Program in Developmental Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD 20892, USA.
Hum Mol Genet. 2012 Dec 1;21(23):5193-201. doi: 10.1093/hmg/dds347. Epub 2012 Aug 21.
Previous meta-analysis of genome-wide association (GWA) studies has identified 180 loci that influence adult height. However, each GWA locus typically comprises a set of contiguous genes, only one of which presumably modulates height. We reasoned that many of the causative genes within these loci influence height because they are expressed in and function in the growth plate, a cartilaginous structure that causes bone elongation and thus determines stature. Therefore, we used expression microarray studies of mouse and rat growth plate, human disease databases and a mouse knockout phenotype database to identify genes within the GWAS loci that are likely required for normal growth plate function. Each of these approaches identified significantly more genes within the GWA height loci than at random genomic locations (P < 0.0001 each), supporting the validity of the approach. The combined analysis strongly implicates 78 genes in growth plate function, including multiple genes that participate in PTHrP-IHH, BMP and CNP signaling, and many genes that have not previously been implicated in the growth plate. Thus, this analysis reveals a large number of novel genes that regulate human growth plate chondrogenesis and thereby contribute to the normal variations in human adult height. The analytic approach developed for this study may be applied to GWA studies for other common polygenic traits and diseases, thus providing a new general strategy to identify causative genes within GWA loci and to translate genetic associations into mechanistic biological insights.
先前的全基因组关联 (GWA) 研究荟萃分析已经确定了 180 个影响成人身高的位点。然而，每个 GWA 位点通常包含一组连续的基因，其中只有一个基因可能调节身高。我们推断，这些位点中的许多致病基因之所以能够影响身高，是因为它们在生长板中表达并发挥作用，生长板是一种软骨结构，它导致骨骼伸长，从而决定身高。因此，我们使用了小鼠和大鼠生长板的表达微阵列研究、人类疾病数据库和小鼠敲除表型数据库，以确定 GWA 身高位点内可能对正常生长板功能所必需的基因。这些方法中的每一种方法都比在随机基因组位置（每个都<0.0001）识别出更多的 GWA 身高位点内的基因，这支持了该方法的有效性。综合分析强烈提示 78 个基因参与生长板功能，包括多个参与 PTHrP-IHH、BMP 和 CNP 信号的基因，以及许多以前未涉及生长板的基因。因此，该分析揭示了大量新的基因，这些基因调节人类生长板软骨发生，从而导致人类成年身高的正常变化。本研究中开发的分析方法可应用于其他常见多基因性状和疾病的 GWA 研究，从而为在 GWA 位点中识别致病基因并将遗传关联转化为机制生物学见解提供了一种新的通用策略。
