RESUMO
BACKGROUND: Osteoporosis (OP) is a high-incidence bone disease that is prone to osteoporotic fractures (OF), so it has attracted widespread attention. AIM: This study investigated the specific expression and role of miR-331 in patients with OP and OF. The findings have profound implications for the clinical prevention and treatment of these conditions. METHODS: The study included 60 OP patients, 46 OF patients, and 40 healthy controls. The expression level of miR-331-3p was detected using RT-qPCR. BMP2 was used to stimulate differentiation in MC3T3-E1 cells. After induction, the expression activity of osteogenic differentiation-related gene markers was detected using RT-qPCR. The target gene analysis was conducted using a luciferase reporter assay. RESULTS: The levels of miR-331-3p were significantly elevated, while NRP2 levels were significantly reduced in OF patients. Post-surgery, miR-331-3p levels decreased over time. MiR-331-3p was found to negatively regulate the luciferase activity of NPR2 in MC3T3-E1 cells. Furthermore, overexpression of miR-331-3p inhibited cell proliferation and decreased the levels of osteoblast differentiation markers. CONCLUSION: The up-regulation of miR-331-3p can promote OP and might also encourage the occurrence of OF by regulating NRP2. However, this needs further verification.
Assuntos
MicroRNAs , Neuropilina-2 , Osteoporose , Fraturas por Osteoporose , MicroRNAs/genética , Humanos , Fraturas por Osteoporose/genética , Fraturas por Osteoporose/metabolismo , Feminino , Osteoporose/genética , Osteoporose/metabolismo , Camundongos , Animais , Pessoa de Meia-Idade , Idoso , Neuropilina-2/genética , Neuropilina-2/metabolismo , Masculino , Diferenciação Celular/genética , Osteoblastos/metabolismo , Proliferação de Células/genética , Osteogênese/genética , Osteogênese/fisiologia , Expressão Gênica/genética , Regulação para CimaRESUMO
BACKGROUND: Fragility fracture is common in the elderly. Osteoblast differentiation is essential for bone healing and regeneration. Expression pattern of long non-coding RNA MIAT during fracture healing was examined, and its role in osteoblast differentiation was investigated. METHODS: 90 women with simple osteoporosis and 90 women with fragility fractures were included. Another 90 age-matched women were set as the control group. mRNA levels were tested using RT-qPCR. Cell viability was detected via CCK-8, and osteoblastic biomarkers, including ALP, OCN, Collagen I, and RUNX2 were tested via ELISA. The downstream miRNAs and genes targeted by MIAT were predicted by bioinformatics analysis, whose functions and pathways were annotated via GO and KEGG analysis. RESULTS: Serum MIAT was upregulated in osteoporosis women with high accuracy of diagnostic efficacy. Serum MIAT was even elevated in the fragility fracture group, but decreased in a time manner after operation. MIAT knockdown promoted osteogenic proliferation and differentiation of MC3T3-E1, but the influences were reversed by miR-181a-5p inhibitor. A total of 137 overlapping target genes of miR-181a-5p were predicted based on the miRDB, TargetScan and microT datasets, which were mainly enriched for terms related to signaling pathways regulating pluripotency of stem cells, cellular senescence, and osteoclast differentiation. CONCLUSIONS: LncRNA MIAT serves as a promising biomarker for osteoporosis, and promotes osteogenic differentiation via targeting miR-181a-5p.
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Biomarcadores , Diferenciação Celular , Consolidação da Fratura , Osteoblastos , RNA Longo não Codificante , RNA Longo não Codificante/genética , Humanos , Feminino , Biomarcadores/sangue , Biomarcadores/metabolismo , Consolidação da Fratura/genética , Consolidação da Fratura/fisiologia , Idoso , Diferenciação Celular/genética , Osteoblastos/metabolismo , Animais , Camundongos , MicroRNAs/genética , Osteoporose/genética , Osteoporose/metabolismo , Osteogênese/genética , Osteogênese/fisiologia , Pessoa de Meia-Idade , Fraturas por Osteoporose/genética , Proliferação de Células/genética , Regulação para CimaRESUMO
BACKGROUND: Osteoporotic vertebral compression fractures (OVCF) in the elderly increase refracture risk post-surgery, leading to higher mortality rates. Genome-wide association studies (GWAS) have identified susceptibility genes for osteoporosis, but the phenotypic variance explained by these genes has been limited, indicating the need to explore additional causal factors. Epigenetic modifications, such as DNA methylation, may influence osteoporosis and refracture risk. However, prospective cohorts for assessing epigenetic alterations in Chinese elderly patients are lacking. Here, we propose to conduct a prospective cohort study to investigate the causal network of DNA polymorphisms, DNA methylation, and environmental factors on the development of osteoporosis and the risk of refracture. METHODS: We will collect vertebral and peripheral blood from 500 elderly OVCF patients undergoing surgery, extract DNA, and generate whole genome genotype data and DNA methylation data. Observation indicators will be collected and combined with one-year follow-up data. A healthy control group will be selected from a natural population cohort. Epigenome-wide association studies (EWAS) of osteoporosis and bone mineral density will be conducted. Differential methylation analysis will compare candidate gene methylation patterns in patients with and without refracture. Multi-omics prediction models using genetic variants and DNA methylation sites will be built to predict OVCF risk. DISCUSSION: This study will be the first large-scale population-based study of osteoporosis and bone mineral density phenotypes based on genome-wide data, multi-time point methylation data, and phenotype data. By analyzing methylation changes related to osteoporosis and bone mineral density in OVCF patients, the study will explore the feasibility of DNA methylation in evaluating postoperative osteoporosis intervention effects. The findings may identify new molecular markers for effective anti-osteoporosis treatment and inform individualized prevention and treatment strategies. TRIAL REGISTRATION: chictr.org.cn ChiCTR2200065316, 02/11/2022.
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Metilação de DNA , Osteoporose , Fraturas por Osteoporose , Fraturas da Coluna Vertebral , Humanos , Estudos Prospectivos , Idoso , Feminino , Osteoporose/genética , Masculino , Fraturas por Osteoporose/genética , Fraturas da Coluna Vertebral/genética , Estudo de Associação Genômica Ampla , Densidade Óssea/genética , Fraturas por Compressão/genética , Pessoa de Meia-Idade , Epigênese Genética , Recidiva , Idoso de 80 Anos ou mais , China/epidemiologiaRESUMO
The novel metaPGS, integrating multiple fracture-related genetic traits, surpasses traditional polygenic scores in predicting fracture risk. Demonstrating a robust association with incident fractures, this metaPGS offers significant potential for enhancing clinical fracture risk assessment and tailoring prevention strategies. INTRODUCTION: Current polygenic scores (PGS) have limited predictive power for fracture risk. To improve genetic prediction, we developed and evaluated a novel metaPGS combining genetic information from multiple fracture-related traits. METHODS: We derived individual PGS from genome-wide association studies of 16 fracture-related traits and employed an elastic-net logistic regression model to examine the association between the 16 PGSs and fractures. An optimal metaPGS was constructed by combining 11 significant individual PGSs selected by the elastic regularized regression model. We evaluated the predictive power of the metaPGS alone and in combination with clinical risk factors recommended by guidelines. The discrimination ability of metaPGS was assessed using the concordance index. Reclassification was assessed using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). RESULTS: The metaPGS had a significant association with incident fractures (HR 1.21, 95% CI 1.18-1.25 per standard deviation of metaPGS), which was stronger than previously developed bone mineral density (BMD)-related individual PGSs. Models with PGS_FNBMD, PGS_TBBMD, and metaPGS had slightly higher but statistically non-significant c-index than the base model (0.640, 0.644, 0.644 vs. 0.638). However, the reclassification analysis showed that compared to the base model, the model with metaPGS improves the reclassification of fracture. CONCLUSIONS: The metaPGS is a promising approach for stratifying fracture risk in the European population, improving fracture risk prediction by combining genetic information from multiple fracture-related traits.
Assuntos
Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Herança Multifatorial , Fraturas por Osteoporose , Humanos , Medição de Risco/métodos , Estudo de Associação Genômica Ampla/métodos , Feminino , Masculino , Fraturas por Osteoporose/genética , Pessoa de Meia-Idade , Idoso , Polimorfismo de Nucleotídeo Único , Densidade Óssea/genética , Densidade Óssea/fisiologia , Fatores de Risco , AdultoRESUMO
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.
Assuntos
Estudo de Associação Genômica Ampla , Análise da Randomização Mendeliana , Osteoporose , Humanos , Osteoporose/genética , Osteoporose/sangue , Fraturas Ósseas/genética , Fraturas Ósseas/sangue , Fraturas Ósseas/epidemiologia , Polimorfismo de Nucleotídeo Único , Fator de Crescimento de Fibroblastos 23 , Predisposição Genética para Doença , Feminino , Fraturas por Osteoporose/genética , Fraturas por Osteoporose/sangue , Fraturas por Osteoporose/epidemiologiaRESUMO
PURPOSE OF REVIEW: The purpose of this review is to outline the principles of clinical genetic testing and to provide practical guidance to clinicians in navigating genetic testing for patients with suspected monogenic forms of osteoporosis. RECENT FINDINGS: Heritability assessments and genome-wide association studies have clearly shown the significant contributions of genetic variations to the pathogenesis of osteoporosis. Currently, over 50 monogenic disorders that present primarily with low bone mass and increased risk of fractures have been described. The widespread availability of clinical genetic testing offers a valuable opportunity to correctly diagnose individuals with monogenic forms of osteoporosis, thus instituting appropriate surveillance and treatment. Clinical genetic testing may identify the appropriate diagnosis in a subset of patients with low bone mass, multiple or unusual fractures, and severe or early-onset osteoporosis, and thus clinicians should be aware of how to incorporate such testing into their clinical practices.
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Densidade Óssea , Testes Genéticos , Osteoporose , Humanos , Osteoporose/genética , Densidade Óssea/genética , Estudo de Associação Genômica Ampla , Fraturas por Osteoporose/genética , Fraturas Ósseas/genética , Predisposição Genética para DoençaRESUMO
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.
Assuntos
Teorema de Bayes , Aprendizado de Máquina , Fraturas por Osteoporose , Pós-Menopausa , Idoso , Feminino , Humanos , Pessoa de Meia-Idade , Estratificação de Risco Genético , Estudo de Associação Genômica Ampla , Fraturas por Osteoporose/genética , Fraturas por Osteoporose/epidemiologia , Polimorfismo de Nucleotídeo Único , Pós-Menopausa/genética , Medição de RiscoRESUMO
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.
Assuntos
MicroRNAs , Fraturas por Osteoporose , Humanos , Histona Desacetilases/genética , Histona Desacetilases/metabolismo , MicroRNAs/genética , MicroRNAs/metabolismo , Fraturas por Osteoporose/genética , Proteínas Repressoras/genética , Proteínas Repressoras/metabolismo , Regulação para CimaRESUMO
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.
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Fraturas do Quadril , Osteoporose , Fraturas por Osteoporose , Masculino , Humanos , Feminino , Idoso , Estudos de Coortes , Fraturas do Quadril/epidemiologia , Osteoporose/epidemiologia , Osteoporose/genética , Fraturas por Osteoporose/epidemiologia , Fraturas por Osteoporose/genética , Fraturas por Osteoporose/prevenção & controle , Densidade Óssea/genética , Fatores de Risco , Medição de Risco , Absorciometria de FótonRESUMO
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).
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Osteoporose , Fraturas por Osteoporose , Humanos , Idoso , Densidade Óssea/genética , Predisposição Genética para Doença , Osteoporose/genética , Osteoporose/epidemiologia , Fraturas por Osteoporose/genética , Estratificação de Risco Genético , MineraisRESUMO
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.
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Fraturas por Osteoporose , Inibidores da Bomba de Prótons , Humanos , Fraturas por Osteoporose/induzido quimicamente , Fraturas por Osteoporose/epidemiologia , Fraturas por Osteoporose/genética , Estudos Retrospectivos , Citocromo P-450 CYP2C19/genética , Hospitais , GenótipoRESUMO
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.
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Osteoporose , Fraturas por Osteoporose , Humanos , Densidade Óssea , Osteoporose/diagnóstico , Osteoporose/genética , Fatores de Risco , Curva ROC , Genômica , Medição de Risco/métodos , Absorciometria de Fóton , Fraturas por Osteoporose/etiologia , Fraturas por Osteoporose/genéticaRESUMO
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.
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Densidade Óssea , Remodelação Óssea , Fraturas por Osteoporose , Feminino , Humanos , Masculino , Biomarcadores , Densidade Óssea/genética , Remodelação Óssea/genética , Estudos de Casos e Controles , População do Leste Asiático , Fraturas por Osteoporose/genética , Polimorfismo de Nucleotídeo Único/genética , Profilinas/genéticaRESUMO
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.
Assuntos
Fraturas do Quadril , Fraturas por Osteoporose , Humanos , Feminino , Idoso , Densidade Óssea/genética , Medição de Risco/métodos , Fraturas por Osteoporose/epidemiologia , Fraturas por Osteoporose/genética , Fraturas do Quadril/epidemiologia , Fraturas do Quadril/genética , Fraturas do Quadril/complicações , Saúde da Mulher , Fatores de Risco , Absorciometria de Fóton/métodosRESUMO
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.
Assuntos
Osteoporose , Fraturas por Osteoporose , Humanos , Análise da Randomização Mendeliana/métodos , Estudo de Associação Genômica Ampla , Osteoporose/genética , Densidade Óssea/genética , Fraturas por Osteoporose/etiologia , Fraturas por Osteoporose/genéticaRESUMO
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.
Assuntos
Doenças de Pequenos Vasos Cerebrais , Osteoporose , Fraturas por Osteoporose , Animais , Camundongos , Doenças de Pequenos Vasos Cerebrais/patologia , Células Endoteliais/patologia , Mutação/genética , Osteoporose/genética , Osteoporose/complicações , Fraturas por Osteoporose/diagnóstico por imagem , Fraturas por Osteoporose/genética , Fraturas por Osteoporose/complicaçõesRESUMO
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.
Assuntos
Osteoporose , Fraturas por Osteoporose , Humanos , Feminino , Fraturas por Osteoporose/genética , Fraturas por Osteoporose/complicações , Polimorfismo de Nucleotídeo Único/genética , Densidade Óssea/genética , Pós-Menopausa/genética , Osteoporose/complicações , Fatores de Risco , Medição de Risco/métodos , Predisposição Genética para DoençaRESUMO
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.
Assuntos
Fraturas por Compressão , Interleucina-6 , Fraturas por Osteoporose , Fraturas da Coluna Vertebral , Fator de Crescimento Transformador beta , Humanos , Fraturas por Compressão/genética , Frequência do Gene , Interleucina-6/genética , Fraturas por Osteoporose/genética , Polimorfismo Genético , Fraturas da Coluna Vertebral/genética , Fator de Crescimento Transformador beta/genética , Vértebras Torácicas/metabolismo , Vértebras Torácicas/patologia , Vértebras Lombares/metabolismo , Vértebras Lombares/patologiaRESUMO
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.
Assuntos
Densidade Óssea , Fraturas por Osteoporose , Masculino , Feminino , Humanos , Densidade Óssea/genética , Exoma/genética , Estudo de Associação Genômica Ampla , Fraturas por Osteoporose/genética , Estudos de Associação Genética , Polimorfismo de Nucleotídeo ÚnicoRESUMO
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.