Biomarker For Parkinson's Disease Research Articles

Brain-enriched miR-128: Reduced in exosomes from Parkinson's patient plasma, improves synaptic integrity, and prevents 6-OHDA mediated neuronal apoptosis.

Parkinson's disease (PD) is a progressive neurodegenerative disorder associated with the death of mid-brain dopaminergic neurons. Unfortunately, no effective cure or diagnostic biomarkers for PD are available yet. To address this, the present study focuses on brain-enriched small non-coding regulatory RNAs called microRNAs (miRNAs) that are released into the circulation packaged inside small extracellular vesicles called exosomes. We collected blood samples from PD patients and isolated exosomes from the plasma. qPCR-based detection revealed a particular neuron-enriched miR-128 to be significantly decreased in the patient-derived exosomes. Interestingly, a concomitant decreased expression of miR-128 was observed in the cellular models of PD. Fluorescent live cell imaging and flow-cytometry revealed that over-expression of miR-128 can prevent 6-OHDA-mediated mitochondrial superoxide production and induction of neuronal death respectively. This neuroprotective effect was found to be induced by miR-128-mediated inhibition of FoxO3a activation, a transcription factor involved in apoptosis. miR-128 over-expression also resulted in down-regulation of pro-apoptotic FoxO3a targets- FasL and PUMA, at both transcript and protein levels. Further downstream, miR-128 over-expression inhibited activation of caspases-8, -9 and -3, preventing both the intrinsic and extrinsic pathways of apoptosis. Additionally, over expression of miR-128 prevented down-regulation of synaptic proteins- Synaptophysin and PSD-95 and attenuated neurite shortening, thereby maintaining overall neuronal integrity. Thus, our study depicts the intracellular role of miR-128 in neuronal apoptosis and neurodegeneration and its implications as a biomarker being detectable in the circulating exosomes of PD patient blood. Thus, characterization of such exosomal brain-enriched miRNAs hold promise for effective detection and diagnosis of PD.

A computational approach based on weighted gene co-expression network analysis for biomarkers analysis of Parkinson's disease and construction of diagnostic model.

Parkinson's disease (PD) is a common age-related chronic neurodegenerative disease. There is currently no affordable, effective, and less invasive test for PD diagnosis. Metabolite profiling in blood and blood-based gene transcripts is thought to be an ideal method for diagnosing PD. In this study, the objective is to identify the potential diagnostic biomarkers of PD by analyzing microarray gene expression data of samples from PD patients. A computational approach, namely, Weighted Gene Co-expression Network Analysis (WGCNA) was used to construct co-expression gene networks and identify the key modules that were highly correlated with PD from the GSE99039 dataset. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was performed to identify the hub genes in the key modules with strong association with PD. The selected hub genes were then used to construct a diagnostic model based on logistic regression analysis, and the Receiver Operating Characteristic (ROC) curves were used to evaluate the efficacy of the model using the GSE99039 dataset. Finally, Reverse Transcription-Polymerase Chain Reaction (RT-PCR) was used to validate the hub genes. WGCNA identified two key modules associated with inflammation and immune response. Seven hub genes, LILRB1, LSP1, SIPA1, SLC15A3, MBOAT7, RNF24, and TLE3 were identified from the two modules and used to construct diagnostic models. ROC analysis showed that the diagnostic model had a good diagnostic performance for PD in the training and testing datasets. Results of the RT-PCR experiments showed that there were significant differences in the mRNA expression of LILRB1, LSP1, and MBOAT7 among the seven hub genes. The 7-gene panel (LILRB1, LSP1, SIPA1, SLC15A3, MBOAT7, RNF24, and TLE3) will serve as a potential diagnostic signature for PD.

Intranasal delivery of mitochondrial protein humanin rescues cell death and promotes mitochondrial function in Parkinson's disease.

Rationale: Mitochondrial dysfunction is a key factor in the pathogenesis of Parkinson's disease (PD). Accordingly, many aspects of mitochondrial function have been studied as a putative therapeutic target. Here we present a novel strategy to promote mitochondrial function and protect against Parkinson's disease by the peptide encoded within mitochondrial genome, mitochondria-derived peptide (MDP) humanin (HN). Methods: To test humanin as a potential biomarker in PD, we measured protein levels of circulating humanin from the plasma of PD patients and transgenic or neurotoxic mouse models of PD. Next, we aimed to identify whether HN peptide treatment can regulate its activity or expression. Using mouse models of PD, we assessed HN delivery to the brain via the nasal route of administration. We further revealed a possible mechanism underlying the therapeutic effectiveness of HN peptide for PD using in vitro and ex vivo model of PD. Results: Although the expression of intracellular HN was not correlated with PD, HN treatment itself could induce intracellular HN expression and enhance mitochondrial biogenesis inducing mitochondrial gene expression. After intranasal administration, HN peptide resulted in neuroprotection and behavioral recovery in an animal model of PD. Interestingly, HN peptide following intranasal delivery was found within the brain, mainly via the trigeminal pathways. Mechanistically, HN treatment induced activation of phosphatidylinositol-3-kinase/protein kinase B (PI3K/AKT) signaling pathway which led to enhanced mitochondrial biogenesis resulting in upregulation of mitochondrial gene including humanin. Conclusion: These data support a novel role of mitochondrial protein humanin in mitochondrial function and neuronal survival against Parkinson's disease, in which humanin treatment is sufficient for stimulating mitochondrial gene expression.

Uncovering ferroptosis in Parkinson's disease via bioinformatics and machine learning, and reversed deducing potential therapeutic natural products.

Objective: Ferroptosis, a novel form of cell death, is closely associated with excessive iron accumulated within the substantia nigra in Parkinson's disease (PD). Despite extensive research, the underlying molecular mechanisms driving ferroptosis in PD remain elusive. Here, we employed a bioinformatics and machine learning approach to predict the genes associated with ferroptosis in PD and investigate the interactions between natural products and their active ingredients with these genes. Methods: We comprehensively analyzed differentially expressed genes (DEGs) for ferroptosis associated with PD (PDFerDEGs) by pairing 3 datasets (GSE7621, GSE20146, and GSE202665) from the NCBI GEO database and the FerrDb V2 database. A machine learning approach was then used to screen PDFerDEGs for signature genes. We mined the interacted natural product components based on screened signature genes. Finally, we mapped a network combined with ingredients and signature genes, then carried out molecular docking validation of core ingredients and targets to uncover potential therapeutic targets and ingredients for PD. Results: We identified 109 PDFerDEGs that were significantly enriched in biological processes and KEGG pathways associated with ferroptosis (including iron ion homeostasis, iron ion transport and ferroptosis, etc.). We obtained 29 overlapping genes and identified 6 hub genes (TLR4, IL6, ADIPOQ, PTGS2, ATG7, and FADS2) by screening with two machine learning algorithms. Based on this, we screened 263 natural product components and subsequently mapped the "Overlapping Genes-Ingredients" network. According to the network, top 5 core active ingredients (quercetin, 17-beta-estradiol, glycerin, trans-resveratrol, and tocopherol) were molecularly docked to hub genes to reveal their potential role in the treatment of ferroptosis in PD. Conclusion: Our findings suggested that PDFerDEGs are associated with ferroptosis and play a role in the progression of PD. Taken together, core ingredients (quercetin, 17-beta-estradiol, glycerin, trans-resveratrol, and tocopherol) bind well to hub genes (TLR4, IL6, ADIPOQ, PTGS2, ATG7, and FADS2), highlighting novel biomarkers for PD.

Biomarkers of Parkinson's Disease: From Basic Research to Clinical Practice.

Parkinson's disease (PD) is a common neurodegenerative disease characterized pathologically by dopaminergic neuron loss and the formation of Lewy bodies, which are enriched with aggregated α-synuclein (α-syn). PD currently has no cure, but therapeutic strategies are available to alleviate symptoms. Early diagnosis can greatly improve therapeutic interventions, but the clinical diagnosis of PD remains challenging and depends mainly on clinical features and imaging tests. Efficient and specific biomarkers are crucial for the diagnosis, monitoring, and evaluation of PD. Here, we reviewed the biomarkers of PD in different tissues and biofluids, along with the current clinical biochemical detection methods. We found that the sensitivity and specificity of single biomarkers are limited, and selecting appropriate indicators for combined detection can improve the diagnostic accuracy of PD.

MicroRNA Pathological Mechanisms between Parkinson's Disease, Alzheimer's Disease, Glaucoma, and Macular Degeneration.

Reactive oxygen species (ROS) play an essential role in regulating various functions of organisms such as gene transcription, signalling transduction and immune response. However, overproduction of ROS can lead to oxidative stress, which is related to various ageing diseases including eye and brain degenerative diseases. Ocular measurements have recently been suggested as potential sources of biomarkers for the early detection of brain neurodegenerative diseases. MicroRNAs (miRNAs) are useful biomarkers for various diseases including degenerative diseases. miRNAs play an important role in the oxidative stress mechanisms of ageing diseases. In this paper, the role of miRNAs related to oxidative stress mechanisms in four ageing diseases, Parkinson's disease (PD), Alzheimer's disease (AD), glaucoma and age-related macular degeneration was reviewed. The common miRNA biomarkers related to the four diseases were also discussed. The results show that these eye and brain ageing diseases share many common miRNA biomarkers. It indicates that the ocular condition may be a prognostic biomarker for PD or AD patients. When a patient's eye condition changes, this can be a warning of a change in PD or AD status.

Neuromelanin-Sensitive Magnetic Resonance Imaging as a Measure for Differential Diagnosis of Essential Tremor and Parkinson's Disease.

We sought to evaluate whether the neuromelanin-sensitive magnetic resonance imaging (NM-MRI) features of the substantia nigra (SN) have utility in the differential diagnosis of Parkinson's disease (PD) and essential tremor (ET). This study enrolled 23 patients with PD, 20 patients with ET, and 18 healthy participants. All subjects underwent clinical examination, motor and cognitive assessments, and NM-MRI scans. The area and contrast-to-noise ratio (CNR) values of SN were defined according to NM-MRI images. Then, receiver operating characteristic (ROC) analysis was conducted to characterize the diagnostic power of the SN area and CNR values of SN. Compared with ET and control groups, the PD group showed a significant reduction of the area of SN (P = 0.003, PD vs. ET; P = 0.001, PD vs. control) and in the SN to midbrain area ratio in the same layer (P = 0.006, PD vs. ET; P = 0.005, PD vs. control). The SN area had a sensitivity of 65% and a specificity of 87% for distinguishing ET from PD, with an area under the curve (AUC) of 0.7630 and a Youden index of 0.5200, whereas the ratio of the SN area to midbrain area in the same layer had a sensitivity of 60% and a specificity of 87% for distinguishing ET from PD, with an AUC of 0.7478 and a Youden index of 0.4700. Compared with the ET group, the mean CNR value of the SN and the respective CNR values of the three subregions were all weakened in the PD group, and only the CNR in the middle part was significantly different from the control group (P = 0.006). The sensitivity of the CNR value of the middle part of the SN for differentiating ET from PD was 65%, the specificity was 87%, the AUC was 0.7500, and the Youden index was 0.5200.Based on our findings, we conclude that NM-MRI can improve diagnostic accuracy in PD and can be used as a specific and sensitive potential diagnostic biomarker for PD.

Potential Biomarkers for Parkinson Disease from Functional Enrichment and Bioinformatic Analysis of Global Gene Expression Patterns of Blood and Substantia Nigra Tissues.

The Parkinson disease (PD) is the second most common neurodegenerative disorder affecting the central nervous system and motor functions. The biological complexity of PD is yet to reveal potential targets for intervention or to slow the disease severity. Therefore, this study aimed to compare the fidelity of blood to substantia nigra (SN) tissue gene expression from PD patients to provide a systematic approach to predict role of the key genes of PD pathobiology. Differentially expressed genes (DEGs) from multiple microarray data sets of PD blood and SN tissue from GEO database are identified. Using the theoretical network approach and variety of bioinformatic tools, we prioritized the key genes from DEGs. A total of 540 and 1024 DEGs were identified in blood and SN tissue samples, respectively. Functional pathways closely related to PD such as ERK1 and ERK2 cascades, mitogen-activated protein kinase (MAPK) signaling, Wnt, nuclear factor-κB (NF-κB), and PI3K-Akt signaling were observed by enrichment analysis. Expression patterns of 13 DEGs were similar in both blood and SN tissues. Comprehensive network topological analysis and gene regulatory networks identified additional 10 DEGs functionally connected with molecular mechanisms of PD through the mammalian target of rapamycin (mTOR), autophagy, and AMP-activated protein kinase (AMPK) signaling pathways. Potential drug molecules were identified by chemical-protein network and drug prediction analysis. These potential candidates can be further validated in vitro/in vivo to be used as biomarkers and/or novel drug targets for the PD pathology and/or to arrest or delay the neurodegeneration over the years, respectively.

Decreased cerebrospinal fluid orexin levels not associated with clinical sleep disturbance in Parkinson's disease: A retrospective study.

Patients with Parkinson's disease (PD) often suffer from sleep disturbances, including excessive daytime sleepiness (EDS) and rapid eye movement sleep behavior disorder (RBD). These symptoms are also experienced by patients with narcolepsy, which is characterized by orexin neuronal loss. In PD, a decrease in orexin neurons is observed pathologically, but the association between sleep disturbance in PD and cerebrospinal fluid (CSF) orexin levels is still unclear. This study aimed to clarify the role of orexin as a biomarker in patients with PD. CSF samples were obtained from a previous cohort study conducted between 2015 and 2020. We cross-sectionally and longitudinally examined the association between CSF orexin levels, sleep, and clinical characteristics. We analyzed 78 CSF samples from 58 patients with PD and 21 samples from controls. CSF orexin levels in patients with PD (median = 272.0 [interquartile range = 221.7-334.5] pg/mL) were lower than those in controls (352.2 [296.2-399.5] pg/mL, p = 0.007). There were no significant differences in CSF orexin levels according to EDS, RBD, or the use of dopamine agonists. Moreover, no significant correlation was observed between CSF orexin levels and clinical characteristics by multiple linear regression analysis. Furthermore, the longitudinal changes in orexin levels were also not correlated with clinical characteristics. This study showed decreased CSF orexin levels in patients with PD, but these levels did not show any correlation with any clinical characteristics. Our results suggest the limited efficacy of CSF orexin levels as a biomarker for PD, and that sleep disturbances may also be affected by dysfunction of the nervous system other than orexin, or by dopaminergic treatments in PD. Understanding the reciprocal role of orexin among other neurotransmitters may provide a better treatment strategy for sleep disturbance in patients with PD.

Identification of RNA markers associated with Parkinson's disease using multiplex gene expression analysis

Introduction. Parkinson's disease (PD) is a neurodegenerative disorder, and the development of biomarkers is essential due to complicated PD diagnosis and progression assessment.
 Objective. To identify PD RNA markers by multiplex expression profiling of 760 genes associated with the main neuropathological processes.
 Materials and methods. We studied the expression of 760 genes associated with the main neuropathological processes using Nanostring nCounter Human Neuropathology Panel in 29 blood samples obtained from PD patients, including 13 samples from those in the early stage and 16 samples from those in the advanced stage, and in 16 control blood samples.
 Results. The comparison of gene expression in the patients with early PD and in the controls demonstrated differential expression of genes CDKN1A and CPT1B. The comparison of gene expression in the patients with advanced PD and in the controls showed LRP1 upregulation in the advanced PD group. We also revealed СPT1B upregulation in advanced disease, with a positive correlation between СPT1B expression and PD duration.
 Discussion. The variably expressed genes may be relevant as PD biomarkers for diagnosis and progression assessment.

Diffusion along perivascular spaces as marker for impairment of glymphatic system in Parkinson’s disease

The brain glymphatic system is involved in the clearance of misfolding α-synuclein, the impaired glymphatic system may contribute to the progression of Parkinson’s disease (PD). We aimed to analyze the diffusion tensor image along the perivascular space (DTI-ALPS) and perivascular space (PVS) burden to reveal the relationship between the glymphatic system and PD. A cross-sectional study using a 7 T MRI of 76 PD patients and 48 controls was performed to evaluate the brain’s glymphatic system. The DTI-ALPS and PVS burden in basal ganglia were calculated. Correlation analyses were conducted between DTI-ALPS, PVS burden and clinical features. We detected lower DTI-ALPS in the PD subgroup relative to controls, and the differences were more pronounced in patients with Hoehn & Yahr stage greater than two. The decreased DTI-ALPS was only evident in the left hemisphere in patients in the early stage but involved both hemispheres in more advanced PD patients. Decreased DTI-ALPS were also correlated with longer disease duration, higher Unified Parkinson’s Disease Rating Scale motor score (UPDRS III) and UPDRS total scores, as well as higher levodopa equivalent daily dose. Moreover, the decreased DTI-ALPS correlated with increased PVS burden, and both indexes correlated with PD disease severity. This study demonstrated decreased DTI-ALPS in PD, which might initiate from the left hemisphere and progressively involve right hemisphere with the disease progression. Decreased DTI-ALPS index correlated with increased PVS burden, indicating that both metrics could provide supporting evidence of an impaired glymphatic system. MRI evaluation of the PVS burden and diffusion along PVS are potential imaging biomarkers for PD for disease progression.

Identification of exosomal biomarkers and its optimal isolation and detection method for the diagnosis of Parkinson's disease: A systematic review and meta-analysis.

Recently, there has been growing interest in exosomal biomarkers for their active targeting and specificity for delivering their cargos (proteins, lipids, nucleic acids) from the parent cell to the recipient cell. Currently, the clinical diagnosis of Parkinson's disease (PD) is mainly based on a clinician's neuropsychological examination and motor symptoms (e.g., bradykinesia, rigidity, postural instability, and resting tremor). However, this diagnosis method is not accurate due to overlapping criteria of other neurodegenerative diseases. Exosomes are differentially expressed in PD and a combination of types and contents of exosomes might be used as a biomarker in PD. Here, we systematically reviewed and meta-analyzed exosomal contents, types and sources of exosomes, method of isolation, and protein quantification tools to determine the optimum exosome-related attributes for PD diagnosis. Pubmed, Embase, and ISI Web of Science were searched for relevant studies. 25 studies were included in the meta-analysis. The Ratio of Mean (RoM) with 95% confidence intervals (CI) was calculated to estimate the effect size. Biomarker performances were rated by random-effects meta-analysis with the Restricted Maximum Likelihood (REML) method. The study protocol is available at PROSPERO (CRD42022331885). Exosomal α-synuclein (α-Syn) was significantly altered in PD patients from healthy controls [RoM =1.67, 95% CI (0.99to 2.35); p=0.00] followed by tau [RoM =1.33, 95% CI (0.79to 1.87); p=0.00], PS-129 [RoM =0.97, 95% CI (0.54to 1.40); p=0.00], and DJ-1/PARK7 [RoM =0.93, 95% CI (0.64to 1.21); p=0.00]. Central nervous system derived L1CAM exosome [RoM =1.24, 95% CI (1.04to 1.45); p=0.00] from either plasma [RoM =1.35, 95% CI (1.09to 1.61); p=0.00]; or serum [RoM =1.47, 95% CI (1.05to 1.90); p=0.00] has been found the optimum type of exosome. The exosome isolation by ExoQuick [RoM =1.16, 95% CI (0.89to 1.43); p=0.00] and protein quantification method by ELISA [RoM =1.28, 95% CI (1.15to 1.41); p=0.00] has been found the optimum isolation and quantification method, respectively for PD diagnosis. This meta-analysis suggests that α-Syn in L1CAM exosome derived from blood, isolated by ExoQuick kit, and quantified by ELISA can be used for PD diagnosis.

Identifying and distinguishing of essential tremor and Parkinson’s disease with grouped stability analysis based on searchlight-based MVPA

BackgroundSince both essential tremor (ET) and Parkinson’s disease (PD) are movement disorders and share similar clinical symptoms, it is very difficult to recognize the differences in the presentation, course, and treatment of ET and PD, which leads to misdiagnosed commonly.PurposeAlthough neuroimaging biomarker of ET and PD has been investigated based on statistical analysis, it is unable to assist the clinical diagnosis of ET and PD and ensure the efficiency of these biomarkers. The aim of the study was to identify the neuroimaging biomarkers of ET and PD based on structural magnetic resonance imaging (MRI). Moreover, the study also distinguished ET from PD via these biomarkers to validate their classification performance.MethodsThis study has developed and implemented a three-level machine learning framework to identify and distinguish ET and PD. First of all, at the model-level assessment, the searchlight-based machine learning method has been used to identify the group differences of patients (ET/PD) with normal controls (NCs). And then, at the feature-level assessment, the stability of group differences has been tested based on structural brain atlas separately using the permutation test to identify the robust neuroimaging biomarkers. Furthermore, the identified biomarkers of ET and PD have been applied to classify ET from PD based on machine learning techniques. Finally, the identified biomarkers have been compared with the previous findings of the biology-level assessment.ResultsAccording to the biomarkers identified by machine learning, this study has found widespread alterations of gray matter (GM) for ET and large overlap between ET and PD and achieved superior classification performance (PCA + SVM, accuracy = 100%).ConclusionsThis study has demonstrated the significance of a machine learning framework to identify and distinguish ET and PD. Future studies using a large data set are needed to confirm the potential clinical application of machine learning techniques to discern between PD and ET.

Dysregulation of miR-543 in Parkinson's disease: Impact on the neuroprotective gene SIRT1.

Parkinson's disease (PD) is a progressive and age-dependent neurodegenerative disease characterised clinically by a variety of motor symptoms and cognitive impairment. PD was initially considered to be a grey matter disease; however, recently, evidence has emerged that white matter changes in PD precede the neuronal loss seen in the grey matter. The cause of these initial white matter changes is yet to be elucidated. Here, we explored whether dysregulated miRNAs and their target mRNA could provide insight into the underlying mechanisms of early white matter changes in PD. We analysed the expression of miRNAs in three different stages of PD through RNA-sequencing and validated the differential expression of miRNAs through quantitative reverse transcription polymerase chain reaction. With bioinformatic analyses, we predicted target genes of dysregulated miRNAs and investigated their biomarker potential. Finally, in vitro, we confirmed the targetting of thegene SIRT1 by miR-543. We identified 12 dysregulated miRNAs in PD and found that miR-543 holds potential as a biomarker for late-stage PD with dementia. We report upregulation of miR-543 in early PD white matter tissue and downregulation of SIRT1. In vitro experiments showed that the upregulation of miR-543 results in the downregulation of SIRT1 in the white matter, but not in the grey matter. We validated SIRT1 as a target of miR-543 in the brain and showed its function as a potential biomarker. Our results highlight the idea that dysregulation of miR-543 in early PD white matter, resulting in the dysregulation of SIRT1, potentially influencing the early white matter changes observed in PD.

The Role of Cannabinoid Type 2 Receptors in Parkinson's Disease.

Parkinson's disease (PD) is the second most frequent neurodegenerative disease and currently represents a clear unmet medical need. Therefore, novel preventive and therapeutic strategies are needed. Cannabinoid type 2 (CB2) receptors, one of the components of the endocannabinoid system, can regulate neuroinflammation in PD. Here, we review the current preclinical and clinical studies investigating the CB2 receptors in PD with the aim to clarify if these receptors could have a role in PD. Preclinical data show that CB2 receptors could have a neuroprotective action in PD and that the therapeutic targeting of CB2 receptors could be promising. Indeed, it has been shown that different CB2 receptor-selective agonists exert protective effects in different PD models. Moreover, the alterations in the expression of CB2 receptors observed in brain tissues from PD animal models and PD patients suggest the potential value of CB2 receptors as possible novel biomarkers for PD. However, to date, there is no direct evidence of the role of CB2 receptors in PD. Further studies are strongly needed in order to fully clarify the role of CB2 receptors in PD and thus pave the way to novel possible diagnostic and therapeutic opportunities for PD.

Preliminary Effects of Osteopathic Manipulative Medicine on Reactive Oxygen Species in Parkinson's Disease: A Randomized Controlled Pilot Study.

Context Parkinson's disease (PD) is the second most common neurodegenerative disorder and causes many clinical manifestations including bradykinesia, tremor, postural instability, and musculoskeletal stiffness. Neurodegeneration is commonly associated with oxidative stress. Oxidative stress has not been measured in PD in relation to the manual techniques used in Osteopathic Manipulative Treatment (OMT). Objective To investigate the effect of OMT on oxidative stress biomarkers in PD. Methods In this randomized non-blinded study, 32 PD subjects were separated by block randomization into counseling and OMT groups, receiving respective interventions twice a week for six weeks. The counseling arm received informative sessions while the OMT arm received a set treatment protocol. Biomarkers of oxidative stress, malondialdehyde (MDA), dityrosine (DT), 3-nitrotyrosine (3-NT), 8-hydroxy-2-deoxyguanosine (8-OHdG), and 8-isoprostane were measured before and after the first session and at weeks three, six, and 10 (four weeks after conclusion of intervention). Results No significant changes were found in blood plasma levels of MDA, DT, 3-NT, or 8-OHdG during or after intervention compared to controls (p > 0.05). No significant changes were found in urine 8-OHdG or 8-isoprostane during or after intervention compared to controls (p > 0.05). Conclusion OMT used in this study did not significantly affect the chosen oxidative stress biomarkers, however many limitations of the study may have impeded possible findings.

Quantitative Determination of Endogenous Tetrahydroisoquinolines, Potential Parkinson's Disease Biomarkers, in Mammals.

Current diagnostic options for Parkinson's disease are very limited and primarily based on characteristic clinical symptoms. Thus, there are urgent needs for reliable biomarkers that enable us to diagnose the disease in the early stages, differentiate it from other atypical Parkinsonian syndromes, monitor its progression, increase knowledge of its pathogenesis, and improve the development of potent therapies. A promising group of potential biomarkers are endogenous tetrahydroisoquinoline metabolites, which are thought to contribute to the multifactorial etiology of Parkinson's disease. The aim of this critical review is to highlight trends and limitations of available traditional and modern analytical techniques for sample pretreatment (extraction and derivatization procedures) and quantitative determination of tetrahydroisoquinoline derivatives in various types of mammalian fluids and tissues (urine, plasma, cerebrospinal fluid, brain tissue, liver tissue). Particular attention is paid to the most sensitive and specific analytical techniques, involving immunochemistry and gas or liquid chromatography coupled with mass spectrometric, fluorescence, or electrochemical detection. The review also includes a discussion of other relevant agents proposed and tested in Parkinson's disease.

Transcriptomic analysis reveals an association of FCGBP with Parkinson’s disease

Transcriptomics in Parkinson’s disease (PD) offers new insights into the molecular mechanism of PD pathogenesis. Several pathways, such as inflammation and protein degradation, have been identified by differential gene expression analysis. Our aim was to identify gene expression differences underlying the disease etiology and the discovery of pre-symptomatic risk biomarkers for PD from a multicenter study in the context of the PROPAG-AGEING project. We performed RNA sequencing from 47 patients with de novo PD, 10 centenarians, and 65 healthy controls. Using identified differentially expressed genes, functional annotations were assigned using gene ontology to unveil significant enriched biological processes. The expression of 16 selected genes was validated using OpenArray® assays and samples from independent cohorts of 201 patients with advanced PD, 340 healthy siblings of PD patients, and 177 healthy controls. Differential gene expression analysis identified higher FCGBP expression in patients with de novo PD compared with healthy controls and compared with centenarians. Furthermore, FCGBP showed no differences in terms of population origin or aging process. The increased FCGBP expression was validated in patients with advanced PD and their siblings. Thus, we provided evidence for an upregulation of FCGBP mRNA levels not only in patients with PD but also in individuals at putative higher risk of PD, suggesting that it could be important in gut–brain PD interaction, mediating the connection between microbiota and intestinal inflammatory processes, as well as neuroinflammation and neurodegeneration.

Plasma p-tau181, neurofilament light chain and association with cognition in Parkinson’s disease

Early identification of cognitive impairment in Parkinson’s disease (PD) has important clinical and research implications. The aim of our study was to investigate the role of plasma tau phosphorylated at amino acid 181 (p-tau181) and plasma neurofilament light chain (NfL) as biomarkers of cognition in PD. Baseline concentrations of plasma p-tau181 and NfL were measured in a cohort of 136 patients with PD and 63 healthy controls (HC). Forty-seven PD patients were followed up for up to 2 years. Cross-sectional and longitudinal associations between baseline plasma biomarkers and cognitive progression were investigated using linear regression and linear mixed effects models. At baseline, plasma p-tau181 concentration was significantly higher in PD subjects compared with HC (p = 0.026). In PD patients, higher plasma NfL was associated with lower MMSE score at baseline, after adjusting for age, sex and education (p = 0.027). Baseline plasma NfL also predicted MMSE decline over time in the PD group (p = 0.020). No significant association between plasma p-tau181 concentration and baseline or longitudinal cognitive performance was found. While the role of p-tau181 as a diagnostic biomarker for PD and its relationship with cognition need further elucidation, plasma NfL may serve as a feasible, non-invasive biomarker of cognitive progression in PD.

Understanding how people with Parkinson's disease turn in gait from a real-world in-home dataset

IntroductionTurning in gait digital parameters may be useful in measuring disease progression in Parkinson's disease (PD), however challenges remain over algorithm validation in real-world settings. The influence of clinician observation on turning outcomes is poorly understood. Our objective is to describe a unique in-home video dataset and explore the use of turning parameters as biomarkers in PD. Methods11 participants with PD, 11 control participants stayed in a home-like setting living freely for 5 days (with two sessions of clinical assessment), during which high-resolution video was captured. Clinicians watched the videos, identified turns and documented turning parameters. ResultsFrom 85 hours of video 3869 turns were evaluated, averaging at 22.7 turns per hour per person. 6 participants had significantly different numbers of turning steps and/or turn duration between “ON” and “OFF” medication states. Positive Spearman correlations were seen between the Movement Disorders Society-sponsored revision of the Unified Parkinson's Disease Rating Scale III score with a) number of turning steps (rho = 0.893, p < 0.001), and b) duration of turn (rho = 0.744, p = 0.009) “OFF” medications. A positive correlation was seen “ON” medications between number of turning steps and clinical rating scale score (rho = 0.618, p = 0.048). Both cohorts took more steps and shorter durations of turn during observed clinical assessments than when free-living. ConclusionThis study shows proof of concept that real-world free-living turn duration and number of turning steps recorded can distinguish between PD medication states and correlate with gold-standard clinical rating scale scores. It illustrates a methodology for ecological validation of real-world digital outcomes.