Computational identification and analysis of neurodegenerative disease associated protein kinases in hominid genomes

Genome- and Exome-Wide Association Studies Revealed Candidate Genes Associated with DaTscan Imaging Features

Introduction

Despite remarkable progress in identifying Parkinson's disease (PD) genetic risk loci, the genetic basis of PD remains largely unknown. With the help of the endophenotype approach and using data from dopamine transporter single-photon emission computerized tomography (DaTscan), we identified potentially involved genes in PD.

Method

We conducted an imaging genetic study by performing exome-wide association study (EWAS) and genome-wide association study (GWAS) on the specific binding ratio (SBR) of six DaTscan anatomical areas between 489 and 559 subjects of Parkinson's progression markers initiative (PPMI) cohort and 83,623 and 36,845 single-nucleotide polymorphisms (SNPs)/insertion-deletion mutations (INDELs). We also investigated the association of cerebrospinal fluid (CSF) protein concentration of our significant genes with PD progression using PPMI CSF proteome data.

Results

Among 83,623 SNPs/INDELs in EWAS, one SNP (rs201465075) on 1 q32.1 locus was significantly (P value = 4.03 × 10-7) associated with left caudate DaTscan SBR, and 33 SNPs were suggestive. Among 36,845 SNPs in GWAS, one SNP (rs12450112) on 17 p.12 locus was significantly (P value = 1.34 × 10-6) associated with right anterior putamen DaTscan SBR, and 39 SNPs were suggestive among which 8 SNPs were intergenic. We found that rs201465075 and rs12450112 are most likely related to IGFN1 and MAP2K4 genes. The protein level of MAP2K4 in the CSF was significantly associated with PD progression in the PPMI cohort; however, proteomic data were not available for the IGFN1 gene.

Conclusion

We have shown that particular variants of IGFN1 and MAP2K4 genes may be associated with PD. Since DaTscan imaging could be positive in other Parkinsonian syndromes, caution should be taken when interpreting our results. Future experimental studies are also needed to verify these findings.

Proteomics analysis of prefrontal cortex of Alzheimer's disease patients revealed dysregulated proteins in the disease and novel proteins associated with amyloid-β pathology

BACKGROUND

Alzheimer's disease (AD) is a progressive, chronic, and neurodegenerative disease, and the most common cause of dementia worldwide. Currently, the mechanisms underlying the disease are far from being elucidated. Thus, the study of proteins involved in its pathogenesis would allow getting further insights into the disease and identifying new markers for AD diagnosis.

METHODS

We aimed here to analyze protein dysregulation in AD brain by quantitative proteomics to identify novel proteins associated with the disease. 10-plex TMT (tandem mass tags)-based quantitative proteomics experiments were performed using frozen tissue samples from the left prefrontal cortex of AD patients and healthy individuals and vascular dementia (VD) and frontotemporal dementia (FTD) patients as controls (CT). LC-MS/MS analyses were performed using a Q Exactive mass spectrometer.

RESULTS

In total, 3281 proteins were identified and quantified using MaxQuant. Among them, after statistical analysis with Perseus (p value < 0.05), 16 and 155 proteins were defined as upregulated and downregulated, respectively, in AD compared to CT (Healthy, FTD and VD) with an expression ratio ≥ 1.5 (upregulated) or ≤ 0.67 (downregulated). After bioinformatics analysis, ten dysregulated proteins were selected as more prone to be associated with AD, and their dysregulation in the disease was verified by qPCR, WB, immunohistochemistry (IHC), immunofluorescence (IF), pull-down, and/or ELISA, using tissue and plasma samples of AD patients, patients with other dementias, and healthy individuals.

CONCLUSIONS

We identified and validated novel AD-associated proteins in brain tissue that should be of further interest for the study of the disease. Remarkably, PMP2 and SCRN3 were found to bind to amyloid-β (Aβ) fibers in vitro, and PMP2 to associate with Aβ plaques by IF, whereas HECTD1 and SLC12A5 were identified as new potential blood-based biomarkers of the disease.

Deciphering the distinct transcriptomic and gene regulatory map in adult macaque basal ganglia cells

BACKGROUND

The basal ganglia are a complex of interconnected subcortical structures located beneath the mammalian cerebral cortex. The degeneration of dopaminergic neurons in the basal ganglia is the primary pathological feature of Parkinson's disease. Due to a lack of integrated analysis of multiomics datasets across multiple basal ganglia brain regions, very little is known about the regulatory mechanisms of this area.

FINDINGS

We utilized high-throughput transcriptomic and epigenomic analysis to profile over 270,000 single-nucleus cells to create a cellular atlas of the basal ganglia, characterizing the cellular composition of 4 regions of basal ganglia in adult macaque brain, including the striatum, substantia nigra (SN), globus pallidum, and amygdala. We found a distinct epigenetic regulation on gene expression of neuronal and nonneuronal cells across regions in basal ganglia. We identified a cluster of SN-specific astrocytes associated with neurodegenerative diseases and further explored the conserved and primate-specific transcriptomics in SN cell types across human, macaque, and mouse. Finally, we integrated our epigenetic landscape of basal ganglia cells with human disease heritability and identified a regulatory module consisting of candidate cis-regulatory elements that are specific to medium spiny neurons and associated with schizophrenia.

CONCLUSIONS

In general, our macaque basal ganglia atlas provides valuable insights into the comprehensive transcriptome and epigenome of the most important and populous cell populations in the macaque basal ganglia. We have identified 49 cell types based on transcriptomic profiles and 47 cell types based on epigenomic profiles, some of which exhibit region specificity, and characterized the molecular relationships underlying these brain regions.

Characterization of gene expression patterns in mild cognitive impairment using a transcriptomics approach and neuroimaging endophenotypes

INTRODUCTION

Identification of novel therapeutics and risk assessment in early stages of Alzheimer's disease (AD) is a crucial aspect of addressing this complex disease. We characterized gene-expression patterns at the mild cognitive impairment (MCI) stage to identify critical mRNA measures and gene clusters associated with AD pathogenesis.

METHODS

We used a transcriptomics approach, integrating magnetic resonance imaging (MRI) and peripheral blood-based gene expression data using persistent homology (PH) followed by kernel-based clustering.

RESULTS

We identified three clusters of genes significantly associated with diagnosis of amnestic MCI. The biological processes associated with each cluster were mitochondrial function, NF-kB signaling, and apoptosis. Cluster-level associations with cortical thickness displayed canonical AD-like patterns. Driver genes from clusters were also validated in an external dataset for prediction of amyloidosis and clinical diagnosis.

DISCUSSION

We found a disease-relevant transcriptomic signature sensitive to prodromal AD and identified a subset of potential therapeutic targets associated with AD pathogenesis.

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.

Exosome/microvesicle content is altered in leucine-rich repeat kinase 2 mutant induced pluripotent stem cell-derived neural cells

Extracellular vesicles, including exosomes/microvesicles (EMVs), have been described as sensitive biomarkers that represent disease states and response to therapies. In light of recent reports of disease-mirroring EMV molecular signatures, the present study profiled two EMVs from different Parkinson's disease (PD) tissue sources: (a) neural progenitor cells derived from an endogenous adult stem/progenitor cell, called adult human neural progenitor (AHNP) cells, that we found to be pathological when isolated from postmortem PD patients' substantia nigra; and (b) leucine-rich repeat kinase 2 (LRRK2) gene identified patient induced pluripotent stem cells (iPSCs), which were used to isolate EMVs and begin to characterize their cargoes. Initial characterization of EMVs derived from idiopathic patients (AHNPs) and mutant LRRK2 patients showed differences between both phenotypes and when compared with a sibling control in EMV size and release based on Nanosight analysis. Furthermore, molecular profiling disclosed that neurodegenerative-related gene pathways altered in PD can be reversed using gene-editing approaches. In fact, the EMV cargo genes exhibited normal expression patterns after gene editing. This study shows that EMVs have the potential to serve as sensitive biomarkers of disease state in both idiopathic and gene-identified PD patients and that following gene-editing, EMVs reflect a corrected state. This is relevant for both prodromal and symptomatic patient populations where potential responses to therapies can be monitored via non-invasive liquid biopsies and EMV characterizations.

The exploration of novel Alzheimer's therapeutic agents from the pool of FDA approved medicines using drug repositioning, enzyme inhibition and kinetic mechanism approaches

Novel drug development is onerous, time consuming and overpriced process with particularly low success and relatively high enfeebling rates. To overcome this burden, drug repositioning approach is being used to predict the possible therapeutic effects of FDA approved drugs in different diseases. Herein, we designed a computational and enzyme inhibitory mechanistic approach to fetch the promising drugs from the pool of FDA approved drugs against AD. The binding interaction patterns and conformations of screened drugs within active region of AChE were confirmed through molecular docking profiles. The possible associations of selected drugs with AD genes were predicted by pharmacogenomics analysis and confirmed through data mining. The stability behaviour of docked complexes (Drugs-AChE) were checked by MD simulations. The possible therapeutic potential of repositioned drugs against AChE were checked by in vitro analysis. Taken together, Cinitapride displayed a comparable results with standard and can be used as possible therapeutic agent in the treatment of AD.