Helicobacter pylori infection exacerbates nonalcoholic fatty liver disease through lipid metabolic pathways: a transcriptomic study.

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Xingcen Chen, Ruyi Peng, Dongzi Peng, Deliang Liu, Rong Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4196201/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Jul, 2024 Read the published version in Journal of Translational Medicine → Version 1 posted 4 You are reading this latest preprint version Abstract Background The relationship between Helicobacter pylori ( H. pylori ) infection and nonalcoholic fatty liver disease (NAFLD) have attracted increased clinical attention. However, most of those current studies involve cross-sectional studies and meta-analyses, and experimental mechanistic exploration still needs to be improved. This study aimed to investigate the mechanisms by which H. pylori impacts NAFLD. Methods We established two H. pylori -infected (Cag A positive and Cag A negative) mouse models with 16 weeks of chow diet (CD) or high-fat diet (HFD) feeding. Body weight, liver triglyceride, blood glucose, serum biochemical parameters, inflammatory factors, and insulin resistance were measured, and histological analysis of liver tissues was performed. Mouse livers were subjected to transcriptome RNA sequencing analysis. Results Although H. pylori infection could not significantly affect serum inflammatory factor levels and mouse liver pathology, serum insulin and homeostatic model assessment for insulin resistance levels increased in CD mode. In contrast, H. pylori infection significantly aggravated hepatic pathological steatosis induced by HFD and elevated serum inflammatory factors and lipid metabolism parameters. Hepatic transcriptomic analysis revealed 767 differentially expressed genes (DEGs) in the H. pylori -infected group in the CD groups, and the "nonalcoholic fatty liver disease" pathway was significantly enriched in KEGG analysis. There were 578 DEGs in H. pylori infection combined with the HFD feeding group, and DEGs were significantly enriched in "fatty acid degradation" and "PPAR pathway." Exploring the effect of different Cag A statuses on mouse liver revealed that fatty acid binding protein 5 was differentially expressed in Cag A- H. Pylori and DEGs enrichment pathways were concentrated in the "PPAR pathway" and "fatty acid degradation." Conclusions H. pylori infection may exacerbate the development of NAFLD by regulating hepatic lipid metabolism, and the H. pylori virulence factor Cag A plays a vital role in this regulation. Helicobacter pylori nonalcoholic fatty liver disease transcriptome sequencing FABP5 PPAR signaling pathway Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. INTRODUCTION Helicobacter pylori ( H. pylori ) infects approximately 4.4 billion people worldwide, with a prevalence of 43.1% (40.3–45.9) [ 1 , 2 ]. A family-based epidemiological survey revealed that the prevalence of H. pylori infection in China was approximately 40.66%, 43.45% in adults, and 20.55% in children and adolescents [ 3 ]. Multitudinous studies have confirmed that H. pylori infection is an essential factor in the progression from gastritis to gastric cancer [ 4 , 5 ]. Cytotoxin-associated gene A (Cag A) is considered the most vital virulence factor of H. pylori , and several studies have shown that Cag A is directly associated with DNA damage in gastric epithelial cells and gastric mucosal carcinogenesis [ 6 , 7 ]. In addition to gastritis, gastric ulcers, and gastric cancer, many extragastric diseases, such as atherosclerosis, Parkinson's disease, and nonalcoholic fatty liver disease (NAFLD), are also closely associated with H. pylori infection [ 8 ]. NAFLD is defined as a clinicopathologic syndrome characterized by excessive fat deposition in hepatocytes, excluding alcohol and other definite liver-damaging factors. The disease spectrum includes simple hepatocellular steatosis, nonalcoholic steatohepatitis (NASH), NASH-related liver fibrosis, and hepatocellular carcinoma (HCC). The pathogenesis of NAFLD remains unknown, and the multiple-hit theory reviewed by Buzzetti et al. is widely acknowledged in academia [ 9 ]. NAFLD has become the most common chronic liver disease worldwide, with a global prevalence of approximately 32.4% (29.9–34.9) [ 10 , 11 ]. Although NAFLD is an urgent public health problem, no country is fully prepared to address it [ 12 ]. No effective agents have been approved for NAFLD treatment, and the primary clinical management regimen for NAFLD is to identify patients with a high risk of disease progression and lose weight through dietary modification and physical exercise [ 10 ]. It is pressing to recognize and manage NAFLD correctly. Inspiringly, with the specification of the NAFLD definition, the nomenclature for new fatty liver diseases: metabolic dysfunction-associated steatotic liver disease (MASLD) will provide more accurate and high-quality studies for NAFLD/MASLD [ 13 ]. Since the first report of H. pylori DNA detected in the livers of NAFLD patients [ 14 ], several clinical studies have focused on the relationship between H. pylori infection and NAFLD. Many scholars discuss the relationship between the two and believe that H. pylori infection may be used as a combustion aid in the multiple-hit theory of NAFLD, exacerbating the progression of NAFLD through the aspects of inflammatory factors, adipokines, the intestinal barrier, and the intestinal flora [ 15 , 16 ]. Yu et al. substantiated that eradication of H. pylori in H. pylori -positive NAFLD patients ameliorated fasting blood glucose (FBG), serum triglycerides (TGs), insulin resistance (IR), and body mass index (BMI) [ 17 ]. The study by Abdel-Razik et al. reached similar conclusions [ 18 ]. However, other studies have found no association between H. pylori infection and NAFLD. A Mendelian randomization study by Liu et al. revealed no causal link between H. pylori infection and NAFLD and no significant association between H. pylori infection and TGs, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), or FBG levels [ 19 ]. Interestingly, a cross-sectional study by Kang et al. indicated that Cag A status may be critical to influencing the relationship between the two, and there was no association between the Cag A positive H. pylori group and NAFLD (OR: 1.05; 95% CI: 0.81–1.37), and in multivariate analysis, the Cag A negative (Cag A-) H. pylori group was significantly associated with NAFLD (OR: 1.30; 95% CI: 1.01–1.67) [ 20 ]. Therefore, this study aimed to explore the effect of H. pylori infection with different Cag A status on the liver under different dietary patterns and to explore the relationship between H. pylori infection and NAFLD. 2. METHODS 2.1 H. pylori culture The rodent-adapted H. pylori Sydney strain (SS1) (Cag A+) was donated by Professor Yong Xie (Department of Gastroenterology, First Affiliated Hospital of Nanchang University, Jiangxi, China). H. pylori Cag A- was isolated from gastric ulcer patients’ specimens via gastroscopy. The H. pylori strains grown on Columbia blood agar plates supplemented with antibiotics (10 mg/L vancomycin, 5 mg/L cefsulodin, 5 mg/L amphotericin B, and 5 mg/L trimethoprim) and 10% sheep blood (Bianzhen Biotech, Nanjing, China) at 37°C under microaerophilic conditions (5% O 2 , 10% CO 2 , and 85% N 2 ) for 3–4 days. Then, the H. pylori strain, which was in the early log phase with good motility and activity for subculture or intervention, was harvested and resuspended in phosphate buffer saline (PBS). The H. pylori concentration was estimated by measuring the OD 600 nm , where OD 600 nm corresponds to approximately 2 × 10 8 colony-forming units (CFU)/ml. 2.2 Animals and treatment All animal studies were performed according to the National Institutes of Health recommendations for the Care and Use of Laboratory Animals and were approved by the Central South University Animal Ethics Committee. Male C57BL/6J mice (specific pathogen-free grade) aged 6–8 weeks were purchased from Hunan SJA Laboratory Animal Co., Ltd and housed in animal quarters at 20–22 ° C with a 12-h light cycle and fed ad libitum. After one week of adaptive feeding, 48 mice were randomly divided into six groups (PBS, SS1, Cag A-, PBS + HFD, SS1 + HFD, and Cag A-+HFD) of 8 mice each. Four groups were intragastrically infused seven times with 1 × 10 9 CFU of H. pylori SS1 or H. pylori Cag A- at 1-day intervals and fed either a regular chow diet (CD) or a high-fat diet (HFD) (Research Diets, D09100310). Caloric composition of CD versus HFD was shown in Table 1 . At the same time, the other two groups received PBS by gavage and were fed the corresponding diet for 16 weeks. The animal experiments were conducted in two parts. The first part focused on examining the impact of H. pylori (SS1) infection on mice's physiological metabolism and liver transcriptomics under different dietary patterns ( Results Section 3.1 –3.3). The second part investigated the effects of H. pylori infection, with different Cag A status, on the liver transcriptomics of mice under different dietary patterns ( Results Section 3.4– 3.5 ). Mice were fasted overnight prior to sacrifice. Six animals per group were used for testing and statistical analysis. Table 1 Caloric composition table of mouse diet Dietary component Protein Carbohydrate Fat Calories Chow diet 22.9% 66.0% 11.1% 3.37 Kcal/gm High fat diet 20.0% 40.0% 40.0% 4.49 Kcal/gm 2.3 Biochemical analysis Serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), total cholesterol (TC), HDL-C, and LDL-C were assayed by an automatic biochemical analyzer (Rayto Life and Analytical Sciences, Chemray 240) with corresponding commercial kits. Enzyme-linked immunosorbent assay (ELISA) kits (Jiangsu Meimian Industrial, MM-0040M1, MM-0163M1, MM-0132M1, and MM-0579M1) were used to detect Interleukin 1β (IL-1β), Interleukin 6 (IL-6), Tumor necrosis factor α (TNF-α) and insulin levels in mouse serum. Hepatic TGs were measured by a commercial kit (Nanjing Jiancheng Bioengineering Institute, A110-1-1) according to the manufacturer's instructions. 2.4 Histopathologic examination Fresh mouse liver tissues were fixed in 4% paraformaldehyde and embedded in paraffin. Embedded tissues were cut at 4 µm thickness and then stained with a hematoxylin-eosin (H&E) kit (Powerful Biology, Wuhan, China) for histological assessment according to the rodent model NAFLD scoring system proposed by Liang et al. [ 21 ]. Frozen samples were cut into 8-µm sections and stained with an Oil Red O staining kit (Powerful Biology, Wuhan, China) according to the manufacturer’s instructions. Masson staining was used to observe fibrosis in the liver of mice. After staining with iron hematoxylin, Ponceau, and aniline blue, collagen fibers were blue, and muscle fibers, cytoplasm, and cellulose were red. Immunohistochemical (IHC) staining was performed using the following methods: Paraffin slices, 4 µm thick, were grilled at 65°C for 60 minutes, then dewaxed in xylene and rehydrated in a series of increasingly diluted ethanol. High-temperature antigen retrieval was achieved by microwave treatment in 0.1 M citrate solution (pH 6.0) for 10 minutes. The slices were treated with 3% H 2 O 2 at room temperature for 20 minutes, followed by incubation with goat serum for 20 minutes, and subsequently with anti-FABP5 rabbit polyclonal antibody (Proteintech, Wuhan;1:100) overnight at 4°C. The following day, the slices were brought to room temperature and incubated with the secondary anti-rabbit antibody for 20 minutes after washing with PBS. DAB coloration was applied, followed by mounting with hematoxylin and subsequent microscopic examination. All the samples were examined under a light microscope at 200× magnification. 2.5 Intraperitoneal glucose tolerance test (IPGTT) and intraperitoneal insulin tolerance test (IPITT) In the 15th week of intervention, the mice were pre-stimulated for approximately one week. Sixteen hours of fasting and water deprivation preceded the IPGTT procedure, and the mice were injected intraperitoneally with glucose solution (2 g/kg body weight). Blood samples were collected by tail puncture at 0, 30, 60, 90, and 120 min to measure blood glucose levels using a glucometer. The area under the curve (AUC) was calculated for the IPGTT. IPITT was performed at three-day intervals. Mice were fasted for six hours and injected with insulin (0.75 IU/kg body weight) (Jiangsu Wanbang Biochemistry Medicine Co. Ltd., Xuzhou, China). Blood glucose levels were measured at 0, 15, 30, 60, and 90 min after insulin injection. The AUC of the IPITT was calculated. 2.6 RNA‑sequencing Total RNA preparation and subsequent RNA-seq library construction were performed using the APExBIO Technology LLC (Shanghai, China) service. Briefly, total RNA was isolated using a commercial kit (Tiangen Biotech, DP424), and RNA libraries were established using an RNA cleaning and concentration kit (APExBIO Technology LLC, K1159) after quality inspection and purity testing. The RNA quality was verified using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA). The qualified libraries were subjected to Illumina NovaSeq 6000 double-end sequencing according to the effective concentration and target data volume to obtain paired sequences with a read length of 150 bp. The filtered reads were mapped to the mouse genome reference sequence (GRCm39.dna.toplevel.fa Ensembl release103) using HISAT2. The gene expression levels are expressed as fragments per kilobase per million fragments (FPKM). Genes were considered differentially expressed when |fold change| >1.5 and P value < 0.05. Differential expression analysis was performed using DESeq2. KEGG and GO enrichment analyses of differentially expressed genes were performed using the R package ClusterProfiler (v4.2.2), and significant pathways were identified with a P value < 0.05. 2.7 Quantitative real-time PCR (qRT-PCR) Total RNA was extracted from the livers with AG RNAex Pro Reagent (Accurate Biotechnology, AG21101), an Evo M-MLV RT Mix Kit with gDNA Clean for qPCR Ver.2 (Accurate Biotechnology, AG11728) reverse-transcribed the extracted total RNA into cDNA. qRT-PCR was performed using the SYBR Green Premix Pro Taq HS qPCR Kit IV (Accurate Biotechnology, AG11746) and the targeting gene primers. All the gene primer sequences are shown in Table 2 . PCR was performed in triplicate on the qRT-PCR detection system with the following cycling parameters: 95°C (30 s), 40 cycles of 95°C (5 s), 55°C (30 s), and 72°C (30 s). The qRT-PCR data were quantified by the 2 −ΔΔCt method. Table 2 Sequences of primers used for qRT-PCR Gene Forward primer Reverse primer Gapdh AGGTCGGTGTGAACGGATTTG GGGGTCGTTGATGGCAACA Fabp5 AGAGCACAGTGAAGACGAC CATGACACACTCCACGATCA Ppar-γ TCGCTGATGCACTGCCTATG GAGAGGTCCACAGAGCTGATT Fgf21 CTGCTGGGGGTCTACCAAG CTGCGCCTACCACTGTTCC Srebf-1 GATGTGCGAACTGGACACAG CATAGGGGGCGTCAAACAG Il-1β GAAATGCCACCTTTTGACAGTG TGGATGCTCTCATCAGGACAG Tnf-α CCTGTAGCCCACGTCGTAG GGGAGTAGACAAGGTACAACCC 2.8 Statistical analysis The data are expressed as the mean ± standard deviation (SD) and analyzed by unpaired student’s t-test and one-way analysis of variance (ANOVA) with GraphPad Prism 9.0 software. At least three independent biological replicates were performed for each group. p < 0.05 was considered statistically significant. 3. RESULTS 3.1 H. pylori infection exacerbates hepatic lipid deposition and insulin resistance in mice Mice infected with H. pylori had a slightly lower body weight curve than non-infected mice under CD conditions. Although there was no statistical difference between the two groups, infected mice showed an increasing trend in liver weight and liver weight ratio compared with non-infected mice. TG content in the liver of H. pylori -infected mice was significantly higher than that of non-infected mice (Supplementary Fig. 1A-D). Histopathological observations of the liver are shown in Fig. 1 A, and the semiquantitative score of NAFLD also tended to be higher in mice infected with H. pylori (Fig. 1 B). In the HFD setting, the trend of physiological parameters in H. pylori -infected mice was similar to that in the CD groups. The weight curve of H. pylori -infected mice was slightly lower than that of non-infected mice, and the liver weight and liver weight ratio of infected mice tended to increase (Supplementary Fig. 1E-H). Notably, liver pathological changes were more prominent in mice on an HFD, and H. pylori -infected mouse livers had more pronounced hepatocyte damage, such as hepatocyte macrovesicular steatosis and hepatocyte swelling (Fig. 1 C). Thus, there were significant differences between H. pylori -infected mice and non-infected mice in hepatic TG content and NAFLD score (Fig. 1 D). IPGTT and IPITT tested glucose homeostasis and insulin sensitivity. Interestingly, H. pylori infection affects mice glucose regulation ability and insulin resistance in the CD groups. In the CD groups, the AUC of IPGTT, IPITT, was significantly higher in H. pylori -infected mice than in the non-infected group. Serum insulin levels and IR levels were also higher in the infected group than in the non-infected group (Supplementary Fig. 2). In the HFD feeding, glucose and insulin regulation were weaker, and serum insulin levels were higher in H. pylori -infected mice than in non-infected mice. However, IR scores were not significantly different between the two groups (Supplementary Fig. 2). 3.2 H. pylori infection combined with HFD feeding had the most significant effect on serum metabolism and inflammation in mice Serum LDL-C in H. pylori -infected mice in the CD groups was statistically different from that in the non-infected mice. However, HDL-C, TC, and serum liver enzymes (ALT, AST) showed no significant difference. Serum inflammatory cytokines IL-1β, IL-6, and TNF-α were slightly increased in H. pylori -infected mice (Fig. 2 ). In contrast, H. pylori infection combined with HFD feeding had a more pronounced effect on serum biochemical parameters in mice. Although there was no statistical difference in serum liver enzymes between the two groups, serum TC, LDL-C, and serum inflammatory cytokines IL-6 and TNF-α were significantly higher in the H. pylori -infected group than those in the non-infected group (Fig. 2 ). 3.3 RNA-seq reflects different gene expression profiles in the liver of H. pylori -infected mice fed with different dietary patterns Differential expression genes (DEGs) were identified as | fold changes | > 1.5, with a P value < 0.05. Through the analysis of the RNA transcriptome sequencing results of the liver of mice in the CD groups, 767 DEGs were present in the liver of mice in the H. pylori -infected group (Fig. 3 A), including 396 down-regulated genes and 371 up-regulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses to identify the biological processes associated with the DEGs. Visualization of the DEGs enriched functional results showed that the "fatty acid metabolic process" was significantly expressed (Fig. 3 B). The enrichment results significantly expressed the "Nonalcoholic fatty liver disease" pathway in the KEGG enrichment analysis (Fig. 3 C). In GO enrichment analysis, the top 3 significantly enriched in the biological process were "cellular process," "metabolic process," and "biological regulation (Fig. 3 D)." Analysis of the RNA transcriptome sequencing results of the liver of mice in the HFD groups showed that there were a total of 578 DEGs in the liver of mice infected with H. pylori (Fig. 4 A), including 245 down-regulated genes and 333 up-regulated genes. Visualization of the DEGs enriched functional results showed that "long-chain fatty acid metabolic process" and "regulation of lipid metabolic process " were significantly expressed (Fig. 4 B). In KEGG enrichment analysis, the "PPAR signaling pathway," "Fatty acid degradation," and "Retinol metabolism" pathways were significantly expressed in the enrichment results (Fig. 4 C). The GO enrichment analysis results were similar to those of the CD groups, and the top three biological processes were "cellular process," "metabolic process," and "biological regulation (Fig. 4 D)." 3.4 Differential gene expression profiles in livers of H. pylori -infected mice with different Cag A status on a uniform diet In the CD pattern, there were 1511 DEGs in Cag A- H. pylori infection compared with Cag A + H. pylori infection (Fig. 5 A), of which 780 were up-regulated, and 731 were down-regulated. Fatty acid binding protein 5 (Fabp5), a critical intracellular transporter of fatty acid and a key regulator of the PPAR pathway, was significantly up-regulated in the Cag A- group. The visualized DEG enrichment function results showed that the "fatty acid metabolic process" and "fat catabolic process" were significantly expressed (Fig. 5 B). The "PPAR signaling pathway" and "Fatty acid degradation" pathways were enriched in KEGG enrichment analysis. GO enrichment analysis results are shown in Fig. 5 D. In HFD feeding, there were 1400 DEGs in Cag A- H. pylori infection compared with Cag A + H. pylori infection (Fig. 6 A), of which 762 were up-regulated and 638 were down-regulated. Fabp5 was stably and highly expressed in this group. The visualized DEGs enrichment function results showed that "fatty acid oxidation" and "long-chain fatty acids" were significantly expressed (Fig. 6 B). The KEGG enrichment analysis enriched the "PPAR signaling pathway" and "Fatty acid degradation" pathways. GO enrichment analysis results are shown in Fig. 6 D. 3.5 qRT-PCR and IHC verified the expression level of differentially expressed genes in mouse liver Subsequently, qRT-PCR results showed that H. pylori infection significantly increased the expression levels of sterol regulatory element binding transcription factor 1 (Srebf1), fibroblast growth factor 21(Fgf21), the critical factors of lipid metabolism, Il-1β, and Tnf-α in the liver (Fig. 7 A-D). We performed qRT-PCR to validate the transcriptome sequencing DEGs, and the validation results are shown in Fig. 7 E, F. Meanwhile, For the most significantly differentially expressed Fabp5, we performed IHC staining of the mouse liver. Fabp5 expression levels were lower in Cag A + H. pylori -infected mouse livers. In contrast, cells with strong positive Fabp5 expression displayed in Cag A- H. pylori -infected mouse livers, mainly distributed in interstitial tissues. The results were shown in Fig. 7 G. 4. DISCUSSION We established mouse models of H. pylori infection under different dietary patterns to investigate the association between H. pylori infection and NAFLD. In the CD groups, TG content in liver tissue, serum insulin, and HOMA-IR scores demonstrated that H. pylori infection could cause hepatic TG deposition and insulin resistance in mice. However, serum biochemical parameters, liver enzymes, and liver pathology indicated that H. pylori infection does not significantly affect mice's physiological metabolism. We suspected the possible reasons may be: (1) H. pylori infection duration is not long enough, the systemic chronic inflammatory response is not apparent, and (2) H. pylori infection alone is insufficient to produce significant changes in liver pathology. Analysis of the liver transcriptome sequencing results showed that H. pylori infection induced 767 DEGs in mouse liver tissues, of which 371 genes were up-regulated, and 396 genes were down-regulated. Enrichment analysis showed that some DEGs were significantly involved in the "fatty acid metabolism" and "non-alcoholic fatty liver disease" pathway. These transcriptome results illustrate the link between H. pylori infection and NAFLD. Based on HFD feeding, H. pylori infection had a more evident effect on the physiological metabolism of mice. Although there was no statistical difference in body weight and liver weight between the two groups, liver TG content, serum TC, LDL-C, and serum inflammatory cytokines IL-6 and TNF-α were significantly higher in the H. pylori -infected group than in the non-infected group. H. pylori infection combined with HFD feeding resulted in more significant hepatic lipid deposition and hepatocyte macrovesicular steatosis in mice, and there were significant differences in NAFLD scores in mice, which coincided with the findings of He et al. [ 22 ]. At the same time, mice infected with H. pylori showed decreased sensitivity to glucose and insulin. Analysis of liver transcriptome sequencing results showed that H. pylori infection under HFD feeding conditions induced differential expression of 578 genes in mouse liver tissues, of which 245 genes were up-regulated and 333 genes were down-regulated. Enrichment analysis found that some DEGs were significantly involved in the "long-chain fatty acid metabolic process " and "regulation of lipid metabolic process." Meanwhile, "Retinol metabolism" and "PPAR signaling pathway" were significantly enriched in KEGG analysis. The results of these analyses illustrate that HFD-based H. pylori infection impacts hepatic lipid metabolism. By comparing the effect of H. pylori strain infection with different Cag A status on liver transcriptomics under the uniform dietary pattern, we explored the possible role of the virulence factor Cag A in the relationship between H. pylori infection and NAFLD. The comparison revealed that the "PPAR signaling pathway" and "Fatty acid degradation" pathways were significantly enriched in DEGs from livers of Cag A- H. pylori -infected mice regardless of dietary pattern. In addition, Fabp5 was upregulated in the transcriptome DEGs, a critical regulator of lipid metabolism. Several experimental studies have explored the relationship between H. pylori and NAFLD directly. He et al. reported that H. pylori infection combined with 12 weeks of HFD feeding promoted central obesity and IR in mice to a comparable extent as HFD feeding alone for 24 weeks, and dynamic changes in the gut microbiota may cause these effects [ 22 ]. Subsequently, the authors measured hepatic lipid deposition in the liver, and NAFLD scores revealed that H. pylori infection significantly aggravated HFD-induced NAFLD and different H. pylori strains, most notably SS1, had different exacerbating effects on NAFLD [ 23 ]. Notably, the H. pylori strains used in the above studies (SS1 and NCTC 11637) did not include the Cag A- strain, and we established a Cag A- strain control in combination with clinical epidemiological studies and H. pylori virulence factor studies to explore the effects of different H. pylori strains further. In addition, H. pylori infection has been demonstrated to promote CCl 4 -induced liver fibrosis in animal models [ 24 ]. In this study, it was possible that HFD plus H. pylori infection only intervened for 16 weeks, and no significant hepatic fibrosis was observed via Masson staining of liver sections. Combined with the reported literature [ 25 ], we estimated that HFD feeding alone requires at least 24 weeks to visualize significant fibrosis in the livers of mice. Previous studies have confirmed that Cag A is closely related to the occurrence of gastric cancer. Reports on Cag A combined with extragastric diseases are common in patients with atherosclerosis [ 26 , 27 ], and only two studies have reported the association between Cag A and NAFLD. Kang et al. suggested that the H. pylori Cag A- strain may be associated with NAFLD [ 20 ]. In contrast, Barreyro et al. reported no significant association between H. pylori infection, Cag A status, and ultrasonographically diagnosed NAFLD in NAFLD patients with dyspeptic symptoms [ 28 ]. Moreover, the results suggested that Cag A + but not Cag A- was associated with higher AST and fibrosis 4 scores in patients. Our study is the first transcriptomical research to mechanistically explore the relationship between Cag A, H. pylori , and NAFLD. Sequencing analysis of liver transcriptomes infected with different H. pylori strains revealed that “Nonalcoholic fatty liver disease” and “PPAR signaling pathway” were enriched according to KEGG enrichment analysis, and Fabp5 expression was significantly different in the Cag A- groups. Fabp5 is a member of the fatty acid binding protein family, which is mainly involved in the uptake, transport, and metabolism of fatty acids and related metabolites in the cytoplasm and regulating lipid metabolism and cell growth [ 29 ]. Fabp5 is essential for the pathogenesis of IR associated with obesity and lipid metabolism [ 30 , 31 ]. Loss of Fabp5 gene expression leads to increased systemic insulin sensitivity in animal models of obesity and IR, and adipocytes isolated from Fabp5 -/- mice also exhibit increased insulin-stimulated glucose transport capacity [ 30 ]. In contrast, mice with high Fabp5 expression in adipose tissue exhibited significantly decreased systemic insulin sensitivity, and Fabp5 may regulate blood glucose and blood lipid metabolism by affecting leptin expression. In this study, we detected the differential expression of Fabp5 in each group by qRT-PCR. Interestingly, Fabp5 was highly expressed in both the Cag A- groups but not in the Cag A + groups, regardless of the dietary ingredient. In addition, two bioinformatics studies predicted the crucial role of Fabp5 in NAFLD. High Fabp5 expression was significantly associated with poor prognosis in NAFLD-related HCC patients [ 32 , 33 ]. These results fit our results to some extent. Therefore, we speculated that other virulence factors of H. pylori , such as vacuolating toxin A, neutrophils activating protein, upregulated Fabp5 expression through some mechanisms, while the presence of Cag A, the most potent virulence factor, masked the mechanisms. However, additional experimental studies are needed to explore the underlying mechanisms of H. pylori virulence factors and extragastric diseases such as NAFLD. The enrichment analysis results suggested that the retinol metabolic and PPAR signaling pathways were significantly enriched in the HFD groups. Retinol and its primary metabolites, retinal and all-trans retinoic acid (atRA), are collectively referred to as naturally occurring retinoids, which control energy balance, obesity, and inflammatory processes. Total cellular reflectance retinoic acid binding protein (CRABP) is the primary receptor for intracellular retinoid transport, and Fabp5 also has a high affinity for atRA and long-chain fatty acids. Fabp5 competitively binds atRA with CRABP2, and when the Fabp5/CRABP2 ratio is high, atRA binds Fabp5 and activates the downstream PPAR pathway, a crucial pathway regulating glucose and lipid metabolism [ 34 , 35 ]. We speculate that the overexpression of Fabp5 in mouse hepatocytes caused by H. pylori infection inhibits CRABP2, binds to atRA for transport, activates the downstream PPAR pathway, and, in turn, regulates fatty acid degradation pathways. Our experimental results concatenate H. pylori infection exacerbating NAFLD into a complete clue. 5. CONCLUSION In summary, we established a mouse model of NAFLD plus H. pylori infection and found that chronic H. pylori infection significantly aggravated HFD-induced hepatic lipid deposition and IR. Through transcriptome sequencing analysis and related validation, we discovered that H. pylori infection may promote the development of NAFLD by regulating lipid metabolism. However, how does H. pylori infection regulate Fabp5 expression in the liver, through hepatic macrophages? H. pylori exoteric vesicles? Or other pathways. Basic experiments are needed to explore the underlying mechanisms involved in NAFLD, which will help us better comprehend NAFLD and gain insight into the pathways through which H. pylori causes extragastric diseases. Abbreviations H. pylori: Helicobacter pylori NAFLD: Nonalcoholic fatty liver disease Cag A: Cytotoxin-associated gene A Fabp5 : Fatty acid binding protein 5 PPAR : Peroxisome proliferator-activated receptor IR : Insulin resistance HOMA-IR : Homeostatic model assessment for insulin resistance FBG : Fasting blood glucose TG : Triglyceride BMI : Body mass index HDL-C : High-density lipoprotein cholesterol LDL-C : Low-density lipoprotein cholesterol HFD : High-fat diet CD : Chow diet ALT : Alanine aminotransferase AST : Aspartate aminotransferase TC : Total cholesterol IPGTT : Intraperitoneal glucose tolerance test IPITT : Intraperitoneal insulin tolerance test KEGG : Kyoto Encyclopedia of Genes and Genomes GO : Gene Ontology DEG : Differentially expressed gene IL-1β : Interleukin 1β TNF-α : Tumor necrosis factor α IL-6 : Interleukin 6 atRA : All-trans retinoic acid Declarations Ethics approval and consent to participate The animal studies were performed according to the National Institutes of Health recommendations for the Care and Use of Laboratory Animals and were approved by the Central South University Animal Ethics Committee. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests Funding This work was supported by the National Natural Science Foundation of China (Grant No. 82070547) and the Natural Science Foundation of Hunan Province (Grant Nos. 2024JJ5492). Authors' contributions CXC performed the research, contributed to the analysis and wrote the paper; PRY and PDZ wrote the paper and supervised the research; LDL supervised the research and revised the manuscript; and LR designed the research, supervised the research and revised the manuscript. All the authors read and approved the final manuscript. Acknowledgements Not applicable. References Li Y, Choi H, Leung K, Jiang F, Graham DY, Leung WK. 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NF-κB/miR-223-3p/ARID1A axis is involved in Helicobacter pylori CagA-induced gastric carcinogenesis and progression. Cell Death Dis. 2018;9(1):12. Cover TL, Lacy DB, Ohi MD. The Helicobacter pylori Cag Type IV Secretion System. Trends Microbiol. 2020;28(8):682–95. Santos M, de Brito BB, da Silva F, Sampaio MM, Marques HS, Oliveira E, Silva N, et al. Helicobacter pylori infection: Beyond gastric manifestations. World J Gastroenterol. 2020;26(28):4076–93. Buzzetti E, Pinzani M, Tsochatzis EA. The multiple-hit pathogenesis of non-alcoholic fatty liver disease (NAFLD). Metabolism. 2016;65(8):1038–48. Powell EE, Wong VW, Rinella M. Non-alcoholic fatty liver disease. Lancet. 2021;397(10290):2212–24. Riazi K, Azhari H, Charette JH, Underwood FE, King JA, Afshar EE, et al. The prevalence and incidence of NAFLD worldwide: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2022;7(9):851–61. Lazarus JV, Mark HE, Villota-Rivas M, Palayew A, Carrieri P, Colombo M, et al. The global NAFLD policy review and preparedness index: Are countries ready to address this silent public health challenge. J Hepatol. 2022;76(4):771–80. Rinella ME, Lazarus JV, Ratziu V, Francque SM, Sanyal AJ, Kanwal F, et al. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. J Hepatol. 2023;79(6):1542–56. Cindoruk M, Cirak MY, Unal S, Karakan T, Erkan G, Engin D, et al. Identification of Helicobacter species by 16S rDNA PCR and sequence analysis in human liver samples from patients with various etiologies of benign liver diseases. Eur J Gastroenterol Hepatol. 2008;20(1):33–6. Cheng DD, He C, Ai HH, Huang Y, Lu NH. The Possible Role of Helicobacter pylori Infection in Non-alcoholic Fatty Liver Disease. Front Microbiol. 2017;8:743. Chen X, Peng R, Peng D, Xiao J, Liu D, Li R. An update: is there a relationship between H. pylori infection and nonalcoholic fatty liver disease? why is this subject of interest. Front Cell Infect Microbiol. 2023;13:1282956. Yu YY, Tong YL, Wu LY, Yu XY. Helicobacter pylori infection eradication for nonalcoholic fatty liver disease: a randomized controlled trial. Sci Rep. 2022;12(1):19530. Abdel-Razik A, Mousa N, Shabana W, Refaey M, Elhelaly R, Elzehery R, et al. Helicobacter pylori and non-alcoholic fatty liver disease: A new enigma. Helicobacter. 2018;23(6):e12537. Liu Y, Xu H, Zhao Z, Dong Y, Wang X, Niu J. No evidence for a causal link between Helicobacter pylori infection and nonalcoholic fatty liver disease: A bidirectional Mendelian randomization study. Front Microbiol. 2022;13:1018322. Kang SJ, Kim HJ, Kim D, Ahmed A. Association between cagA negative Helicobacter pylori status and nonalcoholic fatty liver disease among adults in the United States. PLoS ONE. 2018;13(8):e0202325. Liang W, Menke AL, Driessen A, Koek GH, Lindeman JH, Stoop R, et al. Establishment of a general NAFLD scoring system for rodent models and comparison to human liver pathology. PLoS ONE. 2014;9(12):e115922. He C, Yang Z, Cheng D, Xie C, Zhu Y, Ge Z, et al. Helicobacter pylori Infection Aggravates Diet-induced Insulin Resistance in Association With Gut Microbiota of Mice. EBioMedicine. 2016;12:247–54. He C, Cheng D, Wang H, Wu K, Zhu Y, Lu N. Helicobacter pylori infection aggravates diet-induced nonalcoholic fatty liver in mice. Clin Res Hepatol Gastroenterol. 2018;42(4):360–7. Goo MJ, Ki MR, Lee HR, Yang HJ, Yuan DW, Hong IH, et al. Helicobacter pylori promotes hepatic fibrosis in the animal model. Lab Invest. 2009;89(11):1291–303. Willebrords J, Pereira IV, Maes M, Crespo Yanguas S, Colle I, Van Den Bossche B, et al. Strategies, models and biomarkers in experimental non-alcoholic fatty liver disease research. Prog Lipid Res. 2015;59:106–25. Sevlever G, Arias E, Martinetto H, Ferreira M, La Mura R, Ameriso SF. Cag A positive helicobacter Pylori strains are associated with carotid atherosclerosis and predominate in asymptomatic plaques. STROKE. 20082008;39(2):712–712. Jamkhande PG, Gattani SG, Farhat SA. Helicobacter pylori and cardiovascular complications: a mechanism based review on role of Helicobacter pylori in cardiovascular diseases. Integr Med Res. 20162017;5(4):244–9. Barreyro FJ, Sanchez N, Caronia V, Elizondo K, Jorda G, Schneider A et al. Helicobacter pylori Infection and Cag-A Strain Are Associated With NAFLD Severity. Am J Gastroenterol. 20222023;117(10):S892–892893. Zimmerman AW, Veerkamp JH. New insights into the structure and function of fatty acid-binding proteins. Cell Mol Life Sci. 2002;59(7):1096–116. Maeda K, Uysal KT, Makowski L, Görgün CZ, Atsumi G, Parker RA, et al. Role of the fatty acid binding protein mal1 in obesity and insulin resistance. Diabetes. 2003;52(2):300–7. Xu B, Chen L, Zhan Y, Marquez K, Zhuo L, Qi S, et al. The Biological Functions and Regulatory Mechanisms of Fatty Acid Binding Protein 5 in Various Diseases. Front Cell Dev Biol. 2022;10:857919. Yang F, Ni B, Lian Q, Qiu X, He Y, Zhang Q, et al. Key genes associated with non-alcoholic fatty liver disease and hepatocellular carcinoma with metabolic risk factors. Front Genet. 2023;14:1066410. Simoni-Nieves A, Salas-Silva S, Chávez-Rodríguez L, Escobedo-Calvario A, Desoteux M, Bucio L, et al. The Consumption of Cholesterol-Enriched Diets Conditions the Development of a Subtype of HCC with High Aggressiveness and Poor Prognosis. Cancers (Basel). 2021;13(7):1721. Napoli JL. Cellular retinoid binding-proteins, CRBP, CRABP, FABP5: Effects on retinoid metabolism, function and related diseases. Pharmacol Ther. 2017;173:19–33. Schug TT, Berry DC, Toshkov IA, Cheng L, Nikitin AY, Noy N. Overcoming retinoic acid-resistance of mammary carcinomas by diverting retinoic acid from PPARbeta/delta to RAR. Proc Natl Acad Sci U S A. 2008;105(21):7546–51. Supplementary Files Supplementarymaterials.docx Cite Share Download PDF Status: Published Journal Publication published 29 Jul, 2024 Read the published version in Journal of Translational Medicine → Version 1 posted Reviewers agreed at journal 14 Apr, 2024 Reviewers invited by journal 14 Apr, 2024 Editor assigned by journal 01 Apr, 2024 First submitted to journal 31 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4196201","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":290958811,"identity":"b8d53a75-d4e9-493e-914a-8eb40fbd5c80","order_by":0,"name":"Xingcen Chen","email":"","orcid":"","institution":"The Second Xiangya Hospital of Central South University","correspondingAuthor":false,"prefix":"","firstName":"Xingcen","middleName":"","lastName":"Chen","suffix":""},{"id":290958812,"identity":"4c335fac-0972-41a2-8420-9b1245b9acaa","order_by":1,"name":"Ruyi Peng","email":"","orcid":"","institution":"The Second Xiangya Hospital of Central South University Department of Gastroenterology","correspondingAuthor":false,"prefix":"","firstName":"Ruyi","middleName":"","lastName":"Peng","suffix":""},{"id":290958813,"identity":"573e07f5-6f4a-4507-a1db-87c4e88e130a","order_by":2,"name":"Dongzi Peng","email":"","orcid":"","institution":"The Second Xiangya Hospital of Central South University Department of Gastroenterology","correspondingAuthor":false,"prefix":"","firstName":"Dongzi","middleName":"","lastName":"Peng","suffix":""},{"id":290958814,"identity":"c92b7547-10f9-4d31-8193-652b75cb4326","order_by":3,"name":"Deliang Liu","email":"","orcid":"","institution":"The Second Xiangya Hospital of Central South University Department of Gastroenterology","correspondingAuthor":false,"prefix":"","firstName":"Deliang","middleName":"","lastName":"Liu","suffix":""},{"id":290958815,"identity":"7b99c766-04f5-4ff5-b184-62eaf699a15e","order_by":4,"name":"Rong Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYFAC5gaGBww2EDYPcVoYGxgSGNJI13KYBC0GNxLbJBL3nJeXn5HA+OBtG4O8OSEtkjOAWhKe3TbccCOB2XBuG4PhzgYCWvglQFoO3E4wkEhgk+ZtY0gwOEBACxtEy7kEoMPYfxOlBWrLgQSGGwlszERpkex52GyRcCDZcMOZh82Sc85JGG4gpMXgePLBGx8O2MnLtycf/PCmzEaeoC0MAgkwFjCCGBgkCKkHAn6Cho6CUTAKRsGIBwAL7z+biUxR0wAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-2695-1640","institution":"The Second Xiangya Hospital of Central South University Department of Gastroenterology","correspondingAuthor":true,"prefix":"","firstName":"Rong","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-03-31 15:11:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4196201/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4196201/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12967-024-05506-y","type":"published","date":"2024-07-29T15:57:11+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":54859535,"identity":"19e5199c-d379-4c03-ad33-19bd42af37df","added_by":"auto","created_at":"2024-04-17 19:12:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":752068,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of \u003cem\u003eH. pylori\u003c/em\u003e infection combined with CD/HFD feeding on liver pathology in mice. (A) Gross observation, HE staining, Masson staining and Oil Red O staining in CD groups, 200× magnification under a light microscope.(B) Semi-quantitative NAFLD score by HE staining in CD groups. (C) Gross observation, HE staining, Masson staining and Oil Red O staining in HFD groups, 200× magnification under a light microscope. (D) Semi-quantitative NAFLD score by HE staining in HFD groups. Data are expressed as mean ± SD, n=6, *P\u0026lt;0.05, **P\u0026lt;0.01, ***P\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4196201/v1/1d0eb54ef8e0344d61585472.png"},{"id":54859533,"identity":"bb756f8e-fd01-4cd5-a17c-2caf85281553","added_by":"auto","created_at":"2024-04-17 19:12:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":70295,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of \u003cem\u003eH. pylori\u003c/em\u003e infection combined with CD/HFD feeding on physiological metabolism in mice. (A) Serum total cholesterol (TC, mmol/L). (B) Serum high-density lipoprotein cholesterol (HDL-C, mmol/L). (C) Serum low-density lipoprotein cholesterol (LDL-C, mmol/L). (D) Serum alanine aminotransferase (ALT, U/L). (E) Serum aspartate aminotransferase (AST, U/L). Serum inflammatory factor: (F) IL-1 beta (pg/mL). (G) IL-6 (pg/mL). (H) TNF-α (pg/mL). Data are expressed as mean ± SD, n=6, *P\u0026lt;0.05, **P\u0026lt;0.01, ***P\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4196201/v1/06febf641b0968f84b83792a.png"},{"id":54859534,"identity":"83fdf93c-2480-44f6-9e20-cbbc46a736c2","added_by":"auto","created_at":"2024-04-17 19:12:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":473383,"visible":true,"origin":"","legend":"\u003cp\u003ePBS vs \u003cem\u003eH. pylori\u003c/em\u003e transcriptomic DEGs analysis. (A) volcano plot of DEGs; (B) DEGs enrichment results visualization, circular cnetplot; (C) KEGG enrichment analysis; and (D) GO enrichment analysis.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4196201/v1/039461bf5e76b3c6be4f44f0.png"},{"id":54859536,"identity":"295b6561-133a-442a-a56e-cd9fd3af64f5","added_by":"auto","created_at":"2024-04-17 19:12:52","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":448082,"visible":true,"origin":"","legend":"\u003cp\u003ePBS+HFD vs \u003cem\u003eH. pylori\u003c/em\u003e+HFD transcriptomic DEGs analysis. (A) volcano plot of DEGs; (B) DEGs enrichment results visualization, circular cnetplot; (C) KEGG enrichment analysis; and (D) GO enrichment analysis.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4196201/v1/3be16d1768a79f4240152543.png"},{"id":54859540,"identity":"2b392a74-3691-4b4a-9522-79064c69c8a2","added_by":"auto","created_at":"2024-04-17 19:12:52","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":514773,"visible":true,"origin":"","legend":"\u003cp\u003eCag A+ vs Cag A- transcriptomic DEGs analysis. (A) volcano plot of DEGs; (B) DEGs enrichment results visualization, circular cnetplot; (C) KEGG enrichment analysis; and (D) GO enrichment analysis.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4196201/v1/c39fedfee62c2307e86f4c30.png"},{"id":54859538,"identity":"16203975-0722-4358-bb97-8662ad618d62","added_by":"auto","created_at":"2024-04-17 19:12:52","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":524012,"visible":true,"origin":"","legend":"\u003cp\u003eHFD+Cag A+ vs HFD+Cag A- transcriptomic DEGs analysis. (A) volcano plot of DEGs; (B) DEGs enrichment results visualization, circular cnetplot; (C) KEGG enrichment analysis; and (D) GO enrichment analysis.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4196201/v1/32af5a11ded9587b15f4029b.png"},{"id":54859537,"identity":"d1a1a4e9-cb31-4fe1-85b2-320701842be7","added_by":"auto","created_at":"2024-04-17 19:12:52","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":458061,"visible":true,"origin":"","legend":"\u003cp\u003eqRT-PCR and IHC validated DEGs expression in mouse liver. Critical lipid metabolism factor Srebf (A), Fgf21 (B) inflammatory factor Il-1β (C), Tnf-α (D). DEGs Fabp5, PPAR-γ were expressed in mouse liver (E, F). Results of Fabp5 IHC staining in mouse liver in each group (G), 200× magnification under a light microscope. Data are expressed as mean ± SD, n=6, *P\u0026lt;0.05, **P\u0026lt;0.01, ***P\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-4196201/v1/c95563a856ac8b11e35c02dc.png"},{"id":61793416,"identity":"72f2ba60-8158-4ce6-a546-07c5049a946b","added_by":"auto","created_at":"2024-08-05 16:12:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3849270,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4196201/v1/f0cefe52-ce70-4a02-8975-c82a8e222661.pdf"},{"id":54859539,"identity":"9fe1dfff-e21d-428b-a336-3c2f1afb31e2","added_by":"auto","created_at":"2024-04-17 19:12:52","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":177730,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-4196201/v1/b3bad134600a4d89e85d7ae1.docx"}],"financialInterests":"","formattedTitle":"Helicobacter pylori infection exacerbates nonalcoholic fatty liver disease through lipid metabolic pathways: a transcriptomic study.","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003e \u003cem\u003eHelicobacter pylori\u003c/em\u003e (\u003cem\u003eH. pylori\u003c/em\u003e) infects approximately 4.4\u0026nbsp;billion people worldwide, with a prevalence of 43.1% (40.3\u0026ndash;45.9) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. A family-based epidemiological survey revealed that the prevalence of \u003cem\u003eH. pylori\u003c/em\u003e infection in China was approximately 40.66%, 43.45% in adults, and 20.55% in children and adolescents [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Multitudinous studies have confirmed that \u003cem\u003eH. pylori\u003c/em\u003e infection is an essential factor in the progression from gastritis to gastric cancer [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Cytotoxin-associated gene A (Cag A) is considered the most vital virulence factor of \u003cem\u003eH. pylori\u003c/em\u003e, and several studies have shown that Cag A is directly associated with DNA damage in gastric epithelial cells and gastric mucosal carcinogenesis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In addition to gastritis, gastric ulcers, and gastric cancer, many extragastric diseases, such as atherosclerosis, Parkinson's disease, and nonalcoholic fatty liver disease (NAFLD), are also closely associated with \u003cem\u003eH. pylori\u003c/em\u003e infection [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNAFLD is defined as a clinicopathologic syndrome characterized by excessive fat deposition in hepatocytes, excluding alcohol and other definite liver-damaging factors. The disease spectrum includes simple hepatocellular steatosis, nonalcoholic steatohepatitis (NASH), NASH-related liver fibrosis, and hepatocellular carcinoma (HCC). The pathogenesis of NAFLD remains unknown, and the \u003cem\u003emultiple-hit\u003c/em\u003e theory reviewed by Buzzetti et al. is widely acknowledged in academia [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. NAFLD has become the most common chronic liver disease worldwide, with a global prevalence of approximately 32.4% (29.9\u0026ndash;34.9) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although NAFLD is an urgent public health problem, no country is fully prepared to address it [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. No effective agents have been approved for NAFLD treatment, and the primary clinical management regimen for NAFLD is to identify patients with a high risk of disease progression and lose weight through dietary modification and physical exercise [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. It is pressing to recognize and manage NAFLD correctly. Inspiringly, with the specification of the NAFLD definition, the nomenclature for new fatty liver diseases: metabolic dysfunction-associated steatotic liver disease (MASLD) will provide more accurate and high-quality studies for NAFLD/MASLD [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSince the first report of \u003cem\u003eH. pylori\u003c/em\u003e DNA detected in the livers of NAFLD patients [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], several clinical studies have focused on the relationship between \u003cem\u003eH. pylori\u003c/em\u003e infection and NAFLD. Many scholars discuss the relationship between the two and believe that \u003cem\u003eH. pylori\u003c/em\u003e infection may be used as a combustion aid in the \u003cem\u003emultiple-hit\u003c/em\u003e theory of NAFLD, exacerbating the progression of NAFLD through the aspects of inflammatory factors, adipokines, the intestinal barrier, and the intestinal flora [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Yu et al. substantiated that eradication of \u003cem\u003eH. pylori\u003c/em\u003e in \u003cem\u003eH. pylori\u003c/em\u003e-positive NAFLD patients ameliorated fasting blood glucose (FBG), serum triglycerides (TGs), insulin resistance (IR), and body mass index (BMI) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The study by Abdel-Razik et al. reached similar conclusions [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, other studies have found no association between \u003cem\u003eH. pylori\u003c/em\u003e infection and NAFLD. A Mendelian randomization study by Liu et al. revealed no causal link between \u003cem\u003eH. pylori\u003c/em\u003e infection and NAFLD and no significant association between \u003cem\u003eH. pylori\u003c/em\u003e infection and TGs, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), or FBG levels [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Interestingly, a cross-sectional study by Kang et al. indicated that Cag A status may be critical to influencing the relationship between the two, and there was no association between the Cag A positive \u003cem\u003eH. pylori\u003c/em\u003e group and NAFLD (OR: 1.05; 95% CI: 0.81\u0026ndash;1.37), and in multivariate analysis, the Cag A negative (Cag A-) \u003cem\u003eH. pylori\u003c/em\u003e group was significantly associated with NAFLD (OR: 1.30; 95% CI: 1.01\u0026ndash;1.67) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Therefore, this study aimed to explore the effect of \u003cem\u003eH. pylori\u003c/em\u003e infection with different Cag A status on the liver under different dietary patterns and to explore the relationship between \u003cem\u003eH. pylori\u003c/em\u003e infection and NAFLD.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 \u003cem\u003eH. pylori\u003c/em\u003e culture\u003c/h2\u003e \u003cp\u003eThe rodent-adapted \u003cem\u003eH. pylori\u003c/em\u003e Sydney strain (SS1) (Cag A+) was donated by Professor Yong Xie (Department of Gastroenterology, First Affiliated Hospital of Nanchang University, Jiangxi, China). \u003cem\u003eH. pylori\u003c/em\u003e Cag A- was isolated from gastric ulcer patients\u0026rsquo; specimens via gastroscopy. The \u003cem\u003eH. pylori\u003c/em\u003e strains grown on Columbia blood agar plates supplemented with antibiotics (10 mg/L vancomycin, 5 mg/L cefsulodin, 5 mg/L amphotericin B, and 5 mg/L trimethoprim) and 10% sheep blood (Bianzhen Biotech, Nanjing, China) at 37\u0026deg;C under microaerophilic conditions (5% O\u003csub\u003e2\u003c/sub\u003e, 10% CO\u003csub\u003e2\u003c/sub\u003e, and 85% N\u003csub\u003e2\u003c/sub\u003e) for 3\u0026ndash;4 days. Then, the \u003cem\u003eH. pylori\u003c/em\u003e strain, which was in the early log phase with good motility and activity for subculture or intervention, was harvested and resuspended in phosphate buffer saline (PBS). The \u003cem\u003eH. pylori\u003c/em\u003e concentration was estimated by measuring the OD\u003csub\u003e600 nm\u003c/sub\u003e, where OD\u003csub\u003e600 nm\u003c/sub\u003e corresponds to approximately 2 \u0026times; 10\u003csup\u003e8\u003c/sup\u003e colony-forming units (CFU)/ml.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Animals and treatment\u003c/h2\u003e \u003cp\u003e All animal studies were performed according to the National Institutes of Health recommendations for the Care and Use of Laboratory Animals and were approved by the Central South University Animal Ethics Committee. Male C57BL/6J mice (specific pathogen-free grade) aged 6\u0026ndash;8 weeks were purchased from Hunan SJA Laboratory Animal Co., Ltd and housed in animal quarters at 20\u0026ndash;22 \u0026deg; C with a 12-h light cycle and fed ad libitum. After one week of adaptive feeding, 48 mice were randomly divided into six groups (PBS, SS1, Cag A-, PBS\u0026thinsp;+\u0026thinsp;HFD, SS1\u0026thinsp;+\u0026thinsp;HFD, and Cag A-+HFD) of 8 mice each. Four groups were intragastrically infused seven times with 1 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e CFU of \u003cem\u003eH. pylori\u003c/em\u003e SS1 or \u003cem\u003eH. pylori\u003c/em\u003e Cag A- at 1-day intervals and fed either a regular chow diet (CD) or a high-fat diet (HFD) (Research Diets, D09100310). Caloric composition of CD versus HFD was shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. At the same time, the other two groups received PBS by gavage and were fed the corresponding diet for 16 weeks. The animal experiments were conducted in two parts. The first part focused on examining the impact of \u003cem\u003eH. pylori\u003c/em\u003e (SS1) infection on mice's physiological metabolism and liver transcriptomics under different dietary patterns (\u003cspan refid=\"Sec11\" class=\"InternalRef\"\u003eResults\u003c/span\u003e Section \u003cspan refid=\"Sec12\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e\u0026ndash;3.3). The second part investigated the effects of \u003cem\u003eH. pylori\u003c/em\u003e infection, with different Cag A status, on the liver transcriptomics of mice under different dietary patterns (\u003cspan refid=\"Sec11\" class=\"InternalRef\"\u003eResults\u003c/span\u003e Section 3.4\u0026ndash;\u003cspan refid=\"Sec13\" class=\"InternalRef\"\u003e3.5\u003c/span\u003e). Mice were fasted overnight prior to sacrifice. Six animals per group were used for testing and statistical analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCaloric composition table of mouse diet\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietary component\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProtein\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCarbohydrate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFat\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCalories\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChow diet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.37 Kcal/gm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh fat diet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.49 Kcal/gm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Biochemical analysis\u003c/h2\u003e \u003cp\u003eSerum alanine aminotransferase (ALT), aspartate aminotransferase (AST), total cholesterol (TC), HDL-C, and LDL-C were assayed by an automatic biochemical analyzer (Rayto Life and Analytical Sciences, Chemray 240) with corresponding commercial kits. Enzyme-linked immunosorbent assay (ELISA) kits (Jiangsu Meimian Industrial, MM-0040M1, MM-0163M1, MM-0132M1, and MM-0579M1) were used to detect Interleukin 1β (IL-1β), Interleukin 6 (IL-6), Tumor necrosis factor α (TNF-α) and insulin levels in mouse serum. Hepatic TGs were measured by a commercial kit (Nanjing Jiancheng Bioengineering Institute, A110-1-1) according to the manufacturer's instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Histopathologic examination\u003c/h2\u003e \u003cp\u003eFresh mouse liver tissues were fixed in 4% paraformaldehyde and embedded in paraffin. Embedded tissues were cut at 4 \u0026micro;m thickness and then stained with a hematoxylin-eosin (H\u0026amp;E) kit (Powerful Biology, Wuhan, China) for histological assessment according to the rodent model NAFLD scoring system proposed by Liang et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Frozen samples were cut into 8-\u0026micro;m sections and stained with an Oil Red O staining kit (Powerful Biology, Wuhan, China) according to the manufacturer\u0026rsquo;s instructions. Masson staining was used to observe fibrosis in the liver of mice. After staining with iron hematoxylin, Ponceau, and aniline blue, collagen fibers were blue, and muscle fibers, cytoplasm, and cellulose were red. Immunohistochemical (IHC) staining was performed using the following methods: Paraffin slices, 4 \u0026micro;m thick, were grilled at 65\u0026deg;C for 60 minutes, then dewaxed in xylene and rehydrated in a series of increasingly diluted ethanol. High-temperature antigen retrieval was achieved by microwave treatment in 0.1 M citrate solution (pH 6.0) for 10 minutes. The slices were treated with 3% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e at room temperature for 20 minutes, followed by incubation with goat serum for 20 minutes, and subsequently with anti-FABP5 rabbit polyclonal antibody (Proteintech, Wuhan;1:100) overnight at 4\u0026deg;C. The following day, the slices were brought to room temperature and incubated with the secondary anti-rabbit antibody for 20 minutes after washing with PBS. DAB coloration was applied, followed by mounting with hematoxylin and subsequent microscopic examination. All the samples were examined under a light microscope at 200\u0026times; magnification.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Intraperitoneal glucose tolerance test (IPGTT) and intraperitoneal insulin tolerance test (IPITT)\u003c/h2\u003e \u003cp\u003eIn the 15th week of intervention, the mice were pre-stimulated for approximately one week. Sixteen hours of fasting and water deprivation preceded the IPGTT procedure, and the mice were injected intraperitoneally with glucose solution (2 g/kg body weight). Blood samples were collected by tail puncture at 0, 30, 60, 90, and 120 min to measure blood glucose levels using a glucometer. The area under the curve (AUC) was calculated for the IPGTT. IPITT was performed at three-day intervals. Mice were fasted for six hours and injected with insulin (0.75 IU/kg body weight) (Jiangsu Wanbang Biochemistry Medicine Co. Ltd., Xuzhou, China). Blood glucose levels were measured at 0, 15, 30, 60, and 90 min after insulin injection. The AUC of the IPITT was calculated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 RNA‑sequencing\u003c/h2\u003e \u003cp\u003eTotal RNA preparation and subsequent RNA-seq library construction were performed using the APExBIO Technology LLC (Shanghai, China) service. Briefly, total RNA was isolated using a commercial kit (Tiangen Biotech, DP424), and RNA libraries were established using an RNA cleaning and concentration kit (APExBIO Technology LLC, K1159) after quality inspection and purity testing. The RNA quality was verified using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA). The qualified libraries were subjected to Illumina NovaSeq 6000 double-end sequencing according to the effective concentration and target data volume to obtain paired sequences with a read length of 150 bp. The filtered reads were mapped to the mouse genome reference sequence (GRCm39.dna.toplevel.fa Ensembl release103) using HISAT2. The gene expression levels are expressed as fragments per kilobase per million fragments (FPKM). Genes were considered differentially expressed when |fold change| \u0026gt;1.5 and P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Differential expression analysis was performed using DESeq2. KEGG and GO enrichment analyses of differentially expressed genes were performed using the R package ClusterProfiler (v4.2.2), and significant pathways were identified with a P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Quantitative real-time PCR (qRT-PCR)\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted from the livers with AG RNAex Pro Reagent (Accurate Biotechnology, AG21101), an Evo M-MLV RT Mix Kit with gDNA Clean for qPCR Ver.2 (Accurate Biotechnology, AG11728) reverse-transcribed the extracted total RNA into cDNA. qRT-PCR was performed using the SYBR Green Premix Pro Taq HS qPCR Kit IV (Accurate Biotechnology, AG11746) and the targeting gene primers. All the gene primer sequences are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. PCR was performed in triplicate on the qRT-PCR detection system with the following cycling parameters: 95\u0026deg;C (30 s), 40 cycles of 95\u0026deg;C (5 s), 55\u0026deg;C (30 s), and 72\u0026deg;C (30 s). The qRT-PCR data were quantified by the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSequences of primers used for qRT-PCR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward primer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReverse primer\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGapdh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAGGTCGGTGTGAACGGATTTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGGGTCGTTGATGGCAACA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFabp5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAGAGCACAGTGAAGACGAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCATGACACACTCCACGATCA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePpar-γ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCGCTGATGCACTGCCTATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGAGAGGTCCACAGAGCTGATT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFgf21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTGCTGGGGGTCTACCAAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTGCGCCTACCACTGTTCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSrebf-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGATGTGCGAACTGGACACAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCATAGGGGGCGTCAAACAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIl-1β\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGAAATGCCACCTTTTGACAGTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTGGATGCTCTCATCAGGACAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTnf-α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCTGTAGCCCACGTCGTAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGGAGTAGACAAGGTACAACCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Statistical analysis\u003c/h2\u003e \u003cp\u003eThe data are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) and analyzed by unpaired student\u0026rsquo;s t-test and one-way analysis of variance (ANOVA) with GraphPad Prism 9.0 software. At least three independent biological replicates were performed for each group. \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 \u003cem\u003eH. pylori\u003c/em\u003e infection exacerbates hepatic lipid deposition and insulin resistance in mice\u003c/h2\u003e \u003cp\u003eMice infected with \u003cem\u003eH. pylori\u003c/em\u003e had a slightly lower body weight curve than non-infected mice under CD conditions. Although there was no statistical difference between the two groups, infected mice showed an increasing trend in liver weight and liver weight ratio compared with non-infected mice. TG content in the liver of \u003cem\u003eH. pylori\u003c/em\u003e-infected mice was significantly higher than that of non-infected mice (Supplementary Fig.\u0026nbsp;1A-D). Histopathological observations of the liver are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, and the semiquantitative score of NAFLD also tended to be higher in mice infected with \u003cem\u003eH. pylori\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the HFD setting, the trend of physiological parameters in \u003cem\u003eH. pylori\u003c/em\u003e-infected mice was similar to that in the CD groups. The weight curve of \u003cem\u003eH. pylori\u003c/em\u003e-infected mice was slightly lower than that of non-infected mice, and the liver weight and liver weight ratio of infected mice tended to increase (Supplementary Fig.\u0026nbsp;1E-H). Notably, liver pathological changes were more prominent in mice on an HFD, and \u003cem\u003eH. pylori\u003c/em\u003e-infected mouse livers had more pronounced hepatocyte damage, such as hepatocyte macrovesicular steatosis and hepatocyte swelling (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Thus, there were significant differences between \u003cem\u003eH. pylori\u003c/em\u003e-infected mice and non-infected mice in hepatic TG content and NAFLD score (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003eIPGTT and IPITT tested glucose homeostasis and insulin sensitivity. Interestingly, \u003cem\u003eH. pylori\u003c/em\u003e infection affects mice glucose regulation ability and insulin resistance in the CD groups. In the CD groups, the AUC of IPGTT, IPITT, was significantly higher in \u003cem\u003eH. pylori\u003c/em\u003e-infected mice than in the non-infected group. Serum insulin levels and IR levels were also higher in the infected group than in the non-infected group (Supplementary Fig.\u0026nbsp;2). In the HFD feeding, glucose and insulin regulation were weaker, and serum insulin levels were higher in \u003cem\u003eH. pylori\u003c/em\u003e-infected mice than in non-infected mice. However, IR scores were not significantly different between the two groups (Supplementary Fig.\u0026nbsp;2).\u003c/p\u003e \u003cp\u003e3.2 \u003cem\u003eH. pylori\u003c/em\u003e infection combined with HFD feeding had the most significant effect on serum metabolism and inflammation in mice\u003c/p\u003e \u003cp\u003eSerum LDL-C in \u003cem\u003eH. pylori\u003c/em\u003e-infected mice in the CD groups was statistically different from that in the non-infected mice. However, HDL-C, TC, and serum liver enzymes (ALT, AST) showed no significant difference. Serum inflammatory cytokines IL-1β, IL-6, and TNF-α were slightly increased in \u003cem\u003eH. pylori\u003c/em\u003e-infected mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn contrast, \u003cem\u003eH. pylori\u003c/em\u003e infection combined with HFD feeding had a more pronounced effect on serum biochemical parameters in mice. Although there was no statistical difference in serum liver enzymes between the two groups, serum TC, LDL-C, and serum inflammatory cytokines IL-6 and TNF-α were significantly higher in the \u003cem\u003eH. pylori\u003c/em\u003e-infected group than those in the non-infected group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e3.3 RNA-seq reflects different gene expression profiles in the liver of \u003cem\u003eH. pylori\u003c/em\u003e-infected mice fed with different dietary patterns\u003c/p\u003e \u003cp\u003eDifferential expression genes (DEGs) were identified as | fold changes | \u0026gt; 1.5, with a P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Through the analysis of the RNA transcriptome sequencing results of the liver of mice in the CD groups, 767 DEGs were present in the liver of mice in the \u003cem\u003eH. pylori\u003c/em\u003e-infected group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), including 396 down-regulated genes and 371 up-regulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses to identify the biological processes associated with the DEGs. Visualization of the DEGs enriched functional results showed that the \"fatty acid metabolic process\" was significantly expressed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). The enrichment results significantly expressed the \"Nonalcoholic fatty liver disease\" pathway in the KEGG enrichment analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). In GO enrichment analysis, the top 3 significantly enriched in the biological process were \"cellular process,\" \"metabolic process,\" and \"biological regulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\"\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAnalysis of the RNA transcriptome sequencing results of the liver of mice in the HFD groups showed that there were a total of 578 DEGs in the liver of mice infected with \u003cem\u003eH. pylori\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), including 245 down-regulated genes and 333 up-regulated genes. Visualization of the DEGs enriched functional results showed that \"long-chain fatty acid metabolic process\" and \"regulation of lipid metabolic process \" were significantly expressed (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). In KEGG enrichment analysis, the \"PPAR signaling pathway,\" \"Fatty acid degradation,\" and \"Retinol metabolism\" pathways were significantly expressed in the enrichment results (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). The GO enrichment analysis results were similar to those of the CD groups, and the top three biological processes were \"cellular process,\" \"metabolic process,\" and \"biological regulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD).\"\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e3.4 Differential gene expression profiles in livers of \u003cem\u003eH. pylori\u003c/em\u003e-infected mice with different Cag A status on a uniform diet\u003c/p\u003e \u003cp\u003eIn the CD pattern, there were 1511 DEGs in Cag A- \u003cem\u003eH. pylori\u003c/em\u003e infection compared with Cag A\u0026thinsp;+\u0026thinsp;\u003cem\u003eH. pylori\u003c/em\u003e infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), of which 780 were up-regulated, and 731 were down-regulated. Fatty acid binding protein 5 (Fabp5), a critical intracellular transporter of fatty acid and a key regulator of the PPAR pathway, was significantly up-regulated in the Cag A- group. The visualized DEG enrichment function results showed that the \"fatty acid metabolic process\" and \"fat catabolic process\" were significantly expressed (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). The \"PPAR signaling pathway\" and \"Fatty acid degradation\" pathways were enriched in KEGG enrichment analysis. GO enrichment analysis results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn HFD feeding, there were 1400 DEGs in Cag A- \u003cem\u003eH. pylori\u003c/em\u003e infection compared with Cag A\u0026thinsp;+\u0026thinsp;\u003cem\u003eH. pylori\u003c/em\u003e infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA), of which 762 were up-regulated and 638 were down-regulated. Fabp5 was stably and highly expressed in this group. The visualized DEGs enrichment function results showed that \"fatty acid oxidation\" and \"long-chain fatty acids\" were significantly expressed (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). The KEGG enrichment analysis enriched the \"PPAR signaling pathway\" and \"Fatty acid degradation\" pathways. GO enrichment analysis results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.5 qRT-PCR and IHC verified the expression level of differentially expressed genes in mouse liver\u003c/h2\u003e \u003cp\u003eSubsequently, qRT-PCR results showed that \u003cem\u003eH. pylori\u003c/em\u003e infection significantly increased the expression levels of sterol regulatory element binding transcription factor 1 (Srebf1), fibroblast growth factor 21(Fgf21), the critical factors of lipid metabolism, Il-1β, and Tnf-α in the liver (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-D). We performed qRT-PCR to validate the transcriptome sequencing DEGs, and the validation results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE, F. Meanwhile, For the most significantly differentially expressed Fabp5, we performed IHC staining of the mouse liver. Fabp5 expression levels were lower in Cag A\u0026thinsp;+\u0026thinsp;\u003cem\u003eH. pylori\u003c/em\u003e-infected mouse livers. In contrast, cells with strong positive Fabp5 expression displayed in Cag A- \u003cem\u003eH. pylori\u003c/em\u003e-infected mouse livers, mainly distributed in interstitial tissues. The results were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eG.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eWe established mouse models of \u003cem\u003eH. pylori\u003c/em\u003e infection under different dietary patterns to investigate the association between \u003cem\u003eH. pylori\u003c/em\u003e infection and NAFLD. In the CD groups, TG content in liver tissue, serum insulin, and HOMA-IR scores demonstrated that \u003cem\u003eH. pylori\u003c/em\u003e infection could cause hepatic TG deposition and insulin resistance in mice. However, serum biochemical parameters, liver enzymes, and liver pathology indicated that \u003cem\u003eH. pylori\u003c/em\u003e infection does not significantly affect mice's physiological metabolism. We suspected the possible reasons may be: (1) \u003cem\u003eH. pylori\u003c/em\u003e infection duration is not long enough, the systemic chronic inflammatory response is not apparent, and (2) \u003cem\u003eH. pylori\u003c/em\u003e infection alone is insufficient to produce significant changes in liver pathology. Analysis of the liver transcriptome sequencing results showed that \u003cem\u003eH. pylori\u003c/em\u003e infection induced 767 DEGs in mouse liver tissues, of which 371 genes were up-regulated, and 396 genes were down-regulated. Enrichment analysis showed that some DEGs were significantly involved in the \"fatty acid metabolism\" and \"non-alcoholic fatty liver disease\" pathway. These transcriptome results illustrate the link between \u003cem\u003eH. pylori\u003c/em\u003e infection and NAFLD.\u003c/p\u003e \u003cp\u003eBased on HFD feeding, \u003cem\u003eH. pylori\u003c/em\u003e infection had a more evident effect on the physiological metabolism of mice. Although there was no statistical difference in body weight and liver weight between the two groups, liver TG content, serum TC, LDL-C, and serum inflammatory cytokines IL-6 and TNF-α were significantly higher in the \u003cem\u003eH. pylori\u003c/em\u003e-infected group than in the non-infected group. \u003cem\u003eH. pylori\u003c/em\u003e infection combined with HFD feeding resulted in more significant hepatic lipid deposition and hepatocyte macrovesicular steatosis in mice, and there were significant differences in NAFLD scores in mice, which coincided with the findings of He et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. At the same time, mice infected with \u003cem\u003eH. pylori\u003c/em\u003e showed decreased sensitivity to glucose and insulin. Analysis of liver transcriptome sequencing results showed that \u003cem\u003eH. pylori\u003c/em\u003e infection under HFD feeding conditions induced differential expression of 578 genes in mouse liver tissues, of which 245 genes were up-regulated and 333 genes were down-regulated. Enrichment analysis found that some DEGs were significantly involved in the \"long-chain fatty acid metabolic process \" and \"regulation of lipid metabolic process.\" Meanwhile, \"Retinol metabolism\" and \"PPAR signaling pathway\" were significantly enriched in KEGG analysis. The results of these analyses illustrate that HFD-based \u003cem\u003eH. pylori\u003c/em\u003e infection impacts hepatic lipid metabolism.\u003c/p\u003e \u003cp\u003eBy comparing the effect of \u003cem\u003eH. pylori\u003c/em\u003e strain infection with different Cag A status on liver transcriptomics under the uniform dietary pattern, we explored the possible role of the virulence factor Cag A in the relationship between \u003cem\u003eH. pylori\u003c/em\u003e infection and NAFLD. The comparison revealed that the \"PPAR signaling pathway\" and \"Fatty acid degradation\" pathways were significantly enriched in DEGs from livers of Cag A- \u003cem\u003eH. pylori\u003c/em\u003e-infected mice regardless of dietary pattern. In addition, Fabp5 was upregulated in the transcriptome DEGs, a critical regulator of lipid metabolism.\u003c/p\u003e \u003cp\u003eSeveral experimental studies have explored the relationship between \u003cem\u003eH. pylori\u003c/em\u003e and NAFLD directly. He et al. reported that \u003cem\u003eH. pylori\u003c/em\u003e infection combined with 12 weeks of HFD feeding promoted central obesity and IR in mice to a comparable extent as HFD feeding alone for 24 weeks, and dynamic changes in the gut microbiota may cause these effects [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Subsequently, the authors measured hepatic lipid deposition in the liver, and NAFLD scores revealed that \u003cem\u003eH. pylori\u003c/em\u003e infection significantly aggravated HFD-induced NAFLD and different \u003cem\u003eH. pylori\u003c/em\u003e strains, most notably SS1, had different exacerbating effects on NAFLD [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Notably, the \u003cem\u003eH. pylori\u003c/em\u003e strains used in the above studies (SS1 and NCTC 11637) did not include the Cag A- strain, and we established a Cag A- strain control in combination with clinical epidemiological studies and \u003cem\u003eH. pylori\u003c/em\u003e virulence factor studies to explore the effects of different \u003cem\u003eH. pylori\u003c/em\u003e strains further. In addition, \u003cem\u003eH. pylori\u003c/em\u003e infection has been demonstrated to promote CCl\u003csub\u003e4\u003c/sub\u003e-induced liver fibrosis in animal models [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In this study, it was possible that HFD plus \u003cem\u003eH. pylori\u003c/em\u003e infection only intervened for 16 weeks, and no significant hepatic fibrosis was observed via Masson staining of liver sections. Combined with the reported literature [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], we estimated that HFD feeding alone requires at least 24 weeks to visualize significant fibrosis in the livers of mice.\u003c/p\u003e \u003cp\u003ePrevious studies have confirmed that Cag A is closely related to the occurrence of gastric cancer. Reports on Cag A combined with extragastric diseases are common in patients with atherosclerosis [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and only two studies have reported the association between Cag A and NAFLD. Kang et al. suggested that the \u003cem\u003eH. pylori\u003c/em\u003e Cag A- strain may be associated with NAFLD [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In contrast, Barreyro et al. reported no significant association between \u003cem\u003eH. pylori\u003c/em\u003e infection, Cag A status, and ultrasonographically diagnosed NAFLD in NAFLD patients with dyspeptic symptoms [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Moreover, the results suggested that Cag A\u0026thinsp;+\u0026thinsp;but not Cag A- was associated with higher AST and fibrosis 4 scores in patients. Our study is the first transcriptomical research to mechanistically explore the relationship between Cag A, \u003cem\u003eH. pylori\u003c/em\u003e, and NAFLD. Sequencing analysis of liver transcriptomes infected with different \u003cem\u003eH. pylori\u003c/em\u003e strains revealed that \u0026ldquo;Nonalcoholic fatty liver disease\u0026rdquo; and \u0026ldquo;PPAR signaling pathway\u0026rdquo; were enriched according to KEGG enrichment analysis, and Fabp5 expression was significantly different in the Cag A- groups.\u003c/p\u003e \u003cp\u003eFabp5 is a member of the fatty acid binding protein family, which is mainly involved in the uptake, transport, and metabolism of fatty acids and related metabolites in the cytoplasm and regulating lipid metabolism and cell growth [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Fabp5 is essential for the pathogenesis of IR associated with obesity and lipid metabolism [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Loss of Fabp5 gene expression leads to increased systemic insulin sensitivity in animal models of obesity and IR, and adipocytes isolated from Fabp5 -/- mice also exhibit increased insulin-stimulated glucose transport capacity [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In contrast, mice with high Fabp5 expression in adipose tissue exhibited significantly decreased systemic insulin sensitivity, and Fabp5 may regulate blood glucose and blood lipid metabolism by affecting leptin expression.\u003c/p\u003e \u003cp\u003eIn this study, we detected the differential expression of Fabp5 in each group by qRT-PCR. Interestingly, Fabp5 was highly expressed in both the Cag A- groups but not in the Cag A\u0026thinsp;+\u0026thinsp;groups, regardless of the dietary ingredient. In addition, two bioinformatics studies predicted the crucial role of Fabp5 in NAFLD. High Fabp5 expression was significantly associated with poor prognosis in NAFLD-related HCC patients [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. These results fit our results to some extent. Therefore, we speculated that other virulence factors of \u003cem\u003eH. pylori\u003c/em\u003e, such as vacuolating toxin A, neutrophils activating protein, upregulated Fabp5 expression through some mechanisms, while the presence of Cag A, the most potent virulence factor, masked the mechanisms. However, additional experimental studies are needed to explore the underlying mechanisms of \u003cem\u003eH. pylori\u003c/em\u003e virulence factors and extragastric diseases such as NAFLD.\u003c/p\u003e \u003cp\u003eThe enrichment analysis results suggested that the retinol metabolic and PPAR signaling pathways were significantly enriched in the HFD groups. Retinol and its primary metabolites, retinal and all-trans retinoic acid (atRA), are collectively referred to as naturally occurring retinoids, which control energy balance, obesity, and inflammatory processes. Total cellular reflectance retinoic acid binding protein (CRABP) is the primary receptor for intracellular retinoid transport, and Fabp5 also has a high affinity for atRA and long-chain fatty acids. Fabp5 competitively binds atRA with CRABP2, and when the Fabp5/CRABP2 ratio is high, atRA binds Fabp5 and activates the downstream PPAR pathway, a crucial pathway regulating glucose and lipid metabolism [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. We speculate that the overexpression of Fabp5 in mouse hepatocytes caused by \u003cem\u003eH. pylori\u003c/em\u003e infection inhibits CRABP2, binds to atRA for transport, activates the downstream PPAR pathway, and, in turn, regulates fatty acid degradation pathways. Our experimental results concatenate \u003cem\u003eH. pylori\u003c/em\u003e infection exacerbating NAFLD into a complete clue.\u003c/p\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eIn summary, we established a mouse model of NAFLD plus \u003cem\u003eH. pylori\u003c/em\u003e infection and found that chronic \u003cem\u003eH. pylori\u003c/em\u003e infection significantly aggravated HFD-induced hepatic lipid deposition and IR. Through transcriptome sequencing analysis and related validation, we discovered that \u003cem\u003eH. pylori\u003c/em\u003e infection may promote the development of NAFLD by regulating lipid metabolism. However, how does \u003cem\u003eH. pylori\u003c/em\u003e infection regulate Fabp5 expression in the liver, through hepatic macrophages? \u003cem\u003eH. pylori\u003c/em\u003e exoteric vesicles? Or other pathways. Basic experiments are needed to explore the underlying mechanisms involved in NAFLD, which will help us better comprehend NAFLD and gain insight into the pathways through which \u003cem\u003eH. pylori\u003c/em\u003e causes extragastric diseases.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH. pylori:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cem\u003eHelicobacter pylori\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNAFLD:\u003c/strong\u003e Nonalcoholic fatty liver disease\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCag A:\u0026nbsp;\u003c/strong\u003eCytotoxin-associated gene A\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFabp5\u003c/strong\u003e: Fatty acid binding protein 5\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePPAR\u003c/strong\u003e: Peroxisome proliferator-activated receptor\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIR\u003c/strong\u003e: Insulin resistance\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHOMA-IR\u003c/strong\u003e:\u0026nbsp;Homeostatic model assessment for insulin resistance\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFBG\u003c/strong\u003e: Fasting blood glucose\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTG\u003c/strong\u003e: Triglyceride\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e: Body mass index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHDL-C\u003c/strong\u003e: High-density lipoprotein cholesterol\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLDL-C\u003c/strong\u003e: Low-density lipoprotein cholesterol\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHFD\u003c/strong\u003e: High-fat diet\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCD\u003c/strong\u003e: Chow diet\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eALT\u003c/strong\u003e:\u0026nbsp;Alanine aminotransferase\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAST\u003c/strong\u003e:\u0026nbsp;Aspartate aminotransferase\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTC\u003c/strong\u003e: Total cholesterol\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIPGTT\u003c/strong\u003e: Intraperitoneal glucose tolerance test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIPITT\u003c/strong\u003e:\u0026nbsp;Intraperitoneal insulin tolerance test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKEGG\u003c/strong\u003e: Kyoto Encyclopedia of Genes and Genomes\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGO\u003c/strong\u003e: Gene Ontology\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDEG\u003c/strong\u003e: Differentially expressed gene\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIL-1\u0026beta;\u003c/strong\u003e: Interleukin 1\u0026beta;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTNF-\u0026alpha;\u003c/strong\u003e:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eTumor necrosis factor \u0026alpha;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIL-6\u003c/strong\u003e:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eInterleukin 6\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eatRA\u003c/strong\u003e: All-trans retinoic acid\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe animal studies were performed according to the National Institutes of Health recommendations for the Care and Use of Laboratory Animals and were approved by the Central South University Animal Ethics Committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (Grant No. 82070547) and the Natural Science Foundation of Hunan Province (Grant Nos. 2024JJ5492).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCXC performed the research, contributed to the analysis and wrote the paper; PRY and PDZ wrote the paper and supervised the research; LDL supervised the research and\u0026nbsp;revised the manuscript; and LR designed the research, supervised the research and\u0026nbsp;revised the manuscript.\u0026nbsp;All the authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLi Y, Choi H, Leung K, Jiang F, Graham DY, Leung WK. 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Cellular retinoid binding-proteins, CRBP, CRABP, FABP5: Effects on retinoid metabolism, function and related diseases. Pharmacol Ther. 2017;173:19\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchug TT, Berry DC, Toshkov IA, Cheng L, Nikitin AY, Noy N. Overcoming retinoic acid-resistance of mammary carcinomas by diverting retinoic acid from PPARbeta/delta to RAR. Proc Natl Acad Sci U S A. 2008;105(21):7546\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Helicobacter pylori, nonalcoholic fatty liver disease, transcriptome sequencing, FABP5, PPAR signaling pathway","lastPublishedDoi":"10.21203/rs.3.rs-4196201/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4196201/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe relationship between \u003cem\u003eHelicobacter pylori\u003c/em\u003e (\u003cem\u003eH. pylori\u003c/em\u003e) infection and nonalcoholic fatty liver disease (NAFLD) have attracted increased clinical attention. However, most of those current studies involve cross-sectional studies and meta-analyses, and experimental mechanistic exploration still needs to be improved. This study aimed to investigate the mechanisms by which \u003cem\u003eH. pylori\u003c/em\u003e impacts NAFLD.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe established two \u003cem\u003eH. pylori\u003c/em\u003e-infected (Cag A positive and Cag A negative) mouse models with 16 weeks of chow diet (CD) or high-fat diet (HFD) feeding. Body weight, liver triglyceride, blood glucose, serum biochemical parameters, inflammatory factors, and insulin resistance were measured, and histological analysis of liver tissues was performed. Mouse livers were subjected to transcriptome RNA sequencing analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAlthough \u003cem\u003eH. pylori\u003c/em\u003e infection could not significantly affect serum inflammatory factor levels and mouse liver pathology, serum insulin and homeostatic model assessment for insulin resistance levels increased in CD mode. In contrast, \u003cem\u003eH. pylori\u003c/em\u003e infection significantly aggravated hepatic pathological steatosis induced by HFD and elevated serum inflammatory factors and lipid metabolism parameters. Hepatic transcriptomic analysis revealed 767 differentially expressed genes (DEGs) in the \u003cem\u003eH. pylori\u003c/em\u003e-infected group in the CD groups, and the \"nonalcoholic fatty liver disease\" pathway was significantly enriched in KEGG analysis. There were 578 DEGs in \u003cem\u003eH. pylori\u003c/em\u003e infection combined with the HFD feeding group, and DEGs were significantly enriched in \"fatty acid degradation\" and \"PPAR pathway.\" Exploring the effect of different Cag A statuses on mouse liver revealed that fatty acid binding protein 5 was differentially expressed in Cag A- \u003cem\u003eH. Pylori\u003c/em\u003e and DEGs enrichment pathways were concentrated in the \"PPAR pathway\" and \"fatty acid degradation.\"\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003e \u003cem\u003eH. pylori\u003c/em\u003e infection may exacerbate the development of NAFLD by regulating hepatic lipid metabolism, and the \u003cem\u003eH. pylori\u003c/em\u003e virulence factor Cag A plays a vital role in this regulation.\u003c/p\u003e","manuscriptTitle":"Helicobacter pylori infection exacerbates nonalcoholic fatty liver disease through lipid metabolic pathways: a transcriptomic study.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-17 19:12:47","doi":"10.21203/rs.3.rs-4196201/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-04-14T09:50:46+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-14T08:52:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-01T12:12:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Translational Medicine","date":"2024-03-31T11:11:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d7f2d901-d899-4b26-9aae-9cf3de7abfd8","owner":[],"postedDate":"April 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-05T16:00:59+00:00","versionOfRecord":{"articleIdentity":"rs-4196201","link":"https://doi.org/10.1186/s12967-024-05506-y","journal":{"identity":"journal-of-translational-medicine","isVorOnly":false,"title":"Journal of Translational Medicine"},"publishedOn":"2024-07-29 15:57:11","publishedOnDateReadable":"July 29th, 2024"},"versionCreatedAt":"2024-04-17 19:12:47","video":"","vorDoi":"10.1186/s12967-024-05506-y","vorDoiUrl":"https://doi.org/10.1186/s12967-024-05506-y","workflowStages":[]},"version":"v1","identity":"rs-4196201","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4196201","identity":"rs-4196201","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}