Systemic retinal biomarkers

Ranchod, Tushar M.

doi:10.1097/icu.0000000000000784

Cited by 6 publications

(3 citation statements)

References 40 publications

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“…Numerous studies have focused on the identification of systemic biomarkers (mostly for AD and PD) that can be obtained noninvasively, are sensitive and specific, and are reliable [2 ]. However, to our knowledge, most of these studies do not collect ocular imaging data despite the fact that AI-DLS has already shown its ability to identify a number of retinal systemic biomarkers or oculomics in large populations studies [7,74]. AI using ophthalmologic imaging parameters thus has a potentially important role in the diagnosis and monitoring of neurodegenerative diseases.…”

Section: Discussionmentioning

confidence: 99%

Artificial intelligence in ophthalmology: an insight into neurodegenerative disease

Patil¹,

Biousse²,

Newman

2022

Current Opinion in Ophthalmology

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Purpose of reviewThe aging world population accounts for the increasing prevalence of neurodegenerative diseases such as Alzheimer's and Parkinson's which carry a significant health and economic burden. There is therefore a need for sensitive and specific noninvasive biomarkers for early diagnosis and monitoring. Advances in retinal and optic nerve multimodal imaging as well as the development of artificial intelligence deep learning systems (AI-DLS) have heralded a number of promising advances of which ophthalmologists are at the forefront.Recent findingsThe association among retinal vascular, nerve fiber layer, and macular findings in neurodegenerative disease is well established. In order to optimize the use of these ophthalmic parameters as biomarkers, validated AI-DLS are required to ensure clinical efficacy and reliability. Varied image acquisition methods and protocols as well as variability in neurogenerative disease diagnosis compromise the robustness of ground truths that are paramount to developing high-quality training datasets.SummaryIn order to produce effective AI-DLS for the diagnosis and monitoring of neurodegenerative disease, multicenter international collaboration is required to prospectively produce large inclusive datasets, acquired through standardized methods and protocols. With a uniform approach, the efficacy of resultant clinical applications will be maximized.

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Section: Discussionmentioning

confidence: 99%

Artificial intelligence in ophthalmology: an insight into neurodegenerative disease

Patil¹,

Biousse²,

Newman

2022

Current Opinion in Ophthalmology

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“…A recent review suggests that retinal photographs could be used in deep learning techniques for prediction of systemic diseases, including cardiovascular disease, while retinal optical coherence tomography (OCT) and optical coherence tomography angiography (OCT-A) are being used in prediction of cardiovascular disease in non-deep learning studies [37]. Considering the accessibility, non-invasive origin of retinal examination and its possible resemblance to coronary arteries we aimed to investigate the associations between ophthalmic parameters, CYP4F2 (rs2108622) and ABCA1 (rs1883025) polymorphisms and CAD.…”

Section: Introductionmentioning

confidence: 99%

Coronary artery disease, its associations with ocular, genetic and blood lipid parameters

Matulevičiūtė

Tatarūnas

Skipskis

et al. 2023

Eye

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Background/objectives To investigate the associations between ophthalmic parameters, CYP4F2 (rs2108622) and ABCA1 (rs1883025) polymorphisms and coronary artery disease, considering the accessibility, non-invasive origin of retinal examination and its possible resemblance to coronary arteries. Subjects/methods Overall 165 participants divided into groups based on the coronary angiography results and clinical status: control group (N = 73), MI group (N = 63), 3VD (three vessel disease) (N = 24). All the participants underwent total ophthalmic examination – optical coherence tomography (OCT) and OCT angiography of the macula region were performed and evaluated. Total cholesterol, high-density lipoprotein, low-density lipoprotein and triglyceride cholesterol (Tg-C) were tested. A standard manufacturer’s protocol for CYP4F2 (rs2108622) and ABCA1 (rs1883025) was used for genotyping with TaqMan probes. Results GCL+ layer was thicker in control group vs. 3VD group (74.00; 62.67–94.67 (median; min.-max.) vs. 71.06; 51.33–78.44, p = 0.037). T allele carriers under ABCA1 rs1883025 dominant model were shown to have ticker retina and smaller foveal avascular zone in superficial capillary plexus and smaller Tg-C concentration. ABCA1 rs1883025 was associated with retinal thickness (OR = 0.575, 95% CI 0.348–0.948, p = 0.030). Univariate logistic regression showed that ABCA1 rs1883025 CT genotype is associated with decreased risk for coronary artery disease development under overdominant genetic model (OR = 0.498, 95% CI 0.254–0.976; p = 0.042) and codominant genetic model (OR = 0.468, 95% CI 0.232–0.945, p = 0.034). Conclusions Results of this study confirmed that non-invasive methods such as OCT of eye might be used for identification of patients at risk of CAD.

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“…Oculomics, a rapidly developing field dedicated to identifying ocular biomarkers for systemic disease, is gaining attention for several cardiovascular and neurological applications [ 7 ]. A variety of retinal microvasculature features have become recognizable for their associations with systemic disease states [ 8 ]. Optical coherence tomography angiography (OCT-A) has emerged as a powerful clinical tool to image the retinal capillary bed, as it provides higher transverse and axial resolution than conventional color fundus photography or intravenous fluorescein angiography [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Efficacy of CRISPR-Based Gene Editing in a Sickle Cell Disease Patient as Measured through the Eye

Pinhas

Zhou

Otero-Marquez

et al. 2022

Case Reports in Hematology

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Sickle cell disease (SCD) exists on a phenotypic spectrum with variable genetic expressivity, making it difficult to assess an individual patient’s risk of complications at any particular point in time. Current and emerging SCD treatments, including CRISPR-based gene editing, result in a variable proportion of affected red blood cells (RBCs) still vulnerable to sickling. Clinical serological indicators of disease such as hemoglobin, indirect bilirubin, and reticulocyte count and clinical metrics including number of emergency department visits and hospitalizations over time often fall short in their ability to objectively quantify ischemic disease activity and efficacy of treatments. Clearly, better clinical biomarkers are needed. The rapidly developing field of oculomics leverages the transparent nature of the ocular tissue to directly study the retinal microvasculature in order to characterize the status of systemic diseases. In this case report, we demonstrate the ability of optical coherence tomography angiography (OCT-A) to detect and measure micro-occlusive events within the retinal capillary bed before and after RBC exchange transfusion and following CRISPR-based gene editing, as an indicator of systemic ischemic disease activity and measure of treatment efficacy. The implications of these findings are discussed.

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Systemic retinal biomarkers

Cited by 6 publications

References 40 publications

Artificial intelligence in ophthalmology: an insight into neurodegenerative disease

Artificial intelligence in ophthalmology: an insight into neurodegenerative disease

Coronary artery disease, its associations with ocular, genetic and blood lipid parameters

Efficacy of CRISPR-Based Gene Editing in a Sickle Cell Disease Patient as Measured through the Eye

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