Pazoki Raha
Department of Epidemiology and Biostatistics (inc MRC-HPA Centre), School of Public Health, Imperial College London, London, UK.
Methods Mol Biol. 2018;1793:145-156. doi: 10.1007/978-1-4939-7868-7_10.
An important aspect of public health is disease prediction and health promotion through better targeting of preventive strategies. Well-targeted preventive strategies will eventually decrease burden of diseases and thus precise prediction plays a crucial role in public health. Many investigators put efforts into finding models that improve prediction using known risk factors of diseases. Recently with the overwhelming load of genetic loci discovered for complex diseases through genome-wide association studies (GWAS), much of attention has been focused on the role of these genetic loci to improve prediction models. Genetic loci in solo explain little variance of diseases. It is thus necessary to create new genetic parameters that combine the effect of as many genetic loci as possible. Such new parameters aim to better distinguish individuals who will develop a disease from those who will not. In this chapter, various polygenic methods that use multiple genetic loci to directly or indirectly improve precision of genetic prediction are discussed.
公共卫生的一个重要方面是通过更精准地制定预防策略来进行疾病预测和促进健康。精准的预防策略最终将减轻疾病负担,因此精确预测在公共卫生中起着至关重要的作用。许多研究人员致力于寻找利用疾病已知风险因素来改善预测的模型。最近,通过全基因组关联研究(GWAS)发现了大量与复杂疾病相关的基因位点,人们的注意力大多集中在这些基因位点在改善预测模型方面的作用上。单个基因位点对疾病变异的解释很少。因此,有必要创建新的基因参数,将尽可能多的基因位点的效应结合起来。这样的新参数旨在更好地区分将患疾病的个体和不会患疾病的个体。在本章中,将讨论各种使用多个基因位点直接或间接提高遗传预测精度的多基因方法。