Association of Inner Retinal Thickness with Prevalent Dementia and Brain Atrophy in a General Older Population

Association of sarcopenia with regional brain atrophy and white matter lesions in a general older population: the Hisayama Study

Sarcopenia has been reported to be associated with cognitive decline and the risk of dementia. However, few studies have addressed the association between sarcopenia and brain morphological changes in the general population. A total of 1373 community-dwelling participants aged ≥ 65 years underwent brain MRI. Sarcopenia was defined based on the Asian Working Group for Sarcopenia's criteria. The pattern of regional gray matter volume loss associated with sarcopenia were assessed using a voxel-based morphometry (VBM) analysis. Regional brain volumes, intracranial volumes (ICV), and white matter lesions volumes (WMLV) were also measured using FreeSurfer. An analysis of covariance was used to examine the associations of sarcopenia with regional brain volumes in proportion to ICV. Of the participants, 112 had sarcopenia. The participants with sarcopenia had significantly lower total brain volume/ICV and total gray matter volume/ICV and higher WMLV/ICV than those without sarcopenia after adjusting for confounders. In VBM, sarcopenia was associated with lower gray matter volume in the frontal lobe, insula, cingulate gyrus, hippocampus, amygdala, and basal ganglia. Using FreeSurfer, we confirmed that the participants with sarcopenia had significantly lower frontal, insular, cingulate, and hippocampal volumes than those without sarcopenia. The current study showed that participants with sarcopenia had significantly lower volume in the frontal lobe, insula, cingulate, and hippocampus and higher WMLV than participants without sarcopenia. As these brain regions are likely to play an important role in cognitive function, these changes may suggest a shared underlying mechanism for the progression of sarcopenia and cognitive decline.

Retinal and Choroidal Phenotypes Across Novel Subtypes of Type 2 Diabetes Mellitus

PURPOSE

To investigate longitudinal changes in choroidal thickness (CT) and ganglion cell-inner plexiform layer thickness (GC-IPLT) across distinct phenotypes of type 2 diabetes mellitus (T2DM) patients.

DESIGN

Prospective cohort study.

METHODS

T2DM patients were categorized into 5 groups (SAID, SIDD, SIRD, MOD, and MARD) using K-means clustering based on β-cell function and insulin resistance. Swept-source optical coherence tomography measured baseline and 4-year follow-up CT and GC-IPLT. Linear mixed-effects models assessed absolute and relative changes in CT and GC-IPLT across subtypes.

RESULTS

Over a median 4.11-year follow-up, CT and GC-IPLT decreased significantly across all groups. Choroidal thinning rates were most pronounced in SIDD (-6.5 ± 0.53 µm/year and -3.5 ± 0.24%/year) and SAID (-6.27 ± 0.8 µm/year and -3.19 ± 0.37%/year), while MARD showed the slowest thinning rates (-3.63 ± 0.34 µm/year and -1.98 ± 0.25%/year). SIRD exhibited the greatest GC-IPLT loss (-0.66 ± 0.05 µm/year and -0.91 ± 0.07%/year), with the least in SIDD (-0.36 ± 0.05 µm/year and -0.49 ± 0.07%/year), all statistically significant (all P < 0.001). Adjusted for confounding variables, SIDD and SAID groups showed faster CT thinning than MARD [-2.57 µm/year (95% CI: -4.16 to -0.97; P = 0.002) and -2.89 µm/year (95% CI: -4.12 to -1.66; P < 0.001), respectively]. GC-IPLT thinning was notably accelerated in SIRD versus MARD, but slowed in SIDD relative to MARD [differences of -0.16 µm/year (95% CI: -0.3 to -0.03; P = 0.015) and 0.15 µm/year (95% CI: 0.03 to 0.27; P = 0.015), respectively].

CONCLUSIONS

Microvascular damage in the choroid is associated with SIDD patients, whereas early signs of retinal neurodegeneration are evident in SIRD patients. All these changes may precede the onset of DR.

Retinal thickness predicts the risk of cognitive decline over five years

BACKGROUND

Dementia poses a significant burden on healthcare systems. Early identification of individuals at risk for cognitive decline is crucial. The retina, an extension of the central nervous system, reflects neurodegenerative changes. Optical coherence tomography (OCT) is a non-invasive tool for assessing retinal health and has shown promise in predicting cognitive decline. However, prior studies produced mixed results.

METHODS

This study investigated a large cohort (n = 490) of Asian individuals attending memory clinics. Participants underwent comprehensive neuropsychological testing annually for five years. Retinal thickness was measured by OCT at baseline. We assessed the association between baseline retinal thickness and subsequent cognitive decline.

RESULTS

Participants with a significantly thinner macular ganglion cell-inner plexiform layer (GCIPL) at baseline (≤ 79 μm) had a 38% greater risk of cognitive decline compared to those who did not (≥ 88 μm; p = 0.037). In a multivariable model accounting for age, education, cerebrovascular disease status, hypertension, hyperlipidemia, diabetes and smoking, thinner GCIPL was associated with an increased risk of cognitive decline (hazard ratio = 1.14, 95% CI = 1.01-1.30, p = 0.035). Retinal nerve fiber layer (RNFL) thickness was not associated with cognitive decline.

CONCLUSIONS

This study suggests that OCT-derived macular GCIPL thickness may be a valuable biomarker for identifying individuals at risk of cognitive decline. Our findings highlight GCIPL as a potentially more sensitive marker compared to RNFL thickness for detecting early neurodegenerative changes.

TRIAL REGISTRATION NUMBER AND NAME OF THE TRIAL REGISTRY

National Healthcare Group Domain-Specific Review Board (NHG DSRB) reference numbers DSRB Ref: 2018/01368. Name of the trial: Harmonisation project.

Eye-brain connections revealed by multimodal retinal and brain imaging genetics

The retina, an anatomical extension of the brain, forms physiological connections with the visual cortex of the brain. Although retinal structures offer a unique opportunity to assess brain disorders, their relationship to brain structure and function is not well understood. In this study, we conducted a systematic cross-organ genetic architecture analysis of eye-brain connections using retinal and brain imaging endophenotypes. We identified novel phenotypic and genetic links between retinal imaging biomarkers and brain structure and function measures from multimodal magnetic resonance imaging (MRI), with many associations involving the primary visual cortex and visual pathways. Retinal imaging biomarkers shared genetic influences with brain diseases and complex traits in 65 genomic regions, with 18 showing genetic overlap with brain MRI traits. Mendelian randomization suggests bidirectional genetic causal links between retinal structures and neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, our findings reveal the genetic basis for eye-brain connections, suggesting that retinal images can help uncover genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.

Distinct retinal reflectance spectra from retinal hyperspectral imaging in Parkinson's disease

BACKGROUND

Recent developments in the retinal hyperspectral imaging method have indicated its potential in addressing challenges posed by neurodegenerative disorders, such as Alzheimer's disease. This human clinical study is the first to assess reflectance spectra obtained from this imaging as a tool for diagnosing patients with Parkinson's disease (PD).

METHODS

Retinal hyperspectral imaging was conducted on a total of 40 participants, including 20 patients with PD and 20 controls. Following preprocessing, retinal reflectance spectra were computed for the macular retina defined by four rectangular regions. Linear discriminant analysis classifiers underwent training to discern patients with PD from control participants. To assess the performance of the selected features, nested leave-one-out cross-validation was employed using machine learning. The indicated values include the area under the curve (AUC) and the corresponding 95% confidence interval (CI).

RESULTS

Retinal reflectance spectra of PD patients exhibited variations in the spectral regions, particularly at shorter wavelengths (superonasal retina, wavelength < 490 nm; inferonasal retina, wavelength < 510 nm) when compared to those of controls. Retinal reflectance spectra yielded an AUC of 0.60 (95% CI: 0.43-0.78) and 0.60 (95% CI: 0.43-0.78) for the superonasal and inferonasal retina, respectively, distinguishing individuals with and without PD.

CONCLUSION

Reflectance spectra obtained from retinal hyperspectral imaging tended to decrease at shorter wavelengths across a broad spectral range in PD patients. Further investigations building upon these preliminary findings are imperative to focus on the retinal spectral signatures associated with PD pathological hallmarks, including α-synuclein.

Association between retinopathy and risk of dementia in a general Japanese population: the Hisayama Study

We investigated the association of retinopathy with the risk of dementia in a general older Japanese population. A total of 1709 population-based residents aged 60 years or older without dementia were followed prospectively for 10 years (2007-2017). They underwent color fundus photography in 2007. Retinopathy was graded according to the Modified Airlie House Classification. Main outcome was the Incidence of dementia. A Cox proportional hazards model was used to estimate the hazard ratios (HRs) and their 95% confidence intervals (CIs) for the risk of dementia by the presence of retinopathy. During the follow-up period, 374 participants developed all-cause dementia. The cumulative incidence of dementia was significantly higher in those with retinopathy than those without (p < 0.05). Individuals with retinopathy had significantly higher risk of developing dementia than those without after adjustment for potential confounding factors (HR 1.64, 95% CI 1.19-2.25). Regarding the components of retinopathy, the presence of microaneurysms was significantly associated with a higher multivariable-adjusted HR for incident dementia (HR 1.94, 95% CI 1.37-2.74). Our findings suggest that, in addition to systemic risk factors, retinal microvascular signs from fundus photography provide valuable information for estimating the risk of developing dementia.

Structural changes in the retina and serum HMGB1 levels are associated with decreased cognitive function in patients with Parkinson's disease

BACKGROUND

Cognitive impairment is a serious nonmotor symptom in patients with Parkinson's disease (PD). Currently, there are few studies investigating the relationship of serum markers and retinal structural changes with cognitive function in PD.

OBJECTIVE

To investigate the relationship between retinal structural changes, serum high mobility group box-1 (HMGB1) levels and cognitive function and motor symptoms in PD patients.

METHODS

Eighty-nine participants, including 47 PD patients and 42 healthy subjects, were enrolled. PD patients were divided into Parkinson's disease with normal cognitive (PD-NC), Parkinson's disease with mild cognitive impairment (PD-MCI), and Parkinson's disease with dementia (PDD) groups. The motor and nonmotor symptoms of PD patients were evaluated with clinical scale. Serum HMGB1 levels were detected by enzyme-linked immunosorbent assay (ELISA), and ganglion cell-inner plexiform layer complex (GCIPL) thickness changes in the macula were quantitatively analyzed by swept source optical coherence tomography (SS-OCT) in all patients.

RESULTS

Compared with the control group, the macular GCIPL (t = -2.308, P = 0.023) was thinner and serum HMGB1 (z = -2.285, P = 0.022) was increased in PD patients. Macular GCIPL thickness in patients with PD-MCI and PDD were significantly lower than that in PD-NC patients, but there were no significant difference between the PD-MCI and PDD groups. Serum HMGB1 levels in patients with PD-MCI and PDD were significantly higher than those in PD-NC patients, and serum HMGB1 levels in PDD patients were higher than those in PD-MCI patients. Correlation analysis showed that serum HMGB1 levels in PD patients were positively correlated with disease duration, HY stage, UPDRS-I score, UPDRS-III score, and UPDRS total score and negatively correlated with MOCA score. Macular GCIPL thickness was negatively correlated with HY stage and positively correlated with MOCA score, and macular GCIPL thickness was negatively correlated with serum HMGB1 level. Logistic regression analysis showed that elevated serum HMGB1 level, thinner macular GCIPL thickness, and higher HY stage were independent risk factors for Parkinson's disease with cognitive impairment (PD-CI). The areas under the receiver operating characteristic curve (AUC) for the serum HMGB1 level and macular GCIPL thickness-based diagnosis of PD-MCI, PDD and PD-CI based on in patients with PD were 0.786 and 0.825, 0.915 and 0.856, 0.852 and 0.841, respectively. The AUC for the diagnosis of PD-MCI, PDD and PD-CI with serum HMGB1 level and GCIPL thickness combined were 0.869, 0.967 and 0.916, respectively.

CONCLUSION

The macular GCIPL thickness and serum HMGB1 level are potential markers of cognitive impairment in PD patients, and their combination can significantly improve the accuracy of the diagnosis of cognitive impairment in PD.

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.

Exploiting multi-granularity visual features for retinal layer segmentation in human eyes

Accurate segmentation of retinal layer boundaries can facilitate the detection of patients with early ophthalmic disease. Typical segmentation algorithms operate at low resolutions without fully exploiting multi-granularity visual features. Moreover, several related studies do not release their datasets that are key for the research on deep learning-based solutions. We propose a novel end-to-end retinal layer segmentation network based on ConvNeXt, which can retain more feature map details by using a new depth-efficient attention module and multi-scale structures. In addition, we provide a semantic segmentation dataset containing 206 retinal images of healthy human eyes (named NR206 dataset), which is easy to use as it does not require any additional transcoding processing. We experimentally show that our segmentation approach outperforms state-of-the-art approaches on this new dataset, achieving, on average, a Dice score of 91.3% and mIoU of 84.4%. Moreover, our approach achieves state-of-the-art performance on a glaucoma dataset and a diabetic macular edema (DME) dataset, showing that our model is also suitable for other applications. We will make our source code and the NR206 dataset publicly available at (https://github.com/Medical-Image-Analysis/Retinal-layer-segmentation).

Associations Between Thinner Retinal Neuronal Layers and Suboptimal Brain Structural Integrity in a Middle-Aged Cohort

Purpose

The retina has potential as a biomarker of brain health and Alzheimer's disease (AD) because it is the only part of the central nervous system which can be easily imaged and has advantages over brain imaging technologies. Few studies have compared retinal and brain measurements in a middle-aged sample. The objective of our study was to investigate whether retinal neuronal measurements were associated with structural brain measurements in a middle-aged population-based cohort.

Participants and Methods

Participants were members of the Dunedin Multidisciplinary Health and Development Study (n=1037; a longitudinal cohort followed from birth and at ages 3, 5, 7, 9, 11, 13, 15, 18, 21, 26, 32, 38, and most recently at age 45, when 94% of the living Study members participated). Retinal nerve fibre layer (RNFL) and ganglion cell-inner plexiform layer (GC-IPL) thickness were measured by optical coherence tomography (OCT). Brain age gap estimate (brainAGE), cortical surface area, cortical thickness, subcortical grey matter volumes, white matter hyperintensities, were measured by magnetic resonance imaging (MRI).

Results

Participants with both MRI and OCT data were included in the analysis (RNFL n=828, female n=413 [49.9%], male n=415 [50.1%]; GC-IPL n=825, female n=413 [50.1%], male n=412 [49.9%]). Thinner retinal neuronal layers were associated with older brain age, smaller cortical surface area, thinner average cortex, smaller subcortical grey matter volumes, and increased volume of white matter hyperintensities.

Conclusion

These findings provide evidence that the retinal neuronal layers reflect differences in midlife structural brain integrity consistent with increased risk for later AD, supporting the proposition that the retina may be an early biomarker of brain health.

The Eye as a Diagnostic Tool for Alzheimer’s Disease

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder impacting cognition, function, and behavior in the elderly population. While there are currently no disease-modifying agents capable of curing AD, early diagnosis and management in the preclinical stage can significantly improve patient morbidity and life expectancy. Currently, the diagnosis of Alzheimer’s disease is a clinical one, often supplemented by invasive and expensive biomarker testing. Over the last decade, significant advancements have been made in our understanding of AD and the role of ocular tissue as a potential biomarker. Ocular biomarkers hold the potential to provide noninvasive and easily accessible diagnostic and monitoring capabilities. This review summarizes current research for detecting biomarkers of Alzheimer’s disease in ocular tissue.

Eye-brain connections revealed by multimodal retinal and brain imaging genetics in the UK Biobank

As an anatomical extension of the brain, the retina of the eye is synaptically connected to the visual cortex, establishing physiological connections between the eye and the brain. Despite the unique opportunity retinal structures offer for assessing brain disorders, less is known about their relationship to brain structure and function. Here we present a systematic cross-organ genetic architecture analysis of eye-brain connections using retina and brain imaging endophenotypes. Novel phenotypic and genetic links were identified between retinal imaging biomarkers and brain structure and function measures derived from multimodal magnetic resonance imaging (MRI), many of which were involved in the visual pathways, including the primary visual cortex. In 65 genomic regions, retinal imaging biomarkers shared genetic influences with brain diseases and complex traits, 18 showing more genetic overlaps with brain MRI traits. Mendelian randomization suggests that retinal structures have bidirectional genetic causal links with neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, cross-organ imaging genetics reveals a genetic basis for eye-brain connections, suggesting that the retinal images can elucidate genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.