Christopher F. Chabris is with the Department of Psychology, Union College, Schenectady, NY. James J. Lee, Gregoire Borst, and Steven Pinker are with the Department of Psychology, Harvard University, Cambridge, MA. Daniel J. Benjamin is with the Department of Economics, Cornell University, Ithaca, NY. Jonathan P. Beauchamp, Edward L. Glaeser, and David I. Laibson are with the Department of Economics, Harvard University.
Am J Public Health. 2013 Oct;103 Suppl 1(Suppl 1):S152-66. doi: 10.2105/AJPH.2013.301327. Epub 2013 Aug 8.
We explain why traits of interest to behavioral scientists may have a genetic architecture featuring hundreds or thousands of loci with tiny individual effects rather than a few with large effects and why such an architecture makes it difficult to find robust associations between traits and genes.
We conducted a genome-wide association study at 2 sites, Harvard University and Union College, measuring more than 100 physical and behavioral traits with a sample size typical of candidate gene studies. We evaluated predictions that alleles with large effect sizes would be rare and most traits of interest to social science are likely characterized by a lack of strong directional selection. We also carried out a theoretical analysis of the genetic architecture of traits based on R.A. Fisher's geometric model of natural selection and empirical analyses of the effects of selection bias and phenotype measurement stability on the results of genetic association studies.
Although we replicated several known genetic associations with physical traits, we found only 2 associations with behavioral traits that met the nominal genome-wide significance threshold, indicating that physical and behavioral traits are mainly affected by numerous genes with small effects.
The challenge for social science genomics is the likelihood that genes are connected to behavioral variation by lengthy, nonlinear, interactive causal chains, and unraveling these chains requires allying with personal genomics to take advantage of the potential for large sample sizes as well as continuing with traditional epidemiological studies.
我们解释了为什么对行为科学家有意义的特征可能具有具有数百或数千个具有微小个体效应的基因座的遗传结构，而不是具有少数几个大效应的基因座的遗传结构，以及为什么这种结构使得很难在特征和基因之间找到稳健的关联。
我们在哈佛大学和联合学院两个地点进行了全基因组关联研究，用典型的候选基因研究样本量测量了 100 多种身体和行为特征。我们评估了以下预测：具有大效应大小的等位基因是罕见的，而社会科学感兴趣的大多数特征可能缺乏强烈的定向选择。我们还根据 R.A. Fisher 的自然选择几何模型对特征的遗传结构进行了理论分析，并对选择偏差和表型测量稳定性对遗传关联研究结果的影响进行了实证分析。
尽管我们复制了几个与身体特征有关的已知遗传关联，但我们只发现了 2 个与行为特征有关的关联达到了全基因组显著水平的阈值，这表明身体和行为特征主要受许多具有小效应的基因影响。
社会科学基因组学的挑战是基因与行为变异之间可能通过长而非线性的相互作用因果链联系在一起，而解开这些链需要与个人基因组学结盟，以利用大样本量的潜力，同时继续进行传统的流行病学研究。
