Deep Learning of the Retina Enables Phenome- and Genome-Wide Analyses of the Microvasculature.
Circulation
; 145(2): 134-150, 2022 01 11.
Article
em En
| MEDLINE
| ID: mdl-34743558
ABSTRACT
BACKGROUND:
The microvasculature, the smallest blood vessels in the body, has key roles in maintenance of organ health and tumorigenesis. The retinal fundus is a window for human in vivo noninvasive assessment of the microvasculature. Large-scale complementary machine learning-based assessment of the retinal vasculature with phenome-wide and genome-wide analyses may yield new insights into human health and disease.METHODS:
We used 97 895 retinal fundus images from 54 813 UK Biobank participants. Using convolutional neural networks to segment the retinal microvasculature, we calculated vascular density and fractal dimension as a measure of vascular branching complexity. We associated these indices with 1866 incident International Classification of Diseases-based conditions (median 10-year follow-up) and 88 quantitative traits, adjusting for age, sex, smoking status, and ethnicity.RESULTS:
Low retinal vascular fractal dimension and density were significantly associated with higher risks for incident mortality, hypertension, congestive heart failure, renal failure, type 2 diabetes, sleep apnea, anemia, and multiple ocular conditions, as well as corresponding quantitative traits. Genome-wide association of vascular fractal dimension and density identified 7 and 13 novel loci, respectively, that were enriched for pathways linked to angiogenesis (eg, vascular endothelial growth factor, platelet-derived growth factor receptor, angiopoietin, and WNT signaling pathways) and inflammation (eg, interleukin, cytokine signaling).CONCLUSIONS:
Our results indicate that the retinal vasculature may serve as a biomarker for future cardiometabolic and ocular disease and provide insights into genes and biological pathways influencing microvascular indices. Moreover, such a framework highlights how deep learning of images can quantify an interpretable phenotype for integration with electronic health record, biomarker, and genetic data to inform risk prediction and risk modification.Palavras-chave
Texto completo:
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Bases de dados:
MEDLINE
Assunto principal:
Retina
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Genômica
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Microvasos
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Estudo de Associação Genômica Ampla
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Análise da Randomização Mendeliana
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Aprendizado Profundo
Tipo de estudo:
Prognostic_studies
Limite:
Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Circulation
Ano de publicação:
2022
Tipo de documento:
Article