Cortical Bone Porosity Identifies Diabetes Subjects With Fragility Fractures

皮质骨孔隙度可识别患有脆性骨折的糖尿病受试者

• 批准号: 7943886
• 负责人: THOMAS M LINK
• 金额: $ 42.09万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7943886
• 关键词: Adult; Affect; Age; Animal Model; Ankle; Applications Grants; Architecture; Area; Biological Markers; Body mass index; Bone Density; Bone Diseases; Bone Marrow; Clinical; Cohort Studies; Coin; Data; Diabetes Mellitus; Diagnosis; Diagnostic Procedure; Disease; Distal; Fatty acid glycerol esters; Female; Femur; Finite Element Analysis; Fracture; Functional disorder; Genomics; Goals; Hip Fractures; Hip region structure; Image; Imaging Techniques; Institution; Insulin-Dependent Diabetes Mellitus; Intramural Research; Lateral; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy; Measurement; Measures; Mechanics; Metabolism; Metric; Monitor; Nature; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Observational Study; Osteoporosis; Patients; Performance; Peripheral; Pilot Projects; Play; Porosity; Postmenopause; Prevention; Process; Property; Proteomics; Public Health; Radial; Research; Resolution; Risk; Roentgen Rays; Role; Structure; Surrogate Markers; Techniques; Treatment Efficacy; United States National Institutes of Health; Validation; Vertebral column; Woman; abstracting; aged; base; bone; bone mass; bone quality; bone strength; diabetic; diabetic patient; digital; experience; foot; humerus; imaging modality; improved; in vivo; musculoskeletal imaging; non-diabetic; normal aging; novel; patient population; prevent; substantia spongiosa; tibia; trend

DESCRIPTION (provided by applicant): Cortical Bone Porosity Identifies Diabetes Subjects With Fragility Fractures Abstract The broad challenge area for this grant application is (03) Biomarker Discovery and Validation. Quantitative imaging techniques have, due to their non-invasive nature, gained substantial significance as biomarkers. This is in particular true for musculoskeletal imaging where imaging biomarkers are developed to better understand bone structure and stability. Thus the specific challenge area 03-AR-102* focuses on developing novel imaging (proteomic, or genomic) approaches to identify the risk for fragility fractures. This project will define and validate novel measures of bone quality that are more predictive than bone mineral density measurements. Bone mineral density (BMD) is currently the best-established bone biomarker to predict fracture risk in osteoporosis. Dual X-ray absorptiometry (DXA) has shown good performance in differentiating subjects with and without fractures, predicting fracture risk and monitoring therapy. However, in certain disease entities limitations of BMD measurements have been acknowledged and among these diabetic bone disease is of outstanding importance. A large number of studies have shown that while fracture risk in subjects with type II diabetes is increased, diabetics also have a higher BMD. This paradox has not been well understood and specific diagnostic techniques to better assess fracture risk in diabetic subjects have not been established. The NIH has previously coined the term "bone quality" to better characterize entities of bone strength which are not well quantified with bone mass or BMD. It is generally accepted that bone quality must play a central role in the increased number of fragility fractures in diabetics and among the measures of bone quality those focusing on cortical and trabecular bone architecture are outstanding. Finding a strong, non-invasive bone quality biomarker to better predict fragility fractures in diabetic patients is clearly a major challenge area, given the increasing socio-economical burden of diabetes and the devastating consequences of fragility fractures in these patients. In a recent intramural research pilot project we were able to study bone structure parameters in diabetic subjects with and without low energy fractures and non-diabetic controls. We obtained BMD measurements using quantitative CT (QCT) and studied cortical and trabecular bone structure with high resolution peripheral QCT (hr-pQCT) and high resolution MRI. Hr-pQCT is a novel imaging modality currently providing the best isotropic spatial resolution (voxel size) to visualize cortical and trabecular bone structure in vivo at the distal tibia and radius. Our research group has acquired extensive experience with this technique, in particular concerning image post-processing to extract structural parameters including cortical porosity and finite element analysis derived surrogate markers of bone strength. We also performed bone marrow MR spectroscopy of the lumbar spine in a subset of these patients to characterize bone marrow fat composition, as this may be of significant importance in understanding pathophysiology of diabetic bone disease. The results of this study showed, that while neither BMD nor trabecular structure parameters were able to differentiate fragility fracture and non-fracture diabetic patient groups, substantial, significant differences in cortical bone porosity and parameters based on finite element analysis were found. Also a trend was found for higher bone marrow fat in diabetic subjects versus normal controls. These findings need to be confirmed by studying larger patient groups, yet could potentially have substantial implications for quantifying risk of fragility fractures in diabetic subjects. In this grant application we propose to study cortical porosity in four subject groups, with and without diabetes and with and without fragility fractures to clinically validate the results found in our pilot study. Our hypothesis is that using hr-pQCT derived measures of cortical bone porosity and finite element analysis as well as MR spectroscopy derived bone marrow fat we will be able to differentiate diabetic subjects with and without fragility fractures. We also hypothesize that diabetic subjects with fragility fractures will have different cortical bone structure compared to non-diabetic subjects with and without fragility fractures and that BMD based parameters will not be able to differentiate diabetics with fractures versus diabetics and controls without fracture. Finding a strong, non-invasive bone quality biomarker to better predict fragility fractures in diabetic patients is clearly a major challenge area, given the increasing socio-economical burden of diabetes and the devastating consequences of fragility fractures in these patients. We believe, based on our preliminary data, that with our novel biomarkers we may be able to better characterize fracture risk in diabetic patients.

描述（由申请人提供）：皮质骨孔隙率识别出具有脆弱性骨折的糖尿病受试者摘要该赠款应用的广泛挑战领域是（03）生物标志物发现和验证。定量成像技术由于其非侵入性而具有与生物标志物的重要意义。对于肌肉骨骼成像而言，这是尤其是这样的，其中开发成像生物标志物以更好地理解骨骼结构和稳定性。因此，特定的挑战区域03-ar-102*着重于开发新型成像（蛋白质组学或基因组）方法，以鉴定脆性骨折的风险。该项目将定义和验证与骨矿物质密度测量更为可预测性的新型骨质测量。目前，骨矿物质密度（BMD）是预测骨质疏松症骨折风险的最完善的骨生物标志物。双X射线吸收率（DXA）在有或没有断裂的分化受试者中表现出良好的表现，可以预测断裂风险和监测治疗。但是，在某些疾病中，已经确认了BMD测量的局限性，其中糖尿病性骨骼疾病非常重要。大量研究表明，尽管II型糖尿病患者的骨折风险增加了，但糖尿病患者的BMD也更高。尚未确定这种悖论尚未得到充分理解和特定的诊断技术来更好地评估糖尿病患者的骨折风险。 NIH先前已经创造了“骨质”一词，以更好地表征骨骼强度的实体，而骨骼强度未通过骨骼或BMD进行很好的量化。人们普遍认为，骨骼质量必须在糖尿病患者的脆弱性骨折数量增加以及关注皮质和小梁骨结构的骨质质量的量度中起着核心作用。鉴于糖尿病的社会经济负担增加以及这些患者脆弱性骨折的毁灭性后果，发现糖尿病患者中有强大的无侵袭性骨质生物标志物可以更好地预测糖尿病患者的脆弱性骨折。在最近的壁内研究试验项目中，我们能够研究有或没有低能量骨折和非糖尿病控制的糖尿病受试者的骨结构参数。我们使用定量CT（QCT）获得了BMD测量，并研究了具有高分辨率外围QCT（HR-PQCT）和高分辨率MRI的皮质和小梁骨结构。 HR-PQCT是一种新型的成像方式，目前提供了最好的各向同性空间分辨率（体素大小），可在胫骨远端和半径的体内可视化皮质和小梁骨结构。我们的研究小组已经获得了这种技术的丰富经验，特别是关于图像后处理，以提取结构参数，包括皮质孔隙率和有限元分析得出骨强度的替代标记。我们还在这些患者的一部分中进行了腰椎MR光谱法，以表征骨髓脂肪组成，因为这对于理解糖尿病骨病的病理生理学可能至关重要。这项研究的结果表明，尽管BMD和小梁结构参数都无法区分脆性断裂和非骨折糖尿病患者群体，但基于有限元分析的皮质骨孔隙率和参数存在很大的，显着的差异。同样，在糖尿病受试者和正常对照组中，还发现了较高的骨髓脂肪的趋势。这些发现需要通过研究较大的患者群体来确认，但可能对量化糖尿病患者脆性骨折的风险具有重大意义。在此赠款应用中，我们建议研究四个受试者组的皮质孔隙率，患有和没有糖尿病，并且没有脆弱性骨折，以在临床上验证我们的试点研究中发现的结果。我们的假设是，使用HR-PQCT衍生的皮质骨孔隙率和有限元分析的度量以及MR光谱衍生的骨髓脂肪，我们将能够区分有和没有脆性骨折的糖尿病受试者。我们还假设，与有或没有脆性骨折的非糖尿病患者相比，具有脆性骨折的糖尿病患者将具有不同的皮质骨结构，而基于BMD的参数将无法用骨折与无骨折的糖尿病患者与糖尿病患者相比，将糖尿病患者分化。鉴于糖尿病的社会经济负担增加以及这些患者脆弱性骨折的毁灭性后果，发现糖尿病患者中有强大的无侵袭性骨质生物标志物可以更好地预测糖尿病患者的脆弱性骨折。我们认为，根据我们的初步数据，使用新型的生物标志物，我们可能能够更好地表征糖尿病患者的骨折风险。