Multiple polygenic scores improve bone mineral density prediction in an independent sample of Caucasian women

2021 ◽  
pp. postgradmedj-2021-139722
Author(s):  
Xiangxue Xiao ◽  
Qing Wu
Keyword(s):  
Risk Factors ◽  
Bone Mineral Density ◽  
Bone Mineral ◽  
Clinical Risk Factors ◽  
Mineral Density ◽  
Genome Wide ◽  
Single Score ◽  
Caucasian Women ◽  
Score Model ◽  
Conventional Risk Factors

Purpose of the studyTo determine if multiple Genetic Risk Scores (GRSs) improve bone mineral density (BMD) prediction over single GRS in an independent sample of Caucasian women.Study designBased on summary statistics of four genome-wide association studies related to two osteoporosis-associated traits, namely BMD and heel quantitative ultrasound derived estimated BMD (eBMD), four GRSs were derived for 1205 individuals in the Genome-Wide Scan for Female Osteoporosis Gene Study. The effect of each GRS on BMD variation was assessed using multivariable linear regression, with conventional risk factors adjusted for. Next, the eBMD-related GRS that explained the most variance in BMD was selected to be entered into a multi-score model, along with the BMD-related GRS. Elastic net regularised regression was used to develop the multiscore model, which estimated the joint effect of two GRSs (GRS_BMD and GRS_eBMD) on BMD variation, after being adjusted for conventional risk factors.ResultsWith the same clinical risk factors having been adjusted for, the model that included GRS_BMD performed best by explaining 32.53% of the variance in BMD; the single-score model that included GRS_eBMD explained 34.03% of BMD variance. The model that includes both GRS_BMD and GRS_ eBMD, as well as the clinical risk factors, aggregately explained 35.05% in BMD variation. Compared with the single GRS models, the multiscore model explained significantly more variance in BMD.ConclusionsThe multipolygenic score model explained a considerable amount of BMD variation. Compared with single score models, multipolygenic score model provided significant improvement in explaining BMD variation.

scholarly journals Prognostic value of lower bone mineral density in predicting adverse cardiovascular disease in Asian women

Heart ◽  
2021 ◽  
pp. heartjnl-2020-318764
Author(s):  
Jiesuck Park ◽  
Yeonyee Elizabeth Yoon ◽  
Kyoung Min Kim ◽  
In-Chang Hwang ◽  
Wonjae Lee ◽  
...  
Keyword(s):  
Risk Factors ◽  
Bone Mineral Density ◽  
Cardiovascular Disease ◽  
Clinical Diagnosis ◽  
Bone Mineral ◽  
Prognostic Value ◽  
Clinical Risk Factors ◽  
Mineral Density ◽  
Clinical Risk ◽  
Incremental Prognostic Value

ObjectiveWe investigated whether the evaluation of bone mineral density (BMD) provides independent and incremental prognostic value for predicting atherosclerotic cardiovascular disease (ASCVD) in women.MethodsA total of 12 681 women aged 50–80 years (mean, 63.0±7.8 years) who underwent dual-energy X-ray absorptiometry were retrospectively analysed. We assessed the hazard ratio (HR) for ASCVD events (ASCVD death, non-fatal myocardial infarction and ischaemic stroke) according to the BMD or a clinical diagnosis of osteopenia or osteoporosis, with adjustment for clinical risk factors, including age, body mass index, hypertension, type 2 diabetes, hyperlipidaemia, current smoking and previous fracture. We also evaluated whether the addition of BMD or a clinical diagnosis of osteopenia or osteoporosis to clinical risk factors improved the prediction for ASCVD events.ResultsIn total, 468 women (3.7%) experienced ASCVD events during follow-up (median, 9.2 years). Lower BMD at the lumbar spine, femur neck and total hip was independently associated with higher risk for ASCVD events (adjusted HR per 1-standard deviation decrease in BMD: 1.16, p<0.001; 1.29, p<0.001; 1.38, p<0.001; respectively). A clinical diagnosis of osteoporosis was also independently associated with higher risk for ASCVD events (adjusted HR: 1.79, p<0.001). The addition of BMD or a clinical diagnosis of osteopenia or osteoporosis to clinical risk factors demonstrated significant incremental value in discriminating ASCVD events (addition of total hip BMD, p for difference <0.001).ConclusionThe evaluation of BMD provides independent and incremental prognostic value for ASCVD in women and thus may improve risk stratification in women.

scholarly journals Association of Bone Mineral Density With Fractures Across the Spectrum of Chronic Kidney Disease: The Regina CKD-MBD Study

2019 ◽  
Vol 6 ◽  
pp. 205435811987053 ◽  
Author(s):  
Bhanu Prasad ◽  
Thomas Ferguson ◽  
Navdeep Tangri ◽  
Chee Yong Ng ◽  
Thomas L. Nickolas
Keyword(s):  
Risk Factors ◽  
Bone Mineral Density ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Fracture Risk ◽  
Bone Mineral ◽  
Biochemical Markers ◽  
Clinical Risk Factors ◽  
Mineral Density ◽  
Clinical Risk

Background: Recent studies have demonstrated that measurement of areal bone mineral density by dual-energy x-ray absorptiometry (DXA) predicts fractures in patients with chronic kidney disease (CKD). However, whether fracture risk prediction through bone mineral density (BMD) is enhanced due to the assessment of biochemical markers of chronic kidney disease and mineral and bone disease (CKD-MBD) or clinical risk factors is not clear. We hypothesized that in a select cohort of patients managed in a CKD clinic, that combining T-Scores with biochemical markers would optimize fracture discrimination than using DXA alone. Objective: To examine the relationships among BMD, biochemical markers of CKD-MBD, and fracture risk across Kidney Disease Improving Global Outcomes (KDIGO) glomerular filtration rate (GFR) categories G3a to G5. Design: Retrospective study. Setting: Patients were recruited from the multidisciplinary CKD clinic, Regina General Hospital, Canada. Patients: A total of 374 patients who received a DXA scan upon initial referral to Regina Multidisciplinary CKD Program from January 31, 2001 to January 31, 2010, were included in this study. The patients were followed for a total of 5 years. Methods: We conducted a retrospective review of 374 consecutive patients who underwent DXA imaging at the point of entry into our multidisciplinary CKD program. Areal BMD, T- and Z-Scores were obtained at the lumbar spine, total hip, mean of left and right femoral neck, and the one-third radius. We collected data on demographic, cross-sectional biochemical markers of mineral metabolism and fractures (identified through self-reported questionnaires, hospital electronic medical records, and physician billing records). We were able to gather data on 8/11 variables of Fracture Risk Assessment (FRAX) tool. Results: In our cohort, 14.3% of GFR categories G3a and G3b, 15.7% of GFR category G4, and 19.7% of GFR category G5 experienced a clinical fracture during the study period. On multivariate analysis, each decline of 1.0 SD in total hip BMD T-Score was associated with a significant increase in the risk of fracture (OR = 1.46, 95% confidence interval [CI], 1.12-1.89). Adding CKD-MBD markers and clinical risk factors did not further contribute to the model. Low BMD was the only independent risk factor for fracture in patients with CKD. Limitations: Self-reporting by patients and administrative records were used to identify fractures. We did not perform spine imaging to ascertain morphometric vertebral fractures. We were unable to gather all 11 variables of FRAX score and information on ethnicity. We were unable to capture site of fracture (hips, spine, etc) from billing records. Albumin excretion rates were not collected at baseline. Treatment of the underlying bone disease with pharmacotherapeutic agents may have attenuated patients’ fracture risk and thus underestimated the association between BMD and future fracture. Conclusions: Our findings confirm that BMD predicts fracture. The addition of cross-sectional CKD-MBD parameters and clinical risk factors to BMD did not add to fracture prediction. Prospective studies should investigate the utility of longitudinal biochemical markers on improving fracture risk assessment.

scholarly journals Metabolomics insights into osteoporosis through association with bone mineral density

2021 ◽  
Author(s):  
Xiaoyu Zhang ◽  
Hanfei Xu ◽  
Gloria H. Y. Li ◽  
Michelle T. Long ◽  
Ching-Lung Cheung ◽  
...  
Keyword(s):  
Risk Factors ◽  
Bone Mineral Density ◽  
Fracture Risk ◽  
Bone Mineral ◽  
Osteoporotic Fracture ◽  
Plasma Metabolites ◽  
P Value ◽  
Mineral Density ◽  
Negatively Associated ◽  
Conventional Risk Factors

AbstractOsteoporosis, a disease characterized by low bone mineral density (BMD), increases the risk for fractures. Conventional risk factors alone do not completely explain measured BMD or osteoporotic fracture risk. Metabolomics may provide additional information. We aim to identify BMD-associated metabolomic markers that are predictive of fracture risk. We assessed 209 plasma metabolites by LC-MS/MS in 1,552 Framingham Offspring Study participants, and measured femoral neck (FN) and lumbar spine (LS) BMD 2-10 years later using dual energy x-ray absorptiometry. We assessed osteoporotic fractures up to 27-year follow-up after metabolomic profiling. We identified twenty-seven metabolites associated with FN-BMD or LS-BMD by LASSO regression with internal validation. Incorporating selected metabolites significantly improved the prediction and the classification of osteoporotic fracture risk beyond conventional risk factors (AUC=0.74 for the model with identified metabolites and risk factors vs AUC=0.70 with risk factors alone, p=0.001; Net reclassification index=0.07, p=0.03). We replicated significant improvement in fracture prediction by incorporating selected metabolites in 634 participants from the Hong Kong Osteoporosis Study (HKOS). The glycine, serine, and threonine metabolism pathway (including four identified metabolites: creatine, dimethylglycine, glycine, and serine) was significantly enriched (FDR p-value=0.028). Furthermore, three causally related metabolites (glycine, Phosphatidylcholine [PC], and Triacylglycerol [TAG]) were negatively associated with FN-BMD while PC and TAG were negatively associated with LS-BMD through Mendelian randomization analysis. In summary, metabolites associated with BMD are helpful in osteoporotic fracture risk prediction. Potential causal mechanisms explaining the three metabolites on BMD are worthy of further experimental validation. Our findings may provide novel insights into the pathogenesis of osteoporosis.

Analysis of Clinical Risk Factors for Refracture in Osteoporosis

2020 ◽  
Vol 10 (10) ◽  
pp. 2337-2341
Author(s):  
Ming Li ◽  
Faqing Wan ◽  
Jia Liu ◽  
Qiuyan Hao ◽  
Bo Chen
Keyword(s):  
Risk Factors ◽  
Bone Mineral Density ◽  
Elderly Patients ◽  
Bone Mineral ◽  
Preventive Measures ◽  
Clinical Risk Factors ◽  
Early Investigation ◽  
Mineral Density ◽  
Clinical Risk ◽  
Lying Down

Objective: To observe and explore the clinical risk factors for refracture in patients with osteoporosis. Methods: A total of 32 patients with fractures and refractures after osteoporosis diagnosis from our hospital were enrolled from June to December 2018. The clinical situations of the two groups (fracture or refracture) were compared with particular regard for the main risk factors after fracture. Results: Through an analysis of the clinical data, we found that sex, age, time needed to stand from lying down, and low bone mineral density T-score are clinical risk factors for refracture. People of an older age, a bone mineral density T-score lower than normal, and females who require more time to stand from a lying down position have a higher risk of refracture. Conclusion: There a number of complex risk factors for refracture in elderly patients with osteoporosis. Early investigation and targeted preventive measures have great significance in reducing the incidence of refracture.

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