Past, present and future role of retinal imaging in neurodegenerative disease

High Levels of Mutant Huntingtin Protein in Tear Fluid From Huntington's Disease Gene Expansion Carriers

OBJECTIVE

Huntington's disease (HD) is an autosomal dominant, fully penetrant, neurodegenerative disease that most commonly affects middle-aged adults. HD is caused by a CAG repeat expansion in the HTT gene, resulting in the expression of mutant huntingtin (mHTT). Our aim was to detect and quantify mHTT in tear fluid, which, to our knowledge, has never been measured before.

METHODS

We recruited 20 manifest and 13 premanifest HD gene expansion carriers, and 20 age-matched controls. All patients underwent detailed assessments, including the Unified Huntington's Disease Rating Scale (UHDRS) total motor score (TMS) and total functional capacity (TFC) score. Tear fluid was collected using paper Schirmer's strips. The level of tear mHTT was determined using single-molecule counting SMCxPRO technology.

RESULTS

The average tear mHTT levels in manifest (67,223 ± 80,360 fM) and premanifest patients (55,561 ± 45,931 fM) were significantly higher than those in controls (1,622 ± 2,179 fM). We noted significant correlations between tear mHTT levels and CAG repeat length, "estimated years to diagnosis," disease burden score and UHDRS TMS and TFC. The receiver operating curve demonstrated an almost perfect score (area under the curve [AUC] = 0.9975) when comparing controls to manifest patients. Similarly, the AUC between controls and premanifest patients was 0.9846. The optimal cutoff value for distinguishing between controls and manifest patients was 4,544 fM, whereas it was 6,596 fM for distinguishing between controls and premanifest patients.

CONCLUSION

Tear mHTT has potential for early and noninvasive detection of alterations in HD patients and could be integrated into both clinical trials and clinical diagnostics.

Artificial intelligence in the diagnosis of glaucoma and neurodegenerative diseases

Artificial Intelligence is a rapidly expanding field within computer science that encompasses the emulation of human intelligence by machines. Machine learning and deep learning - two primary data-driven pattern analysis approaches under the umbrella of artificial intelligence - has created considerable interest in the last few decades. The evolution of technology has resulted in a substantial amount of artificial intelligence research on ophthalmic and neurodegenerative disease diagnosis using retinal images. Various artificial intelligence-based techniques have been used for diagnostic purposes, including traditional machine learning, deep learning, and their combinations. Presented here is a review of the literature covering the last 10 years on this topic, discussing the use of artificial intelligence in analysing data from different modalities and their combinations for the diagnosis of glaucoma and neurodegenerative diseases. The performance of published artificial intelligence methods varies due to several factors, yet the results suggest that such methods can potentially facilitate clinical diagnosis. Generally, the accuracy of artificial intelligence-assisted diagnosis ranges from 67-98%, and the area under the sensitivity-specificity curve (AUC) ranges from 0.71-0.98, which outperforms typical human performance of 71.5% accuracy and 0.86 area under the curve. This indicates that artificial intelligence-based tools can provide clinicians with useful information that would assist in providing improved diagnosis. The review suggests that there is room for improvement of existing artificial intelligence-based models using retinal imaging modalities before they are incorporated into clinical practice.

Multifunctional adaptive optics optical coherence tomography allows cellular scale reflectometry, polarimetry, and angiography in the living human eye

Clinicians are unable to detect glaucoma until substantial loss or dysfunction of retinal ganglion cells occurs. To this end, novel measures are needed. We have developed an optical imaging solution based on adaptive optics optical coherence tomography (AO-OCT) to discern key clinical features of glaucoma and other neurodegenerative diseases at the cellular scale in the living eye. Here, we test the feasibility of measuring AO-OCT-based reflectance, retardance, optic axis orientation, and angiogram at specifically targeted locations in the living human retina and optic nerve head. Multifunctional imaging, combined with focus stacking and global image registration algorithms, allows us to visualize cellular details of retinal nerve fiber bundles, ganglion cell layer somas, glial septa, superior vascular complex capillaries, and connective tissues. These are key histologic features of neurodegenerative diseases, including glaucoma, that are now measurable in vivo with excellent repeatability and reproducibility. Incorporating this noninvasive cellular-scale imaging with objective measurements will significantly enhance existing clinical assessments, which is pivotal in facilitating the early detection of eye disease and understanding the mechanisms of neurodegeneration.

Retinal perfusion is linked to cognition and brain MRI biomarkers in Black Americans

INTRODUCTION

We investigated whether retinal capillary perfusion is a biomarker of cerebral small vessel disease and impaired cognition among Black Americans, an understudied group at higher risk for dementia.

METHODS

We enrolled 96 Black Americans without known cognitive impairment. Four retinal perfusion measures were derived using optical coherence tomography angiography. Neurocognitive assessment and brain magnetic resonance imaging (MRI) were performed. Multiple linear regression analyses were performed.

RESULTS

Lower retinal capillary perfusion was correlated with worse Oral Symbol Digit Test (P < = 0.005) and Fluid Cognition Composite scores (P < = 0.02), but not with the Crystallized Cognition Composite score (P > = 0.41). Lower retinal perfusion was also correlated with higher free water and peak width of skeletonized mean diffusivity, and lower fractional anisotropy (all P < 0.05) on MRI (N = 35).

DISCUSSION

Lower retinal capillary perfusion is associated with worse information processing, fluid cognition, and MRI biomarkers of cerebral small vessel disease, but is not related to crystallized cognition.

Impacts of Chronic Kidney Disease on Retinal Neurodegeneration: A Cross-Cohort Analysis

PURPOSE

To assess the cross-sectional and longitudinal associations between chronic kidney disease (CKD) and ganglion cell-inner plexiform layer (GCIPL) thickness in a UK Biobank population and a Chinese cohort.

DESIGN

Prospective observational cohort study and cross-sectional study.

METHOD

This study included 23,014 individuals without neurodegenerative diseases from the UK Biobank, and 3 years of annual follow-up data of 2197 individuals from a Chinese cohort. Three groups were defined by estimated glomerular filtration rate (eGFR) based on serum creatinine classifying CKD severity as no CKD, mild CKD, and moderate to severe CKD (MS-CKD). GCIPL thickness, measured using optical coherence tomography, was analyzed through linear regression over time to determine its decline rate in micrometers per year. Linear regression models were used to assess the correlation between renal function and both the baseline GCIPL thickness and the GCIPL decline rate.

RESULTS

The cross-sectional analysis in a largely white population showed that poorer renal function negatively correlated with GCIPL thickness with a mean of 0.15 µm thinner (95% confidence interval [CI] -0.30 to -0.01; P = .042) in mild CKD and 0.83 µm thinner (95% CI -1.34 to -0.32; P = .001) in MS-CKD compared with that of control subjects without CKD. Longitudinal analysis in the Chinese cohort showed that the GCIPL decreased more rapidly in persons with poorer renal function. After correcting for all confounding factors, the rate of GCIPL thinning was 0.30 µm/year (95% CI -0.41 to -0.19; P < .001) more in the mild CKD group and 0.52 µm/year (95% CI -0.79 to -0.26; P < .001) more in the MS-CKD group compared with control subjects without CKD. This relationship also occurred in individuals with diabetes or hypertension.

CONCLUSIONS

Poor renal function was associated with a lower baseline GCIPL thickness in the UK population and a faster decline rate in Chinese participants. However, the detailed underlying mechanisms still need further exploration.

Deep Learning Models for the Screening of Cognitive Impairment Using Multimodal Fundus Images

OBJECTIVE

We aimed to develop a deep learning system capable of identifying subjects with cognitive impairment quickly and easily based on multimodal ocular images.

DESIGN

Cross sectional study.

SUBJECTS

Participants of Beijing Eye Study 2011 and patients attending Beijing Tongren Eye Center and Beijing Tongren Hospital Physical Examination Center.

METHODS

We trained and validated a deep learning algorithm to assess cognitive impairment using retrospectively collected data from the Beijing Eye Study 2011. Cognitive impairment was defined as a Mini-Mental State Examination score < 24. Based on fundus photographs and OCT images, we developed 5 models based on the following sets of images: macula-centered fundus photographs, optic disc-centered fundus photographs, fundus photographs of both fields, OCT images, and fundus photographs of both fields with OCT (multimodal). The performance of the models was evaluated and compared in an external validation data set, which was collected from patients attending Beijing Tongren Eye Center and Beijing Tongren Hospital Physical Examination Center.

MAIN OUTCOME MEASURES

Area under the curve (AUC).

RESULTS

A total of 9424 retinal photographs and 4712 OCT images were used to develop the model. The external validation sets from each center included 1180 fundus photographs and 590 OCT images. Model comparison revealed that the multimodal performed best, achieving an AUC of 0.820 in the internal validation set, 0.786 in external validation set 1, and 0.784 in external validation set 2. We evaluated the performance of the multi-model in different sexes and different age groups; there were no significant differences. The heatmap analysis showed that signals around the optic disc in fundus photographs and the retina and choroid around the macular and optic disc regions in OCT images were used by the multimodal to identify participants with cognitive impairment.

CONCLUSIONS

Fundus photographs and OCT can provide valuable information on cognitive function. Multimodal models provide richer information compared with single-mode models. Deep learning algorithms based on multimodal retinal images may be capable of screening cognitive impairment. This technique has potential value for broader implementation in community-based screening or clinic settings.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Ocular biomarkers of cognitive decline based on deep-learning retinal vessel segmentation

BACKGROUND

The current literature shows a strong relationship between retinal neuronal and vascular alterations in dementia. The purpose of the study was to use NFN+ deep learning models to analyze retinal vessel characteristics for cognitive impairment (CI) recognition.

METHODS

We included 908 participants from a community-based cohort followed for over 15 years (the prospective KaiLuan Study) who underwent brain magnetic resonance imaging (MRI) and fundus photography between 2021 and 2022. The cohort consisted of both cognitively healthy individuals (N = 417) and those with cognitive impairment (N = 491). We employed the NFN+ deep learning framework for retinal vessel segmentation and measurement. Associations between Retinal microvascular parameters (RMPs: central retinal arteriolar / venular equivalents, arteriole to venular ratio, fractal dimension) and CI were assessed by Pearson correlation. P < 0.05 was considered statistically significant. The correlation between the CI and RMPs were explored, then the correlation coefficients between CI and RMPs were analyzed. Random Forest nonlinear classification model was used to predict whether one having cognitive decline or not. The assessment criterion was the AUC value derived from the working characteristic curve.

RESULTS

The fractal dimension (FD) and global vein width were significantly correlated with the CI (P < 0.05). Age (0.193), BMI (0.154), global vein width (0.106), retinal vessel FD (0.099), and CRAE (0.098) were the variables in this model that were ranked in order of feature importance. The AUC values of the model were 0.799.

CONCLUSIONS

Establishment of a predictive model based on the extraction of vascular features from fundus images has a high recognizability and predictive power for cognitive function and can be used as a screening method for CI.

Ultra-Widefield Imaging of the Retinal Macrovasculature in Parkinson Disease Versus Controls With Normal Cognition Using Alpha-Shapes Analysis

Purpose

To investigate retinal vascular characteristics using ultra-widefield (UWF) scanning laser ophthalmoscopy in Parkinson disease (PD).

Methods

Individuals with an expert-confirmed clinical diagnosis of PD and controls with normal cognition without PD underwent Optos California UWF imaging. Patients with diabetes, uncontrolled hypertension, glaucoma, dementia, other movement disorders, or known retinal or optic nerve pathology were excluded. Images were analyzed using Vasculature Assessment and Measurement Platform for Images of the Retina (VAMPIRE-UWF) software, which describes retinal vessel width gradient and tortuosity, provides vascular network fractal dimensions, and conducts alpha-shape analysis to further characterize vascular morphology (complexity, Opαmin; spread, OpA).

Results

In the PD cohort, 53 eyes of 38 subjects were assessed; in the control cohort, 51 eyes of 33 subjects were assessed. Eyes with PD had more tortuous retinal arteries in the superotemporal quadrant (P = 0.043). In eyes with PD, alpha-shape analysis revealed decreased OpA, indicating less retinal vasculature spread compared to controls (P = 0.032). Opαmin was decreased in PD (P = 0.044), suggesting increased vascular network complexity. No differences were observed in fractal dimension in any region of interest.

Conclusions

This pilot study suggests that retinal vasculature assessment on UWF images using alpha-shape analysis reveals differences in retinal vascular network spread and complexity in PD and may be a more sensitive metric compared to fractal dimension.

Translational Relevance

Retinal vasculature assessment using these novel methods may be useful in understanding ocular manifestations of PD and the development of retinal biomarkers.

Thinner inner retinal layers are associated with lower cognitive performance, lower brain volume, and altered white matter network structure-The Maastricht Study

INTRODUCTION

The retina may provide non-invasive, scalable biomarkers for monitoring cerebral neurodegeneration.

METHODS

We used cross-sectional data from The Maastricht study (n = 3436; mean age 59.3 years; 48% men; and 21% with type 2 diabetes [the latter oversampled by design]). We evaluated associations of retinal nerve fiber layer, ganglion cell layer, and inner plexiform layer thicknesses with cognitive performance and magnetic resonance imaging indices (global grey and white matter volume, hippocampal volume, whole brain node degree, global efficiency, clustering coefficient, and local efficiency).

RESULTS

After adjustment, lower thicknesses of most inner retinal layers were significantly associated with worse cognitive performance, lower grey and white matter volume, lower hippocampal volume, and worse brain white matter network structure assessed from lower whole brain node degree, lower global efficiency, higher clustering coefficient, and higher local efficiency.

DISCUSSION

The retina may provide biomarkers that are informative of cerebral neurodegenerative changes in the pathobiology of dementia.

Retina pathology as a target for biomarkers for Alzheimer's disease: Current status, ophthalmopathological background, challenges, and future directions

There is emerging evidence that amyloid beta protein (Aβ) and tau-related lesions in the retina are associated with Alzheimer's disease (AD). Aβ and hyperphosphorylated (p)-tau deposits have been described in the retina and were associated with small amyloid spots visualized by in vivo imaging techniques as well as degeneration of the retina. These changes correlate with brain amyloid deposition as determined by histological quantification, positron emission tomography (PET) or clinical diagnosis of AD. However, the literature is not coherent on these histopathological and in vivo imaging findings. One important reason for this is the variability in the methods and the interpretation of findings across different studies. In this perspective, we indicate the critical methodological deviations among different groups and suggest a roadmap moving forward on how to harmonize (i) histopathologic examination of retinal tissue; (ii) in vivo imaging among different methods, devices, and interpretation algorithms; and (iii) inclusion/exclusion criteria for studies aiming at retinal biomarker validation.

Associations of inner retinal layers with risk of incident dementia: An individual participant data analysis of four prospective cohort studies

INTRODUCTION

Our main objective was to investigate whether retinal neurodegeneration, estimated from lower thickness of inner retinal layers, was associated with incident all-cause dementia and Alzheimer's disease (AD).

METHODS

We performed an individual participant data meta-analysis using unpublished data from four prospective cohort studies with a total of 69,955 participants (n = 1087 cases of incident all-cause dementia; n = 520 cases incident AD; follow-up time median [interquartile range] 11.3 [8.8-11.5] years).

RESULTS

General baseline characteristics of the study population were mean (standard deviation) age, 58.1 (8.8) years; 47% women. After adjustment, lower baseline macular retinal nerve fiber layer thickness was significantly associated with a 10% and 11% higher incidence of all-cause dementia and AD, respectively. Lower baseline macular ganglion cell-inner plexiform layer thickness was not significantly associated with these outcomes.

DISCUSSION

These findings suggest that retinal neurodegeneration precedes the onset of clinical dementia. Retinal imaging tools may be informative biomarkers for the study of the early pathophysiology of dementia.

Retinotopic degeneration of the retina and optic tracts in autosomal dominant Alzheimer's disease

INTRODUCTION

We investigated the correlation between retinal thickness and optic tract integrity in subjects with autosomal dominant Alzheimer's disease (ADAD) causing mutations.

METHODS

Retinal thicknesses and diffusion tensor images (DTI) were obtained using optical coherence tomography and magnetic resonance imaging, respectively. The association between retinal thickness and DTI measures was adjusted for age, sex, retinotopy, and correlation between eyes.

RESULTS

Optic tract mean diffusivity and axial diffusivity were negatively correlated with retinotopically defined ganglion cell inner plexiform thickness (GCIPL). Fractional anisotropy was negatively correlated with retinotopically defined retinal nerve fiber layer thickness. There was no correlation between outer nuclear layer (ONL) thickness and any DTI measure.

DISCUSSION

In ADAD, GCIPL thickness is significantly associated with retinotopic optic tract DTI measures even in minimally symptomatic subjects. Similar associations were not present with ONL thickness or when ignoring retinotopy. We provide in vivo evidence for optic tract changes resulting from ganglion cell pathology in ADAD.

Combining retinal structural and vascular measurements improves discriminative power for multiple sclerosis patients

Data on how retinal structural and vascular parameters jointly influence the diagnostic performance of detection of multiple sclerosis (MS) patients without optic neuritis (MSNON) are lacking. To investigate the diagnostic performance of structural and vascular changes to detect MSNON from controls, we performed a cross-sectional study of 76 eyes from 51 MS participants and 117 eyes from 71 healthy controls. Retinal macular ganglion cell complex (GCC), retinal nerve fiber layer (RNFL) thicknesses, and capillary densities from the superficial (SCP) and deep capillary plexuses (DCP) were obtained from the Cirrus AngioPlex. The best structural parameter for detecting MS was compensated RNFL from the optic nerve head (AUC = 0.85), followed by GCC from the macula (AUC = 0.79), while the best vascular parameter was the SCP (AUC = 0.66). Combining structural and vascular parameters improved the diagnostic performance for MS detection (AUC = 0.90; p<0.001). Including both structure and vasculature in the joint model considerably improved the discrimination between MSNON and normal controls compared to each parameter separately (p = 0.027). Combining optical coherence tomography (OCT)-derived structural metrics and vascular measurements from optical coherence tomography angiography (OCTA) improved the detection of MSNON. Further studies may be warranted to evaluate the clinical utility of OCT and OCTA parameters in the prediction of disease progression.

Potential Retinal Biomarkers in Alzheimer's Disease

Alzheimer's disease (AD) represents a major diagnostic challenge, as early detection is crucial for effective intervention. This review examines the diagnostic challenges facing current AD evaluations and explores the emerging field of retinal alterations as early indicators. Recognizing the potential of the retina as a noninvasive window to the brain, we emphasize the importance of identifying retinal biomarkers in the early stages of AD. However, the examination of AD is not without its challenges, as the similarities shared with other retinal diseases introduce complexity in the search for AD-specific markers. In this review, we address the relevance of using the retina for the early diagnosis of AD and the complex challenges associated with the search for AD-specific retinal biomarkers. We provide a comprehensive overview of the current landscape and highlight avenues for progress in AD diagnosis by retinal examination.

Retinal electrophysiology in central nervous system disorders. A review of human and mouse studies

The retina and brain share similar neurochemistry and neurodevelopmental origins, with the retina, often viewed as a "window to the brain." With retinal measures of structure and function becoming easier to obtain in clinical populations there is a growing interest in using retinal findings as potential biomarkers for disorders affecting the central nervous system. Functional retinal biomarkers, such as the electroretinogram, show promise in neurological disorders, despite having limitations imposed by the existence of overlapping genetic markers, clinical traits or the effects of medications that may reduce their specificity in some conditions. This narrative review summarizes the principal functional retinal findings in central nervous system disorders and related mouse models and provides a background to the main excitatory and inhibitory retinal neurotransmitters that have been implicated to explain the visual electrophysiological findings. These changes in retinal neurochemistry may contribute to our understanding of these conditions based on the findings of retinal electrophysiological tests such as the flash, pattern, multifocal electroretinograms, and electro-oculogram. It is likely that future applications of signal analysis and machine learning algorithms will offer new insights into the pathophysiology, classification, and progression of these clinical disorders including autism, attention deficit/hyperactivity disorder, bipolar disorder, schizophrenia, depression, Parkinson's, and Alzheimer's disease. New clinical applications of visual electrophysiology to this field may lead to earlier, more accurate diagnoses and better targeted therapeutic interventions benefiting individual patients and clinicians managing these individuals and their families.

PET imaging of retinal inflammation in mice exposed to blue light using [18F]-DPA-714

Purpose

Positron emission tomography (PET) is widely used in high-precision imaging, which may provide a simple and noninvasive method for the detection of pathology and therapeutic effects. [18F]-DPA-714 is a second-generation translocator protein (TSPO) positron emission tomography radiotracer that shows great promise in a model of neuroinflammation. In this study, [18F]-DPA-714 micro-PET imaging was used to evaluate retinal inflammation in mice exposed to blue light, a well-established model of age-related macular degeneration (AMD) for molecular mechanism research and drug screening.

Methods

C57BL/6J melanized mice were subjected to 10,000, 15,000, and 20,000 lux blue light for 5 days (8 h/day) to develop the retinal injury model, and the structure and function of the retina were assessed using hematoxylin-eosin (HE) staining, electroretinography (ERG), and terminal-deoxynucleotidyl transferase (TdT)-mediated nick-end labeling (TUNEL) immunostaining. Then, [18F]-DPA-714 was injected approximately 100 μCi through each tail vein, and static imaging was performed 1 h after injection. Finally, the mice eyeballs were collected for biodistribution and immune analysis.

Results

The blue light exposure significantly destroyed the structure and function of the retina, and the uptake of [18F]-DPA-714 in the retinas of the mice exposed to blue light were the most significantly upregulated, which was consistent with the biodistribution data. In addition, the immunohistochemical, western blot, and immunofluorescence data showed an increase in microglial TSPO expression.

Conclusions

[18F]-DPA-714 micro-PET imaging might be a good method for evaluating early inflammatory status during retinal pathology.

The gut-retina axis: a new perspective in the prevention and treatment of diabetic retinopathy

Diabetic retinopathy (DR) is a microvascular lesion that occurs as a complication of diabetes mellitus. Many studies reveal that retinal neurodegeneration occurs early in its pathogenesis, and abnormal retinal function can occur in patients without any signs of microvascular abnormalities. The gut microbiota is a large, diverse colony of microorganisms that colonize the human intestine. Studies indicated that the gut microbiota is involved in the pathophysiological processes of DR and plays an important role in its development. On the one hand, numerous studies demonstrated the involvement of gut microbiota in retinal neurodegeneration. On the other hand, alterations in gut bacteria in RD patients can cause or exacerbate DR. The present review aims to underline the critical relationship between gut microbiota and DR. After a brief overview of the composition, function, and essential role of the gut microbiota in ocular health, and the review explores the concept of the gut-retina axis and the conditions of the gut-retina axis crosstalk. Because gut dysbiosis has been associated with DR, the review intends to determine changes in the gut microbiome in DR, the hypothesized mechanisms linking to the gut-retina axis, and its predictive potential.

Association of long-term exposure to ambient air pollution with retinal neurodegeneration: The prospective alienor study

Chronic exposure to air pollution may have adverse effects on neurodegenerative diseases. Glaucoma, the second leading cause of blindness worldwide, is a neurodegenerative disease of the optic nerve, characterized by progressive thinning of the retinal nerve fiber layer (RNFL). We investigated the relationship of air pollution exposure with longitudinal changes of RNFL thickness in the Alienor study, a population-based cohort of residents of Bordeaux, France, aged 75 years or more. Peripapillary RNFL thickness was measured using optical coherence tomography imaging every 2 years from 2009 to 2020. Measurements were acquired and reviewed by specially trained technicians to control quality. Air pollution exposure (particulate matter ≤2.5 μm (PM_2.5), black carbon (BC), nitrogen dioxide (NO₂)) was estimated at the participants' geocoded residential address using land-use regression models. For each pollutant, the 10-year average of past exposure at first RNFL thickness measurement was estimated. Associations of air pollution exposure with RNFL thickness longitudinal changes were assessed using linear mixed models adjusted for potential confounders, allowing for intra-eye and intra-individual correlation (repeated measurements). The study included 683 participants with at least one RNFL thickness measurement (62% female, mean age 82 years). The average RNFL was 90 μm (SD:14.4) at baseline. Exposure to higher levels of PM_2.5 and BC in the previous 10 years was significantly associated with a faster RNFL thinning during the 11-year follow-up (-0.28 μm/year (95% confidence interval (CI) [-0.44;-0.13]) and -0.26 μm/year (95% CI [-0.40;-0.12]) per interquartile range increment; p < 0.001 for both). The size of the effect was similar to one year of age in the fitted model (-0.36 μm/year). No statistically significant associations were found with NO₂ in the main models. This study evidenced a strong association of chronic exposure to fine particulate matter with retinal neurodegeneration, at air pollution levels below the current recommended thresholds in Europe.

Epidemiology, Translation and Clinical Research of Ophthalmology

The human eye is a complex and vital organ that plays a significant role in maintaining a high quality of human life [...].

Retinal Functional and Structural Neural Indices: Potential Biomarkers for the Monitoring of Cerebral Neurodegeneration: The Maastricht Study

BACKGROUND

If retinal indices of neurodegeneration are to be biomarkers for the monitoring of cerebral neurodegeneration, it is important to establish whether potentially modifiable risk factors for dementia are associated with retinal neurodegenerative changes.

OBJECTIVE

To study associations of dementia risk factors with retinal sensitivity, an index of retinal neural function, and retinal nerve fiber layer (RNFL) thickness, an index of retinal neural structure.

METHODS

We used cross-sectional data from The Maastricht Study (up to 5,666 participants, 50.5% men, mean age 59.7), and investigated associations with regression analyses (adjusted for potential confounders).

RESULTS

Most risk factors under study (i.e., hyperglycemia, unhealthy diet, lower cardiorespiratory fitness, smoking, alcohol consumption, and hypertension) were significantly associated with lower retinal sensitivity and lower RNFL thickness.

CONCLUSION

Findings of this population-based study support the concept that retinal neural indices may be biomarkers for the monitoring of therapeutic strategies that aim to prevent early-stage cerebral neurodegeneration and, ultimately, dementia.

Retinal photoreceptor layer thickness has disease specificity and distinguishes predicted FTLD-Tau from biomarker-determined Alzheimer's disease

While Alzheimer's disease (AD) is associated with inner retina thinning (retinal nerve fiber layer and ganglion cell layer), we have observed photoreceptor outer nuclear layer (ONL) thinning in patients with frontotemporal lobar degeneration tauopathy (FTLD-Tau) compared to normal controls. We hypothesized that ONL thinning may distinguish FTLD-Tau from patients with biomarker evidence of AD neuropathologic change (ADNC) and will correlate with FTLD-Tau disease severity. Predicted FTLD-Tau (pFTLD-Tau; n = 21; 33 eyes) and predicted ADNC (pADNC; n = 24; 46 eyes) patients were consecutively enrolled, underwent optical coherence tomography macula imaging, and disease was categorized (pFTLD-Tau vs. pADNC) with cerebrospinal fluid biomarkers, genetic testing, and autopsy data when available. Adjusting for age, sex, and race, pFTLD-Tau patients had a thinner ONL compared to pADNC, while retinal nerve fiber layer and ganglion cell layer were not significantly different. Reduced ONL thickness correlated with worse performance on Folstein Mini-Mental State Examination and clinical dementia rating plus frontotemporal dementia sum of boxes for pFTLD-Tau but not pADNC. Photoreceptor ONL thickness may serve as an important noninvasive diagnostic marker that distinguishes FTLD-Tau from AD neuropathologic change.

Starburst amacrine cells, involved in visual motion perception, loose their synaptic input from dopaminergic amacrine cells and degenerate in Parkinson's disease patients

BACKGROUND

The main clinical symptoms characteristic of Parkinson's disease (PD) are bradykinesia, tremor, and other motor deficits. However, non-motor symptoms, such as visual disturbances, can be identified at early stages of the disease. One of these symptoms is the impairment of visual motion perception. Hence, we sought to determine if the starburst amacrine cells, which are the main cellular type involved in motion direction selectivity, are degenerated in PD and if the dopaminergic system is related to this degeneration.

METHODS

Human eyes from control (n = 10) and PD (n = 9) donors were available for this study. Using immunohistochemistry and confocal microscopy, we quantified starburst amacrine cell density (choline acetyltransferase [ChAT]-positive cells) and the relationship between these cells and dopaminergic amacrine cells (tyrosine hydroxylase-positive cells and vesicular monoamine transporter-2-positive presynapses) in cross-sections and wholemount retinas.

RESULTS

First, we found two different ChAT amacrine populations in the human retina that presented different ChAT immunoreactivity intensity and different expression of calcium-binding proteins. Both populations are affected in PD and their density is reduced compared to controls. Also, we report, for the first time, synaptic contacts between dopaminergic amacrine cells and ChAT-positive cells in the human retina. We found that, in PD retinas, there is a reduction of the dopaminergic synaptic contacts into ChAT cells.

CONCLUSIONS

Taken together, this work indicates degeneration of starburst amacrine cells in PD related to dopaminergic degeneration and that dopaminergic amacrine cells could modulate the function of starburst amacrine cells. Since motion perception circuitries are affected in PD, their assessment using visual tests could provide new insights into the diagnosis of PD.

Retinal imaging biomarkers of Alzheimer's disease: A systematic review and meta-analysis of studies using brain amyloid beta status for case definition

Introduction

We performed a systematic review and meta-analysis of the association between retinal imaging parameters and Alzheimer's disease (AD).

Methods

PubMed, EMBASE, and Scopus were systematically searched for prospective and observational studies. Included studies had AD case definition based on brain amyloid beta (Aβ) status. Study quality assessment was performed. Random-effects meta-analyses of standardized mean difference, correlation, and diagnostic accuracy were conducted.

Results

Thirty-eight studies were included. There was weak evidence of peripapillary retinal nerve fiber layer thinning on optical coherence tomography (OCT) (p = 0.14, 11 studies, n = 828), increased foveal avascular zone area on OCT-angiography (p = 0.18, four studies, n = 207), and reduced arteriole and venule vessel fractal dimension on fundus photography (p < 0.001 and p = 0.08, respectively, three studies, n = 297) among AD cases.

Discussion

Retinal imaging parameters appear to be associated with AD. Small study sizes and heterogeneity in imaging methods and reporting make it difficult to determine utility of these changes as AD biomarkers.

Highlights

We performed a systematic review on retinal imaging and Alzheimer's disease (AD).We only included studies in which cases were based on brain amyloid beta status.Several retinal biomarkers were associated with AD but clinical utility is uncertain.Studies should focus on biomarker-defined AD and use standardized imaging methods.

Retinal Neurodegeneration Measured With Optical Coherence Tomography and Neuroimaging in Alzheimer Disease: A Systematic Review

BACKGROUND

Optical coherence tomography (OCT) has enabled several retinal alterations to be detected in patients with Alzheimer disease (AD), alterations that could be potential biomarkers. However, the relationship between the retina and other biomarkers of AD has been underresearched. We gathered and analyzed the literature about the relationship between retinal and cerebral alterations detected via neuroimaging in patients with AD, mild cognitive impairment (MCI), and preclinical AD.

METHODS

This systematic review followed the PRISMA Statement guidelines through the 27 items on its checklist. We searched in PubMed, BVS, Scopus, and the Cochrane Library, using the keywords: Alzheimer's disease, optical coherence tomography, white matter, cortex, atrophy, cortical thickness, neuroimaging, magnetic resonance imaging, and positron emission tomography. We included articles that studied the retina in relation to neuroimaging in patients with AD, MCI, and preclinical AD. We excluded studies without OCT, without neuroimaging, clinical cases, opinion articles, systematic reviews, and animal studies.

RESULTS

Of a total of 35 articles found, 23 were finally included. Although mixed results were found, most of these corroborate the relationship between retinal and brain disorders.

CONCLUSIONS

More rigorous research is needed in the field, including homogenized, longitudinal, and prolonged follow-up studies, as well as studies that include all stages of AD. This will enable better understanding of the retina and its implications in AD, leading to the discovery of retinal biomarkers that reflect brain alterations in AD patients in an accessible and noninvasive manner.

Consumption of Coffee and Tea Is Associated with Macular Retinal Nerve Fiber Layer Thickness: Results from the UK Biobank

Coffee and tea drinking are thought to be protective for the development and progression of neurodegenerative disorders. This study aims to investigate associations between coffee and tea consumption with macular retinal nerve fiber layer (mRNFL) thickness, a marker of neurodegeneration. After quality control and eligibility screening, 35,557 out of 67,321 United Kingdom (UK) Biobank participants from six assessment centers were included in this cross-sectional study. In the touchscreen questionnaire, participants were asked how many cups of coffee and tea were consumed daily on average over the last year. Self-reported coffee and tea consumption were divided into four categories including 0 cup/day, 0.5-1 cups/day, 2-3 cups/day, and ≥4 cups/day, respectively. The mRNFL thickness was measured by the optical coherence tomography (Topcon 3D OCT-1000 Mark II) and automatically analyzed by segmentation algorithms. After adjusting for covariates, coffee consumption was significantly associated with an increased mRNFL thickness (β = 0.13, 95% CI = 0.01~0.25), which was more prominent in those who drank 2~3 cups coffee per day (β = 0.16, 95% CI = 0.03~0.30). The mRNFL thickness was also significantly increased in tea drinkers (β = 0.13, 95% CI = 0.01~0.26), especially for those who drank more than 4 cups of tea per day (β = 0.15, 95% CI = 0.01~0.29). The positive associations with mRNFL thickness, indicating that both coffee and tea consumptions had likely neuroprotective potentials. Causal links and underlying mechanisms for these associations should be explored further.

Structural and functional changes in the retina in Parkinson's disease

Parkinson's disease is caused by degeneration of dopaminergic neurons, originating in the substantia nigra pars compacta and characterised by bradykinesia, rest tremor and rigidity. In addition, visual disorders and retinal abnormalities are often present and can be identified by decreased visual acuity, abnormal spatial contrast sensitivity or even difficulty in complex visual task completion. Because of their early onset in patients with de novo Parkinson's disease, the anatomical retinal changes and electrophysiological modification could be valuable markers even at early stages of the disease. However, due to the concomitant occurrence of normal ageing, the relevance and specificity of these predictive values can be difficult to interpret. This review examines retinal dysfunction arising in Parkinson's disease. We highlight the electrophysiological delays and decreased amplitude in the electroretinography recorded in patients and animal models. We relate this to coexisting anatomical changes such as retinal nerve fibre layer and macular thinning, measured using optical coherence tomography, and show that functional measures are more consistent overall than optical coherence-measured structural changes. We review the underlying chemical changes seen with loss of retinal dopaminergic neurons and the effect of levodopa treatment on the retina in Parkinson's disease. Finally, we consider whether retinal abnormalities in Parkinson's disease could have a role as potential markers of poorer outcomes and help stratify patients at early stages of the disease. We emphasise that retinal measures can be valuable, accessible and cost-effective methods in the early evaluation of Parkinson's disease pathogenesis with potential for patient stratification.

Proteostasis in aging-associated ocular disease

Vision impairment has devastating consequences for the quality of human life. The cells and tissues associated with the visual process must function throughout one's life span and maintain homeostasis despite exposure to a variety of insults. Maintenance of the proteome is termed proteostasis, and is vital for normal cellular functions, especially at an advanced age. Here we describe basic aspects of proteostasis, from protein synthesis and folding to degradation, and discuss the current status of the field with a particular focus on major age-related eye diseases: age-related macular degeneration, cataract, and glaucoma. Our intent is to allow vision scientists to determine where and how to harness the proteostatic machinery for extending functional homeostasis in the aging retina, lens, and trabecular meshwork. Several common themes have emerged despite these tissues having vastly different metabolisms. Continued exposure to insults, including chronic stress with advancing age, increases proteostatic burden and reduces the fidelity of the degradation machineries including the ubiquitin-proteasome and the autophagy-lysosome systems that recognize and remove damaged proteins. This "double jeopardy" results in an exponential accumulation of cytotoxic proteins with advancing age. We conclude with a discussion of the challenges in maintaining an appropriate balance of protein synthesis and degradation pathways, and suggest that harnessing proteostatic capacities should provide new opportunities to design interventions for attenuating age-related eye diseases before they limit sight.

Association of retinal thickness and microvasculature with cognitive performance and brain volumes in elderly adults

BACKGROUND

Retinal structural and microvascular changes can be visualized and have been linked with cognitive decline and brain changes in cerebral age-related disorders. We investigated the association between retinal structural and microvascular changes with cognitive performance and brain volumes in elderly adults.

MATERIALS AND METHODS

All participants underwent magnetic resonance imaging (MRI), and a battery of neuropsychological examinations. Macula retinal thicknesses (retinal nerve fiber layer, mRNFL, and ganglion cell-inner plexiform layer, GCIPL) were imaged and measured with swept-source optical coherence tomography (SS-OCT) while Optical Coherence Tomography Angiography (OCTA) imaged and measured the superficial vascular complex (SVC) and deep vascular complex (DVC) of the retina.

RESULTS

Out of the 135 participants, 91 (67.41%) were females and none had dementia. After adjusting for risk factors, Shape Trail Test (STT)-A correlated with SVC (P < 0.001), DVC (P = 0.015) and mRNFL (P = 0.013) while STT-B correlated with SVC (P = 0.020) and GCIPL (P = 0.015). mRNFL thickness correlated with Montreal Cognitive Assessment (MoCA) (P = 0.007) and Stroop A (P = 0.030). After adjusting for risk factors and total intracranial volume, SVC correlated with hippocampal volume (P < 0.001). Hippocampal volume correlated (P < 0.05) with most cognitive measures. Stroop B (P < 0.001) and Stroop C (P = 0.020) correlated with white matter volume while Stroop measures and STT-A correlated with gray matter volume (P < 0.05).

CONCLUSION

Our findings suggest that the retinal structure and microvasculature can be useful pointers for cognitive performance, giving a choice for early discovery of decline in cognition and potential early treatment.

Artificial intelligence in dementia

PURPOSE OF REVIEW

Artificial intelligence tools are being rapidly integrated into clinical environments and may soon be incorporated into dementia diagnostic paradigms. A comprehensive review of emerging trends will allow physicians and other healthcare providers to better anticipate and understand these powerful tools.

RECENT FINDINGS

Machine learning models that utilize cerebral biomarkers are demonstrably effective for dementia identification and prediction; however, cerebral biomarkers are relatively expensive and not widely available. As eye images harbor several ophthalmic biomarkers that mirror the state of the brain and can be clinically observed with routine imaging, eye-based machine learning models are an emerging area, with efficacy comparable with cerebral-based machine learning models. Emerging machine learning architectures like recurrent, convolutional, and partially pretrained neural networks have proven to be promising frontiers for feature extraction and classification with ocular biomarkers.

SUMMARY

Machine learning models that can accurately distinguish those with symptomatic Alzheimer's dementia from those with mild cognitive impairment and normal cognition as well as predict progressive disease using relatively inexpensive and accessible ocular imaging inputs are impactful tools for the diagnosis and risk stratification of Alzheimer's dementia continuum. If these machine learning models can be incorporated into clinical care, they may simplify diagnostic efforts. Recent advancements in ocular-based machine learning efforts are promising steps forward.

Biomarkers involved in the pathogenesis of cerebral small-vessel disease

Cerebral small-vessel disease (CSVD) has been found to have a strong association with vascular cognitive impairment (VCI) and functional loss in elderly patients. At present, the diagnosis of CSVD mainly relies on brain neuroimaging markers, but they cannot fully reflect the overall picture of the disease. Currently, some biomarkers were found to be related to CSVD, but the underlying mechanisms remain unclear. We aimed to systematically review and summarize studies on the progress of biomarkers related to the pathogenesis of CSVD, which is mainly the relationship between these indicators and neuroimaging markers of CSVD. Concerning the pathophysiological mechanism of CSVD, the biomarkers of CSVD have been described as several categories related to sporadic and genetic factors. Monitoring of biomarkers might contribute to the early diagnosis and progression prediction of CSVD, thus providing ideas for better diagnosis and treatment of CSVD.

FIVES: A Fundus Image Dataset for Artificial Intelligence based Vessel Segmentation

Retinal vasculature provides an opportunity for direct observation of vessel morphology, which is linked to multiple clinical conditions. However, objective and quantitative interpretation of the retinal vasculature relies on precise vessel segmentation, which is time consuming and labor intensive. Artificial intelligence (AI) has demonstrated great promise in retinal vessel segmentation. The development and evaluation of AI-based models require large numbers of annotated retinal images. However, the public datasets that are usable for this task are scarce. In this paper, we collected a color fundus image vessel segmentation (FIVES) dataset. The FIVES dataset consists of 800 high-resolution multi-disease color fundus photographs with pixelwise manual annotation. The annotation process was standardized through crowdsourcing among medical experts. The quality of each image was also evaluated. To the best of our knowledge, this is the largest retinal vessel segmentation dataset for which we believe this work will be beneficial to the further development of retinal vessel segmentation.

Alterations of optic tract and retinal structure in patients after thalamic stroke

Objectives

To investigate the association between degeneration of retinal structure and shrinkage of the optic tract in patients after thalamic stroke.

Materials and methods

Patients with unilateral thalamic stroke were included. Structural magnetic resonance imaging (MRI) and optical coherence tomography (OCT) were performed to obtain parameters of optic tract shrinkage (lateral index) and retina structural thickness (retinal nerve fiber layer, RNFL; peripapillary retinal nerve fiber layer, pRNFL; ganglion cell-inner plexiform layer, GCIP), respectively. Visual acuity (VA) examination under illumination was conducted using Snellen charts and then converted to the logarithm of the minimum angle of resolution (LogMAR). We investigated the association between LI and OCT parameters and their relationships with VA.

Results

A total of 33 patients and 23 age-sex matched stroke-free healthy controls were enrolled. Patients with thalamic stroke showed altered LI compared with control participants (P = 0.011) and a significantly increased value of LI in the subgroup of disease duration more than 6 months (P = 0.004). In these patients, LI were significantly associated with pRNFL thickness (β = 0.349, 95% confidence interval [CI]: 0.134–0.564, P = 0.002) after adjusting for confounders (age, sex, hypertension, diabetes, dyslipidemia, and lesion volume). LI and pRNFL were both significantly associated with VA in all patients (LI: β = −0.275, 95% CI: −0.539 to −0.011, P = 0.041; pRNFL: β = −0.023, 95% CI: −0.046 to −0.001, P = 0.040) and in subgroup of disease duration more than 6 months (LI: β = −0.290, 95% CI: −0.469 to −0.111, P = 0.002; pRNFL: β = −0.041, 95% CI: −0.065 to −0.017, P = 0.003).

Conclusion

Shrinkage of the optic tract can be detected in patients with thalamic stroke, especially after 6 months of stroke onset. In these patients, the extent of optic tract atrophy is associated with pRNFL thickness, and they are both related to visual acuity changes.

Retinal magnification factors at the fixation locus derived from schematic eyes with four individualized surfaces

Retinal magnification factors (RMFs) allow the conversion of angles to lengths in retinal images. In this work, we propose paraxial and non-paraxial RMF calculation methods that incorporate the individual topography and separation of the anterior and posterior surfaces of the cornea and crystalline lens, assuming homogeneous ocular media. Across 34 eyes, the two RMF methods differ by 0.1% on average, due to surface tilt, decenter, and lack of rotational symmetry in the non-paraxial modeling, which results in up to 2.2% RMF variation with retinal meridian. Differences with widely used individualized RMF calculation methods are smallest for eyes with ∼24 mm axial length, and as large as 7.5% in a 29.7 mm long eye (15D myope). To better model the capture of retinal images, we propose the tracing of chief rays, instead of the scaling of posterior nodal or principal distances often used in RMF definitions. We also report that RMF scale change is approximately proportional to both refractive error and axial separation between the ophthalmoscope's exit pupil and the eye's entrance pupil, resulting in RMF changes as large as 13% for a 1cm displacement in a 15D myopic eye. Our biometry data shows weak correlation and statistical significance between surface radii and refractive error, as well as axial length, whether considering all eyes in the study, or just the high myopes, defined as those with refractive error sphere equivalent ≤ -4D. In contrast, vitreous thicknesses show a strong correlation (r ≤ -0.92) and significance (p ≤ 10-13) with refractive error when considering all eyes or just high myopes (r ≤ -0.95; p ≤ 10-5). We also found that potential RMF change with depth of cycloplegia and/or residual accommodation is smaller than 0.2%. Finally, we propose the reporting of individual ocular biometry data and a detailed RMF calculation method description in scientific publications to facilitate the comparison of retinal imaging biomarker data across studies.

Retinal vessel diameters and function in cardiovascular risk and disease

In the last two decades evidence has gradually accumulated suggesting that the eye may be a unique window for cardiovascular risk stratification based on the assessment of subclinical damage of retinal microvascular structure and function. This can be facilitated by non-invasive analysis of static retinal vessel diameters and dynamic recording of flicker light-induced and endothelial function-related dilation of both retinal arterioles and venules. Recent new findings have made retinal microvascular biomarkers strong candidates for clinical implementation as reliable risk predictors. Beyond a review of the current evidence and state of research, the article aims to discuss the methodological benefits and pitfalls and to identify research gaps and future directions. Above all, the potential use for screening and treatment monitoring of cardiovascular disease risk are highlighted. The article provides fundamental comprehension of retinal vessel imaging by explaining anatomical and physiological essentials of the retinal microcirculation leading to a detailed description of the methodological approach. This allows for better understanding of the underlying retinal microvascular pathology associated with the prevalence and development of cardiovascular disease. A body of new evidence is presented on the clinical validity and predictive value of retinal vessel diameters and function for incidence cardiovascular disease and outcome. Findings in children indicate the potential for utility in childhood cardiovascular disease prevention, and the efficacy of exercise interventions highlight the treatment sensitivity of retinal microvascular biomarkers. Finally, coming from the availability of normative data, solutions for diagnostic challenges are discussed and conceptual steps towards clinical implementation are put into perspective.

Discrete Wavelet Transform Analysis of the Electroretinogram in Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder

Background

To evaluate the electroretinogram waveform in autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) using a discrete wavelet transform (DWT) approach.

Methods

A total of 55 ASD, 15 ADHD and 156 control individuals took part in this study. Full field light-adapted electroretinograms (ERGs) were recorded using a Troland protocol, accounting for pupil size, with five flash strengths ranging from –0.12 to 1.20 log photopic cd.s.m^–2. A DWT analysis was performed using the Haar wavelet on the waveforms to examine the energy within the time windows of the a- and b-waves and the oscillatory potentials (OPs) which yielded six DWT coefficients related to these parameters. The central frequency bands were from 20–160 Hz relating to the a-wave, b-wave and OPs represented by the coefficients: a20, a40, b20, b40, op80, and op160, respectively. In addition, the b-wave amplitude and percentage energy contribution of the OPs (%OPs) in the total ERG broadband energy was evaluated.

Results

There were significant group differences (p < 0.001) in the coefficients corresponding to energies in the b-wave (b20, b40) and OPs (op80 and op160) as well as the b-wave amplitude. Notable differences between the ADHD and control groups were found in the b20 and b40 coefficients. In contrast, the greatest differences between the ASD and control group were found in the op80 and op160 coefficients. The b-wave amplitude showed both ASD and ADHD significant group differences from the control participants, for flash strengths greater than 0.4 log photopic cd.s.m^–2 (p < 0.001).

Conclusion

This methodological approach may provide insights about neuronal activity in studies investigating group differences where retinal signaling may be altered through neurodevelopment or neurodegenerative conditions. However, further work will be required to determine if retinal signal analysis can offer a classification model for neurodevelopmental conditions in which there is a co-occurrence such as ASD and ADHD.

The electroretinogram b-wave amplitude: a differential physiological measure for Attention Deficit Hyperactivity Disorder and Autism Spectrum Disorder

Background

Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent childhood neurodevelopmental disorder. It shares some genetic risk with Autism Spectrum Disorder (ASD), and the conditions often occur together. Both are potentially associated with abnormal glutamate and GABA neurotransmission, which can be modelled by measuring the synaptic activity in the retina with an electroretinogram (ERG). Reduction of retinal responses in ASD has been reported, but little is known about retinal activity in ADHD. In this study, we compared the light-adapted ERGs of individuals with ADHD, ASD and controls to investigate whether retinal responses differ between these neurodevelopmental conditions.

Methods

Full field light-adapted ERGs were recorded from 15 ADHD, 57 ASD (without ADHD) and 59 control participants, aged from 5.4 to 27.3 years old. A Troland protocol was used with a random series of nine flash strengths from −0.367 to 1.204 log photopic cd.s.m⁻². The time-to-peak and amplitude of the a- and b-waves and the parameters of the Photopic Negative Response (PhNR) were compared amongst the three groups of participants, using generalised estimating equations.

Results

Statistically significant elevations of the ERG b-wave amplitudes, PhNR responses and faster timings of the b-wave time-to-peak were found in those with ADHD compared with both the control and ASD groups. The greatest elevation in the b-wave amplitudes associated with ADHD were observed at 1.204 log phot cd.s.m⁻² flash strength (p < .0001), at which the b-wave amplitude in ASD was significantly lower than that in the controls. Using this measure, ADHD could be distinguished from ASD with an area under the curve of 0.88.

Conclusions

The ERG b-wave amplitude appears to be a distinctive differential feature for both ADHD and ASD, which produced a reversed pattern of b-wave responses. These findings imply imbalances between glutamate and GABA neurotransmission which primarily regulate the b-wave formation. Abnormalities in the b-wave amplitude could provisionally serve as a biomarker for both neurodevelopmental conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11689-022-09440-2.

Retinal Glutamate Neurotransmission: From Physiology to Pathophysiological Mechanisms of Retinal Ganglion Cell Degeneration

Glutamate neurotransmission and metabolism are finely modulated by the retinal network, where the efficient processing of visual information is shaped by the differential distribution and composition of glutamate receptors and transporters. However, disturbances in glutamate homeostasis can result in glutamate excitotoxicity, a major initiating factor of common neurodegenerative diseases. Within the retina, glutamate excitotoxicity can impair visual transmission by initiating degeneration of neuronal populations, including retinal ganglion cells (RGCs). The vulnerability of RGCs is observed not just as a result of retinal diseases but has also been ascribed to other common neurodegenerative and peripheral diseases. In this review, we describe the vulnerability of RGCs to glutamate excitotoxicity and the contribution of different glutamate receptors and transporters to this. In particular, we focus on the N-methyl-d-aspartate (NMDA) receptor as the major effector of glutamate-induced mechanisms of neurodegeneration, including impairment of calcium homeostasis, changes in gene expression and signalling, and mitochondrial dysfunction, as well as the role of endoplasmic reticular stress. Due to recent developments in the search for modulators of NMDA receptor signalling, novel neuroprotective strategies may be on the horizon.

The Molecular Mechanism of Retina Light Injury Focusing on Damage from Short Wavelength Light

Natural visible light is an electromagnetic wave composed of a spectrum of monochromatic wavelengths, each with a characteristic color. Photons are the basic units of light, and their wavelength correlates to the energy of light; short-wavelength photons carry high energy. The retina is a fragile neuronal tissue that senses light and generates visual signals conducted to the brain. However, excessive and intensive light exposure will cause retinal light damage. Within the visible spectrum, short-wavelength light, such as blue light, carries higher energy, and thus the retinal injury, is more significant when exposed to these wavelengths. The damage mechanism triggered by different short-wavelength light varies due to photons carrying different energy and being absorbed by different photosensitive molecules in the retinal neurons. However, photooxidation might be a common molecular step to initiate cell death. Herein, we summarize the historical understanding of light, the key molecular steps related to retinal light injury, and the death pathways of photoreceptors to further decipher the molecular mechanism of retinal light injury and explore potential neuroprotective strategies.

Retinal biomarkers of Cerebral Small Vessel Disease: A systematic review

INTRODUCTION

Cerebral Small Vessel Disease (CSVD), a progressive degenerative disorder of small caliber cerebral vessels, represents a major contributor to stroke and vascular dementia incidence worldwide. We sought to conduct a systematic review of the role of retinal biomarkers in diagnosis and characterization of CSVD.

METHODS

We conducted a systematic review of MEDLINE, PubMed, Scopus, the Cochrane Library Database, and Web of Science. We identified studies of sporadic CSVD (including CSVD not otherwise specified, Cerebral Amyloid Angiopathy, and Hypertensive Arteriopathy) and the most common familial CSVD disorders (including CADASIL, Fabry disease, and MELAS). Included studies used one or more of the following tools: visual fields assessment, fundus photography, Optical Coherence Tomography and OCT Angiography, Fluorescein Angiography, Electroretinography, and Visual Evoked Potentials.

RESULTS

We identified 48 studies of retinal biomarkers in CSVD, including 9147 cases and 12276 controls. Abnormalities in retinal vessel diameter (11 reports, n = 11391 participants), increased retinal vessel tortuosity (11 reports, n = 617 participants), decreased vessel fractal dimension (5 reports, n = 1597 participants) and decreased retinal nerve fiber layer thickness (5 reports, n = 4509 participants) were the biomarkers most frequently associated with CSVD. We identified no reports conducting longitudinal retinal evaluations of CSVD, or systematically evaluating diagnostic performance.

CONCLUSION

Multiple retinal biomarkers were associated with CSVD or its validated neuroimaging biomarkers. However, existing evidence is limited by several shortcomings, chiefly small sample size and unstandardized approaches to both biomarkers' capture and CSVD characterization. Additional larger studies will be required to definitively determine whether retinal biomarkers could be successfully incorporated in future research efforts and clinical practice.

A Deep Learning System for Fully Automated Retinal Vessel Measurement in High Throughput Image Analysis

Motivation

Retinal microvasculature is a unique window for predicting and monitoring major cardiovascular diseases, but high throughput tools based on deep learning for in-detail retinal vessel analysis are lacking. As such, we aim to develop and validate an artificial intelligence system (Retina-based Microvascular Health Assessment System, RMHAS) for fully automated vessel segmentation and quantification of the retinal microvasculature.

Results

RMHAS achieved good segmentation accuracy across datasets with diverse eye conditions and image resolutions, having AUCs of 0.91, 0.88, 0.95, 0.93, 0.97, 0.95, 0.94 for artery segmentation and 0.92, 0.90, 0.96, 0.95, 0.97, 0.95, 0.96 for vein segmentation on the AV-WIDE, AVRDB, HRF, IOSTAR, LES-AV, RITE, and our internal datasets. Agreement and repeatability analysis supported the robustness of the algorithm. For vessel analysis in quantity, less than 2 s were needed to complete all required analysis.

Solving neurodegeneration: common mechanisms and strategies for new treatments

Across neurodegenerative diseases, common mechanisms may reveal novel therapeutic targets based on neuronal protection, repair, or regeneration, independent of etiology or site of disease pathology. To address these mechanisms and discuss emerging treatments, in April, 2021, Glaucoma Research Foundation, BrightFocus Foundation, and the Melza M. and Frank Theodore Barr Foundation collaborated to bring together key opinion leaders and experts in the field of neurodegenerative disease for a virtual meeting titled "Solving Neurodegeneration". This "think-tank" style meeting focused on uncovering common mechanistic roots of neurodegenerative disease and promising targets for new treatments, catalyzed by the goal of finding new treatments for glaucoma, the world's leading cause of irreversible blindness and the common interest of the three hosting foundations. Glaucoma, which causes vision loss through degeneration of the optic nerve, likely shares early cellular and molecular events with other neurodegenerative diseases of the central nervous system. Here we discuss major areas of mechanistic overlap between neurodegenerative diseases of the central nervous system: neuroinflammation, bioenergetics and metabolism, genetic contributions, and neurovascular interactions. We summarize important discussion points with emphasis on the research areas that are most innovative and promising in the treatment of neurodegeneration yet require further development. The research that is highlighted provides unique opportunities for collaboration that will lead to efforts in preventing neurodegeneration and ultimately vision loss.

Retinal imaging biomarkers of neurodegenerative diseases

The timely detection of neurodegenerative diseases is central to improving clinical care as well as enabling the development and deployment of disease-modifying therapies. Retinal imaging is emerging as a method to detect features of a number of neurodegenerative diseases, given the anatomical and functional similarities between the retina and the brain. This review provides an overview of the current status of retinal imaging biomarkers of neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, Lewy body dementia, frontotemporal dementia, Huntington's disease and multiple sclerosis. Whilst research findings are promising, efforts to harmonise study designs and imaging methods will be important in translating these findings into clinical care. Doing so may mean that eye care providers will play important roles in the detection of a variety of neurodegenerative diseases in future.

Retinal Nerve Fiber Layer Thickness and Associations With Cognitive Impairment in Parkinson’s Disease

Objective

This study intended to investigate whether retinal nerve fiber layer (RNFL) thickness could become a potential marker in patients with Parkinson’s disease with cognitive impairment (PD-CI).

Methods

Fifty-seven PD patients and 45 age-matched healthy controls (HCs) were recruited in our cross-sectional study and completed optical coherence tomography (OCT) evaluations. PD with normal cognition (PD-NC) and cognitive impairment (PD-CI) patients were divided following the 2015 Movement Disorder Society criteria. RNFL thickness was quantified in subfields of the 3.0-mm circle surrounding the optic disk; while a battery of neuropsychiatric assessments was conducted to estimate the Parkinsonism severity. General linear models and one-way ANOVA were adopted to assess RNFL thickness between subgroups with different cognitive statuses; logistic regression analyses were applied to determine the relation between RNFL and PD-CI cases.

Results

Compared with HCs, more thinning of the RNFL was observed in the inferior and temporal sectors in PD patients, especially in the PD-CI group. Inferior RNFL thickness was reduced in PD-CI compared with PD-NC patients. Logistic regression analysis found that inferior RNFL thickness was independently associated with PD-CI cases (odds ratio = 0.923, p = 0.014). Receiver operating characteristic analysis showed that the RNFL-involved combined model provided a high accuracy in screening cognitive deficiency in PD cases (area under the curve = 0.85, p &lt; 0.001).

Conclusion

Reduced RNFL thickness especially in the inferior sector is independently associated with PD-CI patients. Our study present new perspectives into verifying possible indicators for neuropathological processes or disease severity in Parkinsonians with cognitive dysfunction.

Neurovascular coupling unit dysfunction and dementia: Retinal measurements as tools to move towards population-based evidence

Dysfunction of the neurovascular coupling unit may be an important contributor to dementia. The neurovascular coupling unit comprises neuronal structures (e.g. astrocytes) and vascular structures (e.g. endothelial cells) that functionally interact both at the level of the arterioles as well as at the capillary level (blood-brain barrier) to regulate optimal metabolic conditions in the brain. However, it remains unclear how and to what extent dysfunction of the neurovascular coupling unit contributes to the early-stage pathobiology of dementia. Currently, limited data are available on the association between neurovascular coupling unit dysfunction, as quantified by cerebral imaging techniques, and cognitive performance. In particular, there is a lack of population-based human data (defined as studies with a sample size ~n>500). This is an important limitation because population-based studies, in comparison with smaller clinical studies, provide data which is better representative of the general population; are less susceptible to selection bias; and have a larger statistical power to detect small associations. To acquire population-based data, however, alternative imaging techniques than cerebral imaging techniques may be required. Disadvantages of cerebral imaging techniques, which limit use in population-based studies, are that these techniques are relatively expensive, time-consuming, and/or invasive. In this review, we propose that retinal imaging techniques can be used for population-based studies: on the one hand the retina and brain have many anatomical and physiological similarities; and on the other hand retinal imaging techniques are non-invasive, highly accurate, relatively inexpensive, and require relatively short measurement time. To provide support for this concept, we provide an overview on the human (population-based) evidence on the associations of retinal indices of neurodegeneration, microvascular dysfunction, and dysfunction of the neurovascular coupling unit with magnetic resonance imaging (MRI) features of structural brain abnormalities and cognitive performance.

PET imaging of retinal inflammation in mice exposed to blue light using [18F]-DPA-714

Purpose

Positron emission tomography (PET) is widely used in high-precision imaging, which may provide a simple and noninvasive method for the detection of pathology and therapeutic effects. [¹⁸F]-DPA-714 is a second-generation translocator protein (TSPO) positron emission tomography radiotracer that shows great promise in a model of neuroinflammation. In this study, [¹⁸F]-DPA-714 micro-PET imaging was used to evaluate retinal inflammation in mice exposed to blue light, a well-established model of age-related macular degeneration (AMD) for molecular mechanism research and drug screening.

Methods

C57BL/6J melanized mice were subjected to 10,000, 15,000, and 20,000 lux blue light for 5 days (8 h/day) to develop the retinal injury model, and the structure and function of the retina were assessed using hematoxylin-eosin (HE) staining, electroretinography (ERG), and terminal-deoxynucleotidyl transferase (TdT)-mediated nick-end labeling (TUNEL) immunostaining. Then, [¹⁸F]-DPA-714 was injected approximately 100 μCi through each tail vein, and static imaging was performed 1 h after injection. Finally, the mice eyeballs were collected for biodistribution and immune analysis.

Results

The blue light exposure significantly destroyed the structure and function of the retina, and the uptake of [¹⁸F]-DPA-714 in the retinas of the mice exposed to blue light were the most significantly upregulated, which was consistent with the biodistribution data. In addition, the immunohistochemical, western blot, and immunofluorescence data showed an increase in microglial TSPO expression.

Conclusions

[¹⁸F]-DPA-714 micro-PET imaging might be a good method for evaluating early inflammatory status during retinal pathology.

The emerging role of extracellular vesicles in retinal diseases

As a type of nanosized membranous vesicles secreted by living cells, extracellular vesicles (EVs) mediate intercellular communications with excellent physicochemical stability and biocompatibility. By delivering biologically active molecules including proteins, nucleic acids and lipids, EVs participate in many physiological and pathological processes. Increasing studies have suggested that EVs may be biomarkers for liquid biopsy of retinal diseases due to the ability to transfer through the blood-retinal barrier. EVs also represent a novel cell-free strategy to repair tissue damage in regenerative medicine. Evidence has indicated that EVs can be engineered and modified to enhance their efficacy. In this review, an overview of the characteristics, isolation, and identification of EVs is provided. Moreover, recent advances with EVs in the diagnosis and treatment of retinal diseases and the engineering approaches to elevate their effects are introduced, and opportunities and challenges for clinical application are discussed.