Brain atrophy progression in Parkinson's disease is shaped by connectivity and local vulnerability

Network analysis of α-synuclein pathology progression reveals p21-activated kinases as regulators of vulnerability

α-Synuclein misfolding and progressive accumulation drives a pathogenic process in Parkinson's disease. To understand cellular and network vulnerability to α-synuclein pathology, we developed a framework to quantify network-level vulnerability and identify new therapeutic targets at the cellular level. Full brain α-synuclein pathology was mapped in mice over 9 months. Empirical pathology data was compared to theoretical pathology estimates from a diffusion model of pathology progression along anatomical connections. Unexplained variance in the model enabled us to derive regional vulnerability that we compared to regional gene expression. We identified gene expression patterns that relate to regional vulnerability, including 12 kinases that were enriched in vulnerable regions. Among these, an inhibitor of group II PAKs demonstrated protection from neuron death and α-synuclein pathology, even after delayed compound treatment. This study provides a framework for the derivation of cellular vulnerability from network-based studies and identifies a promising therapeutic pathway for Parkinson's disease.

Neuroimaging meta-analyses reveal convergence of interoception, emotion, and social cognition across neurodegenerative diseases

INTRODUCTION

Simultaneous interoceptive, emotional, and social cognition deficits are observed across neurodegenerative diseases. Indirect evidence suggests shared neurobiological bases underlying these impairments, termed the allostatic-interoceptive network (AIN). However, no study has yet explored the convergence of these deficits in neurodegenerative diseases or examined how structural and functional changes contribute to cross-domain impairments.

METHODS

A PRISMA Activated Likelihood Estimate (ALE) metanalyses encompassed studies meeting inclusion criteria: interoception, emotion, or social cognition tasks; neurodegenerative diseases (behavioral variant frontotemporal dementia (bvFTD), primary progressive aphasias (PPAs) Alzheimer's disease (AD), Parkinson's Disease (PD), multiple sclerosis (MS)); and neuroimaging (structural: MRI voxel-based morphometry; functional: fMRI and FDG-PET).

RESULTS

From 20,593 studies, 170 met inclusion criteria (58 interoception, 65 emotion, and 47 social cognition) involving 7032 participants (4963 patients and 2069 healthy controls). In all participants combined, conjunction analyses revealed AIN involvement of the insula, amygdala, orbitofrontal cortex, anterior cingulate, striatum, thalamus, and hippocampus across domains. In bvFTD this conjunction was replicated across domains, with further involvement of the temporal pole, temporal fusiform cortex, and angular gyrus. A convergence of interoception and emotion in the striatum, thalamus, and hippocampus in PD and the posterior insula in PPAs was also observed. In AD and MS, disruptions in the AIN were observed during interoception, but no convergence with emotion was identified.

INTERPRETATION

Neurodegeneration induces dysfunctional AIN across atrophy, connectivity, and metabolism, more accentuated in bvFTD. Findings bolster the predictive coding theories of large-scale AIN, calling for more synergistic approaches to understanding interoception, emotion, and social cognition impairments in neurodegeneration.

Brain aging patterns in a large and diverse cohort of 49,482 individuals

Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis.

Neuroanatomical and cognitive biomarkers of alpha-synuclein propagation in a mouse model of synucleinopathy prior to onset of motor symptoms

Significant evidence suggests that misfolded alpha-synuclein (aSyn), a major component of Lewy bodies, propagates in a prion-like manner contributing to disease progression in Parkinson's disease (PD) and other synucleinopathies. In fact, timed inoculation of M83 hemizygous mice with recombinant human aSyn preformed fibrils (PFF) has shown symptomatic deficits after substantial spreading of pathogenic alpha-synuclein, as detected by markers for the phosphorylation of S129 of aSyn. However, whether accumulated toxicity impact human-relevant cognitive and structural neuroanatomical measures is not fully understood. Here we performed a single unilateral striatal PFF injection in M83 hemizygous mice, and using two assays with translational potential, ex vivo magnetic resonance imaging (MRI) and touchscreen testing, we examined the combined neuroanatomical and behavioral impact of aSyn propagation. In PFF-injected mice, we observed widespread atrophy in bilateral regions that project to or receive input from the injection site using MRI. We also identified early deficits in reversal learning prior to the emergence of motor symptoms. Our findings highlight a network of regions with related cellular correlates of pathology that follow the progression of aSyn spreading, and that affect brain areas relevant for reversal learning. Our experiments suggest that M83 hemizygous mice injected with human PFF provides a model to understand how misfolded aSyn affects human-relevant pre-clinical measures and suggest that these pre-clinical biomarkers could be used to detect early toxicity of aSyn and provide better translational measures between mice and human disease.

Neural correlates of obesity across the lifespan

Associations between brain and obesity are bidirectional: changes in brain structure and function underpin over-eating, while chronic adiposity leads to brain atrophy. Investigating brain-obesity interactions across the lifespan can help better understand these relationships. This study explores the interaction between obesity and cortical morphometry in children, young adults, adults, and older adults. We also investigate the genetic, neurochemical, and cognitive correlates of the brain-obesity associations. Our findings reveal a pattern of lower cortical thickness in fronto-temporal brain regions associated with obesity across all age cohorts and varying age-dependent patterns in the remaining brain regions. In adults and older adults, obesity correlates with neurochemical changes and expression of inflammatory and mitochondrial genes. In children and older adults, adiposity is associated with modifications in brain regions involved in emotional and attentional processes. Thus, obesity might originate from cognitive changes during early adolescence, leading to neurodegeneration in later life through mitochondrial and inflammatory mechanisms.

A neurocomputational view of the effects of Parkinson's disease on speech production

The purpose of this article is to review the scientific literature concerning speech in Parkinson's disease (PD) with reference to the DIVA/GODIVA neurocomputational modeling framework. Within this theoretical view, the basal ganglia (BG) contribute to several different aspects of speech motor learning and execution. First, the BG are posited to play a role in the initiation and scaling of speech movements. Within the DIVA/GODIVA framework, initiation and scaling are carried out by initiation map nodes in the supplementary motor area acting in concert with the BG. Reduced support of the initiation map from the BG in PD would result in reduced movement intensity as well as susceptibility to early termination of movement. A second proposed role concerns the learning of common speech sequences, such as phoneme sequences comprising words; this view receives support from the animal literature as well as studies identifying speech sequence learning deficits in PD. Third, the BG may play a role in the temporary buffering and sequencing of longer speech utterances such as phrases during conversational speech. Although the literature does not support a critical role for the BG in representing sequence order (since incorrectly ordered speech is not characteristic of PD), the BG are posited to contribute to the scaling of individual movements in the sequence, including increasing movement intensity for emphatic stress on key words. Therapeutic interventions for PD have inconsistent effects on speech. In contrast to dopaminergic treatments, which typically either leave speech unchanged or lead to minor improvements, deep brain stimulation (DBS) can degrade speech in some cases and improve it in others. However, cases of degradation may be due to unintended stimulation of efferent motor projections to the speech articulators. Findings of spared speech after bilateral pallidotomy appear to indicate that any role played by the BG in adult speech must be supplementary rather than mandatory, with the sequential order of well-learned sequences apparently represented elsewhere (e.g., in cortico-cortical projections).

Structural underpinnings and long-term effects of resilience in Parkinson's disease

Resilience in neuroscience generally refers to an individual's capacity to counteract the adverse effects of a neuropathological condition. While resilience mechanisms in Alzheimer's disease are well-investigated, knowledge regarding its quantification, neurobiological underpinnings, network adaptations, and long-term effects in Parkinson's disease is limited. Our study involved 151 Parkinson's patients from the Parkinson's Progression Marker Initiative Database with available Magnetic Resonance Imaging, Dopamine Transporter Single-Photon Emission Computed Tomography scans, and clinical information. We used an improved prediction model linking neuropathology to symptom severity to estimate individual resilience levels. Higher resilience levels were associated with a more active lifestyle, increased grey matter volume in motor-associated regions, a distinct structural connectivity network and maintenance of relative motor functioning for up to a decade. Overall, the results indicate that relative maintenance of motor function in Parkinson's patients may be associated with greater neuronal substrate, allowing higher tolerance against neurodegenerative processes through dynamic network restructuring.

Disruption of Electroencephalogram Coherence between Cortex/Striatum and Midbrain Dopaminergic Regions in the Knock-Out Mice with Combined Loss of Alpha, Beta, and Gamma Synucleins

The malfunctioning of the brain synucleins is associated with pathogenesis of Parkinson's disease. Synucleins' ability to modulate various pre-synaptic processes suggests their modifying effects on the electroencephalogram (EEG) recorded from different brain structures. Disturbances in interrelations between them are critical for the onset and evolution of neurodegenerative diseases. Recently, we have shown that, in mice lacking several synucleins, differences between the frequency spectra of EEG from different brain structures are correlated with specificity of synucleins' combinations. Given that EEG spectra are indirect characteristics of inter-structural relations, in this study, we analyzed a coherence of instantaneous values for EEGs recorded from different structures as a direct measure of "functional connectivity" between them.

METHODS

EEG data from seven groups of knock-out (KO) mice with combined deletions of alpha, beta, and gamma synucleins versus a group of wild-type (WT) mice were compared. EEG coherence was estimated between the cortex (MC), putamen (Pt), ventral tegmental area (VTA), and substantia nigra (SN) in all combinations.

RESULTS

EEG coherence suppression, predominantly in the beta frequency band, was observed in KO mice versus WT littermates. The suppression was minimal in MC-Pt and VTA-SN interrelations in all KO groups and in all inter-structural relations in mice lacking either all synucleins or only beta synuclein. In other combinations of deleted synucleins, significant EEG coherence suppression in KO mice was dominant in relations with VTA and SN.

CONCLUSION

Deletions of the synucleins produced significant attenuation of intra-cerebral EEG coherence depending on the imbalance of different types of synucleins.

Grey matter networks in women and men with dementia with Lewy bodies

Sex differences permeate many aspects of dementia with Lewy bodies (DLB), yet sex differences in patterns of neurodegeneration in DLB remain largely unexplored. Here, we test whether grey matter networks differ between sexes in DLB and compare these findings to sex differences in healthy controls. In this cross-sectional study, we analysed clinical and neuroimaging data of patients with DLB and cognitively healthy controls matched for age and sex. Grey matter networks were constructed by pairwise correlations between 58 regional volumes after correction for age, intracranial volume, and centre. Network properties were compared between sexes and diagnostic groups. Additional analyses were conducted on w-scored data to identify DLB-specific sex differences. Data from 119 (68.7 ± 8.4 years) men and 45 women (69.9 ± 9.1 years) with DLB, and 164 healthy controls were included in this study. Networks of men had a lower nodal strength compared to women. In comparison to healthy women, the grey matter networks of healthy men showed a higher global efficiency, modularity, and fewer modules. None of the network measures showed significant sex differences in DLB. Comparing DLB patients with healthy controls revealed global differences in women and more local differences in men. Modular analyses showed a more distinct demarcation between cortical and subcortical regions in men compared with women. While topologies of grey matter networks differed between sexes in healthy controls, those sex differences were diluted in DLB patients. These findings suggest a disease-driven convergence of neurodegenerative patterns in women and men with DLB, which may inform precision medicine in DLB.

Striato-cortical functional connectivity changes in mild cognitive impairment with Lewy bodies

BACKGROUND

Functional connectivity changes in clinically overt neurodegenerative diseases such as dementia with Lewy bodies have been described, but studies on connectivity changes in the pre-dementia phase are scarce.

OBJECTIVES

We concentrated on evaluating striato-cortical functional connectivity differences between patients with Mild Cognitive Impairment with Lewy bodies and healthy controls and on assessing the relation to cognition.

METHODS

Altogether, we enrolled 77 participants (47 patients, of which 35 met all the inclusion criteria for the final analysis, and 30 age- and gender-matched healthy controls, of which 28 met all the inclusion criteria for the final analysis) to study the seed-based connectivity of the dorsal, middle, and ventral striatum. We assessed correlations between functional connectivity in the regions of between-group differences and neuropsychological scores of interest (visuospatial and executive domains z-scores).

RESULTS

Subjects with Mild Cognitive Impairment with Lewy Bodies, as compared to healthy controls, showed increased connectivity from the dorsal part of the striatum particularly to the bilateral anterior part of the temporal cortex with an association with executive functions.

CONCLUSIONS

We were able to capture early abnormal connectivity within cholinergic and noradrenergic pathways that correlated with cognitive functions known to be linked to cholinergic/noradrenergic deficits. The knowledge of specific alterations may improve our understanding of early neural changes in pre-dementia stages and enhance research of disease modifying therapy.

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.

Distinctive whole-brain cell types predict tissue damage patterns in thirteen neurodegenerative conditions

For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most neurodegenerative studies focus on neuronal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell types' contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell types extensively predicts tissue damage in 13 neurodegenerative conditions, including early- and late-onset Alzheimer's disease, Parkinson's disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, mutations in presenilin-1, and 3 clinical variants of frontotemporal lobar degeneration (behavioral variant, semantic and non-fluent primary progressive aphasia) along with associated three-repeat and four-repeat tauopathies and TDP43 proteinopathies types A and C. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, in spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorder pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.

White matter injury across neurodegenerative disease

Oligodendrocytes (OLs), the myelin-generating cells of the central nervous system (CNS), are active players in shaping neuronal circuitry and function. It has become increasingly apparent that injury to cells within the OL lineage plays a central role in neurodegeneration. In this review, we focus primarily on three degenerative disorders in which white matter loss is well documented: Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). We discuss clinical data implicating white matter injury as a key feature of these disorders, as well as shared and divergent phenotypes between them. We examine the cellular and molecular mechanisms underlying the alterations to OLs, including chronic neuroinflammation, aggregation of proteins, lipid dysregulation, and organellar stress. Last, we highlight prospects for therapeutic intervention targeting the OL lineage to restore function.

Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measures

Brain aging is a complex process influenced by various lifestyle, environmental, and genetic factors, as well as by age-related and often co-existing pathologies. MRI and, more recently, AI methods have been instrumental in understanding the neuroanatomical changes that occur during aging in large and diverse populations. However, the multiplicity and mutual overlap of both pathologic processes and affected brain regions make it difficult to precisely characterize the underlying neurodegenerative profile of an individual from an MRI scan. Herein, we leverage a state-of-the art deep representation learning method, Surreal-GAN, and present both methodological advances and extensive experimental results that allow us to elucidate the heterogeneity of brain aging in a large and diverse cohort of 49,482 individuals from 11 studies. Five dominant patterns of neurodegeneration were identified and quantified for each individual by their respective (herein referred to as) R-indices. Significant associations between R-indices and distinct biomedical, lifestyle, and genetic factors provide insights into the etiology of observed variances. Furthermore, baseline R-indices showed predictive value for disease progression and mortality. These five R-indices contribute to MRI-based precision diagnostics, prognostication, and may inform stratification into clinical trials.

Alpha-Synuclein Contribution to Neuronal and Glial Damage in Parkinson's Disease

Parkinson's disease (PD) is a complex neurodegenerative disease characterized by the progressive loss of dopaminergic neurons in the substantia nigra and the widespread accumulation of alpha-synuclein (αSyn) protein aggregates. αSyn aggregation disrupts critical cellular processes, including synaptic function, mitochondrial integrity, and proteostasis, which culminate in neuronal cell death. Importantly, αSyn pathology extends beyond neurons-it also encompasses spreading throughout the neuronal environment and internalization by microglia and astrocytes. Once internalized, glia can act as neuroprotective scavengers, which limit the spread of αSyn. However, they can also become reactive, thereby contributing to neuroinflammation and the progression of PD. Recent advances in αSyn research have enabled the molecular diagnosis of PD and accelerated the development of targeted therapies. Nevertheless, despite more than two decades of research, the cellular function, aggregation mechanisms, and induction of cellular damage by αSyn remain incompletely understood. Unraveling the interplay between αSyn, neurons, and glia may provide insights into disease initiation and progression, which may bring us closer to exploring new effective therapeutic strategies. Herein, we provide an overview of recent studies emphasizing the multifaceted nature of αSyn and its impact on both neuron and glial cell damage.

Network connectivity and local transcriptomic vulnerability underpin cortical atrophy progression in Parkinson's disease

Parkinson's disease pathology is hypothesized to spread through the brain via axonal connections between regions and is further modulated by local vulnerabilities within those regions. The resulting changes to brain morphology have previously been demonstrated in both prodromal and de novo Parkinson's disease patients. However, it remains unclear whether the pattern of atrophy progression in Parkinson's disease over time is similarly explained by network-based spreading and local vulnerability. We address this gap by mapping the trajectory of cortical atrophy rates in a large, multi-centre cohort of Parkinson's disease patients and relate this atrophy progression pattern to network architecture and gene expression profiles. Across 4-year follow-up visits, increased atrophy rates were observed in posterior, temporal, and superior frontal cortices. We demonstrated that this progression pattern was shaped by network connectivity. Regional atrophy rates were strongly related to atrophy rates across structurally and functionally connected regions. We also found that atrophy progression was associated with specific gene expression profiles. The genes whose spatial distribution in the brain was most related to atrophy rate were those enriched for mitochondrial and metabolic function. Taken together, our findings demonstrate that both global and local brain features influence vulnerability to neurodegeneration in Parkinson's disease.

Predicting longitudinal brain atrophy in Parkinson's disease using a Susceptible-Infected-Removed agent-based model

Parkinson's disease is a progressive neurodegenerative disorder characterized by accumulation of abnormal isoforms of alpha-synuclein. Alpha-synuclein is proposed to act as a prion in Parkinson's disease: In its misfolded pathologic state, it favors the misfolding of normal alpha-synuclein molecules, spreads trans-neuronally, and causes neuronal damage as it accumulates. This theory remains controversial. We have previously developed a Susceptible-Infected-Removed (SIR) computational model that simulates the templating, propagation, and toxicity of alpha-synuclein molecules in the brain. In this study, we test this model with longitudinal MRI collected over 4 years from the Parkinson's Progression Markers Initiative (1,068 T1 MRI scans, 790 Parkinson's disease scans, and 278 matched control scans). We find that brain deformation progresses in subcortical and cortical regions. The SIR model recapitulates the spatiotemporal distribution of brain atrophy observed in Parkinson's disease. We show that connectome topology and geometry significantly contribute to model fit. We also show that the spatial expression of two genes implicated in alpha-synuclein synthesis and clearance, SNCA and GBA, also influences the atrophy pattern. We conclude that the progression of atrophy in Parkinson's disease is consistent with the prion-like hypothesis and that the SIR model is a promising tool to investigate multifactorial neurodegenerative diseases over time.

Mitochondrial function-associated genes underlie cortical atrophy in prodromal synucleinopathies

Isolated rapid eye movement sleep behaviour disorder (iRBD) is a sleep disorder characterized by the loss of rapid eye movement sleep muscle atonia and the appearance of abnormal movements and vocalizations during rapid eye movement sleep. It is a strong marker of incipient synucleinopathy such as dementia with Lewy bodies and Parkinson's disease. Patients with iRBD already show brain changes that are reminiscent of manifest synucleinopathies including brain atrophy. However, the mechanisms underlying the development of this atrophy remain poorly understood. In this study, we performed cutting-edge imaging transcriptomics and comprehensive spatial mapping analyses in a multicentric cohort of 171 polysomnography-confirmed iRBD patients [67.7 ± 6.6 (49-87) years; 83% men] and 238 healthy controls [66.6 ± 7.9 (41-88) years; 77% men] with T1-weighted MRI to investigate the gene expression and connectivity patterns associated with changes in cortical thickness and surface area in iRBD. Partial least squares regression was performed to identify the gene expression patterns underlying cortical changes in iRBD. Gene set enrichment analysis and virtual histology were then done to assess the biological processes, cellular components, human disease gene terms, and cell types enriched in these gene expression patterns. We then used structural and functional neighbourhood analyses to assess whether the atrophy patterns in iRBD were constrained by the brain's structural and functional connectome. Moreover, we used comprehensive spatial mapping analyses to assess the specific neurotransmitter systems, functional networks, cytoarchitectonic classes, and cognitive brain systems associated with cortical changes in iRBD. All comparisons were tested against null models that preserved spatial autocorrelation between brain regions and compared to Alzheimer's disease to assess the specificity of findings to synucleinopathies. We found that genes involved in mitochondrial function and macroautophagy were the strongest contributors to the cortical thinning occurring in iRBD. Moreover, we demonstrated that cortical thinning was constrained by the brain's structural and functional connectome and that it mapped onto specific networks involved in motor and planning functions. In contrast with cortical thickness, changes in cortical surface area were related to distinct genes, namely genes involved in the inflammatory response, and to different spatial mapping patterns. The gene expression and connectivity patterns associated with iRBD were all distinct from those observed in Alzheimer's disease. In summary, this study demonstrates that the development of brain atrophy in synucleinopathies is constrained by specific genes and networks.

Different pieces of the same puzzle: a multifaceted perspective on the complex biological basis of Parkinson's disease

The biological basis of the neurodegenerative movement disorder, Parkinson's disease (PD), is still unclear despite it being 'discovered' over 200 years ago in Western Medicine. Based on current PD knowledge, there are widely varying theories as to its pathobiology. The aim of this article was to explore some of these different theories by summarizing the viewpoints of laboratory and clinician scientists in the PD field, on the biological basis of the disease. To achieve this aim, we posed this question to thirteen "PD experts" from six continents (for global representation) and collated their personal opinions into this article. The views were varied, ranging from toxin exposure as a PD trigger, to LRRK2 as a potential root cause, to toxic alpha-synuclein being the most important etiological contributor. Notably, there was also growing recognition that the definition of PD as a single disease should be reconsidered, perhaps each with its own unique pathobiology and treatment regimen.

Synaptic mechanisms underlying onset and progression of memory deficits caused by hippocampal and midbrain synucleinopathy

Cognitive deficits, including working memory, and visuospatial deficits are common and debilitating in Parkinson's disease. α-synucleinopathy in the hippocampus and cortex is considered as the major risk factor. However, little is known about the progression and specific synaptic mechanisms underlying the memory deficits induced by α-synucleinopathy. Here, we tested the hypothesis that pathologic α-Synuclein (α-Syn), initiated in different brain regions, leads to distinct onset and progression of the pathology. We report that overexpression of human α-Syn in the murine mesencephalon leads to late onset memory impairment and sensorimotor deficits accompanied by reduced dopamine D1 expression in the hippocampus. In contrast, human α-Syn overexpression in the hippocampus leads to early memory impairment, altered synaptic transmission and plasticity, and decreased expression of GluA1 AMPA-type glutamate receptors. These findings identify the synaptic mechanisms leading to memory impairment induced by hippocampal α-synucleinopathy and provide functional evidence of the major neuronal networks involved in disease progression.

Sex differences in grey matter networks in dementia with Lewy bodies

Objectives

Sex differences permeate many aspects of dementia with Lewy bodies (DLB), including epidemiology, pathogenesis, disease progression, and symptom manifestation. However, less is known about potential sex differences in patterns of neurodegeneration in DLB. Here, we test whether grey matter networks also differ between female and male DLB patients. To assess the specificity of these sex differences to DLB, we additionally investigate sex differences in healthy controls (HCs).

Methods

A total of 119 (68.7 ± 8.4 years) male and 45 female (69.9 ± 9.1 years) DLB patients from three European centres and the Mayo Clinic were included in this study. Additionally, we included 119 male and 45 female age-matched HCs from the Mayo Clinic. Grey matter volumes of 58 cortical, subcortical, cerebellar, and pontine brain regions derived from structural magnetic resonance images were corrected for age, intracranial volume, and centre. Sex-specific grey matter networks for DLB patients and HCs were constructed by correlating each pair of brain regions. Network properties of the correlation matrices were compared between sexes and groups. Additional analyses were conducted on W-scored data to identify DLB-specific findings.

Results

Networks of male HCs and male DLB patients were characterised by a lower nodal strength compared to their respective female counterparts. In comparison to female HCs, the grey matter networks of male HCs showed a higher global efficiency, modularity, and a lower number of modules. None of the global and nodal network measures showed significant sex differences in DLB.

Conclusions

The disappearance of sex differences in the structural grey matter networks of DLB patients compared to HCs may indicate a sex-dependent network vulnerability to the alpha-synuclein pathology in DLB. Future studies might investigate whether the differences in structural network measures are associated with differences in cognitive scores and clinical symptoms between the sexes.

Nucleus accumbens atrophy in Parkinson's disease (Mavridis' atrophy): 10 years later

Parkinson's disease (PD) is a common neurodegenerative disorder associated with gray matter atrophy. The human nucleus accumbens (NA) is a major part of the ventral striatum and modulator of the reward network of the brain. It plays an important role in several cognitive and emotional functions. In patients with PD, dysfunction of this nucleus is correlated not only with movement disorders but also with various neuropsychological deficits and psychiatric symptoms. The human NA suffers atrophy in PD, which is called Mavridis' atrophy (MA), a well established characteristic of PD that was first described 10 years ago. The purpose of this article is to review the current knowledge regarding the clinical significance of MA. We currently know that it begins in early-stage PD patients, precedes clinical phenotype, and is part of the degeneration of the dopaminergic nigrostriatal system in these patients. MA has several clinical consequences. It is, more specifically, associated with the expression (and severity) of specific neuropsychiatric PD symptoms, namely cognitive impairment, apathy, disinhibition, and impulsive behavior, while its association with motor symptoms remains unclear. MA was recently suggested as a marker of global dysfunction in the mesocorticolimbic network. With new research data, new questions about MA emerge and further research is obviously necessary in order to effectively apply MA, as an imaging finding, to clinical practice.

Brain atrophy in prodromal synucleinopathy is shaped by structural connectivity and gene expression

Isolated REM sleep behaviour disorder (iRBD) is a synucleinopathy characterized by abnormal behaviours and vocalizations during REM sleep. Most iRBD patients develop dementia with Lewy bodies, Parkinson's disease, or multiple system atrophy over time. Patients with iRBD exhibit brain atrophy patterns that are reminiscent of those observed in overt synucleinopathies. However, the mechanisms linking brain atrophy to the underlying alpha-synuclein pathophysiology are poorly understood. Our objective was to investigate how the prion-like and regional vulnerability hypotheses of alpha-synuclein might explain brain atrophy in iRBD. Using a multicentric cohort of 182 polysomnography-confirmed iRBD patients who underwent T1-weighted MRI, we performed vertex-based cortical surface and deformation-based morphometry analyses to quantify brain atrophy in patients (67.8 years, 84% men) and 261 healthy controls (66.2 years, 75%) and investigated the morphological correlates of motor and cognitive functioning in iRBD. Next, we applied the agent-based Susceptible-Infected-Removed model (i.e., a computational model that simulates in silico the spread of pathologic alpha-synuclein based on structural connectivity and gene expression) and tested if it recreated atrophy in iRBD by statistically comparing simulated regional brain atrophy to the atrophy observed in patients. The impact of SNCA and GBA gene expression and brain connectivity was then evaluated by comparing the model fit to the one obtained in null models where either gene expression or connectivity was randomized. The results showed that iRBD patients present with cortical thinning and tissue deformation, which correlated with motor and cognitive functioning. Next, we found that the computational model recreated cortical thinning (r = 0.51, p = 0.0007) and tissue deformation (r = 0.52, p = 0.0005) in patients, and that the connectome's architecture along with SNCA and GBA gene expression contributed to shaping atrophy in iRBD. We further demonstrated that the full agent-based model performed better than network measures or gene expression alone in recreating the atrophy pattern in iRBD. In summary, atrophy in iRBD is extensive, correlates with motor and cognitive function, and can be recreated using the dynamics of agent-based modelling, structural connectivity, and gene expression. These findings support the concepts that both prion-like spread and regional susceptibility account for the atrophy observed in prodromal synucleinopathies. Therefore, the agent-based Susceptible-Infected-Removed model may be a useful tool for testing hypotheses underlying neurodegenerative diseases and new therapies aimed at slowing or stopping the spread of alpha-synuclein pathology.