Comparative transcriptome analysis of peripheral blood mononuclear cells in hepatitis B-related acute-on-chronic liver failure

Omics in acute-on-chronic liver failure

Acute-on-chronic liver failure (ACLF) is a critical syndrome that develops in patients with chronic liver disease and is characterized by acute decompensation, single- or multiple-organ failure and high short-term mortality. Over the past few decades, ACLF has been progressively recognized as an independent clinical entity, and several criteria and prognostic scores have been proposed and validated by different scientific societies. However, controversies still exist in some aspects across regions, which mainly involve whether the definition of underlying liver diseases should include cirrhosis and non-cirrhosis. The pathophysiology of ACLF is complicated and remains unclear, although accumulating evidence based on different aetiologies of ACLF shows that it is closely associated with intense systemic inflammation and immune-metabolism disorder, which result in mitochondrial dysfunction and microenvironment imbalance, leading to disease development and organ failure. In-depth insight into the biological pathways involved in the mechanisms of ACLF and potential mechanistic targets that improve patient survival still needs to be investigated. Omics-based analytical techniques, including genomics, transcriptomics, proteomics, metabolomics and microbiomes, have developed rapidly and can offer novel insights into the essential pathophysiologic process of ACLF. In this paper, we briefly reviewed and summarized the current knowledge and recent advances in the definitions, criteria and prognostic assessments of ACLF; we also described the omics techniques and how omics-based analyses have been applied to investigate and characterize the biological mechanisms of ACLF and identify potential predictive biomarkers and therapeutic targets for ACLF. We also outline the challenges, future directions and limitations presented by omics-based analyses in clinical ACLF research.

Distinct immunometabolic signatures in circulating immune cells define disease outcome in acute-on-chronic liver failure

BACKGROUND AND AIMS

Acute-on-chronic liver failure (ACLF) is a complication of cirrhosis characterized by multiple organ failure and high short-term mortality. The pathophysiology of ACLF involves elevated systemic inflammation leading to organ failure, along with immune dysfunction that heightens susceptibility to bacterial infections. However, it is unclear how these aspects are associated with recovery and nonrecovery in ACLF.

APPROACH AND RESULTS

Here, we mapped the single-cell transcriptome of circulating immune cells from patients with ACLF and acute decompensated (AD) cirrhosis and healthy individuals. We further interrogate how these findings, as well as immunometabolic and functional profiles, associate with ACLF-recovery (ACLF-R) or nonrecovery (ACLF-NR). Our analysis unveiled 2 distinct states of classical monocytes (cMons). Hereto, ACLF-R cMons were characterized by transcripts associated with immune and stress tolerance, including anti-inflammatory genes such as RETN and LGALS1 . Additional metabolomic and functional validation experiments implicated an elevated oxidative phosphorylation metabolic program as well as an impaired ACLF-R cMon functionality. Interestingly, we observed a common stress-induced tolerant state, oxidative phosphorylation program, and blunted activation among lymphoid populations in patients with ACLF-R. Conversely, ACLF-NR cMon featured elevated expression of inflammatory and stress response genes such as VIM , LGALS2 , and TREM1 , along with blunted metabolic activity and increased functionality.

CONCLUSIONS

This study identifies distinct immunometabolic cellular states that contribute to disease outcomes in patients with ACLF. Our findings provide valuable insights into the pathogenesis of ACLF, shedding light on factors driving either recovery or nonrecovery phenotypes, which may be harnessed as potential therapeutic targets in the future.

Revealing disease subtypes and heterogeneity in common variable immunodeficiency through transcriptomic analysis

Common Variable Immunodeficiency (CVID) is a primary immunodeficiency characterized by reduced levels of specific immunoglobulins, resulting in frequent infections, autoimmune disorders, increased cancer risk, and diminished antibody production despite an adequate B cell count. With its clinical manifestations being highly variable, the classification of CVID, including the widely recognized Freiburg classification, is primarily based on clinical symptoms and genetic variations. Our study aims to refine the classification of CVID by analyzing transcriptomics data to identify distinct disease subtypes. We utilized the GSE51405 dataset, examining transcriptomic profiles from 30 CVID patients without complications. Employing a combination of clustering techniques-KMeans, hierarchical agglomerative clustering, spectral clustering, and Gaussian Mixture models-and differential gene expression analysis with R's limma package, we integrated molecular findings with demographic data (age and gender) through correlation analysis and identified common genes among clusters. Three distinct clusters of CVID patients were identified using KMeans, Agglomerative Clustering, and Gaussian Mixture Models, highlighting the disease's heterogeneity. Differential expression analysis unveiled 31 genes with variable expression levels across these clusters. Notably, nine genes (EIF5A, RPL21, ANP32A, DTX3L, NCF2, CDC42EP3, CHP1, FOLR3, and DEFA4) exhibited consistent differential expression across all clusters, independent of demographic factors. The study recommends categorizing patients based on the four genes, NCF2, CHP1, FOLR3, and DEFA4-as they may assist in prognostic prediction. Transcriptomic analysis of common variable immunodeficiency (CVID) patients identified three distinct clusters based on gene expression, independent of age and gender. Nine differentially expressed genes were identified across these clusters, suggesting potential biomarkers for CVID subtype classification. These findings highlight the genetic heterogeneity of CVID and provide novel insights into disease classification and potential personalized treatment approaches.

SEMA6B induces macrophage-mediated inflammation and hepatocyte apoptosis in hepatitis B virus-related acute-on-chronic liver failure

Rationale: Patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) have a high short-term mortality rate. Semaphorin-6B (SEMA6B) plays a crucial role in the pathogenesis of HBV-ACLF, but its molecular basis remains unclear. This study aimed to elucidate the mechanisms of SEMA6B in HBV-ACLF progression. Methods: A total of 321 subjects with HBV-ACLF, liver cirrhosis (LC), chronic hepatitis B (CHB), and normal controls (NC) from a prospective multicenter cohort were studied. 84 subjects (HBV-ACLF, n = 50; LC, n = 10; CHB, n = 10; NC, n = 14) among them underwent mRNA sequencing using peripheral blood mononuclear cells (PBMCs) to clarify the mechanisms of SEMA6B in HBV-ACLF. These mechanisms were validated through in vitro studies with hepatocytes and macrophages, as well as in vivo using SEMA6B knockout mice and mice treated with synthetic SEMA6B siRNA. Results: Transcriptome analysis of PBMCs showed that SEMA6B was among the most differentially expressed genes when comparing patients with HBV-ACLF to those with LC, CHB, or NC. ROC analysis demonstrated the reliable diagnostic value of SEMA6B for HBV-ACLF in both the sequencing cohort and an external validation cohort (AUROC = 0.9788 and 0.9026, respectively). SEMA6B levels were significantly higher in the HBV-ACLF patients, especially in non-survivors, with high expression mainly observed in macrophages and hepatocytes in liver tissue. Genes significantly associated with highly expressed SEMA6B were enriched in inflammation and apoptosis pathways in HBV-ACLF non-survivors. Overexpression of SEMA6B in macrophages activated systemic inflammatory responses, while its overexpression in hepatocytes inhibited proliferation through G0/G1 cell cycle arrest and induced apoptosis. Knocking out SEMA6B rescued mice with liver failure by improving liver functions, reducing inflammatory responses, and decreasing hepatocyte apoptosis. Transcriptome analysis of liver tissue showed that SEMA6B knockout significantly ameliorated the liver failure signature, significantly downregulating inflammation-related pathways. Importantly, therapeutic delivery of synthetic SEMA6B siRNA also improved liver function, and reduced both inflammation and hepatocyte apoptosis in mice with liver failure. Conclusion: SEMA6B, a potential diagnostic biomarker for HBV-ACLF, exacerbates liver failure through macrophage-mediated systemic inflammation and hepatocyte apoptosis. These findings highlight SEMA6B as a promising early treatment target for HBV-ACLF patients.

Thrombospondin 1 enhances systemic inflammation and disease severity in acute-on-chronic liver failure

BACKGROUND

The key role of thrombospondin 1 (THBS1) in the pathogenesis of acute-on-chronic liver failure (ACLF) is unclear. Here, we present a transcriptome approach to evaluate THBS1 as a potential biomarker in ACLF disease pathogenesis.

METHODS

Biobanked peripheral blood mononuclear cells (PBMCs) from 330 subjects with hepatitis B virus (HBV)-related etiologies, including HBV-ACLF, liver cirrhosis (LC), and chronic hepatitis B (CHB), and normal controls (NC) randomly selected from the Chinese Group on the Study of Severe Hepatitis B (COSSH) prospective multicenter cohort underwent transcriptome analyses (ACLF = 20; LC = 10; CHB = 10; NC = 15); the findings were externally validated in participants from COSSH cohort, an ACLF rat model and hepatocyte-specific THBS1 knockout mice.

RESULTS

THBS1 was the top significantly differentially expressed gene in the PBMC transcriptome, with the most significant upregulation in ACLF, and quantitative polymerase chain reaction (ACLF = 110; LC = 60; CHB = 60; NC = 45) was used to verify that THBS1 expression corresponded to ACLF disease severity outcome, including inflammation and hepatocellular apoptosis. THBS1 showed good predictive ability for ACLF short-term mortality, with an area under the receiver operating characteristic curve (AUROC) of 0.8438 and 0.7778 at 28 and 90 days, respectively. Enzyme-linked immunosorbent assay validation of the plasma THBS1 using an expanded COSSH cohort subjects (ACLF = 198; LC = 50; CHB = 50; NC = 50) showed significant correlation between THBS1 with ALT and γ-GT (P = 0.01), and offered a similarly good prognostication predictive ability (AUROC = 0.7445 and 0.7175) at 28 and 90 days, respectively. ACLF patients with high-risk short-term mortality were identified based on plasma THBS1 optimal cut-off value (< 28 µg/ml). External validation in ACLF rat serum and livers confirmed the functional association between THBS1, the immune response and hepatocellular apoptosis. Hepatocyte-specific THBS1 knockout improved mouse survival, significantly repressed major inflammatory cytokines, enhanced the expression of several anti-inflammatory mediators and impeded hepatocellular apoptosis.

CONCLUSIONS

THBS1 might be an ACLF disease development-related biomarker, promoting inflammatory responses and hepatocellular apoptosis, that could provide clinicians with a new molecular target for improving diagnostic and therapeutic strategies.

Etiology of viral induced acute liver failure and defensins as potential therapeutic agents in ALF treatment

Acute liver failure (ALF) is a rare and severe disease, which, despite continuous advances in medicine, is still characterized by high mortality (65-85%). Very often, a liver transplant is the only effective treatment for ALF. Despite the implementation of prophylactic vaccinations in the world, the viral background of ALF is still a problem and leads to many deaths. Depending on the cause of ALF, it is sometimes possible to reverse this condition with appropriate therapies, which is why the search for effective antiviral agents seems to be a very desirable direction of research. Defensins, which are our natural antimicrobial peptides, have a very high potential to be used as therapeutic agents for infectious liver diseases. Previous studies on the expression of human defensins have shown that increased expression of human α and β-defensins in HCV and HBV infections is associated with a better response to treatment. Unfortunately, conducting clinical trials for ALF is very difficult due to the severity of the disease and the low incidence, therefore animal models are important for the development of new therapeutic strategies. One of the best animal models that has real reference to research on acute liver failure (ALF) is rabbit hemorrhagic disease in rabbits caused by the Lagovirus europaeus virus. So far, there have been no studies on the potential of defensins in rabbits infected with Lagovirus europaeus virus.

Comparative Transcriptional Signature Analysis of Peripheral Blood Mononuclear Cells in Early Stage of Hepatitis B-related Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is a prevalent and life-threatening tumor with high morbidity and mortality. Proper prediction and prognosis are incredibly stressed to diagnose HCC and increase patient survival. Objectives: This research aims to evaluate gene expression levels of pre-differentiated transcripts for those suffering from chronic hepatitis B (CHB) and HCC. Methods: To examine the previously analyzed peripheral blood mononuclear cells (PBMCs) transcriptomic array data, we selected seven differentially expressed genes (DEGs) in normal versus CHB and CHB versus HCC (CD44, SP3, USP8, E2F2, UFM1, IFN regulative factor binding protein 2 (IRF2BP2), and T-cell intracellular antigen 1 (TIA1)). The study included individuals with treatment-naïve CHB (n = 30) and primary HCC (n = 25) and healthy controls (n = 15). Subsequently, the expression of genes was assayed using qRT-PCR. A phylogenetic evaluation was performed using direct sequencing of HBsAg. Results: In HCC patients, 60% (n = 15) were HBeAg-positive. HBeAg was negative in all CHB patients, but all were anti-HBe-positive. The hepatitis B virus (HBV) load of HCC patients was more than that of CHB subjects. All patients were of the Iranian race and HBV D genotype. The expression of five transcriptional markers (CD44, SP3, USP8, E2F2, and UFM1) was higher in HCC patients than in CHB and healthy subjects, which was similar to the initial microarray data analysis. Conclusions: Transcriptional signatures may be related to the pathogenesis of HCC and used as diagnostic biological markers for the initial monitoring and prediction of HCC.

Differentiating between liver diseases by applying multiclass machine learning approaches to transcriptomics of liver tissue or blood-based samples

Background & Aims

Liver disease carries significant healthcare burden and frequently requires a combination of blood tests, imaging, and invasive liver biopsy to diagnose. Distinguishing between inflammatory liver diseases, which may have similar clinical presentations, is particularly challenging. In this study, we implemented a machine learning pipeline for the identification of diagnostic gene expression biomarkers across several alcohol-associated and non-alcohol-associated liver diseases, using either liver tissue or blood-based samples.

Methods

We collected peripheral blood mononuclear cells (PBMCs) and liver tissue samples from participants with alcohol-associated hepatitis (AH), alcohol-associated cirrhosis (AC), non-alcohol-associated fatty liver disease, chronic HCV infection, and healthy controls. We performed RNA sequencing (RNA-seq) on 137 PBMC samples and 67 liver tissue samples. Using gene expression data, we implemented a machine learning feature selection and classification pipeline to identify diagnostic biomarkers which distinguish between the liver disease groups. The liver tissue results were validated using a public independent RNA-seq dataset. The biomarkers were computationally validated for biological relevance using pathway analysis tools.

Results

Utilizing liver tissue RNA-seq data, we distinguished between AH, AC, and healthy conditions with overall accuracies of 90% in our dataset, and 82% in the independent dataset, with 33 genes. Distinguishing 4 liver conditions and healthy controls yielded 91% overall accuracy in our liver tissue dataset with 39 genes, and 75% overall accuracy in our PBMC dataset with 75 genes.

Conclusions

Our machine learning pipeline was effective at identifying a small set of diagnostic gene biomarkers and classifying several liver diseases using RNA-seq data from liver tissue and PBMCs. The methodologies implemented and genes identified in this study may facilitate future efforts toward a liquid biopsy diagnostic for liver diseases.

Lay summary

Distinguishing between inflammatory liver diseases without multiple tests can be challenging due to their clinically similar characteristics. To lay the groundwork for the development of a non-invasive blood-based diagnostic across a range of liver diseases, we compared samples from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, and non-alcohol-associated fatty liver disease. We used a machine learning computational approach to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to discover a small set of gene biomarkers for effective diagnosis of these liver diseases.

Alterations in Immune-Related Defensin Alpha 4 (DEFA4) Gene Expression in Health and Disease

Defensin Alpha 4 (DEFA4) is the fourth member of the Alpha Defensins family known as a part of antimicrobial peptides in the innate immune system. DEFA4 has a strong preference to kill Gram-negative bacteria more than Gram-positive bacteria. In addition, DEFA4 exhibits antiviral activity against human immunodeficiency virus type 1 (HIV-1) in vitro. Moreover, DEFA4 can act as an inhibitor of corticosterone production (Corticostatin). On the other hand, alternations in DEFA4 gene expression have been reported in different disorders such as diseases related to inflammation and immunity dysfunction, brain-related disorders, and various cancers. The up-regulation of DEFA4 appears to be involved in the malignant transformation or aggressive form of cancer. Interestingly, the modified version of DEFA4 fragment (1-11) was potent and efficient against antibiotic-resistant bacteria. This review provides a general background abSaudi Arabia out DEFA4 and sheds light on changes in DEFA4 gene expression in different diseases. The paper also discusses other aspects related to DEFA4 as an antimicrobial and antiviral agent. The research was conducted based on available articles obtained from databases starting from 1988 to the present.

Identification of a Potential miRNA-mRNA Regulatory Network Associated With the Prognosis of HBV-ACLF

Background

Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is a life-threatening disease with a high mortality rate; the systemic inflammatory response plays a vital role in disease progression. We aimed to determine if a miRNA–mRNA co-regulatory network exists in the peripheral blood mononuclear cells (PBMCs) of HBV-ACLF patients, which might be important for prognosis.

Methods

Transcriptome-wide microRNA (miRNA) and mRNA microarrays were used to define the miRNA and mRNA expression profiles of the PBMCs of HBV-ACLF patients in a discovery cohort. The targets of the miRNAs were predicted. We built a miRNA-mRNA regulatory network through bioinformatics analysis, and used quantitative real-time polymerase chain reaction (qRT-PCR) to assess the importance of candidate miRNAs and mRNAs. We also assessed the direct and transcriptional regulatory effects of miRNAs on target mRNAs using a dual-luciferase reporter assay.

Results

The miRNA/mRNA PBMC expression profiles of the discovery cohort, of whom eight survived and eight died, revealed a prognostic interactive network involving 38 miRNAs and 313 mRNAs; this was constructed by identifying the target genes of the miRNAs. We validated the expression data in another cohort, of whom 43 survived and 35 died; miR-6840-3p, miR-6861-3p, JADE2, and NR3C2 were of particular interest. The levels of miR-6840-3p and miR-6861-3p were significantly increased in the PBMCs of the patients who died, and thus predicted prognosis (areas under the curve values = 0.665 and 0.700, respectively). The dual-luciferase reporter assay indicated that miR-6840-3p directly targeted JADE2.

Conclusion

We identified a prognostic miRNA-mRNA co-regulatory network in the PBMCs of HBV-ACLF patients. miR-6840-3p-JADE2 is a potential miRNA–mRNA pair contributing to a poor prognosis.

N-myc and STAT interactor correlates with severity and prognosis in acute-on-chronic liver failure of hepatitis B virus

BACKGROUND AND AIM

Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is characterized by acute deterioration of chronic liver disease with excessive inflammation. N-myc and STAT interactor (NMI), an inflammation-mediated protein, involves in various inflammatory-related diseases, but the role of NMI in development and prognosis in HBV-ACLF remains to be elucidated.

METHODS

Serum NMI from healthy controls (HCs, n = 20), chronic hepatitis B (CHB, n = 50) patients, and HBV-ACLF patients (n = 50) was determined using ELISA. NMI from peripheral blood mononuclear cells and liver was confirmed using quantitative real-time polymerase chain reaction, Western blot, and immunofluorescence.

RESULTS

Serum NMI was increased 1.9-fold or 2.2-fold from HBV-ACLF patients compared with that from HCs (P < 0.01) or CHB patients (P < 0.01). Consistently, NMI from peripheral blood mononuclear cells was upregulated significantly from HBV-ACLF patients compared with that from HCs and CHB patients at mRNA and protein levels. Hepatic NMI from HBV-ACLF patients was 2.8-fold higher than that from HCs. Serum NMI was correlated with Model for End-stage Liver Disease, Chronic Liver Failure Consortium ACLF score, and ACLF grades. In contrast, serum NMI was significantly decreased in HBV-ACLF ameliorated patients during follow-up, whereas serum NMI was sustained at high levels in non-ameliorated patients. Elevated serum NMI (≥ 198.5 pg/mL) was correlated with poor survival rate of HBV-ACLF patients. Using receiver operating characteristics curves, it was suggested that serum NMI was a potential biomarker in predicting 3-month mortality of HBV-ACLF patients.

CONCLUSIONS

Our study highlights the potential role of NMI in assessing the development and prognosis of HBV-ACLF.

The Effect of Modified Sini Decoction on Survival Rates of Patients with Hepatitis B Virus Related Acute-on-Chronic Liver Failure

Aim of the Study. To verify the effect of modified sini decoction on patients with hepatitis B virus related acute-on-chronic liver failure. Materials and Methods. A retrospective cohort study was conducted. Patients who had been treated with modified sini decoction and standard comprehensive internal medicine were assigned to an observation group, and patients who had been treated with standard comprehensive internal medicine were selected as a control group. The total bilirubin (TBIL), albumin (ALB), alanine aminotransferase (ALT), prothrombin activity (PTA), CTP, and MELD scores were analyzed at weeks 4, 8, and 12 after treatment, respectively. Meanwhile, the 12-week survival rate was analyzed. Results. The levels of TBIL and ALT were remarkably decreased, while the levels of ALB and PTA were remarkably increased in both groups at weeks 4, 8, and 12 after treatment, respectively, but the effects in the observation group were greater (P < 0.05). The CTP and MELD scores at 8-week and 12-week were lower in the observation group than in the control group (P < 0.05). At 12 weeks, the mean survival times of the observation group and the control group were 66.7 and 45.5 d, respectively. Significant improvement of 12-week survival rate [39/62 (62.9%) versus 18/50 (36.0%), P = 0.001] was observed in the observation group after treatment. Conclusions. Modified sini decoction could protect the liver function and improve the survival rates of patients with hepatitis B virus related acute-on-chronic liver failure.

Transcriptome analysis of peripheral blood mononuclear cells from chronic hepatitis B and hepatocellular carcinoma patients: a network-based attitude

Aim: The aim of the study was constructing a protein–protein interaction network for chronic hepatitis B (CHB) and hepatocellular carcinoma (HCC) patients. Materials & methods: Comprehensive gene expression profile of peripheral blood mononuclear cells of CHB and HCC were obtained from Gene Expression Omnibus/NCBI database. Differentially expressed genes (DEGs) of samples were analyzed using GEO2R web application. Results: The majority of DEGs in both CHB and HCC has been enriched in immune system responses. However, there was a significant disparity between the enrichment of these genes (especially genes associated with Toll-like receptor-and-TNF) in CHB-HCC compared with normal-CHB. Conclusion: The transcriptome properties of peripheral blood mononuclear cells are changed in patients with HBV-HCC. The immune response genes are the most deregulated genes in HCC patients.

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