Biomarker For Parkinson's Disease Research Articles

Lab-made disposable screen-printed electrochemical sensors and immunosensors modified with Pd nanoparticles for Parkinson's disease diagnostics.

Anew conductive ink based on the addition of carbon black to a poly(vinyl alcohol) matrix is developed and investigated for electrochemical sensing and biosensing applications. The produced devices were characterized using morphological and electrochemical techniques and modified with Pd nanoparticles to enhance electrical conductivity and reaction kinetics. With the aid of chemometrics, the parameters for metal deposition were investigated and the sensor was applied tothe determination of Parkinson's disease biomarkers, specifically epinephrine and α-synuclein. A linear behavior was obtained in the range 0.75 to 100μmol L-1 of the neurotransmitter, and the device displayed a limit of detection (LOD) of 0.051μmol L-1. The three-electrode system was then tested using samples of synthetic cerebrospinal fluid. Afterward, the device was modified with specific antibodies to quantify α-synuclein using electrochemical impedance spectroscopy. In phosphate buffer, a linear range was obtained for α-synuclein concentrations from 1.5 to 15μgmL-1, with a calculated LOD of 0.13μgmL-1. The proposed immunosensor was also applied to blood serum samples, and, in this case, the linear range was observed from 6.0 to 100.5μgmL-1 of α-synuclein, with a LOD = 1.3µgmL-1. Both linear curves attend the range for the real diagnosis, demonstrating its potential application to complex matrices.

Longitudinal prognosis of Parkinson’s outcomes using causal connectivity

Despite the prevalence of Parkinson’s disease (PD), there are no clinically-accepted neuroimaging biomarkers to predict the trajectory of motor or cognitive decline or differentiate Parkinson’s disease from atypical progressive parkinsonian diseases. Since abnormal connectivity in the motor circuit and basal ganglia have been previously shown as early markers of neurodegeneration, we hypothesize that patterns of interregional connectivity could be useful to form patient-specific predictive models of disease state and of PD progression. We use fMRI data from subjects with Multiple System Atrophy (MSA), Progressive Supranuclear Palsy (PSP), idiopathic PD, and healthy controls to construct predictive models for motor and cognitive decline and differentiate between the four subgroups. Further, we identify the specific connections most informative for progression and diagnosis. When predicting the one-year progression in the MDS-UPDRS-III1*1*A summary of all acronyms used in this paper is presented in Appendix A. Supplementary Data. and Montreal Cognitive assessment (MoCA), we achieve new state-of-the-art mean absolute error performance. Additionally, the balanced accuracy we achieve in the diagnosis of PD, MSA, PSP, versus healthy controls surpasses that attained in most clinics, underscoring the relevance of the brain connectivity features. Our models reveal the connectivity between deep nuclei, motor regions, and the thalamus as the most important for prediction. Collectively these results demonstrate the potential of fMRI connectivity as a prognostic biomarker for PD and increase our understanding of this disease.

Lysosomal Polygenic Burden Drives Cognitive Decline in Parkinson's Disease with Low Alzheimer Risk.

Genetics influence cognitive progression in Parkinson's disease, possibly through mechanisms related to Lewy and Alzheimer's disease pathology. Lysosomal polygenic burden has recently been linked to more severe Lewy pathology post mortem. To assess the influence of lysosomal polygenic burden on cognitive progression in Parkinson's disease patients with low Alzheimer's disease risk. Using Cox regression we assessed association between lysosomal polygenic scores and time to Montreal Cognitive Assessment score ≤ 21 in the Parkinson's Progression Markers Initiative cohort (n = 374), with replication in data from the Parkinson's Disease Biomarker Program (n = 777). Patients were stratified by Alzheimer's disease polygenic risk. The lysosomal polygenic score was associated with faster progression of cognitive decline in patients with low Alzheimer's disease risk in both datasets (P = 0.0032 and P = 0.0054, respectively). Our study supports complex interplay between genetics and neuropathology in Parkinson's disease-related cognitive impairment, emphasizing the role of lysosomal polygenic burden. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Evaluation of Parkinson's disease early diagnosis using single-channel EEG features and auditory cognitive assessment.

Parkinson's disease (PD) often presents with subtle early signs, making diagnosis difficult. F-DOPA PET imaging provides a reliable measure of dopaminergic function and is a primary tool for early PD diagnosis. This study aims to evaluate the ability of machine-learning (ML) extracted EEG features to predict F-DOPA results and distinguish between PD and non-PD patients. These features, extracted using a single-channel EEG during an auditory cognitive assessment, include EEG feature A0 associated with cognitive load in healthy subjects, and EEG feature L1 associated with cognitive task differentiation. Participants in this study are comprised of cognitively healthy patients who had undergone an F-DOPA PET scan as a part of their standard care (n = 32), and cognitively healthy controls (n = 20). EEG data collected using the Neurosteer system during an auditory cognitive task, was decomposed using wavelet-packet analysis and machine learning methods for feature extraction. These features were used in a connectivity analysis that was applied in a similar manner to fMRI connectivity. A preliminary model that relies on the features and their connectivity was used to predict initially unrevealed F-DOPA test results. Then, generalized linear mixed models (LMM) were used to discern between PD and non-PD subjects based on EEG variables. The prediction model correctly classified patients with unrevealed scores as positive F-DOPA. EEG feature A0 and the Delta band revealed distinct activity patterns separating between study groups, with controls displaying higher activity than PD patients. In controls, EEG feature L1 showed variations between resting state and high-cognitive load, an effect lacking in PD patients. Our findings exhibit the potential of single-channel EEG technology in combination with an auditory cognitive assessment to distinguish positive from negative F-DOPA PET scores. This approach shows promise for early PD diagnosis. Additional studies are needed to further verify the utility of this tool as a potential biomarker for PD.

Metabolomic analysis of serum short-chain fatty acid concentrations in a mouse of MPTP-induced Parkinson's disease after dietary supplementation with branched-chain amino acids.

The gut microbiota and microbial metabolites influence the enteric nervous system and the central nervous system via the microbial-gut-brain axis. Increasing body of evidence suggests that disturbances in the metabolism of peripheral branched-chain amino acids (BCAAs) can contribute to the development of neurodegenerative diseases through neuroinflammatory signaling. Preliminary research has shown that longitudinal changes in serum amino acid levels in mouse models of Parkinson's disease (PD) are negatively correlated with disease progression. Therefore, the aim of the present study was to determine the changes in serum levels of short-chain fatty acids (SCFAs) in a mouse model of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD after dietary BCAA supplementation. In our research, gas chromatography-mass spectrometry was used to detect serum SCFA concentrations. The data were then analyzed with principal component analysis and orthogonal partial least squares discriminant analysis. Finally, the correlations of serum SCFA levels with gut and motor function in MPTP-induced PD mice were explored. Propionic acid, acetic acid, butyric acid, and isobutyric acid concentrations were elevated in MPTP + H-BCAA mice compared with MPTP mice. Propionic acid concentration was increased the most, while the isovaleric acid concentration was decreased. Propionic acid concentration was positively correlated with fecal weight and water content and negatively correlated with the pole-climbing duration. In conclusion, these results not only suggest that propionic acid may be a potential biomarker for PD, but also indicate the possibility that PD may be treated by altering circulating levels of SCFA.

Selenium and selenoproteins role in Parkinson’s disease: Is there a link between selenoproteins and accumulated alpha-synuclein?

BackgroundWhile Parkinson's disease (PD) etiology is not clear yet, accumulated alpha-synuclein is proposed to induce neurodegeneration. Selenium (Se) and its functional proteins play a key role in aggregation of misfolded proteins. However, their implications in neurodegenerative process are unclear. AimDiagnosing Se and selenoprotein P (SelP), selenoprotein S (SelS) proportions in serum of PD patients to compare with healthy controls, whether the changes in their concentration could be a biomarker for PD. MethodsSe concentration was investigated in 30 PD patients and 30 controls using atomic absorption spectrometry. Also, alpha-Synuclein, SelP, and SelS levels were evaluated by ELISA. The parameters were compared in PD patients and controls. Also, the variations within the case group according to their age, disorder stage, and drug administration were evaluated. ResultsPD subjects had higher Se concentration. The mean SelP in PD patients was lower from controls, whilst SelS levels were higher. Also, the concentration of alpha-synuclein was higher in PD patients. However, age, stage (except UPDRS III), and disorder duration had no influence on the Se and selenoproteins level, whilst there was a direct association between alpha-synuclein levels and disorder stage. Also, alpha-synuclein proportions in subjects using levodopa was significantly higher. ConclusionOur results suggest that serum levels of Se and SelP could be a biomarker or risk factor for PD. Although SelS interferes to reduce aggregated proteins, its pathway in PD is not clearly understood. Future studies could focus on how SelS can reduce on alpha-synuclein aggregation. Thus, other studies should be performed on this issue to induce the selenoproteins in PD.

Neuromuscular assessment of force development, postural, and gait performance under cognitive-motor dual-tasking in healthy older adults and people with early Parkinson's disease: Study protocol for a cross-sectional Mobile Brain/Body Imaging (MoBI) study.

Neuromuscular dysfunction is common in older adults and more pronounced in neurodegenerative diseases. In Parkinson's disease (PD), a complex set of factors often prevents the effective performance of activities of daily living that require intact and simultaneous performance of the motor and cognitive tasks. The cross-sectional study includes a multifactorial mixed-measure design. Between-subject factor grouping the sample will be Parkinson's Disease (early PD vs. healthy). The within-subject factors will be the task complexity (single- vs. dual-task) in each motor activity, i.e., overground walking, semi-tandem stance, and isometric knee extension, and a walking condition (wide vs. narrow lane) will be implemented for the overground walking activity only. To study dual-task (DT) effects, in each motor activity participants will be given a secondary cognitive task, i.e., a visual discrimination task for the overground walking, an attention task for the semi-tandem, and mental arithmetic for the isometric extension. Analyses of DT effects and underlying neuronal correlates will focus on both gait and cognitive performance where applicable. Based on an a priori sample size calculation, a total N = 42 older adults (55-75 years) will be recruited. Disease-specific changes such as laterality in motor unit behavior and cortical control of movement will be studied with high-density surface electromyography and electroencephalography during static and dynamic motor activities, together with whole-body kinematics. This study will be one of the first to holistically address early PD neurophysiological and neuromuscular patterns in an ecologically valid environment under cognitive-motor DT conditions of different complexities. The outcomes of the study aim to identify the biomarker for early PD either at the electrophysiological, muscular or kinematic level or in the communication between these systems. ClinicalTrials.Gov, NCT05477654. This study was approved by the Medical Ethical Committee (106/2021).

Severity Classification Using Dynamic Time Warping-Based Voice Biomarkers for Patients With COVID-19: Feasibility Cross-Sectional Study.

In Japan, individuals with mild COVID-19 illness previously required to be monitored in designated areas and were hospitalized only if their condition worsened to moderate illness or worse. Daily monitoring using a pulse oximeter was a crucial indicator for hospitalization. However, a drastic increase in the number of patients resulted in a shortage of pulse oximeters for monitoring. Therefore, an alternative and cost-effective method for monitoring patients with mild illness was required. Previous studies have shown that voice biomarkers for Parkinson disease or Alzheimer disease are useful for classifying or monitoring symptoms; thus, we tried to adapt voice biomarkers for classifying the severity of COVID-19 using a dynamic time warping (DTW) algorithm where voice wavelets can be treated as 2D features; the differences between wavelet features are calculated as scores. This feasibility study aimed to test whether DTW-based indices can generate voice biomarkers for a binary classification model using COVID-19 patients' voices to distinguish moderate illness from mild illness at a significant level. We conducted a cross-sectional study using voice samples of COVID-19 patients. Three kinds of long vowels were processed into 10-cycle waveforms with standardized power and time axes. The DTW-based indices were generated by all pairs of waveforms and tested with the Mann-Whitney U test (α<.01) and verified with a linear discrimination analysis and confusion matrix to determine which indices were better for binary classification of disease severity. A binary classification model was generated based on a generalized linear model (GLM) using the most promising indices as predictors. The receiver operating characteristic curve/area under the curve (ROC/AUC) validated the model performance, and the confusion matrix calculated the model accuracy. Participants in this study (n=295) were infected with COVID-19 between June 2021 and March 2022, were aged 20 years or older, and recuperated in Kanagawa prefecture. Voice samples (n=110) were selected from the participants' attribution matrix based on age group, sex, time of infection, and whether they had mild illness (n=61) or moderate illness (n=49). The DTW-based variance indices were found to be significant (P<.001, except for 1 of 6 indices), with a balanced accuracy in the range between 79% and 88.6% for the /a/, /e/, and /u/ vowel sounds. The GLM achieved a high balance accuracy of 86.3% (for /a/), 80.2% (for /e/), and 88% (for /u/) and ROC/AUC of 94.8% (95% CI 90.6%-94.8%) for /a/, 86.5% (95% CI 79.8%-86.5%) for /e/, and 95.6% (95% CI 92.1%-95.6%) for /u/. The proposed model can be a voice biomarker for an alternative and cost-effective method of monitoring the progress of COVID-19 patients in care.

Profiling Analysis of Tryptophan Metabolites in the Urine of Patients with Parkinson's Disease Using LC-MS/MS.

Although Parkinson's disease (PD) is a representative neurodegenerative disorder and shows characteristic motor impediments, the pathophysiological mechanisms and treatment targets for PD have not yet been clearly identified. Since several tryptophan metabolites produced by gut microbiota could pass the blood-brain barrier and, furthermore, might influence the central nervous system, tryptophan metabolites within the indole, kynurenine, and serotonin metabolic pathways might be the most potent targets for PD development. Furthermore, most metabolites are circulated via the blood, play roles in and/or are metabolized via the host organs, and finally are excreted into the urine. Therefore, profiling the overall tryptophan metabolic pathways in urine samples of patients with PD is important to understanding the pathological mechanisms, finding biomarkers, and discovering therapeutic targets for PD. However, the development of profiling analysis based on tryptophan metabolism pathways in human urine samples is still challenging due to the wide physiological ranges, the varied signal response, and the structural diversity of tryptophan metabolites in complicated urine matrices. In this study, an LC-MS/MS method was developed to profile 21 tryptophan metabolites within the indole, kynurenine, and serotonin metabolic pathways in human urine samples using ion-pairing chromatography and multiple reaction monitoring determination. The developed method was successfully applied to urine samples of PD patients (n = 41) and controls (n = 20). Further, we investigated aberrant metabolites to find biomarkers for PD development and therapeutic targets based on the quantitative results. Unfortunately, most tryptophan metabolites in the urine samples did not present significant differences between control and PD patients, except for indole-3-acetic acid. Nonetheless, indole-3-acetic acid was reported for the first time for its aberrant urinary levels in PD patients and tentatively selected as a potential biomarker for PD. This study provides accurate quantitative results for 21 tryptophan metabolites in biological samples and will be helpful in revealing the pathological mechanisms of PD development, discovering biomarkers for PD, and further providing therapeutic targets for various PD symptoms. In the near future, to further investigate the relationship between gut microbial metabolites and PD, we will employ studies on microbial metabolites using plasma and stool samples from control and PD patients.

Mitochondrial Dysfunction in Dopaminergic Neurons Derived from Patients with LRRK2- and SNCA-Associated Genetic Forms of Parkinson's Disease.

Parkinson's disease (PD) is the second most common neurodegenerative disease. Some cases of PD may be caused by genetic factors, among which mutations in the LRRK2 and SNCA genes play an important role. To develop effective neuroprotective strategies for PD, it is important to diagnose the disease at the earliest stages of the neurodegenerative process. Therefore, the detection of diagnostic and prognostic markers of Parkinson's disease (PD) is an urgent medical need. Advances in induced pluripotent stem cell (iPSC) culture technology provide new opportunities for the search for new biomarkers of PD and its modeling in vitro. In our work, we used a new technology for multiplex profiling of gene expression using barcoding on the Nanostring platform to assess the activity of mitochondrial genes on iPSC-derived cultures of dopaminergic neurons obtained from patients with LRRK2- and SNCA-associated genetic forms PD and a healthy donor. Electron microscopy revealed ultrastructural changes in mitochondria in both LRRK2 and SNCA mutant cells, whereas mitochondria in cells from a healthy donor were normal. In a culture with the SNCA gene mutation, the ratio of the area occupied by mitochondria to the total area of the cytoplasm was significantly lower than in the control and in the line with the LRRK2 gene mutation. Transcriptome analysis of 105 mitochondria proteome genes using the Nanostring platform revealed differences between the diseased and normal cells in the activity of genes involved in respiratory complex function, the tricarboxylic acid cycle, ATP production, mitochondria-endoplasmic reticulum interaction, mitophagy, regulation of calcium concentration, and mitochondrial DNA replication.

Using 18F-AV-133 VMAT2 PET Imaging to Monitor Progressive Nigrostriatal Degeneration in Parkinson Disease.

There are limited validated biomarkers in Parkinson disease (PD) which substantially hinders the ability to monitor disease progression and consequently measure the efficacy of disease-modifying treatments. Imaging biomarkers, such as vesicular monoamine transporter type 2 (VMAT2) PET, enable enhanced diagnostic accuracy and detect early neurodegenerative changes associated with prodromal PD. This study sought to assess whether 18F-AV-133 VMAT2 PET is sensitive enough to monitor and quantify disease progression over a 2-year window. 18F-AV-133 PET scans were performed on participants with PD and REM sleep behavior disorder (RBD) and neurologic controls (NC). All participants were scanned twice ∼26 months apart. Regional tracer retention was calculated with a primary visual cortex reference region and expressed as the standard uptake volume ratio. Regions of interest included caudate, anterior, and posterior putamen. At the time of scanning, participants underwent clinical evaluation including UPDRSMOTOR test, Sniffin' Sticks, and Hospital Anxiety and Depression Score. Over the 26-month interval, a significant decline in PET signal was observed in all 3 regions in participants with PD (N = 26) compared with NC (N = 12), consistent with a decrease in VMAT2 level and ongoing neurodegeneration. Imaging trajectory calculations suggest that the neurodegeneration in PD occurs over ∼33 years [CI: 27.2-39.5], with ∼10.5 years [CI: 9.1-11.3] of degeneration in the posterior putamen before it becomes detectable on a VMAT2 PET scan, a further ∼6.5 years [CI: 1.6-12.7] until symptom onset, and a further ∼3 years [CI: 0.3-8.7] until clinical diagnosis. Over a 2-year period, 18F-AV-133 VMAT2 PET was able to detect progression of nigrostriatal degeneration in participants with PD, and it represents a sensitive tool to identify individuals at risk of progression to PD, which are currently lacking using clinical readouts. Trajectory models propose that there is nigrostriatal degeneration occurring for 20 years before clinical diagnosis. These data demonstrate that VMAT2 PET provides a sensitive measure to monitor neurodegenerative progression of PD which has implications for PD diagnostics and subsequently clinical trial patient stratification and monitoring. This study provides Class IV evidence that VMAT2 PET can detect patients with Parkinson disease and quantify progression over a 2-year window.

LncRNA MEG8 ameliorates Parkinson's disease neuro-inflammation through miR-485-3p/FBXO45 axis.

Studies suggest that LncRNA maternally expressed 8, small nucleolar RNA host gene (MEG8) contributes to inflammatory regulation, while the function and potential mechanisms of MEG8 in Parkinson's disease (PD) are unknown. This study aimed to assess the clinical value and biological function of MEG8 in PD. One hundred and two PD patients, eighty-six AD patients, and eighty healthy controls were enrolled in this study. Lipopolysaccharide (LPS)-induced microglia BV2 constructs an in vitro cell model. RT-qPCR was conducted to quantify the levels of MEG8, miR-485-3p, and FBXO45 in serum and cells. ROC curve was employed to examine the diagnostic value of MEG8 in PD. Serum and cellular pro-inflammatory factor secretion were quantified by ELISA. Dual-luciferase reporter and RIP assay to validate the targeting relationship between miR-485-3p and FBXO45. MEG8 and FBXO45 were significantly decreased in the serum of PD patients and LPS-induced bv2, while miR-485-3p was increased (P < 0.05). ROC curve confirmed that serum MEG8 has high sensitivity and specificity to identify PD patients from healthy controls and AD patients, respectively. Elevated MEG8 alleviated LPS-induced inflammatory factor overproduction compared with LPS-induced BV2 (P < 0.05), but this alleviating effect was eliminated by miR-485-3p (P < 0.05). The LPS-induced inflammatory response was suppressed by the low expression of miR-485-3p but significantly reversed by silencing of FBXO45. MEG8 was a sponge for miR-485-3p and inhibited its levels and promoted FBXO45 expression (P < 0.05). Elevated MEG8 is a potential diagnostic biomarker for PD and may mitigate inflammatory damage in PD via the miR-485-3p/FBXO45 axis.

Central retina thickness measured with spectral-domain optical coherence tomography in Parkinson disease: A meta-analysis.

Optical coherence tomography (OCT) can detect visual alterations associated with Parkinson disease, such as damage to the retinal nerve fiber layer or changes in retinal vasculature. Macula thinning in association with Parkinson disease (PD) remains controversial. Therefore, we conducted a meta-analysis to investigate the central retina thickness in PD measured using spectral-domain OCT (SD-OCT). We searched PubMed and the Excerpta Medica database to identify studies that compared macular thickness between patients with PD and healthy controls published before July 31, 2021. A random-effects model was used to examine PD-associated changes in macular thickness. Meta-regression analysis was performed by assessing heterogeneity, publication bias, and study quality. Thirty-two studies with a cross-sectional design were selected, including 2118 patients with PD and 2338 controls. We identified significant differences in the thickness of the ganglion cell-inner plexiform layer (standardized mean difference [SMD], -0.41; 95% confidence interval [CI], -0.66 to -0.16; I2 = 80%), ganglion cell complex (SMD, -0.33; 95% CI, -0.50 to -0.17; I2 = 0%), and of all inner and outer sectors of the macula (SMD range, -0.21 to -0.56; all P < .05) between patients with PD and controls. These results corroborate the increased prevalence of changes in OCT measures in individuals with PD, highlighting the efficacy of SD-OCT-determined macular thickness as a biomarker for PD. Our findings may provide helpful guidelines for clinicians in rapidly evolving areas of PD diagnosis.

Inflammatory Blood Biomarkers Are Associated with Long-Term Clinical Disease Severity in Parkinson's Disease.

An altered immune response has been identified as a pathophysiological factor in Parkinson's disease (PD). We aimed to identify blood immunity-associated proteins that discriminate PD from controls and that are associated with long-term disease severity in PD patients. Immune response-derived proteins in blood plasma were measured using Proximity Extension Technology by OLINK in a cohort of PD patients (N = 66) and age-matched healthy controls (N = 52). In a selection of 30 PD patients, we evaluated changes in protein levels 7-10 years after the baseline and assessed correlations with motor and cognitive assessments. Data from the Parkinson's Disease Biomarkers Program (PDBP) cohort and the Parkinson's Progression Markers Initiative (PPMI) cohort were used for independent validation. PD patients showed an altered immune response compared to controls based on a panel of four proteins (IL-12B, OPG, CXCL11, and CSF-1). The expression levels of five inflammation-associated proteins (CCL23, CCL25, TNFRSF9, TGF-alpha, and VEGFA) increased over time in PD and were partially associated with more severe motor and cognitive symptoms at follow-up. Increased CCL23 levels were associated with cognitive decline and the APOE4 genotype. Our findings provide further evidence for an altered immune response in PD that is associated with disease severity in PD over a long period of time.

The association of serum neurofilament light chains with early symptoms related to Parkinson's disease: A cross-sectional study

Neurofilament light chains (NfL), released with neural axon injury, is considered as a potential biomarker for Parkinson's disease (PD). The relationship between NfL and PD has been studied mainly in diagnosed patients. Few large-scale studies analyze the association between NfL levels and multiple non-motor symptoms linked to early PD in the general population. Therefore, this study aims to determine the association of NfL with early symptoms of PD, and effectively respond to the development of early symptoms of PD. We examined the relationship between serum NfL and early non-motor symptoms of PD (smell dysfunction, sleep problems, cognitive function) and serum Klotho levels in the general population using data from the 2013–2014 National Health and Nutrition Examination Survey (NHANES). The relationship between serum NfL and early symptoms of PD in 1125 participants was analyzed by multiple linear regression and logistic regression models. The results showed a significant association between serum NfL and early symptoms of PD. There was a significant positive correlation between NfL and smell dysfunction, short sleep and long sleep. There was a significant negative correlation between NfL and Klotho levels and cognitive function test results. Further, we observed gender and age differences in the association of NfL with early symptoms of PD. Our study demonstrate that elevated serum NfL levels are positively associated with an increased risk of early PD-related symptoms, suggesting that serum NfL can be a promising biomarker for early PD.

Increased diversity of Malassezia species on the skin of Parkinson's disease patients.

Parkinson's disease (PD) is characterized by motor disorders and the composition of Lewy bodies (LBs) in the substantia nigra. Due to the lack of a definitive biomarker, the current treatments do not modify the progression of PD. Recently, researchers revealed lipid dysregulation and some potential volatile biomarkers of PD related to a unique odor from PD patients by metabolomics of sebum, which is supposed to cause a potential change for skin microflora. In this study, we identified the 4 Malassezia species in PD patients and compared them with healthy controls. We collected 95 sebum samples (47 PDs and 48 Controls) by cotton swabs and extracted the DNA. The identification of Malassezia species was performed by Nested PCR. Specific primers for each species were used to amplify corresponding yeasts in each sample. M. restricta and M. globosa are the most common species for both groups. The prevalence of M. slooffiae and M. sympodialis were significantly higher in the PD group compared with controls (63.8% vs. 29.1 and 74.5% vs. 54.2% respectively), the binary logistic regression model further indicated that M. slooffiae (OR = 9.358, p < 0.001) was associated with PD. Moreover, the diversity of Malassezia species was significantly greater (3.5 vs. 2.9 species per individual, p = 0.002) in the PD group. Based on our results, we preliminarily observed a change in Malassezia species incidence and diversity on the skin of PD patients, which could be associated with lipid dysregulation; meanwhile, it might also be a noninvasive biomarker for PD.

Longitudinal dysregulation of long non-coding RNAs in Parkinson's disease.

Long non-coding RNAs (lncRNAs) have been suggested as potential biomarkers for Parkinson's disease (PD). This study aimed to identify blood-based lncRNA transcripts that are dysregulated in PD over time and could serve as peripheral biomarkers. Using RNA-sequencing data from the Parkinson's Progression Markers Initiative, differential expression between case and control groups at five different time points was detected, and pathway analysis was conducted. Seven transcripts, not previously linked to PD, were consistently dysregulated across all time points, while PD-linked lncRNAs were dysregulated at some but not all time points. Pathway analysis highlighted pathways, known to be affected in PD. This suggested that dysregulated lncRNA transcripts could play a role in PD pathogenesis by affecting well-known PD pathways and highlighted their potential as longitudinal biomarkers for PD. Further studies are needed to validate these findings and explore the potential use of identified lncRNAs as diagnostic and therapeutic targets.

Evaluation of ferritin and TfR level in plasma neural-derived exosomes as potential markers of Parkinson's disease.

Early diagnosis of Parkinson's disease (PD) remains challenging. It has been suggested that abnormal brain iron metabolism leads to excessive iron accumulation in PD, although the mechanism of iron deposition is not yet fully understood. Ferritin and transferrin receptor (TfR) are involved in iron metabolism, and the exosome pathway is one mechanism by which ferritin is transported and regulated. While the blood of healthy animals contains a plentiful supply of TfR-positive exosomes, no studies have examined ferritin and TfR in plasma neural-derived exosomes. Plasma exosomes were obtained from 43 patients with PD and 34 healthy controls. Neural-derived exosomes were isolated with anti-human L1CAM antibody immunoabsorption. Transmission electron microscopy and western blotting were used to identify the exosomes. ELISAs were used to quantify ferritin and TfR levels in plasma neural-derived exosomes of patients with PD and controls. Receivers operating characteristic (ROC) curves were applied to map the diagnostic accuracy of ferritin and TfR. Independent predictors of the disease were identified using logistic regression models. Neural-derived exosomes exhibited the typical exosomal morphology and expressed the specific exosome marker CD63. Ferritin and TfR levels in plasma neural-derived exosomes were significantly higher in patients with PD than controls (406.46 ± 241.86 vs. 245.62 ± 165.47 ng/μg, P = 0.001 and 1728.94 ± 766.71 vs. 1153.92 ± 539.30 ng/μg, P < 0.001, respectively). There were significant positive correlations between ferritin and TfR levels in plasma neural-derived exosomes in control group, PD group and all the individuals (rs = 0.744, 0.700, and 0.752, respectively). The level of TfR was independently associated with the disease (adjusted odds ratio 1.002; 95% CI 1.000-1.003). ROC performances of ferritin, TfR, and their combination were moderate (0.730, 0.812, and 0.808, respectively). However, no relationship was found between the biomarkers and disease progression. It is hypothesized that ferritin and TfR in plasma neural-derived exosomes may be potential biomarkers for PD, and that they may participate in the mechanism of excessive iron deposition in PD.

Identification of diagnostic and prognostic biomarkers of PD using a multiplex proteomics approach

Given the complexity of Parkinson's disease (PD), achieving acceptable diagnostic and prognostic accuracy will require the support of a panel of diverse biomarkers. We used Proximity extension assays to measure a panel of 92 proteins in CSF of 120 newly diagnosed PD patients and 45 control subjects without neurological disease. From 75 proteins detectable in the CSF of >90% of the subjects, regularized regression analysis identified four proteins (β-NGF, CD38, tau and NCAN) as downregulated in newly diagnosed PD patients (age at diagnosis 67.2 ± 9.4 years) compared to controls (age 65.4 ± 10.9 years). Higher tau (β −0.82 transformed MMSE points/year, 95% CI −1.37 to −0.27, P = 0.005) was also linked to faster cognitive decline over the first ten years after PD diagnosis. These findings provide insights into multiple aspects of PD pathophysiology and may serve as the foundation for identifying new biomarkers and therapeutic targets.

Neuromuscular assessment of force development, postural, and gait performance under cognitive-motor dual-tasking in healthy older adults and early Parkinson's disease patients: Study protocol for a cross-sectional Mobile Brain/Body Imaging (MoBI) study

Background: Neuromuscular dysfunction is common in older adults and more pronounced in neurodegenerative diseases. In Parkinson's disease (PD), a complex set of factors often prevents the effective performance of activities of daily living that require intact and simultaneous performance of the motor and cognitive tasks. Methods: The cross-sectional study includes a multifactorial mixed-measure design. Between-subject factor grouping the sample will be Parkinson’s Disease (early PD vs. healthy). The within-subject factors will be the task complexity (single- vs. dual-task) in each motor activity, i.e., overground walking, semi-tandem stance, and isometric knee extension, and a walking condition (wide vs. narrow lane) will be implemented for the overground walking activity only. To study dual-task (DT) effects, in each motor activity participants will be given a secondary cognitive task, i.e., a visual discrimination task for the overground walking, an attention task for the semi-tandem, and mental arithmetic for the isometric extension. Analyses of DT effects and underlying neuronal correlates will focus on both gait and cognitive performance where applicable. Based on an a priori sample size calculation, a total N = 42 older adults (55-75 years) will be recruited. Disease-specific changes such as laterality in motor unit behavior and cortical control of movement will be studied with high-density surface electromyography and electroencephalography during static and dynamic motor activities, together with whole-body kinematics. Discussion: This study will be one of the first to holistically address early PD neurophysiological and neuromuscular patterns in an ecologically valid environment under cognitive-motor DT conditions of different complexities. The outcomes of the study aim to identify the biomarker for early PD either at the electrophysiological, muscular or kinematic level or in the communication between these systems. Clinical Trial Registration: ClinicalTrials.Gov, NCT05477654. This study was approved by the Medical Ethical Committee (106/2021).