Integrating Pathways of Parkinson's Disease in a Molecular Interaction Map

Parkinson's disease (PD) is a major neurodegenerative chronic disease, most likely caused by a complex interplay of genetic and environmental factors. Information on various aspects of PD pathogenesis is rapidly increasing and needs to be efficiently organized, so that the resulting data is available for exploration and analysis. Here we introduce a computationally tractable, comprehensive molecular interaction map of PD. This map integrates pathways implicated in PD pathogenesis such as synaptic and mitochondrial dysfunction, impaired protein degradation, alpha-synuclein pathobiology and neuroinflammation. We also present bioinformatics tools for the analysis, enrichment and annotation of the map, allowing the research community to open new avenues in PD research. The PD map is accessible at http://minerva.uni.lu/pd_map.     

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions.     

Mapping Spatiotemporal Microproteomics Landscape in Experimental Model of Traumatic Brain Injury Unveils a link to Parkinson's Disease,

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Highlights

• •Spatiotemporal microproteomics analysis of TBI.
• •Injury site microproteomics reveal distinct phases in 10-day frame post TBI.
• •Uninjured proteomic profile is restored in TBI at 10 days post injury.
• •Substantia nigra protein post 3 days suggest link to Parkinson's disease.

     

Mass Spectrometry–Based Proteomics Analysis of Human Substantia Nigra From Parkinson's Disease Patients Identifies Multiple Pathways Potentially Involved in the Disease

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra (SN) of the brain. Despite decades of studies, the precise pathogenic mechanism of PD is still elusive. An unbiased proteomic analysis of PD patient’s brain allows the identification of critical proteins and molecular pathways that lead to dopamine cell death and α-synuclein deposition and the resulting devastating clinical symptoms. In this study, we conducted an in-depth proteome analysis of human SN tissues from 15 PD patients and 15 healthy control individuals combining Orbitrap mass spectrometry with the isobaric tandem mass tag–based multiplexing technology. We identified 10,040 proteins with 1140 differentially expressed proteins in the SN of PD patients. Pathway analysis showed that the ribosome pathway was the most enriched one, followed by gamma-aminobutyric acidergic synapse, retrograde endocannabinoid signaling, cell adhesion molecules, morphine addiction, Prion disease, and PD pathways. Strikingly, the majority of the proteins enriched in the ribosome pathway were mitochondrial ribosomal proteins (mitoribosomes). The subsequent protein–protein interaction analysis and the weighted gene coexpression network analysis confirmed that the mitoribosome is the most enriched protein cluster. Furthermore, the mitoribosome was also identified in our analysis of a replication set of ten PD and nine healthy control SN tissues. This study provides potential disease pathways involved in PD and paves the way to study further the pathogenic mechanism of PD.     

Molecular Biology of Catecholamine-Related Enzymes in Relation to Parkinson's Disease

1. Catecholamine (dopamine, norepinephrine, and epinephrine) biosynthesis is regulated by tyrosine hydroxylase (TH). TH activity is regulated by the concentration of the cofactor tetrahydrobiopterin (BH4), whose level is regulated by GTP cyclohydrolase I (GCH) activity. Thus, GCH activity indirectly regulates TH activity and catecholamine levels.2. TH activity in the nigrostriatal dopaminergic neurons is most sensitive to the decrease in BH4.3. Mutations of GCH result in reductions in GCH activity, BH4, TH activity, and dopamine, causing either recessively inherited GCH deficiency or dominantly inherited hereditary progressive dystonia [HPD; Segawa's disease; also called dopa-responsive dystonia (DRD)].4. In juvenile parkinsonism and Parkinson's disease, which have dopamine deficiency in the basal ganglia as HPD/DRD, the GCH gene may be normal, and the molecular mechanism of the dopamine deficiency in the basal ganglia is different from that in HPD/DRD.     

Network Analysis Identifies SOD2 mRNA as a Potential Biomarker for Parkinson's Disease

Increasing evidence indicates that Parkinson''s disease (PD) and type 2 diabetes (T2DM) share dysregulated molecular networks. We identified 84 genes shared between PD and T2DM from curated disease-gene databases. Nitric oxide biosynthesis, lipid and carbohydrate metabolism, insulin secretion and inflammation were identified as common dysregulated pathways. A network prioritization approach was implemented to rank genes according to their distance to seed genes and their involvement in common biological pathways. Quantitative polymerase chain reaction assays revealed that a highly ranked gene, superoxide dismutase 2 (SOD2), is upregulated in PD patients compared to healthy controls in 192 whole blood samples from two independent clinical trials, the Harvard Biomarker Study (HBS) and the Diagnostic and Prognostic Biomarkers in Parkinson''s disease (PROBE). The results from this study reinforce the idea that shared molecular networks between PD and T2DM provides an additional source of biologically meaningful biomarkers. Evaluation of this biomarker in de novo PD patients and in a larger prospective longitudinal study is warranted.     

Automated Network Analysis Identifies Core Pathways in Glioblastoma

Background

Glioblastoma multiforme (GBM) is the most common and aggressive type of brain tumor in humans and the first cancer with comprehensive genomic profiles mapped by The Cancer Genome Atlas (TCGA) project. A central challenge in large-scale genome projects, such as the TCGA GBM project, is the ability to distinguish cancer-causing “driver” mutations from passively selected “passenger” mutations.

Principal Findings

In contrast to a purely frequency based approach to identifying driver mutations in cancer, we propose an automated network-based approach for identifying candidate oncogenic processes and driver genes. The approach is based on the hypothesis that cellular networks contain functional modules, and that tumors target specific modules critical to their growth. Key elements in the approach include combined analysis of sequence mutations and DNA copy number alterations; use of a unified molecular interaction network consisting of both protein-protein interactions and signaling pathways; and identification and statistical assessment of network modules, i.e. cohesive groups of genes of interest with a higher density of interactions within groups than between groups.

Conclusions

We confirm and extend the observation that GBM alterations tend to occur within specific functional modules, in spite of considerable patient-to-patient variation, and that two of the largest modules involve signaling via p53, Rb, PI3K and receptor protein kinases. We also identify new candidate drivers in GBM, including AGAP2/CENTG1, a putative oncogene and an activator of the PI3K pathway; and, three additional significantly altered modules, including one involved in microtubule organization. To facilitate the application of our network-based approach to additional cancer types, we make the method freely available as part of a software tool called NetBox.     

Mutational Analysis of Angiogenin Gene in Parkinson's Disease

Mutations in the angiogenic factor, angiogenin (ANG), have been identified in patients with both familial and sporadic amyotrophic lateral sclerosis (ALS) and are thought to have a neuroprotective function. Parkinsonism has been noted in kindreds with ANG mutations and variants in the ANG gene have been found to associate with PD in two Caucasian populations. We therefore hypothesized that mutations in ANG may also contribute to idiopathic Parkinson''s disease (PD). We sequenced ANG gene in a total of 1498 participants comprising 750 PD patients and 748 age/gender matched controls from Taiwan. We identified one novel synonymous substitution, c.C100T (p.L10L), in a single heterozygous state in one PD patient, which was not observed in controls. The clinical phenotypes and [^99mTc]-TORDAT-SPECT images of the p.L10L carrier were similar to that seen in idiopathic PD. In addition, we also identified one common variant, c.T330G (p.G110G, rs11701), which was previously reported to associate with PD risk in Caucasians. However, the frequency of TG/GG genotype was comparable between PD cases and controls (odds ratio: 0.85, 95% confidence interval: 0.29–2.55, P = 0.78). Our results did not support that ANG rs11701 variant is a genetic risk factor for PD in our population. We conclude that mutations in ANG are not a common cause for idiopathic PD.     

Integrative Pathway-Based Approach for Genome-Wide Association Studies: Identification of New Pathways for Rheumatoid Arthritis and Type 1 Diabetes

Genome-wide association studies (GWAS) led to the identification of numerous novel loci for a number of complex diseases. Pathway-based approaches using genotypic data provide tangible leads which cannot be identified by single marker approaches as implemented in GWAS. The available pathway analysis approaches mainly differ in the employed databases and in the applied statistics for determining the significance of the associated disease markers.So far, pathway-based approaches using GWAS data failed to consider the overlapping of genes among different pathways or the influence of protein–interactions. We performed a multistage integrative pathway (MIP) analysis on three common diseases - Crohn''s disease (CD), rheumatoid arthritis (RA) and type 1 diabetes (T1D) - incorporating genotypic, pathway, protein- and domain-interaction data to identify novel associations between these diseases and pathways. Additionally, we assessed the sensitivity of our method by studying the influence of the most significant SNPs on the pathway analysis by removing those and comparing the corresponding pathway analysis results. Apart from confirming many previously published associations between pathways and RA, CD and T1D, our MIP approach was able to identify three new associations between disease phenotypes and pathways. This includes a relation between the influenza-A pathway and RA, as well as a relation between T1D and the phagosome and toxoplasmosis pathways. These results provide new leads to understand the molecular underpinnings of these diseases.The developed software herein used is available at http://www.cogsys.cs.uni-tuebingen.de/software/GWASPathwayIdentifier/index.htm.     

Comparative Efficacy and Acceptability of Antidepressants in Parkinson's Disease: A Network Meta-Analysis

Background

Depression is a common non-motor symptom in patients with Parkinson''s disease (PD). There are many kinds of antidepressants being used, such as tricyclic antidepressants (TCAs), selective serotonin reuptake inhibitors (SSRIs), serotonin and norepinephrine reuptake inhibitors (SNRIs), and Dopamine agonists which are suggested as alternative antidepressants for the treatment of depression in PD. Which one should we choose first? Literatures have shown inconsistent results.

Methods

We conducted a network meta-analysis of randomized controlled trials to compare the efficacy and acceptability of therapeutic methods for the treatment of depression in Parkinson''s disease.

Results

We used the odds ratios (OR) as effect size firstly and the results indicated no statistical significance between each compared intervention. Then we used the logarithm of the individual odds ratios as effect size. With efficacy of TCAs as the standard of comparison, the degree of incoherence (a measure of how closely the entire network fits together) was small (ω =  4.824827e-05). The logor were: SSRIs −0.69 (95% CI −1.28– −0.10); Pramipexole −0.73 (−1.71– −0.26); Pergolide −1.97 (−3.67– 0.27); SNRIs −0.86 (−1.86– 0.15); Placebo −1.24 (−1.99– −0.50). With Placebo as the standard of comparison, the logor were: TCAs 1.24 (0.50– 1.99); SSRIs 0.55 (−0.03– 1.13); Pramipexole 0.51 (−0.12– 1.15); Pergolide −0.73 (−2.25– 0.80); SNRIs 0.38 (−0.42– 1.19); TCAs, pramipexole, pergolide and SNRIs showed better profile of acceptability, leading to significant fewer discontinuations than that of SSRIs.

Conclusions

There is insufficient evidence to support antidepressant efficacy for SSRIs, pramipexole, pergolide and SNRIs. TCAs might be the best choice when starting antidepressant treatment in patients of Parkinson''s disease because it has the most favorable balance between benefits and acceptability, followed by pramipexole and SNRIs, SSRIs might be the last choice.     

Molecular Docking-Based Identification of Potential Natural Neuroprotective Molecules for Parkinson's Disease

Background: Parkinson's disease (PD) is a common progressive neurodegenerative and the prevailing treatments are ineffective in the early stages of the disease. Therefore, other strategies must be devised to halt the steady decrease of dopaminergic neurons in the brain. In Parkinson's disease, a dysregulated ACE/Ang II/AT1R axis in the brain causes free radical damage, apoptosis, and neuronal destruction. Current PD treatments only alleviate symptoms and do not reverse the degradation mechanism of dopaminergic neurons. As a result, it is critical to discover alternate, dependable medicines for the treatment of Parkinson's disease. Method : In the present study, homology modelling of MAS receptor, in silico docking and molecular dynamic studies (MDS) were employed to determine the efficacy of flavonoids as MASR activators. Result : The flavonoids Pterosupin and Amentoflavone exhibited best binding and therefore, the stability of these complexes were evaluated with MDS studies. The Pterosupin-MASR complex demonstrated better stability, stronger interactions and minimal fluctuation than the Amentoflavone-MASR complex. Conclusion : The data from the present study indicated that the flavonoid Pterosupin possesses better binding, favourable pharmacokinetic properties and stability. However, subsequent in vitro and in vivo assessments are necessary to validate its efficacy.     

Olfactory Functions in Parkinson's Disease and Alzheimer's Disease

The aim of this investigation was to compare olfactory functionsof patients suffering from Parkinson's disease (PD) and Alzheimer'sdisease (AD). Olfactory threshold, odor identification abilityand odor memory performance were assessed in 21 non-dementedPD patients and in 22 AD patients. Both patient groups wereimpaired in relation to an age-matched control group for themeasure of odor identification. AD patients showed a higherolfactory threshold and poorer odor memory performance. ChemSenses 22: 105–110, 1997.     

iBIG: An Integrative Network Tool for Supporting Human Disease Mechanism Studies

Understanding the mechanism of complex human diseases is a major scientific challenge. Towards this end, we developed a web-based network tool named iBIG (stands for integrative BIoloGy), which incorporates a variety of information on gene interaction and regulation. The generated network can be annotated with various types of information and visualized directly online. In addition to the gene networks based on physical and pathway interactions, networks at a functional level can also be constructed. Furthermore, a supplementary R package is provided to process microarray data and generate a list of important genes to be used as input for iBIG. To demonstrate its usefulness, we collected 54 microarrays on common human diseases including cancer, neurological disorders, infectious diseases and other common diseases. We processed the microarray data with our R package and constructed a network of functional modules perturbed in common human diseases. Networks at the functional level in combination with gene networks may provide new insight into the mechanism of human diseases. iBIG is freely available at http://lei.big.ac.cn/ibig.