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Aims

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.

Methods

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.


Bone & Joint Research
Vol. 11, Issue 8 | Pages 548 - 560
17 Aug 2022
Yuan W Yang M Zhu Y

Aims

We aimed to develop a gene signature that predicts the occurrence of postmenopausal osteoporosis (PMOP) by studying its genetic mechanism.

Methods

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.


Bone & Joint Research
Vol. 11, Issue 5 | Pages 304 - 316
17 May 2022
Kim MH Choi LY Chung JY Kim E Yang WM

Aims

The association of auraptene (AUR), a 7-geranyloxycoumarin, on osteoporosis and its potential pathway was predicted by network pharmacology and confirmed in experimental osteoporotic mice.

Methods

The network of AUR was constructed and a potential pathway predicted by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) terms enrichment. Female ovariectomized (OVX) Institute of Cancer Research mice were intraperitoneally injected with 0.01, 0.1, and 1 mM AUR for four weeks. The bone mineral density (BMD) level was measured by dual-energy X-ray absorptiometry. The bone microstructure was determined by histomorphological changes in the femora. In addition, biochemical analysis of the serum and assessment of the messenger RNA (mRNA) levels of osteoclastic markers were performed.


Bone & Joint Research
Vol. 10, Issue 12 | Pages 820 - 829
15 Dec 2021
Schmidutz F Schopf C Yan SG Ahrend M Ihle C Sprecher C

Aims

The distal radius is a major site of osteoporotic bone loss resulting in a high risk of fragility fracture. This study evaluated the capability of a cortical index (CI) at the distal radius to predict the local bone mineral density (BMD).

Methods

A total of 54 human cadaver forearms (ten singles, 22 pairs) (19 to 90 years) were systematically assessed by clinical radiograph (XR), dual-energy X-ray absorptiometry (DXA), CT, as well as high-resolution peripheral quantitative CT (HR-pQCT). Cortical bone thickness (CBT) of the distal radius was measured on XR and CT scans, and two cortical indices mean average (CBTavg) and gauge (CBTg) were determined. These cortical indices were compared to the BMD of the distal radius determined by DXA (areal BMD (aBMD)) and HR-pQCT (volumetric BMD (vBMD)). Pearson correlation coefficient (r) and intraclass correlation coefficient (ICC) were used to compare the results and degree of reliability.


Bone & Joint Research
Vol. 8, Issue 8 | Pages 405 - 413
1 Aug 2019
Huang J Bao X Xia W Zhu L Zhang J Ma J Jiang N Yang J Chen Q Jing T Liu J Ma D Xu G

Objectives

X-linked hypophosphataemic rickets (XLHR) is a disease of impaired bone mineralization characterized by hypophosphataemia caused by renal phosphate wasting. The main clinical manifestations of the disorder are O-shaped legs, X-shaped legs, delayed growth, and bone pain. XLHR is the most common inheritable form of rickets, with an incidence of 1/20 000 in humans. It accounts for approximately 80% of familial cases of hypophosphataemia and serves as the prototype of defective tubular phosphate (PO43+) transport, due to extra renal defects resulting in unregulated FGF23 activity. XLHR is caused by loss-of-function mutations in the PHEX gene. The aim of this research was to identify the genetic defect responsible for familial hypophosphataemic rickets in a four-generation Chinese Han pedigree and to analyze the function of this mutation.

Methods

The genome DNA samples of all members in the pedigree were extracted from whole blood. We sequenced all exons of the PHEX and FGF23 genes, as well as the adjacent splice site sequence with Sanger sequencing. Next, we analyzed the de novo mutation c.1692 del A of the PHEX gene with an online digital service and investigated the mutant PHEX with SWISS-MODEL, immunofluorescence, and protein stability detection.


Bone & Joint Research
Vol. 8, Issue 11 | Pages 544 - 549
1 Nov 2019
Zheng W Liu C Lei M Han Y Zhou X Li C Sun S Ma X

Objectives

The objective of this study was to investigate the association of four single-nucleotide polymorphisms (SNPs) of the cannabinoid receptor 2 (CNR2) gene, gene-obesity interaction, and haplotype combination with osteoporosis (OP) susceptibility.

Methods

Chinese patients with OP were recruited between March 2011 and December 2015 from our hospital. In this study, a total of 1267 post-menopausal female patients (631 OP patients and 636 control patients) were selected. The mean age of all subjects was 69.2 years (sd 15.8). A generalized multifactor dimensionality reduction (GMDR) model and logistic regression model were used to examine the interaction between SNP and obesity on OP. For OP patient-control haplotype analyses, the SHEsis online haplotype analysis software (http://analysis.bio-x.cn/) was employed.