Hepatokine fibrinogen-like protein 1 drives liver-kidney crosstalk to promote renal fibrosis

Wu, Wen-Hui; Zhu, Li-Zeng; Liu, Kang; Cao, Lin; Fan, Yuan-Ming; Zhou, Ping; Zhang, Yue; Ma, Gaoxiang; Liu, Jin-Feng; Liu, Bao-Lin; Qi, Lian-Wen; Liu, Qun

doi:10.1038/s41467-025-68188-0

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Published: 09 January 2026

Hepatokine fibrinogen-like protein 1 drives liver-kidney crosstalk to promote renal fibrosis

Nature Communications volume 17, Article number: 1453 (2026) Cite this article

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Abstract

The concept of organ-organ communication in systemic diseases has gained significant traction. Despite accumulating evidence of liver-kidney crosstalk, the underlying regulatory mechanisms remain poorly understood. Here, we identify hepatokine fibrinogen-like protein 1 (FGL1) as a pivotal mediator driving liver-kidney communication in renal fibrosis. Integrative RNA sequencing and clinical analyses revealed FGL1 upregulation in the liver post-renal injury, with subsequent selective accumulation in fibrotic kidneys. Hepatocyte-specific knockout of FGL1 improved renal morphology, attenuated collagen deposition, and inhibited fibrosis markers in unilateral ureteral obstruction and adenine-induced mouse models. Conversely, FGL1 overexpression exacerbated renal fibrosis. Mechanistically, FGL1 binds to TGF-β receptor ALK5 and blocks its interaction with K48-linked polyubiquitin. Structural analyses identified critical residues in FGL1-ALK5 interaction. Hepatic FGL1 is transcriptionally regulated by STAT3, and activated by inflammatory cytokines (IL-6, IL-1β and TNF-α). Pharmacological inhibition by p-hydroxybenzaldehyde (screened out from 4080 compounds) or an anti-FGL1 monoclonal antibody significantly reduced renal fibrosis without hepatotoxicity. These findings establish FGL1 as a key mediator of pathogenic liver-kidney crosstalk and highlights therapeutic strategies to targeting organ-organ networks in renal fibrosis.

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Introduction

The concept of organ-organ crosstalk, mediated by endocrine factors such as secreted proteins and extracellular vesicles, has revolutionized our understanding of systemic health and disease¹. Recent studies have identified diverse mediators, including hepatokines, cytokines, myokines, adipokines, and metabolites^2,3,4. Coagulation factor XI, a liver-derived protein, exhibits cardioprotective roles in liver-heart crosstalk independent of its coagulation function⁵. A brain-heart axis is characterized by which myocardial infarction triggers brain-mediated monocytic TNF generation to enhance slow-wave sleep and promote cardiac repair⁶. Liver-bone communication is regulated by hepatocyte Sirtuin 2, which modulates LRG1 in extracellular vesicles to suppress osteoclast differentiation⁷. Emerging scientific data also reveal gut-liver interactions mediated by microbiota-derived metabolites⁸, heart-kidney dialog via cardiac natriuretic peptides⁹, and other tissue-tissue crosstalk¹⁰. These findings not only deepen our understanding of systemic disease mechanisms but also highlight therapeutic opportunities to target inter-organ signaling hubs.

Renal fibrosis, a pathological hallmark of chronic kidney disease (CKD), is characterized by excessive extracellular matrix (ECM) deposition, leading to irreversible structural and functional kidney decline¹¹. Multiple drivers, including TGF-β, Ang II, oxidative stress, and hemodynamic imbalances, contribute to disease progression¹². TGF-β signaling, a central regulator, activates myofibroblasts, induces epithelial-mesenchymal transition (EMT) and promotes collagen synthesis through canonical SMAD-dependent pathways^13,14. In spite of these scientific insights, current therapies targeting intrinsic renal pathways remain insufficient, underscoring the need to explore systemic mediators and inter-organ communication mechanisms.

The liver, a key endocrine organ, secretes hepatokines that regulate distant systemic physiology and pathology¹⁵. For instance, activin-E, predominantly expressed and secreted by the liver, is elevated in individuals with obesity and non-alcoholic fatty liver disease¹⁶. Similarly, ANGPTL3, another hepatokine, modulates plasma triglyceride levels by inhibiting lipoprotein lipase in oxidative tissues¹⁷. Clinical and experimental evidence underscores the functional interplay between hepatic and renal pathology. Acute liver injury or advanced cirrhosis frequently precipitates renal impairment¹⁸. Bile duct ligation (BDL) models demonstrate that liver injury can induce renal damage, supporting the existence of a liver-kidney axis¹⁹. Despite these associations, the molecular mediators of liver-kidney crosstalk in renal fibrosis remain largely unexplored. Identifying these hepatokines and their mechanisms of action could unveil novel therapeutic strategies to disrupt fibrotic signaling networks.

In this work, we combine transcriptomic profiling, functional genetics, and pharmacological interventions to characterize key endocrinal mediators for liver-kidney dialog, underlying mechanisms, and candidate drugs in renal fibrosis. Our findings position FGL1 as a pivotal mediator of liver-kidney crosstalk and a promising therapeutic target, bridging the gap between systemic mediators and localized fibrotic pathways.

Results

Integrative RNA sequencing and clinical correlation analysis identify FGL1 as a key mediator of liver-kidney communication

To identify endocrine mediators of liver-kidney crosstalk, we combined RNA sequencing with clinical correlation analysis. First, we established a unilateral ureteral obstruction (UUO) mouse model of renal fibrosis and conducted RNA sequencing on liver tissues 14 days post-surgery (Fig. 1a). Of the 56,980 genes detected in liver tissues, 966 exhibited significantly differential expression in response to renal injury (p < 0.05, Fig. 1b). The top-ranked upregulated hepatokines included Fgl1, Orm2, Mt2, Saa1, and Saa2 (Log₂fold-change > 4, adjusted p < 0.0001). qPCR validated robust hepatic upregulation of these five hepatokines (Fig. 1c). To identify hepatokines that potentially translocate to the kidneys, we analyzed their expressions in the kidneys of UUO mice. Strikingly, FGL1 protein expression was markedly elevated in obstructed kidneys, whereas the other four candidate hepatokines showed no significant changes (Fig. 1d).

**Fig. 1: The hepatokine FGL1 is significantly upregulated in renal fibrosis.**

Next, clinical correlation was further assessed using serum samples from CKD patients (n = 18) and healthy individuals (n = 18). FGL1 protein level was significantly elevated in CKD patients (p = 0.0058, Fig. 1e) and positively correlated with renal injury markers, blood urea nitrogen (BUN, r = 0.51) and creatinine (CR, r = 0.51) (Fig. 1f). The remaining hepatokines exhibited weak clinical associations. These findings prioritized FGL1 as a key candidate mediator for liver-kidney communication. Single-cell transcriptomic profiling (n = 2 datasets) confirmed FGL1 expression specific to hepatocytes (2.93 ± 0.83) with negligible detection in kidney cells (Fig. 1g, h and Supplementary Fig. 1a, b). Intriguingly, while hepatic Fgl1 mRNA was markedly upregulated in UUO mice, total liver FGL1 protein levels remained unchanged (Supplementary Fig. 1c), suggesting rapid secretion into systemic circulation (Fig. 1i) and subsequent renal accumulation. In another BDL-induced liver injury mouse model, we also observed that FGL1 was rapidly mobilized from the liver to circulation and subsequently deposited in the kidneys (Supplementary Fig. 1d, e). Hemoperfusion experiments demonstrated significant reduction of renal FGL1 following blood clearance (p = 0.032, Fig. 1j), directly linking circulating FGL1 to renal deposition. Strikingly, in hepatocyte-FGL1 overexpressed UUO mice, biophotonic imaging detected FGL1 enrichment exclusively in injured kidneys, with no detectable signal in lung, heart, white adipose, spleen, or skeletal muscle (Fig. 1k).

Hepatic FGL1 drives renal fibrosis using gain- and loss-of-function approaches

To investigate the role of FGL1 in liver-kidney crosstalk, we generated mice with hepatocyte-specific FGL1 deletion using a Cre/loxP-dependent conditional knockout (HepKO) system (Supplementary Fig.2a–d). In male mice subjected to UUO, hepatocyte-specific FGL1 knockout ameliorated renal morphological damage and reduced collagen deposition (Fig. 2a–f). Second harmonic generation (SHG) microscopy confirmed that fibrillar collagen was greatly attenuated in the kidney of FGL1 HepKO mice (Fig. 2g, h). In line with these observations, FGL1 knockout suppressed the expression of ECM deposition marker (FN), EMT marker (VIMENTIN), and fibrogenic factors (Fig. 2i, j).

**Fig. 2: Hepatocyte-specific deletion of FGL1 alleviates UUO-induced renal fibrosis in mice.**

Furthermore, we injected AAV8-TBG-Cre to selectively ablate FGL1 in hepatocytes of adult FGL1^fl/fl mice (Supplementary Fig. 3a, b). In the UUO model, FGL1 HepKO mice exhibited a marked reduction in renal fibrosis, as indicated by diminished collagen deposition and decreased expression of key fibrotic markers (Supplementary Fig. 3c–f). Notably, these renoprotective effects were also observed in female mice subjected to UUO (Supplementary Fig. 4). Additionally, FGL1 HepKO ameliorated adenine-induced renal fibrosis and improved kidney function in mice (Supplementary Fig. 5).

To complement loss-of-function studies, we employed a gain-of-function approach through hepatocyte AAV8-TBG-FGL1 overexpression (Fig. 3a and Supplementary Fig. 6a, b). In UUO model mice, hepatic FGL1 overexpression exacerbated tubular dilation and collagen deposition (Fig. 3b, c), paralleled by elevated COL-I and α-SMA levels via immunohistochemistry or immunofluorescence (Fig. 3d, e). FGL1 overexpression further upregulated fibrosis-related proteins and genes in the kidney (Fig. 3f, g).

**Fig. 3: Hepatocyte-specific FGL1 overexpression aggravates UUO-induced renal fibrosis in mice.**

Additionally, we employed cellular models to characterize the role of FGL1 in liver-kidney communication. HEK-293T cells were transfected with FGL1 plasmids to generate FGL1-enriched conditioned medium (Fig. 3h). Co-culture of HK-2 cells with this medium further enhanced the TGF-β-induced upregulation of FN, VIMENTIN, and PAI-1, as determined by Western blot (Fig. 3i, j), and increased the levels of α-SMA, as shown by immunofluorescence (Fig. 3k). Recombinant human FGL1 (rhFGL1) protein produced similar effects in the presence of TGF-β stimulation (Fig. 3l, m). We further confirmed that FGL1 promotes the secretion (in culture supernatants) of FN, a result that directly supports its role in driving ECM accumulation (Supplementary Fig. 6c, d). Besides, treatment with rhFGL1 alone did not significantly upregulate the expression of fibrosis-associated genes (Supplementary Fig. 6e).

FGL1 interacts with ALK5 to prevent its ubiquitination

Upon treatment with FGL1-enriched conditioned medium from HEK-293T cells, FGL1 was predominantly localized to the plasma membrane fraction in HK-2 cells (Fig. 4a). Proteomic analysis revealed TGF-β/SMAD signaling pathway stood out as the most enriched biological process in the kidney after FGL1 overexpression (Fig. 4b–d). Next, we screened for direct interaction between FGL1 and members of the TGF-β receptor family. Surface plasmon resonance (SPR) results demonstrated that FGL1 selectively bound to ALK5 with a strong affinity (KD = 12.6 nM, Fig. 4e) but could not or was weakly bound to ALK1, ALK2, ALK3, ALK4, ALK6, ALK7, TGFβR2, BMPR2, AMHR2, ACVR2A, and ACVR2B (Supplementary Fig. 7). Bio-layer interferometry (BLI) further confirmed that FGL1 displayed favorable binding affinity to ALK5 (Fig. 4f). Bimolecular fluorescence complementation (BiFC) detected a direct interaction of FGL1 with ALK5 in HEK-293T cells (Fig. 4g). This interaction was confirmed by reciprocal co-immunoprecipitation (Co-IP) (Fig. 4h, i).

**Fig. 4: Identification of ALK5 as a binding receptor of FGL1 in the kidney.**

To characterize the binding regions of ALK5 to FGL1, we generated their respective truncated forms. SPR (Fig. 4j) and Co-IP (Supplementary Fig. 8a) showed that the 200–503 amino acid region of ALK5 interacted with FGL1, but the 1–200 amino acid region could not. On the other hand, the 150–312 amino acid region of FGL1 could interact with ALK5, while the 1–150 amino acid region could not (Supplementary Fig. 8b). Molecular docking analysis predicted that 8 amino acids of FGL1 could form eight hydrogens with 6 amino acids of ALK5, i.e., FGL1^E222 with ALK5^W277, FGL1^Q224 with ALK5^E218, FGL1^W225 with ALK5^G214, FGL1^D252 with ALK5^R237, FGL1^R260 with ALK5^R237, FGL1^D280 with ALK5^R237, FGL1^Y286 with ALK5^T274, and FGL1^W291 with ALK5^T272 (Fig. 4k). Simultaneous mutation of the 8 amino acids of FGL1 diminished the interaction of FGL1 with ALK5 by Co-IP (Supplementary Fig. 8c). Single mutation of FGL1^D252A, FGL1^R260A, FGL1^D280A, FGL1^Y286A or FGL1^W291A considerably disrupted the binding of FGL1 to ALK5, while the interactions of FGL1^E222A, FGL1^Q224A, and FGL1^W225A remained their intact (Fig. 4l). Simultaneously mutation of the 6 amino acids of ALK5 diminished the interaction of ALK5 with FGL1 (Supplementary Fig. 8d). Single mutations of ALK5^E218A, ALK5^R237A, ALK5^T272A, ALK5^T274A or ALK5^W277A considerably disrupted the binding of ALK5 to FGL1, while ALK5^G214A remained unaffected (Fig. 4m).

Following FGL1 interaction with ALK5, hepatocyte-specific FGL1 knockout significantly suppressed TGF-β/SMAD signaling pathway in fibrotic kidneys of UUO mice, whereas FGL1 overexpression activated this pathway. Interestingly, we found that the protein level of ALK5 was also regulated by FGL1 (Fig. 5a, b). 3D imaging of ALK5 distribution demonstrated that FGL1 overexpression elevated ALK5 protein levels (Fig. 5c). In addition, administration of HK-2 cells with SB431542, a specific inhibitor of ALK5, blocked FGL1-induced profibrotic effect (Fig. 5d). To assess FGL1’s effect on ALK5 stability, we monitored ALK5 degradation in HEK-293T cells under basal conditions. ALK5 underwent rapid degradation (0–12 h), but FGL1 overexpression markedly stabilized the receptor (Fig. 5e). Cellular thermal shift assays demonstrated that FGL1 overexpression increased ALK5 stability at multiple temperatures (Fig. 5f). ALK5 degradation was blocked with the proteasome inhibitor MG132 but not the lysosome inhibitor chloroquine, suggesting the involvement of the proteasome pathway. (Supplementary Fig. 9). FGL1 overexpression decreased ALK5 ubiquitination, while mutations of binding sites in FGL1 (D252A, R260A, D280A, Y286A, and W291A) abolished this effect (Fig. 5g). Similarly, pretreatment with rhFGL1 reduced ALK5 ubiquitination (Fig. 5h).

**Fig. 5: FGL1 specifically interacts with ALK5 and enhances ALK5 protein stability.**

SMAD7 is a known negative regulator of TGF-β pathway, competitively binding ALK5 to promote receptor ubiquitination. In HEK-293T cells, the inhibitory effect of FGL1 on AKL5 ubiquitination was abolished by SMAD7 overexpression (Fig. 5i). Co-IP assays demonstrated that increasing FGL1 levels progressively attenuated the ALK5-SMAD7 interaction (Fig. 5j). Consistent with this, Western blot showed that FGL1 dose-dependently counteracted SMAD7-mediated ALK5 degradation (Fig. 5k). Screening of ubiquitin mutants (K6R, K11R, K27R, K29R, K33R, K48R, and K63R) revealed that SMAD7 specifically promotes K48-linked polyubiquitin interact with ALK5, as mutation of K48R abolished this ubiquitination (Fig. 5l).

STAT3 transcriptionally upregulates FGL1 expression in the liver

To delineate the transcriptional mechanism underlying FGL1 regulation, we screened potential transcription factors using the GTRD, KnockTF, ENCODE, and JASPAR databases and identified six candidates: STAT3, JUN, CREB1, GATA3, CEBPB, and MAX (Supplementary Fig. 10a). Subsequent qPCR analysis revealed significantly elevated Stat3 mRNA levels at day 1, 3, 7, and 14 in the liver of UUO mice (Supplementary Fig. 10b), which positively correlated with Fgl1 expression (r = 0.71, Supplementary Fig. 10c). To validate STAT3’s regulatory role, we performed STAT3 gradient overexpression experiments in HEK-293T cells, demonstrating a dose-dependent enhancement of FGL1 promoter activity (Supplementary Fig. 10d). RNA sequencing showed that inflammatory response stood out as one of the most enriched biological processes in the liver of UUO mice (Supplementary Fig. 10e). ELISA revealed significant induction of inflammatory cytokines such as IL-6, IL-1β, and TNF-α in the serum (Supplementary Fig. 10f). These inflammatory cytokines exhibited a positive correlation with circulating FGL1 protein levels (Supplementary Fig. 10g). In vitro experiments using AML12 hepatocytes demonstrated that individual treatment with IL-6, IL-1β, and TNF-α upregulated STAT3 phosphorylation and FGL1 protein levels (Supplementary Fig. 10h, i). Critically, STAT3 inhibitor (S3I-201) abolished inflammatory cytokines-induced FGL1 production, confirming STAT3’s essential role in FGL1 regulation (Supplementary Fig. 10j).

High-throughput screening identifies FGL1 inhibitors with therapeutic potential in renal fibrosis

Based on the promising therapeutic potential of inhibiting FGL1 for the treatment of renal fibrosis, we performed a luciferase reporter-based high-throughput screening in HEK-293T cells to identify FGL1 inhibitors (Fig. 6a). A structurally diverse library of 4080 natural small-molecule compounds was evaluated (Supplementary Data 2). Initial selection of the top 30 candidates was based on their ability to suppress FGL1 promoter activity by >2-fold (Fig. 6b). Further refinement excluded compounds with unfavorable ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiles or cytotoxicity in HEK-293T and AML12 cells (Fig. 6c and Supplementary Fig. 11a, b), narrowing the list to 10 candidates: coumarin VI, glucose, leucic acid, atractyloside A, trichostatin A, anemoside A3, mulberroside C, primin, paradol, and p-hydroxybenzaldehyde (PHBA).

**Fig. 6: Screening and validation of p-hydroxybenzaldehyde as a down-regulator of FGL1 transcription in hepatocytes.**

Among the 10 candidates, PHBA demonstrated the strongest reduction of FGL1 mRNA and protein levels (Fig. 6d, e). PHBA (5, 10, 20, 40 μM) dose-dependently inhibited both FGL1 promoter activity and FGL1 protein expression without hepatocyte toxicity (Fig. 6f–h and Supplementary Fig. 11c). p-Hydroxybenzyl alcohol and p-hydroxybenzonic acid, two structural analogs of PHBA, showed no such activity, underscoring PHBA’s specificity (Supplementary Fig. 11d). In UUO mice, oral administration of PHBA (10, 50 mg/kg) effectively reduced Fgl1 mRNA in the liver (Fig. 6i, j) and FGL1 protein levels in serum (Fig. 6k). Consequently, PHBA attenuated the renal fibrosis phenotype (Fig. 6l) and significantly suppressed the expression of fibrosis-related proteins and genes (Supplementary Fig. 12a, b). Additionally, PHBA was relatively safe in observed time, as evidenced by stable ALT/AST levels and intact liver/heart histology (Supplementary Fig. 12c, d).

In parallel, a monoclonal antibody against FGL1 (anti-FGL1 mAb) was evaluated. Intraperitoneal administration of anti-FGL1 mAb in UUO mice reduced serum FGL1 levels (Fig. 7a), alleviated renal injury and collagen deposition, as evidenced by morphological observations, HE and Masson staining (Fig. 7b, c). Anti-FGL1 mAb also suppressed fibrosis-associated proteins and genes in the kidney (Fig. 7d, e).

**Fig. 7: Neutralizing antibody against FGL1 alleviates UUO-induced renal fibrosis in mice.**

Discussion

This study has identified FGL1 as a pivotal hepatokine driving pathogenic liver-kidney crosstalk in renal fibrosis. Renal injury triggers systemic inflammation and activates STAT3 to transcriptionally upregulate hepatic FGL1. Notably, FGL1 accumulates selectively in fibrotic kidneys, where it binds to ALK5 to stabilize TGF-β signaling by blocking receptor ubiquitination. Pharmacologically targeting of FGL1 via small-molecule inhibitors or anti-FGL1 monoclonal antibodies by disrupting interorgan networks could constitute a glimmer of light towards the treatment of CKD (Fig. 7f).

The role of the liver as an endocrine organ has gained clinical relevance. It is able to synthesize and release hepatokines that have the capacity to act at a distance in other organs such as the heart⁵, adipose tissue²⁰, skeletal muscle²¹, bone⁷ and the central nervous system²². However, clinical evidence regarding the liver-kidney axis remains limited, though existing data underscore significant comorbidity between the hepatic and renal systems. Hepatorenal syndrome exemplifies a severe renal complication of advanced liver disease^23,24, and nonalcoholic fatty liver disease has been established as a risk factor for CKD^25,26. Our study advances the understanding of the liver-kidney axis by revealing a pathogenic feedback loop—renal injury initiates the secretion of hepatic FGL1 via circulating inflammatory mediators. The FGL1 released subsequently reaches the injured kidneys, where it exacerbates renal fibrosis, ultimately forming a deleterious cross-organ pathological circuit. We hypothesize that this phenomenon may be a self-protective mechanism of the liver in response to stressors such as inflammation—wherein upregulation of FGL1 secretion helps the liver counteract external injurious factors and facilitates timely restoration of organ function. This hypothesis is supported by the positive correlation between circulating inflammatory factors and FGL1 levels, which is consistent with reported findings that extrahepatic inflammation elevates plasma FGL1²⁷. In addition, this interpretation aligns with previous observations that hepatic FGL1 secretion under stress protects mice and nonhuman primates from acute liver injury²⁸. In inter-organ communication, hepatokines mediate the liver’s dual roles, thus supporting repair as a “rescuer” or, in disease, propagate a “shared fate” of systemic damage^5,29,30. Beyond these established roles, we found that the liver might act as an inadvertent “guardian” and exacerbate injury in organ-organ crosstalk via hepatokines—a portrayal that echoes the colloquial expression “caught in the crossfire”. Apart from the liver-kidney axis, such a role of hepatokines in other organs has not been reported and warrants further investigation.

Beyond its recognized role in liver regeneration, FGL1 has recently been identified as a functional ligand of LAG3 and implicated in immune checkpoint regulation³¹. Given the established contribution of immune cells to renal injury, we sought to determine whether the FGL1-LAG3 axis participates in renal fibrosis. Our data provide no substantial evidence that circulating FGL1 exacerbates fibrosis via LAG3 engagement on renal immune cells (Supplementary Figs. 13 and 14). Instead, we have identified a novel pathway wherein hepatocyte-derived FGL1 promotes fibrosis by binding to ALK5. Although rhFGL1 alone did not induce fibrosis-related gene expression, it potently amplified TGF-β–driven fibrotic responses (Supplementary Fig. 6e). Mechanistically, FGL1 interacts with the 218–277 domain of ALK5, stabilize the receptor against proteasomal degradation, and thereby increasing its availability for TGF-β signaling. This synergy arises from FGL1 and TGF-β engaging distinct regions of ALK5, rather than competing for the same binding site, leading to enhanced activation of the pro-fibrosis pathway. Notably, FGL1 exhibits context-dependent functional duality: its overexpression under basal conditions does not induce injury (Supplementary Fig. 15), whereas in experimental injury models such as UUO, it acts as a pathogenic amplifier that markedly exacerbates fibrosis progression.

Current therapies for CKD include ACE inhibitors, angiotensin receptor blockers, and SGLT2 inhibitors³². Our work introduces hepatic FGL1 inhibition as a paradigm shift in inter-organ crosstalk disruption. The natural product PHBA reduced renal FGL1 deposition and fibrosis without inducing hepatotoxicity. In addition, we started PHBA treatment 4 days after UUO for 2 weeks to mimic a scenario in the clinic. PHBA significantly ameliorated renal fibrosis phenotype (Supplementary Fig. 16), suggesting potential efficacy against established CKD. Compared to small-molecule agents, anti-FGL1 monoclonal antibodies offer distinct advantages, including superior target specificity and prolonged therapeutic effects. Drug repositioning accelerates therapeutic development by leveraging existing agents. Aspirin, a cost-effectively agent shown to promote FGL1 degradation in hepatocellular carcinoma³³, reduced FGL1 protein levels in hepatocytes and in the serum of UUO mice. It also preserved renal structural integrity and attenuated renal fibrosis (Supplementary Figs. 17 and 18). However, a clinical trial observed no benefit or harm from low-dose aspirin in CKD patients³⁴. Given reported associations between aspirin and renal damage^35,36, the long-term safety of FGL1-targeted therapies requires evaluation. Further validation in additional animal models is needed to assess the anti-renal fibrosis potential of aspirin, particularly its dosage regimen and safety profile.

Our study has several limitations. First, while both surgical and chemical models were used, UUO does not replicate the functional decline of human CKD^37,38. Future work should include the 5/6 nephrectomy model to improve clinical relevance³⁹. Second, the effects of FGL1 on other renal cell types remain unclear, necessitating further investigation to define its pathogenic role. Finally, AAV8-mediated FGL1 overexpression is constrained by uncontrolled expression. Liver-specific knock-in models should be used to achieve tightly regulated, spatiotemporally controlled expression.

In conclusion, our findings redefine FGL1 as a linchpin in liver-kidney communication, bridging mechanistic insight with translational potential. By elucidating how organ-organ dialog perpetuates chronic disease, this work advocates for therapies targeting interorgan networks and moves beyond traditional organ-centric frameworks.

Method

Human subject recruitment study participants

All procedures were approved by the Medical Ethics Committee of Jiangsu Province Hospital and adhered to the principles of the Declaration of Helsinki (2024-SR-299). All participants were informed about the use of their serum, and written informed consent was obtained. Serum from 18 CKD patients and 18 age- and sex-matched healthy controls were collected from Jiangsu Province Hospital (Supplementary Table 1). CKD patients with a glomerular filtration rate of less than 60 mL/min per 1.73 m², or a marker of kidney damage, or both, for a duration of at least 3 months were recruited. Patients with acute kidney injury, liver disease, active vasculitis, gastrointestinal pathology or cancer were excluded from the study. Age- and sex-matched healthy subjects were also recruited.

Animal treatment

Animal experiments were conducted in accordance with the guidelines for Animal Experimentation of China Pharmaceutical University (Nanjing, China), and the protocols were approved by the Animal Ethics Committee of the institution (No: 2024-11-092). C57BL/6 J mice (8 weeks, 20–23 g) were purchased from Jiangsu GemPharmatech Biotechnology (Nanjing, China) and randomly assigned to different treatment groups. All animals were housed under controlled humidity and temperature in standard facilities (24–26 °C) under specific pathogen-free conditions with a 12 h dark/light cycle (lights on between 8 a.m. and 8 p.m.), with ad libitum access to water and chow (Xie Tong Bio-Technology Co., Ltd., China. Lot No. XTI01WC-011). Mice were euthanized by cervical dislocation. The investigators were not blinded to the treatment groups, but no subjective assessments were made.

UUO-induced renal fibrosis model

Mouse models of renal fibrosis were established by procedures for UUO⁴⁰. Following sodium pentobarbital anesthesia (30 mg/kg, i.p.), the left ureter was double-ligated using 5-0 silk via dorsal incision. Sham controls underwent identical surgical exposure without ligation.

Adenine-induced renal fibrosis model

Experimental groups received daily oral gavage of adenine suspension (80 mg/kg) for 3 weeks, while controls received equivalent saline volumes⁴¹.

p-Hydroxybenzaldehyde (PHBA) and aspirin (ASP) treatment in vivo

Drug dosages were determined through interspecies conversion and prior pharmacokinetic studies⁴². The mice were administered with PHBA or ASP at 10 and 50 mg/kg/day. In UUO mice, the treatment groups were administered the appropriate drugs via oral gavage for 14 consecutive days post-surgery. In addition, PHBA treatment was initiated 4 days after UUO and continued for 2 weeks to mimic the clinic scenario.

Hepatocyte-specific FGL1 knockout mice

To specifically knockout FGL1 in hepatocytes, we produced a mouse line by crossing female FGL1-floxed mice (FGL1^fl/fl) with male Alb-Cre transgenic mice (Gempharmatech Co., Ltd, 8–9 weeks old). The F1 progeny, either male or female, with heterozygous deletion of the FGL1 gene (FGL1^fl/-) and carrying the Alb-Cre transgene (FGL1^fl/-, Alb-Cre) were obtained. These mice were then crossed with FGL1^fl/fl mice of opposite sex to generate the F2 progeny, which expressed complete deletion of FGL1 in hepatocytes (FGL1^fl/fl, Alb-Cre), herein referred to as FGL1 HepKO mice. Genotype verification was performed through tail biopsy PCR analysis.

AAV-mediated hepatic FGL1 knockout in mice

For hepatic FGL1 knockout, AAV8-mediated delivery of Cre recombinase was employed in C57BL/6J mice. Each FGL1^fl/fl mouse received a single tail vein injection of 7 μL of AAV8-TBG-Cre virus suspension (virus titer >10¹³ vg/mL, Hanbio Biotech Co., Ltd) blended with 193 μL saline. Control mice were injected with AAV8-TBG-Ctrl. Three weeks after injection, mice were sacrificed, and liver tissues were collected for analysis. The knockout efficiency was confirmed by qPCR.

AAV-mediated hepatic FGL1 overexpression in mice

For hepatic FGL1 reconstitution, AAV8-mediated delivery was employed in C57BL/6J mice. Each mouse received a single tail vein injection of 7 μL of AAV8-TBG-FGL1-EGFP virus suspension (virus titer >10¹³ vg/mL, PackGene Biotech Co., Ltd) blended with 193 μL saline. Control mice were injected with AAV8-TBG-Ctrl. Hepatic transduction efficiency was confirmed by Western blot after 3 weeks of injection.

Neutralizing antibody against FGL1 in mice

Mice were stratified into four groups: (1) Sham+IgG (100 μg); (2) Sham+Anti-FGL1 mAb (100 μg); (3) UUO+IgG (100 μg); (4) UUO+Anti-FGL1 mAb (100 μg). Intraperitoneal injections were initiated 24 h post-surgery and repeated on days 4, 8, and 12 after surgery. Euthanasia was performed on day 14 via cervical dislocation under anesthesia.

RNA-seq analysis

Mice livers were preserved in RNAlater and sent to Majorbio (Shanghai, China) for sequencing. After RNA quality check, a sequencing library was created using TruSeq technology. Sequencing was performed on a HiSeq X Ten (Illumina). Differentially expressed genes were identified based on an adjusted p < 0.05. For heatmap visualization of differentially expressed genes, the data were subjected to z-score normalization.

Single-cell RNA-seq analysis

The gene expression levels of Fgl1, Orm2, Mt2, Saa1, and Saa2 in various cell types of liver or kidney were analyzed using published scRNA-seq data^43,44. The scRNA-seq data were obtained from the Gene Expression Omnibus dataset (GSE115469, GSE131685).

Cell culture

Human renal proximal tubular epithelial cells (HK-2), human embryonic kidney cells (HEK-293T) and mouse hepatocytes (AML12) were obtained from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China; STR-authenticated). Cells were maintained in DMEM/F12 (HK-2) or DMEM(HEK-293T/AML12) supplemented with 10% fetal bovine serum and 1% penicillin/streptomycin at 37 °C/5% CO₂. HK-2 cells were exposed to 10 ng/mL TGF-β and/or 400 ng/mL FGL1; AML12 cells were exposed to IL-6, IL-1β, and TNF-α (25 ng/mL each).

Cytotoxicity assessment

Cell Counting Kit-8 (CCK8) was used to analyze the cell viability of AML12 cells or HEK-293T cells. Briefly, AML12 or HEK-293T cells were treated with varying concentrations of the candidate compounds for 24 h. Then, the CCK8 solution was added, and the cells were stored in the incubator for 2 h. The optical density of each well was measured at 450 nm using a microplate reader.

ELISA quantification

The sera of humans and mice were collected by centrifuging at 2000 × g for 10 min. The levels of FGL1 in the different experimental groups were determined using the human or mouse FGL1 ELISA kits according to the manufacturer’s instructions. The levels of IL-6, IL-1β and TNF-α were determined using ELISA kits. Serum ALT and AST activities were measured using commercial kits. The levels of blood urea nitrogen and creatinine were determined according to the manufacturer’s instructions.

Histological analysis

Kidney, liver and heart tissues were fixed in 4% paraformaldehyde (PFA) and embedded in paraffin wax. For histological evaluation, sections were stained with Hematoxylin and Eosin (HE) to assess general tissue morphology. To evaluate collagen deposition, sections were stained using Masson’s trichrome stain. Fibrotic areas were quantified using ImageJ software. Image acquisition was performed with a NanoZoomer RS scanner (Hamamatsu, Japan).

Three-dimensional (3D) visualization of the kidneys

Mice were surgically anesthetized with 2% isoflurane and perfused with 20 mL of PBS followed by 20 mL of 4% PFA solution. Kidneys were rapidly dissected, fixed in 4% PFA at 4 °C for 24 h, followed by 1 h post-fixation at room temperature. Kidney tissues were stored in PBS at 4 °C for subsequent processing. Tissue clearing was performed using the Enhanced Tissue Clearing Kit according to the manufacturer’s protocol. Cleared kidneys were mounted in a refractive index-matched imaging chamber and subjected to light-sheet microscopy using the LS18 system (Nuohai Life Science, China) equipped with a 6.3× objective. For whole-organ imaging, the 562 nm laser power was maintained at 50% intensity. Three-dimensional scanning was achieved through multiplane acquisition (X/Y/Z axes) with 2 μm isotropic resolution. Raw image stacks were preprocessed using Combine Software (Nuohai Life Science, China) for background subtraction and noise reduction. Subsequent 3D reconstruction was performed with Imaris x64 software (Bitplane, Switzerland) using surface rendering algorithms. Orthogonal projections were generated at 90° intervals to demonstrate spatial relationships within the kidney architecture.

Immunofluorescence staining

For kidney tissue analysis, cryosections were incubated with primary antibodies in a humidified dark chamber at 4 °C for 16 h. After PBS washes (3 × 5 min), sections were incubated with species-matched secondary antibodies (1:200) for 1 h, followed by 10 min DAPI nuclear counterstaining. In vitro experiments using HK-2 cells were conducted as follows: cells were fixed with 4% PFA for 15 min, permeabilized with 0.2% Triton X-100 for 10 min, and blocked with 5% BSA for 1 h. Primary antibody incubation was performed overnight at 4 °C, followed by 2 h secondary antibody treatment and DAPI staining for 10 min. All images were acquired using an FV3000 confocal microscope (Olympus, Japan) with a 60× oil-immersion objective.

Immunohistochemical staining

Formalin-fixed paraffin-embedded kidney sections (4 μm thickness) were deparaffinized in xylene (3 × 5 min) and rehydrated through a graded ethanol series (100–70%). Antigen retrieval was performed in 10 mM citrate buffer (pH 6.0) at 95 °C for 20 min. Following endogenous peroxidase quenching with 3% H₂O₂, sections were incubated with primary antibodies for 1 h at 37 °C. Whole-slide digital imaging was conducted using the NanoZoomer RS scanner (Hamamatsu, Japan) at 40 × magnification.

Western blot analysis

Tissues and cells were harvested and immediately lysed in RIPA buffer supplemented with protease and phosphatase inhibitors to prevent protein degradation and dephosphorylation. Lysates were incubated on ice for 30 min to ensure complete lysis. Cell debris was removed by centrifugation at 12,000 × g for 10 min at 4 °C, and the resulting supernatant (total protein extract) was collected and stored at −80 °C until further use. Protein concentration was quantified using the BCA Protein Assay Kit following the manufacturer’s instructions. The immunoblotting procedures were performed as previously described⁴⁵. Antibodies used in this study are listed in Supplementary Table 2. Semi-quantitative analysis of protein bands was conducted using ImageJ software (v1.8.0), with band densities normalized to the housekeeping proteins GAPDH or β-TUBULIN for loading control.

Real-time fluorescence quantitative PCR (RT-qPCR)

Total mRNA was isolated from tissues or cells using a High Pure RNA Isolation Kit, with RNA concentration and purity verified by NanoDrop spectrophotometry (A260/A280 ratio 1.8–2.0). Reverse transcription was performed with cDNA Synthesis SuperMix according to the manufacturer’s protocol. Relative expression levels of target genes were calculated using the 2^−ΔΔCt method, normalized to Actb as the endogenous control. Primer sets for genes are summarized in Supplementary Table 3.

Label-free quantitative proteomics analysis

Kidney tissues from UUO-AAV-Ctrl mice (n = 3, negative control) and UUO-AAV-FGL1 mice (n = 3, experimental group) were snap-frozen in liquid nitrogen, pulverized, and homogenized in SDS-based lysis buffer (50 mM Tris-HCl, pH 8.0, 150 mM NaCl, 1% SDS, protease/phosphatase inhibitors) with ultrasonication (400 W, 10 cycles). Lysates were denatured (95 °C, 10 min), centrifuged (16,000 × g, 20 min, 4 °C), and quantified via tryptophan fluorescence assay⁴⁶.

Each biological sample was processed in technical duplicate (n = 2). Aliquots of 100 μg protein were subjected to FASP: reduced with DTT, alkylated with IAA, and digested with trypsin (50:1, 37 °C, 16 h). Peptides were desalted and analyzed on an EASY-nLC 1200 UHPLC-Q Exactive Plus Orbitrap MS (Thermo Fisher Scientific, USA) with a C18 column (75 μm × 25 cm, 1.9 μm). LC gradient: 2–35% acetonitrile (0.1% formic acid) over 90 min (300 nL/min, 50 °C). MS acquisition: DDA mode (m/z 350-1800, resolution 70/17.5 k for full/ms² scans, HCD collision energy 27%, dynamic exclusion 30 s).

A pooled QC sample was analyzed at regular intervals (RSD for retention time <2%, peak intensity <15%). Raw data were processed with MaxQuant (v2.1.6.0) against UniProt Mus musculus database (UP000000589), with trypsin (2 missed cleavages), carbamidomethylation (Cys), oxidation (Met)/acetylation (N-term) as modifications, and FDR < 1%. Differentially expressed proteins (DEPs: FC > 1.2 or FC < 0.83, adjusted p < 0.05) were analyzed via R packages (limma v3.54.0, clusterProfiler v4.6.2) with Benjamini-Hochberg correction and Fisher’s exact test. Detailed parameters are in Supplementary Data 1.

Prediction of FGL1–ALK5 interactions

The AlphaFold3-predicted structures of the FGL1 and ALK5 were used as the initial structures for the MD simulations. The protein was first solvated with a regular cubic SPC water box with an 8.0 Å minimum distance to the box surface. To keep the whole system neutral, 7 Na+ ions were added to the solvent. The protein was parameterized using the ff14SB force fields. The resulting topology and coordinate files were generated using the tleap module in Amber20. All simulations were conducted using the pmemd.CUDA tool in Amber20.

Plasmids and transfection

HA-FGL1, Flag-ALK5, Myc-Smad7 and Ubiquitin plasmids were generated by cloning the indicated genes into pcDNA3.1 (PPL Co., Ltd, China). Site-directed mutagenesis was generated using a QuickMutation Site-Directed Mutagenesis Kit according to the manufacturer’s instructions, and plasmids were transfected with Lipofectamine 2000 according to the manufacturer’s protocol.

Bimolecular fluorescence complementation (BiFC)

Reconstitution of Venus fluorescent signal was performed as follows: HEK-293T cells seeded in 35-mm imaging dishes were co-transfected with pBiFC-FGL1-VC155 (1 μg) +pBiFC-ALK5-VN173 (1 μg). Negative control groups received either pBiFC-FGL1-VC155 + VN173 vector or pBiFC-ALK5-VN173 + VC155 vector. At 24 h post-transfection, live cells were stained with 5 μg/mL Hoechst 33342 for 15 min. The fluorescent signals were captured using an FV3000 confocal microscope (Olympus, Japan) with a 60× oil objective, employing 405 nm (Hoechst) and 515 nm (Venus) excitation wavelengths.

Co-immunoprecipitation assay

FGL1-ALK5 interaction was investigated through Co-IP using the crosslinker-enhanced protocol. Cells were lysed in 500 μL IP buffer supplemented with protease inhibitor cocktail. Lysates were clarified by centrifugation at 12,000 × g for 10 min at 4 °C, followed by protein quantification using BCA assay. For each immunoprecipitation, 400 μg total protein was pre-cleared with 20 μL protein A/G magnetic beads for 1 h at 4 °C. Pre-cleared lysates were incubated with 2 μg of specific antibodies or species-matched IgG control overnight at 4 °C with gentle rotation. Immune complexes were captured by adding 25 μL pre-washed magnetic beads (50% slurry) for 6 h at 4 °C. After five washes with PBS, bound proteins were eluted at 95 °C for 5 min and analyzed by immunoblotting.

Bio-layer interferometry (BLI)

Real-time binding kinetics were quantified using the Octet RED96e system (Sartorius, Germany). His-tagged FGL1 was loaded onto Ni-NTA biosensors to achieve 1 nm wavelength shift. After baseline stabilization in kinetics buffer (PBS + 0.01% Tween 20 + 0.1% BSA), sensors were exposed to serially diluted ALK5 (3.9–125 nM) for the association phase (150 s), followed by dissociation monitoring in analyte-free buffer (60 s). Reference subtraction was performed using buffer-only sensors and blank-loaded biosensors. Binding curves were globally fitted to a 1:1 Langmuir model using Octet Analysis Studio to obtain corresponding kinetic parameters⁴⁷.

Surface plasmon resonance (SPR)

Detailed binding thermodynamics were characterized using Biacore T200 (Cytiva, USA). CM5 sensor chips were activated with EDC/NHS (1:1) for 7 min at 10 μL/min. FGL1 in 10 mM sodium acetate (pH 4.0) was immobilized to achieve 8500 RU, followed by ethanolamine blocking. ALK5, ALK5_1-125 and ALK5_200-503 in HBS-EP were injected over the chip surface at 30 μL/min using multicycle kinetics. Concentration series (0.39–50 nM) were analyzed at contact time 60 s and dissociation 30 s. Data were processed using standard double-referencing and fitted to a 1:1 binding model using Biacore T200 Evaluation software (Cytiva, USA). The binding curves were analyzed to determine the equilibrium dissociation constant (KD).

High-throughput screening

A library of 4080 natural compounds was screened using HEK-293T cells. These cells were transfected with 10 μg of the pGL3-FGL1-promoter luciferase plasmid (reporter plasmid) and 1 μg of the pRL-TK-promoter luciferase plasmid (Renilla luciferase, used as an internal control). Following 24 h of transfection, cells were digested and reseeded into 384-well plates. After 24 h, natural compounds (10 μM) were subsequently added to the wells and incubated for another 24 h. Luciferase activity was quantified using the Dual-Glo Luciferase Assay Kit and detected by Envision Microplate System (PerkinElmer, USA).

Statistical analysis

Data are presented as mean ± standard deviation (SD). Multiple group comparisons were analyzed by one-way ANOVA with Tukey’s correction, while pairwise comparisons were assessed using two-tailed Student’s t tests. Statistical analyses were conducted using Prism 9.0 Software. Significance was defined as p < 0.05.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

Source data for Figs. 1–7 and Supplementary Figs. 1–18 have been provided as Source Datafiles. All data supporting the findings described in this manuscript are available in the article and in the Supplementary Information and from the corresponding author upon request. The RNA sequence data generated in this study have been deposited in the NCBI database under accession code PRJNA1254202. The scRNA-seq data were obtained from Gene Expression Omnibus datasets GSE115469 and GSE131685. The mass spectrometry proteomics generated in this study have been deposited in the ProteomeXchange Consortium under accession code PXD064971 [https://www.iprox.cn//page/project.html?id=IPX0012283000]. Source data are provided with this paper.

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Acknowledgements

This study was supported by the National Natural Science Foundation of China (Grant 82330123 to L.W.Q.), the Frontier Technologies R&D Program of Jiangsu (Grant BF2024074 to L.W.Q.), the National Natural Science Foundation of China (Grant 82374103 and 82174036 to Q.L.) and Fundamental Research Funds for the Central Universities (Grant 2632024TD03 to Q.L.). We thank Wei Jiang in China Pharmaceutical University for assistance in SPR and BLI experiments. Special thanks go to Dr. Raphael N. Alolga for his valuable assistance in polishing this manuscript.

Author information

These authors contributed equally: Wen-Hui Wu, Li-Zeng Zhu, Kang Liu.

Authors and Affiliations

State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
Wen-Hui Wu, Li-Zeng Zhu, Lin Cao, Yuan-Ming Fan, Ping Zhou, Yue Zhang, Gaoxiang Ma, Jin-Feng Liu, Bao-Lin Liu, Lian-Wen Qi & Qun Liu
School of Life Science and Biopharmaceutics, Shenyang Pharmaceutical University, Shenyang, China
Wen-Hui Wu & Lian-Wen Qi
Department of Nephrology, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
Kang Liu
Pukou Hospital of Chinese Medicine affiliated to China Pharmaceutical University, Nanjing, China
Gaoxiang Ma

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Wen-Hui Wu
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Contributions

Conceptualization: Q.L., L.W.Q., and W.H.W.; Methodology: W.H.W., L.Z.Z., Y.M.F., P.Z., B.L.L, and J.F.L.; Investigation: W.H.W., L.Z.Z., L.C., Y.M.F., and Y.Z.; Visualization: L.C. and Y.M.F. Funding acquisition: Q.L. and L.W.Q.; Project administration: L.W.Q. and Q.L.; Supervision: K.L. and G.M.; Writing–original draft: B.L.L, W.H.W., L.Z.Z. and L.C.; Writing–review and editing: Q.L., L.W.Q., W.H.W., and B.L.L.

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Correspondence to Lian-Wen Qi or Qun Liu.

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Wu, WH., Zhu, LZ., Liu, K. et al. Hepatokine fibrinogen-like protein 1 drives liver-kidney crosstalk to promote renal fibrosis. Nat Commun 17, 1453 (2026). https://doi.org/10.1038/s41467-025-68188-0

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Received: 05 July 2025
Accepted: 16 December 2025
Published: 09 January 2026
Version of record: 09 February 2026
DOI: https://doi.org/10.1038/s41467-025-68188-0