Imaging genomics: data fusion in uncovering disease heritability

Interpretation of how genome-wide association study (GWAS) variants alter disease risk can be conceptualized as a progression from DNA to RNA to protein to pathways, with each level incorporating additional genetic variation as well as environmental influences. Trends in Molecular Medicine.

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.