NPAS2 Promotes MASLD and Hepatocarcinogenesis through SIRT1-Mediated PPARγ Suppression

NPAS2 Promotes MASLD and Hepatocarcinogenesis through SIRT1-Mediated PPARγ Suppression | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article NPAS2 Promotes MASLD and Hepatocarcinogenesis through SIRT1-Mediated PPARγ Suppression Peng Yuan, Jiao Mu, Jiali Ye, Jiahao Zhang, Bichan Xu, Hongxin Zhang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8137044/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Emerging evidence suggests a link between circadian disruption and metabolic dysfunction-associated steatotic liver disease (MASLD), although the precise mechanisms are not yet fully understood. As a central circadian regulator, the role of NPAS2 in the pathogenesis and progression of MASLD to hepatocellular carcinoma (HCC) is not well characterized. This study aimed to clarify the functional and mechanistic contributions of NPAS2 to the development of MASLD and the progression to HCC. Analysis of clinical liver biopsies and high-fat diet (HFD)-fed murine models consistently demonstrated significant upregulation of NPAS2 in MASLD, at both mRNA and protein levels. In vitro, free fatty acid (FFA)-treated LO2 hepatocytes with NPAS2 knockdown showed attenuated lipid accumulation and inflammatory responses, whereas NPAS2 overexpression exacerbated steatotic phenotypes. In hepatocyte-specific NPAS2 knockout mice subjected to HFD, we observed comprehensive metabolic improvement including reduced hepatic steatosis, improved insulin sensitivity, attenuated endoplasmic reticulum stress, and suppressed pro-fibrotic signaling. Mechanistically, NPAS2 was found to transcriptionally activate SIRT1 by directly binding to an E-box motif in its promoter region. SIRT1 subsequently deacetylated PPARγ, leading to its destabilization and functional suppression. The clinical relevance of this axis was underscored by strong correlations between NPAS2 expression and both SIRT1 (positive) and PPARγ (negative) in human MASLD specimens. Furthermore, in a diethylnitrosamine (DEN)-induced HCC model coupled with HFD feeding, NPAS2 deficiency conferred remarkable protection against tumor development. Conversely, NPAS2 overexpression accelerated hepatocarcinogenesis. Critically, pharmacological PPARγ activation by pioglitazone rescued NPAS2-driven metabolic dysfunction in vitro. Our study reveals NPAS2 as a critical node connecting circadian dysfunction to MASLD-HCC progression and identifies the NPAS2-SIRT1-PPARγ axis as a therapeutic target. These findings provide a rationale for chronotherapeutic strategies to disrupt this pathogenic cascade, offering new hope for combating MASLD-related complications. Biological sciences/Cancer/Cancer metabolism Biological sciences/Cancer/Cancer models MASLD circadian rhythm NPAS2 SIRT1/PPARγ HCC Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Metabolic dysfunction-associated steatotic liver disease (MASLD, formerly known as NAFLD) has emerged as the most prevalent chronic liver disorder worldwide, currently affecting 38% of adults and 7–14% of children and adolescents, with adult prevalence projected to exceed 55% by 2040[ 1 ]. While the "multiple-hit hypothesis" has replaced the earlier "two-hit hypothesis," providing a clearer framework for understanding disease pathogenesis, the molecular drivers orchestrating progression to steatohepatitis (MASH, formerly NASH), fibrosis, and ultimately hepatocellular carcinoma (HCC) remain incompletely understood[ 2 ]. This mechanistic gap explains the current lack of targeted therapies, with management still relying on lifestyle modifications and metabolic control that show limited efficacy in advanced disease[ 1 , 3 ]. Consequently, MASLD-related complications now represent the fastest-growing cause of liver-related mortality, with MASLD-HCC emerging as the most rapidly increasing indication for orthotopic liver transplantation (rising from 2.1% to 16.2% of cases between 2000–2016)[ 4 ]. Among patients with MASLD cirrhosis, HCC develops at an annual incidence of 0.7–2.6%[ 5 ], while global projections suggest a 122% increase in MASLD-HCC cases by 2030[ 6 ]. The escalating clinical and economic burden underscores the urgent need to decipher pathogenic mechanisms that could enable precision therapeutics. Metabolic homeostasis is sustained by circadian coordination of nutrient handling. Environmental or genetic disruption of this timing system—manifested as dampened amplitude or phase-shifted oscillations of clock-controlled genes (CCGs)—is now recognized as a causal determinant of metabolic disorders[ 7 ]. The hepatic circadian network exemplifies how the molecular clock is hard-wired to metabolism. BMAL1, REV-ERBα/β, Neuronal PAS Domain Protein 2 (NPAS2), and PER/CRY occupy promoters of key metabolic genes, enabling time-of-day–specific transcription[ 8 , 9 ]. Within this framework, PPAR family members display pronounced circadian expression[ 10 ]. PPARα cooperates with PGC-1α to activate fatty-acid β-oxidation during the active phase[ 11 ], while rhythmic repression of SREBP-1c by clock components temporally restrains lipogenesis[ 12 , 13 ], together forming an antiphasic “catabolism–anabolism” cycle that preserves hepatic lipid balance. An additional layer of control is provided by post-translational regulation. Acetylation of PPARγ modulates adipose plasticity and systemic metabolic rhythms, and pharmacological manipulation of PPARγ acetylation holds promise for restoring metabolic oscillations in models of obesity and aging[ 14 ]. Importantly, this circadian-metabolic interplay is bidirectional. Highly conserved nutrient-sensing pathways actively communicate cellular metabolic status to the circadian clock, creating a sophisticated feedback network[ 15 ]. For instance, high-fat diet (HFD)-induced metabolic disturbances can directly alter circadian parameters, modifying both period length and amplitude of locomotor activity rhythms[ 16 ]. These findings not only establish the central role of the circadian system in lipid metabolic regulation, but more importantly reveal a vicious cycle wherein metabolic disturbances (e.g., HFD) disrupt circadian gene expression, which in turn exacerbates metabolic dysfunction through aberrant regulation of lipid homeostasis - potentially serving as a key driver in MASLD pathogenesis. NPAS2 uniquely integrates circadian and metabolic signals through its hypoxia-sensitive PAS domain. Unlike other clock proteins, it specifically responds to steatotic stress while maintaining canonical clock functions via BMAL1 heterodimerization[ 17 ]. Emerging evidence has highlighted NPAS2's critical responsiveness to metabolic perturbations. In a compelling non-human primate model, maternal HFD was shown to induce persistent epigenetic reprogramming of the hepatic NPAS2 locus through increased H3K14ac at its promoter region[ 18 ]. This modification was associated with persistent metabolic dysfunction and non-alcoholic fatty liver disease that lasts at least until the age of 3[ 19 – 22 ]. The orphan nuclear receptor SHP has been identified as a key upstream regulator of NPAS2, modulating hepatic lipid metabolism through transcriptional repression of NPAS2 [ 17 ]. However, this finding alone cannot fully explain NPAS2's pleiotropic metabolic effects. To elucidate the role of NPAS2 in the development and progression of MASLD and its associated HCC, we systematically analyzed public datasets, assessed its expression patterns in clinical liver biopsies and HFD murine models, and employed a series of functional validation approaches to decipher its molecular mechanisms in regulating MASLD metabolic homeostasis. Furthermore, through preclinical models and clinical specimens, we elucidated the therapeutic potential of targeting the NPAS2 regulatory axis for precision medicine in MASLD. These findings not only provide novel insights into the circadian-metabolic crosstalk in liver diseases, but also open new avenues for developing chronotherapeutic strategies against MASLD and its malignant complications. Materials and methods Collection of human liver samples This study utilized human liver tissues from two cohorts: normal controls and patients with MASLD. Normal control tissues (n=8) were acquired from surgical resection of hepatic cysts or hemangiomas. All control tissues were histologically confirmed to be free of steatosis, inflammation, and fibrosis. The MASLD cohort (n=18) consisted of liver biopsy samples from patients diagnosed according to established clinical and histopathological criteria. All patients provided written informed consent prior to participation. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki and was approved by the Institutional Ethics Committee of the Fourth Military Medical University. To minimize confounding factors, control and MASLD groups were matched for age, sex, and body mass index (BMI) where possible. Generation of Genetically Modified Mice The hepatocyte-specific NPAS2 knockout ( Npas2 LKO) mice on a C57BL/6J background were generated using the CRISPR/Cas9-mediated genome editing system.[23]. Briefly, sgRNAs and donor oligonucleotides were designed to insert loxP sites flanking critical exons of the Npas2 gene. Npas2 fl/fl mice were then crossed with transgenic mice expressing Cre recombinase under the control of the albumin promoter (Alb-Cre) to achieve hepatocyte-specific deletion. Npas2 fl/fl ; Alb-Cre - littermates were used as controls throughout the study. All mice were genotyped by PCR analysis of tail DNA prior to experiments. For hepatic NPAS2 overexpression (OE), adult C57BL/6J mice were intravenously injected with 1×10 11 viral genomes (vg) of an adeno-associated virus serotype 8 vector expressing mouse Npas2 under the control of the liver-specific thyroxine-binding globulin (TBG) promoter (AAV8-TBG- Npas2 ). Control mice received an equivalent dose of AAV8-TBG-GFP. Cell Culture and Steatosis Model Establishment The human hepatic LO2 cell line was obtained from STEM RECELL. Cells were routinely maintained in high-glucose Dulbecco's Modified Eagle Medium (DMEM, Gibco, Cat# 11965092) supplemented with 10% fetal bovine serum (FBS, Gibco, Cat# 10270106) and 1% penicillin/streptomycin (Gibco, Cat# 15140122) at 37°C in a 5% CO₂ humidified atmosphere. To establish an in vitro model of hepatic steatosis, LO2 cells were treated with a free fatty acid (FFA) mixture. A 100 mM stock solution of oleic acid (OA) and palmitic acid (PA) at a 2:1 molar ratio was prepared in 0.1 M NaOH by conjugation with fatty acid-free bovine serum albumin (BSA, Sigma, Cat# A8806). The FFA working solution was prepared by diluting the stock in complete culture medium to a final concentration of 0.5 mM (OA: 0.33 mM, PA: 0.17 mM). Cells were treated with the FFA mixture or an equivalent concentration of BSA (vehicle control) for 24 to 48 hours to induce lipid accumulation. Generation of Stable Knockdown and Overexpression Cell Lines For NPAS2 knockdown (KD), lentiviral vectors expressing short hairpin RNAs (shRNAs) targeting human NPAS2 (shNPAS2) or a non-targeting control scramble sequence (shCtrl) were constructed (Ambion). The target sequences were as follows: shNPAS2: 5'-[ CGUCGGAUGUCAUGGAUCA]-3' For NPAS2 overexpression (OE), the full-length coding sequence of human NPAS2 was cloned into a lentiviral expression vector (pCDH-CMV-MCS-EF1-Puro, [Invitrogen]). Lentiviral particles were produced by co-transfecting 293T cells with the transfer plasmid (shRNA or OE) and packaging plasmids (psPAX2 and pMD2.G) using polyethylenimine (PEI, Polysciences, Cat# 24765). Viral supernatants were collected 48 and 72 hours post-transfection, filtered through a 0.45 μm filter, and used to transduce LO2 cells in the presence of 8 μg/mL polybrene (Sigma, Cat# H9268). For stable cell line selection, transduced cells were cultured under puromycin (InvivoGen, Cat# ant-pr-1) selection (2 μg/mL) for at least 7 days. The knockdown and overexpression efficiency was validated at both the mRNA and protein levels by quantitative RT-PCR (qRT-PCR) and Western blot analysis, respectively, prior to functional experiments. Bioinformatics Analysis The expression levels of NPAS2 in human and murine MASLD/HCC samples were assessed using publicly available datasets from the Gene Expression Omnibus (GEO) database. The human MASLD dataset GSE35251, comprising 206 MASLD patients and 10 healthy controls, was analyzed. The murine MASLD-HCC progression dataset GSE67680, profiling gene expression across the spectrum from normal liver to steatosis, MASH, and HCC, was analyzed. Differential expression analysis of the NPAS2 / Npas2 gene between predefined sample groups for each dataset was performed using the GEO2R interactive web tool (https://www.ncbi.nlm.nih.gov/geo/geo2r/). For each comparison, the default parameters of GEO2R were used. The potential interaction between PPARγ and SIRT1 was computationally predicted using the STRING database (version 12.0, https://string-db.org/ ). Quantitative Real-Time PCR (qRT-PCR) Analysis Total RNA was extracted from liver tissues or cultured LO2 cells using TRIzol™ Reagent (Invitrogen, Cat# 15596026) according to the manufacturer's instructions. RNA concentration and purity were determined by measuring the absorbance at 260/280 nm using a NanoDrop spectrophotometer (Thermo Fisher Scientific). RNA integrity was confirmed by 1% agarose gel electrophoresis. Complementary DNA (cDNA) was synthesized from 1 µg of total RNA using the PrimeScript™ RT Master Mix (Perfect Real Time) (Takara, Cat# RR036A) in a 20 µL reaction volume. qRT-PCR was performed in triplicate for each sample using TB Green™ Premix Ex Taq™ II (Tli RNaseH Plus) (Takara, Cat# RR820A) on a QuantStudio™ 6 Pro Real-Time PCR System (Applied Biosystems). The amplification program consisted of an initial denaturation at 95°C for 30 seconds, followed by 40 cycles of 95°C for 5 seconds and 60°C for 30 seconds. A melt curve analysis was performed at the end of each run to confirm the specificity of amplification. The relative mRNA expression levels were calculated using the comparative 2^(-ΔΔCt) method and normalized to the expression of the housekeeping gene β-actin (ACTB). All primer sequences used are listed in Supplementary Table 2. Western Blotting Analysis Liver tissues and cultured cells were lysed in RIPA Lysis and Extraction Buffer (Thermo Fisher Scientific, Cat# 89900) supplemented with a Halt™ Protease and Phosphatase Inhibitor Cocktail (Thermo Fisher Scientific, Cat# 78440). Protein concentrations were determined using a BCA Protein Assay Kit (Pierce, Cat# 23225). Equal amounts of protein (typically 20-35 µg per lane) were separated by SDS-polyacrylamide gel electrophoresis (SDS-PAGE) on 8-12% gels and subsequently transferred onto polyvinylidene fluoride (PVDF) membranes (Millipore, Cat# IPVH00010). The membranes were blocked with 5% (w/v) non-fat milk in Tris-buffered saline containing 0.1% Tween-20 (TBST) for 1 hour at room temperature and then incubated with specific primary antibodies diluted in blocking buffer overnight at 4°C. After washing three times with TBST, the membranes were incubated with appropriate horseradish peroxidase (HRP)-conjugated secondary antibodies (Jackson ImmunoResearch) for 1 hour at room temperature. Protein bands were visualized using an enhanced chemiluminescence (ECL) substrate (Millipore, Cat# WBKLS0500) and imaged with a ChemiDoc™ Touch Imaging System (Bio-Rad). Band intensities were quantified using Image Lab™ Software (Bio-Rad). All antibodies used, including their catalog numbers and dilutions, are listed in Supplementary Table 5. Hematoxylin and Eosin (H&E) and Immunohistochemistry (IHC) Paraffin-embedded liver sections (4-5 μm) were prepared. For H&E staining, sections were deparaffinized, rehydrated, and stained using standard protocols. For IHC, after antigen retrieval in citrate buffer (pH 6.0) and blocking of endogenous peroxidase, sections were incubated overnight at 4°C with primary antibodies against NPAS2 and Ki-67. Binding was detected using an HRP-conjugated secondary antibody and a DAB substrate kit (MXB Biotechnologies, Cat#KIT-9720). All sections were counterstained with hematoxylin, imaged under an Olympus BX53 microscope, and evaluated by blinded observers. All antibodies used, including their catalog numbers and dilutions, are listed in Supplementary Table 6. Oil Red O Staining Frozen liver sections (8 μm) were fixed in 4% PFA, stained with filtered Oil Red O working solution (0.3% in 60% isopropanol) for 15 min, and counterstained with hematoxylin. LO2 hepatocytes were fixed in 4% PFA and stained as above. For quantification, stained lipid droplets were eluted with 100% isopropanol and the absorbance was measured at 510 nm. Lipid accumulation was quantified from images using ImageJ software. Nile Red Staining for Cultured Cells LO2 hepatocytes were washed with PBS and fixed with 4% PFA for 15 min at room temperature. After washing, cells were incubated with a Nile Red working solution (1 μg/mL in PBS, Sigma-Aldrich, Cat# 72485) for 10 min in the dark. Nuclei were counterstained with DAPI (1 μg/mL, Thermo Fisher Scientific, Cat# D1306) for 5 min. Following final washes, images were immediately captured using a fluorescence microscope (Nikon Eclipse Ti2) with standard FITC (for neutral lipids) and DAPI filter sets. Fluorescence intensity was quantified using ImageJ software to assess relative lipid content. Measurement of Hepatic and Serum Lipid Profiles Upon sacrifice, mouse blood was collected and centrifuged at 3,000 rpm for 15 minutes at 4°C to obtain serum. Liver tissues (approximately 100 mg) were homogenized in 1 mL of ice-cold PBS using a mechanical homogenizer. Lipids were extracted from the homogenates using a chloroform-methanol (2:1, v/v) mixture according to the method of Folch et al[24]. The concentrations of triglycerides (TGs) and total cholesterol (TC) in both serum and hepatic lipid extracts were quantified using commercial enzymatic assay kits according to the manufacturers' protocols (BioVision, Cat# K622, Cat# K603). Assessment of Liver Function Liver injury was assessed by measuring the activity of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in the serum. The assays were performed using commercial ALT (Cat# A7526-120) and AST (Cat# A5598-120) Activity Assay Kits (Sigma-Aldrich) according to the manufacturer's instructions. Evaluation of Insulin Resistance For the assessment of insulin sensitivity, mice were fasted for 6 hours prior to blood collection. Fasting blood glucose levels were measured using a portable glucometer (OneTouch Ultra, LifeScan). Fasting serum insulin levels were determined using a Mouse Insulin ELISA Kit (Crystal Chem, Cat# 90080) according to the manufacturer's protocol. The homeostatic model assessment of insulin resistance (HOMA-IR) index was calculated using the following formula: HOMA-IR = [Fasting Glucose (mmol/L) × Fasting Insulin (μU/mL)] / 22.5. Analysis of Public ChIP-seq Data To identify direct transcriptional targets of NPAS2, we re-analyzed a publicly available NPAS2 ChIP-on-chip dataset (GSE from [GSE11923]). The association of NPAS2 binding with specific biological pathways was investigated by performing Gene Ontology (GO) biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the genes whose promoter regions (± 3 kb from the transcription start site) were bound by NPAS2. Co-Immunoprecipitation (Co-IP) To investigate protein-protein interactions, Co-IP was performed. LO2 cells were lysed in NP-40 lysis buffer (Beyotime, Cat# P0013F) supplemented with protease inhibitors. For each reaction, 500 μg of total protein was incubated with 2 μg of anti-PPARγ antibody (Cell Signaling Technology, Cat# 2443S) or normal rabbit IgG (negative control, Cell Signaling Technology, Cat# 2729S) overnight at 4°C with gentle rotation. Protein A/G Magnetic Beads (MedChemExpress, Cat# HY-K0202) were then added and incubated for 2 hours. The immunoprecipitates were washed five times with lysis buffer, eluted in 2× SDS loading buffer by boiling for 10 minutes, and analyzed by Western blotting using antibodies against SIRT1 and PPARγ. Chromatin Immunoprecipitation-quantitative PCR (ChIP-qPCR) ChIP assays were performed using the SimpleChIP® Plus Enzymatic Chromatin IP Kit (Magnetic Beads, Cell Signaling Technology, Cat# 9005) according to the manufacturer's protocol. Briefly, LO2 cells were cross-linked with 1% formaldehyde for 10 min. Chromatin was digested with micrococcal nuclease to obtain DNA fragments predominantly between 150-900 bp. Digested chromatin was immunoprecipitated overnight at 4°C with 5 μg of anti-NPAS2 antibody (Santa Cruz Biotechnology, Cat# sc-365-829) or normal rabbit IgG. After reversing cross-links, the purified DNA was analyzed by qPCR using primers specifically flanking the E-box element in the SIRT1 promoter region. The results are presented as the percentage of input. Luciferase Reporter Assay The transcriptional activity of NPAS2 on the SIRT1 promoter was measured using a dual-luciferase reporter assay system. A series of truncated fragments of the human SIRT1 gene promoter were cloned into the pGL4.10[luc2] vector (Promega). LO2 cells were co-transfected with these reporter constructs and a NPAS2 expression plasmid or empty vector control, using Lipofectamine 3000. The pRL-TK Renilla luciferase vector (Promega) was included as an internal control for normalization. 48 hours post-transfection, firefly and Renilla luciferase activities were measured sequentially using the Dual-Luciferase® Reporter Assay System (Promega, Cat# E1960) on a GloMax® Navigator Microplate Luminometer. Firefly luciferase activity was normalized to Renilla luciferase activity for each sample. Rescue Experiments via SIRT1 Modulation To investigate the role of SIRT1 in the NPAS2-PPARγ axis, rescue experiments were performed. In NPAS2 -overexpressing LO2 cells, SIRT1 was knocked down using specific siRNAs (Santa Cruz Biotechnology, Cat# sc-40986) transfected with Lipofectamine RNAiMAX (Invitrogen, Cat# 13778150). Conversely, in NPAS2 -knockdown cells, SIRT1 was overexpressed using a SIRT1 -expression plasmid (Addgene) transfected with Lipofectamine 3000 (Invitrogen, Cat# L3000015). The efficiency of all manipulations was confirmed by Western blot 48 hours post-transfection. Cell Counting Kit-8 (CCK-8) Proliferation Assay The viability and proliferation of LO2 hepatocytes were assessed using the Cell Counting Kit-8 (CCK-8, Dojindo Laboratories, Cat# CK04) according to the manufacturer's instructions. Briefly, cells were seeded in 96-well plates at a density of 3 × 10³ cells per well. After the respective treatments, 10 μL of CCK-8 reagent was added to each well followed by incubation at 37°C for 2 hours. The absorbance of the formazan product was measured at 450 nm using a microplate reader (BioTek Synergy H1). The relative cell viability was expressed as a percentage of the absorbance in the control group. Pharmacological Treatments The PPARγ agonist Pioglitazone (MedChemExpress, Cat# HY-13952) was prepared as a 10 mM stock solution in dimethyl sulfoxide (DMSO) and stored at -20°C. For in vitro studies, LO2 hepatocytes were treated with Pioglitazone at a final concentration of 10 μM for 48 hours in the presence or absence of free fatty acid (FFA) challenge. The equivalent volume of DMSO (≤0.1%) was used as the vehicle control. The selective SIRT1 inhibitor EX-527 (MedChemExpress, Cat# HY-15452) was dissolved in DMSO to generate a 50 mM stock solution. Statistical Analysis All statistical analyses were performed using GraphPad Prism 9. Data are presented as mean ± SEM from at least three independent biological replicates (n ≥ 3). Normality was assessed using the Shapiro–Wilk test. For comparisons between two groups of normally distributed data, an unpaired two-tailed Welch’s t-test was applied without assuming equal variances. For comparisons among three or more groups, two-way ANOVA followed by Tukey’s post hoc test was used. Non-normally distributed data were analyzed using appropriate non-parametric tests, such as the Mann–Whitney U test for two-group comparisons or the Kruskal–Wallis test for multiple groups. Correlations were evaluated using Pearson’s correlation coefficient. A p-value of less than 0.05 was considered statistically significant. Results NPAS2 links circadian disruption to MASLD progression in humans and experimental models Given emerging evidence linking circadian clock disruption to metabolic liver diseases, we investigated the role of the core circadian regulator NPAS2 in MASLD pathogenesis using both clinical samples and experimental models. Our study cohort comprised 8 healthy controls and 18 MASLD patients, with liver biopsy analysis demonstrating significant upregulation of NPAS2 in MASLD patients compared to non-steatotic controls. qPCR revealed a 1.7-fold increase in mRNA expression (p<0.001; Fig. 1A), which was confirmed at the protein level by Western blot (Fig. 1B). These clinical findings were further supported by analysis of the GSE35251 dataset, showing significantly higher NPAS2 expression in 206 MASLD patients compared to 10 healthy controls (p<0.01). Notably, NPAS2 expression levels correlated positively with serum ALT levels (r=0.25, p=0.05), suggesting a potential link between NPAS2 dysregulation and liver injury (Fig S1A-B). These human data were corroborated in experimental models, where HFD-fed mice developed pronounced hepatic steatosis characterized by macrovesicular lipid accumulation (H&E staining) and neutral lipid deposition (Oil Red O staining) (Fig. 1C), accompanied by more severe NPAS2 dysregulation, including a 2.6-fold mRNA upregulation and increased protein expression (Fig. 1C-E). Longitudinal assessment of murine MASLD-HCC progression models (GSE67680) revealed a stepwise elevation of Npas2 from steatosis to MASH-HCC, with peak expression observed in advanced HCC stages, though the initial transition from normal liver to steatosis showed only a non-significant upward trend (Fig. S1C). Notably, circadian profiling in HFD-fed mice uncovered profound disruption of Npas2 rhythmicity, characterized by amplitude reduction (Fig. 1F). This disruption paralleled the development of metabolic abnormalities, suggesting a potential relationship between NPAS2 dysregulation and hepatic steatosis. NPAS2 regulates lipid accumulation and inflammatory responses in hepatocytes To mechanistically interrogate NPAS2's role in hepatic steatosis, we established an in vitro model using oleic acid/palmitic acid (OA/PA)-treated LO2 hepatocytes to mimic lipid overload conditions. Western blot analysis confirmed significant induction of NPAS2 protein expression upon lipid challenge (Fig. 2A), suggesting its potential involvement in steatosis development. To elucidate the functional consequences of NPAS2 dysregulation, we established stable LO2 cell lines with NPAS2 knockdown (KD, using shRNA) and overexpression, with efficiency confirmed by Western blot (Fig. S2A-B). Functional analyses revealed that NPAS2 knockdown markedly attenuated lipid droplet accumulation, as demonstrated by Oil Red O and Nile Red staining (Fig. 2B). Conversely, NPAS2 overexpression exacerbated lipid deposition (Fig. 2C). These morphological findings were corroborated by biochemical measurements showing that NPAS2 knockdown significantly decreased cellular TG (14% reduction) and TC (4.5% reduction) levels (Fig. 2D), while NPAS2 overexpression increased TG by 16% and TC by 6.1% (Fig. 2E). Notably, NPAS2 regulation extended beyond lipid metabolism to modulate inflammatory responses. NPAS2 knockdown substantially downregulated key proinflammatory cytokines, including Il1b (48.7% reduction), Il6 (41.2% reduction), and Tnf (58.2% reduction; Fig. 2F). In stark contrast, NPAS2 overexpression amplified cytokine production ( Il1b : 125.3% increase; Il6 : 65.7% increase; Tnf : 179.7% increase; all p<0.01), suggesting NPAS2 may serve as a critical node linking metabolic dysregulation and inflammation in hepatic steatosis. Hepatocyte-specific Npas2 knockout ameliorates diet-induced hepatic steatosis in vivo To validate these findings in a physiological context, we generated hepatocyte-specific Npas2 knockout mice using CRISPR/Cas9 technology (Fig. 3A and Fig. S3). When challenged with a 16-week HFD, Npas2 LKO mice exhibited significant metabolic improvements compared to controls, including reduced liver weight (27.8% decrease) and liver-to-body weight ratio (24.4% decrease; Fig. 3B), along with decreased hepatic and serum triglyceride and total cholesterol levels (Fig. 3C-3D). These changes occurred with minimal effects on body weight (Fig. 3E). Histopathological analysis confirmed marked improvements in Npas2 LKO mice, showing reduced steatosis and decreased lipid accumulation (Fig. 3F). Consistent with these phenotypic improvements, serum markers of liver injury (ALT and AST) were significantly reduced in Npas2 LKO mice (40.5% and 24.4% decrease respectively; Fig. 3G). Notably, both hepatic ALT and AST levels were significantly downregulated in Npas2 LKO mice (46.1% and 50.7% decrease respectively; Fig. 3H), further supporting the amelioration of liver injury. To elucidate the mechanistic basis for NPAS2-mediated amelioration of hepatic steatosis, we performed comprehensive analysis of lipid metabolism pathways. Surprisingly, NPAS2 deletion resulted in coordinated upregulation across all major lipid metabolic pathways: (1) Fatty acid uptake ( Cd36 , Fabp4 ), (2) Lipid storage ( Plin2 , Adrp ), (3) De novo lipogenesis ( Srebf1, Acaca , Fasn ), (4) Fatty acid oxidation ( Cpt1a , Acox1 ) (Fig. 3I). This global activation of lipid metabolic genes suggests that NPAS2 knockout enhances hepatic lipid turnover rather than simply suppressing individual pathways. The net metabolic consequence of this reprogramming appears to be a shift toward more efficient lipid handling, evidenced by reduced steatosis despite increased expression of both lipogenic and lipolytic genes. NPAS2 Drives MASLD Progression Through PPARγ Suppression-Mediated ‘Multiple Hits’ Mechanism While our metabolic profiling revealed global activation of lipid pathways in NPAS2-deficient livers, this paradoxical coexistence of upregulated lipogenesis and β-oxidation genes could not fully explain the observed attenuation of hepatic steatosis. We therefore hypothesized that NPAS2 ablation might ameliorate MASLD through modulating the "multiple hits" beyond lipid metabolism - particularly insulin resistance, cellular stress, and inflammatory responses - which collectively drive disease progression. Systematic analyses revealed that Npas2 LKO produced significant metabolic improvements. First, Npas2 LKO mice showed enhanced insulin sensitivity, demonstrated by a 36.3% reduction in HOMA-IR (Fig4A) and increased p-AKT levels (p-AKT, a key mediator of insulin signaling; Fig4B). Second, NPAS2 deficiency markedly attenuated endoplasmic reticulum (ER) stress. This was evidenced by reduced expression of ER chaperone Grp78 (26.9% decrease) and stress-response factors including, Xbp1s (46.5%), Chop (43.7%), Atf4 (45.2%), and Orp150 (56.8%) (Fig4C). Concurrently, oxidative damage was significantly alleviated (21.3% decrease in lipid peroxidation marker MDA), with compensatory upregulation of antioxidant enzymes SOD2 and GPX (Fig4D). NPAS2 deficiency suppressed hepatic and systemic pro-inflammatory responses (IL-1β, IL-6, and TNF-α downregulation; Fig4E) and fibrogenic signaling (e.g., Col1a1 , Col3a1 , Acta2 and Tgfb 1 reduced by 45–62.8%；Fig4F). Strikingly, these phenotypic improvements precisely mirrored the known pleiotropic effects of PPARγ activation[3, 25-28]. Intriguingly, these multifaceted improvements occurred without alterations in PPARα or PPARβ/δ expression at either transcriptional or translational levels, but were accompanied by a specific increase in PPARγ protein despite unaltered mRNA levels, suggesting post-translational regulation (Fig4G). Notably, re-analysis of public NPAS2 ChIP-on-chip datasets revealed significant enrichment of NPAS2 binding at loci annotated to lipid metabolic processes (GO:0006629), with KEGG pathway analysis specifically highlighting the PPAR signaling pathway (ko03320, top 10 enriched) (FigS4). This genomic binding pattern, coupled with our phenotypic data, strongly implicates NPAS2 in the direct regulation of PPARγ-centered metabolic networks. The connection between NPAS2 and PPARγ was further underscored by their robust anti-phase circadian oscillation (Fig4H). The temporal dissociation of NPAS2 (a transcriptional repressor) and PPARγ (a metabolic activator) protein levels suggests a time-of-day-specific regulatory axis, wherein NPAS2 may periodically suppress PPARγ stability or activity during its peak expression phases. Together, the ChIP-based genomic evidence and dynamic protein oscillation establish NPAS2 as a novel circadian governor of PPARγ signaling in hepatic metabolism. NPAS2 Regulates PPARγ Stability Through Transcriptional Control of SIRT1 Having established NPAS2's role in suppressing PPARγ activity, we next investigated the molecular mechanism underlying this regulation. Although co-immunoprecipitation assays ruled out direct physical interaction between NPAS2 and PPARγ (Fig. S5), we noted that PPARγ's metabolic functions are known to be regulated by rhythmic acetylation[14]. This led us to hypothesize that NPAS2 might modulate PPARγ through post-translational modifications. Strikingly, we found that NPAS2 overexpression significantly increased PPARγ acetylation, while NPAS2 knockdown markedly reduced it (Fig. 5A). These opposing effects strongly suggest that NPAS2 regulates PPARγ stability through acetylation-dependent proteasomal degradation. This acetylation phenotype directed our attention to SIRT1, the major hepatic deacetylase known to regulate PPARγ stability and metabolic function[29]. Bioinformatic analysis using the STRING database further provided multiple lines of evidence supporting a protein-protein interaction between PPARγ and SIRT1 (Fig. S6), reinforcing their functional connection. Our results from qRT-PCR and Western blot analysis showed that NPAS2 knockdown significantly decreased SIRT1 expression, while overexpression of NPAS2 markedly increased SIRT1 expression in LO2 cells, at both mRNA and protein levels (Figure 5B-C), indicating a transcriptional regulation of SIRT1 by NPAS2. Given that a previous study in C57BL/6J mice liver tissue using chromatin immunoprecipitation sequencing analysis has identified Sirt1 is among the top ten direct transcriptional targets of NPAS2[30], we hypothesized that SIRT1 might be a direct transcriptional target of NPAS2 in human hepatocytes. To test the possibility, a series of truncated promoter constructs were developed to determine their transcriptional activity in hepatocytes with overexpression of NPAS2. Results from luciferase reporter assay revealed that SIRT1 promoter construct (from −110 to +45) abolished the transcriptional activity of the reporter gene (Figure 5D). Site-directed mutagenesis further identified an E-box within putative DNA-binding sites (nt-44 to nt-38) was critical for NPAS2-regulated SIRT1 transcription in LO2 cells (Fig. 5E). In addition, ChIP-PCR assay also showed that NPAS2 directly bind to the promoter of SIRT1 (Fig. 5F). To further determine whether NPAS2 downregulates the expression and acetylation of PPARγ through upregulating SIRT1, SIRT1 was knocked-down or overexpressed in LO2 cells with NPAS2 overexpression or knockdown. As shown in Fig.5G, overexpression of SIRT1 significantly attenuated the upregulation of PPARγ expression and acetylation induced by NPAS2 knockdown, whereas knockdown of SIRT1 reversed the suppression of PPARγ expression and acetylation caused by NPAS2 overexpression. Together, these results suggest that NPAS2 downregulates PPARγ expression through directly transcriptional up-regulating SIRT1 in hepatocytes. NPAS2 Deficiency Attenuates MASLD-HCC Progression by Modulating the SIRT1-PPAR γ Axis Clinical immunohistochemical analysis demonstrated significantly elevated NPAS2 expression in MASLD-HCC tissues (Fig. 6A). Notably, NPAS2 expression levels exhibited a strong positive correlation with SIRT1 (r = 0.602, p < 0.01) while showing a significant negative correlation with PPARγ (r = -0.512, p < 0.01), suggesting a potential regulatory relationship within this molecular axis during MASLD-HCC progression(Supplementary Table 1). To functionally characterize NPAS2's role in hepatocarcinogenesis, we established a DEN-induced HCC model in HFD-fed mice with hepatocyte-specific Npas2 knockout (Fig. 6B). The Npas2 LKO mice displayed remarkable protection against HCC development, as evidenced by a 60% reduction in tumor incidence and significantly decreased tumor burden (Fig. 6C-D). Histopathological examination showed substantial improvement in liver architecture, with markedly attenuated steatosis visible on H&E staining (Fig. 6D). These morphological improvements were accompanied by reduced liver-to-body weight ratios and significantly lower serum ALT/AST levels (Fig. 6E-F), indicating improved hepatic function. The tumor microenvironment in Npas2 LKO mice showed reduced inflammatory signaling, with significant decreases in pro-inflammatory cytokines TNF-α, IL-1β, and IL-6 (Fig. 6G). At the molecular level, NPAS2 deficiency led to pronounced suppression of cellular proliferation, as demonstrated by decreased Ki67 staining (Fig. 6H). Furthermore, we observed substantial downregulation of established HCC markers including Afp , Gpc3 , Epcam , and Cd44 (Fig. 6I). Western blot analyses confirmed these phenotypic changes were associated with NPAS2-dependent regulation of the SIRT1-PPARγ axis, as genetic ablation attenuated SIRT1 activity while increasing PPARγ acetylation (Fig. 6J). Collectively, these findings establish NPAS2 as a critical driver of MASLD-HCC progression through its modulation of the SIRT1-PPARγ signaling pathway. NPAS2 Overexpression Exacerbates MASLD-HCC Pathogenesis via SIRT1-PPARγ Axis Activation To further validate the oncogenic properties of NPAS2, we employed AAV8-mediated hepatic overexpression (Fig. 7A), which resulted in an increase in both NPAS2 mRNA and protein levels compared to controls (Fig. S7). Consistent with our clinical findings, NPAS2 overexpression markedly accelerated disease progression in the DEN-HFD model, with tumor incidence increasing dramatically from 10% (1/10) in control animals to 50% (5/10) in NPAS2 overexpressing mice (Fig. 7B). Macroscopic examination of liver specimens revealed significantly larger tumor volumes in NPAS2 overexpressing mice compared to controls. Histopathological analysis demonstrated exacerbated hepatic steatosis and more severe architectural distortion, as evidenced by H&E staining (Fig. 7C). These pathological changes correlated with increased liver-to-body weight ratios (Fig. 7D) and elevated serum ALT/AST levels (Fig. 7E), indicating profound hepatic dysfunction. At the molecular level, NPAS2 overexpression created a pro-tumorigenic microenvironment characterized by significantly elevated levels of inflammatory cytokines, including TNF-α, IL-6, and IL-1β (Fig. 7F). Immunohistochemical analysis revealed enhanced proliferative activity in NPAS2 overexpressing livers, as demonstrated by increased Ki-67 staining (Fig. 7G). Furthermore, qRT-PCR analysis showed upregulation of stemness markers ( Epcam , Cd44 ) and established HCC markers ( Afp , Gpc3 ) in these animals (Fig. 7H). Most importantly, Western blot analysis confirmed that NPAS2 overexpression maintained SIRT1 activity while simultaneously suppressing PPARγ acetylation (Fig. 7I), providing direct evidence that NPAS2 exerts its oncogenic effects through modulation of the SIRT1-PPARγ signaling axis. These findings collectively demonstrate that NPAS2 overexpression promotes hepatocarcinogenesis by sustaining a pro-proliferative, inflammatory microenvironment through its regulatory effects on the SIRT1-PPARγ pathway. Pharmacological Activation of PPARγ Attenuates NPAS2-Induced MASLD Progression To elucidate the mechanistic link between NPAS2 and PPARγ suppression in MASLD-HCC progression, we utilized a free fatty acid (FAA)-induced cellular model combined with pharmacological intervention (Fig. 8A). In NPAS2 overexpression LO2 hepatocytes, pioglitazone treatment (10 μM, 48h) effectively restored PPARγ transcriptional activity, as evidenced by significant upregulation of its downstream targets Cd36 and Fabp4 (Fig. 8B). This molecular restoration translated to functional metabolic improvements, including reduced intracellular lipid accumulation (quantified by Oil Red O and Nile Red staining; Fig. 8C-D) and normalized lipid profiles, with triglyceride and total cholesterol levels decreasing by 4% and 7.7%, respectively (Fig. 8E). Notably, CCK-8 assays revealed that pioglitazone treatment normalized the aberrant proliferative phenotype observed in NPAS2 overexpression LO2 cells under FAA conditions, suggesting that PPARγ activation may counteract the tumor-promoting effects of NPAS2 overexpression (Fig. 8F). This finding supports the hypothesis that NPAS2-mediated PPARγ suppression contributes to the malignant transformation of hepatocytes in MASLD progression. The therapeutic potential was further enhanced through combined treatment with the SIRT1 inhibitor EX527 (5 mg/kg), which synergistically restored PPARγ protein levels (Fig. S8). These results provide compelling evidence that NPAS2 drives metabolic dysfunction and tumor progression primarily through SIRT1-mediated suppression of PPARγ activity. The robust therapeutic effects observed with both monotherapy and combination treatment underscore the clinical relevance of targeting the NPAS2-SIRT1-PPARγ axis as a potential strategy to halt MASLD-associated HCC progression at the molecular level. Discussion The increasing global prevalence of MASLD/MASH and its progression to hepatocellular carcinoma represents a critical public health challenge. The circadian regulator NPAS2 has emerged as a critical player in metabolic liver disease, yet its mechanistic role in driving MASLD progression to HCC remained poorly understood. Our study provides compelling evidence that NPAS2 orchestrates hepatic metabolic dysfunction through SIRT1-PPARγ axis, establishing a molecular bridge between circadian disruption and liver pathogenesis (Fig. 9 ). These findings significantly advance our understanding of MASLD-HCC progression while revealing novel therapeutic opportunities. The profound metabolic alterations observed in NPAS2-manipulated models reinforce the emerging paradigm that circadian machinery plays fundamental roles in hepatic homeostasis. Our demonstration that NPAS2 knockout attenuates HFD-induced steatosis and inflammation aligns with previous reports showing metabolic disturbances in other circadian gene-modified mice (BMAL1, CLOCK)[ 9 , 31 , 32 ]. Notably, the hypoxia-sensitive PAS domain of NPAS2 raises an intriguing possibility that the hypoxic microenvironment characteristic of steatotic liver disease may directly contribute to NPAS2 induction. This hypothesis aligns with existing evidence demonstrating that lipid overload increases oxygen demand while impairing hepatic perfusion, creating localized hypoxic conditions[ 33 ]. Our hepatocyte-specific knockout experiments provide definitive evidence that NPAS2 acts as a driver rather than a passive marker of disease progression. While we primarily focused on downstream mechanisms, future studies should investigate whether hypoxia-inducible factors (HIFs) or other metabolic stress signals directly regulate NPAS2 expression in fatty liver conditions. Our mechanistic dissection of this novel regulatory axis reveals how circadian regulators exert profound control over hepatic metabolism through coordinated transcriptional regulation of key metabolic effectors. Specifically, we demonstrate that NPAS2-mediated upregulation of SIRT1 promotes PPARγ destabilization through enhanced deacetylation, establishing a steatotic microenvironment that accelerates MASLD pathogenesis. Our results initially appear to present a metabolic paradox - NPAS2 knockout improves hepatic steatosis while unexpectedly upregulating lipogenic genes. However, this apparent contradiction is resolved when considering the pleiotropic nature of PPARγ's regulatory functions. While PPARγ activation is known to transcriptionally promote adipogenesis, its net metabolic effects in hepatocytes are more complex and context-dependent. The observed metabolic improvement likely results from PPARγ's dominant beneficial effects on (1) insulin sensitization that enhances fructose clearance and fatty acid oxidation, (2) attenuation of cellular stress responses (ER and oxidative stress), and (3) suppression of inflammatory cascades - all of which collectively outweigh its lipogenic actions. This mirrors the clinical duality of PPARγ agonists like thiazolidinediones, which improve systemic metabolism while causing undesirable adipose expansion[ 34 ]. Our findings carry important therapeutic implications that require nuanced consideration. Our data reveal that targeted PPARγ activation in NPAS2 overexpression hepatocytes can disrupt the pathogenic cycle, while accumulating evidence has also illuminated pioglitazone demonstrate efficacy against hepatic steatosis[ 35 , 36 ], their context-dependent association with HCC risk necessitates precision medicine approaches tailored to individual metabolic contexts. Notably, PPARγ acetylation exhibits robust diurnal oscillations in healthy adipose tissue (peaking at ZT0 and troughing at ZT18), a rhythm disrupted in obesity, aging, and circadian misalignment[ 14 ]. The circadian expression of NPAS2, coupled with the established role of PPARγ acetylation as a hub linking adipose plasticity and metabolic rhythms, provides compelling evidence for chronotherapeutic optimization. Building on these findings, we propose that timed administration of PPARγ agonists during NPAS2 trough phases, could synergistically enhance hepatic specificity by leveraging metabolic rhythmicity while mitigating off-target effects. This dual chronopharmacological strategy, grounded in conserved circadian-metabolic crosstalk, holds significant promise for improving MASLD treatment outcomes. The context-dependent duality of SIRT1 presents both therapeutic challenges and opportunities. While hepatic SIRT1 activation promotes tumorigenesis through PPARγ destabilization in our metabolic liver disease model, its protective roles in alcoholic liver disease (via NAD+-dependent pathways) and cardiovascular systems caution against systemic inhibition[ 37 , 38 ]. This tissue-specific functional dichotomy suggests that targeted hepatic SIRT1 modulation may offer safer therapeutic outcomes than global approaches. Our findings raise several mechanistic questions requiring further investigation. First, whether SIRT1 directly regulates PGC-1α acetylation in steatotic hepatocytes, as established in other metabolic tissues but unverified in this context [ 39 , 40 ]. Should PGC-1α prove to be negatively regulated by the NPAS2-SIRT1 axis, it would establish a self-reinforcing pathogenic cascade characterized by (1) PPARγ-mediated lipid homeostasis disruption and (2) PGC-1α-driven mitochondrial dysfunction. This dual perturbation could create a metabolic vicious cycle where diminished PPARγ activity exacerbates hepatic steatosis through multiple pathological hits, while suppressed PGC-1α impairs mitochondrial biogenesis, forcing a metabolic shift toward glycolysis - mirroring the Warburg effect characteristic of both advanced MASLD and cancer metabolism[ 41 ]. Such mechanisms would collectively generate a pro-oncogenic microenvironment ripe for malignant transformation, representing a critical direction for future investigation. While LO2 hepatocytes provide a tractable model for early metabolic dysregulation, future studies using patient-derived primary hepatocytes and organoids will further validate the translational potential of targeting the NPAS2-SIRT1-PPARγ axis. Collectively, NPAS2’s role in early metabolic dysregulation positions it as a promising preventive target. Pharmacological intervention via combined pioglitazone and SIRT1 inhibition could disrupt the NPAS2-SIRT1-PPARγ axis, offering a novel strategy to intercept MASLD-HCC progression in high-risk populations—particularly those with circadian disruption phenotypes. Our work establishes NPAS2 as a central node linking circadian biology and hepatic pathophysiology, with translational implications for precision chronotherapy. Conclusion Based on consistent evidence obtained from clinical cohorts, multi-omics datasets, genetically engineered mouse models, and in vitro mechanistic investigations, this study systematically elucidates the central role of the core circadian transcription factor NPAS2 in metabolic dysfunction-associated steatotic liver disease (MASLD) and its progression to hepatocellular carcinoma (HCC). NPAS2 exhibits disrupted rhythmicity in disease states, and operates through a hierarchical regulatory axis wherein it transcriptionally activates the deacetylase SIRT1, which in turn promotes deacetylation and proteasomal degradation of PPARγ, thereby alleviating its protective metabolic functions. Importantly, pharmacological PPARγ activation via pioglitazone significantly rescues NPAS2-induced metabolic disturbances and proliferative phenotypes. Our findings not only uncover a novel circadian-regulated pathway underlying MASLD–HCC progression but also provide a mechanistic rationale for targeting circadian components in the development of targeted therapies for metabolic liver diseases. Declarations Acknowledgements We acknowledge the patients who participated in the trial and the contributions of all investigators. We also thank Tangdu Hospital, Fourth Military Medical University for providing relevant experimental facilities and technical support. Author contributions Jiao Mu, Jiali Ye and Jiahao Zhang performed most of the experiments and analyzed data; Bichan Xu, Wen Huang and Hui Gong participated in the in vitro and vivo study. Peng Yuan and Jiali Ye designed the overall study, Peng Yuan and Menghui Yuan supervised the experiments. Jiao Mu and Jiali Ye wrote the paper. Hongxin Zhang, Shuhan Lu, Bin Chen and Qiang Chen revised the paper. Peng Yuan acquired the funding. All authors read and approved the final manuscript. Funding This study was supported by the National Science Basic Research Plan in Shaanxi Province of China (grants 2024JC-YBMS-731). Convergence Research Funding Initiative of Fourth Military Medical University (2024JC030). Xi'an Jiaotong University Faculty Discovery and Innovation Initiative (xzy012025152). Data availability All datasets generated and/or analyzed during this study are available from the corresponding author upon reasonable request. Ethics approval and consent to participate All experimental procedures involved were performed according to protocols approved by The Fourth Military Medical University. All healthy controls and patients with MDD provided written informed consent for providing blood samples in accordance with the local ethical committee. The study was conducted with approval from the Research Ethics Committee. Competing interests The authors declare no competing interests. References Z.M. Younossi, M. Kalligeros, L. 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16:26:58","extension":"html","order_by":56,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":176282,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/bbc9c27f514ccb55332f1519.html"},{"id":97371323,"identity":"5423fa6e-739a-48ae-a9f0-71f2ada53ba6","added_by":"auto","created_at":"2025-12-03 16:28:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":52570715,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHepatic NPAS2 expression is elevated in MASLD.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003eqPCR analysis of \u003cem\u003eNPAS2\u003c/em\u003e mRNA in human MASLD (n=18) and control livers (n=8). \u003cstrong\u003e(B)\u003c/strong\u003e(Left) Representative Western blot images of NPAS2 protein levels in liver tissues from MASLD patients (n=18) and healthy controls (n=8); (Right) Quantitative heatmap of band intensity grayscale values derived from Western blot analysis. Each row represents an individual biological replicate (MASLD: n=18; controls: n=8), with color intensity reflecting relative NPAS2 expression levels (scale bar shown). \u003cstrong\u003e(C)\u003c/strong\u003eRepresentative H\u0026amp;E and Oil Red O staining of liver sections from HFD-fed and chow-fed mice (scale bars: 50 μm). \u003cstrong\u003e(D)\u003c/strong\u003e qPCR analysis of \u003cem\u003eNpas2\u003c/em\u003e mRNA in HFD-fed and chow-fed murine livers (n=6/group).\u003cstrong\u003e (E) \u003c/strong\u003e(Left) Representative Western blot images showing NPAS2 protein levels in liver tissues from HFD-fed and chow-fed mice (n=6/group); (Right) Quantitative heatmap of band intensity grayscale values derived from Western blot analysis. Each row represents an individual biological replicate (n=6/group), with color intensity reflecting relative NPAS2 expression levels (scale bar shown). \u003cstrong\u003e(F)\u003c/strong\u003e Diurnal \u003cem\u003eNpas2\u003c/em\u003e expression patterns in HFD-fed and chow-fed mice (n=6/group).\u003c/p\u003e\n\u003cp\u003eData presented as mean ± SEM. Statistical analysis by two-tailed Welch’s t-test (A,B,D,E) or Cosinor regression (F). *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/07266e00ccc619b654cec69e.png"},{"id":97360637,"identity":"a9c954cd-6d74-4d9d-9c88-3f94fd3fc65f","added_by":"auto","created_at":"2025-12-03 14:25:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":19001926,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNPAS2 modulates lipid metabolism and inflammation in hepatocytes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A) \u003c/strong\u003e(Left) Representative Western blot images showing NPAS2 protein levels in LO2 hepatocytes treated with free fatty acid (FAA) versus untreated controls (n=3/group); (Right) Quantitative heatmap of band intensity grayscale values derived from Western blot analysis. Each row represents an independent biological replicate (n=3/group), with color intensity reflecting relative NPAS2 expression levels (scale bar shown). \u003cstrong\u003e(B,C)\u003c/strong\u003eRepresentative Oil Red O (scale bars: 20 μm) and Nile Red staining (scale bars: 10 μm) of lipid droplets in NPAS2 knockdown (sh\u003cem\u003eNpas2\u003c/em\u003e, B) or overexpression (\u003cem\u003eNPAS2\u003c/em\u003e-OE, C) LO2 cells under FAA conditions. \u003cstrong\u003e(D,E)\u003c/strong\u003e Triglyceride (TG) and total cholesterol (TC) levels in sh\u003cem\u003eNpas2\u003c/em\u003e(D, n=6) or \u003cem\u003eNPAS2\u003c/em\u003e-OE (E, n=6) LO2 cells versus controls (n=6). \u003cstrong\u003e(F,G)\u003c/strong\u003e qPCR analysis of inflammatory cytokines in sh\u003cem\u003eNpas2\u003c/em\u003e (F, n=6) or \u003cem\u003eNPAS2\u003c/em\u003e-OE (G, n=6) LO2 cells versus controls (n=6).\u003c/p\u003e\n\u003cp\u003eData presented as mean ± SEM. Statistical analysis by two-tailed Welch’s t-test (A，and D-F). *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/a4e90721197c74a01add99a7.png"},{"id":97370105,"identity":"f748547e-6810-4009-ab50-79496c452dfc","added_by":"auto","created_at":"2025-12-03 16:26:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48048118,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHepatocyte-specific NPAS2 knockout improves metabolic parameters in HFD-fed mice.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003e Schematic of hepatocyte-specific \u003cem\u003eNpas2\u003c/em\u003e knockout (LKO) mouse generation and experimental design, including high-fat diet (HFD) or normal chow (NC) feeding regimen. \u003cstrong\u003e(B)\u003c/strong\u003eLiver weight and liver-to-body weight ratio in HFD-fed \u003cem\u003eNpas2\u003c/em\u003e LKO and control mice (n=8/group). \u003cstrong\u003e(C)\u003c/strong\u003e Hepatic triglyceride (TG) and total cholesterol (TC) levels in \u003cem\u003eNpas2\u003c/em\u003e LKO and control mice (n=8). \u003cstrong\u003e(D)\u003c/strong\u003e Serum TG and TC levels in \u003cem\u003eNpas2\u003c/em\u003e LKO and control mice (n=8/group). \u003cstrong\u003e(E)\u003c/strong\u003e Body weight trajectory of \u003cem\u003eNpas2\u003c/em\u003e LKO and control mice (n=8/group) during 16-week HFD feeding. \u003cstrong\u003e(F)\u003c/strong\u003eRepresentative H\u0026amp;E and Oil Red O staining of liver sections from HFD-fed \u003cem\u003eNpas2\u003c/em\u003e LKO and control mice. \u003cstrong\u003e(G)\u003c/strong\u003e Serum ALT and AST levels in \u003cem\u003eNpas2\u003c/em\u003e LKO and control mice (n=6/group). \u003cstrong\u003e(G)\u003c/strong\u003e Hepatic ALT and AST levels in \u003cem\u003eNpas2\u003c/em\u003e LKO and control mice (n=6/group). \u003cstrong\u003e(I)\u003c/strong\u003e qPCR analysis of lipid metabolism genes in \u003cem\u003eNpas2\u003c/em\u003e LKO and control livers (n=8/group).\u003c/p\u003e\n\u003cp\u003eData presented as mean ± SEM. Statistical analysis by two-way ANOVA (B-D, G-I) or Welch’s t-test (E). *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/303c2568d269778ee18a6d68.png"},{"id":97371498,"identity":"44c815f7-7236-4111-bad5-b8b66107696d","added_by":"auto","created_at":"2025-12-03 16:29:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":29758100,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNPAS2 regulates metabolic dysfunction through PPARγ signaling.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003e (Left) Fasting blood glucose, (Middle) serum insulin levels, and (Right) HOMA-IR index (n=6/group) in control and \u003cem\u003eNpas2\u003c/em\u003e LKO mice.\u003cstrong\u003e (B) \u003c/strong\u003e(left) Representative Western blots of p-AKT and total AKT; (right) Quantification of p-AKT/AKT ratio (n=6/group). \u003cstrong\u003e(C)\u003c/strong\u003e Hepatic mRNA expression of ER stress markers (\u003cem\u003eGrp78\u003c/em\u003e, \u003cem\u003eXbp1s\u003c/em\u003e, \u003cem\u003eChop\u003c/em\u003e, \u003cem\u003eAtf4\u003c/em\u003e, \u003cem\u003eOrp150\u003c/em\u003e) by qPCR (n=6/group). \u003cstrong\u003e(D) \u003c/strong\u003e(Left) Hepatic malondialdehyde (MDA) content; (Right) Antioxidant enzyme (SOD2, GPX) activities in liver homogenates (n=6/group). \u003cstrong\u003e(E)\u003c/strong\u003e (Left) Hepatic pro-inflammatory cytokine (\u003cem\u003eIl1b\u003c/em\u003e, \u003cem\u003eIl6\u003c/em\u003e, \u003cem\u003eTnf\u003c/em\u003e) mRNA levels (n=6/group); (Right) Serum cytokine concentrations by ELISA (n=6/group). \u003cstrong\u003e(F)\u003c/strong\u003e Hepatic mRNA expression of fibrosis-related genes (\u003cem\u003eCol1a1\u003c/em\u003e, \u003cem\u003eCol3a1\u003c/em\u003e, \u003cem\u003eActa2\u003c/em\u003e, \u003cem\u003eTgfb\u003c/em\u003e1) by qPCR (n=6/group). \u003cstrong\u003e(G)\u003c/strong\u003e (Left) qPCR and (Right)\u003cstrong\u003e \u003c/strong\u003eWestern blot analysis of PPARα, PPARβ/δ, and PPARγ in \u003cem\u003eNpas2\u003c/em\u003eLKO and overexpression models (n=6/group). \u003cstrong\u003e(H) \u003c/strong\u003eTemporal expression patterns of NPAS2 and PPARγ proteins in liver lysates.\u003c/p\u003e\n\u003cp\u003eData presented as mean ± SEM. Statistical analysis by two-way ANOVA (A-G) or Welch’s t-test (E). *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/ed00c2dd64d7b247b3a939b4.png"},{"id":97360668,"identity":"7d01a9cb-0fcb-4fb9-aef5-0dc35695234c","added_by":"auto","created_at":"2025-12-03 14:25:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":16650149,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNPAS2 transcriptionally regulates SIRT1 to control PPARγ acetylation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Acetylated PPARγ levels in \u003cem\u003eNPAS2\u003c/em\u003e knockdown (sh\u003cem\u003eNPAS2\u003c/em\u003e) or \u003cem\u003eNPAS2\u003c/em\u003e-overexpressing （\u003cem\u003eNPAS2\u003c/em\u003e-OE）and control hepatocytes by immunoprecipitation. \u003cstrong\u003e(B)\u003c/strong\u003e qPCR analysis of \u003cem\u003eSIRT1\u003c/em\u003e mRNA in sh\u003cem\u003eNPAS2\u003c/em\u003e or \u003cem\u003eNPAS2\u003c/em\u003e-OE and control hepatocytes (n=6/group). \u003cstrong\u003e(C)\u003c/strong\u003eWestern blot analysis of SIRT1 protein in sh\u003cem\u003eNPAS2\u003c/em\u003eor \u003cem\u003eNPAS2\u003c/em\u003e-OE and control hepatocytes. \u003cstrong\u003e(D)\u003c/strong\u003e Luciferase reporter assay of \u003cem\u003eSIRT1\u003c/em\u003e promoter constructs in \u003cem\u003eNPAS2\u003c/em\u003e-OE and control hepatocytes. \u003cstrong\u003e(E)\u003c/strong\u003e Site-directed mutagenesis analysis of the \u003cem\u003eSIRT1\u003c/em\u003e E-box element. \u003cstrong\u003e(F)\u003c/strong\u003e ChIP-PCR of NPAS2 binding to the \u003cem\u003eSIRT1\u003c/em\u003e promoter. \u003cstrong\u003e(G)\u003c/strong\u003e Western blot analysis of PPARγ and acetylated PPARγ in LO2 cells with NPAS2/SIRT1 combinatorial modulation.\u003c/p\u003e\n\u003cp\u003eData presented as mean ± SEM. Statistical analysis by Welch's t-test (B, D and E). *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/aa0c8be8265dd069966967c2.png"},{"id":97371252,"identity":"1b719897-c512-434c-a15d-99c4cd075992","added_by":"auto","created_at":"2025-12-03 16:28:37","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":77997936,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNPAS2 deficiency protects against MASLD-HCC progression.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eImmunohistochemical analysis of NPAS2, SIRT1, and PPARγ expression in human MASLD-HCC and normal liver tissues (n=20, scale bars: 100 μm). \u003cstrong\u003e(B) \u003c/strong\u003eSchematic of DEN-induced HCC model in HFD-fed \u003cem\u003eNpas2\u003c/em\u003eLKO mice. \u003cstrong\u003e(C) \u003c/strong\u003eTumor incidence in control and \u003cem\u003eNpas2\u003c/em\u003e LKO mice (n=10/group). \u003cstrong\u003e(D) \u003c/strong\u003eRepresentative macroscopic liver images and H\u0026amp;E staining of liver sections.\u003cstrong\u003e (E) \u003c/strong\u003eLiver-to-body weight ratios in control and \u003cem\u003eNpas2\u003c/em\u003e LKO mice (n=8/group).\u003cstrong\u003e (F) \u003c/strong\u003eSerum ALT and AST levels in control and \u003cem\u003eNpas2\u003c/em\u003e LKO mice (n=8/group). \u003cstrong\u003e(G) \u003c/strong\u003eHepatic pro-inflammatory cytokine (\u003cem\u003eTnf\u003c/em\u003e, \u003cem\u003eIl6\u003c/em\u003e, \u003cem\u003eIl1b\u003c/em\u003e) mRNA levels by qPCR in control and \u003cem\u003eNpas2\u003c/em\u003e LKO mice (n=8/group). \u003cstrong\u003e(H) \u003c/strong\u003eRepresentative immunohistochemistry and quantification of Ki67-positive cells.\u003cstrong\u003e (I) \u003c/strong\u003emRNA expression of HCC markers (\u003cem\u003eAfp\u003c/em\u003e, \u003cem\u003eGpc3\u003c/em\u003e, \u003cem\u003eEpcam\u003c/em\u003e, \u003cem\u003eCd44\u003c/em\u003e) by qRT-PCR in control and \u003cem\u003eNpas2\u003c/em\u003e LKO mice (n=6/group).\u003cstrong\u003e (J) \u003c/strong\u003eWestern blot analysis of SIRT1 activity markers and PPARγ acetylation status in control and \u003cem\u003eNpas2\u003c/em\u003e LKO mice.\u003c/p\u003e\n\u003cp\u003eData presented as mean ± SEM. Statistical analysis by two-way ANOVA (E-I). *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/ea7c132f30ca9def1810596d.png"},{"id":97360653,"identity":"8f3e7deb-95ba-4577-88b2-80d537e4fb46","added_by":"auto","created_at":"2025-12-03 14:25:18","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":50298432,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNPAS2 overexpression accelerates MASLD-HCC pathogenesis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eSchematic of AAV8-mediated \u003cem\u003eNpas2\u003c/em\u003eoverexpression (OE) strategy. \u003cstrong\u003e(B) \u003c/strong\u003eTumor incidence in DEN-induced HCC models with \u003cem\u003eNpas2-\u003c/em\u003eOE and wild-type controls (n=10/group). \u003cstrong\u003e(C) \u003c/strong\u003eRepresentative macroscopic liver images and H\u0026amp;E staining.\u003cstrong\u003e (D) \u003c/strong\u003eLiver-to-body weight ratios in control and \u003cem\u003eNpas2-\u003c/em\u003eOE mice (n=6/group).\u003cstrong\u003e (E)\u003c/strong\u003e Serum ALT and AST levels in control and \u003cem\u003eNpas2-\u003c/em\u003eOE mice (n=6/group).\u003cstrong\u003e (F) \u003c/strong\u003eHepatic pro-inflammatory cytokine (\u003cem\u003eTnf\u003c/em\u003e, \u003cem\u003eIl6\u003c/em\u003e, \u003cem\u003eIl1b\u003c/em\u003e) mRNA levels by qPCR in control and \u003cem\u003eNpas2-\u003c/em\u003eOE mice (n=6/group). \u003cstrong\u003e(G) \u003c/strong\u003eRepresentative immunohistochemistry and quantification of Ki67-positive cells in control and \u003cem\u003eNpas2-\u003c/em\u003eOE mice (n=6/group).\u003cstrong\u003e (H) \u003c/strong\u003emRNA expression of stemness markers (\u003cem\u003eEpcam\u003c/em\u003e, \u003cem\u003eCd44\u003c/em\u003e) and HCC markers (\u003cem\u003eAfp\u003c/em\u003e, \u003cem\u003eGpc3\u003c/em\u003e) by qRT-PCR in control and \u003cem\u003eNpas2-\u003c/em\u003eOE mice (n=6/group).\u003cstrong\u003e (I) \u003c/strong\u003eWestern blot analysis of SIRT1 activity markers and PPARγ acetylation status in control and \u003cem\u003eNpas2-\u003c/em\u003eOE mice.\u003c/p\u003e\n\u003cp\u003eData presented as mean ± SEM. Statistical analysis by two-way ANOVA (D-H) or Welch's t-test (E). *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/00144b03d540067525767bfc.png"},{"id":97371218,"identity":"ce63de0d-09fe-47d7-972c-9743c62d54d1","added_by":"auto","created_at":"2025-12-03 16:28:32","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":32641573,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePharmacological PPARγ activation rescues NPAS2-mediated metabolic dysregulation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A) \u003c/strong\u003eSchematic of experimental design using free fatty acid (FFA)-treated LO2 hepatocytes with \u003cem\u003eNPAS2\u003c/em\u003eoverexpression (OE) and pioglitazone intervention.\u003cstrong\u003e (B) \u003c/strong\u003eqRT-PCR analysis of PPARγ downstream targets (\u003cem\u003eCd36\u003c/em\u003e and \u003cem\u003eFabp4\u003c/em\u003e) in \u003cem\u003eNPAS2\u003c/em\u003e-OE LO2 cells treated with or without pioglitazone (10 μM, 48h，n=6/group). \u003cstrong\u003e(C) \u003c/strong\u003eRepresentative images of intracellular lipid accumulation by Oil Red O staining. \u003cstrong\u003e(D)\u003c/strong\u003e Representative images of neutral lipid content by Nile Red staining. \u003cstrong\u003e(E) \u003c/strong\u003eCellular triglyceride and total cholesterol levels measured by enzymatic assays (n=6/group). \u003cstrong\u003e(F) \u003c/strong\u003eCell proliferation assessed by CCK-8 assay under FFA conditions with or without pioglitazone treatment.\u003c/p\u003e\n\u003cp\u003eData presented as mean ± SEM. Statistical analysis by Welch's t-test (E). *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"fig8.png","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/cc1509a7045e2bc63f46a650.png"},{"id":97370973,"identity":"3cd31aa4-f935-49b7-936d-8c4109dc018b","added_by":"auto","created_at":"2025-12-03 16:28:13","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":8031819,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic model of NPAS2-driven metabolic dysregulation and hepatocarcinogenesis in MASLD progression.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig9.png","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/b153007d02ec5ec7af35bf74.png"},{"id":97360605,"identity":"bb946b81-4a59-492d-8a3c-5dd2b47ccbf5","added_by":"auto","created_at":"2025-12-03 14:25:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1077075,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/de735eca-802f-4e43-8519-01e1bc8a7f9c.pdf"},{"id":97360624,"identity":"1e2f46bd-3886-41cd-aec7-e8748c3afd30","added_by":"auto","created_at":"2025-12-03 14:25:16","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":31911,"visible":true,"origin":"","legend":"Supplementary information","description":"","filename":"Supplementaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/30a0f17641856c9850c4249a.docx"},{"id":97360621,"identity":"29b6881b-5128-48e8-8c22-fc1eb42aa5f9","added_by":"auto","created_at":"2025-12-03 14:25:16","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":463127,"visible":true,"origin":"","legend":"","description":"","filename":"FigS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/a20e058a36a1bb6eee9d073a.tif"},{"id":97371019,"identity":"726d09f5-ab61-45ce-90df-a7221c809bb7","added_by":"auto","created_at":"2025-12-03 16:28:16","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":327509,"visible":true,"origin":"","legend":"","description":"","filename":"figS2.tif","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/cb12fd96f63dc9ff54c2eacf.tif"},{"id":97360623,"identity":"bffbaf9c-fd4c-40ec-ad74-0742f37ba14f","added_by":"auto","created_at":"2025-12-03 14:25:16","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":313068,"visible":true,"origin":"","legend":"","description":"","filename":"FigS3.tif","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/54bb242221ede3e02c3674d1.tif"},{"id":97360620,"identity":"966e81a1-1640-4ce8-b788-8165f67bb777","added_by":"auto","created_at":"2025-12-03 14:25:16","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":580725,"visible":true,"origin":"","legend":"","description":"","filename":"FigS4.tif","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/27fce9f06b43386bcd98963c.tif"},{"id":97360643,"identity":"db5f00ae-4e72-4211-b4cc-cc17014b2ebf","added_by":"auto","created_at":"2025-12-03 14:25:17","extension":"tif","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":232804,"visible":true,"origin":"","legend":"","description":"","filename":"FigS5.tif","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/ceff962d7234c9d039e31cb4.tif"},{"id":97360636,"identity":"96a1f05d-bc9e-4b13-9f2e-66be2a050a44","added_by":"auto","created_at":"2025-12-03 14:25:17","extension":"svg","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":520620,"visible":true,"origin":"","legend":"","description":"","filename":"FigS6.svg","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/97870c6db66c39a22db1a124.svg"},{"id":97360641,"identity":"8f7606f5-fafa-41a8-b9da-297699ebe89e","added_by":"auto","created_at":"2025-12-03 14:25:17","extension":"tif","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":293294,"visible":true,"origin":"","legend":"","description":"","filename":"FigS7.tif","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/1846661dded004dae3868b1e.tif"},{"id":97360631,"identity":"b8ea1a6a-73c8-4239-83c4-f415b277e715","added_by":"auto","created_at":"2025-12-03 14:25:17","extension":"tif","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":756254,"visible":true,"origin":"","legend":"","description":"","filename":"FigS8.tif","url":"https://assets-eu.researchsquare.com/files/rs-8137044/v1/ffc3389b5cf77c0c7ebbd936.tif"}],"financialInterests":"(Not answered)","formattedTitle":"NPAS2 Promotes MASLD and Hepatocarcinogenesis through SIRT1-Mediated PPARγ Suppression","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMetabolic dysfunction-associated steatotic liver disease (MASLD, formerly known as NAFLD) has emerged as the most prevalent chronic liver disorder worldwide, currently affecting 38% of adults and 7\u0026ndash;14% of children and adolescents, with adult prevalence projected to exceed 55% by 2040[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. While the \"multiple-hit hypothesis\" has replaced the earlier \"two-hit hypothesis,\" providing a clearer framework for understanding disease pathogenesis, the molecular drivers orchestrating progression to steatohepatitis (MASH, formerly NASH), fibrosis, and ultimately hepatocellular carcinoma (HCC) remain incompletely understood[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This mechanistic gap explains the current lack of targeted therapies, with management still relying on lifestyle modifications and metabolic control that show limited efficacy in advanced disease[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Consequently, MASLD-related complications now represent the fastest-growing cause of liver-related mortality, with MASLD-HCC emerging as the most rapidly increasing indication for orthotopic liver transplantation (rising from 2.1% to 16.2% of cases between 2000\u0026ndash;2016)[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Among patients with MASLD cirrhosis, HCC develops at an annual incidence of 0.7\u0026ndash;2.6%[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], while global projections suggest a 122% increase in MASLD-HCC cases by 2030[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The escalating clinical and economic burden underscores the urgent need to decipher pathogenic mechanisms that could enable precision therapeutics.\u003c/p\u003e\u003cp\u003eMetabolic homeostasis is sustained by circadian coordination of nutrient handling. Environmental or genetic disruption of this timing system\u0026mdash;manifested as dampened amplitude or phase-shifted oscillations of clock-controlled genes (CCGs)\u0026mdash;is now recognized as a causal determinant of metabolic disorders[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The hepatic circadian network exemplifies how the molecular clock is hard-wired to metabolism. BMAL1, REV-ERBα/β, Neuronal PAS Domain Protein 2 (NPAS2), and PER/CRY occupy promoters of key metabolic genes, enabling time-of-day\u0026ndash;specific transcription[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Within this framework, PPAR family members display pronounced circadian expression[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. PPARα cooperates with PGC-1α to activate fatty-acid β-oxidation during the active phase[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], while rhythmic repression of SREBP-1c by clock components temporally restrains lipogenesis[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], together forming an antiphasic \u0026ldquo;catabolism\u0026ndash;anabolism\u0026rdquo; cycle that preserves hepatic lipid balance. An additional layer of control is provided by post-translational regulation. Acetylation of PPARγ modulates adipose plasticity and systemic metabolic rhythms, and pharmacological manipulation of PPARγ acetylation holds promise for restoring metabolic oscillations in models of obesity and aging[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eImportantly, this circadian-metabolic interplay is bidirectional. Highly conserved nutrient-sensing pathways actively communicate cellular metabolic status to the circadian clock, creating a sophisticated feedback network[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. For instance, high-fat diet (HFD)-induced metabolic disturbances can directly alter circadian parameters, modifying both period length and amplitude of locomotor activity rhythms[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. These findings not only establish the central role of the circadian system in lipid metabolic regulation, but more importantly reveal a vicious cycle wherein metabolic disturbances (e.g., HFD) disrupt circadian gene expression, which in turn exacerbates metabolic dysfunction through aberrant regulation of lipid homeostasis - potentially serving as a key driver in MASLD pathogenesis.\u003c/p\u003e\u003cp\u003eNPAS2 uniquely integrates circadian and metabolic signals through its hypoxia-sensitive PAS domain. Unlike other clock proteins, it specifically responds to steatotic stress while maintaining canonical clock functions via BMAL1 heterodimerization[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Emerging evidence has highlighted NPAS2's critical responsiveness to metabolic perturbations. In a compelling non-human primate model, maternal HFD was shown to induce persistent epigenetic reprogramming of the hepatic \u003cem\u003eNPAS2\u003c/em\u003e locus through increased H3K14ac at its promoter region[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This modification was associated with persistent metabolic dysfunction and non-alcoholic fatty liver disease that lasts at least until the age of 3[\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The orphan nuclear receptor SHP has been identified as a key upstream regulator of NPAS2, modulating hepatic lipid metabolism through transcriptional repression of \u003cem\u003eNPAS2\u003c/em\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, this finding alone cannot fully explain NPAS2's pleiotropic metabolic effects.\u003c/p\u003e\u003cp\u003eTo elucidate the role of NPAS2 in the development and progression of MASLD and its associated HCC, we systematically analyzed public datasets, assessed its expression patterns in clinical liver biopsies and HFD murine models, and employed a series of functional validation approaches to decipher its molecular mechanisms in regulating MASLD metabolic homeostasis. Furthermore, through preclinical models and clinical specimens, we elucidated the therapeutic potential of targeting the NPAS2 regulatory axis for precision medicine in MASLD. These findings not only provide novel insights into the circadian-metabolic crosstalk in liver diseases, but also open new avenues for developing chronotherapeutic strategies against MASLD and its malignant complications.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eCollection of human liver samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study utilized human liver tissues from two cohorts: normal controls and patients with MASLD. Normal control tissues (n=8) were acquired from surgical resection of hepatic cysts or hemangiomas. All control tissues were histologically confirmed to be free of steatosis, inflammation, and fibrosis. The MASLD cohort (n=18) consisted of liver biopsy samples from patients diagnosed according to established clinical and histopathological criteria. All patients provided written informed consent prior to participation. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki and was approved by the Institutional Ethics Committee of the Fourth Military Medical University. To minimize confounding factors, control and MASLD groups were matched for age, sex, and body mass index (BMI) where possible.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGeneration of Genetically Modified Mice\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe hepatocyte-specific NPAS2 knockout (\u003cem\u003eNpas2\u0026nbsp;\u003c/em\u003eLKO) mice on a C57BL/6J background were generated using the CRISPR/Cas9-mediated genome editing system.[23]. Briefly, sgRNAs and donor oligonucleotides were designed to insert loxP sites flanking critical exons of the \u003cem\u003eNpas2\u003c/em\u003e gene. Npas2\u003csup\u003efl/fl\u003c/sup\u003e mice were then crossed with transgenic mice expressing Cre recombinase under the control of the albumin promoter (Alb-Cre) to achieve hepatocyte-specific deletion. \u003cem\u003eNpas2\u003c/em\u003e\u003csup\u003efl/fl\u003c/sup\u003e; Alb-Cre\u003csup\u003e-\u003c/sup\u003e littermates were used as controls throughout the study. All mice were genotyped by PCR analysis of tail DNA prior to experiments.\u003c/p\u003e\n\u003cp\u003eFor hepatic \u003cem\u003eNPAS2\u003c/em\u003e overexpression (OE), adult C57BL/6J mice were intravenously injected with 1\u0026times;10\u003csup\u003e11\u003c/sup\u003e viral genomes (vg) of an adeno-associated virus serotype 8 vector expressing mouse \u003cem\u003eNpas2\u003c/em\u003e under the control of the liver-specific thyroxine-binding globulin (TBG) promoter (AAV8-TBG-\u003cem\u003eNpas2\u003c/em\u003e). Control mice received an equivalent dose of AAV8-TBG-GFP.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell Culture and Steatosis Model Establishment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe human hepatic LO2 cell line was obtained from STEM RECELL. Cells were routinely maintained in high-glucose Dulbecco\u0026apos;s Modified Eagle Medium (DMEM, Gibco, Cat# 11965092) supplemented with 10% fetal bovine serum (FBS, Gibco, Cat# 10270106) and 1% penicillin/streptomycin (Gibco, Cat# 15140122) at 37\u0026deg;C in a 5% CO₂ humidified atmosphere.\u003c/p\u003e\n\u003cp\u003eTo establish an in vitro model of hepatic steatosis, LO2 cells were treated with a free fatty acid (FFA) mixture. A 100 mM stock solution of oleic acid (OA) and palmitic acid (PA) at a 2:1 molar ratio was prepared in 0.1 M NaOH by conjugation with fatty acid-free bovine serum albumin (BSA, Sigma, Cat# A8806). The FFA working solution was prepared by diluting the stock in complete culture medium to a final concentration of 0.5 mM (OA: 0.33 mM, PA: 0.17 mM). Cells were treated with the FFA mixture or an equivalent concentration of BSA (vehicle control) for 24 to 48 hours to induce lipid accumulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGeneration of Stable Knockdown and Overexpression Cell Lines\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor NPAS2 knockdown (KD), lentiviral vectors expressing short hairpin RNAs (shRNAs) targeting human NPAS2 (shNPAS2) or a non-targeting control scramble sequence (shCtrl) were constructed (Ambion). The target sequences were as follows:\u003c/p\u003e\n\u003cp\u003eshNPAS2: 5\u0026apos;-[ CGUCGGAUGUCAUGGAUCA]-3\u0026apos;\u003c/p\u003e\n\u003cp\u003eFor NPAS2 overexpression (OE), the full-length coding sequence of human NPAS2 was cloned into a lentiviral expression vector (pCDH-CMV-MCS-EF1-Puro, [Invitrogen]).\u003c/p\u003e\n\u003cp\u003eLentiviral particles were produced by co-transfecting 293T cells with the transfer plasmid (shRNA or OE) and packaging plasmids (psPAX2 and pMD2.G) using polyethylenimine (PEI, Polysciences, Cat# 24765). Viral supernatants were collected 48 and 72 hours post-transfection, filtered through a 0.45 \u0026mu;m filter, and used to transduce LO2 cells in the presence of 8 \u0026mu;g/mL polybrene (Sigma, Cat# H9268).\u003c/p\u003e\n\u003cp\u003eFor stable cell line selection, transduced cells were cultured under puromycin (InvivoGen, Cat# ant-pr-1) selection (2 \u0026mu;g/mL) for at least 7 days. The knockdown and overexpression efficiency was validated at both the mRNA and protein levels by quantitative RT-PCR (qRT-PCR) and Western blot analysis, respectively, prior to functional experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBioinformatics Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe expression levels of NPAS2 in human and murine MASLD/HCC samples were assessed using publicly available datasets from the Gene Expression Omnibus (GEO) database. The human MASLD dataset GSE35251, comprising 206 MASLD patients and 10 healthy controls, was analyzed. The murine MASLD-HCC progression dataset GSE67680, profiling gene expression across the spectrum from normal liver to steatosis, MASH, and HCC, was analyzed. Differential expression analysis of the \u003cem\u003eNPAS2\u003c/em\u003e/\u003cem\u003eNpas2\u003c/em\u003e gene between predefined sample groups for each dataset was performed using the GEO2R interactive web tool (https://www.ncbi.nlm.nih.gov/geo/geo2r/). For each comparison, the default parameters of GEO2R were used. The potential interaction between PPAR\u0026gamma; and SIRT1 was computationally predicted using the STRING database (version 12.0,\u0026nbsp;\u003ca href=\"https://string-db.org/\" target=\"_blank\"\u003ehttps://string-db.org/\u003c/a\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative Real-Time PCR (qRT-PCR) Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted from liver tissues or cultured LO2 cells using TRIzol\u0026trade; Reagent (Invitrogen, Cat# 15596026) according to the manufacturer\u0026apos;s instructions. RNA concentration and purity were determined by measuring the absorbance at 260/280 nm using a NanoDrop spectrophotometer (Thermo Fisher Scientific). RNA integrity was confirmed by 1% agarose gel electrophoresis. Complementary DNA (cDNA) was synthesized from 1 \u0026micro;g of total RNA using the PrimeScript\u0026trade; RT Master Mix (Perfect Real Time) (Takara, Cat# RR036A) in a 20 \u0026micro;L reaction volume.\u003c/p\u003e\n\u003cp\u003eqRT-PCR was performed in triplicate for each sample using TB Green\u0026trade; Premix Ex Taq\u0026trade; II (Tli RNaseH Plus) (Takara, Cat# RR820A) on a QuantStudio\u0026trade; 6 Pro Real-Time PCR System (Applied Biosystems). The amplification program consisted of an initial denaturation at 95\u0026deg;C for 30 seconds, followed by 40 cycles of 95\u0026deg;C for 5 seconds and 60\u0026deg;C for 30 seconds. A melt curve analysis was performed at the end of each run to confirm the specificity of amplification. The relative mRNA expression levels were calculated using the comparative 2^(-\u0026Delta;\u0026Delta;Ct) method and normalized to the expression of the housekeeping gene \u0026beta;-actin (ACTB). All primer sequences used are listed in Supplementary Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWestern Blotting Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLiver tissues and cultured cells were lysed in RIPA Lysis and Extraction Buffer (Thermo Fisher Scientific, Cat# 89900) supplemented with a Halt\u0026trade; Protease and Phosphatase Inhibitor Cocktail (Thermo Fisher Scientific, Cat# 78440). Protein concentrations were determined using a BCA Protein Assay Kit (Pierce, Cat# 23225). Equal amounts of protein (typically 20-35 \u0026micro;g per lane) were separated by SDS-polyacrylamide gel electrophoresis (SDS-PAGE) on 8-12% gels and subsequently transferred onto polyvinylidene fluoride (PVDF) membranes (Millipore, Cat# IPVH00010).\u003c/p\u003e\n\u003cp\u003eThe membranes were blocked with 5% (w/v) non-fat milk in Tris-buffered saline containing 0.1% Tween-20 (TBST) for 1 hour at room temperature and then incubated with specific primary antibodies diluted in blocking buffer overnight at 4\u0026deg;C. After washing three times with TBST, the membranes were incubated with appropriate horseradish peroxidase (HRP)-conjugated secondary antibodies (Jackson ImmunoResearch) for 1 hour at room temperature. Protein bands were visualized using an enhanced chemiluminescence (ECL) substrate (Millipore, Cat# WBKLS0500) and imaged with a ChemiDoc\u0026trade; Touch Imaging System (Bio-Rad). Band intensities were quantified using Image Lab\u0026trade; Software (Bio-Rad). All antibodies used, including their catalog numbers and dilutions, are listed in Supplementary Table 5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHematoxylin and Eosin (H\u0026amp;E) and Immunohistochemistry (IHC)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParaffin-embedded liver sections (4-5 \u0026mu;m) were prepared. For H\u0026amp;E staining, sections were deparaffinized, rehydrated, and stained using standard protocols. For IHC, after antigen retrieval in citrate buffer (pH 6.0) and blocking of endogenous peroxidase, sections were incubated overnight at 4\u0026deg;C with primary antibodies against NPAS2 and Ki-67. Binding was detected using an HRP-conjugated secondary antibody and a DAB substrate kit (MXB Biotechnologies, Cat#KIT-9720). All sections were counterstained with hematoxylin, imaged under an Olympus BX53 microscope, and evaluated by blinded observers. All antibodies used, including their catalog numbers and dilutions, are listed in Supplementary Table 6.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOil Red O Staining\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrozen liver sections (8 \u0026mu;m) were fixed in 4% PFA, stained with filtered Oil Red O working solution (0.3% in 60% isopropanol) for 15 min, and counterstained with hematoxylin. LO2 hepatocytes were fixed in 4% PFA and stained as above. For quantification, stained lipid droplets were eluted with 100% isopropanol and the absorbance was measured at 510 nm.\u003c/p\u003e\n\u003cp\u003eLipid accumulation was quantified from images using ImageJ software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNile Red Staining for Cultured Cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLO2 hepatocytes were washed with PBS and fixed with 4% PFA for 15 min at room temperature. After washing, cells were incubated with a Nile Red working solution (1 \u0026mu;g/mL in PBS, Sigma-Aldrich, Cat# 72485) for 10 min in the dark. Nuclei were counterstained with DAPI (1 \u0026mu;g/mL, Thermo Fisher Scientific, Cat# D1306) for 5 min. Following final washes, images were immediately captured using a fluorescence microscope (Nikon Eclipse Ti2) with standard FITC (for neutral lipids) and DAPI filter sets. Fluorescence intensity was quantified using ImageJ software to assess relative lipid content.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasurement of Hepatic and Serum Lipid Profiles\u003cbr\u003e\u003c/strong\u003eUpon sacrifice, mouse blood was collected and centrifuged at 3,000 rpm for 15 minutes at 4\u0026deg;C to obtain serum. Liver tissues (approximately 100 mg) were homogenized in 1 mL of ice-cold PBS using a mechanical homogenizer. Lipids were extracted from the homogenates using a chloroform-methanol (2:1, v/v) mixture according to the method of Folch et al[24]. The concentrations of triglycerides (TGs) and total cholesterol (TC) in both serum and hepatic lipid extracts were quantified using commercial enzymatic assay kits according to the manufacturers\u0026apos; protocols (BioVision, Cat# K622, Cat# K603).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of Liver Function\u003cbr\u003e\u003c/strong\u003eLiver injury was assessed by measuring the activity of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in the serum. The assays were performed using commercial ALT (Cat# A7526-120) and AST (Cat# A5598-120) Activity Assay Kits (Sigma-Aldrich) according to the manufacturer\u0026apos;s instructions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEvaluation of Insulin Resistance\u003cbr\u003e\u003c/strong\u003eFor the assessment of insulin sensitivity, mice were fasted for 6 hours prior to blood collection. Fasting blood glucose levels were measured using a portable glucometer (OneTouch Ultra, LifeScan). Fasting serum insulin levels were determined using a Mouse Insulin ELISA Kit (Crystal Chem, Cat# 90080) according to the manufacturer\u0026apos;s protocol. The homeostatic model assessment of insulin resistance (HOMA-IR) index was calculated using the following formula:\u003cbr\u003eHOMA-IR = [Fasting Glucose (mmol/L) \u0026times; Fasting Insulin (\u0026mu;U/mL)] / 22.5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of Public ChIP-seq Data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify direct transcriptional targets of NPAS2, we re-analyzed a publicly available NPAS2 ChIP-on-chip dataset (GSE \u0026nbsp;from [GSE11923]). The association of NPAS2 binding with specific biological pathways was investigated by performing Gene Ontology (GO) biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the genes whose promoter regions (\u0026plusmn; 3 kb from the transcription start site) were bound by NPAS2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCo-Immunoprecipitation (Co-IP)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate protein-protein interactions, Co-IP was performed. LO2 cells were lysed in NP-40 lysis buffer (Beyotime, Cat# P0013F) supplemented with protease inhibitors. For each reaction, 500 \u0026mu;g of total protein was incubated with 2 \u0026mu;g of anti-PPAR\u0026gamma; antibody (Cell Signaling Technology, Cat# 2443S) or normal rabbit IgG (negative control, Cell Signaling Technology, Cat# 2729S) overnight at 4\u0026deg;C with gentle rotation. Protein A/G Magnetic Beads (MedChemExpress, Cat# HY-K0202) were then added and incubated for 2 hours. The immunoprecipitates were washed five times with lysis buffer, eluted in 2\u0026times; SDS loading buffer by boiling for 10 minutes, and analyzed by Western blotting using antibodies against SIRT1 and PPAR\u0026gamma;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChromatin Immunoprecipitation-quantitative PCR (ChIP-qPCR)\u003cbr\u003e\u003c/strong\u003eChIP assays were performed using the SimpleChIP\u0026reg; Plus Enzymatic Chromatin IP Kit (Magnetic Beads, Cell Signaling Technology, Cat# 9005) according to the manufacturer\u0026apos;s protocol. Briefly, LO2 cells were cross-linked with 1% formaldehyde for 10 min. Chromatin was digested with micrococcal nuclease to obtain DNA fragments predominantly between 150-900 bp. Digested chromatin was immunoprecipitated overnight at 4\u0026deg;C with 5 \u0026mu;g of anti-NPAS2 antibody (Santa Cruz Biotechnology, Cat# sc-365-829) or normal rabbit IgG. After reversing cross-links, the purified DNA was analyzed by qPCR using primers specifically flanking the E-box element in the \u003cem\u003eSIRT1\u003c/em\u003e promoter region. The results are presented as the percentage of input.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLuciferase Reporter Assay\u003cbr\u003e\u003c/strong\u003eThe transcriptional activity of NPAS2 on the \u003cem\u003eSIRT1\u003c/em\u003e promoter was measured using a dual-luciferase reporter assay system. A series of truncated fragments of the human\u003cem\u003e\u0026nbsp;SIRT1\u0026nbsp;\u003c/em\u003egene promoter were cloned into the pGL4.10[luc2] vector (Promega). LO2 cells were co-transfected with these reporter constructs and a NPAS2 expression plasmid or empty vector control, using Lipofectamine 3000. The pRL-TK \u003cem\u003eRenilla\u003c/em\u003e luciferase vector (Promega) was included as an internal control for normalization. 48 hours post-transfection, firefly and \u003cem\u003eRenilla\u003c/em\u003e luciferase activities were measured sequentially using the Dual-Luciferase\u0026reg; Reporter Assay System (Promega, Cat# E1960) on a GloMax\u0026reg; Navigator Microplate Luminometer. Firefly luciferase activity was normalized to \u003cem\u003eRenilla\u003c/em\u003e luciferase activity for each sample.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRescue Experiments via SIRT1 Modulation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the role of SIRT1 in the NPAS2-PPAR\u0026gamma; axis, rescue experiments were performed. In \u003cem\u003eNPAS2\u003c/em\u003e-overexpressing LO2 cells, \u003cem\u003eSIRT1\u003c/em\u003e was knocked down using specific siRNAs (Santa Cruz Biotechnology, Cat# sc-40986) transfected with Lipofectamine RNAiMAX (Invitrogen, Cat# 13778150). Conversely, in \u003cem\u003eNPAS2\u003c/em\u003e-knockdown cells, \u003cem\u003eSIRT1\u003c/em\u003e was overexpressed using a \u003cem\u003eSIRT1\u003c/em\u003e-expression plasmid (Addgene) transfected with Lipofectamine 3000 (Invitrogen, Cat# L3000015). The efficiency of all manipulations was confirmed by Western blot 48 hours post-transfection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell Counting Kit-8 (CCK-8) Proliferation Assay\u003cbr\u003e\u003c/strong\u003eThe viability and proliferation of LO2 hepatocytes were assessed using the Cell Counting Kit-8 (CCK-8, Dojindo Laboratories, Cat# CK04) according to the manufacturer\u0026apos;s instructions. Briefly, cells were seeded in 96-well plates at a density of 3 \u0026times; 10\u0026sup3; cells per well. After the respective treatments, 10 \u0026mu;L of CCK-8 reagent was added to each well followed by incubation at 37\u0026deg;C for 2 hours. The absorbance of the formazan product was measured at 450 nm using a microplate reader (BioTek Synergy H1). The relative cell viability was expressed as a percentage of the absorbance in the control group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePharmacological Treatments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe PPAR\u0026gamma; agonist Pioglitazone (MedChemExpress, Cat# HY-13952) was prepared as a 10 mM stock solution in dimethyl sulfoxide (DMSO) and stored at -20\u0026deg;C. For in vitro studies, LO2 hepatocytes were treated with Pioglitazone at a final concentration of 10 \u0026mu;M for 48 hours in the presence or absence of free fatty acid (FFA) challenge. The equivalent volume of DMSO (\u0026le;0.1%) was used as the vehicle control. The selective SIRT1 inhibitor EX-527 (MedChemExpress, Cat# HY-15452) was dissolved in DMSO to generate a 50 mM stock solution.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were performed using GraphPad Prism 9. Data are presented as mean \u0026plusmn; SEM from at least three independent biological replicates (n \u0026ge; 3). Normality was assessed using the Shapiro\u0026ndash;Wilk test. For comparisons between two groups of normally distributed data, an unpaired two-tailed Welch\u0026rsquo;s t-test was applied without assuming equal variances. For comparisons among three or more groups, two-way ANOVA followed by Tukey\u0026rsquo;s post hoc test was used. Non-normally distributed data were analyzed using appropriate non-parametric tests, such as the Mann\u0026ndash;Whitney U test for two-group comparisons or the Kruskal\u0026ndash;Wallis test for multiple groups. Correlations were evaluated using Pearson\u0026rsquo;s correlation coefficient. A p-value of less than 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eNPAS2 links circadian disruption to MASLD progression in humans and experimental models\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven emerging evidence linking circadian clock disruption to metabolic liver diseases, we investigated the role of the core circadian regulator NPAS2 in MASLD pathogenesis using both clinical samples and experimental models. Our study cohort comprised 8 healthy controls and 18 MASLD patients, with liver biopsy analysis demonstrating significant upregulation of NPAS2 in MASLD patients compared to non-steatotic controls. qPCR revealed a 1.7-fold increase in mRNA expression (p\u0026lt;0.001; Fig. 1A), which was confirmed at the protein level by Western blot (Fig. 1B). These clinical findings were further supported by analysis of the GSE35251 dataset, showing significantly higher \u003cem\u003eNPAS2\u003c/em\u003e expression in 206 MASLD patients compared to 10 healthy controls (p\u0026lt;0.01). Notably, \u003cem\u003eNPAS2\u003c/em\u003e expression levels correlated positively with serum ALT levels (r=0.25, p=0.05), suggesting a potential link between NPAS2 dysregulation and liver injury (Fig S1A-B). These human data were corroborated in experimental models, where HFD-fed mice developed pronounced hepatic steatosis characterized by macrovesicular lipid accumulation (H\u0026amp;E staining) and neutral lipid deposition (Oil Red O staining) (Fig. 1C), accompanied by more severe NPAS2 dysregulation, including a 2.6-fold mRNA upregulation and increased protein expression (Fig. 1C-E). Longitudinal assessment of murine MASLD-HCC progression models (GSE67680) revealed a stepwise elevation of \u003cem\u003eNpas2\u003c/em\u003e from steatosis to MASH-HCC, with peak expression observed in advanced HCC stages, though the initial transition from normal liver to steatosis showed only a non-significant upward trend (Fig. S1C). Notably, circadian profiling in HFD-fed mice uncovered profound disruption of \u003cem\u003eNpas2\u003c/em\u003e rhythmicity, characterized by amplitude reduction (Fig. 1F). This disruption paralleled the development of metabolic abnormalities, suggesting a potential relationship between NPAS2 dysregulation and hepatic steatosis.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNPAS2 regulates lipid accumulation and inflammatory responses in hepatocytes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo mechanistically interrogate NPAS2\u0026apos;s role in hepatic steatosis, we established an in vitro model using oleic acid/palmitic acid (OA/PA)-treated LO2 hepatocytes to mimic lipid overload conditions. Western blot analysis confirmed significant induction of NPAS2 protein expression upon lipid challenge (Fig. 2A), suggesting its potential involvement in steatosis development. To elucidate the functional consequences of NPAS2 dysregulation, we established stable LO2 cell lines with \u003cem\u003eNPAS2\u003c/em\u003e knockdown (KD, using shRNA) and overexpression, with efficiency confirmed by Western blot (Fig. S2A-B). Functional analyses revealed that NPAS2 knockdown markedly attenuated lipid droplet accumulation, as demonstrated by Oil Red O and Nile Red staining (Fig. 2B). Conversely, NPAS2 overexpression exacerbated lipid deposition (Fig. 2C). These morphological findings were corroborated by biochemical measurements showing that NPAS2 knockdown significantly decreased cellular TG (14% reduction) and TC (4.5% reduction) levels (Fig. 2D), while NPAS2 overexpression increased TG by 16% and TC by 6.1% (Fig. 2E). Notably, NPAS2 regulation extended beyond lipid metabolism to modulate inflammatory responses. NPAS2 knockdown substantially downregulated key proinflammatory cytokines, including \u003cem\u003eIl1b\u003c/em\u003e (48.7% reduction), \u003cem\u003eIl6\u003c/em\u003e (41.2% reduction), and \u003cem\u003eTnf\u003c/em\u003e (58.2% reduction; Fig. 2F). In stark contrast, NPAS2 overexpression amplified cytokine production (\u003cem\u003eIl1b\u003c/em\u003e: 125.3% increase; \u003cem\u003eIl6\u003c/em\u003e: 65.7% increase; \u003cem\u003eTnf\u003c/em\u003e: 179.7% increase; all p\u0026lt;0.01), suggesting NPAS2 may serve as a critical node linking metabolic dysregulation and inflammation in hepatic steatosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHepatocyte-specific \u003cem\u003eNpas2\u003c/em\u003e knockout ameliorates diet-induced hepatic steatosis in vivo\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo validate these findings in a physiological context, we generated hepatocyte-specific \u003cem\u003eNpas2\u003c/em\u003e knockout mice using CRISPR/Cas9 technology (Fig. 3A and Fig. S3). When challenged with a 16-week HFD, \u003cem\u003eNpas2\u003c/em\u003e LKO mice exhibited significant metabolic improvements compared to controls, including reduced liver weight (27.8% decrease) and liver-to-body weight ratio (24.4% decrease; Fig. 3B), along with decreased hepatic and serum triglyceride and total cholesterol levels (Fig. 3C-3D). These changes occurred with minimal effects on body weight (Fig. 3E). Histopathological analysis confirmed marked improvements in \u003cem\u003eNpas2\u003c/em\u003e LKO mice, showing reduced steatosis and decreased lipid accumulation (Fig. 3F). Consistent with these phenotypic improvements, serum markers of liver injury (ALT and AST) were significantly reduced in \u003cem\u003eNpas2\u003c/em\u003e LKO mice (40.5% and 24.4% decrease respectively; Fig. 3G). Notably, both hepatic ALT and AST levels were significantly downregulated in \u003cem\u003eNpas2\u003c/em\u003e LKO mice (46.1% and 50.7% decrease respectively; Fig. 3H), further supporting the amelioration of liver injury.\u003c/p\u003e\n\u003cp\u003eTo elucidate the mechanistic basis for NPAS2-mediated amelioration of hepatic steatosis, we performed comprehensive analysis of lipid metabolism pathways. Surprisingly, NPAS2 deletion resulted in coordinated upregulation across all major lipid metabolic pathways: (1) Fatty acid uptake (\u003cem\u003eCd36\u003c/em\u003e, \u003cem\u003eFabp4\u003c/em\u003e), (2) Lipid storage (\u003cem\u003ePlin2\u003c/em\u003e, \u003cem\u003eAdrp\u003c/em\u003e), (3) De novo lipogenesis (\u003cem\u003eSrebf1,\u0026nbsp;\u003c/em\u003e\u003cem\u003eAcaca\u003c/em\u003e\u003cem\u003e, Fasn\u003c/em\u003e), (4) Fatty acid oxidation (\u003cem\u003eCpt1a\u003c/em\u003e\u003cem\u003e, Acox1\u003c/em\u003e) (Fig. 3I). This global activation of lipid metabolic genes suggests that NPAS2 knockout enhances hepatic lipid turnover rather than simply suppressing individual pathways. The net metabolic consequence of this reprogramming appears to be a shift toward more efficient lipid handling, evidenced by reduced steatosis despite increased expression of both lipogenic and lipolytic genes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNPAS2 Drives MASLD Progression Through PPAR\u0026gamma; Suppression-Mediated \u0026lsquo;Multiple Hits\u0026rsquo; Mechanism\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhile our metabolic profiling revealed global activation of lipid pathways in NPAS2-deficient livers, this paradoxical coexistence of upregulated lipogenesis and\u0026nbsp;\u0026beta;-oxidation genes could not fully explain the observed attenuation of hepatic steatosis. We therefore hypothesized that NPAS2 ablation might ameliorate MASLD through modulating the \u0026quot;multiple hits\u0026quot; beyond lipid metabolism - particularly insulin resistance, cellular stress, and inflammatory responses - which collectively drive disease progression.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSystematic analyses revealed that \u003cem\u003eNpas2\u003c/em\u003e LKO produced significant metabolic improvements. First, \u003cem\u003eNpas2\u003c/em\u003e LKO mice showed enhanced insulin sensitivity, demonstrated by a 36.3% reduction in HOMA-IR (Fig4A) and increased p-AKT levels (p-AKT, a key mediator of insulin signaling; Fig4B). Second, NPAS2 deficiency markedly attenuated endoplasmic reticulum (ER) stress. This was evidenced by reduced expression of ER chaperone \u003cem\u003eGrp78\u003c/em\u003e (26.9% decrease) and stress-response factors including, \u003cem\u003eXbp1s\u003c/em\u003e (46.5%), \u003cem\u003eChop\u003c/em\u003e (43.7%), \u003cem\u003eAtf4\u003c/em\u003e (45.2%), and \u003cem\u003eOrp150\u003c/em\u003e (56.8%) (Fig4C). Concurrently, oxidative damage was significantly alleviated (21.3% decrease in lipid peroxidation marker MDA), with compensatory upregulation of antioxidant enzymes SOD2 and GPX (Fig4D). NPAS2 deficiency suppressed hepatic and systemic pro-inflammatory responses (IL-1\u0026beta;, IL-6, and TNF-\u0026alpha; downregulation; Fig4E) and fibrogenic signaling (e.g., \u003cem\u003eCol1a1\u003c/em\u003e, \u003cem\u003eCol3a1\u003c/em\u003e, \u003cem\u003eActa2\u003c/em\u003e and \u003cem\u003eTgfb\u003c/em\u003e1\u0026nbsp;reduced by 45\u0026ndash;62.8%；Fig4F).\u003c/p\u003e\n\u003cp\u003eStrikingly, these phenotypic improvements precisely mirrored the known pleiotropic effects of PPAR\u0026gamma; activation[3, 25-28]. Intriguingly, these multifaceted improvements occurred without alterations in PPAR\u0026alpha; or PPAR\u0026beta;/\u0026delta; expression at either transcriptional or translational levels, but were accompanied by a specific increase in PPAR\u0026gamma; protein despite unaltered mRNA levels, suggesting post-translational regulation (Fig4G). Notably, re-analysis of public NPAS2 ChIP-on-chip datasets revealed significant enrichment of NPAS2 binding at loci annotated to lipid metabolic processes (GO:0006629), with KEGG pathway analysis specifically highlighting the PPAR signaling pathway (ko03320, top 10 enriched) (FigS4). This genomic binding pattern, coupled with our phenotypic data, strongly implicates NPAS2 in the direct regulation of PPAR\u0026gamma;-centered metabolic networks. The connection between NPAS2 and PPAR\u0026gamma; was further underscored by their robust anti-phase circadian oscillation (Fig4H). The temporal dissociation of NPAS2 (a transcriptional repressor) and PPAR\u0026gamma; (a metabolic activator) protein levels suggests a time-of-day-specific regulatory axis, wherein NPAS2 may periodically suppress PPAR\u0026gamma; stability or activity during its peak expression phases. Together, the ChIP-based genomic evidence and dynamic protein oscillation establish NPAS2 as a novel circadian governor of PPAR\u0026gamma; signaling in hepatic metabolism.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNPAS2 Regulates PPAR\u0026gamma; Stability Through Transcriptional Control of SIRT1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHaving established NPAS2\u0026apos;s role in suppressing PPAR\u0026gamma; activity, we next investigated the molecular mechanism underlying this regulation. Although co-immunoprecipitation assays ruled out direct physical interaction between NPAS2 and PPAR\u0026gamma; (Fig. S5), we noted that PPAR\u0026gamma;\u0026apos;s metabolic functions are known to be regulated by rhythmic acetylation[14]. This led us to hypothesize that NPAS2 might modulate PPAR\u0026gamma; through post-translational modifications. Strikingly, we found that NPAS2 overexpression significantly increased PPAR\u0026gamma; acetylation, while NPAS2 knockdown markedly reduced it (Fig. 5A). These opposing effects strongly suggest that NPAS2 regulates PPAR\u0026gamma; stability through acetylation-dependent proteasomal degradation.\u003c/p\u003e\n\u003cp\u003eThis acetylation phenotype directed our attention to SIRT1, the major hepatic deacetylase known to regulate PPAR\u0026gamma; stability and metabolic function[29]. Bioinformatic analysis using the STRING database further provided multiple lines of evidence supporting a protein-protein interaction between PPAR\u0026gamma; and SIRT1 (Fig. S6), reinforcing their functional connection. Our results from qRT-PCR and Western blot analysis showed that NPAS2 knockdown significantly decreased SIRT1 expression, while overexpression of NPAS2 markedly increased SIRT1 expression in LO2 cells, at both mRNA and protein levels (Figure 5B-C), indicating a transcriptional regulation of \u003cem\u003eSIRT1\u003c/em\u003e by NPAS2. Given that a previous study in C57BL/6J mice liver tissue using chromatin immunoprecipitation sequencing analysis has identified \u003cem\u003eSirt1\u003c/em\u003e is among the top ten direct transcriptional targets of NPAS2[30], we hypothesized that \u003cem\u003eSIRT1\u003c/em\u003e might be a direct transcriptional target of NPAS2 in human hepatocytes. To test the possibility, a series of truncated promoter constructs were developed to determine their transcriptional activity in hepatocytes with overexpression of NPAS2. Results from luciferase reporter assay revealed that \u003cem\u003eSIRT1\u003c/em\u003e promoter construct (from \u0026minus;110 to +45) abolished the transcriptional activity of the reporter gene (Figure 5D). Site-directed mutagenesis further identified an E-box within putative DNA-binding sites (nt-44 to nt-38) was critical for NPAS2-regulated \u003cem\u003eSIRT1\u003c/em\u003e transcription in LO2 cells (Fig. 5E). In addition, ChIP-PCR assay also showed that NPAS2 directly bind to the promoter of \u003cem\u003eSIRT1\u003c/em\u003e (Fig. 5F).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo further determine whether NPAS2 downregulates the expression and acetylation of PPAR\u0026gamma; through upregulating SIRT1, SIRT1 was knocked-down or overexpressed in LO2 cells with NPAS2 overexpression or knockdown. As shown in Fig.5G, overexpression of SIRT1 significantly attenuated the upregulation of PPAR\u0026gamma; expression and acetylation induced by NPAS2 knockdown, whereas knockdown of SIRT1 reversed the suppression of PPAR\u0026gamma; expression and acetylation caused by NPAS2 overexpression. Together, these results suggest that NPAS2 downregulates PPAR\u0026gamma; expression through directly transcriptional up-regulating \u003cem\u003eSIRT1\u003c/em\u003e in hepatocytes. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNPAS2 Deficiency Attenuates MASLD-HCC Progression by Modulating the SIRT1-PPAR\u003c/strong\u003e\u003cstrong\u003e\u0026gamma;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Axis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical immunohistochemical analysis demonstrated significantly elevated NPAS2 expression in MASLD-HCC tissues (Fig. 6A).\u0026nbsp;Notably, NPAS2 expression levels exhibited a strong positive correlation with SIRT1 (r = 0.602, p \u0026lt; 0.01) while showing a significant negative correlation with PPAR\u0026gamma; (r = -0.512, p \u0026lt; 0.01), suggesting a potential regulatory relationship within this molecular axis during MASLD-HCC progression(Supplementary Table 1).\u003c/p\u003e\n\u003cp\u003eTo functionally characterize NPAS2\u0026apos;s role in hepatocarcinogenesis, we established a DEN-induced HCC model in HFD-fed mice with hepatocyte-specific \u003cem\u003eNpas2\u003c/em\u003e knockout (Fig. 6B). The \u003cem\u003eNpas2\u003c/em\u003e LKO mice displayed remarkable protection against HCC development, as evidenced by a 60% reduction in tumor incidence and significantly decreased tumor burden (Fig. 6C-D). Histopathological examination showed substantial improvement in liver architecture, with markedly attenuated steatosis visible on H\u0026amp;E staining (Fig. 6D). These morphological improvements were accompanied by reduced liver-to-body weight ratios and significantly lower serum ALT/AST levels (Fig. 6E-F), indicating improved hepatic function. The tumor microenvironment in \u003cem\u003eNpas2\u0026nbsp;\u003c/em\u003eLKO mice showed reduced inflammatory signaling, with significant decreases in pro-inflammatory cytokines TNF-\u0026alpha;, IL-1\u0026beta;, and IL-6 (Fig. 6G). At the molecular level, NPAS2 deficiency led to pronounced suppression of cellular proliferation, as demonstrated by decreased Ki67 staining (Fig. 6H). Furthermore, we observed substantial downregulation of established HCC markers including \u003cem\u003eAfp\u003c/em\u003e, \u003cem\u003eGpc3\u003c/em\u003e, \u003cem\u003eEpcam\u003c/em\u003e, and \u003cem\u003eCd44\u003c/em\u003e (Fig. 6I). Western blot analyses confirmed these phenotypic changes were associated with NPAS2-dependent regulation of the SIRT1-PPAR\u0026gamma; axis, as genetic ablation attenuated SIRT1 activity while increasing PPAR\u0026gamma; acetylation (Fig. 6J). Collectively, these findings establish NPAS2 as a critical driver of MASLD-HCC progression through its modulation of the SIRT1-PPAR\u0026gamma; signaling pathway.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNPAS2 Overexpression Exacerbates MASLD-HCC Pathogenesis via SIRT1-PPAR\u0026gamma; Axis Activation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further validate the oncogenic properties of NPAS2, we employed AAV8-mediated hepatic overexpression (Fig. 7A), which resulted in an increase in both NPAS2 mRNA and protein levels compared to controls (Fig. S7). Consistent with our clinical findings, NPAS2 overexpression markedly accelerated disease progression in the DEN-HFD model, with tumor incidence increasing dramatically from 10% (1/10) in control animals to 50% (5/10) in NPAS2 overexpressing mice (Fig. 7B). Macroscopic examination of liver specimens revealed significantly larger tumor volumes in NPAS2 overexpressing mice compared to controls. Histopathological analysis demonstrated exacerbated hepatic steatosis and more severe architectural distortion, as evidenced by H\u0026amp;E staining (Fig. 7C). These pathological changes correlated with increased liver-to-body weight ratios (Fig. 7D) and elevated serum ALT/AST levels (Fig. 7E), indicating profound hepatic dysfunction.\u003c/p\u003e\n\u003cp\u003eAt the molecular level, NPAS2 overexpression created a pro-tumorigenic microenvironment characterized by significantly elevated levels of inflammatory cytokines, including TNF-\u0026alpha;, IL-6, and IL-1\u0026beta; (Fig. 7F). Immunohistochemical analysis revealed enhanced proliferative activity in NPAS2 overexpressing livers, as demonstrated by increased Ki-67 staining (Fig. 7G). Furthermore, qRT-PCR analysis showed upregulation of stemness markers (\u003cem\u003eEpcam\u003c/em\u003e, \u003cem\u003eCd44\u003c/em\u003e) and established HCC markers (\u003cem\u003eAfp\u003c/em\u003e, \u003cem\u003eGpc3\u003c/em\u003e) in these animals (Fig. 7H). Most importantly, Western blot analysis confirmed that NPAS2 overexpression maintained SIRT1 activity while simultaneously suppressing PPAR\u0026gamma; acetylation (Fig. 7I), providing direct evidence that NPAS2 exerts its oncogenic effects through modulation of the SIRT1-PPAR\u0026gamma; signaling axis. These findings collectively demonstrate that NPAS2 overexpression promotes hepatocarcinogenesis by sustaining a pro-proliferative, inflammatory microenvironment through its regulatory effects on the SIRT1-PPAR\u0026gamma; pathway.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePharmacological Activation of PPAR\u0026gamma; Attenuates NPAS2-Induced MASLD Progression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo elucidate the mechanistic link between NPAS2 and PPAR\u0026gamma; suppression in MASLD-HCC progression, we utilized a free fatty acid (FAA)-induced cellular model combined with pharmacological intervention (Fig. 8A). In NPAS2 overexpression LO2 hepatocytes, pioglitazone treatment (10\u0026nbsp;\u0026mu;M, 48h) effectively restored PPAR\u0026gamma; transcriptional activity, as evidenced by significant upregulation of its downstream targets \u003cem\u003eCd36\u003c/em\u003e and \u003cem\u003eFabp4\u003c/em\u003e (Fig. 8B). This molecular restoration translated to functional metabolic improvements, including reduced intracellular lipid accumulation (quantified by Oil Red O and Nile Red staining; Fig. 8C-D) and normalized lipid profiles, with triglyceride and total cholesterol levels decreasing by 4% and 7.7%, respectively (Fig. 8E). Notably, CCK-8 assays revealed that pioglitazone treatment normalized the aberrant proliferative phenotype observed in NPAS2 overexpression LO2 cells under FAA conditions, suggesting that PPAR\u0026gamma; activation may counteract the tumor-promoting effects of NPAS2 overexpression (Fig. 8F). This finding supports the hypothesis that NPAS2-mediated PPAR\u0026gamma; suppression contributes to the malignant transformation of hepatocytes in MASLD progression.\u003c/p\u003e\n\u003cp\u003eThe therapeutic potential was further enhanced through combined treatment with the SIRT1 inhibitor EX527 (5 mg/kg), which synergistically restored PPAR\u0026gamma; protein levels (Fig. S8). These results provide compelling evidence that NPAS2 drives metabolic dysfunction and tumor progression primarily through SIRT1-mediated suppression of PPAR\u0026gamma; activity. The robust therapeutic effects observed with both monotherapy and combination treatment underscore the clinical relevance of targeting the NPAS2-SIRT1-PPAR\u0026gamma; axis as a potential strategy to halt MASLD-associated HCC progression at the molecular level.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe increasing global prevalence of MASLD/MASH and its progression to hepatocellular carcinoma represents a critical public health challenge. The circadian regulator NPAS2 has emerged as a critical player in metabolic liver disease, yet its mechanistic role in driving MASLD progression to HCC remained poorly understood. Our study provides compelling evidence that NPAS2 orchestrates hepatic metabolic dysfunction through SIRT1-PPARγ axis, establishing a molecular bridge between circadian disruption and liver pathogenesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig17\" class=\"InternalRef\"\u003e9\u003c/span\u003e). These findings significantly advance our understanding of MASLD-HCC progression while revealing novel therapeutic opportunities.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe profound metabolic alterations observed in NPAS2-manipulated models reinforce the emerging paradigm that circadian machinery plays fundamental roles in hepatic homeostasis. Our demonstration that NPAS2 knockout attenuates HFD-induced steatosis and inflammation aligns with previous reports showing metabolic disturbances in other circadian gene-modified mice (BMAL1, CLOCK)[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Notably, the hypoxia-sensitive PAS domain of NPAS2 raises an intriguing possibility that the hypoxic microenvironment characteristic of steatotic liver disease may directly contribute to NPAS2 induction. This hypothesis aligns with existing evidence demonstrating that lipid overload increases oxygen demand while impairing hepatic perfusion, creating localized hypoxic conditions[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Our hepatocyte-specific knockout experiments provide definitive evidence that NPAS2 acts as a driver rather than a passive marker of disease progression. While we primarily focused on downstream mechanisms, future studies should investigate whether hypoxia-inducible factors (HIFs) or other metabolic stress signals directly regulate NPAS2 expression in fatty liver conditions.\u003c/p\u003e\u003cp\u003eOur mechanistic dissection of this novel regulatory axis reveals how circadian regulators exert profound control over hepatic metabolism through coordinated transcriptional regulation of key metabolic effectors. Specifically, we demonstrate that NPAS2-mediated upregulation of SIRT1 promotes PPARγ destabilization through enhanced deacetylation, establishing a steatotic microenvironment that accelerates MASLD pathogenesis. Our results initially appear to present a metabolic paradox - NPAS2 knockout improves hepatic steatosis while unexpectedly upregulating lipogenic genes. However, this apparent contradiction is resolved when considering the pleiotropic nature of PPARγ's regulatory functions. While PPARγ activation is known to transcriptionally promote adipogenesis, its net metabolic effects in hepatocytes are more complex and context-dependent. The observed metabolic improvement likely results from PPARγ's dominant beneficial effects on (1) insulin sensitization that enhances fructose clearance and fatty acid oxidation, (2) attenuation of cellular stress responses (ER and oxidative stress), and (3) suppression of inflammatory cascades - all of which collectively outweigh its lipogenic actions. This mirrors the clinical duality of PPARγ agonists like thiazolidinediones, which improve systemic metabolism while causing undesirable adipose expansion[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur findings carry important therapeutic implications that require nuanced consideration. Our data reveal that targeted PPARγ activation in NPAS2 overexpression hepatocytes can disrupt the pathogenic cycle, while accumulating evidence has also illuminated pioglitazone demonstrate efficacy against hepatic steatosis[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], their context-dependent association with HCC risk necessitates precision medicine approaches tailored to individual metabolic contexts. Notably, PPARγ acetylation exhibits robust diurnal oscillations in healthy adipose tissue (peaking at ZT0 and troughing at ZT18), a rhythm disrupted in obesity, aging, and circadian misalignment[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The circadian expression of NPAS2, coupled with the established role of PPARγ acetylation as a hub linking adipose plasticity and metabolic rhythms, provides compelling evidence for chronotherapeutic optimization. Building on these findings, we propose that timed administration of PPARγ agonists during NPAS2 trough phases, could synergistically enhance hepatic specificity by leveraging metabolic rhythmicity while mitigating off-target effects. This dual chronopharmacological strategy, grounded in conserved circadian-metabolic crosstalk, holds significant promise for improving MASLD treatment outcomes.\u003c/p\u003e\u003cp\u003eThe context-dependent duality of SIRT1 presents both therapeutic challenges and opportunities. While hepatic SIRT1 activation promotes tumorigenesis through PPARγ destabilization in our metabolic liver disease model, its protective roles in alcoholic liver disease (via NAD+-dependent pathways) and cardiovascular systems caution against systemic inhibition[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. This tissue-specific functional dichotomy suggests that targeted hepatic SIRT1 modulation may offer safer therapeutic outcomes than global approaches. Our findings raise several mechanistic questions requiring further investigation. First, whether SIRT1 directly regulates PGC-1α acetylation in steatotic hepatocytes, as established in other metabolic tissues but unverified in this context [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Should PGC-1α prove to be negatively regulated by the NPAS2-SIRT1 axis, it would establish a self-reinforcing pathogenic cascade characterized by (1) PPARγ-mediated lipid homeostasis disruption and (2) PGC-1α-driven mitochondrial dysfunction. This dual perturbation could create a metabolic vicious cycle where diminished PPARγ activity exacerbates hepatic steatosis through multiple pathological hits, while suppressed PGC-1α impairs mitochondrial biogenesis, forcing a metabolic shift toward glycolysis - mirroring the Warburg effect characteristic of both advanced MASLD and cancer metabolism[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Such mechanisms would collectively generate a pro-oncogenic microenvironment ripe for malignant transformation, representing a critical direction for future investigation.\u003c/p\u003e\u003cp\u003eWhile LO2 hepatocytes provide a tractable model for early metabolic dysregulation, future studies using patient-derived primary hepatocytes and organoids will further validate the translational potential of targeting the NPAS2-SIRT1-PPARγ axis. Collectively, NPAS2\u0026rsquo;s role in early metabolic dysregulation positions it as a promising preventive target. Pharmacological intervention via combined pioglitazone and SIRT1 inhibition could disrupt the NPAS2-SIRT1-PPARγ axis, offering a novel strategy to intercept MASLD-HCC progression in high-risk populations\u0026mdash;particularly those with circadian disruption phenotypes. Our work establishes NPAS2 as a central node linking circadian biology and hepatic pathophysiology, with translational implications for precision chronotherapy.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBased on consistent evidence obtained from clinical cohorts, multi-omics datasets, genetically engineered mouse models, and in vitro mechanistic investigations, this study systematically elucidates the central role of the core circadian transcription factor NPAS2 in metabolic dysfunction-associated steatotic liver disease (MASLD) and its progression to hepatocellular carcinoma (HCC). NPAS2 exhibits disrupted rhythmicity in disease states, and operates through a hierarchical regulatory axis wherein it transcriptionally activates the deacetylase SIRT1, which in turn promotes deacetylation and proteasomal degradation of PPARγ, thereby alleviating its protective metabolic functions. Importantly, pharmacological PPARγ activation via pioglitazone significantly rescues NPAS2-induced metabolic disturbances and proliferative phenotypes. Our findings not only uncover a novel circadian-regulated pathway underlying MASLD\u0026ndash;HCC progression but also provide a mechanistic rationale for targeting circadian components in the development of targeted therapies for metabolic liver diseases.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the patients who participated in the trial and the contributions of all investigators. We also thank Tangdu Hospital, Fourth Military Medical University for providing relevant experimental facilities and technical support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJiao Mu, Jiali Ye and Jiahao Zhang performed most of the experiments and analyzed data; Bichan Xu, Wen Huang and Hui Gong participated in the in vitro and vivo study. Peng Yuan and Jiali Ye designed the overall study, Peng Yuan and Menghui Yuan supervised the experiments. Jiao Mu and Jiali Ye wrote the paper. Hongxin Zhang, Shuhan Lu, Bin Chen and Qiang Chen revised the paper. Peng Yuan acquired the funding. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the National Science Basic Research Plan in Shaanxi Province of China (grants 2024JC-YBMS-731). Convergence Research Funding Initiative of Fourth Military Medical University (2024JC030). \u0026nbsp;Xi\u0026apos;an Jiaotong University Faculty Discovery and Innovation Initiative (xzy012025152).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll datasets generated and/or analyzed during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll experimental procedures involved were performed according to protocols approved by The Fourth Military Medical University. All healthy controls and patients with MDD provided written informed consent for providing blood samples in accordance with the local ethical committee. The study was conducted with approval from the Research Ethics Committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZ.M. Younossi, M. Kalligeros, L. Henry, Epidemiology of metabolic dysfunction-associated steatotic liver disease, Clin Mol Hepatol, 31 (2025) S32-s50.\u003c/li\u003e\n\u003cli\u003eS. Iturbe-Rey, C. Maccali, M. Arrese, P. Aspichueta, C.P. Oliveira, R.E. Castro, A. Lapitz, L. Izquierdo-Sanchez, L. Bujanda, M.J. Perugorria, J.M. Banales, P.M. Rodrigues, Lipotoxicity-driven metabolic dysfunction-associated steatotic liver disease (MASLD), Atherosclerosis, 400 (2025) 119053.\u003c/li\u003e\n\u003cli\u003eM. Huttasch, M. Roden, S. Kahl, Obesity and MASLD: Is weight loss the (only) key to treat metabolic liver disease?, Metabolism, 157 (2024) 155937.\u003c/li\u003e\n\u003cli\u003eZ. 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White, Mitochondria and Cancer, Mol Cell, 61 (2016) 667-676.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cell-death-and-disease","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddis","sideBox":"Learn more about [Cell Death \u0026 Disease](http://www.nature.com/cddis/)","snPcode":"41419","submissionUrl":"https://mts-cddis.nature.com/cgi-bin/main.plex","title":"Cell Death \u0026 Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"MASLD, circadian rhythm, NPAS2, SIRT1/PPARγ, HCC","lastPublishedDoi":"10.21203/rs.3.rs-8137044/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8137044/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEmerging evidence suggests a link between circadian disruption and metabolic dysfunction-associated steatotic liver disease (MASLD), although the precise mechanisms are not yet fully understood. As a central circadian regulator, the role of NPAS2 in the pathogenesis and progression of MASLD to hepatocellular carcinoma (HCC) is not well characterized. This study aimed to clarify the functional and mechanistic contributions of NPAS2 to the development of MASLD and the progression to HCC. Analysis of clinical liver biopsies and high-fat diet (HFD)-fed murine models consistently demonstrated significant upregulation of NPAS2 in MASLD, at both mRNA and protein levels. In vitro, free fatty acid (FFA)-treated LO2 hepatocytes with NPAS2 knockdown showed attenuated lipid accumulation and inflammatory responses, whereas NPAS2 overexpression exacerbated steatotic phenotypes. In hepatocyte-specific NPAS2 knockout mice subjected to HFD, we observed comprehensive metabolic improvement including reduced hepatic steatosis, improved insulin sensitivity, attenuated endoplasmic reticulum stress, and suppressed pro-fibrotic signaling. Mechanistically, NPAS2 was found to transcriptionally activate \u003cem\u003eSIRT1\u003c/em\u003e by directly binding to an E-box motif in its promoter region. SIRT1 subsequently deacetylated PPARγ, leading to its destabilization and functional suppression. The clinical relevance of this axis was underscored by strong correlations between NPAS2 expression and both SIRT1 (positive) and PPARγ (negative) in human MASLD specimens. Furthermore, in a diethylnitrosamine (DEN)-induced HCC model coupled with HFD feeding, NPAS2 deficiency conferred remarkable protection against tumor development. Conversely, NPAS2 overexpression accelerated hepatocarcinogenesis. Critically, pharmacological PPARγ activation by pioglitazone rescued NPAS2-driven metabolic dysfunction in vitro.\u003c/p\u003e\u003cp\u003eOur study reveals NPAS2 as a critical node connecting circadian dysfunction to MASLD-HCC progression and identifies the NPAS2-SIRT1-PPARγ axis as a therapeutic target. These findings provide a rationale for chronotherapeutic strategies to disrupt this pathogenic cascade, offering new hope for combating MASLD-related complications.\u003c/p\u003e","manuscriptTitle":"NPAS2 Promotes MASLD and Hepatocarcinogenesis through SIRT1-Mediated PPARγ Suppression","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-03 14:24:56","doi":"10.21203/rs.3.rs-8137044/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2026-01-07T12:12:51+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-12-30T04:12:31+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-12-21T03:20:59+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-12-17T03:24:55+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-12-03T09:13:12+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-12-02T00:46:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-20T13:36:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cell Death \u0026 Disease","date":"2025-11-19T08:42:41+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2025-11-18T21:25:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-17T15:05:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cell-death-and-disease","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddis","sideBox":"Learn more about [Cell Death \u0026 Disease](http://www.nature.com/cddis/)","snPcode":"41419","submissionUrl":"https://mts-cddis.nature.com/cgi-bin/main.plex","title":"Cell Death \u0026 Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8f71d18c-f941-49df-aa04-fa234c6b7b78","owner":[],"postedDate":"December 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":58921591,"name":"Biological sciences/Cancer/Cancer metabolism"},{"id":58921592,"name":"Biological sciences/Cancer/Cancer models"}],"tags":[],"updatedAt":"2026-01-07T12:17:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-03 14:24:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8137044","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8137044","identity":"rs-8137044","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}