BioProject

Osteoporosis is a significant health concern, and the role of microRNAs (miRNAs) in cell growth and development regulation is well recognized. High-throughput sequencing technology is widely employed in current research. This study aimed to identify and validate miRNAs associated with osteoporosis. Bone specimens were collected from patients with osteoporosis (n=3) and without osteoporosis (n=3). High-throughput sequencing was utilized to screen for miRNAs, followed by analysis using volcano maps, Wayne maps, gene ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The identified miRNAs were further confirmed using qRT-PCR. Sequencing analysis revealed 12 down-regulated and five upregulated miRNAs in osteoporosis. GO and KEGG analysis indicated the association of these miRNAs with bone metabolism. qRT-PCR results demonstrated a significant decrease in miR-140-5p, miR-127-3p, miR-199b-5p, miR-181a-5p, miR-181d-5p, and miR-542-3p (all P<0.05) in osteoporosis compared to controls, while miR-486-3p and miR-486-5p exhibited a significant increase (P<0.05). This study utilized high-throughput sequencing to identify differential miRNA expression in individuals with osteoporosis. Specifically, six miRNAs (miR-140-5p, miR-127-3p, miR-199b-5p, miR-181a-5p, miR-181d-5p, and miR-542) showed decreased expression, whereas two miRNAs (miR-486-3p and miR-486-5p) exhibited increased expression. The differential expression of these miRNAs may serve as predictive indicators, potentially aiding in the prognosis and management of osteoporosis. Overall design: Sample Type: Specimens were obtained from the femoral intertrochanteric area or vertebrae of six orthopedic surgery patients at Guangzhou University of Chinese Medicine Affiliated Orthopedic Hospital. The samples included bone specimens from individuals with a background of persistent pain in the lower back and legs, as well as individuals diagnosed with osteoporosis based on bone mineral density (BMC) or bone mineral density (BMD) levels. Experimental Conditions: 1. Specimen Preservation: The collected specimens were treated with liquid nitrogen within 15 minutes of harvesting and preserved in an RNA Fixer Reagent at a temperature of -80°C until the RNA extraction process. 2. RNA Isolation: RNA quantity and quality assessment were performed by Novogene Co., Ltd. RNA degradation and contamination were examined on agarose gels, and the purity and concentration of RNA were determined using a Nano Photometer® spectrophotometer and a Qubit® RNA Assay Kit, respectively. 3. Library Preparation: The small RNA library was constructed using 3 μg of total RNA per sample. The NEBNext Multiplex Small RNA Library Prep Set for Illumina was used, and index codes were incorporated to assign sequences to individual samples. The library quality was assessed using the Agilent Bioanalyzer 2100 system. 4. Clustering and Sequencing: Index-coded samples were clustered using the TruSeq SR Cluster Kit, and sequencing was performed on an Illumina Hiseq 2500/2000 platform, generating 50-bp single-end reads. Study Variables: 1. Differential Expression Analysis: DESeq and DEGseq packages were used to analyze differential expression between two conditions/groups, taking into account samples with and without biological replicates. Adjusted p-values and q-values were calculated to determine significant differential expression. 2. Target Gene Prediction: The psRobot tar in miRanda was utilized to predict the target genes of miRNAs. 3. Quantitative RT-PCR: qRT-PCR was performed using the Gene Amp PCR System 9700, and PCR primers are listed in Table 2. 4. Gene Ontology Enrichment Analysis: The differentially expressed miRNAs were subjected to gene ontology (GO) enrichment analysis to identify enriched biological processes and molecular functions. 5. KEGG Pathway Analysis: KEGG pathway analysis was conducted using the KOBAS program to evaluate the statistical enrichment of potential gene candidates. 6. Statistical Analysis: Statistical analysis was performed using the Mann-Whitney U-test or Wilcoxon signed-rank test. The results were presented as averages ± standard deviations (SD), and two-sided p-values less than 0.05 were considered statistically significant.