Suppr超能文献

常见复杂疾病中的基因-环境相互作用:构建一个综合模型——美国国立卫生研究院研讨会的建议

Gene-environment interplay in common complex diseases: forging an integrative model—recommendations from an NIH workshop.

作者信息

Bookman Ebony B, McAllister Kimberly, Gillanders Elizabeth, Wanke Kay, Balshaw David, Rutter Joni, Reedy Jill, Shaughnessy Daniel, Agurs-Collins Tanya, Paltoo Dina, Atienza Audie, Bierut Laura, Kraft Peter, Fallin M Daniele, Perera Frederica, Turkheimer Eric, Boardman Jason, Marazita Mary L, Rappaport Stephen M, Boerwinkle Eric, Suomi Stephen J, Caporaso Neil E, Hertz-Picciotto Irva, Jacobson Kristen C, Lowe William L, Goldman Lynn R, Duggal Priya, Gunnar Megan R, Manolio Teri A, Green Eric D, Olster Deborah H, Birnbaum Linda S

机构信息

National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA.

出版信息

Genet Epidemiol. 2011 May;35(4):217-25. doi: 10.1002/gepi.20571.

Abstract

Although it is recognized that many common complex diseases are a result of multiple genetic and environmental risk factors, studies of gene-environment interaction remain a challenge and have had limited success to date. Given the current state-of-the-science, NIH sought input on ways to accelerate investigations of gene-environment interplay in health and disease by inviting experts from a variety of disciplines to give advice about the future direction of gene-environment interaction studies. Participants of the NIH Gene-Environment Interplay Workshop agreed that there is a need for continued emphasis on studies of the interplay between genetic and environmental factors in disease and that studies need to be designed around a multifaceted approach to reflect differences in diseases, exposure attributes, and pertinent stages of human development. The participants indicated that both targeted and agnostic approaches have strengths and weaknesses for evaluating main effects of genetic and environmental factors and their interactions. The unique perspectives represented at the workshop allowed the exploration of diverse study designs and analytical strategies, and conveyed the need for an interdisciplinary approach including data sharing, and data harmonization to fully explore gene-environment interactions. Further, participants also emphasized the continued need for high-quality measures of environmental exposures and new genomic technologies in ongoing and new studies.

摘要

尽管人们认识到许多常见的复杂疾病是多种遗传和环境风险因素共同作用的结果,但基因-环境相互作用的研究仍然是一项挑战,并且迄今为止取得的成功有限。鉴于当前的科学现状,美国国立卫生研究院(NIH)通过邀请来自不同学科的专家就基因-环境相互作用研究的未来方向提供建议,来寻求加速健康与疾病中基因-环境相互作用研究的方法。NIH基因-环境相互作用研讨会的参与者一致认为,需要继续重视疾病中遗传和环境因素之间相互作用的研究,并且研究需要围绕多方面的方法来设计,以反映疾病、暴露特征以及人类发育相关阶段的差异。参与者指出,靶向性方法和非靶向性方法在评估遗传和环境因素的主要效应及其相互作用方面都有优缺点。研讨会上所代表的独特观点使得人们能够探索多样的研究设计和分析策略,并传达了采用跨学科方法(包括数据共享和数据协调)以充分探索基因-环境相互作用的必要性。此外,参与者还强调在正在进行的和新的研究中,持续需要高质量的环境暴露测量方法和新的基因组技术。

相似文献

2
3
4
Macromolecular crowding: chemistry and physics meet biology (Ascona, Switzerland, 10-14 June 2012).
Phys Biol. 2013 Aug;10(4):040301. doi: 10.1088/1478-3975/10/4/040301. Epub 2013 Aug 2.
5
The future of Cochrane Neonatal.
Early Hum Dev. 2020 Nov;150:105191. doi: 10.1016/j.earlhumdev.2020.105191. Epub 2020 Sep 12.
6
The Minderoo-Monaco Commission on Plastics and Human Health.
Ann Glob Health. 2023 Mar 21;89(1):23. doi: 10.5334/aogh.4056. eCollection 2023.
7
Environmental genomics and human health.
G Ital Med Lav Ergon. 2011 Jan-Mar;33(1):31-4.
8
Lessons Learned From Past Gene-Environment Interaction Successes.
Am J Epidemiol. 2017 Oct 1;186(7):778-786. doi: 10.1093/aje/kwx230.
9
Incorporation of Biological Knowledge Into the Study of Gene-Environment Interactions.
Am J Epidemiol. 2017 Oct 1;186(7):771-777. doi: 10.1093/aje/kwx229.

引用本文的文献

4
Ethical, Legal, and Social Implications of Gene-Environment Interaction Research.
Genet Epidemiol. 2025 Jan;49(1):e22591. doi: 10.1002/gepi.22591. Epub 2024 Sep 24.
6
Comparative neurogenetics of dog behavior complements efforts towards human neuropsychiatric genetics.
Hum Genet. 2023 Aug;142(8):1231-1246. doi: 10.1007/s00439-023-02580-y. Epub 2023 Aug 14.
7
Modeling the enigma of complex disease etiology.
J Transl Med. 2023 Feb 25;21(1):148. doi: 10.1186/s12967-023-03987-x.
8
Gene-environment interactions and their impact on human health.
Genes Immun. 2023 Feb;24(1):1-11. doi: 10.1038/s41435-022-00192-6. Epub 2022 Dec 30.
9
Multidimensional molecular measurements-environment interaction analysis for disease outcomes.
Biometrics. 2022 Dec;78(4):1542-1554. doi: 10.1111/biom.13526. Epub 2021 Aug 1.
10
Genetic variants related to physical activity or sedentary behaviour: a systematic review.
Int J Behav Nutr Phys Act. 2021 Jan 22;18(1):15. doi: 10.1186/s12966-020-01077-5.

本文引用的文献

1
Genetic association and gene-environment interaction: a new method for overcoming the lack of exposure information in controls.
Am J Epidemiol. 2011 Jan 15;173(2):225-35. doi: 10.1093/aje/kwq352. Epub 2010 Nov 17.
2
An Environment-Wide Association Study (EWAS) on type 2 diabetes mellitus.
PLoS One. 2010 May 20;5(5):e10746. doi: 10.1371/journal.pone.0010746.
4
Gene--environment-wide association studies: emerging approaches.
Nat Rev Genet. 2010 Apr;11(4):259-72. doi: 10.1038/nrg2764.
5
PhenX: a toolkit for interdisciplinary genetics research.
Curr Opin Lipidol. 2010 Apr;21(2):136-40. doi: 10.1097/MOL.0b013e3283377395.
7
Gene-environment interaction and children's health and development.
Curr Opin Pediatr. 2010 Apr;22(2):197-201. doi: 10.1097/MOP.0b013e328336ebf9.
8
Methods for investigating gene-environment interactions in candidate pathway and genome-wide association studies.
Annu Rev Public Health. 2010;31:21-36. doi: 10.1146/annurev.publhealth.012809.103619.
9
A novel approach to simulate gene-environment interactions in complex diseases.
BMC Bioinformatics. 2010 Jan 5;11:8. doi: 10.1186/1471-2105-11-8.
10
Evaluating epistatic interaction signals in complex traits using quantitative traits.
BMC Proc. 2009 Dec 15;3 Suppl 7(Suppl 7):S82. doi: 10.1186/1753-6561-3-s7-s82.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验