Aug 2026· Endocrine, Metabolic & Immune Disorders - Drug Targets· Vol 26· 0 citations
Medicine
TL;DR
These findings bridge the gap between metabolic lipotoxicity and epigenetic regulation, suggesting that lactylation acts as a critical driver in NAFLD pathogenesis.
Abstract
Background
Nonalcoholic fatty liver disease (NAFLD) is characterized by profound metabolic reprogramming. Recent evidence suggests that lactate, beyond its role as a metabolic waste product, may modulate histone lactylation, linking metabolic stress to the epigenetic regulation of disease progression. However, the specific lactate-related gene (LRG) signatures driving NAFLD remain to be elucidated.
Methods
We integrated transcriptomic mining of the GSE164760 dataset with in vivo validation to decode the LRG landscape. Differentially expressed LRGs were identified using strict thresholds and subsequently intersected with the GeneCards database. Functional enrichment (GO/KEGG) and Protein-Protein Interaction (PPI) networks were constructed to screen for hub genes. Key biomarkers were subsequently corroborated in a high-fat diet (HFD)- induced rat NAFLD model via Western blotting.
Results
A total of 98 differentially expressed LRGs were identified, which were primarily enriched in molecular catabolism and xenobiotic stress responses. From this network, eight pivotal hub genes were distilled: CREBBP, EP300, HDAC1, HIF1A, PARP1, SIRT1, STAT3, and TP53. Diagnostic modeling demonstrated their predictive value, with AUC scores ranging from 0.60 to 0.81, among which PARP1 and STAT3 exhibited high diagnostic potential (AUC > 0.80). Experimental validation in the rat model confirmed the disruption of this metabolic-epigenetic regulatory module, revealing significant dysregulation in protein expression that reflects a compensatory stress response to lipotoxicity.
Discussion
These findings bridge the gap between metabolic lipotoxicity and epigenetic regulation, suggesting that lactylation acts as a critical driver in NAFLD pathogenesis.
Conclusion
This study delineates a preliminary, hypothesis-generating lactate-associated gene signature in NAFLD, highlighting a complex regulatory network governing hepatocyte metabolic plasticity and survival. These eight core biomarkers offer promising tissue-based targets for mechanistic intervention, though further validation in peripheral blood is required to establish their non-invasive diagnostic utility.
To determine lactate metabolism-associated biomarkers for non-alcoholic fatty liver disease (NAFLD). Based on NAFLD datasets from the gene expression omnibus database and lactate metabolism-related genes from GeneCards database, NAFLD-lactate metabolism hub genes (NAFLD-LM HGs) were screened via differential analysis, weighted gene co-expression network analysis and four machine learning algorithms. Their diagnostic efficacy was evaluated; molecular subtyping was performed; single-cell RNA sequencing (scRNA-seq) was subsequently conducted; and validation was finally conducted in NAFLD mouse models. We finally screened out eight NAFLD-LM HGs, namely CCAAT/enhancer-binding protein alpha (CEBPA), flavin containing dimethylaniline monooxygenase 1 (FMO1), insulin-like growth factor-binding protein 1 (IGFBP1), krüppel-like factor 4 (KLF4), low-density lipoprotein receptor (LDLR), myelocytomatosis oncogene (MYC), nuclear receptor subfamily 4 group A member 2 (NR4A2), and thymidylate synthase (TYMS), with a diagnostic rate of 0.798 and an area under the curve of 0.948. These genes drove the molecular heterogeneity in NAFLD patients by modulating of metabolism and immune microenvironment. The results of scRNA-seq clarified that Th17 cells were identified as the most abundant annotated cell subset. Through animal experiments, five genes (LDLR, MYC, IGFBP1, NR4A2, and KLF4) were established to have potential protective effects against NAFLD. Five genes (LDLR, MYC, IGFBP1, NR4A2, KLF4) are identified as "protective factors", and their downregulation is associated with NAFLD progression. The remaining three genes (CEBPA, FMO1, TYMS) exhibit inconsistent expression patterns, suggesting bidirectional regulation.
Xiao-Cui Wang, Xinhe Wang, Liang Zhao et al.· Clinical and Experimental Me...· 0 citations
Summary Kidney fibrosis, the final pathological outcome of chronic kidney disease, lacks reliable biomarkers, and the role of lactylation in its pathogenesis remains poorly defined. We integrated multi-omics, machine learning, and experimental validation to identify lactylation-associated biomarkers using two public transcriptomic datasets. After batch correction and differential expression analysis, 13 overlapping lactylation-modified genes were obtained, and eight hub genes were identified via 113 model combinations. Downregulated hub genes regulate core renal metabolic pathways including TCA cycle and oxidative phosphorylation, while upregulated genes mediate immune-inflammatory activation and cytokine signaling. Immune infiltration analysis showed significant immune cell enrichment in fibrotic tissues, with hub genes correlated with T cell subsets. Six hub genes were validated in UUO mouse models and human fibrotic kidney tissues. A five-gene diagnostic panel exhibited robust diagnostic performance with AUCs of 0.89–0.90. This study establishes a lactylation-related diagnostic signature, reveals metabolic-immune crosstalk, and supports early clinical diagnosis of kidney fibrosis.
Ye Kuang, Xiuhong Xiang, Chuan-Mei Peng et al.· iScience· 0 citations
Three candidate biomarkers co-dysregulated across T2DM and MCI transcriptomes and associated with uric acid metabolism are identified and considered hypothesis-generating and require validation in larger independent cohorts.
Yan Liu, Dongmei Kang, Yuan Lei· Experimental biology and med...· 0 citations
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a major complication of obesity. Although the endocrine-crosstalk mediated by adipo- and hepatokines is crucial for metabolic homeostasis, its precise molecular involvement in the progressive transition toward steatohepatitis (MASH) and hepatocellular carcinoma (HCC) remains poorly characterized.
This study aimed to comprehensively analyse these alterations throughout the MASLD-MASH-HCC continuum to identify non-invasive biomarkers and actionable therapeutic targets.
We evaluated the expression profiles of 56 adipo- and hepatokines in normal and diseased hepatic tissues across 18 well-defined patient cohorts spanning MASLD, MASH, and HCC phenotypes. This integrated in-house retrospective tissue biopsies with extensive in silico transcriptomic datasets. Key candidates were further validated at protein level in patient serum by ELISA assays. Finally, their functional impact on tumour cell proliferation was assessed in vitro using Hep3B and SNU-387 human HCC cell lines.
A progressive and consistent dysregulation of multiple adipo- and hepatokines was identified across the entire disease spectrum. Notably, ANGPTL2, ANGPT1, and ITLN1 exhibited the most robust, reproducible alterations across independent cohorts, which was successfully confirmed by circulating serum analysis. Functionally, treatment with ANGPTL2 and ITLN1 significantly reduced HCC cell proliferation. In sharp contrast, ANGPT1 administration markedly increased tumour cell proliferation, suggesting a distinct, divergent role in metabolic-driven hepatic tumour progression.
These findings demonstrate a profound, stage-dependent disruption of the liver-adipose tissue axis during metabolic-driven hepatic oncogenesis, positioning ANGPTL2, ANGPT1, and ITLN1 as promising biomarkers and potential therapeutic targets in HCC. Funding: ISCIII(PI23/00652; DTS24/00093; co-financed UE), JdA(PI-0046-2024, BIO139), FSEEN & CIBERobn/ehd.
J. López-Cánovas, J. M. Zamora Olaya, I. Sáez-Escobar et al.· European Journal of Endocrin...· 0 citations
INTRODUCTION
Characterized as an idiopathic primary myocardial disorder, dilated cardiomyopathy (DCM) predominantly affects children and elderly adults. However, a lack of specific clinical symptoms and reliable biomarkers impedes timely diagnosis and rational clinical management of DCM.
METHODS
Whole-genome expression profiles (GSE120895, GSE9800) were retrieved from the Gene Expression Omnibus database via the GEOquery R package. A series of bioinformatic methods were employed, including DEG, GSVA, WGCNA, GO/KEGG enrichment, PPI, and immune infiltration analysis. Key biomarkers were validated by qRT-PCR in a Doxorubicin (DOX)-induced DCM model.
RESULTS
In total, 629 differentially expressed genes (DEGs) were screened out between DCM and control groups. Combined analysis of DEGs and WGCNA outputs identified 13 hub genes overlapping with oxidative stress-associated gene modules. Receiver Operating Characteristic (ROC) curve analyses confirmed that these hub genes exhibit favorable diagnostic efficiency for DCM. Functional enrichment results showed that these genes are mainly enriched in transmembrane transport and nucleotide metabolism pathways. Immune infiltration analysis indicated significantly elevated infiltration levels of five immune cell subsets in DCM myocardial tissues. In vivo experiments verified the significant upregulation of five core hub genes in DOX-induced DCM mice. By screening hub genes with diagnostic potency based on public transcriptome datasets and validating their expression alterations in a DOX-induced DCM animal model, this study provides partial experimental evidence to support the above bioinformatic outcomes.
DISCUSSION
Through integrative analysis of multiple datasets and molecular biology validation, this study provides robust evidence supporting the involvement of these hub genes in DCM pathogenesis. Although validation was limited to a single murine model, the findings lay the groundwork for future mechanistic studies and clinical exploration of these candidate genes.
CONCLUSION
Hub genes including MVP, WISP1, FCN1, AMPD3, RARRES1, FTL, and KRT14 possess promising auxiliary diagnostic potential, which provides novel clues for subsequent clinical evaluation research on DCM.
BACKGROUND
This study focuses on exploring the co-morbid mechanisms by which Bisphenol A (BPA) induces non-alcoholic fatty liver disease (NAFLD) and osteoarthritis (OA).
METHOD
This study identified potential BPA targets utilizing the SwissTargetPrediction database. These targets were integrated with genes associated with NAFLD and OA, which were screened via Weighted Gene Co-expression Network Analysis and differential gene expression analysis. To elucidate the underlying biological mechanisms, functional enrichment and immune infiltration analyses were conducted. Core genes associated with comorbidity were pinpointed via machine learning. The interactions and cellular localization were further validated by molecular docking, molecular dynamics simulations, and single-cell transcriptomics. Finally, in vitro experiments were employed to verify the effects on chondrocyte function, and hepatic lipid metabolism.
RESULTS
Functional enrichment analysis indicates that BPA-induced NAFLD and OA comorbidity pathways are enriched in muscle cell proliferation, DNA metabolism, and inflammation pathways. RHOB has been identified as a core gene, participating in disease progression by regulating signaling pathways such as Hippo and IL-17. Single-cell sequencing revealed that RHOB is primarily expressed in hepatocytes and cholangiocytes in NAFLD, while enriching in HomC and EC cell clusters in OA. In vitro experiments confirmed that BPA exposure suppresses RHOB expression, thereby promoting lipid accumulation in hepatocytes and impairing chondrocyte function. Concurrently, rescue experiments demonstrated that its overexpression significantly reversed these pathological states.
CONCLUSION
BPA exposure drives the co-morbidity of OA and NAFLD by inhibiting RHOB. Consequently, limiting BPA exposure or modulating the RHOB pathway represents a viable approach for intervening in related diseases.
