Spectral-Domain OCT Measurements in Alzheimer's Disease: A Systematic Review and Meta-analysis

Retinal layers and symptoms and inflammation in schizophrenia

Schizophrenia is a neurodevelopmental disorder that affects brain structure and function. The retina, as well as the brain, consists of neuronal and glial cells packed in layers. Cortical volume and brain thickness are associated with inflammatory biomarkers, however, no study has been performed associating inflammatory biomarkers and retina in schizophrenia. our study aims to compare the retinal macular thickness and volume and peripapillary thickness in patients with schizophrenia and controls, and associate it to symptoms of schizophrenia, to interleukin-6 (IL-6) and C Reactive Protein (CRP) levels. Optical coherence tomography was performed to assess retinal layer thickness and volume, and CRP and IL-6 levels were measured in patients with schizophrenia and controls. Positive, negative, and general symptoms of schizophrenia were measured with the Positive and Negative Syndrome Scale (PANSS). A linear regression controlling for confounding factors was performed. 70 subjects were included, 35 patients, and 35 controls matched for sex and age. Patients with schizophrenia presented a significantly lower macular volume (p < 0.05) and thickness (< 0.05) than controls. PANSS positive, general and total scores were associated with retinal nerve fiber layer (RNFL) thickness (p < 0.05). There was no association between inflammatory markers (CRP and IL-6) levels and the retinal layer. A reduction in macular volume and thickness was found in patients with schizophrenia. The severity of schizophrenia symptoms was associated with RNFL thickness. CRP and IL-6 are not associated with retinal thickness/volume in schizophrenia or controls.

Linking physiology and demographics, non-ocular pathology and pharmaceutical drug use to standard OCT measures of the inner retina: The PPP project

PURPOSE

To assess the associations between physiology and demographics, non-ocular pathology and pharmaceutical drug use against peri-papillary retinal nerve fibre layer thickness (pRNFL T) and other optical coherence tomography (OCT) inner retinal measures in normal, healthy eyes.

METHODS

A retrospective, cross-sectional study of 705 consecutive participants with bilateral normal, healthy optic nerves and maculae. PRNFL Ts, vertical cup/disc ratio (CDR), cup volume and macular ganglion cell layer-inner plexiform layer (GCL-IPL) Ts were extracted from Cirrus OCT scans, then regressed against predictor variables of participants' physiology and demographics (eye laterality, refraction, intraocular pressure [IOP], age, sex, race/ethnicity, etc.) and non-ocular pathology and pharmaceutical drug use according to the World Health Organisation classifications. Associations were assessed for statistical significance (p < 0.05) and clinical significance (|β| > 95% limits of agreement for repeated measures).

RESULTS

A multitude of non-ocular pathology and pharmaceutical drug use were statistically and clinically significantly associated with deviations in standard OCT inner retinal measures, exceeding the magnitude of other factors such as age, IOP and race/ethnicity. Thinner inner retina and larger optic nerve cup measures were linked to use of systemic corticosteroids, sex hormones/modulators, presence of vasomotor/allergic rhinitis and other diseases and drugs (up to -29.3 [-49.88, -8.72] μm pRNFL T, 0.31 [0.07, 0.54] vertical CDR, 0.29 [0.03, 0.54] mm3 cup volume and -10.18 [-16.62, -3.74] μm macular GCL-IPL T; all p < 0.05). Thicker inner retina and smaller optic nerve cup measures were diffusely associated with use of antineoplastic agents, presence of liver or urinary diseases and other diseases and drugs (up to 67.12 [64.92, 69.31] μm pRNFL T, -0.31 [-0.53, -0.09] vertical CDR, -0.06 [-0.11, 0] mm3 cup volume and 28.84 [14.51, 43.17] μm macular GCL-IPL T; all p < 0.05).

CONCLUSION

There are a multitude of systemic diseases and drugs associated with altered OCT inner retinal measures, with magnitudes far exceeding those of other factors such as age, IOP and race/ethnicity. These systemic factors should at least be considered during OCT assessments to ensure precise interpretation of normal versus pathological inner retinal health.

Alzheimer's disease pathophysiology in the Retina

The retina is an emerging CNS target for potential noninvasive diagnosis and tracking of Alzheimer's disease (AD). Studies have identified the pathological hallmarks of AD, including amyloid β-protein (Aβ) deposits and abnormal tau protein isoforms, in the retinas of AD patients and animal models. Moreover, structural and functional vascular abnormalities such as reduced blood flow, vascular Aβ deposition, and blood-retinal barrier damage, along with inflammation and neurodegeneration, have been described in retinas of patients with mild cognitive impairment and AD dementia. Histological, biochemical, and clinical studies have demonstrated that the nature and severity of AD pathologies in the retina and brain correspond. Proteomics analysis revealed a similar pattern of dysregulated proteins and biological pathways in the retina and brain of AD patients, with enhanced inflammatory and neurodegenerative processes, impaired oxidative-phosphorylation, and mitochondrial dysfunction. Notably, investigational imaging technologies can now detect AD-specific amyloid deposits, as well as vasculopathy and neurodegeneration in the retina of living AD patients, suggesting alterations at different disease stages and links to brain pathology. Current and exploratory ophthalmic imaging modalities, such as optical coherence tomography (OCT), OCT-angiography, confocal scanning laser ophthalmoscopy, and hyperspectral imaging, may offer promise in the clinical assessment of AD. However, further research is needed to deepen our understanding of AD's impact on the retina and its progression. To advance this field, future studies require replication in larger and diverse cohorts with confirmed AD biomarkers and standardized retinal imaging techniques. This will validate potential retinal biomarkers for AD, aiding in early screening and monitoring.

Analysis of the Retinal and Choroidal Vasculature Using Ultrawidefield Fundus Imaging in Mild Cognitive Impairment and Normal Cognition

Purpose

To utilize ultrawidefield (UWF) imaging to evaluate retinal and choroidal vasculature and structure in individuals with mild cognitive impairment (MCI) compared with that of controls with normal cognition.

Design

Prospective cross sectional study.

Participants

One hundred thirty-one eyes of 82 MCI patients and 230 eyes of 133 cognitively normal participants from the Eye Multimodal Imaging in Neurodegenerative Disease Study.

Methods

A scanning laser ophthalmoscope (California, Optos Inc) was used to obtain UWF fundus color images. Images were analyzed with the Vasculature Assessment Platform for Images of the Retina UWF (VAMPIRE-UWF 2.0, Universities of Edinburgh and Dundee) software.

Main outcome measures

Imaging parameters included vessel width gradient, vessel width intercept, large vessel choroidal vascular density, vessel tortuosity, and vessel fractal dimension.

Results

Both retinal artery and vein width gradients were less negative in MCI patients compared with controls, demonstrating decreased rates of vessel thinning at the periphery (P < 0.001; P = 0.027). Retinal artery and vein width intercepts, a metric that extrapolates the width of the vessel at the center of the optic disc, were smaller in MCI patients compared with that of controls (P < 0.001; P = 0.017). The large vessel choroidal vascular density, which quantifies the vascular area versus the total choroidal area, was greater in MCI patients compared with controls (P = 0.025).

Conclusions

When compared with controls with normal cognition, MCI patients had thinner retinal vasculature manifested in both the retinal arteries and the veins. In MCI, these thinner arteries and veins attenuated at a lower rate when traveling toward the periphery. MCI patients also had increased choroidal vascular density.

Financial Disclosures

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

Contrast Sensitivity, Visual Field, Color Vision, Motion Perception, and Cognitive Impairment: A Systematic Review

OBJECTIVES

To examine relationships between visual function (ie, contrast sensitivity, visual field, color vision, and motion perception) and cognitive impairment, including any definition of "cognitive impairment," mild cognitive impairment, or dementia.

DESIGN

Systematic review and meta-analyses.

SETTING AND PARTICIPANTS

Any settings; participants with (cases) or without (controls) cognitive impairment.

METHODS

We searched 4 databases (to January 2024) and included published studies that compared visual function between cases and controls. Standardized mean differences (SMD) with 95% CIs were calculated where data were available. Data were sufficient for meta-analyses when cases were people with dementia. The Joanna Briggs Institute checklists were used for quality assessment.

RESULTS

Fifty-one studies/69 reports were included. Cross-sectional evidence shows that people with dementia had worse contrast sensitivity function and color vision than controls: measured by contrast sensitivity (log units) on letter charts, SMD -1.22 (95% CI -1.98, -0.47), or at varied spatial frequencies, -0.92 (-1.28, -0.57); and by pseudoisochromatic plates, -1.04 (-1.59, -0.49); color arrangement, -1.30 (-2.31, -0.29); or matching tests, -0.51 (-0.78, -0.24). They also performed more poorly on tests of motion perception, -1.20 (-1.73, -0.67), and visual field: mean deviation, -0.87 (-1.29, -0.46), and pattern standard deviation, -0.69 (-1.24, -0.15). Results were similar when cases were limited to participants with clinically diagnosed Alzheimer disease. Sources of bias included lack of clarity on study populations or settings and definitions of cognitive impairment. The 2 included longitudinal studies with follow-ups of approximately 10 years were of good quality but reported inconsistent results.

CONCLUSIONS AND IMPLICATIONS

In the lack of longitudinal data, cross-sectional studies indicate that individuals with cognitive impairment have poorer visual function than those with normal cognition. Additional longitudinal data are needed to understand whether poor visual function precedes cognitive impairment and the most relevant aspects of visual function, dementia pathologies, and domains of cognition.

Targeting complement C3a receptor resolves mitochondrial hyperfusion and subretinal microglial activation in progranulin-deficient frontotemporal dementia

Mutations in progranulin ( GRN ) cause frontotemporal dementia ( GRN -FTD) due to deficiency of the pleiotropic protein progranulin. GRN -FTD exhibits diverse pathologies including lysosome dysfunction, lipofuscinosis, microgliosis, and neuroinflammation. Yet, how progranulin loss causes disease remains unresolved. Here, we report that non-invasive retinal imaging of GRN -FTD patients revealed deficits in photoreceptors and the retinal pigment epithelium (RPE) that correlate with cognitive decline. Likewise, Grn -/- mice exhibit early RPE dysfunction, microglial activation, and subsequent photoreceptor loss. Super-resolution live imaging and transcriptomic analyses identified RPE mitochondria as an early driver of retinal dysfunction. Loss of mitochondrial fission protein 1 (MTFP1) in Grn -/- RPE causes mitochondrial hyperfusion and bioenergetic defects, leading to NF-kB-mediated activation of complement C3a-C3a receptor signaling, which drives further mitochondrial hyperfusion and retinal inflammation. C3aR antagonism restores RPE mitochondrial integrity and limits subretinal microglial activation. Our study identifies a previously unrecognized mechanism by which progranulin modulates mitochondrial integrity and complement-mediated neuroinflammation.

Correlation between serum biomarkers, brain volume, and retinal neuronal loss in early-onset Alzheimer's disease

PURPOSE

To compare the peripapillary retinal nerve fiber layer (pRNFL), retinal nerve fiber layer (RNFL), and ganglion cell complex (GCC) thickness measurement in early-onset Alzheimer's disease (EOAD) and controls using spectral domain optical coherence tomography (SD-OCT). We also assessed the relationship between SD-OCT measurements and cognitive measures, serum biomarkers for Alzheimer's disease (AD), and cerebral microstructural volume.

METHODS

pRNFL, RNFL, and GCC thicknesses were measured in 43 EOAD and 42 controls using SD-OCT. Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) were used to assess cognitive status, magnetic resonance imaging (MRI) tool was used to quantify cerebral microstructural volume, and serum biomarkers were quantified from peripheral blood.

RESULTS

EOAD patients had thinner pRNFL (P < 0.001), RNFL (P = 0.008), and GCC (P = 0.018) thicknesses compared to controls after adjusting for multiple factors. pRNFL thickness correlated (P = 0.016) with serum t-tau level. Serum Aβ42 (P < 0.05) concentration correlated with RNFL thickness. Importantly, occipital lobe volume (P = 0.010) correlated with GCC thicknesses in EOAD patients.

CONCLUSION

Our findings suggest that retinal thickness may be useful markers for assessing neurodegenerative process in EOAD.

Structural neuroimaging changes associated with subjective cognitive decline from a clinical sample

BACKGROUND

Alzheimer's disease (AD) is characterized by progressive deterioration of cognitive functions. Some individuals with subjective cognitive decline (SCD) are in the early phase of the disease and subsequently progress through the AD continuum. Although neuroimaging biomarkers could be used for the accurate and early diagnosis of preclinical AD, the findings in SCD samples have been heterogeneous. This study established the morphological differences in brain magnetic resonance imaging (MRI) findings between individuals with SCD and those without cognitive impairment based on a clinical sample of patients defined according to SCD-Initiative recommendations. Moreover, we investigated baseline structural changes in the brains of participants who remained stable or progressed to mild cognitive impairment or dementia.

METHODS

This study included 309 participants with SCD and 43 healthy controls (HCs) with high-quality brain MRI at baseline. Among the 99 subjects in the SCD group who were followed clinically, 32 progressed (SCDp) and 67 remained stable (SCDnp). A voxel-wise statistical comparison of gray and white matter (WM) volume was performed between the HC and SCD groups and between the HC, SCDp, and SCDnp groups. XTRACT ATLAS was used to define the anatomical location of WM tract damage. Region-of-interest (ROI) analyses were performed to determine brain volumetric differences. White matter lesion (WML) burden was established in each group.

RESULTS

Voxel-based morphometry (VBM) analysis revealed that the SCD group exhibited gray matter atrophy in the middle frontal gyri, superior orbital gyri, superior frontal gyri, right rectal gyrus, whole occipital lobule, and both thalami and precunei. Meanwhile, ROI analysis revealed decreased volume in the left rectal gyrus, bilateral medial orbital gyri, middle frontal gyri, superior frontal gyri, calcarine fissure, and left thalamus. The SCDp group exhibited greater hippocampal atrophy (p < 0.001) than the SCDnp and HC groups on ROI analyses. On VBM analysis, however, the SCDp group exhibited increased hippocampal atrophy only when compared to the SCDnp group (p < 0.001). The SCD group demonstrated lower WM volume in the uncinate fasciculus, cingulum, inferior fronto-occipital fasciculus, anterior thalamic radiation, and callosum forceps than the HC group. However, no significant differences in WML number (p = 0.345) or volume (p = 0.156) were observed between the SCD and HC groups.

CONCLUSIONS

The SCD group showed brain atrophy mainly in the frontal and occipital lobes. However, only the SCDp group demonstrated atrophy in the medial temporal lobe at baseline. Structural damage in the brain regions was anatomically connected, which may contribute to early memory decline.

Prognostic potentials of AI in ophthalmology: systemic disease forecasting via retinal imaging

BACKGROUND

Artificial intelligence (AI) that utilizes deep learning (DL) has potential for systemic disease prediction using retinal imaging. The retina's unique features enable non-invasive visualization of the central nervous system and microvascular circulation, aiding early detection and personalized treatment plans for personalized care. This review explores the value of retinal assessment, AI-based retinal biomarkers, and the importance of longitudinal prediction models in personalized care.

MAIN TEXT

This narrative review extensively surveys the literature for relevant studies in PubMed and Google Scholar, investigating the application of AI-based retina biomarkers in predicting systemic diseases using retinal fundus photography. The study settings, sample sizes, utilized AI models and corresponding results were extracted and analysed. This review highlights the substantial potential of AI-based retinal biomarkers in predicting neurodegenerative, cardiovascular, and chronic kidney diseases. Notably, DL algorithms have demonstrated effectiveness in identifying retinal image features associated with cognitive decline, dementia, Parkinson's disease, and cardiovascular risk factors. Furthermore, longitudinal prediction models leveraging retinal images have shown potential in continuous disease risk assessment and early detection. AI-based retinal biomarkers are non-invasive, accurate, and efficient for disease forecasting and personalized care.

CONCLUSION

AI-based retinal imaging hold promise in transforming primary care and systemic disease management. Together, the retina's unique features and the power of AI enable early detection, risk stratification, and help revolutionizing disease management plans. However, to fully realize the potential of AI in this domain, further research and validation in real-world settings are essential.

Predicting the cognitive impairment with multimodal ophthalmic imaging and artificial neural network for community screening

BACKGROUND/AIMS

To investigate the comprehensive prediction ability for cognitive impairment in a general elder population using the combination of the multimodal ophthalmic imaging and artificial neural networks.

METHODS

Patients with cognitive impairment and cognitively healthy individuals were recruited. All subjects underwent medical history, blood pressure measurement, the Montreal Cognitive Assessment, medical optometry, intraocular pressure and custom-built multimodal ophthalmic imaging, which integrated pupillary light reaction, multispectral imaging, laser speckle contrast imaging and retinal oximetry. Multidimensional parameters were analysed by Student's t-test. Logistic regression analysis and back-propagation neural network (BPNN) were used to identify the predictive capability for cognitive impairment.

RESULTS

This study included 104 cognitive impairment patients (61.5% female; mean (SD) age, 68.3 (9.4) years), and 94 cognitively healthy age-matched and sex-matched subjects (56.4% female; mean (SD) age, 65.9 (7.6) years). The variation of most parameters including decreased pupil constriction amplitude (CA), relative CA, average constriction velocity, venous diameter, venous blood flow and increased centred retinal reflectance in 548 nm (RC548) in cognitive impairment was consistent with previous studies while the reduced flow acceleration index and oxygen metabolism were reported for the first time. Compared with the logistic regression model, BPNN had better predictive performance (accuracy: 0.91 vs 0.69; sensitivity: 93.3% vs 61.70%; specificity: 90.0% vs 68.66%).

CONCLUSIONS

This study demonstrates retinal spectral signature alteration, neurodegeneration and angiopathy occur concurrently in cognitive impairment. The combination of multimodal ophthalmic imaging and BPNN can be a useful tool for predicting cognitive impairment with high performance for community screening.

Age-related macular degeneration and neurodegenerative disorders: Shared pathways in complex interactions

Age-related macular degeneration (AMD) is a leading cause of irreversible blindness in the elderly, and neurodegenerative disorders such as Alzheimer disease and Parkinson disease are debilitating conditions that affect millions worldwide. Despite the different clinical manifestations of these diseases, growing evidence suggests that they share common pathways in their pathogenesis including inflammation, oxidative stress, and impaired autophagy. In this review, we explore the complex interactions between AMD and neurodegenerative disorders, focusing on their shared mechanisms and potential therapeutic targets. We also discuss the current opportunities and challenges for developing effective treatments that can target these pathways to prevent or slow down disease progression in AMD. Some of the promising strategies that we explore include modulating the immune response, reducing oxidative stress, enhancing autophagy and lysosomal function, and targeting specific protein aggregates or pathways. Ultimately, a better understanding of the shared pathways between AMD and neurodegenerative disorders may pave the way for novel and more efficacious treatments.

Quantifying Putative Retinal Gliosis in Preclinical Alzheimer's Disease

Purpose

Neuroinflammation plays a significant role in the pathology of Alzheimer's disease (AD). Mouse models of AD and postmortem biopsy of patients with AD reveal retinal glial activation comparable to central nervous system immunoreactivity. We hypothesized that the surface area of putative retinal gliosis observed in vivo using en face optical coherence tomography (OCT) imaging will be larger in patients with preclinical AD versus controls.

Methods

The Spectralis II instrument was used to acquire macular centered 20 × 20 and 30 × 25-degrees spectral domain OCT images of 76 participants (132 eyes). A cohort of 22 patients with preclinical AD (40 eyes, mean age = 69 years, range = 60-80 years) and 20 control participants (32 eyes, mean age = 66 years, range = 58-82 years, P = 0.11) were included for the assessment of difference in surface area of putative retinal gliosis and retinal nerve fiber layer (RNFL) thickness. The surface area of putative retinal gliosis and RNFL thickness for the nine sectors of the Early Treatment Diabetic Retinopathy Study (ETDRS) map were compared between groups using generalized linear mixed models.

Results

The surface area of putative retinal gliosis was significantly greater in the preclinical AD group (0.97 ± 0.55 mm2) compared to controls (0.68 ± 0.40 mm2); F(1,70) = 4.41, P = 0.039; Cohen's d = 0.61. There was no significant difference between groups for RNFL thickness in the 9 ETDRS sectors, P > 0.05.

Conclusions

Our analysis shows greater putative retinal gliosis in preclinical AD compared to controls. This demonstrates putative retinal gliosis as a potential biomarker for AD-related neuroinflammation.

The usefulness of the retina for identifying people with type 2 diabetes with prodromal stages of dementia

Type 2 diabetes (T2D) is associated with cognitive impairment and dementia. The detection of cognitive impairment is important because this population is at higher risk of experiencing difficulties in the self-management of diabetes. Mild cognitive impairment (MCI) often remains undiagnosed due to lack of simple tools for screening at large scale. This represents an important gap in the patients' management because subjects with diabetes and MCI are at high risk of progressing to dementia. Due to its developmental origin as a brain-derived tissue, the retina has been proposed as a potential means of non-invasive and readily accessible exploration of brain pathology. Recent evidence showed that retinal imaging and/or functional tests are correlated with the cognitive function and brain changes in T2D. Simple retinal functional tests (i.e. retinal microperimetry) have proven to be useful as reliable tool for the cognitive evaluation and monitoring in patients with T2D>65 years. This review gives an overall update on the usefulness of retinal imaging in identifying patients with T2D at risk of developing dementia.

Deep neural network-estimated age using optical coherence tomography predicts mortality

The concept of biological age has emerged as a measurement that reflects physiological and functional decline with ageing. Here we aimed to develop a deep neural network (DNN) model that predicts biological age from optical coherence tomography (OCT). A total of 84,753 high-quality OCT images from 53,159 individuals in the UK Biobank were included, among which 12,631 3D-OCT images from 8,541 participants without any reported medical conditions at baseline were used to develop an age prediction model. For the remaining 44,618 participants, OCT age gap, the difference between the OCT-predicted age and chronological age, was calculated for each participant. Cox regression models assessed the association between OCT age gap and mortality. The DNN model predicted age with a mean absolute error of 3.27 years and showed a strong correlation of 0.85 with chronological age. After a median follow-up of 11.0 years (IQR 10.9-11.1 years), 2,429 deaths (5.44%) were recorded. For each 5-year increase in OCT age gap, there was an 8% increased mortality risk (hazard ratio [HR] = 1.08, CI:1.02-1.13, P = 0.004). Compared with an OCT age gap within ± 4 years, OCT age gap less than minus 4 years was associated with a 16% decreased mortality risk (HR = 0.84, CI: 0.75-0.94, P = 0.002) and OCT age gap more than 4 years showed an 18% increased risk of death incidence (HR = 1.18, CI: 1.02-1.37, P = 0.026). OCT imaging could serve as an ageing biomarker to predict biological age with high accuracy and the OCT age gap, defined as the difference between the OCT-predicted age and chronological age, can be used as a marker of the risk of mortality.

Optical coherence tomography as a potential surrogate marker of dopaminergic modulation across the life span

The retina has been considered a "window to the brain" and shares similar innervation by the dopaminergic system with the cortex in terms of an unequal distribution of D1 and D2 receptors. Here, we provide a comprehensive overview that Optical Coherence Tomography (OCT), a non-invasive imaging technique, which provides an "in vivo" representation of the retina, shows promise to be used as a surrogate marker of dopaminergic neuromodulation in cognition. Overall, most evidence supports reduced retinal thickness in individuals with dopaminergic dysregulation (e.g., patients with Parkinson's Disease, non-demented older adults) and with poor cognitive functioning. By using the theoretical framework of metacontrol, we derive hypotheses that retinal thinning associated to decreased dopamine (DA) levels affecting D1 families, might lead to a decrease in the signal-to-noise ratio (SNR) affecting cognitive persistence (depending on D1-modulated DA activity) but not cognitive flexibility (depending on D2-modulated DA activity). We argue that the use of OCT parameters might not only be an insightful for cognitive neuroscience research, but also a potentially effective tool for individualized medicine with a focus on cognition. As our society progressively ages in the forthcoming years and decades, the preservation of cognitive abilities and promoting healthy aging will hold of crucial significance. OCT has the potential to function as a swift, non-invasive, and economical method for promptly recognizing individuals with a heightened vulnerability to cognitive deterioration throughout all stages of life.

Normal-Tension Glaucoma and Potential Clinical Links to Alzheimer's Disease

Glaucoma is a group of optic neuropathies and the world's leading cause of irreversible blindness. Normal-tension glaucoma (NTG) is a subtype of glaucoma that is characterized by a typical pattern of peripheral retinal loss, in which the patient's intraocular pressure (IOP) is considered within the normal range (<21 mmHg). Currently, the only targetable risk factor for glaucoma is lowering IOP, and patients with NTG continue to experience visual field loss after IOP-lowering treatments. This demonstrates the need for a better understanding of the pathogenesis of NTG and underlying mechanisms leading to neurodegeneration. Recent studies have found significant connections between NTG and cerebral manifestations, suggesting NTG as a neurodegenerative disease beyond the eye. Gaining a better understanding of NTG can potentially provide new Alzheimer's Disease diagnostics capabilities. This review identifies the epidemiology, current biomarkers, altered fluid dynamics, and cerebral and ocular manifestations to examine connections and discrepancies between the mechanisms of NTG and Alzheimer's Disease.

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.

Recent advances in the use of optical coherence tomography in neuro-ophthalmology: A review

Optical coherence tomography (OCT) is an in vivo imaging modality that provides non-invasive, high resolution and fast cross-sectional images of the optic nerve head, retina and choroid. OCT angiography (OCTA) is an emerging tool. It is a non-invasive, dye-free imaging approach of visualising the microvasculature of the retina and choroid by employing motion contrast imaging for blood flow detection and is gradually receiving attention for its potential roles in various neuro-ophthalmic and retinal conditions. We will review the clinical utility of the OCT in the management of various common neuro-ophthalmic and neurological disorders. We also review some of the OCTA research findings in these conditions. Finally, we will discuss the limitations of OCT as well as introduce other emerging technologies.

Retinal Thinning in Adults with Autism Spectrum Disorder

Since the retina shares its embryological origin with the central nervous system, optical coherence tomography (OCT), an imaging technique frequently employed in ophthalmology to analyze the macula and intraretinal layer thicknesses and volumes, has recently become increasingly important in psychiatric research. We examined 34 autistic and 31 neurotypical adults (NT) using OCT. Autistic adults had reduced overall macular and outer nuclear layer (ONL) thickness and volume compared to NT. Both macular and ONL thickness showed significant inverse associations with the severity of autistic symptoms measured with the Social Responsiveness Scale 2 (SRS-2). Longitudinal studies across different age groups are required to clarify whether retinal changes may represent a possible trait marker.

[Retinal optical coherence tomography biomarkers in dementia]

BACKGROUND

Due to the general aging of society, the prevalence and incidence of dementia are expected to increase considerably. In order to timely identify patients and assess their need for treatment and/or supportive measures, comprehensive and easy access screening methods are required, which, however, are yet to be developed. To date, several biomarkers for the presence of dementia on high-resolution spectral domain optical coherence tomography (OCT) and OCT angiography (OCT-A) images were identified.

AIM

To summarize previously identified OCT biomarkers in dementia and to assess their suitability for comprehensive screening examinations.

MATERIAL AND METHODS

A literature search was conducted on PubMed until March 2023 for the keywords "dementia", "mild cognitive impairment", "OCT", "OCT angiography" and "retinal biomarkers". Relevant publications were identified and summarized.

RESULTS

Numerous unspecific alterations on OCT imaging and OCT‑A were identified in patients with (predementia) dementia according to many population and clinical studies. These include a reduced thickness of the peripapillary retinal nerve fiber layer, the ganglion cell complex and the central retinal region. Additionally, a reduced vascular density and an enlarged foveal avascular zone (FAZ) were identified on OCT‑A imaging.

CONCLUSION

The currently known OCT biomarkers are too unspecific, and there is to date no OCT or OCT-A-based signature distinguishing between different types of dementia. Further longitudinal studies with larger sample sizes are warranted to develop and evaluate such distinct OCT signatures for different types of dementia and their respective early disease stages and to assess their prognostic value. Only then is the inclusion in comprehensive screening investigations feasible.

Deep Learning and Machine Learning Algorithms for Retinal Image Analysis in Neurodegenerative Disease: Systematic Review of Datasets and Models

Purpose

Retinal images contain rich biomarker information for neurodegenerative disease. Recently, deep learning models have been used for automated neurodegenerative disease diagnosis and risk prediction using retinal images with good results.

Methods

In this review, we systematically report studies with datasets of retinal images from patients with neurodegenerative diseases, including Alzheimer's disease, Huntington's disease, Parkinson's disease, amyotrophic lateral sclerosis, and others. We also review and characterize the models in the current literature which have been used for classification, regression, or segmentation problems using retinal images in patients with neurodegenerative diseases.

Results

Our review found several existing datasets and models with various imaging modalities primarily in patients with Alzheimer's disease, with most datasets on the order of tens to a few hundred images. We found limited data available for the other neurodegenerative diseases. Although cross-sectional imaging data for Alzheimer's disease is becoming more abundant, datasets with longitudinal imaging of any disease are lacking.

Conclusions

The use of bilateral and multimodal imaging together with metadata seems to improve model performance, thus multimodal bilateral image datasets with patient metadata are needed. We identified several deep learning tools that have been useful in this context including feature extraction algorithms specifically for retinal images, retinal image preprocessing techniques, transfer learning, feature fusion, and attention mapping. Importantly, we also consider the limitations common to these models in real-world clinical applications.

Translational Relevance

This systematic review evaluates the deep learning models and retinal features relevant in the evaluation of retinal images of patients with neurodegenerative disease.

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.

Neurodegeneration with Brain Iron Accumulation Disorders and Retinal Neurovascular Structure

BACKGROUND

The unique neurovascular structure of the retina has provided an opportunity to observe brain pathology in many neurological disorders. However, such studies on neurodegeneration with brain iron accumulation (NBIA) disorders are lacking.

OBJECTIVES

To investigate NBIA's neurological and ophthalmological manifestations.

METHODS

This cross-sectional study was conducted on genetically confirmed NBIA patients and an age-gender-matched control group. The thickness of retinal layers, central choroidal thickness (CCT), and capillary plexus densities were measured by spectral domain-optical coherence tomography (SD-OCT) and OCT angiography, respectively. The patients also underwent funduscopy, electroretinography (ERG), visual evoked potential (VEP), and neurological examination (Pantothenate-Kinase Associated Neurodegeneration-Disease Rating Scale [PKAN-DRS]). The generalized estimating equation model was used to consider inter-eye correlations.

RESULTS

Seventy-four patients' and 80 controls' eyes were analyzed. Patients had significantly decreased visual acuity, reduced inner or outer sectors of almost all evaluated layers, increased CCT, and decreased vessel densities, with abnormal VEP and ERG in 32.4% and 45.9%, respectively. There were correlations between visual acuity and temporal peripapillary nerve fiber layer (positive) and between PKAN-DRS score and disease duration (negative), and scotopic b-wave amplitudes (positive). When considering only the PKAN eyes, ONL was among the significantly decreased retinal layers, with no differences in retinal vessel densities. Evidence of pachychoroid was only seen in patients with Kufor Rakeb syndrome.

CONCLUSION

Observing pathologic structural and functional neurovascular changes in NBIA patients may provide an opportunity to elucidate the underlying mechanisms and differential retinal biomarkers in NBIA subtypes in further investigations. © 2023 International Parkinson and Movement Disorder Society.

Quantitative Analysis of Retinal Perfusion in Patients with Frontotemporal Dementia Using Optical Coherence Tomography Angiography

BACKGROUND

Optical coherence tomography angiography (OCT-A) provides detailed visualization of the perfusion of the vascular network of the eye. While in other forms of dementia, such as Alzheimer's disease and mild cognitive impairment, reduced retinal perfusion was frequently reported, data of patients with frontotemporal dementia (FTD) are lacking.

OBJECTIVE

Retinal and optic nerve head perfusion was evaluated in patients with FTD with OCT-A. Quantitative OCT-A metrics were analyzed and correlated with clinical markers and vascular cerebral lesions in FTD patients.

METHODS

OCT-A was performed in 18 eyes of 18 patients with FTD and 18 eyes of 18 healthy participants using RTVue XR Avanti with AngioVue. In addition, patients underwent a detailed ophthalmological, neurological, and neuropsychological examination, cerebral magnetic resonance imaging (MRI), and lumbar puncture.

RESULTS

The flow density in the optic nerve head (ONH) and in the superficial capillary plexus (SCP) of the macula of patients was significantly lower compared to that of healthy controls (p < 0.001). Similarly, the VD in the deep capillary plexus (DCP) of the macula of patients was significantly lower compared to that of healthy controls (p < 0.001). There was no significant correlation between the flow density data, white matter lesions in brain MRI, cognitive deficits, and cerebrospinal fluid markers of dementia.

CONCLUSIONS

Patients with FTD showed a reduced flow density in the ONH, and in the superficial and deep retinal capillary plexus of the macula, when compared with that of healthy controls. Quantitative analyses of retinal perfusion using OCT-A may therefore help in the diagnosis and monitoring of FTD. Larger and longitudinal studies are necessary to evaluate if OCT-A is a suitable biomarker for patients with FTD.

Chromatic pupillometry for evaluating melanopsin retinal ganglion cell function in Alzheimer's disease and other neurodegenerative disorders: a review

The evaluation of pupillary light reflex (PLR) by chromatic pupillometry may provide a unique insight into specific photoreceptor functions. Chromatic pupillometry refers to evaluating PLR to different wavelengths and intensities of light in order to differentiate outer/inner retinal photoreceptor contributions to the PLR. Different protocols have been tested and are now established to assess in-vivo PLR contribution mediated by melanopsin retinal ganglion cells (mRGCs). These intrinsically photosensitive photoreceptors modulate the non-image-forming functions of the eye, which are mainly the circadian photoentrainment and PLR, via projections to the hypothalamic suprachiasmatic and olivary pretectal nucleus, respectively. In this context, chromatic pupillometry has been used as an alternative and non-invasive tool to evaluate the mRGC system in several clinical settings, including hereditary optic neuropathies, glaucoma, and neurodegenerative disorders such as Parkinson's disease (PD), idiopathic/isolated rapid eye movement sleep behavior disorder (iRBD), and Alzheimer's disease (AD). The purpose of this article is to review the key steps of chromatic pupillometry protocols for studying in-vivo mRGC-system functionality and provide the main findings of this technique in the research setting on neurodegeneration. mRGC-dependent pupillary responses are short-wavelength sensitive, have a higher threshold of activation, and are much slower and sustained compared with rod- and cone-mediated responses, driving the tonic component of the PLR during exposure to high-irradiance and continuous light stimulus. Thus, mRGCs contribute mainly to the tonic component of the post-illumination pupil response (PIPR) to bright blue light flash that persists after light stimulation is switched off. Given the role of mRGCs in circadian photoentrainment, the use of chromatic pupillometry to perform a functional evaluation of mRGcs may be proposed as an early biomarker of mRGC-dysfunction in neurodegenerative disorders characterized by circadian and/or sleep dysfunction such as AD, PD, and its prodromal phase iRBD. The evaluation by chromatic pupillometry of mRGC-system functionality may lay the groundwork for a new, easily accessible biomarker that can be exploited also as the starting point for future longitudinal cohort studies aimed at stratifying the risk of conversion in these disorders.

Correlation of mild cognitive impairment with the thickness of retinal nerve fiber layer and serum indicators in type 2 diabetic patients

Background

Cognitive Impairment arising from type 2 diabetes mellitus (T2DM) has garnered significant attention in recent times. However, there are few studies on the identification and diagnosis of markers of cognitive impairment. Notably, alterations in the Retinal Nerve Fiber Layer's (RNFL) thickness can potentially serve as an indicative measure of central nervous system changes. Further investigations have indicated that the decline in cognitive function within T2DM patients is intricately linked to persistent systemic inflammation and the accumulation of advanced glycosylation end products. Comprehensive studies are warranted to unveil these complex associations.

Objective

This study aims to explore the potential of utilizing the RNFL thickness and serological concentrations of IL-18, irisin, CML, and RAGE as diagnostic indicators for Mild Cognitive Impairment (MCI) among individuals with T2DM.

Methods

The thickness of RNFL were determined in all patients and controls using optical coherence tomography (OCT). The serum levels of IL-18, irisin, CML and RAGE were detected by ELISA kit. In addition, Cognitive assessment was performed by the Mini-Mental State Examination (MMSE) and the Montreal Cognitive assessment (MoCA).

Results

The average RNFL thickness in the right eye were decreased in T2DM and T2DM combined with MCI (T2DM-MCI) patients and were positively correlated with MoCA and MMSE scores. The serum levels of IL-18, CML and RAGE in T2DM and T2DM-MCI increased significantly (p<0.05) and were negative correlated with MoCA and MMSE scores. The level of irisin in T2DM and T2DM-MCI decreased significantly (p<0.05) and were positively correlated with MoCA and MMSE scores. The area under the ROC curve of T2DM-MCI predicted by the average RNFL thickness in the right eye, CML and RAGE were 0.853, 0.874 and 0.815. The diagnostic efficacy of the combination of average RNFL thickness in the right eye, CML, and RAGE for the diagnosis of T2DM-MCI was 0.969.

Conclusion

The average RNFL thickness in the right eye, CML and RAGE have possible diagnostic value in T2DM-MCI patients.

Optical Coherence Tomography in Schizophrenia Spectrum Disorders: A Systematic Review and Meta-analysis

Background

Inner retinal atrophy has been demonstrated in schizophrenia spectrum disorder (SSD) using optical coherence tomography (OCT). This systematic review and meta-analysis investigated the role of contemporary Fourier domain OCT devices in SSD.

Methods

MEDLINE, PubMed, Scopus, Embase, PsycInfo, PYSNDEX, World Health Organization, and Cochrane databases were searched from inception until May 2022. All peer-reviewed adult SSD case-control studies using Fourier domain OCT were included. Ocular pathologies known to affect retinal OCT scans were excluded. Search, data appraisal, and summary data extraction were independently performed by 2 authors.

Results

The review criteria was met by k = 36 studies, with k = 24 studies (1074 cases, 854 controls) suitable for meta-analysis. The SSD group exhibited a thinner global peripapillary retinal nerve fiber layer (-3.26 μm, 95% CI, -5.07 to -1.45, I2 = 64%, k = 21), thinner average macular layer (-7.88 μm, 95% CI, -12.73 to -3.04, I2 = 65%, k = 11), and thinner macular ganglion cell-inner plexiform sublayer (-2.44 μm, 95% CI, -4.13 to -0.76, I2 = 30%, k = 8) compared with the control group. Retinal nerve fiber layer findings remained significant after exclusion of metabolic disease, low quality, outlier, and influential studies. Studies involving eye examinations to exclude eye disease were associated with greater atrophy in SSD. Except for cardiometabolic disease, most studies did not report clinically significant covariate data known to influence retinal thickness.

Conclusions

Individuals with SSD generally exhibited retinal atrophy, possibly paralleling reduced brain volumes documented in clinical imaging. Prospective longitudinal studies that collect clinical data, including various illness phases, and control for confounders will be necessary to evaluate retinal atrophy as a biomarker in SSD.

Optic Disc and Retinal Architecture Changes in Patients with Spinocerebellar Ataxia Type 2

BACKGROUND

ATXN2 is the causative gene of spinocerebellar ataxia type 2 (SCA2) and has been implicated in glaucoma pathogenesis. Therefore, studying ocular changes in SCA2 could uncover clinically relevant changes.

OBJECTIVE

The aim was to investigate optic disc and retinal architecture in SCA2.

METHODS

We evaluated 14 patients with SCA2 and 26 controls who underwent intraocular pressure measurement, fundoscopy, and macular and peripapillary spectral domain optical coherence tomography (SD-OCT). We compared SD-OCT measurements in SCA2 and controls, and the frequency of glaucomatous changes among SCA2, controls, and 76 patients with other SCAs (types 1, 3, 6, and 7).

RESULTS

The macula, peripapillary retinal nerve fiber and inner plexiform layers were thinner in SCA2 than in controls. Increased cup-to-disc ratio was more frequent in SCA2 than in controls and other SCAs.

CONCLUSIONS

Ocular changes are part of SCA2 phenotype. Future studies should further investigate retinal and optic nerve architecture in this disorder.

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.

A Convolutional Neural Network Using Multimodal Retinal Imaging for Differentiation of Mild Cognitive Impairment from Normal Cognition

Purpose

To develop a machine learning tool capable of differentiating eyes of subjects with normal cognition from those with mild cognitive impairment (MCI) using OCT and OCT angiography (OCTA).

Design

Evaluation of a diagnostic technology.

Participants

Subjects with normal cognition were compared to subjects with MCI.

Methods

A multimodal convolutional neural network (CNN) was built to predict likelihood of MCI from ganglion cell-inner plexiform layer (GC-IPL) thickness maps, OCTA images, and quantitative data including patient characteristics.

Main Outcome Measures

Area under the receiver operating characteristic curve (AUC) and summaries of the confusion matrix (sensitivity and specificity) were used as performance metrics for the prediction outputs of the CNN.

Results

Images from 236 eyes of 129 cognitively normal subjects and 154 eyes of 80 MCI subjects were used for training, validating, and testing the CNN. When applied to the independent test set using inputs including GC-IPL thickness maps, OCTA images, and quantitative OCT and OCTA data, the AUC value for the CNN was 0.809 (95% confidence interval [CI]: 0.681-0.937). This model achieved a sensitivity of 79% and specificity of 83%. The AUC value for GC-IPL thickness maps alone was 0.681 (95% CI: 0.529-0.832), for OCTA images alone was 0.625 (95% CI: 0.466-0.784) and for both GC-IPL maps and OCTA images was 0.693 (95% CI: 0.543-0.843). Models using quantitative data alone were also tested, with a model using quantitative data derived from images, 0.960 (95% CI: 0.902-1.00), outperforming a model using demographic data alone, 0.580 (95% CI: 0.417-0.742).

Conclusions

This novel CNN was able to identify an MCI diagnosis using an independent test set comprised of OCT and OCTA images and quantitative data. The GC-IPL thickness maps provided more useful decision support than the OCTA images. The addition of quantitative data inputs also provided significant decision support to the CNN to identify individuals with MCI. Quantitative imaging metrics provided superior decision support than demographic data.

Financial Disclosures

Proprietary or commercial disclosure may be found after the references.

Eye Adult Changes in Thought (Eye ACT) Study: Design and Report on the Inaugural Cohort

Background

Conflicting research on retinal biomarkers of Alzheimer's disease and related dementias (AD/ADRD) is likely related to limited sample sizes, study design, and protocol differences.

Objective

The prospective Eye Adult Changes in Thought (Eye ACT) seeks to address these gaps.

Methods

Eye ACT participants are recruited from ACT, an ongoing cohort of dementia-free, older adults followed biennially until AD/ADRD, and undergo visual function and retinal imaging assessment either in clinic or at home.

Results

330 participants were recruited as of 03/2023. Compared to ACT participants not in Eye ACT (N = 1868), Eye ACT participants (N = 330) are younger (mean age: 70.3 versus 71.2, p = 0.014), newer to ACT (median ACT visits since baseline: 3 versus 4, p < 0.001), have more years of education (17.7 versus 16.2, p < 0.001) and had lower rates of visual impairment (12% versus 22%, p < 0.001). Compared to those seen in clinic (N = 300), Eye ACT participants seen at home (N = 30) are older (77.2 versus 74.9, p = 0.015), more frequently female (60% versus 49%, p = 0.026), and have significantly worse visual acuity (71.1 versus 78.9 Early Treatment Diabetic Retinopathy Study letters, p < 0.001) and contrast sensitivity (-1.9 versus -2.1 mean log units at 3 cycles per degree, p = 0.002). Cognitive scores and retinal imaging measurements are similar between the two groups.

Conclusions

Participants assessed at home had significantly worse visual function than those seen in clinic. By including these participants, Eye ACT provides a unique longitudinal cohort for evaluating potential retinal biomarkers of dementia.

Normative Database of the Superior-Inferior Thickness Asymmetry for All Inner and Outer Macular Layers of Adults for the Posterior Pole Algorithm of the Spectralis SD-OCT

BACKGROUND

This study aims to establish a reference for the superior-inferior hemisphere asymmetry in thickness values for all macular layers for the posterior pole algorithm (PPA) available for the Spectralis SD-OCT device.

METHODS

We examined 300 eyes of 300 healthy Caucasian volunteers aged 18-84 years using the PPA, composed of a grid of 64 (8 × 8) cells, to analyze the thickness asymmetries of the following automatically segmented macular layers: retinal nerve fiber layer (RNFL); ganglion cell layer (GCL); inner plexiform layer (IPL); inner nuclear layer (INL); outer plexiform layer (OPL); outer nuclear layer (ONL); retinal pigment epithelium (RPE); inner retina; outer retina; complete retina. Mean ± standard deviation and the 2.5th and 97.5th percentiles of the thickness asymmetry values were obtained for all the corresponding cells.

RESULTS

All the macular layers had significant superior-inferior thickness asymmetries. GCL, IPL, INL, ONL and RPE showed significantly greater thicknesses in the superior than the inferior hemisphere, whereas RNFL and OPL were thicker in the inferior hemisphere. The largest differences between hemispheres were for RNFL and ONL.

CONCLUSIONS

This is the first normative database of macular thickness asymmetries for the PPA and should be considered to distinguish normal from pathological values when interpreting superior-inferior macular asymmetries.

High Myopia Normative Database of Peripapillary Retinal Nerve Fiber Layer Thickness to Detect Myopic Glaucoma in a Chinese Population

PURPOSE

To develop and validate the performance of a high myopia (HM)-specific normative database of peripapillary retinal nerve fiber layer (pRNFL) thickness in differentiating HM from highly myopic glaucoma (HMG).

DESIGN

Cross-sectional multicenter study.

PARTICIPANTS

A total of 1367 Chinese participants (2325 eyes) with nonpathologic HM or HMG were included from 4 centers. After quality control, 1108 eyes from 694 participants with HM were included in the normative database; 459 eyes from 408 participants (323 eyes with HM and 136 eyes with HMG) and 322 eyes from 197 participants (131 eyes with HM and 191 eyes with HMG) were included in the internal and external validation sets, respectively. Only HMG eyes with an intraocular pressure > 21 mmHg were included.

METHODS

The pRNFL thickness was measured with swept-source (SS) OCT. Four strategies of pRNFL-specified values were examined, including global and quadrantic pRNFL thickness below the lowest fifth or the lowest first percentile of the normative database.

MAIN OUTCOMES MEASURES

The accuracy, sensitivity, and specificity of the HM-specific normative database for detecting HMG.

RESULTS

Setting the fifth percentile of the global pRNFL thickness as the threshold, using the HM-specific normative database, we achieved an accuracy of 0.93 (95% confidence interval [CI], 0.90-0.95) and 0.85 (95% CI, 0.81-0.89), and, using the first percentile as the threshold, we acheived an accuracy of 0.85 (95% CI, 0.81-0.88) and 0.70 (95% CI, 0.65-0.75) in detecting HMG in the internal and external validation sets, respectively. The fifth percentile of the global pRNFL thickness achieved high sensitivities of 0.75 (95% CI, 0.67-0.82) and 0.75 (95% CI, 0.68-0.81) and specificities of 1.00 (95% CI, 0.99-1.00) and 1.00 (95% CI, 0.97-1.00) in the internal and external validation datasets, respectively. Compared with the built-in database of the OCT device, the HM-specific normative database showed a higher sensitivity and specificity than the corresponding pRNFL thickness below the fifth or first percentile (P < 0.001 for all).

CONCLUSIONS

The HM-specific normative database is more capable of detecting HMG eyes than the SS OCT built-in database, which may be an effective tool for differential diagnosis between HMG and HM.

FINANCIAL DISCLOSURE(S)

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

Differential Study of Retinal Thicknesses in the Eyes of Alzheimer's Patients, Multiple Sclerosis Patients and Healthy Subjects

Multiple sclerosis (MS) and Alzheimer's disease (AD) cause retinal thinning that is detectable in vivo using optical coherence tomography (OCT). To date, no papers have compared the two diseases in terms of the structural differences they produce in the retina. The purpose of this study is to analyse and compare the neuroretinal structure in MS patients, AD patients and healthy subjects using OCT. Spectral domain OCT was performed on 21 AD patients, 33 MS patients and 19 control subjects using the Posterior Pole protocol. The area under the receiver operating characteristic (AUROC) curve was used to analyse the differences between the cohorts in nine regions of the retinal nerve fibre layer (RNFL), ganglion cell layer (GCL), inner plexiform layer (IPL) and outer nuclear layer (ONL). The main differences between MS and AD are found in the ONL, in practically all the regions analysed (AUROCFOVEAL = 0.80, AUROCPARAFOVEAL = 0.85, AUROCPERIFOVEAL = 0.80, AUROC_PMB = 0.77, AUROCPARAMACULAR = 0.85, AUROCINFERO_NASAL = 0.75, AUROCINFERO_TEMPORAL = 0.83), and in the paramacular zone (AUROCPARAMACULAR = 0.75) and infero-temporal quadrant (AUROCINFERO_TEMPORAL = 0.80) of the GCL. In conclusion, our findings suggest that OCT data analysis could facilitate the differential diagnosis of MS and AD.

Structural and Functional Retinal Changes in Patients with Mild Cognitive Impairment with and without Diabetes

Our objective is to analyze retinal changes using optical coherence tomography angiography (OCT-A) in patients with mild cognitive impairment (MCI) to characterize structural and vascular alterations. This cross-sectional study involved 117 eyes: 39 eyes from patients with MCI plus diabetes (DM-MCI), 39 eyes from patients with MCI but no diabetes (MCI); and 39 healthy control eyes (C). All patients underwent a visual acuity measurement, a structural OCT, an OCT-A, and a neuropsychological examination. Our study showed a thinning of retinal nerve fiber layer thickness (RNFL) and a decrease in macular thickness when comparing the MCI-DM group to the C group (p = 0.008 and p = 0.016, respectively). In addition, an increase in arteriolar thickness (p = 0.016), a reduction in superficial capillary plexus density (p = 0.002), and a decrease in ganglion cell thickness (p = 0.027) were found when comparing the MCI-DM group with the MCI group. Diabetes may exacerbate retinal vascular changes when combined with mild cognitive impairment.

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.

Automatic Segmentation of Retinal Layers in Multiple Neurodegenerative Disorder Scenarios

Retinal Optical Coherence Tomography (OCT) allows the non-invasive direct observation of the central nervous system, enabling the measurement and extraction of biomarkers from neural tissue that can be helpful in the assessment of ocular, systemic and Neurological Disorders (ND). Deep learning models can be trained to segment the retinal layers for biomarker extraction. However, the onset of ND can have an impact on the neural tissue, which can lead to the degraded performance of models not exposed to images displaying signs of disease during training. We present a fully automatic approach for the retinal layer segmentation in multiple neurodegenerative disorder scenarios, using an annotated dataset of patients of the most prevalent NDs: Alzheimer's disease, Parkinson's disease, multiple sclerosis and essential tremor, along with healthy control patients. Furthermore, we present a two-part, comprehensive study on the effects of ND on the performance of these models. The results show that images of healthy patients may not be sufficient for the robust training of automated segmentation models intended for the analysis of ND patients, and that using images representative of different NDs can increase the model performance. These results indicate that the presence or absence of patients of ND in datasets should be taken into account when training deep learning models for retinal layer segmentation, and that the proposed approach can provide a valuable tool for the robust and reliable diagnosis in multiple scenarios of ND.

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 Optical Coherence Tomography Features Associated With Incident and Prevalent Parkinson Disease

BACKGROUND AND OBJECTIVES

Cadaveric studies have shown disease-related neurodegeneration and other morphological abnormalities in the retina of individuals with Parkinson disease (PD); however, it remains unclear whether this can be reliably detected with in vivo imaging. We investigated inner retinal anatomy, measured using optical coherence tomography (OCT), in prevalent PD and subsequently assessed the association of these markers with the development of PD using a prospective research cohort.

METHODS

This cross-sectional analysis used data from 2 studies. For the detection of retinal markers in prevalent PD, we used data from AlzEye, a retrospective cohort of 154,830 patients aged 40 years and older attending secondary care ophthalmic hospitals in London, United Kingdom, between 2008 and 2018. For the evaluation of retinal markers in incident PD, we used data from UK Biobank, a prospective population-based cohort where 67,311 volunteers aged 40-69 years were recruited between 2006 and 2010 and underwent retinal imaging. Macular retinal nerve fiber layer (mRNFL), ganglion cell-inner plexiform layer (GCIPL), and inner nuclear layer (INL) thicknesses were extracted from fovea-centered OCT. Linear mixed-effects models were fitted to examine the association between prevalent PD and retinal thicknesses. Hazard ratios for the association between time to PD diagnosis and retinal thicknesses were estimated using frailty models.

RESULTS

Within the AlzEye cohort, there were 700 individuals with prevalent PD and 105,770 controls (mean age 65.5 ± 13.5 years, 51.7% female). Individuals with prevalent PD had thinner GCIPL (-2.12 μm, 95% CI -3.17 to -1.07, p = 8.2 × 10-5) and INL (-0.99 μm, 95% CI -1.52 to -0.47, p = 2.1 × 10-4). The UK Biobank included 50,405 participants (mean age 56.1 ± 8.2 years, 54.7% female), of whom 53 developed PD at a mean of 2,653 ± 851 days. Thinner GCIPL (hazard ratio [HR] 0.62 per SD increase, 95% CI 0.46-0.84, p = 0.002) and thinner INL (HR 0.70, 95% CI 0.51-0.96, p = 0.026) were also associated with incident PD.

DISCUSSION

Individuals with PD have reduced thickness of the INL and GCIPL of the retina. Involvement of these layers several years before clinical presentation highlight a potential role for retinal imaging for at-risk stratification of PD.

Retinal mid-peripheral capillary free zones are enlarged in cognitively unimpaired older adults at high risk for Alzheimer's disease

BACKGROUND

Compared to standard neuro-diagnostic techniques, retinal biomarkers provide a probable low-cost and non-invasive alternative for early Alzheimer's disease (AD) risk screening. We have previously quantified the periarteriole and perivenule capillary free zones (mid-peripheral CFZs) in cognitively unimpaired (CU) young and older adults as novel metrics of retinal tissue oxygenation. There is a breakdown of the inner retinal blood barrier, pericyte loss, and capillary non-perfusion or dropout in AD leading to potential enlargement of the mid-peripheral CFZs. We hypothesized the mid-peripheral CFZs will be enlarged in CU older adults at high risk for AD compared to low-risk individuals.

METHODS

20 × 20° optical coherence tomography angiography images consisting of 512 b-scans, 512 A-scans per b-scan, 12-µm spacing between b-scans, and 5 frames averaged per each b-scan location of the central fovea and of paired major arterioles and venules with their surrounding capillaries inferior to the fovea of 57 eyes of 37 CU low-risk (mean age: 66 years) and 50 eyes of 38 CU high-risk older adults (mean age: 64 years; p = 0.24) were involved in this study. High-risk participants were defined as having at least one APOE e4 allele and a positive first-degree family history of AD while low-risk participants had neither of the two criteria. All participants had Montreal Cognitive Assessment scores ≥ 26. The mid-peripheral CFZs were computed in MATLAB and compared between the two groups.

RESULTS

The periarteriole CFZ of the high-risk group (75.8 ± 9.19 µm) was significantly larger than that of the low-risk group (71.3 ± 7.07 µm), p = 0.005, Cohen's d = 0.55. The perivenule CFZ of the high-risk group (60.4 ± 8.55 µm) was also significantly larger than that of the low-risk group (57.3 ± 6.40 µm), p = 0.034, Cohen's d = 0.42. There were no significant differences in foveal avascular zone (FAZ) size, FAZ effective diameter, and vessel density between the two groups, all p > 0.05.

CONCLUSIONS

Our results show larger mid-peripheral CFZs in CU older adults at high risk for AD, with the potential for the periarteriole CFZ to serve as a novel retinal vascular biomarker for early AD risk detection.

Potential Ocular Biomarkers for Early Detection of Alzheimer's Disease and Their Roles in Artificial Intelligence Studies

Alzheimer's disease (AD) is the leading cause of dementia worldwide. Early detection is believed to be essential to disease management because it enables physicians to initiate treatment in patients with early-stage AD (early AD), with the possibility of stopping the disease or slowing disease progression, preserving function and ultimately reducing disease burden. The purpose of this study was to review prior research on the use of eye biomarkers and artificial intelligence (AI) for detecting AD and early AD. The PubMed database was searched to identify studies for review. Ocular biomarkers in AD research and AI research on AD were reviewed and summarized. According to numerous studies, there is a high likelihood that ocular biomarkers can be used to detect early AD: tears, corneal nerves, retina, visual function and, in particular, eye movement tracking have been identified as ocular biomarkers with the potential to detect early AD. However, there is currently no ocular biomarker that can be used to definitely detect early AD. A few studies that used AI with ocular biomarkers to detect AD reported promising results, demonstrating that using AI with ocular biomarkers through multimodal imaging could improve the accuracy of identifying AD patients. This strategy may become a screening tool for detecting early AD in older patients prior to the onset of AD symptoms.

Frequency of coexistent eye diseases and cognitive impairment or dementia: a systematic review and meta-analysis

OBJECTIVE

We aim to quantify the co-existence of age-related macular degeneration (AMD), glaucoma, or diabetic retinopathy (DR) and cognitive impairment or dementia.

METHOD

MEDLINE, EMBASE, PsycINFO and CINAHL were searched (to June 2020). Observational studies reporting incidence or prevalence of AMD, glaucoma, or DR in people with cognitive impairment or dementia, and of cognitive impairment or dementia among people with AMD, glaucoma, or DR were included.

RESULTS

Fifty-six studies (57 reports) were included but marked by heterogeneities in the diagnostic criteria or definitions of the diseases, study design, and case mix. Few studies reported on the incidence. Evidence was sparse but consistent in individuals with mild cognitive impairment where 7.7% glaucoma prevalence was observed. Prevalence of AMD and DR among people with cognitive impairment ranged from 3.9% to 9.4% and from 11.4% to 70.1%, respectively. Prevalence of AMD and glaucoma among people with dementia ranged from 1.4 to 53% and from 0.2% to 25.9%, respectively. Prevalence of DR among people with dementia was 11%. Prevalence of cognitive impairment in people with AMD, glaucoma, and DR ranged from 8.4% to 52.4%, 12.3% to 90.2%, and 3.9% to 77.8%, respectively, and prevalence of dementia in people with AMD, glaucoma and DR ranged from 9.9% to 62.6%, 2.5% to 3.3% and was 12.5%, respectively.

CONCLUSIONS

Frequency of comorbid eye disease and cognitive impairment or dementia varied considerably. While more population-based estimations of the co-existence are needed, interdisciplinary collaboration might be helpful in the management of these conditions to meet healthcare needs of an ageing population.

TRIAL REGISTRATION

PROSPERO registration: CRD42020189484.

Optical coherence tomography angiography in Parkinson's disease: a systematic review and meta-analysis

BACKGROUND

To examine the association between optical coherence tomography angiography (OCTA) retinal measurements and Parkinson's disease (PD).

METHODS

We searched MEDLINE and EMBASE from inception up to November 5th, 2021 for studies examining the differences between OCTA retinal measurements in PD patients and healthy controls. We used the Hartung-Knapp-Sidik-Jonkman random-effects method to combine study-specific standardized mean differences (SMD) in pooled effect estimates and a meta-analytic extension of the E-value metric to quantify the confounding bias capable of nullifying the pooled estimates.

RESULTS

Nine eligible studies for our systematic review were identified through our search strategy. The pooled SMD between the retinal vessel density of PD patients and healthy participants in the whole superficial vascular plexus (SVP), foveal SVP, parafoveal SVP and foveal avascular zone (FAZ) was -0.68 (95% CI: -1.18 to -0.17, p value = 0.02, n = 7 studies), -0.14 (95% CI: -0.88 to 0.59, p value = 0.62, n = 5 studies), -0.59 (95% CI: -1.41 to 0.23, p value = 0.12, n = 5 studies) and -0.20 (95% CI: -0.79 to 0.38, p value = 0.39, n = 5 studies), respectively. An unmeasured confounder would need to be associated with a 3.01-fold, 1.54-fold, 2.81-fold and 1.70-fold increase in the risk of PD and OCTA retinal measurements, in order for the pooled SMD estimate of vessel density in whole SVP, parafoveal SVP and FAZ, respectively, to be nullified.

CONCLUSIONS

Our results provide evidence on an inverse association between whole SVP vessel density and PD.

Retina and microvascular alterations in migraine: a systemic review and meta-analysis

Objective

This study aimed to evaluate the retina and microvascular alterations with optical coherence tomography (OCT) or optical coherence tomography angiography (OCTA) in patients with migraine with aura (MA) and migraine without aura (MO).

Methods

PubMed, Embase, and Cochrane Library databases were searched to find relevant literature on patients with MA or MO using OCT/OCTA devices. The eligible data were analyzed by Stata Software (version 15.0).

Results

There were 16 studies identified, involving 379 eyes with MA, 583 eyes with MO, and 658 eyes of healthy controls. The thickness of the peripapillary retinal nerve fiber layer (pRNFL) of patients with MA decreased significantly in most regions. The foveal avascular zone (FAZ) area and perimeter in MA patients significantly enlarged, while the perfusion density (PD) in the macular deep capillary plexus (mDCP) significantly decreased in the whole image and its subregions except for the fovea, with the PD in radial peripapillary capillary (RPC) decreasing inside the disk. Patients with MO demonstrated a significantly decreased thickness of pRNFL in most regions, and the FAZ parameters were significantly enlarged. No statistical significance was observed in the retina and microvascular features of patients with MA and MO.

Conclusion

The eyes affected by MA and MO demonstrated significantly reduced thickness of pRNFL and enlarged FAZ. Patients with MA showed retinal microvascular impairments, including a decreased PD in mDCP. The OCT and OCTA could detect membrane morphology and circulation status in migraine and might provide the basis for the diagnosis and follow-up of patients with migraine.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, CRD42023397653.

Acrolein Induces Retinal Abnormalities of Alzheimer's Disease in Mice

It is reported that retinal abnormities are related to Alzheimer's disease (AD) in patients and animal models. However, it is unclear whether the retinal abnormities appear in the mouse model of sporadic Alzheimer's disease (sAD) induced by acrolein. We investigated the alterations of retinal function and structure, the levels of β-amyloid (Aβ) and phosphorylated Tau (p-Tau) in the retina, and the changes in the retinal vascular system in this mouse model. We demonstrated that the levels of Aβ and p-Tau were increased in the retinas of mice from the acrolein groups. Subsequently, a decreased amplitudes of b-waves in the scotopic and photopic electroretinogram (ERG), decreased thicknesses of the retinal nerve fiber layer (RNFL) in the retina, and slight retinal venous beading were found in the mice induced by acrolein. We propose that sAD mice induced by acrolein showed abnormalities in the retina, which may provide a valuable reference for the study of the retina in sAD.

The association between retina thinning and hippocampal atrophy in Alzheimer's disease and mild cognitive impairment: a meta-analysis and systematic review

Introduction

The retina is the "window" of the central nervous system. Previous studies discovered that retinal thickness degenerates through the pathological process of the Alzheimer's disease (AD) continuum. Hippocampal atrophy is one of the typical clinical features and diagnostic criteria of AD. Former studies have described retinal thinning in normal aging subjects and AD patients, yet the association between retinal thickness and hippocampal atrophy in AD is unclear. The optical coherence tomography (OCT) technique has access the non-invasive to retinal images and magnetic resonance imaging can outline the volume of the hippocampus. Thus, we aim to quantify the correlation between these two parameters to identify whether the retina can be a new biomarker for early AD detection.

Methods

We systematically searched the PubMed, Embase, and Web of Science databases from inception to May 2023 for studies investigating the correlation between retinal thickness and hippocampal volume. The Newcastle-Ottawa Quality Assessment Scale (NOS) was used to assess the study quality. Pooled correlation coefficient r values were combined after Fisher's Z transformation. Moderator effects were detected through subgroup analysis and the meta-regression method.

Results

Of the 1,596 citations initially identified, we excluded 1,062 studies after screening the titles and abstract (animal models, n = 99; irrelevant literature, n = 963). Twelve studies met the inclusion criteria, among which three studies were excluded due to unextractable data. Nine studies were eligible for this meta-analysis. A positive moderate correlation between the retinal thickness was discovered in all participants of with AD, mild cognitive impairment (MCI), and normal controls (NC) (r = 0.3469, 95% CI: 0.2490-0.4377, I2 = 5.0%), which was significantly higher than that of the AD group (r = 0.1209, 95% CI:0.0905-0.1510, I2 = 0.0%) (p < 0.05). Among different layers, the peripapillary retinal nerve fiber layer (pRNFL) indicated a moderate positive correlation with hippocampal volume (r = 0.1209, 95% CI:0.0905-0.1510, I2 = 0.0%). The retinal pigmented epithelium (RPE) was also positively correlated [r = 0.1421, 95% CI:(-0.0447-0.3192), I2 = 84.1%]. The retinal layers and participants were the main overall heterogeneity sources. Correlation in the bilateral hemisphere did not show a significant difference.

Conclusion

The correlation between RNFL thickness and hippocampal volume is more predominant in both NC and AD groups than other layers. Whole retinal thickness is positively correlated to hippocampal volume not only in AD continuum, especially in MCI, but also in NC.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, CRD42022328088.

Ratiometric Analysis of In Vivo Optical Coherence Tomography Retinal Layer Thicknesses for Detection of Changes in Alzheimer's Disease

We analyzed ophthalmic retinal optical coherence tomography (OCT) images from patients with Alzheimer's disease (AD) to identify retinal layer thickness and ratio changes that may serve as image-based biomarkers for the disease. One three-dimensional volume before and one after diagnosis for each of 48 patients were segmented to identify retinal layer and total retinal thicknesses. Between before- and after-diagnosis retinal OCT images, there were significant thickness changes in six of ten (60%) retinal layers across all 48 patients. Through a comparison with age-matched healthy subjects, the significant changes were attributed to AD only (NFL and PR2 layers), age only (GCL, IPL, and RPE layers), or both AD and age (OPL layer). Analyzing ratios of retinal layer thicknesses, 53 of 90 (58.89%) ratios had significant changes. The four independently non-significant layers were assessed to be affected by neither AD nor age (INL layer) or both AD and age (ELM, PR1, and BM layers). The demonstrated image segmentation, measurement, and ratiometric analysis of retinal layers in AD patients may yield a noninvasive OCT image-based retinal biomarker that can be used to detect retinal changes associated with this disease.

Quantitatively Evaluating the Relationships between Insulin Resistance and Retinal Neurodegeneration with Optical Coherence Tomography in Early Type 2 Diabetes Mellitus

INTRODUCTION

The aim of this study was to quantitatively assess retinal neurodegenerative changes with optical coherence tomography (Cirrus HD-OCT) in type 2 diabetes mellitus (T2DM) patients without diabetic retinopathy (DR) and evaluate their relationships with insulin resistance (IR) and associated systemic indicators.

METHODS

102 T2DM patients without DR and 48 healthy controls were included in this observational cross-sectional study. The OCT parameters of macular retinal thickness (MRT) and ganglion cell-inner plexiform layer (GCIPL) thicknesses were evaluated between diabetic and normal eyes. The receiver operating characteristics (ROC) curve was generated to evaluate the discrimination power of early diabetes. Correlation and multiple regression analysis were performed between ophthalmological parameters and T2DM-related demographic and anthropometric variables, and serum biomarkers and homeostasis model assessment of insulin resistance (HOMA-IR) scores.

RESULTS

MRT and GCIPL thicknesses showed significant thinning in patients, especially in inferotemporal area. High body mass index (BMI) correlated with decreased GCIPL thicknesses and elevated intraocular pressure (IOP). A negative correlation between waist-to-hip circumference ratio (WHR) and GCIPL thicknesses was also found. High-density lipoprotein (HDL) and fasting C-peptide (CP0) were associated with GCIPL thickness but only in inferotemporal region (r = 0.20, p = 0.04; r = -0.20, p = 0.05, respectively). Multiple regression analysis showed that increased HOMA-IR scores independently predicted both average (β = -0.30, p = 0.05) and inferotemporal (β = -0.34, p = 0.03) GCIPL thinning.

CONCLUSION

Retinal thinning in early T2DM was associated with obesity-related metabolic disorders. IR as an independent risk factor for retinal neurodegeneration may increase the risk of developing glaucoma.