Genome Institute of Singapore, A*STAR, Singapore.
Curr Opin Lipidol. 2010 Apr;21(2):123-7. doi: 10.1097/MOL.0b013e328336eae9.
Genome-wide association studies (GWASs) and the resequencing of extremes are two methods currently being used to identify the causative variants in dyslipidemia.
GWASs are high-throughput, array-based platforms. They are nonhypothesis-based and scan within and across many genes. Associated variants identified via GWAS are likely to be common, have modest effect sizes, and are more likely to be a disease marker rather than the true causative variant. Currently, GWAS-identified variants explain only a small amount of heritability associated with dyslipidemia. Resequencing of extremes involves deep sequencing of two groups of individuals, one at each extreme of the phenotype. It is usually used to evaluate genomic regions with a high prior index of suspicion (e.g. genes underlying strong linkage peaks). The associations detected are more likely to reflect causative variants of larger effect size than GWAS-identified variants. The proportion of heritability associated with dyslipidemia explained by rare variants is currently unknown.
Both methods have identified variants that are associated with dyslipidemia and will continue to be used as they play complementary roles.
全基因组关联研究(GWAS)和极端重测序是目前用于鉴定血脂异常致病变异的两种方法。
GWAS 是高通量、基于阵列的平台。它们不是基于假设的,而是在许多基因内和跨基因进行扫描。通过 GWAS 鉴定的相关变异可能是常见的,效应大小适中,更可能是疾病标志物而不是真正的致病变异。目前,GWAS 鉴定的变异仅能解释血脂异常相关遗传率的一小部分。极端重测序涉及两组个体的深度测序,一组处于表型的极值。它通常用于评估具有高先前可疑指数(例如,强连锁峰下的基因)的基因组区域。检测到的关联更有可能反映出比 GWAS 鉴定的变异具有更大效应的致病变异。目前尚不清楚罕见变异与血脂异常相关的遗传率比例。
这两种方法都已经鉴定出与血脂异常相关的变异,并且由于它们发挥互补作用,将继续被使用。