) different models of AAA; and iv) different stimuli-induced expression changes of VSMCs. The ingenuity pathway analysis (IPA) results showed that 1) three upregulated pathways, including osteoarthritis, pulmonary fibrosis idiopathic, and chronic myeloid leukemia, in ApoE^–/– at 6 weeks were discontinued; instead, 13 upregulated pathways, including cardiac hypertrophy, NOD1/2 neuroinflammation, Th1-dendritic cell maturation, osteoclasts in rheumatoid arthritis, multiple sclerosis, pathogen-induced cytokine storm, TEM1, nitric oxide and ROS in macrophages, phagosome formation, pyroptosis, and FAK, were continued through ApoE^–/– at 32 weeks to 78 weeks ( Figure 2D ), suggesting that atherosclerosis has two-wave inflammation with the first wave at 6 weeks of HFD and the second wave from 32 weeks continuing to 78 weeks of HFD; and the 13 pathways were conserved in advancing atherosclerotic inflammation; 2) 9 upregulated pathways were found specific in ApoE^–/– Ang II at 7 days, including tumor microenvironment, cachexia, protein coupled receptor, IL-17, SLE, NF-KB, pyroptosis, role of tissue factor in cancer, and wound healing; 7 upregulated pathways were found specific in ApoE^–/– Ang II at 28 days, including S100 family, crosstalk between DC and NK Cells, Th1, macrophage classical activation, IL-8, ISGylation, and role of osteoclasts in rheumatoid arthritis; but no upregulated pathway was found specific in ApoE^–/– Ang II at 14 days ( Figure 2D ); and 3) Several pathways were upregulated in human myocardial infarction, AAA, and aortic occlusive diseases ( Supplementary Figures S1A–C ).

To further examine secreted/soluble molecules of innate immune responses, we collected a comprehensive list of 1325 cytokines and chemokines from the Human Protein Atlas (HPA) database (https://www.proteinatlas.org/search/cytokine; https://www.proteinatlas.org/search/chemokine). As shown in Figure 3A , a) 1.51%, 8.68%, and 15.77% of cytokine and chemokine genes were significantly upregulated in ApoE^–/– aorta with HFD at 6 weeks, 32 weeks, and 78 weeks, respectively; b) 8.23% and 24.98% of cytokine and chemokine genes were upregulated in two aneurysm mouse models, including BAPN-Ang II-induced AAA and PPE-induced AAA, respectively, suggesting that PPE-induced AAA induced the highest cytokine and chemokine responses; c) upregulations of cytokine and chemokine genes in ApoE^–/– Ang II-induced AAA in three time points, including 7 days (19.32%), 14 days (3.55%), and 28 days (10.34%), which were in a twin-peak pattern ( Figure 3B ); d) By comparison, 0.3% to 1.3% of cytokine and chemokine genes were upregulated in human atherosclerotic aorta and human aneurysm aorta, respectively, which were much lower than that in mouse models of aortic diseases.

To further examine intercellular communication and intercellular interaction mediators of innate immune responses as we reported (75, 76), we collected a comprehensive list of 2202 plasma membrane protein genes from the HPA database (https://www.proteinatlas.org/search/subcell_location%3APlasma+membrane%2CCell+Junctions) (77) and a list of 373 clusters of differentiation (CDs) (75). Surprisingly, 124 (33%) out of 373 CD markers overlapped with those of plasma membrane protein genes, suggesting that 67% of CDs may have multiple subcellular membrane locations, as we reported (58). As shown in Figure 3A , a) 1.45%, 4.95%, and 9.08% of plasma membrane protein genes, 1.34%, 17.43%, and 30.83% of CD marker genes were significantly upregulated in ApoE^–/– aorta with HFD at 6 weeks, 32 weeks, and 78 weeks, respectively; b) 4.13% and 13.4% of plasma membrane protein genes, 8.58% and 39.14% of CD marker genes were upregulated in two aneurysm mouse models, including BAPN-Ang II-induced AAA and PPE-induced AAA, respectively, suggesting that PPE-induced AAA model induced the highest plasma membrane protein genes and CD marker genes responses among AAA models; c) upregulations of plasma membrane protein and CD marker genes in ApoE^–/– Ang II-induced AAA in three time points, including 7 days (11.67% and 24.93%), 14 days (2.72% and 3.49%), and 28 days (4.68% and 18.23%), respectively, which were in a twin-peak pattern. Of note, the upregulation scales of cytokines (15.77%), plasma membrane protein genes (9.08%), and CD marker genes (30.83%) in ApoE^–/– HFD at 78 weeks were similar to those of cytokines (19.32%), plasma membrane protein genes (11.67%), and CD marker genes (24.93%) in ApoE^–/– Ang II at 7 days, suggesting that Ang II in ApoE^–/– HFD background significantly accelerates and shortens the inflammation upregulation process by 7 – 8 times. Venn diagram analysis of ApoE^–/–HFD time course in Figure 3C showed upregulation of 17 cytokines and chemokines in ApoE^–/– at 6 weeks, representing the first wave cytokines and chemokines, 19 atherosclerosis-specific cytokines and chemokines at 32 weeks, 102 second wave cytokines and chemokines were shared between 32 and 78 weeks; however, 78 weeks showed 106 atherosclerosis-specific cytokines and chemokines. Of note, atherosclerosis-stage-specific cytokines and chemokines were not reported in the original report (78). Venn diagram analysis of ApoE^–/– Ang II-induced AAA time course showed 132 at 7 days AAA-specific cytokines and chemokines (AAA stage-specific cytokines and chemokines were not reported in the original paper (79), 21 at 14 days AAA-specific cytokines and chemokines, and 34 at 28 days AAA-specific cytokines and chemokines ( Figure 3D ). Furthermore, 160 ApoE^–/– Ang II AAA-stage-specific cytokines and chemokines have also been identified at Ang II infusion for 7 days, 14 days, and 28 days, and 94 atherosclerosis stage-specific cytokines and chemokines have been identified at HFD feeding for 6 weeks, 32 weeks, and 78 weeks ( Figure 3E ).

It has been reported that nucleoli are a nuclear stress response membraneless organelle (63–65). Single-cell measurement of nuclear proteins and RNAs in vivo was recently developed (80). However, global nuclear stresses in CVDs remain poorly characterized. We hypothesized that transcriptomic reprogramming of nuclear membrane proteins, nucleoli proteins, and nucleoplasm proteins is modulated as a novel read-out for nuclear stresses ( Figure 4A ). To examine this hypothesis, we collected three complete lists of 280 nuclear membrane proteins (NMPs), 1425 nucleoli proteins (NPs), and 6750 nucleoplasm proteins (NPPs) from the comprehensive HPA database (https://www.proteinatlas.org/). The results showed that: a) 0.7% of NMPs, 0.8% of NPs, 1.2% of NPPs in ApoE^–/– HFD at 6 weeks, 2.9% of NMPs, 2.7% of NPs, 2.9% of NPPs in ApoE^–/– HFD at 32 weeks, 5.4% of NMPs, 5.5% of NPs, 5.5% of NPPs in ApoE^–/– HFD at 78 weeks were significantly upregulated, respectively; b) 4.3% of NMPs, 4.1% of NPs, 4.0% of NPPs in BAPN Ang II-induced AAA, 7.1% of NMPs, 7.3% of NPs, 7.96% of NPPs in PPE-induced AAA were significantly upregulated, respectively, suggesting that nuclear stresses induced in BAPN Ang II-induced AAA and PPE-induced AAA were higher than that of ApoE^–/– Ang II-induced AAA; c) upregulations of nuclear stress genes in ApoE^–/– Ang II-induced AAA model in three time points, including at 7 days (8.9% NMPs, 8.4% NPs, 8.67% NPPs), at 14 days (1.1% NMPs, 1.0% NPs, 1.3% NPPs) and at 28 days (2.1% NMPs, 2.3% NPs and 2.67% NPPs), which were in a twin-peak pattern; and d) By comparison, 0% to 0.8% of nuclear stress genes were upregulated in human atherosclerotic aorta and human aneurysm aorta, which were much lower than that in mouse models of aortic diseases ( Figure 4B ). The upregulated nuclear membrane protein genes in ApoE^–/– HFD at 6 weeks, 32 weeks, and 78 weeks, ApoE^–/– Ang II-AAA at 7days, 14 days, and 28 days, human MI, human AAA, and human AOD were shown in the Supplementary Figures S2A–E . The upregulated nucleoli genes in ApoE^–/– HFD at 6 weeks, 32 weeks, and 78 weeks, ApoE^–/– Ang II-AAA at 7days, 14 days, and 28 days, human MI, human AAA, and human AOD were shown in the Supplementary Figures S2F–J . However, the upregulated nucleoplasm genes in human MI, human AAA, and human AOD were shown in the Supplementary Figures S2K–M .

In analyzing upregulated nucleoli pathways by the Metascape we found that no specific pathways in ApoE^–/– at 6 weeks; 7 upregulated nucleoli pathways specific in ApoE^–/– at 32 weeks, including 2 innate immune pathways (highlighted in red) such as positive regulation of immune response and network map of SARS-CoV-2 and 3 differentiation pathways (highlighted in blue) such as mitotic cell cycle, epithelial cell differentiation, and regulation of hemopoiesis; 16 upregulated nucleoli pathways specific in ApoE^–/– at 78 weeks, including 4 innate immune pathways (highlighted in red) such as oxidative damage response, positive regulation of inflammatory response, TNFR2 non-canonical NF-kB, and regulation of cellular response to stress, and one master transcription factor (highlighted in yellow) such as TNFR2 non-canonical NF-kappa B; 4 upregulated nucleoli genes shared between ApoE^–/– at 32 and 78 weeks, including 2 innate immune pathways (highlighted in red) such as hematopoietic progenitor cell differentiation and response to toxic substance ( Figure 4C ); 18 pathways were specific in ApoE^–/– Ang II at 7 days, including 4 innate immune pathways (highlighted in red) such as myeloid dendritic cell activation, regulation of leukocyte differentiation, regulation of defense response, and regulation of I-kappaB kinase/NF-kappaB (NF-kB) signaling, five differentiation pathways (highlighted in blue) such as endoderm differentiation, regulation of mitotic nuclear division, regulation of animal organ morphogenesis, ectoderm differentiation, and skeletal system development, and one master transcription factor (highlighted in yellow) such as regulation of I-kappaB kinase/NF-kappaB (NF-kB) signaling; 2 pathways were found specific in ApoE^–/– Ang II at 14 days; 8 upregulated pathways were found specific in ApoE^–/– Ang II at 28 days, including 1 innate immune pathway (highlighted in red) such as inflammatory response, and differentiation pathways (highlighted in blue) such as hematopoietic progenitor cell differentiation and in utero embryonic development ( Figure 4D ).

In analyzing upregulated nucleoplasm pathways by IPA, we found that: 1) 6 upregulated pathways were found specific in ApoE^–/– at 6 weeks including 3 innate immune pathways (highlighted in red) such as senescence, osteoarthritis, and chronic myeloid leukemia; 8 upregulated pathways were found specific in ApoE^–/– at 32 weeks including 3 innate immune pathways (highlighted in red) such as IL-10, PI3K signaling in B lymphocytes, and IL-12 signaling and production in macrophages, and one master gene (highlighted in yellow) such as aryl hydrocarbon receptor; and 10 upregulated pathways were found specific in ApoE^–/– at 78 weeks including 8 innate immune pathways (highlighted in red) such as neuroinflammation, role of osteoclasts in rheumatoid arthritis, PKCθ signaling in T lymphocytes, pyroptosis, IL-7, prolactin, PDGF, immunogenic cell death, and BMP ( Figure 4E ); 14 upregulated pathways were found specific in ApoE^–/– Ang II at 7 days including 6 innate immune pathways (highlighted in red) such as hepatic fibrosis, pulmonary healing, dendritic cell maturation, pulmonary fibrosis idiopathic, role of chondrocytes in rheumatoid arthritis, and pyroptosis, and one differentiation pathway (highlighted in blue) such as regulation of the epithelial mesenchymal transition by growth factors; 4 upregulated pathways were found specific in ApoE^–/– Ang II at 14 days including one innate immune pathway (highlighted in red) such as phagosome formation; and 14 upregulated pathways were found specific in ApoE^–/– Ang II at 28 days including 5 innate immune pathways (highlighted in red) such as T cell exhaustion, PI3K signaling in B lymphocytes, macrophage classical activation, IL-12 signaling and production in macrophages, and role of hypercytokinemia/hyperchemokinemia in the pathogenesis of influenza ( Figure 4F ).

We previously reported that transcription factors (TFs) GATA3, HDAC6, and Bcl-6 regulate Treg plasticity and determine Treg conversion into either novel antigen-presenting cell-like Treg or type 1 T helper cell (Th1)-Treg (21), suggesting that non-Treg T helper cell subsets such as Th2 TF GATA3, follicular T helper cell (Tfh) TF Bcl-6 and HDAC6 cooperate with Treg-specific TF Foxp3 to determine Treg transcriptomes and functions. We hypothesized that aortic diseases upregulate specific TFs. To test this hypothesis, we collected 1496 TFs from a comprehensive HPA database (https://www.proteinatlas.org/search/protein_class:Transcription+factors) as we reported recently (11, 23–25, 75, 77, 81). As shown in Figure 5A , we found that: 1) 19, 35, and 69 TFs were upregulated in ApoE^–/– at 6 weeks, 32 weeks, and 78 weeks, respectively; 2) 31 and 107 TFs were upregulated in BAPN Ang II-induced AAA and PPE-induced AAA, respectively; 3) 112, 18, and 29 TFs were upregulated in ApoE^–/– Ang II-induced AAA at 7 days, 14 days, and 28 days, respectively, also indicating the twin-peak pattern as found in innate immune genes, nuclear membrane genes, nucleoli genes, and nucleoplasm genes; and 4) TF expressions were also upregulated in 0.1% to 1.6% in four human aorta samples but on much smaller scales than that in mouse aortas. The upregulated TFs in human MI, AAA, and AOD were shown in the Supplementary Figures S3A–C .

The Metascape pathway analysis of upregulated TFs showed that: 1) 2 upregulated pathways were found specific in ApoE^–/– at 6 weeks including a differentiation pathway (highlighted in blue) such as epithelial cell differentiation; 9 upregulated pathways were found specific in ApoE^–/– 32 weeks including 4 differentiation pathways (highlighted in blue) such as regulation of stem cell differentiation, lymphoid progenitor cell differentiation, regulation of chondrocyte differentiation, and leukocyte differentiation; 14 upregulated pathways were found specific in ApoE^–/– 78 weeks including 7 differentiation pathways (highlighted in blue) such as stem cell population maintenance, myeloid cell differentiation, hematopoietic stem cell differentiation, Th1 and Th2 cell differentiation, cytodifferentiation, regulation of stem cell proliferation, and hemopoiesis; suggesting that TF pathways in three different stages of atherosclerosis progression in ApoE^–/– HFD aortas are significantly different ( Figure 5B ). 12 TFs upregulated pathways were found specific in ApoE^–/– Ang II at 7 days including 6 differentiation pathways (highlighted in blue) such as mesenchyme development, muscle structure development, embryonic organ development, neural crest differentiation, cytodifferentiation, and cartilage development; 3 TFs upregulated pathways were found specific in ApoE^–/– Ang II at 14 days, including 3 differentiation pathways (highlighted in blue) such as cell morphogenesis involved in neuron differentiation, neuron fate commitment, dopaminergic neuron differentiation; 13 upregulated pathways were found specific in ApoE^–/– Ang II at 28 days including 3 differentiation pathways (highlighted in blue) such as myeloid cell differentiation, positive regulation of myeloid cell differentiation, and hematopoietic stem cell differentiation ( Figure 5C ), suggesting that TF pathways in three different stages of AAA progression in ApoE^–/– Ang II aorta model are significantly different.

Pioneer transcription factors are a special group of TFs whose their binding to regulatory regions is the first event in gene transcription and can occur in silent or heterochromatin regions (82) ( Figure 5D ). We hypothesized that pioneer TF upregulation is a feature of aortic disease progression. Therefore, we examined 15 pioneer TFs (83) and found that one (ASCL1) and two (CEBPA and GATA) pioneer TFs were upregulated in ApoE^–/– at 6 weeks and 78 weeks, respectively; one (SOX2) pioneer TFs was upregulated in PPE-AAA; and one (GATA) and one (FOXA) pioneer TFs were upregulated in ApoE^–/– Ang II-AAA at 7 days and 14 days, indicating that five pioneer TFs, including ASCL1, CEBPA, GATA, SOX2, and FOXA, play significant role in aortic diseases ( Figure 5E ). These results demonstrated that upregulation of pioneer TFs in atherosclerosis and aortic aneurysms are disease-stage-specific events.

Based on those findings outlined in the introduction, we hypothesized that innate immune responses play significant roles in contributing to VSMC trans-differentiation and phenotypic switching in aortic diseases and VSMCs in pathologies are innate immune cells and contribute to aortic diseases, as cellular mechanisms ( Figure 6A ). As shown in Figure 6B , innate immune genes were upregulated in VSMCs stimulated by proinflammatory DAMPs (2, 33) such as high glucose (84), cholesterol, and proinflammatory pathogen-associated molecular pattern (PAMP) lipopolysaccharide (LPS, an endotoxin from gram-negative bacteria) stimulated signal transducer and activator of transcription 1 (STAT1)^–/– VSMCs and LPS stimulated wild-type (WT) VSMCs (85), respectively. In addition, innate immune genes were upregulated in human VSMCs stimulated by metabolic DAMP (86, 87) homocysteine (Hcy) (10 μM), Hcy (100 μM), Hcy (100 μM) versus Hcy (10 μM) (87–89), proinflammatory cytokine IL-17 (49, 50), anti-inflammatory (90, 91), Treg-inducing (21), aneurysm-suppressing (92) and VSMC senescence/Marfan syndrome-inducing (93) cytokine TGF-β (1 ng/ml), and TGF-β (5 ng/ml), respectively. The upregulated innate immune genes in VSMCs stimulate with Hcy, IL-17, TGF-β, cholesterol, and glucose were shown in the Supplementary Figures S4A–F .

The IPA analysis and gene analysis showed that: one upregulated innate immune gene was found specific in Hcy (10 µM)-treated VSMCs including lipid metabolism regulator insulin induced gene 1 (INSIG1) (94); 2 upregulated genes were found specific in Hcy (100 µM)-treated VSMCs, including mitochondrial interacting RING E3 ligase TRIM4 (95) and CR2; one upregulated gene was found to overlap between Hcy (10 µM) and Hcy (100 µM)-treated VSMCs including inflammation mediator Toll-like receptor 5 (TLR5) (96) ( Figure 6C ); 24 upregulated innate genes in IL-17-treated VSMCs were different from 8 innate immune genes in TGF-β-treated VSMCs ( Figure 6D ); 3 pathways were upregulated in VSMCs stimulated by high glucose such as positive regulation of catabolic process, response to hormone, and negative regulation of cell differentiation; 20 pathways were upregulated in cholesterol-loaded VSMCs, including TLR, regulation of inflammatory response, immune effector process, Legionellosis, cytokine signaling, response to type II interferon, lung fibrosis, regulation of DNA-binding transcription factor activity, positive regulation of cytokine production, leukocyte activation, response to virus, innate immune response, TNF, IL-18, positive regulation of response to external stimulus, defense response to bacterium, regulation of leukocyte activation, TLR cascades, response to bacterium, and regulation of response to cytokine stimulus ( Figure 6E ); 5 pathways were specifically upregulated in LPS-stimulated VSMCs, including regulation of defense response, interferon, non-genomic actions of 1,25 dihydroxyvitamin D3, regulation of type I interferon production, SARS-CoV-2 innate immunity evasion, and cell-specific immune response; 7 pathways were specifically upregulated in LPS-stimulated STAT1^–/– VSMCs, including NOD-like receptor, lipid and atherosclerosis, cellular response to virus, Kaposi sarcoma-associated herpesvirus infection, TLR4 cascade, cellular response to cytokine stimulus, and apoptosis; and 9 pathways were specifically upregulated in cholesterol-loaded VSMCs, including regulation of inflammatory response, immune effector process, leukocyte activation, IL-18, positive regulation of response to external stimulus, Legionellosis, lung fibrosis, TLR cascades, and response to bacterium ( Figure 6F ).

Furthermore, we examined cytokines and chemokines ( Figure 7A ) and found that 0.75%, 5.7%, 4.45%, and 4.75% of cytokine and chemokine genes were upregulated in VSMCs stimulated by high glucose, cholesterol, STAT1^–/– LPS-stimulated VSMCs, and WT LPS-stimulated VSMCs, respectively. In addition, 0.45%, 0.075%, 0.3%, 3.1%, 0.5%, and 1.4% of cytokine and chemokine genes were upregulated in human VSMCs stimulated by Hcy (10 μM), Hcy (100 μM), Hcy (100 μM) versus (10 μM), IL-17, TGF-β (1 ng/ml), and TGF-β (5 ng/ml), respectively. Venn diagram analysis in Figure 7B showed i) 5 high glucose-specific upregulated cytokines, including ITGA5, ENPP1, MCAM, CD248, and ITGA1; ii) 17 cholesterol loading-specific upregulated cytokines, including CDH5, IL2RG, CD68, TEK, CD93, ACKR1, ICAM2, CD302, ENPP3, CD200, BST2, TNFRSF9, BST, CXCR4, S1PR1, and IL13RA2; iii) 11 LPS-specific upregulated cytokines, including CD74, CD44, ICAM1, TLR3, PVR, SELP, IL15RA, GYPC, ICAM4, CD47, and VCAM1; iv) 5 high homocysteine-specific upregulated cytokines, including PROM1, NCAM1, RHAG, CR2, and BMPR1b; and v) 3 TGF-specific upregulated cytokines, including CSF1R, SEMA7A, and SDC1, suggesting that stimulation-specific upregulated cytokines were identified among total upregulated cytokines in VSMCs.

We also examined 2202 plasma membrane proteins from the HPA database (77) and a list of 373 CD markers (75). Surprisingly, 124 (33%) out of 373 CD markers overlapped with those of plasma membrane proteins, suggesting that 67% of CD markers may have multiple subcellular membrane locations. As shown in Figure 7A , we found that 1.4%, 2.8%, 1.7%, and 2.1% of plasma membrane protein genes were upregulated in VSMCs stimulated by high glucose, cholesterol, STAT1^–/– LPS-stimulated VSMCs and WT LPS-stimulated VSMCs, respectively. In addition, 1.34%, 6.7%, 4.29%, and 5.09% of CD marker genes were upregulated in VSMCs stimulated by high glucose, cholesterol, STAT1^–/– LPS-stimulated VSMCs and WT LPS-stimulated VSMCs, respectively. Moreover, 0.3%, 0.5%, 0.4%, 2.8%, 0.3%, and 1.0% of plasma membrane protein genes were upregulated in human VSMCs stimulated by Hcy (10 μM), Hcy (100 μM), Hcy (100 μM) versus Hcy (10 μM), IL-17, TGF-β (1 ng/ml), and TGF-β (5 ng/ml), respectively. Furthermore, 0.54%, 0.27%, 0.54%, 4.56%, 0%, and 0.8% of CD marker genes were upregulated in human VSMCs stimulated by Hcy (10 μM), Hcy (100 μM), Hcy (100 μM) versus Hcy (10 μM), IL-17, TGF-B (1 ng/ml), and TGF-B (5 ng/ml), respectively. These results demonstrated that in atherosclerotic and aneurysm conditions, CD marker genes are upregulated more than plasma membrane protein genes in VSMCs.

Next, we examined the upregulated CD marker genes and plasma membrane protein genes in VSMCs stimulated by aortic disease conditions in 8065 markers of human 79 cell types identified in the tissue cell type section in the HPA database (https://www.proteinatlas.org/humanproteome/tissue+cell+type) ( Figure 7C ) and found that 18 cell types exhibit a proportion of upregulated plasma membrane protein genes within the cell-type markers that ranges from 2% to less than 5%, including proximal enterocytes, paneth cells, intestinal goblet cells, basal keratinocytes, squamous epithelial cells, cholangiocytes, enteroendocrine cells, pancreatic endocrine cells, microglial cells, syncytiotrophoblasts, extravillous trophoblasts, cardiomyocytes, skeletal myocytes, melanocytes, monocytes, macrophages, Hofbauer cells, Kupffer cells; 12 cell types exhibit a proportion of upregulated plasma membrane protein genes within the cell-type markers that equal to or greater than 5%, including alveolar cells type 1, alveolar cells type 2, thymic epithelial cells, Leydig cells, endothelial cells, smooth muscle cells, adipocytes, fibroblasts, peritubular cells, endometrial stromal cells, granulocytes, Langerhans cells; 20 cell types exhibit a proportion of upregulated CD marker genes within the cell-type markers that ranges from 2% to less than 5%, including paneth cells, distal enterocytes, basal prostatic cells, glandular and luminal cells, thymic epithelial cells, Leydig cells, extravillous trophoblasts, endothelial cells, smooth muscle cells, adipocytes, melanocytes, fibroblasts, peritubular cells, T-cells, NK-cells, monocytes, macrophages, Hofbauer cells, Kupffer cells, dendritic cells; and 3 cell types exhibit a proportion of upregulated CD marker genes within the cell-type markers that equal to or greater than 5%, including endometrial stromal cells, granulocytes, and Langerhans cells.

Taken together, these results have demonstrated that VSMCs are innate immune cells as judged by the upregulation of innate immune genes, cytokine and chemokine genes, plasma membrane protein genes and CD marker genes in VSMCs in response to various DAMPs, and the upregulation of plasma membrane and CD marker genes indicated the trans-differentiation potentials of VSMCs into 30 new cell types and 23 new cell types, respectively.

We hypothesized that, as innate immune cells, the VSMC nucleus responds to DAMP stimulations by upregulating genes in the nuclear membrane, nucleoli, and nucleoplasm. As shown in Figure 8A , 0%, 2.5%, 1.1%, and 1.1% of nuclear membrane protein genes were upregulated in VSMCs stimulated by high glucose, cholesterol, STAT1^–/– LPS, and WT LPS, respectively. Also, 0.35%, 1.96%, 1.5%, and 1.2% of nucleoli genes were upregulated in VSMCs stimulated by high glucose, cholesterol, STAT1^–/– LPS, and WT LPS, respectively. In addition, 0.4%, 2.2%, 1.5%, and 1.4% of nucleoplasm genes were upregulated in VSMCs stimulated by high glucose, cholesterol, STAT1^–/– LPS, and WT LPS, respectively. Moreover, 0%, 0%, 0%, 0.7%, 0%, and 0.36% of nuclear membrane protein genes were upregulated in human VSMCs stimulated by Hcy (10 μM), Hcy (100 μM), Hcy (100 μM) versus Hcy (10 μM), IL-17, TGF-β (1 ng/ml), and TGF- β (5 ng/ml), respectively. Furthermore, 0.07%, 0.21%, 0.3%, 1.7%, 0.14%, and 0.28% of nucleoli protein genes were upregulated in human VSMCs stimulated by Hcy (10 μM), Hcy (100 μM), Hcy (100 μM) versus Hcy (10 μM), IL-17, TGF- β (1 ng/ml), and TGF- β (5 ng/ml), respectively. Finally, 0.35%, 0.3%, 0.4%, 1.7%, 0.3%, and 0.7% of nucleoplasm protein genes were upregulated in human VSMCs stimulated by Hcy (10 μM), Hcy (100 μM), Hcy (100 μM) versus Hcy (10 μM), IL-17, TGF- β (1 ng/ml), and TGF- β (5 ng/ml), respectively. The upregulated nuclear membrane genes in VSMCs stimulated by LPS, IL-17, Hcy, cholesterol, and TGF-B were shown in the Supplementary Figures S5A–D .

We also noticed that upregulations of nucleoli genes or pathways in VSMCs were different under different stimuli. i) 4, 6, and 7 of upregulated pathways were specific to WT LPS-stimulated VSMCs, STAT1^–/– LPS-stimulated VSMCs, and cholesterol-loaded VSMCs, respectively ( Figure 8B ); ii) 1, 3, and 24 of upregulated nucleoli genes were specific to Hcy (10 μM)-treated VSMCs, Hcy (100 μM)-treated VSMCs, and IL-17-treated VSMCs, respectively ( Figure 8C ); and iii) 24, 1, and 3 of upregulated nucleoli genes were specific to IL-17-treated VSMCs, TGF- β (1 ng/ml)-treated VSMCs, and TGF- β (5 ng/ml)-treated VSMCs, respectively ( Figure 8D ). The upregulated nucleoli genes in VSMCs stimulated by LPS, IL-17, Hcy, cholesterol, and TGF-β were shown in the Supplementary Figures S5E–H . In addition, we also noticed that upregulated pathways of nucleoplasm genes in VSMCs were different under different stimuli: a) 10, 11, and 16 upregulated nucleoplasm pathways were specific to WT LPS-stimulated VSMC, STAT1^–/– LPS-stimulated VSMCs, and cholesterol-loaded VSMCs, respectively ( Figure 8E ); b) 1, 4, and 20 upregulated nucleoplasm pathways were specific to Hcy (10 μM)-treated VSMCs, Hcy (100 μM)-treated VSMCs, and IL-17-treated VSMCs ( Figure 8F ); and c) 19, 8, and 11 upregulated nucleoplasm pathways were specific to IL-17-treated VSMCs, TGF-β (1 ng/ml)-treated VSMCs, and TGF-β (5 ng/ml)-treated VSMCs ( Figure 8G ).

We hypothesized that VSMCs, as innate immune cells, respond to DAMP stimulations by upregulating TF genes. As shown in Figure 9A , 0.067%, 2.7%, 2.2%, and 2.3% of TF genes were upregulated in VSMCs stimulated by high glucose, cholesterol, STAT1^–/– LPS and WT LPS, respectively. In addition, 0.4%, 0.3%, 0.5%, 2.5%, 0.27%, and 0.8% of TF genes were upregulated in human VSMCs stimulated by Hcy (10 μM), Hcy (100 μM), Hcy (100 μM) versus Hcy (10 μM), IL-17-treated VSMCs, and VSMCs stimulated by TGF-β (1 ng/ml) and TGF-β (5 ng/ml), respectively.

We also noticed that upregulations of TF genes or pathways in VSMCs were different under different stimuli: i) 12 of the upregulated TF pathways were specific to WT LPS-stimulated VSMCs which include 4 differentiation pathways (highlighted in blue) such as muscle structure development, embryonic organ development, sensory organ morphogenesis, and epithelial cell differentiation; 13 of the upregulated TF pathways were specific to STAT1^–/– LPS-stimulated VSMCs which include 2 differentiation pathways (highlighted in blue) such as eye development and Hematopoietic stem cell differentiation, and one master TF pathway NF-kappa B signaling; and 12 of the upregulated TF pathways were specific to cholesterol-loaded VSMCs including 6 differentiation pathways such as endoderm differentiation, aorta development, white fat cell differentiation, blastocyst formation, cell fate commitment, and osteoclast differentiation ( Figure 9B ); ii) 15 of the upregulated TF pathways were specific to IL-17-treated VSMCs including 6 differentiation pathways (highlighted in blue) such as regulation of epithelial cell differentiation, sensory organ development, neural crest differentiation, hematopoietic stem cell differentiation, regulation of myeloid cell differentiation, and glandular epithelial cell differentiation; 2 of the upregulated TF pathways were specific to TGF-β (1 ng/ml)-treated VSMCs including one differentiation pathway (highlighted in blue) embryonic placenta development; 6 of the upregulated TF pathways were specific to TGF-β (5 ng/ml)-treated VSMCs including skeletal muscle cell differentiation, gonad development, heart morphogenesis, and heart development ( Figure 9C ); and iii) 6, 5, and 38 upregulated TFs genes were specific to Hcy (10 μM)-treated VSMCs, Hcy (100 μM)-treated VSMCs, and IL-17-treated VSMCs ( Figure 9D ). The upregulated TFs in VSMCs under different DAMP stimulations were shown in the Supplementary Figures S6A–F .

In addition, we also found that three pioneer TFs, including EBF1, FOXA, and PAX7 were upregulated in VSMCs stimulated by various DAMPs ( Figure 9E ). EBF1 and FOXA were upregulated in cholesterol-loaded VSMCs, but FOXA was also upregulated in LPS-stimulated VSMCs. PAX7 was upregulated in IL-17-stimulated VSMCs. Taken together, these results demonstrated that upregulation of pioneer TFs in VSMCs is DAMPs-stimulation-specific.

Previous reports classified TFs into basic helix-loop-helix TFs, zinc finger TFs, homeobox TFs, leucine zipper TFs, and nuclear receptor TFs based on their structural features (https://www.tutorialspoint.com/transcription-factors-definition-effects-and-types#) (97). We and others reported that TFs such as NF-kB (19) and AP-1 (8, 98) migrate from the cytosol to the nucleus in activated cardiovascular cells in response to DAMP stimulation. We hypothesized that transcription factor trafficking from the cytosol to the nucleus and sub-nuclear compartments is modulated in aortic diseases and VSMC inflammation. Based on subcellular localization, we used a Venn diagram (not shown due to space limits) and classified 1496 TFs into possible eight groups in physiological conditions, including 1) 0.13% nuclear membrane TFs, 2) 3.14% nucleoli TFs, 3) 64.43% nucleoplasm TFs, 4) 0% nuclear membrane and nucleoli TFs, 5) 8.49% nucleoli and nucleoplasm TFs, 6) 2.07% nuclear membrane and nucleoplasm TFs, 7) 0% nuclear membrane, nucleoplasm, and nucleoli TFs, and 8) 21.7% non-nucleus TFs as cytosolic signal relaying TFs ( Figure 10A ). As shown in Figure 10B , i) upregulated nucleoli TFs were decreased from 3.14% to 1.47% in aortic diseases, and 0% in VSMCs responding to various DAMPs, which was in a contrast to the roles of nucleoli as a nuclear stress organelle; ii) upregulated nucleoplasm TFs were increased from 64.43% to 70.96% in aortic diseases and 72.18% in VSMCs in response to DAMPs; iii) upregulated nucleoli and nucleoplasm TFs were increased from 8.49% to 11.3% in aortic diseases and 9.77% in VSMCs responding to DAMPs; and iv) non-nucleus-localized TFs were decreased from 21.7% to 13.7% in aortic diseases and 18.05% in VSMC inflammation, which was a contrast to the posttranslational activation and migration from cytosol to nucleus of well-characterized TFs such as NF-kB and AP-1. Our results have demonstrated for the first time that the nuclear and cytosol localizations of TFs are changed in aortic diseases and VSMC immunity, which are new additions to the current TF classification and functions.

As we reported, epigenetic memory plays significant roles in establishing trained immunity and inflammation (4, 67, 98), and the expressions of the majority of histone modification enzymes in CVDs and other inflammations are downregulated (99). Histone modification enzymes facilitate the modification process (e.g., acetylation), enabling the binding of TFs to specific DNA sequences and enhancing gene expression ( Figure 11A ). We hypothesized that the expressions of a minority of histone modification enzymes are upregulated in aortic diseases and VSMC inflammation. As we reported, a few histone modification enzymes were upregulated in ApoE^–/– at 6 weeks, 78 weeks, PPE-AAA, ApoE^–/– Ang II-AAA at 7 days and 28 days, cholesterol-loaded VSMCs, and TGF-β (1 ng/ml)-stimulated VSMCs, and the rest of aortic diseases and VSMC inflammations had no upregulation of histone modification enzymes ( Figures 11B, C ). The majority of upregulated enzymes were localized in nucleoli and nucleoplasm, which was similar to that of upregulated TFs. The 8 upregulated enzymes in ApoE^–/– Ang II-AAA in three time points, such as 7 days, 14 days, and 28 days, were not overlapped ( Figure 11B ).

We previously reported that cell death plays significant roles in activated T cells (20, 56, 100–102), CD4⁺Foxp3⁺ Tregs in vascular inflammation (18, 19), activated ECs in atherosclerosis (8, 11, 33, 103), MI (104), angiogenesis (105), activated VSMCs in neointima hyperplasia (12), non-alcoholic fatty liver disease (106), ischemia-reperfusion in the liver (107), and ultrasound-treated cancer cells (57, 108, 109). We hypothesized that oxidative stress cell death, necrotic cell death (110), and pyroptotic cell death play significant roles in atherosclerosis, aortic aneurysms, and VSMC inflammation (37, 111–114) ( Figure 12A ). As shown in Figure 12B , we found that: 1) 2.9%, 8.8%, and 8.8% of oxidative stress-induced cell death genes; 1.47%, 8.8%, and 10.29% of necrotic cell death genes; 0%, 14%, and 16% of pyroptosis cell death were upregulated in ApoE^–/– at 6 weeks, 32 weeks, and 78 weeks, respectively; 2) 5.88% and 16.67% of oxidative stress cell death genes; 7.35% and 22.06% of necrotic cell death genes; 8% and 52% of pyroptosis cell death were upregulated in BAPN+Ang II-AAA and PPE-AAA, respectively; 3) 21.57%, 3.92%, and 9.8% of oxidative stress cell death genes; 17.65%, 0%, and 5.88% of necrotic cell death genes; and 24%, 4%, and 16% of pyroptosis cell death were upregulated in ApoE^–/– Ang II-AAA at 7 days, 14 days, and 28 days, respectively, also indicating the twin peak pattern as found in innate immune genes and nuclear stress genes.

On the other hand, the removal of billions of apoptotic cells from the system via the process of efferocytosis is essential for homeostasis, which is actively anti-inflammatory, promotes resolution, and prevents aneurysm (96). However, aberrations in efferocytosis are associated with numerous inflammatory pathologies, including atherosclerosis (97) and probably aortic aneurysm ( Figure 12A ). We hypothesized that efferocytosis genes are upregulated in atherogenesis and aortic aneurysm models. As shown in Figure 12B , 0%, 14.89%, and 15.53% of efferocytosis genes were upregulated in ApoE^–/– at 6 weeks, 32 weeks, and 78 weeks, respectively; PPE-AAA upregulated more efferocytosis genes (27.66%) than that of other AAA models; ApoE^–/– Ang II-AAA at 7 days and 28 days upregulated more efferocytosis genes (29.79% and 17.02%) than that of 14 days. These results demonstrated that upregulation of efferocytosis genes may play important roles in atherosclerosis and aortic aneurysms. We also noticed that upregulations of cell death genes in VSMCs were different under different stimuli. i) 0.98%, 10.78%, 5.88%, and 4.9% of oxidative stress cell death genes, 0%, 5.88%, 2.94%, and 7.35% of necrotic cell death genes, 0%, 10%, 12%, and 8% of pyroptosis cell death were upregulated in VSMCs stimulated by high glucose, cholesterol, STAT1^–/– LPS and WT LPS, respectively; ii) 0%, 0%, 1.96%, 0%, and 0% of oxidative stress cell death genes, 0%, 0%, 0%, 1.47%, and 0% of necrotic cell death genes were upregulated in Hcy (10 μM)-treated VSMCs, Hcy (100 μM)-treated VSMCs, IL-17-treated VSMCs, TGF-β (1 ng/ml)-treated VSMCs, and TGF-β (5 ng/ml)-treated VSMCs, respectively ( Figure 12C ). We also examined the efferocytosis in VSMCs treated with different stimulations. As shown in Figure 12C , 0%, 4.26%, 4.26%, and 8.51% of efferocytosis genes were upregulated by high glucose, cholesterol, STAT1^–/– LPS and WT LPS, respectively.

Fibrosis is the compensating process for tissue injury caused by chronic inflammation, which is initially beneficial and maintains extracellular homeostasis. However, in the case of atherosclerosis and aortic aneurysms, activated resident fibroblasts and VSMCs perpetually remodel the extracellular matrix (ECM) under the control of autocrine and paracrine signaling from the immune cells. In consequence, excessive ECM secretion, disorganized ECM, and thickening of the affected tissue result (115). We hypothesized that fibrosis genes are upregulated in the atherogenesis and aortic aneurysm models. As shown in Figure 13A , 1.67%, 10%, and 16.34% of fibrosis genes were upregulated in ApoE^–/– at 6 weeks, 32 weeks, and 78 weeks, respectively; PPE-AAA upregulated more fibrosis genes (19.69%) than that of other AAA models; ApoE^–/– Ang II-AAA at 7 days and 28 days upregulated more fibrosis genes (20% and 9.27%) than that of 14 days. These results demonstrated that upregulation of fibrosis genes may play important roles in atherosclerosis and aortic aneurysms.

Previous reports showed that VSMCs in CVDs can be transdifferentiated into other seven cell types, including 82 markers from mesenchymal stem cell-like VSMCs (48), fibroblast-like VSMCs, myofibroblast-like VSMCs (48), macrophage-like VSMCs, foam cell-like VSMCs (48), osteogenic-like VSMCs (48), and adipocyte-like VSMCs (46–48). We hypothesized that the expression of these seven cell-type marker genes is upregulated in VSMCs stimulated by various DAMPs.

As shown in Figure 13B , PRG4 was the most frequently upregulated fibroblast-like and myofibroblast-like gene in VSMCs stimulated by cholesterol and TGF-β; SPP1 was the upregulated fibroblast and osteogenic gene in VSMCs stimulated by high glucose; CNN1 was the upregulated contractile gene marker in VSMCs stimulated by high glucose and TGF-β; MYA11 and SMTN were the upregulated contractile gene markers in VSMCs stimulated by high glucose and IL-17; CD44 and OLFM2 were the mesenchymal-like marker upregulated in VSMCs stimulated by LPS and TGF-β; LGALS3 and CD68 were the upregulated macrophage-like and foam cell markers in VSMCs stimulated by cholesterol; BMP2 was the upregulated osteogenic marker in VSMCs simulated by cholesterol and IL-17; and PPARGC1 and TMEM26 were the upregulated adipocyte markers in VSMCs stimulated by cholesterol and Hcy. Taken together, these results have demonstrated that cholesterol and TGF-β upregulate multiple cell type markers in VSMC, and high glucose, high Hcy, LPS, and IL-17 upregulate one or two cell type markers, suggesting that trans-differentiation of VSMCs to multiple cell types is induced under those stimuli.

It has been documented that seven cell types were identified in cell trans-differentiation. However, a significant question remained whether cell trans-differentiation in atherosclerosis or AAA is only limited to the seven documented cell type trans-differentiation or can be potentially trans-differentiated to other cell types. Of note, the NIH-funded human protein atlas database explores all the cell type specific marker expressions, which provide a new opportunity, and a unique and non-biased manner to examine the trans-differentiation potential with the markers of all the cell types identified so far. Therefore, we used this approach to examine the trans-differentiation potentials in the mouse aortas with atherosclerosis and AAA. We collected 8065 genes for 79 cell type markers from the “very high” gene groups of all the tissue cell type sections in the HPA (https://www.proteinatlas.org/humanproteome/tissue+cell+type) in order to determine whether VSMCs increase the expression of some of those 79 cell type markers in response to DAMPs. As shown in Figure 13C , since 79 cell types have different numbers of very high gene numbers as markers, the percentage was presented by dividing the numbers of upregulated gene markers by the total number of markers for any given specific cell type. Four groups were selected to be representatives from all the aortic disease groups and VSMC groups, including ApoE^–/– at 32 weeks, ApoE^–/– Ang II at 28 days, cholesterol-loaded VSMCs, and WT LPS-stimulated VSMCs, to be analyzed. The results showed that: 1) the 31 cell types exhibiting a proportional increase of 5% or more cell type markers in ApoE^–/– at 32 weeks included basal respiratory cells, club cells (nonciliated secretory epithelial cells present in bronchioles of distal pulmonary airways) (116), breast glandular cells, basal squamous epithelial cells, Schwann cells (required for successful nerve regeneration; they partially “de-differentiate” in response to injury, re-initiating the expression of developmental genes that support nerve repair), B-cells, monocytes, macrophages, Hofbauer cells [placental villous macrophages of fetal origin that are present throughout pregnancy (117)], Kupffer cells (resident liver macrophages and play a critical role in maintaining liver functions) (118), Langerhans cells (originate from the bone marrow and then migrate into the epithelium to perform the function of antigen recognition and presentation) (119), ionocytes, paneth cells, distal enterocytes, prostatic glandular cells, breast myoepithelial cells, basal keratinocytes, squamous epithelial cells, ductal cells, cholangiocytes, thymic epithelial cells, cytotrophoblasts, syncytiotrophoblasts, extravillous trophoblasts, smooth muscle cells, melanocytes, fibroblasts, endometrial stromal cells, NK-cells, granulocytes, and dendritic cells; 2) the 18 cell types exhibiting a proportional increase of 5% or more cell type markers in ApoE^–/– Ang II-AAA at 28 days included thymic epithelial cells, Leydig cells, theca cells, Schwann cells, smooth muscle cells, fibroblasts, endometrial stromal cells, T-cells, B-cells, plasma cells, NK-cells, granulocytes, monocytes, macrophages, Hofbauer cells, Kupffer cells, dendritic cells, and Langerhans cells; 3) the 18 cell types exhibiting a proportional increase of or more cell type markers in cholesterol-loaded VSMCs, exclude the trans-differentiation cell types discussed earlier, include basal respiratory cells, thymic epithelial cells, Leydig cells (produce the high levels of androgen, testosterone or androstenedione, required for differentiation of male genitalia and brain masculinization) (120), theca cells (differentiate into small luteal cells that produce progesterone in response to luteinizing hormone) (121), syncytiotrophoblasts [a continuous, specialized layer of placenta epithelial cells. They cover the entire surface of villous trees and are in direct contact with maternal blood (https://www.ncbi.nlm.nih.gov/books/NBK53245/)], endothelial cells, peritubular cells, endometrial stromal cells, club cells, ionocytes, glandular and luminal cells, cytotrophoblasts, extravillous trophoblasts, melanocytes, granulocytes, monocytes, Hofbauer cells, and Langerhans cells; and 4) 6 cell types exhibiting a proportional increase of 5% or more in LPS-stimulated VSMCs, exclude the trans-differentiation cell types discussed earlier, include basal respiratory cells, exocrine glandular cells, ductal cells, thymic epithelial cells, pancreatic endocrine cells, and endometrial stromal cells.

Taken together, these results have demonstrated for the first time that 1) atherosclerotic aorta and AAA aorta, i) increase inflammatory cell type recruitment into aorta, ii) upregulate a few other structural cell types for trans-differentiation of vascular cells and immune cells, and iii) increase proliferation of new cell types in aortic diseases; and 2) upregulation of 18 new cell type markers in cholesterol-loaded VSMCs and upregulation of 6 new cell types in LPS-stimulated VSMCs suggest new trans-differentiation potentials of VSMCs stimulated by DAMPs.

To elucidate the molecular mechanisms underlying upregulation of innate immune genes, cytokine and chemokine genes in aortic diseases and VSMC stimulated by DAMPs, we hypothesized that a list of master TFs and master genes are partially responsible for upregulation of those innate immune-related gene lists. As we have shown previously ( Figure 4E ), in the pathways upregulated in ApoE^–/– at 32 weeks, the aryl hydrocarbon receptor (AHR) pathway was upregulated. Also, in ApoE^–/– Ang II at 7 days, ApoE^–/– at 78 weeks, and VSMCs stimulated with LPS, the NF-kB pathway was upregulated ( Figures 2E , 4C, D ). In IL-17-treated VSMCs, NFKBID and NFKBIZ were upregulated ( Figure 9D ). As shown in Figures 14A, 14B , upregulated genes from innate immune genes, cytokines and chemokines, plasma membrane proteins, nuclear membrane proteins, nucleoli proteins, nucleoplasm proteins, TFs, oxidative stress cell death genes, necrotic cell death genes, pyroptosis cell death genes, efferocytosis genes, and fibrosis genes were downregulated in 5 master gene-deficient transcriptomic datasets including inflammatory TFs AHR^–/– dataset (62, 122–124), nuclear factor-kB (NF-kB)^–/– with and without LPS stimulation dataset (125–127), superoxide-generating NADPH oxidase heavy chain subunit (NOX2)^–/– dataset (23, 37, 128, 129), endoplasmic reticulum (ER) stress (130) inducer) stimulation dataset, eukaryotic translation initiation factor 2 alpha kinase 3 (PRKR-like endoplasmic reticulum kinase, PERK^–/– (7, 131)) and PERK^–/– with tunicamycin (inhibitor of the UDP-N-acetylglucosamine-dolichol phosphate N-acetylglucosamine-1-phosphate transferase) dataset, trained immunity (innate immune memory)-promoting histone lysine methyltransferase SET7^–/– dataset (132, 133) and were upregulated in antioxidant TF NRF2^–/– transcriptomic datasets (11), respectively. Our analysis showed that AhR and PERK deficiency had the most significant downregulation of innate immune genes, cytokines and chemokines, oxidative stress cell death genes, and nuclear stress genes ( Figure 14A ).

Oxidative stress is one of the pivotal factors in the pathogenesis of atherosclerosis and AAA. NRF2 is crucial for the oxidative stress response, and the development of atherosclerosis and AAA is intimately linked to the NRF2 signaling pathway. NRF2 signaling controls a variety of physiological and pathological processes that are involved in the development of atherosclerosis, including inflammation, foam cell production, lipid homeostasis regulation, macrophage polarization, and redox regulation (134, 135). NRF2 deficiency in mice accelerates atherosclerotic lesions and increased expression of inflammatory cytokines, such as TNFα, IL-6 and IL-1β (136) as well as AAA formation (137). Therefore, we used the NRF2^–/– transcriptomic datasets to examine the upregulation of upregulated innate immune genes, cytokines and chemokines, and other gene lists in aortic diseases and VSMCs under different stimulation. Our analysis showed that NRF2 deficiency increased the upregulation of innate immune genes, cytokine and chemokine genes, CD marker genes, pyroptosis cell death genes, and fibrosis genes in aortic diseases and DAMPs stimulated VSMCs ( Figure 14B ). Furthermore, as shown in Figure 14C , among the 256 upregulated cytokines and chemokines in ApoE^–/– Ang II at 7 days, there were 27 and 7 cytokines and chemokines downregulated by SET7^–/– and itaconate, respectively; in 47 upregulated cytokines and chemokines in ApoE^–/– Ang II at 14 days, there were 7 and 2 cytokines and chemokines downregulated by SET7^–/– and itaconate, respectively; in 137 upregulated cytokines and chemokines in ApoE^–/– Ang II at 28 days, there were 20 and 6 cytokines and chemokines downregulated by SET7^–/– and itaconate, respectively; in 20 upregulated cytokines and chemokines in ApoE^–/– at 6 weeks, there were 4 and 0 cytokines and chemokines downregulated by SET7^–/– and itaconate, respectively; in 115 upregulated cytokines and chemokines in ApoE^–/– at 32 weeks, there were 14 and 6 cytokines and chemokines downregulated by SET7^–/– and itaconate, respectively; in 209 upregulated cytokines and chemokines in ApoE^–/– at 78 weeks, there were 24 and 8 cytokines and chemokines downregulated by SET7^–/– and itaconate, respectively. The anti-inflammatory cytokines that were upregulated in AAA at 7, 14, and 28 days include IL-6, Il-2, IL-11, and IL-10 ( Figure 14D ); however, the anti-inflammatory cytokines that were upregulated in atherosclerosis include IL-6 and IL-2 ( Figure 14E ).

Taken together, our results have demonstrated that TFs AHR and NF-kB, ER stress-promoting PERK, trained immunity (innate immune memory)-promoting SET7, and reactive oxygen species (ROS)-oxidative stress-generating enzyme NOX2 (37), and antioxidative TF NRF2 play significant roles in regulating upregulation of innate immune genes and other inflammatory genes in aortic diseases and VSMCs responding to DAMPs.