2.1. Expression profile of innatomic and secretomic genes, canonical and noncanonical inflammasome pathway regulators, trained immune genes, and lipid peroxidation genes in patients’ nonalcoholic steatohepatitis (NASH) microarray data and microarray/RNA-seq data from various mouse models of nonalcoholic fatty liver disease

The 10 microarray datasets were collected from the National Institutes of Health- (NIH-) National Center for Biotechnology Information- (NCBI-) Gene Expression Omnibus (GEO) database and analyzed with an online software GEO2R (Figures 1(a) and 1(b)). One dataset was from the high-fat diet (HFD) and methionine- and choline-deficient (MCD) diet model (GSE35961). One dataset was from the high-fat-cholesterol diet- (HFCD-) induced diet model. One dataset was from the glycine N-methyltransferase- (GNMT-) KO genetic model, (4) the liver-specific methionine adenosyltransferase 1A- (MAT1A-) KO (GSE63027) genetic model. There were two human NASH microarrays (GSE63067 and GSE17470) [49]. For the mechanism studies, we collected one dataset from caspase-11-KO mice (GSE115094) (Figures 1(a) and 1(b)). One dataset was from caspase-1-KO mice (GSE32515). One human dataset was for trained immunity pathway (GSE24187). For datasets not formatted for GEO2R, analysis was performed using DESeq2 in R Studio as described by Mistry et al. (2015) (Figure 1(c)). In brief, the expression data obtained from NCBI GEO database was converted to an expression set R script element. Differential gene expression was analyzed using the DESeq2 library. The numbers and detailed information of the 7 GEO datasets are listed in Supplementary Tables 2A and 2B.

2.2. Ingenuity Pathway Analysis (IPA)

IPA was used to characterize the clinical relevance and molecular and cellular functions related to the identified genes. Differentially expressed genes were identified and uploaded into IPA for analysis. Core and canonical pathway analysis was used to identify molecular and cellular pathways [14, 15].

2.3. Statistical Analysis

We applied a statistical method similar to a meta-analysis [14, 27]. GEO dataset integrity used 7 housekeeping genes (Supplementary Tables 1 and 2) [44]. The target genes with expression changes more than 1.5-fold were defined as upregulated genes, while genes with their expression decreased more than 1.5-fold were defined as downregulated genes. Fold change calculations were performed in Excel as previously described by our group. Briefly, differential gene expression data were imported into Excel and then analyzed by four Excel Macros: (1) organize the DEG data from the DESeq2 and GEO2R, (2) filter data for significant p values, (3) filter data for fold change ± 1.5, and (4) retrieve expression data for various genes of interest (Figure 1(c)).

3.1. Human NASH and NAFLD Mouse Models Upregulate Both Cytokines and Chemokines Classified in the Innate Immune Database and Canonical Secretome

At least 11 NAFLD mouse models have been established [45, 46] including diet-induced and genetic-induced models [47, 48], but no model accurately reflects the disease’s progression in humans [3]. We include four mouse models that best represent the metabolic and inflammatory characteristics of human NAFLD [3, 46–48].

We hypothesized that diet- and genetically induced NAFLD mouse models can share common pathways critical to the development of the disease. To test this, we collected microarray datasets from NAFLD mouse models and human NASH (Supplementary Table 2a). The datasets we analyzed include (1) the high-fat diet (HFD) and methionine- and choline-deficient (MCD) diet model (GSE35961) [49], (2) the high-fat-cholesterol diet- (HFCD-) induced diet model [50], (3) the glycine N-methyltransferase- (GNMT-) KO genetic model, (4) the liver-specific methionine adenosyltransferase 1A- (MAT1A-) KO (GSE63027) [51] genetic model, and (5) two human NASH microarrays (GSE63067 [51] and GSE17470 [52]). The qualities of the datasets were assessed using a few housekeeping genes (Supplementary Tables 1a and 1b).

Cytokines and chemokines [53–55] play significant roles in promoting the onset and progression of NAFLD [55]; however, their expression changes in human NASH and NAFLD mouse models remained poorly characterized. Cytokines and chemokines in the liver are soluble mediators of local and systemic inflammation (Figure 2(a)) [8, 43, 56, 57]. To analyze liver inflammation, we used IPA and classified 53 cytokines and chemokines from 1376 innate immune genes [58, 59] from the Innate Immunity Database [58, 60]. Human NASH upregulated six (11.3%) and four (7.5%) out of 53 innate immune cytokines and chemokines, respectively (Figure 2(b)). Of note, upregulations of C-X-C motif chemokine ligand 10 (CXCL10) and CKLF-like MARVEL transmembrane domain-containing 2 (CMTM2) were shared in these two human NASH datasets. MCD+HFD and MAT1A-KO upregulated 13 (24.5%) and 6 (11.3%) out of 53 innate immune cytokines and chemokines, respectively (Figure 2(c)). MCD+HFD, MAT1A-KO, GNMT-KO, and HFCD downregulated 9 (17%), 3 (5.7%), 1 (1.9%), and 12 (22.6%) out of 53 innate immune cytokines and chemokines, respectively.

To determine whether NAFLD mouse models share innate immune cytokines and chemokines with human NASH, we performed Venn diagram analysis. Six innate immune cytokines and chemokines including CXCL10, tumor necrosis factor (ligand) superfamily, member 13b (TNFSF13B), lymphotoxin beta (LTB, TNFSF3), TNFSF10, interleukin 1 receptor antagonist (IL-1RN), and nicotinamide phosphoribosyltransferase (NAMPT) were shared between human NASH and NAFLD mouse models (Figure 2(d)). Two NAFLD mouse models upregulated 22 (78.6%) specific innate immune cytokines and chemokines; and human NASH upregulated two (25%) specific cytokines and chemokines C-C motif chemokine ligands 20 (CCL20) and CMTM2.

To ensure a comprehensive analysis of liver inflammation in human NASH and NAFLD mouse models, we collect 2641 canonical secretome genes [61]. The 123 cytokines and chemokines were classified with IPA out of 2641 human canonical secretome genes. Human NASH upregulated 4 (3.3%) and 11 (8.9%) out of 123 canonical secretomic cytokines and chemokines (Figure 2(e)). Of note, upregulations of CXCL10 and thymic stromal lymphopoietin (TSLP) were shared in the two human NASH datasets. MCD+HFD, MAT1A-KO, GNMT-KO, and HFCD models upregulated 21 (17.1%), 7 (5.7%), 0, and 3 (2.4%) (Figure 2(f)) and downregulated 10 (8.1%), 4 (3.3%), 1 (0.8%), and 10 (8.1%) out of 123 canonical secretomic cytokines and chemokines, respectively.

To determine whether NAFLD mouse models share canonical secretomic cytokines and chemokines with human NASH, we performed Venn diagram analysis. Seven canonical secretomic cytokines and chemokines including TSLP, CXCL10, CCL28, CCL25, CXCL14, IL21, and IL1RN were shared between NAFLD mouse models and human NASH (Figure 2(g)). By comparison, three NAFLD mouse models upregulated 32 (82.1%) specific canonical secretomic cytokines and chemokines; and human NASH upregulated 8 (53.3%) specific cytokines and chemokines including erythropoietin (EPO), IL17F, CCL8, IL27, CCL21, CXCL12, CCL15, and CCL20.

Caspase-1-deficient mice are protected from high fat-induced hepatic steatosis, inflammation, and early fibrogenesis [62], suggesting that pyroptosis-related caspase-1/inflammasomes [6] promote NASH progression. However, an important question remains whether noncanonical inflammasome pathway-related caspase-4/11 [63] plays any role in progression of NAFLD.

To determine whether NASH/NAFLD upregulated cytokines and chemokines classified into noncanonical secretomes, we collected four types of secretomes with total 11,385 proteins including canonical secretome (2641 proteins) [61], caspase-1-dependent noncanonical secretome (961 proteins) [23], caspase-4-dependent noncanonical secretome (1223 proteins) [24], and exosome secretome (6560 proteins) [25]. We combined human NASH and NAFLD mouse upregulated cytokines and chemokines and performed Venn diagram analysis. Among 15 human NASH-upregulated cytokines and chemokines, two cytokines CMTM2 and LTB were nonclassified, 12 out of 15 (80%) were classified in the canonical secretome, TNFSF10 was classified in canonical and exosome secretomes, and NAMPT was classified in canonical and caspase-4 secretomes (Figure 2(h)). Of note, since 123 cytokines and chemokines identified with the IPA are derived from the canonical secretome, it was expected that the high percentage (80%) NASH-upregulated cytokines and chemokines were from the canonical secretome. Among 26 NAFLD mouse-upregulated cytokines and chemokines, one was the nonclassified, 15 were classified in the canonical secretome, seven were classified in canonical and exosome secretomes, NAMPT was classified in canonical and caspase-4 secretomes, and two cytokines were classified in canonical, exosomes, and caspase-4 secretomes (Figure 2(i)).

Taken together, our results have demonstrated innate immune secretomic cytokines and chemokines suggesting that human NASH and NAFLD mouse models share innate immune mechanisms and there is a significant role of exosomes and caspase-4 secretomic in driving liver and systemic inflammations.

3.2. Human NASH Can Be Classified into Metabolic and Immune NASH; MCD+HFD, GNMT-KO, MAT1A-KO, and HFCD Can Be Classified into Inflammatory, SAM Accumulation, Cholesterol/Mevalonate, and LXR/RXR-Fatty Acid β-Oxidation NAFLD, Respectively

To determine the signaling pathways mediating the transcriptomic changes in human NASH and NAFLD mouse models, we performed IPA analysis for the top 20 pathways for significantly modulated genes in each dataset. Human NASH dataset GSE17470 had top upregulated pathways including phospholipases, liver X receptor (LXR)/retinoid X receptor (RXR) activation, fatty acid β-oxidation I, and leukocyte extravasation, among which leukocyte extravasation was shared by the second human NASH and MCD+HFD, LXR/RXR activation was shared by HFCD, and fatty acid β-oxidation was shared by GNMT-KO and HFCD (Table 1, Supplementary Figure 1).

The GNMT-KO (GSE63027) had top upregulated pathways including fatty acid β-oxidation I, stearate biosynthesis I, antioxidant action of vitamin C, oxidative phosphorylation, glutaryl-CoA degradation kinase, triacylglycerol biosynthesis, and tricarboxylic acid cycle (TCA) cycle II, among which fatty acid β-oxidation I and stearate biosynthesis I were shared with the first human NASH (GSE17470). The MAT1A-KO (GSE63027) had top upregulated pathways including nicotine degradation II, superpathway of cholesterol biosynthesis, cholesterol biosynthesis I, cholesterol biosynthesis III, mevalonate pathway I, and NAD salvage pathway II, among which nicotine degradation II was shared with the first human NASH.

The HFCD model (GSE53381) has only four upregulated pathways including LXR/RXR activation and fatty acid β-oxidation I, among which LXR/RXR activation was shared with the first human NASH, fatty acid β-oxidation II was shared with the first human NASH and GNMT-KO, and nicotine degradation II was shared with MAT1A-KO.

The second human NASH (GSE63067) had top upregulated pathways including NF-κB signaling and neuroinflammation (Table 1). The MCD+HFD model (GSE35961) had top upregulated pathways including leukocyte extravasation, antibody Fc fragment gamma (Fcγ) receptor-mediated phagocytosis, IL-8 signaling, Rac signaling, and glucose 6-phosphate (G6P) signaling, among which IL-8 signaling was shared with the second human NASH.

Taken together, our results have demonstrated that the two human NASH datasets have diversified signaling pathways, which allow us to classify the first one into LRX/RXR activation-related metabolic NASH and the second NASH into NF-κB signaling [64]/T helper cell 17 (Th17) [56, 65] inflammatory NASH. IPA of upregulated genes in each mouse models of NASH and human NASH identified top pathways for significantly modulated genes. The major differences between metabolic NASH and immune NASH include the following: first, numerous inflammation and immune pathways are identified on the top pathway list, and second, metabolic reprogramming in any given mouse models affects four metabolic pathways including (1) increased glycolysis, (ii) glutaminolysis, (iii) increased accumulation of tricarboxylic acid cycle metabolites and acetyl-coenzyme A production, and (iv) increased mevalonate synthesis. Furthermore, this classification provides a criterion for mouse model stratification and selection, providing novel insight of which mouse models best represent various human cases of NASH/NAFLD.

3.3. Canonical and Noncanonical Inflammasome Pathways Play Differential Roles in the Pathogenesis of NASH/NAFLD

To examine the differential roles of caspase-1- and caspase-11-dependent pyroptosis, we collected 90 canonical and 14 noncanonical inflammasome pathway regulator genes and determined the expression changes of these inflammasome regulators in four NAFLD mouse models.

MCD+HFD upregulated 18 (20%) including caspase-1 and downregulated 11 (12.2%) out of 90 canonical inflammasome pathway regulators. MAT1A-KO upregulated 5 (5.6%) and downregulated 4 (4.4%) out of 90 canonical inflammasome pathway regulators. GNMT-KO upregulated 1 (1.1%) and downregulated 2 (2.2%) out of 90 canonical inflammasome pathway regulators. HFCD upregulated 7 (7.8%) and downregulated 26 (28.9%) out of 90 canonical inflammasome pathway regulators (Figure 3(b)). In addition, MCD+HFD downregulated 6 out of 14 (42.8%) noncanonical inflammasome pathway regulators. MAT1A-KO upregulated 3 (21.4%) and downregulated 3 (21.4%) out of 14 noncanonical inflammasome pathway regulators. GNMT-KO downregulated 1 out of 14 (7.1%) noncanonical inflammasome pathway regulators. HFCD upregulated 1 (7.1%) and downregulated 9 (64.3%) out of 14 noncanonical inflammasome pathway regulators (Figure 3(c)).

Taken together, these results have demonstrated that the MCD+HFD upregulates more canonical inflammasome regulators than the other three NAFLD models. Conversely, the MAT1A-KO upregulates more noncanonical inflammasome regulators including caspase-4 than other models, suggesting that canonical and noncanonical inflammasome pathways are regulated differentially in various NAFLD models. The HFCD downregulates more than upregulates canonical and noncanonical inflammasome regulators, suggesting that HFCD model uses more focused set of regulators in modulating the expression of these regulators.

3.4. Trained Immunity (TI) Enzymes Are Significantly Upregulated in Human NASH and NAFLD Mouse Models; the HFD Upregulates TI Enzymes More Than Cytokines, Chemokines, and Canonical and Noncanonical Inflammasome Regulators; and Statins Promote rather than Suppress TI Enzyme Expressions

We hypothesized that the expressions of TI enzymes are modulated in NASH and NAFLD to establish metabolic reprogramming and achieve innate immune memory [66]. Three metabolic pathways play significant roles in establishing TI (Figure 4). To examine this, we collected 71 glycolysis enzyme genes, 24 acetyl-CoA generation enzyme genes, and 10 mevalonate genes [27, 29, 30, 67, 68].

The first human NASH upregulated 25 (35.2%) and downregulated 5 (7%) out of 71 glycolysis enzymes genes (Table 2(a)). The second human NASH upregulated 5 out of 71 (7%) genes. The MCD+HFD upregulated 20 (28.2%) and downregulated 24 (33.8%) out of 71 genes. The MAT1A-KO upregulated 6 (8.5%) and downregulated 13 (18.3%) out of 71 genes. The GNMT-KO model upregulated 7 (9.9%) and downregulated 4 (5.6%) out of 71 genes. The HFCD upregulated 17 (23.9%) and downregulated 8 (11.3%) out of 71 genes.

Furthermore, the first human NASH upregulated 4 out of 24 (16.6%) acetyl-CoA generation enzyme genes. The second human NASH upregulated 1 out of 24 (4.2%) genes. The MCD+HFD upregulated 3 (12.5%) and downregulated 7 (29.2%) out of 24 genes. The MAT1A-KO upregulated 1 (4.2%) and downregulated 4 (16.7%) out of 24 genes. The HFCD upregulated 7 (29.2%) and downregulated 2 (8.3%) out of 24 genes (Table 2(b)).

In addition, the first human NASH upregulated 2 (20%) and downregulated 3 (30%) out of 10 mevalonate pathway enzyme genes. The second human NASH upregulated 1 out of 10 (10%) gene. The MCD+HFD upregulated 7 (70%) and downregulated 1 (10%) out of 10 genes. The MAT1A-KO upregulated 4 (40%) and downregulated 1 (10%) out of 10 genes. The GNMT-KO upregulated 3 out of 10 (30%) genes. The HFCD upregulated 7 out of 10 (70%) genes (Table 2(c)).

Statins (β-hydroxy β-methylglutaryl-CoA (HMG-CoA) reductase inhibitors) block cholesterol synthesis and mevalonate generation, preventing TI induction [69]; and statin treatments do not revert the TI phenotype in patients with familiar hypercholesterolemia [70]. We hypothesized that statins may modulate TI enzyme expression in NAFLD models. For this, we collected two microarray datasets of statin-treated human primary hepatocytes [71].

Among the 2004 differentially expressed genes, 16 genes were overlapped with 99 TI enzyme genes (16.2%) [27], of which 15 (15.2%) genes were upregulated and one (1%) gene was downregulated by atorvastatin (Figures 5(a)–5(c)). In addition, among 2448 differentially expressed genes in rosuvastatin-treated human primary hepatocytes, 19 genes were overlapped with 99 TI enzyme genes (19.2%), of which 15 (15.2%) genes were upregulated and 4 (4%) genes were downregulated by rosuvastatin. Then, we used Venn diagram to determine the causative effects of statins in TI enzyme genes upregulated in NAFLD models. The results showed that the atorvastatin treatment overlapped with 13 TI enzyme genes upregulated in human and mouse NASH/NAFLD models. Similarly, rosuvastatin treatment overlapped with 15 TI enzyme genes upregulated in human and mouse NAFLD models. These results have demonstrated that TI inhibitors, statins, promote the expression of TI enzyme genes not only in mevalonate pathways but also in glycolysis pathways and acetyl-CoA generation pathway.

3.5. Expression Analysis of Lipid Peroxidation Enzymes Indicates That There Are Two Representative NASH/NAFLD Models: The MCD+HFD Model Is Proinflammatory Cytokine- and Canonical and Noncanonical Inflammasome-Upregulated Model; in Contrast, the HFCD Model Is Lipid Peroxidation Enzyme- and TI Enzyme-Upregulated Model

Arachidonic acid (AA) undergoes oxidative metabolism under enzymatic or nonenzymatic mechanisms. Cyclooxygenase (COX), lipoxygenase (LOX), and cytochrome p450s (CYPs) mediated enzymatic peroxidation of AA to the respective metabolites. The 12-lipoxygenase (12-LO) and 15-lipoxygenase (15-LO) mediated conversion of AA to 12- and 15-hydroperoxyeicosatetraenoic acid (HpETE) and the downstream glutathione peroxidase- (GPx-) mediated conversion to the respective hydroxyeicosatetraenoic acids (12- and 15-HETE). ROS-induced lipid peroxidation (LPO) of 12- and 15-HpETE results in the generation of 4-hydroxynonenal (4-HNE) and 4-hydroxydodecadeinal (4-HDDE). These reactive aldehydes interact with and inactivate GPx, leading to an increased rate of 12-HpETE and 15-HpETE peroxidation [72]. The nonenzymatic peroxidation mediates conversion of AA to 4-HNE and MDA metabolites [73] (Figure 6).

We hypothesized that downregulation of lipid peroxidation antioxidant enzymes CYPs and GPXs is inversely associated with upregulation of cytokines and chemokines in NAFLD and that upregulation of proinflammatory lipid peroxidation enzymes COXs and LOXs [74] is associated with upregulations of TI enzymes in NAFLD. To examine these hypotheses, we collected 26 COX lipid peroxidation enzymes, 44 cytochrome P450 CYP lipid peroxidation antioxidant (anti-inflammatory) enzymes [75, 76], 26 AA metabolism enzymes, and 8 hepatic glutathione peroxidase antioxidant (anti-inflammatory) enzymes [77].

The MCD+HFD upregulated 2 (7.7%) and downregulated 9 (34.6%) COXs (Table 3(a)). The MAT1A-KO upregulated 2 (7.7%) and downregulated 1 (3.8%) out of 26 COXs. The GNMT-KO upregulated 3 (11.5%) COXs. The HFCD upregulated 9 (34.6%) and downregulated 1 (3.8%) COXs.

The MCD+HFD upregulated 6 (13.6%) and downregulated 13 (29.5%) CYP lipid peroxidation antioxidant enzymes (CYP-LPAEs) (Table 3(c)). The MAT1A-KO upregulated 4 (9.1%) and downregulated 8 (18.2%) CYP-LPAEs. The GNMT-KO upregulated 5 (11.4%) and downregulated 8 (18.2%) CYP-LPAEs. The HFCD upregulated 22 (50%) and downregulated 1 (2.3%) CYP-LPAEs (Figure 6(c)).

The MCD+HFD upregulated 4 (15.4%) and downregulated 11 (42.3%) AA metabolism enzyme genes (Table 3(d)). The MAT1A-KO upregulated 4 (15.4%) and downregulated 6 (23.1%) genes. The GNMT-KO upregulated 4 (15.4%) and downregulated 7 (26.9%) genes. The HFCD upregulated 24 (92.3%) genes (Figure 6(d)).

The MCD+HFD upregulated 4 out of 8 (50%) GPXs (Table 3(b)). The MAT1A-KO upregulated 2 (25%) GPXs. The GNMT-KO upregulated 1 out of 8 (12.5%) GPXs. The HFCD downregulated 1 out of 8 (12.5%) GPXs (Figure 6(e)).

Taken together, our results have demonstrated that, first, proinflammatory MCD+HFD upregulates 7.7% COXs, 13.6% CYP-LPAEs, 15.4% AA metabolism enzymes, and 50% GPXs and downregulates 34.6% COXs, 29.5% CYP-LPAEs, and 42.3% AA metabolism enzymes, which are in big contrast with that of less inflammatory HFCD with upregulations of 34.6% COXs, 50% CYP-LPAEs, and 92.3% AA metabolism enzymes and downregulation of 3.8% COXs, 2.3% CYP-LPAEs, and 12.5% GPXs; second, significant upregulation of lipid peroxidation enzymes in HFCD is positively correlated with significant upregulation of TI enzymes and is, however, inversely associated with low-level upregulation of canonical inflammasome regulators (6.7%), noncanonical inflammasome regulators (7.1%), and 2.4% secretomic cytokines; third, no upregulation of GPXs in HFCD (Table 3(b)) is well correlated with other’s findings that GPX4 decreases lipid peroxidation and inflammation, and caspase-11-dependent pyroptosis mediates atherosclerosis [78], endotoxic shock [79], and septic death in GPX4-KO mice [33]; and fourth, the MCD+HFD and HFCD are the two representative models: the MCD+HFD is a model of NASH/NAFLD with upregulation of proinflammatory cytokines and canonical and noncanonical inflammasome regulators. In contrast, the HFCD is a model with upregulation of lipid peroxidation enzymes and TI enzymes.

3.6. As Upstream Master Regulators, Caspase-11 and Caspase-1 Partially Upregulate the Expressions of Cytokines, Chemokines, Canonical and Noncanonical Inflammasome Pathway Regulators, TI Enzymes, and Lipid Peroxidation Enzymes

It has been reported that caspase-11 mediates hepatocyte pyroptosis and promotes the progression of MCD diet-induced NASH/NAFLD [80]; and inflammasome-gasdermin D-pyroptosis [81] may regulate the progression of NASH/NAFLD [82]. In addition to promoting inflammation by enzymatic cleavage of pre-IL-1β, pre-IL-18, and N-terminal GSDMD, caspase-1 also cleaves as many as 114 substrates, suggesting that caspase-1 may regulate inflammation indirectly via all the protein substrate-mediated signaling [15], 38 interaction protein-mediated signaling [15], and GSDMD-secretome-mediated signaling [23]. However, an important question remains whether caspase-11 modulates the expression of cytokines, chemokines, and TI enzymes. We hypothesized that caspase-11 promotes inflammatory cytokines and chemokines upregulated in NASH/NAFLD and modulates the expression of canonical and noncanonical inflammasome pathway genes and TI enzymes. To examine this hypothesis, we collected all the cytokines and chemokines, canonical and noncanonical inflammasome pathway genes, and TI enzymes upregulated in NASH/NAFLD and crossed with caspase-11-KO and caspase-1-KO datasets (Supplementary Table 2b).

Among 39 innatomic and secretomic cytokines and chemokines upregulated in NASH/NAFLD, caspase-11 deficiency upregulated 18 (46.2%) and downregulated 8 (20.5%) NASH/NAFLD-upregulated cytokines and chemokines. In comparison, caspase-1 deficiency upregulated one cytokine CXCL14 (2.6%) and downregulated one cytokine LTB (2.6%) NASH/NAFLD-upregulated cytokines and chemokines (Table 4(a)). These results suggest that capsase-11 deficiency promotes the upregulation of most cytokines and chemokines induced by NASH/NAFLD. In addition, caspase-11 deficiency upregulated 5 (17.9%) and downregulated 5 (17.9%) canonical inflammasome regulators induced by NASH/NAFLD. However, caspase-1 deficiency did not modulate the expression of canonical inflammasome regulators induced by NASH/NAFLD (Table 4(b)). Furthermore, caspase-11 deficiency upregulated 6 (8.8%) and downregulated 31 (45.6%) TI enzymes upregulated in NASH/NAFLD. In comparison, caspase-1 deficiency upregulated 4 (5.9%) and downregulated 6 (8.8%) TI enzymes upregulated in NASH/NAFLD (Table 4(c)). Finally, caspase-11 deficiency upregulated 13 (28.3%) and downregulated 6 (13%) lipid peroxidation enzymes upregulated in NASH/NAFLD. In comparison, caspase-1 deficiency upregulated 3 (6.5%) and downregulated 6 (13%) lipid peroxidation enzymes upregulated in NASH/NAFLD (Table 4(d)).

Taken together, our results have demonstrated that, first, caspase-11 and caspase-1 partially modulate the expressions of cytokines, chemokines, canonical and noncanonical inflammasome pathway regulators, TI enzymes, and lipid peroxidation enzymes; second, in the context of NASH/NAFLD, caspase-11 has stronger capacities than caspase-1 in modulating inflammatory gene expressions; and third, experimental conditions in caspase-11 deficiency [79] and caspase-1 deficiency [83] were not exactly the same as NASH/NAFLD. Since we used inflammatory gene lists upregulated in the four NASH/NAFLD models for the analyses, our results are at least partially relevant to NASH/NAFLD pathology. Future work on transcriptomic analysis of caspase-11 deficiency and caspase-1 deficiency in NASH/NAFLD models, respectively, is needed to verify these findings presented here.