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

Increased Neuronal Nitric Oxide Synthase in Alzheimer's Disease Mediates Spontaneous Calcium Signaling and Divergent Glutamatergic Calcium Responses

Nitrosative stress is a feature of Alzheimer's disease (AD). Aims: We aimed to identify the cause underpinning increased nitric oxide (NO) in neurons and the impact of NO on neuronal function in AD. Results: We analyzed neuronal nitric oxide synthase (nNOS) protein levels in postmortem tissue and induced pluripotent stem cell (iPSC)-derived neurons from Alzheimer's patients and controls by immunohistochemistry and Western blots. Furthermore, we assessed the impact of modulating nNOS function or NO levels on neuronal glutamatergic signaling using calcium imaging. We show that nNOS protein levels are increased in early and severely affected brain regions of AD postmortem tissue, but not late and mildly affected regions, or cognitively normal individuals. The increased nNOS phenotype was also present in iPSC-derived neurons from late-onset Alzheimer's disease (LOAD) patients compared with controls, along with increased levels of nitrite, a stable marker of NO. Innovation: We observed a divergent functional impact of NO that included strengthening the calcium response in control neurons, while dysregulating calcium signaling and altering the amplitude and kinetics of the calcium responses to glutamate in the AD neurons. Pharmacological scavenging of NO or inhibition of nNOS prevented aberrant spontaneous calcium signaling in AD neurons. Conclusion: Together these data identify increases in nNOS protein in AD. Functional data suggest that NO modulation of glutamatergic calcium signaling is neuroprotective under nonpathogenic conditions, with increased nNOS and NO contributing to dysregulated spontaneous calcium signaling in AD neurons.

Brain Region-Dependent Alternative Splicing of Alzheimer Disease (AD)-Risk Genes Is Associated With Neuropathological Features in AD

PURPOSE

Alzheimer disease (AD) is one of the most complex diseases and is characterized by AD-related neuropathological features, including accumulation of amyloid-β plaques and tau neurofibrillary tangles. Dysregulation of alternative splicing (AS) contributes to these features, and there is heterogeneity in features across brain regions between AD patients, leading to different severity and progression rates; however, brain region-specific AS mechanisms still remain unclear. Therefore, we aimed to systemically investigate AS in multiple brain regions of AD patients and how they affect clinical features.

METHODS

We analyzed RNA sequencing (RNA-Seq) data obtained from brain regions (frontal and temporal) of AD patients. Reads were mapped to the hg19 reference genome using the STAR aligner, and exon skipping (ES) rates were estimated as percent spliced in (PSI) by rMATs. We focused on AD-risk genes discovered by genome-wide association studies, and accordingly evaluated associations between PSI of skipped exons in AD-risk genes and Braak stage and plaque density mean (PM) for each brain region. We also integrated whole-genome sequencing data of the ascertained samples with RNA-Seq data to identify genetic regulators of feature-associated ES.

RESULTS

We identified 26 and 41 ES associated with Braak stage in frontal and temporal regions, respectively, and 10 and 50 ES associated with PM. Among those, 10 were frontal-specific (CLU and NTRK2), 65 temporal-specific (HIF1A and TRPC4AP), and 26 shared ES (APP) that accompanied functional Gene Ontology terms, including axonogenesis in shared-ES genes. We further identified genetic regulators that account for 44 ES (44% of the total). Finally, we present as a case study the systematic regulation of an ES in APP, which is important in AD pathogenesis.

CONCLUSION

This study provides new insights into brain region-dependent AS regulation of the architecture of AD-risk genes that contributes to AD pathologies, ultimately allowing identification of a treatment target and region-specific biomarkers for AD.

Acrolein, an endogenous aldehyde induces synaptic dysfunction in vitro and in vivo: Involvement of RhoA/ROCK2 pathway

Acrolein, an unsaturated aldehyde, is increased in the brain of Alzheimer's disease (AD) patients and identified as a potential inducer of sporadic AD. Synaptic dysfunction, as a typical pathological change occurring in the early stage of AD, is most closely associated with the severity of dementia. However, there remains a lack of clarity on the mechanisms of acrolein inducing AD-like pathology and synaptic impairment. In this study, acrolein-treated primary cultured neurons and mice were applied to investigate the effects of acrolein on cognitive impairment and synaptic dysfunction and their signaling mechanisms. In vitro, ROCK inhibitors, Fasudil, and Y27632, could attenuate the axon ruptures and synaptic impairment caused by acrolein. Meanwhile, RNA-seq distinct differentially expressed genes in acrolein models and initially linked activated RhoA/Rho-kinase2 (ROCK2) to acrolein-induced synaptic dysfunction, which could regulate neuronal cytoskeleton and neurite. The Morris water maze test and in vivo field excitatory postsynaptic potential (fEPSP) were performed to evaluate spatial memory and long-term potential (LTP), respectively. Acrolein induced cognitive impairment and attenuated LTP. Furthermore, the protein level of Synapsin 1 and postsynaptic density 95 (PSD95) and dendritic spines density were also decreased in acrolein-exposed mice. These changes were improved by ROCK2 inhibitor Fasudil or in ROCK2^+/- mice. Together, our findings suggest that RhoA/ROCK2 signaling pathway plays a critical role in acrolein-induced synaptic damage and cognitive dysfunction, suggesting inhibition of ROCK2 should benefit to the early AD.

Deregulation of ncRNA in Neurodegenerative Disease: Focus on circRNA, lncRNA and miRNA in Amyotrophic Lateral Sclerosis

Parallel and massive sequencing of total RNA samples derived from different samples are possible thanks to the use of NGS (Next Generation Sequencing) technologies. This allowed characterizing the transcriptomic profile of both cell and tissue populations, increasing the knowledge of the molecular pathological processes of complex diseases, such as neurodegenerative diseases (NDs). Among the NDs, Amyotrophic Lateral Sclerosis (ALS) is caused by the progressive loss of motor neurons (MNs), and, to date, the diagnosis is often made by exclusion because there is no specific symptomatologic picture. For this reason, it is important to search for biomarkers that are clinically useful for carrying out a fast and accurate diagnosis of ALS. Thanks to various studies, it has been possible to propose several molecular mechanisms associated with the disease, some of which include the action of non-coding RNA, including circRNAs, miRNAs, and lncRNAs which will be discussed in the present review. The evidence analyzed in this review highlights the importance of conducting studies to better characterize the different ncRNAs in the disease to use them as possible diagnostic, prognostic, and/or predictive biomarkers of ALS and other NDs.

Omics sciences for systems biology in Alzheimer's disease: State-of-the-art of the evidence

Alzheimer's disease (AD) is characterized by non-linear, genetic-driven pathophysiological dynamics with high heterogeneity in biological alterations and disease spatial-temporal progression. Human in-vivo and post-mortem studies point out a failure of multi-level biological networks underlying AD pathophysiology, including proteostasis (amyloid-β and tau), synaptic homeostasis, inflammatory and immune responses, lipid and energy metabolism, oxidative stress. Therefore, a holistic, systems-level approach is needed to fully capture AD multi-faceted pathophysiology. Omics sciences - genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics - embedded in the systems biology (SB) theoretical and computational framework can generate explainable readouts describing the entire biological continuum of a disease. Such path in Neurology is encouraged by the promising results of omics sciences and SB approaches in Oncology, where stage-driven pathway-based therapies have been developed in line with the precision medicine paradigm. Multi-omics data integrated in SB network approaches will help detect and chart AD upstream pathomechanistic alterations and downstream molecular effects occurring in preclinical stages. Finally, integrating omics and neuroimaging data - i.e., neuroimaging-omics - will identify multi-dimensional biological signatures essential to track the clinical-biological trajectories, at the subpopulation or even individual level.

Defining early changes in Alzheimer's disease from RNA sequencing of brain regions differentially affected by pathology

Tau pathology in Alzheimer’s disease (AD) spreads in a predictable pattern that corresponds with disease symptoms and severity. At post-mortem there are cortical regions that range from mildly to severely affected by tau pathology and neuronal loss. A comparison of the molecular signatures of these differentially affected areas within cases and between cases and controls may allow the temporal modelling of disease progression. Here we used RNA sequencing to explore differential gene expression in the mildly affected primary visual cortex and moderately affected precuneus of ten age-, gender- and RNA quality-matched post-mortem brains from AD patients and healthy controls. The two regions in AD cases had similar transcriptomic signatures but there were broader abnormalities in the precuneus consistent with the greater tau load. Both regions were characterised by upregulation of immune-related genes such as those encoding triggering receptor expressed on myeloid cells 2 and membrane spanning 4-domains A6A and milder changes in insulin/IGF1 signalling. The precuneus in AD was also characterised by changes in vesicle secretion and downregulation of the interneuronal subtype marker, somatostatin. The ‘early’ AD transcriptome is characterised by perturbations in synaptic vesicle secretion on a background of neuroimmune dysfunction. In particular, the synaptic deficits that characterise AD may begin with the somatostatin division of inhibitory neurotransmission.

Sustained Stimulation of β2AR Inhibits Insulin Signaling in H9C2 Cardiomyoblast Cells Through the PKA-Dependent Signaling Pathway

INTRODUCTION

This study aimed to investigate the role of β2 adrenergic receptor (β2AR) in insulin signaling transduction in H9C2 cardiomyoblast cells to understand the formation of the β2AR-insulin receptor (IR) protein complex and its role in insulin-induced Glut4 expression.

METHODS

H9C2 cells were treated with various protein inhibitors (CGP, β1AR inhibitor CGP20712; ICI, β2AR inhibitor ICI 118,551; PKI, PKA inhibitor myristoylated PKI; PD 0325901, MEK inhibitor; SP600125, JNK inhibitor) with or without insulin or isoproterenol (ISO) before RNA-sequencing (RNA-Seq) and quantitative-PCR (Q-PCR). Yeast two-hybrid, co-immunoprecipitation and His-tag pull-down assay were carried out to investigate the formation of the β2AR-IR protein complex. The intracellular concentrations of cAMP in H9C2 cells were tested by high performance liquid chromatography (HPLC) and the phosphorylation of JNK was tested by Western blot.

RESULTS

Gene Ontology (GO) analysis revealed that the most significantly enriched processes in the domain of molecular function (MF) were catalytic activity and binding, whereas in the domain of biological processes (BP) were metabolic process and cellular process. Furthermore, the enriched processes in the domain of cellular components (CC) were cell and cell parts. The Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis showed that the most significant pathways that have been altered included the PI3K-Akt and MAPK signaling pathways. Q-PCR, which was performed to verify the gene expression levels exhibited consistent results. In evaluating the signaling pathways, the sustained stimulation of β2AR by ISO inhibited insulin signalling, and the effect was primarily through the cAMP-PKA-JNK pathway and MEK/JNK signaling pathway. Yeast two-hybrid, co-immunoprecipitation and His-tag pull-down assay revealed that β2AR, IR, insulin receptor substrate 1 (IRS1), Grb2-associated binding protein 1 (GAB1) and Grb2 existed in the same protein complex.

CONCLUSION

The sustained stimulation of β2AR might inhibit insulin signaling transduction through the cAMP-PKA-JNK and MEK/JNK pathways in H9C2 cells.

Blood-based systems biology biomarkers for next-generation clinical trials in Alzheimer's disease

Alzheimer's disease (AD)-a complex disease showing multiple pathomechanistic alterations-is triggered by nonlinear dynamic interactions of genetic/epigenetic and environmental risk factors, which, ultimately, converge into a biologically heterogeneous disease. To tackle the burden of AD during early preclinical stages, accessible blood-based biomarkers are currently being developed. Specifically, next-generation clinical trials are expected to integrate positive and negative predictive blood-based biomarkers into study designs to evaluate, at the individual level, target druggability and potential drug resistance mechanisms. In this scenario, systems biology holds promise to accelerate validation and qualification for clinical trial contexts of use-including proof-of-mechanism, patient selection, assessment of treatment efficacy and safety rates, and prognostic evaluation. Albeit in their infancy, systems biology-based approaches are poised to identify relevant AD "signatures" through multifactorial and interindividual variability, allowing us to decipher disease pathophysiology and etiology. Hopefully, innovative biomarker-drug codevelopment strategies will be the road ahead towards effective disease-modifying drugs.
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A Systematic Bioinformatics Workflow With Meta-Analytics Identified Potential Pathogenic Factors of Alzheimer's Disease

Potential pathogenic factors, other than well-known APP, APOE4, and PSEN, can be further identified from transcriptomics studies of differentially expressed genes (DEGs) that are specific for Alzheimer’s disease (AD), but findings are often inconsistent or even contradictory. Evidence corroboration by combining meta-analysis and bioinformatics methods may help to resolve existing inconsistencies and contradictions. This study aimed to demonstrate a systematic workflow for evidence synthesis of transcriptomic studies using both meta-analysis and bioinformatics methods to identify potential pathogenic factors. Transcriptomic data were assessed from GEO and ArrayExpress after systematic searches. The DEGs and their dysregulation states from both DNA microarray and RNA sequencing datasets were analyzed and corroborated by meta-analysis. Statistically significant DEGs were used for enrichment analysis based on KEGG and protein–protein interaction network (PPIN) analysis based on STRING. AD-specific modules were further determined by the DIAMOnD algorithm, which identifies significant connectivity patterns between specific disease-associated proteins and non-specific proteins. Within AD-specific modules, the nodes of highest degrees (>95th percentile) were considered as potential pathogenic factors. After systematic searches of 225 datasets, extensive meta-analyses among 25 datasets (21 DNA microarray datasets and 4 RNA sequencing datasets) identified 9,298 DEGs. The dysregulated genes and pathways in AD were associated with impaired amyloid-β (Aβ) clearance. From the AD-specific module, Fyn, and EGFR were the most statistically significant and biologically relevant. This meta-analytical study suggested that the reduced Aβ clearance in AD pathogenesis was associated with the genes encoding Fyn and EGFR, which were key receptors in Aβ downstream signaling.

Transcriptional Regulation Analysis of Alzheimer's Disease Based on FastNCA Algorithm

Background:

Understanding the relationship between genetic variation and gene expression is a central issue in genetics. Although many studies have identified genetic variations associated with gene expression, it is unclear how they perturb the underlying regulatory network of gene expression.

Objective:

To explore how genetic variations perturb potential transcriptional regulation networks of Alzheimer’s disease (AD) to paint a more complete picture of the complex landscape of transcription regulation.

Methods:

Fast network component analysis (FastNCA), which can capture the genetic variations in the form of single nucleotide polymorphisms (SNPs), is applied to analyse the expression activities of TFs and their regulatory strengths on TGs using microarray and RNA-seq data of AD. Then, multi-data fusion analysis was used to analyze the different TGs regulated by the same TFs in the different data by constructing the transcriptional regulatory networks of differentially expressed genes.

Results:

the common TF regulating TGs are not necessarily identical in different data, they may be involved in the same pathways that are closely related to the pathogenesis of AD, such as immune response, signal transduction and cytokine-cytokine receptor interaction pathways. Even if they are involved in different pathways, these pathways are also confirmed to have a potential link with AD.

Conclusion:

The study shows that the pathways of different TGs regulated by the same TFs in different data are all closely related to AD. Multi-data fusion analysis can form a certain complement to some extent and get more comprehensive results in the process of exploring the pathogenesis of AD.

The Rat Prefrontal-Cortex Transcriptome: Effects of Aging and Sporadic Alzheimer's Disease-Like Pathology

Alzheimer's disease (AD) is the most widespread late-life dementia and involves the prefrontal cortex, a vulnerable brain region implicated in memory, emotion, cognition, and decision-making behavior. To understand the molecular differences between the effects of aging and AD on the prefrontal cortex, this study characterized the age-dependent changes in gene expression in Wistar rats (control) and OXYS rats (rodents that simulate key characteristics of sporadic AD) using RNA sequencing. We found that major altered biological processes during aging in Wistar rats were associated with immune processes. Gene expression changes during development of AD-like pathology as well as at the preclinical stage were related to neuronal plasticity, catalytic activity, lipid and immune processes, and mitochondria. A comparison of genes between data sets "OXYS rats" and "human AD" revealed similarity in expression alterations of genes related primarily to mitochondrial function; immune, endocrine, and circulatory systems; signal transduction; neuronal and synaptic processes; hypoxia; and apoptosis. Expression changes in mitochondrial processes identified in OXYS rats by RNA sequencing were confirmed by ultrastructural neuronal organelle alterations and low activity of respiratory chain complexes I, IV, and V in cortical mitochondria, suggesting that mitochondrial dysfunction appears to mediate or possibly even initiate the development of AD.

Suppression of Alzheimer's Disease-Like Pathology Progression by Mitochondria-Targeted Antioxidant SkQ1: A Transcriptome Profiling Study

Alzheimer's disease (AD) is the most common type of dementia, with increasing prevalence and no disease-modifying treatment available yet. There is increasing evidence—from interventions targeting mitochondria—that may shed some light on new strategies for the treatment of AD. Previously, using senescence-accelerated OXYS rats that simulate key characteristics of sporadic AD, we have shown that treatment with mitochondria-targeted antioxidant SkQ1 (plastoquinonyl-decyltriphenylphosphonium) from age 12 to 18 months (that is, during active progression of AD-like pathology)—via improvement of mitochondrial function—prevented the neuronal loss and synaptic damage, enhanced neurotrophic supply, and decreased amyloid-β_1–42 protein levels and tau hyperphosphorylation in the hippocampus. In the present study, we continued to explore the mechanisms of the anti-AD effects of SkQ1 in an OXYS rat model through deep RNA sequencing (RNA-seq) and focused upon the cell-specific gene expression alterations in the hippocampus. According to RNA-seq results, OXYS rats had 1,159 differentially expressed genes (DEGs) relative to Wistar rats (control), and 6-month treatment with SkQ1 decreased their number twofold. We found that 10.5% of all DEGs in untreated (control) OXYS rats were associated with mitochondrial function, whereas SkQ1 eliminated differences in the expression of 76% of DEGs (93 from 122 genes). Using transcriptome approaches, we found that the anti-AD effects of SkQ1 are associated with an improvement of the activity of many signaling pathways and intracellular processes. SkQ1 changed the expression of genes in neuronal, glial, and endothelial cells, and these genes are related to mitochondrial function, neurotrophic and synaptic activity, calcium processes, immune and cerebrovascular systems, catabolism, degradation, and apoptosis. Thus, RNA-seq analysis yields a detailed picture of transcriptional changes during the development of AD-like pathology and can point to the molecular and genetic mechanisms of action of the agents (including SkQ1) holding promise for the prevention and treatment of AD.

Higher Mass Accuracy MALDI-TOF/TOF Lipid Imaging of Human Brain Tissue in Alzheimer's Disease

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) is a well-established technique for elucidating the location and relative abundance of a range of biomolecules. More recently, research into this technique has shifted from simple discovery and demonstration of utility to application in biomedical research. Here, we describe a protocol utilizing MALDI-IMS for the spatial mapping of lipids in brain tissue from normal human brains and brains from patients with Alzheimer's disease, in the context of Alzheimer's disease. Improved accuracy calibration of the instrument from the tissue surface is emphasized, as this allows for significantly improved mass determination in time of flight (TOF)-based instruments enabling more confident preliminary lipid identification. This improved initial result allows MALDI-IMS data to be complemented with additional instrumentation, such as liquid chromatography mass spectrometry workflows or specialized non-TOF systems such as Fourier transform cyclotron resonance instruments. This method is not limited to human tissue and can be applied to virtually any lipid-rich formalin-fixed tissue. © 2019 by John Wiley & Sons, Inc.

The relationship between the morphological subtypes of microglia and Alzheimer's disease neuropathology

Microglial associations with both the major Alzheimer's disease (AD) pathognomonic entities, β-amyloid-positive plaques and tau-positive neurofibrillary tangles, have been noted in previous investigations of both human tissue and mouse models. However, the precise nature of their role in the pathogenesis of AD is debated; the major working hypothesis is that pro-inflammatory activities of activated microglia contribute to disease progression. In contrast, others have proposed that microglial dystrophy with a loss of physiological and neuroprotective activities promotes neurodegeneration. This immunohistochemical study sought to gain clarity in this area by quantifying the morphological subtypes of microglia in the mildly-affected primary visual cortex (PVC), the moderately affected superior frontal cortex (SFC) and the severely affected inferior temporal cortex (ITC) of 8 AD cases and 15 age and gender-matched, non-demented controls with ranging AD-type pathology. AD cases had increased β-amyloid and tau levels compared to controls in all regions. Neuronal loss was observed in the SFC and ITC, and was associated with atrophy in the latter. A major feature of the ITC in AD was a decrease in ramified (healthy) microglia with image analysis confirming reductions in arborized area and skeletal complexity. Activated microglia were not associated with AD but were increased in non-demented controls with greater AD-type pathology. Microglial clusters were occasionally associated with β-amyloid- and tau-positive plaques but represented less than 2% of the total microglial population. Dystrophic microglia were not associated with AD, but were inversely correlated with brain pH suggesting that agonal events were responsible for this morphological subtype. Overall these novel findings suggest that there is an early microglial reaction to AD-type pathology but a loss of healthy microglia is the prominent feature in severely affected regions of the AD brain.

Identification of exon skipping events associated with Alzheimer's disease in the human hippocampus

BACKGROUND

At least 90% of human genes are alternatively spliced. Alternative splicing has an important function regulating gene expression and miss-splicing can contribute to risk for human diseases, including Alzheimer's disease (AD).

METHODS

We developed a splicing decision model as a molecular mechanism to identify functional exon skipping events and genetic variation affecting alternative splicing on a genome-wide scale by integrating genomics, transcriptomics, and neuroimaging data in a systems biology approach. In this study, we analyzed RNA-Seq data of hippocampus brain tissue from Alzheimer's disease (AD; n = 24) and cognitively normal elderly controls (CN; n = 50) and identified three exon skipping events in two genes (RELN and NOS1) as significantly associated with AD (corrected p-value < 0.05 and fold change > 1.5). Next, we identified single-nucleotide polymorphisms (SNPs) affecting exon skipping events using the splicing decision model and then performed an association analysis of SNPs potentially affecting three exon skipping events with a global cortical measure of amyloid-β deposition measured by [18F] Florbetapir position emission tomography (PET) scan as an AD-related quantitative phenotype. A whole-brain voxel-based analysis was also performed.

RESULTS

Two exons in RELN and one exon in NOS1 showed significantly lower expression levels in the AD participants compared to CN participants, suggesting that the exons tend to be skipped more in AD. We also showed the loss of the core protein structure due to the skipped exons using the protein 3D structure analysis. The targeted SNP-based association analysis identified one intronic SNP (rs362771) adjacent to the skipped exon 24 in RELN as significantly associated with cortical amyloid-β levels (corrected p-value < 0.05). This SNP is within the splicing regulatory element, i.e., intronic splicing enhancer. The minor allele of rs362771 conferred decreases in cortical amyloid-β levels in the right temporal and bilateral parietal lobes.

CONCLUSIONS

Our results suggest that exon skipping events and splicing-affecting SNPs in the human hippocampus may contribute to AD pathogenesis. Integration of multiple omics and neuroimaging data provides insights into possible mechanisms underlying AD pathophysiology through exon skipping and may help identify novel therapeutic targets.

Evidence supporting oxidative stress in a moderately affected area of the brain in Alzheimer's disease

The pathogenesis of Alzheimer's disease (AD) remains to be elucidated. Oxidative damage and excessive beta-amyloid oligomers are components of disease progression but it is unclear how these factors are temporally related. At post mortem, the superior temporal gyrus (STG) of AD cases contains plaques, but displays few tangles and only moderate neuronal loss. The STG at post mortem may represent a brain region that is in the early stages of AD or alternately a region resistant to AD pathogenesis. We evaluated expression profiles and activity of endogenous anti-oxidants, oxidative damage and caspase activity in the STG of apolipoprotein ε4-matched human AD cases and controls. Total superoxide dismutase (SOD) activity was increased, whereas total glutathione peroxidase (GPX), catalase (CAT) and peroxiredoxin (Prx) activities, were decreased in the AD-STG, suggesting that hydrogen peroxide accumulates in this brain region. Transcripts of the transcription factor NFE2L2 and inducible HMOX1, were also increased in the AD-STG, and this corresponded to increased Nuclear factor erythroid 2-related factor (NRF-2) and total heme-oxygenase (HO) activity. The protein oxidation marker 4-hydroxynonenal (4-HNE), remained unchanged in the AD-STG. Similarly, caspase activity was unaltered, suggesting that subtle redox imbalances in early to moderate stages of AD do not impact STG viability.

Understanding Alzheimer Disease at the Interface between Genetics and Transcriptomics

Over 25 genes are known to affect the risk of developing Alzheimer disease (AD), the most common neurodegenerative dementia. However, mechanistic insights and improved disease management remains limited, due to difficulties in determining the functional consequences of genetic associations. Transcriptomics is increasingly being used to corroborate or enhance interpretation of genetic discoveries. These approaches, which include second and third generation sequencing, single-cell sequencing, and bioinformatics, reveal allele-specific events connecting AD risk genes to expression profiles, and provide converging evidence of pathophysiological pathways underlying AD. Simultaneously, they highlight brain region- and cell-type-specific expression patterns, and alternative splicing events that affect the straightforward relation between a genetic variant and AD, re-emphasizing the need for an integrated approach of genetics and transcriptomics in understanding AD.

Whole transcriptome profiling of Late-Onset Alzheimer's Disease patients provides insights into the molecular changes involved in the disease

Alzheimer’s Disease (AD) is the most common cause of dementia affecting the elderly population worldwide. We have performed a comprehensive transcriptome profiling of Late-Onset AD (LOAD) patients using second generation sequencing technologies, identifying 2,064 genes, 47 lncRNAs and 4 miRNAs whose expression is specifically deregulated in the hippocampal region of LOAD patients. Moreover, analyzing the hippocampal, temporal and frontal regions from the same LOAD patients, we identify specific sets of deregulated miRNAs for each region, and we confirm that the miR-132/212 cluster is deregulated in each of these regions in LOAD patients, consistent with these miRNAs playing a role in AD pathogenesis. Notably, a luciferase assay indicates that miR-184 is able to target the 3’UTR NR4A2 - which is known to be involved in cognitive functions and long-term memory and whose expression levels are inversely correlated with those of miR-184 in the hippocampus. Finally, RNA editing analysis  reveals a general RNA editing decrease in LOAD hippocampus, with 14 recoding sites significantly and differentially edited in 11 genes. Our data underline specific transcriptional changes in LOAD brain and provide an important source of information for understanding the molecular changes characterizing LOAD progression.

Gene regulation and genetics in neurochemistry, past to future

Ask any neuroscientist to name the most profound discoveries in the field in the past 60 years, and at or near the top of the list will be a phenomenon or technique related to genes and their expression. Indeed, our understanding of genetics and gene regulation has ushered in whole new systems of knowledge and new empirical approaches, many of which could not have even been imagined prior to the molecular biology boon of recent decades. Neurochemistry, in the classic sense, intersects with these concepts in the manifestation of neuropeptides, obviously dependent upon the central dogma (the established rules by which DNA sequence is eventually converted into protein primary structure) not only for their conformation but also for their levels and locales of expression. But, expanding these considerations to non-peptide neurotransmitters illustrates how gene regulatory events impact neurochemistry in a much broader sense, extending beyond the neurochemicals that translate electrical signals into chemical ones in the synapse, to also include every aspect of neural development, structure, function, and pathology. From the beginning, the mutability - yet relative stability - of genes and their expression patterns were recognized as potential substrates for some of the most intriguing phenomena in neurobiology - those instances of plasticity required for learning and memory. Near-heretical speculation was offered in the idea that perhaps the very sequence of the genome was altered to encode memories. A fascinating component of the intervening progress includes evidence that the central dogma is not nearly as rigid and consistent as we once thought. And this mutability extends to the potential to manipulate that code for both experimental and clinical purposes. Astonishing progress has been made in the molecular biology of neurochemistry during the 60 years since this journal debuted. Many of the gains in conceptual understanding have been driven by methodological progress, from automated high-throughput sequencing instruments to recombinant-DNA vectors that can convey color-coded genetic modifications in the chromosomes of live adult animals. This review covers the highlights of these advances, both theoretical and technological, along with a brief window into the promising science ahead. This article is part of the 60th Anniversary special issue.

Transcriptomics Profiling of Alzheimer's Disease Reveal Neurovascular Defects, Altered Amyloid-β Homeostasis, and Deregulated Expression of Long Noncoding RNAs

The underlying genetic variations of late-onset Alzheimer's disease (LOAD) cases remain largely unknown. A combination of genetic variations with variable penetrance and lifetime epigenetic factors may converge on transcriptomic alterations that drive LOAD pathological process. Transcriptome profiling using deep sequencing technology offers insight into common altered pathways regardless of underpinning genetic or epigenetic factors and thus represents an ideal tool to investigate molecular mechanisms related to the pathophysiology of LOAD. We performed directional RNA sequencing on high quality RNA samples extracted from hippocampi of LOAD and age-matched controls. We further validated our data using qRT-PCR on a larger set of postmortem brain tissues, confirming downregulation of the gene encoding substance P (TAC1) and upregulation of the gene encoding the plasminogen activator inhibitor-1 (SERPINE1). Pathway analysis indicates dysregulation in neural communication, cerebral vasculature, and amyloid-β clearance. Beside protein coding genes, we identified several annotated and non-annotated long noncoding RNAs that are differentially expressed in LOAD brain tissues, three of them are activity-dependent regulated and one is induced by Aβ(1-42) exposure of human neural cells. Our data provide a comprehensive list of transcriptomics alterations in LOAD hippocampi and warrant holistic approach including both coding and non-coding RNAs in functional studies aimed to understand the pathophysiology of LOAD.

The rise and fall of insulin signaling in Alzheimer's disease

The prevalence of both diabetes and Alzheimer's disease (AD) are reaching epidemic proportions worldwide. Alarmingly, diabetes is also a risk factor for Alzheimer's disease. The AD brain is characterised by the accumulation of peptides called Aβ as plaques in the neuropil and hyperphosphorylated tau protein in the form of neurofibrillary tangles within neurons. How diabetes confers risk is unknown but a simple linear relationship has been proposed whereby the hyperinsulinemia associated with type 2 diabetes leads to decreased insulin signaling in the brain, with downregulation of the PI3K/AKT signalling pathway and its inhibition of the major tau kinase, glycogen synthase kinase 3β. The earliest studies of post mortem AD brain tissue largely confirmed this cascade of events but subsequent studies have generally found either an upregulation of AKT activity, or that the relationship between insulin signaling and AD is independent of glycogen synthase kinase 3β altogether. Given the lack of success of beta-amyloid-reducing therapies in clinical trials, there is intense interest in finding alternative or adjunctive therapeutic targets for AD. Insulin signaling is a neuroprotective pathway and represents an attractive therapeutic option. However, this incredibly complex signaling pathway is not fully understood in the human brain and particularly in the context of AD. Here, we review the ups and downs of the research efforts aimed at understanding how diabetes modifies AD risk.

Genomic expression profiling and bioinformatics analysis on diabetic nephrology with ginsenoside Rg3

Diabetic nephropathy (DN), a common diabetes-related complication, is the leading cause of progressive chronic kidney disease (CKD) and end‑stage renal disease. Despite the rapid development in the treatment of DN, currently available therapies used in early DN cannot prevent progressive CKD. The exact pathogenic mechanisms and the molecular events underlying DN development remain unclear. Ginsenoside Rg3 is a herbal medicine with numerous pharmacological effects. To gain a greater understanding of the molecular mechanism and signaling pathway underlying the effect of ginsenoside Rg3 in DN therapy, an RNA sequencing approach was performed to screen differential gene expression in a rat model of DN treated with ginsenoside Rg3. A combined bioinformatics analysis was then conducted to obtain insights into the underlying molecular mechanisms of the disease development, in order to identify potential novel targets for the treatment of DN. Six Sprague‑Dawley male rats were randomly divided into 3 groups: Normal control group, DN group and ginsenoside‑Rg3 treatment group, with two rats in each group. RNA sequencing was adopted for transcriptome profiling of cells from the renal cortex of DN rat model. Differentially expressed genes were screened out. Cluster analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to analyze the differentially expressed genes. In total, 78 differentially expressed genes in the DN control group were identified when compared with the normal control group, of which 52 genes were upregulated and 26 genes were downregulated. Differential expression of 43 genes was observed in the ginsenoside‑Rg3 treatment group when compared with the DN control group, consisting of 10 upregulated genes and 33 downregulated genes. Notably, 21 that were downregulated in the DN control group compared with the control were then shown to be upregulated in the ginsenoside‑Rg3 treatment group compared with the DN control group. In addition, 7 upregulated genes in the DN control group compared with the control were then shown to be downregulated in the ginsenoside‑Rg3 treatment group compared with the DN control group. Cluster analysis based on differentially expressed genes indicated that the transcriptomes are quite different among the samples. Distinct GO terms associated with these groups of genes were shown to be enriched. KEGG pathway analysis demonstrated that differentially expressed genes were predominantly involved in the fatty acid metabolism pathway and peroxisome proliferator‑activated receptor (PPAR) signaling pathway. To the best of our knowledge, this study was the first to present whole genome expression profiling in DN with ginsenoside‑Rg3 treatment by RNA‑Seq. A set of differentially expressed genes and pathways were identified. These data provided an insight into understanding the molecular mechanisms underlying the effect of ginsenoside‑Rg3 treatment of DN.

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.

"Omics" in pharmaceutical research: overview, applications, challenges, and future perspectives

In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of "omics" technologies, including genomics, proteomics, metabolomics, transcriptomics, lipidomics, cytomics, metallomics, ionomics, interactomics, and phenomics. These "omics" are often based on global analyses of biological samples using high through-put analytical approaches and bioinformatics and may provide new insights into biological phenomena. In this paper, the development and advances in these omics made in the past decades are reviewed, especially genomics, transcriptomics, proteomics and metabolomics; the applications of omics technologies in pharmaceutical research are then summarized in the fields of drug target discovery, toxicity evaluation, personalized medicine, and traditional Chinese medicine; and finally, the limitations of omics are discussed, along with the future challenges associated with the multi-omics data processing, dynamics omics analysis, and analytical approaches, as well as amenable solutions and future prospects.

Alternative Splicing in Alzheimer's Disease

Neurodegenerative diseases have a variety of different genes contributing to their underlying pathology. Unfortunately, for many of these diseases it is not clear how changes in gene expression affect pathology. Transcriptome analysis of neurodegenerative diseases using ribonucleic acid sequencing (RNA Seq) and real time quantitative polymerase chain reaction (RT-qPCR) provides for a platform to allow investigators to determine the contribution of various genes to the disease phenotype. In Alzheimer's disease (AD) there are several candidate genes reported that may be associated with the underlying pathology and are, in addition, alternatively spliced. Thus, AD is an ideal disease to examine how alternative splicing may affect pathology. In this context, genes of particular interest to AD pathology include the amyloid precursor protein (APP), TAU, and apolipoprotein E (APOE). Here, we review the evidence of alternative splicing of these genes in normal and AD patients, and recent therapeutic approaches to control splicing.

Systematically evaluating interfaces for RNA-seq analysis from a life scientist perspective

RNA-sequencing (RNA-seq) has become an established way for measuring gene expression in model organisms and humans. While methods development for refining the corresponding data processing and analysis pipeline is ongoing, protocols for typical steps have been proposed and are widely used. Several user interfaces have been developed for making such analysis steps accessible to life scientists without extensive knowledge of command line tools. We performed a systematic search and evaluation of such interfaces to investigate to what extent these can indeed facilitate RNA-seq data analysis. We found a total of 29 open source interfaces, and six of the more widely used interfaces were evaluated in detail. Central criteria for evaluation were ease of configuration, documentation, usability, computational demand and reporting. No interface scored best in all of these criteria, indicating that the final choice will depend on the specific perspective of users and the corresponding weighting of criteria. Considerable technical hurdles had to be overcome in our evaluation. For many users, this will diminish potential benefits compared with command line tools, leaving room for future improvement of interfaces.

RNA-Seq data mining: downregulation of NeuroD6 serves as a possible biomarker for alzheimer's disease brains

Alzheimer's disease (AD) is the most common cause of dementia worldwide with no curative therapies currently available. Previously, global transcriptome analysis of AD brains by microarray failed to identify the set of consistently deregulated genes for biomarker development of AD. Therefore, the molecular pathogenesis of AD remains largely unknown. Whole RNA sequencing (RNA-Seq) is an innovative technology for the comprehensive transcriptome profiling on a genome-wide scale that overcomes several drawbacks of the microarray-based approach. To identify biomarker genes for AD, we analyzed a RNA-Seq dataset composed of the comprehensive transcriptome of autopsized AD brains derived from two independent cohorts. We identified the core set of 522 genes deregulated in AD brains shared between both, compared with normal control subjects. They included downregulation of neuronal differentiation 6 (NeuroD6), a basic helix-loop-helix (bHLH) transcription factor involved in neuronal development, differentiation, and survival in AD brains of both cohorts. We verified the results of RNA-Seq by analyzing three microarray datasets of AD brains different in brain regions, ethnicities, and microarray platforms. Thus, both RNA-Seq and microarray data analysis indicated consistent downregulation of NeuroD6 in AD brains. These results suggested that downregulation of NeuroD6 serves as a possible biomarker for AD brains.

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.

The genetics of Alzheimer's disease

Alzheimer’s disease (AD) is a complex and heterogeneous neurodegenerative disorder, classified as either early onset (under 65 years of age), or late onset (over 65 years of age). Three main genes are involved in early onset AD: amyloid precursor protein (APP), presenilin 1 (PSEN1), and presenilin 2 (PSEN2). The apolipoprotein E (APOE) E4 allele has been found to be a main risk factor for late-onset Alzheimer’s disease. Additionally, genome-wide association studies (GWASs) have identified several genes that might be potential risk factors for AD, including clusterin (CLU), complement receptor 1 (CR1), phosphatidylinositol binding clathrin assembly protein (PICALM), and sortilin-related receptor (SORL1). Recent studies have discovered additional novel genes that might be involved in late-onset AD, such as triggering receptor expressed on myeloid cells 2 (TREM2) and cluster of differentiation 33 (CD33). Identification of new AD-related genes is important for better understanding of the pathomechanisms leading to neurodegeneration. Since the differential diagnoses of neurodegenerative disorders are difficult, especially in the early stages, genetic testing is essential for diagnostic processes. Next-generation sequencing studies have been successfully used for detecting mutations, monitoring the epigenetic changes, and analyzing transcriptomes. These studies may be a promising approach toward understanding the complete genetic mechanisms of diverse genetic disorders such as AD.

Transcriptome analysis of distinct mouse strains reveals kinesin light chain-1 splicing as an amyloid-β accumulation modifier

Alzheimer's disease (AD) is characterized by the accumulation of amyloid-β (Aβ). The genes that govern this process, however, have remained elusive. To this end, we combined distinct mouse strains with transcriptomics to directly identify disease-relevant genes. We show that AD model mice (APP-Tg) with DBA/2 genetic backgrounds have significantly lower levels of Aβ accumulation compared with SJL and C57BL/6 mice. We then applied brain transcriptomics to reveal the genes in DBA/2 that suppress Aβ accumulation. To avoid detecting secondarily affected genes by Aβ, we used non-Tg mice in the absence of Aβ pathology and selected candidate genes differently expressed in DBA/2 mice. Additional transcriptome analysis of APP-Tg mice with mixed genetic backgrounds revealed kinesin light chain-1 (Klc1) as an Aβ modifier, indicating a role for intracellular trafficking in Aβ accumulation. Aβ levels correlated with the expression levels of Klc1 splice variant E and the genotype of Klc1 in these APP-Tg mice. In humans, the expression levels of KLC1 variant E in brain and lymphocyte were significantly higher in AD patients compared with unaffected individuals. Finally, functional analysis using neuroblastoma cells showed that overexpression or knockdown of KLC1 variant E increases or decreases the production of Aβ, respectively. The identification of KLC1 variant E suggests that the dysfunction of intracellular trafficking is a causative factor of Aβ pathology. This unique combination of distinct mouse strains and model mice with transcriptomics is expected to be useful for the study of genetic mechanisms of other complex diseases.

Neuropathology of alcoholism

Chronic alcohol consumption results in structural changes to the brain. In alcoholics without coexisting thiamine deficiency or liver disease this is largely restricted to a loss of white-matter volume. When it occurs, neuronal loss is limited in anatomic distribution and only detected with quantitative techniques. This relative paucity of neurodegeneration is reflected in studies of gene and protein expression in postmortem brain where findings are subtle and discordant between studies. In alcoholics with coexisting pathologies, neuronal loss is more marked and affects a wider range of anatomic regions, especially subcortical nuclei. Although this more widespread damage may reflect a more severe drinking history, there is evidence linking thiamine deficiency and the consequences of liver disease to the pathogenesis of alcohol-related brain damage. Furthermore, a range of other factors, such as cigarette smoking and mood disorders, that are common in alcoholics, have the potential to influence studies of brain pathology and should be considered in further studies of the neuropathology of alcoholism.

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.

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.

ChiTaRS: a database of human, mouse and fruit fly chimeric transcripts and RNA-sequencing data

Chimeric RNAs that comprise two or more different transcripts have been identified in many cancers and among the Expressed Sequence Tags (ESTs) isolated from different organisms; they might represent functional proteins and produce different disease phenotypes. The ChiTaRS database of Chimeric Transcripts and RNA-Sequencing data (http://chitars.bioinfo.cnio.es/) collects more than 16 000 chimeric RNAs from humans, mice and fruit flies, 233 chimeras confirmed by RNA-seq reads and ∼2000 cancer breakpoints. The database indicates the expression and tissue specificity of these chimeras, as confirmed by RNA-seq data, and it includes mass spectrometry results for some human entries at their junctions. Moreover, the database has advanced features to analyze junction consistency and to rank chimeras based on the evidence of repeated junction sites. Finally, ‘Junction Search’ screens through the RNA-seq reads found at the chimeras’ junction sites to identify putative junctions in novel sequences entered by users. Thus, ChiTaRS is an extensive catalog of human, mouse and fruit fly chimeras that will extend our understanding of the evolution of chimeric transcripts in eukaryotes and can be advantageous in the analysis of human cancer breakpoints.

Non-coding RNA and pseudogenes in neurodegenerative diseases: "The (un)Usual Suspects"

Neurodegenerative disorders and cancer are severe diseases threatening human health. The glaring differences between neurons and cancer cells mask the processes involved in their pathogenesis. Defects in cell cycle, DNA repair, and cell differentiation can determine unlimited proliferation in cancer, or conversely, compromise neuronal plasticity, leading to cell death and neurodegeneration. Alteration in regulatory networks affecting gene expression contribute to human diseases onset, including neurodegenerative disorders, and deregulation of non-coding RNAs – particularly microRNAs (miRNAs) – is supposed to have a significant impact. Recently, competitive endogenous RNAs (ceRNAs) – acting as sponges – have been identified in cancer, indicating a new and intricate regulatory network. Given that neurodegenerative disorders and cancer share altered genes and pathways, and considering the emerging role of miRNAs in neurogenesis, we hypothesize ceRNAs may be implicated in neurodegenerative diseases. Here we propose, and computationally predict, such regulatory mechanism may be shared between the diseases. It is predictable that similar regulation occurs in other complex diseases, and further investigation is needed.

The bench scientist's guide to statistical analysis of RNA-Seq data

BACKGROUND

RNA sequencing (RNA-Seq) is emerging as a highly accurate method to quantify transcript abundance. However, analyses of the large data sets obtained by sequencing the entire transcriptome of organisms have generally been performed by bioinformatics specialists. Here we provide a step-by-step guide and outline a strategy using currently available statistical tools that results in a conservative list of differentially expressed genes. We also discuss potential sources of error in RNA-Seq analysis that could alter interpretation of global changes in gene expression.

FINDINGS

When comparing statistical tools, the negative binomial distribution-based methods, edgeR and DESeq, respectively identified 11,995 and 11,317 differentially expressed genes from an RNA-seq dataset generated from soybean leaf tissue grown in elevated O3. However, the number of genes in common between these two methods was only 10,535, resulting in 2,242 genes determined to be differentially expressed by only one method. Upon analysis of the non-significant genes, several limitations of these analytic tools were revealed, including evidence for overly stringent parameters for determining statistical significance of differentially expressed genes as well as increased type II error for high abundance transcripts.

CONCLUSIONS

Because of the high variability between methods for determining differential expression of RNA-Seq data, we suggest using several bioinformatics tools, as outlined here, to ensure that a conservative list of differentially expressed genes is obtained. We also conclude that despite these analytical limitations, RNA-Seq provides highly accurate transcript abundance quantification that is comparable to qRT-PCR.

Gene expression profiling in human neurodegenerative disease

Transcriptome study in neurodegenerative disease has advanced considerably in the past 5 years. Increasing scientific rigour and improved analytical tools have led to more-reproducible data. Many transcriptome analysis platforms assay the expression of the entire genome, enabling a complete biological context to be captured. Gene expression profiling (GEP) is, therefore, uniquely placed to discover pathways of disease pathogenesis, potential therapeutic targets, and biomarkers. This Review summarizes microarray human GEP studies in the common neurodegenerative diseases amyotrophic lateral sclerosis (ALS), Parkinson disease (PD) and Alzheimer disease (AD). Several interesting reports have compared pathological gene expression in different patient groups, disease stages and anatomical areas. In all three diseases, GEP has revealed dysregulation of genes related to neuroinflammation. In ALS and PD, gene expression related to RNA splicing and protein turnover is disrupted, and several studies in ALS support involvement of the cytoskeleton. GEP studies have implicated the ubiquitin-proteasome system in PD pathogenesis, and have provided evidence of mitochondrial dysfunction in PD and AD. Lastly, in AD, a possible role for dysregulation of intracellular signalling pathways, including calcium signalling, has been highlighted. This Review also provides a discussion of methodological considerations in microarray sample preparation and data analysis.

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.

Gene expression profiling and therapeutic interventions in neurodegenerative diseases: a comprehensive study on potentiality and limits

INTRODUCTION

Neurodegenerative diseases are incurable debilitating disorders of the nervous system that affect approximately 30 million people worldwide. Despite profuse efforts attempting to define the molecular mechanisms underlying neurodegeneration, many aspects of these pathologies remain elusive. The novelty of their mechanisms represents a challenge to biology, to their related biomarkers identification and drug discovery. Because of their multifactorial aspects and complexity, gene expression analysis platforms have been extensively used to investigate altered pathways during degeneration and to identify potential biomarkers and drug targets.

AREAS COVERED

This work offers an overview of the gene expression profiling studies carried out on Alzheimer's disease, Huntington's disease, Parkinson's disease and prion disease specimens. Therapeutic approaches are also discussed.

EXPERT OPINION

Although many therapeutic approaches have been tested, some of them acting on several altered cellular pathways, no effective cures for these neurodegenerative diseases have been identified. Microarray technology must be associated with functional proteomics and physiology in an effort to identify specific and selective biomarkers and druggable targets, thus allowing the successful discovery of disease-modifying therapeutic treatments.

R-SAP: a multi-threading computational pipeline for the characterization of high-throughput RNA-sequencing data

The rapid expansion in the quantity and quality of RNA-Seq data requires the development of sophisticated high-performance bioinformatics tools capable of rapidly transforming this data into meaningful information that is easily interpretable by biologists. Currently available analysis tools are often not easily installed by the general biologist and most of them lack inherent parallel processing capabilities widely recognized as an essential feature of next-generation bioinformatics tools. We present here a user-friendly and fully automated RNA-Seq analysis pipeline (R-SAP) with built-in multi-threading capability to analyze and quantitate high-throughput RNA-Seq datasets. R-SAP follows a hierarchical decision making procedure to accurately characterize various classes of transcripts and achieves a near linear decrease in data processing time as a result of increased multi-threading. In addition, RNA expression level estimates obtained using R-SAP display high concordance with levels measured by microarrays.

Single-cell and regional gene expression analysis in Alzheimer's disease

The clinical manifestations of Alzheimer's disease (AD) are secondary to the substantial loss of cortical neurons. To be effective, neuroprotective strategies will need to target the primary pathogenic mechanisms of AD prior to cell loss. The differences between neurons are largely determined by their specific repertoire of mRNAs. Thus, transcriptomic analyses that do not assume a priori etiological hypotheses are potentially powerful tools that can be used to understand the pathogenesis of complex diseases, including AD. The human brain comprises thousands of different cell types of both neuronal and non-neuronal origins. Information about individual cell-type-specific gene expression patterns will allow for a better understanding of the mechanisms that govern the progression of AD, which may lead to new therapeutic targets for prevention and treatment of the disease. This review provides an overview of the current technologies in use and the developments for single-cell extraction and transcriptome analysis. Recent transcriptome profiling studies on individual AD-afflicted brain cells are also discussed.

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.

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.