A Meta-Analysis of the Transferability of Bone Mineral Density Genetic Loci Associations From European to African Ancestry Populations

Annexin A family: A new perspective on the regulation of bone metabolism

Osteoblast-mediated bone formation and osteoclast-mediated bone resorption are critical processes in bone metabolism. Annexin A, a calcium-phospholipid binding protein, regulates the proliferation and differentiation of bone cells, including bone marrow mesenchymal stem cells, osteoblasts, and osteoclasts, and has gradually become a marker gene for the diagnosis of osteoporosis. As calcium channel proteins, the annexin A family members are closely associated with mechanical stress, which can target annexins A1, A5, and A6 to promote bone cell differentiation. Despite the significant clinical potential of annexin A family members in bone metabolism, few studies have reported on these mechanisms. Therefore, based on a review of relevant literature, this article elaborates on the specific functions and possible mechanisms of annexin A family members in bone metabolism to provide new ideas for their application in the prevention and treatment of bone diseases, such as osteoporosis.

Looking back on 30+ years of the Johnston County Osteoarthritis Project while looking forward with the Johnston County Health Study: A narrative review

Over the last 30 years, knowledge of the epidemiology of osteoarthritis (OA) has dramatically advanced, and Osteoarthritis and Cartilage has been on the forefront of disseminating research findings from large OA cohort studies, including the Johnston County OA Project (JoCoOA). The JoCoOA is a population-based, prospective longitudinal cohort that began roughly 30 years ago with a key focus on understanding prevalence, incidence, and progression of OA, as well as its risk factors, in a predominantly rural population of Black and White adults 45+ years old in a county in the southeastern United States. Selected OA results that will be discussed in this review include racial differences, lifetime risk, biomarkers, mortality, and OA risk factors. The new Johnston County Health Study will also be introduced. This new cohort study of OA and comorbid conditions builds upon current OA knowledge and JoCoOA infrastructure and is designed to reflect changes in demographics and urbanization in the county and the region.

A novel non-invasive method for predicting bone mineral density and fracture risk using demographic and anthropometric measures

Fractures are costly to treat and can significantly increase morbidity. Although dual-energy x-ray absorptiometry (DEXA) is used to screen at risk people with low bone mineral density (BMD), not all areas have access to one. We sought to create a readily accessible, inexpensive, high-throughput prediction tool for BMD that may identify people at risk of fracture for further evaluation. Anthropometric and demographic data were collected from 492 volunteers (♂275, ♀217; [44 ​± ​20] years; Body Mass Index (BMI) = [27.6 ​± ​6.0] kg/m2) in addition to total body bone mineral content (BMC, kg) and BMD measurements of the spine, pelvis, arms, legs and total body. Multiple-linear-regression with step-wise removal was used to develop a two-step prediction model for BMC followed by BMC. Model selection was determined by the highest adjusted R2, lowest error of estimate, and lowest level of variance inflation (α ​= ​0.05). Height (HTcm), age (years), sexm=1, f=0, %body fat (%fat), fat free mass (FFMkg), fat mass (FMkg), leg length (LLcm), shoulder width (SHWDTHcm), trunk length (TRNKLcm), and pelvis width (PWDTHcm) were observed to be significant predictors in the following two-step model (p ​< ​0.05). Step1: BMC (kg) = (0.006 3 × HT) ​+ ​(-0.002 4 × AGE) ​+ ​(0.171 2 × SEXm=1, f=0) ​+ ​(0.031 4 × FFM) ​+ ​(0.001 × FM) ​+ ​(0.008 9 × SHWDTH) ​+ ​(-0.014 5 × TRNKL) ​+ ​(-0.027 8 × PWDTH) - 0.507 3; R2 ​= ​0.819, SE ​± ​0.301. Step2: Total body BMD (g/cm2) = (-0.002 8 × HT) ​+ ​(-0.043 7 × SEXm=1, f=0) ​+ ​(0.000 8 × %FAT) ​+ ​(0.297 0 × BMC) ​+ ​(-0.002 3 × LL) ​+ ​(0.002 3 × SHWDTH) ​+ ​(-0.002 5 × TRNKL) ​+ ​(-0.011 3 × PWDTH) ​+ ​1.379; R2 ​= ​0.89, SE ​± ​0.054. Similar models were also developed to predict leg, arm, spine, and pelvis BMD (R2 ​= ​0.796-0.864, p ​< ​0.05). The equations developed here represent promising tools for identifying individuals with low BMD at risk of fracture who would benefit from further evaluation, especially in the resource or time restricted setting.

Mediating oxidative stress through the Palbociclib/miR-141-3p/STAT4 axis in osteoporosis: a bioinformatics and experimental validation study

Osteoporosis is a common bone disease characterized by loss of bone mass, reduced bone strength, and deterioration of bone microstructure. ROS-induced oxidative stress plays an important role in osteoporosis. However, the biomarkers and molecular mechanisms of oxidative stress are still unclear. We obtained the datasets from the Gene Expression Omnibus (GEO) database, and performed differential analysis, Venn analysis, and weighted correlation network analysis (WGCNA) analysis out the hub genes. Then, the correlation between inflammatory factors and hub genes was analyzed, and a Mendelian randomization (MR) analysis was performed on cytokines and osteoporosis outcomes. In addition, "CIBERSORT" was used to analyze the infiltration of immune cells and single-cell RNA-seq data was used to analyze the expression distribution of hub genes and cell-cell communications. Finally, we collected human blood samples for RT-qPCR and Elisa experiments, the miRNA-mRNA network was constructed using the miRBase database, the 3D structure was predicted using the RNAfold, Vfold3D database, and the drug sensitivity analysis was performed using the RNAactDrug database. We obtained three differentially expressed genes associated with oxidative stress: DBH, TAF15, and STAT4 by differential, WGCNA clustering, and Venn screening analyses, and further analyzed the correlation of these 3 genes with inflammatory factors and immune cell infiltration and found that STAT4 was significantly and positively correlated with IL-2. Single-cell data analysis showed that the STAT4 gene was highly expressed mainly in dendritic cells and monocytes. In addition, the results of RT-qPCR and Elisa experiments verified that the expression of STAT4 was consistent with the previous analysis, and a significant causal relationship between IL-2 and STAT4 SNPs and osteoporosis was found by Mendelian randomization. Finally, through miRNA-mRNA network and drug sensitivity analysis, we analyzed to get Palbociclib/miR-141-3p/STAT4 axis, which can be used for the prevention and treatment of osteoporosis. In this study, we proposed the Palbociclib/miR-141-3p/STAT4 axis for the first time and provided new insights into the mechanism of oxidative stress in osteoporosis.

Ethnic disparities in fracture risk assessment using polygenic scores

Whether the PGS developed using data from European ancestry is predictive of fracture risk for minorities remains unclear. This study demonstrated that PGSs based on common BMD-related genetic variants discovered in the European ancestry cohort are predictive of fracture risk in people of Asian but not African ancestry.

PURPOSE

Large-scale genome-wide association studies (GWAS) on bone mineral density (BMD) have been conducted predominantly in European cohorts. Genetic models based on common variants associated with BMD have been evaluated using almost exclusively European data, which could potentially exacerbate health disparities due to different linkage disequilibrium among different ethnic groups.

METHODS

UK Biobank (UKB) is a large-scale population-based observational study starting in 2006 that recruited 502,617 individuals aged between 40 and 69 years with genotypic and phenotypic data available. Based on the summary statistics of two GWAS studies of femoral neck BMD and total body BMD, we derived four PGSs and assessed the association between each PGS and prevalent/incident fractures within each ethnic group separately using Multivariate logistic regressions and Cox proportional hazard models. All models were adjusted for age, sex, and the first four principal components.

RESULTS

We assessed four PGSs derived from European cohorts. Significant associations were observed between PGSs and fracture in European and Asian cohorts but not in the African cohort. Of all four PGSs, [Formula: see text] performed the best. A standard deviation decreases in [Formula: see text] were associated with an increased hazard ratio (HR) of 1.24 (1.22-1.27), 1.28 (0.83-1.99), and 1.34 (1.10-1.64) in European, African, and Asian ancestry, respectively. A low BMD-related PGS is associated with up to 2.35- and 4.31-fold increased fracture risk in European and Asian populations.

CONCLUSIONS

These results showed that PGSs based on common BMD-related genetic variants discovered in the European ancestry cohort are predictive of fracture risk in people of Asian but not African ancestry.

Metabolome-Wide Mendelian Randomization Assessing the Causal Relationship Between Blood Metabolites and Bone Mineral Density

Mounting evidence has supported osteoporosis (OP) as a metabolic disorder. Recent metabolomics studies have discovered numerous metabolites related to bone mineral density (BMD). However, the causal effects of metabolites on BMD at distinct sites remained underexplored. Leveraging genome-wide association datasets, we conducted two-sample Mendelian randomization (MR) analyses to investigate the causal relationship between 486 blood metabolites and bone mineral density at five skeletal sites including heel (H), total body (TB), lumbar spine (LS), femoral neck (FN), and ultra-distal forearm (FA). Sensitivity analyses were performed to test the presence of the heterogeneity and the pleiotropy. To exclude the influences of reverse causation, genetic correlation, and linkage disequilibrium (LD), we further performed reverse MR, linkage disequilibrium regression score (LDSC), and colocalization analyses. In the primary MR analyses, 22, 10, 3, 7, and 2 metabolite associations were established respectively for H-BMD, TB-BMD, LS-BMD, FN-BMD, and FA-BMD at the nominal significance level (IVW, P < 0.05) and passing sensitivity analyses. Among these, one metabolite, androsterone sulfate showed a strong effect on four out of five BMD phenotypes (Odds ratio [OR] for H-BMD = 1.045 [1.020, 1.071]; Odds ratio [OR] for TB-BMD = 1.061 [1.017, 1.107]; Odds ratio [OR] for LS-BMD = 1.088 [1.023, 1.159]; Odds ratio [OR] for FN-BMD = 1.114 [1.054, 1.177]). Reverse MR analysis provided no evidence for the causal effects of BMD measurements on these metabolites. Colocalization analysis have found that several metabolite associations might be driven by shared genetic variants such as mannose for TB-BMD. This study identified some metabolites causally related to BMD at distinct sites and several key metabolic pathways, which shed light on predictive biomarkers and drug targets for OP.

STARD3NL inhibits the osteogenic differentiation by inactivating the Wnt/β‐catenin pathway via binding to Annexin A2 in osteoporosis

Osteoporosis is one of the leading forms of systemic diseases related to bone metabolism in the world. STARD3 N‐terminal like (STARD3NL) showed robust association with osteoporosis‐related traits. Yet, the molecular functional mechanisms of STARD3NL in osteoblasts is still obscure. In this study, we demonstrated a high level of STARD3NL expression in the bone tissues from the patients with low bone mass and ovariectomized (OVX)‐induced osteoporotic mice. We identified Stard3nl as a potent factor that negatively and positively regulates osteoblast differentiation and cell proliferation, respectively. Furthermore, inhibition of Stard3nl induced β‐catenin gene expression and the nuclear translocation of β‐catenin, as well as Wnt signalling activities, contributing to the activation of Wnt/β‐catenin signalling. Mechanistic studies revealed that Stard3nl bound with Annexin A2 (Anxa2) to suppress β‐catenin expression, resulting into the suppression of Wnt signalling and downstream osteogenic differentiation. Moreover, adeno‐associated virus 9 (AAV9)‐mediated silencing of Stard3nl reversed bone loss in OVX‐induced osteoporotic mice by the injection into the knee joints. Collectively, our study revealed that Stard3nl suppressed osteogenesis via binding with Anxa2, resulting into the inactivation of Wnt signalling. It also highlights the preventive and therapeutic potential of STARD3NL as a specific and novel target for osteoporotic patients.

Evolutionary Genetic Signatures of Selection on Bone-Related Variation within Human and Chimpanzee Populations

Bone strength and the incidence and severity of skeletal disorders vary significantly among human populations, due in part to underlying genetic differentiation. While clinical models predict that this variation is largely deleterious, natural population variation unrelated to disease can go unnoticed, altering our perception of how natural selection has shaped bone morphologies over deep and recent time periods. Here, we conduct the first comparative population-based genetic analysis of the main bone structural protein gene, collagen type I α 1 (COL1A1), in clinical and 1000 Genomes Project datasets in humans, and in natural populations of chimpanzees. Contrary to predictions from clinical studies, we reveal abundant COL1A1 amino acid variation, predicted to have little association with disease in the natural population. We also find signatures of positive selection associated with intron haplotype structure, linkage disequilibrium, and population differentiation in regions of known gene expression regulation in humans and chimpanzees. These results recall how recent and deep evolutionary regimes can be linked, in that bone morphology differences that developed among vertebrates over 450 million years of evolution are the result of positive selection on subtle type I collagen functional variation segregating within populations over time.

The Polygenic and Monogenic Basis of Paediatric Fractures

PURPOSE OF REVIEW

Fractures are frequently encountered in paediatric practice. Although recurrent fractures in children usually unveil a monogenic syndrome, paediatric fracture risk could be shaped by the individual genetic background influencing the acquisition of bone mineral density, and therefore, the skeletal fragility as shown in adults. Here, we examine paediatric fractures from the perspective of monogenic and complex trait genetics.

RECENT FINDINGS

Large-scale genome-wide studies in children have identified ~44 genetic loci associated with fracture or bone traits whereas ~35 monogenic diseases characterized by paediatric fractures have been described. Genetic variation can predispose to paediatric fractures through monogenic risk variants with a large effect and polygenic risk involving many variants of small effects. Studying genetic factors influencing peak bone attainment might help in identifying individuals at higher risk of developing early-onset osteoporosis and discovering drug targets to be used as bone restorative pharmacotherapies to prevent, or even reverse, bone loss later in life.