Laboratory of Bioinformatics and Population Genetics, Department of Agricultural Biotechnology, Seoul National University, Seoul 151-742, Republic of Korea.
Hum Genet. 2012 Nov;131(11):1795-804. doi: 10.1007/s00439-012-1203-1. Epub 2012 Jul 24.
Many anthropometric measures, including body mass index (BMI), waist-to-hip ratio (WHR), and subcutaneous fat thickness, are used as indicators of nutritional status, fertility and predictors of future health outcomes. While BMI is currently the best available estimate of body adiposity, WHR and skinfold thickness at various sites (biceps, triceps, suprailiac, and subscapular) are used as indices of body fat distribution. Copy number variation (CNV) is an attractive emerging approach to the study of associations with various diseases. In this study, we investigated the dosage effect of genes in the CNV genome widely associated with fat distribution phenotypes in large cohorts. We used the Affymetrix genome-wide human SNP Array 5.0 data of 8,842 healthy unrelated adults in KARE cohorts and identified CNVs associated with BMI and fat distribution-related traits including WHR and subcutaneous skinfold thickness at suprailiac (SUP) and subscapular (SUB) sites. CNV segmentation of each chromosome was performed using Golden Helix SVS 7.0, and single regression analysis was used to identify CNVs associated with each phenotype. We found one CNV for BMI, 287 for WHR, 2,157 for SUP, and 2,102 for SUB at the 5% significance level after Holm-Bonferroni correction. Genes included in the CNV were used for the analysis of functional annotations using the Database for Annotation, Visualization and Integrated Discovery (DAVID v6.7b) tool. Functional gene classification analysis identified five significant gene clusters (metallothionein, ATP-binding proteins, ribosomal proteins, kinesin family members, and zinc finger proteins) for SUP, three (keratin-associated proteins, zinc finger proteins, keratins) for SUB, and one (protamines) for WHR. BMI was excluded from this analysis because the entire structure of no gene was identified in the CNV. Based on the analysis of genes enriched in the clusters, the fat distribution traits of KARE cohorts were related to the fat redistribution associated with the aging process. In addition to structural variation, dosage effect analysis of genes based on CNV is useful to gain an understanding of the comprehensive biological phenomena underlying particular phenotypes and/or diseases.
许多人体测量指标,包括体重指数(BMI)、腰臀比(WHR)和皮下脂肪厚度,被用作营养状况、生育能力的指标和未来健康结果的预测因子。虽然 BMI 是目前评估身体肥胖程度的最佳估计值,但 WHR 和各个部位(肱二头肌、肱三头肌、髂前上棘和肩胛下)的皮褶厚度被用作身体脂肪分布的指标。拷贝数变异(CNV)是研究与各种疾病关联的一种有吸引力的新兴方法。在这项研究中,我们研究了与脂肪分布表型广泛相关的 CNV 基因组中基因的剂量效应。我们使用 KARE 队列中 8842 名健康无关成年人的 Affymetrix 全基因组人类 SNP 阵列 5.0 数据,确定了与 BMI 和与脂肪分布相关的特征(包括 WHR 和髂前上棘(SUP)和肩胛下(SUB)部位的皮下皮褶厚度)相关的 CNV。使用 Golden Helix SVS 7.0 对每条染色体进行 CNV 分割,并使用单回归分析来确定与每种表型相关的 CNV。在 Holm-Bonferroni 校正后,我们在 5%的显著水平下发现了一个与 BMI 相关的 CNV,287 个与 WHR 相关,2157 个与 SUP 相关,2102 个与 SUB 相关。在 CNV 中包含的基因用于使用数据库进行功能注释分析,用于注释、可视化和综合发现(DAVID v6.7b)工具。功能基因分类分析确定了五个与 SUP 相关的显著基因簇(金属硫蛋白、ATP 结合蛋白、核糖体蛋白、驱动蛋白家族成员和锌指蛋白)、三个与 SUB 相关的(角蛋白相关蛋白、锌指蛋白、角蛋白)和一个与 WHR 相关的(鱼精蛋白)。由于在 CNV 中没有识别出整个基因结构,因此排除了 BMI 的分析。基于对簇中富集基因的分析,KARE 队列的脂肪分布特征与与衰老过程相关的脂肪再分布有关。除了结构变异外,基于 CNV 的基因剂量效应分析有助于了解特定表型和/或疾病背后的综合生物学现象。