This study examined the relationship between obesity (OB) and osteoporosis (OP), aiming to identify shared genetic markers and molecular mechanisms to facilitate the development of therapies that target both conditions simultaneously. Using weighted gene co-expression network analysis (WGCNA), we analyzed datasets from the Gene Expression Omnibus (GEO) database to identify co-expressed gene modules in OB and OP. These modules underwent Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interaction analysis to discover Hub genes. Machine learning refined the gene selection, with further validation using additional datasets. Single-cell analysis emphasized specific cell subpopulations, and enzyme-linked immunosorbent assay (ELISA), protein blotting, and cellular staining were used to investigate key genes.Aims
Methods
Previous studies have suggested that selenium as a trace element is involved in bone health, but findings related to the specific effect of selenium on bone health remain inconclusive. Thus, we performed a meta-analysis by including all the relevant studies to elucidate the association between selenium status (dietary intake or serum selenium) and bone health indicators (bone mineral density (BMD), osteoporosis (OP), or fracture). PubMed, Embase, and Cochrane Library were systematically searched to retrieve relevant articles published before 15 November 2022. Studies focusing on the correlation between selenium and BMD, OP, or fracture were included. Effect sizes included regression coefficient (β), weighted mean difference (WMD), and odds ratio (OR). According to heterogeneity, the fixed-effect or random-effect model was used to assess the association between selenium and bone health.Aims
Methods
We aimed to develop a gene signature that predicts the occurrence of postmenopausal osteoporosis (PMOP) by studying its genetic mechanism. Five datasets were obtained from the Gene Expression Omnibus database. Unsupervised consensus cluster analysis was used to determine new PMOP subtypes. To determine the central genes and the core modules related to PMOP, the weighted gene co-expression network analysis (WCGNA) was applied. Gene Ontology enrichment analysis was used to explore the biological processes underlying key genes. Logistic regression univariate analysis was used to screen for statistically significant variables. Two algorithms were used to select important PMOP-related genes. A logistic regression model was used to construct the PMOP-related gene profile. The receiver operating characteristic area under the curve, Harrell’s concordance index, a calibration chart, and decision curve analysis were used to characterize PMOP-related genes. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression of the PMOP-related genes in the gene signature.Aims
Methods
Despite the interest in the association of gut microbiota with bone health, limited population-based studies of gut microbiota and bone mineral density (BMD) have been made. Our aim is to explore the possible association between gut microbiota and BMD. A total of 3,321 independent loci of gut microbiota were used to calculate the individual polygenic risk score (PRS) for 114 gut microbiota-related traits. The individual genotype data were obtained from UK Biobank cohort. Linear regressions were then conducted to evaluate the possible association of gut microbiota with L1-L4 BMD (n = 4,070), total BMD (n = 4,056), and femur total BMD (n = 4,054), respectively. PLINK 2.0 was used to detect the single-nucleotide polymorphism (SNP) × gut microbiota interaction effect on the risks of L1-L4 BMD, total BMD, and femur total BMD, respectively.Aims
Methods
To investigate whether idiopathic osteonecrosis of the femoral head (ONFH) is related to impaired osteoblast activities. We cultured osteoblasts isolated from trabecular bone explants taken from the femoral head and the intertrochanteric region of patients with idiopathic ONFH, or from the intertrochanteric region of patients with osteoarthritis (OA), and compared their viability, mineralization capacity, and secretion of paracrine factors.Aims
Methods
Little is known about tissue changes underlying bone marrow lesions (BMLs) in non-weight-bearing joints with osteoarthritis (OA). Our aim was to characterize BMLs in OA of the hand using dynamic histomorphometry. We therefore quantified bone turnover and angiogenesis in subchondral bone at the base of the thumb, and compared the findings with control bone from hip OA. Patients with OA at the base of the thumb, or the hip, underwent preoperative MRI to assess BMLs, and tetracycline labelling to determine bone turnover. Three groups were compared: trapezium bones removed by trapeziectomy from patients with thumb base OA (n = 20); femoral heads with (n = 24); and those without (n = 9) BMLs obtained from patients with hip OA who underwent total hip arthroplasty.Objectives
Methods
The exact aetiology and pathogenesis of microdamage-induced long bone fractures remain unknown. These fractures are likely to be the result of inadequate bone remodelling in response to damage. This study aims to identify an association of osteocyte apoptosis, the presence of osteocytic osteolysis, and any alterations in sclerostin expression with a fracture of the third metacarpal (Mc-III) bone of Thoroughbred racehorses. A total of 30 Mc-III bones were obtained; ten bones were fractured during racing, ten were from the contralateral limb, and ten were from control horses. Each Mc-III bone was divided into a fracture site, condyle, condylar groove, and sagittal ridge. Microcracks and diffuse microdamage were quantified. Apoptotic osteocytes were measured using TUNEL staining. Cathepsin K, matrix metalloproteinase-13 (MMP-13), HtrA1, and sclerostin expression were analyzed.Objectives
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