Osteoporosis (OP) is a chronic metabolic bone disease characterized by the decrease of bone tissue per unit volume under the combined action of
Aim. Osteoarthritis (OA) is caused by complex interactions between
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
Rheumatoid arthritis (RA) is a systematic autoimmune disorder, characterized by synovial inflammation, bone and cartilage destruction, and disease involvement in multiple organs. Although numerous drugs are employed in RA treatment, some respond little and suffer from severe side effects. This study aimed to screen the candidate therapeutic targets and promising drugs in a novel method. We developed a module-based and cumulatively scoring approach that is a deeper-layer application of weighted gene co-expression network (WGCNA) and connectivity map (CMap) based on the high-throughput datasets.Aims
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The objective of this study was to investigate the association of four single-nucleotide polymorphisms (SNPs) of the cannabinoid receptor 2 ( 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 (Objectives
Methods
We have previously investigated an association between the genome copy number variation (CNV) and acetabular dysplasia (AD). Hip osteoarthritis is associated with a genetic polymorphism in the aspartic acid repeat in the N-terminal region of the asporin ( Acetabular coverage of all subjects was evaluated using radiological findings (Sharp angle, centre-edge (CE) angle, acetabular roof obliquity (ARO) angle, and minimum joint space width). Genomic DNA was extracted from peripheral blood leukocytes. Agilent’s region-targeted high-density oligonucleotide tiling microarray was used to analyse 64 female AD patients and 32 female control subjects. All statistical analyses were performed using EZR software (Fisher’s exact probability test, Pearson’s correlation test, and Student’s Objectives
Methods
Given the function of adiponectin (ADIPOQ) on the inflammatory condition of obesity and osteoarthritis (OA), we hypothesized that the ADIPOQ gene might be a candidate gene for a marker of susceptibility to OA. We systematically screened three tagging polymorphisms (rs182052, rs2082940 and rs6773957) in the ADIPOQ gene, and evaluated the association between the genetic variants and OA risk in a case-controlled study that included 196 OA patients and 442 controls in a northern Chinese population. Genotyping was performed using the Sequenom MassARRAY iPLEX platform.Objectives
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