DOPA decarboxylase is an emerging biomarker for Parkinsonian disorders including preclinical Lewy body disease

Proteomic changes in Alzheimer's disease associated with progressive Aβ plaque and tau tangle pathologies

Proteomics can shed light on the dynamic and multifaceted alterations in neurodegenerative disorders like Alzheimer's disease (AD). Combining radioligands measuring β-amyloid (Aβ) plaques and tau tangles with cerebrospinal fluid proteomics, we uncover molecular events mirroring different stages of AD pathology in living humans. We found 127 differentially abundant proteins (DAPs) across the AD spectrum. The strongest Aβ-related proteins were mainly expressed in glial cells and included SMOC1 and ITGAM. A dozen proteins linked to ATP metabolism and preferentially expressed in neurons were independently associated with tau tangle load and tau accumulation. Only 20% of the DAPs were also altered in other neurodegenerative diseases, underscoring AD's distinct proteome. Two co-expression modules related, respectively, to protein metabolism and microglial immune response encompassed most DAPs, with opposing, staggered trajectories along the AD continuum. We unveil protein signatures associated with Aβ and tau proteinopathy in vivo, offering insights into complex neural responses and potential biomarkers and therapeutics targeting different disease stages.

Unraveling the Complexity of Parkinson's Disease: Insights into Pathogenesis and Precision Interventions

Parkinson's disease (PD) is a neurodegenerative disorder characterized by dopaminergic neuron loss, leading to motor and non-motor symptoms. Early detection before symptom onset is crucial but challenging. This study presents a framework integrating circuit modeling, non-equilibrium dynamics, and optimization to understand PD pathogenesis and enable precision interventions. Neuronal firing patterns, particularly oscillatory activity, play a critical role in PD pathology. The basal ganglia network, specifically the subthalamic nucleus-external globus pallidus (STN-GPe) circuitry, exhibits abnormal activity associated with motor dysfunction. The framework leverages the non-equilibrium landscape and flux theory to identify key connections generating pathological activity, providing insights into disease progression and potential intervention points. The intricate STN-GPe interplay is highlighted, shedding light on compensatory mechanisms within this circuitry may initially counteract changes but later contribute to pathological alterations as disease progresses. The framework addresses the need for comprehensive evaluation methods to assess intervention outcomes. Cross-correlations between state variables provide superior early warning signals compared to traditional indicators relying on critical slowing down. By elucidating compensatory mechanisms and circuit dynamics, the framework contributes to improved management, early detection, risk assessment, and potential prevention/delay of PD development. This pioneering research paves the way for precision medicine in neurodegenerative disorders.

Research advancement in fluid biomarkers for Parkinson's disease

INTRODUCTION

Diagnostic criteria for Parkinson's disease (PD) rely on clinical, mainly motor, features, implying that pre-motor phase cannot be accurately identified. To achieve a reliable early diagnosis, similar to what has been done for Alzheimer's disease (AD), a shift from clinical to biological identification of PD is being pursued. This shift has taken great advantage from the research on cerebrospinal fluid (CSF) biomarkers as they mirror the ongoing molecular pathogenic mechanisms taking place in PD, thus intercepting the disease timely with respect to clinical manifestations.

AREAS COVERED

CSF α-synuclein seed amplification assay (αS-SAA) has emerged as the most promising biomarker of α-synucleinopathy. CSF biomarkers reflecting AD-pathology and axonal damage (neurofilament light chain) and a novel marker of dopaminergic dysfunction (DOPA decarboxylase) add valuable diagnostic and prognostic information in the neurochemical characterization of PD.

EXPERT OPINION

A biological classification system of PD, encompassing pathophysiological and staging biomarkers, might ensure both early identification and prognostic characterization of the patients. This approach could allow for the best setting for disease-modifying treatments which are currently under investigation.

Associations Between Neuropsychiatric Symptoms and Inflammation in Neurodegenerative Dementia: A Systematic Review

Background

Neuropsychiatric symptoms are common in dementia and linked to adverse outcomes. Inflammation is increasingly recognized as playing a role as a driver of early disease progression in Alzheimer's disease (AD) and related dementias. Inflammation has also been linked to primary psychiatric disorders, however its association with neuropsychiatric symptoms in neurodegenerative dementias remains uncertain.

Methods

We conducted a systematic literature review investigating associations between inflammation and neuropsychiatric symptoms in neurodegenerative dementias, including AD, Lewy body, Frontotemporal, Parkinson's (PD) and Huntington's disease dementias.

Results

Ninety-nine studies met our inclusion criteria, and the majority (n = 59) investigated AD and/or mild cognitive impairment (MCI). Thirty-five studies included PD, and only 6 investigated non-AD dementias. Inflammation was measured in blood, CSF, by genotype, brain tissue and PET imaging. Overall, studies exhibited considerable heterogeneity and evidence for specific inflammatory markers was inconsistent, with lack of replication and few longitudinal studies with repeat biomarkers. Depression was the most frequently investigated symptom. In AD, some studies reported increases in peripheral IL-6, TNF-a associated with depressive symptoms. Preliminary investigations using PET measures of microglial activation found an association with agitation. In PD, studies reported positive associations between TNF-a, IL-6, CRP, MCP-1, IL-10 and depression.

Conclusion

Central and peripheral inflammation may play a role in neuropsychiatric symptoms in neurodegenerative dementias; however, the evidence is inconsistent. There is a need for multi-site longitudinal studies with detailed assessments of neuropsychiatric symptoms combined with replicable peripheral and central markers of inflammation.

Associations of cerebrospinal fluid monoamine metabolites with striatal dopamine transporter binding and 123I-meta-iodobenzylguanidine cardiac scintigraphy in Parkinson's disease: Multivariate analyses

Cerebrospinal fluid (CSF) homovanillic acid (HVA) and 5-hydroxyindole acetic acid (5-HIAA), dopamine and serotonin metabolites, are decreased in Parkinson's disease (PD). Although some reported associations between HVA and striatal dopamine transporter (DAT) or 5-HIAA and cardiac 123I-meta-iodobenzylguanidine (MIBG) findings, respectively, whether these are direct associations remained unknown. We retrospectively reviewed 57 drug-naïve patients with PD who underwent CSF analyses and DAT and cardiac MIBG imaging. Z-score of striatal DAT specific binding ratio (Z-SBR) was measured, and the positivity of MIBG abnormalities were judged by an expert. The mean age was 75.5 ± 8.7 years. Thirty-three were MIBG-positive and 24 were MIBG-negative. 5-HIAA levels were significantly lower in the MIBG-positive group. Logistic regression analysis showed that MIBG positivity was associated with 5-HIAA level (odds ratio = 0.751, p = 0.006) but not with age, sex, and HVA. DAT Z-SBR correlated with both HVA and 5-HIAA. Multiple regression analysis showed that HVA was the only significant variable associated with Z-SBR (t = 3.510, p < 0.001). We confirmed direct associations between 5-HIAA and cardiac MIBG, and between HVA and striatal DAT binding.

Prediction of Future Parkinson Disease Using Plasma Proteins Combined With Clinical-Demographic Measures

BACKGROUND AND OBJECTIVES

Identification of individuals at high risk of developing Parkinson disease (PD) several years before diagnosis is crucial for developing treatments to prevent or delay neurodegeneration. This study aimed to develop predictive models for PD risk that combine plasma proteins and easily accessible clinical-demographic variables.

METHODS

Using data from the UK Biobank (UKB), which recruited participants across the United Kingdom, we conducted a longitudinal study to identify predictors for incident PD. Participants with baseline plasma proteins and no PD were included. Through machine learning, we narrowed down predictors from a pool of 1,463 plasma proteins and 93 clinical-demographic. These predictors were then externally validated using the Parkinson's Progression Marker Initiative (PPMI) cohort. To further investigate the temporal trends of predictors, a nested case-control study was conducted within the UKB.

RESULTS

A total of 52,503 participants without PD (median age 58, 54% female) were included. Over a median follow-up duration of 14.0 years, 751 individuals were diagnosed with PD (median age 65, 37% female). Using a forward selection approach, we selected a panel of 22 plasma proteins for optimal prediction. Using an ensemble tree-based Light Gradient Boosting Machine (LightGBM) algorithm, the model achieved an area under the receiver operating characteristic curve (AUC) of 0.800 (95% CI 0.785-0.815). The LightGBM prediction model integrating both plasma proteins and clinical-demographic variables demonstrated enhanced predictive accuracy, with an AUC of 0.832 (95% CI 0.815-0.849). Key predictors identified included age, years of education, history of traumatic brain injury, and serum creatinine. The incorporation of 11 plasma proteins (neurofilament light, integrin subunit alpha V, hematopoietic PGD synthase, histamine N-methyltransferase, tubulin polymerization promoting protein family member 3, ectodysplasin A2 receptor, Latexin, interleukin-13 receptor subunit alpha-1, BAG family molecular chaperone regulator 3, tryptophanyl-TRNA synthetase, and secretogranin-2) augmented the model's predictive accuracy. External validation in the PPMI cohort confirmed the model's reliability, producing an AUC of 0.810 (95% CI 0.740-0.873). Notably, alterations in these predictors were detectable several years before the diagnosis of PD.

DISCUSSION

Our findings support the potential utility of a machine learning-based model integrating clinical-demographic variables with plasma proteins to identify individuals at high risk for PD within the general population. Although these predictors have been validated by PPMI, additional validation in a more diverse population reflective of the general community is essential.

Molecular signatures of normal pressure hydrocephalus: a large-scale proteomic analysis of cerebrospinal fluid

Given the persistent challenge of differentiating idiopathic Normal Pressure Hydrocephalus (iNPH) from similar clinical entities, we conducted an in-depth proteomic study of cerebrospinal fluid (CSF) in 28 shunt-responsive iNPH patients, 38 Mild Cognitive Impairment (MCI) due to Alzheimer's disease, and 49 healthy controls. Utilizing the Olink Explore 3072 panel, we identified distinct proteomic profiles in iNPH that highlight significant downregulation of synaptic markers and cell-cell adhesion proteins. Alongside vimentin and inflammatory markers upregulation, these results suggest ependymal layer and transependymal flow dysfunction. Moreover, downregulation of multiple proteins associated with congenital hydrocephalus (e.g., L1CAM, PCDH9, ISLR2, ADAMTSL2, and B4GAT1) points to a possible shared molecular foundation between congenital hydrocephalus and iNPH. Through orthogonal partial least squares discriminant analysis (OPLS-DA), a panel comprising 13 proteins has been identified as potential diagnostic biomarkers of iNPH, pending external validation. These findings offer novel insights into the pathophysiology of iNPH, with implications for improved diagnosis.

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

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

Potential convergence of olfactory dysfunction in Parkinson's disease and COVID-19: The role of neuroinflammation

Parkinson's disease (PD) is a prevalent neurodegenerative disorder that affects 7-10 million individuals worldwide. A common early symptom of PD is olfactory dysfunction (OD), and more than 90% of PD patients suffer from OD. Recent studies have highlighted a high incidence of OD in patients with SARS-CoV-2 infection. This review investigates the potential convergence of OD in PD and COVID-19, particularly focusing on the mechanisms by which neuroinflammation contributes to OD and neurological events. Starting from our fundamental understanding of the olfactory bulb, we summarize the clinical features of OD and pathological features of the olfactory bulb from clinical cases and autopsy reports in PD patients. We then examine SARS-CoV-2-induced olfactory bulb neuropathology and OD and emphasize the SARS-CoV-2-induced neuroinflammatory cascades potentially leading to PD manifestations. By activating microglia and astrocytes, as well as facilitating the aggregation of α-synuclein, SARS-CoV-2 could contribute to the onset or exacerbation of PD. We also discuss the possible contributions of NF-κB, the NLRP3 inflammasome, and the JAK/STAT, p38 MAPK, TLR4, IL-6/JAK2/STAT3 and cGAS-STING signaling pathways. Although olfactory dysfunction in patients with COVID-19 may be reversible, it is challenging to restore OD in patients with PD. With the emergence of new SARS-CoV-2 variants and the recurrence of infections, we call for continued attention to the intersection between PD and SARS-CoV-2 infection, especially from the perspective of OD.

Increased CSF DOPA Decarboxylase Correlates with Lower DaT-SPECT Binding: Analyses in Biopark and PPMI Cohorts

BACKGROUND

Recent studies identified increased cerebrospinal fluid (CSF) DOPA decarboxylase (DDC) as a promising biomarker for parkinsonian disorders, suggesting a compensation to dying dopaminergic neurons. A correlation with 123I-FP-CIT-SPECT (DaT-SPECT) imaging could shed light on this link.

OBJECTIVE

The objective is to assess the relationship between CSF DDC levels and DaT-SPECT binding values.

METHODS

A total of 51 and 72 Parkinson's disease (PD) subjects with available DaT-SPECT and CSF DDC levels were selected from the PPMI and Biopark cohorts, respectively. DDC levels were analyzed using proximity extension assay and correlated with DaT-SPECT striatal binding ratios (SBR). All analyses were corrected for age and sex.

RESULTS

CSF DDC levels in PD patients correlated negatively with DaT-SPECT SBR in both putamen and caudate nucleus. Additionally, SBR decreased with increased DDC levels over time in PD patients.

CONCLUSION

CSF DDC levels negatively correlate with DaT-SPECT SBR in levodopa-treated PD. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Integrative analysis of plasma and substantia nigra in Parkinson's disease: unraveling biomarkers and insights from the lncRNA-miRNA-mRNA ceRNA network

Introduction

Parkinson's disease (PD) is a rapidly growing neurological disorder characterized by diverse movement symptoms. However, the underlying causes have not been clearly identified, and accurate diagnosis is challenging. This study aimed to identify potential biomarkers suitable for PD diagnosis and present an integrative perspective on the disease.

Methods

We screened the GSE7621, GSE8397-GPL96, GSE8397-GPL97, GSE20163, and GSE20164 datasets in the NCBI GEO database to identify differentially expressed (DE) mRNAs in the substantia nigra (SN). We also screened the GSE160299 dataset from the NCBI GEO database to identify DE lncRNAs and miRNAs in plasma. We then constructed 2 lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) regulatory networks based on the ceRNA hypothesis. To understand the biological function, we performed Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analyses for each ceRNA network. The receiver operating characteristic analyses (ROC) was used to assess ceRNA results.

Results

We identified 7 upregulated and 29 downregulated mRNAs as common DE mRNAs in the 5 SN datasets. In the blood dataset, we identified 31 DE miRNAs (9 upregulated and 22 downregulated) and 332 DE lncRNAs (69 upregulated and 263 downregulated). Based on the determined interactions, 5 genes (P2RX7, HSPA1, SLCO4A1, RAD52, and SIRT4) appeared to be upregulated as a result of 10 lncRNAs sponging 4 miRNAs (miR-411, miR-1193, miR-301b, and miR-514a-2/3). Competing with 9 genes (ANK1, CBLN1, RGS4, SLC6A3, SYNGR3, VSNL1, DDC, KCNJ6, and SV2C) for miR-671, a total of 26 lncRNAs seemed to function as ceRNAs, influencing genes to be downregulated.

Discussion

In this study, we successfully constructed 2 novel ceRNA regulatory networks in patients with PD, including 36 lncRNAs, 5 miRNAs, and 14 mRNAs. Our results suggest that these plasma lncRNAs are involved in the pathogenesis of PD by sponging miRNAs and regulating gene expression in the SN of the brain. We propose that the upregulated and downregulated lncRNA-mediated ceRNA networks represent mechanisms of neuroinflammation and dopamine neurotransmission, respectively. Our ceRNA network, which was associated with PD, suggests the potential use of DE miRNAs and lncRNAs as body fluid diagnostic biomarkers. These findings provide an integrated view of the mechanisms underlying gene regulation and interactions in PD.

Functional differentiation of olive PLP_deC genes: insights into metabolite biosynthesis and genetic improvement at the whole-genome level

KEY MESSAGE

This study identified 16 pyridoxal phosphate-dependent decarboxylases in olive at the whole-genome level, conducted analyses on their physicochemical properties, evolutionary relationships and characterized their activity. Group II pyridoxal phosphate-dependent decarboxylases (PLP_deC II) mediate the biosynthesis of characteristic olive metabolites, such as oleuropein and hydroxytyrosol. However, there have been no report on the functional differentiation of this gene family at the whole-genome level. This study conducted an exploration of the family members of PLP_deC II at the whole-genome level, identified 16 PLP_deC II genes, and analyzed their gene structure, physicochemical properties, cis-acting elements, phylogenetic evolution, and gene expression patterns. Prokaryotic expression and enzyme activity assays revealed that OeAAD2 and OeAAD4 could catalyze the decarboxylation reaction of tyrosine and dopa, resulting in the formation of their respective amine compounds, but it did not catalyze phenylalanine and tryptophan. Which is an important step in the synthetic pathway of hydroxytyrosol and oleuropein. This finding established the foundational data at the molecular level for studying the functional aspects of the olive PLP_deC II gene family and provided essential gene information for genetic improvement of olive.

Gardenin A treatment attenuates inflammatory markers, synuclein pathology and deficits in tyrosine hydroxylase expression and improves cognitive and motor function in A53T-α-syn mice

Oxidative stress and neuroinflammation are widespread in the Parkinson's disease (PD) brain and contribute to the synaptic degradation and dopaminergic cell loss that result in cognitive impairment and motor dysfunction. The polymethoxyflavone Gardenin A (GA) has been shown to activate the NRF2-regulated antioxidant pathway and inhibit the NFkB-dependent pro-inflammatory pathway in a Drosophila model of PD. Here, we evaluate the effects of GA on A53T alpha-synuclein overexpressing (A53TSyn) mice. A53TSyn mice were treated orally for 4 weeks with 0, 25, or 100 mg/kg GA. In the fourth week, mice underwent behavioral testing and tissue was harvested for immunohistochemical analysis of tyrosine hydroxylase (TH) and phosphorylated alpha synuclein (pSyn) expression, and quantification of synaptic, antioxidant and inflammatory gene expression. Results were compared to vehicle-treated C57BL6J mice. Treatment with 100 mg/kg GA improved associative memory and decreased abnormalities in mobility and gait in A53TSyn mice. GA treatment also reduced pSyn levels in both the cortex and hippocampus and attenuated the reduction in TH expression in the striatum seen in A53Tsyn mice. Additionally, GA increased cortical expression of NRF2-regulated antioxidant genes and decreased expression of NFkB-dependent pro-inflammatory genes. GA was readily detectable in the brains of treated mice and modulated the lipid profile in the deep gray brain tissue of those animals. While the beneficial effects of GA on cognitive deficits, motor dysfunction and PD pathology are promising, future studies are needed to further fully elucidate the mechanism of action of GA, optimizing dosing and confirm these effects in other PD models.

Fluid and tissue biomarkers in Parkinson's disease: Immunodetection or seed amplification? Central or peripheral?

Over the last two decades there have been meaningful developments on biomarkers of neurodegenerative diseases, extensively (but not solely) focusing on their proteinopathic nature. Accordingly, in Alzheimer's disease determination of levels of total and phosphorylated tau (τ and p-τ, usually p-τ181) along with amyloid-beta1-42 (Aβ1-42) by immunodetection in cerebrospinal fluid (CSF) and currently even in peripheral blood, have been widely accepted and introduced to routine diagnosis. In the case of Parkinson's disease, α-synuclein as a potential biomarker (both for diagnosis and progression tracking) has proved more elusive under the immunodetection approach. In recent years, the emergence of the so-called seed amplification assays is proving to be a game-changer, with mounting evidence under different technical approaches and using a variety of biofluids or tissues, yielding promising diagnostic accuracies. Currently the least invasive but at once more reliable source of biosamples and techniques are being sought. Here we overview these advances.

A critical appraisal of blood-based biomarkers for Alzheimer's disease

Biomarkers that predict the clinical onset of Alzheimer's disease (AD) enable the identification of individuals in the early, preclinical stages of the disease. Detecting AD at this point may allow for more effective therapeutic interventions and optimized enrollment for clinical trials of novel drugs. The current biological diagnosis of AD is based on the AT(N) classification system with the measurement of brain deposition of amyloid-β (Aβ) ("A"), tau pathology ("T"), and neurodegeneration ("N"). Diagnostic cut-offs for Aβ1-42, the Aβ1-42/Aβ1-40 ratio, tau and hyperphosphorylated-tau concentrations in cerebrospinal fluid have been defined and may support AD clinical diagnosis. Blood-based biomarkers of the AT(N) categories have been described in the AD continuum. Cross-sectional and longitudinal studies have shown that the combination of blood biomarkers tracking neuroaxonal injury (neurofilament light chain) and neuroinflammatory pathways (glial fibrillary acidic protein) enhance sensitivity and specificity of AD clinical diagnosis and improve the prediction of AD onset. However, no international accepted cut-offs have been identified for these blood biomarkers. A kit for blood Aβ1-42/Aβ1-40 is commercially available in the U.S.; however, it does not provide a diagnosis, but simply estimates the risk of developing AD. Although blood-based AD biomarkers have a great potential in the diagnostic work-up of AD, they are not ready for the routine clinical use.

Comprehensive proteomics of CSF, plasma, and urine identify DDC and other biomarkers of early Parkinson's disease

Parkinson's disease (PD) starts at the molecular and cellular level long before motor symptoms appear, yet there are no early-stage molecular biomarkers for diagnosis, prognosis prediction, or monitoring therapeutic response. This lack of biomarkers greatly impedes patient care and translational research-L-DOPA remains the standard of care more than 50 years after its introduction. Here, we performed a large-scale, multi-tissue, and multi-platform proteomics study to identify new biomarkers for early diagnosis and disease monitoring in PD. We analyzed 4877 cerebrospinal fluid, blood plasma, and urine samples from participants across seven cohorts using three orthogonal proteomics methods: Olink proximity extension assay, SomaScan aptamer precipitation assay, and liquid chromatography-mass spectrometry proteomics. We discovered that hundreds of proteins were upregulated in the CSF, blood, or urine of PD patients, prodromal PD patients with DAT deficit and REM sleep behavior disorder or anosmia, and non-manifesting genetic carriers of LRRK2 and GBA mutations. We nominate multiple novel hits across our analyses as promising markers of early PD, including DOPA decarboxylase (DDC), also known as L-aromatic acid decarboxylase (AADC), sulfatase-modifying factor 1 (SUMF1), dipeptidyl peptidase 2/7 (DPP7), glutamyl aminopeptidase (ENPEP), WAP four-disulfide core domain 2 (WFDC2), and others. DDC, which catalyzes the final step in dopamine synthesis, particularly stands out as a novel hit with a compelling mechanistic link to PD pathogenesis. DDC is consistently upregulated in the CSF and urine of treatment-naïve PD, prodromal PD, and GBA or LRRK2 carrier participants by all three proteomics methods. We show that CSF DDC levels correlate with clinical symptom severity in treatment-naïve PD patients and can be used to accurately diagnose PD and prodromal PD. This suggests that urine and CSF DDC could be a promising diagnostic and prognostic marker with utility in both clinical care and translational research.

Parkinson's Disease Drug Therapies in the Clinical Trial Pipeline: 2024 Update

Background

For the past five years, our annual reports have been tracking the clinical development of new drug-based therapies for the neurodegenerative condition of Parkinson's disease (PD). These reviews have followed the progress both of "symptomatic treatments" (ST - improves/reduces symptoms of the condition) and "disease-modifying treatments" (DMT - attempts to delay/slow progression by addressing the underlying biology of PD). Efforts have also been made to further categorize these experimental treatments based on their mechanisms of action and class of drug.

Methods

A dataset of clinical trials for drug therapies in PD using trial data downloaded from the ClinicalTrials.gov online registry was generated. A breakdown analysis of all the studies that were active as of January 31st, 2024, was conducted. This analysis involved categorizing the trials based on both the mechanism of action (MOA) and the drug target.

Results

There were 136 active Phase 1-3 trials evaluating drug therapies for PD registered on ClinicalTrials.gov, as of January 31, 2024. Of these trials, 76 (56%) were classified as ST trials and 60 (44%) were designated DMT. More than half (58%) of the trials were in Phase 2 testing stage, followed by Phase 1 (30%) and Phase 3 (12%). 35 of the trials were registered since our last report, with the remaining 101 trials appearing in at least one earlier report.

Conclusions

The drug development pipeline for PD remains in a robust state with a wide variety of approaches being developed and evaluated in Phase 1 and 2. Yet again, however, only a limited number of DMTs are transitioning to Phase 3.

Biofluid Markers and Tissue Biopsies Analyses for the Prodromal and Earliest Phase of Parkinson's Disease

The recent development of new methods to detect misfolded α-synuclein (αSyn) aggregates in biofluids and tissue biopsies in the earliest Parkinson's disease (PD) phases is dramatically challenging the biological definition of PD. The αSyn seed amplification methods in cerebrospinal fluid (CSF) showed high sensitivity and specificity for early diagnosis of PD and Lewy bodies disorders. Several studies in isolated REM sleep behavior disorders and other at-risk populations also demonstrated a high prevalence of CSF αSyn positivity and its potential value in predicting the phenoconversion to clinically manifested diseases. Growing evidence exists for αSyn aggregates in olfactory mucosa, skin, and other tissues in subjects with PD or at-risk subjects. DOPA decarboxylase and numerous other candidates have been additionally proposed for either diagnostic or prognostic purposes in earliest PD phases. The newly described αSyn detection in blood, through its quantification in neuronally-derived exosome vesicles, represents a technical challenge that could open a new scenario for the biological diagnosis of PD. Despite this growing evidence in the field, most of method of αSyn detection and markers still need to be validated in ongoing longitudinal studies through an accurate assessment of different prodromal disease subtypes and scenarios before being definitively implemented in clinical settings.

Expression of Human L-Dopa Decarboxylase (DDC) under Conditions of Oxidative Stress

Oxidative stress is known to influence mRNA levels, translation, and proteolysis. The importance of oxidative stress has been demonstrated in several human diseases, including neurodegenerative disorders. L-Dopa decarboxylase (DDC) is the enzyme that converts L-Dopa to dopamine (DA). In spite of a large number of studies, little is known about the biological significance of the enzyme under physiological and pathological conditions. Here, we investigated the relationship between DDC expression and oxidative stress in human neural and non-neural cells. Oxidative stress was induced by treatment with H2O2. Our data indicated that mRNA and protein expression of DDC was enhanced or remained stable under conditions of ROS induction, despite degradation of total RNA and increased cytotoxicity and apoptosis. Moreover, DDC silencing caused an increase in the H2O2-induced cytotoxicity. The current study suggests that DDC is involved in the mechanisms of oxidative stress.

Tracking neurodegenerative diseases in biofluids: Combining pathology and pathophysiology markers is the way

Biofluid biomarkers to track neurodegenerative diseases in vitam are urgently needed. Recent studies show that large-scale proteomic analyses based on the proximity extension assay may reveal novel biomarkers reflecting disease pathophysiology. Such biomarkers will likely express their maximal clinical value when used in combination with pathology-specific biomarkers.

Gardenin A improves cognitive and motor function in A53T-α-syn mice

Oxidative stress and neuroinflammation are widespread in the Parkinson's disease (PD) brain and contribute to the synaptic degradation and dopaminergic cell loss that result in cognitive impairment and motor dysfunction. The polymethoxyflavone Gardenin A (GA) has been shown to activate the NRF2-regulated antioxidant pathway and inhibit the NFkB-dependent pro-inflammatory pathway in a Drosophila model of PD. Here, we evaluate the effects of GA on A53T alpha-synuclein overexpressing (A53TSyn) mice. A53TSyn mice were treated orally for 4 weeks with 0, 25, or 100 mg/kg GA. In the fourth week, mice underwent behavioral testing and tissue was harvested for immunohistochemical analysis of tyrosine hydroxylase (TH) and phosphorylated alpha synuclein (pSyn) expression, and quantification of synaptic, antioxidant and inflammatory gene expression. Results were compared to vehicle-treated C57BL6 mice. Treatment with 100 mg/kg GA improved associative memory and decreased abnormalities in mobility and gait in A53TSyn mice. GA treatment also reduced cortical and hippocampal levels of pSyn and attenuated the reduction in TH expression in the striatum. Additionally, GA increased cortical expression of NRF2-regulated antioxidant genes and decreased expression of NFkB-dependent pro-inflammatory genes. GA was readily detectable in the brains of treated mice and modulated the lipid profile in the deep gray brain tissue of those animals. While the beneficial effects of GA on cognitive deficits, motor dysfunction and PD pathology are promising, future studies are needed to further fully elucidate the mechanism of action of GA, optimizing dosing and confirm these effects in other PD models.

Significance Statement

The polymethoxyflavone Gardenin A can improve cognitive and motor function and attenuate both increases in phosphorylated alpha synuclein and reductions in tyrosine hydroxylase expression in A53T alpha synuclein overexpressing mice. These effects may be related to activation of the NRF2-regulated antioxidant response and downregulation of NFkB-dependent inflammatory response by Gardenin A in treated animals. The study also showed excellent brain bioavailability of Gardenin A and modifications of the lipid profile, possibly through interactions between Gardenin A with the lipid bilayer, following oral administration. The study confirms neuroprotective activity of Gardenin A previously reported in toxin induced Drosophila model of Parkinson's disease.