Ehsan Vaghefi, Songyang An, Rini Corbett, David Squirrell
{"title":"基于视网膜图像的深度学习心脏 BioAge 与端粒长度和心血管生物标志物的关联。","authors":"Ehsan Vaghefi, Songyang An, Rini Corbett, David Squirrell","doi":"10.1097/OPX.0000000000002158","DOIUrl":null,"url":null,"abstract":"<p><strong>Significance: </strong>Our retinal image-based deep learning (DL) cardiac biological age (BioAge) model could facilitate fast, accurate, noninvasive screening for cardiovascular disease (CVD) in novel community settings and thus improve outcome with those with limited access to health care services.</p><p><strong>Purpose: </strong>This study aimed to determine whether the results issued by our DL cardiac BioAge model are consistent with the known trends of CVD risk and the biomarker leukocyte telomere length (LTL), in a cohort of individuals from the UK Biobank.</p><p><strong>Methods: </strong>A cross-sectional cohort study was conducted using those individuals in the UK Biobank who had LTL data. These individuals were divided by sex, ranked by LTL, and then grouped into deciles. The retinal images were then presented to the DL model, and individual's cardiac BioAge was determined. Individuals within each LTL decile were then ranked by cardiac BioAge, and the mean of the CVD risk biomarkers in the top and bottom quartiles was compared. The relationship between an individual's cardiac BioAge, the CVD biomarkers, and LTL was determined using traditional correlation statistics.</p><p><strong>Results: </strong>The DL cardiac BioAge model was able to accurately stratify individuals by the traditional CVD risk biomarkers, and for both males and females, those issued with a cardiac BioAge in the top quartile of their chronological peer group had a significantly higher mean systolic blood pressure, hemoglobin A 1c , and 10-year Pooled Cohort Equation CVD risk scores compared with those individuals in the bottom quartile (p<0.001). Cardiac BioAge was associated with LTL shortening for both males and females (males: -0.22, r2 = 0.04; females: -0.18, r2 = 0.03).</p><p><strong>Conclusions: </strong>In this cross-sectional cohort study, increasing CVD risk whether assessed by traditional biomarkers, CVD risk scoring, or our DL cardiac BioAge, CVD risk model, was inversely related to LTL. At a population level, our data support the growing body of evidence that suggests LTL shortening is a surrogate marker for increasing CVD risk and that this risk can be captured by our novel DL cardiac BioAge model.</p>","PeriodicalId":19649,"journal":{"name":"Optometry and Vision Science","volume":" ","pages":"464-469"},"PeriodicalIF":1.6000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11462873/pdf/","citationCount":"0","resultStr":"{\"title\":\"Association of retinal image-based, deep learning cardiac BioAge with telomere length and cardiovascular biomarkers.\",\"authors\":\"Ehsan Vaghefi, Songyang An, Rini Corbett, David Squirrell\",\"doi\":\"10.1097/OPX.0000000000002158\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Significance: </strong>Our retinal image-based deep learning (DL) cardiac biological age (BioAge) model could facilitate fast, accurate, noninvasive screening for cardiovascular disease (CVD) in novel community settings and thus improve outcome with those with limited access to health care services.</p><p><strong>Purpose: </strong>This study aimed to determine whether the results issued by our DL cardiac BioAge model are consistent with the known trends of CVD risk and the biomarker leukocyte telomere length (LTL), in a cohort of individuals from the UK Biobank.</p><p><strong>Methods: </strong>A cross-sectional cohort study was conducted using those individuals in the UK Biobank who had LTL data. These individuals were divided by sex, ranked by LTL, and then grouped into deciles. The retinal images were then presented to the DL model, and individual's cardiac BioAge was determined. Individuals within each LTL decile were then ranked by cardiac BioAge, and the mean of the CVD risk biomarkers in the top and bottom quartiles was compared. The relationship between an individual's cardiac BioAge, the CVD biomarkers, and LTL was determined using traditional correlation statistics.</p><p><strong>Results: </strong>The DL cardiac BioAge model was able to accurately stratify individuals by the traditional CVD risk biomarkers, and for both males and females, those issued with a cardiac BioAge in the top quartile of their chronological peer group had a significantly higher mean systolic blood pressure, hemoglobin A 1c , and 10-year Pooled Cohort Equation CVD risk scores compared with those individuals in the bottom quartile (p<0.001). Cardiac BioAge was associated with LTL shortening for both males and females (males: -0.22, r2 = 0.04; females: -0.18, r2 = 0.03).</p><p><strong>Conclusions: </strong>In this cross-sectional cohort study, increasing CVD risk whether assessed by traditional biomarkers, CVD risk scoring, or our DL cardiac BioAge, CVD risk model, was inversely related to LTL. At a population level, our data support the growing body of evidence that suggests LTL shortening is a surrogate marker for increasing CVD risk and that this risk can be captured by our novel DL cardiac BioAge model.</p>\",\"PeriodicalId\":19649,\"journal\":{\"name\":\"Optometry and Vision Science\",\"volume\":\" \",\"pages\":\"464-469\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11462873/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Optometry and Vision Science\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/OPX.0000000000002158\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/6/28 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"OPHTHALMOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optometry and Vision Science","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/OPX.0000000000002158","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/28 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"OPHTHALMOLOGY","Score":null,"Total":0}
Association of retinal image-based, deep learning cardiac BioAge with telomere length and cardiovascular biomarkers.
Significance: Our retinal image-based deep learning (DL) cardiac biological age (BioAge) model could facilitate fast, accurate, noninvasive screening for cardiovascular disease (CVD) in novel community settings and thus improve outcome with those with limited access to health care services.
Purpose: This study aimed to determine whether the results issued by our DL cardiac BioAge model are consistent with the known trends of CVD risk and the biomarker leukocyte telomere length (LTL), in a cohort of individuals from the UK Biobank.
Methods: A cross-sectional cohort study was conducted using those individuals in the UK Biobank who had LTL data. These individuals were divided by sex, ranked by LTL, and then grouped into deciles. The retinal images were then presented to the DL model, and individual's cardiac BioAge was determined. Individuals within each LTL decile were then ranked by cardiac BioAge, and the mean of the CVD risk biomarkers in the top and bottom quartiles was compared. The relationship between an individual's cardiac BioAge, the CVD biomarkers, and LTL was determined using traditional correlation statistics.
Results: The DL cardiac BioAge model was able to accurately stratify individuals by the traditional CVD risk biomarkers, and for both males and females, those issued with a cardiac BioAge in the top quartile of their chronological peer group had a significantly higher mean systolic blood pressure, hemoglobin A 1c , and 10-year Pooled Cohort Equation CVD risk scores compared with those individuals in the bottom quartile (p<0.001). Cardiac BioAge was associated with LTL shortening for both males and females (males: -0.22, r2 = 0.04; females: -0.18, r2 = 0.03).
Conclusions: In this cross-sectional cohort study, increasing CVD risk whether assessed by traditional biomarkers, CVD risk scoring, or our DL cardiac BioAge, CVD risk model, was inversely related to LTL. At a population level, our data support the growing body of evidence that suggests LTL shortening is a surrogate marker for increasing CVD risk and that this risk can be captured by our novel DL cardiac BioAge model.
期刊介绍：
Optometry and Vision Science is the monthly peer-reviewed scientific publication of the American Academy of Optometry, publishing original research since 1924. Optometry and Vision Science is an internationally recognized source for education and information on current discoveries in optometry, physiological optics, vision science, and related fields. The journal considers original contributions that advance clinical practice, vision science, and public health. Authors should remember that the journal reaches readers worldwide and their submissions should be relevant and of interest to a broad audience. Topical priorities include, but are not limited to: clinical and laboratory research, evidence-based reviews, contact lenses, ocular growth and refractive error development, eye movements, visual function and perception, biology of the eye and ocular disease, epidemiology and public health, biomedical optics and instrumentation, novel and important clinical observations and treatments, and optometric education.
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