Prediction of Major Adverse Cardiovascular Events From Retinal, Clinical, and Genomic Data in Individuals With Type 2 Diabetes: A Population Cohort Study

Mordi, Ify; Trucco, Emanuele; Syed, Mohammad Ghouse; MacGillivray, Tom; Nar, Adi; Huang, Yu; George, Gittu; Hogg, Stephen; Radha, Venkatesan; Prathiba, Vijayaraghavan; Anjana, Ranjit Mohan; Mohan, Viswanathan; Palmer, Colin N.A.; Pearson, Ewan R.; Lang, Chim C.; Doney, Alex S. F.

doi:10.2337/dc21-1124

Cited by 15 publications

(12 citation statements)

References 41 publications

(33 reference statements)

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“…We used 2 separate deep learning–based models: the VAMPIRE fractal dimension estimation module, based on a robustly validated U-Net segmentation algorithm developed by the universities of Dundee and Edinburgh, and AutoMorph, an openly available fully automated pipeline for the extraction of retinal features . Rejection rate based on image quality was similar to previous reports using retinal imaging . Given the challenges in the agreement between different segmentation tools, we can have greater confidence in our findings on retinal fractal dimension with results from 2 independent fully automated segmentation systems.…”

Section: Discussionmentioning

confidence: 69%

Association Between Retinal Features From Multimodal Imaging and Schizophrenia

et al. 2023

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ImportanceThe potential association of schizophrenia with distinct retinal changes is of clinical interest but has been challenging to investigate because of a lack of sufficiently large and detailed cohorts.ObjectiveTo investigate the association between retinal biomarkers from multimodal imaging (oculomics) and schizophrenia in a large real-world population.Design, Setting, and ParticipantsThis cross-sectional analysis used data from a retrospective cohort of 154 830 patients 40 years and older from the AlzEye study, which linked ophthalmic data with hospital admission data across England. Patients attended Moorfields Eye Hospital, a secondary care ophthalmic hospital with a principal central site, 4 district hubs, and 5 satellite clinics in and around London, United Kingdom, and had retinal imaging during the study period (January 2008 and April 2018). Data were analyzed from January 2022 to July 2022.Main Outcomes and MeasuresRetinovascular and optic nerve indices were computed from color fundus photography. Macular retinal nerve fiber layer (RNFL) and ganglion cell–inner plexiform layer (mGC-IPL) thicknesses were extracted from optical coherence tomography. Linear mixed-effects models were used to examine the association between schizophrenia and retinal biomarkers.ResultsA total of 485 individuals (747 eyes) with schizophrenia (mean [SD] age, 64.9 years [12.2]; 258 [53.2%] female) and 100 931 individuals (165 400 eyes) without schizophrenia (mean age, 65.9 years [13.7]; 53 253 [52.8%] female) were included after images underwent quality control and potentially confounding conditions were excluded. Individuals with schizophrenia were more likely to have hypertension (407 [83.9%] vs 49 971 [48.0%]) and diabetes (364 [75.1%] vs 28 762 [27.6%]). The schizophrenia group had thinner mGC-IPL (−4.05 μm, 95% CI, −5.40 to −2.69; P = 5.4 × 10−9), which persisted when investigating only patients without diabetes (−3.99 μm; 95% CI, −6.67 to −1.30; P = .004) or just those 55 years and younger (−2.90 μm; 95% CI, −5.55 to −0.24; P = .03). On adjusted analysis, retinal fractal dimension among vascular variables was reduced in individuals with schizophrenia (−0.14 units; 95% CI, −0.22 to −0.05; P = .001), although this was not present when excluding patients with diabetes.Conclusions and RelevanceIn this study, patients with schizophrenia had measurable differences in neural and vascular integrity of the retina. Differences in retinal vasculature were mostly secondary to the higher prevalence of diabetes and hypertension in patients with schizophrenia. The role of retinal features as adjunct outcomes in patients with schizophrenia warrants further investigation.

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Section: Discussionmentioning

confidence: 69%

Association Between Retinal Features From Multimodal Imaging and Schizophrenia

et al. 2023

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“… 329 In T2DM, retinal parameters and a genome-wide polygenic risk score for coronary heart disease have independent and incremental prognostic value compared with conventional cardiovascular risk assessment. 330 Risk of macrovascular complications in patients with diabetes and retinal artery occlusion for at least 5 years after an obstruction event is increased compared with those who do not have such occlusion. Therefore, retinopathy can predict cardiovascular risk in patients with T2DM.…”

Section: Introductionmentioning

confidence: 99%

Diabetic vascular diseases: molecular mechanisms and therapeutic strategies

Liu

et al. 2023

Sig Transduct Target Ther

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Vascular complications of diabetes pose a severe threat to human health. Prevention and treatment protocols based on a single vascular complication are no longer suitable for the long-term management of patients with diabetes. Diabetic panvascular disease (DPD) is a clinical syndrome in which vessels of various sizes, including macrovessels and microvessels in the cardiac, cerebral, renal, ophthalmic, and peripheral systems of patients with diabetes, develop atherosclerosis as a common pathology. Pathological manifestations of DPDs usually manifest macrovascular atherosclerosis, as well as microvascular endothelial function impairment, basement membrane thickening, and microthrombosis. Cardiac, cerebral, and peripheral microangiopathy coexist with microangiopathy, while renal and retinal are predominantly microangiopathic. The following associations exist between DPDs: numerous similar molecular mechanisms, and risk-predictive relationships between diseases. Aggressive glycemic control combined with early comprehensive vascular intervention is the key to prevention and treatment. In addition to the widely recommended metformin, glucagon-like peptide-1 agonist, and sodium-glucose cotransporter-2 inhibitors, for the latest molecular mechanisms, aldose reductase inhibitors, peroxisome proliferator-activated receptor-γ agonizts, glucokinases agonizts, mitochondrial energy modulators, etc. are under active development. DPDs are proposed for patients to obtain more systematic clinical care requires a comprehensive diabetes care center focusing on panvascular diseases. This would leverage the advantages of a cross-disciplinary approach to achieve better integration of the pathogenesis and therapeutic evidence. Such a strategy would confer more clinical benefits to patients and promote the comprehensive development of DPD as a discipline.

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“…Oculomics is an emerging research area that utilizes ocular information derived from non-invasive and easily accessible ocular examinations to gain insights into systemic health. Some researchers have reported the use of oculomics in the context of PPPM [ 25 ], especially for the use of oculomics of retinal vascular morphological features (RVFs) as prediction biomarkers for cardiovascular diseases (CVDs) [ 26 – 29 ]. However, only a few studies have investigated their relationship with aneurysms [ 30 , 31 ].…”

Section: Introductionmentioning

confidence: 99%

Integrating oculomics with genomics reveals imaging biomarkers for preventive and personalized prediction of arterial aneurysms

et al. 2023

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Objective Arterial aneurysms are life-threatening but usually asymptomatic before requiring hospitalization. Oculomics of retinal vascular features (RVFs) extracted from retinal fundus images can reflect systemic vascular properties and therefore were hypothesized to provide valuable information on detecting the risk of aneurysms. By integrating oculomics with genomics, this study aimed to (i) identify predictive RVFs as imaging biomarkers for aneurysms and (ii) evaluate the value of these RVFs in supporting early detection of aneurysms in the context of predictive, preventive and personalized medicine (PPPM). Methods This study involved 51,597 UK Biobank participants who had retinal images available to extract oculomics of RVFs. Phenome-wide association analyses (PheWASs) were conducted to identify RVFs associated with the genetic risks of the main types of aneurysms, including abdominal aortic aneurysm (AAA), thoracic aneurysm (TAA), intracranial aneurysm (ICA) and Marfan syndrome (MFS). An aneurysm-RVF model was then developed to predict future aneurysms. The performance of the model was assessed in both derivation and validation cohorts and was compared with other models employing clinical risk factors. An RVF risk score was derived from our aneurysm-RVF model to identify patients with an increased risk of aneurysms. Results PheWAS identified a total of 32 RVFs that were significantly associated with the genetic risks of aneurysms. Of these, the number of vessels in the optic disc (‘ntreeA’) was associated with both AAA (β = −0.36, P = 6.75e−10) and ICA (β = −0.11, P = 5.51e−06). In addition, the mean angles between each artery branch (‘curveangle_mean_a’) were commonly associated with 4 MFS genes (FBN1: β = −0.10, P = 1.63e−12; COL16A1: β = −0.07, P = 3.14e−09; LOC105373592: β = −0.06, P = 1.89e−05; C8orf81/LOC441376: β = 0.07, P = 1.02e−05). The developed aneurysm-RVF model showed good discrimination ability in predicting the risks of aneurysms. In the derivation cohort, the C-index of the aneurysm-RVF model was 0.809 [95% CI: 0.780–0.838], which was similar to the clinical risk model (0.806 [0.778–0.834]) but higher than the baseline model (0.739 [0.733–0.746]). Similar performance was observed in the validation cohort, with a C-index of 0.798 (0.727–0.869) for the aneurysm-RVF model, 0.795 (0.718–0.871) for the clinical risk model and 0.719 (0.620–0.816) for the baseline model. An aneurysm risk score was derived from the aneurysm-RVF model for each study participant. The individuals in the upper tertile of the aneurysm risk score had a significantly higher risk of aneurysm compared to those in the lower tertile (hazard ratio = 17.8 [6.5–48.8], P = 1.02e−05). Conclusion We identified a significant association between certain RVFs and the risk of aneurysms and revealed the impressive capability of using RVFs to predict the future risk of aneurysms by a PPPM approach. Our finds have great potential to support not only the predictive diagnosis of aneurysms but also a preventive and more personalized screening plan which may benefit both patients and the healthcare system. Graphical abstract

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Prediction of Major Adverse Cardiovascular Events From Retinal, Clinical, and Genomic Data in Individuals With Type 2 Diabetes: A Population Cohort Study

Cited by 15 publications

References 41 publications

Association Between Retinal Features From Multimodal Imaging and Schizophrenia

Association Between Retinal Features From Multimodal Imaging and Schizophrenia

Diabetic vascular diseases: molecular mechanisms and therapeutic strategies

Integrating oculomics with genomics reveals imaging biomarkers for preventive and personalized prediction of arterial aneurysms

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