Getting from Genes to Function in Lung Disease A National Heart, Lung, and Blood Institute Workshop Report

被引:5
|
作者
Ober, Carole [2 ]
Butte, Atul J. [3 ,4 ]
Elias, Jack A. [5 ]
Lusis, A. Jake [6 ]
Gan, Weiniu [1 ]
Banks-Schlegel, Susan [1 ]
Schwartz, David [7 ]
机构
[1] NHLBI, Airway Biol & Dis Branch, Div Lung Dis, NIH, Bethesda, MD 20892 USA
[2] Univ Chicago, Dept Human Genet, Chicago, IL 60637 USA
[3] Stanford Univ, Sch Med, Dept Pediat, Stanford, CA 94305 USA
[4] Stanford Univ, Sch Med, Dept Med, Stanford, CA 94305 USA
[5] Yale Univ, Sch Med, Dept Internal Med, New Haven, CT 06510 USA
[6] Univ Calif Los Angeles, Dept Med, Los Angeles, CA 90024 USA
[7] Natl Jewish Hlth, Dept Med, Denver, CO USA
基金
美国国家卫生研究院;
关键词
genetics; epigenetics; genomics; bioinformatics; lung disease; GENOME-WIDE ASSOCIATION; ASTHMA; VARIANTS; SUSCEPTIBILITY; RISK;
D O I
10.1164/rccm.201002-0180PP
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Genome-wide association studies (GWAS) have revealed novel genes and pathways involved in lung disease, many of which are potential targets for therapy. However, despite numerous successes, a large proportion of the genetic variance in disease risk remains unexplained, and the function of the associated genetic variations identified by GWAS and the mechanisms by which they alter individual risk for disease or pathogenesis are still largely unknown. The National Heart, Lung, and Blood Institute (NHLBI) convened a 2-day workshop to address these shortcomings and to make recommendations for future research areas that will move the scientific community beyond gene discovery. Topics of individual sessions ranged from data integration and systems genetics to functional validation of genetic variations in humans and model systems. There was broad consensus among the participants for five high-priority areas for future research, including the following: (1) integrated approaches to characterize the function of genetic variations, (2) studies on the role of environment and mechanisms of transcriptional and post-transcriptional regulation, (3) development of model systems to study gene function in complex biological systems, (4) comparative phenomic studies across lung diseases, and (5) training in and applications of bioinformatic approaches for comprehensive mining of existing data sets. Last, it was agreed that future research on lung diseases should integrate approaches across "-omic" technologies and to include ethnically/racially diverse populations in human studies of lung disease whenever possible.
引用
收藏
页码:732 / 737
页数:6
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