人类全基因组关联研究

D. Kiel, E. Duncan, F. Rivadeneira
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引用次数: 2

摘要

技术变革和更新的统计方法导致全基因组关联研究(GWAS)在确定共同性状和疾病的基因位点方面取得了前所未有的成功。在GWAS之前,骨质疏松和骨折的遗传学研究仅限于大量的全基因组连锁和候选基因关联研究。GWAS使用高通量微阵列同时在一个或多个个体中对数十万甚至数百万种最常见的遗传变异,单核苷酸多态性(snp)进行基因分型。骨骼遗传学领域已经超越了早期对BMD表型的关注。研究人员最近使用英国生物银行研究的数据报道了迄今为止最大的骨骼表型GWAS meta分析。最近的一项研究表明,已知的遗传关联如何成功地预测药物机制和临床开发的成功。在骨骼肌(BMD)中尤其如此,它支持将遗传学用于药物靶标适应症。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human Genome‐Wide Association Studies
Technological changes and newer statistical approaches have resulted in genome‐wide association studies (GWAS) with unprecedented success in identifying loci underlying common traits and diseases. Before the GWAS, the field of genetics of osteoporosis and fracture had been confined to a very large number of genome‐wide linkage and candidate gene association studies. GWAS use high‐throughput microarrays to genotype simultaneously in one or more individuals hundreds of thousands and even millions of the most common forms of genetic variation, single nucleotide polymorphisms (SNPs). The field of skeletal genetics has expanded beyond the early focus on the BMD phenotype exclusively. The largest GWAS meta‐analysis for skeletal phenotypes to date was recently reported by investigators using data from the UK Biobank Study. A recent study demonstrated how known genetic associations are successful predictors of drug mechanisms and success in clinical development. This is particularly the case in the musculoskeletal (BMD), which supports the use of genetics for drug‐target indication.
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