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. 2025 Sep 26;27:180. doi: 10.1186/s13075-025-03647-z

The Glycolysis-HIF-1α axis induces IL-1β of macrophages in rheumatoid arthritis

Yimeng Jia 1,2,#, Rongli Li 1,3,#, Linfang Huang 4, Xunyao Wu 5, Lidan Zhao 1,2, Huaxia Yang 1,2, Xin You 1,2, Yunyun Fei 1,2,6,✉
PMCID: PMC12465665  PMID: 41013704

Abstract

Background

Rheumatoid arthritis (RA) is an aggressive, systemic autoimmune disease in which overactivated macrophages play a critical role in its pathogenesis. This study aimed to explore the potential role of glycolytic reprogramming in the production of proinflammatory cytokines by macrophages in RA.

Methods

The Seahorse assay was conducted on RA or healthy control (HC) serum-treated human monocyte-derived macrophages (HMDMs) to evaluate glycolysis levels. RNA sequencing was performed to identify activated signaling pathways and key molecules in HMDMs stimulated by RA serum. The proinflammatory cytokines and hypoxia-inducible factor 1α (HIF-1α) were verified by Western blotting and quantitative polymerase chain reaction (qPCR).

Results

We found that HMDMs stimulated with RA serum showed higher aerobic glycolysis levels than those treated with HC serum, along with higher expression of glycolysis-related genes, including hexokinase2 (HK2), pyruvate kinase L/R (PKLR), and phosphoglycerate kinase 1 (PGK1). Furthermore, RA serum-treated macrophages exhibited a higher level of interleukin-1 beta (IL-1β), and the expression of IL-1β positively correlated with HK2. Inhibition of glycolysis by 3-bromopyruvate (3BrPA) or HK2 knockdown significantly suppressed IL-1β production in macrophages. The HIF-1α-associated signaling pathways and HIF-1α protein levels were also elevated in RA serum-treated macrophages. Inhibition of glycolysis by 3BrPA or knockdown of HK2 reduced HIF-1α. Inhibiting HIF-1α can suppress IL-1β production of RA serum-treated macrophages, and vice versa. TNF-α and IL-1β enhanced HIF-1α and IL-1β expression in macrophages, an effect attenuated by glycolysis inhibition. Blocking TNF-α and IL-1β in RA serum diminished both glycolysis and IL-1β production.

Conclusion

Our findings demonstrate that RA serum triggers aerobic glycolysis in macrophages, which promotes HIF-1α to drive IL-1β production. Notably, IL-1β within RA serum amplifies its own expression via this glycolysis-HIF-1α axis, establishing a pathogenic positive feedback loop in RA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-025-03647-z.

Keywords: Rheumatoid arthritis, Macrophage, Glycolysis, HIF-1α, IL-1β

Introduction

Rheumatoid arthritis (RA) is one of the most prevalent immune-mediated inflammatory diseases characterized by pain, swelling, and stiffness that typically affects symmetrically distributed small and large joints [1]. A proportion of patients continue to experience persistent, treatment-resistant disease, and sustained remission is rarely achieved [2]. Therefore, pathobiological understanding of RA must be enhanced to develop new therapeutic targets.

There is increasing evidence of metabolic changes in stromal and immune cells of autoimmune diseases [3]. In RA, the increased energy demand and the resulting immune metabolic reprogramming have been confirmed, with the upregulation of the glycolytic pathway being one of the most evident metabolic adaptations [4]. In the affected joints of RA patients, an increase in glucose consumption has been detected [5]. Inhibiting glycolysis has been shown to impair cytokine secretion, proliferation, and invasion in RA fibroblast-like synoviocytes (FLS) [6].

Macrophages are central effectors of RA acting through the release of cytokines, reactive oxygen intermediates, nitrogen intermediates, matrix-degrading enzymes, phagocytosis, and antigen presentation [7]. One of the key mechanisms through which currently effective biologic agents alleviate RA in clinical practice is by reducing macrophage infiltration in the synovium [8]. Metabolic reprogramming is functional to support macrophage activities and sustain their polarization in specific contexts [9]. In arthritic joints, macrophages display hypermetabolic activity and produce excess amounts of succinate sensed via GPR91 to amplify cytokine release [10]. Furthermore, RA macrophages express elevated levels of the glycolytic enzyme α-enolase, which is recognized by autoantibodies to trigger inflammatory cytokine production [11]. Increased mitochondrial activity and ATP production of macrophages have also been observed in patients with RA [12]. However, research on the catalysts of aberrant upregulation of glycolysis in RA macrophages and its potential pathogenic mechanisms remains limited. In the present study, we investigated the altered glycolytic profile of macrophages induced by RA serum and explored the effect of this glycolytic reprogramming on macrophage function and its potential mechanisms. We further identified the critical factors in RA serum that drive the reprogramming of glycolysis in macrophages.

Method

Patients and controls

Fifty-eight treatment-naïve active RA patients (37 females and 21 males, age 48.7 ± 11.6 years, disease duration 12 (4–45) months) were recruited from Peking Union Medical College Hospital (PUMCH) between March 2021 and May 2024 (Supplementary Table 1). All RA patients fulfilled the 2010 ACR/EULAR classification criteria for RA [13], and active RA was defined as Disease Activity Score 28 (DAS28) score ≥ 3.2. Sixty-four gender- and age-matched healthy volunteers (42 females and 22 males, age 44.9 ± 10.3 years) were enrolled as healthy controls (HC). Serum samples of RA and HC were collected and stored at − 80 °C until use within 1 year. The study was approved by the institutional review board of PUMCH (K23C2052), and written informed consent was obtained from all subjects.

Cell Preparation

Monocytes were isolated from RA patients and paired HC peripheral blood mononuclear cells (PBMCs) with CD14+ MicroBeads (Miltenyi Biotec). Monocytes (3 × 105 cells) were seeded onto 96-well plates and were incubated in a complete DMEM medium supplemented with Macrophage Colony-Stimulating Factor (M-CSF) (50ng/ml, Peprotech) for 7 days to differentiate into adherent human monocyte-derived macrophages (HMDMs). Complete DMEM contains DMEM (Gibco), 10% fetal bovine serum (FBS, Gibco), and penicillin and streptomycin (Gibco). Tohoku Hospital Pediatrics-1 (THP-1) cell line (ATCC TIB-202) was purchased from the American Type Culture Collection and cultured according to their specific indications, using an RPMI 1640 medium supplemented with 10% fetal bovine serum (FBS, Gibco), and penicillin and streptomycin (Gibco). Cell differentiation was induced via a 24 h exposure to 100ng/ml phorbol 12-myristate 13-acetate (PMA, Multisciences).

Macrophage polarization and in vitro stimulation

Resting (M0) macrophages were defined as HMDMs without additional stimulation [14]. For M1 polarization, M0 were stimulated with lipopolysaccharide (LPS) (100ng/ml, Sigma, L2630) plus Interferon-γ (IFN-γ) (20ng/ml, Novoprotein, CI57) for 48 h. For the human serum stimulation, M0 were treated with 20% RA or HC serum for 6, 12, 24–48 h separately. For cytokines stimulation, HMDMs were incubated with 50ng/ml Tumor necrosis factor alpha (TNF-α) (Peprotech, 300–01 A), 50ng/ml Interleukin-1 beta (IL-1β) (Peprotech, 200-01B), 50ng/ml Granulocyte-macrophage colony stimulating factor (GM-CSF) (Novoprotein, C003), 50ng/ml Interleukin-6 (IL-6) (Peprotech, 200-06) and 50ng/ml IFN-γ (Novoprotein, CI57) for 24 h. For inhibition of glycolysis, HMDMs were pretreated with 10 µM or 40 µM of 3-Bromopyruvic acid (3BrPA, HY-19992, MedChemExpress), 5mM of 2-Deoxy-D-glucose (2-DG, MedChemExpress, HY-13966) for 3 h. For stabilization and inhibition of HIF-1α, HMDMs were pretreated with 100 µM of Dimethyloxallyl Glycine (DMOG, MedChemExpress, HY-15893) and 20 µM of LW6 (HY-13671, MedChemExpress) for 3 h, respectively. For cytokine blocking, HMDMs were incubated with RA serum with 100ng/ml of Interleukin-1 receptor antagonist (IL-1RN, HY-P7029, MedChemExpress), 10 µg/ml of Infliximab (HY-P9970, MedChemExpress), or Lenzilumab (HY-P99207, MedChemExpress) for 24 h, respectively.

Metabolic measurement

HMDMs were detached from cell culture plates with 0.25% trypsin (Thermo, 25200072) and incubated at 37 °C in a 5% CO₂ incubator for 5 min, with the digestion process repeated twice. The digested macrophages were then seeded onto Seahorse Extracellular Flux (XF) 96 plates (Seahorse Biosciences) precoated with Poly-L-Lysine solution (Solarbio, P2100) at a density of 5 × 10⁴ cells per well. The metabolic phenotype of HMDMs was assessed using a Seahorse XFe96 Extracellular Flux Analyzer (Seahorse Biosciences) according to the manufacturer’s instructions. The extracellular acidification rate (ECAR) was measured to assess glycolysis levels using the Glycolysis Stress Test kit (103020-100, Agilent Technology), following the manufacturer’s protocol.

RNA sequencing (RNA-Seq) and data analysis

HMDMs (M0) from 4 HCs were treated with 20% RA serum or HC serum for 24 h. Total RNA was extracted using TRIzol reagent (Invitrogen, USA) for subsequent RNA sequencing (BioMarker, China). Raw data in FASTQ format were first processed in-house using custom scripts, and clean data were obtained by removing reads containing adapters, reads containing poly-N sequences, and low-quality reads. HTSeq v0.6.0 was used to count the read numbers mapped to each gene. Differential expression analysis was performed using the DESeq2 R package (v1.10.1) with a significance threshold of p < 0.05 and |fold change| >1.5.

Pathway enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases. Gene Set Enrichment Analysis (GSEA) was conducted on the KEGG database and the C7 gene sets from MSigDB collections using the clusterProfiler R package (v3.21). Significantly enriched pathways were identified using a cutoff of p < 0.05 and a Benjamini-Hochberg-adjusted p < 0.25.

Real-time quantitative polymerase chain reaction (RT-qPCR)

Total RNA was extracted with RNA-Quick Purification Kit (EScience Biotech, China) and subjected to reverse transcription using PrimeScript RT Master Mix (Takara). RT-qPCR was performed with SYBR Premix Ex Taq II (Tli RNaseH Plus, Takara) using the Sequences of primers listed in Supplementary Table 2.

Enzyme-linked immunosorbent assay (ELISA)

Levels of IL-1β, IL-6, and TNF-α in the cell culture supernatants were measured with commercially available standard sandwich enzyme-linked kits (Liankebio).

Western blot analysis

Cells were lysed in 1×RIPA buffer (Solarbio, China) containing protease/phosphatase inhibitors. BioRad Transfer system was used and Tanon 5800 Multi Image was used for scanning. The primary and secondary antibodies used were as follows: IL-1β (1:1000, 12703, Cell signaling technology), HIF-1α ( 1:1000, ab82832, Abcam), β-actin (1:2000, A228, Sigma), Anti-rabbit IgG-HRP ( 1:4000, BE0101, Easybio), and Anti-mouse IgG-HRP ( 1:4000, BE0102, Easybio).

SiRNA transfection

Small interfering RNA (siRNA) against HK2 (20 nmol), HIF-1α (100 nmol), and negative control siRNAs were synthesized by RiboBio (Guangzhou, China). Cells were cultured at 70–80% confluence and transfected with siRNAs using Lipofectamine 3000 reagent (Thermo Fisher Scientific, United States) following the manufacturer’s protocol. Sequences of siRNA were listed in Supplementary Table 2.

Statistical analysis

All the data were analyzed using IBM SPSS statistics (Version 25.0, IBM, USA) and GraphPad Prism 8 (GraphPad Software, USA) software. The data were first performed with the normality distribution. Data with normal distributions were analyzed using one-way ANOVA for multiple-group comparisons and t-tests for two-group comparisons. For non-normally distributed data, the Kruskal-Wallis test was used for multiple groups, and the Mann-Whitney test for two groups. The Pearson correlation analysis was adopted for correlation analysis. Statistical significance was defined as a two-sided p-value < 0.05.

Result

RA serum promotes glycolytic reprogramming of macrophages

Previous studies indicate that macrophages in RA patients predominantly exhibit a pro-inflammatory phenotype [15]. To evaluate the glycolytic capacity of macrophages in RA, we first measured extracellular acidification rate (ECAR) in HMDMs stimulated with or without M1- polarizing condition from RA patients and healthy controls (HC) using a Seahorse XF analyzer. The maximum ECAR of HMDMs significantly increased under M1-polarizing conditions (Fig. 1A-B). Glycolysis and glycolytic capacity also tended to be upregulated in response to M1-polarizing conditions (Fig. 1B and Figure S1A). However, we did not observe significant differences in glycolytic levels between macrophages from RA and HC, regardless of whether they were in a resting (M0) or activated (M1) state.

Fig. 1.

Fig. 1

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RA serum promotes glycolytic reprogramming of macrophages.Resting macrophages (M0) were stimulated with M1 condition (100ng/ml LPS + 20ng/ml IFN-γ) for 48 h, RA serum (20%), or HC serum (20%) for 24 h.(A-B) Seahorse analysis of extracellular acidification rate (ECAR) in macrophages stimulated with M0 or M1 conditions from HC (n = 5) and RA patients (n = 5), respectively.(C-D) Seahorse analysis of ECAR in macrophages under HC serum or RA serum stimulation from HC (n = 5) and RA patients (n = 5), respectively.(E) Expression of glycolytic enzymes including HK2, PKLR, PGK1, and PFKM in macrophages stimulated with RA or HC serum for 6 h, 12 h, 24 h, and 48 h (n = 8).Paired t-test or Wilcoxon Signed-Rank Test was performed to analyze the statistics with/without treatment of the same group. Two-tailed student’s t-test or Mann-Whitney Test was performed to compare statistics from two independent groups. *, p < 0.05; **, p < 0.01; HK2, hexokinase2; PKLR, Pyruvate Kinase L/R; PGK1, Phosphoglycerate Kinase 1; PFKM, Phosphofructokinase, Muscle

Next, we explored whether factors in RA serum affect glycolysis and treated macrophages from RA and HC with serum from either RA or HC separately. Macrophages treated with RA serum exhibited higher levels of glycolysis and glycolytic capacity than those treated with HC serum, regardless of whether the macrophages were derived from HC or RA (Fig. 1C-D and Figure S1B). We further measured the expression of key genes related to the glycolytic pathway in HMDMs at the transcriptional level. Consistent with the Seahorse findings, hexokinase2 (HK2), pyruvate kinase L/R (PKLR), and phosphoglycerate kinase 1 (PGK1) expression were increased in RA serum-treated HMDMs compared to HC serum-treated HMDMs (Fig. 1E). These findings suggest that macrophages in RA patients undergo glycolytic reprogramming, a process that may depend more on environmental signaling stimuli.

RA serum induces IL-1β expression of macrophages in a glycolysis-dependent manner

Activated macrophages in RA produce a variety of proinflammatory cytokines that promote and maintain inflammation [15]. To assess the effect of RA serum on macrophage proinflammatory function, we analyzed expression of key inflammatory cytokines including IL-1β, TNF-α, and IL-6. Compared to HC serum-stimulated macrophages, RA serum-treated macrophages showed significantly elevated IL-1β mRNA and protein levels, but no significant changes in TNF-α or IL-6 expression (Fig. 2A-B). Furthermore, elevated IL-1β levels positively correlated with HK2 expression (r = 0.87, p < 0.0001), suggesting a potential association between glycolysis and IL-1β production (Fig. 2C). To investigate whether glycolytic reprogramming influences IL-1β production after RA serum exposure, we pretreated HMDMs with the HK inhibitor 3BrPA before RA serum stimulation. Western blot analysis confirmed that 3BrPA significantly reduced RA serum-induced IL-1β levels (Fig. 2D).

Fig. 2.

Fig. 2

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RA serum induces IL-1β of macrophages in a glycolysis-dependent manner.(A) IL-1β, IL-6, and TNFα mRNA levels in macrophages treated with HC serum or RA serum for 6 h, 12 h, 24 h, and 48 h (n = 8). Data were analyzed using Paired t-test or Wilcoxon Signed-Rank Test.(B) IL-1β, IL-6, and TNFα production in macrophages following treatment with HC serum or RA serum for 24 h detected by ELISA (n = 10). (C) Correlation analysis of IL-1β with HK2 in macrophages treated with HC serum and RA serum (n = 16). (D) IL-1β levels in RA serum-treated macrophages pretreated ± 3BrPA (10µM or 40µM) for 3 h determined by Western blot (n = 4).(E) RA serum-induced IL-1β mRNA (n = 6) and protein (n = 8) levels in PMA-Differentiated THP-1 Cells transfected with siRNAs for HK2 (si-HK2) or control siRNA (si-NC).Data were shown as mean ± SEM and were analyzed using Two-tailed student’s t-test or one-way ANOVA. *, p < 0.05; **, p < 0.01. 3BrPA, 3-Bromopyruvic acid

Since PMA-differentiated THP-1 cells serve as a reliable macrophage model [16], we validated our findings in this system. RA serum-treated THP-1 cells showed higher HK2 and IL-1β levels compared to HC serum-treated cells (Figure S2A), with IL-1β expression positively correlating with HK2 (Figure S2B). Moreover, HK2 knockdown via siRNA in THP-1 cells downregulated RA serum-induced IL-1β production (Fig. 2E and Figure S2C). Collectively, these data suggested that RA serum induces IL-1β expression of macrophages in a glycolysis-dependent manner.

Transcriptome profile of RA serum- and HC serum-treated macrophages

To investigate the impact of RA serum on macrophages at the transcriptomic level, we performed transcriptome analysis on macrophages stimulated with RA or HC serum (n = 4). Through screening of differentially expressed genes (DEGs) (p < 0.05 and |fold change| >1.5), we identified transcriptionally active gene signatures in RA serum-stimulated macrophages, characterized by 140 upregulated and 37 downregulated genes (Fig. 3A and Figure S3A). KEGG and GO biological process analyses revealed enriched gene sets related to chemotaxis, migration, and cytokine-cytokine receptor interactions (Fig. 3B-C). KEGG and GSEA analyses showed activation of inflammatory response pathways including the NF-κB, JAK-STAT, TNF, and IL-17 signaling pathways (Fig. 3C-D). Innate immune responses including the NOD-like receptor, Toll-like receptor, and RIG-I-like receptor signaling pathways were enhanced. Additionally, pathways associated with proliferation, differentiation, and survival including the MAPK, Hippo, and PI3K-Akt signaling pathways were significantly enriched in RA serum-stimulated macrophages (Fig. 3C-D and Figure S3B). Together, these transcriptome analyses suggest that RA serum promotes macrophage activation and inflammatory responses.

Fig. 3.

Fig. 3

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Transcriptome profile of RA serum- and HC serum-treated macrophages. HMDMs were stimulated with RA serum (n = 4) and HC serum (n = 4) for 24 h, and total RNA was extracted for RNA-Seq analysis. (A) Heatmap of upregulated (n = 140) and downregulated (n = 37) DEGs (|Fold change| >1.5, p < 0.05) between RA serum- and HC serum-treated macrophages. (B-C) GO biological process enrichment analysis and KEGG enrichment analysis between RA serum- and HC serum-treated macrophages. (D) Bubble plots showed Gene Set Enrichment Analysis (GSEA) of RA serum- and HC serum-treated macrophage. DEGs, differentially expressed genes; GO, gene ontology; KEGG, Kyoto Encyclopedia of Genes and Genome; NES, Normalized Enrichment Scores

Glycolysis-HIF-1α axis contributes to RA serum-induced IL-1β in macrophages

We next explored the molecular mechanism of RA serum-induced glycolysis-dependent IL-1β expression of macrophages. Previous studies have demonstrated that stabilized hypoxia-inducible factor 1α (HIF-1α) led to enhanced IL-1β production during inflammation, an effect suppressed by inhibition of glycolysis [17]. Our transcriptome analysis indicated that upstream signaling pathways of HIF-1α were significantly enriched including PI3K-Akt, MAPK, JAK-STAT, and NF-κB signaling pathways, which regulate the expression and stability of HIF-1α (Figs. 3D and 4A). Remarkably, RA serum-treated macrophages exhibited significantly higher HIF-1 signaling than the HC serum-treated macrophages (Fig. 4B). Furthermore, downstream signaling and targets of HIF-1α, including angiogenesis signaling, genes associated with hypoxic response (e.g., CDKN1A, SERPINE1), glycolysis (e.g., GLUT1, ENO2) were increased in the RA serum treated macrophages (Fig. 4C and Figure S4A-B). In light of these results, we detected HIF-1α in RA serum- and HC serum-treated HMDMs, which showed that RA serum induced a significantly higher level of HIF-1α and IL1-β in macrophages (Fig. 4D).

Fig. 4.

Fig. 4

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Glycolysis-HIF-1α axis contributes to RA serum-induced IL-1β in macrophages. (A) Illustration of the HIF-1 signaling pathway. (B)Mean expression of genes in the HIF-1 signaling pathway gene set (M47421) in the RA serum- and HC serum-treated macrophages, as determined by RNA-seq. Boxplots display median, 25th percentile, and 75th percentile, with whiskers representing minimum and maximum. Data were analyzed using Paired t-test.(C)Quantitation of select HIF-1α downstream effectors for glycolysis in RA serum-treated macrophage relative to HC serum-treated macrophage analyzed by RNA-seq. (D) Representative western blot images and summary of HIF-1α and IL-1β in macrophages incubated in HC or RA serum for 24 h (n = 5).(E) HIF-1α expression by 3BrPA-treated and untreated macrophages stimulated with RA serum (n = 5).(F) RA serum-induced HIF-1α in si-NC and si-HK2 transfected PMA-Differentiated THP-1 Cells (n = 6).(G)IL-1β of macrophages pretreated with LW6 or DMOG for 3 h followed by 24 h of RA serum stimulation (n = 5).Data were shown as mean ± SEM and were analyzed using one-way ANOVA or Two-tailed student’s t-test. *, p < 0.05; **, p < 0.01. HIF, Hypoxia-inducible factor; DMOG, Dimethyloxalylglycine; LW6, HIF-1α inhibitor

Considering that RA serum induced glycolysis-dependent IL-1β production, we aimed to determine whether RA serum-induced HIF-1α is also dependent on glycolysis. We pretreated RA serum-stimulated HMDMs with 3BrPA to inhibit glycolysis and subsequently observed a significant reduction in HIF-1α expression (Fig. 4E). Furthermore, knockdown of HK2 in PMA-differentiated THP-1 cells attenuated HIF-1α induced by RA serum (Fig. 4F). We further examined the functional relationship between HIF-1α and IL-1β. The HIF-1α stabilizer DMOG enhanced RA serum-induced IL-1β expression, while the HIF-1α inhibitor LW6 significantly reduced it (Fig. 4G). Additionally, HIF-1α knockdown attenuated IL-1β induction in PMA-differentiated THP-1 cells (Figure S4C-D). These results establish HIF-1α as the mechanistic link explaining glycolysis-dependent IL-1β production. Glycolysis-HIF-1α axis contributes to the upregulation of IL-1β in macrophages triggered by RA serum.

Blocking IL-1β in the RA serum attenuates glycolysis-HIF-1α axis mediated IL-1β

Given that cytokine receptor interaction and cellular response to cytokine stimulus-related signaling were enriched in our transcriptome analysis (Fig. 3B-D), we further investigated whether inflammatory mediators in RA serum were implicated in the glycolysis-HIF-1α axis-induced IL-1β in macrophages. TNF-α, IL-6, and IL-1β are key mediators of cell migration and inflammation in RA [18]. GM-CSF and IFN-γ are prototypical cytokines that drive the differentiation of proinflammatory M1-like macrophages [19]. In HMDMs, stimulation with IL-1β, TNF-α, or GM-CSF significantly upregulated HK2 and IL-1β expression, whereas IL-6 and IFN-γ showed no such effect (Fig. 5A). Notably, this cytokine-specific pattern became more pronounced under combinatorial stimulation conditions, where IL-1β demonstrated synergistic effects with either TNF-α or GM-CSF in amplifying HK2 and IL-1β expression (Figure S5A). HIF-1α expression was similarly elevated by TNF-α or IL-1β alone or in combination. Furthermore, glycolytic inhibition suppressed TNF-α- or IL-1β-induced HIF-1α and IL-1β expression but not GM-CSF-driven responses (Figs. 5B and S5B), indicating glycolysis-dependence for TNF-α- and IL-1β-induced IL-1β production.

Fig. 5.

Fig. 5

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Blocking IL-1β in the RA serum attenuates glycolysis-HIF-1α axis mediated IL-1β. (A)qPCR analysis of HK2, HIF-1α, and IL-1β mRNA expression in HMDMs stimulated for 24 h with IL-1β, TNF-α, GM-CSF, IFN-γ, or IL-6 (n = 7).(B)Representative image of IL-1β and HIF-1α expression in HMDMs pretreated with or without 2-DG (5 mM, 3 h) followed by 24 h stimulation with IL-1β, TNF-α, or GM-CSF (n = 4).(C)Extracellular acidification rate (ECAR) measured by Seahorse assay in HMDMs exposed to RA serum with or without IL-1RN, infliximab, or lenzilumab (n = 6).(D-E) Western blot analysis of HIF-1α and IL-1β expression in macrophages treated with RA serum in the presence or absence of (D) IL-1RN or (E) infliximab for 24 h (n = 6).Data were shown as mean ± SEM and were analyzed using one-way ANOVA or Two-tailed student’s t-test. *, p < 0.05; **, p < 0.01. 2-DG: 2-Deoxy-D-glucose; IL-1RN: Interleukin-1 receptor antagonist; IFX: Infliximab

We next examined whether blocking IL-1β, TNF-α, or GM-CSF in RA serum could reverse the glycolysis induced by RA serum by measuring the extracellular acidification rate (ECAR). Both TNF-α and IL-1β blockade significantly inhibited RA serum-induced glycolysis, whereas GM-CSF blockade had no effect (Fig. 5C). These findings suggest that TNF-α and IL-1β in RA serum contribute to the upregulation of glycolysis in macrophages. Furthermore, IL-1β blockade attenuated the expression of HIF-1α and IL-1β in HMDMs stimulated by RA serum (Fig. 5D). Although TNF-α blockade reduced IL-1β production, it did not affect HIF-1α levels (Fig. 5E). Collectively, these results indicate that IL-1β in RA serum promotes IL-1β production through the glycolysis-HIF-1α axis.

Discussion

This study first reports the glycolytic reprogramming of macrophages induced by RA serum and its regulation of IL-1β secretion. We further confirmed that IL-1β in the RA serum enhances the production of IL-1β through the glycolysis-HIF-1α axis, revealing a positive feedback loop (Fig. 6). Most studies focused on glucose metabolism of macrophage under the inflammatory stimuli toward M1 or M2 [20]. In contrast, our investigation examined the phenotypic changes in human-derived macrophages stimulated with serum from RA patients, reflecting the contributions of extracellular environmental to this disease. Notably, we observed no significant differences in glycolysis between macrophages derived from RA patients and those obtained from HC. However, macrophages stimulated with RA serum exhibited higher glycolytic activity compared to those stimulated with HC serum, indicating that alterations in macrophage glucose metabolism rely more on the cellular microenvironment than inherent cellular characteristics, thereby underscoring the plasticity of macrophages. The serum of RA patients contains a complex milieu of bioactive molecules, among which cytokines represent particularly potent mediators. Our study identified IL-1β as a key regulator that cooperatively upregulates HK2 and HIF-1α, synergizing with other cytokines to drive inflammation. Notably, blockade of IL-1β and TNF-α attenuated the serum-induced glycolytic upregulation, highlighting their central role in this metabolic reprogramming. Recent studies have reported that the TNF-α/TNFR2 axis mediates natural killer cell and Treg cell proliferation by promoting aerobic glycolysis [21, 22]. Interestingly, biologics including TNFi reduce the expression of GLUT1, PKM2 and GAPDH in the RA synovial tissue biopsies of responders compared to non-responders [23]. IL-1β has also been shown to enhance glycolysis in FLS and chondrocytes [24, 25]. Furthermore, this IL-1β-mediated glycolytic regulation was corroborated in RA synovial tissue, where synovial macrophage-derived IL-1β, in combination with TGF-β, induces a metabolic shift in fibroblasts toward glycolysis, promoting their pathogenic behavior [26]. In contrast, neutralizing GM-CSF in RA serum failed to reduce glycolysis induction, suggesting that GM-CSF is not the primary cytokine in RA serum mediating glycolysis upregulation. Multi-omics studies demonstrated that GM-CSF-differentiated macrophages preferentially utilize the tricarboxylic acid cycle (TCA cycle) and oxidative phosphorylation (OXPHOS) rather than glycolysis [27], and OXPHOS inhibition suppresses GM-CSF expression [28]. Additionally, clinical GM-CSF blockade reduces CCL22/IL-6 but not IL-1β in RA patients [29]. While IFN-γ and LPS synergistically promote M1 polarization with enhanced glycolysis [20], our study found that IFN-γ alone suppressed HK2 expression. Recent work shows IFN-γ enhances glycolysis primarily via fructose-2,6-bisphosphatase 3 (PFKFB3) upregulation [30], suggesting it may act through alternative glycolytic regulators rather than HK2, particularly in the absence of LPS.

Fig. 6.

Fig. 6

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Schematic summary illustrating the critical role of glycolysis-HIF-1α axis in promoting IL-1β in rheumatoid arthritis (RA). RA serum induces glycolytic reprogramming in macrophages via HK2 upregulation, which promotes HIF-1α to amplify IL-1β production. Notably, IL-1β within RA serum amplifies its own production via this glycolysis-HIF-1α axis, establishing a pathogenic positive feedback loop in RA

Beyond cytokines, other serum components significantly influence macrophage metabolism in RA. Elevated levels of glycolytic metabolites, such as lactate and succinate, stabilize HIF-1α in macrophages, amplifying pro-inflammatory cytokine production [17, 31]. Similarly, increased amino acid metabolites like quinolinic acid (QUIN) have been demonstrated to directly induce glycolytic activity [32]. Certain metal ions contribute to metabolic dysregulation, with extracellular zinc enhances IL-1 secretion via mTORC1-mediated glycolysis [33]. Additionally, the endogenous ligand Syntenin-1, enriched in RA serum, reprograms naïve macrophages into a glycolytic phenotype, further amplifying metabolic and inflammatory networks [34]. Cell-cell crosstalk represents another critical layer of metabolic regulation. Spatial transcriptomics has revealed close proximity between fibroblasts and macrophages in the synovial lining of relapsing RA patients, a feature absent in remission cases [35]. This physical interaction facilitates metabolic cross-talk that prolongs macrophage survival, collectively sustaining chronic inflammation [36].

We observed expression of HK2 correlated with IL-1β and HK2 inhibition downregulated the RA serum induced IL-1β. Glycolytic enzymes like HK2 can translocate to nuclei or mitochondria, performing non-metabolic functions in survival, growth, and cytokine regulation [37]. As a key metabolic regulator, mitochondrial-bound HK2 inhibits release of pro-apoptotic proteins, promoting cell survival [38]. Beyond our findings in macrophages, HK2 is elevated in RA FLS versus OA FLS [6], and HK2Col1 mice show attenuated arthritis activity and bone erosion [39], positioning HK2 as a critical link between metabolic reprogramming and synovitis in RA.

Accumulating evidence supports hypoxia and HIF signaling in regulating several essential pathophysiological characteristics of RA, including synovial inflammation, angiogenesis, and cartilage destruction [40]. Induction of aerobic glycolysis through an Akt-mTOR-HIF-1α pathway represents the metabolic basis of trained immunity [41]. Moreover, recent studies have demonstrated that glucose metabolism also affected HIF-1α [42]. We found that inhibition of glycolysis can affect the level of HIF-1α induced by RA serum, which in turn affects the expression of IL-1β. Metabolic enzymes PKM2 has been found to stabilize HIF-1α promoting M1 macrophage differentiation [43]. Beyond the HIF-dependent regulation of IL-1β expression found in our study, glycolytic flux can also modulate inflammation through post-translational modification of inflammatory components. For instance, accumulation of methylglyoxal (MGO), an intermediate metabolite of glycolysis, has been shown to covalently modify and inactivate NOD-like receptor thermal protein domain associated protein 3 (NLRP3) [44], illustrating additional complexity in how glycolytic reprogramming shapes macrophage inflammatory responses.

Integrated analysis of spatial transcriptomics and single-cell RNA sequencing revealed that the IL-1β response signature colocalizes with tissue macrophages and lining FLS in the synovial lining compartment [45]. The IL-1β driving this response may originate from either resident macrophages adopting an inflammatory phenotype or infiltrating activated monocytes, implicating these cells as key contributors to FLS activation. Mechanistically, IL-1β is a well-established inducer of matrix metalloproteinases (MMPs), which play a critical role in joint destruction in RA [46]. Spatial multi-omics further demonstrate that IL-1 pathway downregulation in rituximab responders correlates with clinical efficacy, implicating IL-1 signaling modulation in therapeutic response [47]. Together, these findings highlight macrophages as a key source of IL-1β in RA, driving FLS activation and disease progression, and underscore the potential of targeting this axis for treatment.

While our research sheds light on the glycolytic reprogramming of macrophages induced by RA serum and its potential mechanisms, several limitations should be noted. First, although our data demonstrate that blocking TNF-α or IL-1β in serum significantly inhibits macrophage glycolysis, cytokines may not be the sole regulators of this glycolytic reprogramming. Further experimental validation is needed to identify additional contributing factors. Second, further in vivo experiments could provide stronger evidence for the glycolysis-HIF-1α axis and potential therapeutic strategies targeting this pathway.

In summary, RA serum induce glycolytic reprogramming in macrophages, which further enhances IL-1β through HIF-1α, suggesting that targeting the glycolysis-HIF-1α axis may be a potential therapeutic approach for RA.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 (771.4KB, docx)
Supplementary Material 2 (1.1MB, docx)

Acknowledgements

We thank all the members of the National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID) for helpful support and appreciate for the participation of all the patients and healthy volunteers in this study.

Author contributions

YY.F. conceptualized and designed the project and supervised the project. YM.J. and RL.L. acquired the data, performed the data analysis, and drafted the manuscript. LF.H. performed transcriptome analysis. XY.W. reviewed the manuscript and provided valuable input. LD.Z., HX.Y. and X.Y. participated in the sample collection.

Funding

This work was supported by Beijing Natural Science Fundation (7242103), the Natural Science Foundation of Hunan Province(no.2024JJ759), the National Natural Science Foundation of China (82572065), the National High-Level Hospital Clinical Research Funding (2022-PUMCH-C-039, 2022-PUMCH-B-013); Chinese Academy of Medical Science Innovation Fund (CIFMS 2023-I2M-C & T-B-006).

Data availability

Data from RNA sequencing have been deposited in National Genomics Data Center (NGDC) and are accessible through the GSA-human Series accession number [ [HRA010531](https:/ngdc.cncb.ac.cn/gsa-human/submit/hra/subHRA015074/detail) ]. The rest of the data generated during this study is available within the article or its supplementary materials.

Declarations

Ethics approval and consent to participate

The study was approved by the institutional review board of PUMCH (K23C2052), and written informed consent was obtained from all subjects in accordance with the Declaration of Helsinki.

Consent for publication

The manuscript is approved by all authors for publication.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Yimeng Jia and Rongli Li contributed equally to this work.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1 (771.4KB, docx)
Supplementary Material 2 (1.1MB, docx)

Data Availability Statement

Data from RNA sequencing have been deposited in National Genomics Data Center (NGDC) and are accessible through the GSA-human Series accession number [ [HRA010531](https:/ngdc.cncb.ac.cn/gsa-human/submit/hra/subHRA015074/detail) ]. The rest of the data generated during this study is available within the article or its supplementary materials.

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