Changes in Retinal Structure and Ultrastructure in the Aged Mice Correlate With Differences in the Expression of Selected Retinal miRNAs

Protective Effect of Topiramate against Diabetic Retinopathy and Computational Approach Recognizing the Role of NLRP3/IL-1β/TNF-α Signaling

The possible impact of topiramate against diabetic retinopathy (DREN) and its molecular mechanisms in relation to the nod-like receptor family pyrin domain containing 3 (NLRP3) inflammasome has not been studied before. Thus, in the present study, we aimed to utilize a computational approach to investigate the possible protective effect of topiramate on experimental DREN and explore its impact on NLRP3/interlukin-1β signaling and brain-derived neurotrophic factor (BDNF) expression. Male albino mice were distributed to four experimental groups and assigned the following categorizations: (i) saline, (ii) diabetic, (iii) diabetic + topiramate 10 mg/kg and (iv) diabetic + topiramate 30 mg/kg. We observed shrinkage of total retinal thickness and elevation in retinal glutamate, malondialdehyde, NLRP3 and interlukin-1β but decreased glutathione (GSH) levels in the diabetic mice. Additionally, retinal ultra-structures in the diabetic group showed abnormalities and vacuolations in the pigmented epithelium, the photoreceptor segment, the outer nuclear layer, the inner nuclear layer and the ganglion cell layer (GCL). Mice treated with topiramate 10 or 30 mg/kg showed downregulation in retinal malondialdehyde, NLRP3 and interlukin-1β levels; improvements in the retinal pathologies; enhanced immunostaining for BDNF and improved ultra-structures in different retinal layers. Overall, the current results suggest topiramate as a neuroprotective agent for DREN, and future studies are warranted to further elucidate the mechanism of its protective action.

Derivation of human retinal cell densities using high-density, spatially localized optical coherence tomography data from the human retina

This study sought to identify demographic variations in retinal thickness measurements from optical coherence tomography (OCT), to enable the calculation of cell density parameters across the neural layers of the healthy human macula. From macular OCTs (n = 247), ganglion cell (GCL), inner nuclear (INL), and inner segment-outer segment (ISOS) layer measurements were extracted using a customized high-density grid. Variations with age, sex, ethnicity, and refractive error were assessed with multiple linear regression analyses, with age-related distributions further assessed using hierarchical cluster analysis and regression models. Models were tested on a naïve healthy cohort (n = 40) with Mann-Whitney tests to determine generalizability. Quantitative cell density data were calculated from histological data from previous human studies. Eccentricity-dependent variations in OCT retinal thickness closely resemble topographic cell density maps from human histological studies. Age was consistently identified as significantly impacting retinal thickness (p = .0006, .0007, and .003 for GCL, INL and ISOS), with gender affecting ISOS only (p < .0001). Regression models demonstrated that age-related changes in the GCL and INL begin in the 30th decade and were linear for the ISOS. Model testing revealed significant differences in INL and ISOS thickness (p = .0008 and .0001; however, differences fell within the OCT's axial resolution. Qualitative comparisons show close alignment between OCT and histological cell densities when using unique, high-resolution OCT data, and correction for demographics-related variability. Overall, this study describes a process to calculate in vivo cell density from OCT for all neural layers of the human retina, providing a framework for basic science and clinical investigations.

Retinal imaging in animal models: Searching for biomarkers of neurodegeneration

There is a pressing need for novel diagnostic and progression biomarkers of neurodegeneration. However, the inability to determine disease duration and stage in patients with Alzheimer's disease (AD) hinders their discovery. Because animal models of disease allow us to circumvent some of these limitations, they have proven to be of paramount importance in clinical research. Due to the clear optics of the eye, the retina combined with optical coherence tomography (OCT) offers the perfect opportunity to image neurodegeneration in the retina in vivo, non-invasively, directly, quickly, and inexpensively. Based on these premises, our group has worked towards uncovering neurodegeneration-associated changes in the retina of the triple-transgenic mouse model of familial AD (3×Tg-AD). In this work, we present an overview of our work on this topic. We report on thickness variations of the retina and retinal layers/layer aggregates caused by healthy aging and AD-like conditions and discuss the implications of focusing research efforts solely on retinal thickness. We explore what other information is embedded in the OCT data, extracted based on texture analysis and deep-learning approaches, to further identify biomarkers that could be used for early detection and diagnosis. We were able to detect changes in the retina of the animal model of AD as early as 1 month of age. We also discuss our work to develop an optical coherence elastography system to measure retinal elasticity, which can be used in conjunction with conventional OCT. Finally, we discuss the potential application of these technologies in human patients and the steps needed to make OCT a helpful screening tool for the detection of neurodegeneration.

Serum miRNA modulations indicate changes in retinal morphology

Background

Age-related macular degeneration (AMD) is the leading cause of vision loss in the developed world and the detection of its onset and progression are based on retinal morphological assessments. MicroRNA (miRNA) have been explored extensively as biomarkers for a range of neurological diseases including AMD, however differences in experimental design and the complexity of human biology have resulted in little overlap between studies. Using preclinical animal models and clinical samples, this study employs a novel approach to determine a serum signature of AMD progression.

Methods

Serum miRNAs were extracted from mice exposed to photo-oxidative damage (PD; 0, 1, 3 and 5 days), and clinical samples from patients diagnosed with reticular pseudodrusen or atrophic AMD. The expression of ~800 miRNAs was measured using OpenArray™, and differential abundance from controls was determined using the HTqPCR R package followed by pathway analysis with DAVID. MiRNA expression changes were compared against quantifiable retinal histological indicators. Finally, the overlap of miRNA changes observed in the mouse model and human patient samples was investigated.

Results

Differential miRNA abundance was identified at all PD time-points and in clinical samples. Importantly, these were associated with inflammatory pathways and histological changes in the retina. Further, we were able to align findings in the mouse serum to those of clinical patients.

Conclusion

In conclusion, serum miRNAs are a valid tool as diagnostics for the early detection of retinal degeneration, as they reflect key changes in retinal health. The combination of pre-clinical animal models and human patient samples led to the identification of a preliminary serum miRNA signature for AMD. This study is an important platform for the future development of a diagnostic serum miRNA panel for the early detection of retinal degeneration.

Retinal Aging in 3× Tg-AD Mice Model of Alzheimer's Disease

The retina, as part of the central nervous system (CNS), can be the perfect target for in vivo, in situ, and noninvasive neuropathology diagnosis and assessment of therapeutic efficacy. It has long been established that several age-related brain changes are more pronounced in Alzheimer's disease (AD). Nevertheless, in the retina such link is still under-explored. This study investigates the differences in the aging of the CNS through the retina of 3× Tg-AD and wild-type mice. A dedicated optical coherence tomograph imaged mice's retinas for 16 months. Two neural networks were developed to model independently each group's ages and were then applied to an independent set containing images from both groups. Our analysis shows a mean absolute error of 0.875±1.1 × 10⁻² and 1.112±1.4 × 10⁻² months, depending on training group. Our deep learning approach appears to be a reliable retinal OCT aging marker. We show that retina aging is distinct in the two classes: the presence of the three mutated human genes in the mouse genome has an impact on the aging of the retina. For mice over 4 months-old, transgenic mice consistently present a negative retina age-gap when compared to wild-type mice, regardless of training set. This appears to contradict AD observations in the brain. However, the ‘black-box” nature of deep-learning implies that one cannot infer reasoning. We can only speculate that some healthy age-dependent neural adaptations may be altered in transgenic animals.

miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale

Analyzing all features of small non-coding RNA sequencing data can be demanding and challenging. To facilitate this process, we developed miRMaster. After the analysis of over 125 000 human samples and 1.5 trillion human small RNA reads over 4 years, we present miRMaster 2 with a wide range of updates and new features. We extended our reference data sets so that miRMaster 2 now supports the analysis of eight species (e.g. human, mouse, chicken, dog, cow) and 10 non-coding RNA classes (e.g. microRNAs, piRNAs, tRNAs, rRNAs, circRNAs). We also incorporated new downstream analysis modules such as batch effect analysis or sample embeddings using UMAP, and updated annotation data bases included by default (miRBase, Ensembl, GtRNAdb). To accommodate the increasing popularity of single cell small-RNA sequencing data, we incorporated a module for unique molecular identifier (UMI) processing. Further, the output tables and graphics have been improved based on user feedback and new output formats that emerged in the community are now supported (e.g. miRGFF3). Finally, we integrated differential expression analysis with the miRNA enrichment analysis tool miEAA. miRMaster is freely available at https://www.ccb.uni-saarland.de/mirmaster2.

Sex and Age-Related Differences in Neuroinflammation and Apoptosis in Balb/c Mice Retina Involve Resolvin D1

(1) Background: The pro-resolving lipid mediator Resolvin D1 (RvD1) has already shown protective effects in animal models of diabetic retinopathy. This study aimed to investigate the retinal levels of RvD1 in aged (24 months) and younger (3 months) Balb/c mice, along with the activation of macro- and microglia, apoptosis, and neuroinflammation. (2) Methods: Retinas from male and female mice were used for immunohistochemistry, immunofluorescence, transmission electron microscopy, Western blotting, and enzyme-linked immunosorbent assays. (3) Results: Endogenous retinal levels of RvD1 were reduced in aged mice. While RvD1 levels were similar in younger males and females, they were markedly decreased in aged males but less reduced in aged females. Both aged males and females showed a significant increase in retinal microglia activation compared to younger mice, with a more marked reactivity in aged males than in aged females. The same trend was shown by astrocyte activation, neuroinflammation, apoptosis, and nitrosative stress, in line with the microglia and Müller cell hypertrophy evidenced in aged retinas by electron microscopy. (4) Conclusions: Aged mice had sex-related differences in neuroinflammation and apoptosis and low retinal levels of endogenous RvD1.