Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Neuroscientist. 2011 Apr;17(2):174-84. doi: 10.1177/1073858410381533. Epub 2011 Jan 20.
Genome-wide association studies (GWAS) allow for a large number of samples to be assayed simultaneously, using a genome-wide tagging single nucleotide polymorphism (SNP) approach. The initial boon of success from disease studies such as macular degeneration and inflammatory bowel disease has been mitigated by lack of genome-wide significance for psychiatric disorders and related traits, despite evaluations of large populations. In addition to SNP genotypes, which are common variants typically attributing small or modest relative risk, copy number variations can be detected based on the same data set. Several rare recurrent copy number variations have been associated with psychiatric diseases in genome-wide analyses. Proper and responsible study design, followed by rigorous data quality assessment of genomic matching of cases and controls, is most likely to uncover regions of significant association that replicate in independent cohorts, thereby maximizing the chance of significant and confident association.
全基因组关联研究 (GWAS) 允许同时对大量样本进行检测,使用全基因组标记单核苷酸多态性 (SNP) 方法。尽管对大量人群进行了评估,但精神障碍和相关特征的全基因组关联研究仍缺乏成功,这降低了黄斑变性和炎症性肠病等疾病研究最初的成功。除了 SNP 基因型外,基于相同数据集还可以检测到常见的变体,这些变体通常归因于小或适度的相对风险。在全基因组分析中,已经发现了几种罕见的重复拷贝数变异与精神疾病有关。适当和负责任的研究设计,以及对病例和对照的基因组匹配进行严格的数据质量评估,最有可能发现复制到独立队列中的显著关联区域,从而最大程度地提高关联的显著和置信度。