A novel immune-related genes signature after bariatric surgery is histologically associated with non-alcoholic fatty liver disease

Identification of differentially expressed autophagy-related genes in cases of intracranial aneurysm: Bioinformatics analysis

OBJECTIVE

Recent research indicates that autophagy is essential for the rupture of intracranial aneurysm (IA). This study aimed to examine and validate potential autophagy-related genes (ARGs) in cases of IA using bioinformatics analysis.

METHODS

Two expression profiles (GSE54083 and GSE75436) were obtained from the Gene Expression Omnibus database. Differentially expressed ARGs (DEARGs) in cases of IA were screened using GSE75436, and enrichment analysis and Protein-Protein Interaction (PPI) networks were used to identify the hub genes and related pathways. Furthermore, a novel predictive diagnostic signature for IA based on the hub genes was constructed. The area under the Receiver Operating Characteristic curve (AUC) was used to evaluate the signature performance in GSE75436.

RESULTS

In total, 75 co-expressed DEARGs were identified in the GSE75436 and GSE54083 dataset (28 upregulated and 47 downregulated genes). Enrichment analysis of DEARGs revealed several enriched terms associated with proteoglycans in cancer and human immunodeficiency virus 1 infection. PPI analysis revealed interactions between these genes. Hub DEARGs included insulin-like growth factor 1, clusters of differentiation 4, cysteine-aspartic acid protease 8, Bcl-2-like protein 11, mouse double mutant 2 homolog, toll-like receptor 4, growth factor receptor-bound protein 2, Jun proto-oncogene, AP-1 transcription factor subunit, hypoxia inducible factor 1 alpha, and erythroblastic oncogene B-2. Notably, the signature showed good performance in distinguishing IA (AUC = 0.87). The sig calibration curves showed good calibration.

CONCLUSION

Bioinformatic analysis identified 75 potential DEARGs in cases of IA. This study revealed that IA is affected by autophagy, which could explain the pathogenesis of IA and aid in its diagnosis and treatment. However, future research with experimental validation is necessary to identify potential DEARGs in cases of IA.

Probiotic consumption and hepatic steatosis: results from the NHANES 2011-2016 and Mendelian randomization study

Background

Recent research showed that probiotics treatment may reduce insulin resistance, regulate lipid metabolism, raise liver enzyme levels, and ameliorate inflammation in individuals with metabolic associated fatty liver disease (MAFLD). However, the possible effects of probiotic use on the progression of hepatic steatosis (HS) have not been identified. The purpose of this study was to investigate this in a large population database.

Methods

The cross-sectional research was conducted among adults with complete data on probiotic yogurt consumption and HS in the 2011-2016 National Health and Nutrition Examination Survey (NHANES). Probiotic yogurt consumption was assessed using a dietary supplement questionnaire, while HS was evaluated with HS index (HSI). To explore their relationship, weighted univariate regression analysis, subgroup analysis, and interaction analysis were conducted. To evaluate the causal association between yogurt consumption and NAFLD, mendelian randomization analysis (MR) were performed. A restricted cubic spline (RCS) was used to analyze the relationship curve between the leves of yogurt consumption and hepatic steatosis.

Results

A total of 7,891 participants were included in the study represented 146.7 million non-institutionalized residents of the United States, of whom 4,322 (54.77%) were diagnosed with HS. Multivariable logistic regression showed probiotic yogurt consumption had significantly inverse relationship for HS (OR = 0.84, 95% CI: 0.72-0.97, p = 0.02) after adjusting for all covariates. Once more, the independent relationship between probiotic yogurt consumption and HS was verified by subgroup analysis and interaction analysis. The MR analysis results indicate that there is no causal relationship between yogurt consumption and NAFLD. The RCS model demonstrated a robust J-shaped link between yogurt consumption and HS, revealing a significant decrease in risk within the lower range of yogurt consumption, which attained the lowest risk close to 0.4 cup.

Conclusion

According to the NHANES data, the consumption of probiotics and yogurt has a beneficial effect on HS, whereas the MR results indicated it was not related to NAFLD. The RCS analysis indicates a J-shaped relationship between yogurt consumption and HS, which may account for the inconsistency in the results. Based on these findings, we recommend that adults take half a cup of yogurt daily.

Identification and experimental validation of autophagy-related genes in abdominal aortic aneurysm

AIM

Autophagy plays essential roles in abdominal aortic aneurysm (AAA) development and progression. The objective of this study was to verify the autophagy-related genes (ARGs) underlying AAA empirically and using bioinformatics analysis.

METHODS

Two gene expression profile datasets GSE98278 and GSE57691 were downloaded from the Gene Expression Omnibus (GEO) database, and principal component analysis was performed. Following, the R software (version 4.0.0) was employed to analyze potentially differentially expressed genes related with AAA and autophagy. Subsequently, the candidate genes were screened using protein-protein interaction (PPI), gene ontology (GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Finally, quantitative real-time polymerase chain reaction (RT-qPCR) was performed to detect the RNA expression levels of the top five selected abnormal ARGs in clinical samples obtained from the normal and AAA patients.

RESULTS

According to the information contained (97 AAA patients and 10 healthy controls) in the two datasets, a total of 44 differentially expressed autophagy-related genes (6 up-regulated genes and 38 down-regulated genes) were screened. GO enrichment analysis of differentially expressed autophagy-related genes (DEARGs) demonstrated that some enrichment items were associated with inflammation, and PPI analysis indicated interaction between these genes. RT-qPCR results presented that the expression levels of IL6, PPARG, SOD1, and MAP1LC3B were in accordance with the bioinformatics prediction results acquired from the mRNA chip.

CONCLUSION

Bioinformatics analysis identified 44 potential autophagy-related differentially expressed genes in AAA. Further verification by RT- qPCR presented that IL6, PPARG, SOD1, and MAP1LC3B may affect the development of AAA by regulating autophagy. These findings might help explain the pathogenesis of AAA and be helpful in its diagnosis and treatment.

Integrative analyses of hub genes and their association with immune infiltration in adipose tissue, liver tissue and skeletal muscle of obese patients after bariatric surgery

Bariatric surgery (BS) is an effective treatment for obesity. Adipose tissue, liver tissue and skeletal muscle are important metabolic tissues. This study investigated hub genes and their association with immune infiltration in these metabolic tissues of obese patients after BS by bioinformatic analysis with Gene Expression Omnibus datasets. Differentially expressed genes (DEGs) were identified, and a protein–protein interaction network was constructed to identify hub genes. As a result, 121 common DEGs were identified and mainly enriched in cytokine–cytokine receptor interactions, chemokine signaling pathway, neutrophil activation and immune responses. Immune cell infiltration analysis showed that the abundance of M1 macrophages was significantly lower in adipose and liver tissue after BS (p<0.05). Ten hub genes (TYROBP, TLR8, FGR, NCF2, HCK, CCL2, LAPTM5, MNDA and S100A9) that were all downregulated after BS were also associated with immune cells. Consistently, results in the validated dataset showed that the expression levels of these hub genes were increased in obese patients and mice, and decreased after BS. In conclusion, this study analysed the potential immune and inflammatory mechanisms of BS in three key metabolic tissues of obese patients, and revealed hub genes associated with immune cell infiltration, thus providing potential targets for obesity treatment.

Regulatory network of metformin on adipogenesis determined by combining high-throughput sequencing and GEO database

Adipose differentiation and excessive lipid accumulation are the important characteristics of obesity. Metformin, as a classic hypoglycaemic drug, has been proved to reduce body weight in type 2 diabetes, the specific mechanism has not been completely clear. A few studies have explored its effect on adipogenesis in vitro, but the existing experimental results are ambiguous. 3T3-L1 preadipocytes were used to explore the effects of metformin on the morphological and physiological changes of lipid droplets during adipogenesis. A high throughput sequencing was used to examine the effects of metformin on the transcriptome of adipogenesis. Considering the inevitable errors among independent experiments, we performed integrated bioinformatics analysis to identify important genes involved in adipogenesis and reveal potential molecular mechanisms. During the process of adipogenesis, metformin visibly relieved the morphological and functional changes. In addition, metformin reverses the expression pattern of genes related to adipogenesis at the transcriptome level. Combining with integrated bioinformatics analyses to further identify the potential targeted genes regulated by metformin during adipogenesis. The present study identified novel changes in the transcriptome of metformin in the process of adipogenesis that might shed light on the underlying mechanism by which metformin impedes the progression of obesity.

Systemic immune-inflammation index is associated with hepatic steatosis: Evidence from NHANES 2015-2018

BACKGROUND

As a novel inflammatory marker, Systemic Immune-Inflammation Index (SII) has not been studied with hepatic steatosis. The aim of this study was to investigate the possible relationship between SII and hepatic steatosis.

METHODS

In the cross-sectional investigation, adults having complete information on SII, hepatic steatosis, and bariatric surgery from the 2015-2018 National Health and Nutrition Examination Survey (NHANES) were included. Hepatic steatosis was evaluated with heaptic steatosis index (HSI). The platelet count × neutrophil count/lymphocyte count was used to compute SII. We investigated the independent interaction between SII and hepatic steatosis using weighted multivariable regression analysis and subgroup analysis. To explore the potential relationship between SII, bariatric surgery and hepatic steatosis by controlling potential confounders by propensity score matching.

RESULTS

The study involved 10505 participants in total, 5937 (56.5%) of whom had hepatic steatosis according to the diagnosis. After adjusted for covariates, multivariable logistic regression revealed that high SII level was an independent risk factor for hepatic steatosis (OR = 1.30, 95% CI: 1.10-1.52, P 0.01). Unexpectedly, bariatric surgery reduced SII even after PSM corrected for differences of BMI and HSI.

CONCLUSIONS

In US adults, SII was positively correlated with an increase in hepatic steatosis. The SII may be a simple and affordable way to identify hepatic steatosis. Bariatric surgery may reduce SII without resorting to weight loss. This needs to be verified in additional prospective research.

Exploring the landscape, hot topics, and trends of bariatric metabolic surgery with machine learning and bibliometric analysis

Background

This study aimed to analyze the landscape of publications on bariatric metabolic surgery through machine learning and help experts and scholars from various disciplines better understand bariatric metabolic surgery's hot topics and trends.

Methods

In January 2021, publications indexed in PubMed under the Medical Subject Headings (MeSH) term 'Bariatric Surgery' from 1946 to 2020 were downloaded. Python was used to extract publication dates, abstracts, and research topics from the metadata of publications for bibliometric evaluation. Descriptive statistical analysis, social network analysis (SNA), and topic modeling with latent Dirichlet allocation (LDA) were used to reveal bariatric metabolic surgery publication growth trends, landscape, and research topics.

Results

A total of 21,798 records of bariatric metabolic surgery-related literature data were collected from PubMed. The number of publications indexed to bariatric metabolic surgery had expanded rapidly. Obesity Surgery and Surgery for Obesity and Related Diseases are currently the most published journals in bariatric metabolic surgery. The bariatric metabolic surgery research mainly included five topics: bariatric surgery intervention, clinical case management, basic research, body contour, and surgical risk study.

Conclusion

Despite a rapid increase in bariatric metabolic surgery-related publications, few studies were still on quality of life, psychological status, and long-term follow-up. In addition, basic research has gradually increased, but the mechanism of bariatric metabolic surgery remains to be further studied. It is predicted that the above research fields may become potential hot topics in the future.

Integrated Bioinformatics Analysis Identifies Robust Biomarkers and Its Correlation With Immune Microenvironment in Nonalcoholic Fatty Liver Disease

Objective: Nonalcoholic fatty liver disease (NAFLD) is a serious threat to human health worldwide. In this study, the aim is to analyze diagnosis biomarkers in NAFLD and its relationship with the immune microenvironment based on bioinformatics analysis.

Methods: We downloaded microarray datasets (GSE48452 and GSE63067) from the Gene Expression Omnibus (GEO) database for screening differentially expressed genes (DEGs). The hub genes were screened by a series of machine learning analyses, such as support vector machine (SVM), least absolute shrinkage and selection operator (LASSO), and weighted gene co-expression network analysis (WGCNA). It is worth mentioning that we used the gene enrichment analysis to explore the driver pathways of NAFLD occurrence. Subsequently, the aforementioned genes were validated by external datasets (GSE66676). Moreover, the CIBERSORT algorithm was used to estimate the proportion of different types of immune cells. Finally, the Spearman analysis was used to verify the relationship between hub genes and immune cells.

Results: Hub genes (CAMK1D, CENPV, and TRHDE) were identified. In addition, we found that the pathogenesis of NAFLD is mainly related to nutrient metabolism and the immune system. In correlation analysis, CENPV expression had a strong negative correlation with resting memory CD4 T cells, and TRHDE expression had a strong positive correlation with naive B cells.

Conclusion: CAMK1D, CENPV, and TRHDE play regulatory roles in NAFLD. In particular, CENPV and TRHDE may regulate the immune microenvironment by mediating resting memory CD4 T cells and naive B cells, respectively, and thus influence disease progression.

A Distinctive NAFLD Signature in Adipose Tissue from Women with Severe Obesity

Development and severity of nonalcoholic fatty liver disease (NAFLD) have been linked to obesity and white adipose tissue (WAT) dysfunction plays a key role in this relation. We compared the main features of subcutaneous (SAT) and visceral WAT (VAT) tissue dysfunction in 48 obese women without (Ob) and with NAFLD (Ob-NAFLD) undergoing bariatric surgery and matched for age, BMI and T2D status. Fat cell area, adipocyte size distribution, the degree of histological fibrosis and the mRNA expression of adipokines and genes implicated in inflammation, adipogenesis, angiogenesis, metabolism and extracellular matrix remodeling were measured by RT-qPCR in both fat depots. Ob-NAFLD group showed higher TG and lower HDL circulating levels, increased VAT fat cell area and similar WAT fibrosis in comparison with Ob group. A sPLS-DA was performed in order to identify the set of genes that better characterize the presence of NAFLD. Finally, we build a multinomial logistic model including seven genes that explained 100% of the variance in NAFLD and correctly predicted 100% of cases. Our data support the existence of distinctive NAFLD signatures in WAT from women with severe obesity. A better understanding of these pathways may help in future strategies for the prevention and treatment of NAFLD.