Biological networks in Parkinson's disease: an insight into the epigenetic mechanisms associated with this disease

Multi-Ancestry Transcriptome-Wide Association Studies of Cognitive Function, White Matter Hyperintensity, and Alzheimer's Disease

Genetic variants increase the risk of neurocognitive disorders in later life, including vascular dementia (VaD) and Alzheimer's disease (AD), but the precise relationships between genetic risk factors and underlying disease etiologies are not well understood. Transcriptome-wide association studies (TWASs) can be leveraged to better characterize the genes and biological pathways underlying genetic influences on disease. To date, almost all existing TWASs on VaD and AD have been conducted using expression studies from individuals of a single genetic ancestry, primarily European. Using the joint likelihood-based inference framework in Multi-ancEstry TRanscriptOme-wide analysis (METRO), we leveraged gene expression data from European ancestry (EA) and African ancestry (AA) samples to identify genes associated with general cognitive function, white matter hyperintensity (WMH), and AD. Regions were fine-mapped using Fine-mapping Of CaUsal gene Sets (FOCUS). We identified 266, 23, 69, and 2 genes associated with general cognitive function, WMH, AD (using EA GWAS summary statistics), and AD (using AA GWAS), respectively (Bonferroni-corrected alpha = p < 2.9 × 10-6), some of which had been previously identified. Enrichment analysis showed that many of the identified genes were in pathways related to innate immunity, vascular dysfunction, and neuroinflammation. Further, the downregulation of ICA1L was associated with a higher WMH and with AD, indicating its potential contribution to overlapping AD and VaD neuropathology. To our knowledge, our study is the first TWAS on cognitive function and neurocognitive disorders that used expression mapping studies for multiple ancestries. This work may expand the benefits of TWASs beyond a single ancestry group and help to identify gene targets for pharmaceuticals or preventative treatments for dementia.

Uncovering potential molecular markers and pathological mechanisms of Parkinson's disease and myocardial infarction based on bioinformatics analysis

BACKGROUND

The direct association between Parkinson's disease (PD) and Myocardial infarction (MI) has been the subject of relatively limited research.

OBJECTIVE

The purpose of this study was to identify the genes most associated with PD and MI to explore their common pathogenesis.

METHODS

The gene expression profiles of PD and MI were downloaded from GEO database. Differential expression analysis was performed to identify the common differential expression genes (DEGs) of PD and MI, followed by functional annotation. Subsequently, protein-protein interaction network were constructed, and hub DEGs were identified based on CytoHubba plugin and LASSO regression analysis. To explore the potential molecular mechanism of hub DEGs, GSEA analysis, immune correlation analysis, drug prediction and molecular docking were performed, and transcription factors (TF) and lncRNA-miRNA-mRNA (ceRNA) regulatory networks were constructed.

RESULTS

A total of 48 DEGs with the same expression trend were identified in the MI vs. normal control (NC) and PD vs. NC groups. Functional annotation results showed that the common DEGs were significantly enriched in immune and inflammation-related pathways. RPS4Y1 and UTY were the most relevant hub DEGs for PD and MI, and may be involved in the HALLMARK_MYC_TARGETS_V1 and HALLMARK_PROTEIN_SECRETION pathways. TP63 was a common TF of RPS4Y1 and UTY. The PVT1/KCNQ1OT1-hsa-miR-31-5p-RPS4Y1 and KCNQ1OT1-hsa-let-7a-5p/hsa-miR-19b-3p-UTY axes may play an important role in regulating PD and MI. CYCLOHEXIMIDE and ATALAREN may be potential drugs for the treatment of PD and MI comorbidity. In addition, PD and MI exhibit different patterns of immune cell infiltration and immune function status, which may be related to the specific pathological processes of the disease.

CONCLUSIONS

This study revealed for the first time that RPS4Y1 and UTY may be common biomarkers of PD and MI and may be potential therapeutic targets. This study provides new perspective on the common molecular mechanisms between PD and MI.

Identification of diagnose related therapeutic targets of Danggui buxue decoction in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is the fastest growing neurological disease. Currently, there is no disease-modifying therapy to slow the progression of the disease. Danggui buxue decoction (DBD) is widely used in the clinic because of its therapeutic effect. However, little is known about the molecular mechanism of DBD against PD. This study intends to explore the possible molecular mechanisms involved in DBD treatment of PD based on network pharmacology, and provide potential research directions for future research.

METHODS

Firstly, the active components and target genes of DBD were screened from the traditional Chinese medicine systems pharmacology (TCMSP), DrugBank and UniProt database. Secondly, target genes of PD were identified from the (GEO) dataset, followed by identification of common target genes of DBD and PD. Thirdly, analysis of protein-protein interaction (PPI), functional enrichment and diagnosis was performed on common target genes, followed by correlation analysis between core target genes, immune cell, miRNAs, and transcription factors (TFs). Finally, molecular docking between core target genes and active components, and real-time PCR were performed.

RESULTS

A total of 72 common target genes were identified between target genes of DBD and target genes of PD. Among which, 11 target genes with potential diagnostic value were further identified, including TP53, AKT1, IL1B, MMP9, NOS3, RELA, MAPK14, HMOX1, TGFB1, NOS2, and ERBB2. The combinations with the best docking binding were identified, including kaempferol-AKT1/HMOX1/NOS2/NOS3, quercetin-AKT1/ERBB2/IL1B/HMOX1/MMP9/TP53/NOS3/TGFB1. Moreover, IL1B and NOS2 respectively positively and negatively correlated with neutrophil and Type 1 T helper cell. Some miRNA-core target gene regulatory pairs were identified, such as hsa-miR-185-5p-TP53/TGFB1/RELA/MAPK14/IL1B/ERBB2/AKT1 and hsa-miR-214-3p-NOS3. These core target genes were significantly enriched in focal adhesion, TNF, HIF-1, and ErbB signaling pathway.

CONCLUSION

Diagnostic TP53, AKT1, IL1B, MMP9, NOS3, RELA, MAPK14, HMOX1, TGFB1, NOS2, and ERBB2 may be considered as potential therapeutic targets of DBD in the treatment of PD.

Unraveling Dysregulated Cell Signaling Pathways, Genetic and Epigenetic Mysteries of Parkinson's Disease

Parkinson's disease (PD) is a prevalent and burdensome neurodegenerative disorder that has been extensively researched to understand its complex etiology, diagnosis, and treatment. The interplay between genetic and environmental factors in PD makes its pathophysiology difficult to comprehend, emphasizing the need for further investigation into genetic and epigenetic markers involved in the disease. Early diagnosis is crucial for optimal management of the disease, and the development of novel diagnostic biomarkers is ongoing. Although many efforts have been made in the field of recognition and interpretation of the mechanisms involved in the pathophysiology of the disease, the current knowledge about PD is just the tip of the iceberg. By scrutinizing genetic and epigenetic patterns underlying PD, new avenues can be opened for dissecting the pathology of the disorder, leading to more precise and efficient diagnostic and therapeutic approaches. This review emphasizes the importance of studying dysregulated cell signaling pathways and molecular processes associated with genes and epigenetic alterations in understanding PD, paving the way for the development of novel therapeutic strategies to combat this devastating disease.

ISLET: individual-specific reference panel recovery improves cell-type-specific inference

We propose a statistical framework ISLET to infer individual-specific and cell-type-specific transcriptome reference panels. ISLET models the repeatedly measured bulk gene expression data, to optimize the usage of shared information within each subject. ISLET is the first available method to achieve individual-specific reference estimation in repeated samples. Using simulation studies, we show outstanding performance of ISLET in the reference estimation and downstream cell-type-specific differentially expressed genes testing. We apply ISLET to longitudinal transcriptomes profiled from blood samples in a large observational study of young children and confirm the cell-type-specific gene signatures for pancreatic islet autoantibody. ISLET is available at https://bioconductor.org/packages/ISLET .

Neuroprotective effects of GSK-343 in an in vivo model of MPTP-induced nigrostriatal degeneration

Parkinson's disease (PD) is characterized by the degeneration of dopaminergic nigrostriatal neurons, which causes disabling motor disorders. Scientific findings support the role of epigenetics mechanism in the development and progression of many neurodegenerative diseases, including PD. In this field, some studies highlighted an upregulation of Enhancer of zeste homolog 2 (EZH2) in the brains of PD patients, indicating the possible pathogenic role of this methyltransferase in PD. The aim of this study was to evaluate the neuroprotective effects of GSK-343, an EZH2 inhibitor, in an in vivo model of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced dopaminergic degeneration. Specifically, nigrostriatal degeneration was induced by MPTP intraperitoneal injection. GSK-343 was administered intraperitoneally daily at doses of 1 mg/kg, 5 mg/kg and 10 mg/kg, mice were killed 7 days after MPTP injection. Our results demonstrated that GSK-343 treatment significantly improved behavioral deficits and reduced the alteration of PD hallmarks. Furthermore, GSK-343 administration significantly attenuated the neuroinflammatory state through the modulation of canonical and non-canonical NF-κB/IκBα pathway as well as the cytokines expression and glia activation, also reducing the apoptosis process. In conclusion, the obtained results provide further evidence that epigenetic mechanisms play a pathogenic role in PD demonstrating that the inhibition of EZH2, mediated by GSK-343, could be considered a valuable pharmacological strategy for PD.

DNA methylation as a mediator of genetic and environmental influences on Parkinson's disease susceptibility: Impacts of alpha-Synuclein, physical activity, and pesticide exposure on the epigenome

Parkinson's disease (PD) is a neurodegenerative disorder with a complex etiology and increasing prevalence worldwide. As PD is influenced by a combination of genetic and environment/lifestyle factors in approximately 90% of cases, there is increasing interest in identification of the interindividual mechanisms underlying the development of PD as well as actionable lifestyle factors that can influence risk. This narrative review presents an outline of the genetic and environmental factors contributing to PD risk and explores the possible roles of cytosine methylation and hydroxymethylation in the etiology and/or as early-stage biomarkers of PD, with an emphasis on epigenome-wide association studies (EWAS) of PD conducted over the past decade. Specifically, we focused on variants in the SNCA gene, exposure to pesticides, and physical activity as key contributors to PD risk. Current research indicates that these factors individually impact the epigenome, particularly at the level of CpG methylation. There is also emerging evidence for interaction effects between genetic and environmental contributions to PD risk, possibly acting across multiple omics layers. We speculated that this may be one reason for the poor replicability of the results of EWAS for PD reported to date. Our goal is to provide direction for future epigenetics studies of PD to build upon existing foundations and leverage large datasets, new technologies, and relevant statistical approaches to further elucidate the etiology of this disease.

A co-expression network based molecular characterization of genes responsive for Braak stages in Parkinson's disease

The progression of Parkinson's disease (PD) is defined by six Braak stages. We used transcriptome data from PD patients with Braak stage information to understand underlying molecular mechanisms for the progress of the disease. We created networks of genes with decreased/increased co-expression from control group to Braak 5-6 stages. These networks are significantly associated with PD related mechanisms such as mitochondrial dysfunction and synaptic signaling among others. Applying Weighted Gene Correlation Network Analysis (WGCNA) algorithm to the co-expression networks led to more specific modules enriched with neurodegeneration related disease pathways, seizure, abnormality of coordination, and hypotonia. Furthermore, we showed that one of the co-expression networks is clustered into three major communities with dedicated molecular functions: (i) tubulin folding pathway, gap junction related mechanisms, neuronal system (ii) synaptic vesicle, intracellular vesicle, proteasome complex, PD genes (iii) energy metabolism, mitochondrial mechanisms, oxidative phosphorylation, TCA cycle, PD genes. The co-expression relations we identified in this study as crucial players in the disease progression cover several known PD-associated genes and genes whose products are known to physically interact with alpha-synuclein protein.

Dynamic changes in immune gene co-expression networks predict development of type 1 diabetes

Significant progress has been made in elucidating genetic risk factors influencing Type 1 diabetes (T1D); however, features other than genetic variants that initiate and/or accelerate islet autoimmunity that lead to the development of clinical T1D remain largely unknown. We hypothesized that genetic and environmental risk factors can both contribute to T1D through dynamic alterations of molecular interactions in physiologic networks. To test this hypothesis, we utilized longitudinal blood transcriptomic profiles in The Environmental Determinants of Diabetes in the Young (TEDDY) study to generate gene co-expression networks. In network modules that contain immune response genes associated with T1D, we observed highly dynamic differences in module connectivity in the 600 days (~ 2 years) preceding clinical diagnosis of T1D. Our results suggest that gene co-expression is highly plastic and that connectivity differences in T1D-associated immune system genes influence the timing and development of clinical disease.

Histone Methylation Regulation in Neurodegenerative Disorders

Advances achieved with molecular biology and genomics technologies have permitted investigators to discover epigenetic mechanisms, such as DNA methylation and histone posttranslational modifications, which are critical for gene expression in almost all tissues and in brain health and disease. These advances have influenced much interest in understanding the dysregulation of epigenetic mechanisms in neurodegenerative disorders. Although these disorders diverge in their fundamental causes and pathophysiology, several involve the dysregulation of histone methylation-mediated gene expression. Interestingly, epigenetic remodeling via histone methylation in specific brain regions has been suggested to play a critical function in the neurobiology of psychiatric disorders, including that related to neurodegenerative diseases. Prominently, epigenetic dysregulation currently brings considerable interest as an essential player in neurodegenerative disorders, such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), Amyotrophic lateral sclerosis (ALS) and drugs of abuse, including alcohol abuse disorder, where it may facilitate connections between genetic and environmental risk factors or directly influence disease-specific pathological factors. We have discussed the current state of histone methylation, therapeutic strategies, and future perspectives for these disorders. While not somatically heritable, the enzymes responsible for histone methylation regulation, such as histone methyltransferases and demethylases in neurons, are dynamic and reversible. They have become promising potential therapeutic targets to treat or prevent several neurodegenerative disorders. These findings, along with clinical data, may provide links between molecular-level changes and behavioral differences and provide novel avenues through which the epigenome may be targeted early on in people at risk for neurodegenerative disorders.

LncRNA SNHG12 promotes proliferation and epithelial mesenchymal transition in hepatocellular carcinoma through targeting HEG1 via miR-516a-5p

Hepatocellular carcinoma (HCC) is the most common cancer and its prognosis is poor due to metastasis and recurrence. EMT is associated with metastasis. A deep understanding of regulatory mechanism of EMT is critical. LncRNA is involved in regulation of various biological processes including EMT. This study aimed to investigate the regulatory signal axis among lncRNA SNHG12, miR-516a-5p and the target gene HEG1 during EMT. Cell cycle and apoptosis were analyzed by flow cytometry. Tumorigenesis was analyzed by clone formation assay. Wound healing assay and transwell assay was performed to detect migration and invasion, respectively. Interaction among SNHG12, miR-516a-5p and HEG1 were analyzed by dual luciferase assay and RIP assay. We also detected expression of RNA and protein by QPCR and western blotting. Finally, tumor growth was analyzed by tumorigenesis assay in vivo. Ki-67 and HEG1 level in tumor tissues was analyzed by IHC. SNHG12 and HEG1 were upregulated, miR-516a-5p was downregulated in HCC cell lines. SNHG12 could interact with and inhibit miR-516a-5p. MiR-516a-5p could interact with HEG1 and inhibit HEG1 expression. Knock down SNHG12 inhibited proliferation, migration, invasion, EMT and promoted apoptosis of HCC cells. Such effects were antagonized by inhibiting miR-516a-5p. SNHG12 overexpression lead to opposite results. Similar results were observed in mice. SNHG12 could promote EMT in HCC through targeting and inhibiting miR-516a-5p, which eventually upregulated HEG1 expression, in both cell and mice.

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.

Integrated analysis of microRNA and transcription factors in the bone marrow of patients with acute monocytic leukemia

Acutemonocytic leukemia (AMoL) is a distinct subtype of acute myeloid leukemia (AML) with poor prognosis. However, the molecular mechanisms and key regulators involved in the global regulation of gene expression levels in AMoL are poorly understood. In order to elucidate the role of microRNAs (miRNAs/miRs) and transcription factors (TFs) in AMoL pathogenesis at the network level, miRNA and TF expression level profiles were systematically analyzed by miRNA sequencing and TF array, respectively; this identified 285 differentially expressed miRNAs and 139 differentially expressed TFs in AMoL samples compared with controls. By combining expression level profile data and bioinformatics tools available for predicting TF and miRNA targets, a comprehensive AMoL-specific miRNA-TF-mediated regulatory network was constructed. A total of 26 miRNAs and 23 TFs were identified as hub nodes in the network. Among these hubs, miR-29b-3p, MYC, TP53 and NFKB1 were determined to be potential AMoL regulators, and were subsequently extracted to construct sub-networks. A hypothetical pathway model was also proposed for miR-29b-3p to reveal the potential co-regulatory mechanisms of miR-29b-3p, MYC, TP53 and NFKB1 in AMoL. The present study provided an effective approach to discover critical regulators via a comprehensive regulatory network in AMoL, in addition to enhancing understanding of the pathogenesis of this disease at the molecular level.

Cognitive function: holarchy or holacracy?

Cognition is the most complex function of the brain. When exploring the inner workings of cognitive processes, it is crucial to understand the complexity of the brain's dynamics. This paper aims to describe the integrated framework of the cognitive function, seen as the result of organization and interactions between several systems and subsystems. We briefly describe several organizational concepts, spanning from the reductionist hierarchical approach, up to the more dynamic theory of open complex systems. The homeostatic regulation of the mechanisms responsible for cognitive processes is showcased as a dynamic interplay between several anticorrelated mechanisms, which can be found at every level of the brain's organization, from molecular and cellular level to large-scale networks (e.g., excitation-inhibition, long-term plasticity-long-term depression, synchronization-desynchronization, segregation-integration, order-chaos). We support the hypothesis that cognitive function is the consequence of multiple network interactions, integrating intricate relationships between several systems, in addition to neural circuits.

Protein Interaction Studies for Understanding the Tremor Pathway in Parkinson's Disease

BACKGROUND

Tremor is one of the most noticeable features, which occurs during the early stages of Parkinson's Disease (PD). It is one of the major pathological hallmarks and does not have any interpreted mechanism. In this study, we have framed a hypothesis and deciphered protein- protein interactions between the proteins involved in impairment in sodium and calcium ion channels and thus cause synaptic plasticity leading to a tremor.

METHODS

Literature mining for retrieval of proteins was done using Science Direct, PubMed Central, SciELO and JSTOR databases. A well-thought approach was used, and a list of differentially expressed proteins in PD was collected from different sources. A total of 71 proteins were retrieved, and a protein interaction network was constructed between them by using Cytoscape.v.3.7. The network was further analysed using the BiNGO plugin for retrieval of overrepresented biological processes in Tremor-PD datasets. Hub nodes were also generated in the network.

RESULTS

The Tremor-PD pathway was deciphered, which demonstrates the cascade of protein interactions that might lead to tremors in PD. Major proteins involved were LRRK2, TUBA1A, TRAF6, HSPA5, ADORA2A, DRD1, DRD2, SNCA, ADCY5, TH, etc. Conclusion: In the current study, it is predicted that ADORA2A and DRD1/DRD2 are equally contributing to the progression of the disease by inhibiting the activity of adenylyl cyclase and thereby increases the permeability of the blood-brain barrier, causing an influx of neurotransmitters and together they alter the level of dopamine in the brain which eventually leads to tremor.

Gene Prioritization in Parkinson's Disease Using Human Protein-Protein Interaction Network

Parkinson's disease (PD) is the second-most common neurodegenerative disorder, and the actual cause of this disease is still unknown. Identifying the target genes that are associated with disease plays an essential role in the treatment of PD. Various genetic studies have determined the significant target genes for disease progression, although this continues to be challenging in the field of drug designing. In this study, we proposed a network-based approach to identify target genes for PD using gene mutation, gene expression, and gene deletion analysis. The subnetwork of PD genes was constructed from human protein-protein interaction network, and the potential genes were identified using network centrality measures. Two genes, PARK1 and PARK2, were identified as target genes by integrating gene mutation and expression data into the subnetwork. Gene deletion analysis was carried out to determine the significant target, and results revealed that VDAC1 and ATP5C1 genes were crucial for the Parkinson's subnetwork. Thus, findings from the network-based approach will provide additional insight for understanding the disease mechanism of PD. Future enhancement of this study may help in predicting disease biomarkers as well as designing novel compounds in rational drug designing.

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.

Long noncoding RNA and messenger RNA abnormalities in pediatric sepsis: a preliminary study

BACKGROUND

Sepsis represents a complex disease with dysregulated inflammatory response and high mortality rate. Long noncoding RNAs (lncRNAs) have been reported to play regulatory roles in a variety of biological processes. However, studies evaluating the function of lncRNAs in pediatric sepsis are scarce, and current knowledge of the role of lncRNAs in pediatric sepsis is still limited. The present study explored the expression patterns of both lncRNAs and mRNAs between pediatric sepsis patients and healthy controls based on a comprehensive microarray analysis.

METHODS

LncRNA and mRNA microarray was used to detect the expression of lncRNAs and mRNAs in the septic and control groups. Aberrantly expressed mRNAs and lncRNAs identified were further interpreted by enrichment analysis, receiver operating characteristic (ROC) curve analysis, co-expression network analysis, and quantitative real-time PCR (qPCR).

RESULTS

A total of 1488 differetially expressed lncRNAs and 1460 differentially expressed mRNAs were identified. A co-expression network of the identified lncRNAs and mRNAs was constructed. In this network, lncRNA lnc-RP11-1220 K2.2.1-7 is correlated with mRNA CXCR1 and CLEC4D; lncRNA lnc-ANXA3-2 is correlated with mRNA CLEC4D; lncRNA lnc-TRAPPC5-1 is correlated with mRNA DYSF and HLX; lncRNA lnc-ZNF638-1 is correlated with mRNA DYSF and HLX. Significantly different expressions between pediatric sepsis patients and controls were validated by qPCR for the 4 lncRNAs and 4 co-expressed mRNAs, validating the microarray results.

CONCLUSIONS

Our study contributes to a comprehensive understading of the involvment of lncRNAs and mRNAs in pediatric sepsis, which may guide subsequent experimental research. Furthermore, our study may also provide potential candidate lncRNAs and mRNAs for the diagnosis and treatment of pediatric sepsis.

Skeletal muscle transcriptional networks linked to type I myofiber grouping in Parkinson's disease

Parkinson's disease (PD) is a common neurodegenerative disorder impacting cognition, movement, and quality of life in >10 million individuals worldwide. We recently characterized and quantified a skeletal muscle pathology in PD represented by exaggerated type I myofiber grouping presumed to result from denervation-reinnervation processes. Our previous findings indicated that impaired neuromuscular junction integrity may be involved in type I grouping, which is associated with excessive motor unit activation during weight-bearing tasks. In this study, we performed transcriptional profiling to test the hypothesis that type I grouping severity would link to distinct gene expression networks. We generated transcriptome-wide poly(A) RNA-Seq data from skeletal muscle of individuals with PD [n = 12 (9 men, 3 women); 67 ± 2 yr], age- and sex-matched older adults (n = 12; 68 ± 2 yr), and sex-matched young adults (n = 12; 30 ± 1 yr). Differentially expressed genes were evaluated across cohorts. Weighted gene correlation network analysis (WGCNA) was performed to identify gene networks most correlated with indicators of abnormal type I grouping. Among coexpression networks mapping to phenotypes pathologically increased in PD muscle, one network was highly significantly correlated to type I myofiber group size and another to percentage of type I myofibers found in groups. Annotation of coexpressed networks revealed that type I grouping is associated with altered expression of genes involved in neural development, postsynaptic signaling, cell cycle regulation and cell survival, protein and energy metabolism, inflammation/immunity, and posttranscriptional regulation (microRNAs). These transcriptomic findings suggest that skeletal muscle may play an active role in signaling to promote myofiber survival, reinnervation, and remodeling, perhaps to an extreme in PD.NEW & NOTEWORTHY Despite our awareness of the impact of Parkinson's disease (PD) on motor function for over two centuries, limited attention has focused on skeletal muscle. We previously identified type I myofiber grouping, a novel indicator of muscle dysfunction in PD, presumably a result of heightened rates of denervation/reinnervation. Using transcriptional profiling to identify networks associated with this phenotype, we provide insight into potential mechanistic roles of skeletal muscle in signaling to promote its survival in PD.

Investigating the energy crisis in Alzheimer disease using transcriptome study

Alzheimer disease (AD) is a devastating neurological disorder, which initiates from hippocampus and proliferates to cortical regions. The neurons of hippocampus require higher energy to preserve the firing pattern. In AD, aberrant energy metabolism is the critical factor for neurodegeneration. However, the reason for the energy crisis in hippocampus neurons is still unresolved. Transcriptome analysis enables us in understanding the underlying mechanism of energy crisis. In this study, we identified variants/differential gene/transcript expression profiles from hippocampus RNA-seq data. We predicted the effect of variants in transcription factor (TF) binding using in silico tools. Further, a hippocampus-specific co-expression and functional interaction network were designed to decipher the relationships between TF and differentially expressed genes (DG). Identified variants predominantly influence TF binding, which subsequently regulates the DG. From the results, we hypothesize that the loss of vascular integrity is the fundamental attribute for the energy crisis, which leads to neurodegeneration.

miR-1185-1 and miR-548q Are Biomarkers of Response to Weight Loss and Regulate the Expression of GSK3B

The aim of the present investigation was to identify putative miRNAs involved in the response to weight loss. Reverse-transcribed RNA isolated from white blood cells (WBCs) of a subpopulation from the Reduction of the Metabolic Syndrome in Navarra-Spain (RESMENA-S) study (low-responders (LR) and high-responders (HR)) was hybridized in a gene expression microarray. Moreover, miRNAs were sequenced by miRNA-Seq. It was found that miR-548q and miR-1185-1 were overexpressed in HR, both in the microarray and in the miRNA-Seq. A bioinformatic prediction of putative target genes of the selected miRNAs found that GSK3B, a putative target for miR-548q and miR-1185-1, was downregulated in HR. Particular 3′-UTR binding regions of GSK3B were cloned downstream of the firefly luciferase gene. HEK-293T cells were co-transfected with either 0.25 μg of empty pmiR-GLO or pmiR-GLO-548q-3′-UTR/pmiR-GLO-1185-1-3′-UTR, and 7.5 pmol of miR-548q/miR-1185-1 mimics, demonstrating that miR-1185-1 bound to the 3′-UTR region of GSK3B. THP-1 cells were transfected with either 20/40 nM of miR-548q/miR-1185-1 mimics, evidencing that miR-1185-1inhibited the expression of the gene when transfected at doses of 20/40 nM, whereas miR-548q inhibited GSK3B expression at a dose of 40 nM. As a conclusion, miR-548q and miR-1185-1 levels in WBCs are biomarkers of response to weight-loss diets and could be involved in the regulation of the proinflammatory gene GSK3B.

α-synuclein accumulation in SH-SY5Y cell impairs autophagy in microglia by exosomes overloading miR-19a-3p

Aims: To reveal whether miRNAs in exosomes from α-synuclein transgenic SH-SY5Y cells are able to regulate autophagy in recipient microglia. Materials & methods: Microarray analysis and experimental verification were adopted to assess the significance of autophagy-associated miRNAs in exosomes from neuronal model of α-synucleinopathies. Results: We found that miR-19a-3p increased remarkably in the exosomes from α-synuclein gene transgenic SH-SY5Y cells. Further study inferred that α-synuclein gene transgenic SH-SY5Y cell-derived exosomes and miR-19a-3p mimic consistently inhibited the expression of phosphatase and tensin homolog and increased the phosphorylation of AKT and mTOR, both of which ultimately lead to the dysfunction of autophagy in recipient microglia. Conclusion: The data suggested that enhanced expression of miR-19a-3p in exosomes suppress autophagy in recipient microglia by targeting the phosphatase and tensin homolog/AKT/mTOR signaling pathway.

Comparison of Methods for Differential Co-expression Analysis for Disease Biomarker Prediction

In the recent past, a number of methods have been developed for analysis of biological data. Among these methods, gene co-expression networks have the ability to mine functionally related genes with similar co-expression patterns, because of which such networks have been most widely used. However, gene co-expression networks cannot identify genes, which undergo condition specific changes in their relationships with other genes. In contrast, differential co-expression analysis enables finding co-expressed genes exhibiting significant changes across disease conditions. In this paper, we present some significant outcomes of a comparative study of four co-expression network module detection techniques, namely, THD-Module Extractor, DiffCoEx, MODA, and WGCNA, which can perform differential co-expression analysis on both gene and miRNA expression data (microarray and RNA-seq) and discuss the applications to Alzheimer's disease and Parkinson's disease research. Our observations reveal that compared to other methods, THD-Module Extractor is the most effective in finding modules with higher functional relevance and biological significance.

SIRPα deficiency accelerates the pathologic process in models of Parkinson disease

Microglia-mediated neuroinflammation is a crucial pathophysiological contributor to several aging-related neurodegenerative disorders, including Parkinson's disease (PD). During the process of aging or stress, microglia undergoes several transcriptional and morphological changes that contribute to aberrant immunological responses, which is known as priming. Key molecules involved in the process, however, are not clearly defined. In the present study, we have demonstrated that level of microglial signal regulatory protein α (SIRPα) decreased during aging or inflammatory challenge. Functional studies suggested that downregulation of SIRPα released the brake of inflammatory response in microglia, revealing an inhibitory effect of SIRPα in microglial activation. Furthermore, we assessed the impact of SIRPα downregulation in PD pathogenesis using both cell culture and animal models. Our results showed that SIRPα deficiency resulted in abnormal inflammatory response and phagocytic activity of microglia, which in turn, further accelerated degeneration of dopaminergic neurons in 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine or lipopolysaccharides mice models. These results collectively demonstrate that dysregulation of SIRPα signaling in microglia during aging plays a critical role in the pathogenesis of age-related neurological disorders such as PD.

Retracted Article: Long noncoding RNA HOTAIR promotes cell apoptosis by sponging miR-221 in Parkinson's disease

Parkinson's disease (PD) is a common neurological disorder that is detrimental to the health of older people worldwide. Long noncoding RNAs (lncRNAs) have been reported to play essential roles in the pathogenesis and therapeutics of PD. LncRNA homeobox transcript antisense intergenic RNA (HOTAIR) is expressed in PD samples; however, the exact roles of HOTAIR and its mechanism remain largely unclear. Herein, the neurotoxins 1-methyl-4-phenylpyridine (MPP⁺) and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) were used to establish PD models in vitro and in vivo. The expressions of HOTAIR and microRNA-221 (miR-221) were measured by the quantitative real-time polymerase chain reaction (qRT-PCR). Cell viability and apoptosis were detected by the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) assay and western blot or flow cytometry, respectively. The interaction between HOTAIR and miR-221 was explored by luciferase activity and RNA immunoprecipitation (RIP). The tyrosine hydroxylase (TH)-positive cells in MPTP-treated-mouse midbrains were analyzed by immunohistochemistry. The HOTAIR expression was up-regulated and that of miR-221 was down-regulated in the serum of PD patients and MPP⁺-treated SH-SY5Y cells. Overexpression of HOTAIR inhibited cell viability and promoted apoptosis in MPP⁺-treated SH-SY5Y cells. However, the down-regulation of HOTAIR showed an opposite effect. Moreover, miR-221 was validated to be bound to HOTAIR, and its addition reversed the regulatory effect of HOTAIR on cell viability and apoptosis in MPP⁺-treated SH-SY5Y cells. Moreover, the knockdown of HOTAIR attenuated the degree of PD and cell apoptosis by regulating miR-221 in MPTP-treated mice. In conclusion, HOTAIR contributed to cell apoptosis by sponging miR-221 in PD. This study elucidates a new mechanism for understanding the pathogenesis of PD and provides a promising target for the treatment of PD.

Parkinson's disease (PD) is a common neurological disorder that is detrimental to the health of older people worldwide.

Characterizing early drug resistance-related events using geometric ensembles from HIV protease dynamics

The use of antiretrovirals (ARVs) has drastically improved the life quality and expectancy of HIV patients since their introduction in health care. Several millions are still afflicted worldwide by HIV and ARV resistance is a constant concern for both healthcare practitioners and patients, as while treatment options are finite, the virus constantly adapts via complex mutation patterns to select for resistant strains under the pressure of drug treatment. The HIV protease is a crucial enzyme for viral maturation and has been a game changing drug target since the first application. Due to similarities in protease inhibitor designs, drug cross-resistance is not uncommon across ARVs of the same class. It is known that resistance against protease inhibitors is associated with a wider active site, but results from our large scale molecular dynamics simulations combined with statistical tests and network analysis further show, for the first time, that there are regions of local expansions and compactions associated with high levels of resistance conserved across eight different protease inhibitors visible in their complexed form within closed receptor conformations. The observed conserved expansion sites may provide an alternative drug-targeting site. Further, the method developed here is novel, supplementary to methods of variation analysis at sequence level, and should be applicable in analysing the structural consequences of mutations in other contexts using molecular ensembles.

A meta-analysis of public microarray data identifies biological regulatory networks in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is a long-term degenerative disease that is caused by environmental and genetic factors. The networks of genes and their regulators that control the progression and development of PD require further elucidation.

METHODS

We examine common differentially expressed genes (DEGs) from several PD blood and substantia nigra (SN) microarray datasets by meta-analysis. Further we screen the PD-specific genes from common DEGs using GCBI. Next, we used a series of bioinformatics software to analyze the miRNAs, lncRNAs and SNPs associated with the common PD-specific genes, and then identify the mTF-miRNA-gene-gTF network.

RESULT

Our results identified 36 common DEGs in PD blood studies and 17 common DEGs in PD SN studies, and five of the genes were previously known to be associated with PD. Further study of the regulatory miRNAs associated with the common PD-specific genes revealed 14 PD-specific miRNAs in our study. Analysis of the mTF-miRNA-gene-gTF network about PD-specific genes revealed two feed-forward loops: one involving the SPRK2 gene, hsa-miR-19a-3p and SPI1, and the second involving the SPRK2 gene, hsa-miR-17-3p and SPI. The long non-coding RNA (lncRNA)-mediated regulatory network identified lncRNAs associated with PD-specific genes and PD-specific miRNAs. Moreover, single nucleotide polymorphism (SNP) analysis of the PD-specific genes identified two significant SNPs, and SNP analysis of the neurodegenerative disease-specific genes identified seven significant SNPs. Most of these SNPs are present in the 3'-untranslated region of genes and are controlled by several miRNAs.

CONCLUSION

Our study identified a total of 53 common DEGs in PD patients compared with healthy controls in blood and brain datasets and five of these genes were previously linked with PD. Regulatory network analysis identified PD-specific miRNAs, associated long non-coding RNA and feed-forward loops, which contribute to our understanding of the mechanisms underlying PD. The SNPs identified in our study can determine whether a genetic variant is associated with PD. Overall, these findings will help guide our study of the complex molecular mechanism of PD.