Genetics of Bone Structure and Metabolism

描述（由申请人提供）：骨质疏松症是一种以进行性、年龄相关的骨量和密度降低、正常骨结构破坏和随之而来的骨强度降低为特征的疾病，导致骨折易感性增加。在老年人中，骨质疏松性骨折与大量的合并症和死亡率相关。随着世界人口的老龄化，骨质疏松症伴随的人类痛苦和经济成本预计将急剧增加。在发达的工业化国家，如美国，加拿大和欧盟。美国已经阐明了饮食、行为和环境因素对年龄相关骨折风险的影响，并开始揭示遗传基础。然而，大多数对骨质疏松症风险基因的搜索都没有达到最佳动力，发展中国家的骨质疏松症相关研究刚刚起步或根本不存在。我们建议进行第一次联合全基因组连锁和关联研究的基因影响骨相关表型的变化，在人口从发展中国家：尼泊尔东部的吉瑞尔。2000名成员已经在400多个标记位点进行了基因分型，单一的、完整的、非近交的Jirel谱系目前是基因组扫描研究中最大和最强大的数据集。(1)我们将对所有2000名个体进行广泛的骨相关特征的表征，包括跟骨的骨超声衰减，使用双能X射线吸收测定法评估的3个区域（股骨近端、腰椎和前臂）的骨矿物质密度，以及与骨形成、转换和代谢相关的12种生物标志物。(2)我们将使用定量遗传分析技术来确定每个骨相关性状中归因于基因的变异量，并评估共同基因影响骨相关表型对（多效性）的程度。(3)我们将进行全基因组连锁分析，将每种骨相关表型的基因以及影响多种表型的多效性基因定位到特定的染色体区域。(4)我们将对1000名参与者进行约550，000个单核苷酸多态性的基因分型，并使用新的基于谱系的遗传关联方法来提名和优先考虑所有QTL的位置候选基因。(5)最后，使用这些相同的分析方法和SNP标记集，我们将在1000名欧洲-美国参与者中进行分析，以验证我们在Fels纵向研究中对骨质疏松症相关性状遗传学的单独资助研究中的发现。该项目的目标是影响骨相关表型的QTL的定位，鉴定和表征，提名的位置候选基因可能有助于这些性状的变化，并通过扩展，骨质疏松症的人口由共同研究者在这个项目。风险-对一般人类的影响，以及对世界上未充分研究的地区的人们产生更具体影响的风险。公共卫生相关性：随着世界人口的老龄化，与骨质疏松症相关的人类痛苦和经济成本都将急剧增加。因为它将使用为此目的而收集的最强大的家庭数据集，该项目将提高对影响骨密度和代谢测量的基因的身份的认识，这些测量可预测骨质疏松性骨折的风险。

DESCRIPTION (provided by applicant): Osteoporosis, a disorder characterized by progressive, age-related decreases in bone mass and density, disruption of normal bone architecture, and consequent reduction in bone strength, results in increased susceptibility to fracture. In older persons, osteoporotic fracture is associated with substantial comorbidity and mortality. As the world's population ages, the attendant human suffering and economic costs of osteoporosis are predicted to increase dramatically. Research on osteoporosis in the developed, industrialized countries like the U.S., Canada, and the E.U. nations has elucidated the contributions of dietary, behavioral, and environmental factors to age-related fracture risks and has begun to unravel the genetic underpinnings as well. However, most searches for osteoporosis risk genes are less than optimally powered and osteoporosis-related research in developing countries is nascent or nonexistent. We propose to conduct the first combined whole genome linkage and association study for genes affecting variation in bone-related phenotypes in a population from a developing country: the Jirels of Eastern Nepal. With 2000 members already genotyped at over 400 marker loci, the single, unbroken, non-inbred Jirel pedigree currently is the largest and most powerful dataset available to a genome scanning study. (1) We will characterize all 2000 individuals for a broad range of bone-related traits including bone ultrasound attenuation of the calcaneous, bone mineral densities in 3 regions (proximal femur, lumbar spine, and forearm) assessed using dual-energy X-ray absorptiometry, and 12 biomarkers related to bone formation, turn-over, and metabolism. (2) We will use quantitative genetic analysis techniques to determine the amount of variation in each of the bone-related traits that is attributable to genes and assess the degree to which common genes influence pairs of bone-related phenotypes (pleiotropy). (3) We will conduct genome-wide linkage analysis to localize genes for each of the bone related phenotypes - as well as pleiotropic genes affecting multiple phenotypes - to specific chromosomal regions. (4) We will genotype 1000 of the participants for approximately 550,000 single nucleotide polymorphisms and use novel, pedigree-based genetic association methods to nominate and prioritize positional candidate genes for all QTLs. (5) Finally, using these same analytical methods and SNP marker sets, we will perform analyses to validate our findings in 1000 Euro-American participants of a separately funded study of the genetics of osteoporosis-related traits in the Fels Longitudinal study The goals of this project are the localization, identification, and characterization of QTLs influencing bone-related phenotypes, the nomination of positional candidate genes likely contributing to variation in these traits - and, by extension, osteoporosis population directed by co-investigators on this project. risk - in humans in general, as well as those with effects more specific to peoples from an understudied region of the world. PUBLIC HEALTH RELEVANCE: As the world's population ages, both the human suffering and economic costs associated with osteoporosis will increase dramatically. Because it will use the most powerful family data set assembled for this purpose, this project will enhance knowledge about the identities of genes affecting measures of bone density and metabolism that predict risk of osteoporotic fracture.