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Progress and Research Priorities in Imaging Genomics for Heart and Lung Disease: Summary of an NHLBI Workshop
Circulation: Cardiovascular Imaging ( IF 7.5 ) Pub Date : 2021-08-13 , DOI: 10.1161/circimaging.121.012943
Matthew Nayor 1, 2 , Li Shen 3 , Gary M Hunninghake 4 , Peter Kochunov 5 , R Graham Barr 6 , David A Bluemke 7 , Ulrich Broeckel 8 , Peter Caravan 9 , Susan Cheng , Paul S de Vries 10 , Udo Hoffmann 11 , Márton Kolossváry 11 , Huiqing Li 12 , James Luo 12 , Elizabeth M McNally 13 , George Thanassoulis 14 , Donna K Arnett 15 , Ramachandran S Vasan 16
Affiliation  

Imaging genomics is a rapidly evolving field that combines state-of-the-art bioimaging with genomic information to resolve phenotypic heterogeneity associated with genomic variation, improve risk prediction, discover prevention approaches, and enable precision diagnosis and treatment. Contemporary bioimaging methods provide exceptional resolution generating discrete and quantitative high-dimensional phenotypes for genomics investigation. Despite substantial progress in combining high-dimensional bioimaging and genomic data, methods for imaging genomics are evolving. Recognizing the potential impact of imaging genomics on the study of heart and lung disease, the National Heart, Lung, and Blood Institute convened a workshop to review cutting-edge approaches and methodologies in imaging genomics studies, and to establish research priorities for future investigation. This report summarizes the presentations and discussions at the workshop. In particular, we highlight the need for increased availability of imaging genomics data in diverse populations, dedicated focus on less common conditions, and centralization of efforts around specific disease areas.

中文翻译:

心肺疾病影像基因组学的进展和研究重点:NHLBI 研讨会总结

成像基因组学是一个快速发展的领域,它将最先进的生物成像与基因组信息相结合,以解决与基因组变异相关的表型异质性,改善风险预测,发现预防方法,并实现精准诊断和治疗。现代生物成像方法提供了卓越的分辨率,为基因组学研究生成离散和定量的高维表型。尽管在结合高维生物成像和基因组数据方面取得了实质性进展,但成像基因组学的方法仍在不断发展。认识到成像基因组学对心脏和肺部疾病研究的潜在影响,国家心肺和血液研究所召开了一次研讨会,回顾成像基因组学研究的前沿方法和方法,并确定未来研究的研究重点。本报告总结了研讨会上的演讲和讨论。我们特别强调需要增加不同人群中成像基因组学数据的可用性,专注于不太常见的疾病,并围绕特定疾病领域集中工作。
更新日期:2021-08-17
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