PINK1-driven mitophagy regulates RANKL-induced osteoclastogenesis in bone-marrow macrophages

PINK1-driven mitophagy regulates RANKL-induced osteoclastogenesis in bone-marrow macrophages | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article PINK1-driven mitophagy regulates RANKL-induced osteoclastogenesis in bone-marrow macrophages Shenggui Xu, Zhenxing Yu, Huiyu Chen, Chengshou Lin, Weizhong Guo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7249673/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background : Excessive bone resorption by osteoclasts is a hallmark of osteoporosis, yet the molecular mechanisms that govern osteoclast differentiation remain incompletely defined. By integrating in-silico public transcriptomic dataset analysis with in-vitro validation, we sought to identify novel regulators of osteoclastogenesis. Methods: Differential‑expression and STRING network analyses of two independent RNA‑seq datasets of RANKL‑stimulated macrophages (GSE172007, GSE272401) were performed with limma , clusterProfiler and CytoHubba. For in-vitro analyses, RAW264.7 macrophages were transfected with a PINK1 over‑expression vector (OE‑PINK1) or PINK1‑specific siRNA (si‑PINK1) and exposed to RANKL + M‑CSF. Osteoclast viability (CCK‑8), apoptosis/mitophagy proteins (Bax, Bcl‑2, Beclin‑1, LC3‑II), mitochondrial membrane potential (JC‑1) and intracellular ROS were quantified. Expression of osteoclast markers (TRAP, Cathepsin K, NFATc1, c‑Fos) was assessed by qRT‑PCR and Western blot. Results: In-silico screening highlighted PTEN‑induced kinase 1 (PINK1) as a top‑degree hub within 220 high‑confidence, RANKL‑responsive genes enriched for osteoclast differentiation pathways. In vitro, PINK1 over‑expression (i) increased cell viability, (ii) raised Bax and lowered Bcl‑2, (iii) elevated Beclin‑1 and LC3‑II, (iv) preserved mitochondrial ΔΨm and suppressed ROS, and (v) up‑regulated TRAP, Cathepsin K, NFATc1 and c‑Fos. Conversely, PINK1 silencing produced the opposite effects, depolarizing ΔΨm and provoking ROS accumulation. Conclusion: Overall, our combined in‑silico and experimental approach identifies PINK1-mediated mitophagy as a pivotal driver of RANKL‑induced osteoclastogenesis. PINK1 couples mitochondrial quality control to osteoclast survival and resorptive gene expression, making it a promising therapeutic target for osteoporosis and other bone‑resorptive disorders. PINK1 Osteoclastogenesis Apoptosis Autophagy Mitochondria Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1 INTRODUCTION Osteoporosis poses an ever‑growing threat to public health [1]. Resulting fractures often trigger complications such as hypostatic pneumonia and pressure ulcers, both of which can be life‑threatening [2]. The disease originates from disturbed bone homeostasis—the delicate balance between bone formation (osteogenesis) and bone resorption (osteoclastogenesis) [3, 4]. Osteoclasts arise from differentiation of either hematopoietic stem cells or monocytes [5]. This differentiation and maturation process also known as osteoclastogenesis, encompasses several stages, including conversion to tartrate‑resistant acid‑phosphatase (TRAP)‑positive cells, activation of bone‑resorptive machinery and, ultimately, spontaneous apoptosis [6]. Four key ligands coordinate this process: RANK, its ligand RANKL, macrophage colony‑stimulating factor (M‑CSF) and the decoy receptor osteoprotegerin (OPG) [7]. RANKL, a highly conserved member of the TNF family, interacts with its receptor, RANK (encoded by Tnfrsf11a), expressed on the surface of Raw264.7 cells through M-CSF stimulation [8]. OPG serves as a competitive inhibitor, impeding the combination of RANKL to RANK. OPG polymorphisms are linked to osteoporosis risk [8, 9]. There is a pressing and unmet medical demand for innovative treatment approaches for osteoporosis, as existing anti‑resorptive drugs are only partially effective and can cause notable side effects, highlighting the need for new molecular targets. To discover such targets, we first conducted an integrative bioinformatics analysis of two independent RANKL‑stimulated RNA‑seq datasets. Network ranking of the shared differentially expressed genes pinpointed PTEN‑induced kinase 1 (PINK1) as a top hub gene. PINK1 is a mitochondria-based serine/threonine-protein kinase that plays a crucial role in maintaining mitochondrial quality control [10]. It is instrumental in initiating mitophagy, while simultaneously contributing to mitochondrial biogenesis [11]. Growing evidence indicates that PINK1‑dependent quality control influences diverse pathological conditions, including neurodegenerative conditions [12], pulmonary disorders [13], heart issues [14], and kidney diseases [15]. Nevertheless, the specific role of PINK1 in osteoclastogenesis remain unexplored. To fill this gap, we induced osteoclast differentiation in RAW264.7 macrophages with M‑CSF and RANKL, and modulated PINK1 expression by over‑expression or siRNA‑mediated knock‑down. We then examined the consequences for osteoclast formation, apoptosis, mitophagy, mitochondrial integrity and downstream signaling. Our combined in‑silico and experimental approach provides new insight into osteoclast biology and identifies PINK1 as a potential therapeutic lever for osteoporosis. 2 MATERIALS AND METHODS 2.1 Public‑dataset acquisition and preprocessing Raw RNA‑seq count matrices and associated platform annotations for GSE172007 and GSE272401 (primary mouse bone‑marrow macrophages) were downloaded from the NCBI Gene Expression Omnibus (GEO) using the GEOquery package in R (v 4.3.1). Background correction and trimmed mean normalization were applied with edgeR; counts were then log₂‑transformed. Probe or transcript identifiers were mapped to official gene Symbols. Where necessary, batch‑effect correction was carried out, after which the data were log₂‑transformed to yield the final gene‑expression matrix. 2.2 Differential expression analysis Differentially expressed genes (DEGs) were identified with limma. A linear model was fitted to each gene and empirical‑Bayes moderation was employed to shrink gene‑wise variance estimates. Resulting statistics were adjusted for multiple testing by the Benjamini–Hochberg procedure, yielding the false‑discovery rate (FDR). Genes with |log₂ fold‑change (logFC)| > 1 and adj.P.Val < 0.05 were deemed significant. Visualization was carried out in ggplot2 for volcano plots (logFC vs –log₁₀ FDR) and pheatmap for heat‑maps of the top 40 DEGs, clustered with Euclidean distance and complete linkage. 2.3 Functional enrichment analysis Enrichment analyses were performed in clusterProfiler using the intersection of DEGs common to both datasets (|logFC| > 1, FDR < 0.05). Gene Symbols were first converted to Entrez IDs via org.Mm.eg.db. Gene Ontology (GO) enrichment was carried out separately for Biological Process (BP), Cellular Component (CC) and Molecular Function (MF) with p.adjust < 0.05 as the significance threshold. KEGG pathway enrichment employed the same statistical framework and significance cut‑off. Results were visualized with dotplot(), displaying the ten most significant terms per ontology or pathway set. 2.4 Protein–protein interaction (PPI) network and hub‑gene identification The intersection of DEGs common to both datasets (|logFC| > 1, FDR < 0.05) was uploaded to the STRING database (version 11.5) with the minimum required interaction score set to 0.7. Disconnected nodes were removed, and the resulting PPI network was exported to Cytoscape (version 3.9.1). Hub genes were ranked with the CytoHubba plugin using the Degree centrality metric; the top‑degree sub‑network was visualized with node color proportional to Degree. 2.5 Cell culture and osteoclastogenic induction RAW264.7 murine macrophages (ATCC, Manassas, VA, USA) were maintained in α‑MEM (Hyclone, Logan, UT, USA) supplemented with 10 % fetal bovine serum (FBS; Invitrogen, Carlsbad, CA, USA), 100 U mL⁻¹ penicillin and 100 µg mL⁻¹ streptomycin at 37 °C in a humidified 5 % CO₂ atmosphere. For osteoclast differentiation, cells were seeded at 1 × 10³ cells per well in 24‑well plates and stimulated with 50 ng mL⁻¹ recombinant murine M‑CSF and 50 ng mL⁻¹ RANKL (both Invitrogen). The medium was replaced every two days, and cells were collected after four days for downstream assays. 2.6 Cell Transfection A PINK1 over‑expression plasmid (OE‑PINK1) and its empty‑vector control (OE‑NC), as well as a small‑interfering RNA targeting PINK1 (si‑PINK1) and scrambled control (si‑NC), were obtained from GenePharma (Shanghai, China). Transfections were carried out with Lipofectamine 2000 (Invitrogen) according to the manufacturer’s instructions. Three hours post‑transfection, cells were transferred to the osteoclast‑induction medium described above. 2.7 Western blot RAW264.7 cells were lysed in RIPA buffer (Solarbio, Beijing, China) supplemented with protease inhibitors. Protein concentration was determined with a BCA assay kit (Solarbio). Equal amounts of protein (40 µg) were resolved by SDS‑PAGE and electro‑transferred to PVDF membranes (Solarbio). Membranes were blocked in 5% non‑fat milk and incubated overnight at 4 °C with the following primary antibodies (all 1:1000 dilution unless specified): PINK1 (ab186303), Bcl‑2 (ab182858), Bax (ab32503), Beclin‑1 (ab302669), LC3 (ab62721), TRAP (ab52750), Cathepsin K (ab300569), GAPDH (ab8245) (all Abcam, Cambridge, MA, USA), NFATc1 (#5862, Cell Signalling Technology, Beverly, MA, USA) and c‑Fos (ab208942, Abcam). After washing, membranes were incubated for 1 hour at room temperature with HRP‑conjugated secondary antibody (ab205718, 1:2500, Abcam). Bands were visualised using an enhanced chemiluminescence kit (ECL‑Plus, Solarbio) following the manufacturer’s guidelines and were quantified with ImageJ. 2.8 CCK-8 assay Transfected RAW264.7 cells were seeded in 96‑well plates at 1 × 10³ cells per well. At 0, 12, 24 and 48 h, 10 µL of CCK‑8 reagent (Solarbio) was added to each well and incubated for 2 h at 37 °C. Absorbance was measured at 450 nm with a microplate reader (SK601, Seikagaku, Tokyo, Japan) to assess cell viability. 2.9 Mitochondrial membrane potential (ΔΨm) measurement Mitochondrial ΔΨm was assessed with the JC‑1 assay kit (ab113850, Abcam). RAW264.7 cells were collected after the indicated treatments and incubated with JC‑1 working solution (10 µg mL⁻¹) for 15 min at 37 °C in the dark. The dye emits green fluorescence (monomers) at low ΔΨm and red fluorescence (aggregates) at high ΔΨm [16]. After washing with PBS, fluorescence was measured on a microplate reader (SK601, Seikagaku) at 530 nm (monomer) and 590 nm (aggregate). Mitochondrial membrane potential was expressed as the red/green fluorescence ratio. 2.10 Intracellular ROS detection Reactive oxygen species (ROS) were quantified using a ROS assay kit (ab287839, Abcam). Briefly, 4 × 10⁴ RAW264.7 cells per condition were incubated with 1 × ROS Label reagent for 30 min at 37 °C in the dark. Cells were then washed with assay buffer I containing 10 % FBS, resuspended in PBS, and imaged with a fluorescence microscope (Carl Zeiss, Jena, Germany). Mean fluorescence intensity was calculated with ImageJ to reflect intracellular ROS levels. 2.11 QRT-PCR otal RNA was extracted from RAW264.7 cells with RNAiso Reagent (Takara, Dalian, China). One microgram of RNA was reverse‑transcribed to cDNA using the PrimeScript™ RT Master Mix kit (RR036A, Takara). qRT‑PCR was performed with SYBR® Premix Ex Taq™ (Takara) on an ABI 7500 real‑time PCR system. GAPDH served as the internal control. Relative mRNA expression was calculated by the 2 –ΔΔCt method. Primer sequences are listed in Table 1. 2.12 Statistical analysis Data are expressed as mean ± SD from three independent experiments. Statistical tests were conducted in GraphPad Prism 8 (GraphPad Software, La Jolla, CA, USA). Two‑group comparisons used the two‑tailed Student’s t ‑test, while one‑way ANOVA followed by Tukey’s post‑hoc test was applied to multi‑group comparisons. A P value < 0.05 was considered statistically significant. 3 RESULTS 3.1 Transcriptomic screen nominates PINK1 as a hub regulator of RANKL-induced osteoclastogenesis To obtain an unbiased list of genes responsive to osteoclastogenic stimulation, we analyzed two independent RNA‑seq datasets, namely GSE172007 and GSE272401, having transcriptomic data of control macrophages isolated form C57BL6 background and their in vitro RANKL-stimulated counterparts. Differential expression analyses using |log₂FC| > 1 and FDR < 0.05 thresholds yielded 3075 and 310 differentially expressed genes (DEGs) between control and RANKL-stimulated macrophages respectively in GSE172007 and GSE272401 (Figure 1A and B). Unsupervised clustering of the DEGs from each dataset produced a clear separation between RANKL and control samples (Figure 1C and D), confirming data quality and the expected transcriptional re‑programming. Intersecting the two DEG lists identified 220 common genes (7.6 % overlap), which we considered high‑confidence RANKL targets (Figure 1E). Functional annotation of this consensus set revealed significant enrichment for Biological Process terms related to chemotaxis, ERK1/2 signaling and inflammatory signaling; Cellular Component terms linked to extracellular matrix and plasma‑membrane microdomains; and Molecular Function terms highlighting immune interactions and integrin binding (Figure 2A). KEGG analysis further pointed to pathways central to osteoclast biology, including “Osteoclast differentiation”, “PI3K‑Akt signaling” and redox‑linked metabolism such as “Glutathione metabolism” (Figure 2B). Protein–protein interaction mapping of the common 220 DEGs in STRING (confidence ≥ 0.7) followed by degree‑based ranking in CytoHubba isolated 14 top‑degree hubs. Strikingly, PINK1 occupied a central position alongside its mitophagy partners and core mitochondrial enzymes (Figure 2C). Notably, PINK1 is significant up‑regulated in RANKL-stimulated macrophages in both GSE172007 and GSE272401 datasets (Figure 2D and E). Taken together, the convergence of differential expression, pathway enrichment and network centrality nominates PINK1 as a key node within the transcriptional program that drives RANKL‑mediated osteoclastogenesis. 3.2 PINK1 promotes RANKL‑induced osteoclastogenesis Next, we aimed to delineate the functional role of PINK1 during osteoclast differentiation. In this context, RAW264.7 macrophages were transfected with either a PINK1 over‑expression construct (OE‑PINK1) or a small‑interfering RNA targeting PINK1 (si‑PINK1). Three hours after transfection the cells were exposed to RANKL to initiate osteoclastogenesis. Immuno-blotting confirmed that PINK1 protein was markedly up‑regulated in the OE‑PINK1 group and substantially down‑regulated in the si‑PINK1 group relative to controls (Figure 3A). Functional read‑out by CCK‑8 revealed that PINK1 over‑expression significantly enhanced the viability of RANKL‑treated RAW264.7 cells, whereas PINK1 knock‑down produced the opposite effect (Figure 3B). Collectively, these data indicate that PINK1 acts as a positive regulator of RANKL‑driven osteoclast formation. 3.3 PINK1 enhances apoptosis and mitophagy in RANKL‑stimulated osteoclasts To clarify how PINK1 influences cell fate during osteoclastogenesis, we analyzed canonical apoptotic and mitophagy markers in RANKL‑treated RAW264.7 cells following PINK1 gain‑ or loss‑of‑function manipulation. Western blotting demonstrated that PINK1 over‑expression markedly increased the pro‑apoptotic protein Bax, whereas PINK1 silencing reduced Bax levels (Figure 4). In contrast, the anti‑apoptotic protein Bcl‑2 declined in the OE‑PINK1 group but rose when PINK1 was knocked down, indicating a shift toward apoptosis driven by PINK1. We next assessed markers of mitochondrial autophagy. Over‑expression of PINK1 elevated Beclin‑1 and the autophagosome marker LC3‑II, while PINK1 depletion suppressed both proteins (Figure 4), consistent with enhanced mitophagic flux. Collectively, these findings show that PINK1 not only accelerates RANKL‑induced osteoclast formation (Section 3.2) but also promotes apoptosis and mitophagy, highlighting its multifaceted role in osteoclast biology. 3.4 PINK1 sustains mitochondrial membrane potential and restrains ROS production in RANKL‑stimulated osteoclasts Mitochondrial function was evaluated by the JC‑1 assay, which reports membrane potential (ΔΨm) through the ratio of red JC‑1 aggregates to green monomers [17]. Over‑expression of PINK1 significantly increased the JC‑1 aggregate/monomer ratio, indicating a more polarized mitochondrial membrane, whereas PINK1 silencing sharply decreased this ratio in RANKL‑treated RAW264.7 cells (Figure 5A). The loss of ΔΨm observed in the si‑PINK1 group denotes pronounced mitochondrial depolarization. Reactive‑oxygen‑species (ROS) measurements mirrored these findings. PINK1 over‑expression lowered intracellular ROS compared with vector controls, whereas PINK1 knock‑down provoked a marked ROS surge under RANKL stimulation (Figure 5B). Thus, PINK1 deficiency compromises mitochondrial membrane integrity and accelerates oxidative stress, linking impaired mitochondrial function to excessive ROS accumulation during osteoclastogenesis. 3.5 PINK1 up‑regulates canonical osteoclast marker genes Finally, we next examined whether PINK1 modulates the transcriptional program characteristic of mature osteoclasts. Expression of tartrate‑resistant acid phosphatase (TRAP), Cathepsin K, NFATc1, and c‑Fos was quantified in RANKL‑stimulated RAW264.7 cells following PINK1 gain‑ or loss‑of‑function. PINK1 over‑expression significantly increased the mRNA and protein levels of all four markers, whereas PINK1 knock‑down produced the opposite effect (Figure 6A and B). These results indicate that PINK1 positively regulates the osteoclastogenic gene set, reinforcing its role as a driver of RANKL‑induced osteoclast differentiation. 4 DISCUSSION Using an integrative workflow that combined two independent RANKL‑stimulated transcriptome datasets, STRING network analysis and CytoHubba hub‑gene ranking, we first identified PINK1 as a top‑degree hub among 220 high‑confidence osteoclast‑responsive genes (Figure 1 and 2). Functional studies in RAW264.7 cells confirmed and extended this in‑silico prediction: PINK1 over‑expression promoted RANKL‑induced osteoclastogenesis, whereas PINK1 silencing suppressed it. Specifically, PINK1 gain‑of‑function increased cell viability, osteoclast marker expression, mitochondrial membrane potential and mitophagy, while reducing intracellular ROS. Conversely, PINK1 knock‑down produced the opposite phenotype (Figure 3-6). Together, these findings position PINK1 as a central regulator of osteoclast differentiation and function. Our data align well with previous reports. Lee et al . [18] showed that PINK1 deficiency impairs osteoblast differentiation by disrupting mitochondrial homeostasis and increasing mitochondrial ROS; PINK1 levels were also lower in bone from osteoporotic patients. Wang et al . [19] further demonstrated that gold nanoparticles enhance osteoclastogenesis via PINK1‑mediated mitophagy in periodontal ligament stem cells. The present study extends these observations by providing both bioinformatic and mechanistic evidence that PINK1 positively regulates osteoclast formation. Apoptosis is a key contributor to age‑related bone loss [20]. Two key modulators of this process are Bcl‑2 and Bax, members of the Bcl‑2 protein family that exert opposing effects on mitochondrial membrane integrity [21]. Bcl‑2 preserves outer‑membrane continuity, blocks pore formation and thereby suppresses the downstream apoptotic cascade [21]. Bax, in contrast, oligomerizes within the outer membrane, increases permeability and releases pro‑death factors such as cytochrome c, thereby activating the apoptosis process [22]. A high Bax/Bcl‑2 ratio consequently predisposes cells to apoptosis [23]. Li et al . [24] reported that PINK1/Parkin‑dependent mitophagy modulates this balance in osteoblasts. Concordantly, we observed that PINK1 over‑expression elevated Bax while reducing Bcl‑2 in RANKL‑treated RAW264.7 cells, whereas PINK1 knock‑down had the opposite effect, underscoring PINK1’s pro‑apoptotic influence in differentiating osteoclasts. Mitochondria govern energy generation, calcium buffering and cell‑death signaling [25]. The mitochondrial oxidative phosphorylation system is responsible for generating ATPs to support cellular functions, with ROS being produced as by-products of this process [26]. Impaired mitochondrial function limits osteoblast differentiation, while excessive ROS disrupts bone‑forming capacity [26]. Growing evidence indicates that mitophagy, the selective removal of damaged mitochondria, supports bone health by preserving mitochondrial quality, promoting osteoblast survival and ultimately increasing bone mass [27]. Beclin-1 is a crucial initiator protein for autophagy. It is part of the class III phosphoinositide 3-kinase (PI3K) complex, playing a key role in the early stages of autophagy [28]. On the other hand, LC3 protein binds to autophagic vesicle membranes. It exists in two forms: unmodified LC3-I and modified LC3-II. Conversion of LC3‑I to membrane‑bound LC3‑II marks autophagosome maturation [29]. Beclin‑1 and LC3 interact cooperatively to orchestrate phagophore expansion and closure [30]. Zhong et al . [10] showed that PINK1 mutations impair mitophagy. In line with this, our data reveal that PINK1 over‑expression elevates Beclin‑1 and LC3‑II levels, while PINK1 silencing lowers ΔΨm and spikes ROS, findings consistent with Lee et al . [18], and indicative of compromised mitochondrial fitness. Transcriptionally, NFATc1 partners with c‑Fos to form the AP‑1 complex, a master regulator of osteoclast differentiation [31]. Downstream targets include TRAP and Cathepsin K, enzymatic markers integral to bone resorption [32]. Here, PINK1 up‑regulated NFATc1, c‑Fos, TRAP and Cathepsin K in RANKL‑stimulated RAW264.7 cells, further corroborating its pro‑osteoclastogenic role. Together, these findings situate PINK1 at the nexus of mitochondrial quality control, apoptotic regulation and osteoclast gene expression, offering new mechanistic insight and a potential therapeutic entry point for osteoporosis management. A limitation of the present study is the exclusive use of cell‑based assays; in‑vivo models and clinical specimens will be required to validate PINK1 as a therapeutic target in osteoporosis. Nonetheless, the combined in-silico discovery and in‑vitro validation presented here provide compelling evidence that PINK1 integrates mitochondrial quality control with osteoclast differentiation, making it a promising lever for modulating bone resorption. 5 CONCLUSION By coupling transcriptomic screening with mechanistic cell studies, we identified PINK1 as a hub gene in RANKL‑driven osteoclastogenesis and verified its functional importance in RAW264.7 cells. PINK1 over‑expression accelerated osteoclast differentiation, promoted apoptosis and enhanced mitophagy, whereas PINK1 silencing depolarised the mitochondrial membrane, heightened intracellular ROS and suppressed canonical osteoclast markers. These findings deepen our understanding of the mitochondrial checkpoints that govern osteoclast biology and highlight PINK1 as a promising therapeutic target for osteoporosis and other bone‑resorptive disorders. Declarations Acknowledgements Not applicable. Authors’ contributions Conception and design: Shenggui Xu and Weizhong Guo. Method: Zhenxing Yu. Data Collection: Huiyu Chen. Manuscript Writing: Shenggui Xu. Manuscript revision: Weizhong Guo and Chengshou Lin. Research supervision: Weizhong Guo and Chengshou Lin. All authors contributed to the article and approved the submitted version. Conflict of interest The authors declare that there are no conflicts of interest regarding the publication of this paper. Availability of data and materials The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. Funding This study was supported by Natural Science Foundation of Ningde (Project No. 2022J13). Ethics approval All animal procedures were carried out in compliance with the guidelines for scientific animal procedures approved by the ethics committee of Mindong Hospital Affiliated to Fujian Medical University (Animal Ethics No. 202209181330000176963). 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Idelalisib inhibits osteoclast differentiation and pre-osteoclast migration by blocking the PI3Kdelta-Akt-c-Fos/NFATc1 signaling cascade. Arch Pharm Res. 2019;42(8):712-21. Nakamura M, Aoyama N, Yamaguchi S, Sasano Y. Expression of tartrate-resistant acid phosphatase and cathepsin K during osteoclast differentiation in developing mouse mandibles. Biomed Res. 2021;42(1):13-21. Table Table 1. Primers for qRT-PCR. Name Primers for qRT-PCR (5’-3’) TRAP Forward TTGTTGACAGCGGTCCATCT Reverse GGTGCCCTCCTTCTTAACCC Cathepsin K Forward CTCCAGTCAAGAACCAGGGC Reverse CCGTTCTGCTGCACGTATTG NFATc1 Forward TCAGAGTGAGACCGAGAGGC Reverse GAGTCCGACCTCTCCTTTGC c-fos Forward TACTACCATTCCCCAGCCGA Reverse GCTGTCACCGTGGGGATAAA GAPDH Forward CCCTTAAGAGGGATGCTGCC Reverse TACGGCCAAATCCGTTCACA Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7249673","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":511473503,"identity":"2a2b6e15-3c9c-4584-ae3f-c8902ae2ea2c","order_by":0,"name":"Shenggui Xu","email":"","orcid":"","institution":"Mindong Hospital Affifiliated to Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shenggui","middleName":"","lastName":"Xu","suffix":""},{"id":511473504,"identity":"5a907ba2-1e4e-40f7-a4ad-c969cd441318","order_by":1,"name":"Zhenxing Yu","email":"","orcid":"","institution":"Mindong Hospital Affifiliated to Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhenxing","middleName":"","lastName":"Yu","suffix":""},{"id":511473505,"identity":"8884f911-e66c-4668-a30a-a9eef292a67b","order_by":2,"name":"Huiyu Chen","email":"","orcid":"","institution":"Mindong Hospital Affifiliated to Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Huiyu","middleName":"","lastName":"Chen","suffix":""},{"id":511473507,"identity":"adef3bd8-3b73-4052-83db-941466e64728","order_by":3,"name":"Chengshou Lin","email":"","orcid":"","institution":"Mindong Hospital Affifiliated to Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chengshou","middleName":"","lastName":"Lin","suffix":""},{"id":511473509,"identity":"d26da083-cf77-4954-aad3-184549e7330f","order_by":4,"name":"Weizhong Guo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYFACHhBhw8DGzthAkpY0BjZmErUcZmBgJlaDwfmzh1/zVJyX52NmbpPm3cEgzy92gICWA+fSrHnO3DZsY2YEajnDYDhzdgJ+LWYHe8yMedtuM0K0tDEkGNwmpOUwD0jLOXsStBzjMX7M23YgkXgt9md4zBjnnElOBmpptpzbJkHYL5L9Z4w/vKmws53f3v7wxts2G3l+aQJagIBNAspgATIk8CqFAeYP6IxRMApGwSgYBSgAAG4qOx8jzZ2NAAAAAElFTkSuQmCC","orcid":"","institution":"Mindong Hospital Affifiliated to Fujian Medical University","correspondingAuthor":true,"prefix":"","firstName":"Weizhong","middleName":"","lastName":"Guo","suffix":""}],"badges":[],"createdAt":"2025-07-30 07:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7249673/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7249673/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90940526,"identity":"fc632e18-865a-4183-bc1f-949b82442180","added_by":"auto","created_at":"2025-09-09 18:01:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":23292151,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTranscriptomic screening of RANKL‑induced osteoclastogenesis\u003c/strong\u003e. (A and B) Volcano plots for GSE172007 (A) and GSE272401 (B) datasets comparing RANKL‑treated samples with PBS controls. The x‑axis is log₂ fold‑change (log₂FC) and the y‑axis is –log₁₀(\u003cem\u003eadjusted P\u003c/em\u003e). Vertical dashed lines indicate |log₂FC| = 1 and the horizontal dashed line marks \u003cem\u003eFDR\u003c/em\u003e = 0.05. Genes meeting both thresholds are colored red (up‑regulated) or blue (down‑regulated); non‑significant genes are grey. Several canonical osteoclast genes are labelled for reference. (C and D) Unsupervised hierarchical‑clustering heat‑maps of the top 40 differentially expressed genes (DEGs) in GSE172007 (C) and GSE272401 (D) datasets comparing RANKL‑treated samples with PBS controls. (E) Venn diagram summarizing 220 (7.6%) shared DEGs overlapping between the two datasets (|log₂FC| \u0026gt; 1, \u003cem\u003eFDR\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7249673/v1/5cb08f00ebd4914d7bfd8c30.png"},{"id":90940523,"identity":"9ab9c7bd-5023-4538-9688-e81505b0e62c","added_by":"auto","created_at":"2025-09-09 18:01:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5945805,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional enrichment and network analyses pinpoint PINK1 as a central hub in osteoclast‑related transcriptional programs. \u003c/strong\u003e(A) Gene Ontology (GO) enrichment of the 220 shared DEGs. The bar-plot is faceted by ontology: Biological Process (BP), Cellular Component (CC) and Molecular Function (MF). Only the top 10 terms per ontology are displayed; all satisfy \u003cem\u003ep.adjust\u003c/em\u003e \u0026lt; 0.05.\u003cstrong\u003e \u003c/strong\u003e(B) Bar-chart showing KEGG pathway enrichment for the 220 DEGs shared between GSE172007 and GSE272401. Pathways are ordered by significance. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(C) Protein‑protein interaction (PPI) sub‑network of the top 14 hub genes identified with CytoHubba (Degree ranking) after importing the STRING v11.5 network (confidence ≥ 0.7) into Cytoscape v3.9.1. Node color reflects Degree centrality (red = high, yellow = moderate).\u003cstrong\u003e \u003c/strong\u003e(D and E) Expression of Pink1 in GSE172007 (D) and GSE272401 (E) datasets comparing RANKL‑treated samples with PBS controls. Box‑ and whisker‑plots show normalized counts (FPKM) for PBS controls (blue) versus RANKL‑treated samples (orange); dots denote individual replicates (n = 2 for GSE172007 and n = 3 for GSE272401 per group).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7249673/v1/01ed871debe4cc6863f97684.png"},{"id":90940522,"identity":"8a8d4439-03eb-4975-938b-fda563eff1e1","added_by":"auto","created_at":"2025-09-09 18:01:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":707218,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePINK1 promotes RANKL-induced osteoclastogenesis\u003c/strong\u003e. A) Western blot showing PINK1 protein levels 24 hours after transfection with the PINK1 over‑expression plasmid (OE‑PINK1) or PINK1‑specific siRNA (si‑PINK1). OE‑NC and si‑NC denote the corresponding empty‑vector and scrambled controls; GAPDH serves as the loading control. Bar-graph (right) shows the quantification of relative protein expression. (B) Cell viability measured by the CCK‑8 assay at the indicated time points following RANKL stimulation. Data are expressed as mean ± SD (n = 3). *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 vs untreated control group; \u003csup\u003e\u0026amp;\u0026amp;\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 vs OE‑NC group; \u003csup\u003e#\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, \u003csup\u003e##\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 vs si‑NC group\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7249673/v1/345e105af407dda70d046451.png"},{"id":90940520,"identity":"a039be91-f967-4e8f-a1e4-4017954dcadd","added_by":"auto","created_at":"2025-09-09 18:01:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":515677,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePINK1 enhances apoptosis and mitophagy in RANKL‑stimulated osteoclasts. \u003c/strong\u003eRepresentative Western blots and corresponding densitometric analyses of the pro‑apoptotic protein Bax, anti‑apoptotic protein Bcl‑2, and the mitophagy markers Beclin‑1 and LC3‑II (normalized to GAPDH). RAW264.7 cells were transfected with PINK1 over‑expression plasmid (OE‑PINK1), PINK1‑specific siRNA (si‑PINK1) or their respective controls (OE‑NC, si‑NC) and then stimulated with RANKL for 24 hours. Data are expressed as mean ± SD (n = 3). *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 vs untreated control group; \u003csup\u003e\u0026amp;\u0026amp;\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 vs OE‑NC group; \u003csup\u003e#\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, \u003csup\u003e##\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 vs si‑NC group\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7249673/v1/72917d1aac75211f3aabecb3.png"},{"id":90940521,"identity":"dfeab771-b102-4dad-ad40-2f87aa101f3c","added_by":"auto","created_at":"2025-09-09 18:01:45","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":940065,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePINK1 sustains mitochondrial membrane potential and restrains ROS production in RANKL‑stimulated osteoclasts. \u003c/strong\u003e(A) JC‑1 staining of cells transfected with PINK1 over‑expression plasmid (OE‑PINK1), PINK1‑specific siRNA (si‑PINK1) or their respective controls (OE‑NC, si‑NC) after 24 h of RANKL treatment. Healthy mitochondria show red JC‑1 aggregates, whereas depolarised mitochondria display green JC‑1 monomers. Representative fluorescence micrographs (scale bar = 50 µm) and quantitative red/green fluorescence ratios are shown. (B) Intracellular reactive oxygen species (ROS) levels measured with a commercial ROS detection kit under the same experimental conditions. Data are expressed as mean ± SD (n = 3). *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 vs untreated control group; \u003csup\u003e\u0026amp;\u0026amp;\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 vs OE‑NC group; \u003csup\u003e#\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, \u003csup\u003e##\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 vs si‑NC group\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7249673/v1/31b7e9cde8092eb5849b84a1.png"},{"id":90940524,"identity":"e52bda67-fcfb-40e0-ac74-5f94c453a090","added_by":"auto","created_at":"2025-09-09 18:01:45","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":932494,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePINK1 up‑regulates canonical osteoclast marker genes\u003c/strong\u003e. (A) Representative Western blots and densitometric quantification of the same proteins, normalised to GAPDH, under identical experimental conditions. (B) Relative mRNA levels of TRAP, Cathepsin K, NFATc1, and c‑Fos measured by qRT‑PCR 24 hours after transfection with PINK1 over‑expression plasmid (OE‑PINK1), PINK1‑specific siRNA (si‑PINK1) or their respective controls (OE‑NC, si‑NC) followed by RANKL stimulation. Data are expressed as mean ± SD (n = 3). *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 vs untreated control group; \u003csup\u003e\u0026amp;\u0026amp;\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 vs OE‑NC group; \u003csup\u003e#\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, \u003csup\u003e##\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 vs si‑NC group\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7249673/v1/70ac08065b88fc0a703bec84.png"},{"id":90940949,"identity":"a4b36f59-a0ae-4d1d-8230-c265e3f2b674","added_by":"auto","created_at":"2025-09-09 18:10:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":32644522,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7249673/v1/212aa278-87b8-4f85-bd4e-c2357a68faaf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"PINK1-driven mitophagy regulates RANKL-induced osteoclastogenesis in bone-marrow macrophages","fulltext":[{"header":"1 INTRODUCTION","content":"\u003cp\u003eOsteoporosis poses an ever‑growing threat to public health [1]. Resulting fractures often trigger complications such as hypostatic pneumonia and pressure ulcers, both of which can be life‑threatening [2]. The disease originates from disturbed bone homeostasis—the delicate balance between bone formation (osteogenesis) and bone resorption (osteoclastogenesis) [3, 4]. Osteoclasts arise from differentiation of either hematopoietic stem cells or monocytes [5].\u0026nbsp;This differentiation and maturation process also known as osteoclastogenesis, encompasses several stages, including conversion to tartrate‑resistant acid‑phosphatase (TRAP)‑positive cells, activation of bone‑resorptive machinery and, ultimately, spontaneous apoptosis [6].\u0026nbsp;Four key ligands coordinate this process: RANK, its ligand RANKL, macrophage colony‑stimulating factor (M‑CSF) and the decoy receptor osteoprotegerin (OPG) [7].\u0026nbsp;RANKL, a highly conserved member of the TNF family, interacts with its receptor, RANK (encoded by Tnfrsf11a), expressed on the surface of Raw264.7 cells through M-CSF stimulation [8]. OPG serves as a competitive inhibitor, impeding the combination of RANKL to RANK. OPG polymorphisms are linked to osteoporosis risk [8, 9].\u0026nbsp;There is a pressing and unmet medical demand for innovative treatment approaches for osteoporosis, as existing anti‑resorptive drugs are only partially effective and can cause notable side effects, highlighting the need for new molecular targets.\u003c/p\u003e\n\u003cp\u003eTo discover such targets, we first conducted an integrative bioinformatics analysis of two independent RANKL‑stimulated RNA‑seq datasets. Network ranking of the shared differentially expressed genes pinpointed PTEN‑induced kinase 1 (PINK1) as a top hub gene. PINK1 is a mitochondria-based serine/threonine-protein kinase that plays a crucial role in maintaining mitochondrial quality control [10]. It is instrumental in initiating mitophagy, while simultaneously contributing to mitochondrial biogenesis [11]. Growing evidence indicates that PINK1‑dependent quality control influences diverse pathological conditions, including neurodegenerative conditions [12], pulmonary disorders [13], heart issues [14], and kidney diseases [15].\u0026nbsp;Nevertheless, the specific role of PINK1 in osteoclastogenesis\u0026nbsp;remain unexplored.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo fill this gap, we induced osteoclast differentiation in RAW264.7 macrophages with M‑CSF and RANKL, and modulated PINK1 expression by over‑expression or siRNA‑mediated knock‑down. We then examined the consequences for osteoclast formation, apoptosis, mitophagy, mitochondrial integrity and downstream signaling. Our combined \u003cem\u003ein‑silico\u003c/em\u003e and experimental approach provides new insight into osteoclast biology and identifies PINK1 as a potential therapeutic lever for osteoporosis.\u003c/p\u003e"},{"header":"2 MATERIALS AND METHODS ","content":"\u003cp\u003e\u003cstrong\u003e2.1 Public‑dataset acquisition and preprocessing\u003cbr\u003e\u003c/strong\u003eRaw RNA‑seq count matrices and associated platform annotations for GSE172007 and GSE272401 (primary mouse bone‑marrow macrophages) were downloaded from the NCBI Gene Expression Omnibus (GEO) using the GEOquery package in R (v 4.3.1). Background correction and trimmed mean normalization were applied with edgeR; counts were then log₂‑transformed. Probe or transcript identifiers were mapped to official gene Symbols. Where necessary, batch‑effect correction was carried out, after which the data were log₂‑transformed to yield the final gene‑expression matrix.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Differential expression analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferentially expressed genes (DEGs) were identified with limma. A linear model was fitted to each gene and empirical‑Bayes moderation was employed to shrink gene‑wise variance estimates. Resulting statistics were adjusted for multiple testing by the Benjamini–Hochberg procedure, yielding the false‑discovery rate (FDR). Genes with |log₂ fold‑change (logFC)| \u0026gt; 1 and \u003cem\u003eadj.P.Val\u003c/em\u003e \u0026lt; 0.05 were deemed significant. Visualization was carried out in ggplot2 for volcano plots (logFC vs –log₁₀ FDR) and pheatmap for heat‑maps of the top 40 DEGs, clustered with Euclidean distance and complete linkage.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Functional enrichment analysis\u003c/strong\u003e\u003cbr\u003eEnrichment analyses were performed in clusterProfiler using the intersection of DEGs common to both datasets (|logFC| \u0026gt; 1, FDR \u0026lt; 0.05). Gene Symbols were first converted to Entrez IDs via org.Mm.eg.db. Gene Ontology (GO) enrichment was carried out separately for Biological Process (BP), Cellular Component (CC) and Molecular Function (MF) with p.adjust \u0026lt; 0.05 as the significance threshold.\u0026nbsp;KEGG pathway enrichment employed the same statistical framework and significance cut‑off.\u003cbr\u003e\u0026nbsp;Results were visualized with dotplot(), displaying the ten most significant terms per ontology or pathway set.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Protein–protein interaction (PPI) network and hub‑gene identification\u003c/strong\u003e\u003cbr\u003eThe intersection of DEGs common to both datasets (|logFC| \u0026gt; 1, FDR \u0026lt; 0.05) was uploaded to the STRING database (version 11.5) with the minimum required interaction score set to 0.7. Disconnected nodes were removed, and the resulting PPI network was exported to Cytoscape (version 3.9.1). Hub genes were ranked with the CytoHubba plugin using the Degree centrality metric; the top‑degree sub‑network was visualized with node color proportional to Degree.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Cell culture and osteoclastogenic induction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRAW264.7 murine macrophages (ATCC, Manassas, VA, USA) were maintained in α‑MEM (Hyclone, Logan, UT, USA) supplemented with 10 % fetal bovine serum (FBS; Invitrogen, Carlsbad, CA, USA), 100 U mL⁻¹ penicillin and 100 µg mL⁻¹ streptomycin at 37 °C in a humidified 5 % CO₂ atmosphere. For osteoclast differentiation, cells were seeded at 1 × 10³ cells per well in 24‑well plates and stimulated with 50 ng mL⁻¹ recombinant murine M‑CSF and 50 ng mL⁻¹ RANKL (both Invitrogen). The medium was replaced every two days, and cells were collected after four days for downstream assays.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Cell Transfection\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA PINK1 over‑expression plasmid (OE‑PINK1) and its empty‑vector control (OE‑NC), as well as a small‑interfering RNA targeting PINK1 (si‑PINK1) and scrambled control (si‑NC), were obtained from GenePharma (Shanghai, China). Transfections were carried out with Lipofectamine 2000 (Invitrogen) according to the manufacturer’s instructions. Three hours post‑transfection, cells were transferred to the osteoclast‑induction medium described above.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.7 Western blot\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRAW264.7 cells were lysed in RIPA buffer (Solarbio, Beijing, China) supplemented with protease inhibitors. Protein concentration was determined with a BCA assay kit (Solarbio). Equal amounts of protein (40 µg) were resolved by SDS‑PAGE and electro‑transferred to PVDF membranes (Solarbio). Membranes were blocked in 5% non‑fat milk and incubated overnight at 4 °C with the following primary antibodies (all 1:1000 dilution unless specified): PINK1 (ab186303), Bcl‑2 (ab182858), Bax (ab32503), Beclin‑1 (ab302669), LC3 (ab62721), TRAP (ab52750), Cathepsin K (ab300569), GAPDH (ab8245) (all Abcam, Cambridge, MA, USA), NFATc1 (#5862, Cell Signalling Technology, Beverly, MA, USA) and c‑Fos (ab208942, Abcam). After washing, membranes were incubated for 1 hour at room temperature with HRP‑conjugated secondary antibody (ab205718, 1:2500, Abcam). Bands were visualised using an enhanced chemiluminescence kit (ECL‑Plus, Solarbio) following the manufacturer’s guidelines and were quantified with ImageJ.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8 CCK-8 assay\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTransfected RAW264.7 cells were seeded in 96‑well plates at 1 × 10³ cells per well. At 0, 12, 24 and 48 h, 10 µL of CCK‑8 reagent (Solarbio) was added to each well and incubated for 2 h at 37 °C. Absorbance was measured at 450 nm with a microplate reader (SK601, Seikagaku, Tokyo, Japan) to assess cell viability.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.9 Mitochondrial membrane potential (ΔΨm) measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMitochondrial ΔΨm was assessed with the JC‑1 assay kit (ab113850, Abcam). RAW264.7 cells were collected after the indicated treatments and incubated with JC‑1 working solution (10 µg mL⁻¹) for 15 min at 37 °C in the dark. The dye emits green fluorescence (monomers) at low ΔΨm and red fluorescence (aggregates) at high ΔΨm [16].\u0026nbsp;After washing with PBS, fluorescence was measured on a microplate reader (SK601, Seikagaku) at 530 nm (monomer) and 590 nm (aggregate). Mitochondrial membrane potential was expressed as the red/green fluorescence ratio.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.10\u003c/strong\u003e \u003cstrong\u003eIntracellular ROS detection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReactive oxygen species (ROS) were quantified using a ROS assay kit (ab287839, Abcam). Briefly, 4 × 10⁴ RAW264.7 cells per condition were incubated with 1 × ROS Label reagent for 30 min at 37 °C in the dark. Cells were then washed with assay buffer I containing 10 % FBS, resuspended in PBS, and imaged with a fluorescence microscope (Carl Zeiss, Jena, Germany). Mean fluorescence intensity was calculated with ImageJ to reflect intracellular ROS levels.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.11 QRT-PCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eotal RNA was extracted from RAW264.7 cells with RNAiso Reagent (Takara, Dalian, China). One microgram of RNA was reverse‑transcribed to cDNA using the PrimeScript™ RT Master Mix kit (RR036A, Takara). qRT‑PCR was performed with SYBR® Premix Ex Taq™ (Takara) on an ABI 7500 real‑time PCR system. GAPDH served as the internal control. Relative mRNA expression was calculated by the 2\u003csup\u003e–ΔΔCt\u0026nbsp;\u003c/sup\u003emethod. Primer sequences are listed in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.12 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are expressed as mean ± SD from three independent experiments. Statistical tests were conducted in GraphPad Prism 8 (GraphPad Software, La Jolla, CA, USA). Two‑group comparisons used the two‑tailed Student’s \u003cem\u003et\u003c/em\u003e‑test, while one‑way ANOVA followed by Tukey’s post‑hoc test was applied to multi‑group comparisons. A \u003cem\u003eP\u003c/em\u003e value \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"3 RESULTS","content":"\u003cp\u003e\u003cstrong\u003e3.1 Transcriptomic screen nominates PINK1 as a hub regulator of RANKL-induced osteoclastogenesis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo obtain an unbiased list of genes responsive to osteoclastogenic stimulation, we analyzed two independent RNA‑seq datasets, namely GSE172007 and GSE272401, having transcriptomic data of control macrophages isolated form C57BL6 background and their \u003cem\u003ein vitro\u003c/em\u003e RANKL-stimulated counterparts. Differential expression analyses using |log₂FC| \u0026gt; 1 and FDR \u0026lt; 0.05 thresholds yielded 3075 and 310 differentially expressed genes (DEGs) between control and RANKL-stimulated macrophages respectively in GSE172007 and GSE272401 (Figure 1A and B). Unsupervised clustering of the DEGs from each dataset produced a clear separation between RANKL and control samples (Figure 1C and D), confirming data quality and the expected transcriptional re‑programming. Intersecting the two DEG lists identified 220 common genes (7.6 % overlap), which we considered high‑confidence RANKL targets (Figure 1E). Functional annotation of this consensus set revealed significant enrichment for Biological Process terms related to chemotaxis, ERK1/2 signaling and inflammatory signaling; Cellular Component terms linked to extracellular matrix and plasma‑membrane microdomains; and Molecular Function terms highlighting immune interactions and integrin binding (Figure 2A). KEGG analysis further pointed to pathways central to osteoclast biology, including “Osteoclast differentiation”, “PI3K‑Akt signaling” and redox‑linked metabolism such as “Glutathione metabolism” (Figure 2B). Protein–protein interaction mapping of the common 220 DEGs in STRING (confidence ≥ 0.7) followed by degree‑based ranking in CytoHubba isolated 14 top‑degree hubs. Strikingly, PINK1 occupied a central position alongside its mitophagy partners and core mitochondrial enzymes (Figure 2C). Notably, PINK1 is significant up‑regulated in RANKL-stimulated macrophages in both GSE172007 and GSE272401 datasets (Figure 2D and E). Taken together, the convergence of differential expression, pathway enrichment and network centrality nominates PINK1 as a key node within the transcriptional program that drives RANKL‑mediated osteoclastogenesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 PINK1 promotes RANKL‑induced osteoclastogenesis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNext, we aimed to delineate the functional role of PINK1 during osteoclast differentiation. In this context, RAW264.7 macrophages were transfected with either a PINK1 over‑expression construct (OE‑PINK1) or a small‑interfering RNA targeting PINK1 (si‑PINK1). Three hours after transfection the cells were exposed to RANKL to initiate osteoclastogenesis. Immuno-blotting confirmed that PINK1 protein was markedly up‑regulated in the OE‑PINK1 group and substantially down‑regulated in the si‑PINK1 group relative to controls (Figure 3A). Functional read‑out by CCK‑8 revealed that PINK1 over‑expression significantly enhanced the viability of RANKL‑treated RAW264.7 cells, whereas PINK1 knock‑down produced the opposite effect (Figure 3B). Collectively, these data indicate that PINK1 acts as a positive regulator of RANKL‑driven osteoclast formation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 PINK1 enhances apoptosis and mitophagy in RANKL‑stimulated osteoclasts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo clarify how PINK1 influences cell fate during osteoclastogenesis, we analyzed canonical apoptotic and mitophagy markers in RANKL‑treated RAW264.7 cells following PINK1 gain‑ or loss‑of‑function manipulation. Western blotting demonstrated that PINK1 over‑expression markedly increased the pro‑apoptotic protein Bax, whereas PINK1 silencing reduced Bax levels (Figure 4). In contrast, the anti‑apoptotic protein Bcl‑2 declined in the OE‑PINK1 group but rose when PINK1 was knocked down, indicating a shift toward apoptosis driven by PINK1. We next assessed markers of mitochondrial autophagy. Over‑expression of PINK1 elevated Beclin‑1 and the autophagosome marker LC3‑II, while PINK1 depletion suppressed both proteins (Figure 4), consistent with enhanced mitophagic flux. Collectively, these findings show that PINK1 not only accelerates RANKL‑induced osteoclast formation (Section 3.2) but also promotes apoptosis and mitophagy, highlighting its multifaceted role in osteoclast biology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 PINK1 sustains mitochondrial membrane potential and restrains ROS production in RANKL‑stimulated osteoclasts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMitochondrial function was evaluated by the JC‑1 assay, which reports membrane potential (ΔΨm) through the ratio of red JC‑1 aggregates to green monomers [17]. Over‑expression of PINK1 significantly increased the JC‑1 aggregate/monomer ratio, indicating a more polarized mitochondrial membrane, whereas PINK1 silencing sharply decreased this ratio in RANKL‑treated RAW264.7 cells (Figure 5A). The loss of ΔΨm observed in the si‑PINK1 group denotes pronounced mitochondrial depolarization. Reactive‑oxygen‑species (ROS) measurements mirrored these findings. PINK1 over‑expression lowered intracellular ROS compared with vector controls, whereas PINK1 knock‑down provoked a marked ROS surge under RANKL stimulation (Figure 5B). Thus, PINK1 deficiency compromises mitochondrial membrane integrity and accelerates oxidative stress, linking impaired mitochondrial function to excessive ROS accumulation during osteoclastogenesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePINK1\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eup‑regulates canonical osteoclast marker genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinally, we next examined whether PINK1 modulates the transcriptional program characteristic of mature osteoclasts. Expression of tartrate‑resistant acid phosphatase (TRAP), Cathepsin K, NFATc1, and c‑Fos was quantified in RANKL‑stimulated RAW264.7 cells following PINK1 gain‑ or loss‑of‑function. PINK1 over‑expression significantly increased the mRNA and protein levels of all four markers, whereas PINK1 knock‑down produced the opposite effect (Figure 6A and B). These results indicate that PINK1 positively regulates the osteoclastogenic gene set, reinforcing its role as a driver of RANKL‑induced osteoclast differentiation.\u003c/p\u003e"},{"header":"4 DISCUSSION","content":"\u003cp\u003eUsing an integrative workflow that combined two independent RANKL‑stimulated transcriptome datasets, STRING network analysis and CytoHubba hub‑gene ranking, we first identified PINK1 as a top‑degree hub among 220 high‑confidence osteoclast‑responsive genes (Figure 1 and 2). Functional studies in RAW264.7 cells confirmed and extended this \u003cem\u003ein‑silico\u003c/em\u003e prediction: PINK1 over‑expression promoted RANKL‑induced osteoclastogenesis, whereas PINK1 silencing suppressed it. Specifically, PINK1 gain‑of‑function increased cell viability, osteoclast marker expression, mitochondrial membrane potential and mitophagy, while reducing intracellular ROS. Conversely, PINK1 knock‑down produced the opposite phenotype (Figure 3-6). Together, these findings position PINK1 as a central regulator of osteoclast differentiation and function.\u003c/p\u003e\n\u003cp\u003eOur data align well with previous reports. Lee \u003cem\u003eet al\u003c/em\u003e. [18] showed that PINK1 deficiency impairs osteoblast differentiation by disrupting mitochondrial homeostasis and increasing mitochondrial ROS; PINK1 levels were also lower in bone from osteoporotic patients. Wang \u003cem\u003eet al\u003c/em\u003e. [19] further demonstrated that gold nanoparticles enhance osteoclastogenesis via PINK1‑mediated mitophagy in periodontal ligament stem cells. The present study extends these observations by providing both bioinformatic and mechanistic evidence that PINK1 positively regulates osteoclast formation.\u003c/p\u003e\n\u003cp\u003eApoptosis is a key contributor to age‑related bone loss [20]. Two key modulators of this process are Bcl‑2 and Bax, members of the Bcl‑2 protein family that exert opposing effects on mitochondrial membrane integrity [21]. Bcl‑2 preserves outer‑membrane continuity, blocks pore formation and thereby suppresses the downstream apoptotic cascade [21]. Bax, in contrast, oligomerizes within the outer membrane, increases permeability and releases pro‑death factors such as cytochrome c, thereby activating the apoptosis process [22]. A high Bax/Bcl‑2 ratio consequently predisposes cells to apoptosis [23]. Li \u003cem\u003eet al\u003c/em\u003e. [24] reported that PINK1/Parkin‑dependent mitophagy modulates this balance in osteoblasts. Concordantly, we observed that PINK1 over‑expression elevated Bax while reducing Bcl‑2 in RANKL‑treated RAW264.7 cells, whereas PINK1 knock‑down had the opposite effect, underscoring PINK1’s pro‑apoptotic influence in differentiating osteoclasts.\u003c/p\u003e\n\u003cp\u003eMitochondria govern energy generation, calcium buffering and cell‑death signaling [25]. The mitochondrial oxidative phosphorylation system is responsible for generating ATPs to support cellular functions, with ROS being produced as by-products of this process [26]. Impaired mitochondrial function limits osteoblast differentiation, while excessive ROS disrupts bone‑forming capacity [26]. Growing evidence indicates that mitophagy, the selective removal of damaged mitochondria, supports bone health by preserving mitochondrial quality, promoting osteoblast survival and ultimately increasing bone mass [27]. Beclin-1 is a crucial initiator protein for autophagy. It is part of the class III phosphoinositide 3-kinase (PI3K) complex, playing a key role in the early stages of autophagy [28]. On the other hand, LC3 protein binds to autophagic vesicle membranes. It exists in two forms: unmodified LC3-I and modified LC3-II. Conversion of LC3‑I to membrane‑bound LC3‑II marks autophagosome maturation [29]. Beclin‑1 and LC3 interact cooperatively to orchestrate phagophore expansion and closure [30]. Zhong\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e. [10] showed that PINK1 mutations impair mitophagy. In line with this, our data reveal that PINK1 over‑expression elevates Beclin‑1 and LC3‑II levels, while PINK1 silencing lowers ΔΨm and spikes ROS, findings consistent with Lee \u003cem\u003eet al\u003c/em\u003e. [18], and indicative of compromised mitochondrial fitness.\u003c/p\u003e\n\u003cp\u003eTranscriptionally, NFATc1 partners with c‑Fos to form the AP‑1 complex, a master regulator of osteoclast differentiation [31]. Downstream targets include TRAP and Cathepsin K, enzymatic markers integral to bone resorption [32]. Here, PINK1 up‑regulated NFATc1, c‑Fos, TRAP and Cathepsin K in RANKL‑stimulated RAW264.7 cells, further corroborating its pro‑osteoclastogenic role. Together, these findings situate PINK1 at the nexus of mitochondrial quality control, apoptotic regulation and osteoclast gene expression, offering new mechanistic insight and a potential therapeutic entry point for osteoporosis management.\u003c/p\u003e\n\u003cp\u003eA limitation of the present study is the exclusive use of cell‑based assays; in‑vivo models and clinical specimens will be required to validate PINK1 as a therapeutic target in osteoporosis. Nonetheless, the combined \u003cem\u003ein-silico\u003c/em\u003e discovery and \u003cem\u003ein‑vitro\u003c/em\u003e validation presented here provide compelling evidence that PINK1 integrates mitochondrial quality control with osteoclast differentiation, making it a promising lever for modulating bone resorption.\u003c/p\u003e"},{"header":"5 CONCLUSION","content":"\u003cp\u003eBy coupling transcriptomic screening with mechanistic cell studies, we identified PINK1 as a hub gene in RANKL‑driven osteoclastogenesis and verified its functional importance in RAW264.7 cells. PINK1 over‑expression accelerated osteoclast differentiation, promoted apoptosis and enhanced mitophagy, whereas PINK1 silencing depolarised the mitochondrial membrane, heightened intracellular ROS and suppressed canonical osteoclast markers. These findings deepen our understanding of the mitochondrial checkpoints that govern osteoclast biology and highlight PINK1 as a promising therapeutic target for osteoporosis and other bone‑resorptive disorders.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConception and design: Shenggui Xu and Weizhong Guo. Method: Zhenxing Yu. Data Collection: Huiyu Chen. Manuscript Writing: Shenggui Xu. Manuscript revision: Weizhong Guo and Chengshou Lin. Research supervision: Weizhong Guo and Chengshou Lin. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no conflicts of interest regarding the publication of this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Natural Science Foundation of Ningde (Project No. 2022J13).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal procedures were carried out in compliance with the guidelines for scientific animal procedures approved by the ethics committee of Mindong Hospital Affiliated to Fujian Medical University (Animal Ethics No. 202209181330000176963).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"REFERENCES","content":"\u003col\u003e\n\u003cli\u003eArceo-Mendoza RM, Camacho PM. Postmenopausal Osteoporosis: Latest Guidelines. Endocrinol Metab Clin North Am. 2021;50(2):167-78.\u003c/li\u003e\n\u003cli\u003eReid IR. A broader strategy for osteoporosis interventions. Nat Rev Endocrinol. 2020;16(6):333-9.\u003c/li\u003e\n\u003cli\u003eFischer V, Haffner-Luntzer M. Interaction between bone and immune cells: Implications for postmenopausal osteoporosis. Semin Cell Dev Biol. 2022;123:14-21.\u003c/li\u003e\n\u003cli\u003eKim JM, Lin C, Stavre Z, Greenblatt MB, Shim JH. Osteoblast-Osteoclast Communication and Bone Homeostasis. Cells. 2020;9(9).\u003c/li\u003e\n\u003cli\u003eTuckermann J, Adams RH. The endothelium-bone axis in development, homeostasis and bone and joint disease. Nat Rev Rheumatol. 2021;17(10):608-20.\u003c/li\u003e\n\u003cli\u003eKim JE. Osteoclastogenesis and Osteogenesis. Int J Mol Sci. 2022;23(12).\u003c/li\u003e\n\u003cli\u003eAnwar A, Sapra L, Gupta N, Ojha RP, Verma B, Srivastava RK. 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Acta Neuropathol Commun. 2020;8(1):189.\u003c/li\u003e\n\u003cli\u003eWang J, Zhang Y, Luo Y, Liu ML, Niu W, Li ZC, et al. PDK1 upregulates PINK1-mediated pulmonary endothelial cell mitophagy during hypoxia-induced pulmonary vascular remodeling. Mol Biol Rep. 2023;50(7):5585-96.\u003c/li\u003e\n\u003cli\u003ePopov SV, Mukhomedzyanov AV, Voronkov NS, Derkachev IA, Boshchenko AA, Fu F, et al. Regulation of autophagy of the heart in ischemia and reperfusion. Apoptosis. 2023;28(1-2):55-80.\u003c/li\u003e\n\u003cli\u003eLin Q, Li S, Jiang N, Shao X, Zhang M, Jin H, et al. PINK1-parkin pathway of mitophagy protects against contrast-induced acute kidney injury via decreasing mitochondrial ROS and NLRP3 inflammasome activation. Redox Biol. 2019;26:101254.\u003c/li\u003e\n\u003cli\u003ePerelman A, Wachtel C, Cohen M, Haupt S, Shapiro H, Tzur A. JC-1: alternative excitation wavelengths facilitate mitochondrial membrane potential cytometry. 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J Diabetes Res. 2017;2017:6483572.\u003c/li\u003e\n\u003cli\u003eGao J, Feng Z, Wang X, Zeng M, Liu J, Han S, et al. SIRT3/SOD2 maintains osteoblast differentiation and bone formation by regulating mitochondrial stress. Cell Death Differ. 2018;25(2):229-40.\u003c/li\u003e\n\u003cli\u003eBader V, Winklhofer KF. PINK1 and Parkin: team players in stress-induced mitophagy. Biol Chem. 2020;401(6-7):891-9.\u003c/li\u003e\n\u003cli\u003eHill SM, Wrobel L, Ashkenazi A, Fernandez-Estevez M, Tan K, Burli RW, et al. VCP/p97 regulates Beclin-1-dependent autophagy initiation. Nat Chem Biol. 2021;17(4):448-55.\u003c/li\u003e\n\u003cli\u003ePena-Martinez C, Rickman AD, Heckmann BL. Beyond autophagy: LC3-associated phagocytosis and endocytosis. Sci Adv. 2022;8(43):eabn1702.\u003c/li\u003e\n\u003cli\u003eKong Z, Yao T. Role for autophagy-related markers Beclin-1 and LC3 in endometriosis. BMC Womens Health. 2022;22(1):264.\u003c/li\u003e\n\u003cli\u003eYeon JT, Kim KJ, Son YJ, Park SJ, Kim SH. Idelalisib inhibits osteoclast differentiation and pre-osteoclast migration by blocking the PI3Kdelta-Akt-c-Fos/NFATc1 signaling cascade. Arch Pharm Res. 2019;42(8):712-21.\u003c/li\u003e\n\u003cli\u003eNakamura M, Aoyama N, Yamaguchi S, Sasano Y. Expression of tartrate-resistant acid phosphatase and cathepsin K during osteoclast differentiation in developing mouse mandibles. Biomed Res. 2021;42(1):13-21.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"548\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 548px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1. Primers for qRT-PCR.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 168px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eName\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 272px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimers for qRT-PCR (5\u0026rsquo;-3\u0026rsquo;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003eTRAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eForward\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 272px;\"\u003e\n \u003cp\u003eTTGTTGACAGCGGTCCATCT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eReverse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 272px;\"\u003e\n \u003cp\u003eGGTGCCCTCCTTCTTAACCC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003eCathepsin K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eForward\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 272px;\"\u003e\n \u003cp\u003eCTCCAGTCAAGAACCAGGGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eReverse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 272px;\"\u003e\n \u003cp\u003eCCGTTCTGCTGCACGTATTG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003eNFATc1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eForward\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 272px;\"\u003e\n \u003cp\u003eTCAGAGTGAGACCGAGAGGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eReverse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 272px;\"\u003e\n \u003cp\u003eGAGTCCGACCTCTCCTTTGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 168px;\"\u003e\n \u003cp\u003ec-fos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eForward\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 272px;\"\u003e\n \u003cp\u003eTACTACCATTCCCCAGCCGA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eReverse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 272px;\"\u003e\n \u003cp\u003eGCTGTCACCGTGGGGATAAA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eGAPDH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eForward\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 272px;\"\u003e\n \u003cp\u003eCCCTTAAGAGGGATGCTGCC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eReverse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 272px;\"\u003e\n \u003cp\u003eTACGGCCAAATCCGTTCACA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"PINK1, Osteoclastogenesis, Apoptosis, Autophagy, Mitochondria","lastPublishedDoi":"10.21203/rs.3.rs-7249673/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7249673/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Excessive bone resorption by osteoclasts is a hallmark of osteoporosis, yet the molecular mechanisms that govern osteoclast differentiation remain incompletely defined. By integrating \u003cem\u003ein-silico \u003c/em\u003epublic transcriptomic dataset analysis with \u003cem\u003ein-vitro \u003c/em\u003evalidation, we sought to identify novel regulators of osteoclastogenesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Differential‑expression and STRING network analyses of two independent RNA‑seq datasets of RANKL‑stimulated macrophages (GSE172007, GSE272401) were performed with \u003cem\u003elimma\u003c/em\u003e, \u003cem\u003eclusterProfiler\u003c/em\u003eand CytoHubba. For \u003cem\u003ein-vitro\u003c/em\u003e analyses, RAW264.7 macrophages were transfected with a PINK1 over‑expression vector (OE‑PINK1) or PINK1‑specific siRNA (si‑PINK1) and exposed to RANKL + M‑CSF. Osteoclast viability (CCK‑8), apoptosis/mitophagy proteins (Bax, Bcl‑2, Beclin‑1, LC3‑II), mitochondrial membrane potential (JC‑1) and intracellular ROS were quantified. Expression of osteoclast markers (TRAP, Cathepsin K, NFATc1, c‑Fos) was assessed by qRT‑PCR and Western blot.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003e\u003cem\u003eIn-silico\u003c/em\u003escreening highlighted PTEN‑induced kinase 1 (PINK1) as a top‑degree hub within 220 high‑confidence, RANKL‑responsive genes enriched for osteoclast differentiation pathways. In vitro, PINK1 over‑expression (i) increased cell viability, (ii) raised Bax and lowered Bcl‑2, (iii) elevated Beclin‑1 and LC3‑II, (iv) preserved mitochondrial ΔΨm and suppressed ROS, and (v) up‑regulated TRAP, Cathepsin K, NFATc1 and c‑Fos. Conversely, PINK1 silencing produced the opposite effects, depolarizing ΔΨm and provoking ROS accumulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Overall, our combined \u003cem\u003ein‑silico\u003c/em\u003e and experimental approach identifies PINK1-mediated mitophagy as a pivotal driver of RANKL‑induced osteoclastogenesis. PINK1 couples mitochondrial quality control to osteoclast survival and resorptive gene expression, making it a promising therapeutic target for osteoporosis and other bone‑resorptive disorders.\u003c/p\u003e","manuscriptTitle":"PINK1-driven mitophagy regulates RANKL-induced osteoclastogenesis in bone-marrow macrophages","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-09 18:01:40","doi":"10.21203/rs.3.rs-7249673/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-17T20:07:46+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-03T02:09:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-22T10:38:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-15T08:02:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"306435741647046387907276072004847435315","date":"2025-09-07T17:28:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"268137318655008902948183557959010674149","date":"2025-09-03T04:40:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"50056398636484835312537124491777862956","date":"2025-09-03T00:57:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-02T16:44:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-01T07:49:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-31T07:31:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Medical Research","date":"2025-07-30T07:14:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a654d1bd-c319-477a-ad67-948d8997ada9","owner":[],"postedDate":"September 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-17T14:26:00+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-09 18:01:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7249673","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7249673","identity":"rs-7249673","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}