Martinez-Marignac Veronica L, Valladares Adan, Cameron Emily, Chan Andrea, Perera Arjuna, Globus-Goldberg Rachel, Wacher Niels, Kumate Jesús, McKeigue Paul, O'Donnell David, Shriver Mark D, Cruz Miguel, Parra Esteban J
Department of Anthropology, University of Toronto at Mississauga, 3359 Mississauga Rd. Room 4026, South Bldg, L5L 1C6, Mississauga, ON, Canada,
Hum Genet. 2007 Feb;120(6):807-19. doi: 10.1007/s00439-006-0273-3. Epub 2006 Oct 26.
Admixture mapping is a recently developed method for identifying genetic risk factors involved in complex traits or diseases showing prevalence differences between major continental groups. Type 2 diabetes (T2D) is at least twice as prevalent in Native American populations as in populations of European ancestry, so admixture mapping is well suited to study the genetic basis of this complex disease. We have characterized the admixture proportions in a sample of 286 unrelated T2D patients and 275 controls from Mexico City and we discuss the implications of the results for admixture mapping studies. Admixture proportions were estimated using 69 autosomal ancestry-informative markers (AIMs). Maternal and paternal contributions were estimated from geographically informative mtDNA and Y-specific polymorphisms. The average proportions of Native American, European and, West African admixture were estimated as 65, 30, and 5%, respectively. The contributions of Native American ancestors to maternal and paternal lineages were estimated as 90 and 40%, respectively. In a logistic model with higher educational status as dependent variable, the odds ratio for higher educational status associated with an increase from 0 to 1 in European admixture proportions was 9.4 (95%, credible interval 3.8-22.6). This association of socioeconomic status with individual admixture proportion shows that genetic stratification in this population is paralleled, and possibly maintained, by socioeconomic stratification. The effective number of generations back to unadmixed ancestors was 6.7 (95% CI 5.7-8.0), from which we can estimate that genome-wide admixture mapping will require typing about 1,400 evenly distributed AIMs to localize genes underlying disease risk between populations of European and Native American ancestry. Sample sizes of about 2,000 cases will be required to detect any locus that contributes an ancestry risk ratio of at least 1.5.
混合映射是一种最近开发的方法，用于识别与复杂性状或疾病相关的遗传风险因素，这些性状或疾病在主要大陆群体之间表现出患病率差异。2型糖尿病（T2D）在美洲原住民人群中的患病率至少是欧洲血统人群的两倍，因此混合映射非常适合研究这种复杂疾病的遗传基础。我们对来自墨西哥城的286名无亲缘关系的T2D患者和275名对照样本的混合比例进行了特征分析，并讨论了结果对混合映射研究的影响。使用69个常染色体祖先信息标记（AIMs）估计混合比例。通过具有地理信息的线粒体DNA和Y特异性多态性估计母系和父系贡献。美洲原住民、欧洲和西非混合的平均比例分别估计为65%、30%和5%。美洲原住民祖先对母系和父系谱系的贡献分别估计为90%和40%。在以较高教育程度为因变量的逻辑模型中，欧洲混合比例从0增加到1与较高教育程度相关的优势比为9.4（95%，可信区间3.8 - 22.6）。社会经济地位与个体混合比例之间的这种关联表明，该人群中的遗传分层与社会经济分层平行，并且可能由社会经济分层维持。回到未混合祖先的有效世代数为6.7（95%可信区间5.7 - 8.0），由此我们可以估计，全基因组混合映射将需要对大约1400个均匀分布的AIMs进行分型，以定位欧洲和美洲原住民血统人群之间疾病风险的潜在基因。需要大约2000例的样本量来检测任何一个贡献至少1.5的祖先风险比的基因座。
