遗传风险评分在复杂疾病遗传学研究中的应用

The application of genetic risk score in genetic studies of complex human diseases

心血管疾病、2型糖尿病、原发性高血压、哮喘、肥胖、肿瘤等复杂疾病在全球范围内流行,并成为人类死亡的主要原因。越来越多的人开始关注遗传易感性在复杂疾病发病机制中的作用。至今,与复杂疾病相关的易感基因和基因序列变异仍未完全清楚。人们希望通过遗传关联研究来阐明复杂疾病的遗传基础。近年来,全基因组关联研究和候选基因研究发现了大量与复杂疾病有关的基因序列变异。这些与复杂疾病有因果和(或)关联关系的基因序列变异的发现促进了复杂疾病预测和防治方法的产生和发展。遗传风险评分(Genetic risk score,GRS)作为探索单核苷酸多态(Single nucleotide polymorphisms,SNPs)与复杂疾病临床表型之间关系的新兴方法,综合了若干SNPs的微弱效应,使基因多态对疾病的预测性大幅度提升。该方法在许多复杂疾病遗传学研究中得到成功应用。本文重点介绍了GRS的计算方法和评价标准,简要列举了运用GRS取得的系列成果,并对运用过程中所存在的局限性进行了探讨,最后对遗传风险评分的未来发展方向进行了展望。

Complex diseases such as cardiovascular disease, type 2 diabetes, essential hypertension, asthma, obesity and cancer have spread across the globe and become the predominant cause of death. There are growing concerns over the role of genetic susceptibility in pathogenesis of complex diseases. However, the related susceptibility genes and sequence variations are still unknown. To elucidate the genetic basis of complex diseases, researchers have identified a large number of genetic variants associated with complex diseases through genome-wide association studies（GWAS） and candidate gene studies recently. The identification of these causal and/or associated variants promotes the development of approaches for complex diseases prediction and prevention. Genetic risk score（GRS）, an emerging method for exploring correlation between single nucleotide polymorphisms（SNPs） and clinical phenotypes of complex diseases, integrates weak effects of multiple SNPs and dramatically enhances predictability of complex diseases by gene polymorphisms. This method has been applied successfully in genetic studies of many complex diseases. Here we focus on the introduction of the computational methods and evaluation criteria of GRS, enumerate a series of achievements through GRS application, discuss some limitations during application, and finally prospect the future of GRS.