Retinal Optical Coherence Tomography Features Associated With Incident and Prevalent Parkinson Disease

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.

Neuroimaging and fluid biomarkers in Parkinson's disease in an era of targeted interventions

A major challenge in Parkinson's disease is the variability in symptoms and rates of progression, underpinned by heterogeneity of pathological processes. Biomarkers are urgently needed for accurate diagnosis, patient stratification, monitoring disease progression and precise treatment. These were previously lacking, but recently, novel imaging and fluid biomarkers have been developed. Here, we consider new imaging approaches showing sensitivity to brain tissue composition, and examine novel fluid biomarkers showing specificity for pathological processes, including seed amplification assays and extracellular vesicles. We reflect on these biomarkers in the context of new biological staging systems, and on emerging techniques currently in development.

Intravitreal MPTP drives retinal ganglion cell loss with oral nicotinamide treatment providing robust neuroprotection

Neurodegenerative diseases have common underlying pathological mechanisms including progressive neuronal dysfunction, axonal and dendritic retraction, and mitochondrial dysfunction resulting in neuronal death. The retina is often affected in common neurodegenerative diseases such as Parkinson's and Alzheimer's disease. Studies have demonstrated that the retina in patients with Parkinson's disease undergoes changes that parallel the dysfunction in the brain. These changes classically include decreased levels of dopamine, accumulation of alpha-synuclein in the brain and retina, and death of dopaminergic nigral neurons and retinal amacrine cells leading to gross neuronal loss. Exploring this disease's retinal phenotype and vision-related symptoms is an important window for elucidating its pathophysiology and progression, and identifying novel ways to diagnose and treat Parkinson's disease. 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is commonly used to model Parkinson's disease in animal models. MPTP is a neurotoxin converted to its toxic form by astrocytes, transported to neurons through the dopamine transporter, where it causes mitochondrial Complex I inhibition and neuron degeneration. Systemic administration of MPTP induces retinal changes in different animal models. In this study, we assessed the effects of MPTP on the retina directly via intravitreal injection in mice (5 mg/mL and 50 mg/mL to 7, 14 and 21 days post-injection). MPTP treatment induced the reduction of retinal ganglion cells-a sensitive neuron in the retina-at all time points investigated. This occurred without a concomitant loss of dopaminergic amacrine cells or neuroinflammation at any of the time points or concentrations tested. The observed neurodegeneration which initially affected retinal ganglion cells indicated that this method of MPTP administration could yield a fast and straightforward model of retinal ganglion cell neurodegeneration. To assess whether this model could be amenable to neuroprotection, mice were treated orally with nicotinamide (a nicotinamide adenine dinucleotide precursor) which has been demonstrated to be neuroprotective in several retinal ganglion cell injury models. Nicotinamide was strongly protective following intravitreal MPTP administration, further supporting intravitreal MPTP use as a model of retinal ganglion cell injury. As such, this model could be utilized for testing neuroprotective treatments in the context of Parkinson's disease and retinal ganglion cell injury.

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.

A review on the new age methodologies for early detection of Alzheimer's and Parkinson's disease

BACKGROUNDS

Neurodegenerative diseases (NDDs) such as Alzheimer's (AD) and Parkinson's (PD) are often diagnosed late, impeding effective treatment; therefore, early detection is imperative. Modern methodologies can serve a pivotal role in fulfilling the crucial need for timely detection and intervention in this context.

OBJECTIVES

Evaluate early detection's significance and summarize key technologies (biomarkers, neuroimaging, AI/ML, genetics, digital health) for enhanced diagnostic strategies in AD and PD.

METHODS

This study employs a focused descriptive review approach, encompassing analysis of peer-reviewed articles and clinical trials from existing literature, to provide a nuanced exploration of the subject matter.

FINDINGS

This review underscores the efficacy of non-invasive biomarkers, biosensors and emerging promising technologies for advancing early diagnosis of AD and PD.

CONCLUSION

The landscape of early NDD detection has been reshaped by technology, yet challenges persist, encompassing the domains of validation and ethics. A collaborative effort between medical professionals, researchers and technologists is imperative to effectively address and combat NDDs.

Precision Medicine-Are We There Yet? A Narrative Review of Precision Medicine's Applicability in Primary Care

Precision medicine (PM), also termed stratified, individualised, targeted, or personalised medicine, embraces a rapidly expanding area of research, knowledge, and practice. It brings together two emerging health technologies to deliver better individualised care: the many "-omics" arising from increased capacity to understand the human genome and "big data" and data analytics, including artificial intelligence (AI). PM has the potential to transform an individual's health, moving from population-based disease prevention to more personalised management. There is however a tension between the two, with a real risk that this will exacerbate health inequalities and divert funds and attention from basic healthcare requirements leading to worse health outcomes for many. All areas of medicine should consider how this will affect their practice, with PM now strongly encouraged and supported by government initiatives and research funding. In this review, we discuss examples of PM in current practice and its emerging applications in primary care, such as clinical prediction tools that incorporate genomic markers and pharmacogenomic testing. We look towards potential future applications and consider some key questions for PM, including evidence of its real-world impact, its affordability, the risk of exacerbating health inequalities, and the computational and storage challenges of applying PM technologies at scale.

A topographical atlas of α-synuclein dosage and cell type-specific expression in adult mouse brain and peripheral organs

Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide and presents pathologically with Lewy pathology and dopaminergic neurodegeneration. Lewy pathology contains aggregated α-synuclein (αSyn), a protein encoded by the SNCA gene which is also mutated or duplicated in a subset of familial PD cases. Due to its predominant presynaptic localization, immunostaining for the protein results in a diffuse reactivity pattern, providing little insight into the types of cells expressing αSyn. As a result, insight into αSyn expression-driven cellular vulnerability has been difficult to ascertain. Using a combination of knock-in mice that target αSyn to the nucleus (SncaNLS) and in situ hybridization of Snca in wild-type mice, we systematically mapped the topography and cell types expressing αSyn in the mouse brain, spinal cord, retina, and gut. We find a high degree of correlation between αSyn protein and RNA levels and further identify cell types with low and high αSyn content. We also find high αSyn expression in neurons, particularly those involved in PD, and to a lower extent in non-neuronal cell types, notably those of oligodendrocyte lineage, which are relevant to multiple system atrophy pathogenesis. Surprisingly, we also found that αSyn is relatively absent from select neuron types, e.g., ChAT-positive motor neurons, whereas enteric neurons universally express some degree of αSyn. Together, this integrated atlas provides insight into the cellular topography of αSyn, and provides a quantitative map to test hypotheses about the role of αSyn in network vulnerability, and thus serves investigations into PD pathogenesis and other α-synucleinopathies.

Retinal Alterations Predict Early Prodromal Signs of Neurodegenerative Disease

Neurodegenerative diseases are an increasingly common group of diseases that occur late in life with a significant impact on personal, family, and economic life. Among these, Alzheimer's disease (AD) and Parkinson's disease (PD) are the major disorders that lead to mild to severe cognitive and physical impairment and dementia. Interestingly, those diseases may show onset of prodromal symptoms early after middle age. Commonly, the evaluation of these neurodegenerative diseases is based on the detection of biomarkers, where functional and structural magnetic resonance imaging (MRI) have shown a central role in revealing early or prodromal phases, although it can be expensive, time-consuming, and not always available. The aforementioned diseases have a common impact on the visual system due to the pathophysiological mechanisms shared between the eye and the brain. In Parkinson's disease, α-synuclein deposition in the retinal cells, as well as in dopaminergic neurons of the substantia nigra, alters the visual cortex and retinal function, resulting in modifications to the visual field. Similarly, the visual cortex is modified by the neurofibrillary tangles and neuritic amyloid β plaques typically seen in the Alzheimer's disease brain, and this may reflect the accumulation of these biomarkers in the retina during the early stages of the disease, as seen in postmortem retinas of AD patients. In this light, the ophthalmic evaluation of retinal neurodegeneration could become a cost-effective method for the early diagnosis of those diseases, overcoming the limitations of functional and structural imaging of the deep brain. This analysis is commonly used in ophthalmic practice, and interest in it has risen in recent years. This review will discuss the relationship between Alzheimer's disease and Parkinson's disease with retinal degeneration, highlighting how retinal analysis may represent a noninvasive and straightforward method for the early diagnosis of these neurodegenerative diseases.

Association of retinal neurodegeneration with the progression of cognitive decline in Parkinson's disease

Retinal thickness may serve as a biomarker in Parkinson's disease (PD). In this prospective longitudinal study, we aimed to determine if PD patients present accelerated thinning rate in the parafoveal ganglion cell-inner plexiform layer (pfGCIPL) and peripapillary retinal nerve fiber layer (pRNFL) compared to controls. Additionally, we evaluated the relationship between retinal neurodegeneration and clinical progression in PD. A cohort of 156 PD patients and 72 controls underwent retinal optical coherence tomography, visual, and cognitive assessments between February 2015 and December 2021 in two Spanish tertiary hospitals. The pfGCIPL thinning rate was twice as high in PD (β [SE] = -0.58 [0.06]) than in controls (β [SE] = -0.29 [0.06], p < 0.001). In PD, the progression pattern of pfGCIPL atrophy depended on baseline thickness, with slower thinning rates observed in PD patients with pfGCIPL below 89.8 µm. This result was validated with an external dataset from Moorfields Eye Hospital NHS Foundation Trust (AlzEye study). Slow pfGCIPL progressors, characterized by older at baseline, longer disease duration, and worse cognitive and disease stage scores, showed a threefold increase in the rate of cognitive decline (β [SE] = -0.45 [0.19] points/year, p = 0.021) compared to faster progressors. Furthermore, temporal sector pRNFL thinning was accelerated in PD (βtime x group [SE] = -0.67 [0.26] μm/year, p = 0.009), demonstrating a close association with cognitive score changes (β [SE] = 0.11 [0.05], p = 0.052). This study suggests that a slower pattern of pfGCIPL tissue loss in PD is linked to more rapid cognitive decline, whereas changes in temporal pRNFL could track cognitive deterioration.

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.

Altered Outer Retinal Structure, Electrophysiology and Visual Perception in Parkinson's Disease

BACKGROUND

Visual biomarkers of Parkinson's disease (PD) are attractive as the retina is an outpouching of the brain. Although inner retinal neurodegeneration in PD is well-established this has overlap with other neurodegenerative diseases and thus outer retinal (photoreceptor) measures warrant further investigation.

OBJECTIVE

To examine in a cross-sectional study whether clinically implementable measures targeting outer retinal function and structure can differentiate PD from healthy ageing and whether these are sensitive to intraday levodopa (L-DOPA) dosing.

METHODS

Centre-surround perceptual contrast suppression, macular visual field sensitivity, colour discrimination, light-adapted electroretinography and optical coherence tomography (OCT) were tested in PD participants (n = 16) and controls (n = 21). Electroretinography and OCT were conducted before and after midday L-DOPA in PD participants, or repeated after ∼2 hours in controls.

RESULTS

PD participants had decreased center-surround contrast suppression (p < 0.01), reduced macular visual field sensitivity (p < 0.05), color vision impairment (p < 0.01) photoreceptor dysfunction (a-wave, p < 0.01) and photoreceptor neurodegeneration (outer nuclear layer thinning, p < 0.05), relative to controls. Effect size comparison between inner and outer retinal parameters showed that photoreceptor metrics were similarly robust in differentiating the PD group from age-matched controls as inner retinal changes. Electroretinography and OCT were unaffected by L-DOPA treatment or time.

CONCLUSIONS

We show that outer retinal outcomes of photoreceptoral dysfunction (decreased cone function and impaired color vision) and degeneration (i.e., outer nuclear layer thinning) were equivalent to inner retinal metrics at differentiating PD from healthy age-matched adults. These findings suggest outer retinal metrics may serve as useful biomarkers for PD.