Belsky Daniel W, Israel Salomon
a Center for the Study of Aging and Human Development , Duke University Medical Center , Durham , North Carolina , USA.
Biodemography Soc Biol. 2014;60(2):137-55. doi: 10.1080/19485565.2014.946591.
The sequencing of the human genome and the advent of low-cost genome-wide assays that generate millions of observations of individual genomes in a matter of hours constitute a disruptive innovation for social science. Many public use social science datasets have or will soon add genome-wide genetic data. With these new data come technical challenges, but also new possibilities. Among these, the lowest-hanging fruit and the most potentially disruptive to existing research programs is the ability to measure previously invisible contours of health and disease risk within populations. In this article, we outline why now is the time for social scientists to bring genetics into their research programs. We discuss how to select genetic variants to study. We explain how the polygenic architecture of complex traits and the low penetrance of individual genetic loci pose challenges to research integrating genetics and social science. We introduce genetic risk scores as a method of addressing these challenges and provide guidance on how genetic risk scores can be constructed. We conclude by outlining research questions that are ripe for social science inquiry.
人类基因组测序以及低成本全基因组检测方法的出现，使得在数小时内就能对数百万个个体基因组进行观测，这对社会科学而言是一项颠覆性创新。许多供公众使用的社会科学数据集已经或很快将加入全基因组遗传数据。这些新数据既带来了技术挑战，也带来了新的可能性。其中，最容易实现且对现有研究项目最具潜在颠覆性的是能够测量人群中以前看不见的健康和疾病风险轮廓。在本文中，我们概述了为何现在是社会科学家将遗传学纳入其研究项目的时候。我们讨论了如何选择要研究的基因变体。我们解释了复杂性状的多基因结构以及单个基因位点的低外显率如何给整合遗传学和社会科学的研究带来挑战。我们引入基因风险评分作为应对这些挑战的一种方法，并提供关于如何构建基因风险评分的指导。我们最后概述了适合社会科学探究的研究问题。
