Guoqing Ouyang’s research while affiliated with First Affiliated Hospital of China Medical University and other places

Background The global burden of non-alcoholic steatohepatitis (NASH)-related liver cancer (NRLC) is increasing, making NASH the fastest-growing cause of liver cancer worldwide. This study presents a comprehensive analysis of NRLC burden at the global, regional, and national levels, further categorized by age, sex, and sociodemographic index (SDI). Method Data on NRLC from the Global Burden of Disease, Injuries, and Risk Factors (GBD) study 2021 were downloaded at global, regional, and national levels. The numbers and age-standardized rates (ASRs) of incidence, mortality, and disability-adjusted life years (DALYs) were analyzed to quantify the global burden of NRLC. Additionally, percentage changes in ASRs were used to identify trends in NRLC from 1990 to 2021. Results Globally, both the number of cases and ASRs for NRLC increased between 1990 and 2021. In 2021, there were 42,291 new cases, 40,925 deaths, and 995,475 DALYs attributed to NRLC. East Asia, South Asia, and Southeast Asia reported the highest absolute case numbers, while Western, Southern, and Eastern Sub-Saharan Africa exhibited the highest ASRs. From 1990 to 2021, Australasia, Southern Latin America, and High-income North America showed the most significant increases in NRLC incidence. Nationally, Mongolia, Gambia, and Mozambique exhibited the highest ASR in 2021.The greatest percentage increases in ASIR occurred in Australia, the United Kingdom, and New Zealand between 1990 and 2021. NRLC incidence rates were higher in men and increased with age, peaking at 80–89 years. Similar patterns were observed for NRLC-related deaths and DALYs. Regionally, ASRs initially declined but then increased as SDI rose. At the national level, ASRs consistently decreased with higher SDI. Conclusion This study highlights the substantial burden of NRLC at global, regional, and national levels. Males and older individuals bear a higher disease burden, and considerable variation exists across different regions and countries. These findings provide critical insights for formulating effective strategies to prevent and manage NRLC.

Background Branched-chain amino acid metabolism is involved in the pathogenesis of various liver diseases. In this study, we investigate the potential role of branched-chain amino acid metabolism-related genes in the pathogenesis of hepatic ischemia reperfusion (HIRI). Methods The gene Expression profiles of HIRI were obtained from the Gene Expression Omnibu database. To determine the differential expression of branched-chain amino acid metabolism-related genes between HIRI and normal tissues. Then, the GO and KEGG analyses were performed, and the protein-protein interaction network was constructed. Next, the random forest and LASSO algorithms were used to screen hub genes, and machine learning techniques were used to build diagnostic models. immunoinfiltration was analyzed in both HIRI patients and controls and the ceRNA network was established. Finally, quantitative real-time PCR was used to verify the expression of hub gene. Results Based on data set GSE23649, three central DEGs (SLC7A5, SLC1A5, SLC43A2) were determined by the intersection of three machine learning algorithms and used to establish a nomogram that yielded a high predictive performance (area under the curve 0.733−0.922). In the external GSE15480 dataset, AUC value for three key genes is as high as 1.000. Further analysis of nomogram, decision curve and calibration curve also confirme the predictive efficacy of diagnosis. GSEA and GSVA suggest that these three marker genes were involved in multiple pathways associated with HIRI progression. Immunoinfiltration analysis suggest that the proportion of macrophages, neutrophils, aDCs, Treg, and Th1 cells in HIRI group is higher than that in control group, with statistical significance(P<0.05). The ceRNA network demonstrates the complex regulatory relationships among the three hub genes and these mRNA levels were further confirmed in mouse HIRI liver samples. Conclusions Our study have provided a comprehensive understanding of the association between branched-chain amino acid and HIRI, may provide potential target for HIRI treatment and diagnosis. And provide new insights into the mechanisms of HIRI. Graphical Abstract

Background and aims Alcohol-related liver disease (ALD) is a worldwide burden. Cuproptosis has been shown to play a key role in the development of several diseases. However, the role and mechanisms of cuproptosis in ALD remain unclear. Methods The RNA-sequencing data of ALD liver samples were downloaded from the Gene Expression Omnibus (GEO) database. Bioinformatical analyses were performed using the R data package. We then identified key genes through multiple machine learning methods. Immunoinfiltration analyses were used to identify different immune cells in ALD patients and controls. The expression levels of key genes were further verified. Results We identified three key cuproptosis-related genes (CRGs) (DPYD, SLC31A1, and DBT) through an in-depth analysis of two GEO datasets, including 28 ALD samples and eight control samples. The area under the curve (AUC) value of these three genes combined in determining ALD was 1.0. In the external datasets, the three key genes had AUC values as high as 1.0 and 0.917, respectively. Nomogram, decision curve, and calibration curve analyses also confirmed these genes’ ability to predict the diagnosis. These three key genes were found to be involved in multiple pathways associated with ALD progression. We confirmed the mRNA expression of these three key genes in mouse ALD liver samples. Regarding immune cell infiltration, the numbers of B cells, CD8 (+) T cells, NK cells, T-helper cells, and Th1 cells were significantly lower in ALD patient samples than in control liver samples. Single sample gene set enrichment analysis (ssGSEA) was then used to estimate the immune microenvironment of different CRG clusters and CRG-related gene clusters. In addition, we calculated CRG scores through principal component analysis (PCA) and selected Sankey plots to represent the correlation between CRG clusters, gene clusters, and CRG scores. Finally, the three key genes were confirmed in mouse ALD liver samples and liver cells treated with ethanol. Conclusions We first established a prognostic model for ALD based on 3 CRGs and robust prediction efficacy was confirmed. Our investigation contributes to a comprehensive understanding of the role of cuproptosis in ALD, presenting promising avenues for the exploration of therapeutic strategies.

Background Acetaminophen (APAP) is commonly used as an antipyretic analgesic. However, acetaminophen overdose may contribute to liver injury and even liver failure. Acetaminophen-induced liver injury (AILI) is closely related to mitochondrial oxidative stress and dysfunction, which play critical roles in cuproptosis. Here, we explored the potential role of cuproptosis-related genes (CRGs) in AILI. Methods The gene expression profiles were obtained from the Gene Expression Omnibus database. The differential expression of CRGs was determined between the AILI and control samples. Protein protein interaction, correlation, and functional enrichment analyses were performed. Machine learning was used to identify hub genes. Immune infiltration was evaluated. The AILI mouse model was established by intraperitoneal injection of APAP solution. Quantitative real-time PCR and western blotting were used to validate hub gene expression in the AILI mouse model. The copper content in the mouse liver samples and AML12 cells were quantified using a colorimetric assay kit. Ammonium tetrathiomolybdate (ATTM), was administered to mouse models and AML12 cells in order to investigate the effects of copper chelator on AILI. Results The analysis identified 7,809 differentially expressed genes, 4,245 of which were downregulated and 3,564 of which were upregulated. Four optimal feature genes (OFGs; SDHB, PDHA1, NDUFB2, and NDUFB6) were identified through the intersection of two machine learning algorithms. Further nomogram, decision curve, and calibration curve analyses confirmed the diagnostic predictive efficacy of the four OFGs. Enrichment analysis indicated that the OFGs were involved in multiple pathways, such as IL-17 pathway and chemokine signaling pathway, that are related to AILI progression. Immune infiltration analysis revealed that macrophages were more abundant in AILI than in control samples, whereas eosinophils and endothelial cells were less abundant. Subsequently, the AILI mouse model was successfully established, and histopathological analysis using hematoxylin–eosin staining along with liver function tests revealed a significant induction of liver injury in the APAP group. Consistent with expectations, both mRNA and protein levels of the four OFGs exhibited a substantial decrease. The administration of ATTAM effectively mitigates copper elevation induced by APAP in both mouse model and AML12 cells. However, systemic administration of ATTM did not significantly alleviate AILI in the mouse model. Conclusion This study first revealed the potential role of CRGs in the pathological process of AILI and offered novel insights into its underlying pathogenesis.

Background Hepatocellular carcinoma (HCC) is one of the most lethal malignancies worldwide. PANoptosis is a recently unveiled programmed cell death pathway, Nonetheless, the precise implications of PANoptosis within the context of HCC remain incompletely elucidated. Methods We conducted a comprehensive bioinformatics analysis to evaluate both the expression and mutation patterns of PANoptosis-related genes (PRGs). We categorized HCC into two clusters and identified differentially expressed PANoptosis-related genes (DEPRGs). Next, a PANoptosis risk model was constructed using LASSO and multivariate Cox regression analyses. The relationship between PRGs, risk genes, the risk model, and the immune microenvironment was studies. In addition, drug sensitivity between high- and low-risk groups was examined. The expression profiles of these four risk genes were elucidate by qRT-PCR or immunohistochemical (IHC). Furthermore, the effect of CTSC knock down on HCC cell behavior was verified using in vitro experiments. Results We constructed a prognostic signature of four DEPRGs (CTSC, CDCA8, G6PD, and CXCL9). Receiver operating characteristic curve analyses underscored the superior prognostic capacity of this signature in assessing the outcomes of HCC patients. Subsequently, patients were stratified based on their risk scores, which revealed that the low-risk group had better prognosis than those in the high-risk group. High-risk group displayed a lower Stromal Score, Immune Score, ESTIMATE score, and higher cancer stem cell content, tumor mutation burden (TMB) values. Furthermore, a correlation was noted between the risk model and the sensitivity to 56 chemotherapeutic agents, as well as immunotherapy efficacy, in patient with. These findings provide valuable guidance for personalized clinical treatment strategies. The qRT−PCR analysis revealed that upregulated expression of CTSC, CDCA8, and G6PD, whereas downregulated expression of CXCL9 in HCC compared with adjacent tumor tissue and normal liver cell lines. The knockdown of CTSC significantly reduced both HCC cell proliferation and migration. Conclusion Our study underscores the promise of PANoptosis-based molecular clustering and prognostic signatures in predicting patient survival and discerning the intricacies of the tumor microenvironment within the context of HCC. These insights hold the potential to advance our comprehension of the therapeutic contribution of PANoptosis plays in HCC and pave the way for generating more efficacious treatment strategies.

Background and aims Cuproptosis has emerged as a significant contributor in the progression of various diseases. This study aimed to assess the potential impact of cuproptosis-related genes (CRGs) on the development of hepatic ischemia and reperfusion injury (HIRI). Methods The datasets related to HIRI were sourced from the Gene Expression Omnibus database. The comparative analysis of differential gene expression involving CRGs was performed between HIRI and normal liver samples. Correlation analysis, function enrichment analyses, and protein-protein interactions were employed to understand the interactions and roles of these genes. Machine learning techniques were used to identify hub genes. Additionally, differences in immune cell infiltration between HIRI patients and controls were analyzed. Quantitative real-time PCR and western blotting were used to verify the expression of the hub genes. Results Seventy-five HIRI and 80 control samples from three databases were included in the bioinformatics analysis. Three hub CRGs (NLRP3, ATP7B and NFE2L2) were identified using three machine learning models. Diagnostic accuracy was assessed using a receiver operating characteristic (ROC) curve for the hub genes, which yielded an area under the ROC curve (AUC) of 0.832. Remarkably, in the validation datasets GSE15480 and GSE228782, the three hub genes had AUC reached 0.904. Additional analyses, including nomograms, decision curves, and calibration curves, supported their predictive power for diagnosis. Enrichment analyses indicated the involvement of these genes in multiple pathways associated with HIRI progression. Comparative assessments using CIBERSORT and gene set enrichment analysis suggested elevated expression of these hub genes in activated dendritic cells, neutrophils, activated CD4 memory T cells, and activated mast cells in HIRI samples versus controls. A ceRNA network underscored a complex regulatory interplay among genes. The genes mRNA and protein levels were also verified in HIRI-affected mouse liver tissues. Conclusion Our findings have provided a comprehensive understanding of the association between cuproptosis and HIRI, establishing a promising diagnostic pattern and identifying latent therapeutic targets for HIRI treatment. Additionally, our study offers novel insights to delve deeper into the underlying mechanisms of HIRI.

Background and Aims Acute hepatitis E (AHE) is still a public health issue worldwide. Here, we report the global burden of AHE in 204 countries and territories from 1990 to 2019 by age, sex and socio‐demographic index (SDI), and predict the future trends to 2030. Methods Data on AHE were collected from the Global Burden of Diseases, Injuries and Risk Factors Study 2019. The average annual percentage change (AAPC) and joinpoint analysis were used to determine the burden trend. Results In 2019, there were 19.47 million (95% UI, 16.04 to 23.37 million) incident cases of AHE globally, with a 19% increase since 1990. Age‐standardized rate (ASR) of disability‐adjusted life years (DALYs), prevalent and incident cases declined from 1990 to 2019. In 2019, the ASR of incidence, prevalence and DALYs due to HEV infection were highest in the same regions of South Asia for both sexes. Southern Sub‐Saharan Africa presented the highest increases in the ASR for incidence of HEV infection in both males (AAPC = .25) and females (AAPC = .24) from 1990 to 2019. Incident cases are higher in males than females before 55–59 years old. The SDI values were negatively correlated with the age‐standardized DALYs. Between 2019 and 2030, the ASR for incidence and prevalence of HEV for both sexes showed an increasing trend. Conclusions Although the overall ASR of AHE decreased, the burden of AHE remains an underappreciated problem for society. The findings may provide useful information for policymakers to develop appropriate strategies aimed at reducing the burden of AHE.

Background Liver cancer due to hepatitis C (LCDHC) is one of the leading causes of cancer-related deaths worldwide, and the burden of LCDHC is increasing. We aimed to report the burden of LCDHC at the global, regional, and national levels in 204 countries from 1990 to 2019, stratified by etiology, sex, age, and Sociodemographic Index. Methods Data on LCDHC were available from the Global Burden of Disease, Injuries, and Risk Factors (GBD) study 2019. Numbers and age-standardized mortality, incidence, and disability-adjusted life year (DALY) rates per 100,000 population were estimated through a systematic analysis of modeled data from the GBD 2019 study. The trends in the LCDHC burden were assessed using the annual percentage change. Results Globally, in 2019, there were 152,225 new cases, 141,810 deaths, and 2,878,024 DALYs due to LCDHC. From 1990 to 2019, the number of incidences, mortality, and DALY cases increased by 80.68%, 67.50%, and 37.20%, respectively. However, the age-standardized incidence, mortality, and DALY rate had a decreasing trend during this period. In 2019, the highest age-standardized incidence rates (ASIRs) of LCDHC were found in high-income Asia Pacific, North Africa and the Middle East, and Central Asia. At the regional level, Mongolia, Egypt, and Japan had the three highest ASIRs in 2019. The incidence rates of LCDHC were higher in men and increased with age, with a peak incidence in the 95+ age group for women and the 85–89 age group for men in 2019. A nonlinear association was found between the age-standardized rates of LCDHC and sociodemographic index values at the regional and national levels. Conclusions Although the age-standardized rates of LCDHC have decreased, the absolute numbers of incident cases, deaths, and DALYs have increased, indicating that LCDHC remains a significant global burden. In addition, the burden of LCDHC varies geographically. Male and older adult/s individuals have a higher burden of LCDHC. Our findings provide insight into the global burden trend of LCDHC. Policymakers should establish appropriate methods to achieve the HCV elimination target by 2030 and reducing the burden of LCDHC.

Background and aims Cuproptosis has been identified as a key player in the development of several diseases. In this study, we investigate the potential role of cuproptosis-related genes in the pathogenesis of nonalcoholic fatty liver disease (NAFLD). Method The gene expression profiles of NAFLD were obtained from the Gene Expression Omnibus database. Differential expression of cuproptosis-related genes (CRGs) were determined between NAFLD and normal tissues. Protein–protein interaction, correlation, and function enrichment analyses were performed. Machine learning was used to identify hub genes. Immune infiltration was analyzed in both NAFLD patients and controls. Quantitative real-time PCR was employed to validate the expression of hub genes. Results Four datasets containing 115 NAFLD and 106 control samples were included for bioinformatics analysis. Three hub CRGs (NFE2L2, DLD, and POLD1) were identified through the intersection of three machine learning algorithms. The receiver operating characteristic curve was plotted based on these three marker genes, and the area under the curve (AUC) value was 0.704. In the external GSE135251 dataset, the AUC value of the three key genes was as high as 0.970. Further nomogram, decision curve, calibration curve analyses also confirmed the diagnostic predictive efficacy. Gene set enrichment analysis and gene set variation analysis showed these three marker genes involved in multiple pathways that are related to the progression of NAFLD. CIBERSORT and single-sample gene set enrichment analysis indicated that their expression levels in macrophages, mast cells, NK cells, Treg cells, resting dendritic cells, and tumor-infiltrating lymphocytes were higher in NAFLD compared with control liver samples. The ceRNA network demonstrated a complex regulatory relationship between the three hub genes. The mRNA level of these hub genes were further confirmed in a mouse NAFLD liver samples. Conclusion Our study comprehensively demonstrated the relationship between NAFLD and cuproptosis, developed a promising diagnostic model, and provided potential targets for NAFLD treatment and new insights for exploring the mechanism for NAFLD.

A comprehensive report on the global burden of glucose 6-phosphate dehydrogenase (G6PD) deficiency is currently unavailable. Here we assess G6PD deficiency burden and trends by analyzing data from the Global Burden of Disease, Injuries, and Risk Factors Study (GBD) 2019, including the number and age-standardized rate of incidence (ASIR), prevalence (ASPR), and Years Lived with Disability (YLDs) from 1990 to 2019. Globally, there were increased trends in incident, prevalent and YLDs cases, the global ASIR and ASPR also increased during this period. Females had a greater burden of YLDs compared to males. In low and low-middle Social Development Index (SDI) regions, especially in Sub-Saharan Africa and South Asia, experienced higher ASPR and age-standardized YLDs rate (ASYR). India had the highest incident and prevalent number of G6PD deficiency. Malaysia showed the pronounced decreases in ASPR and ASYR. The highest and lowest ASYRs were observed at SDI values of 0.41 and 0.84, respectively. Together, G6PD deficiency continues to pose a heavy public health burden. Low and low-middle SDI regions need to allocate more efforts towards primary prevention to reduce its high burden.