Fully automated epicardial adipose tissue volume quantification with deep learning and relationship with CAC score and micro/macrovascular complications in people living with type 2 diabetes: the multicenter EPIDIAB study.

BACKGROUND: The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipose tissue (EAT) and the micro and macrovascular complications (MVC) of type 2 diabetes (T2D). METHODS: EPIDIAB is a post hoc analysis from the AngioSafe T2D study, which is a multicentric study aimed at determining the safety of antihyperglycemic drugs on retina and including patients with T2D screened for diabetic retinopathy (DR) (n = 7200) and deeply phenotyped for MVC. Patients included who had undergone cardiac CT for CAC (Coronary Artery Calcium) scoring after inclusion (n = 1253) were tested with a validated deep learning segmentation pipeline for EAT volume quantification. RESULTS: Median age of the study population was 61 [54;67], with a majority of men (57%) a median duration of the disease 11 years [5;18] and a mean HbA1c of7.8 ± 1.4%. EAT was significantly associated with all traditional CV risk factors. EAT volume significantly increased with chronic kidney disease (CKD vs no CKD: 87.8 [63.5;118.6] vs 82.7 mL [58.8;110.8], p = 0.008), coronary artery disease (CAD vs no CAD: 112.2 [82.7;133.3] vs 83.8 mL [59.4;112.1], p = 0.0004, peripheral arterial disease (PAD vs no PAD: 107 [76.2;141] vs 84.6 mL[59.2; 114], p = 0.0005 and elevated CAC score (> 100 vs < 100 AU: 96.8 mL [69.1;130] vs 77.9 mL [53.8;107.7], p < 0.0001). By contrast, EAT volume was neither associated with DR, nor with peripheral neuropathy. We further evidenced a subgroup of patients with high EAT volume and a null CAC score. Interestingly, this group were more likely to be composed of young women with a high BMI, a lower duration of T2D, a lower prevalence of microvascular complications, and a higher inflammatory profile. CONCLUSIONS: Fully-automated EAT volume quantification could provide useful information about the risk of both renal and macrovascular complications in T2D patients.

Untargeted Multiomics Approach Coupling Lipidomics and Metabolomics Profiling Reveals New Insights in Diabetic Retinopathy.

Diabetic retinopathy (DR) is a microvascular complication of diabetes mellitus (DM) which is the main cause of vision loss in the working-age population. Currently known risk factors such as age, disease duration, and hemoglobin A1c lack sufficient efficiency to distinguish patients with early stages of DR. A total of 194 plasma samples were collected from patients with type 2 DM and DR (moderate to proliferative (PDR) or control (no or mild DR) matched for age, gender, diabetes duration, HbA1c, and hypertension. Untargeted lipidomic and metabolomic approaches were performed. Partial-least square methods were used to analyze the datasets. Levels of 69 metabolites and 85 lipid species were found to be significantly different in the plasma of DR patients versus controls. Metabolite set enrichment analysis indicated that pathways such as metabolism of branched-chain amino acids (methylglutaryl carnitine p = 0.004), the kynurenine pathway (tryptophan p < 0.001), and microbiota metabolism (p-Cresol sulfate p = 0.004) were among the most enriched deregulated pathways in the DR group. Moreover, Glucose-6-phosphate (p = 0.001) and N-methyl-glutamate (p < 0.001) were upregulated in DR. Subgroup analyses identified a specific signature associated with PDR, macular oedema, and DR associated with chronic kidney disease. Phosphatidylcholines (PCs) were dysregulated, with an increase of alkyl-PCs (PC O-42:5 p < 0.001) in DR, while non-ether PCs (PC 14:0-16:1, p < 0.001; PC 18:2-14:0, p < 0.001) were decreased in the DR group. Through an unbiased multiomics approach, we identified metabolites and lipid species that interestingly discriminate patients with or without DR. These features could be a research basis to identify new potential plasma biomarkers to promote 3P medicine.

Early humoral response to COVID-19 vaccination in patients living with obesity and diabetes in France. The COVPOP OBEDIAB study with results from the ANRS0001S COV-POPART cohort.

BACKGROUND: Patients with diabetes and obesity are populations at high-risk for severe COVID-19 outcomes and have shown blunted immune responses when administered different vaccines. Here we used the 'ANRS0001S COV-POPART' French nationwide multicenter prospective cohort to investigate early humoral response to COVID-19 vaccination in the sub-cohort ('COVPOP OBEDIAB') of patients with obesity and diabetes. METHODS: Patients with diabetes (n = 390, type 1 or 2) or obesity (n = 357) who had received two vaccine doses and had no history of previous COVID-19 infection and negative anti-nucleocapsid (NCP) antibodies were included and compared against healthy subjects (n = 573). Humoral response was assessed at baseline, at one month post-first dose (M0) and one-month post-second dose (M1), through percentage of responders (positive anti-spike SARS-CoV-2 IgG antibodies (Sabs), geometric means of Sabs; BAU/mL), proportion of individuals with anti-RBD antibodies, and proportion of individuals with anti-SARS-CoV-2-specific neutralizing antibodies (Nabs). Potential clinical and biological factors associated with weak response (defined as Sabs < 264 BAU/mL) and presence of non-reactive anti-RBD antibodies at M1 were evaluated. Univariate and multivariate regressions were performed to estimate crude and adjusted coefficients with 95 % confidence intervals. Poor glycemic control was defined as HbA1c ≥ 7.5 % at inclusion. RESULTS: Patients with diabetes, particularly type 2 diabetes, and patients with obesity were less likely to have positive Sabs and anti-RBD antibodies after the first and second dose compared to controls (p < 0.001). At M1, we found Sabs seroconversion in 94.1 % of patients with diabetes versus 99.7 % in controls, anti-RBD seroconversion in 93.8 % of patients with diabetes versus 99.1 % in controls, and Nabs seroconversion in 95.7 % of patients with diabetes versus 99.6 % in controls (all p < 0.0001). Sabs and anti-RBD seroconversion at M0 and M1 were also significantly lower in obese patients than controls, at respectively 82.1 % versus 89.9 % (p = 0.001; M0 Sabs), 94.4 % versus 99.7 % (p 0.001; M1 Sabs), 79.0 % vs 86.2 % (p = 0.004 M0 anti-RBD), and 96.99 % vs 99.1 % (p = 0.012 M1 anti-RBD). The factors associated with low vaccine response (BAU < 264/mL) in patients with diabetes were chronic kidney disease (adjusted OR = 6.88 [1.77;26.77], p = 0.005) and poor glycemic control (adjusted OR = 3.92 [1.26;12.14], p = 0.018). In addition, BMI ≥ 40 kg/m2 was found to be associated with a higher vaccine response (adjusted OR = 0.10 [0.01;0.91], p = 0.040) than patients with BMI < 40 kg/m2. CONCLUSION: COVID-19 vaccine humoral response was lower in patients with obesity and diabetes one month after second dose compared to controls, especially in diabetic patients with CKD or inadequate glycemic control. These findings point to the need for post-vaccination serological checks in these high-risk populations.

Evolution of Quantitative Optical Coherence Tomography Angiography Markers with Glycemic Control: A Pilot Study.

Aim: We aimed to analyze changes in retinal microvascularization with intensive reduction of glycated hemoglobin A1c (HbA1c) in patients with poorly controlled diabetes using quantitative optical coherence tomography angiography (OCT-A) metrics. Method: This was a retrospective observational study in patients with uncontrolled diabetes admitted to the hospital for glycemic control. A second set of 15 healthy volunteers was included to serve as a control group. OCT-A was performed at inclusion and at 3 months to measure foveal avascular zone area (FAZA), vessel density (VD) of the superficial capillary plexus (SCP) and deep capillary plexus (DCP), acircularity index (AI), and fractal dimension (FD). Results: This analysis included 35 patients (35 eyes): 28 type-2 diabetics and 7 type-1 diabetics. Mean HbA1c was 13.1 ± 2.0% at inclusion and 7.0 ± 1.5% at 3 months. In the short period from inclusion to 3 months post-inclusion, patients showed significant decrease in VD−DCP (28.8% vs. 27.8%; p = 0.014), a significant increase in FAZA (0.300 mm2 vs. 0.310 mm2; p < 0.001), and a significant increase in AI (1.31 vs. 1.34; p < 0.01). Multivariate analysis found an increase in FAZA was correlated with baseline HbA1c level and age (R2 = 0.330), and a decrease in VD-DCP was correlated with HbA1c decrease and diabetes duration (R2 = 0.286). Conclusions: Rapid glycemic control in patients with uncontrolled diabetes led to possible short-term microvascular damage that correlated to both initial and decreased HbA1c.

Phenotypic Characteristics and Development of a Hospitalization Prediction Risk Score for Outpatients with Diabetes and COVID-19: The DIABCOVID Study.

Diabetes mellitus (DM) has been identified as a risk factor for severe COVID-19. DM is highly prevalent in the general population. Defining strategies to reduce the health care system burden and the late arrival of some patients thus seems crucial. The study aim was to compare phenotypic characteristics between in and outpatients with diabetes and infected by COVID-19, and to build an easy-to-use hospitalization prediction risk score. This was a retrospective observational study. Patients with DM and laboratory- or CT-confirmed COVID-19, who did (n = 185) and did not (n = 159) require hospitalization between 10 March and 10 April 2020, were compared. Data on diabetes duration, treatments, glycemic control, complications, anthropometrics and peripheral oxygen saturation (SpO2) were collected from medical records. Stepwise multivariate logistic regressions and ROC analyses were performed to build the DIAB score, a score using no more than five easy-to-collect clinical parameters predicting the risk of hospitalization. The DIAB score was then validated in two external cohorts (n = 132 and n = 2036). Hospitalized patients were older (68.0 ± 12.6 vs. 55.2 ± 12.6 years, p < 0.001), with more class III obesity (BMI ≥ 40 kg/m2, 9.7 vs. 3.5%, p = 0.03), hypertension (81.6 vs. 44.3%, p < 0.0001), insulin therapy (37% vs. 23.7%, p = 0.009), and lower SpO2 (91.6 vs. 97.3%, p < 0.0001) than outpatients. Type 2 DM (T2D) was found in 94% of all patients, with 10 times more type 1 DM in the outpatient group (11.3 vs. 1.1%, p < 0.0001). A DIAB score > 27 points predicted hospitalization (sensitivity 77.7%, specificity 89.2%, AUC = 0.895), and death within 28 days. Its performance was validated in the two external cohorts. Outpatients with diabetes were found to be younger, with fewer diabetic complications and less severe obesity than inpatients. DIAB score is an easy-to-use score integrating five variables to help clinicians better manage patients with DM and avert the saturation of emergency care units.

Glucagon-like Peptide 1 Receptor Agonists, Diabetic Retinopathy and Angiogenesis: The AngioSafe Type 2 Diabetes Study.

AIMS: Recent trials provide conflicting results on the association between glucagon-like peptide 1 receptor agonists (GLP-1RA) and diabetic retinopathy (DR). The aim of the AngioSafe type 2 diabetes (T2D) study was to determine the role of GLP-1RA in angiogenesis using clinical and preclinical models. METHODS: We performed two studies in humans. In study 1, we investigated the effect of GLP-1RA exposure from T2D diagnosis on the severity of DR, as diagnosed with retinal imaging (fundus photography). In study 2, a randomized 4-week trial, we assessed the effect of liraglutide on circulating hematopoietic progenitor cells (HPCs), and angio-miRNAs.We then studied the experimental effect of Exendin-4, on key steps of angiogenesis: in vitro on human endothelial cell proliferation, survival and three-dimensional vascular morphogenesis; and in vivo on ischemia-induced neovascularization of the retina in mice. RESULTS: In the cohort of 3154 T2D patients, 10% displayed severe DR. In multivariate analysis, sex, disease duration, glycated hemoglobin (HbA1c), micro- and macroangiopathy, insulin therapy and hypertension remained strongly associated with severe DR, while no association was found with GLP-1RA exposure (o 1.139 [0.800-1.622], P = .47). We further showed no effect of liraglutide on HPCs, and angio-miRNAs. In vitro, we demonstrated that exendin-4 had no effect on proliferation and survival of human endothelial cells, no effect on total length and number of capillaries. Finally, in vivo, we showed that exendin-4 did not exert any negative effect on retinal neovascularization. CONCLUSIONS: The AngioSafe T2D studies provide experimental and clinical data confirming no effect of GLP-1RA on angiogenesis and no association between GLP-1 exposure and severe DR.