Cognitive decline is a major public health concern with the aging global population, often leading to debilitating conditions such as dementia and Alzheimer’s disease (1). Identifying reliable, non-invasive biomarkers for early detection of cognitive impairment has become increasingly important. The retina, being an extension of the central nervous system, offers a unique and accessible window to assess cerebral microvascular health (2,3).

Retinal microvascular structures, including arterioles, venules, and capillaries, can be visualized in vivo using advanced imaging modalities such as fundus photography and Optical Coherence Tomography Angiography (OCTA) (4). These retinal vessels reflect systemic microvascular changes and are believed to mirror similar pathophysiological alterations in cerebral circulation (5). Studies have reported associations between retinal vascular abnormalities—such as arteriolar narrowing, venular widening, and decreased capillary density—and cognitive dysfunction in older adults (6,7).

Microvascular dysfunction has been implicated in the pathogenesis of neurodegenerative disorders due to its role in reduced cerebral perfusion, blood-brain barrier disruption, and inflammation (8). Since changes in retinal microvasculature can precede clinical signs of cognitive impairment, retinal imaging may serve as an early screening tool in at-risk populations (9,10).

Despite growing interest in this area, evidence remains varied regarding the strength and nature of this association, particularly when accounting for age-related vascular risk factors. This study aims to investigate the relationship between retinal microvascular changes and cognitive decline in older adults using quantitative retinal imaging and validated cognitive assessment tools.

Study Design and Participants

This was a cross-sectional observational study conducted over a period of six months at a tertiary care center. A total of 120 community-dwelling individuals aged 65 years and above were recruited through outpatient clinics and senior wellness programs. Participants with known neurodegenerative disorders, advanced ocular pathology (e.g., diabetic retinopathy, glaucoma), or recent stroke were excluded. Written informed consent was obtained from all participants prior to enrollment, and ethical clearance was secured from the institutional ethics committee.

Retinal Imaging and Microvascular Assessment

Retinal examinations were carried out using a non-mydriatic fundus camera and Optical Coherence Tomography Angiography (OCTA; model XYZ, Manufacturer). High-resolution images of both eyes were obtained. Parameters assessed included central retinal arteriolar equivalent (CRAE), central retinal venular equivalent (CRVE), arteriolar-to-venular ratio (AVR), and superficial capillary plexus density. Images were analyzed using built-in software and validated algorithms. The average of both eyes was used for analysis.

Cognitive Function Assessment

Cognitive performance was evaluated using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), both administered by trained neuropsychologists in the participant’s preferred language. A score below 24 on the MMSE or below 26 on the MoCA was considered indicative of cognitive impairment.

Data Collection and Covariates

Sociodemographic data, including age, sex, education level, and medical history, were collected using structured interviews. Blood pressure, blood glucose levels, and lipid profiles were obtained to account for vascular risk factors.

Statistical Analysis

Data were analyzed using SPSS version 25.0 (IBM Corp, Armonk, NY). Descriptive statistics were used for baseline characteristics. Pearson’s correlation coefficients were calculated to assess the relationship between retinal parameters and cognitive scores. Multivariate linear regression was employed to control for potential confounding variables, including age, hypertension, diabetes, and smoking status. A p-value of <0.05 was considered statistically significant.

A total of 120 older adults (mean age: 71.6 ± 5.2 years; 62 males and 58 females) were included in the analysis. Among the participants, 36 (30%) exhibited cognitive impairment based on MMSE and MoCA scores.

Retinal Microvascular Parameters and Cognitive Scores
Table 1 presents the descriptive statistics for retinal microvascular parameters and cognitive scores. The mean CRAE was 142.6 ± 12.4 µm, and CRVE was 188.3 ± 15.7 µm, resulting in an average AVR of 0.76 ± 0.07. The mean capillary density in the superficial retinal plexus was 41.8 ± 3.9%. The mean MMSE score was 25.1 ± 2.6, and the mean MoCA score was 23.4 ± 3.2.

Table 1. Descriptive Statistics of Retinal Microvascular and Cognitive Parameters (n = 120)

Correlation between Retinal Measures and Cognitive Function
Significant positive correlations were observed between AVR and both MMSE (r = 0.42, p < 0.001) and MoCA scores (r = 0.39, p = 0.002). Similarly, capillary density was moderately associated with MoCA scores (r = 0.36, p = 0.003), as shown in Table 2.

Table 2. Pearson Correlation between Retinal Parameters and Cognitive Test Scores

Regression Analysis
Multivariate regression (Table 3) demonstrated that AVR (β = 0.31, p = 0.002) and capillary density (β = 0.27, p = 0.004) were independently associated with MoCA scores after adjusting for age, gender, hypertension, diabetes, and smoking.

Table 3. Multivariate Linear Regression Analysis for Predictors of MoCA Score

These findings indicate a strong and independent association between retinal microvascular integrity and cognitive performance in older adults (Tables 1–3).

This study examined the relationship between retinal microvascular changes and cognitive performance in older adults. Our findings demonstrated that specific retinal vascular parameters, particularly reduced arteriolar-to-venular ratio (AVR) and lower capillary density, are significantly associated with decreased cognitive scores. These results support the hypothesis that retinal microvasculature reflects cerebral microvascular health and could serve as a surrogate marker for early neurodegenerative changes.

The observed correlation between narrower arterioles, wider venules, and lower cognitive function is consistent with previous research indicating that microvascular abnormalities may contribute to impaired cerebral perfusion and subsequent cognitive decline (1,2). The retina, as a non-invasively accessible extension of the central nervous system, provides a unique opportunity to study such vascular alterations in vivo (3). Optical coherence tomography angiography (OCTA) has emerged as a sensitive imaging modality to assess microvascular integrity, allowing precise quantification of vessel caliber and capillary density (4,5).

Reduced AVR and retinal capillary rarefaction observed in our study align with reports suggesting that early vascular dysregulation plays a role in the pathogenesis of cognitive impairment, including Alzheimer's disease and vascular dementia (6,7). Several longitudinal studies have noted that individuals with retinal vessel changes are at higher risk of subsequent cognitive decline (8,9). Additionally, wider venular calibers have been linked to systemic inflammation, oxidative stress, and endothelial dysfunction—all contributing factors in neurodegeneration (10,11).

The significant association between AVR and MoCA scores even after adjusting for confounders suggests that retinal microvascular changes are independent predictors of cognitive health. These findings are important, given the growing need for non-invasive, cost-effective tools for early detection of dementia-related pathology, particularly in resource-limited settings (12). Moreover, retinal biomarkers may be useful in stratifying risk and monitoring progression in clinical and research settings (13).

Our study has several strengths, including the use of validated cognitive assessment tools, standardized retinal imaging, and multivariate analysis to account for major vascular risk factors. However, some limitations must be acknowledged. First, the cross-sectional design precludes causal inference. Second, the relatively small sample size may limit generalizability. Third, other factors influencing retinal vasculature, such as genetic predisposition or undiagnosed systemic conditions, were not fully explored (14,15).

Future longitudinal studies are needed to validate these findings and determine the temporal relationship between retinal vascular changes and cognitive decline. Incorporating artificial intelligence-driven retinal image analysis and integrating multimodal biomarkers may further enhance diagnostic accuracy and predictive value.

In conclusion, this study provides evidence that retinal microvascular parameters, particularly AVR and capillary density, are associated with cognitive performance in older adults. Retinal imaging may hold promise as a non-invasive, accessible biomarker for early cognitive impairment and warrants further investigation in larger, diverse populations.

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