Monoaminergic Markers Across the Cognitive Spectrum of Lewy Body Disease

Unveiling Parkinson's disease through biomarker research: current insights and future prospects

Parkinson's disease (PD) is a neurodegenerative condition marked by the gradual depletion of dopaminergic neurons in the substantia nigra. Despite substantial strides in comprehending potential causative mechanisms, the validation of biomarkers with unequivocal evidence for routine clinical application remains elusive. Consequently, the diagnosis heavily relies on patients' clinical assessments and medical backgrounds. The imperative need for diagnostic and prognostic biomarkers arises due to the prevailing limitations of treatments, which predominantly address symptoms without modifying the disease course. This comprehensive review aims to elucidate the existing landscape of diagnostic and prognostic biomarkers for PD, drawing insights from contemporary literature.

Parkinson disease-associated cognitive impairment

Parkinson disease (PD) is the second most common neurodegenerative disorder, affecting >1% of the population ≥65 years of age and with a prevalence set to double by 2030. In addition to the defining motor symptoms of PD, multiple non-motor symptoms occur; among them, cognitive impairment is common and can potentially occur at any disease stage. Cognitive decline is usually slow and insidious, but rapid in some cases. Recently, the focus has been on the early cognitive changes, where executive and visuospatial impairments are typical and can be accompanied by memory impairment, increasing the risk for early progression to dementia. Other risk factors for early progression to dementia include visual hallucinations, older age and biomarker changes such as cortical atrophy, as well as Alzheimer-type changes on functional imaging and in cerebrospinal fluid, and slowing and frequency variation on EEG. However, the mechanisms underlying cognitive decline in PD remain largely unclear. Cortical involvement of Lewy body and Alzheimer-type pathologies are key features, but multiple mechanisms are likely involved. Cholinesterase inhibition is the only high-level evidence-based treatment available, but other pharmacological and non-pharmacological strategies are being tested. Challenges include the identification of disease-modifying therapies as well as finding biomarkers to better predict cognitive decline and identify patients at high risk for early and rapid cognitive impairment.

Comparison of Locus Coeruleus Pathology with Nigral and Forebrain Pathology in Parkinson's Disease

BACKGROUND

Pathology in the noradrenergic A6 locus coeruleus has not been compared with more rostral dopaminergic A9 substantia nigra and A10 ventral tegmental area, and cholinergic Ch4 basal nucleus and Ch1/2 septal regions in the same cases of Parkinson's disease (PD).

OBJECTIVE

To determine whether there is a gradient of caudal to rostral cell loss in PD.

METHODS

Postmortem brains were collected from longitudinally followed donors with PD (n = 14) and aged-matched healthy donors (n = 13), six with restricted brainstem Lewy pathology (RLP), fixed in formalin and serial tissue slabs processed for cell and pathological quantitation. Noradrenergic A6 neurons were assessed and compared with previously published midbrain and basal forebrain data. From these data, regression estimates of pathological onset and progression were determined.

RESULTS

Restricted Lewy pathology (RLP) cases had high pathological variability but no significant reduction in neurons. Pathology containing A6 neuron loss started at PD diagnosis and progressed faster (2.4% p.a) than the loss of dopaminergic A9 neurons (2% loss p.a.). Cases with dementia had significantly more pathology in noradrenergic and cholinergic neurons, had greater noradrenergic A6 neuron loss (29% more, progressing at 3.2% p.a.), and a selective loss of lateral A10 nonmelanized dopamine-producing neurons (starting a decade following diagnosis).

CONCLUSIONS

These findings show that in the same Parkinson's disease cases cell loss in these neurotransmitter systems does not follow a strict caudal to rostral trajectory and suggests symptom onset may relate to substantial pathology in the noradrenergic A6 locus coeruleus neurons in people with reduced dopamine-producing A9 substantia nigra neurons. © 2021 International Parkinson and Movement Disorder Society.

Genetic Architecture and Molecular, Imaging and Prodromic Markers in Dementia with Lewy Bodies: State of the Art, Opportunities and Challenges

Dementia with Lewy bodies (DLB) is one of the most common causes of dementia and belongs to the group of α-synucleinopathies. Due to its clinical overlap with other neurodegenerative disorders and its high clinical heterogeneity, the clinical differential diagnosis of DLB from other similar disorders is often difficult and it is frequently underdiagnosed. Moreover, its genetic etiology has been studied only recently due to the unavailability of large cohorts with a certain diagnosis and shows genetic heterogeneity with a rare contribution of pathogenic mutations and relatively common risk factors. The rapid increase in the reported cases of DLB highlights the need for an easy, efficient and accurate diagnosis of the disease in its initial stages in order to halt or delay the progression. The currently used diagnostic methods proposed by the International DLB consortium rely on a list of criteria that comprises both clinical observations and the use of biomarkers. Herein, we summarize the up-to-now reported knowledge on the genetic architecture of DLB and discuss the use of prodromal biomarkers as well as recent promising candidates from alternative body fluids and new imaging techniques.

Molecular Factors Mediating Neural Cell Plasticity Changes in Dementia Brain Diseases

Neural plasticity-the ability to alter a neuronal response to environmental stimuli-is an important factor in learning and memory. Short-term synaptic plasticity and long-term synaptic plasticity, including long-term potentiation and long-term depression, are the most-characterized models of learning and memory at the molecular and cellular level. These processes are often disrupted by neurodegeneration-induced dementias. Alzheimer's disease (AD) accounts for 50% of cases of dementia. Vascular dementia (VaD), Parkinson's disease dementia (PDD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD) constitute much of the remaining cases. While vascular lesions are the principal cause of VaD, neurodegenerative processes have been established as etiological agents of many dementia diseases. Chief among such processes is the deposition of pathological protein aggregates in vivo including β-amyloid deposition in AD, the formation of neurofibrillary tangles in AD and FTD, and the accumulation of Lewy bodies composed of α-synuclein aggregates in DLB and PDD. The main symptoms of dementia are cognitive decline and memory and learning impairment. Nonetheless, accurate diagnoses of neurodegenerative diseases can be difficult due to overlapping clinical symptoms and the diverse locations of cortical lesions. Still, new neuroimaging and molecular biomarkers have improved clinicians' diagnostic capabilities in the context of dementia and may lead to the development of more effective treatments. Both genetic and environmental factors may lead to the aggregation of pathological proteins and altered levels of cytokines, such that can trigger the formation of proinflammatory immunological phenotypes. This cascade of pathological changes provides fertile ground for the development of neural plasticity disorders and dementias. Available pharmacotherapy and disease-modifying therapies currently in clinical trials may modulate synaptic plasticity to mitigate the effects neuropathological changes have on cognitive function, memory, and learning. In this article, we review the neural plasticity changes seen in common neurodegenerative diseases from pathophysiological and clinical points of view and highlight potential molecular targets of disease-modifying therapies.

An SBM-based machine learning model for identifying mild cognitive impairment in patients with Parkinson's disease

OBJECTIVE

To identify Parkinson's disease with mild cognitive impairment (PD-MCI) through surface-based morphometry (SBM) based machine learning model.

METHODS

93 patients with parkinson's disease (35 PD with normal cognition, 58 PD-MCI) were examined, obtaining 276 SBM variables per subject. 20 healthy control subjects were used as the reference. After extracting features with statistically significance, support vector machine (SVM) model with grid search method was applied to identify patients with PD-MCI. Accuracy, matthews correlation coefficient (MCC), receiver operating characteristic curve (ROC), precision-recall curve (PR), AUC-ROC, AUC-PR and leave-one-out cross validation (LOOCV) strategy were employed for model evaluation.

RESULTS

PD-MCI is characterized by widespread structural abnormality. SVM model with SBM features achieved an accuracy of 80.00% and area under the ROC of 0.86 for identifying PD-MCI. MCC, AUC-PR, and LOOCV classification accuracy were 0.56, 0.89, and 78.08%, respectively.

CONCLUSION

Automatic identification of PD-MCI could be realized by SBM-based machine learning model.

Biofluid Markers for Prodromal Parkinson's Disease: Evidence From a Catecholaminergic Perspective

Parkinson's disease (PD) is the most frequent of all Lewy body diseases, a family of progressive neurodegenerative disorders characterized by intra-neuronal cytoplasmic inclusions of α-synuclein. Its most defining features are bradykinesia, tremor, rigidity and postural instability. By the time PD manifests with motor signs, 70% of dopaminergic midbrain neurons are lost, and the disease is already in the middle or late stage. However, there are various non-motor symptoms occurring up to 20 years before the actual parkinsonism that are closely associated with profound deficiency of myocardial noradrenaline content and peripheral sympathetic denervation, as evidenced by neuroimaging experiments in recent years. Additionally, there is an inherent autotoxicity of catecholamines in the neuronal cells in which they are produced, forming toxic catecholaldehyde intermediates that make α-synuclein prone to aggregation, initiating a cascade of events that ultimately leads to neuronal death. The etiopathogenesis of PD and related synucleinopathies thus may well be a prototypical example of a catecholamine-regulated neurodegeneration, given that the synucleinopathy in PD spreads in synergy with central and peripheral catecholaminergic dysfunction from the earliest phases onward. That is why catecholamines and their metabolites, precursors, or derivatives in cerebrospinal fluid or plasma could be of particular interest as biomarkers for prodromal and de novo PD. Because there is great demand for such markers, this mini-review summarizes all catecholamine-related studies to date, in addition to providing profound neurochemical evidence on a systemic and cellular level to further emphasize this hypothesis and with emphasis on extracellular vesicles as a novel diagnostic and therapeutic incentive.

Age- and disease-specific changes of the kynurenine pathway in Parkinson's and Alzheimer's disease

The kynurenine (Kyn) pathway, which regulates neuroinflammation and N‐methyl‐d‐aspartate receptor activation, is implicated in Parkinson’s disease (PD) and Alzheimer’s disease (AD). Age‐related changes in Kyn metabolism and altered cerebral Kyn uptake along large neutral amino acid transporters, could contribute to these diseases. To gain further insight into the role and prognostic potential of the Kyn pathway in PD and AD, we investigated systemic and cerebral Kyn metabolite production and estimations of their transporter‐mediated uptake in the brain. Kyn metabolites and large neutral amino acids were retrospectively measured in serum and cerebrospinal fluid (CSF) of clinically well‐characterized PD patients (n = 33), AD patients (n = 33), and age‐matched controls (n = 39) using solid‐phase extraction‐liquid chromatographic‐tandem mass spectrometry. Aging was disease independently associated with increased Kyn, kynurenic acid and quinolinic acid in serum and CSF. Concentrations of kynurenic acid were reduced in CSF of PD and AD patients (p = 0.001; p = 0.002) but estimations of Kyn brain uptake did not differ between diseased and controls. Furthermore, serum Kyn and quinolinic acid levels strongly correlated with their respective content in CSF and Kyn in serum negatively correlated with AD disease severity (p = 0.002). Kyn metabolites accumulated with aging in serum and CSF similarly in PD patients, AD patients, and control subjects. In contrast, kynurenic acid was strongly reduced in CSF of PD and AD patients. Differential transporter‐mediated Kyn uptake is unlikely to majorly contribute to these cerebral Kyn pathway disturbances. We hypothesize that the combination of age‐ and disease‐specific changes in cerebral Kyn pathway activity could contribute to reduced neurogenesis and increased excitotoxicity in neurodegenerative disease.

Parkinson's Disease: Biomarkers, Treatment, and Risk Factors

Parkinson's disease (PD) is a progressive neurodegenerative disorder caused mainly by lack of dopamine in the brain. Dopamine is a neurotransmitter involved in movement, motivation, memory, and other functions; its level is decreased in PD brain as a result of dopaminergic cell death. Dopamine loss in PD brain is a cause of motor deficiency and, possibly, a reason of the cognitive deficit observed in some PD patients. PD is mostly not recognized in its early stage because of a long latency between the first damage to dopaminergic cells and the onset of clinical symptoms. Therefore, it is very important to find reliable molecular biomarkers that can distinguish PD from other conditions, monitor its progression, or give an indication of a positive response to a therapeutic intervention. PD biomarkers can be subdivided into four main types: clinical, imaging, biochemical, and genetic. For a long time protein biomarkers, dopamine metabolites, amino acids, etc. in blood, serum, cerebrospinal liquid (CSF) were considered the most promising. Among the candidate biomarkers that have been tested, various forms of α-synuclein (α-syn), i.e., soluble, aggregated, post-translationally modified, etc. were considered potentially the most efficient. However, the encouraging recent results suggest that microRNA-based analysis may bring considerable progress, especially if it is combined with α-syn data. Another promising analysis is the advanced metabolite profiling of body fluids, called "metabolomics" which may uncover metabolic fingerprints specific for various stages of PD. Conventional pharmacological treatment of PD is based on the replacement of dopamine using dopamine precursors (levodopa, L-DOPA, L-3,4 dihydroxyphenylalanine), dopamine agonists (amantadine, apomorphine) and MAO-B inhibitors (selegiline, rasagiline), which can be used alone or in combination with each other. Potential risk factors include environmental toxins, drugs, pesticides, brain microtrauma, focal cerebrovascular damage, and genomic defects. This review covers molecules that might act as the biomarkers of PD. Then, PD risk factors (including genetics and non-genetic factors) and PD treatment options are discussed.