Effects of circulating inflammatory proteins on osteoporosis and fractures: evidence from genetic correlation and Mendelian randomization study.

Objective: There is a controversy in studies of circulating inflammatory proteins (CIPs) in association with osteoporosis (OP) and fractures, and it is unclear if these two conditions are causally related. This study used MR analyses to investigate the causal associations between 91 CIPs and OP and 9 types of fractures. Methods: Genetic variants data for CIPs, OP, and fractures were obtained from the publicly available genome-wide association studies (GWAS) database. We used inverse variance weighted (IVW) as the primary analysis, pleiotropy, and heterogeneity tests to analyze the validity and robustness of causality and reverse MR analysis to test for reverse causality. Results: The IVW results with Bonferroni correction indicated that CXCL11 (OR = 1.2049; 95% CI: 1.0308-1.4083; P = 0.0192) can increase the risk of OP; IL-4 (OR = 1.2877; 95% CI: 1.1003-1.5070; P = 0.0016), IL-7 (OR = 1.2572; 95% CI: 1.0401-1.5196; P = 0.0180), IL-15RA (OR = 1.1346; 95% CI: 1.0163-1.2668; P = 0.0246), IL-17C (OR = 1.1353; 95% CI: 1.0272-1.2547; P = 0.0129), CXCL10 (OR = 1.2479; 95% CI: 1.0832-1.4377; P = 0.0022), eotaxin/CCL11 (OR = 1.1552; 95% CI: 1.0525-1.2678; P = 0.0024), and FGF23 (OR = 1.9437; 95% CI: 1.1875-3.1816; P = 0.0082) can increase the risk of fractures; whereas IL-10RB (OR = 0.9006; 95% CI: 0.8335-0.9730; P = 0.0080), CCL4 (OR = 0.9101; 95% CI: 0.8385-0.9878; P = 0.0242), MCP-3/CCL7 (OR = 0.8579; 95% CI: 0.7506-0.9806; P = 0.0246), IFN-γ [shoulder and upper arm (OR = 0.7832; 95% CI: 0.6605-0.9287; P = 0.0049); rib(s), sternum and thoracic spine (OR = 0.7228; 95% CI: 0.5681-0.9197; P = 0.0083)], ß-NGF (OR = 0.8384; 95% CI: 0.7473-0.9407; P = 0.0027), and SIRT2 (OR = 0.5167; 95% CI: 0.3296-0.8100; P = 0.0040) can decrease fractures risk. Conclusion: Mendelian randomization (MR) analyses indicated the causal associations between multiple genetically predicted CIPs and the risk of OP and fractures.

Enhanced osteoporotic fracture prediction in postmenopausal women using Bayesian optimization of machine learning models with genetic risk score.

This study aimed to enhance the fracture risk prediction accuracy in major osteoporotic fractures (MOFs) and hip fractures (HFs) by integrating genetic profiles, machine learning (ML) techniques, and Bayesian optimization. The genetic risk score (GRS), derived from 1,103 risk single nucleotide polymorphisms (SNPs) from genome-wide association studies (GWAS), was formulated for 25,772 postmenopausal women from the Women's Health Initiative dataset. We developed four ML models: Support Vector Machine (SVM), Random Forest, XGBoost, and Artificial Neural Network (ANN) for binary fracture outcome and 10-year fracture risk prediction. GRS and FRAX clinical risk factors (CRFs) were used as predictors. Death as a competing risk was accounted for in ML models for time-to-fracture data. ML models were subsequently fine-tuned through Bayesian optimization, which displayed marked superiority over traditional grid search. Evaluation of the models' performance considered an array of metrics such as accuracy, weighted F1 Score, the area under the precision-recall curve (PRAUC), and the area under the receiver operating characteristic curve (AUC) for binary fracture predictions, and the C-index, Brier score, and dynamic mean AUC over a 10-year follow-up period for fracture risk predictions. We found that GRS-integrated XGBoost with Bayesian optimization is the most effective model, with an accuracy of 91.2% (95% CI: 90.4-92.0%) and an AUC of 0.739 (95% CI: 0.731-0.746) in MOF binary predictions. For 10-year fracture risk modeling, the XGBoost model attained a C-index of 0.795 (95% CI: 0.783-0.806) and a mean dynamic AUC of 0.799 (95% CI: 0.788-0.809). Compared to FRAX, the XGBoost model exhibited a categorical net reclassification improvement (NRI) of 22.6% (P = .004). A sensitivity analysis, which included BMD but lacked GRS, reaffirmed these findings. Furthermore, portability tests in diverse non-European groups, including Asians and African Americans, underscored the model's robustness and adaptability. This study accentuates the potential of combining genetic insights and optimized ML in strengthening fracture predictions, heralding new preventive strategies for postmenopausal women.

This study presents a novel method for improving osteoporotic fracture predictions in postmenopausal women. By integrating genetic risk scores from genome wide association studies with established clinical risk factors and employing advanced machine learning techniques like Support Vector Machine, Random Forest, XGBoost, and Artificial Neural Networks, we analyze data from over 25,000 Women's Health Initiative participants. Our findings show that incorporating genetic risk scores significantly boosts predictive accuracy. The XGBoost model, optimized with Bayesian methods, outperforms existing algorithms. This approach underscores the value of genetic data in clinical evaluations and advances the personalized management of osteoporosis. It enables more accurate risk stratification and the development of tailored preventive strategies, likely reducing osteoporotic fractures among postmenopausal women and setting a new standard for future precision-based interventions.

Association between circHIPK3/miR-378a-3p/HDAC4 axis and osteoporotic fractures: A comprehensive investigation.

BACKGROUND: Osteoporotic fractures (OFs) are a significant public health issue, which can lead to pain and impaired mobility. The underlying mechanisms of OFs remain unclear, but recent studies have suggested that the circRNA-miRNA-mRNA pathway may play a crucial role. PURPOSE: This study aimed to investigate the potential involvement of the circHIPK3/miR-378a-3p/HDAC4 pathway in the pathogenesis of OFs. METHODS: We collected tissue and serum samples from 10 patients with OFs and 10 healthy controls. The expression levels of circHIPK3, miR-378a-3p, and HDAC4 were measured by qPCR and WB. Additionally, we quantified the serum levels of bone metabolism-related indicators (ALP, OC, TRAP, OCIF, ODF) using ELISA. RESULTS: Our results revealed significant upregulation of circHIPK3 and HDAC4 in both tissue and serum samples from OF patients compared with controls. Simultaneously, we detected a lower expression level of miR-378a-3p in OF tissues and serum than that in the control group. Furthermore, the serum levels of bone metabolism-related indicators ALP, TRAP, OCIF, and ODF were significantly higher in OF patients than in the control group. Interestingly, the serum level of OCIF was lower in OF patients than in the control group. CONCLUSION: Our study provides important evidence for the involvement of the circHIPK3/miR-378a-3p/HDAC4 pathway in the pathogenesis of OFs. The upregulation of circHIPK3 and HDAC4 and downregulation of miR-378a-3p observed in OF patients suggests their potential regulatory effects on bone metabolism. Meanwhile, abnormal expression of serum bone metabolism-related indicators may contribute to the development of OFs by disrupting the balance of bone remodeling.

Utilize polygenic risk score to enhance fracture risk estimation and improve the performance of FRAX in patients with osteoporosis.

This study examined the use of polygenic risk scores (PGS) in combination with the Fracture Risk Assessment Tool (FRAX) to enhance fragility fractures risk estimation in osteoporosis patients. Analyzing data from over 57,000 participants, PGS improved fracture risk estimation, especially for individuals with intermediate to low risks, allowing personalized preventive strategies. INTRODUCTION: Osteoporosis and fragility fractures are multifactorial, with contributions from both clinical and genetic determinants. However, whether using polygenic risk scores (PGS) may enhance the risk estimation of osteoporotic fracture in addition to Fracture Risk Assessment Tool (FRAX) remains unknown. This study investigated the collective association of PGS and FRAX with fragility fracture. METHODS: We conducted a cohort study from the Taiwan Precision Medicine Initiative (TPMI) at Taichung Veterans General Hospital, Taiwan. Genotyping was performed to compute PGS associated with bone mineral density (BMD). Phenome-wide association studies were executed to pinpoint phenotypes correlated with the PGS. Logistic regression analysis was conducted to ascertain factors associated with osteoporotic fractures. RESULTS: Among all 57,257 TPMI participants, 3744 (904 men and 2840 women, with a mean age of 66.7) individuals had BMD testing, with 540 (14.42%) presenting with fractures. The 3744 individuals who underwent BMD testing were categorized into four quartiles (Q1-Q4) based on PGS; 540 (14.42%) presented with fractures. Individuals with PGS-Q1 exhibited lower BMD, a higher prevalence of major fractures, and elevated FRAX-major and FRAX-hip than those with PGS-Q4. PGS was associated with major fractures after adjusting age, sex, and FRAX scores. Notably, the risk of major fractures (PGS-Q1 vs. Q4) was significantly higher in the subgroups of FRAX-major scores < 10% and 10-20%, but not in participants with a FRAX-major score ≧ 20%. CONCLUSIONS: Our study highlights the potential of PGS to augment fracture risk estimation in conjunction with FRAX, particularly in individuals with middle to low risks. Incorporating genetic testing could empower physicians to tailor personalized preventive strategies for osteoporosis.

Identifying Rare Genetic Determinants for Improved Polygenic Risk Prediction of Bone Mineral Density and Fracture Risk.

Osteoporosis and fractures severely impact the elderly population. Polygenic risk scores for bone mineral density have demonstrated potential clinical utility. However, the value of rare genetic determinants in risk prediction has not been assessed. With whole-exome sequencing data from 436,824 UK Biobank participants, we assigned White British ancestry individuals into a training data set (n = 317,434) and a test data set (n = 74,825). In the training data set, we developed a common variant-based polygenic risk score for heel ultrasound speed of sound (SOS). Next, we performed burden testing to identify genes harboring rare determinants of bone mineral density, targeting influential rare variants with predicted high deleteriousness. We constructed a genetic risk score, called ggSOS, to incorporate influential rare variants in significant gene burden masks into the common variant-based polygenic risk score. We assessed the predictive performance of ggSOS in the White British test data set, as well as in populations of non-White British European (n = 18,885), African (n = 7165), East Asian (n = 2236), South Asian (n = 9829), and other admixed (n = 1481) ancestries. Twelve genes in pivotal regulatory pathways of bone homeostasis harbored influential rare variants associated with SOS (p < 5.5 × 10-7 ), including AHNAK, BMP5, CYP19A1, FAM20A, FBXW5, KDM5B, KREMEN1, LGR4, LRP5, SMAD6, SOST, and WNT1. Among 4013 (5.4%) individuals in the test data set carrying these variants, a one standard deviation decrease in ggSOS was associated with 1.35-fold (95% confidence interval [CI] 1.16-1.57) increased hazard of major osteoporotic fracture. However, compared with a common variant-based polygenic risk score (C-index = 0.641), ggSOS had only marginally improved prediction accuracy in identifying at-risk individuals (C-index = 0.644), with overlapping confidence intervals. Similarly, ggSOS did not demonstrate substantially improved predictive performance in non-European ancestry populations. In summary, modeling the effects of rare genetic determinants may assist polygenic prediction of fracture risk among carriers of influential rare variants. Nonetheless, improved clinical utility is not guaranteed for population-level risk screening. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

CYP2C19 genotypes and osteoporotic fractures in long-term users of proton pump inhibitors: A hospital-based study.

Proton pump inhibitors (PPIs) are commonly prescribed medications. The existing data suggest that individuals at a high risk of fractures have been exposed to high doses of PPIs for prolonged durations. CYP2C19 plays a pivotal role in metabolism of PPIs and thereby influences their pharmacokinetic profile. Hence, we hypothesize that CYP2C19 genotypes may be associated with fragility fracture among PPIs users due to PPI exposure. This study aimed to investigate the association between CYP2C19 genotypes, bone mineral density (BMD), and osteoporotic fracture in a hospital-based population. This retrospective cohort study enrolled patients who were prescribed long-term PPIs at Taichung Veterans General Hospital using data extracted from the Taiwan Precision Medicine Initiative between January 2010 and April 2021. Associations between CYP2C19 phenotypes, comorbidities, and fractures in PPI users were analyzed. We enrolled 1518 long-term PPI users; 571 (38%), 727 (48%), and 220 (14%) CYP2C19 normal metabolizers (NMs), intermediate metabolizers (IMs), and poor metabolizers (PMs), respectively. Among them, 49 (3.2%) patients developed fractures within the 1-year follow-up period; 20 (3.5%) fractures in NMs, 24 (3.3%) in IMs, and 5 (2.3%) in PMs, respectively. No significant difference was observed among CYP2C19 genotypes and fracture. Additionally, BMD measurements during the 1-year follow-up period were made available among 75 participants. No significant difference in BMD between CYP2C19 PMs and non-PMs was found. This real-world, hospital-based study concludes that CYP2C19 PMs/IMs are not associated with an increased risk for fractures or reduced BMD in individuals on long-term PPI therapy.

Association of PFN1 Gene Polymorphisms with Bone Mineral Density, Bone Turnover Markers, and Osteoporotic Fractures in Chinese Population.

Recent studies have discovered an association between the PFN1 gene and Paget's disease. However, it is currently unknown whether the PFN1 gene is related to osteoporosis. This study was performed to investigate the association of Single-Nucleotide Polymorphisms (SNPs) in the PFN1 gene with Bone Mineral Density (BMD) as well as bone turnover markers and osteoporotic fractures in Chinese subjects. A total of 2836 unrelated Chinese subjects comprising 1247 healthy subjects and 1589 osteoporotic fractures patients (Fracture group) were enrolled in this study. Seven tagSNPs (rs117337116, rs238243, rs6559, rs238242, rs78224458, rs4790714, and rs13204) of the PFN1 gene were genotyped. The BMD of the lumbar spine 1-4 (L1-4), femoral neck, and total hip as well as bone turnover markers, such as ß-C-Terminal telopeptide of type 1 collagen (ß-CTX) and Procollagen type 1 N-terminal Propeptide (P1NP), were measured. The association between 7 tagSNPs and BMD and bone turnover markers was analyzed in 1247 healthy subjects only. After age matching, we selected 1589 osteoporotic fracture patients (Fracture group) and 756 nonfracture controls (Control group, selected from 1247 healthy subjects) for a case-control study, respectively. For the case-control study, we used logistic regression to investigate the relationship between 7 tagSNPs and osteoporotic fractures risk. In the All group, the PFN1 haplotype GAT was associated with the ß-CTX (P = 0.007). In the Female group, the PFN1 haplotype GAT was associated with the ß-CTX (P = 0.005). In the Male group, the rs13204, the rs78224458, and the PFN1 haplotype GAC were associated with the BMD of the L1-4 (all P = 0.012); the rs13204, the rs78224458, and the PFN1 haplotype GAC were associated with the BMD of the femoral neck (all P = 0.012); the rs13204 and rs78224458 were associated with the BMD of the total hip (both P = 0.015); and the PFN1 haplotype GAT was associated with the ß-CTX (P = 0.013). In the subsequent case-control study, the rs13204 and rs78224458 in the male group were associated with the risk of L1-4 fracture (P = 0.016 and 0.010, respectively) and total hip fracture (P = 0.013 and 0.016, respectively). Our study reveals that PFN1 gene polymorphisms are associated with BMD in Chinese males and ß-CTX in Chinese people and confirmed the relationship between PFN1 gene polymorphisms and Chinese male osteoporotic fractures in a case-control study.

A genome-wide genomic score added to standard recommended stratification tools does not improve the identification of patients with very low bone mineral density.

The role of integrating genomic scores (GSs) needs to be assessed. Adding a GS to recommended stratification tools does not improve the prediction of very low bone mineral density. However, we noticed that the GS performed equally or above individual risk factors in discrimination. PURPOSE: We aimed to investigate whether adding a genomic score (GS) to recommended stratification tools improves the discrimination of participants with very low bone mineral density (BMD). METHODS: BMD was measured in three thoracic vertebrae using CT. All participants provided information on standard osteoporosis risk factors. GSs and FRAX scores were calculated. Participants were grouped according to mean BMD into very low (<80 mg/cm3), low (80-120 mg/cm3), and normal (>120 mg/cm3) and according to the Bone Health and Osteoporosis Foundation recommendations for BMD testing into an "indication for BMD testing" and "no indication for BMD testing" group. Different models were assessed using the area under the receiver operating characteristics curves (AUC) and reclassification analyses. RESULTS: In the total cohort (n=1421), the AUC for the GS was 0.57 (95% CI 0.52-0.61) corresponding to AUCs for osteoporosis risk factors. In participants without indication for BMD testing, the AUC was 0.60 (95% CI 0.52-0.69) above or equal to AUCs for osteoporosis risk factors. Adding the GS to a clinical risk factor (CRF) model resulted in AUCs not statistically significant from the CRF model. Using probability cutoff values of 6, 12, and 24%, we found no improved reclassification or risk discrimination using the CRF-GS model compared to the CRF model. CONCLUSION: Our results suggest adding a GS to a CRF model does not improve prediction. However, we noticed that the GS performed equally or above individual risk factors in discrimination. Clinical risk factors combined showed superior discrimination to individual risk factors and the GS, underlining the value of combined CRFs in routine clinics as a stratification tool.

Validation of a genome-wide polygenic score in improving fracture risk assessment beyond the FRAX tool in the Women's Health Initiative study.

BACKGROUND: Previous study has established two polygenic scores (PGSs) related to femoral neck bone mineral density (BMD) (PGS_FNBMDldpred) and total body BMD (PGS_TBBMDldpred) that are associated with fracture risk. However, these findings have not yet been externally validated in an independent cohort. OBJECTIVES: This study aimed to validate the predictive performance of the two established PGSs and to investigate whether adding PGSs to the Fracture Risk Assessment Tool (FRAX) improves the predictive ability of FRAX in identifying women at high risk of major osteoporotic fracture (MOF) and hip fractures (HF). METHODS: The study used the Women's Health Initiative (WHI) cohort of 9,000 postmenopausal women of European ancestry. Cox Proportional Hazard Models were used to assess the association between each PGS and MOF/HF risk. Four models were formulated to investigate the effect of adding PGSs to the FRAX risk factors: (1) Base model: FRAX risk factors; (2) Base model + PGS_FNBMDldpred; (3) Base model + PGS_TBBMDldpred; (4) Base model + metaPGS. The reclassification ability of models with PGS was further assessed using the Net Reclassification Improvement (NRI) and the Integrated discrimination improvement (IDI). RESULTS: The study found that the PGSs were not significantly associated with MOF or HF after adjusting for FRAX risk factors. The FRAX base model showed moderate discrimination of MOF and HF, with a C-index of 0.623 (95% CI, 0.609 to 0.641) and 0.702 (95% CI, 0.609 to 0.718), respectively. Adding PGSs to the base FRAX model did not improve the ability to discriminate MOF or HF. Reclassification analysis showed that compared to the model without PGS, the model with PGS_TBBMDldpred (1.2%, p = 0.04) and metaPGS (1.7%, p = 0.05) improve the reclassification of HF, but not MOF. CONCLUSIONS: The findings suggested that incorporating genetic information into the FRAX tool has minimal improvement in predicting HF risk for elderly Caucasian women. These results highlight the need for further research to identify other factors that may contribute to fracture risk in elderly Caucasian women.

Mendelian randomization analysis does not reveal a causal influence of mental diseases on osteoporosis.

Introduction: Osteoporosis (OP) is primarily diagnosed through bone mineral density (BMD) measurements, and it often leads to fracture. Observational studies suggest that several mental diseases (MDs) may be linked to OP, but the causal direction of these associations remain unclear. This study aims to explore the potential causal association between five MDs (Schizophrenia, Depression, Alzheimer's disease, Parkinson's disease, and Epilepsy) and the risk of OP. Methods: First, single-nucleotide polymorphisms (SNPs) were filtered from summary-level genome-wide association studies using quality control measures. Subsequently, we employed two-sample Mendelian randomization (MR) analysis to indirectly analyze the causal effect of MDs on the risk of OP through bone mineral density (in total body, femoral neck, lumbar spine, forearm, and heel) and fractures (in leg, arm, heel, spine, and osteoporotic fractures). Lastly, the causal effect of the MDs on the risk of OP was evaluated directly through OP. MR analysis was performed using several methods, including inverse variance weighting (IVW)-random effects, IVW-fixed effects, maximum likelihood, weighted median, MR-Egger regression, and penalized weighted median. Results: The results did not show any evidence of a causal relationship between MDs and the risk of OP (with almost all P values > 0.05). The robustness of the above results was proved to be good. Discussion: In conclusion, this study did not find evidence supporting the claim that MDs have a definitive impact on the risk of OP, which contradicts many existing observational reports. Further studies are needed to determine the potential mechanisms of the associations observed in observational studies.

Mutations in ARHGEF15 cause autosomal dominant hereditary cerebral small vessel disease and osteoporotic fracture.

Cerebral small vessel disease (CSVD) is a prominent cause of ischemic and hemorrhagic stroke and a leading cause of vascular dementia, affecting small penetrating vessels of the brain. Despite current advances in genetic susceptibility studies, challenges remain in defining the causative genes and the underlying pathophysiological mechanisms. Here, we reported that the ARHGEF15 gene was a causal gene linked to autosomal dominant inherited CSVD. We identified one heterozygous nonsynonymous mutation of the ARHGEF15 gene that cosegregated completely in two families with CSVD, and a heterozygous nonsynonymous mutation and a stop-gain mutation in two individuals with sporadic CSVD, respectively. Intriguingly, clinical imaging and pathological findings displayed severe osteoporosis and even osteoporotic fractures in all the ARHGEF15 mutation carriers. In vitro experiments indicated that ARHGEF15 mutations resulted in RhoA/ROCK2 inactivation-induced F-actin cytoskeleton disorganization in vascular smooth muscle cells and endothelial cells and osteoblast dysfunction by inhibiting the Wnt/ß-catenin signaling pathway in osteoblast cells. Furthermore, Arhgef15-e(V368M)1 transgenic mice developed CSVD-like pathological and behavioral phenotypes, accompanied by severe osteoporosis. Taken together, our findings provide strong evidence that loss-of-function mutations of the ARHGEF15 gene cause CSVD accompanied by osteoporotic fracture.

Exome-wide screening identifies novel rare risk variants for bone mineral density.

Bone mineral density (BMD) is an independent risk factor of osteoporosis-related fractures. We performed gene-based burden tests to assess the association between rare variants and BMD, and identified several BMD candidate genes. PURPOSE: BMD is highly heritable and a major predictor of osteoporotic fractures, but its genetic basis remains unclear. We aimed to identify rare risk variants contributing to BMD. METHODS: Utilizing the newly released UK Biobank 200,643 exome dataset, we conducted a gene-based exome-wide association study in males and females, respectively. First, 100,639 males and 117,338 females with BMD values were included in the polygenic risk scores (PRS) analysis. Among individuals with lower 30% PRS, cases were individuals with top 10% BMD, and individuals with bottom 10% BMD were the controls. Considering the effects of vitamin D (VD), individuals with the highest 30% VD concentration were selected for VD-BMD analysis. After quality control, 741 males and 697 females were included in the BMD analysis, and 717 males and 708 females were included in the VD-BMD analysis. The variants were annotated by ANNOVAR software, then BMD and VD-BMD qualified variants were imported into the SKAT R-package to perform gene-based burden tests, respectively. RESULTS: The gene-based burden test of the exonic variants identified genome-wide candidate associations in ANKRD18A (P = 1.60 × 10-5, PBonferroni adjust = 2.11 × 10-3), C22orf31 (P = 3.49 × 10-4, PBonferroni adjust = 3.17 × 10-2), and SPATC1L (P = 1.09 × 10-5, PBonferroni adjust = 8.80 × 10-3). For VD-BMD analysis, three genes were associated with BMD, such as NIPAL1 (P = 1.06 × 10-3, PBonferroni adjust = 3.91 × 10-2). CONCLUSIONS: Our study suggested that rare variants contribute to BMD, providing new sights for broadening the genetic structure of BMD.

Genome-wide polygenic risk score for major osteoporotic fractures in postmenopausal women using associated single nucleotide polymorphisms.

BACKGROUND: Osteoporosis is highly polygenic and heritable, with heritability ranging from 50 to 80%; most inherited susceptibility is associated with the cumulative effect of many common genetic variants. However, existing genetic risk scores (GRS) only provide a few percent predictive power for osteoporotic fracture. METHODS: We derived and validated a novel genome-wide polygenic score (GPS) comprised of 103,155 common genetic variants to quantify this susceptibility and tested this GPS prediction ability in an independent dataset (n = 15,776). RESULTS: Among postmenopausal women, we found a fivefold gradient in the risk of major osteoporotic fracture (MOF) (p < 0.001) and a 15.25-fold increased risk of severe osteoporosis (p < 0.001) across the GPS deciles. Compared with the remainder of the GPS distribution, the top GPS decile was associated with a 3.59-, 2.48-, 1.92-, and 1.58-fold increased risk of any fracture, MOF, hip fracture, and spine fracture, respectively. The top GPS decile also identified nearly twofold more high-risk osteoporotic patients than the top decile of conventional GRS based on 1103 conditionally independent genome-wide significant SNPs. Although the relative risk of severe osteoporosis for postmenopausal women at around 50 is relatively similar, the cumulative incident at 20-year follow-up is significantly different between the top GPS decile (13.7%) and the bottom decile (< 1%). In the subgroup analysis, the GPS transferability in non-Hispanic White is better than in other racial/ethnic groups. CONCLUSIONS: This new method to quantify inherited susceptibility to osteoporosis and osteoporotic fracture affords new opportunities for clinical prevention and risk assessment.

Correlations of IL-6 and TGF-ß Gene Polymorphisms and Expressions With Osteoporotic, Thoracolumbar, Vertebral Compression Fracture.

Context: Associations between genes and diseases manifest as the influence of gene expression on disease development as well as the impact of variations in the disease-related genes themselves. It's important to determine the genetic variations that can lead to compressed fractures of osteoporotic, thoracic lumbar vertebrae to develop personalized clinical methods to prevent or delay the disease's development. Objective: The study intended to explore the correlations between the gene polymorphisms and gene expressions of the interleukin-6 (IL-6) gene and the transforming growth factor-beta (TGF-ß) gene and osteoporotic, thoracolumbar, vertebral compression fracture. Design: The research team performed an observational study using data from medical records. Setting: The study took place at Xuzhou Medical University in Xuzhou, China. Participants: Participants were 200 patients with an osteoporotic, thoracolumbar, vertebral compression fracture who had been admitted to the hospital at the university between 2019 and 2021 prior to the study and 200 healthy people The research team divided the participants into two groups. The patients became participants in the disease group, and the healthy individuals became participants in the control group. Outcome Measures: The research team: (1) collected peripheral blood from the two groups, (2) extracted genomic deoxyribonucleic acids (DNAs) from karyocytes, (3) examined the IL-6 and TGF-ß gene polymorphisms, and (4) analyzed and correlated participants' clinical data with the gene polymorphisms and expressions. The team used a quantitative polymerase chain reaction (qPCR) to examine the expression levels of IL-6 and TGF-ß. Results: Compared to the control group, the disease group: (1) had allele distributions that were significantly different at the rs2069829 locus of the IL-6 gene (P < .001) and at the rs3087453 of the TGF-ß gene (P = .004); (2) had significantly higher frequencies of allele T at the rs2069829 locus of the IL-6 gene and of allele G at the rs3087453 locus of the TGF-ß gene; (3) had genotype distributions that were significantly different at the rs2069829 locus (P < .001) and the rs2069857 locus (P = .048) of the IL-6 gene and at the rs3087453 locus (P < .001) of the TGF-ß gene; (4) had frequencies that were significantly higher of the TT genotype at the rs2069829 locus, the CC genotype at the rs2069857 locus, and the GC genotype at the rs3087453 locus of the IL-6 gene and the TGF-ß gene; (5) had dominant models that were significantly different at the rs2069829 locus of the IL-6 gene (P = .009) and at rs3087453 locus of the TGF-ß gene (P = .026) and had a recessive model that was significantly different at the rs2069857 locus of the IL-6 gene (P = .040); (6) had significantly different haplotypes CC (P < .001) and TC (P < .001) at the rs2069829 locus and the rs2069857 locus of the IL-6 gene and a significantly different haplotype AC (P = .011) at the rs1800469 locus and the rs3087453 locus of the TGF-ß gene; (7) had an IL-6 gene polymorphism at the rs2069857 locus that was related to the expression of the IL-6 gene (P < .05) and an expression of the IL-6 gene for participants with the AA genotype that was significantly lower than for other genotypes; (8) had a TGF-ß gene polymorphism at the rs1800469 locus that was associated with the expression of the TGF-ß gene (P < .05), and an expression for participants with the GG genotype that was significantly higher than for other genotypes; (9) had an IL-6 gene polymorphism at the rs2069857 locus with an overt correlation with the genotype of osteoporotic, thoracolumbar, vertebral compression fracture (P < .001). Also, participants in the disease group with the genotype CC mainly had type 2 and 3 fractures, while those with genotype AA primarily had type 0 and 1 fractures. Conclusions: IL-6 and TGF-ß gene polymorphisms and expressions are significantly related to osteoporotic, thoracolumbar, vertebral compression fracture.

The clinical utility of the BMD-related comprehensive genome-wide polygenic score in identifying individuals with a high risk of osteoporotic fractures.

The potential of bone mineral density (BMD)-related genome-wide polygenic score (PGS) in identifying individuals with a high risk of fractures remains unclear. This study suggests that an efficient PGS enables the identification of strata with up to a 1.5-fold difference in fracture incidence. Incorporating PGS into clinical diagnosis is anticipated to increase the population-level screening benefits. PURPOSE: This study sought to construct genome-wide polygenic scores for femoral neck and total body BMD and to estimate their potential in identifying individuals with a high risk of osteoporotic fractures. METHODS: Genome-wide polygenic scores were developed and validated for femoral neck and total body BMD. We externally tested the PGSs, both by themselves and in combination with available clinical risk factors, in 455,663 European ancestry individuals from the UK Biobank. The predictive accuracy of the developed genome-wide PGS was also compared with previously published restricted PGS employed in fracture risk assessment. RESULTS: For each unit decrease in PGSs, the genome-wide PGSs were associated with up to 1.17-fold increased fracture risk. Out of four studied PGSs, [Formula: see text] (HR: 1.03; 95%CI 1.01-1.05, p = 0.001) had the weakest and the [Formula: see text] (HR: 1.17; 95%CI 1.15-1.19, p < 0.0001) had the strongest association with an incident fracture. In the reclassification analysis, compared to the FRAX base model, the models with [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] improved the reclassification of fracture by 1.2% (95% CI, 1.0 to 1.3%), 0.2% (95% CI, 0.1 to 0.3%), 1.4% (95% CI, 1.3 to 1.5%), and 2.2% (95% CI, 2.1 to 2.4%), respectively. CONCLUSIONS: Our findings suggested that an efficient PGS estimate enables the identification of strata with up to a 1.7-fold difference in fracture incidence. Incorporating PGS information into clinical diagnosis is anticipated to increase the benefits of screening programs at the population level.

Integrated Analysis of Crucial Genes and miRNAs Associated with Osteoporotic Fracture of Type 2 Diabetes.

Purpose: The aim of this study is to explore pathological mechanisms of bone fragility in type 2 diabetes mellitus (T2DM) patients. Methods: Identifying common genes for T2DM and osteoporosis by taking the intersection is shared by the Comparative Toxicogenomics Database (CTD), DISEASES, and GeneCards databases. The differentially expressed genes (DEGs) and the differentially expressed miRNAs (DEMs) were identified by analyzing the Gene Expression Omnibus (GEO) datasets (GSE35958, GSE43950, and GSE70318). FunRich and miRNet were applied to predict potential upstream transcription factors and downstream target genes of candidate DEMs, respectively. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore potential mechanisms using Metascape. Eventually, a miRNA-gene network was constructed by Cytoscape software. Results: 271 common targets and 35 common DEGs between T2DM and osteoporosis were screened out in the above databases, and a total of ten DEMs were obtained in the GSE70318. SP1 was predicted to potentially regulate most of the DEMs. Enrichment analysis showed the PI3K-Akt signaling pathway and AGE-RAGE signaling pathway in diabetic complications may play an important role in diabetic skeletal fragility. Two genes (NAMPT and IGFBP5) were considered as key genes involving in the development of diabetic osteoporosis. Through the construction of the miRNA-gene network, most of the hub genes were found to be potentially modulated by miR-96-5p and miR-7-5p. Conclusion: The study uncovered several important genes, miRNAs, and pathological mechanisms involved in diabetic skeletal fragility, among which the PI3K-Akt signaling pathway and AGE-RAGE signaling pathway in diabetic complications may play important roles.

Identifying Causes of Fracture Beyond Bone Mineral Density: Evidence From Human Genetics.

New therapies may help to prevent osteoporotic fractures other than through increasing bone mineral density (BMD). Because fracture risk has an important genetic component, we aim to identify loci increasing fracture risk that do not decrease BMD, using a recently-proposed structural equation model adapted to remove genetic influences of BMD on fracture risk. We used summary statistics of the largest genome-wide association studies (GWASs) for BMD and for fracture in these analyses. We next estimated the genetic correlation between the non-BMD or BMD-related genetic effects and other clinical risk factors for fracture. Last, based on white British participants in the UK Biobank, we conducted genetic risk score analyses to assess whether the aggregated genetic effects conferred increased major osteoporotic fracture risk. We found that only three loci affecting fracture risk exhibited genetic effects not mediated by BMD: SOST, CPED1-WNT16, and RSPO3, while these three loci simultaneously conferred BMD-related effects. No strong genetic associations between non-BMD or BMD-related effects and 16 clinical risk factors were observed. However, non-BMD effects might be genetic correlated with hip bone size. In the UK Biobank, a 1 standard deviation (1-SD) increase in the non-BMD genetic risk score conferred an odds ratio of 1.17 for incident major osteoporotic fracture, compared to 1.29 by a BMD-related genetic risk score. Our study suggests that the majority of common genetic predisposition toward fracture risk acts upon BMD. Although non-BMD genetic effects may exist, they are not strongly correlated with most traditional clinical risk factors. Risk loci harboring non-BMD genetic effects may influence other perspectives of bone quality, or confer effects that existing GWASs fail to capture, but they demonstrate weaker impact on fracture risk than BMD-related genetic effects. These findings suggest that most successful drug development programs for osteoporosis should focus on pathways identified through BMD-associated loci. © 2022 American Society for Bone and Mineral Research (ASBMR).

Circulating MicroRNAs as Biomarkers of Osteoporosis and Fragility Fractures.

CONTEXT: Measurement of circulating microRNAs (miRNAs) as potential biomarkers of fragility fracture risk has recently become a subject of investigation. OBJECTIVE: Measure by next-generation sequencing (NGS), global miRNA expression in serum samples of osteoporotic subjects vs individuals with normal bone mineral density (BMD). DESIGN: Samples were collected from patients with different bone phenotypes and/or fragility fractures who did not receive any antiresorptive and/or bone-forming drug at the time of blood collection. SETTING: Samples and data were collected at 7 medical centers in Italy. PATIENTS: NGS prescreening: 50 osteoporotic patients vs 30 individuals with normal BMD. Droplet digital polymerase chain reaction (ddPCR) validation: 213 patients with different bone phenotypes, including the NGS-analyzed cohort. RESULTS: NGS identified 5 miRNAs (miR-8085, miR-320a-3p, miR-23a-3p, miR-4497, miR-145-5p) differentially expressed in osteoporosis cases without fractures vs controls. ddPCR validation confirmed lower c-miR-23a-3p expression in osteoporotic patients, with or without fracture, than in osteopenic and normal subjects and increased c-miR-320a-3p expression in osteoporotic patients with fracture and lower expression in osteoporotic patients without fracture. ddPCR analysis showed a significantly increased expression of miR-21-5p in osteoporotic patients, with or without fracture, than in osteopenic and normal subjects, not evidenced by the NGS prescreening. DISCUSSION: Our study confirmed levels of c-miR-23a-3p and c-miR-21-5p as able to distinguish osteoporotic patients and subjects with normal BMD. Increased levels of c-miR-320a-3p specifically associated with fractures, independently by BMD, suggesting c-miR-320a-3p as a prognostic indicator of fracture risk in osteoporotic patients, to be confirmed in prospective studies on incident fractures.

Causal associations of circulating adiponectin with cardiometabolic diseases and osteoporotic fracture.

Circulating adiponectin shows some relationships with the occurrence of cardiometabolic diseases and osteoporotic fracture, but little is known about their causal associations. This two-sample Mendelian randomization (MR) study aims to explore the causal roles of circulating adiponectin in cardiometabolic diseases and osteoporotic fracture. We used 15 single nucleotide polymorphisms associated with circulating adiponectin as the instrumental variables. Inverse variance weighted, weighted median and MR-Egger regression methods were applied to study the causal associations. The results found that high circulating adiponectin was causally associated with reduced risk of type 2 diabetes (beta-estimate: -0.030, 95% CI: -0.048 to -0.011, SE: 0.009, P-value = 0.002) and may be the risk factor of coronary artery disease (beta-estimate: 0.012, 95% CI: 0.001 to 0.023, SE: 0.006, P-value = 0.030). No causal associations were seen between circulating adiponectin and other outcomes including heart failure, atrial fibrillation, cerebral ischemia, intracerebral hemorrhage or osteoporotic fracture. This study found the potential causal roles of high circulating adiponectin in reduced risk of type 2 diabetes and increased risk of coronary artery disease, which may help prevent and treat these two diseases.

Serum Periostin Level and Genetic Polymorphisms Are Associated with Vertebral Fracture in Chinese Postmenopausal Women.

PURPOSES: In order to investigate the association between serum periostin levels and the variation of its encoding gene POSTN and the prevalence of vertebral fractures and bone mineral density (BMD) in Chinese postmenopausal women, an association study was performed. MATERIALS AND METHODS: 385 postmenopausal women were recruited. For participants without a history of vertebral fracture, lateral X-rays of the spine covering the fourth thoracic spine to the fifth lumbar spine were performed to detect any asymptomatic vertebral fractures. Ten tag-single nucleotide polymorphisms (SNP) of POSTN were genotyped. Serum periostin levels, biochemical parameters, and BMD were measured individually. RESULTS: rs9603226 was significantly associated with vertebral fractures. Compared to allele G, the minor allele A carriers of rs9603226 had a 1.722-fold higher prevalence of vertebral fracture (p = 0.037). rs3923854 was significantly associated with the serum periostin level. G/G genotype of rs3923854 had a higher serum periostin level than C/C and C/G (67.26 ± 19.90 ng/mL vs. 54.57 ± 21.44 ng/mL and 54.34 ± 18.23 ng/mL). Furthermore, there was a negative correlation between the serum level of periostin and BMD at trochanter and total hip. CONCLUSION: Our study suggested that genetic variation of POSTN could be a predicting factor for the risk of vertebral fractures. The serum level of periostin could be a potential biochemical parameter for osteoporosis in Chinese postmenopausal women.