GENOME SCAN FOR BONE AGE PHENOTYPE IN FRAMINGHAM COHORTS

背景资料。生物年龄提供了一个人在特定年龄段的形态和机能状态的总体估计。衰老过程的不同个体速率导致了时间年龄和生物年龄之间的差异。骨龄是生物体生物年龄的模型。骨学评分系统(OSS)已被开发用于测量与年龄相关的手骨放射学改变的进展、生物年龄和一般健康状况。众所周知，遗传因素在与年龄相关的骨骼特征的变异性中发挥作用，这是OSS评分的组成部分。目标。这项拟议的研究的目的是确定OSS评分衡量的骨老化是否可能由一组基因控制，并确定这些基因的染色体位置。这将在弗雷明翰研究的原始和后代队列中的337个家系成员中进行。为了更好地评估总性状变异的遗传成分，不同的健康和活动相关因素将被评估与骨老化的协变性。方法：研究方法。参与者的手之前都被拍过X光片。对于每个X线片，将使用四组特征来估计OSS评分：a.骨刺，例如骨赘、Heberden结节和外生骨化；b.骨孔：骨吸收陷窝和皮质的小梁化；c.骨硬化：骨质疏松症和硬化核；以及d.非创伤性关节畸形和关节腔变窄。根据协变量调整后的年代和OSS年龄预测值之间的标准化差异将在随后的分析中用作骨龄的衡量标准。将进行方差分解分析以评估遗传力，并将进行基因组扫描以确定骨龄评分与399个常染色体微卫星标记的潜在联系。意义重大。了解导致不同骨老化速度的遗传机制可能对退行性骨病的治疗有很大的帮助。确定骨质疏松症和骨性关节炎的最高风险个体将允许应用更好的药物遗传学或生活方式策略。在健康人群中使用骨龄表型进行基因组搜索可能会发现通常导致衰老的遗传源。了解遗传和环境对衰老的贡献将有助于改进延长寿命和健康监测的战略。

BACKGROUND. Biological age provides a general estimate of the morphological and functional status of an individual at a particular chronological age. Different individual rates of the aging process lead to disparities between chronological and biological age. Bone age serves as a model of biological age of an organism. An osteographic scoring system (OSS) has been developed to measure progression of age-related radiographic changes on hand bones, biological age, and general health status. It is well known that genetic factors play a role in variability of age-related bone traits, components of OSS score. OBJECTIVES. The aim of the proposed study is to determine whether bone aging, as measured by OSS score, may be governed by a set of genes, and to determine the chromosomal location of these genes. This will be done in members of 337 pedigrees from the Original and Offspring Cohorts of Framingham Study. To better assess the genetic component of total trait variance, different health- and activity-related factors will be evaluated for covariation with bone aging. METHODS. Hands of participants were previously radiographed. For each roentgenogram OSS score will be estimated, using four groups of features: A. Bony spurs, such as osteophytes, Heberden nodes, and exostoses; B. Bone porosity: resorption lacunae and trabecularization of cortex; C. Osteosclerosis: enostosis and sclerotic nuclei; and D. Non-traumatic articular deformities and joint cavities narrowing. The standardized difference between the chronological and the predicted by OSS age, adjusted on covariates, will be used as a measure of bone age in subsequent analyses. Variance decomposition analysis will be done to evaluate heritability, and a genome scan will be performed to identify potential linkage of bone age score with 399 autosomal microsatellite markers. SIGNIFICANCE. Understanding of the genetic mechanisms leading to different rates of bone aging may significantly contribute to the treatment of degenerative bone disease. Identifying the highest risk individuals for osteoporosis and osteoarthritis will allow to apply better pharmacogenetic or life-style strategies. A genome search using a bone age phenotype in a healthy population may discover genetic sources of aging in general. Knowledge of genetic and environmental contributions to aging will help to improve strategies for increasing longevity and health monitoring.