Cichon Sven, Craddock Nick, Daly Mark, Faraone Stephen V, Gejman Pablo V, Kelsoe John, Lehner Thomas, Levinson Douglas F, Moran Audra, Sklar Pamela, Sullivan Patrick F
Am J Psychiatry. 2009 May;166(5):540-56. doi: 10.1176/appi.ajp.2008.08091354. Epub 2009 Apr 1.
The authors conducted a review of the history and empirical basis of genomewide association studies (GWAS), the rationale for GWAS of psychiatric disorders, results to date, limitations, and plans for GWAS meta-analyses.
A literature review was carried out, power and other issues discussed, and planned studies assessed.
Most of the genomic DNA sequence differences between any two people are common (frequency >5%) single nucleotide polymorphisms (SNPs). Because of localized patterns of correlation (linkage disequilibrium), 500,000 to 1,000,000 of these SNPs can test the hypothesis that one or more common variants explain part of the genetic risk for a disease. GWAS technologies can also detect some of the copy number variants (deletions and duplications) in the genome. Systematic study of rare variants will require large-scale resequencing analyses. GWAS methods have detected a remarkable number of robust genetic associations for dozens of common diseases and traits, leading to new pathophysiological hypotheses, although only small proportions of genetic variance have been explained thus far and therapeutic applications will require substantial further effort. Study design issues, power, and limitations are discussed. For psychiatric disorders, there are initial significant findings for common SNPs and for rare copy number variants, and many other studies are in progress.
GWAS of large samples have detected associations of common SNPs and of rare copy number variants with psychiatric disorders. More findings are likely, since larger GWAS samples detect larger numbers of common susceptibility variants, with smaller effects. The Psychiatric GWAS Consortium is conducting GWAS meta-analyses for schizophrenia, bipolar disorder, major depressive disorder, autism, and attention deficit hyperactivity disorder. Based on results for other diseases, larger samples will be required. The contribution of GWAS will depend on the true genetic architecture of each disorder.
作者对全基因组关联研究（GWAS）的历史和实证基础、精神疾病GWAS的基本原理、迄今的研究结果、局限性以及GWAS荟萃分析计划进行了综述。
进行文献综述，讨论效能及其他问题，并评估计划中的研究。
任意两个人之间的大多数基因组DNA序列差异是常见的（频率>5%）单核苷酸多态性（SNP）。由于局部的相关性模式（连锁不平衡），其中50万至100万个SNP能够检验一个或多个常见变异解释疾病部分遗传风险的假设。GWAS技术还能检测基因组中的一些拷贝数变异（缺失和重复）。对罕见变异的系统研究将需要大规模的重测序分析。GWAS方法已检测到大量针对数十种常见疾病和性状的稳健遗传关联，从而产生了新的病理生理假设，尽管到目前为止仅解释了一小部分遗传变异，且治疗应用还需要付出巨大的进一步努力。文中讨论了研究设计问题、效能及局限性。对于精神疾病，常见SNP和罕见拷贝数变异已有初步的重要发现，还有许多其他研究正在进行中。
对大样本的GWAS已检测到常见SNP和罕见拷贝数变异与精神疾病之间的关联。可能会有更多发现，因为更大的GWAS样本能检测到更多效应较小的常见易感性变异。精神疾病GWAS联盟正在对精神分裂症、双相情感障碍、重度抑郁症、自闭症和注意力缺陷多动障碍进行GWAS荟萃分析。基于其他疾病的研究结果，将需要更大的样本。GWAS的贡献将取决于每种疾病的真实遗传结构。
