Objective: Osteoporosis (OP) is the most common bone disease. The genetic and metabolic factors play important roles in OP development. However, the genetic basis of OP is still elusive. The study aimed to explore the relationships between OP and dietary habits. Methods: This study used large-scale genome-wide association study (GWAS) summary statistics from the UK Biobank to explore potential associations between OP and 143 dietary habits. The GWAS summary data of OP included 9434 self-reported OP cases and 444,941 controls, and the GWAS summary data of the dietary habits included 455,146 participants of European ancestry. Linkage disequilibrium score regression (LDSC) was used to detect the genetic correlations between OP and each of the 143 dietary habits, followed by Mendelian randomization (MR) analysis to further assess the causal relationship between OP and candidate dietary habits identified by LDSC. Results: The LDSC analysis identified seven candidate dietary habits that showed genetic associations with OP including cereal type such as biscuit cereal (coefficient = −0.1693, p value = 0.0183), servings of raw vegetables per day (coefficient = 0.0837, p value = 0.0379), and spirits measured per month (coefficient = 0.115, p value = 0.0353). MR analysis found that OP and PC17 (butter) (odds ratio [OR] = 0.974, 95% confidence interval [CI] = (0.973, 0.976), p value = 0.000970), PC35 (decaffeinated coffee) (OR = 0.985, 95% CI = (0.983, 0.987), p value = 0.00126), PC36 (overall processed meat intake) (OR = 1.035, 95% CI = (1.033, 1.037), p value = 0.000976), PC39 (spirits measured per month) (OR = 1.014, 95% CI = (1.011, 1.015), p value = 0.00153), and servings of raw vegetables per day (OR = 0.978, 95% CI = (0.977, 0.979), p value = 0.000563) were clearly causal. Conclusions: Our findings provide new clues for understanding the genetic mechanisms of OP, which focus on the possible role of dietary habits in OP pathogenesis.

Adequate new bone regeneration in bone defects has always been a challenge as it requires excellent and efficient osteogenesis. Calcium phosphate (CaP) bioceramics, including hydroxyapatite (HA) and biphasic calcium phosphates (BCPs), have been extensively used in clinical bone defect filling due to their good osteoinductivity and biodegradability. Here, for the first time, we designed and fabricated two porous CaP bioceramic granules with core−shell structures, named in accordance with their composition as BCP@HA and HA@BCP (core@shell). The spherical shape and the porous structure of these granules were achieved by the calcium alginate gel molding technology combined with a H 2 O 2 foaming process. These granules could be stacked to build a porous structure with a porosity of 65−70% and a micropore size distribution between 150 and 450 μm, which is reported to be good for new bone ingrowth. In vitro experiments confirmed that HA@BCP bioceramic granules could promote the proliferation and osteogenic ability when cocultured with bone marrow mesenchymal stem cells, while inhibiting the differentiation of RAW264.7 cells into osteoclasts. In vivo, 12 weeks of implantation in a critical-sized femoral bone defect animal model showed a higher bone volume fraction and bone mineral density in the HA@BCP group than in the BCP@HA or pure HA or BCP groups. From histological analysis, we discovered that the new bone tissue in the HA@BCP group was invading from the surface to the inside of the granules, and most of the bioceramic phase was replaced by the new bone. A higher degree of vascularization at the defect region repaired by HA@BCP was revealed by 3D microvascular perfusion angiography in terms of a higher vessel volume fraction. The current study demonstrated that the core−shell structured HA@BCP bioceramic granules could be a promising candidate for bone defect repair.

BackgroundJuvenile idiopathic arthritis (JIA) is the most common rheumatic disease in children, and its pathogenesis is still unclear. Genome-wide association studies (GWASs) of JIA have identified hundreds of risk factors, but few of them implicated specific biological mechanisms.MethodsA cross-tissue transcriptome-wide association study (TWAS) was performed with the functional summary-based imputation software (FUSION) tool based on GWAS summary datasets (898 JIA patients and 346,102 controls from BioBank Japan (BBJ)/FinnGen). The gene expression reference weights of skeletal muscle and the whole blood were obtained from the Genotype-Tissue Expression (GTExv8) project. JIA-related genes identified by TWAS findings genes were further compared with the differentially expressed genes (DEGs) identified by the mRNA expression profile of JIA from the Gene Expression Omnibus (GEO) database (accession number: GSE1402). Last, candidate genes were analyzed using functional enrichment and annotation analysis by Metascape to examine JIA-related gene sets.ResultsThe TWAS identified 535 significant genes with P < 0.05 and contains 350 for Asian and 195 for European (including 10 genes both expressed in Asian and European), such as CDC16 (P = 1.72E-03) and PSMD5-AS1 (P = 3.65E-02). Eight overlapping genes were identified based on TWAS results and DEGs of JIA patients, such as SIRPB1 (PTWAS = 4.21E-03, PDEG = 1.50E-04) and FRAT2 (PTWAS = 2.82E-02, PDEG = 1.43E-02). Pathway enrichment analysis of TWAS identified 183 pathways such as cytokine signaling in the immune system and cell adhesion molecules. By integrating the results of DEGs pathway and process enrichment analyses, 19 terms were identified such as positive regulation of T-cell activation.ConclusionBy conducting two populations TWAS, we identified a group of JIA-associated genes and pathways, which may provide novel clues to uncover the pathogenesis of JIA.

Objective To identify novel candidate genes whose expression is associated with bone mineral density (BMD) and body lean mass (LM) in children. Methods A tissue-specific transcriptome-wide association study (TWAS) was conducted utilizing a large-scale genome-wide association study (GWAS) dataset associated with BMD and LM and involving 10,414 participants. The measurement of BMD and LM phenotypes was made based on total-body dual-energy X-ray absorptiometry (TB-DXA) scans. TWAS was conducted by using FUSION software. Reference panels for muscle skeleton (MS), peripheral blood (NBL) and whole blood (YBL) were used for TWAS analysis. Functional enrichment and protein–protein interaction (PPI) analyses of the genes identified by TWAS were performed by using the online tool Metascape (http://metascape.org). Results For BMD, we identified 174 genes with P < 0.05, such as IKZF1 (P = 1.46 × 10−9) and CHKB (P = 8.31 × 10−7). For LM, we identified 208 genes with P < 0.05, such as COPS5 (P = 3.03 × 10−12) and MRPS33 (P = 5.45 × 10−10). Gene ontology (GO) enrichment analysis of the BMD-associated genes revealed 200 GO terms, such as protein catabolic process (Log P = −5.09) and steroid hormone-mediated signaling pathway (Log P = −3.13). GO enrichment analysis of the LM-associated genes detected 287 GO terms, such as the apoptotic signaling pathway (Log P = −8.08) and lipid storage (Log P = −3.55). Conclusion This study identified several candidate genes for BMD and LM in children, providing novel clues to the genetic mechanisms underlying the development of childhood BMD and LM.

Objectives Red blood cell distribution width (RDW) with prognosis in various infectious diseases. For fractured patients admitted to the intensive care units (ICU), an accurate and fast appraisal is essential. To investigate the association between RDW and prognosis in fractured patients admitted to the ICU utilizing the MIMIC‐III database. Methods A retrospective cohort from the MIMIC III database from 2001 and 2012 was constructed. RDW and other information were collected with in‐hospital mortality as the primary outcome and 90‐day mortality and hospital and intensive care unit (ICU) length of stay (LOS) as secondary outcomes. Univariate and multivariate logistic regression models with propensity score inverse probability of treatment weighting (IPTW) were used to investigate the prognostic value of RDW. A nomogram was built with significant prognostic factors to predict in‐hospital mortality, and the performance of the nomogram was evaluated and compared with other severity assessment scores. Subgroup analysis was also conducted. Results A total of 2721 fracture patients admitted to the ICU were identified. After IPTW, the group with higher RDW was significantly associated with elevated in‐hospital mortality (odds ratio [OR]: 1.68, 95% confidence interval [CI]: 1.19–2.37), 90‐day mortality (OR: 1.39, 95% CI: 1.04–1.86), prolonged hospital LOS (OR: 1.25, 95% CI: 1.03–1.50), and ICU LOS significantly (OR: 1.26, 95% CI: 1.05–1.53) in the multivariate logistics model. The nomogram showed optimal discriminative ability and predictive accuracy with an area under the receiver operating characteristic curve of 0.77. Conclusion RDW independently predicted in‐hospital mortality, 90‐day mortality, and hospital and ICU LOS in fractured patients admitted to ICU. The nomogram including RDW could also be a promising tool with potential clinical benefits.