Turner Stephen T, Kardia Sharon L R, Boerwinkle Eric, de Andrade Mariza
Division of Hypertension and Department of Internal Medicine, Mayo Clinic and Foundation, Rochester, Minnesota 55905, USA.
Genet Epidemiol. 2004 Jul;27(1):64-73. doi: 10.1002/gepi.20002.
Multivariate linkage analyses of correlated traits provide greater statistical power to identify genetic loci with effects too small to be detected in single trait analyses. We conducted genomewide multivariate analyses of systolic BP, diastolic BP, and body mass index (BMI) in 1,848 non-Hispanic white subjects (968 females, 880 males) from 279 multigenerational pedigrees from Rochester, Minnesota. Blood pressure was measured by random zero sphygmomanometer; body mass index was calculated from measurements of height and weight; and genotypes were measured at 520 microsatellite marker loci distributed across the 22 autosomes. Univariate linkage analyses demonstrated tentative evidence of linkage (defined by univariate LOD scores of 1.30-1.99) for diastolic BP on chromosome 18 and for BMI on chromosomes 3, 10, and 18. Bivariate linkage analyses showed tentative evidence of linkage (defined by bivariate LOD scores of 2.06-2.86) for systolic and diastolic BP on chromosome 14 and for either measure of BP and BMI on chromosomes 2, 3, 10, and 18; and suggestive evidence of linkage (defined by bivariate LOD scores of 2.87-3.99) for either measure of BP and BMI on chromosomes 10 and chromosome 15. Trivariate linkage analyses of systolic and diastolic BP and BMI provided evidence of a region influencing all three traits on chromosome 10, where the trivariate LOD score rose to a maximum value of 4.09 (at 144 cM, P=0.0007), and possibly on chromosome 2, where it rose to a maximum value of 2.80 (at 77 cM, P=0.0075). For genomewide linkage analyses to succeed in localizing genes influencing BP, it may be advantageous to exploit the greater statistical power of multivariate linkage analyses to identify loci with pleiotropic effects on correlated traits.
对相关性状进行多变量连锁分析可提供更大的统计效力,以识别那些在单性状分析中因效应过小而无法检测到的基因座。我们对来自明尼苏达州罗切斯特市279个多代家系的1848名非西班牙裔白人受试者(968名女性,880名男性)的收缩压、舒张压和体重指数(BMI)进行了全基因组多变量分析。血压通过随机零位血压计测量;体重指数根据身高和体重测量值计算得出;在分布于22条常染色体上的520个微卫星标记位点进行基因分型。单变量连锁分析显示,18号染色体上舒张压以及3号、10号和18号染色体上BMI存在连锁的初步证据(以单变量LOD分数1.30 - 1.99定义)。双变量连锁分析显示,14号染色体上收缩压和舒张压存在连锁的初步证据(以双变量LOD分数2.06 - 2.86定义),2号、3号、10号和18号染色体上血压的任一测量值与BMI存在连锁的初步证据;10号染色体和15号染色体上血压的任一测量值与BMI存在连锁的提示性证据(以双变量LOD分数2.87 - 3.99定义)。收缩压、舒张压和BMI的三变量连锁分析提供了证据,表明10号染色体上存在一个影响所有这三个性状的区域,其中三变量LOD分数升至最大值4.09(在144 cM处,P = 0.0007),2号染色体上可能也存在,其升至最大值2.80(在77 cM处,P = 0.0075)。为使全基因组连锁分析成功定位影响血压的基因,利用多变量连锁分析更大的统计效力来识别对相关性状具有多效性影响的基因座可能是有利的。