Aging-associated increase of GATA4 levels in articular cartilage is linked to impaired regenerative capacity of chondrocytes and osteoarthritis

  1. Meagan J Makarczyk
  2. Yiqian Zhang
  3. Alyssa Aguglia
  4. Olivia Bartholomew
  5. Sophie Hines
  6. Kate Li
  7. Suyash Sinkar
  8. Silvia Liu
  9. Craig Duvall
  10. Hang Lin  Is a corresponding author
  1. Department of Orthopaedic Surgery, University of Pittsburgh School of Medicine, United States
  2. Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, United States
  3. Xiangya Hospital Central South University, China
  4. Department of Biological Sciences, University of Pittsburgh Kenneth P. Dietrich School of Arts & Sciences, United States
  5. Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, United States
  6. Organ Pathobiology and Therapeutics Institute, University of Pittsburgh School of Medicine, United States
  7. Department of Biomedical Engineering, Vanderbilt University, United States
  8. Bethel Family Musculoskeletal Research Center (BMRC), University of Pittsburgh School of Medicine, United States

eLife Assessment

This study presents an important finding on the role of GATA4 in aging- and OA-associated cartilage pathology. The conclusions are well supported by compelling in vitro and in vivo evidence. This work will be of broad interest to both cell biologists and orthopedic/skeletal health clinicians.

https://doi.org/10.7554/eLife.106224.4.sa0

Abstract

Although the causal association between aging and osteoarthritis (OA) has been documented, our understanding of the underlying mechanism remains incomplete. To define the regulatory molecules governing chondrocyte aging, we performed transcriptomic analysis of young and old human chondrocytes from healthy donors. The data predicted that GATA-binding protein 4 (GATA4) may play a key role in mediating the difference between young and old chondrocytes. Results from immunostaining and western blot showed significantly higher GATA4 levels in old human or mouse chondrocytes when compared to young cells. Moreover, overexpressing GATA4 in young chondrocytes remarkably reduced their cartilage-forming capacity in vitro and induced the upregulation of proinflammatory cytokines. Conversely, suppressing GATA4 expression in old chondrocytes, through either siRNA or a small-molecule inhibitor NSC140905, increased the production of aggrecan and collagen type II, and also decreased levels of matrix-degrading enzymes. In OA mice induced by surgical destabilization of the medial meniscus, intra-articular injection of lentiviral vectors carrying mouse Gata4 resulted in a higher OA severity, synovial inflammation, and pain level when compared to control vectors. Mechanistically, we found that overexpressing GATA4 significantly increased the phosphorylation of SMAD1/5. Our work demonstrates that the aging-associated increase of GATA4 in chondrocytes plays a vital role in OA progression, which may also serve as a target to reduce OA in the older population.

Introduction

Aging is an inevitable phenomenon resulting in limited functionality, loss of structural integrity, and inability to effectively resist injury and disease (Xiong et al., 2022). Osteoarthritis (OA), the world’s most common form of degenerative disease, has been closely associated with the advancement of age (Rahmati et al., 2017). Specifically, OA is estimated to affect 32.5 million Americans, with most cases occurring in adults over the age of 45 (Makarczyk et al., 2021). In fact, 1 in 3 people over the age of 65 are suffering from OA (Hawker and King, 2022). There are many contributors linked to the onset and progression of aging, such as organelle dysfunction and telomere shortening (Xiong et al., 2022), but the molecular mechanism underlying age-related OA has not been fully understood. Prior studies have demonstrated the role of DNA damage on chondrocyte aging due to oxidative stresses, resulting in an aged phenotype (Copp et al., 2022; Loeser et al., 2016). Aged cells can also undergo a state similar to permanent cell cycle arrest known as cellular senescence, which leads to a low-grade state of chronic inflammation and contributes to OA onset and progression in aged individuals (Loeser et al., 2016; Ji et al., 2022; Franceschi et al., 2000).

OA is now considered a whole joint disease, but cartilage degradation still represents the central feature (Makarczyk et al., 2021). The physiological role of articular cartilage is to support and protect the bones of diarthrodial joints through absorbing mechanical loads and facilitating frictionless movements. The extracellular matrix (ECM) of the cartilage is composed primarily of collagen type II and glycosaminoglycans (GAGs), and the constant breakdown and rebuilding of ECM components in the cartilage is common in healthy adults (Makarczyk et al., 2021; Makarczyk, 2023). Many growth factors contribute to the chondro-supportive environment in the knee joint. Particularly, transforming growth factor β (TGFβ) plays a key role in maintaining chondrocytes and replenishing ECM loss. However, during OA, TGFβ can induce catabolic processes in chondrocytes, resulting in matrix stiffening, osteophytes, and chondrocyte hypertrophy (Shen et al., 2014; Roman-Blas et al., 2007; van der Kraan, 2017). Furthermore, as we age, the regenerative response of chondrocytes begins to decline (Rahmati et al., 2017). The whole joint nature of OA and the limited regenerative capacity of chondrocytes have contributed to the difficulty in developing disease-modifying osteoarthritis drugs (DMOADs). To date, no DMOADs have reached FDA approval (Makarczyk et al., 2021).

Currently, OA-associated changes in chondrocytes have been widely examined, which have significantly enhanced our understanding of this disease and promoted the development of potential treatments. However, OA is a combined consequence of different physiological stressors, including aging, injuries, obesity, etc. Therefore, aged chondrocytes in healthy humans without OA do not necessarily exhibit all the features of OA chondrocytes. In this study, to understand key regulators that contribute to an ‘aged’ state in chondrocytes prior to OA onset, we first compared the transcriptome of young and old human chondrocytes isolated from healthy donors without joint diseases and employed unbiased analysis to define the key regulatory molecules that mediate chondrocyte aging. Assessment of the chondrocyte genome demonstrated the upregulation of several factors in aged chondrocytes, and transcription factor GATA-binding protein 4 (GATA4) specifically drew our attention since it is associated with DNA damage and cellular senescence (Copp et al., 2022; Kang et al., 2015). Mechanistically, upregulation of GATA4 was shown to increase nuclear factor κB (NFκB) pathway activation (Qiao et al., 2019; Jia et al., 2018). NFκB is thought to amplify and potentially propagate cellular senescence during the aging process through the senescence-associated secretory phenotype (SASP), which could contribute to a low-grade state of chronic inflammation (Rahman et al., 2022). Furthermore, the upregulation of GATA4 in OA chondrocytes was also reported (Kang et al., 2019; Schlett et al., 2023). We thus hypothesized that the increased GATA4 level contributes to chondrocyte aging and accelerated OA progression upon injuries. We first tested the hypothesis by increasing or suppressing GATA4 expression in healthy chondrocytes and examining their cartilage-forming capacity. When GATA4 was overexpressed, we found that there were alterations to the TGFβ signaling pathway and activation of the NFκB signaling pathway. We also assessed the role of GATA4 in vivo by injecting lentiviral vectors carrying control or mouse Gata4 genes into the knee joints of OA mice induced by surgically created destabilization of the medial meniscus (DMM). Lastly, a mechanistic study was conducted to explore how GATA4 impacts chondrocyte phenotypes and functions.

Results

GATA4 is predicted to regulate chondrocyte aging

To limit the influence of in vitro expansion on cell phenotype, P0 human chondrocytes were used for RNA sequencing (RNA-seq, Figure 1A). The volcano plot showed that 303 genes are upregulated and 163 genes are downregulated in aged chondrocytes compared to young cells (Figure 1B). The top 50 most changed genes are listed in Figure 1C. Interestingly, the OA pathway was identified to be activated in old chondrocytes (Figure 1E).

Figure 1 with 3 supplements see all
GATA4 is predicted to regulate chondrocyte aging.

(A) Healthy chondrocytes were isolated from knee joint cartilage from young and old donors without osteoarthritis (assessed by experienced surgeons). P0 cells were used for RNA sequencing analysis. (B) Volcano plot demonstrating 303 upregulated and 163 downregulated genes in old chondrocytes when compared to young cells. (C) Top 50 genes that are significantly differently expressed in young and old chondrocytes. (D) Activation z-score of top 10 transcription regulators that are activated (positive) or inhibited (negative) in aged versus young chondrocytes. A comprehensive list of gene names can be found in Appendix 1—table 3. (E) Ingenuity Pathway Analysis (IPA) of young versus old cells. The gray bars indicate that no activity pattern is identified in IPA despite the highly significant association of the genes within the pathway. Orange, positive z-score; white, zero z-score. OBs = osteoblasts; OCs = osteoclasts. (F) GATA4 IHC of healthy human cartilage tissue from young and aged donors. Bar = 50 µm. (G) Relative protein levels of GATA4 in P1 chondrocytes from individual human donors were analyzed by western blot.

Through Ingenuity Pathway Analysis (IPA) Upstream Regulator Analysis, transcriptional regulators that may mediate the difference between young and old cells were predicted, and the top 20 of them are shown in Figure 1D. Given that GATA4 was previously shown to regulate chondrocyte senescence (Kang et al., 2015) and be involved in the activation of NFκB pathway in tissues like the nucleus pulposus (Wang et al., 2022) and synovium (Shi et al., 2021; Chen et al., 2022), it was selected for further investigation in this study. Initial data analysis predicted that GATA4 was upregulated in aged chondrocytes compared to young donors (Figure 1D). Immunohistochemistry (IHC) results indicated that GATA4 was more abundant in articular cartilage harvested from aged individuals (Figure 1F; Figure 1—figure supplement 1). Analyzing knee joints collected from young and old mice also demonstrated that GATA4 levels were higher in aged cartilage tissues compared to young (Figure 1—figure supplement 2). To further confirm the findings, western blot was used to examine GATA4 levels in isolated chondrocytes, and the results indicated that aging correlates with the increase of GATA4 in chondrocytes (Figure 1G). Lastly, we were interested in assessing whether or not this upregulation of GATA4 in aged individuals was associated with DNA damage. Therefore, we employed the doxorubicin, which is known to cause DNA damage (Qiao et al., 2020) and assessed the expression of DNA damage marker, phosphorylated histone variant H2AX (γH2AX) (Prabhu et al., 2024), senescence associated marker, P21, GATA4, and protein subunit of the NFκB transcription factor complex, phosphorylated P65 (Zhao et al., 2020). Results shown in Figure 1—figure supplement 3 indicated increased protein content of γH2AX, P21, GATA4, and pP65 (Figure 1—figure supplement 3). While these findings indicate that DNA damage might be associated with the increase in GATA4, further assessments should be conducted.

Overexpressing GATA4 impairs the hyaline cartilage formation capacity of young chondrocytes

To examine the functions of GATA4 in chondrocytes, we first overexpressed it in healthy young human chondrocytes (Figure 2A). Real-time quantitative PCR (RT-qPCR), immunostaining, and western blot confirmed the significantly increased GATA4 expression after infection, which did not impact the expression levels of collagen type II (COLII)-α1 (COL2A1) and aggrecan (ACAN), but significantly upregulated the expression of collagen type X (COLX)-α1 (COL10A1) and Indian hedgehog (IHH), two representative chondrocytic hypertrophy markers (Figure 2—figure supplement 1). We then examined the cartilage formation capacity of cells by culturing cells in chondrogenic medium for 7 days. IHC, RT-qPCR, and western blot demonstrated the continuous overexpression of GATA4 in newly formed tissues (Figure 2B–D). Interestingly, significantly reduced GAG and COLII production was found in the overexpression GATA4 group (GATA4 group) compared to the GFP control group (Figure 2E–G). Similar results were observed in the study testing chondrocytes from individual donors (Figure 2—figure supplement 2). Interestingly, GATA4 overexpression did not impact the expression of COL10A1 and IHH in the cartilage pellets (Figure 2G). Additionally, tissues from the GATA4 group secreted more proinflammatory cytokines, including IL6, IL8, tumor necrosis factor-alpha (TNFA), and chemokine CCL2 (Figure 2H, I), as well as enzymes that can break down cartilage, including matrix metalloproteinases (MMP)1, 2, 12, and a disintegrin and metalloproteinases (ADAMTS) 5 (Figure 2J, K). Although the expression levels of the MMP13 gene decreased in the GATA4 group, the protein levels showed no difference between the two groups (Figure 2—figure supplement 3).

Figure 2 with 3 supplements see all
Overexpressing GATA4 impairs the hyaline cartilage formation capacity of young chondrocytes.

(A) Timeline depicting the study. (B) IHC to assess GATA4 protein levels in young cells overexpressing GFP control or GATA4. Scale bar = 50 µm. (C) RT-qPCR analysis of GATA4 gene expression in two groups. (D) Western blot to measure GATA4 protein levels. (E) Safranin O staining and (F) collagen type II (COLII) IHC to examine the production of cartilage matrix. Scale bar = 50 µm. (G) RT-qPCR analysis of gene expression of cartilage matrix proteins aggrecan (ACAN) and collagen type II-α1 (COL2A1) and hypertrophy markers collagen type X-α1 (COL10A1) and Indian hedgehog (IHH). (H) RT-qPCR analysis of gene expression of proinflammatory cytokines, including interleukin (IL)6, IL8, and tumor necrosis factor-alpha (TNFA) (n = 6). (I) Concentrations of IL6, IL8, and chemokine (C–C motif) ligand 2 (CCL2) in condition medium (n = 3). (J) RT-qPCR analysis of relative gene expression of matrix-degrading enzymes, including matrix metalloproteinases (MMP) 1, 2, 3, 12, and 13, and a disintegrin and metalloproteinase (ADAMTS) 4 and 5 (n = 6). (K) MMP1 concentration in condition medium (n = 3). Student’s two-tailed t-test with Welch’s correction for standard deviation and a p-value of 0.05 was used for all statistical analysis. Created with BioRender.com.

GATA4 overexpression activates SMAD1/5

Increased SMAD1/5 phosphorylation represents a key feature of aged chondrocytes (Vinuesa, 2021). We thus examined whether increased GATA4 levels are associated with SMAD1/5 activation (Figure 3A). In the experiment testing chondrocytes from individual donors (Figure 3B, D–G), overexpression of GATA4, even without the stimulation of TGFβ3, was sufficient to activate SMAD1/5, but not SMAD2/3. In addition, the group that was co-treated with GATA4 overexpression and TGFβ3 displayed the highest phosphorylated SMAD1/5 (pSMAD1/5) levels in all tested groups. Of note, activation of SMAD2/3 was not impacted by GATA levels. A similar trend was also observed in the study using pooled chondrocytes (Figure 3C).

GATA4 overexpression activates SMAD1/5.

(A) Schematic showing the experiment. Western blot to assess protein levels of phosphorylated SMAD1/5 (pSMAD1/5), phosphorylated SMAD2/3 (pSMAD2/3), and GATA4 in pellets derived from young (B) individual (Y1–3) or (C) pooled chondrocytes, which were infected with lentiviral vectors carrying GATA4 or control genes and then stimulated with (+) or without (−) TGFβ3 for 2 hr. Relative protein levels of (D) GATA4, (E) pSMAD1/5, and (F) pSMAD2/3 were semi-quantified using ImageJ (n = 3). (G) The ratio of pSMAD1/5 compared to pSMAD2/3 was also calculated. Statistics were conducted using one-way analysis of variance (ANOVA) with Dunnett’s post hoc analysis. Created with BioRender.com.

Suppressing GATA4 in old chondrocytes promotes ECM formation and lowers proinflammatory cytokines

We then tested the potential of suppressing GATA4 in reversing chondrocyte aging (Figure 4A). Several GATA4 siRNAs were tested to examine their capacity to suppress GATA4. Based on RT-qPCR results, siRNA2 was selected to be used in all following studies because it induced the lowest expression of GATA4 (Figure 4—figure supplement 1). GATA4 knockdown resulted in increased cartilage formation from old chondrocytes, which did not influence the expression of hypertrophy marker COL10A1 (Figure 4B–D). Moreover, although we did not see a difference between the scrambled control and GATA4 siRNA groups regarding the expression of IL6 and IL8, the protein level of IL8 was higher in the GATA4 group. Interestingly, the protein level of CCL2 was significantly decreased after GATA4 knockdown (Figure 4E, F). We also tested the expression levels of MMPs and ADAMTSs (Figure 4H–I). In general, suppressing GATA4 either decreased or caused no significant changes to the levels of these enzymes. In particular, MMP13 levels were reduced, in both gene and protein levels (in condition medium), after GATA4 knockdown. Mechanistically, GATA4 siRNA treatment also lowered the phosphorylation of SMAD1/5 and pP65 (Figure 4G).

Figure 4 with 2 supplements see all
Influence of GATA4 knockdown on in vitro cartilage formation of old chondrocytes.

(A) Schematic showing the study. (B) Safranin O staining and (C) COLII IHC to examine the production of cartilage matrix in the scrambled control or GATA4 siRNA group. Scale bar = 50 µm. (D) RT-qPCR analysis of relative gene expression of cartilage matrix proteins ACAN and COL2A1 and hypertrophy marker COL10A1 (n = 6). (E) RT-qPCR analysis of relative gene expression of proinflammatory cytokines IL6 and IL8 (n = 6). (F) Concentrations of IL6, IL8, and chemokine (CCL2) in condition medium (n = 3). (G) The relative protein levels of pSMAD1/5, pSMAD2/3, and phosphorylated p65 (pP65) in two groups. (H) RT-qPCR analysis of relative gene expression of matrix-degrading enzymes, including MMP1, 2, 3, 12, and 13, and ADAMTS 4 and 5 (n = 6). (I) MMP1, 2, and 13 concentrations in condition medium (n = 3). Student’s two-tailed t-test with Welch’s correction for standard deviation and a p-value of 0.05 was used for all statistical analysis. Created with BioRender.com.

In a separate study, we used a small-molecule GATA4 inhibitor NSC140905, which was shown to significantly promote cartilage formation from old chondrocytes and reduce the expression of proinflammatory cytokines (Figure 4—figure supplement 2). Taken together, suppressing GATA4 partially restored the capacity of old chondrocytes to create new cartilage.

Gata4 overexpression in the knee joints accelerates OA progression in mice

The physiological functions of GATA4 were further examined using a mouse model (Figure 5A). Specifically, lentiviral vectors carrying Gata4 or mCherry genes were injected into the knee joints of young mice. One week after the injection, DMM surgery was conducted to induce OA. Since we expected that Gata4 overexpression would accelerate OA progression, we harvested samples for analysis 6 weeks after DMM.

Figure 5 with 1 supplement see all
Gata4 overexpression in the knee joints accelerates OA progression in mice.

(A) Schematic of the study. Mice received one intra-articular injection of lentiviral vectors that carried mCherry or Gata4 gene 1 week before DMM surgery was performed. Knee joints were harvested 6 weeks post-surgery. Levels of Gata4 (B, C) and pP65 (D, E) were assessed with IHC (B, D), and the staining was semi-quantitated with ImageJ (C, E). Cartilage degradation was assessed with (F) Safranin O/fast green (FG) staining, and (G) OARSI score was calculated. (H) Knee hyperalgesia 6 weeks post-surgery. 507 g was the threshold baseline for non-surgery mice (dashed line). Student’s two-tailed t-test with Welch’s correction for standard deviation and a p-value of 0.05 was used for all statistical analysis. Created with BioRender. com.

Results from IHC indicated a successful Gata4 overexpression in hyaline cartilage even 6 weeks after injection (Figure 5B, C). Interestingly, mice overexpressing Gata4 in the knee joint resulted in the elevation of pP65 (Figure 5D, E), suggesting increased inflammation. Moreover, the mice in the Gata4 group displayed more severe OA and higher knee hyperalgesia than the control group, as revealed by a lower withdrawal threshold (Figure 5F–H). Interestingly, mice from the Gata4 group displayed higher synovial inflammation (Figure 5—figure supplement 1).

Discussion

The causal relationship between aging and OA has been documented, and understanding the molecular mechanisms is essential for the development of treatment methods. In this study, we discovered the critical roles of aging-associated increases in GATA4 levels. Specifically, overexpressing GATA4 in young chondrocytes impaired their capacity to form normal hyaline cartilage, while suppressing GATA4 in old chondrocytes restored their chondrogenic potential. We also demonstrated that GATA4 functions partially by promoting the activation of SMAD1/5. Our in vivo work further confirmed that high Gata4 expression accelerated OA progression in mice. Lastly, we defined a small-molecule GATA4 inhibitor that can partially restore the capacity of old chondrocytes to create healthy cartilage, representing a potential DMOAD for further validation in the future.

Given the recognized challenges in harvesting healthy cartilage tissues from donors without arthritis, there are limited reports investigating chondrocyte aging per se. The current findings include proliferation and post-expansion chondrogenic capacity reduction with aging (Barbero et al., 2004), increased MMP13 production in response to catabolic stimuli (Forsyth et al., 2005), and altered response to TGFβ (van der Kraan, 2017). One of our recent studies again demonstrated that aged chondrocytes displayed a reduced proliferation potential compared to young cells. Additionally, cartilage tissues generated by old chondrocytes contained more senescent cells than those from young cells (Shen et al., 2021). However, to the best of our knowledge, there were no publications describing the transcriptomic comparisons between young and old chondrocytes, which would be informative in defining targets to stop or reverse chondrocyte aging.

Through transcriptomic analysis, we were able to assess the expression of different genes and genetic pathways that occur as chondrocytes age. Of note, hypoxia-inducible factor 1α (HIF1α) was the most differentially expressed gene predicted to regulate chondrocyte aging. The connection between HIF1α and aging has been previously reported (Yeo, 2019). Furthermore, additional studies have investigated HIF1α in association with OA and assessed its use as a therapeutic target (Hu et al., 2020; Zeng et al., 2022). Therefore, we decided to focus on GATA4, which was less studied in chondrocytes but highly associated with cellular senescence, an aging hallmark. However, our selection did not dampen the importance of HIF1α and other molecules listed in Figure 1D in chondrocyte aging. They can be further studied in the future using the same strategy employed in the current work.

The GATA family consists of several proteins (GATA1–6) with different variations of DNA-binding domains composed of zinc finger structures (Wang et al., 2022). Particularly, GATA4, 5, and 6 are involved in the development of the mesoderm and endoderm tissues (Romano and Miccio, 2020), in which GATA4 has been detected in the development of structures such as the heart (Dobrzycki et al., 2020; Ang et al., 2016), pancreas (Villamayor et al., 2020), lung, and liver (Tremblay et al., 2018; Molkentin, 2000). In addition, GATA4 and GATA6 are the only members that are associated with aging (Jiao et al., 2021). Particularly, GATA4 is unique in that it regulates tissues in a context-dependent manner and adopts a multifaceted role in the body, contributing to other age-related diseases such as atherosclerosis (Mahmoud et al., 2019) and heart failure (Katanasaka et al., 2016).

Furthermore, GATA4 might be associated with metabolic regulation. A study conducted by Patankar et al. investigated how GATA4 regulates obesity. Specifically, they used intestine-specific Gata4 knockout mice to study diet-induced obesity, showing that the knockout mice were resistant to the high-fat diet, and that glucagon-like peptide-1 (GLP-1) release was increased. These findings indicated a decreased risk for the development of insulin resistance in knockout mice (Patankar et al., 2011). This work was taken a step further in a subsequent publication, in which the same team investigated the dietary lipid-dependent and -independent effects on the development of steatosis and fibrosis in Gata4 knockout mice. The results from this work suggested that the knockdown of Gata4 increases GLP-1 release, in turn suppressing the development of hepatic steatosis and fibrosis, ultimately blocking hepatic de novo lipogenesis (Patankar et al., 2012). These studies are especially interesting with the rise of GLP-1-based therapy for the treatment of OA (Meurot et al., 2022; Yang et al., 2025). Thus, the coupling of GATA4-related metabolic dysfunction and OA should be further investigated.

In 2015, GATA4 was first introduced as a senescence regulator in a study conducted by Kang et al., 2015. This work demonstrated the role of GATA4 in human fibroblasts and determined that the inhibition of autophagy caused GATA4 accumulation following DNA damage. They examined the presence of GATA4 in the human brain and found that there was an increase of GATA4 in the prefrontal cortex of aged human samples (Kang et al., 2015). Further studies have shown that GATA4 regulates angiogenesis and inflammation in fibroblast-like synoviocytes (FLSs) in rheumatoid arthritis, indicating that GATA4 is required for the inflammation induced by IL1β. This study also demonstrated that GATA4 binds to promoter regions on vascular endothelial growth factor (VEGF)-A and VEGFC to enhance transcription and regulate angiogenesis (Jia et al., 2018). In chondrocytes specifically, previous studies demonstrated that increased GATA4 levels are associated with chondrocyte senescence (Kang et al., 2019; Chung et al., 2023; Chung et al., 2020), an important change often observed in OA chondrocytes. Moreover, suppressing GATA4 with siRNA was shown to effectively abolish ionizing radiation-induced senescent phenotype in chondrocytes (Kang et al., 2019). Of note, all these studies relevant to chondrocytes were conducted in vitro. Herein, we, for the first time, demonstrate the role of GATA4 in regulating chondrocyte aging.

A theory of chondrocyte aging proposed by van der Kramm suggests that alterations to the TGFβ pathway induce chondrocyte hypertrophy and result in articular cartilage that is prone to OA development (van der Kraan, 2017). While investigating the function of GATA4 in chondrocytes, we assessed how its levels contribute to TGFβ alterations in chondrocytes and found that GATA4 levels negatively correlated with the anabolic potential of chondrocytes (Figures 2 and 4). Our study indicated that there was an observed decrease in chondrogenesis and an increase in hypertrophy-related genes following GATA4 overexpression (Figure 2G). To maintain healthy cartilage homeostasis, numerous pathways are involved. In particular, TGFβ is a crucial cytokine necessary for cartilage homeostasis during OA (Thielen et al., 2023; van der Kraan et al., 2012), and aged chondrocytes respond differently to TGFβ compared to their young counterparts (Baugé et al., 2014).

Mechanistically, in the TGFβ pathway, TGFβ binds to the heterotetrameric receptor complex, which can be grouped into three receptor types (type I, type II, and type III). When TGFβ binds to its corresponding receptor, the activin-receptor-like kinases (ALKs) are activated (van Caam et al., 2017). Typically, the anabolic binding of TGFβ to ALK4/5 results in the phosphorylation of SMAD2/3, protecting chondrocytes from hypertrophy (Thielen et al., 2023). However, there can also be catabolic effects associated with the expression of SMAD1/5, typically expressed when TGFβ binds to ALK1/2/3/6 (Thielen et al., 2023; van Caam et al., 2017). The phosphorylation of SMAD1/5 results in the promotion of ECM degrading proteins such as MMP13 (Vinuesa, 2021; Thielen et al., 2023). As mentioned previously, research has demonstrated that aged chondrocytes respond differently to TGFβ compared to young chondrocytes (Baugé et al., 2014; Wiegertjes et al., 2021). Chondrocyte aging has been linked to the increase of pSMAD1/5 signaling (Vinuesa, 2021). These previous studies and literature review inspired us to explore the potential association between GATA4 levels and the activation of SMAD1/5.

Our results found that GATA4 resulted in the phosphorylation of SMAD1/5 even without TGFβ stimulation, which however did not alter the phosphorylation of SMAD2/3. Although there are no current publications specifying the complex relationship of GATA4 and SMAD1/5 in chondrocytes, a prior study reported that GATA4 was regulated by SMAD1/5. Specifically, SMAD1/5 and GATA4 can bind together to promote IL6 expression in macrophages (Lee et al., 2010). In this study, it was shown that GATA4 was necessary for bone morphogenic protein 6 (BMP 6) mediated IL6 induction, in which there are multiple GATA binding domains on the IL6 promoter. This work further showed that GATA4 interacts with SMAD 2, 3, and 4 (Lee et al., 2010). Studies have suggested that BMP pathways and GATA4 work synergistically to regulate SMAD signaling (Güemes et al., 2014). This information indicates that the involvement of GATA4 in the TGFβ signaling pathway is complex, and further studies should be conducted to better assess this relationship.

Additionally, a common hallmark of chondrocyte aging is the alternation of ECM, including composition change (Rahmati et al., 2017) and stiffening (Iijima et al., 2023). The mechanical integrity of ECM can directly affect chondrocyte phenotype and proliferation and contribute to OA (Grogan and D’Lima, 2010). For example, aging induces increased lysyl oxidase-mediated collagen cross-linking and non-enzymatic advanced glycation end-products (AGEs) begin to accumulate, which stiffens the ECM collagen fibrils (Pokharna et al., 1995; Fan et al., 2022). On the other hand, aging is also associated with an increase in aggrecan fragmentation and a decrease in the GAG length and packing density (Lee et al., 2013), which leads to decreased osmotic pressure and compressive resistance. It was found that the indentation modulus of murine cartilage decreases with age, likely associated with the reduced aggrecan content, integrity, and osmotic pressure-endowed pre-tension within collagen fibrils (Fan et al., 2022). Meanwhile, earlier studies also indicate a softening effect of aging on cartilage tissue modulus (Kempson, 1982; Peters et al., 2018). To this day, there is still a paucity of knowledge on the mechanism by which aging impacts the ECM and its reciprocal interplay with resident cells.

Investigating ECM alterations in conjunction with cellular senescence and TGFβ signaling could provide further insights into cartilage aging. A recent study by Fu et al., 2024 associated matrix stiffening with the promotion of chondrocyte senescence. Furthermore, matrix stiffening has been associated with modulating the TGFβ signaling pathway (Vincent, 2013; Massagué, 2012; Allen et al., 2012). Future studies should investigate the potential of matrix stiffening and the effect of GATA4 on pericellular matrix proteins such as decorin (Chery et al., 2021; Li et al., 2020), biglycan, collagen VI and XV, as these proteins assist with the regulation of biochemical interactions and assist with the maintenance of the chondrocyte microenvironment (Chu et al., 2017). Herein, the TGFβ signaling pathway can further alter the extracellular microenvironment (Allen et al., 2012), which could promote cellular senescence and subsequently NFκB pathway activation. Further investigation of ECM alterations and aging could elucidate the molecular events governing these changes, providing key insights on the interplay between chondrocytes and their environment in the context of aging.

While the TGFβ pathway is closely associated with cartilage matrix remodeling, we also found increases in the levels of multiple proinflammatory cytokines after GATA4 overexpression. We investigated the NFκB pathway since it is also activated in aged tissues (Yao et al., 2023; Adler et al., 2007). During the aging process, NFκB is thought to amplify and potentially propagate cellular senescence through the SASP (Rahman et al., 2022). A study by Qiao et al., 2019 indicated that GATA4 regulates NFκB in dental pulp cells and fibroblasts (Jia et al., 2018). Specifically, using siRNAs, they determined that the knockdown of GATA4 decreased p65 production induced by lipopolysaccharide (LPS) (Qiao et al., 2019). Other studies have investigated the role of GATA4 in the synovium and the progression of the disease state of rheumatoid arthritis and OA. Jia et al., 2018 showed that the knockdown of GATA4 attenuated synovial inflammation and joint damage in a collagenase-induced arthritis mouse model. More recently, a study conducted by Chen et al., 2022 investigated the roles of GATA4 in FLSs and determined that GATA4 induced cellular senescence in FLSs in OA progression. Our study also discovered that the siRNA knockdown of GATA4 decreased the phosphorylation of p65 in aged chondrocytes (Figure 4). However, we also noticed that MMP13 expression levels decreased in both GATA4 overexpression and knockdown experiments. It should be noted that MMP13 is constitutively produced in human chondrocytes but is only activated under pathological conditions. Given that MMP13 is regulated by different transcriptional factors and cytokines, as well as RNAs (Vinuesa, 2021), its associations with GATA4 require further investigation in the future. Collectively, these findings further indicate that GATA4 might regulate aging partially through TGFβ and NFκB pathways.

Our current study has not fully explored why aging promotes GATA4 expression. The study from Kang et al., 2015 indicated that DNA damage contributed to GATA4 accumulation. It is known that DNA damage response (DDR) is regulated by ataxia telangiectasia mutated (ATM) and ataxia telangiectasia and Rad3-related (ATR) signaling (Kang et al., 2015; Maréchal and Zou, 2013; Menolfi and Zha, 2020). The activation of these signaling pathways inhibits autophagy-related protein p62 (Wang et al., 2016). In addition, Copp et al., 2022 reported increased DNA damage in old chondrocytes. These studies implied that DNA damage may be a reason for GATA4 upregulation. Our preliminary data and prior work from Kang et al., 2015 support this possibility. Specifically, a DNA damage-inducing agent, doxorubicin, promoted the upregulation of GATA4 in chondrocytes (Figure 1—figure supplement 3). To further link DNA damage to GATA4 accumulation, a study by Chung et al. used Tributyltin (TBT), a well-known endocrine-disrupting chemical, to induce DNA damage in articular chondrocytes. After 24 hr of TBT treatment, there was a significant increase in GATA4 expression and expression of senescence markers (Chung et al., 2023). The study by Kang et al., 2015 demonstrated that the suppression of p62 following DNA damage leads to GATA4 accumulation due to the lack of autophagy. DNA damage is known to increase with age (Yousefzadeh et al., 2021). Therefore, we believe that DNA damage due to aging is a key driver of the upregulation of GATA4 in old chondrocytes.

In conclusion, we have determined that GATA4 is increased in aged chondrocytes compared to young in both humans and mice, which may be induced by increased DNA damage observed in aged cells. We also demonstrated that GATA4 overexpression impaired the quality and quantity of cartilage created by chondrocytes and accelerated OA progression in mice. Conversely, suppressing GATA4 with siRNA or small-molecule inhibitors partially restores the capacity of old chondrocytes to form cartilage. Additionally, our study found that GATA4 can activate SMAD1/5 and change chondrocyte response to TGFβ. Overall, our study indicated that GATA4 could be a contributor to OA onset and progression in aged individuals, which can also serve as a potential target to prevent aging-associated OA.

There are some limitations of this study that can be further addressed in future studies. First, this study has allowed us to examine the potential mechanisms of GATA4 in chondrocyte aging. Although we found that GATA4 was generally increased with aging, some young donors also exhibited increased levels of GATA4, which may be associated with increased DNA damage, as discussed above, or other stressors. Therefore, GATA4 should be used together in conjunction with other aging biomarkers, such as epigenetic clock (Sarkar et al., 2023) to precisely define chondrocyte aging. Future work should examine biological versus chronological aging and epigenetic clock-based assessments to explain the variabilities in GATA4 expression among donors. Second, the TGFβ signaling pathway is complex, and there are multiple studies that have associated it with GATA4. However, the relationship between GATA4 overexpression and SAMD1/5 activation should be further investigated to elucidate specific signaling mechanisms. Third, during our in vivo work, the intra-articular injection of GATA4 lentivirus was not chondrocyte-specific. Therefore, the injection also allowed for other cell types to overexpress GATA4. Future work should be conducted using transgenic mouse lines for cartilage-specific inducible overexpression or depletion of Gata4 to further investigate the role of GATA4 in chondrocytes. Furthermore, studies using GATA4 knockdown do not demonstrate a complete reversal of aging in chondrocytes, and additional in vivo assessment needs to be conducted to verify whether GATA4 could be a therapeutic target for chondrocyte aging. In particular, our in vitro study demonstrated the potential of using small-molecule GATA4 to enhance the quality of cartilage created by old chondrocytes. We can validate the findings in vivo, as well as develop other GATA4 inhibitors. Lastly, our work indicates that GATA4 has a role in chondrocyte aging, but that does not negate the other aging factors and pathways. Combining current findings and investigating the prevalence of GATA4 in association with other aging molecules will further contribute to our understanding of the role of GATA4 in aging and possible OA onset.

Materials and methods

Cell isolation and expansion

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Healthy human knee cartilage tissues were harvested from arthritis-free donors through an established protocol with the National Disease Research Interchange (NDRI). This study was approved by the University of Pittsburgh Committee for Oversight of Research and Clinical Training Involving Decedents. Cartilage was diced into ~1 mm3 pieces with a scalpel and incubated with a dissociation medium that was composed of high glucose Dulbecco’s Modified Eagle Medium (DMEM, Gibco/Thermo Fisher Scientific, Waltham, MA, United States), 2% Antibiotics-Antimycotics (Life Technologies, Carlsbad, CA, United States), and collagenase type II (1 mg/ml (wt/vol), Worthington Biochemical Corporation, Lakewood, NJ, United States). 10 ml medium was used for 1 g of cartilage, and the treatment lasted for 16 hr in a shaker at 37°C. The mixture was then passed through a 70-µm strainer to collect single chondrocytes. Isolated chondrocytes were seeded in tissue culture flasks at 1 × 104 cells/cm2 and maintained in growth medium (GM, DMEM containing 10% fetal bovine serum (Life Technologies) and 1% antibiotics–antimycotics). After cells were fully attached to the culture substrate, the medium was changed every 3 days until cells reached 70–80% confluency. Cells were detached with Trypsin/EDTA (Gibco/Thermo Fisher Scientific) and passaged.

Individual chondrocyte monolayer culture

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Chondrocytes isolated from healthy human cartilage were expanded to passage 1 (P1) and plated in tissue culture 6-well plates at P2, treated with GM, and cultured until cells reached 80% confluency. Media changes occurred every 2 days until cell collection. Appendix 1—table 1 lists the chondrocyte ages and genders used for different experiments.

Young and old chondrocyte pools

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Chondrocytes at passage 0 (P0) were pooled with three to four other young chondrocyte donors and grown in tissue culture flasks with GM at a cell seeding density of 1 × 106 cells per flask. Media was changed weekly. Once cells reached 80% confluency, cells were collected using Trypsin/EDTA. Some cells were frozen using Recovery Cell Culture Freezing Medium (Gibco/Thermo Fisher Scientific), and other cells were used for subsequent passaging. The same methods were used for the old (>45 years) chondrocyte pool. Appendix 1—table 1 lists the chondrocyte ages and genders used in each pool. Due to the extensive amount of work conducted using these pools, two separate chondrocyte pools were made.

RNA-seq and bioinformatics analysis

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The transcriptomic differences among three young and three old chondrocyte donors were assessed through RNA-seq. Individual chondrocyte cultures (P0) were lysed with the QIAzol reagent (QIAGEN, German Town, MD, United States), and RNA was isolated from the lysate using an RNA Easy Plus Universal Kit (QIAGEN). Extracted RNA was quantitated using the Qubit RNA BR Assay Kit (Thermo Fisher Scientific) followed by the RNA quality check using Fragment Analyzer (Agilent Technologies, Santa Clara, CA). For each sample, RNA libraries were prepared from 500 ng RNA using the KAPA mRNA HyperPrep Kit (Roche, Indianapolis, IN) according to the manufacturer’s protocol, followed by quality check using Fragment Analyzer (Agilent Technologies) and fluorescent quantification on the Infinite F Nano + (Tecan, Männedorf, Switzerland). The libraries were normalized and pooled, and then sequenced using the NovaSeq6000 platform (Illumina, San Diego, CA) to an average of 50 M 100PE reads.

Quality control was first applied to raw RNA-seq reads by the tool FastQC. Low-quality reads and adapter sequences were filtered out by the Trimmomatic tool. Surviving reads were then aligned to the human reference genome hg38 using the STAR aligner, and gene counts were quantified. Differential expression analysis was performed based on gene counts by the R package ‘DESeq2’ and DEGs were selected by adjusted p-value ≤0.05 and fold change ≥1.5. These DEGs were then applied to IPA to detect enriched pathways. This software employs databases of prebuilt pathways with known genes summarized from previous studies, checks the overlap between the DEG list and known pathways, and performs statistical tests to determine the enrichment. Significant pathways were defined by p-value ≤0.05. Statistically stringently, FDR = 5% cutoff should be applied to control the false discovery rate. To encourage more gene candidates, this study went by p-value ≤0.05 and fold change ≥1.5 cutoff. All the tools were run by default parameter settings.

IHC to examine the GATA4 levels in native cartilage tissues

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Human cartilage tissues were fixed in 10% buffered formalin (Fisher Chemical, Fair Lawn, NJ) at 4°C overnight and then subjected to a graded ethanol dehydration series, starting from 20% ethanol and progressing to 100% ethanol. Subsequently, they were embedded in Paraplast X-tra (Leica Biosystems Inc Richmond, IL). The Paraplast-embedded samples were sectioned at a thickness of 6 µm using a rotary Leica microtome (Leica Microsystems Inc, Deerfield, IL, Model RM 2255). Young and old mouse knee joints were gifts from Dr. Ana Mario Cuervo’s lab at Albert Einstein College of Medicine, which otherwise were wastes. After the specimens were fixed and decalcified in a formic acid-based bone decalcifier (StatLab, Mckinney, TX, USA) for a period of 2 weeks, they were then embedded and sectioned as described above.

For IHC, the formalin-fixed paraffin-embedded sections first underwent antigen retrieval based on different antibodies. Slides were then blocked with 10% goat or horse serum (Abcam, Cambridge, MA) in phosphate-buffered saline (PBS, Thermo Fisher Scientific) for 1 hr, incubated at 4°C overnight with the primary antibody against GATA4, then incubated with a biotinylated anti-mouse/rabbit immunoglobulin G (IgG) secondary antibody for 1 hr, with signal detection via DAB substrate kit (Abcam). The Nikon Eclipse E800 upright microscope (Melivile, NY, United States) was used to image the stained sections. Antibody specifications can be found in Appendix 1—table 2.

Western blot to examine the GATA4 levels in human chondrocytes

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P1 young and old chondrocytes were used for individual chondrocyte analysis of GATA4. Cells were washed in pre-cooled PBS (Thermo Fisher Scientific) three times. Using the RIPA buffer (Sigma-Aldrich) supplemented with the protease and phosphatase Inhibitor Single-Use Cocktail (Gibco/Thermo Fisher Scientific) and a cell scraper, monolayer culture samples were collected. A pestle was used to homogenize pellets in the RIPA cocktail for pellet culture samples. The protein concentration of the supernatant was determined by the Pierce BCA Protein Assay Kit (Thermo Scientific). Proteins were fractioned electrophoretically on the NuPAGE 4–12%, Bis-Tris Mini Protein Gel (Gibco/Thermo Fisher Scientific) and then transferred to a polyvinylidene fluoride membrane using the iBlot Dry Blotting System (Invitrogen, Waltham, MA, United States). The membrane was blocked with 3% non-fat milk (Bio-Rad, Hercules, CA, USA), diluted with 1× Tris-buffered saline (TBS, Gibco/ Thermo Fisher Scientific) and 0.1% Tween 20 (Sigma-Aldrich) (TBST) at room temperature for 1.5 hr, washed, and incubated with the primary antibody at 4°C overnight on a rotating shaker. The membrane was washed seven times for 3 min with TBST buffer and incubated with horseradish peroxidase-linked secondary antibodies (GE Healthcare Life Sciences, Malborough, MA, United States) for 1.5 hr at room temperature. After being washed five times with TBST, the membrane was incubated in the chemiluminescence substrate SuperSignal West Dura Extended Duration Substrate (Thermo Fisher Scientific). Images were acquired using the ChemiDocTM Touch Imaging System (Bio-Rad). Images were quantified using ImageJ. Antibody information is included in Appendix 1—table 2.

Overexpression of GATA4 in young human chondrocytes

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P2 young, pooled chondrocytes or young, individual chondrocytes were transduced with the lentiviral vector containing GATA4 fused with dTomato gene or the control lentivirus carrying EGFP for 10 hr. After that, flasks were rinsed with PBS for two times and the medium was replaced by fresh GM. Both vectors were created and packed by VectorBuilder (>108 TU/ml, VectorBuilder, Chicago, IL, United States). To detect the number of cells transduced, cultures were imaged with an EVOS M5000 microscope (Thermo Fisher Scientific) after 72 hr of initial transduction. After transduction, western blot, RT-qPCR, and IHC were used to verify the stable expression of GATA4 in cells.

RNA isolation and RT-qPCR

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For pellet culture, samples were first rinsed with PBS twice and a pestle and electric pulverizer were used to crush pellets. Cells were homogenized in Qiazol (QIAGEN). Total RNA was isolated and purified using the RNAeasy Plus Universal Mini Kit (QIAGEN, Cat. No. 74104) according to the manufacturer’s protocol. The reverse transcription to the complementary DNA was accomplished using the SuperScript IV VILO Master Mix (Invitrogen). RT-qPCR was performed on a real-time PCR instrument (QuantStudio 3, Applied Biosystems, Foster City, CA, United States) using the SYBR Green Reaction Mix (Applied Biosystems) with custom primers ordered from Integrated DNA Technologies (IDT, Newark, NJ, United States). Relative gene expression levels were calculated through the 2−ΔΔCt method. Ribosomal protein L13A (RPL13A) was used as the housekeeping gene. Full names and abbreviations of genes and their corresponding proteins are listed in Appendix 1—table 3, and primer sequences are listed in Appendix 1—table 4.

Pellet culture and chondrogenesis of young human chondrocytes overexpressing GATA4

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Following the lentiviral transduction of the GATA4 gene in young, pooled chondrocytes, the cells were collected and formed into pellets at a cell seeding density of 3 × 105 cells per pellet. Pellets were treated with chondrogenic medium (CM, DMEM with 1% vol/vol Insulin-Transferrin-Selenium-Ethanolamine (ITS, Gibco/ Thermo Fisher Scientific), 1% antibiotic–antimycotics, 10–7 µM dexamethasone (Sigma-Aldrich), 40 µg/ml L-proline (Sigma-Aldrich), supplemented with 10 ng/ml transforming growth factor β3 (TGFβ3, Peprotech, Rocky Hill, NJ, United States), and 50 µg/ml ascorbic acid-2-phosphate (Sigma-Aldrich)). Medium was changed daily for 7 days. RT-qPCR, histology, IHC, and western blot were used to characterize the tissues.

Safranin O/Fast green staining

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Pellet samples were fixed in 10% buffered formalin (Fisher Chemical) for 2 hr at room temperature and then rinsed with PBS. Pellets then underwent serial dehydration in 30, 50, 70, 95, and 100% ethanol for 1 hr each. The 100% ethanol was refreshed once for an additional hour prior to sample clearing in xylene. Pellets were cleared in xylene (Fisher Chemical) for 2 hr. Pellets were then placed in Paraplast X-tra (Leica Biosystems Inc) overnight. The next day, pellets were embedded in Paraplast X-tra blocks and sectioned at a 6-μm thickness using a Leica microtome (Leica Microsystems Inc, Model RM 2255).

Slides were stained using Safranin O (0.5%, Catalog number: 50240, Sigma-Aldrich), in 1% acetic acid (Catalog number: A6283, Sigma-Aldrich), 0.005% fast green (0.05 g, Catalog number: 104022, Sigma-Aldrich) in 100 ml distilled water (Invitrogen) and counterstained with Hematoxylin QS solution (Catalog number: H3404, Vector Laboratories INC). Imaging was conducted using a Nikon Eclipse E800 upright microscope.

Luminex multiplex assays

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Upon 7 days of chondrogenesis, condition medium from pellets was collected and flash frozen in liquid nitrogen and immediately stored in –80°C. LUMINEX assays were accomplished using the Bio-Plex 200 system (Bio-Rad). Data collection and analysis were conducted using the Bio-Plex Manager 6.1 software as established in previous studies (Li et al., 2022). LUMINEX kit information can be found in Appendix 1—table 5 and the comprehensive list of proteins assessed in these kits can be found in Appendix 1—table 6.

Knockdown of GATA4 in old human chondrocytes

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The siRNA targeting human GATA4 (ON-TARGET plus Human GATA4 (2626) siRNA, J-008244-06-0005, Horizon Discovery Biosciences Limited, Cambridge, UK) was used in this study with a scrambled siRNA (ON-TARGET plus non-targeting siRNA #1, Catalog number: D-001810-01-05, Horizon Discovery Biosciences Limited) as the control. Old, pooled chondrocytes were transfected with the siRNA using Lipofectamine RNAiMAX reagent (Thermo Fisher Scientific). After 24 hr of incubation, the transfection medium (Opti-MEM Reduced Serum Medium, Thermo Fisher Scientific) was changed to GM. Transfected cells were collected after 48 hr for RT-qPCR to confirm the knockdown efficiency.

Pellet culture and chondrogenesis of old human chondrocytes with GATA4 knockdown

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Following the 48 hr transfection of scrambled control siRNA or siRNA targeting GATA4, cells were collected using Trypsin/EDTA (Thermo Fisher Scientific) and pellets were made at a cell density of 3 × 105 cells per pellet. Pellets were treated with CM supplemented with 10 ng/ml TGFβ3 and 50 µg/ml ascorbic acid-2-phosphate for 7 days. Upon day 7, pellets were collected for RT-qPCR, western blot, and IHC.

GATA4 small-molecule NSC140905

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GATA4 small-molecule, NSC140905, also known as HCA 42027 (Biosynth Ltd, Compton, United Kingdom), was reconstituted to 7.5 mM stock solution using UltraPure DNase/RNase-Free Distilled Water (Invitrogen) on a shaker at 37°C until completely dissolved. Old, pooled chondrocytes were pelleted and treated with CM supplemented with 10 ng/ml TGFβ3 and 50 µg/ml ascorbic acid-2-phosphate with 100 μM NSC140905 for 14 days. Pellets were collected for IHC, western blot, and RT-qPCR.

Animal model

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All animal experiments were approved by the University of Pittsburgh Institutional Animal Care and Use Committee (IACUC). Young (8 weeks) male C57BL/6 mice were purchased from Jackson Laboratory (Bar Harbor, ME, USA) and maintained in pathogen-free conditions, with no more than five mice per cage. Mice were provided ad libitum access to food and water, and a 12-hr light/dark cycle to simulate natural circadian rhythms. To minimize bias, mice were randomly assigned to either control or GATA4 groups, with eight mice in each group.

Intra-articular injection

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Intra-articular injections were administered to mice between 10–12 weeks of age under general anesthesia to safeguard the well-being of the animals and to minimize procedural discomfort. Under general anesthesia with 2% isoflurane in an oxygen mixture, the mice were placed in a supine position, and the right knee joint was positioned at a 90° flexion to facilitate accurate injection into the joint space. The injection site was meticulously identified medial to the patellar tendon. Using a 29-gauge needle, a volume of 10 µl of lentiviral particles encoding either GATA4 or a control vector (at a concentration >108 TU/ml, VectorBuilder) was precisely administered into the intra-articular space of the right knee. The precision of the injection was ensured by employing a consistent technique across all animals, thereby reducing variability in the delivery of the viral vectors.

DMM surgery

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One week after viral vector injection, DMM surgery was performed to induce the OA model on mice at 11–13 weeks of age (Glasson et al., 2007; Chen et al., 2017). Briefly, a medial parapatellar incision was made to expose the right knee joint, followed by a careful opening of the joint capsule. The anterior medial menisco-tibial ligament was identified and transected using microscissors. The joint capsule and skin were subsequently sutured with 6-0 silk thread. For experimental controls, a sham operation was performed in which the joint capsule was exposed as in the DMM surgery, but the medial menisco-tibial ligament was left intact.

Knee hyperalgesia

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We expected accelerated OA development after Gata4 overexpression. To observe these differences, we used 6 weeks as the time point at which control mice had begun displaying mild OA symptoms. Knee hyperalgesia was evaluated using a Pressure Application Measurement (PAM) device (Ugo Basile, Varese, Italy) (Barton et al., 2007; Leuchtweis et al., 2010). Mechanical stimuli were applied to the mouse’s knee joint to assess the degree of hyperalgesia based on the applied pressure and the mouse’s response. Six weeks after either DMM or sham surgery, the mice were carefully removed from their cages to ensure they remained calm and unstimulated. The mouse was held securely by its back to maintain a straight posture, with the right knee joint flexed at approximately 90°. The PAM device was placed on the index finger of the right hand of testers, which, along with the thumb, was used to apply pressure to the medial side of the knee joint, ensuring proper contact. Pressure was gradually applied at a constant rate of 30 g/s while monitoring the pressure curve displayed on the computer. The sensor was released immediately when the mouse exhibited a response to the applied stress, such as head movement, vocalization, or knee withdrawal. The pressure value displayed by the software, and the maximum pressures that mice can withstand were recorded. Two measurements were taken per knee, one on the medial side, and one on the lateral side; the average was calculated for accuracy.

Synovial inflammation score

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After 6 weeks, knee joints were collected and sectioned as described above. Histology staining and IHC were used to assess OA severity. Synovial inflammation score was evaluated according to a scoring protocol outlined in previous studies (Hayer et al., 2021), which relies on the hematoxylin and eosin-stained tissue sections.

Statistical analysis

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Each experiment was carried out with at least three biological replicates. Data are presented as mean ± standard deviation unless otherwise specified. Detailed information of sample size, pre‐processing, and statistical methods have been specified in each figure legend. Prism 10 (GraphPad, San Diego, CA) was used for statistical analysis. The significance level was set at 0.05 and indicated by *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

Appendix 1

Appendix 1—table 1
Information of chondrocyte donors.
RNA sequencing
AgeGenderAscension number
24FemaleP0
36FemaleP0
38FemaleP0
70FemaleP0
73FemaleP0
74FemaleP0
Western blot
AgeGenderAscension number
22MaleP0
26MaleP0
29MaleP0
69MaleP0
70MaleP0
73FemaleP0
Human cartilage tissue IHC
AgeGenderAscension number
24MaleP0
25FemaleP0
27FemaleP0
33MaleP0
67FemaleP0
76FemaleP0
78–1Female
78–2Male
Young chondrocyte pool
AgeGenderAscension number
22MaleP3
29MaleP3
38FemaleP3
42FemaleP3
P3
P3
Old chondrocyte pool #1
AgeGenderAscension number
66MaleP3
70MaleP3
73FemaleP3
Old chondrocyte pool #2
AgeGenderAscension number
66–1MaleP3
66–2MaleP3
70–1MaleP3
70–2MaleP3
Monolayer young individual chondrocytes
AgeGenderAscension number
29MaleP3
36FemaleP3
38FemaleP3
Pellet young individual chondrocytes
AgeGenderAscension number
21MaleP3
35MaleP3
38FemaleP3
Appendix 1—table 2
Antibodies used for immunofluorescence (IF), immunohistochemistry (IHC), or western blot (WB).
AntibodyOriginCat. No.SpeciesAssayDilution
Anti-Human Collagen Type IIMP BiomedicalsSKU 0863171MouseIHC1:200
Biotinylated Goat Anti-Rabbit IgGVector LaboratoriesPK-6101RabbitIHC1:50
Goat Anti-Rabbit IgG H&L (HRP)AbcamAb6721GoatWB1:5000
GAPDH (D16H11) XP Rabbit mAbCell Signaling Technology5174sRabbitWB1:2000
Smad1 (D59D7) XP Rabbit mAbCell Signaling Technology6944sRabbitWB1:500
Anti-GATA4 antibody (ab84593)- DiscontinuedAbcamab84593RabbitIHC/WB1:500
GATA-4 (D3A3M) Rabbit mAbCell Signaling Technology369366sRabbitIHC/WB1:1000
Phospho-Smad1/5 (Ser463/465) (41D10) Rabbit mAbCell Signaling Technology9516sRabbitWB1:500
Phospho-Smad2 (Ser465/467) (138D4) Rabbit mAbCell Signaling Technology3108sRabbitWB1:500
Smad2/3 (D7G7) XP Rabbit mAbCell Signaling Technology8685sRabbitWB1:500
Anti-NF-kB p65 (phospho S536) antibody [EP2294Y]Abcamab76302RabbitWB1:500
Anti-NF-kB p65 antibody [E379]Abcamab32536RabbitWB1:500
Anti-p21 antibody [EPR362] – BSA and Azide freeAbcamab218311RabbitWB1:1000
Phospho-Histone H2A.X (Ser139) (20E3) Rabbit mAbCell Signaling Technology9718sRabbitWB1:500
Appendix 1—table 3
Full names of genes shown in Figure 1.
Transcription regulator nameAcronym
Hypoxia-inducible factor 1-alphaHIF1A
GATA-binding protein 4GATA4
MAF bZIP transcription factor BMAFB
Homeobox D10HOXD10
CCAAT enhancer binding protein alphaCEBPA
Forkhead box L2FOXL2
Caudal type homeobox 2CDX2
Early Growth Response 1EGR1
Signal Transducer and Activator of Transcription 3STAT3
Paired Box 1PAX1
Sequestosome 1SQSTM1
Myocardin Related Transcription Factor BMRTFB
WW Domain Binding Protein 2WBP2
Scleraxis bHLH Transcription FactorSCX
Twist Family bHLH Transcription Factor 1TWIST1
Myocyte Enhancer Factor 2DMEF2D
Lysine Methyltransferase 2DKMT2D
Achaete-scute Family bHLH Transcription Factor 1ASCL1
Recombination Signal Binding Protein for Immunoglobulin kappa J regionRBPJ
SIX homeobox 1SIX1
FERM domain containing 3FRMPD3
CeruloplasminCP
SPARC-related modular calcium binding 2SMOC2
ATP-binding cassette subfamily A member 13ABCA13
Inositol 1,4,5-triphosphate receptor type 1ITPR1
NIM1 serine/threonine protein kinaseNIM1K
Fibroblast growth factor 13FGF13
Ankyrin repeat domain 12ANKRD12
GTP binding protein overexpressed in skeletal muscleGEM
ErythroferroneFAM132B
Pappalysin 1PAPPA
PPARG coactivator 1 alphaPPARGC1A
Synaptotagmin like 2SYTL2
Leucine rich repeat transmembrane neuronal 2LRRTM2
G-protein-coupled receptor class C group 5 member BGPRC5B
Polypeptide N-acetylgalactosaminyltransferase 15GALNT15
Growth associated protein 43GAP43
Fibroblast growth factor binding protein 1FGFBP1
ATRX chromatin remodelerATRX
Protocadherin gamma subfamily B, 2PCDHGB2
Calsyntenin 2CLSTN2
Fibroblast growth factor-binding protein 2FGFBP2
Desmocollin 2DSC2
TNF receptor superfamily member 21TNFRSF21
Kinesin family member 13BKIF13B
Plexin A2PLXNA2
Cysteine rich protein 2CRIP2
Cysteine rich protein 1CRIP1
KLF transcription factor 2KLF2
Serum/glucocorticoid regulated kinase 1SGK1
LIM zinc finger domain containing 2LIMS2
Long intergenic non-protein coding RNA 1133LINC01133
Adipogenesis regulatory factorADIRF
Ornithine decarboxylase 1ODC1
Kazrin, periplakin interacting proteinKAZN
Chondroitin polymerizing factorCHPF
RAB23, member RAS oncogene familyRAB23
Alkaline phosphatase, biomineralization associatedALPL
Signal transducer and activator of transcription 4STAT4
G-protein-coupled receptor 1GPR1
Spectrin alpha, non-erythrocytic 1SPTAN1
Very low-density lipoprotein receptorVLDLR
Fatty acid desaturase 3FADS3
Cancer susceptibility candidate 4CASC4
NAD(P)H quinone dehydrogenase 1NQO1
Pyrroline-5-carboxylate reductase 1PYCR1
ERBB receptor feedback inhibitor 1ERRFI1
NmrA-like family domain containing 1 pseudogeneLOC344887
Desumoylating isopeptidase 2DESI2
Basonuclin zinc finger protein 1BNC1
Appendix 1—table 4
Primers for qRT-PCR.
GeneForward primer (5′–3′)Reverse primer (5′–3′)
RPL13AGCCATCGTGGCTAAACAGGTAGTTGGTGTTCATCCGCTTGC
GATA4CAGTCTACGTGCCCACACCTCCCGCCTGGCTCCAT
ACANAGTCACACCTGAGCAGCATCAGTTCTCAAATTGCATGGGGTGTC
COL2A1GGATGGCTGCACGAAACATACCGGCAAGAAGCAGACCGGCCCTATG
COL10A1CCCTCTTGTTAGTGCCAACCAGATTCCAGTCCTTGGGTCA
IHHAACTCGCTGGCTATCTCGGTGCCCTCATAATGCAGGGACT
IL6ACTCACCTCTTCAGAACGAATTGCCATCTTTGGAAGGTTCAGGTTG
IL8TTTTGCCAAGGAGTGCTAAAGAAACCCTCTGCACCCAGTTTTC
TNFACCTCTCTCTAATCAGCCCTCTGGAGGACCTGGGAGTAGATGAG
MMP1AAAATTACACGCCAGATTTGCCGGTGTGACATTACTCCAGAGTTG
MMP2GGTCACATCGCTCCAGACTTACAGGATCATTGGCTACACACC
MMP3CGGTTCCGCCTGTCTCAAGCGCCAAAAGTGCCTGTCTT
MMP12GGAATCCTAGCCCATGCTTTTCATTACGGCCTTTGGATCACT
MMP13ACTGAGAGGCTCCGAGAAATGGAACCCCGCATCTTGGCTT
ADAMTS4GAGGAGGAGATCGTGTTTCCACCAGCTCTAGTAGCAGCGTC
ADAMTS5GAACATCGACCAACTCTACTCCGCAATGCCCACCGAACCATCT
Appendix 1—table 5
Information of Luminex assay kit.
Target moleculeMethodCatalog number and supplier
IL8Luminex assayHAGP1MAG-12K, EMD Millipore
IL6, CCL2, MMP1, MMP2, MMP13Luminex assayLXSAHM-18, R&D Systems
Appendix 1—table 6
Comprehensive list of proteins assessed in LUMINEX.
Target moleculeCatalog number and supplier
Interleukin 6 (IL6)LXSAHM-18, R&D Systems
Interleukin 13 (IL13)LXSAHM-18, R&D Systems
Matrix Metallopeptidase 3 (MMP3)LXSAHM-18, R&D Systems
Periostin (OSF2)LXSAHM-18, R&D Systems
Vascular Endothelial Growth Factor Receptor 2 (VEGFR2)LXSAHM-18, R&D Systems
MMP8LXSAHM-18, R&D Systems
Adiponectin (AdipoQ)LXSAHM-18, R&D Systems
Complement Factor D/Adipsin (CFD)LXSAHM-18, R&D Systems
Ectonucleotide Pyrophosphatase/Phosphodiesterase 2 Autotaxin (ENPP2)LXSAHM-18, R&D Systems
MMP2LXSAHM-18, R&D Systems
Osteopontin (OPN)LXSAHM-18, R&D Systems
C–C motif ligand 2 (CCL2)LXSAHM-18, R&D Systems
(C–X–C motif) ligand 1 (CXCL1)LXSAHM-18, R&D Systems
IL1raLXSAHM-18, R&D Systems
MMP1LXSAHM-18, R&D Systems
MMP13LXSAHM-18, R&D Systems
Tissue Inhibitor of Metalloproteinase 1 (TIMP1)HTMP1MAG-54K, EMD Millipore
TIMP2HTMP1MAG-54K, EMD Millipore
Angiopoietin 2 (Ang2)HAGP1MAG-12K, EMD Millipore
Bone Morphogenic Protein 9 (BMP9)HAGP1MAG-12K, EMD Millipore
Epidermal Growth Factor (EGF)HAGP1MAG-12K, EMD Millipore
Endoglin (CD105)HAGP1MAG-12K, EMD Millipore
Endothelin 1 (ET1)HAGP1MAG-12K, EMD Millipore
Fibroblast Growth Factor 1 (FGF1)HAGP1MAG-12K, EMD Millipore
FGF2HAGP1MAG-12K, EMD Millipore
Follistatin (FSH)HAGP1MAG-12K, EMD Millipore
Granulocyte Colony-Stimulating Factor (GCSF)HAGP1MAG-12K, EMD Millipore
Heparin-Binding EGF-like Growth Factor (HBEGF)HAGP1MAG-12K, EMD Millipore
Hepatocyte Growth Factor (HGF)HAGP1MAG-12K, EMD Millipore
IL8HAGP1MAG-12K, EMD Millipore
Leptin (LEP)HAGP1MAG-12K, EMD Millipore
Placental Growth Factor (PLGF)HAGP1MAG-12K, EMD Millipore
VEGFAHAGP1MAG-12K, EMD Millipore
VEGFDHAGP1MAG-12K, EMD Millipore

Data availability

The raw and processed RNA-seq data were uploaded to Gene Expression Omnibus (GEO) with accession ID: GSE287861.

The following data sets were generated
    1. Makarczyk M
    2. Zhang Y
    3. Aguglia A
    4. Bartholomew O
    5. Hines S
    6. Sinkar S
    7. Liu S
    8. Duvall C
    9. Lin H
    (2025) NCBI Gene Expression Omnibus
    ID GSE287861. Aging-associated Increase of GATA4 levels in Articular Cartilage is Linked to Impaired Regenerative Capacity of Chondrocytes and Osteoarthritis.

References

    1. Massagué J
    (2012) TGFβ signalling in context
    Nature Reviews. Molecular Cell Biology 13:616–630.
    https://doi.org/10.1038/nrm3434
    1. Yeo EJ
    (2019) Hypoxia and aging
    Experimental & Molecular Medicine 51:1–15.
    https://doi.org/10.1038/s12276-019-0233-3

Article and author information

Author details

  1. Meagan J Makarczyk

    1. Department of Orthopaedic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, United States
    2. Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, United States
    Contribution
    Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review and editing
    Contributed equally with
    Yiqian Zhang
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3444-8028
  2. Yiqian Zhang

    1. Department of Orthopaedic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, United States
    2. Xiangya Hospital Central South University, Changsha, China
    Contribution
    Investigation, Methodology, Writing – original draft
    Contributed equally with
    Meagan J Makarczyk
    Competing interests
    No competing interests declared
  3. Alyssa Aguglia

    Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, United States
    Contribution
    Data curation, Methodology
    Competing interests
    No competing interests declared
  4. Olivia Bartholomew

    Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, United States
    Contribution
    Data curation, Visualization, Methodology, Writing – original draft
    Competing interests
    No competing interests declared
  5. Sophie Hines

    1. Department of Orthopaedic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, United States
    2. Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, United States
    Contribution
    Data curation
    Competing interests
    No competing interests declared
  6. Kate Li

    Department of Biological Sciences, University of Pittsburgh Kenneth P. Dietrich School of Arts & Sciences, Pittsburgh, United States
    Contribution
    Data curation, Methodology, Visualization
    Competing interests
    No competing interests declared
  7. Suyash Sinkar

    Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, United States
    Contribution
    Data curation
    Competing interests
    No competing interests declared
  8. Silvia Liu

    1. Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, United States
    2. Organ Pathobiology and Therapeutics Institute, University of Pittsburgh School of Medicine, Pittsburgh, United States
    Contribution
    Formal analysis, Writing – original draft
    Competing interests
    No competing interests declared
  9. Craig Duvall

    Department of Biomedical Engineering, Vanderbilt University, Nashville, United States
    Contribution
    Investigation, Writing – original draft
    Competing interests
    No competing interests declared
  10. Hang Lin

    1. Department of Orthopaedic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, United States
    2. Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, United States
    3. Bethel Family Musculoskeletal Research Center (BMRC), University of Pittsburgh School of Medicine, Pittsburgh, United States
    Contribution
    Conceptualization, Formal analysis, Funding acquisition, Investigation, Writing – original draft, Writing – review and editing
    For correspondence
    hal46@pitt.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0781-6630

Funding

National Institute of Health (T32 EB001026)

  • Meagan J Makarczyk

Cellular Approaches to Tissue Engineering and Regeneration, Cardiovascular Bioengineering Training Program (T32- HL076124)

  • Meagan J Makarczyk

Ruth L Kirschstein National Research Service Award (NRSA) Individual Predoctoral Fellowship (Parent F31) (1F31AR083814 – 01A1)

  • Meagan J Makarczyk

University of Pittsburgh School of Medicine (Department of Orthopaedic Surgery Startup Fund)

  • Hang Lin

University of Pittsburgh School of Medicine (Orland Bethel Family Musculoskeletal Research Center (BMRC))

  • Hang Lin

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

This work was supported by the Department of Orthopaedic Surgery and the Orland Bethel Family Musculoskeletal Research Center (BMRC) at the University of Pittsburgh, as well as the University of Pittsburgh Center for Research Computing through the resources provided. This study used the Luminex Core Facility of UPCI. MJM was supported by the NIH T32 EB001026 – Cellular Approaches to Tissue Engineering and Regeneration, Cardiovascular Bioengineering Training Program T32-HL076124, and Ruth L Kirschstein National Research Service Award (NRSA) Individual Predoctoral Fellowship (Parent F31) 1F31AR083814 – 01A1. The authors thank the funding support from the NIH (P30AG038072). The Chicago Center on Musculoskeletal Pain Research Core Center, supported by NIH P30AR079206, provided training on pain-assessing methods. Schematic figures were created at https://BioRender.com.

Ethics

This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved Institutional Animal Care and Use Committee (IACUC) protocols (#23052533) of the University of Pittsburgh.

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You can cite all versions using the DOI https://doi.org/10.7554/eLife.106224. This DOI represents all versions, and will always resolve to the latest one.

Copyright

© 2025, Makarczyk, Zhang et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Meagan J Makarczyk
  2. Yiqian Zhang
  3. Alyssa Aguglia
  4. Olivia Bartholomew
  5. Sophie Hines
  6. Kate Li
  7. Suyash Sinkar
  8. Silvia Liu
  9. Craig Duvall
  10. Hang Lin
(2026)
Aging-associated increase of GATA4 levels in articular cartilage is linked to impaired regenerative capacity of chondrocytes and osteoarthritis
eLife 14:RP106224.
https://doi.org/10.7554/eLife.106224.4

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