Impact of the SIK3 pathway inhibition on osteoclast differentiation via oxidative phosphorylation.

Maintenance of bone homeostasis and the balance between bone resorption and formation are crucial for maintaining skeletal integrity. This study sought to investigate the role of salt-inducible kinase 3 (SIK3), a key regulator in cellular energy metabolism, during the differentiation of osteoclasts. Despite osteoclasts being high energy-consuming cells essential for breaking down mineralized bone tissue, the specific function of SIK3 in this process remains unclear. To address this issue, we generated osteoclast-specific SIK3 conditional knockout mice and assessed the impact of SIK3 deletion on bone homeostasis. Our findings revealed that SIK3 conditional knockout mice exhibited increased bone mass and an osteopetrosis phenotype, suggesting a pivotal role for SIK3 in bone resorption. Moreover, we assessed the impact of pterosin B, a SIK3 inhibitor, on osteoclast differentiation. The treatment with pterosin B inhibited osteoclast differentiation, reduced the numbers of multinucleated osteoclasts, and suppressed resorption activity in vitro. Gene expression analysis demonstrated that SIK3 deletion and pterosin B treatment influence a common set of genes involved in osteoclast differentiation and bone resorption. Furthermore, pterosin B treatment altered intracellular metabolism, particularly affecting key metabolic pathways, such as the tricarboxylic acid cycle and oxidative phosphorylation. These results provide valuable insights into the involvement of SIK3 in osteoclast differentiation and the molecular mechanisms underlying osteoclast function and bone diseases.

Osteoporosis is a disease that causes bones to become weak and fragile, increasing the risk of fractures especially in elderly. It is caused by an imbalance between the formation of new bone and the destruction of old bone. Cells called osteoclasts are responsible for breaking down old bone. Excessive osteoclast activity results in bone loss and osteoporosis. Our research has identified a LKB1-SIK3 pathway, which acts as an energy sensor in osteoclasts. We found that this pathway is activated when osteoclast activity is increased, and we were able to reduce osteoclast activity by genetically removing or inhibiting SIK3. These findings suggest that targeting the LKB1-SIK3 pathway may be a promising new approach for the treatment of osteoporosis. Developing drugs that inhibit SIK3 may slow bone loss and reduce the risk of fractures in osteoporotic patients.

Morphological characteristics of DISH in patients with OPLL and its association with high-sensitivity CRP: inflammatory DISH.

OBJECTIVES: To characterize and clarify evidence as to whether the ectopic bone formations of DISH in patients with ossification of the posterior longitudinal ligament (OPLL) are caused by inflammatory or degenerative processes. METHODS: Whole-spine CT and serum high-sensitivity CRP (hs-CRP) levels were obtained from 182 cervical OPLL patients (DISH+, n = 104; DISH-, n = 78). In the DISH+ group, ectopic bone formations were categorized into Flat and Jaggy types, then further divided into three subgroups: group 1 (Jaggy-dominant pattern), group 2 (Equivalence of pattern) and group 3 (Flat-dominant pattern). Data were compared between the DISH+ and DISH- groups, and among the three subgroups. RESULTS: The upper thoracic spine was most affected by the Flat type, whereas the Jaggy type was more frequent in the middle and lower thoracic regions. There was no difference in hs-CRP levels between the DISH+ and DISH- groups. Among the three subgroups, hs-CRP levels in group 3 [mean (s.d.) 0.16 (0.09) mg/dl] were significantly higher than in group 1 [0.04 (0.02) mg/dl] and group 2 [0.08 (0.06) mg/dl]. Higher levels of hs-CRP were associated with a greater number of vertebral units with Flat-type formations (ß = 0.691, P < 0.0001) and with a lesser number of vertebral units with Jaggy-type formations (ß = -0.147, P = 0.036). CONCLUSION: The Flat type in DISH might be caused by an inflammatory pathogenesis rather than a degenerative process presented in the Jaggy type.

Characterization of ligamentum flavum hypertrophy based on m6A RNA methylation modification and the immune microenvironment.

OBJECTIVE: N6-methyladenosine (m6A) has been implicated in the progression of several diseases, and the role of epigenetic regulation in immunity is emerging, particularly for RNA m6A modification. However, it is unclear how m6A-related genes affect the immune microenvironment of ligamentum flavum hyperplasia (LFH). Therefore, we aimed to investigate the effect of m6A modification on the LFH immune microenvironment. METHODS: The GSE113212 dataset was downloaded from the Gene Expression Omnibus (GEO) database. We systematically analyzed m6A regulators in eight patient samples and the corresponding clinical information of the samples. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA) and protein-protein interactions (PPIs) were used to explore the correlation of m6A clusters with the immune microenvironment in LFH. A least absolute shrinkage and selection operator (Lasso) regression was then used to further explore the m6A prognostic signature in LFH. The relative abundance of immune cell types was quantified using a single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm. We explored the relationship between hub genes and small molecule drug sensitivity by clustering hub gene-based samples. In addition, Real-Time quantitative PCR (RT-qPCR) as well as western blotting (WB) were used to validate the gene expression of the differentially expressed genes. RESULTS: A total of 1259 differentially expressed genes were identified, of which 471 were upregulated and 788 were downregulated. A total of three genes showed significant differences (METTL16, PCIF1, and FTO). According to the enrichment analysis, immune factors may play a key role in LFH. ssGSEA was used to cluster the immune infiltration score, construct the hub gene diagnosis model, and screen a total of 6 LFH immune-related prediction model genes. The predictive diagnostic model of LFH was further constructed, revealing that METTL16, PCIF1, FTO and ALKBH5 had superior diagnostic efficiency. RT-qPCR results showed that 6 genes (METTL16, PCIF1, POSTN, TNNC1, MMP1 and ACTA1; P < 0.05) exhibited expression consistent with the results of the bioinformatics analysis of the mRNA microarray. Up-regulated METTL16, PCIF1, and ALKBH5 levels in LFH were validated by western blotting. CONCLUSION: Diversity and complexity of LFH's immune microenvironment are influenced by M6A modification, and our study provides strong evidence for predicting the diagnosis and prognosis of LFH.