Visual Dysfunction Predicts Cognitive Impairment and White Matter Degeneration in Parkinson's Disease

Sensory Loss and Risk of Dementia

Sensory loss in olfaction, vision, and hearing is a risk factor for dementia, but the reasons for this are unclear. This review presents the neurobiological evidence linking each sensory modality to specific dementias and explores the potential mechanisms underlying this. Olfactory deficits can be linked to direct neuropathologic changes in the olfactory system due to Alzheimer disease and Parkinson disease, and may be a marker of disease severity. Visual deficits potentially increase dementia risk in a vulnerable individual by reducing resilience to dementia. Hearing deficits may indicate a susceptibility to Alzheimer disease through a variety of mechanisms. More generally, sensory impairment could be related to factors associated with resilience against dementia. Further research is needed to tease out the specific and synergistic effects of sensory impairment. Studying sensory loss in relation to neurodegenerative biomarkers is necessary to clarify the mechanisms involved. This could produce new monitoring and management strategies for people at risk of dementia.

A neuroimaging measure to capture heterogeneous patterns of atrophy in Parkinson's disease and dementia with Lewy bodies

INTRODUCTION

Parkinson's disease (PD) and Dementia with Lewy bodies (DLB) show heterogeneous brain atrophy patterns which group-average analyses fail to capture. Neuroanatomical normative modelling overcomes this by comparing individuals to a large reference cohort. Patient-specific atrophy patterns are measured objectively and summarised to index overall neurodegeneration (the 'total outlier count'). We aimed to quantify patterns of neurodegenerative dissimilarity in participants with PD and DLB and evaluate the potential clinical relevance of total outlier count by testing its association with key clinical measures in PD and DLB.

MATERIALS AND METHODS

We included 108 participants with PD and 61 with DLB. PD participants were subclassified into high and low visual performers as this has previously been shown to stratify those at increased dementia risk. We generated z-scores from T1w-MRI scans for each participant relative to normative regional cortical thickness and subcortical volumes, modelled in a reference cohort (n = 58,836). Outliers (z < -1.96) were aggregated across 169 brain regions per participant. To measure dissimilarity, individuals' Hamming distance scores were calculated. We also examined total outlier counts between high versus low visual performance in PD; and PD versus DLB; and tested associations between these and cognition.

RESULTS

There was significantly greater inter-individual dissimilarity in brain-outlier patterns in PD poor compared to high visual performers (W = 522.5; p < 0.01) and in DLB compared to PD (W = 5649; p < 0.01). PD poor visual performers had significantly greater total outlier counts compared to high (β = -4.73 (SE = 1.30); t = -3.64; p < 0.01) whereas a conventional group-level GLM failed to identify differences. Higher total outlier counts were associated with poorer MoCA (β = -0.55 (SE = 0.27), t = -2.04, p = 0.05) and composite cognitive scores (β = -2.01 (SE = 0.79); t = -2.54; p = 0.02) in DLB, and visuoperception (β = -0.67 (SE = 0.19); t = -3.59; p < 0.01), in PD.

CONCLUSIONS

Neuroanatomical normative modelling shows promise as a clinically informative technique in PD and DLB, where patterns of atrophy are variable.

Longitudinal Associations of Magnetic Susceptibility with Clinical Severity in Parkinson's Disease

BACKGROUND

Dementia is common in Parkinson's disease (PD), but there is wide variation in its timing. A critical gap in PD research is the lack of quantifiable markers of progression, and methods to identify early stages of dementia. Atrophy-based magnetic resonance imaging (MRI) has limited sensitivity in detecting or tracking changes relating to PD dementia, but quantitative susceptibility mapping (QSM), sensitive to brain tissue iron, shows potential for these purposes.

OBJECTIVE

The objective of the paper is to study, for the first time, the longitudinal relationship between cognition and QSM in PD in detail.

METHODS

We present a longitudinal study of clinical severity in PD using QSM, including 59 PD patients (without dementia at study onset), and 22 controls over 3 years.

RESULTS

In PD, increased baseline susceptibility in the right temporal cortex, nucleus basalis of Meynert, and putamen was associated with greater cognitive severity after 3 years; and increased baseline susceptibility in basal ganglia, substantia nigra, red nucleus, insular cortex, and dentate nucleus was associated with greater motor severity after 3 years. Increased follow-up susceptibility in these regions was associated with increased follow-up cognitive and motor severity, with further involvement of hippocampus relating to cognitive severity. However, there were no consistent increases in susceptibility over 3 years.

CONCLUSIONS

Our study suggests that QSM may predict changes in cognitive severity many months prior to overt cognitive involvement in PD. However, we did not find robust longitudinal changes in QSM over the course of the study. Additional tissue metrics may be required together with QSM for it to monitor progression in clinical practice and therapeutic trials. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Interaction between visual impairment and subjective cognitive complaints on physical activity impairment in U.S. older adults: NHANES 2005-2008

BACKGROUND/AIM

To investigate the independent relationships of visual impairment (VI) and Subjective cognitive complaints (SCC) with physical function impairment (PFI) and the interaction effect between VI and SCC on PFI in American older adults.

METHODS

The data of this cross-sectional study was obtained from the 2005-2008 National Health and Examination Survey (NHANES) conducted in the United States. The VI criterion included both subjective self-reported eyesight conditions and objective visual acuity test results. The self-reported questionnaires were utilized to determine PFI and SCC. According to the survey design of NHANS, original data were weighted to produce nationally representative estimates. Both the unweighted original data and weighted estimates underwent analysis. Crude and adjusted logistic models were employed to assess the pairwise associations among VI, SCC, and PFI. To assess the interactive effect, measures such as the relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S) were calculated.

RESULTS

A total of 2,710 subjects (weighted n = 38,966,687) aged 60 years or older were included. Compared with subjects without subjective visual impairment (SVI), those with SVI had a significant positive association with PFI [weighted OR (95%CI): 3.11 (2.25, 4.31)]. After multi-variable adjusting, the relationship remained significant [weighted OR (95%CI): 1.90 (1.32, 2.72)]. Similarly, those with objective visual impairment (OVI) were positively associated with the risk of PFI in the crude model [weighted OR (95%CI): 2.35 (1.53, 3.61)] and adjusted model [weighted OR (95%CI): 1.84 (1.07, 3.17)]. Moreover, we found the association of SCC with an increased risk of FPI [crude weighted OR (95%CI): 5.02 (3.40, 7.40); adjusted weighted OR (95%CI): 3.29 (2.01, 5.38)]. Ultimately, the additive interaction showed there was a significant positive interaction term between SVI and SCC on PFI, while OVI and SCC did not.

CONCLUSION

Both VI and SCC were significantly associated with PFI in elder adults. Besides, there was a significant synergistic interaction between SVI and SCC on PFI, which indicated the improvement of SVI and SCC may be beneficial for the prevention of PFI. For the elderly, especially those with multiple disabilities, comprehensive and targeted approaches are imperative to foster their overall well-being and health.

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.

Visual impairment as a risk factor of cognitive function impairment A six-year cohort study

PURPOSE

To explore whether baseline visual impairment (VI) increases the risk of cognitive function impairment (CFI).

METHODS

We conducted a population-based cohort study, with a six-year follow-up period. The exposure factor of interest in this study was VI. The Mini-Mental State Examination (MMSE) was used to assess participants' cognitive function. The Logistic regression model was used to investigate whether baseline VI had an effect on CFI. Confounding factors were adjusted in the regression model. The odds ratio (OR) and 95% confidence interval (CI) were used to quantify the effect of VI on CFI.

RESULTS

A total of 3297 participants were included in the present study. The mean age of included participants was 58.5 ± 7.2 years. Male accounted for 1480 (44.9%) of all participants. At baseline, 127 (3.9%) of the participants had VI. The MMSE score of participants who had VI at baseline decreased by 1.7 ± 3.3 points on average during the six-year follow-up, and that of participants who had no VI at baseline decreased by 1.1 ± 3.3 points on average. The difference was significant (t = 2.03, p = 0.040). Results of the multivariable Logistic regression model showed that VI was a risk factor for CFI, with an OR of 1.052 (95%CI: 1.014 to 1.092, p = 0.017).

CONCLUSIONS

Averagely, participants with VI experienced a decline in cognitive function 0.1 points faster per year than participants without VI, as measured by MMSE score. VI is an independent risk factor for CFI.

Neurovascular coupling dysfunction of visual network organization in Parkinson's disease

Parkinson's disease (PD) has been showed perfusion and neural activity alterations in specific regions, such as the motor and visual networks; however, the clinical significance of coupling changes is still unknown. To identify how neurovascular coupling changes during the pathophysiology of PD, patients and healthy controls underwent multiparametric magnetic resonance imaging to measure neural activity organization of segregation and integration using amplitude of low-frequency fluctuation (ALFF) and functional connectivity strength (FCS), and measure vascular responses using cerebral blood flow (CBF). Neurovascular coupling was calculated as the global CBF-ALFF and CBF-FCS coupling and the regional CBF/ALFF and CBF/FCS ratio. Correlations and dynamic causal modeling was then used to evaluate relationships with disease-alterations to clinical variables and information flow. Neurovascular coupling was impaired in PD with decreased global CBF-ALFF and CBF-FCS coupling, as well as decreased CBF/ALFF in the parieto-occipital cortex (dorsal visual stream) and CBF/FCS in the temporo-occipital cortex (ventral visual stream); these decouplings were associated with motor and non-motor impairments. The distinctive patterns of neurovascular coupling alterations within the dorsal and ventral visual streams of the visual system could potentially provide additional understanding into the pathophysiological mechanisms of PD.

Frequency-Dependent Microstate Characteristics for Mild Cognitive Impairment in Parkinson's Disease

Cognitive impairment is typically reflected in the time and frequency variations of electroencephalography (EEG). Integrating time-domain and frequency-domain analysis methods is essential to better understand and assess cognitive ability. Timely identification of cognitive levels in early Parkinson's disease (ePD) patients can help mitigate the risk of future dementia. For the investigation of the brain activity and states related to cognitive levels, this study recruited forty ePD patients for EEG microstate analysis, including 13 with mild cognitive impairment (MCI) and 27 without MCI (control group). To determine the specific frequency band on which the microstate analysis relies, a deep learning framework was employed to discern the frequency dependence of the cognitive level in ePD patients. The input to the convolutional neural network consisted of the power spectral density of multi-channel multi-point EEG signals. The visualization technique of gradient-weighted class activation mapping was utilized to extract the optimal frequency band for identifying MCI samples. Within this frequency band, microstate analysis was conducted and correlated with the Montreal Cognitive Assessment (MoCA) Scale. The deep neural network revealed significant differences in the 1-11.5Hz spectrum of the ePD-MCI group compared to the control group. In this characteristic frequency band, ePD-MCI patients exhibited a pattern of global microstate disorder. The coverage rate and occurrence frequency of microstate A and D increased significantly and were both negatively correlated with the MoCA scale. Meanwhile, the coverage, frequency and duration of microstate C decreased significantly and were positively correlated with the MoCA scale. Our work unveils abnormal microstate characteristics in ePD-MCI based on time-frequency fusion, enhancing our understanding of cognitively related brain dynamics and providing electrophysiological markers for ePD-MCI recognition.

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.

Visual dysfunction is a better predictor than retinal thickness for dementia in Parkinson's disease

BACKGROUND

Dementia is a common and devastating symptom of Parkinson's disease (PD). Visual function and retinal structure are both emerging as potentially predictive for dementia in Parkinson's but lack longitudinal evidence.

METHODS

We prospectively examined higher order vision (skew tolerance and biological motion) and retinal thickness (spectral domain optical coherence tomography) in 100 people with PD and 29 controls, with longitudinal cognitive assessments at baseline, 18 months and 36 months. We examined whether visual and retinal baseline measures predicted longitudinal cognitive scores using linear mixed effects models and whether they predicted onset of dementia, death and frailty using time-to-outcome methods.

RESULTS

Patients with PD with poorer baseline visual performance scored lower on a composite cognitive score (β=0.178, SE=0.05, p=0.0005) and showed greater decreases in cognition over time (β=0.024, SE=0.001, p=0.013). Poorer visual performance also predicted greater probability of dementia (χ² (1)=5.2, p=0.022) and poor outcomes (χ² (1) =10.0, p=0.002). Baseline retinal thickness of the ganglion cell-inner plexiform layer did not predict cognitive scores or change in cognition with time in PD (β=-0.013, SE=0.080, p=0.87; β=0.024, SE=0.001, p=0.12).

CONCLUSIONS

In our deeply phenotyped longitudinal cohort, visual dysfunction predicted dementia and poor outcomes in PD. Conversely, retinal thickness had less power to predict dementia. This supports mechanistic models for Parkinson's dementia progression with onset in cortical structures and shows potential for visual tests to enable stratification for clinical trials.

Clinical trials for cognition in Parkinson's disease: Where are we and how can we do better?

BACKGROUND

Cognitive impairment is common in Parkinson's disease (PD) and has a substantial impact on quality of life. Despite numerous trials targeting various PD features, we still lack effective treatments for cognition beyond cholinesterase inhibitors.

OBJECTIVE

To identify the gaps in recent clinical trials with cognitive outcomes in PD and consider areas for improvement.

METHODS

We examined recent clinical trials with cognitive outcomes in PD registered on ClinicalTrials.gov, excluding trials without cognitive outcomes, non-interventional studies, and in atypical Parkinsonian disorders. Included trials were categorized by treatment approach (investigational medicinal product, behavioral, physical activity, device-based). Details of trial design and outcomes were collected.

RESULTS

178 trials at different stages of trial completion were considered. 46 trials were completed, 25 had available results. Mean follow-up duration was 29.9 weeks. Most common cognitive measure was Montreal Cognitive Assessment. Most were performed in North America or Europe. Majority of the participants identified as non-Hispanic and White. Only eight trials showed improvement in cognition, none showed improvement beyond four months. These included trials of international medicinal products, cognitive and physical interventions and devices. GRADE certainty levels ranged from Moderate to Very Low. Only mevidalen had a Moderate certainty for potential clinical effectiveness.

CONCLUSIONS

Amongst a large number of trials for cognition in PD, only a small proportion were completed. Few showed significant improvement, with no proven long-lasting effects. Trial design, lack of enrichment for at-risk groups, short follow-up duration, insensitive outcome measures likely contribute to lack of detectable benefit and should be considered in future trials.

Structural and Functional Imaging Correlates of Visual Hallucinations in Parkinson's Disease

PURPOSE OF REVIEW

To review recent structural and functional MRI studies of visual hallucinations in Parkinson's disease.

RECENT FINDINGS

Previously, neuroimaging had shown inconsistent findings in patients with Parkinson's hallucinations, especially in studies examining grey matter volume. However, recent advances in structural and functional MRI techniques allow better estimates of structural connections, as well as the direction of connectivity in functional MRI. These provide more sensitive measures of changes in structural connectivity and allow models of the changes in directional functional connectivity to be tested. We identified 27 relevant studies and found that grey matter imaging continues to show heterogeneous findings in Parkinson's patients with visual hallucinations. Newer approaches in diffusion imaging and functional MRI are consistent with emerging models of Parkinson's hallucinations, suggesting shifts in attentional networks. In particular, reduced bottom-up, incoming sensory information, and over-weighting of top-down signals appear to be important drivers of visual hallucinations in Parkinson's disease.

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

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

Changes in both top-down and bottom-up effective connectivity drive visual hallucinations in Parkinson's disease

Visual hallucinations are common in Parkinson's disease and are associated with a poorer quality of life and a higher risk of dementia. An important and influential model that is widely accepted as an explanation for the mechanism of visual hallucinations in Parkinson's disease and other Lewy body diseases is that these arise due to aberrant hierarchical processing, with impaired bottom-up integration of sensory information and overweighting of top-down perceptual priors within the visual system. This hypothesis has been driven by behavioural data and supported indirectly by observations derived from regional activation and correlational measures using neuroimaging. However, until now, there was no evidence from neuroimaging for differences in causal influences between brain regions measured in patients with Parkinson's hallucinations. This is in part because previous resting-state studies focused on functional connectivity, which is inherently undirected in nature and cannot test hypotheses about the directionality of connectivity. Spectral dynamic causal modelling is a Bayesian framework that allows the inference of effective connectivity-defined as the directed (causal) influence that one region exerts on another region-from resting-state functional MRI data. In the current study, we utilize spectral dynamic causal modelling to estimate effective connectivity within the resting-state visual network in our cohort of 15 Parkinson's disease visual hallucinators and 75 Parkinson's disease non-visual hallucinators. We find that visual hallucinators display decreased bottom-up effective connectivity from the lateral geniculate nucleus to primary visual cortex and increased top-down effective connectivity from the left prefrontal cortex to primary visual cortex and the medial thalamus, as compared with non-visual hallucinators. Importantly, we find that the pattern of effective connectivity is predictive of the presence of visual hallucinations and associated with their severity within the hallucinating group. This is the first study to provide evidence, using resting-state effective connectivity, to support a model of aberrant hierarchical predictive processing as the mechanism for visual hallucinations in Parkinson's disease.

Prevalence and characteristics of dry eye disease in Parkinson's disease: a systematic review and meta-analysis

We investigated and characterized the prevalence of dry eye disease (DED) in Parkinson's disease (PD). PubMed and EMBASE databases were searched for relevant studies between January 1, 1979 and March 10, 2022. Quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Study-specific estimates were combined using the DerSimonian-Laird random-effects model. Prevalence of subjective DED symptoms in patients with PD and mean differences in blink rate, corneal thickness, tear film breakup time, and tear secretion volume on Schirmer test I were compared to those in controls. Of 383 studies, 13 (1519 patients with PD) and 12 were included in qualitative and quantitative syntheses, respectively. Meta-analysis revealed a 61.1% prevalence of subjective DED symptoms in PD and that, compared with controls, patients with PD had significantly lower blink rate, thinner corneal thickness, shorter tear film breakup time, and lower tear secretion volumes on Schirmer test I, without and with anesthesia.

Functional and structural brain network correlates of visual hallucinations in Lewy body dementia

Visual hallucinations are a common feature of Lewy body dementia. Previous studies have shown that visual hallucinations are highly specific in differentiating Lewy body dementia from Alzheimer’s disease dementia and Alzheimer–Lewy body mixed pathology cases. Computational models propose that impairment of visual and attentional networks is aetiologically key to the manifestation of visual hallucinations symptomatology. However, there is still a lack of experimental evidence on functional and structural brain network abnormalities associated with visual hallucinations in Lewy body dementia.

We used EEG source localization and network based statistics to assess differential topographical patterns in Lewy body dementia between 25 participants with visual hallucinations and 17 participants without hallucinations. Diffusion tensor imaging was used to assess structural connectivity between thalamus, basal forebrain and cortical regions belonging to the functionally affected network component in the hallucinating group, as assessed with network based statistics. The number of white matter streamlines within the cortex and between subcortical and cortical regions was compared between hallucinating and not hallucinating groups and correlated with average EEG source connectivity of the affected subnetwork. Moreover, modular organization of the EEG source network was obtained, compared between groups and tested for correlation with structural connectivity.

Network analysis showed that compared to non-hallucinating patients, those with hallucinations feature consistent weakened connectivity within the visual ventral network, and between this network and default mode and ventral attentional networks, but not between or within attentional networks. The occipital lobe was the most functionally disconnected region. Structural analysis yielded significantly affected white matter streamlines connecting the cortical regions to the nucleus basalis of Meynert and the thalamus in hallucinating compared to not hallucinating patients. The number of streamlines in the tract between the basal forebrain and the cortex correlated with cortical functional connectivity in non-hallucinating patients, while a correlation emerged for the white matter streamlines connecting the functionally affected cortical regions in the hallucinating group.

This study proposes, for the first time, differential functional networks between hallucinating and not hallucinating Lewy body dementia patients, and provides empirical evidence for existing models of visual hallucinations. Specifically, the outcome of the present study shows that the hallucinating condition is associated with functional network segregation in Lewy body dementia and supports the involvement of the cholinergic system as proposed in the current literature.

Multimodal brain and retinal imaging of dopaminergic degeneration in Parkinson disease

Parkinson disease (PD) is a progressive disorder characterized by dopaminergic neurodegeneration in the brain. The development of parkinsonism is preceded by a long prodromal phase, and >50% of dopaminergic neurons can be lost from the substantia nigra by the time of the initial diagnosis. Therefore, validation of in vivo imaging biomarkers for early diagnosis and monitoring of disease progression is essential for future therapeutic developments. PET and single-photon emission CT targeting the presynaptic terminals of dopaminergic neurons can be used for early diagnosis by detecting axonal degeneration in the striatum. However, these techniques poorly differentiate atypical parkinsonian syndromes from PD, and their availability is limited in clinical settings. Advanced MRI in which pathological changes in the substantia nigra are visualized with diffusion, iron-sensitive susceptibility and neuromelanin-sensitive sequences potentially represents a more accessible imaging tool. Although these techniques can visualize the classic degenerative changes in PD, they might be insufficient for phenotyping or prognostication of heterogeneous aspects of PD resulting from extranigral pathologies. The retina is an emerging imaging target owing to its pathological involvement early in PD, which correlates with brain pathology. Retinal optical coherence tomography (OCT) is a non-invasive technique to visualize structural changes in the retina. Progressive parafoveal thinning and fovea avascular zone remodelling, as revealed by OCT, provide potential biomarkers for early diagnosis and prognostication in PD. As we discuss in this Review, multimodal imaging of the substantia nigra and retina is a promising tool to aid diagnosis and management of PD.

Role of White Matter Abnormalities in the Relationship Between Microbleed Burden and Cognitive Impairment in Cerebral Amyloid Angiopathy

Background: Cerebral amyloid angiopathy (CAA) often presents as cognitive impairment, but the mechanism of cognitive decline is unclear. Recent studies showed that number of microbleeds were associated with cognitive decline. Objective: We aimed to investigate how microbleeds contribute to cognitive impairment in association with white matter tract abnormalities or cortical thickness in CAA. Methods: This retrospective comparative study involved patients with probable CAA according to the Boston criteria (Aβ  + CAA) and patients with Alzheimer’s disease (Aβ  + AD), all of whom showed severe amyloid deposition on amyloid PET. Using mediation analysis, we investigated how FA or cortical thickness mediates the correlation between the number of lobar microbleeds and cognition. Results: We analyzed 30 patients with Aβ  + CAA (age 72.2±7.6, female 53.3%) and 30 patients with Aβ  + AD (age 71.5±7.6, female 53.3%). The two groups showed similar degrees of cortical amyloid deposition in AD-related regions. The Aβ  + CAA group had significantly lower FA values in the clusters of the posterior area than did the Aβ  + AD group (family-wise error-corrected p <  0.05). The correlation between the number of lobar microbleeds and visuospatial function was indirectly mediated by white matter tract abnormality of right posterior thalamic radiation (PTR) and tapetum, while lobar microbleeds and language function was indirectly mediated by the abnormality of left PTR and sagittal stratum. Cortical thickness did not mediate the association between lobar microbleeds and cognition. Conclusion: This result supports the hypothesis that microbleeds burden leads to white matter tract damage and subsequent cognitive decline in CAA.

Thalamic white matter macrostructure and subnuclei volumes in Parkinson's disease depression

Depression is a common non-motor feature of Parkinson's disease (PD) which confers significant morbidity and is challenging to treat. The thalamus is a key component in the basal ganglia-thalamocortical network critical to the pathogenesis of PD and depression but the precise thalamic subnuclei involved in PD depression have not been identified. We performed structural and diffusion-weighted imaging (DWI) on 76 participants with PD to evaluate the relationship between PD depression and grey and white matter thalamic subnuclear changes. We used a thalamic segmentation method to divide the thalamus into its 50 constituent subnuclei (25 each hemisphere). Fixel-based analysis was used to calculate mean fibre cross-section (FC) for white matter tracts connected to each subnucleus. We assessed volume and FC at baseline and 14-20 months follow-up. A generalised linear mixed model was used to evaluate the relationship between depression, subnuclei volume and mean FC for each thalamic subnucleus. We found that depression scores in PD were associated with lower right pulvinar anterior (PuA) subnucleus volume. Antidepressant use was associated with higher right PuA volume suggesting a possible protective effect of treatment. After follow-up, depression scores were associated with reduced white matter tract macrostructure across almost all tracts connected to thalamic subnuclei. In conclusion, our work implicates the right PuA as a relevant neural structure in PD depression and future work should evaluate its potential as a therapeutic target for PD depression.

Association of serum cholesterol with Parkinson's disease in a cohort of statin-free individuals

INTRODUCTION

The role of serum cholesterol in the pathogenesis of Parkinson's disease (PD) remains unclear. The objective of this study was to assess the association between serum cholesterol and PD in a cohort of statin-free newly diagnosed PD patients.

METHODS

This retrospective study used fasting lipid profiles obtained from 672 consecutive statin-free newly diagnosed PD individuals and 540 controls. These PD individuals were identified from three medical institutions during 2017-2021, and the controls were identified from three physical examination centers during the same time period. Logistic regressions were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs), with adjustment of age, sex, and tobacco use history.

RESULTS

Among 672 PD individuals, 112 were excluded in accordance with the current criteria, leaving 560 PD patients. The multivariate binary logistic regression analysis showed that LDL-C was the only variable contributing to the occurrence of PD (OR 1.39, 95% CI: 1.07-2.31, p < .001) after adjusting for age, sex, and tobacco use history; this association persisted following further adjustment for TC and HDL-C. In the subgroup analysis of the adjusted results of LDL-C after correcting for TC and HDL-C, lower LDL-C was associated with a higher risk of PD.

CONCLUSION

Among selected populations of statin-free newly diagnosed PD individuals, low LDL-C might be associated with the occurrence of PD.

Visual dysfunction is associated with cognitive impairment in Parkinson's disease

INTRODUCTION

Visual dysfunction and cognitive impairment are common in Parkinson's disease (PD) but the precise contribution of lower-level visual impairment to visual-input based cognitive performance has not been extensively characterized in PD.

METHODS

We included 49 PD patients and 22 healthy controls (HC). Lower-level visual function tests [high and low contrast visual acuity (HCVA and LCVA) and contrast sensitivity (CS)] and a neuropsychological battery (involving visual cognition) were performed. Pairwise correlations between lower-level visual functions and visual cognition were computed and stepwise linear regressions were fitted introducing age, Geriatric Depression Scale, and lower-level visual functions in the model to calculate their predicted effect on visual cognition.

RESULTS

Compared to controls, patients presented a significant impairment in all cognitive domains (visual attention, visual processing speed and visual perception, visuospatial abilities, visuoconstructive abilities, and visual memory), and lower-level visual functions. HCVA and LCVA were significantly associated with visual cognition in PD. HCVA explained up to 49.3% and 34.2% of the variability in visual perception and visuospatial abilities, respectively, whereas LCVA was mainly associated with short- and long-term visual memory and visuospatial abilities.

CONCLUSION

Lower-level visual dysfunction is highly associated with cognitive performance in PD, when cognitive tests are based on visual input. Our results support that lower-level visual functions should be considered when assessing cognitive status of PD patients and might be useful for predicting cognitive deterioration.

Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities

Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "Fixel-Based Analysis" (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities.

Visual hallucinations

Visual hallucinations have intrigued neurologists and physicians for generations due to patients' vivid and fascinating descriptions. They are most commonly associated with Parkinson's disease and dementia with Lewy bodies, but also occur in people with visual loss, where they are known as Charles Bonnet syndrome. More rarely, they can develop in other neurological conditions, such as thalamic or midbrain lesions, when they are known as peduncular hallucinosis. This review considers the mechanisms underlying visual hallucinations across diagnoses, including visual loss, network dysfunction across the brain and changes in neurotransmitters. We propose a framework to explain why visual hallucinations occur most commonly in Parkinson's disease and dementia with Lewy bodies, and discuss treatment approaches to visual hallucinations in these conditions.