A network view on Parkinson's disease

Unraveling the role of miRNAs in the diagnosis, progression, and therapeutic intervention of Parkinson's disease

Parkinson's disease (PD) is a debilitating neurological disorder characterized by the impairment of the motor system, resulting in symptoms such as resting tremor, cogwheel rigidity, bradykinesia, difficulty with gait, and postural instability. The occurrence of striatal dopamine insufficiency can be attributed to a notable decline in dopaminergic neurons inside the substantia nigra pars compacta. Additionally, the development of Lewy bodies serves as a pathological hallmark of PD. While current therapy approaches for PD aim to preserve dopaminergic neurons or replenish dopamine levels in the brain, it is important to acknowledge that achieving complete remission of the condition remains elusive. MicroRNAs (miRNAs, miR) are a class of small, non-coding ribonucleic acids involved in regulating gene expression at the post-transcriptional level. The miRNAs play a crucial part in the underlying pathogenic mechanisms of several neurodegenerative illnesses, including PD. The aim of this review is to explore the role of miRNAs in regulating genes associated with the onset and progression of PD, investigate the potential of miRNAs as a diagnostic tool, assess the effectiveness of targeting specific miRNAs as an alternative therapeutic strategy to impede disease advancement, and discuss the utilization of newly developed nanoparticles for delivering miRNAs as neurodegenerative therapies.

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.

Proteins and Transcriptional Dysregulation of the Brain Extracellular Matrix in Parkinson's Disease: A Systematic Review

The extracellular matrix (ECM) of the brain is a dynamic structure made up of a vast network of bioactive macromolecules that modulate cellular events. Structural, organizational, and functional changes in these macromolecules due to genetic variation or environmental stressors are thought to affect cellular functions and may result in disease. However, most mechanistic studies to date usually focus on the cellular aspects of diseases and pay less attention to the relevance of the processes governing the dynamic nature of the extracellular matrix in disease pathogenesis. Thus, due to the ECM's diversified biological roles, increasing interest in its involvement in disease, and the lack of sufficient compiled evidence regarding its relationship with Parkinson's disease (PD) pathology, we aimed to compile the existing evidence to boost the current knowledge on the area and provide refined guidance for the future research. Here, in this review, we gathered postmortem brain tissue and induced pluripotent stem cell (iPSC)-related studies from PubMed and Google Scholar to identify, summarize and describe common macromolecular alterations in the expression of brain ECM components in Parkinson's disease (PD). A literature search was conducted up until 10 February 2023. The overall hits from the database and manual search for proteomic and transcriptome studies were 1243 and 1041 articles, respectively. Following a full-text review, 10 articles from proteomic and 24 from transcriptomic studies were found to be eligible for inclusion. According to proteomic studies, proteins such as collagens, fibronectin, annexins, and tenascins were recognized to be differentially expressed in Parkinson's disease. Transcriptomic studies displayed dysregulated pathways including ECM-receptor interaction, focal adhesion, and cell adhesion molecules in Parkinson's disease. A limited number of relevant studies were accessed from our search, indicating that much work remains to be carried out to better understand the roles of the ECM in neurodegeneration and Parkinson's disease. However, we believe that our review will elicit focused primary studies and thus support the ongoing efforts of the discovery and development of diagnostic biomarkers as well as therapeutic agents for Parkinson's disease.

Activation of Embryonic Gene Transcription in Neural Precursor Cells Derived from the Induced Pluripotent Stem Cells of the Patients with Parkinson's Disease

Parkinson's disease (PD) is one of the most common neurodegenerative diseases in the world. Despite numerous studies, the causes of this pathology remain completely unknown. This is, among other things, due to the difficulty of obtaining biological material for analysis. Neural cell cultures derived from the induced pluripotent stem cells (IPSCs) provide a great potential for studying molecular events underlying the pathogenesis of PD. This paper presents the results of bioinformatic analysis of the data obtained using RNA-seq technology in the study of neural precursors (NP) derived from IPSCs of the healthy donors and patients with PD carrying various mutations that are commonly associated with familial PD. This analysis showed that the level of transcription of multiple genes actively expressed in the nervous system at the embryonic stage of development was significantly increased in the NP cells obtained from the patients with PD, unlike in the case of healthy donors. Bioinformatic data have been, in general, confirmed using real-time PCR. The obtained data suggest that one of the causes of PD may be the shift of the gene expression pattern in neuronal cells towards embryonic gene expression pattern (termed dematuration).

Modelling the Human Blood-Brain Barrier in Huntington Disease

While blood–brain barrier (BBB) dysfunction has been described in neurological disorders, including Huntington’s disease (HD), it is not known if endothelial cells themselves are functionally compromised when promoting BBB dysfunction. Furthermore, the underlying mechanisms of BBB dysfunction remain elusive given the limitations with mouse models and post mortem tissue to identify primary deficits. We established models of BBB and undertook a transcriptome and functional analysis of human induced pluripotent stem cell (iPSC)-derived brain-like microvascular endothelial cells (iBMEC) from HD patients or unaffected controls. We demonstrated that HD-iBMECs have abnormalities in barrier properties, as well as in specific BBB functions such as receptor-mediated transcytosis.

Light-Sensitive Lactococcus lactis for Microbe-Gut-Brain Axis Regulating via Upconversion Optogenetic Micro-Nano System

The discovery of the gut-brain axis has proven that brain functions can be affected by the gut microbiota's metabolites, so there are significant opportunities to explore new tools to regulate gut microbiota and thus work on the brain functions. Meanwhile, engineered bacteria as oral live biotherapeutic agents to regulate the host's healthy homeostasis have attracted much attention in microbial therapy. However, whether this strategy is able to remotely regulate the host's brain function in vivo has not been investigated. Here, we engineered three blue-light-responsive probiotics as oral live biotherapeutic agents. They are spatiotemporally delivered and controlled by the upconversion optogenetic micro-nano system. This micro-nano system promotes the small intestine targeting and production of the exogenous L. lactis in the intestines, which realizes precise manipulation of brain functions including anxiety behavior, Parkinson's disease, and vagal afferent. The noninvasive and real-time probiotic intervention strategy makes the communiation from the gut to the host more controllable, which will enable the potential for engineered microbes accurately and effectively regulating a host's health.

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.

Expression Analysis of NF-κB-Related lncRNAs in Parkinson's Disease

Parkinson’s disease (PD) has been shown to affect approximately 1% of the persons aged more than 65 years. This multifactorial disorder has been associated with abnormal function of NF-κB signals. In this research, we have evaluated expressions of NF-κB-related long non-coding RNAs in the circulation of PD patients compared with healthy controls. Expression of PACER was lower in total PD patients compared with healthy persons (Ratio of mean expressions (RME)=0.32, P value<0.001). This pattern was also evident among males (RME=0.25, P value<0.001). Expression of DILC was higher in total PD patients (RME=4.07, P value<0.001), and in both sex-based subgroups (RME=3.77, P value=0.01 and RME=4.25, P value<0.001, for females and males, respectively). Similarly, CEBPA was significantly over-expressed in total PD patients (RME=14.76, P value<0.001), and in both sex-based subgroups (RME=12.42, P value<0.001 and RME=15.80, P value<0.001, for females and males, respectively). ATG5 had a similar expression pattern (RME=2.6, P value=1E-08, RME=1.73, P value=0.03 and RME=3.09, P value=1E-07, for total cases, females and males, respectively). H19 was up-regulated in total cases and male cases compared with corresponding controls (RME=2.19, P value<0.001, RME=2.68, P value=0.01, respectively). Finally, HNFA1-AS was down-regulated in all comparisons (RME=0.10, P value=2E-06, RME=0.08, P value<0.001 and RME=0.12, P value<0.001, for total cases, females and males, respectively). Among PD patients, expressions of NKILA and ADINR were robustly correlated with each other (r=0.75, P value=2.40E-10). In addition, expression levels of DICER1-AS were significantly correlated with those of ADINR, PACER and H19 in these patients (r=0.73, P value=1.76E-9; r=0.72, P value=5.15E-09 and r=0.72, P value=3.09E-09, respectively). Correlation analyses among healthy controls revealed robust correlations between CHAST and CEBPA (r=0.84, P value=3.09E-09), NKILA and ADINR (r=0.80, P value=4.24E-12) as well as between DILC and CHAST (r=0.76, P value=1.70E-10). CEBPA had the best parameters among all assessed genes (AUC=0.96, Sensitivity=0.90 and specificity=0.97). DILC and ATG5 were the most appropriate markers after CEBPA with AUC values of 0.82 and 0.80, respectively. Most notably, combination of all genes improved AUC, sensitivity and specificity parameters to 1, 0.97 and 0.99, respectively. Cumulatively, the current study provides evidence for participation of NF-κB-related lncRNAs in the pathoetiology of PD.

Investigation of Therapeutic Response Markers for Acupuncture in Parkinson's Disease: An Exploratory Pilot Study

In this preliminary pilot study, we investigated the specific genes implicated in the therapeutic response to acupuncture in patients with Parkinson’s disease (PD). Transcriptome alterations following acupuncture in blood samples collected during our previous clinical trial were analyzed along with the clinical data of six patients with PD, of which a representative patient was selected for transcriptomic analysis following acupuncture. We also examined the changes in the expression of PD biomarker genes known to be dysregulated in both the brain and blood of patients with PD. We validated these gene expression changes using quantitative real-time polymerase chain reaction (qPCR) in the blood of the remaining five patients with PD who received acupuncture treatment. Following acupuncture treatment, the transcriptomic alterations in the representative patient were similar to those induced by dopaminergic therapy. Among the PD biomarkers, ankyrin repeat domain 22 (ANKRD22), upregulated following dopaminergic therapy, and synapsin 1 (SYN1), a common gene marker for synaptic dysfunction in PD, were upregulated following acupuncture. These alterations correlated with changes in gait parameters in patients with PD. Our data suggest ANKRD22 and SYN1 as potential biomarkers to predict/monitor therapeutic responses to acupuncture in patients with PD, especially in those with gait disturbance. Further research is needed to confirm these findings in a large sample of patients with PD.

Up-regulated microRNA-218-5p ameliorates the damage of dopaminergic neurons in rats with Parkinson's disease via suppression of LASP1

OBJECTIVE

Parkinson's disease (PD) is a frequent degenerative disease of the nervous system with undefined pathogenesis. This study explored the protective effect of microRNA (miR)-218-5p on dopaminergic neuron injury in substantia nigra (SN) of rats with PD through the regulation of LIM and SH3 domain protein 1 (LASP1).

METHODS

The PD rat model was established by fixed point injection of 6-hydroxydopamine into the rats. The PD rats were injected with miR-218-5p overexpressed recombinant adeno-associated virus (rAAV) or LASP1 silenced rAAV to explore their roles in dopaminergic neurons in SN of rats with PD. The changes in pathological structure of SN were observed and the expression of tyrosine hydroxylase (TH) and deacetylvindoline acetyltransferase (DAT), the dopaminergic neuron apoptosis and oxidative stress factor in the SN were detected. The expression of miR-218-5p, LASP1, Bcl-2 and Bax in SN was detected. The targeting relationship between miR-218-5p and LASP1 was confirmed.

RESULTS

Declined miR-218-5p and overexpressed LASP1 existed in the brain SN of PD rats. Up-regulated miR-218-5p or inhibited LASP1 improved the pathological damage of dopaminergic neurons and increased the number of TH and DAT positive cells in brain SN of PD rats. Furthermore, elevated miR-218-5p or depressed LASP1 inhibited the apoptosis, and oxidative stress of dopaminergic neurons in brain SN of PD rats. In addition, increased miR-218-5p repressed the expression of LASP1 in the brain SN of PD rats. LASP1 was proven to be a direct target of miR-218-5p.

CONCLUSION

The study highlights that up-regulated miR-218-5p could improve the damage of dopaminergic neurons in PD rats, which was related to the inhibition of LASP1.

Non-Coding RNAs in the Brain-Heart Axis: The Case of Parkinson's Disease

Parkinson's disease (PD) is a complex and heterogeneous disorder involving multiple genetic and environmental influences. Although a wide range of PD risk factors and clinical markers for the symptomatic motor stage of the disease have been identified, there are still no reliable biomarkers available for the early pre-motor phase of PD and for predicting disease progression. High-throughput RNA-based biomarker profiling and modeling may provide a means to exploit the joint information content from a multitude of markers to derive diagnostic and prognostic signatures. In the field of PD biomarker research, currently, no clinically validated RNA-based biomarker models are available, but previous studies reported several significantly disease-associated changes in RNA abundances and activities in multiple human tissues and body fluids. Here, we review the current knowledge of the regulation and function of non-coding RNAs in PD, focusing on microRNAs, long non-coding RNAs, and circular RNAs. Since there is growing evidence for functional interactions between the heart and the brain, we discuss the benefits of studying the role of non-coding RNAs in organ interactions when deciphering the complex regulatory networks involved in PD progression. We finally review important concepts of harmonization and curation of high throughput datasets, and we discuss the potential of systems biomedicine to derive and evaluate RNA biomarker signatures from high-throughput expression data.

Common gene expression signatures in Parkinson's disease are driven by changes in cell composition

The etiology of Parkinson’s disease is largely unknown. Genome-wide transcriptomic studies in bulk brain tissue have identified several molecular signatures associated with the disease. While these studies have the potential to shed light into the pathogenesis of Parkinson’s disease, they are also limited by two major confounders: RNA post-mortem degradation and heterogeneous cell type composition of bulk tissue samples. We performed RNA sequencing following ribosomal RNA depletion in the prefrontal cortex of 49 individuals from two independent case-control cohorts. Using cell type specific markers, we estimated the cell type composition for each sample and included this in our analysis models to compensate for the variation in cell type proportions. Ribosomal RNA depletion followed by capture by random primers resulted in substantially more even transcript coverage, compared to poly(A) capture, in post-mortem tissue. Moreover, we show that cell type composition is a major confounder of differential gene expression analysis in the Parkinson’s disease brain. Accounting for cell type proportions attenuated numerous transcriptomic signatures that have been previously associated with Parkinson’s disease, including vesicle trafficking, synaptic transmission, immune and mitochondrial function. Conversely, pathways related to endoplasmic reticulum, lipid oxidation and unfolded protein response were strengthened and surface as the top differential gene expression signatures in the Parkinson’s disease prefrontal cortex. Our results indicate that differential gene expression signatures in Parkinson’s disease bulk brain tissue are significantly confounded by underlying differences in cell type composition. Modeling cell type heterogeneity is crucial in order to unveil transcriptomic signatures that represent regulatory changes in the Parkinson’s disease brain and are, therefore, more likely to be associated with underlying disease mechanisms.

Cerebrospinal fluid proteomics implicates the granin family in Parkinson's disease

Parkinson's disease, the most common age-related movement disorder, is a progressive neurodegenerative disease with unclear etiology. Better understanding of the underlying disease mechanism(s) is an urgent need for the development of disease-modifying therapeutics. Limited studies have been performed in large patient cohorts to identify protein alterations in cerebrospinal fluid (CSF), a proximal site to pathology. We set out to identify disease-relevant protein changes in CSF to gain insights into the etiology of Parkinson's disease and potentially assist in disease biomarker identification. In this study, we used liquid chromatography-tandem mass spectrometry in data-independent acquisition (DIA) mode to identify Parkinson's-relevant biomarkers in cerebrospinal fluid. We quantified 341 protein groups in two independent cohorts (n = 196) and a longitudinal cohort (n = 105 samples, representing 40 patients) consisting of Parkinson's disease and healthy control samples from three different sources. A first cohort of 53 Parkinson's disease and 72 control samples was analyzed, identifying 53 proteins with significant changes (p < 0.05) in Parkinson's disease relative to healthy control. We established a biomarker signature and multiple protein ratios that differentiate Parkinson's disease from healthy controls and validated these results in an independent cohort. The second cohort included 28 Parkinson's disease and 43 control samples. Independent analysis of these samples identified 41 proteins with significant changes. Evaluation of the overlapping changes between the two cohorts identified 13 proteins with consistent and significant changes (p < 0.05). Importantly, we found the extended granin family proteins as reduced in disease, suggesting a potential common mechanism for the biological reduction in monoamine neurotransmission in Parkinson's patients. Our study identifies several novel protein changes in Parkinson's disease cerebrospinal fluid that may be exploited for understanding etiology of disease and for biomarker development.

Inference on chains of disease progression based on disease networks

MOTIVATION

Disease progression originates from the concept that an individual disease may go through different changes as it evolves, and such changes can cause new diseases. It is important to find a progression between diseases since knowing the prior-posterior relationship beforehand can prevent further complications or evolutions to other diseases. Furthermore, the series of progressions can be represented in the form of a chain, which enables us to readily infer successive influences from one disease to another after many passages through other diseases.

METHODS

In this paper, we propose a systematic approach for finding a disease progression chain from a source disease to a target one via exploring a disease network. The network is constructed based on various sets of biomedical data. To find the most influential progression chains, the k-shortest path search algorithm is employed. The most representative algorithms such as A*, Dijkstra, and Yen's are incorporated into the proposed method.

RESULTS

A disease network consisting of 3,302 diseases was constructed based on four sources of biomedical data: disease-protein relations, biological pathways, clinical history, and biomedical literature information. The last three sets of data contain prior-posterior information, and they endow directionality on the edges of the network. The results were interesting and informative: for example, when colitis and respiratory insufficiency were set as a source disease and a target one, respectively, five progression chains were found within several seconds (when k = 5). Each chain was provided with a progression score, which indicates the strength of plausibility relative to others. Similarly, the proposed method can be expanded to any pair of source-target diseases in the network. This can be utilized as a preliminary tool for inferring complications or progressions between diseases.

Panoramic Visualization of Circulating MicroRNAs Across Neurodegenerative Diseases in Humans

Neurodegenerative diseases (NDs) such as Alzheimer’s disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and dementia pose one of the greatest health challenges this century. Although these NDs have been looked at as single entities, the underlying molecular mechanisms have never been collectively visualized to date. With the advent of high-throughput genomic and proteomic technologies, we now have the opportunity to visualize these diseases in a whole new perspective, which will provide a clear understanding of the primary and secondary events vital in achieving the final resolution of these diseases guiding us to new treatment strategies to possibly treat these diseases together. We created a knowledge base of all microRNAs known to be differentially expressed in various body fluids of ND patients. We then used several bioinformatic methods to understand the functional intersections and differences between AD, PD, ALS, and MS. These results provide a unique panoramic view of possible functional intersections between AD, PD, MS, and ALS at the level of microRNA and their cognate genes and pathways, along with the entities that unify and separate them. While the microRNA signatures were apparent for each ND, the unique observation in our study was that hsa-miR-30b-5p overlapped between all four NDS, and has significant functional roles described across NDs. Furthermore, our results also show the evidence of functional convergence of miRNAs which was associated with the regulation of their cognate genes represented in pathways that included fatty acid synthesis and metabolism, ECM receptor interactions, prion diseases, and several signaling pathways critical to neuron differentiation and survival, underpinning their relevance in NDs. Envisioning this group of NDs together has allowed us to propose new ways of utilizing circulating miRNAs as biomarkers  and in visualizing diverse NDs more holistically . The critical molecular insights gained through the discovery of ND-associated miRNAs, overlapping miRNAs, and the functional convergence of microRNAs on vital pathways strongly implicated in neurodegenerative processes can prove immensely valuable in the identifying new generation of biomarkers, along with the development of miRNAs into therapeutics.

Endoplasmic reticulum stress induced autophagy in 6-OHDA-induced Parkinsonian rats

Both endoplasmic reticulum (ER) stress and autophagy involve in the pathological process of Parkinson's disease (PD). But the relationship between them is not clear in PD. A 6-OHDA-induced parkinsonian rat is recognized as a standard model for many years, and it can be used in experimental study. The glucose regulated protein 78 (GRP78) is a master regulator of ER stress, and the C/EBP homologous binding protein (CHOP) is an indicator of the UPR signaling. Besides, the Beclin-1 is also well known as a regulator of autophagy, and P62 is a specific marker to monitor autophagy. Therefore, we investigated the expressions of GRP78, CHOP, Beclin-1 and P62 in 6-OHDA-induced parkinsonian rat. Unilateral 6-OHDA injection into medial forebrain bundle was used except sham-operated rats. The rats were randomly divided into 6 groups: a sham-operated group; a model group; a 3-methyladenine (3-MA) group, administered 3-MA---autophagy inhibitor; a rapamycin group, administered rapamycin---autophagy inducer; a 4-phenylbutyric acids (4-PBA) group, administered 4-PBA---ER stress inhibitor; a tunicamycin (TM) group, administered TM---ER stress inducer. The results showed that the expressions of GRP78, CHOP and Beclin-1 increased, P62 decreased in model group; the expressions of GRP78 and CHOP were unchanged in 3-MA group and rapamycin group; but the expression of Beclin-1 decreased and P62 increased in 4-PBA group, while the expression of Beclin-1 increased and P62 decreased in TM group. These data suggest that ER stress and autophagy occurred in 6-OHDA-induced parkinsonian rat, and ER stress might induce autophagy. The result is important for the pathological mechanism of PD.

A Meta-Analysis of Alzheimer's Disease Brain Transcriptomic Data

BACKGROUND

Microarray technologies have identified imbalances in the expression of specific genes and biological pathways in Alzheimer's disease (AD) brains. However, there is a lack of reproducibility across individual AD studies, and many related neurodegenerative and mental health disorders exhibit similar perturbations.

OBJECTIVE

Meta-analyze publicly available transcriptomic data from multiple brain-related disorders to identify robust transcriptomic changes specific to AD brains.

METHODS

Twenty-two AD, eight schizophrenia, five bipolar disorder, four Huntington's disease, two major depressive disorder, and one Parkinson's disease dataset totaling 2,667 samples and mapping to four different brain regions (temporal lobe, frontal lobe, parietal lobe, and cerebellum) were analyzed. Differential expression analysis was performed independently in each dataset, followed by meta-analysis using a combining p-value method known as Adaptively Weighted with One-sided Correction.

RESULTS

Meta-analysis identified 323, 435, 1,023, and 828 differentially expressed genes specific to the AD temporal lobe, frontal lobe, parietal lobe, and cerebellum brain regions, respectively. Seven of these genes were consistently perturbed across all AD brain regions with SPCS1 gene expression pattern replicating in RNA-Seq data. A further nineteen genes were perturbed specifically in AD brain regions affected by both plaques and tangles, suggesting possible involvement in AD neuropathology. In addition, biological pathways involved in the "metabolism of proteins" and viral components were significantly enriched across AD brains.

CONCLUSION

This study identified transcriptomic changes specific to AD brains, which could make a significant contribution toward the understanding of AD disease mechanisms and may also provide new therapeutic targets.

Computational systems biology approaches for Parkinson's disease

Parkinson's disease (PD) is a prime example of a complex and heterogeneous disorder, characterized by multifaceted and varied motor- and non-motor symptoms and different possible interplays of genetic and environmental risk factors. While investigations of individual PD-causing mutations and risk factors in isolation are providing important insights to improve our understanding of the molecular mechanisms behind PD, there is a growing consensus that a more complete understanding of these mechanisms will require an integrative modeling of multifactorial disease-associated perturbations in molecular networks. Identifying and interpreting the combinatorial effects of multiple PD-associated molecular changes may pave the way towards an earlier and reliable diagnosis and more effective therapeutic interventions. This review provides an overview of computational systems biology approaches developed in recent years to study multifactorial molecular alterations in complex disorders, with a focus on PD research applications. Strengths and weaknesses of different cellular pathway and network analyses, and multivariate machine learning techniques for investigating PD-related omics data are discussed, and strategies proposed to exploit the synergies of multiple biological knowledge and data sources. A final outlook provides an overview of specific challenges and possible next steps for translating systems biology findings in PD to new omics-based diagnostic tools and targeted, drug-based therapeutic approaches.

A workflow for the integrative transcriptomic description of molecular pathology and the suggestion of normalizing compounds, exemplified by Parkinson's disease

The volume of molecular observations on human diseases in public databases is continuously increasing at accelerating rates. A bottleneck is their computational integration into a coherent description, from which researchers may derive new well-founded hypotheses. Also, the need to integrate data from different technologies (genetics, coding and regulatory RNA, proteomics) emerged in order to identify biomarkers for early diagnosis and prognosis of complex diseases and therefore facilitating the development of novel treatment approaches. We propose here a workflow for the integrative transcriptomic description of the molecular pathology in Parkinsons’s Disease (PD), including suggestions of compounds normalizing disease-induced transcriptional changes as a paradigmatic example. We integrated gene expression profiles, miRNA signatures, and publicly available regulatory databases to specify a partial model of the molecular pathophysiology of PD. Six genetic driver elements (2 genes and 4 miRNAs) and several functional network modules that are associated with PD were identified. Functional modules were assessed for their statistical significance, cellular functional homogeneity, literature evidence, and normalizing small molecules. In summary, our workflow for the joint regulatory analysis of coding and non-coding RNA, has the potential to yield clinically as well as biologically relevant information, as demonstrated here on PD data.

Microarray analysis of an synthetic α-synuclein induced cellular model reveals the expression profile of long non-coding RNA in Parkinson's disease

Long non-coding RNAs (lncRNAs) are a new research focus that are reported to influence the pathogenetic process of neurodegenerative disorders. To uncover new disease-associated genes and their relevant mechanisms, we carried out a gene microarray analysis based on a Parkinson's disease (PD) in vitro model induced by α-synuclein oligomers. This cellular model induced by 25 μmol/L α-synuclein oligomers has been confirmed to show the stable, transmissible neurotoxicity of α-synuclein, a typical PD pathological marker. And several differentially expressed lncRNAs and mRNAs were identified in this model, such as G046036, G030771, AC009365.4, RPS14P3, CTB-11I22.1, and G007549. Subsequent ceRNA analysis determined the potential relationships between these lncRNAs and their associated mRNAs and microRNAs. The results of the present study widen our horizon of PD susceptibility genes and provide new pathways towards efficient diagnostic biomarkers and therapeutic targets for PD.

Exploring the anti-proliferative activity of Pelargonium sidoides DC with in silico target identification and network pharmacology

Pelargonium sidoides DC (Geraniaceae) is a medicinal plant indigenous to Southern Africa that has been widely evaluated for its use in the treatment of upper respiratory tract infections. In recent studies, the anti-proliferative potential of P. sidoides was shown, and several phenolic compounds were identified as the bioactive compounds. Little, however, is known regarding their anti-proliferative protein targets. In this study, the anti-proliferative mechanisms of P. sidoides through in silico target identification and network pharmacology methodologies were evaluated. The protein targets of the 12 phenolic compounds were identified using the target identification server PharmMapper and the server for predicting Drug Repositioning and Adverse Reactions via the Chemical-Protein Interactome (DRAR-CPI). Protein-protein and protein-pathway interaction networks were subsequently constructed with Cytoscape 3.4.0 to evaluate potential mechanisms of action. A total of 142 potential human target proteins were identified with the in silico target identification servers, and 90 of these were found to be related to cancer. The protein interaction network was constructed from 86 proteins involved in 209 interactions with each other, and two protein clusters were observed. A pathway enrichment analysis identified over 80 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched with the protein targets and included several pathways specifically related to cancer as well as various signaling pathways that have been found to be dysregulated in cancer. These results indicate that the anti-proliferative activity of P. sidoides may be multifactorial and arises from the collective regulation of several interconnected cell signaling pathways.

Parkinson's disease: SNCA-, PARK2-, and LRRK2- targeting microRNAs elevated in cingulate gyrus

INTRODUCTION

In order to better understand the role of epigenetic influences in the etiology of Parkinson's disease (PD), we studied the expression of microRNAs in gyri cinguli of patients and controls.

METHODS

Expression profiling of 744 well-characterized microRNAs in gyri cinguli from patients and controls using TaqMan array microRNA cards. Verification of significantly dysregulated microRNAs by SYBR Green qRT-PCR.

RESULTS

First screen by TaqMan array identified 43 microRNAs that were upregulated in gyri cinguli from patients. Of those microRNAs, 13 are predicted to regulate at least one of six genes mutated in monogenic forms of PD (DJ-1, PARK2, PINK1, LRRK2, SNCA, and HTRA2). Five of these 13 microRNAs (-144, -199b, -221, -488, -544) were also found upregulated by SYBR Green qRT-PCR and are predicted to regulate either SNCA, PARK2, LRRK2 or combinations thereof. Consistently, expression of SNCA, PARK2, and LRRK2 was reduced in patients. An additional 5 out of ten potential target genes tested were downregulated. These are DRAM (DNA damage regulated autophagy modulator 1), predicted to be regulated by miR-144, EVC (Ellis Van Creveld Protein) by miR-221, ZNF440 (Zinc Finger Protein 440) by miR-199b, MTFMT (Mitochondrial Methionyl-tRNA Formyltransferase) by miR-488 and XIRP2 (Xin Actin Binding Repeat Containing) possibly controlled by miR-544a.

CONCLUSION

The study identified five microRNAs that play a role in the etiology of Parkinson's disease likely by modifying expression of SNCA, PARK2, LRRK2 and additional genes required for normal cellular function.

Extracellular vesicles in neurodegenerative disease - pathogenesis to biomarkers

To develop effective disease-modifying therapies for neurodegenerative diseases, reliable markers of diagnosis, disease activity and progression are a research priority. The fact that neurodegenerative pathology is primarily associated with distinct subsets of cells in discrete areas of the CNS makes the identification of relevant biomarker molecules a challenge. The trafficking of macromolecules from the CNS to the cerebrospinal fluid and blood, mediated by extracellular vesicles (EVs), presents a promising source of CNS-specific biomarkers. EVs are released by almost all cell types and carry a cargo of protein and nucleic acid that varies according to the cell of origin. EV output changes with cell status and reflects intracellular events, so surface marker expression can be used to identify the cell type from which EVs originate. EVs could, therefore, provide an enriched pool of information about core neuropathogenic, cell-specific processes. This Review examines the current knowledge of the biology and function of EVs, discusses the evidence for their involvement in the pathogenesis of neurodegenerative diseases, and considers their potential as biomarkers of disease.

Genome-wide association study of periweaning failure-to-thrive syndrome (PFTS) in pigs

Porcine periweaning-failure-to-thrive syndrome (PFTS) is a condition that affects newly weaned piglets. It is characterised by a progressive debilitation leading to death, in the absence of infectious, nutritional, management or environmental factors. In this study, we present the first report of PFTS in South America and the results of a genome-wide association study to identify the genetic markers associated with the appearance of this condition in a crossbred swine population. Four chromosomal regions were associated with PFTS predisposition, one located on SSCX, one on SSC8, and the two other regions on SSC14. Regions on SSC8 and SSC14 harbour important functional candidate genes involved in human depression and might have an important role in PFTS. Our findings contribute to the increasing knowledge about this syndrome, which has been investigated since 2007, and to the identification of the aetiology of this disease.

Efficient and biologically relevant consensus strategy for Parkinson's disease gene prioritization

BACKGROUND

The systemic information enclosed in microarray data encodes relevant clues to overcome the poorly understood combination of genetic and environmental factors in Parkinson's disease (PD), which represents the major obstacle to understand its pathogenesis and to develop disease-modifying therapeutics. While several gene prioritization approaches have been proposed, none dominate over the rest. Instead, hybrid approaches seem to outperform individual approaches.

METHODS

A consensus strategy is proposed for PD related gene prioritization from mRNA microarray data based on the combination of three independent prioritization approaches: Limma, machine learning, and weighted gene co-expression networks.

RESULTS

The consensus strategy outperformed the individual approaches in terms of statistical significance, overall enrichment and early recognition ability. In addition to a significant biological relevance, the set of 50 genes prioritized exhibited an excellent early recognition ability (6 of the top 10 genes are directly associated with PD). 40 % of the prioritized genes were previously associated with PD including well-known PD related genes such as SLC18A2, TH or DRD2. Eight genes (CCNH, DLK1, PCDH8, SLIT1, DLD, PBX1, INSM1, and BMI1) were found to be significantly associated to biological process affected in PD, representing potentially novel PD biomarkers or therapeutic targets. Additionally, several metrics of standard use in chemoinformatics are proposed to evaluate the early recognition ability of gene prioritization tools.

CONCLUSIONS

The proposed consensus strategy represents an efficient and biologically relevant approach for gene prioritization tasks providing a valuable decision-making tool for the study of PD pathogenesis and the development of disease-modifying PD therapeutics.

PINK1 Deficiency Decreases Expression Levels of mir-326, mir-330, and mir-3099 during Brain Development and Neural Stem Cell Differentiation

PTEN-induced putative kinase 1 (PINK1) is a Parkinson's disease (PD) gene. We examined miRNAs regulated by PINK1 during brain development and neural stem cell (NSC) differentiation, and found that lvels of miRNAs related to tumors and inflammation were different between 1-day-old-wild type (WT) and PINK1-knockout (KO) mouse brains. Notably, levels of miR-326, miR-330 and miR-3099, which are related to astroglioma, increased during brain development and NSC differentiation, and were significantly reduced in the absence of PINK1. Interestingly, in the presence of ciliary neurotrophic factor (CNTF), which pushes differentiation of NSCs into astrocytes, miR-326, miR-330, and miR-3099 levels in KO NSCs were also lower than those in WT NSCs. Furthermore, mimics of all three miRNAs increased expression of the astrocytic marker glial fibrillary acidic protein (GFAP) during differentiation of KO NSCs, but inhibitors of these miRNAs decreased GFAP expression in WT NSCs. Moreover, these miRNAs increased the translational efficacy of GFAP through the 3'-UTR of GFAP mRNA. Taken together, these results suggest that PINK1 deficiency reduce expression levels of miR-326, miR-330 and miR-3099, which may regulate GFAP expression during NSC differentiation and brain development.

Network analysis of human post-mortem microarrays reveals novel genes, microRNAs, and mechanistic scenarios of potential importance in fighting huntington's disease

Huntington's disease is a progressive neurodegenerative disorder characterized by motor disturbances, cognitive decline, and neuropsychiatric symptoms. In this study, we utilized network-based analysis in an attempt to explore and understand the underlying molecular mechanism and to identify critical molecular players of this disease condition. Using human post-mortem microarrays from three brain regions (cerebellum, frontal cortex and caudate nucleus) we selected in a four-step procedure a seed set of highly modulated genes. Several protein-protein interaction networks, as well as microRNA-mRNA networks were constructed for these gene sets with the Elsevier Pathway Studio software and its associated ResNet database. We applied a gene prioritizing procedure based on vital network topological measures, such as high node connectivity and centrality. Adding to these criteria the guilt-by-association rule and exploring their innate biomolecular functions, we propose 19 novel genes from the analyzed microarrays, from which CEBPA, CDK1, CX3CL1, EGR1, E2F1, ERBB2, LRP1, HSP90AA1 and ZNF148 might be of particular interest for experimental validation. A possibility is discussed for dual-level gene regulation by both transcription factors and microRNAs in Huntington's disease mechanism. We propose several possible scenarios for experimental studies initiated via the extra-cellular ligands TGFB1, FGF2 and TNF aiming at restoring the cellular homeostasis in Huntington's disease.

Network Topology Analysis of Post-Mortem Brain Microarrays Identifies More Alzheimer's Related Genes and MicroRNAs and Points to Novel Routes for Fighting with the Disease

Network-based approaches are powerful and beneficial tools to study complex systems in their entirety, elucidating the essential factors that turn the multitude of individual elements into a functional system. In this study we used critical network topology descriptors and guilt-by-association rule to explore and understand the significant molecular players, drug targets and underlying biological mechanisms of Alzheimer’s disease. Analyzing two post-mortem brain gene microarrays (GSE4757 and GSE28146) with Pathway Studio software package we constructed and analyzed a set of protein-protein interaction, as well as miRNA-target networks. In a 4-step procedure the expression datasets were normalized using Robust Multi-array Average approach, while the modulation of gene expression by the disease was statistically evaluated by the empirical Bayes method from the limma Bioconductor package. Representative set of 214 seed-genes (p<0.01) common for the three brain sections of the two microarrays was thus created. The Pathway Studio analysis of the networks built identified 15 new potential AD-related genes and 17 novel AD-involved microRNAs. Using KEGG pathways relevant in Alzheimer’s disease we built an integrated mechanistic network from the interactions between the overlapping genes in these pathways. Routes of possible disease initiation process were thus revealed through the CD4, DCN, and IL8 extracellular ligands. DAVID and IPA enrichment analysis uncovered a number of deregulated biological processes and pathways including neuron projection/differentiation, aging, oxidative stress, chemokine/ neurotrophin signaling, long-term potentiation and others. The findings in this study offer information of interest for subsequent experimental studies.

Neurological Diseases from a Systems Medicine Point of View

The difficulty to understand, diagnose, and treat neurological disorders stems from the great complexity of the central nervous system on different levels of physiological granularity. The individual components, their interactions, and dynamics involved in brain development and function can be represented as molecular, cellular, or functional networks, where diseases are perturbations of networks. These networks can become a useful research tool in investigating neurological disorders if they are properly tailored to reflect corresponding mechanisms. Here, we review approaches to construct networks specific for neurological disorders describing disease-related pathology on different scales: the molecular, cellular, and brain level. We also briefly discuss cross-scale network analysis as a necessary integrator of these scales.

MicroRNA machinery in Parkinson's disease: a platform for neurodegenerative diseases

MicroRNAs (miRNAs) are noncoding RNAs that recognize their protein-coding target genes and whereby subjugate them after transcription. Despite the infancy of this field of science, the role of miRNAs in neurodegeneration is well-acknowledged. This review was conducted to indicate that Parkinson's disease (PD) is not excluded from this rule. To this end, we evaluated the existing literature and arranged PD-associated miRNAs according to their mechanism of action, particularly apoptosis, autophagy, inflammation, mitochondrial dysfunction and oxidative stress. According to this arrangement, a majority of PD-associated miRNAs were indicated to influence autophagic/apoptotic pathways. We also categorized PD-associated miRNAs according to that they could exert detrimental or beneficial or both into three sets, activator, inhibitor, and double-edged, correspondingly. Considering this criterion, a majority of PD-associated miRNAs were included in the activator category. In addition, evidences from genetic association studies investigating genetic variants of or related to miRNAs in PD patients are presented. Finally, possible applications of the miRNA machinery in PD, including mechanistic networks, diagnostic, prognostic and therapeutic potentials, are discussed. But there may be additional miRNAs involved in the pathogenesis of PD which have hitherto remained unknown and thus further studies are needed to explore the issue and to extend this platform.