基因组学
疾病
遗传力
遗传力缺失问题
数据共享
全基因组关联研究
生物
计算生物学
数据科学
基因组
医学
进化生物学
遗传学
病理
计算机科学
遗传变异
基因
基因型
单核苷酸多态性
替代医学
作者
Katherine Hartmann,Christoph Sadée,Ishan Satwah,Francisco Carrillo‐Pérez,Olivier Gevaert
标识
DOI:10.1016/j.molmed.2022.11.002
摘要
Sequencing of the human genome in the early 2000s enabled probing of the genetic basis of disease on a scale previously unimaginable. Now, two decades later, after interrogating millions of markers in thousands of individuals, a significant portion of disease heritability still remains hidden. Recent efforts to unravel this 'missing heritability' have focused on garnering new insight from merging different data types, including medical imaging. Imaging offers promising intermediate phenotypes to bridge the gap between genetic variation and disease pathology. In this review we outline this fusion and provide examples of imaging genomics in a range of diseases, from oncology to cardiovascular and neurodegenerative disease. Finally, we discuss how ongoing revolutions in data science and sharing are primed to advance the field.
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