A comprehensive bioinformatics analysis on multiple Gene Expression Omnibus datasets of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis

Integrative multiomic analysis identifies distinct molecular subtypes of NAFLD in a Chinese population

Nonalcoholic fatty liver disease (NAFLD) has become a common health care burden worldwide. The high heterogeneity of NAFLD remains elusive and impairs outcomes of clinical diagnosis and pharmacotherapy. Several NAFLD classifications have been proposed on the basis of clinical, genetic, alcoholic, or serum metabolic analyses. Yet, accurately predicting the progression of NAFLD to cirrhosis or hepatocellular carcinoma (HCC) in patients remains a challenge. Here, on the basis of a Chinese cohort of patients, we classified NAFLD into three distinct molecular subtypes (NAFLD-mSI, NAFLD-mSII, and NAFLD-mSIII) using integrative multiomics including whole-genome sequencing (WGS), proteomics, phosphoproteomics, lipidomics, and metabolomics across a broad range of liver, blood, and urine specimens. We found that NAFLD-mSI had higher expression of CYP1A2 and CYP3A4, which alleviate hepatic steatosis through mediating free fatty acid/bile acid-mTOR-FXR/PPARα signaling. NAFLD-mSII displayed an elevated risk of liver cirrhosis along with increased hepatic infiltration of M1 and M2 macrophages because of lipid-triggered hepatic CCL2 and CRP production. NAFLD-mSIII exhibited a potential risk for HCC development by increased transcription of CEBPB- and ERCC3-regulated oncogenes because of activation of the EGF-EGFR/CHKA/PI3K-PDK1-AKT cascade. Next, we validated the existence of these three NAFLD molecular subtypes in an external cohort comprising 92 patients with NAFLD across three different Chinese hospitals. These findings may aid in understanding the molecular features underlying NAFLD heterogeneity, thereby facilitating clinical diagnosis and treatment strategies with the aim of preventing the development of liver cirrhosis and HCC.

Liver organoids and their application in liver cancer research

Liver cancer, a common and intractable liver-related disease, is a malignant tumor with a high morbidity, which needs a high treatment cost but still lacks perfect clinical treatment methods. Looking for an effective platform for liver cancer study and drug screening is urgent and important. Traditional analytical methods for liver disease studies mainly rely on the 2D cell culture and animal experiments, which both cannot fully recapitulate physiological and pathological processes of human liver. For example, cell culture can only show basic functions of cells in vitro, while animal models always hold the problem of species divergence. The organoids, a 3D invitro culture system emerged in recent years, is a cell-bound body with different cell types and has partial tissue functions. The organoid technology can reveal the growth state, structure, function and characteristics of the tissue or organ, and plays an important role in reconstructing invitro experimental models that can truly simulate the human liver. In this paper, we will give a brief introduction of liver organoids and review their applications in liver cancer research, especially in liver cancer pathogenesis, drug screening, precision medicine, regenerative medicine, and other fields. We have also discussed advantages and disadvantages of organoids, as well as future directions and perspectives towards liver organoids.

TidyGEO: preparing analysis-ready datasets from Gene Expression Omnibus

TidyGEO is a Web-based tool for downloading, tidying, and reformatting data series from Gene Expression Omnibus (GEO). As a freely accessible repository with data from over 6 million biological samples across more than 4000 organisms, GEO provides diverse opportunities for secondary research. Although scientists may find assay data relevant to a given research question, most analyses require sample-level annotations. In GEO, such annotations are stored alongside assay data in delimited, text-based files. However, the structure and semantics of the annotations vary widely from one series to another, and many annotations are not useful for analysis purposes. Thus, every GEO series must be tidied before it is analyzed. Manual approaches may be used, but these are error prone and take time away from other research tasks. Custom computer scripts can be written, but many scientists lack the computational expertise to create such scripts. To address these challenges, we created TidyGEO, which supports essential data-cleaning tasks for sample-level annotations, such as selecting informative columns, renaming columns, splitting or merging columns, standardizing data values, and filtering samples. Additionally, users can integrate annotations with assay data, restructure assay data, and generate code that enables others to reproduce these steps.

Introducing Critical Genes in Response to Photodynamic Therapy: A Network Analysis

Introduction: Photodynamic therapy (PDT) is applied as an efficient method for preventing the progress of cancers. Light and a photosensitive compound which is known as photosensitizer (PS) are the main parts of PDT. In the present study, molecular events after using PDT in the presence of a super lethal dose of a PS were assessed via protein-protein interaction (PPI) analysis. Methods: Data were extracted from Gene Expression Omnibus (GEO). The gene expression profiles of the treated human Sk-Cha1 cells via PDT were compared with the control cells. Expressed change analysis and PPI network analysis were administrated via Cytoscape software v 3.7.2 to find the critical differentially expressed genes (DEGs). Regulatory relationships between the central DEGs were evaluated and the highlighted genes were identified. Results: The significant amounts of gene expression values were grouped and a few DEGs characterized by tremendously expressed values were identified. EGFR, CANX, HSPA5, MYC, JUN, ITGB1, APP, and CDH1 were highlighted as hub-bottleneck DEGs. EGFR, CDH1, and JUN appeared as a set of SEGs, which play a crucial role in response to PDT in the treated Sk-Cha1 cells. Conclusion: In conclusion, regulatory relationships between EGFR, CDH1, and JUN, which have an effect on the regulation of cellular survival, differentiation, and proliferation, were highlighted in the present investigation.

CD24 Gene Expression as a Risk Factor for Non-Alcoholic Fatty Liver Disease

In light of increasing NAFLD prevalence, early detection and diagnosis are needed for decision-making in clinical practice and could be helpful in the management of patients with NAFLD. The goal of this study was to evaluate the diagnostic accuracy of CD24 gene expression as a non-invasive tool to detect hepatic steatosis for diagnosis of NAFLD at early stage. These findings will aid in the creation of a viable diagnostic approach.

METHODS

This study enrolled eighty individuals divided into two groups; a study group included forty cases with bright liver and a group of healthy subjects with normal liver. Steatosis was quantified by CAP. Fibrosis assessment was performed by FIB-4, NFS, Fast-score, and Fibroscan. Liver enzymes, lipid profile, and CBC were evaluated. Utilizing RNA extracted from whole blood, the CD24 gene expression was detected using real-time PCR technique.

RESULTS

It was detected that expression of CD24 was significantly higher in patients with NAFLD than healthy controls. The median fold change was 6.56 higher in NAFLD cases compared to control subjects. Additionally, CD24 expression was higher in cases with fibrosis stage F1 compared to those with fibrosis stage F0, as the mean expression level of CD24 was 7.19 in F0 cases as compared to 8.65 in F1 patients but without significant difference (p = 0.588). ROC curve analysis showed that CD24 ∆CT had significant diagnostic accuracy in the diagnosis of NAFLD (p = 0.034). The optimum cutoff for CD24 was 1.83 for distinguishing patients with NAFLD from healthy control with sensitivity 55% and specificity 74.4%; and an area under the ROC curve (AUROC) of 0.638 (95% CI: 0.514-0.763) was determined.

CONCLUSION

In the present study, CD24 gene expression was up-regulated in fatty liver. Further studies are required to confer its diagnostic and prognostic value in the detection of NAFLD, clarify its role in the progression of hepatocyte steatosis, and to elucidate the mechanism of this biomarker in the progression of disease.

Zuogui-Jiangtang-Qinggan-Fang alleviates high-fat diet-induced type 2 diabetes mellitus with non-alcoholic fatty liver disease by modulating gut microbiome-metabolites-short chain fatty acid composition

Non-alcoholic fatty liver disease (NAFLD) pathogenesis is affected by dysbiosis of the gut microbiome and the metabolites it generates. Therefore, restoring the equilibrium between the gut microbiome and the generated metabolites may have therapeutic potential for the syndrome. Zuogui Jiangtang Qinggan Fang (ZGJTQGF) is a Chinese herbal formulation used clinically to treat type 2 diabetic mellitus (T2DM) and fatty liver disease. However, its pharmacological mechanisms have not been well characterized. This work aimed to evaluate the hepatoprotective mechanism of ZGJTQGF in T2DM with NAFLD mice by incorporating gut microbiota, short-chain fatty acids（SCFAs）, and metabolomic analysis, and then to provide strong support for clinical treatment of T2DM with NAFLD. The sequencing of 16 S rRNA revealed that ZGJTQGF therapy modified the composition and abundance of the gut microbiome, raised the level of SCFAs, and restored the intestinal mucosal barrier. The non-targeted metabolomic analysis of liver tissues identified 212 compounds, of which108 were differentially expressed between the HFD and ZGJTQGF groups. Moreover, L-glutamic acid, L-Phenylalanine, Glycine, Taurine, Deoxycholic acid, and citric acid levels were also considerably altered by ZGJTQGF. Our findings suggest that ZGJTQGF ameliorates HFD-induced hepatic steatosis by modulating the gut microbiota composition and its metabolites and boosting the levels of SCFAs. More notably, ZGJTQGF may be a promising medication for preventing and treating NAFLD.

Screening of Immune-Related Genes and Predicting the Immunotherapeutic Effects of Formononetin in Breast Cancer: A Bioinformatics Analysis

Objective

Immunotherapy is a promising breast cancer treatment. Nonetheless, tumor heterogeneity and the interaction between immune cells in the tumor microenvironment limit its effectiveness. Formononetin—extracted from the Chinese medicinal plant Astragalus membranaceus—can inhibit tumor growth, induce apoptosis and angiogenesis, and reverse multidrug resistance. However, its efficacy and mechanism of action on the immune cells in breast cancer remain unclear. Here, we screened immune-related genes of breast cancer to determine the potential of formononetin as a therapeutic.

Methods

GSE103512 and GSE139038 breast cancer microarray data and immune-related gene data were obtained from the GEO and ImmPort databases, respectively, to analyze the differentially expressed immune-related genes (IRGs) in breast cancer tissues compared with normal breast tissues. Protein-protein interaction (PPI) analysis was performed using the STRING database to screen differentially expressed IRGs based on the topological parameters. The Kaplan–Meier test was applied to detect differentially expressed IRGs associated with breast cancer survival, and the interaction of formononetin with differentially expressed IRGs was analyzed using molecular docking. Finally, the relationship between differentially expressed IRGs and breast cancer immune cell infiltration was analyzed using the TIMER2.0 database.

Results

A total of 29 differentially expressed IRGs of breast cancer were screened through GEO and ImmPort databases and 10 key differentially expressed IRGs based on the topological parameters from the PPI network. Among these, CXCL12, ESR1, IGF1, and FOS were associated with breast cancer survival. Furthermore, IGF1, ESR1, and CXCL12 were found to have stable binding sites for formononetin. These genes were associated with substantial immune cell infiltration in breast cancer tissues.

Conclusion

In conclusion, formononetin may exert antitumor effects by acting on CXCL12, ESR1, and IGF1 and may have a potential synergistic effect with immune checkpoint inhibitors.

Deep proteomic profiling unveils arylsulfatase A as a non-alcoholic steatohepatitis inducible hepatokine and regulator of glycemic control

Non-alcoholic steatohepatitis (NASH) and type 2 diabetes are closely linked, yet the pathophysiological mechanisms underpinning this bidirectional relationship remain unresolved. Using proteomic approaches, we interrogate hepatocyte protein secretion in two models of murine NASH to understand how liver-derived factors modulate lipid metabolism and insulin sensitivity in peripheral tissues. We reveal striking hepatokine remodelling that is associated with insulin resistance and maladaptive lipid metabolism, and identify arylsulfatase A (ARSA) as a hepatokine that is upregulated in NASH and type 2 diabetes. Mechanistically, hepatic ARSA reduces sulfatide content and increases lysophosphatidylcholine (LPC) accumulation within lipid rafts and suppresses LPC secretion from the liver, thereby lowering circulating LPC and lysophosphatidic acid (LPA) levels. Reduced LPA is linked to improvements in skeletal muscle insulin sensitivity and systemic glycemic control. Hepatic silencing of Arsa or inactivation of ARSA's enzymatic activity reverses these effects. Together, this study provides a unique resource describing global changes in hepatokine secretion in NASH, and identifies ARSA as a regulator of liver to muscle communication and as a potential therapeutic target for type 2 diabetes.

Diagnostic Modalities of Non-Alcoholic Fatty Liver Disease: From Biochemical Biomarkers to Multi-Omics Non-Invasive Approaches

Non-Alcoholic Fatty Liver Disease (NAFLD) is currently the most common cause of chronic liver disease worldwide, and its prevalence is increasing globally. NAFLD is a multifaceted disorder, and its spectrum includes steatosis to steatohepatitis, which may evolve to advanced fibrosis and cirrhosis. In addition, the presence of NAFLD is independently associated with a higher cardiometabolic risk and increased mortality rates. Considering that the vast majority of individuals with NAFLD are mainly asymptomatic, early diagnosis of non-alcoholic steatohepatitis (NASH) and accurate staging of fibrosis risk is crucial for better stratification, monitoring and targeted management of patients at risk. To date, liver biopsy remains the gold standard procedure for the diagnosis of NASH and staging of NAFLD. However, due to its invasive nature, research on non-invasive tests is rapidly increasing with significant advances having been achieved during the last decades in the diagnostic field. New promising non-invasive biomarkers and techniques have been developed, evaluated and assessed, including biochemical markers, imaging modalities and the most recent multi-omics approaches. Our article provides a comprehensive review of the currently available and emerging non-invasive diagnostic tools used in assessing NAFLD, also highlighting the importance of accurate and validated diagnostic tools.

Comparison of hepatic gene expression profiles between three mouse models of Nonalcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) has become the most common chronic liver disorder worldwide. Murine models of NAFLD have been widely used to explore its pathogenesis. In this study, we performed a systematic evaluation of hepatic genome-wide mRNA expression by RNA-Sequencing using three mouse models of NAFLD: leptin receptor deficient db/db mice, high-fat high-sugar diet (HSHF)-induced obese mice, and dexamethasone (DEX)-induced NAFLD mice. As a result, we found both distinct and common pathways in the regulation of lipid metabolism from transcriptomes of three mouse models. Moreover, only a total of 12 differentially expressed genes (DEGs) were commonly detected among all three mouse groups, indicating very little overlap among all three models. Therefore, our results suggest that NAFLD is a heterogeneous disease with highly variable molecular mechanisms.

Identification of key genes and pathways in mild and severe nonalcoholic fatty liver disease by integrative analysis

Background

The global prevalence of nonalcoholic fatty liver disease (NAFLD) is increasing. The pathogenesis of NAFLD is multifaceted, and the underlying mechanisms are elusive. We conducted data mining analysis to gain a better insight into the disease and to identify the hub genes associated with the progression of NAFLD.

Methods

The dataset GSE49541, containing the profile of 40 samples representing mild stages of NAFLD and 32 samples representing advanced stages of NAFLD, was acquired from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using the R programming language. The Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database were used to perform the enrichment analysis and construct protein–protein interaction (PPI) networks, respectively. Subsequently, transcription factor networks and key modules were identified. The hub genes were validated in a mice model of high fat diet (HFD)-induced NAFLD and in cultured HepG2 cells by real-time quantitative PCR.

Results

Based on the GSE49541 dataset, 57 DEGs were selected and enriched in chemokine activity and cellular component, including the extracellular region. Twelve transcription factors associated with DEGs were indicated from PPI analysis. Upregulated expression of five hub genes (SOX9, CCL20, CXCL1, CD24, and CHST4), which were identified from the dataset, was also observed in the livers of HFD-induced NAFLD mice and in HepG2 cells exposed to palmitic acid or advanced glycation end products.

Conclusion

The hub genes SOX9, CCL20, CXCL1, CD24, and CHST4 are involved in the aggravation of NAFLD. Our results offer new insights into the underlying mechanism of NAFLD progression.

Hepatokine Pregnancy Zone Protein Governs the Diet-Induced Thermogenesis Through Activating Brown Adipose Tissue

Intermittent fasting (IF), as a dietary intervention for weight loss, takes effects primarily through increasing energy expenditure. However, whether inter-organ systems play a key role in IF remains unclear. Here, a novel hepatokine, pregnancy zone protein (PZP) is identified, which has significant induction during the refeeding stage of IF. Further, loss of function studies and protein therapeutic experiment in mice revealed that PZP promotes diet-induced thermogenesis through activating brown adipose tissue (BAT). Mechanistically, circulating PZP can bind to cell surface glucose-regulated protein of 78 kDa (GRP78) to promote uncoupling protein 1 (UCP1) expression via a p38 MAPK-ATF2 signaling pathway in BAT. These studies illuminate a systemic regulation in which the IF promotes BAT thermogenesis through the endocrinal system and provide a novel potential target for treating obesity and related disorders.

Dynamic co-expression modular network analysis in nonalcoholic fatty liver disease

Background

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease affecting people’s health worldwide. Exploring the potential biomarkers and dynamic networks during NAFLD progression is urgently important.

Material and methods

Differentially expressed genes (DEGs) in obesity, NAFL and NASH were screened from GSE126848 and GSE130970, respectively. Gene set enrichment analysis of DEGs was conducted to reveal the Gene Ontology (GO) biological process in each period. Dynamic molecular networks were constructed by DyNet to illustrate the common and distinct progression of health- or obesity-derived NAFLD. The dynamic co-expression modular analysis was carried out by CEMiTool to elucidate the key modulators, networks, and enriched pathways during NAFLD.

Results

A total of 453 DEGs were filtered from obesity, NAFL and NASH periods. Function annotation showed that health-NAFLD sequence was mainly associated with dysfunction of metabolic syndrome pathways, while obesity-NAFLD sequence exhibited dysregulation of Cell cycle and Cellular senescence pathways. Nine nodes including COL3A1, CXCL9, CYCS, CXCL10, THY1, COL1A2, SAA1, CDKN1A, and JUN in the dynamic networks were commonly identified in health- and obesity-derived NAFLD. Moreover, CYCS, whose role is unknown in NAFLD, possessed the highest correlation with NAFLD activity score, lobular inflammation grade, and the cytological ballooning grade. Dynamic co-expression modular analysis showed that module 4 was activated in NAFL and NASH, while module 3 was inhibited at NAFLD stages. Module 3 was negatively correlated with CXCL10, and module 4 was positively correlated with COL1A2 and THY1.

Conclusion

Dynamic network analysis and dynamic gene co-expression modular analysis identified a nine-gene signature as the potential key regulator in NAFLD progression, which provided comprehensive regulatory mechanisms underlying NAFLD progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-021-00196-8.

Extra virgin olive oil improved body weight and insulin sensitivity in high fat diet-induced obese LDLr-/-.Leiden mice without attenuation of steatohepatitis

Dietary fatty acids play a role in the pathogenesis of obesity-associated non-alcoholic fatty liver disease (NAFLD), which is associated with insulin resistance (IR). Fatty acid composition is critical for IR and subsequent NAFLD development. Extra-virgin olive oil (EVOO) is the main source of monounsaturated fatty acids (MUFA) in Mediterranean diets. This study examined whether EVOO-containing high fat diets may prevent diet-induced NAFLD using Ldlr−/−. Leiden mice. In female Ldlr−/−.Leiden mice, the effects of the following high fat diets (HFDs) were examined: a lard-based HFD (HFD-L); an EVOO-based HFD (HFD-EVOO); a phenolic compounds-rich EVOO HFD (HFD-OL). We studied changes in body weight (BW), lipid profile, transaminases, glucose homeostasis, liver pathology and transcriptome. Both EVOO diets reduced body weight (BW) and improved insulin sensitivity. The EVOOs did not improve transaminase values and increased LDL-cholesterol and liver collagen content. EVOOs and HFD-L groups had comparable liver steatosis. The profibrotic effects were substantiated by an up-regulation of gene transcripts related to glutathione metabolism, chemokine signaling and NF-kappa-B activation and down-regulation of genes relevant for fatty acid metabolism. Collectivelly, EVOO intake improved weight gain and insulin sensitivity but not liver inflammation and fibrosis, which was supported by changes in hepatic genes expression.

One potential biomarker for teratozoospermia identified by in-depth integrative analysis of multiple microarray data

Teratozoospermia is a common category of male infertility and with the increase in clinical patients and the increasing sophistication of assisted reproductive technology, there is an urgent need for an accurate semen diagnostic biomarker to accomplish rapid diagnosis of patients with teratozoospermia and accurately assess the success rate of assisted reproductive technologies. In this study, we performed gene differential expression analysis on two publicly available DNA microarray datasets (GSE6872 and GSE6967), followed by GSEA analysis to parse their enriched KEGG pathways, and WGCNA analysis to obtain the most highly correlated modules. Subsequent in-depth comparative analysis of the modules screened into the two datasets resulted in a gene set containing the identical expression trend, and then the differentially expressed genes in the set were screened using the corresponding criteria. Finally, three differentially expressed genes common to both datasets were selected. In addition, we validated the expression changes of this gene using another dataset (GSE6968) and in vitro experiments, and only screened one potential semen biomarker gene whose expression trend was identical to those in other datasets, which will also provide an important theoretical basis for the diagnosis and treatment of teratozoospermia.

Behavioral Characterizing of CD24 Knockout Mouse-Cognitive and Emotional Alternations

CD24 is a small, glycophosphatidylinositol-anchored cell surface protein, mostly investigated with respect to cancer, inflammation, and autoimmune diseases. CD24 knockdown or inhibition has been used to test various biochemical mechanisms and neurological conditions; however, the association between CD24 and behavioral phenotypes has not yet been examined. This study aims to characterize cognitive and emotional functions of CD24 knockout mice (CD24-/-) compared with CD24 wild-type mice at three time-points: adolescence, young adulthood, and adulthood. Our results show that CD24-/- mice exhibited better cognitive performance and less anxiety-like behavior compared with WT mice, with no effect on depression-like behavior. This phenotype was constant from childhood (2 months old) to adulthood (6 months old). The results from our study suggest that CD24 may influence important behavioral aspects at the whole-organism level, which should be taken into consideration when using CD24 knockout models.

Remodeling of whole-body lipid metabolism and a diabetic-like phenotype caused by loss of CDK1 and hepatocyte division

Cell cycle progression and lipid metabolism are well-coordinated processes required for proper cell proliferation. In liver diseases that arise from dysregulated lipid metabolism, hepatocyte proliferation is diminished. To study the outcome of CDK1 loss and blocked hepatocyte proliferation on lipid metabolism and the consequent impact on whole-body physiology, we performed lipidomics, metabolomics, and RNA-seq analyses on a mouse model. We observed reduced triacylglycerides in liver of young mice, caused by oxidative stress that activated FOXO1 to promote the expression of Pnpla2/ATGL. Additionally, we discovered that hepatocytes displayed malfunctioning β-oxidation, reflected by increased acylcarnitines (ACs) and reduced β-hydroxybutyrate. This led to elevated plasma free fatty acids (FFAs), which were transported to the adipose tissue for storage and triggered greater insulin secretion. Upon aging, chronic hyperinsulinemia resulted in insulin resistance and hepatic steatosis through activation of LXR. Here, we demonstrate that loss of hepatocyte proliferation is not only an outcome but also possibly a causative factor for liver pathology.

Da-Chai-Hu Decoction Ameliorates High Fat Diet-Induced Nonalcoholic Fatty Liver Disease Through Remodeling the Gut Microbiota and Modulating the Serum Metabolism

The dysbiosis in gut microbiota could affect host metabolism and contribute to the development of nonalcoholic fatty liver disease (NAFLD). Da-Chai-Hu decoction (DCH) has demonstrated protective effects on NAFLD, however, the exact mechanisms remain unclear. In this study, we established a NAFLD rat model using a high fat diet (HFD) and provided treatment with DCH. The changes in gut microbiota post DCH treatment were then investigated using 16S rRNA sequencing. Additionally, serum untargeted metabolomics were performed to examine the metabolic regulations of DCH on NAFLD. Our results showed that DCH treatment improved the dyslipidemia, insulin resistance (IR) and ameliorated pathological changes in NAFLD model rats. 16S rRNA sequencing and untargeted metabolomics showed significant dysfunction in gut microbiota community and serum metabolites in NAFLD model rats. DCH treatment restored the dysbiosis of gut microbiota and improved the dysfunction in serum metabolism. Correlation analysis indicated that the modulatory effects of DCH on the arachidonic acid (AA), glycine/serine/threonine, and glycerophospholipid metabolic pathways were related to alterations in the abundance of Romboutsia, Bacteroides, Lactobacillus, Akkermansia, Lachnoclostridium and Enterobacteriaceae in the gut microflora. In conclusion, our study revealed the ameliorative effects of DCH on NAFLD and indicated that DCH's function on NAFLD may link to the improvement of the dysbiosis of gut microbiota and the modulation of the AA, glycerophospholipid, and glycine/serine/threonine metabolic pathways.

The role of omics in the pathophysiology, diagnosis and treatment of non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is a multifaceted metabolic disorder, whose spectrum covers clinical, histological and pathophysiological developments ranging from simple steatosis to non-alcoholic steatohepatitis (NASH) and liver fibrosis, potentially evolving into cirrhosis, hepatocellular carcinoma and liver failure. Liver biopsy remains the gold standard for diagnosing NAFLD, while there are no specific treatments. An ever-increasing number of high-throughput Omics investigations on the molecular pathobiology of NAFLD at the cellular, tissue and system levels produce comprehensive biochemical patient snapshots. In the clinical setting, these applications are considerably enhancing our efforts towards obtaining a holistic insight on NAFLD pathophysiology. Omics are also generating non-invasive diagnostic modalities for the distinct stages of NAFLD, that remain though to be validated in multiple, large, heterogenous and independent cohorts, both cross-sectionally as well as prospectively. Finally, they aid in developing novel therapies. By tracing the flow of information from genomics to epigenomics, transcriptomics, proteomics, metabolomics, lipidomics and glycomics, the chief contributions of these techniques in understanding, diagnosing and treating NAFLD are summarized herein.

Multiple Gene Expression Dataset Analysis Reveals Toll-Like Receptor Signaling Pathway is Strongly Associated With Chronic Obstructive Pulmonary Disease Pathogenesis

Chronic obstructive pulmonary disease is a complex pulmonary disease that causes airflow obstruction in humans. To identify the core genes in COPD pathogenesis, seven diverse microarray datasets (GSE475, GSE1122, GSE1650, GSE3212, GSE8823, GSE37768, and GSE22148) were downloaded from the gene expression omnibus database. All the datasets were analyzed independently with the R/Bioconductor package to screen the differentially expressed genes (DEGs). The gene ontology and pathway enrichment analysis were performed for the acquired DEGs using DAVID (Database for Annotation, Visualization, and Integrated Discovery). Further protein-protein interaction network was constructed for the DEGs and their potential hub genes and sub-networks were identified using Cytoscape software. From the selected seven datasets, 188 overlapped DEGs were perceived eventually based on considering the repetitive genes between at-least one dataset. Gene Ontology analysis reveals that most of the DEGs were significantly enriched in immune response, inflammatory response, extracellular region, lipid binding, cytokine, and chemokine activity. Moreover, genes from the sub-network analysis were again submitted to the DAVID server to validate the results which uncover the Toll-like receptor signaling pathway was significantly enriched and all the genes present in this pathway were likewise detected as hub genes from Cytoscape software. CXCL9, CXCL10, CXCL11, CCL4, TLR7, and SPP1 hub genes in the toll-like receptor signaling pathway were explored in this study as potential biomarker genes associated with COPD pathogenesis.

Identification of the Novel Target Genes for Osteosarcoma Therapy Based on Comprehensive Bioinformatic Analysis

Osteosarcoma is one of the most common primary malignant tumors of the bone and tends to develop in teenage years. Although multitreatments for the diagnosis and therapy of osteosarcoma have been developed, there are still needs of new methods to prevent and treat the osteosarcoma. Here, we performed bioinformatic analysis to screen for the key genes, molecules, and pathways involved in osteosarcoma survival. Four microarray data sets (GSE99671, GSE87624, GSE65071, and GSE28423), which include data from human bone and osteosarcoma samples, were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed mRNAs and miRNAs were identified. Kyoto Encyclopedia of Genes and Genomes enriched pathways, miRNA-mRNA target, gene/disease relationship, and overall survival was elucidated using related websites and software according to bioinformatic analysis protocols. We found three critical genes miR-29c, blood vessel epicardial substance (BVES), and proteasome 20S subunit beta 2 (PSMB2) through the GEO database and predicting miRNA-mRNA target. Among these genes, BVES and PSMB2 presented a high expression level in osteosarcoma based on GSE99671 and GSE87624 data sets, while miR-29c showed a low expression level in osteosarcoma based on GSE65071 and GSE28423 data sets. Furthermore, we found that the high expression level of miR-29c and BVES associated with better prognosis, while highly expressed PSMB2 associated with poor prognosis. The abnormally expressed mRNAs and miRNAs, which were identified by integrated bioinformatic analysis, provided insights into the molecular mechanisms of osteosarcoma. Notably, we found three critical genes that could be used as novel therapeutic targets for preventing or diagnosing osteosarcoma. Finally, PSMB2 may be the target of miR-29c.

Secondhand Smoke Induces Liver Steatosis through Deregulation of Genes Involved in Hepatic Lipid Metabolism

We investigated the role of secondhand smoke (SHS) exposure, independently of diet, in the development of chronic liver disease. Standard diet-fed mice were exposed to SHS (5 h/day, 5 days/week for 4 months). Genome-wide gene expression analysis, together with molecular pathways and gene network analyses, and histological examination for lipid accumulation, inflammation, fibrosis, and glycogen deposition were performed on the liver of SHS-exposed mice and controls, upon termination of exposure and after one-month recovery in clean air. Aberrantly expressed transcripts were found in the liver of SHS-exposed mice both pre- and post-recovery in clean air (n = 473 vs. 222). The persistent deregulated transcripts (n = 210) predominantly affected genes and functional networks involved in lipid metabolism as well as in the regulation of the endoplasmic reticulum where manufacturing of lipids occurs. Significant hepatic fat accumulation (steatosis) was observed in the SHS-exposed mice, which progressively increased as the animals underwent recovery in clean air. Moderate increases in lobular inflammation infiltrates and collagen deposition as well as loss of glycogen were also detectable in the liver of SHS-exposed mice. A more pronounced phenotype, manifested as a disrupted cord-like architecture with foci of necrosis, apoptosis, inflammation, and macrovesicular steatosis, was observed in the liver of SHS-exposed mice post-recovery. The progressive accumulation of hepatic fat and other adverse histological changes in the SHS-exposed mice are highly consistent with the perturbation of key lipid genes and associated pathways in the corresponding animals. Our data support a role for SHS in the genesis and progression of metabolic liver disease through deregulation of genes and molecular pathways and functional networks involved in lipid homeostasis.

Bioinformatics analysis on multiple Gene Expression Omnibus datasets of the hepatitis B virus infection and its response to the interferon-alpha therapy

Background

Hepatitis B virus (HBV) infection is a global health problem and interferon-alpha (IFN-α) is one of the effective therapies. However, little is known about the genetic background of the HBV infection or the genetic determinants of the IFN-α treatment response. Thus, we aim to explore the possible molecular mechanisms of HBV infection and its response to the IFN-α therapy with a comprehensive bioinformatics analysis.

Methods

The Gene Expression Omnibus datasets (GSE83148, GSE84044 and GSE66698) were collected and the differentially expressed genes (DEGs), key biological processes and intersecting pathways were analyzed. The expression of the co-expressed DEGs in the clinical samples was verified by quantitative real time polymerase chain reaction (qRT-PCR).

Results

Analysis of all the 3 datasets revealed that there were eight up-regulated and one down-regulated co-expressed DEGs following the HBV infection and after IFN-α treatment. In clinical samples, the mRNA level of HKDC1, EPCAM, GSN, ZWINT and PLD3 were significantly increased, while, the mRNA level of PLEKHA2 was significantly decreased in HBV infected liver tissues compared to normal liver tissues. PI3K-Akt signaling pathway, focal adhesion, HTLV-I infection, cytokine-cytokine receptor interaction, metabolic pathways, NF-κB signaling pathway were important pathways associated with the HBV infection and the response of IFN-α treatment.

Conclusions

The co-expressed genes, common biological processes and intersecting pathways identified in the study might play an important role in HBV infection and response of IFN-α treatment. The dysregulated genes may act as novel biomarkers and therapeutic targets for HBV.

Renalase Attenuates Mouse Fatty Liver Ischemia/Reperfusion Injury through Mitigating Oxidative Stress and Mitochondrial Damage via Activating SIRT1

Liver ischemia/reperfusion (IR) injury is a severe complication of liver surgery. Moreover, nonalcoholic fatty liver disease (NAFLD) patients are particularly vulnerable to IR injury, with higher rates of postoperative morbidity and mortality after liver surgeries. Our previous study found that renalase (RNLS) was highly sensitive and responsive to oxidative stress, which may be a promising biomarker for the evaluation of the severity of liver IR injury. However, the role of RNLS in liver IR injury remains unclear. In the present study, we intensively explored the role and mechanism of RNLS in fatty liver IR injury in vivo and in vitro. C57BL/6 mice were divided into 2 groups feeding with high-fat diet (HFD) and control diet (CD), respectively. After 20 weeks' feeding, they were suffered from portal triad blockage and reflow to induce liver IR injury. Additionally, oleic acid (OA) and tert-butyl hydroperoxide (t-BHP) were used in vitro to induce steatotic hepatocytes and to simulate ROS burst and mimic cellular oxidative stress following portal triad blockage and reflow, respectively. Our data showed that RNLS was downregulated in fatty livers, and RNLS administration effectively attenuated IR injury by reducing ROS production and improving mitochondrial function through activating SIRT1. Additionally, the downregulation of RNLS in the fatty liver was mediated by a decrease of signal transduction and activator of transcription 3 (STAT3) expression under HFD conditions. These findings make RNLS a promising therapeutic strategy for the attenuation of liver IR injury.

Non-alcoholic fatty liver disease alters expression of genes governing hepatic nitrogen conversion

BACKGROUND & AIMS

We recently showed that the functional capacity for ureagenesis is deficient in non-alcoholic fatty liver disease (NAFLD) patients. The aim of this study was to assess expression of urea cycle-related genes to elucidate a possible gene regulatory basis to the functional problem.

METHODS

Liver mRNA expression analyses within the gene pathway governing hepatic nitrogen conversion were performed in 20 non-diabetic, biopsy-proven NAFLD patients (8 simple steatosis; 12 non-alcoholic steatohepatitis [NASH]) and 12 obese and 14 lean healthy individuals. Sixteen NAFLD patients were included for gene expression validation. Relationship between gene expressions and functional capacity for ureagenesis was described.

RESULTS

Gene expression of most urea cycle-related enzymes were downregulated in NAFLD vs both control groups; markedly so for the urea cycle flux-generating carbamoyl phosphate synthetase (CPS1) (~3.5-fold, P < .0001). In NASH, CPS1 downregulation paralleled the deficit in ureagenesis (P = .03). Additionally, expression of several genes involved in amino acid uptake and degradation, and the glucagon receptor gene, were downregulated in NAFLD. Conversely, glutamine synthetase (GS) expression increased >1.5-fold (P ≤ .03), inversely related to CPS1 expression (P = .004).

CONCLUSIONS

NAFLD downregulated the expression of urea cycle-related genes. Downregulation of urea cycle flux-generating CPS1 correlated with the loss of functional capacity for ureagenesis in NASH. On gene level, these changes coincided with an increase in the major ammonia scavenging enzyme GS. The effects seemed related to a fatty liver as such rather than NASH or obesity. The findings support gene regulatory mechanisms involved in the deficient ureagenesis of NAFLD, but it remains unexplained how hepatocyte fat accumulation exerts these effects.

Comprehensive and combined omics analysis reveals factors of ischemia-reperfusion injury in liver transplantation

AIM

To explore molecular mechanisms underlying liver ischemia-reperfusion injury (IRI).

MATERIALS & METHODS

Four Gene Expression Omnibus datasets comprising liver transplantation data were collected for a comprehensive analysis. A proteomic analysis was performed and used for correlations analysis with transcriptomic.

RESULTS & CONCLUSION

Ten differentially expressed genes were co-upregulated in four Gene Expression Omnibus datasets, including ATF3, CCL4, DNAJB1, DUSP5, JUND, KLF6, NFKBIA, PLAUR, PPP1R15A and TNFAIP3. The combined analysis demonstrated ten coregulated genes/proteins, including HBB, HBG2, CA1, SLC4A1, PLIN2, JUNB, HBA1, MMP9, SLC2A1 and PADI4. The coregulated differentially expressed genes and coregulated genes/proteins formed a tight interaction network and could serve as the core factors underlying IRI. Comprehensive and combined omics analyses revealed key factors underlying liver IRI, and thus having potential clinical significance.

Large-scale analysis reveals a novel risk score to predict overall survival in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a major cause of cancer mortality and an increasing incidence worldwide; however, there are very few effective diagnostic approaches and prognostic biomarkers.

Materials and methods

One hundred forty-nine pairs of HCC samples from Gene Expression Omnibus (GEO) were obtained to screen differentially expressed genes (DEGs) between HCC and normal samples. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses, and protein–protein interaction network were used. Cox proportional hazards regression analysis was used to identify significant prognostic DEGs, with which a gene expression signature prognostic prediction model was identified in The Cancer Genome Atlas (TCGA) project discovery cohort. The robustness of this panel was assessed in the GSE14520 cohort. We verified details of the gene expression level of the key molecules through TCGA, GEO, and qPCR and used immunohistochemistry for substantiation in HCC tissues. The methylation states of these genes were also explored.

Results

Ninety-eight genes, consisting of 13 upregulated and 85 downregulated genes, were screened out in three datasets. KEGG and Gene ontology analysis for the DEGs revealed important biological features of each subtype. Protein–protein interaction network analysis was constructed, consisting of 64 nodes and 115 edges. A subset of four genes (SPINK1, TXNRD1, LCAT, and PZP) that formed a prognostic gene expression signature was established from TCGA and validated in GSE14520. Next, the expression details of the four genes were validated with TCGA, GEO, and clinical samples. The expression panels of the four genes were closely related to methylation states.

Conclusion

This study identified a novel four-gene signature biomarker for predicting the prognosis of HCC. The biomarkers may also reveal molecular mechanisms underlying development of the disease and provide new insights into interventional strategies.