Imaging genomics: data fusion in uncovering disease heritability.
GWAS
imaging genomics
missing heritability
radiogenomics
Journal
Trends in molecular medicine
ISSN: 1471-499X
Titre abrégé: Trends Mol Med
Pays: England
ID NLM: 100966035
Informations de publication
Date de publication:
02 2023
02 2023
Historique:
received:
14
07
2022
revised:
28
10
2022
accepted:
03
11
2022
pmc-release:
01
02
2024
pubmed:
6
12
2022
medline:
24
1
2023
entrez:
5
12
2022
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 36470817
pii: S1471-4914(22)00292-1
doi: 10.1016/j.molmed.2022.11.002
pmc: PMC10507799
mid: NIHMS1931257
pii:
doi:
Types de publication
Journal Article
Review
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
141-151Subventions
Organisme : NCI NIH HHS
ID : R01 CA260271
Pays : United States
Informations de copyright
Copyright © 2022. Published by Elsevier Ltd.
Déclaration de conflit d'intérêts
Declaration of interests No interests are declared.
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