Berger Mario, Stassen Hans H, Köhler Karola, Krane Vera, Mönks Detlev, Wanner Christoph, Hoffmann Katrin, Hoffmann Michael M, Zimmer Michael, Bickeböller Heike, Lindner Tom H
Division of Nephrology, Department of Medicine, University of Würzburg, Würzburg, Germany.
Eur J Hum Genet. 2006 Feb;14(2):236-44. doi: 10.1038/sj.ejhg.5201546.
Linkage- and association-based approaches have been applied to attempt to unravel the genetic predisposition for complex diseases. However, studies often report contradictory results even when similar population backgrounds are investigated. Unrecognized population substructures could possibly explain these inconsistencies. In an apparently homogeneous German sample of 612 patients with type 2 diabetic and end-stage diabetic nephropathy and 214 healthy controls, we tested for hidden population substructures and their possible effects on association. Using a genetic vector space analysis of genotypes of 20 microsatellite markers, we identified four distinct subsets of cases and controls. The significance of these substructures was demonstrated by subsequent association analyses, using three genetic markers (UCSNP-43,-19,-63; intron 3 of the calpain-10 gene). In the undivided sample, we found no association between individual SNPs or any haplogenotypes (ie the genotype combination of two multilocus haplotypes) and type 2 diabetes. In contrast, when analyzing the four groups separately, we found that there was evidence for association of the common C allele of UCSNP-63 with the trait in the largest group (n=547 cases/101 controls; P=0.002). In this subset haplotype 112 was more frequent in controls than in cases (P=0.006; haplogenotype 112/121: odds ratio (OR)=0.27, 95% confidence intervals (CI)=0.13-0.57), indicating a protective effect against the development of type 2 diabetes. Our study demonstrates that unconsidered population substructures (ethnicity-dependent factors) can severely bias association studies.
基于连锁和关联的方法已被用于试图揭示复杂疾病的遗传易感性。然而，即使在研究相似的人群背景时，研究结果也常常相互矛盾。未被识别的人群亚结构可能是这些不一致结果的原因。在一个表面上同质的德国样本中，有612例2型糖尿病和终末期糖尿病肾病患者以及214名健康对照，我们检测了隐藏的人群亚结构及其对关联的可能影响。通过对20个微卫星标记的基因型进行遗传向量空间分析，我们识别出病例和对照的四个不同子集。随后使用三个遗传标记（UCSNP - 43、-19、-63；钙蛋白酶-10基因内含子3）进行关联分析，证明了这些亚结构的显著性。在未分组的样本中，我们未发现单个单核苷酸多态性（SNP）或任何单倍型（即两个多位点单倍型的基因型组合）与2型糖尿病之间存在关联。相比之下，当分别分析这四组时，我们发现有证据表明在最大的一组中（n = 547例/101对照；P = 0.002），UCSNP - 63的常见C等位基因与该性状存在关联。在这个子集中，单倍型组合112在对照中比在病例中更常见（P = 0.006；单倍型组合112/121：优势比（OR）= 0.27，95%置信区间（CI）= 0.13 - 0.57），表明对2型糖尿病的发生有保护作用。我们的研究表明，未考虑的人群亚结构（种族相关因素）会严重影响关联研究的结果。
