Deep Learning of the Retina Enables Phenome- and Genome-Wide Analyses of the Microvasculature. Issue 2 (11th January 2022)

• Record Type: Journal Article
• Authors: Zekavat, Seyedeh Maryam; Raghu, Vineet K.; Trinder, Mark; Ye, Yixuan; Koyama, Satoshi; Honigberg, Michael C.; Yu, Zhi; Pampana, Akhil; Urbut, Sarah; Haidermota, Sara; O'Regan, Declan P.; Zhao, Hongyu; Ellinor, Patrick T.; Segrè, Ayellet V.; Elze, Tobias; Wiggs, Janey L.; Martone, James; Adelman, Ron A.; Zebardast, Nazlee; Del Priore, Lucian; Wang, Jay C.; Natarajan, Pradeep
• Is Part Of: Circulation. Volume 145:Issue 2(2021)
• Publication Date: 2022-01-11
• Subjects: deep learning -- epidemiology -- genomics -- mendelian randomization analysis -- microvessels -- retina; Blood -- Circulation -- Periodicals; Cardiovascular system -- Periodicals; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; Blood Circulation; Cardiovascular System; Vascular Diseases; 616.1
• DOI: 10.1161/CIRCULATIONAHA.121.057709
• Languages: English
• ISSNs: 0009-7322

Abstract

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. Abstract : Supplemental Digital Content is available in the text.