Abstract Hyperlipidemia and chronic kidney disease (CKD) are well-established risk factors for cardiovascular disease and act synergistically to promote vascular inflammation and disease progression. However, the mechanisms underlying this synergetic effect remain largely unknown. Using a mouse model combining hyperlipidemia (via high-fat diet feeding, HFD) with 5/6 nephrectomy-induced CKD, we made the following significant findings: 1) HFD + CKD upregulated 1179 genes in mouse aortas and induced prominent reactive oxygen species (ROS), far more than either HFD or CKD alone. 2) HFD + CKD upregulated 86 CRISPRi-identified mitochondrial ROS regulators, 36 CRISPRi-identified cellular ROS regulators, and 19 GSEA-collected ROS regulators. These changes were associated with the upregulations of 48 cytokines, 7 highest toxicity uremic toxin receptors—including CD1D, FCGRT, AHR, IL6RA AGER, NR1H3 and NPY5R—in aortas. 3) These uremic toxin receptors emerged as novel promoters of inflammation and trained immunity. Deficiencies in CD1D, AHR, AGER, and the trained immunity promoter SET7 each downregulated up to 5.5 % of the genes upregulated by HFD + CKD. Conversely, activation of NR1H3 using an agonist upregulated up to 12.2 % of these genes. 4) The expression of 46 cytokine genes was strongly associated with NR1H3 upregulation. 5) The NR1H3 agonist also induced the expression of 28 ROS regulators, including YBX2, a novel anti-ROS transcription factor and RNA-binding protein, suggesting a potential negative feedback mechanism. YBX2 deficiency increased the cellular ROS level, while YBX2 overexpression suppressed 27 proinflammatory genes induced by HFD + CKD. Our findings provide novel insights into the role of the NR1H3-YBX2 axis in regulating inflammation accelerated by hyperlipidemia and CKD. Keywords: Uremic toxin receptors, NR1H3-YBX2 axis, Chronic kidney disease (CKD), Hyperlipidemia, Vascular inflammation 1. Introduction Chronic kidney disease (CKD) is a prevalent inflammatory condition [[47]1], affecting over 15 % of the adult population globally. Cardiovascular disease (CVD) is a major comorbidity in CKD, with approximately 50 % of patients in advanced or end-stage CKD (stage 4–5) suffering from CVD. Notably, CVD accounts for nearly half of all deaths among these patients [[48]2]. As CKD progresses, dyslipidemia often worsens. Analysis of data from the 2001–2010 National Health and Nutrition Examination Survey (NHANES) showed that the prevalence of dyslipidemia increased from 45.5 % in stage 1 CKD to 67.8 % in stage 4 CKD [[49]3,[50]4]. Both hyperlipidemia [[51]5] and CKD [[52]6,[53]7] significantly accelerate vascular inflammation, which drives the development and progression of atherosclerosis and its associated complications. In CKD, uremic toxins (UTs)—metabolic byproducts normally eliminated by the kidneys—accumulate and act as danger-associated molecular patterns (DAMPs). These UTs activate the DAMP sensor caspase-11 inflammasome, promoting vascular inflammation and neointimal hyperplasia [[54]6]. Additionally, UTs have been reported to increase the production of reactive oxygen species (ROS) [[55]8], which are known to play a critical role in the pathogenesis of CKD. On the one hand, excessive intracellular ROS levels can oxidize lipids, DNA, and proteins, contributing to cellular stress and damage. On the other hand, ROS also serve as essential secondary messengers in cellular signaling pathways [[56]9]. Thus, normal cell function depends on maintaining an optimal ROS balance. We have further demonstrated that ROS systems constitute a new integrated network that senses homeostasis and alarming stress in organelle metabolic processes [[57]10]. As previously outlined [[58]11], the mitochondrial electron transport chain (ETC)—particularly complexes I and III—and nicotinamide adenine dinucleotide phosphate (NADPH) oxidases (NOX) are major sources of ROS in the kidney. To counteract ROS-induced injury, the kidney employs several antioxidant systems, including superoxide dismutase, catalase, glutathione peroxidase, glutathione reductase, glutathione S-transferase, peroxiredoxin, and thioredoxin [[59]9]. Targeting specific NOX isoforms to reduce ROS production while enhancing antioxidant pathways may help preserve renal structure and function and lower blood pressure [[60]12]. Our work and others’ [[61]11,[62]13] have been reviewed the major mitochondrial ROS, antioxidant systems in the kidney, and redox signaling pathways that leads to inflammation and fibrosis, ultimately contributing CKD progression [[63]9,[64]12]. Recently, Bennett, NK et al. utilized a CRISPR interference (CRISPRi) gene knockdown approach to identify 474 mitochondrial and 283 cellular ROS regulators [[65]14]. However, key questions remain: (1) How do these newly identified mitochondrial and cellular ROS regulators mediate aortic inflammation in the context of hyperlipidemia and CKD? (2) Do uremic toxin receptor signals regulate the expression of these ROS regulators and proinflammatory cytokines in the aorta under hyperlipidemia and CKD conditions? CKD is associated with increased oxidative stress, altered amino acid and lipid metabolism, and the accumulation of advanced glycation and peroxidation products. These processes generate toxic lipid species, lipoproteins, and amino acid metabolites. Vanholder R. et al. identified 9 UTs with the highest toxicity evidence scores, and 15 UTs with the second highest [[66]15,[67]16]. Yet, it remains unexplored whether hyperlipidemia and CKD together upregulate the expressions of those highest toxicity receptors in the aorta for potential increase of their signaling. The nuclear receptor subfamily 1 group H member 3 (NR1H3, also known as liver X receptor-α, LXRα) is associated with pro-inflammatory macrophage populations such as M1 [[68]17] and CD68^+CD14^− macrophages [[69]18,[70]19]. Lipid and cholesterol metabolism, oxygen levels, and cytokine gradients are known to regulate the immune microenvironment in tissues [[71]20]. While the activation of LXR by agonist TO901317 exacerbates podocyte loss and albuminuria in streptozotocin (STZ)-induced diabetic mice, suggesting LXR activation may be harmful for diabetic nephropathy [[72]21]. However, knockout of LXRα/β (NR1H2) (LXRα/β^−/−) in mice led to a ten-fold increase in albumin/creatinine ratio (measures the amount of albumin as a protein in the urine relative to the amount of creatinine as a waste control) and a 40-fold increase in glomerular lipid accumulation compared to the WT controls. After the induction of diabetes by STZ, LXRα/β^−/− mice exhibit glomerular lipid accumulation with upregulated inflammation markers and oxidative stress [[73]22,[74]23]. In addition, LXR agonists-loaded, macrophage-targeted nanocarriers have been shown to reduce atherosclerosis by decreasing cholesterol accumulation and inflammation [[75]24]. Common and differential transcriptional actions of nuclear receptors LXRα and LXRβ in macrophages have been reported [[76]25]. These findings suggest that LXRα/β can be protective. Nevertheless, molecular mechanisms underlying this controversy remain poorly understood. Proteomic analysis has revealed increased NR1H3 expression in CKD rat aortas [[77]26], and transcriptomic studies show elevated NR1H3 monocytes from CKD patients [[78]27]. Moreover, LXRα has been implicated in the development of abdominal aortic aneurysm via ubiquitin-like with PHD and Ring finger domains 1 (UHRF1)-mediated epigenetic modulation of miR-26b-3p [[79]28]. Oxysterols—ligands for NR1H3 [[80]29]—are elevated in CKD, are proapoptotic, and promote proinflammatory cytokine release and platelets aggregation [[81]30]. Patients with certain NR1H3 single-nucleotide polymorphisms (e.g., rs2279238, rs7120118, rs11039155) exhibit higher dyslipidemia-related mortality during hemodialysis [[82]31]. Notably, 7-ketocholesterol and 7β–OH–cholesterol, both NR1H3 ligands, are metabolized in the liver and excreted as bile acids [[83]30]. 7-ketocholesterol (nM) is elevated from 32.3 ± 16.7 in healthy controls to 42.2 ± 30.1 in patients with CKD and hemodialysis [[84]32], and 7β–OH–cholesterol (nM) is elevated from 14.4 ± 7.7 in healthy controls to 42.6 ± 24.1 in patients with CKD and end-stage renal disease (ESRD) [[85]33]. Another ligand-activated transcription factor and key nuclear receptor pathway involves aryl hydrocarbon receptor (AHR) signaling [[86]29,[87]34] which can be activated by UTs derived from amino acid tryptophan metabolism. AHR have prooxidant, proinflammatory, procoagulant, and pro-apoptotic effects on cells involved in the cardiovascular system and is implicated in CKD-associated cardiovascular complications [[88]35]. Proteins and lipids are particularly prone to oxidative damage. Oxidative protein modifications such as carbonylation—through glycation and lipid peroxidation via reacting with lysine and arginine residues—generate advanced glycation end products (AGEs) and advanced peroxidation lipid end products (ALEs) [[89]36], which accumulate in CKD [[90]30]. Hyperglycemia-associated generation of AGEs plays a central role in diabetic nephropathy pathophysiology. Engagement of the receptor for AGE (RAGE, AGER) with its ligands provokes oxidative stress and chronic inflammation in renal tissues, ending up with losses in kidney function. Natural killer T cells (NKT)—restricted by CD1D and share characteristics with both conventional T cells and NK cells— bridge between dyslipidemia and immune regulation by recognize glycolipid antigens via CD1D and secreting both proinflammatory and anti-inflammatory cytokines. NKT cells are known to accumulate in atherosclerosis [[91]37,[92]38]. Beyond lipid antigen presentation, CD1D also mediates intracellular signaling. CD1D-deficient macrophages undergo metabolic reprogramming, downregulating lipid metabolic pathways and increasing exogenous lipid import. This metabolic rewiring primes macrophages for enhanced responses to innate signals, as CD1D-KO cells show higher signaling and cytokine secretion upon Toll-like receptor (TLR) stimulation. Mechanistically, CD1D modulates lipid import by controlling the internalization of the lipid transporter CD36, while blocking lipid uptake through CD36 restores metabolic and immune responses in macrophages [[93]39]. However, the roles of UT receptors such as NR1H3, AHR, CD1D, and RAGE (AGER) in aortic inflammation synergistically induced by hyperlipidemia and CKD remain poorly characterized. Trained immunity (innate immune memory) is characterized by long-lasting hyperactivation of innate immune cells. Trained immunity contributes to the pathophysiology of vascular inflammation and atherosclerosis [[94]40]. As we and others reported [[95]41], innate immune cells, including endothelial cells (ECs) [[96]42,[97]43], vascular smooth muscle cells, and venous cells can develop an exacerbated immunologic response and long-term inflammatory phenotype following brief exposure to endogenous or exogenous pathogen associated molecular patterns (PAMPs)/DAMPs. Trained immunity in vascular cells enhances initial immune responses and facilitates transition to chronic inflammation. However, it is still unclear whether UT receptor signaling promotes trained immunity and whether this effect synergizes with hyperlipidemia and CKD accelerated aortic inflammation in a manner comparable to or greater than histone lysine methyltransferase SET7, a known driver of trained immunity as we [[98]44] and others reported [[99]45,[100]46]. Despite significant progress in the field, several important questions remain unknown. Do hyperlipidemia and CKD synergize to promote metabolic reprogramming, oxidative stress, and inflammation beyond the effects of either condition alone? Do hyperlipidemia and CKD upregulate the expression of uremic toxin (UT) receptors, thereby contributing to enhanced vascular inflammation, metabolic reprogramming, oxidative stress, and trained immunity? Additionally, does the combination of hyperlipidemia and CKD induce the expression of CRISPRi-identified ROS regulators in the aorta [[101]14] and do these regulators play a causal role in promoting vascular inflammation? To address these questions, we established a 5/6 nephrectomy CKD mouse model, performed aortic RNA-sequencing (RNA-seq) transcriptomic analysis, and conducted gene knockout -Omics-based analyses. Our findings provide new insights into how hyperlipidemia and CKD accelerate vascular inflammation through a metabolic reprogramming-oxidative stress linked trained immunity mechanism. These discoveries highlight potential therapeutic targets for the treatment of CKD-accelerated CVDs. 2. Results 2.1. Hyperlipidemia plus CKD upregulated 1179 genes in mouse aortas and induced dominant metabolic reprogramming and mitochondrial dysfunctions, exceeding the effects of HFD or CKD alone We previously reported that caspase-4/11 promotes hyperlipidemia- and CKD-accelerated vascular inflammation by enhancing trained immunity [[102]7]. However, our earlier studies did not comprehensively analyze the aortic RNA sequencing (RNA-seq) data with all the controls. To address this, we performed a detailed transcriptomic and knowledge-based analysis ([103]Fig. 1A), to investigate the differential transcriptomic changes in mouse aortas under hyperlipidemia alone (high fat diet (HFD)-sham (a surgical control for 5/6 nephrectomy-induced CKD model)), CKD alone (normal chow diet (ND)-CKD), and combined HFD + CKD conditions. We used a hyperlipidemia combined with 5/6 nephrectomy-induced CKD mouse model, which exhibited elevated circulating cholesterol and blood urea nitrogen level, as we previously reported [[104]7]. As shown in [105]Fig. 1B, HFD-sham compared to ND-sham upregulated 162 genes and downregulated 212 genes; ND-CKD compared to ND-sham upregulated 250 genes and downregulated 137 genes; HFD + CKD compared to ND-sham upregulated 1179 genes and downregulated 373 genes; HFD + CKD compared to HFD-sham upregulated 621 genes (CKD upregulated gene in the presence of HFD) and downregulated 198 genes; and HFD + CKD compared to ND-CKD upregulated 638 genes (HFD upregulated genes in the presence of CKD) and downregulated 301 genes. As shown in the heat map in [106]Fig. 1C, 179 gene upregulation and 373 gene downregulation in HFD + CKD group was confirmed in comparison to their expressions in ND-sham, HFD-sham and ND-CKD groups. To further interpret the biological significance of these differentially expressed genes, we conducted pathway analysis using Ingenuity Pathway Analysis (IPA). As shown in [107]Fig. 1D1, HFD + CKD upregulated 19 top pathways, including electron transport, ATP synthesis, and heat production by uncoupling proteins, mitochondrial dysfunction, oxidative phosphorylation, histone deacetylase sirtuin signaling, mitochondrial translation, etc. Of note, many HFD + CKD upregulated pathways are involved in metabolic reprogramming, consistent with our prior findings of CKD- and hyperlipidemia-promoted metabolic reprogramming and trained immunity [[108]43,[109]47]. Conversely, [110]Fig. 1D2 showed that HFD + CKD downregulated 10 top pathways, including integrin pathway, integrin-linked kinase (ILK) signaling, germ cell-Sertoli cell (in the testes) junction, cell junction, organization, Rho family GTPase, processing of capped intron containing pre-mRNA, etc. HFD-sham compared to ND-sham upregulated three top pathways such as oleate biosynthesis II, NR1D1 repress gene expression, and fatty acid beta-oxidation III ([111]Suppl. Fig. 1D3). ND-CKD compared to ND-sham upregulated four top pathways such as 24-dehydrocholesterol reductase (DHCR24) signaling (heavily key synthetase in cholesterol synthesis [[112]48]), Class A/1 (the pathway for rhodopsin-like receptors), TRIM21 intracellular antibody signaling (tripartite motif-containing 21 is an intracellular antibody receptor that detects and destroys viruses that have entered a cell), and cAMP signaling ([113]Suppl. Fig. 1D4). HFD + CKD compared to HFD-sham upregulated unique 10 top pathways including five nuclear receptor signaling pathways (50 %) such as farnesoid X receptor (FXR)/retinoid X receptor (RXR) activation, retinoic acid receptor (RAR) activation, xenobiotic metabolism pregnane X receptor (PXR) signaling, xenobiotic metabolism of aryl hydrocarbon receptor (AHR) signaling and peroxisome proliferator-activated receptor (PPAR)α/RXRα activation, suggesting that hyperlipidemia and CKD may have some synergy in promoting disease progression via nuclear receptor. HFD + CKD compared to ND-CKD upregulated 8 unique top pathways, including three degradation pathways (37.5 %) such as mitochondrial protein degradation, glutaryl-CoA degradation and tryptophan degradation pathways. Notably, across the HFD + CKD or HFD groups, as many as 18 mitochondria-related pathways were identified, strongly supporting the conclusion that HFD + CKD and HFD both groups induce mitochondrial dysfunction and mitochondrial metabolic reprogramming ([114]Suppl. Fig. 1D5 and 1D6). Fig. 1. [115]Fig. 1 [116]Open in a new tab Hyperlipidemia plus 5/6 nephrectomy-induced chronic kidney disease (HFD-CKD) upregulated 1179 genes and downregulated 373 genes in wild-type mouse aortas in comparison to that of wild-type (WT, normal diet (ND) Sham) aortas, which were more than that of HFD (HFD-Sham) alone and CKD (ND-CKD) alone in comparison to that of ND Sham aortas. A. Schematic presentation of hyperlipidemia plus 5/6 nephrectomy mouse models (HFD-CKD); B. Bulk RNA-Seq analysis on four groups of mouse aortas including: a) normal diet (ND) Sham (wild-type mice fed with ND and Sham controls for surgical CKD model control), b) high fat diet (HFD) Sham, c) ND CKD, and d) HFD CKD. C. The heat maps of the expression patterns of HFD + CKD versus ND Sham) upregulated 1179 genes and downregulated 373 genes in aortas in all four groups of mouse aortas. D1. HFD plus CKD upregulated 19 top pathways. D2. HFD plus CKD downregulated 10 top pathways. 2.2. Hyperlipidemia plus CKD upregulated 86 CRISPRi-identified mitochondrial ROS regulators, 36 CRISPRi-identified cellular ROS regulators, and 19 GSEA-identified ROS regulators in aortas We recently proposed a novel concept that ROS systems function as an integrated network for sensing homeostasis and alarming stresses in organelle metabolic processes [[117]49]. CKD is a well-known condition associated with increased oxidative stress, which is well correlated with our new finding above that HFD + CKD and HFD both groups induce mitochondrial dysfunction, mitochondrial metabolic reprogramming and other organelle metabolic reprogramming. However, the roles of specific ROS regulatory systems in CKD remain largely unexplored. A recent study by Bennett, NK et al. [[118]14] used CRISPR interference (CRISPRi) technology (a loss-of-function approach) to perform systema-level analysis and identified 474 mitochondrial ROS regulators and 283 cellular ROS regulators as genetic modulators of ROS and energy production. Based on this, we hypothesized that hyperlipidemia plus CKD would upregulate the expressions of both mitochondrial and cellular CRISPRi-identified ROS regulators in mouse aortas. As shown in [119]Fig. 2A, ROS regulators were classified by expression patterns: double-positive populations (representing anti-ROS system) and single-positive populations (associated with ROS promotion). As shown in [120]Fig. 2D and [121]Suppl. Fig. 2, our RNA-seq analysis revealed that hyperlipidemia plus CKD (HFD + CKD) upregulated 86 out of 474 (18.1 %) CRISPRi-identified mitochondrial reactive ROS regulators, 36 out of 283 (12.7 %) CRISPRi-identified cellular ROS regulators, and 19 out of 165 (11.5 %) of Gene Set Enrichment Analysis (GSEA)-identified ROS regulators in mouse aortas. In contrast, the control and single-disease groups upregulated significantly fewer ROS regulators: HFD-sham upregulated two CRISPRi-identified mitochondrial ROS regulators, three CRISPRi-identified cellular ROS regulators, and one GSEA-identified ROS regulator ([122]Fig. 2B and [123]Suppl. Fig. 2); ND-CKD upregulated four CRISPRi-identified mitochondrial ROS regulators, four CRISPRi-identified cellular ROS regulators, and three GSEA-identified ROS regulators ([124]Fig. 2C and [125]Suppl. Fig. 2); HFD + CKD compared to HFD-sham upregulated 30 CRISPRi-identified mitochondrial ROS regulators, 17 CRISPRi-identified cellular ROS regulators, and 11 GSEA-identified ROS regulators ([126]Fig. 2E and [127]Suppl. Fig. 2); and HFD + CKD compared to ND-CKD upregulated 44 CRISPRi-identified mitochondrial ROS regulators, 15 CRISPRi-identified cellular ROS regulators, and 12 GSEA-identified ROS regulators ([128]Fig. 2F and [129]Suppl. Fig. 2). These results demonstrate for the first time that hyperlipidemia combined with CKD upregulates as many as 141 ROS regulators, including 86 CRISPRi-identified mitochondrial ROS regulators, and 36 CRISPRi-identified cellular ROS regulators, and 19 GSEA-identified ROS regulators. This extensive upregulation highlights the profound effect of HFD + CKD in modulating the ROS modulatory network, implicating it as a key driver of metabolic reprogramming, oxidative stress, vascular inflammation, and trained immunity. Moreover, our findings show that HFD + CKD preferentially upregulates CRISPRi-mitochondrial ROS regulators over CRISPRi-cellular or GSEA-identified ROS regulators; and HFD + CKD induces a greater ROS regulatory response compared to CKD or HFD alone in mouse aortas. Fig. 2. [130]Fig. 2 [131]Open in a new tab Hyperlipidemia plus CKD upregulated 86 out of 474 (18.1 %) mitochondrial (mito) reactive oxygen species (ROS) regulators and 36 out of 283 (12.7 %) cellular ROS regulators and 19 out of 163 (11.7 %) general ROS regulators in mouse aortas. A. 474 Mito ROS regulators and 283 cellular ROS regulars are screened in our RNA-seq data. B. HFD Sham upregulated two mito ROS regulators, three cellular ROS regulators and one general ROS regulators. C. ND CKD upregulated four mito ROS regulators, four cellular ROS regulators and three general ROS regulators. D. HFD CKD versus ND Sham upregulated 86 mito ROS regulators and 36 cellular ROS regulators and 19 general ROS regulators. E. HFD CKD versus HFD Sham upregulated 30 mito ROS regulators, 17 cellular ROS regulators and 11 general ROS regulators. F. HFD CKD versus ND CKD upregulated 44 mito ROS regulators, 15 cellular ROS regulators and 12 general ROS regulators. 474 Mito ROS regulators and 283 Cellular ROS regulators were collected from a new PNAS paper (PMID 38207075). These findings suggest a central role for ROS regulatory systems, particularly mitochondrial ROS regulators, in the pathogenesis of CKD- and hyperlipidemia-induced vascular inflammation. 2.3. Hyperlipidemia plus CKD upregulated 48 cytokine genes in aortas to promote inflammation We hypothesized that HFD + CKD upregulates cytokine genes to drive vascular inflammation, as we previously reported [[132]7]. To test this, we analyzed RNA-seq data using a comprehensive list of cytokine genes encoded in the human genome from the Human Protein Atlas database ([133]https://www.proteinatlas.org/). As shown in [134]Fig. 3A, HFD-sham upregulated only two cytokine genes, GDF9 and JUNB. ND-CKD upregulated one cytokine gene, RTN4RL2. In contrast, HFD + CKD significantly upregulated 48 cytokine genes, indicating synergistic inflammatory responses. Pathway enrichment analysis of these 48 cytokines revealed the top 20 pathways involved, including positive regulation of response to external stimulus, regulation of cell-cell adhesion, positive regulation of cytokine production, viral protein interaction with cytokine and cytokine receptor, protein phosphorylation, etc. As shown in [135]Fig. 3B, HFD + CKD compared to HFD-sham upregulated 33 cytokine genes and enriched 19 unique pathways, however, HFD + CKD compared to ND-CKD upregulated 25 cytokine genes and enriched 15 unique pathways. These results clearly indicate that HFD in the presence of CKD induces significantly more cytokine gene expression and signaling pathway activation than HFD alone (only GDF9 and JUNB). Likewise, CKD in the presence of HFD results in far more upregulation than CKD alone (only RTN4RL2). As shown in [136]Fig. 3C, HFD + CKD compared to HFD-sham upregulated 47 cytokine genes and enriched 20 unique pathways. Of note, 11 out of 20 cytokine pathways included positive regulation of response to external stimulus, regulation of cell-cell adhesion, positive regulation of cytokine production, viral protein interaction with cytokine and cytokine receptor, regulation of tumor necrosis factor superfamily cytokine production, negative regulation of cytokine production, negative regulation of cell adhesion, inflammatory response, chemokine signaling pathway, positive regulation of canonical NF-kB signal transduction, and AGE-RAGE signaling pathway in diabetic complication. Together, these findings strongly suggest that hyperlipidemia and CKD synergize to amplify aortic inflammation, potentially via trained immunity mechanisms [[137]42,[138]47]. Fig. 3. [139]Fig. 3 [140]Open in a new tab HFD plus CKD (versus ND Sham) upregulated 48 (4.1 %) Human Protein Atlas (HPA) cytokine genes in mouse aortas. A. Venn diagram of upregulated gene (P < 0.05 and Log2FC > 1) in HFD Sham vs. ND Sham, ND CKD vs. ND Sham, HFD CKD vs. ND Sham with Cytokines. B Venn diagram of upregulated gene (P < 0.05 and Log2FC > 1) in HFD CKD versus HFD Sham, HFD CKD versus ND CKD with Cytokines. C. Pathway comparison for three HFD related datasets including HFD CKD versus ND Sham upregulated cytokines, HFD CKD versus HFD Sham upregulated cytokines, and HFD CKD versus ND CKD upregulated cytokines. 2.4. Hyperlipidemia plus CKD upregulated five highest-toxicity and 4 s highest-toxicity uremic toxin receptors in aortas We previously demonstrated that UTs act as conditional DAMPs, capable of triggering inflammation [[141]50], and UT generations in CKD and other metabolic diseases such as early hyperlipidemia are upregulated. Based on these findings, we hypothesized that hyperlipidemia and CKD together upregulate UT receptors expression in mouse aortas, thereby enhancing inflammatory signaling. Building on reports by Vanholder R. et al. [[142]15,[143]16], who ranked 9 UTs with the highest toxicity evidence scores and 15 UTs with the second highest toxicity evidence scores, we conducted a comprehensive literature search to identify 13 receptors for the highest toxicity UTs and 31 receptors for the second highest toxicity UTs ([144]Suppl. Fig. 3). Although there were some inconsistences among the RNA-seq data within each group, statistical analysis showed that hyperlipidemia plus CKD upregulated five highest toxicity UT receptors (CD1D1, CD1D2, Fc gamma receptor and transporter (FCGRT), Aryl hydrocarbon receptor (AHR), and Interleukin 6 receptor alpha (IL6RA)) ([145]Fig. 4A). Of note, natural killer T cells (NKT) are CD1d-restricted, glycolipid antigens-reactive T cells, which express semi-invariant T cell antigen receptor (TCR) and support cell-mediated immunity against infection, cancer, allergy, autoimmunity, allograft rejection and graft-versus-host disease [[146][51], [147][52], [148][53]]. The scavenger receptor CD36 participates in the development of lipoprotein glomerulopathy (LPG) in immunoglobulin Fc receptor γ chain (F(c)Rγ)-deficient mice with induced chronic graft-versus-host disease (cGVHD) [[149]54]. Hyperlipidemia plus CKD also upregulated four receptors for the UTs with the second highest toxicity evidence scores including AGER, AHR, NR1H3 and NPY5R ([150]Fig. 4B). This data provides the first evidence that hyperlipidemia and CKD synergistically upregulate UT receptors, which may represent a novel mechanism for enhanced receptor-mediated signaling. This new mechanism likely contributes to vascular inflammation, oxidative stress, and metabolic dysregulation in the context of CKD-accelerated CVDs. Fig. 4. [151]Fig. 4 [152]Open in a new tab Hyperlipidemia plus chronic kidney disease (CKD) promote aortic vascular inflammation via upregulating uremic toxin receptors as a new receptor type of danger associated molecular patterns. A. Heatmap of 13 1st highest uremic toxin receptors in each groups. B. Heatmap of 31 2 nd highest uremic toxin receptors in each groups. Red color indicates P < 0.05 and Log2FC > 0.58 in HFD CKD vs. ND Sham. 2.5. 46 cytokine genes were co-upregulated with CD1D and NR1H3 in hyperlipidemia plus CKD aortas Genes that are co-expressed—showing similar expression patterns across biological conditions—often participate in related functional processes, and such co-expression network have been used to identify functionally associated genes in various disease settings [[153]55]. Therefore, we hypothesized that some UT receptors might be co-upregulated with cytokine genes and mitochondrial energy generation genetic disease genes in the context of hyperlipidemia and CKD. To examine this hypothesis, based on their higher expression induced by HFD + CKD in aorta than other groups, we focused on four UT receptors—CD1D1, CD1D2, AHR and NR1H3—and analyzed the co-expression with cytokine genes (log2 fold change (FC) > 1, P < 0.05). We performed the Pearson Correlation analysis ([154]Fig. 5A), and the correlation cutoff was P < 0.05 and Pearson_Correlation R^2 was >0.8. As shown in [155]Suppl Fig 4 and Fig. 5B, the Pearson Correlation Analyses identified that four UT receptors (AHR, CD1D1, CD1D2and NR1H3) were co-expressed with 13, 47, 45, and 46 cytokines in mouse aortas stimulated by HFD + CKD, respectively. To determine potential mechanisms underlying the complete co-upregulation of cytokine genes with uremic toxin receptors, we used transcription factor gene list from the comprehensive Human Protein Atlas database and screened it in our RNA-seq data. Top 10 upregulated transcription factors (p < 0.05 and Log2FC > 2) in HFD CKD vs. ND Sham group were collected for further analysis. We performed Pearson correlation analysis between top 10 transcription factors and uremic toxin receptors CD1D1, CD1D2 and NR1H3 ([156]Supp. Fig. 6A–C). The expressions of three transcription factors were correlated with that of CD1D1, CD1D2 and NR1H3 including MLXIPL, PPAGR and ESRRG. Surprisingly, 34.09 % cytokines were upregulated in ESRRG overexpression condition ([157]Supp. Fig. 6D), which suggest that the transcription factor ESRRG plays an important role in this process and may serve as potential molecular mechanisms underlying the expressions of co-upregulated cytokines and uremic toxins receptors. Taken together, these results demonstrated that 1) signaling pathways and transcription factor machinery up-regulating the expression of UT receptors were partially overlapped with that of the upregulation of cytokines; 2) the co-upregulation of 44 cytokine genes with CD1D and NR1H3 were completely overlapped, suggesting that the signaling pathways and transcription factors controlling the expressions of CD1D and NR1H3 are the same; 3) the numbers of cytokine genes with CD1D and NR1H3 were much more than that of AHR; and 4) co-upregulations of CD1D and AHR with 11 cytokine genes were completely overlapped for AHR but partially overlapped for CD1D. Fig. 5. [158]Fig. 5 [159]Open in a new tab Statistical correlation analysis identified that four uremic toxin receptors such as Antigen-Presenting Glycoprotein CD1d (CD1D1, CD1D2), Aryl Hydrocarbon Receptor (AhR) and Nuclear Receptor Subfamily 1 Group H Member 3 (NR1H3) were co-upregulated with cytokine genes and bioenergetic genes in HFD + CKD mouse aortas, respectively. A. Working model by using RNA-seq data to perform Pearson Correlation Analysis, cut off p < 0.05 and Pearson Correlation R > 0.8. B. Heatmap of four uremic toxin receptors AHR, CD1D1, CD1D2, NR1H3 strongly associated with upregulated cytokines in hyperlipidemia plus chronic kidney disease condition. 2.6. UT receptors functioned as a novel promoter of trained immunity; deficiencies in UT receptors—CD1D, AHR, AGER—as well as the trained immunity promoter SET7 led to the downregulation of up to 5.5 % of genes induced by hyperlipidemia plus CKD in aortas, while activation of NR1H3 upregulated up to 12.2 % of these genes Based on two key findings above: (1) the upregulation of five highest-toxicity and 4 s highest-toxicity UT receptors by hyperlipidemia and CKD, and the co-upregulation of three UT receptors (CD1D, AHR, NR1H3) with cytokines, we hypothesized that deficiencies of UT receptors would downregulate, and activation of UT receptors with its agonist would upregulate gene expression induced by hyperlipidemia plus CKD in aorta. As shown in [160]Fig. 6A, the deficiencies of UT receptors, including CD1D, AHR and AGER led to a downregulation of up to 5 % of HFD plus CKD-induced genes. Meanwhile, the activation of NR1H3 by its agonist resulted in an upregulation of up to 12.2 % of HFD plus CKD-induced genes. These results suggest that CD1D contributes significantly to the expression of genes upregulated by HFD plus CKD; AHR and AGER individually contribute to 4.16 % of HFD plus CKD upregulated genes; and NR1H3, through agonist activation, modulated substantially higher proportion (12.2 %) of HFD plus CKD upregulated genes, highlighting its stronger roles in upregulating cytokines and vascular inflammation than other UT receptors. Moreover, the trained immunity promoter SET7 [[161]44,[162]45] (also known as SETD7, a histone lysine methyltransferase) signaling contributed to 5.5 % of HFD plus CKD upregulated genes in aortas, suggesting that trained immunity is a novel mechanism underlying the synergy between hyperlipidemia and CKD in promoting vascular inflammation. Trained immunity pathways other than SET7, may potentially contribute to the synergy between hyperlipidemia and CKD in promoting vascular inflammation. Fig. 6. [163]Fig. 6 [164]Open in a new tab Deficiencies in uremic toxin receptors—CD1D, AHR, AGER—as well as the trained immunity promoter SET7 led to the downregulation of up to 5.5 % of genes induced by hyperlipidemia plus CKD in mouse aortas, while activation of NR1H3 upregulated up to 12.2 % of these genes. A. The percentage of significantly upregulated genes (P < 0.05, log2FC > 1) in each group was regulated by CD1D KO, AHR KO, AGER KO, NR1H3 agonist and SET7 KD condition. Red color indicates the highest percentage in each group. To determine the signaling pathways through which the UT receptors CD1D, AHR, AGER, NR1H3, and SET7 contribute to the regulation of genes upregulated in by hyperlipidemia (HFD) plus CKD, we analyzed pathway enrichment data, as shown in [165]Suppl. Fig. 5, CD1D upregulated four pathways in HFD + CKD aortas, including fatty acid metabolic process, positive regulation of cytokine production, regulation of mitochondrion organization, and lipid catabolic process. AHR upregulated nine pathways in HFD + CKD aortas, including long-chain fatty acid transport, Omega 9 fatty acid synthesis, Glycerophospholipid biosynthesis, small molecule catabolic process, multicellular organismal-level chemical homeostasis, glutathione metabolic process, regulation of fat cell differentiation, regulation of sequestering of calcium ions, and DNA-templated transcription. AGER upregulated nine pathways in HFD + CKD aortas, including brown fat cell differentiation, Complex III assembly, energy derivation by oxidation of organic compounds, Citric acid cycle (TCA cycle), circadian rhythm, organic acid catabolic process, negative regulation of lipid storage, Insulin resistance, cytochrome c oxidase, mitochondrial. NR1H3 upregulated 15 pathways in HFD + CKD aortas, including response to nutrient levels, alpha-amino acid metabolic process, response to fatty acid, glycerolipids and glycerophospholipids, lipid biosynthetic process, omega 3 Ω 6 fatty acid synthesis, regulation of cold-induced thermogenesis, alcohol metabolic process, cholesterol metabolism with Bloch and Kandutsch Russell biosynthesis pathways, generation of precursor metabolites and energy, peroxisomal protein import, regulation of lipid metabolic process, metabolism of lipids, carbon metabolism, and fatty acid biosynthesis. SET7 upregulated 11 pathways in HFD + CKD aortas, including propanoate metabolism, vitamin B5 (pantothenate) metabolism, regulation of glucose metabolic process, multicellular organismal-level iron ion homeostasis, electron transport chain, nucleoside phosphate metabolic process, monocarboxylic acid transport, apoptotic mitochondrial changes, metabolism of amino acids and derivatives, ribonucleoside diphosphate metabolic process, and regulation of fatty acid metabolic process. In addition, several pathways were shared among these regulators: AHR and RAGE shared one pathway, RAGE and NR1H3 shared three pathways, AHR and NR1H3 shared one pathway, NR1H3 and SET7 shared one pathway, and RAGE and SET7 shared one pathway. These results demonstrated that the UT receptors CD1D, AHR, AGER, and NR1H3 contribute to HFD plus CKD-induced vascular inflammation and metabolic reprogramming. Their signaling overlaps significantly with that of SET7, indicating a common role in promoting the trained immunity synergies between hyperlipidemia and CKD. Based on these findings, we propose a new concept that UT receptors function as trained immunity promoters. Through this new mechanism, the combination of hyperlipidemia and CKD promotes trained immunity and a synergistic increase in vascular pathologies, highlighting potential new targets for therapeutic intervention in cardio-renal-metabolic diseases. 2.7. The NR1H3 agonist upregulated 28 ROS regulators; SET7 upregulated 14 ROS regulators; CD1D upregulated 2 ROS regulators; AHR upregulated 4 ROS regulators; and AGER upregulated 10 ROS regulators that were induced by hyperlipidemia plus CKD in mouse aorta As shown in [166]Fig. 2D, hyperlipidemia plus CKD upregulated 141 ROS regulators in mouse aorta, including 86 mitochondrial ROS regulators, 36 cellular ROS regulators, and 19 GSEA-identified ROS regulators. We hypothesized that UT receptor signaling contributes to this upregulation of ROS regulators in HFD plus CKD conditions. As shown in [167]Fig. 7A, treatment with an NR1H3 agonist upregulated three mitochondrial ROS regulators, one cellular ROS regulator, and two GSEA-identified ROS regulators in ND-CKD aortas. In [168]Fig. 7B, in HFD + CKD compared to HFD-sham aortas, NR1H3 agonist upregulated six mitochondrial ROS regulators, five cellular ROS regulators, and five GSEA-identified ROS general regulators. In HFD + CKD compared to ND-CKD aortas, NR1H3 agonist upregulated eight mitochondrial ROS regulators, three cellular ROS regulators, and five GSEA-identified ROS regulators ([169]Fig. 7C). In total, among the 46 ROS regulators upregulated in HFD + CKD in mouse aortas ([170]Figs. 7D), 15 mitochondrial ROS regulators, eight cellular ROS regulator and 5 GSEA-identified ROS regulators were upregulated by NR1H3 agonist in HFD + CKD compared to ND-sham. In contrast, the downregulation of ROS regulators was observed with loss-of-function models, CD1D1 deficiency downregulated one mitochondrial ROS regulator (PABPC4) in HFD + CKD compared to ND-sham aortas. AHR deficiency downregulated one mitochondrial ROS regulator (MEM143), two cellular ROS regulators, and one GSEA-identified ROS regulator in HFD + CKD compared to ND-sham aortas. AGER deficiency downregulated six mitochondrial ROS regulators, three cellular ROS regulators, and one GSEA-identified ROS regulator in HFD + CKD compared to ND-sham aortas. SET7 knockdown downregulated six mitochondrial ROS regulators, three cellular ROS regulators, and five GSEA-identified ROS regulators in HFD + CKD compared to ND-sham aortas. These results demonstrate that NR1H3 signaling contributes more than other UT receptors, including CD1D, AHR, AGER, and SET7 to the upregulation of 28 ROS regulators including 15 mitochondrial ROS regulators, eight cellular ROS regulators, and 5 GSEA-identified ROS regulators induced by hyperlipidemia plus CKD. Similarly, SET7 contributed to the upregulation of 14 ROS regulators, indicating its substantial role—second only to NR1H3—in mediating ROS regulatory gene expression in response to hyperlipidemia and CKD. Together, these findings support the role of NR1H3 and SET7 in promoting ROS signaling and oxidative stress pathways in vascular inflammation induced by hyperlipidemia and chronic kidney disease. Fig. 7. [171]Fig. 7 [172]Open in a new tab The NR1H3 agonist upregulated 28 ROS regulators in HFD CKD vs. ND Sham. A-C. Heatmap of ROS regulator in CD1D KO, AHR KO, AGER KO, NR1H3 agonist and SET7 KD condition. Each ROS regulated was significantly upregulated (P > 0.05 and Log2FC > 1) in ND CKD vs. ND SHAM, HFD CKD vs. HFD Sham and HFD CKD vs. ND CKD. D. Heatmap of ROS regulator in CD1D KO, AHR KO, AGER KO, NR1H3 agonist and SET7 KD condition. Each ROS regulated was significantly upregulated (P > 0.05 and Log2FC > 1) in HFD CKD vs. ND Sham. Green means ROS inhibitor and Red means ROS promoter. 2.8. NR1H3 agonist upregulates a novel transcription factor, YBX2; YBX2 deficiency increases cellular ROS, while YBX2 overexpression downregulates 38 genes induced by hyperlipidemia plus CKD, including 27 proinflammatory genes We hypothesized that among the 46 ROS regulators upregulated by HFD plus CKD and UT receptor signaling, some ROS regulators may act as master regulators—particularly transcription factors. To identify such candidates, we employed Venn diagram approach to compare transcription factors across three ROS regulator groups: 474 CRISPRi-identified mitochondrial ROS regulators, 283 CRISPRi-identified cellular ROS regulators [[173]14], and 165 GSEA-identified ROS regulators. These were completed against the comprehensive list of 1496 transcription factors from the Human Protein Atlas. As shown in [174]Fig. 8A, we identified seven transcription factors (NRF1, KAT8, RERE, THRA, RCOR3, TSHZ3 and NR1H4) among the 474 mitochondrial ROS regulators, two transcription factors (YBX2, PBRM1) among the 283 cellular ROS regulators, and seven transcription factors (FOXM1, NFE2L2 (NRF2), PAX2, FOXO1, TFAP2A, TP53 and HIF1A) among the GSEA-identified ROS regulators. Fig. 8. [175]Fig. 8 [176]Open in a new tab NR1H3 agonist upregulates a novel transcription factor, YBX2. A. Venn diagram analysis of Mito ROS regulator, Cellular ROS regulator and General ROS regulator with transcription factor list from human protein atlas. B. Among 46 ROS regulators upregulated by hyperlipidemia plus CKD in mouse aortas, YBX2 was the only transcription factors. C. YBX2 deficiency via a CRISPRi technology resulted in increasing cellular ROS detected using DCFDA cellular ROS probe, confirming that YBX2 is an anti-ROS regulator. The data was generated by re-analyzing the data in a PNAS paper (PMID 38207075). D. The correlation analysis of NR1H3 and YBX2 in HFD, CKD or HFD plus CKD condition. E. The Venn diagram of YBX2 inhibited gene with HFD CKD upregulated genes. The 38 genes had 8 top signaling pathways including adult behavior, glucagon signaling, neuronal system, cellular response to steroid hormone, monoatomic ion transmembrane transport, protein homooligomerization, cytokine production and inner ear development. F. The Venn diagram of YBX2 inhibited gene with HFD CKD upregulated cytokines. G. The Venn diagram of YBX2 stabilized genes with 3 groups of ROS regulator. H. Cellular ROS levels of human aortic endothelial cells were measured using DCFDA staining in response to 18 h treatments of uremic toxin phenylacetic acid and four other NR1H3 ligands. Positive control: Pyocyanin 100uM. Negative control: N-acetyl Cysteine 30 mM. Among the 46 ROS regulators upregulated in mouse aortas by hyperlipidemia plus CKD ([177]Fig. 7D), YBX2 was the only transcription factors ([178]Fig. 8B) that was both induced by HFD plus CKD and upregulated by the NR1H3 agonist ([179]Fig. 7D). YBX2 deficiency, created using CRISPRi, significantly increased cellular ROS levels as detected by the dichlorodihydrofluorescein diacetate (DCFDA) cell-permeant ROS probe, demonstrating that YBX2 function as an anti-ROS transcription factor. Of note, the data shown in [180]Fig. 8C were generated by re-analyzing s dataset from Bennett, NK et al., 2024 PNAS paper [[181]14]. Interestingly, we found that YBX2 expression was strongly associated with the UT receptor NR1H3 (R^2 = 0.9665, P = 0.0004), but only under HFD + CKD conditions, not in HFD alone or CKD alone ([182]Fig. 8D). To determine the roles of YBX2 in regulating genes upregulated by HFD plus CKD, we examined overlap between YBX2-overexpression-downregulated genes and HFD plus CKD-upregulated genes in mouse aortas. As shown in [183]Figs. 8E and 38 such genes were overlapped, suggesting that YBX2 directly or indirectly inhibits the expression of these genes. Pathway analysis revealed that the 38 genes YBX2-inhibited genes were enriched in eight major pathways, including adult behavior, glucagon signaling, neuronal system, cellular response to steroid hormone, monoatomic ion transmembrane transport, protein homooligomerization, cytokine production, and inner ear development. To further understand the role of these 38 genes in inflammation, we conducted an extensive literature search. Based on literature searches of the 38 genes: 27 genes were proinflammatory, seven genes were anti-inflammatory, and four genes were poorly characterized with unclear roles in inflammation. We also assessed whether YBX2 modulates the expression of 47 cytokines upregulated by HFD plus CKD ([184]Fig. 2A). As shown in [185]Fig. 8F, four cytokines—CXCL14, NLRP3, FABP4 and KCTD1—were downregulated by YBX2 overexpression. Specifically CXCL14 is both proinflammatory and involved in anti-tumor immunity [[186]56,[187]57], NLRP3 is a well-known proinflammatory inflammasome component [[188]5,[189]58], FABP4 encodes a proinflammatory fatty acid binding protein FABP4 [[190]59], and KCTD1 is associated with scalp-ear-nipple syndrome (some patients may experience skin irritation or inflammation due to the scalp lesions PMID: [191]23541344). To determine whether YBX2 may serve as master anti-ROS transcription factor, we collected a list of YBX2 target genes and performed a Venn diagram analysis ([192]Fig. 8G). We found that YBX2 can stabilize 16 mitochondrial ROS regulators, 9 cellular ROS regulators, and 3 general ROS regulators. Our results have demonstrated for the first time that NR1H3-YBX2 axis plays significant roles in regulating inflammation accelerated by hyperlipidemia and CKD. We hypothesized that the activation of NR1H3 will further promote YBX2 anti-ROS pathway. Based on the European Uremic Toxin Work Group database, phenylacetic acid has been identified as uremic toxin and the plasma concentration in CKD patients can be as high as 3.49 ± 0.33 mmol/l [[193]60], we designed dose-dependent experiments to measure using DCFDA staining the cellular ROS levels of human aortic endothelial cells treated with phenylacetic acid and four other NR1H3 ligands including 24(S),25-epoxy Cholesterol, 24(S)-hydroxy Cholesterol, 25-hydroxy Cholesterol and 27-Hydroxycholesterol. Interestingly, we found that uremic toxin phenylacetic acid will increase cellar ROS levels and had a dose-dependent trend to inhibit ROS. When treated human aortic endothelial cells with four other NR1H3 ligands, we found that they had a dose-dependent response to inhibit cellular ROS levels ([194]Fig. 8H). Combining the new data with [195]Fig. 7D, our results suggested that NR1H3 agonists may activate YBX2-mediated anti-ROS pathway. 3. Discussion We have previously introduced several novel concepts such as: (1) UTs act as DAPMs [[196]50]; (2) Hyperlipidemia and CKD accelerate vascular inflammation via trained immunity [[197]7]. In this study, we present several significant new findings: 1) Hyperlipidemia (HFD) plus CKD upregulates 1179 genes in mouse aortas, activating 18 signaling pathways predominantly related to metabolic reprogramming and mitochondrial dysfunctions —far more than the pathway numbers induced by HFD or CKD alone. 2) HFD plus CKD upregulates 48 cytokine genes and 20 inflammation-related signaling pathways in aortas, intensifying inflammatory responses. 3) HFD plus CKD upregulates 86 CRISPRi-identified mitochondrial ROS regulators, and 36 CRISPRi-identified cellular ROS regulators, and 19 GSEA-identified ROS regulators in mouse aortas, confirming widespread oxidative stress and redox imbalance. 4) HFD plus CKD increases the expression of five highest-toxicity and 4 s-highest toxicity UT receptors in mouse aortas. 5) Co-upregulation of 44 cytokine genes with UT receptors CD1D and NR1H3 are revealed in HFD plus CKD conditions. 6) UT receptors function as a novel promoter of trained immunity. Deficiencies in CD1D, AHR, AGER, and the trained immunity promoter SET7 downregulate up to 5.5 % of HFD + CKD-upregulated genes. In contrast, activation of NR1H3 by its agonist upregulates up to 12.2 % of HFD + CKD-upregulated genes. 7) NR1H3 agonist upregulates 28 ROS regulators, SET7 upregulates 14 ROS regulators, CD1D upregulates 2 ROS regulators, AHR upregulates 4 ROS regulators, and AGER upregulates 10 ROS regulators, which all are induced by HFD plus CKD conditions. 8) Most notably, NR1H3 agonist induces the novel anti-ROS transcription factor and RNA-binding protein YBX2. YBX2 deficiency leads to increased cellular ROS levels, while YBX2 overexpression downregulates 38 genes, including 27 proinflammatory genes, which are otherwise upregulated by HFD plus CKD. It has been reported that NR1H3 ligands are increased in CKD patients and may promotes vascular inflammatory disease ([198]Supp Fig. 6E and F). Previous studies have shown that NR1H3 (LXRa) activation plays protective roles in various diseases, including atherosclerosis, myocardial infarction and reperfusion injury, diabetic nephropathy, periodontal disease, acute lung injury, neuroinflammation, Alzheimer's disease, stroke, and sepsis. However, NR1H3 activation can also promote non-alcoholic fatty liver disease, dysregulated lipid metabolism, viral hepatitis, and asthma [[199]61]. A high cholesterol diet in apolipoprotein E (ApoE)-deficient mice upregulates NR1H3 mRNA in renal proximal tubular cells. Furthermore, high cholesterol diet plus uninephrectomy (UN-CKD) also increases NR1H3 expression and promotes inflammation in renal proximal tubular cells compared to wild-type (WT) controls. However, NR1H3 expression is not elevated as much in high cholesterol diet + UN-CKD condition as in high cholesterol diet alone [[200]62]. Importantly, a critical question remained unanswered but is addressed in this study: NR1H3 plays, as a UT receptor, significant roles in mediating aortic inflammation under hyperlipidemia plus CKD? Based on our findings, we propose a new working model ([201]Fig. 9): 1) HFD plus CKD-stimulated aortic inflammation is an oxidative disease, as evidenced by upregulation of 141 ROS regulators in mouse aorta, including 86 mitochondrial ROS regulators, 36 cellular ROS regulators, and 19 GSEA-identified ROS regulators; 2) Upregulation of UT receptors is a newly identified mechanism contributing to HFD plus CKD-induced inflammation. This correlates closely with elevated oxidative signaling; 3) UT receptors act as trained immunity promotes, even more potent than the classical pathway mediated by SET7 in upregulating proinflammatory genes; and 4) The proinflammatory UT receptor NR1H3 upregulates over 12 % of the genes induced by HFD plus CKD. In addition to upregulating proinflammatory cytokines and ROS regulators, NR1H3 also activates YBX2, a novel anti-ROS transcription factor and RNA-binding protein. Notably, this activation occurs only in the presence of both HFD and CKD, but not with either condition alone. It has been reported that tumor necrosis factor alpha and Interleukin-1b stimulation will increase the expression of antioxidant enzyme Manganese superoxide dismutase (SOD2) as a negative feedback mechanism to protect cell death [[202]63]. In correlation with the report, our results further suggested that the proinflammatory stimulation via NR1H3 may also activate YBX2 anti-ROS pathway and decrease cellular ROS levels. Similar to anti-inflammatory cytokines such as interleukin-35 (IL-35) and IL-10 —which are strongly induced under inflammatory conditions, as we previously reported [[203][64], [204][65], [205][66], [206][67]]—the NR1H3-YBX2 axis may serve as a new negative feedback mechanism to counteract inflammation triggered by hyperlipidemia and CKD. Fig. 9. [207]Fig. 9 [208]Open in a new tab Working model. Uremic toxin receptor NR1H3 contributes to hyperlipidemia- and chronic kidney disease accelerated vascular inflammation, which is partially suppressed by novel YBX2 anti-ROS pathway. Taken together, our study provides new insights into how metabolic reprogramming and ROS contribute to UT receptor signaling, which accelerates vascular inflammation and trained immunity in the setting of hyperlipidemia and CKD. These findings highlight several novel therapeutic targets for future development in the treatments of CKD-promoted cardiovascular and cerebrovascular diseases, as well as inflammation, immune diseases, transplantation complication, aging-related pathologies, and cancer. 3.1. Materials and methods 3.1.1. Hyperlipidemia and 5/6 nephrectomy-induced CKD model Wild-type C57BL/6 mice were purchased from the Jackson Laboratory. The CKD model was established using a two-step 5/6 nephrectomy procedure as previously described [[209]6]. Briefly, at 8 weeks of age, mice underwent surgical exposure of the left kidney followed by ablation of approximately 80–90 % of the renal cortex. At 9 weeks, a right nephrectomy was performed to complete the CKD induction. The mice were sacrificed at 18 weeks of age, and aortic tissues were collected for further analysis. Throughout the study, mice were maintained either on a normal chow diet (5 % fat, Labdiet 5001) or a high-fat diet (HFD) containing 0.2 % (w/w) cholesterol and 20 % (w/w) fat (Test Diet AIN-76A), starting from week 8 until week 18. 3.1.2. Human aortic endothelial cell culture Human aortic endothelial cells (HAECs) (Lonza, CC2535; Walkersville, MD) were cultured in medium M199 (Hyclone Laboratories, Logan, UT) supplemented with 20 % FBS (HyClone), endothelial cell growth supplement (ECGS, 50 μg/ml) (BD Biosciences), heparin (50 μg/ml), and 1 % penicillin, streptomycin, and amphotericin (PSA). HAECs were grown in 0.2 % gelatin-coated flasks, dishes, and plates. Passage 9 of HAECs were used for experimental analysis. 3.2. ROS detection cell-based assay Passage 9 human aortic endothelial cells (HAECs) were seed on 96 well plate for experiment. HAEC were treated 18 h with Phenylacetic acid (Cayman, Ann Arbor, MI. USA 18709), 24(S),25-epoxy Cholesterol (Cayman 10131), 24(S)-hydroxy Cholesterol (Cayman 1000993), 25-hydroxy Cholesterol (Cayman 11097), 27-Hydroxycholesterol (MCE HY-N2371). ROS detection cell-based assay kit (DCFDA) from Cayman Chemical (601520) were used for this experiment. 3.2.1. RNA sequencing (RNA-seq) analysis Total RNA was extracted from whole aortas, and RNA-seq was performed by GENEWIZ. RNA libraries containing Illumina adapter with TruSeq HT indexes were pooled and sequenced on the Illumina Hiseq 2500 platform, generating single-end 75 base pair (bp) reads, with approximately 30 million reads per sample. Raw sequence data (BAM fileswere analyzed by Qlucore Omics Explorer ([210]https://qlucore.com/, New York, NY 10022). 3.3. Public datasets The UT receptor knockout dataset was obtained from the NIH-GEO dataset [211]GSE210192 (RAGE KO), [212]GSE62490 (AHR KO), [213]GSE2436 (CD1D KO), [214]GSE151412 (NR1H3 agonist) and [215]GSE53038 (SET7 KO) and was analyzed by NIH-GEO2R online software. 3.3.1. Ingenuity pathway analysis and metascape analysis Ingenuity pathway analysis (IPA) 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. Gene lists were uploaded to the Metascape website: [216]https://metascape.org/gp/index.html#/main/step1. 3.3.2. Statistical analysis Data were expressed as the mean ± standard error of the mean (SEM) throughout the manuscript. Check the data normality by using GraphPad Prism 10. For non-parametric comparisons in sample size n < 6 between two groups, the Mann Whitney test is used. 3.3.3. Study approval All animal experiments were performed in accordance with the Institutional Animal Care and Use Committee (IACUC) Guidelines and were approved by the IACUC of Temple University School of Medicine with protocol number 5006. CRediT authorship contribution statement Yifan Lu: Validation, Software, Investigation, Formal analysis, Data curation, Conceptualization. Yu Sun: Resources, Methodology, Investigation, Formal analysis. Fatma Saaoud: Writing – review & editing. Keman Xu: Visualization. Ying Shao: Visualization. Baosheng Han: Visualization. Xiaohua Jiang: Visualization. Laisel Martinez: Conceptualization. Roberto I. Vazquez-Padron: Conceptualization. Sadia Mohsin: Conceptualization. Huaqing Zhao: Validation, Software, Methodology. Hong Wang: Conceptualization. Xiaofeng Yang: Supervision. Funding & acknowledgments