Key result
Imaging genomics shows promise for refining cardiopulmonary risk prediction and resolving disease heterogeneity.
Why the study?
Methods for imaging genomics are evolving despite substantial progress, prompting a need to review cutting-edge approaches and establish research priorities for heart and lung disease.
This NHLBI workshop report outlines research priorities for imaging genomics in heart and lung disease, emphasizing the need for diverse population data and centralized disease-specific efforts.
Answers are grounded in this paper and cite their sources.
Imaging genomics may refine future risk prediction in heart and lung disease; leaves open validation and clinical translation pending diverse population data.
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.
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Nayor et al. (2021) conducted a review in Heart and Lung Disease. Imaging genomics was evaluated. The NHLBI workshop highlighted the potential of imaging genomics to resolve phenotypic heterogeneity and improve risk prediction in heart and lung diseases, emphasizing the need for diverse population data.
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