Transcriptome profiling in neurodegenerative disease

RNA-sequencing transcriptomic analysis of scrapie-exposed ovine mesenchymal stem cells

In neurodegenerative diseases, including prion diseases, cellular models arise as useful tools to study the pathogenic mechanisms occurring in these diseases and to assess the efficacy of potential therapeutic compounds. In the present study, a RNA-sequencing analysis of bone marrow-derived ovine mesenchymal stem cells (oBM-MSCs) exposed to scrapie brain homogenate was performed to try to unravel genes and pathways potentially involved in prion diseases and MSC response mechanisms to prions. The oBM-MSCs were cultured in three different conditions (inoculated with brain homogenate of scrapie-infected sheep, with brain homogenate of healthy sheep and in standard growth conditions without inoculum) that were analysed at two exposure times: 2 and 4 days post-inoculation (dpi). Differentially expressed genes (DEGs) in scrapie-treated oBM-MSCs were found in the two exposure times finding the higher number at 2 dpi, which coincided with the inoculum removal time. Pathways enriched in DEGs were related to biological functions involved in prion toxicity and MSC response to the inflammatory environment of scrapie brain homogenate. Moreover, RNA-sequencing analysis was validated amplifying by RT-qPCR a set of 11 DEGs with functions related with prion propagation and its associated toxicity. Seven of these genes displayed significant expression changes in scrapie-treated cells. These results contribute to the knowledge of the molecular mechanisms behind the early toxicity observed in these cells after prion exposure and to elucidate the response of MSCs to neuroinflammation.

CMAUP database update 2024: extended functional and association information of useful plants for biomedical research

Knowledge of the collective activities of individual plants together with the derived clinical effects and targeted disease associations is useful for plant-based biomedical research. To provide the information in complement to the established databases, we introduced a major update of CMAUP database, previously featured in NAR. This update includes (i) human transcriptomic changes overlapping with 1152 targets of 5765 individual plants, covering 74 diseases from 20 027 patient samples; (ii) clinical information for 185 individual plants in 691 clinical trials; (iii) drug development information for 4694 drug-producing plants with metabolites developed into approved or clinical trial drugs; (iv) plant and human disease associations (428 737 associations by target, 220 935 reversion of transcriptomic changes, 764 and 154121 associations by clinical trials of individual plants and plant ingredients); (v) the location of individual plants in the phylogenetic tree for navigating taxonomic neighbors, (vi) DNA barcodes of 3949 plants, (vii) predicted human oral bioavailability of plant ingredients by the established SwissADME and HobPre algorithm, (viii) 21-107% increase of CMAUP data over the previous version to cover 60 222 chemical ingredients, 7865 plants, 758 targets, 1399 diseases, 238 KEGG human pathways, 3013 gene ontologies and 1203 disease ontologies. CMAUP update version is freely accessible at https://bidd.group/CMAUP/index.html.

A Comprehensive Exploration of the Transcriptomic Landscape in Multiple Sclerosis: A Systematic Review

Multiple Sclerosis (MS) is, to date, an incurable disease of the nervous system characterized by demyelination. Several genetic mutations are associated with the disease but they are not able to explain all the diagnosticated cases. Thus, it is suggested that altered gene expression may play a role in human pathologies. In this review, we explored the role of the transcriptomic profile in MS to investigate the main altered biological processes and pathways involved in the disease. Herein, we focused our attention on RNA-seq methods that in recent years are producing a huge amount of data rapidly replacing microarrays, both with bulk and single-cells. The studies evidenced that different MS stages have specific molecular signatures and non-coding RNAs may play a key role in the disease. Sex-dependence was observed before and after treatments used to alleviate symptomatology activating different biological processes in a drug-dependent manner. New pathways, such as neddylation, were found deregulated in MS and inflammation was linked to neuron degeneration areas through spatial transcriptomics. It is evident that the use of RNA-seq in the study of complex pathologies, such as MS, is a valid strategy to shed light on new involved mechanisms.

Predictive modelling of Parkinson's disease progression based on RNA-Sequence with densely connected deep recurrent neural networks

The advent of recent high throughput sequencing technologies resulted in unexplored big data of genomics and transcriptomics that might help to answer various research questions in Parkinson's disease (PD) progression. While the literature has revealed various predictive models that use longitudinal clinical data for disease progression, there is no predictive model based on RNA-Sequence data of PD patients. This study investigates how to predict the PD Progression for a patient's next medical visit by capturing longitudinal temporal patterns in the RNA-Seq data. Data provided by Parkinson Progression Marker Initiative (PPMI) includes 423 PD patients without revealing any race, sex, or age information with a variable number of visits and 34,682 predictor variables for 4 years. We propose a predictive model based on deep Recurrent Neural Network (RNN) with the addition of dense connections and batch normalization into RNN layers. The results show that the proposed architecture can predict PD progression from high dimensional RNA-seq data with a Root Mean Square Error (RMSE) of 6.0 and a rank-order correlation of (r = 0.83, p < 0.0001) between the predicted and actual disease status of PD.

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

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

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.

RNA Dynamics in Alzheimer's Disease

Alzheimer's disease (AD) is the most common age-related neurodegenerative disorder that heavily burdens healthcare systems worldwide. There is a significant requirement to understand the still unknown molecular mechanisms underlying AD. Current evidence shows that two of the major features of AD are transcriptome dysregulation and altered function of RNA binding proteins (RBPs), both of which lead to changes in the expression of different RNA species, including microRNAs (miRNAs), circular RNAs (circRNAs), long non-coding RNAs (lncRNAs), and messenger RNAs (mRNAs). In this review, we will conduct a comprehensive overview of how RNA dynamics are altered in AD and how this leads to the differential expression of both short and long RNA species. We will describe how RBP expression and function are altered in AD and how this impacts the expression of different RNA species. Furthermore, we will also show how changes in the abundance of specific RNA species are linked to the pathology of AD.

RNA sequencing of whole blood reveals early alterations in immune cells and gene expression in Parkinson's disease

Changes in the blood-based RNA transcriptome have the potential to inform biomarkers of Parkinson's disease (PD) progression. Here we sequenced a discovery set of whole-blood RNA species in 4,871 longitudinally collected samples from 1,570 clinically phenotyped individuals from the Parkinson's Progression Marker Initiative (PPMI) cohort. Samples were sequenced to an average of 100 million read pairs to create a high-quality transcriptome. Participants with PD in the PPMI had significantly altered RNA expression (>2,000 differentially expressed genes), including an early and persistent increase in neutrophil gene expression, with a concomitant decrease in lymphocyte cell counts. This was validated in a cohort from the Parkinson's Disease Biomarkers Program (PDBP) consisting of 1,599 participants and by alterations in immune cell subtypes. This publicly available transcriptomic dataset, coupled with available detailed clinical data, provides new insights into PD biological processes impacting whole blood and new paths for developing diagnostic and prognostic PD biomarkers.

Melatonin and Melatonergic Influence on Neuronal Transcription Factors: Implications for the Development of Novel Therapies for Neurodegenerative Disorders

Melatonin is a multifunctional signalling molecule that is secreted by the mammalian pineal gland, and also found in a number of organisms including plants and bacteria. Research has continued to uncover an ever-increasing number of processes in which melatonin is known to play crucial roles in mammals. Amongst these functions is its contribution to cell multiplication, differentiation and survival in the brain. Experimental studies show that melatonin can achieve these functions by influencing transcription factors which control neuronal and glial gene expression. Since neuronal survival and differentiation are processes that are important determinants of the pathogenesis, course and outcome of neurodegenerative disorders; the known and potential influences of melatonin on neuronal and glial transcription factors are worthy of constant examination. In this review, relevant scientific literature on the role of melatonin in preventing or altering the course and outcome of neurodegenerative disorders, by focusing on melatonin's influence on transcription factors is examined. A number of transcription factors whose functions can be influenced by melatonin in neurodegenerative disease models have also been highlighted. Finally, the therapeutic implications of melatonin's influences have also been discussed and the potential limitations to its applications have been highlighted.

Proteomic Profiling of the Substantia Nigra to Identify Determinants of Lewy Body Pathology and Dopaminergic Neuronal Loss

Proteinaceous aggregates containing α-synuclein protein called Lewy bodies in the substantia nigra is a hallmark of Parkinson's disease. The molecular mechanisms of Lewy body formation and associated neuronal loss remain largely unknown. To gain insights into proteins and pathways associated with Lewy body pathology, we performed quantitative profiling of the proteome. We analyzed substantia nigra tissue from 51 subjects arranged into three groups: cases with Lewy body pathology, Lewy body-negative controls with matching neuronal loss, and controls with no neuronal loss. Using a label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach, we characterized the proteome both in terms of protein abundances and peptide modifications. Statistical testing for differential abundance of the most abundant 2963 proteins, followed by pathway enrichment and Bayesian learning of the causal network structure, was performed to identify likely drivers of Lewy body formation and dopaminergic neuronal loss. The identified pathways include (1) Arp2/3 complex-mediated actin nucleation; (2) synaptic function; (3) poly(A) RNA binding; (4) basement membrane and endothelium; and (5) hydrogen peroxide metabolic process. According to the data, the endothelial/basement membrane pathway is tightly connected with both pathologies and likely to be one of the drivers of neuronal loss. The poly(A) RNA-binding proteins, including the ones relevant to other neurodegenerative disorders (e.g., TDP-43 and FUS), have a strong inverse correlation with Lewy bodies and may reflect an alternative mechanism of nigral neurodegeneration.

Molecular subtyping of Alzheimer's disease using RNA sequencing data reveals novel mechanisms and targets

Alzheimer's disease (AD), the most common form of dementia, is recognized as a heterogeneous disease with diverse pathophysiologic mechanisms. In this study, we interrogate the molecular heterogeneity of AD by analyzing 1543 transcriptomes across five brain regions in two AD cohorts using an integrative network approach. We identify three major molecular subtypes of AD corresponding to different combinations of multiple dysregulated pathways, such as susceptibility to tau-mediated neurodegeneration, amyloid-β neuroinflammation, synaptic signaling, immune activity, mitochondria organization, and myelination. Multiscale network analysis reveals subtype-specific drivers such as GABRB2, LRP10, MSN, PLP1, and ATP6V1A We further demonstrate that variations between existing AD mouse models recapitulate a certain degree of subtype heterogeneity, which may partially explain why a vast majority of drugs that succeeded in specific mouse models do not align with generalized human trials across all AD subtypes. Therefore, subtyping patients with AD is a critical step toward precision medicine for this devastating disease.

Meta-Analysis of Gene Expression Changes in the Blood of Patients with Mild Cognitive Impairment and Alzheimer's Disease Dementia

Background: Dementia is a major public health concern affecting approximately 47 million people worldwide. Mild cognitive impairment (MCI) is one form of dementia that affects an individual’s memory with or without affecting their daily life. Alzheimer’s disease dementia (ADD) is a more severe form of dementia that usually affects elderly individuals. It remains unclear whether MCI is a distinct disorder from or an early stage of ADD. Methods: Gene expression data from blood were analyzed to identify potential biomarkers that may be useful for distinguishing between these two forms of dementia. Results: A meta-analysis revealed 91 genes dysregulated in individuals with MCI and 387 genes dysregulated in ADD. Pathway analysis identified seven pathways shared between MCI and ADD and nine ADD-specific pathways. Fifteen transcription factors were associated with MCI and ADD, whereas seven transcription factors were specific for ADD. Mir-335-5p was specific for ADD, suggesting that it may be useful as a biomarker. Diseases that are associated with MCI and ADD included developmental delays, cognition impairment, and movement disorders. Conclusion: These results provide a better molecular understanding of peripheral changes that occur in MCI and ADD patients and may be useful in the identification of diagnostic and prognostic biomarkers.

Innate immune responses to paraquat exposure in a Drosophila model of Parkinson's disease

Parkinson’s disease (PD) is a progressive, neurodegenerative movement disorder characterized by the loss of dopaminergic (DA) neurons. Limited understanding of the early molecular pathways associated with the demise of DA neurons, including those of inflammatory exacerbation of neurodegeneration, is a major impediment to therapeutic development. Recent studies have implicated gene-environment interactions in PD susceptibility. We used transcriptomic profiling in a Drosophila PD model in response to paraquat (PQ)-induced oxidative stress to identify pre-symptomatic signatures of impending neuron dysfunction. Our RNAseq data analysis revealed extensive regulation of innate immune response genes following PQ ingestion. We found that PQ exposure leads to the activation of the NF-κB transcription factor, Relish, and the stress signaling factor JNK, encoded by the gene basket in Drosophila. Relish knockdown in the dopaminergic neurons confers PQ resistance and rescues mobility defects and DA neuron loss. Furthermore, PQ-induced toxicity is mediated through the immune deficiency signaling pathway. Surprisingly, the expression of Relish-dependent anti-microbial peptide (AMPs) genes is suppressed upon PQ exposure causing increased sensitivity to Gram-negative bacterial infection. This work provides a novel link between PQ exposure and innate immune system modulation underlying environmental toxin-induced neurodegeneration, thereby underscoring the role of the innate immune system in PD pathogenesis.

MicroRNA in Alzheimer's disease revisited: implications for major neuropathological mechanisms

Pathology of Alzheimer's disease (AD) goes far beyond neurotoxicity resulting from extracellular deposition of amyloid β (Aβ) plaques. Aberrant cleavage of amyloid precursor protein and accumulation of Aβ in the form of the plaque or neurofibrillary tangles are the known primary culprits of AD pathogenesis and target for various regulatory mechanisms. Hyper-phosphorylation of tau, a major component of neurofibrillary tangles, precipitates its aggregation and prevents its clearance. Lipid particles, apolipoproteins and lipoprotein receptors can act in favor or against Aβ and tau accumulation by altering neural membrane characteristics or dynamics of transport across the blood-brain barrier. Lipids also alter the oxidative/anti-oxidative milieu of the central nervous system (CNS). Irregular cell cycle regulation, mitochondrial stress and apoptosis, which follow both, are also implicated in AD-related neuronal loss. Dysfunction in synaptic transmission and loss of neural plasticity contribute to AD. Neuroinflammation is a final trail for many of the pathologic mechanisms while playing an active role in initiation of AD pathology. Alterations in the expression of microRNAs (miRNAs) in AD and their relevance to AD pathology have long been a focus of interest. Herein we focused on the precise pathomechanisms of AD in which miRNAs were implicated. We performed literature search through PubMed and Scopus using the search term: ('Alzheimer Disease') OR ('Alzheimer's Disease') AND ('microRNAs' OR 'miRNA' OR 'MiR') to reach for relevant articles. We show how a limited number of common dysregulated pathways and abnormal mechanisms are affected by various types of miRNAs in AD brain.

Alterations in micro RNA-messenger RNA (miRNA-mRNA) Coupled Signaling Networks in Sporadic Alzheimer's Disease (AD) Hippocampal CA1

RNA sequencing, DNA microfluidic array, LED-Northern, Western immunoassay and bioinformatics analysis have uncovered a small family of up-regulated human brain enriched microRNAs (miRNAs) and down-regulated messenger RNAs (mRNAs) in short post-mortem interval (PMI) sporadic Alzheimer's disease (AD) brain. At the mRNA level, a large majority of the expression of human brain genes found to be down-regulated in sporadic AD appears to be a consequence of an up-regulation of a specific group of NF-kB-inducible microRNAs (miRNAs). This group of up-regulated miRNAs - including miRNA-34a and miRNA-146a - has strong, energetically favorable, complimentary RNA sequences in the 3' untranslated regions (3'-UTR) of their target mRNAs which ultimately drive the down-regulation in the expression of certain essential brain genes. Interestingly, just 2 significantly up-regulated miRNAs - miRNA-34a and miRNA-146a - appear to down-regulate mRNA targets involved in synaptogenesis (SHANK3), phagocytosis deficits and tau pathology (TREM2), inflammation (CFH; complement factor H) and amyloidogenesis (TSPAN12), all of which are distinguishing pathological features characteristic of middle-to-late stage AD neuropathology. This paper reports the novel finding of parallel miRNA-34a and miRNA-146a up-regulation in sporadic AD hippocampal CA1 RNA pools and proposes an altered miRNA-mRNA coupled signaling network in AD, much of which is supported by current experimental findings in the recent literature.

Cyclin Y-mediated transcript profiling reveals several important functional pathways regulated by Cyclin Y in hippocampal neurons

Cyclin Y (CCNY), which is a cyclin protein known to play a role in cell division, is unexpectedly and thus interestingly expressed in non-proliferating neuronal cells. There have been only a few studies reporting the neuronal functions of CCNY in synapse remodeling and hippocampal long-term potentiation. Therefore, we here provide global and comprehensive information on the putative functions of CCNY in biological and functional pathways in neuronal systems. We adopted high-throughput RNA-sequencing technology for analyzing transcriptomes regulated by CCNY and utilized bioinformatics for identifying putative molecules, biological processes, and functional pathways that are possibly connected to CCNY functions in hippocampal neuronal cells of rats. We revealed that several enriched annotation terms and pathways associated with CCNY expression within neurons, including apoptosis, learning or memory, synaptic plasticity, actin cytoskeleton, focal adhesion, extracellular matrix-receptor interaction and chemokine signaling pathway are targeted by CCNY. In addition, the mRNA levels of some genes enriched for those annotation terms and pathways or genes reported to be altered in Alzheimer's disease mouse model were further validated by quantitative real-time PCR in hippocampal neuronal cells. The present study provides an excellent resource for future investigations of CCNY functions in neuronal systems.

microRNA-132/212 deficiency enhances Aβ production and senile plaque deposition in Alzheimer's disease triple transgenic mice

The abnormal regulation of amyloid-β (Aβ) metabolism (e.g., production, cleavage, clearance) plays a central role in Alzheimer’s disease (AD). Among endogenous factors believed to participate in AD progression are the small regulatory non-coding microRNAs (miRs). In particular, the miR-132/212 cluster is severely reduced in the AD brain. In previous studies we have shown that miR-132/212 deficiency in mice leads to impaired memory and enhanced Tau pathology as seen in AD patients. Here we demonstrate that the genetic deletion of miR-132/212 promotes Aβ production and amyloid (senile) plaque formation in triple transgenic AD (3xTg-AD) mice. Using RNA-Seq and bioinformatics, we identified genes of the miR-132/212 network with documented roles in the regulation of Aβ metabolism, including Tau, Mapk, and Sirt1. Consistent with these findings, we show that the modulation of miR-132, or its target Sirt1, can directly regulate Aβ production in cells. Finally, both miR-132 and Sirt1 levels correlated with Aβ load in humans. Overall, our results support the hypothesis that the miR-132/212 network, including Sirt1 and likely other target genes, contributes to abnormal Aβ metabolism and senile plaque deposition in AD. This study strengthens the importance of miR-dependent networks in neurodegenerative disorders, and opens the door to multifactorial drug targets of AD by targeting Aβ and Tau.

RNA-Sequencing to Elucidate Early Patterns of Dysregulation Underlying the Onset of Alzheimer's Disease

With its ability to perform rapid transcriptome profiling and profound transcriptomic analysis powered by high-throughput sequencing at a high resolution with deep coverage, the advent of RNA sequencing technology, RNA-Seq, outperforms other methods in the field, such as microarrays, and has changed our way of performing transcriptomic investigation. Protocols for preparing libraries for RNA-Seq using the Illumina and Roche 454 sequencing platforms are included in this chapter. Common steps for library preparation in both platforms include RNA fragmentation, cDNA synthesis, adaptor ligation, and PCR amplification of cDNA strands. Illumina adopts solid-phase bridge PCR amplification, while 454 uses water-in-oil emulsion-based PCR amplification. Despite differences in the PCR amplification step, both platforms employ the same sequencing-by-synthesis technology for the sequencing process. Application of the RNA-Seq technique in the context of dysregulation of the transcriptome in Alzheimer's disease is also discussed.

The Antisense Transcriptome and the Human Brain

The transcriptome of a cell is made up of a varied array of RNA species, including protein-coding RNAs, long non-coding RNAs, short non-coding RNAs, and circular RNAs. The cellular transcriptome is dynamic and can change depending on environmental factors, disease state and cellular context. The human brain has perhaps the most diverse transcriptome profile that is enriched for many species of RNA, including antisense transcripts. Antisense transcripts are produced when both the plus and minus strand of the DNA helix are transcribed at a particular locus. This results in an RNA transcript that has a partial or complete overlap with an intronic or exonic region of the sense transcript. While antisense transcription is known to occur at some level in most organisms, this review focuses specifically on antisense transcription in the brain and how regulation of genes by antisense transcripts can contribute to functional aspects of the healthy and diseased brain. First, we discuss different techniques that can be used in the identification and quantification of antisense transcripts. This is followed by examples of antisense transcription and modes of regulatory function that have been identified in the brain.

Conservation and tissue-specific transcription patterns of long noncoding RNAs

Over the past decade, the focus of molecular biology has shifted from being predominately DNA and protein-centric to having a greater appreciation of RNA. It is now accepted that the genome is pervasively transcribed in tissue- and cell-specific manner, to produce not only protein-coding RNAs, but also an array of noncoding RNAs (ncRNAs). Many of these ncRNAs have been found to interact with DNA, protein and other RNA molecules where they exert regulatory functions. Long ncRNAs (lncRNAs) are a subclass of ncRNAs that are particularly interesting due to their cell-specific and species-specific expression patterns and unique conservation patterns. Currently, individual lncRNAs have been classified functionally; however, for the vast majority the functional relevance is unknown. To better categorize lncRNAs, an understanding of their specific expression patterns and evolutionary constraints are needed.

Microglia recapitulate a hematopoietic master regulator network in the aging human frontal cortex

Microglia form the immune system of the brain. Previous studies in cell cultures and animal models suggest altered activation states and cellular senescence in the aged brain. Instead, we analyzed 3 transcriptome data sets from the postmortem frontal cortex of 381 control individuals to show that microglia gene markers assemble into a transcriptional module in a gene coexpression network. These markers predominantly represented M1 and M1/M2b activation phenotypes. Expression of genes in this module generally declines over the adult life span. This decrease was more pronounced in microglia surface receptors for microglia and/or neuron crosstalk than in markers for activation state phenotypes. In addition to these receptors for exogenous signals, microglia are controlled by brain-expressed regulatory factors. We identified a subnetwork of transcription factors, including RUNX1, IRF8, PU.1, and TAL1, which are master regulators (MRs) for the age-dependent microglia module. The causal contributions of these MRs on the microglia module were verified using publicly available ChIP-Seq data. Interactions of these key MRs were preserved in a protein-protein interaction network. Importantly, these MRs appear to be essential for regulating microglia homeostasis in the adult human frontal cortex in addition to their crucial roles in hematopoiesis and myeloid cell-fate decisions during embryogenesis.

Amyloid-beta and Alzheimer's disease: the role of neprilysin-2 in amyloid-beta clearance

Accumulation of the amyloid-beta (Aβ) peptide is a central factor in Alzheimer's disease (AD) pathogenesis as supported by continuing evidence. This review concisely summarizes this evidence supporting a critical role for Aβ in AD before discussing the clearance of this peptide. Mechanisms of clearance of Aβ are critical for preventing pathological elevations in Aβ concentration. Direct degradation of Aβ by endopeptidases has emerged as one important pathway for clearance. Of particular interest are endopeptidases that are sensitive to the neprilysin (NEP) inhibitors thiorphan and phosphoramidon (i.e., are "NEP-like") as these inhibitors induce a dramatic increase in Aβ levels in rodents. This review will focus on neprilysin-2 (NEP2), a NEP-like endopeptidase which cooperates with NEP to control Aβ levels in the brain. The evidence for the involvement of NEP2 in AD is discussed as well as the therapeutic relevance with regards to gene therapy and the development of molecular markers for the disease.

MicroRNA-125b induces tau hyperphosphorylation and cognitive deficits in Alzheimer's disease

Sporadic Alzheimer's disease (AD) is the most prevalent form of dementia, but no clear disease-initiating mechanism is known. Aβ deposits and neuronal tangles composed of hyperphosphorylated tau are characteristic for AD. Here, we analyze the contribution of microRNA-125b (miR-125b), which is elevated in AD. In primary neurons, overexpression of miR-125b causes tau hyperphosphorylation and an upregulation of p35, cdk5, and p44/42-MAPK signaling. In parallel, the phosphatases DUSP6 and PPP1CA and the anti-apoptotic factor Bcl-W are downregulated as direct targets of miR-125b. Knockdown of these phosphatases induces tau hyperphosphorylation, and overexpression of PPP1CA and Bcl-W prevents miR-125b-induced tau phosphorylation, suggesting that they mediate the effects of miR-125b on tau. Conversely, suppression of miR-125b in neurons by tough decoys reduces tau phosphorylation and kinase expression/activity. Injecting miR-125b into the hippocampus of mice impairs associative learning and is accompanied by downregulation of Bcl-W, DUSP6, and PPP1CA, resulting in increased tau phosphorylation in vivo. Importantly, DUSP6 and PPP1CA are also reduced in AD brains. These data implicate miR-125b in the pathogenesis of AD by promoting pathological tau phosphorylation.

Decreased SIRT2 activity leads to altered microtubule dynamics in oxidatively-stressed neuronal cells: implications for Parkinson's disease

The microtubule (MT) system is important for many aspects of neuronal function, including motility, differentiation, and cargo trafficking. Parkinson's disease (PD) is associated with increased oxidative stress and alterations in the integrity of the axodendritic tree. To study dynamic mechanisms underlying the neurite shortening phenotype observed in many PD models, we employed the well-characterized oxidative parkinsonian neurotoxin, 6-hydroxydopamine (6OHDA). In both acute and chronic sub-lethal settings, 6OHDA-induced oxidative stress elicited significant alterations in MT dynamics, including reductions in MT growth rate, increased frequency of MT pauses/retractions, and increased levels of tubulin acetylation. Interestingly, 6OHDA decreased the activity of tubulin deacetylases, specifically sirtuin 2 (SIRT2), through more than one mechanism. Restoration of tubulin deacetylase function rescued the changes in MT dynamics and prevented neurite shortening in neuron-differentiated, 6OHDA-treated cells. These data indicate that impaired tubulin deacetylation contributes to altered MT dynamics in oxidatively-stressed cells, conferring key insights for potential therapeutic strategies to correct MT-related deficits contributing to neuronal aging and disease.

Deciphering the molecular profile of plaques, memory decline and neuron loss in two mouse models for Alzheimer's disease by deep sequencing

One of the central research questions on the etiology of Alzheimer’s disease (AD) is the elucidation of the molecular signatures triggered by the amyloid cascade of pathological events. Next-generation sequencing allows the identification of genes involved in disease processes in an unbiased manner. We have combined this technique with the analysis of two AD mouse models: (1) The 5XFAD model develops early plaque formation, intraneuronal Aβ aggregation, neuron loss, and behavioral deficits. (2) The Tg4–42 model expresses N-truncated Aβ_4–42 and develops neuron loss and behavioral deficits albeit without plaque formation. Our results show that learning and memory deficits in the Morris water maze and fear conditioning tasks in Tg4–42 mice at 12 months of age are similar to the deficits in 5XFAD animals. This suggested that comparative gene expression analysis between the models would allow the dissection of plaque-related and -unrelated disease relevant factors. Using deep sequencing differentially expressed genes (DEGs) were identified and subsequently verified by quantitative PCR. Nineteen DEGs were identified in pre-symptomatic young 5XFAD mice, and none in young Tg4–42 mice. In the aged cohort, 131 DEGs were found in 5XFAD and 56 DEGs in Tg4–42 mice. Many of the DEGs specific to the 5XFAD model belong to neuroinflammatory processes typically associated with plaques. Interestingly, 36 DEGs were identified in both mouse models indicating common disease pathways associated with behavioral deficits and neuron loss.

Analysis considerations for utilizing RNA-Seq to characterize the brain transcriptome

RNA-Seq allows one to examine only gene expression as well as expression of noncoding RNAs, alternative splicing, and allele-specific expression. With this increased sensitivity and dynamic range, there are computational and statistical considerations that need to be contemplated, which are highly dependent on the biological question being asked. We highlight these to provide an overview of their importance and the impact they can have on downstream interpretation of the brain transcriptome.

Integrative biological analysis for neuropsychopharmacology

Although advances in psychotherapy have been made in recent years, drug discovery for brain diseases such as schizophrenia and mood disorders has stagnated. The need for new biomarkers and validated therapeutic targets in the field of neuropsychopharmacology is widely unmet. The brain is the most complex part of human anatomy from the standpoint of number and types of cells, their interconnections, and circuitry. To better meet patient needs, improved methods to approach brain studies by understanding functional networks that interact with the genome are being developed. The integrated biological approaches--proteomics, transcriptomics, metabolomics, and glycomics--have a strong record in several areas of biomedicine, including neurochemistry and neuro-oncology. Published applications of an integrated approach to projects of neurological, psychiatric, and pharmacological natures are still few but show promise to provide deep biological knowledge derived from cells, animal models, and clinical materials. Future studies that yield insights based on integrated analyses promise to deliver new therapeutic targets and biomarkers for personalized medicine.

Brain banking for neurological disorders

Brain banks are used to gather, store, and provide human brain tissue for research and have been fundamental to improving our knowledge of the brain in health and disease. To maintain this role, the legal and ethical issues relevant to the operations of brain banks need to be more widely understood. In recent years, researchers have reported that shortages of high-quality brain tissue samples from both healthy and diseased people have impaired their efforts. Closer collaborations between brain banks and improved strategies for brain donation programmes will be essential to overcome these problems as the demand for brain tissue increases and new research techniques become more widespread, with the potential for substantial scientific advances in increasingly common neurological disorders.

Unique transcriptome patterns of the white and grey matter corroborate structural and functional heterogeneity in the human frontal lobe

The human frontal lobe has undergone accelerated evolution, leading to the development of unique human features such as language and self-reflection. Cortical grey matter and underlying white matter reflect distinct cellular compositions in the frontal lobe. Surprisingly little is known about the transcriptomal landscape of these distinct regions. Here, for the first time, we report a detailed transcriptomal profile of the frontal grey (GM) and white matter (WM) with resolution to alternatively spliced isoforms obtained using the RNA-Seq approach. We observed more vigorous transcriptome activity in GM compared to WM, presumably because of the presence of cellular bodies of neurons in the GM and RNA associated with the nucleus and perinuclear space. Among the top differentially expressed genes, we also identified a number of long intergenic non-coding RNAs (lincRNAs), specifically expressed in white matter, such as LINC00162. Furthermore, along with confirmation of expression of known markers for neurons and oligodendrocytes, we identified a number of genes and splicing isoforms that are exclusively expressed in GM or WM with examples of GABRB2 and PAK2 transcripts, respectively. Pathway analysis identified distinct physiological and biochemical processes specific to grey and white matter samples with a prevalence of synaptic processes in GM and myelination regulation and axonogenesis in the WM. Our study also revealed that expression of many genes, for example, the GPR123, is characterized by isoform switching, depending in which structure the gene is expressed. Our report clearly shows that GM and WM have perhaps surprisingly divergent transcriptome profiles, reflecting distinct roles in brain physiology. Further, this study provides the first reference data set for a normal human frontal lobe, which will be useful in comparative transcriptome studies of cerebral disorders, in particular, neurodegenerative diseases.

Transcriptional regulation and its misregulation in Alzheimer's disease

Alzheimer’s disease (AD) is a devastating neurodegenerative disorder characterized by loss of memory and cognitive function. A key neuropathological event in AD is the accumulation of amyloid-β (Aβ) peptide. The production and clearance of Aβ in the brain are regulated by a large group of genes. The expression levels of these genes must be fine-tuned in the brain to keep Aβ at a balanced amount under physiological condition. Misregulation of AD genes has been found to either increase AD risk or accelerate the disease progression. In recent years, important progress has been made in uncovering the regulatory elements and transcriptional factors that guide the expression of these genes. In this review, we describe the mechanisms of transcriptional regulation for the known AD genes and the misregualtion that leads to AD susceptibility.

Transcriptome analyses of the human retina identify unprecedented transcript diversity and 3.5 Mb of novel transcribed sequence via significant alternative splicing and novel genes

BACKGROUND

The retina is a complex tissue comprised of multiple cell types that is affected by a diverse set of diseases that are important causes of vision loss. Characterizing the transcripts, both annotated and novel, that are expressed in a given tissue has become vital for understanding the mechanisms underlying the pathology of disease.

RESULTS

We sequenced RNA prepared from three normal human retinas and characterized the retinal transcriptome at an unprecedented level due to the increased depth of sampling provided by the RNA-seq approach. We used a non-redundant reference transcriptome from all of the empirically-determined human reference tracks to identify annotated and novel sequences expressed in the retina. We detected 79,915 novel alternative splicing events, including 29,887 novel exons, 21,757 3' and 5' alternate splice sites, and 28,271 exon skipping events. We also identified 116 potential novel genes. These data represent a significant addition to the annotated human transcriptome. For example, the novel exons detected increase the number of identified exons by 3%. Using a high-throughput RNA capture approach to validate 14,696 of these novel transcriptome features we found that 99% of the putative novel events can be reproducibly detected. Further, 15-36% of the novel splicing events maintain an open reading frame, suggesting they produce novel protein products.

CONCLUSIONS

To our knowledge, this is the first application of RNA capture to perform large-scale validation of novel transcriptome features. In total, these analyses provide extensive detail about a previously uncharacterized level of transcript diversity in the human retina.

Parallel comparison of Illumina RNA-Seq and Affymetrix microarray platforms on transcriptomic profiles generated from 5-aza-deoxy-cytidine treated HT-29 colon cancer cells and simulated datasets

BACKGROUND

High throughput parallel sequencing, RNA-Seq, has recently emerged as an appealing alternative to microarray in identifying differentially expressed genes (DEG) between biological groups. However, there still exists considerable discrepancy on gene expression measurements and DEG results between the two platforms. The objective of this study was to compare parallel paired-end RNA-Seq and microarray data generated on 5-azadeoxy-cytidine (5-Aza) treated HT-29 colon cancer cells with an additional simulation study.

METHODS

We first performed general correlation analysis comparing gene expression profiles on both platforms. An Errors-In-Variables (EIV) regression model was subsequently applied to assess proportional and fixed biases between the two technologies. Then several existing algorithms, designed for DEG identification in RNA-Seq and microarray data, were applied to compare the cross-platform overlaps with respect to DEG lists, which were further validated using qRT-PCR assays on selected genes. Functional analyses were subsequently conducted using Ingenuity Pathway Analysis (IPA).

RESULTS

Pearson and Spearman correlation coefficients between the RNA-Seq and microarray data each exceeded 0.80, with 66%~68% overlap of genes on both platforms. The EIV regression model indicated the existence of both fixed and proportional biases between the two platforms. The DESeq and baySeq algorithms (RNA-Seq) and the SAM and eBayes algorithms (microarray) achieved the highest cross-platform overlap rate in DEG results from both experimental and simulated datasets. DESeq method exhibited a better control on the false discovery rate than baySeq on the simulated dataset although it performed slightly inferior to baySeq in the sensitivity test. RNA-Seq and qRT-PCR, but not microarray data, confirmed the expected reversal of SPARC gene suppression after treating HT-29 cells with 5-Aza. Thirty-three IPA canonical pathways were identified by both microarray and RNA-Seq data, 152 pathways by RNA-Seq data only, and none by microarray data only.

CONCLUSIONS

These results suggest that RNA-Seq has advantages over microarray in identification of DEGs with the most consistent results generated from DESeq and SAM methods. The EIV regression model reveals both fixed and proportional biases between RNA-Seq and microarray. This may explain in part the lower cross-platform overlap in DEG lists compared to those in detectable genes.

Pathway analysis of the human brain transcriptome in disease

Pathway analysis is a powerful method for discerning differentially regulated genes and elucidating their biological importance. It allows for the identification of perturbed or aberrantly expressed genes within a biological context from extensive data sets and offers a simplistic approach for interrogating such data sets. With the growing use of microarrays and RNA-Seq, data for genome-wide studies are growing at an alarming rate, and the use of deep sequencing is revealing elements of the genome previously uncharacterised. Through the employment of pathway analysis, mechanisms in complex diseases may be explored and novel causatives found primarily through differentially regulated genes. Further, with the implementation of next generation sequencing, a deeper resolution may be attained, particularly in identification of isoform diversity and SNPs. Here, we look at a broad overview of pathway analysis in the human brain transcriptome and its relevance in teasing out underlying causes of complex diseases. We will outline processes in data gathering and analysis of particular diseases in which these approaches have been successful.

Decoding the non-coding RNAs in Alzheimer's disease

Non-coding RNAs (ncRNAs) are integral components of biological networks with fundamental roles in regulating gene expression. They can integrate sequence information from the DNA code, epigenetic regulation and functions of multimeric protein complexes to potentially determine the epigenetic status and transcriptional network in any given cell. Humans potentially contain more ncRNAs than any other species, especially in the brain, where they may well play a significant role in human development and cognitive ability. This review discusses their emerging role in Alzheimer's disease (AD), a human pathological condition characterized by the progressive impairment of cognitive functions. We discuss the complexity of the ncRNA world and how this is reflected in the regulation of the amyloid precursor protein and Tau, two proteins with central functions in AD. By understanding this intricate regulatory network, there is hope for a better understanding of disease mechanisms and ultimately developing diagnostic and therapeutic tools.

Analyzing gene expression from whole tissue vs. different cell types reveals the central role of neurons in predicting severity of Alzheimer's disease

Alterations in gene expression resulting from Alzheimer’s disease have received considerable attention in recent years. Although expression has been investigated separately in whole brain tissue, in astrocytes and in neurons, a rigorous comparative study quantifying the relative utility of these sources in predicting the progression of Alzheimer’s disease has been lacking. Here we analyze gene expression from neurons, astrocytes and whole tissues across different brain regions, and compare their ability to predict Alzheimer’s disease progression by building pertaining classification models based on gene expression sets annotated to different biological processes. Remarkably, we find that predictions based on neuronal gene expression are significantly more accurate than those based on astrocyte or whole tissue expression. The findings explicate the central role of neurons, particularly as compared to glial cells, in the pathogenesis of Alzheimer’s disease, and emphasize the importance of measuring gene expression in the most relevant (pathogenically ‘proximal’) single cell types.

Altered transcription factor trafficking in oxidatively-stressed neuronal cells

Age-related neurodegenerative diseases are associated with alterations in gene expression in affected neurons. One of the mechanisms that could account for this is altered subcellular localization of transcription factors, which has been observed in human post-mortem brains of each of the major neurodegenerative diseases, including Parkinson's disease (PD). The specific mechanisms are yet to be elucidated; however a potential mechanism involves alterations in nuclear transport. In this study, we examined the nucleocytoplasmic trafficking of select transcription factors in response to a PD-relevant oxidative injury, 6-hydroxydopamine (6OHDA). Utilizing a well-established model of ligand-regulated nucleocytoplasmic shuttling, the glucocorticoid receptor, we found that 6OHDA selectively impaired nuclear import through an oxidative mechanism without affecting nuclear export or nuclear retention. Interestingly, impaired nuclear import was selective as Nrf2 (nuclear factor E2-related factor 2) nuclear localization remained intact in 6OHDA-treated cells. Thus, oxidative stress specifically impacts the subcellular localization of some but not all transcription factors, which is consistent with observations in post-mortem PD brains. Our data further implicate a role for altered microtubule dependent trafficking in the differential effects of 6OHDA on transcription factor import. Oxidative disruption of microtubule-dependent nuclear transport may contribute to selective declines in transcriptional responses of aging or diseased dopaminergic cells.

RNA-Seq and human complex diseases: recent accomplishments and future perspectives

The availability of the human genome sequence has allowed identification of disease-causing mutations in many Mendelian disorders, and detection of significant associations of nucleotide polymorphisms to complex diseases and traits. Despite these progresses, finding the causative variations for most of the common diseases remains a complex task. Several studies have shown gene expression analyses provide a quite unbiased way to investigate complex traits and common disorders' pathogenesis. Therefore, whole-transcriptome analysis is increasingly acquiring a key role in the knowledge of mechanisms responsible for complex diseases. Hybridization- and tag-based technologies have elucidated the involvement of multiple genes and pathways in pathological conditions, providing insights into the expression of thousand of coding and noncoding RNAs, such as microRNAs. However, the introduction of Next-Generation Sequencing, particularly of RNA-Seq, has overcome some drawbacks of previously used technologies. Identifying, in a single experiment, potentially novel genes/exons and splice isoforms, RNA editing, fusion transcripts and allele-specific expression are some of its advantages. RNA-Seq has been fruitfully applied to study cancer and host-pathogens interactions, and it is taking first steps for studying neurodegenerative diseases (ND) as well as neuropsychiatric diseases. In addition, it is emerging as a very powerful tool to study quantitative trait loci associated with gene expression in complex diseases. This paper provides an overview on gene expression profiling of complex diseases, with emphasis on RNA-Seq, its advantages over conventional technologies for studying cancer and ND, and for linking nucleotide variations to gene expression changes, also discussing its limitations.

From Transcriptome to Noncoding RNAs: Implications in ALS Mechanism

In the last years, numerous studies have focused on understanding the metabolism of RNA and its implication in disease processes but abnormal RNA metabolism is still unknown. RNA plays a central role in translating genetic information into proteins and in many other catalytic and regulatory tasks. Recent advances in the study of RNA metabolism revealed complex pathways for the generation and maintenance of functional RNA in amyotrophic lateral sclerosis (ALS). Interestingly, perturbations in RNA processing have been described in ALS at various levels such as gene transcription, mRNA stabilization, transport, and translational regulations. In this paper, we will discuss the alteration of RNA profile in ALS disease, starting from transcription, the first step leading to gene expression, through the posttranscriptional regulation, including RNA/DNA binding proteins and aberrant exon splicing to protein noncoding RNAs, as lncRNA and microRNA.

Alternative splicing of mRNA in the molecular pathology of neurodegenerative diseases

Alternative splicing (AS) is a post-transcriptional process that occurs in multiexon genes, and errors in this process have been implicated in many human diseases. Until recently, technological limitations prevented AS from being examined at the genome-wide scale. With the advent of new technologies, including exon arrays and next-generation sequencing (NGS) techniques (e.g., RNA-Seq), a higher resolution view of the human transcriptome is now available. This is particularly applicable in the study of neurodegenerative brain diseases (NBDs), such as Alzheimer's disease and Parkinson's disease, because the brain has the greatest amount of alternative splicing of all human tissues. Although many of the AS events associated with these disorders were initially identified using low-throughput methodologies, genome-wide analysis allows for more in-depth studies, marking a new chapter in transcript exploration. In this review, the latest technologies used to study the transcriptome and the AS genes that have been associated with a number of neurodegenerative brain diseases are discussed.

Molecular markers and mechanisms of stroke: RNA studies of blood in animals and humans

Whole genome expression microarrays can be used to study gene expression in blood, which comes in part from leukocytes, immature platelets, and red blood cells. Since these cells are important in the pathogenesis of stroke, RNA provides an index of these cellular responses to stroke. Our studies in rats have shown specific gene expression changes 24  hours after ischemic stroke, hemorrhage, status epilepticus, hypoxia, hypoglycemia, global ischemia, and following brief focal ischemia that simulated transient ischemic attacks in humans. Human studies show gene expression changes following ischemic stroke. These gene profiles predict a second cohort with >90% sensitivity and specificity. Gene profiles for ischemic stroke caused by large-vessel atherosclerosis and cardioembolism have been described that predict a second cohort with >85% sensitivity and specificity. Atherosclerotic genes were associated with clotting, platelets, and monocytes, and cardioembolic genes were associated with inflammation, infection, and neutrophils. These gene profiles predicted the cause of stroke in 58% of cryptogenic patients. These studies will provide diagnostic, prognostic, and therapeutic markers, and will advance our understanding of stroke in humans. New techniques to measure all coding and noncoding RNAs along with alternatively spliced transcripts will markedly advance molecular studies of human stroke.

Whole transcriptome sequencing reveals gene expression and splicing differences in brain regions affected by Alzheimer's disease

Recent studies strongly indicate that aberrations in the control of gene expression might contribute to the initiation and progression of Alzheimer's disease (AD). In particular, alternative splicing has been suggested to play a role in spontaneous cases of AD. Previous transcriptome profiling of AD models and patient samples using microarrays delivered conflicting results. This study provides, for the first time, transcriptomic analysis for distinct regions of the AD brain using RNA-Seq next-generation sequencing technology. Illumina RNA-Seq analysis was used to survey transcriptome profiles from total brain, frontal and temporal lobe of healthy and AD post-mortem tissue. We quantified gene expression levels, splicing isoforms and alternative transcript start sites. Gene Ontology term enrichment analysis revealed an overrepresentation of genes associated with a neuron's cytological structure and synapse function in AD brain samples. Analysis of the temporal lobe with the Cufflinks tool revealed that transcriptional isoforms of the apolipoprotein E gene, APOE-001, -002 and -005, are under the control of different promoters in normal and AD brain tissue. We also observed differing expression levels of APOE-001 and -002 splice variants in the AD temporal lobe. Our results indicate that alternative splicing and promoter usage of the APOE gene in AD brain tissue might reflect the progression of neurodegeneration.

Understanding the pathogenesis of Alzheimer's disease: will RNA-Seq realize the promise of transcriptomics?

The prevalence of Alzheimer's disease (AD) is increasing rapidly in the western world and is poised to have a significant economic and societal impact. Current treatments do not alter the underlying disease processes meaning new treatments are required if this imminent epidemic is to be averted. The clinical manifestations of AD are secondary to a substantial loss of cortical neurons. To be effective, neuroprotective strategies will need to be implemented prior to this cell loss. However, this requires the discovery of both pre-clinical markers to identify susceptible patients and the early pathogenic mechanisms to serve as therapeutic targets. Although the biomarkers and pathogenic mechanisms may overlap, it is likely that new approaches are required to identify novel elements of the disease. Transcriptomic analyses, that assume no a priori etiological hypotheses, promise much in elucidating the pathogenesis of complex diseases like AD. Microarrays are the most popular platform for transcriptomic analysis and have been applied across AD models, patient samples and postmortem brain tissue. The results of these studies have been largely discordant which could, to some extent, reflect the limitations of this probe-hybridization-based methodology. In comparison, whole transcriptome sequencing (RNA-Seq) utilizes a highly efficient, next-generation DNA sequencing method with improved dynamic range and scope of transcript detection. RNA-Seq is not only highly suited to investigations of the genomically complex human brain tissue but it can potentially overcome technical issues inherent to case-control comparisons of postmortem brain tissue in neurodegenerative diseases. The volume of data generated by this platform looms as the major logistical hurdle and a systematic experimental approach will be required to maximise the detection of pathogenically relevant signals. Nevertheless, RNA-Seq looks set to deliver a quantum leap forward in our understanding of AD pathogenesis.