Genome-wide association studies, field synopses, and the development of the knowledge base on genetic variation and human diseases.
Genome-wide association studies, field synopses, and the development of the knowledge base on genetic variation and human diseases.
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DOI：
10.1093/aje/kwp119
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发表时间：
2009-08-01
影响因子：
5
通讯作者：
Ioannidis JP
中科院分区：
文献类型：
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作者：
Khoury MJ;Bertram L;Boffetta P;Butterworth AS;Chanock SJ;Dolan SM;Fortier I;Garcia-Closas M;Gwinn M;Higgins JP;Janssens AC;Ostell J;Owen RP;Pagon RA;Rebbeck TR;Rothman N;Bernstein JL;Burton PR;Campbell H;Chockalingam A;Furberg H;Little J;O'Brien TR;Seminara D;Vineis P;Winn DM;Yu W;Ioannidis JP
全基因组关联研究（GWAS）导致关于常见遗传变异和表型的现有数据迅速增加，并发现了许多与常见复杂疾病易感性相关的新位点。整合来自GWAS和候选基因研究的证据取决于数据生产、在线出版、数据库开发和不断更新的数据合成方面的协同努力。在这里，作者总结了这些方面的当前经验和挑战，这些在2008年由人类基因组流行病学网络主办的多学科研讨会上进行了讨论。整合了许多已报道的基因疾病关联的综合领域概要已经系统地发展到几个领域，包括阿尔茨海默病、精神分裂症、膀胱癌、冠心病、早产和各种癌症中的DNA修复基因。作者总结了这些领域概要的见解，并讨论了尚未解决的问题，特别是根据GWAS的证据，他们总结了223个发现的二元结果关联的经验P值和效应大小数据（142个P < 10−7）。它们还提出了一种合作愿景，即为遗传与常见复杂疾病的关联建立可靠的累积证据，并建立关于遗传变异与人类健康的透明、分布式和权威知识库。作为人类基因组流行病学评论的下一步，作者邀请研究人员提交可能在《美国流行病学杂志》上发表的现场概要。
Genome-wide association studies (GWAS) have led to a rapid increase in available data on common genetic variants and phenotypes and numerous discoveries of new loci associated with susceptibility to common complex diseases. Integrating the evidence from GWAS and candidate gene studies depends on concerted efforts in data production, online publication, database development, and continuously updated data synthesis. Here the authors summarize current experience and challenges on these fronts, which were discussed at a 2008 multidisciplinary workshop sponsored by the Human Genome Epidemiology Network. Comprehensive field synopses that integrate many reported gene-disease associations have been systematically developed for several fields, including Alzheimer's disease, schizophrenia, bladder cancer, coronary heart disease, preterm birth, and DNA repair genes in various cancers. The authors summarize insights from these field synopses and discuss remaining unresolved issues—especially in the light of evidence from GWAS, for which they summarize empirical P-value and effect-size data on 223 discovered associations for binary outcomes (142 with P < 10−7). They also present a vision of collaboration that builds reliable cumulative evidence for genetic associations with common complex diseases and a transparent, distributed, authoritative knowledge base on genetic variation and human health. As a next step in the evolution of Human Genome Epidemiology reviews, the authors invite investigators to submit field synopses for possible publication in the American Journal of Epidemiology.
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影响因子：
3.7
作者：
Ioannidis JP;Patsopoulos NA;Evangelou E
通讯作者：
Evangelou E
影响因子：
2
作者：
Harbord, Roger M.;Egger, Matthias;Sterne, Jonathan A. C.
通讯作者：
Sterne, Jonathan A. C.
影响因子：
15.8
作者：
Ioannidis, JPA
通讯作者：
Ioannidis, JPA
影响因子：
30.8
作者：
Allen, Nicole C.;Bagade, Sachin;Bertram, Lars
通讯作者：
Bertram, Lars
影响因子：
30.8
作者：
通讯作者：
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