Computed tomography muscle size and composition associations with hip and spine bone strength over 4 years: SOMMA-CT

项目摘要 骨质疏松性骨折与显著的发病率和死亡率相关，并给美国带来经济负担 预计到2025年将达到200亿美元。衰老加速了肌肉和骨骼的衰退， 骨折风险。了解肌肉和骨骼如何在解剖学、机械学和生物化学上相互作用， 降低骨强度可以通过识别新的骨折风险筛查来深入推进骨折预防 和干预目标，以诊断和治疗年龄相关的肌肉骨骼衰退。计算机断层扫描 (CT)扫描对评估局部肌肉和骨骼表型以识别老年人有很大的希望， 骨折风险高。具体而言，骨强度-三维骨的CT和有限元建模评估 骨形态、骨矿物质密度（BMD）和皮质厚度-是骨折风险的更强预测因子， 单独BMD。基于肌肉、运动和衰老研究（SOMMA），拟议的SOMMA-CT辅助 这项研究的独特定位是探索如何从CT（通过自动和 放射组学分析）、D3 Cr肌肉质量（D3-肌酸稀释）、肌肉性能以及循环肌肉- 骨串扰生物标志物，与髋关节和脊柱的骨强度变化有关（2例临床相关骨折 网站）。SOMMA是一项前瞻性研究，旨在研究与年龄相关的肌肉生物学对行动能力障碍的影响。 (R01 AG059416）。这项在360名SOMMA老年男性和女性（年龄70 - 94岁）中进行的辅助研究将采用 有效且具有成本效益的纵向设计，增加了：1）第4年随访CT扫描和抽血，以及 2)基线和4年CT扫描和血液样本的高级处理，以提取新的纵向 肌肉和骨骼表型。具体目的是：1）确定肌肉数量和组成（CT- 导出的大腿和躯干肌肉面积、肌肉密度、肌间脂肪和肌肉的放射性纹理特征 异质性; D3Cr肌肉质量）与4年内髋关节和脊柱骨强度的变化相关， 衰老2)确定肌肉性能（腿部伸肌比功率; 4米步态速度;完成5个椅子的时间） 站立）与4年以上年龄的髋关节和脊柱骨强度变化相关。我们还将探索 肌肉-骨骼串扰的生物标志物（肌因子：氨基丁酸;骨因子：CTX-1，P1NP）如何与 骨强度的横截面和纵向，并测试如果这些生物标志物介导的肌肉骨骼 目标1 - 2中的协会。科学的前提是大腿和躯干肌肉退化将与 随着髋关节和脊柱骨强度的下降，循环生物标志物将提供关于 肌肉-骨骼串扰对骨骼强度的贡献。这项在老龄化队列中的研究将增加我们的 了解肌肉和骨骼之间的动态相互关系和串扰。新的发现， 该地区可能会影响全球超过1.58亿老年人，他们是骨质疏松性骨折的高风险人群。这 通过提高骨折风险的预测能力， 筛选和鉴定肌肉和/或骨中的新表型，其可以靶向预防骨折。

PROJECT SUMMARY Osteoporotic fractures are associated with significant morbidity and mortality, and their U.S. economic burden is projected to reach $20 billion by 2025. Aging accelerates the decline of both muscle and bone, increasing fracture risk. Understanding how muscle and bone interact anatomically, mechanically, and biochemically to reduce bone strength could profoundly advance fracture prevention by identifying new fracture risk screening and intervention targets to diagnose and treat age-related musculoskeletal decline. Computed tomography (CT) scans hold great promise for assessing regional muscle and bone phenotypes to identify older adults at high risk of fracture. Specifically, bone strength – a CT and finite element modeling assessment of 3D bone morphology, bone mineral density (BMD), and cortical thickness – is a stronger predictor of fracture risk than BMD alone. Building on the Study of Muscle, Mobility & Aging (SOMMA), the proposed SOMMA-CT ancillary study is uniquely positioned to explore how thigh and trunk muscle properties from CT (via automated and radiomic analysis), D3Cr muscle mass (D3-creatine dilution), muscle performance, as well as circulating muscle- bone crosstalk biomarkers, relate to changes in bone strength at the hip and spine (2 clinically-relevant fracture sites). SOMMA is a prospective study examining aging-related muscle biology contributions to mobility disability (R01 AG059416). This ancillary study in 360 SOMMA older men and women (ages 70-94) will employ an efficient and cost-effective longitudinal design that adds: 1) a 4th-year follow-up CT scan and blood draw, and 2) advanced processing of baseline and 4-year CT scans and blood samples to extract new longitudinal muscle and bone phenotypes. Specific Aims are to: 1) Determine if muscle quantity and composition (CT- derived thigh and trunk muscle area, muscle density, intermuscular fat, and radiomic texture features of muscle heterogeneity; D3Cr muscle mass) are associated with changes in hip and spine bone strength over 4 years of aging. 2) Determine if muscle performance (leg extensor specific power; 4-m gait speed; time to complete 5 chair stands) is associated with change in hip and spine bone strength over 4 years of aging. We will also explore how biomarkers of muscle-bone crosstalk (myokines: aminobutyric acids; osteokines: CTX-1, P1NP) relate to bone strength both cross-sectionally and longitudinally, and test if these biomarkers mediate the muscle-bone associations in Aims 1-2. The scientific premise is that thigh and trunk muscle degeneration will be associated with declining hip and spine bone strength, and that circulating biomarkers will offer mechanistic insights on muscle-bone crosstalk contributors to bone strength. This investigation in an aging cohort will increase our knowledge of the dynamic interrelationships and crosstalk between muscle and bone. New discoveries in this area could impact over 158 million older adults worldwide who are at high risk of osteoporotic fracture. This work has strong potential to shift clinical practice paradigms by improving predictive power in fracture risk screening and identifying new phenotypes in muscle and/or bone which could be targeted to prevent fracture.