Non-alcoholic fatty liver disease (NAFLD) is a prevalent liver disorder with no approved pharmacological therapies. Linghe granules, a hospital-based formulation derived from a classic prescription, have demonstrated potential in reducing hepatic fat accumulation and improving metabolic health. This study provides a novel, comprehensive assessment of Linghe granules, integrating clinical, preclinical, and molecular analyses for NAFLD management.

This study aims to evaluate the therapeutic efficacy of Linghe granules in alleviating NAFLD through an integrated approach.

A clinical trial involving 40 patients with NAFLD was conducted, with participants divided into a control group (lifestyle interventions) and a treatment group (lifestyle interventions plus oral Linghe granules). Various metabolic and liver function indicators were assessed before and after treatment. Additionally, a high-fat diet (HFD) was used to induce a NAFLD model in rat, followed by treatment with different doses of Linghe granules. In vitro studies on HepG2 and L02 cells were performed to the effects of the granules on lipid metabolism. Transcriptomic profiling, Weighted Gene Co-expression Network Analysis (WGCNA), Dynamic Network Biomarkers (DNB) analysis, and molecular docking were employed to explore the underlying mechanisms.

Linghe granules led to significant reductions in BMI, liver enzymes (AST, ALT), triglycerides, LDL-C, and GGT in patients with NAFLD, accompanied by a notable decrease in hepatic fat accumulation. In the rat model, treatment improved liver weight, liver function, and lipid metabolism. In vitro, Linghe granules decreased lipid accumulation and regulated key lipid metabolism markers, including sterol regulatory element-binding protein 1 (SREBP-1), stearoyl-CoA desaturase 1 (SCD1), and fatty acid-binding protein 5 (FABP5). Mechanistic analyses revealed that Linghe granules modulated oxidative stress-related pathways and genes involved in lipid metabolism.

This study represents the first integrated evaluation of Linghe granules' efficacy and mechanisms in treating NAFLD, demonstrating their potential to improve liver function, reduce lipid accumulation, and modulate key metabolic markers. These results suggest that Linghe granules may serve as an effective adjunctive treatment for NAFLD.

Background: Obesity is associated with higher 90-day mortality compared to nonobese surgical patients. Bariatric surgery (BS) can reduce obesity-related comorbidities, even in those with persistent obesity. Objective: Evaluate the impact of prior BS on sepsis outcomes in surgical patients with obesity. Setting: University Hospital, United States. Methods: A single-institution retrospective review of all surgical patients with sepsis (SOFA≥2) was conducted. Patients were grouped into people with obesity and prior BS (OB/BS; n = 48), people with obesity without BS (OB; n = 717), nonobese (NOB; n = 574), and nonobese with prior BS (NOB/BS; n = 27). Demographic data, comorbidities, and sepsis presentation were compared. The primary outcome was cumulative 90-day mortality and survival. Results: Most OB/BS patients underwent gastric bypass <5 years from admission (61%). The OB/BS group was younger, more likely to be female, and transferred from an outside hospital. The mean BMI was highest in the OB/BS group (46.3± 14.7 kg/m 2 , P < 0.0005). Charlson Comorbidity Index was lower in the OB/BS and NOB/BS groups (2 (1-4) and 2 (2-4), respectively, P = 0.0033). Cumulative 90-day mortality was significantly lower in the OB/BS cohort (20.8%, P = 0.002). The OB/BS cohort was more likely to die from intra-abdominal sepsis not amenable to source control (60% vs. 22.5% vs. 22.8% vs. 37.5%, P = 0.04). Compared to the other groups, 90-day survival was highest in the OB/BS cohort (log-rank P < 0.009). Conclusions: This study demonstrated improvement in 90-day survival in OB/BS patients despite higher BMIs. However, this group was more likely to die from intra-abdominal sources, likely reflecting surgical complexity in the setting of prior bypasses.

Metabolic associated steatohepatitis (MASH) represents a severe subtype of metabolic associated fatty liver disease (MASLD), with an increased risk of progression to cirrhosis and hepatocellular carcinoma. The nomenclature shift from nonalcoholic steatohepatitis (NASH)/nonalcoholic fatty liver disease (NAFLD) to MASH/MASLD, underscores the pivotal role of metabolic factors in disease progression. Diagnosis of MASH currently hinges on liver biopsy, a procedure whose invasive nature limits its clinical utility. This study aims to identify and validate metabolism-related genes (MRGs) markers for the non-invasive diagnosis of MASH.

This study extracted multiple datasets from the GEO database to identify metabolism-related differentially expressed genes (MRDEGs). Protein-Protein Interaction (PPI) network and machine learning algorithms, including Least Absolute Shrinkage and Selection Operator (LASSO) regression, Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Random Forest (RF), were applied to screen for signature MRDEGs. The diagnostic performance of these MRDEGs was evaluated using the Receiver Operating Characteristic (ROC) curve and further validated using independent external datasets. Additionally, enrichment analysis was performed to uncover key driver pathways in MASH. The infiltration levels of various immune cell types were assessed using single sample Gene Set Enrichment Analysis (ssGSEA). Finally, Spearman correlation analysis confirmed the association between signature genes and immune cells.

We successfully identified seven signature MRDEGs, including CYP7A1, GCK, AKR1B10, HPRT1, GPD1, FADS2, and ENO3, through PPI network analysis and machine learning algorithms. The gene model displayed exceptional diagnostic performance in the training and validation cohorts, as evidenced by the area under ROC curve (AUC) exceeding 0.9. Further enrichment analysis revealed that signature MEDEGs were primarily involved in multiple biological pathways related to glucose and lipid metabolism. Immune infiltration analysis indicated a significant increase in the infiltration levels of activated CD8 T cells, gamma-delta T cells, natural killer cells, and CD56bright NK cells in patients with MASH.

This study successfully identified seven signature MRDEGs as significant diagnostic biomarkers for MASH. The findings not only offer novel strategies for non-invasive diagnosis of MASH but also highlight the substantial role of immune cell infiltration in the progression of MASH.

Metabolic-dysfunction-associated steatohepatitis (MASH) remains a major health challenge. Herein, we identify sphingomyelin phosphodiesterase 3 (SMPD3) as a key driver of hepatic ceramide accumulation through increasing sphingomyelin hydrolysis at the cell membrane. Hepatocyte-specific Smpd3 gene disruption or pharmacological inhibition of SMPD3 alleviates MASH, whereas reintroducing SMPD3 reverses the resolution of MASH. Although healthy livers express low-level SMPD3, lipotoxicity-induced DNA damage suppresses sirtuin 1 (SIRT1), triggering an upregulation of SMPD3 during MASH. This disrupts membrane sphingomyelin-ceramide balance and promotes disease progression by enhancing caveolae-dependent lipid uptake and extracellular vesicle secretion from steatotic hepatocytes to exacerbate inflammation and fibrosis. Consequently, SMPD3 acts as a central hub integrating key MASH hallmarks. Notably, we discovered a bifunctional agent that simultaneously activates SIRT1 and inhibits SMPD3, which shows significant therapeutic potential in MASH treatment. These findings suggest that inhibition of hepatic SMPD3 restores membrane sphingolipid metabolism and holds great promise for developing novel MASH therapies.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is emerging as the leading cause of chronic liver disease worldwide, reflecting the global epidemics of obesity, metabolic syndrome, and type 2 diabetes. Beyond its strong association with excess adiposity, MASLD encompasses a heterogeneous population that includes individuals with normal body weight ("lean MASLD") highlighting the complexity of its pathogenesis. This disease results from a complex interplay between genetic susceptibility, epigenetic modifications, and environmental factors, which converge to disrupt metabolic homeostasis. Adipose tissue dysfunction and insulin resistance trigger an overflow of lipids to the liver, leading to mitochondrial dysfunction, oxidative stress, and hepatocellular injury. These processes promote hepatic inflammation and fibrogenesis, driven by cross talk among hepatocytes, immune cells, and hepatic stellate cells, with key contributions from gut-liver axis perturbations. Recent advances have unraveled pivotal molecular pathways, such as transforming growth factor-β signaling, Notch-induced osteopontin, and sphingosine kinase 1-mediated responses, that orchestrate fibrogenic activation. Understanding these interconnected mechanisms is crucial for developing targeted therapies. This review integrates current knowledge on the pathophysiology of MASLD, emphasizing emerging concepts such as lean metabolic dysfunction-associated steatohepatitis (MASH), epigenetic alterations, hepatic extracellular vesicles, and the relevance of extrahepatic signals. It also discusses novel therapeutic strategies under investigation, aiming to provide a comprehensive and structured overview of the evolving MASLD landscape for both basic scientists and clinicians.

Injured or reactive biliary epithelial cells participate in most chronic liver injuries in a process referred to as ductular reaction, which involves multicellular interactions with marked local infiltration of macrophages and fibrogenic cell activation. The direct roles of biliary epithelial cells in shaping their cellular niche remain unknown.

We aimed at investigating the effects of biliary epithelial cell-derived acute phase response protein orosomucoid 2 (ORM2) in shaping monocyte/macrophage response to liver injury.

Transcriptome data sets from human and mouse livers were used, results were confirmed with multiplex immunofluorescence. A multicellular biliary-niche-on-a-chip derived from primary liver and blood cells (wild-type, Mdr2 -/- mice) was established to model ductular reaction. Human blood cells collected from healthy donors and intrahepatic cholangiocyte organoids derived from normal and cirrhotic liver patients were used.

Our transcriptome data set and multiplex immunofluorescence analyses indicated a previously unrecognised involvement of the acute phase response protein ORM2 in ductular reactions in both human and mouse livers. ORM2 gene expression was increased in biliatresone-challenged, bile acid-challenged and acetaminophen-challenged cholangiocytes. Cholangiocyte-derived ORM2 induced unique transcriptome changes and functional adaptation of liver macrophages. ORM2-activated macrophages exacerbated cholangiocyte cell stress and Orm2 expression, but also tended to promote fibrogenic activation of hepatic stellate cells. Mechanistically, ORM2 effects were mediated by an inositol 1,4,5-trisphosphate receptor type 2-dependent calcium pathway.

This study reveals a paracrine communication circuit during ductular reaction, in which reactive cholangiocyte-derived ORM2 reprogrammes liver macrophages, participating in a pathogenic remodelling of the immune biliary niche.

Understanding disease progression is crucial for detecting critical transitions and finding trigger molecules, facilitating early diagnosis interventions. However, the high dimensionality of data and the lack of aligned samples across disease stages have posed challenges in addressing these tasks. We present a computational framework, Gaussian Graphical Optimal Transport (GGOT), for analyzing disease progressions. The proposed GGOT uses Gaussian graphical models, incorporating protein interaction networks, to characterize the data distributions at different disease stages. Then we use population-level optimal transport to calculate the Wasserstein distances and transport between stages, enabling us to detect critical transitions. By analyzing the per-molecule transport distance, we quantify the importance of each molecule and identify trigger molecules. Moreover, GGOT predicts the occurrence of critical transitions in unseen samples and visualizes the disease progression process. We apply GGOT to the simulation dataset and six disease datasets with varying disease progression rates to substantiate its effectiveness. Compared to existing methods, our proposed GGOT exhibits superior performance in detecting critical transitions.

As a chronic condition, liver fibrosis is characterized by diverse etiological factors, and the pivotal event to its pathogenesis is the activation of quiescent hepatic stellate cells (HSCs) into myofibroblasts. Mesenchyme homeobox 1 (MEOX1) is a transcription factors central to cellular development and differentiation. However, the role of MEOX1 signaling in hepatic fibrosis still remains largely unknown. In this study, we investigated the potential role and mechanism of MEOX1 in liver fibrosis using different models in vivo and in vitro. The hepatic expression of MEOX1 exhibited a positive correlation with the degree of fibrosis in patients diagnosed with non-alcoholic steatohepatitis (NASH), as determined through bioinformatics analysis. Furthermore, MEOX1 demonstrated high expression levels in activated HSCs and fibrotic liver tissues induced by methionine and choline-deficient diet (MCD), thioacetamide (TAA), or carbon tetrachloride (CCl4) treatment in C57/BL6 mice. Mechanistically, MEOX1 facilitated HSC activation, proliferation, and migration. The comprehensive analysis of transcriptome sequencing and chromatin immunoprecipitation sequencing data revealed that connective tissue growth factor (CTGF) served as a target gene for MEOX1 in HSCs. Specifically, MEOX1 bound to the promoter region of CTGF and enhanced its transcriptional activity, thereby mediating the exacerbating effect of MEOX1 on hepatic fibrosis. In conclusion, our current findings elucidate the role of MEOX1 in exacerbating hepatic fibrosis progression through transcriptional activation of CTGF. Our findings provide valuable insights into the therapeutic potential of targeting MEOX1 for the treatment of hepatic fibrosis.

Hepatic deletion of methionine adenosyltransferase-1a (Mat1a) in mice reduces S-adenosylmethionine (SAMe), a key methyl donor essential for many biological processes, which promotes the development and progression of metabolic dysfunction-associated steatotic liver disease (MASLD). Hyperglycemia and reduced MAT1A expression, along with low SAMe levels, are common in MASLD patients. This study explores how Mat1a-knockout (KO) hepatocytes respond to prolonged high glucose conditions, focusing on glucose metabolism and lipid accumulation. Hepatocytes from methionine adenosyltransferase-1a-knockout (Mat1a-KO) mice were incubated in high glucose conditions overnight, allowing for analysis of key metabolic intermediates and gene expression related to glycolysis, gluconeogenesis, glyceroneogenesis, phospholipid synthesis, and very low density lipoprotein (VLDL) secretion. SAMe deficiency in Mat1a-KO hepatocytes led to reduced protein methyltransferase-1 activity, resulting in increased expression of glycolytic enzymes (glucokinase, phosphofructokinase, and pyruvate kinase) and decreased expression of gluconeogenic enzymes (phosphoenolpyruvate carboxykinase, fructose-1,6-bisphosphatase, and glucose-6-phosphatase). These alterations led to a reduction in dihydroxyacetone phosphate (DHAP), which subsequently inhibited mammalian target of rapamycin complex 1 (mTORC1) activity. This inhibition resulted in decreased phosphatidylcholine synthesis via the CDP-choline pathway and impaired VLDL secretion, ultimately causing lipid accumulation. Thus, under high glucose conditions, SAMe deficiency in hepatocytes depletes DHAP, inhibits mTORC1 activity, and promotes lipid buildup.

Metabolic dysfunction-associated steatotic liver disease (MASLD), is one of the most common chronic liver diseases, which encompasses a spectrum of diseases, from metabolic dysfunction-associated steatotic liver (MASL) to metabolic dysfunction-associated steatohepatitis (MASH), and may ultimately progress to MASH-related cirrhosis and hepatocellular carcinoma (HCC). MASLD is a complex disease that is influenced by genetic and environmental factors. Dysregulation of hepatic lipid metabolism plays a crucial role in the development and progression of MASLD. Therefore, the focus of this review is to discuss the links between the genetic variants and DNA methylation of lipid metabolism-related genes and MASLD pathogenesis. We first summarize the interplay between MASLD and the disturbance of hepatic lipid metabolism. Next, we focus on reviewing the role of hepatic lipid related gene loci in the onset and progression of MASLD. We summarize the existing literature around the single nucleotide polymorphisms (SNPs) associated with MASLD identified by genome-wide association studies (GWAS) and candidate gene analyses. Moreover, based on recent evidence from human and animal studies, we further discussed the regulatory function and associated mechanisms of changes in DNA methylation levels in the occurrence and progression of MASLD, with a particular emphasis on its regulatory role of lipid metabolism-related genes in MASLD and MASH. Furthermore, we review the alterations of hepatic DNA and blood DNA methylation levels associated with lipid metabolism-related genes in MASLD and MASH patients. Finally, we introduce potential value of the genetic variants and DNA methylation profiles of lipid metabolism-related genes in developing novel prognostic biomarkers and therapeutic targets for MASLD, intending to provide references for the future studies of MASLD.

Metabolic dysfunction-associated steatotic liver diseases (MASLD), also known as non-alcoholic fatty liver diseases (NAFLD), have become a leading risk factor for hepatocellular carcinoma (HCC) in Western countries. NAFLD progresses from simple steatosis to HCC, with advanced liver fibrosis (ALF) and metabolic dysfunction-associated steatohepatitis (MASH) or non-alcoholic steatohepatitis (NASH) representing the two preceding high-risk stages.

We analysed changes in the DNA methylation landscape from simple steatosis to ALF or NASH and determined their relevance in gene regulation and HCC survival. Methylomic datasets generated from applying the Illumina 450K BeadChip on human MASLD/NAFLD liver samples were analysed using integrative data analyses to identify differentially methylated regions (DMRs) associated with ALF (F3/4 vs. F0/1) or non-fibrotic NASH (NASH-F0/1 vs. NAFLD-F0/1).

Gene Set Enrichment Analysis (GSEA) of genes associated with fibrosis-DMRs showed enrichment in xenobiotic metabolism, UV response and hypoxia pathways. Expression of 25 DMR-associated genes showed significant associations with HCC survival outcomes, including 16 genes with fibrosis-DMRs and 2 with NASH-DMRs mapped to their promoter regions. Binding motifs of seven transcription factors (TFs) were enriched in fibrosis-DMRs. Four DMR-associated genes (ESR1, TYW3, CLGN and TUBB) displayed an inverse relationship between promoter methylation and gene expression during human MASLD progression, which was further validated in a mouse MASLD model.

We propose a model in which changes in promoter DNA methylation during NAFLD progression regulate gene expression, impacting HCC survival outcomes.

Given the obesity epidemic and the prevalence of comorbidities, there is an ongoing need to understand the health consequences of this disease state better. Understanding gene expression signals will facilitate the identification of mechanisms of kidney and liver dysfunction/disease often present in individuals with obesity. qPCR is the standard method for studying changes in relative gene expression. Reference genes (RGs) are obligatory for accurately normalizing mRNA transcript levels across samples. Despite the prevalence of qPCR, the reliability of the data is often compromised because RGs are still used without validation or have proven to be unstable in different tissues and various diseases. In this study, we validated seven reference genes (ACTB, B2M, RPLP0, HPRT1, GAPDH, 18S rRNA, and PPIA) using human liver tissue from 15 lean individuals and 17 individuals with a BMI ≥ 25 and human kidney tissue from 13 lean individuals and 15 individuals with a BMI ≥ 25. Cross-validation of expression stability was performed using the RefFinder platform with four algorithms: NormFinder, BestKeeper, geNorm, and the comparative ΔCt method. In obesity-related studies, the most suitable reference genes in gene expression studies are RPLP0 and HPRT1 in human kidney tissue and RPLP0 and GAPDH in the liver.

The global prevalence of non-alcoholic fatty liver disease (NAFLD) is approximately 30%, and the condition can progress to non-alcoholic steatohepatitis, cirrhosis, and hepatocellular carcinoma. Metabolic and bariatric surgery (MBS) has been shown to be effective in treating obesity and related disorders, including NAFLD.

In this study, comprehensive machine learning was used to identify biomarkers for precise treatment of NAFLD from the perspective of MBS.

Differential expression and univariate logistic regression analyses were performed on lipid metabolism-related genes in a training dataset (GSE83452) and two validation datasets (GSE106737 and GSE48452) to identify consensus-predicted genes (CPGs). Subsequently, 13 machine learning algorithms were integrated into 99 combinations; among which the optimal combination was selected based on the total score of the area under the curve, accuracy, F-score, and recall in the two validation datasets. Hub genes were selected based on their importance ranking in the algorithms and the frequency of their occurrence. Finally, a mouse model of MBS was established, and the mRNA expression of the hub genes was validated via quantitative PCR.

A total of 12 CPGs were identified after intersecting the results of differential expression and logistic regression analyses on a Venn diagram. Four machine learning algorithms with the highest total scores were identified as optimal models. Additionally, PPARA, PLIN2, MED13, INSIG1, CPT1A, and ALOX5AP were identified as hub genes. The mRNA expression patterns of these genes in mice subjected to MBS were consistent with those observed in the three datasets.

Altogether, the six hub genes identified in this study are important for the treatment of NAFLD via MBS and hold substantial promise in guiding personalized treatment of NAFLD in clinical settings.

Up to 50-70% of patients with liver cirrhosis develop hepatic encephalopathy (HE), which is closely related to gut microbiota dysbiosis, with an unclear mechanism. Here, by constructing gut-brain modules to assess bacterial neurotoxins from metagenomic datasets, we found that phenylalanine decarboxylase (PDC) genes, mainly from Ruminococcus gnavus, increased approximately tenfold in patients with cirrhosis and higher in patients with HE. Cirrhotic, not healthy, mice colonized with R. gnavus showed brain phenylethylamine (PEA) accumulation, along with memory impairment, symmetrical tremors and cortex-specific neuron loss, typically found in patients with HE. This accumulation of PEA was primarily driven by decreased monoamine oxidase-B activity in both the liver and serum due to cirrhosis. Targeting PDC or PEA reversed the neurological symptoms induced by R. gnavus. Furthermore, fecal microbiota transplantation from patients with HE to germ-free cirrhotic mice replicated these symptoms and further corroborated the efficacy of targeting PDC or PEA. Clinically, high baseline PEA levels were linked to a sevenfold increased risk of HE after intrahepatic portosystemic shunt procedures. Our findings expand the understanding of the gut-liver-brain axis and identify a promising therapeutic and predictive target for HE.

The incidence of metabolic dysfunction-associated steatohepatitis (MASH) is increasing annually. MASH can progress to cirrhosis and hepatocellular carcinoma. However, the early diagnosis of MASH is challenging.

To screen prospective biomarkers for MASH and verify their effectiveness through in vitro and in vivo experiments.

Microarray datasets (GSE89632, GSE48452, and GSE63067) from the Gene Expression Omnibus database were used to identify differentially expressed genes (DEGs) between patients with MASH and healthy controls. Machine learning methods such as support vector machine recursive feature elimination and least absolute shrinkage and selection operator were utilized to identify optimum feature genes (OFGs). OFGs were validated using the GSE66676 dataset. CIBERSORT was utilized to illustrate the variations in immune cell abundance between patients with MASH and healthy controls. The correlation between OFGs and immune cell populations was evaluated. The OFGs were validated at both transcriptional and protein levels.

Initially, 37 DEGs were identified in patients with MASH compared with healthy controls. In the enrichment analysis, the DEGs were mainly related to inflammatory responses and immune signal-related pathways. Subsequently, using machine learning algorithms, five genes (FMO1, PEG10, TP53I3, ME1, and TRHDE) were identified as OFGs. The candidate biomarkers were validated in the testing dataset and through experiments with animal and cell models. The malic enzyme (ME1) gene (HGNC:6983) expression was significantly upregulated in MASH samples compared to controls (0.4353 ± 0.2262 vs. -0.06968 ± 0.3222, p = 0.00076). Immune infiltration analysis revealed a negative correlation between ME1 expression and plasma cells (R = -0.77, p = 0.0033).

This study found that ME1 plays a regulatory role in early MASH, which may affect disease progression by mediating plasma cells and T cells gamma delta to regulate immune microenvironment. This finding provides a new idea for the early diagnosis, monitoring and potential therapeutic intervention of MASH.

The global rise in Metabolic dysfunction-associated steatotic liver disease (MASLD)/Metabolic dysfunction-associated steatohepatitis (MASH) highlights the urgent necessity for noninvasive biomarkers to detect these conditions early. To address this, we endeavored to construct a diagnostic model for MASLD/MASH using a combination of bioinformatics, molecular/biochemical data, and machine learning techniques. Initially, bioinformatics analysis was employed to identify RNA molecules associated with MASLD/MASH pathogenesis and enriched in ferroptosis and exophagy. This analysis unveiled specific networks related to ferroptosis (GPX4, LPCAT3, ACSL4, miR-4266, and LINC00442) and exophagy (TSG101, HGS, SNF8, miR-4498, miR-5189-5p, and CTBP1-AS2). Subsequently, serum samples from 400 participants (151 healthy, 150 MASH, and 99 MASLD) underwent biochemical and molecular analysis, revealing significant dyslipidemia, impaired liver function, and disrupted glycemic indicators in MASLD/MASH patients compared to healthy controls. Molecular analysis indicated increased expression of LPCAT3, ACSL4, TSG101, HGS, and SNF8, alongside decreased GPX4 levels in MASH and MASLD patients compared to controls. The expression of epigenetic regulators from both networks (miR-4498, miR-5189-5p, miR-4266, LINC00442, and CTBP1-AS2) significantly differed among the studied groups. Finally, supervised machine learning models, including Neural Networks and Random Forest, were applied to molecular signatures and clinical/biochemical data. The Random Forest model exhibited superior performance, and molecular features effectively distinguished between the three studied groups. Clinical features, particularly BMI, consistently served as discriminatory factors, while biochemical features exhibited varying discriminant behavior across MASH, MASLD, and control groups. Our study underscores the significant potential of integrating diverse data types to enable early detection of MASLD/MASH, offering a promising approach for non-invasive diagnostic strategies.

Obesity is attributed to a combination of factors such as lifestyle, environmental influences, and genetic background. Nowadays, the issue of obesity has grown to an epidemic scale. Environmental changes, having contributed to the sharp rise in obesity prevalence, are not the only contributing etiologic factors. Inherent biological variables interact with environmental factors resulting in obesity. Epigenetic mechanisms may explain part of obesity heritability. One of the recently discovered epigenetic mechanisms for controlling gene expression is long non-coding RNAs (lncRNAs). Circulating lncRNA p5549 and p19461 levels were reported to be significantly lower in individuals with obesity. This study aimed to evaluate whether weight loss following metabolic/bariatric surgery (MBS) can be related to altered expression levels of those lncRNAs, which have been reported to be reduced in individuals with obesity.

Comparison of circulating levels of lncRNA p5549 and p19461 before and 12 weeks after MBS in thirty-four patients was conducted to evaluate whether MBS can revert the altered levels of these lncRNAs. None of the participating patients were lost to follow-up, and all underwent re-evaluation of post-surgical expression levels.

lncRNA p5549 expression levels in serum were found to increase significantly in the postoperative samples compared to preoperative samples (fold increase: 4.63 ± 7.68, p = 0.014).

Epigenetic changes in patients with obesity, specifically lncRNA-p5549 expression levels, are reversed after MBS. The postoperative increase in the expression levels of lncRNA- p19461 was not statistically significant.

The ability to accurately quantify biological age could help monitor and control healthy aging. Epigenetic clocks have emerged as promising tools for estimating biological age, yet they have been developed from heterogeneous bulk tissues, and are thus composites of two aging processes, one reflecting the change of cell-type composition with age and another reflecting the aging of individual cell-types. There is thus a need to dissect and quantify these two components of epigenetic clocks, and to develop epigenetic clocks that can yield biological age estimates at cell-type resolution. Here we demonstrate that in blood and brain, approximately 39% and 12% of an epigenetic clock's accuracy is driven by underlying shifts in lymphocyte and neuronal subsets, respectively. Using brain and liver tissue as prototypes, we build and validate neuron and hepatocyte specific DNA methylation clocks, and demonstrate that these cell-type specific clocks yield improved estimates of chronological age in the corresponding cell and tissue-types. We find that neuron and glia specific clocks display biological age acceleration in Alzheimer's Disease with the effect being strongest for glia in the temporal lobe. Moreover, CpGs from these clocks display a small but significant overlap with the causal DamAge-clock, mapping to key genes implicated in neurodegeneration. The hepatocyte clock is found accelerated in liver under various pathological conditions. In contrast, non-cell-type specific clocks do not display biological age-acceleration, or only do so marginally. In summary, this work highlights the importance of dissecting epigenetic clocks and quantifying biological age at cell-type resolution.

Previous studies have reported an association between telomere length and non-alcoholic fatty liver disease (NAFLD). This study aimed to explore the involvement of alternative lengthening of telomere-related genes (ALTRGs) in the pathology of NAFLD, construct a risk signature, and evaluate both treatment and prognosis. Three NAFLD datasets (GSE48452, GSE89632, and GSE63067) were collected from the GEO database and merged into combined GEO datasets. ALTRGs were collected from GeneCards and PubMed databases. Differentially expressed genes (DEGs) were identified, and functional enrichment analysis was performed. This study employed a support vector machine algorithm and least absolute shrinkage and selection operator regression analysis to identify key genes for constructing a diagnostic model. High- and low-risk groups were identified from the combined GEO datasets using the diagnostic model. Gene set enrichment analysis, regulatory network analysis, and intergroup immune infiltration analysis were performed. This study identified the key genes using receiver operating characteristic and Friends analysis. Expression of these genes was validated in a mouse model of NAFLD. Twenty-five genes were differentially expressed, with a positive correlation between FOS and EGR1 and a negative correlation between MYC and CEBPA. A diagnostic model was constructed using 12 genes, and high- and low-risk groups were identified. CAMK2G, ERBB2, FOSB, WT1, and CEBPA showed certain accuracy, and their expression levels were significantly different in the model. Immune infiltration analysis between the risk groups revealed that six immune cells were statistically significant. This includes a strong negative interaction between type 2 T helper cells and SPHK2 in the high-risk group. These findings suggest that ALTRDEGs are potential therapeutic targets and prognostic indicators for NAFLD. However, further investigations are required to elucidate the specific underlying mechanisms.

Being activated by deacetylation, peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α) has become an important regulator of metabolic-related diseases. The activation of Sirtuin 1 (Sirt1) by resveratrol was likely to deacetylate PGC-1α. However, the role of deacetylated PGC-1α in the alleviation of activated Sirt1 on type 2 diabetes mellitus (T2DM)-related fatty liver disease (FLD) remained unexplored. The aim of this study was to investigate the potential impact of Sirt1-mediated deacetylation of PGC-1α on T2DM-associated FLD and its underlying mechanisms. Our findings revealed that, along with the decreased Sirt1, the levels of acetylated PGC-1α were up-regulated in hepatocytes co-stimulated with high glucose (HG) and free fatty acids (FFA). Down-regulated Sirt1 inactivated PGC-1α by inhibiting its deacetylation, while activating Sirt1 improved hepatic injury by reducing lipid droplet accumulation through the deacetylation of PGC-1α. However, the beneficial effects of Sirt1 activation on hepatic steatosis were inhibited by PGC-1α antagonist in vitro. Mechanistically, activating Sirt1 enhanced mitochondrial function by promoting PGC-1α activity, thereby facilitating hepatic fatty acid oxidation (FAO). In conclusion, Sirt1-mediated deacetylation of PGC-1α mitigated hepatic lipotoxicity by enhancing mitochondrial FAO, which contributed to the restoration of mitochondrial function in T2DM. The activation of Sirt1-mediated PGC-1α deacetylation might represent a promising therapeutic approach for T2DM-associated FLD.

Non-invasive diagnostics for metabolic dysfunction-associated fatty liver disease (MAFLD) remain challenging. We aimed to identify novel key genes as non-invasive biomarkers for MAFLD, elucidate causal relationships between biomarkers and MAFLD and determine the role of immune cells as potential mediators.

Utilizing published transcriptome data of patients with biopsy-proven MAFLD, we applied linear models for microarray data, least absolute shrinkage and selector operation (LASSO) regressions and receiver operating characteristic (ROC) curve analyses to identify and validate biomarkers for MAFLD. Using the expression quantitative trait loci database and a cohort of 778 614 Europeans, we used Mendelian randomization to analyse the causal relationships between key biomarkers and MAFLD. Additionally, mediation analysis was performed to examine the involvement of 731 immunophenotypes in these relationships.

We identified 31 differentially expressed genes, and LASSO regression showed three hub genes, IGFBP2, PEG10, and P4HA1, with area under the receiver operating characteristic (AUROC) curve of 0.807, 0.772 and 0.791, respectively, for identifying MAFLD. The model of these three genes had an AUROC of 0.959 and 0.800 in the development and validation data sets, respectively. This model was also validated using serum-based enzyme-linked immunosorbent assay data from MAFLD patients and control subjects (AUROC: 0.819, 95% confidence interval: 0.736-0.902). PEG10 was associated with an increased MAFLD risk (odds ratio = 1.106, p = 0.032) via inverse variance-weighted analysis, and about 30% of this risk was mediated by the percentage of CD11c + CD62L- monocytes.

The MAFLD panels have good diagnostic accuracy, and the causal link between PEG10 and MAFLD was mediated by the percentage of CD11c + CD62L- monocytes.

Lipid homeostasis plays a pivotal role in cellular growth, necessitating the engagement of numerous lipid metabolism genes and the cohesive functioning of organelles. While the nucleus is traditionally recognized for its genetic roles, emerging evidence highlights its significant contribution to lipid homeostasis maintenance. Certain nuclear membrane proteins or associated proteins have the capacity to directly catalyze lipid synthesis or modification processes. Mutations in the genes encoding these proteins can lead to disrupted lipid metabolism, contributing to a spectrum of metabolic disorders. This article provides a comprehensive reviews of the investigations exploring the interplay between nuclear membrane proteins and lipid metabolism. Additionally, it delves into the heterogeneity of the nuclear membrane, positioning it as a novel therapeutic target for managing metabolic disorders and mitigating adverse drug reactions.

Metabolic dysfunction-associated liver disease (MASLD) and alcohol-associated liver disease (ALD) are among the leading causes of liver disease worldwide. The exact roles of epigenetic factors in both diseases remains largely unknown. In this context, liver DNA methylation remains a field that requires further exploration and understanding.

We performed a systematic review of liver DNA methylation in humans with MASLD or ALD using Ovid MEDLINE, Ovid Embase, and Cochrane Library. We included human studies where liver DNA methylation was assessed in patients with MASLD and/or ALD. The Rayyan platform was used to select studies. Risk of bias was assessed with the "risk of bias in non-randomized studies of interventions" tool, ROBINS-I. We performed pathway analysis using the most important differentially methylated genes selected in each article.

Fifteen articles were included in this systematic review. The risk of bias was moderate to serious in all articles and bias due to confounding and patient selection was high. Sixteen common pathways, containing differentially methylated genes, including cancer pathways, were identified in both diseases.

There are common pathways, containing differentially methylated genes, in ALD and MASLD, such as pathways in cancer and peroxisome proliferator-activated receptor (PPAR) signaling pathways. In MASLD, the insulin signaling pathway is one of the most important, and in ALD, the MAPK signaling pathway is the most important. Our study adds one more piece to the puzzle of the mechanisms involved in steatotic liver disease.

Non-alcoholic fatty liver disease (NAFLD) is a growing health problem worldwide, ranging from non-alcoholic fatty liver (NAFL) to the more severe metabolic non-alcoholic steatohepatitis (NASH). Although many studies have elucidated the pathogenesis of NAFLD, the epigenetic regulatory mechanism from NAFL to NASH remains incompletely understood. The histone H3 lysine 4 methyltransferase, MLL4 (also called KMT2D), is a critical epigenetic transcriptional coactivator that mediates overnutrition-induced steatosis in mice, but its potential role in the progression of NASH remains largely unknown. Here, we show that mice lacking the one allele of the Mll4 gene are resistant to hepatic steatosis, inflammation, and fibrosis in NASH conditions compared to wild-type controls. Transcriptome analysis of the livers of control and Mll4+/- mice identified pro-inflammatory genes regulated by the nuclear factor kappa B (NF-κB) signaling pathway as major target genes of MLL4. We show that MLL4 binds to p65 and that MLL4 is required for NF-κB transactivation. Myeloid-specific Mll4 knockout mice showed an almost complete block of NASH, while hepatocyte-specific Mll4 knockout mice showed mild inhibition of steatosis. Pro-inflammatory M1 polarization is decreased and anti-inflammatory M2 polarization is increased in liver macrophages from myeloid-specific Mll4 knockout mice. Importantly, we show that histone H3-lysine 4 methylation mediated by the MLL4-complex plays a critical role in promoting the expression of Ccl2 in hepatocytes and M1 marker genes in macrophages. Our results demonstrate that MLL4, through the NF-κB-MLL4 regulatory axis, exacerbates steatohepatitis in the context of an inflammatory response and represents a potential therapeutic target for NASH.

Non-alcoholic fatty liver disease (NAFLD) and ulcerative colitis (UC) are two common health issues that have gained significant global attention. Previous studies have suggested a possible connection between NAFLD and UC, but the underlying pathophysiology remains unclear. This study investigates common genes, underlying pathogenesis mechanisms, identification of diagnostic markers applicable to both conditions, and exploration of potential therapeutic targets shared by NAFLD and UC.

We obtained datasets for NAFLD and UC from the GEO database. The DEGs in the GSE89632 dataset of the NAFLD and GSE87466 of the UC dataset were analyzed. WGCNA, a powerful tool for identifying modules of highly correlated genes, was employed for both datasets. The DEGs of NAFLD and UC and the modular genes were then intersected to obtain shared genes. Functional enrichment analysis was conducted on these shared genes. Next, we utilize the STRING database to establish a PPI network. To enhance visualization, we employ Cytoscape software. Subsequently, the Cytohubba algorithm within Cytoscape was used to identify central genes. Diagnostic biomarkers were initially screened using LASSO regression and SVM methods. The diagnostic value of ROC curve analysis was assessed to detect diagnostic genes in both training and validation sets for NAFLD and UC. A nomogram was also developed to evaluate diagnostic efficacy. Additionally, we used the CIBERSORT algorithm to explore immune infiltration patterns in both NAFLD and UC samples. Finally, we investigated the correlation between hub gene expression, diagnostic gene expression, and immune infiltration levels.

We identified 34 shared genes that were found to be associated with both NAFLD and UC. These genes were subjected to enrichment analysis, which revealed significant enrichment in several pathways, including the IL-17 signaling pathway, Rheumatoid arthritis, and Chagas disease. One optimal candidate gene was selected through LASSO regression and SVM: CCL2. The ROC curve confirmed the presence of CCL2 in both the NAFLD and UC training sets and other validation sets. This finding was further validated using a nomogram in the validation set. Additionally, the expression levels of CCL2 for NAFLD and UC showed a significant correlation with immune cell infiltration.

This study identified a gene (CCL2) as a biomarker for NAFLD and UC, which may actively participate in the progression of NAFLD and UC. This discovery holds significant implications for understanding the progression of these diseases and potentially developing more effective diagnostic and treatment strategies.

DNA methylation is crucial for chromatin structure, transcription regulation and genome stability, defining cellular identity. Aberrant hypermethylation of CpG-rich regions is common in cancer, influencing gene expression. However, the specific contributions of individual epigenetic modifications to tumorigenesis remain under investigation. In hepatocellular carcinoma (HCC), DNA methylation alterations are documented as in other tumor types. We aimed to identify hypermethylated CpGs in HCC, assess their specificity across other tumor types, and investigate their impact on gene expression. To this end, public methylomes from HCC, other liver diseases, and 27 tumor types as well as expression data from TCGA-LIHC and GTEx were analyzed. This study identified 39 CpG sites that were hypermethylated in HCC compared to control liver tissue, and were located within promoter, gene bodies, and intergenic CpG islands. Notably, these CpGs were predominantly unmethylated in healthy liver tissue and other normal tissues. Comparative analysis with 27 other tumors revealed both common and HCC-specific hypermethylated CpGs. Interestingly, the HCC-hypermethylated genes showed minimal expression in the different healthy tissues, with marginal changes in the level of expression in the corresponding tumors. These findings confirm previous evidence on the limited influence of DNA hypermethylation on gene expression regulation in cancer. It also highlights the existence of mechanisms that allow the selection of tissue-specific methylation marks in normally unexpressed genes during carcinogenesis. Overall, our study contributes to demonstrate the complexity of cancer epigenetics, emphasizing the need of better understanding the interplay between DNA methylation, gene expression dynamics, and tumorigenesis.

The escalating obesity epidemic and aging population have propelled metabolic dysfunction-associated steatohepatitis (MASH) to the forefront of public health concerns. The activation of FXR shows promise to combat MASH and its detrimental consequences. However, the specific alterations within the MASH-related transcriptional network remain elusive, hindering the development of more precise and effective therapeutic strategies. Through a comprehensive analysis of liver RNA-seq data from human and mouse MASH samples, we identified central perturbations within the MASH-associated transcriptional network, including disrupted cellular metabolism and mitochondrial function, decreased tissue repair capability, and increased inflammation and fibrosis. By employing integrated transcriptome profiling of diverse FXR agonists-treated mice, FXR liver-specific knockout mice, and open-source human datasets, we determined that hepatic FXR activation effectively ameliorated MASH by reversing the dysregulated metabolic and inflammatory networks implicated in MASH pathogenesis. This mitigation encompassed resolving fibrosis and reducing immune infiltration. By understanding the core regulatory network of FXR, which is directly correlated with disease severity and treatment response, we identified approximately one-third of the patients who could potentially benefit from FXR agonist therapy. A similar analysis involving intestinal RNA-seq data from FXR agonists-treated mice and FXR intestine-specific knockout mice revealed that intestinal FXR activation attenuates intestinal inflammation, and has promise in attenuating hepatic inflammation and fibrosis. Collectively, our study uncovers the intricate pathophysiological features of MASH at a transcriptional level and highlights the complex interplay between FXR activation and both MASH progression and regression. These findings contribute to precise drug development, utilization, and efficacy evaluation, ultimately aiming to improve patient outcomes.

This study investigates the effects of bariatric surgery on non-alcoholic fatty liver disease (NAFLD) by examining the interplay between gut microbiota, epigenetics, and metabolic health. A cohort of 22 patients undergoing sleeve gastrectomy (SG) was analyzed for changes in gut microbial composition and DNA methylation profiles before and six months after surgery. Correlations between gut microbial abundance and clinical markers at baseline revealed that certain genera were associated with worse metabolic health and liver markers. Following SG, significant improvements were observed in the clinical, anthropometric, and biochemical parameters of the NAFLD patients. Although alpha-diversity indices (i.e., Chao1, Simpson, Shannon) did not show significant changes, beta-diversity analysis revealed a slight shift in microbial composition (PERMANOVA, p = 0.036). Differential abundance analysis identified significant changes in specific bacterial taxa, including an increase in beneficial Lactobacillus species such as Lactobacillus crispatus and Lactobacillus iners and a decrease in harmful taxa like Erysipelotrichia. Additionally, DNA methylation analysis revealed 609 significant differentially methylated CpG sites between the baseline values and six months post-surgery, with notable enrichment in genes related to the autophagy pathway, such as IRS4 and ATG4B. The results highlight the individualized responses to bariatric surgery and underscore the potential for personalized treatment strategies. In conclusion, integrating gut microbiota and epigenetic factors into NAFLD management could enhance treatment outcomes, suggesting that future research should explore microbiome-targeted therapies and long-term follow-ups on liver health post-surgery.

Hepatic steatosis, the first step in the development of nonalcoholic fatty liver disease (NAFLD), is frequently observed in the aging population. However, the underlying molecular mechanism remains largely unknown. In this study, we first employed GSEA enrichment analysis to identify short-chain acyl-CoA dehydrogenase (SCAD), which participates in the mitochondrial β-oxidation of fatty acids and may be associated with hepatic steatosis in elderly individuals. Subsequently, we examined SCAD expression and hepatic triglyceride content in various aged humans and mice and found that triglycerides were markedly increased and that SCAD was upregulated in aged livers. Our further evidence in SCAD-ablated mice suggested that SCAD deletion was able to slow liver aging and ameliorate aging-associated fatty liver. Examination of the molecular pathways by which the deletion of SCAD attenuates steatosis revealed that the autophagic degradation of lipid droplets, which was not detected in elderly wild-type mice, was maintained in SCAD-deficient old mice. This was due to the decrease in the production of acetyl-coenzyme A (acetyl-CoA), which is abundant in the livers of old wild-type mice. In conclusion, our findings demonstrate that the suppression of SCAD may prevent age-associated hepatic steatosis by promoting lipophagy and that SCAD could be a promising therapeutic target for liver aging and associated steatosis.

Nonalcoholic steatohepatitis (NASH) has been an increasingly significant contributor to hepatocellular carcinoma (HCC). Understanding the progression from NASH to HCC is critical to early diagnosis and elucidating the underlying mechanisms.

5 significant prognostic genes related to NASH-HCC transformation were identified through algorithm selection, which were ME1, TP53I3, SOCS2, GADD45G and CYP7A1. A diagnostic model for NASH prediction was established (AUC=0.988). TP53I3 and SOCS2 were selected as potential critical genes in the progression of NASH-HCC by external dataset validation and in vitro experiments on NASH and HCC cell lines. Immune infiltration analysis illustrated the correlation between 5 significant prognostic genes and immune cells. Single-cell analysis identified hepatocytes related to NASH-HCC transformation markers, revealing their promoting role in the transformation from NASH to HCC.

With bulk-seq analysis and single-cell analysis, 5 significant prognostic genes related to NASH-HCC transformation were identified and validated at both dataset and in vitro experiment level. Among them, TP53I3 and SOCS2 might be potential critical genes in NASH-HCC progression. Single-cell analysis identified and revealed the critical role that NASH-HCC related hepatocytes play in NASH-HCC tansformation. Our research may introduce a new perspective to the diagnosis, treatment of NASH-related HCC.

Alterations in DNA methylation (DNAm) have been observed in patients with fatty liver, but whether they are cause or consequence remains unknown. The study aimed to investigate longitudinal association of epigenome-wide DNAm with liver fat content (LFC) in Chinese participants, and explore their temporal relationships.

Data were obtained from 2 waves over a four-year time period of the Shanghai Changfeng Study (discovery, n = 407 and replication, n = 126). LFC and peripheral blood DNAm were repeatedly measured using quantitative hepatic ultrasonography and the 850 K Illumina EPIC BeadChip, respectively. Longitudinal and cross-sectional epigenome-wide association studies (EWASs) were conducted with linear mixed model and linear regression model, respectively. Meta-analysis was performed using METAL. Cross-lagged panel analysis (CLPA) was carried out to infer temporal relationships between the significant CpGs and LFC.

Longitudinal EWAS identified cg11024682 (SREBF1), cg06500161 (ABCG1), cg16740586 (ABCG1), cg15659943 (ABCA1) and cg00163198 (SNX19) significantly associated with LFC with P < 1e-7. Another 6 of the 22 previously reported CpGs were replicated in the present longitudinal EWAS. CLPA showed longitudinal effects of cg11024682 (SREBF1) (β = 0.14 [0.06, 0.23]), cg16740586 (ABCG1) (β = 0.17 [0.08, 0.25]), cg06500161 (ABCG1) (β = 0.12 [0.03, 0.20]), cg17901584 (DHCR24) (β = -0.10 [-0.18, -0.02]), cg00574958 (CPT1A) (β = -0.09 [-0.17, -0.01]), cg08309687 (LINC00649) (β = -0.11 [-0.19, -0.03]), and cg27243685 (ABCG1) (β = 0.09 [0.01, 0.18]) on subsequent LFC. The effects were attenuated when further adjusting for body mass index. High levels of LFC led to alterations in DNAm of cg15659943 (ABCA1) (β = 0.13 [0.04, 0.21]), cg07162647 (β = -0.11 [-0.19, -0.03]), cg06500161 (ABCG1) (β = 0.10 [0.02, 0.18]), and cg27243685 (ABCG1) (β = 0.10 [0.02, 0.18]).

Blood DNAm at SREBF1, ABCG1, DHCR24, CPT1A, and LINC00649 may be predictors of subsequent LFC change. The effects of DNAm at SREBF1 and ABCG1 on LFC were partially influenced by obesity. The findings have potential implications in understanding disease pathogenesis and highlight the potential of DNAm for early detection or intervention of fatty liver.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a common liver disease associated with obesity and is caused by the accumulation of ectopic fat without alcohol consumption. Coxsackievirus and adenovirus receptor (CAR) are vital for cardiac myocyte-intercalated discs and endothelial cell-to-cell tight junctions. CAR has also been reported to be associated with obesity and high blood pressure. However, its function in the liver is still not well understood. The liver of obese mice exhibit elevated CAR mRNA and protein levels. Furthermore, in the liver of patients with non-alcoholic steatohepatitis, CAR is reduced in hepatocyte cell-cell junctions compared to normal levels. We generated liver-specific CAR knockout (KO) mice to investigate the role of CAR in the liver. Body and liver weights were not different between wild-type (WT) and KO mice fed a paired or high-fat diet (HFD). However, HFD induced significant liver damage and lipid accumulation in CAR KO mice compared with WT mice. Additionally, inflammatory cytokines transcription, hepatic permeability, and macrophage recruitment considerably increased in CAR KO mice. We identified a new interaction partner of CAR using a protein pull-down assay and mass spectrometry. Apolipoprotein B mRNA editing enzyme catalytic polypeptide-like 3C (APOBEC3C) demonstrated a complex relationship with CAR, and hepatic CAR expression tightly regulated its level. Moreover, Apolipoprotein B (ApoB) and Low-density lipoprotein receptor (LDLR) levels correlated with APOBEC3C expression in the liver of CAR KO mice, suggesting that CAR may regulate lipid accumulation by controlling APOBEC3C activity. In this study, we showed that hepatic CAR deficiency increased cell-to-cell permeability. In addition, CAR deletion significantly increased hepatic lipid accumulation by inducing ApoB and LDLR expression. Although the underlying mechanism is unclear, CARs may be a target for the development of novel therapies for MAFLD.

Proteostasis is vital for cellular health, with disruptions leading to pathologies including aging, neurodegeneration and metabolic disorders. Traditionally, proteotoxic stress responses were studied as acute reactions to various noxious factors; however, recent evidence reveals that many proteostasis stress-response genes exhibit ~12-hour ultradian rhythms under physiological conditions in mammals. These rhythms, driven by an XBP1s-dependent 12h oscillator, are crucial for managing proteostasis. By exploring the chromatin landscape of the murine 12h hepatic oscillator, we identified RBBP5, a key subunit of the COMPASS complex writing H3K4me3, as an essential epigenetic regulator of proteostasis. RBBP5 is indispensable for regulating both the hepatic 12h oscillator and transcriptional response to acute proteotoxic stress, acting as a co-activator for proteostasis transcription factor XBP1s. RBBP5 ablation leads to increased sensitivity to proteotoxic stress, chronic inflammation, and hepatic steatosis in mice, along with impaired autophagy and reduced cell survival in vitro. In humans, lower RBBP5 expression is associated with reduced adaptive stress-response gene expression and hepatic steatosis. Our findings establish RBBP5 as a central regulator of proteostasis, essential for maintaining mammalian organismal health.