Gene Expression Differences in Peripheral Blood of Parkinson's Disease Patients with Distinct Progression Profiles

Plate-Based Assays for the Characterization of Mitochondrial and Cellular Phenotypes

The mitochondria are essential to eukaryotic life, acting as key drivers of energy generation while also being involved in the regulation of many cellular processes including apoptosis, cell proliferation, calcium homeostasis, and metabolism. Mitochondrial diseases which disrupt these processes lead to a diverse range of pathologies and lack consistency in symptom presentation. In disease, mitochondrial activity and energy homeostasis can be adapted to cellular requirements, and studies using Dictyostelium and human lymphoblastoid cell lines have shown that such changes can be facilitated by the key cellular and energy regulators, TORC1 and AMPK. Fluorescence-based assays are increasingly utilized to measure mitochondrial and cell signalling function in mitochondrial disease research. Here, we describe a streamlined method for the simultaneous measurement of mitochondrial mass, membrane potential, and reactive oxygen species production using MitoTracker Green™ FM, MitoTracker Red™ CMXRos, and DCFH-DA probes. This protocol has been adapted for both Dictyostelium and human lymphoblastoid cell lines. We also describe a method for assessing TORC1 and AMPK activity simultaneously in lymphoblastoid cells. These techniques allow for the characterization of mitochondrial defects in a rapid and easy to implement manner.

Ferroptosis-Related Immune Genes in Hematological Diagnosis of Parkinson's Diseases

Emerging evidence suggested that ferroptosis and immune activation, as well as their interactions, played a crucial role in the occurrence and progression of Parkinson's disease (PD). However, whether this interaction could serve as the basis for a hematological diagnosis of PD remained poorly understood. This study aimed to construct a novel hematological model for PD diagnosis based on the ferroptosis-related immune genes. The brain imaging of PD patients was obtained from the Affiliated Hospital of Nantong University. We used least absolute shrinkage and selection operator (LASSO) to identify the optimal signature ferroptosis-related immune genes based on six gene expression profile datasets of substantia nigra (SN) and peripheral blood of PD patients. Then we used the support vector machine (SVM) classifier to construct the hematological diagnostic model named Ferr.Sig for PD. Gene set enrichment analysis was utilized to execute gene functional annotation. The brain imaging and functional annotation analysis revealed prominent iron deposition and immune activation in the SN region of PD patients. We identified a total of 17 signature ferroptosis-related immune genes using LASSO method and imported them to SVM classifier. The Ferr.Sig model exhibited a high diagnostic accuracy, and its area under the curve (AUC) for distinguishing PD patients from healthy controls in the training and internal validation cohort reached 0.856 and 0.704, respectively. We also used the Ferr.Sig into other external validation cohorts, and a comparable AUC with the internal cohort was obtained, with the AUC of 0.727 in Scherzer's cohort, 0.745 in Roncagli's cohort, and 0.778 in Meiklejohn's cohort. Furthermore, the diagnostic performance of Ferr.Sig was not interfered by the other neurodegenerative diseases. This study revealed the value of ferroptosis-related immune genes in PD diagnosis, which may provide a novel direction and strategy for the development of novel biomarkers with less invasiveness, low cost, and high accuracy for PD screening and diagnosis.

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.

Transcriptome Profiling Reveals Differential Expression of Circadian Behavior Genes in Peripheral Blood of Monozygotic Twins Discordant for Parkinson's Disease

Parkinson’s disease (PD) is one of the most common neurodegenerative diseases. Investigating individuals with the most identical genetic background is optimal for minimizing the genetic contribution to gene expression. These individuals include monozygotic twins discordant for PD. Monozygotic twins have the same genetic background, age, sex, and often similar environmental conditions. The aim of this study was to carry out a transcriptome analysis of the peripheral blood of three pairs of monozygotic twins discordant for PD. We identified the metabolic process “circadian behavior” as a priority process for further study. Different expression of genes included in the term “circadian behavior” confirms that this process is involved in PD pathogenesis. We found increased expression of three genes associated with circadian behavior, i.e., PTGDS, ADORA2A, and MTA1, in twins with PD. These genes can be considered as potential candidate genes for this disease.

Alpha-synuclein overexpression induces epigenomic dysregulation of glutamate signaling and locomotor pathways

Parkinson’s disease (PD) is a neurological disorder with complex interindividual etiology that is becoming increasingly prevalent worldwide. Elevated alpha-synuclein levels can increase risk of PD and may influence epigenetic regulation of PD pathways. Here, we report genome-wide DNA methylation and hydroxymethylation alterations associated with overexpression of two PD-linked alpha-synuclein variants (wild-type and A30P) in LUHMES cells differentiated to dopaminergic neurons. Alpha-synuclein altered DNA methylation at thousands of CpGs and DNA hydroxymethylation at hundreds of CpGs in both genotypes, primarily in locomotor behavior and glutamate signaling pathway genes. In some cases, epigenetic changes were associated with transcription. SMITE network analysis incorporating H3K4me1 ChIP-seq to score DNA methylation and hydroxymethylation changes across promoters, enhancers, and gene bodies confirmed epigenetic and transcriptional deregulation of glutamate signaling modules in both genotypes. Our results identify distinct and shared impacts of alpha-synuclein variants on the epigenome, and associate alpha-synuclein with the epigenetic etiology of PD.

Parkinson's Disease Subtyping Using Clinical Features and Biomarkers: Literature Review and Preliminary Study of Subtype Clustering

The second most common progressive neurodegenerative disorder, Parkinson’s disease (PD), is characterized by a broad spectrum of symptoms that are associated with its progression. Several studies have attempted to classify PD according to its clinical manifestations and establish objective biomarkers for early diagnosis and for predicting the prognosis of the disease. Recent comprehensive research on the classification of PD using clinical phenotypes has included factors such as dominance, severity, and prognosis of motor and non-motor symptoms and biomarkers. Additionally, neuroimaging studies have attempted to reveal the pathological substrate for motor symptoms. Genetic and transcriptomic studies have contributed to our understanding of the underlying molecular pathogenic mechanisms and provided a basis for classifying PD. Moreover, an understanding of the heterogeneity of clinical manifestations in PD is required for a personalized medicine approach. Herein, we discuss the possible subtypes of PD based on clinical features, neuroimaging, and biomarkers for developing personalized medicine for PD. In addition, we conduct a preliminary clustering using gait features for subtyping PD. We believe that subtyping may facilitate the development of therapeutic strategies for PD.

Roles of Non-Coding RNAs as Novel Diagnostic Biomarkers in Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder, affecting 5%of the elderly population. Currently, the diagnosis of PD is mainly based on clinical features and no definitive diagnostic biomarkers have been identified. The discovery of biomarkers at the earliest stages of PD is of extreme interest. This review focuses on the current findings in the field of circulating non-coding RNAs in PD. We briefly describe the more established circulating biomarkers in PD and provide a more thorough review of non-coding RNAs, in particular microRNAs, long non-coding RNAs and circular RNAs, differentially expressed in PD, highlighting their potential for being considered as biomarkers for diagnosis. Together, these studies hold promise for the use of peripheral biomarkers for the diagnosis of PD.

Transcriptome profiling of five brain regions in a 6-hydroxydopamine rat model of Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is a neurodegenerative disease, and its pathogenesis is unclear. Previous studies mainly focus on the lesions of substantia nigra (SN) and striatum (Str) in PD. However, lesions are not limited. The olfactory bulb (OB), subventricular zone (SVZ), and hippocampus (Hippo) are also affected in PD.

AIM

To reveal gene expression changes in the five brain regions (OB, SVZ, Str, SN, and Hippo), and to look for potential candidate genes and pathways that may be correlated with the pathogenesis of PD.

MATERIALS AND METHODS

We established control group and 6-hydroxydopamine (6-OHDA) PD model group, and detected gene expressions in the five brain regions using RNA-seq and real-time quantitative polymerase chain reaction (RT-qPCR). We further analyzed the RNA-seq data by bioinformatics.

RESULTS

We identified differentially expressed genes (DEGs) in all five brain regions. The DEGs were significantly enriched in the "dopaminergic synapse" and "retrograde endocannabinoid signaling," and Gi/o-GIRK is the shared cascade in the two pathways. We further identified Ephx2, Fam111a, and Gng2 as the potential candidate genes in the pathogenesis of PD for further studies.

CONCLUSION

Our study suggested that gene expressions change in the five brain regions following exposure to 6-OHDA. The "dopaminergic synapse," "retrograde endocannabinoid signaling," and Gi/o-GIRK may be the key pathways and cascade of the synaptic damage in 6-OHDA PD rats. Ephx2, Fam111a, and Gng2 may play critical roles in the pathogenesis of PD.

Lymphoblastoid Cell Lines as Models to Study Mitochondrial Function in Neurological Disorders

Neurological disorders, including neurodegenerative diseases, are collectively a major cause of death and disability worldwide. Whilst the underlying disease mechanisms remain elusive, altered mitochondrial function has been clearly implicated and is a key area of study in these disorders. Studying mitochondrial function in these disorders is difficult due to the inaccessibility of brain tissue, which is the key tissue affected in these diseases. To overcome this issue, numerous cell models have been used, each providing unique benefits and limitations. Here, we focussed on the use of lymphoblastoid cell lines (LCLs) to study mitochondrial function in neurological disorders. LCLs have long been used as tools for genomic analyses, but here we described their use in functional studies specifically in regard to mitochondrial function. These models have enabled characterisation of the underlying mitochondrial defect, identification of altered signalling pathways and proteins, differences in mitochondrial function between subsets of particular disorders and identification of biomarkers of the disease. The examples provided here suggest that these cells will be useful for development of diagnostic tests (which in most cases do not exist), identification of drug targets and testing of pharmacological agents, and are a worthwhile model for studying mitochondrial function in neurological disorders.

Periphery and brain, innate and adaptive immunity in Parkinson's disease

Parkinson’s disease (PD) is a neurodegenerative disorder where alpha-synuclein plays a central role in the death and dysfunction of neurons, both, in central, as well as in the peripheral nervous system. Besides the neuronal events observed in patients, PD also includes a significant immune component. It is suggested that the PD-associated immune response will have consequences on neuronal health, thus opening immunomodulation as a potential therapeutic strategy in PD. The immune changes during the disease occur in the brain, involving microglia, but also in the periphery with changes in cells of the innate immune system, particularly monocytes, as well as those of adaptive immunity, such as T-cells. This realization arises from multiple patient studies, but also from data in animal models of the disease, providing strong evidence for innate and adaptive immune system crosstalk in the central nervous system and periphery in PD. Here we review the data showing that alpha-synuclein plays a crucial role in the activation of the innate and adaptive immune system. We will also describe the studies suggesting that inflammation in PD includes early changes in innate and adaptive immune cells that develop dynamically through time during disease, contributing to neuronal degeneration and symptomatology in patients. This novel finding has contributed to the definition of PD as a multisystem disease that should be approached in a more integratory manner rather than a brain-focused classical approach.

Reduced erythrocytic CHCHD2 mRNA is associated with brain pathology of Parkinson's disease

Peripheral biomarkers indicative of brain pathology are critically needed for early detection of Parkinson’s disease (PD). In this study, using NanoString and digital PCR technologies, we began by screening for alterations in genes associated with PD or atypical Parkinsonism in erythrocytes of PD patients, in which PD-related changes have been reported, and which contain ~ 99% of blood α-synuclein. Erythrocytic CHCHD2 mRNA was significantly reduced even at the early stages of the disease. A significant reduction in protein and/or mRNA expression of CHCHD2 was confirmed in PD brains collected at autopsy as well as in the brains of a PD animal model overexpressing α-synuclein, in addition to seeing a reduction of CHCHD2 in erythrocytes of the same animals. Overexpression of α-synuclein in cellular models of PD also resulted in reduced CHCHD2, via mechanisms likely involving altered subcellular localization of p300 histone acetyltransferase. Finally, the utility of reduced CHCHD2 mRNA as a biomarker for detecting PD, including early-stage PD, was validated in a larger cohort of 205 PD patients and 135 normal controls, with a receiver operating characteristic analysis demonstrating > 80% sensitivity and specificity.

Transcriptomic profiles in Parkinson's disease

Transcriptomics in Parkinson's disease offers insights into the pathogenesis of Parkinson's disease but obtaining brain tissue has limitations. In order to bypass this issue, we profile and compare differentially expressed genes and enriched pathways (KEGG) in two peripheral tissues (blood and skin) of 12 Parkinson's disease patients and 12 healthy controls using RNA-sequencing technique and validation with RT-qPCR. Furthermore, we compare our results to previous Parkinson's disease post mortem brain tissue and blood results using the robust rank aggregation method. The results show no overlapping differentially expressed genes or enriched pathways in blood vs. skin in our sample sets (25 vs. 1068 differentially expressed genes with an FDR ≤ 0.05; 1 vs. 9 pathways in blood and skin, respectively). A meta-analysis from previous transcriptomic sample sets using either microarrays or RNA-Seq yields a robust rank aggregation list of cortical gene expression changes with 43 differentially expressed genes; a list of substantia nigra changes with 2 differentially expressed genes and a list of blood changes with 1 differentially expressed gene being statistically significant at FDR ≤ 0.05. In cortex 1, KEGG pathway was enriched, four in substantia nigra and two in blood. None of the differentially expressed genes or pathways overlap between these tissues. When comparing our previously published skin transcription analysis, two differentially expressed genes between the cortex robust rank aggregation and skin overlap. In this study, for the first time a meta-analysis is applied on transcriptomic sample sets in Parkinson's disease. Simultaneously, it explores the notion that Parkinson's disease is not just a neuronal tissue disease by exploring peripheral tissues. The comparison of different Parkinson's disease tissues yields surprisingly few significant differentially expressed genes and pathways, suggesting that divergent gene expression profiles in distinct cell lineages, metabolic and possibly iatrogenic effects create too much transcriptomic noise for detecting significant signal. On the other hand, there are signs that point towards Parkinson's disease-specific changes in non-neuronal peripheral tissues in Parkinson's disease, indicating that Parkinson's disease might be a multisystem disorder.

Mitochondriopathies as a Clue to Systemic Disorders-Analytical Tools and Mitigating Measures in Context of Predictive, Preventive, and Personalized (3P) Medicine

The mitochondrial respiratory chain is the main site of reactive oxygen species (ROS) production in the cell. Although mitochondria possess a powerful antioxidant system, an excess of ROS cannot be completely neutralized and cumulative oxidative damage may lead to decreasing mitochondrial efficiency in energy production, as well as an increasing ROS excess, which is known to cause a critical imbalance in antioxidant/oxidant mechanisms and a "vicious circle" in mitochondrial injury. Due to insufficient energy production, chronic exposure to ROS overproduction consequently leads to the oxidative damage of life-important biomolecules, including nucleic acids, proteins, lipids, and amino acids, among others. Different forms of mitochondrial dysfunction (mitochondriopathies) may affect the brain, heart, peripheral nervous and endocrine systems, eyes, ears, gut, and kidney, among other organs. Consequently, mitochondriopathies have been proposed as an attractive diagnostic target to be investigated in any patient with unexplained progressive multisystem disorder. This review article highlights the pathomechanisms of mitochondriopathies, details advanced analytical tools, and suggests predictive approaches, targeted prevention and personalization of medical services as instrumental for the overall management of mitochondriopathy-related cascading pathologies.

Inflammation and regulatory T cell genes are differentially expressed in peripheral blood mononuclear cells of Parkinson's disease patients

Our aim was to identify the differentially expressed genes (DEGs) in peripheral blood mononuclear cells (PBMC) of Parkinson’s disease (PD) patients and healthy controls by microarray technology and analysis of related molecular pathways by functional annotation. Thirty PD patients and 30 controls were enrolled. Agilent Human 8X60 K Oligo Microarray was used for gene level expression identification. Gene ontology and pathway enrichment analyses were used for functional annotation of DEGs. Protein–protein interaction analyses were performed with STRING. Expression levels of randomly selected DEGs were quantified by real time quantitative polymerase chain reaction (RT-PCR) for validation. Flow cytometry was done to determine frequency of regulatory T cells (Tregs) in PBMC. A total of 361 DEGs (143 upregulated and 218 downregulated) were identified after GeneSpring analysis. DEGs were involved in 28 biological processes, 12 cellular components and 26 molecular functions. Pathway analyses demonstrated that upregulated genes mainly enriched in p53 (CASP3, TSC2, ATR, MDM4, CCNG1) and PI3K/Akt (IL2RA, IL4R, TSC2, VEGFA, PKN2, PIK3CA, ITGA4, BCL2L11) signaling pathways. TP53 and PIK3CA were identified as most significant hub proteins. Expression profiles obtained by RT-PCR were consistent with microarray findings. PD patients showed increased proportions of CD49d⁺ Tregs, which correlated with disability scores. Survival pathway genes were upregulated putatively to compensate neuronal degeneration. Bioinformatics analysis showed an association between survival and inflammation genes. Increased CD49d⁺ Treg ratios might signify the effort of the immune system to suppress ongoing neuroinflammation.

Differentially Expressed Circular RNAs in Peripheral Blood Mononuclear Cells of Patients with Parkinson's Disease

Background

New noninvasive and affordable molecular approaches that will complement current practices and increase the accuracy of Parkinson's disease (PD) diagnosis are urgently needed. Circular RNAs (circRNAs) are stable noncoding RNAs that accumulate with aging in neurons and are increasingly shown to regulate all aspects of neuronal development and function.

Objectives

Τhe aims of this study were to identify differentially expressed circRNAs in blood mononuclear cells of patients with idiopathic PD and explore the competing endogenous RNA networks affected.

Methods

Eighty‐seven circRNAs were initially selected based on relatively high gene expression in the human brain. More than half of these were readily detectable in blood mononuclear cells using real‐time reverse transcription‐polymerase chain reaction. Comparative expression analysis was then performed in blood mononuclear cells from 60 control subjects and 60 idiopathic subjects with PD.

Results

Six circRNAs were significantly down‐regulated in patients with PD. The classifier that best distinguished PD consisted of four circRNAs with an area under the curve of 0.84. Cross‐linking immunoprecipitation‐sequencing data revealed that the RNA‐binding proteins bound by most of the deregulated circRNAs include the neurodegeneration‐associated FUS, TDP43, FMR1, and ATXN2. MicroRNAs predicted to be sequestered by most deregulated circRNAs have the Gene Ontology categories “protein modification” and “transcription factor activity” mostly enriched.

Conclusions

This is the first study that identifies specific circRNAs that may serve as diagnostic biomarkers for PD. Because they are highly expressed in the brain and are derived from genes with essential brain functions, they may also hint on the PD pathways affected. © 2021 Biomedical Research Foundation, Academy of Athens. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Identifying potential gene biomarkers for Parkinson's disease through an information entropy based approach

Parkinson's disease (PD) is a chronic, progressive neurodegenerative disease and represents the most common disease of this type, after Alzheimer's dementia. It is characterized by motor and nonmotor features and by a long prodromal stage that lasts many years. Genetic research has shown that PD is a complex and multisystem disorder. To capture the molecular complexity of this disease we used a complex network approach. We maximized the information entropy of the gene co-expression matrix betweenness to obtain a gene adjacency matrix; then we used a fast greedy algorithm to detect communities. Finally we applied principal component analysis on the detected gene communities, with the ultimate purpose of discriminating between PD patients and healthy controls by means of a random forests classifier. We used a publicly available substantia nigra microarray dataset, GSE20163, from NCBI GEO database, containing gene expression profiles for 10 PD patients and 18 normal controls. With this methodology we identified two gene communities that discriminated between the two groups with mean accuracy of 0.88 ± 0.03 and 0.84 ± 0.03, respectively, and validated our results on an independent microarray experiment. The two gene communities presented a considerable reduction in size, over 100 times, compared to the initial network and were stable within a range of tested parameters. Further research focusing on the restricted number of genes belonging to the selected communities may reveal essential mechanisms responsible for PD at a network level and could contribute to the discovery of new biomarkers for PD.

Creation of a gene expression classifier for predicting Parkinson's disease rate of progression

Parkinson's disease (PD) etiology is heterogeneous, genetic, and multi-factorial, resulting in a varied disease from a mild slow progression to a more severe rapid progression. Prognostic information on the nature of the patient's disease at diagnosis aids the physician in counseling patients on treatment options and life planning. In a cohort of PD patients from the PPMI study, the relative gene expression levels of SKP1A, UBE2K, ALDH1A1, PSMC4, HSPA8 and LAMB2 were measured in baseline blood samples by real-time quantitative PCR. At baseline PD patients were up to 2 years from diagnosis, H&Y scale ≤ 2 and PD treatment naïve. PD-Prediction algorithm comprised of ALDH1A1, LAMB2, UBE2K, SKP1A and age was created by logistic regression for predicting progression to ≤ 70% Modified Schwab and England Activities of Daily Living (S&E-ADL). In relation to patients negative for PD-Prediction (n = 180), patients positive (n = 30) for Cutoff-1 (at 82% specificity, 80.0% sensitivity) had positive hazard ratio (HR+) of 10.6 (95% CI, 2.2-50.1), and positive (n = 23) for Cutoff-2 (at 93% specificity, 47% sensitivity) had HR+ of 17.1 (95% CI, 3.2-89.9) to progress to ≤ 70% S&E-ADL within 3 years (P value < 0.0001). Likewise, patients positive for PD-Prediction Cutoff-1 (n = 49) had HR+ 4.3 (95% CI, 1.6-11.6) for faster time to H&Y 3 in relation to patients negative (n = 170) for PD-Prediction (P value = 0.0002). Our findings show an algorithm that seems to predict fast PD progression and may potentially be used as a tool to assist the physician in choosing an optimal treatment plan, improving the patient's quality of life and overall health outcome.

Genetic networks in Parkinson's and Alzheimer's disease

Parkinson’s disease (PD) and Alzheimer’s disease (AD) are the most common neurodegenerative diseases and there is increasing evidence that they share common physiological and pathological links. Here we have conducted the largest network analysis of PD and AD based on their gene expressions in blood to date. We identified modules that were not preserved between disease and healthy control (HC) networks, and important hub genes and transcription factors (TFs) in these modules. We highlighted that the PD module not preserved in HCs was associated with insulin resistance, and HDAC6 was identified as a hub gene in this module which may have the role of influencing tau phosphorylation and autophagic flux in neurodegenerative disease. The AD module associated with regulation of lipolysis in adipocytes and neuroactive ligand-receptor interaction was not preserved in healthy and mild cognitive impairment networks and the key hubs TRPC5 and BRAP identified as potential targets for therapeutic treatments of AD. Our study demonstrated that PD and AD share common disrupted genetics and identified novel pathways, hub genes and TFs that may be new areas for mechanistic study and important targets in both diseases.

Modified level of miR-376a is associated with Parkinson's disease

Parkinson's disease (PD) is a frequent progressive neurodegenerative disorder. Impaired mitochondrial function is a major feature of sporadic PD. Some susceptibility or causative genes detected in PD are strongly associated with mitochondrial dysfunction including PGC1α, TFAM and GSK3β. microRNAs (miRNAs) are non‐coding RNAs whose altered levels are proven in disparate PD models and human brains. Therefore, the aim of this study was to detect modulations of miRs upstream of PGC1α, TFAM and GSK3β in association with PD onset and progress. In this study, a total of 33 PD subjects and 25 healthy volunteers were recruited. Candidate miRNA (miR‐376a) was selected through target prediction tools and literature survey. Chronic and acute in vitro PD models were created by MPP⁺‐intoxicated SHSY5Y cells. The levels of miR‐376a and aforementioned genes were assessed by RT‐qPCR. The expression of target genes was decreased in chronic model while there were dramatically up‐regulated levels of those genes in acute model of PD. miR‐376a was strongly altered in both acute and chronic PD models as well as PBMCs of PD patients. Our results also showed overexpression of PGC1α, and TFAM in PBMCs is inversely correlated with down‐regulation of miR‐376a, suggesting that miR‐376a possibly has an impact on PD pathogenesis through regulation of these genes which are involved in mitochondrial function. miR‐376a expression in PD‐derived PBMCs was also correlated with disease severity and may serve as a potential biomarker for PD diagnosis. This is the first study showing altered levels of miR‐376a in PD models and PBMCs, suggesting the probable role of this miRNA in PD pathogenesis. The present study also proposed TFAM and PGC1α as target genes of miR‐376a for the first time, through which it possibly can exert its impact on PD pathogenesis.

Nuclear localization and phosphorylation modulate pathological effects of alpha-synuclein

Alpha-synuclein (aSyn) is a central player in Parkinson's disease (PD) but the precise molecular mechanisms underlying its pathogenicity remain unclear. It has recently been suggested that nuclear aSyn may modulate gene expression, possibly via interactions with DNA. However, the biological behavior of aSyn in the nucleus and the factors affecting its transcriptional role are not known. Here, we investigated the mechanisms underlying aSyn-mediated transcription deregulation by assessing its effects in the nucleus and the impact of phosphorylation in these dynamics. We found that aSyn induced severe transcriptional deregulation, including the downregulation of important cell cycle-related genes. Importantly, transcriptional deregulation was concomitant with reduced binding of aSyn to DNA. By forcing the nuclear presence of aSyn in the nucleus (aSyn-NLS), we found the accumulation of high molecular weight aSyn species altered gene expression and reduced toxicity when compared with the wild-type or exclusively cytosolic protein. Interestingly, nuclear localization of aSyn, and the effect on gene expression and cytotoxicity, was also modulated by phosphorylation on serine 129. Thus, we hypothesize that the role of aSyn on gene expression and, ultimately, toxicity, may be modulated by the phosphorylation status and nuclear presence of different aSyn species. Our findings shed new light onto the subcellular dynamics of aSyn and unveil an intricate interplay between subcellular location, phosphorylation and toxicity, opening novel avenues for the design of future strategies for therapeutic intervention in PD and other synucleinopathies.

Translocator Protein Ligand Protects against Neurodegeneration in the MPTP Mouse Model of Parkinsonism

Parkinson's disease is the second most common neurodegenerative disease, after Alzheimer's disease. Parkinson's disease is a movement disorder with characteristic motor features that arise due to the loss of dopaminergic neurons from the substantia nigra. Although symptomatic treatment by the dopamine precursor levodopa and dopamine agonists can improve motor symptoms, no disease-modifying therapy exists yet. Here, we show that Emapunil (AC-5216, XBD-173), a synthetic ligand of the translocator protein 18, ameliorates degeneration of dopaminergic neurons, preserves striatal dopamine metabolism, and prevents motor dysfunction in female mice treated with the MPTP, as a model of parkinsonism. We found that Emapunil modulates the inositol requiring kinase 1α (IRE α)/X-box binding protein 1 (XBP1) unfolded protein response pathway and induces a shift from pro-inflammatory toward anti-inflammatory microglia activation. Previously, Emapunil was shown to cross the blood-brain barrier and to be safe and well tolerated in a Phase II clinical trial. Therefore, our data suggest that Emapunil may be a promising approach in the treatment of Parkinson's disease.SIGNIFICANCE STATEMENT Our study reveals a beneficial effect of Emapunil on dopaminergic neuron survival, dopamine metabolism, and motor phenotype in the MPTP mouse model of parkinsonism. In addition, our work uncovers molecular networks which mediate neuroprotective effects of Emapunil, including microglial activation state and unfolded protein response pathways. These findings not only contribute to our understanding of biological mechanisms of translocator protein 18 (TSPO) function but also indicate that translocator protein 18 may be a promising therapeutic target. We thus propose to further validate Emapunil in other Parkinson's disease mouse models and subsequently in clinical trials to treat Parkinson's disease.

Determination of the activity of uracil-DNA glycosylase by using two-tailed reverse transcription PCR and gold nanoparticle-mediated silver nanocluster fluorescence: a new method for gene therapy-related enzyme detection

The authors present a fluorometric method for ultrasensitive determination of the activity of uracil-DNA glycosylase (UDG). It is based on the use of two-tailed reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and an entropy-driven reaction. The assay involves the following steps: (1) UDG-driven uracil excision repair, (2) two-tailed RT-qPCR-mediated amplification, (3) RNA polymerase-aided amplification, and (4) DNA-modified silver nanoclusters (AgNCs) as a transducer to produce a fluorescent signal. UDG enables uracil to be removed from U·A pairs in DNA1 and produces a depurinated/depyrimidinated site that is readily cleaved by endonuclease IV (Endo IV). The cleaved DNA contains the T7 RNA polymerase primer for the T7 RNA polymerase amplification which produces a large number of microRNA sequences. Subsequent two-tailed RT-qPCR leads to the formation of a prolonged DNA termed DNA3. The prolonged part of DNA3 is then hybridized with an added DNA4/DNA5 duplex, where DNA5 is labeled with gold nanoparticles (AuNPs), and DNA 4 is labeled with AgNCs. The AuNPs quench the fluorescence of the AgNCs. The duplex has a toehold to hybridize the prolong part of DNA3. This results in the formation of a DNA5/DNA3 duplex due to strand displacement (by replacing the DNA4 in the DNA4/DNA5 duplex). DNA4 is released and moves away from the AuNPs. This results in restored AgNC fluorescence, best measured at excitation/emission wavelengths of 575/635 nm. The method has a detection limit as low as 0.1 mU mL^-1 of UDG activity (3σ criterion) with a range of 0.001-0.01 U mL^-1. It was used to measure UDG activity in cell lysates. Conceivably, it may be used to screen for UDG inhibitors such as Ugi. Graphical abstract Schematic presentation of the two-tailed RT-qPCR assay platform for ultrasensitive detection of uracil-DNA glycosylase (UDG). Two-tailed RT-qPCR-mediated amplification and RNA polymerase-aided amplification are utilized for signal amplification. DNA-modified silver nanoclusters (AgNCs) are used as a transducer to produce a fluorescent signal.

Exploring MicroRNA Biomarkers for Parkinson's Disease from mRNA Expression Profiles

Parkinson's disease (PD) is a chronic, progressive neurodegenerative disease characterized by both motor and nonmotor features. The diagnose of PD is based on a review of patients' signs and symptoms, and neurological and physical examinations. So far, no tests have been devised that can conclusively diagnose PD. In this study, we explore both microRNA and gene biomarkers for PD. Microarray gene expression profiles for PD patients and healthy control are analyzed using a principal component analysis (PCA)-based unsupervised feature extraction (FE). 244 genes are selected to be potential gene biomarkers for PD. In addition, we implement these genes into Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and find that the 15 microRNAs (miRNAs), hsa-miR-92a-3p, 16-5p, 615-3p, 877-3p, 100-5p, 320a, 877-5p, 23a-3p, 484, 23b-3p, 15a-5p, 324-3p, 19b-3p, 7b-5p and 505-3p, significantly target these 244 genes. These miRNAs are shown to be significantly related to PD. This reveals that both selected genes and miRNAs are potential biomarkers for PD.

Alpha-synuclein deregulates the expression of COL4A2 and impairs ER-Golgi function

Alpha-synuclein (aSyn) is the major protein component of Lewy bodies and Lewy neurites, the typical pathological hallmarks in Parkinson's disease (PD) and Dementia with Lewy bodies. aSyn is capable of inducing transcriptional deregulation, but the precise effect of specific aSyn mutants associated with familial forms of PD, remains unclear. Here, we used transgenic mice overexpressing human wild-type (WT) or A30P aSyn to compare the transcriptional profiles of the two animal models. We found that A30P aSyn promotes strong transcriptional deregulation and increases DNA binding. Interestingly, COL4A2, a major component of basement membranes, was found to be upregulated in both A30P aSyn transgenic mice and in dopaminergic neurons expressing A30P aSyn, suggesting a crucial role for collagen related genes in aSyn-induced toxicity. Finally, we observed that A30P aSyn alters Golgi morphology and increases the susceptibility to endoplasmic reticulum (ER) stress in dopaminergic cells. In total, our findings provide novel insight into the putative role of aSyn on transcription and on the molecular mechanisms involved, thereby opening novel avenues for future therapeutic interventions in PD and other synucleinopathies.

Progression Rate Associated Peripheral Blood Biomarkers of Parkinson's Disease

Parkinson disease (PD) is one of the most frequent neurodegenerative disorders. The aim of this study was to identify blood biomarkers capable to discriminate PD patients with different progression rates. Differentially expressed genes (DEGs) were acquired by comparing the expression profiles of PD patients with rapid and slow progression rates, using an expression dataset from Gene Expression Omnibus (GEO) under accession code of GSE80599. Altered biological processes and pathways were revealed by functional annotation. Potential biomarkers of PD were identified by protein-protein interaction (PPI) network analysis. Critical transcription factors (TFs) and miRNAs regulating DEGs were predicted by TF analysis and miRNA analysis. A total of 225 DEGs were identified between PD patients with rapid and slow progression profiles. These genes were significantly enriched in biological processes and pathways related to fatty acid metabolism. Among these DEGs, ZFAND4, SRMS, UBL4B, PVALB, DIRAS1, PDP2, LRCH1, and MYL4 were potential progression rate associated biomarkers of PD. Additionally, these DEGs may be regulated by miRNAs of the miR-30 family and TFs STAT1 and GRHL3. Our results may contribute to our understanding of the molecular mechanisms underlying different PD progression profiles.

Gene co-expression network analysis for identifying genetic markers in Parkinson's disease - a three-way comparative approach

Parkinson's disease (PD) is a neurodegenerative disorder involving progressive deterioration of dopaminergic neurons. Although few genetic markers for familial PD are known, the etiology of sporadic PD remains poorly understood. Microarray data was analysed for induced pluripotent stem cells (iPSCs) derived from PD patients and mature neuronal cells (mDA) differentiated from these iPSCs. Combining expression and semantic similarity, a highly-correlated PD interactome was constructed that included interactions of established Parkinson's disease marker genes. A novel three-way comparative approach was employed, delineating topologically and functionally important genes. These genes showed involvement in pathways like Parkin-ubiquitin proteosomal system (UPS), immune associated biological processes and apoptosis. Of interest are three genes, eEF1A1, CASK, and PSMD6 that are linked to PARK2 activity in the cell and thereby form attractive candidate genes for understanding PD. Network biology approach delineated in this study can be applied to other neurodegenerative disorders for identification of important genetic regulators.

Correction: Gene Expression Differences in Peripheral Blood of Parkinson's Disease Patients with Distinct Progression Profiles

[This corrects the article DOI: 10.1371/journal.pone.0157852.].

Association of polymorphisms and reduced expression levels of the NR4A2 gene with Parkinson's disease in a Mexican population

INTRODUCTION

The NR4A2 transcription factor is important in the development, survival and phenotype of dopaminergic neurons and it is postulated as a possible biomarker for Parkinson's disease (PD). Therefore, our aim was to analyze in a sample of a Mexican population with idiopathic PD, mutations (in two hotspot mutation regions) and two polymorphisms (rs34884856 in promotor and rs35479735 intronic regions) of the NR4A2 gene. We also evaluate the levels of NR4A2 gene expression in peripheral blood for a Mexican population, and identify whether they are associated with NR4A2 gene polymorphisms.

METHODS

We conducted a case-control study, which included 227 idiopathic PD cases and 454 unrelated controls. Genetic variants of the NR4A2 gene were genotyped by high-resolution melting (HRM) and validated by an automated sequencing method. The gene expression was performed in peripheral blood using a real-time polymerase chain reaction.

RESULTS

The rs35479735 polymorphism was associated with a higher risk of developing PD. In addition, NR4A2 gene expression was significantly decreased in patients with PD. Linkage disequilibrium analysis showed a haplotype H4 (3C-3G) that showed lower levels of expression, and contained the risk alleles for both polymorphisms.

CONCLUSIONS

In summary, this is the first study in a Mexican population that considers the analysis of NR4A2 in patients with PD. An association was identified between genotype and mRNA expression levels of NR4A2 in patients with PD. These results suggest that polymorphisms and expression of the NR4A2 gene could play an important role in the risk of developing PD in Mexican populations.

Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program

Biomarkers for Parkinson's disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP. We discuss the role of the PDBP in PD biomarker identification and present guidelines to facilitate their development. These guidelines include: harmonizing procedures for biofluid acquisition and clinical assessments, replication of the most promising biomarkers, support and encouragement of publications that report negative findings, longitudinal follow-up of current cohorts including the PDBP, testing of wearable technologies to capture readouts between study visits and development of recently diagnosed (de novo) cohorts to foster identification of the earliest markers of disease onset.

Assessment of brain reference genes for RT-qPCR studies in neurodegenerative diseases

Evaluation of gene expression levels by reverse transcription quantitative real-time PCR (RT-qPCR) has for many years been the favourite approach for discovering disease-associated alterations. Normalization of results to stably expressed reference genes (RGs) is pivotal to obtain reliable results. This is especially important in relation to neurodegenerative diseases where disease-related structural changes may affect the most commonly used RGs. We analysed 15 candidate RGs in 98 brain samples from two brain regions from Alzheimer’s disease (AD), Parkinson’s disease (PD), Multiple System Atrophy, and Progressive Supranuclear Palsy patients. Using RefFinder, a web-based tool for evaluating RG stability, we identified the most stable RGs to be UBE2D2, CYC1, and RPL13 which we recommend for future RT-qPCR studies on human brain tissue from these patients. None of the investigated genes were affected by experimental variables such as RIN, PMI, or age. Findings were further validated by expression analyses of a target gene GSK3B, known to be affected by AD and PD. We obtained high variations in GSK3B levels when contrasting the results using different sets of common RG underlining the importance of a priori validation of RGs for RT-qPCR studies.