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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.

The epicardial adipose tissue (EAT) is the visceral fat depot of the heart which is highly plastic and in direct contact with myocardium and coronary arteries. Because of its singular proximity with the myocardium, the adipokines and pro-inflammatory molecules secreted by this tissue may directly affect the metabolism of the heart and coronary arteries. Its accumulation, measured by recent new non-invasive imaging modalities, has been prospectively associated with the onset and progression of coronary artery disease (CAD) and atrial fibrillation in humans. Recent studies have shown that EAT exhibits beige fat-like features, and express uncoupling protein 1 (UCP-1) at both mRNA and protein levels. However, this thermogenic potential could be lost with age, obesity and CAD. Here we provide an overview of the physiological and pathophysiological relevance of EAT and further discuss whether its thermogenic properties may serve as a target for obesity therapeutic management with a specific focus on the role of immune cells in this beiging phenomenon.

Background: To develop a deep-learning (DL) pipeline that allowed an automated segmentation of epicardial adipose tissue (EAT) from low-dose computed tomography (LDCT) and investigate the link between EAT and COVID-19 clinical outcomes. Methods: This monocentric retrospective study included 353 patients: 95 for training, 20 for testing, and 238 for prognosis evaluation. EAT segmentation was obtained after thresholding on a manually segmented pericardial volume. The model was evaluated with Dice coefficient (DSC), inter-and intraobserver reproducibility, and clinical measures. Uni-and multi-variate analyzes were conducted to assess the prognosis value of the EAT volume, EAT extent, and lung lesion extent on clinical outcomes, including hospitalization, oxygen therapy, intensive care unit admission and death. Results: The mean DSC for EAT volumes was 0.85 ± 0.05. For EAT volume, the mean absolute error was 11.7 ± 8.1 cm3 with a non-significant bias of −4.0 ± 13.9 cm3 and a correlation of 0.963 with the manual measures (p < 0.01). The multivariate model providing the higher AUC to predict adverse outcome include both EAT extent and lung lesion extent (AUC = 0.805). Conclusions: A DL algorithm was developed and evaluated to obtain reproducible and precise EAT segmentation on LDCT. EAT extent in association with lung lesion extent was associated with adverse clinical outcomes with an AUC = 0.805.

In magnetic resonance imaging (MRI), epicardial adipose tissue (EAT) overload remains often overlooked due to tedious manual contouring in images. Automated four-chamber EAT area quantification was proposed, leveraging deep-learning segmentation using multi-frame fully convolutional networks (FCN). The investigation involved 100 subjects—comprising healthy, obese, and diabetic patients—who underwent 3T cardiac cine MRI, optimized U-Net and FCN (noted FCNB) were trained on three consecutive cine frames for segmentation of central frame using dice loss. Networks were trained using 4-fold cross-validation (n = 80) and evaluated on an independent dataset (n = 20). Segmentation performances were compared to inter-intra observer bias with dice (DSC) and relative surface error (RSE). Both systole and diastole four-chamber area were correlated with total EAT volume (r = 0.77 and 0.74 respectively). Networks’ performances were equivalent to inter-observers’ bias (EAT: DSCInter = 0.76, DSCU-Net = 0.77, DSCFCNB = 0.76). U-net outperformed (p < 0.0001) FCNB on all metrics. Eventually, proposed multi-frame U-Net provided automated EAT area quantification with a 14.2% precision for the clinically relevant upper three quarters of EAT area range, scaling patients’ risk of EAT overload with 70% accuracy. Exploiting multi-frame U-Net in standard cine provided automated EAT quantification over a wide range of EAT quantities. The method is made available to the community through a FSLeyes plugin.

This study details the clinical and cellular phenotypes associated with two missense heterozygous mutations in LMNA, c.1745G>T p.(Arg582Leu), and c.1892G>A p.(Gly631Asp), in two patients with early onset of diabetes mellitus, hypertriglyceridemia and non-alcoholic fatty liver disease. In these two patients, subcutaneous adipose tissue was persistent, at least on the abdomen, and the serum leptin level remained in the normal range. Cellular studies showed elevated nuclear anomalies, an accelerated senescence rate and a decrease of replication capacity in patient cells. In cellular models, the overexpression of mutated prelamin A phenocopied misshapen nuclei, while the partial reduction of lamin A expression in patient cells significantly improved nuclear morphology. Altogether, these results suggest a link between lamin A mutant expression and senescence associated phenotypes. Transcriptome analysis of the whole subcutaneous adipose tissue from the two patients and three controls, paired for age and sex using RNA sequencing, showed the up regulation of genes implicated in immunity and the down regulation of genes involved in development and cell differentiation in patient adipose tissue. Therefore, our results suggest that some mutations in LMNA are associated with severe metabolic phenotypes without subcutaneous lipoatrophy, and are associated with nuclear misshaping.

ZMPSTE24 encodes the only metalloprotease, which transforms prelamin into mature lamin A. Up to now, mutations in ZMPSTE24 have been linked to Restrictive Dermopathy (RD), Progeria or Mandibulo-Acral Dysplasia (MAD). We report here the phenotype of a patient referred for severe metabolic syndrome and cardiomyopathy, carrying a mutation in ZMPSTE24. The patient presented with a partial lipodystrophic syndrome associating hypertriglyceridemia, early onset type 2 diabetes, and android obesity with truncal and abdominal fat accumulation but without subcutaneous lipoatrophy. Other clinical features included acanthosis nigricans, liver steatosis, dilated cardiomyopathy, and high myocardial and hepatic triglycerides content. Mutated fibroblasts from the patient showed increased nuclear shape abnormalities and premature senescence as demonstrated by a decreased Population Doubling Level, an increased beta-galactosidase activity and a decreased BrdU incorporation rate. Reduced prelamin A expression by siRNA targeted toward LMNA transcripts resulted in decreased nuclear anomalies. We show here that a central obesity without subcutaneous lipoatrophy is associated with a laminopathy due to a heterozygous missense mutation in ZMPSTE24. Given the high prevalence of metabolic syndrome and android obesity in the general population, and in the absence of familial study, the causative link between mutation and phenotype cannot be formally established. Nevertheless, altered lamina architecture observed in mutated fibroblasts are responsible for premature cellular senescence and could contribute to the phenotype observed in this patient.