Huntington's disease biomarker progression profile identified by transcriptome sequencing in peripheral blood

Association between sex and Huntington's disease: an updated review on symptomatology and prognosis of neurodegenerative disorders

Huntington's disease is a rare autosomal dominant disorder presenting with chorea, rigidity, hypo-/akinesia, cognitive decline, and psychiatric disturbances. Numerous risk factors have been defined in the onset of this disease. However, the number of CAG repeats in the genes are the most crucial factor rendering patients susceptible to the disease. Studies have shown significant differences in onset and disease presentation among the sexes, which prompts analysis of the impact of different sexes on disease etiology and progression. This article therefore discusses the evidence-based role of sex in aspects of symptomatology, pathogenesis, biomarkers, progression, and prognosis of Huntington's disease, with a secondary review of sex-linked differences in Alzheimer's and Parkinson's disease.

Palmitoylation of CYSTM (CYSPD) proteins in yeast

A superfamily of proteins called cysteine transmembrane is widely distributed across eukaryotes. These small proteins are characterized by the presence of a conserved motif at the C-terminal region, rich in cysteines, that has been annotated as a transmembrane domain. Orthologs of these proteins have been involved in resistance to pathogens and metal detoxification. The yeast members of the family are YBR016W, YDL012C, YDR034W-B, and YDR210W. Here, we begin the characterization of these proteins at the molecular level and show that Ybr016w, Ydr034w-b, and Ydr210w are palmitoylated proteins. Protein S-acylation or palmitoylation, is a posttranslational modification that consists of the addition of long-chain fatty acids to cysteine residues. We provide evidence that Ybr016w, Ydr210w, and Ydr034w-b are localized to the plasma membrane and exhibit varying degrees of polarity toward the daughter cell, which is dependent on endocytosis and recycling. We suggest the names CPP1, CPP2, and CPP3 (C terminally palmitoylated protein) for YBR016W, YDR210W, and YDR034W-B, respectively. We show that palmitoylation is responsible for the binding of these proteins to the membrane indicating that the cysteine transmembrane on these proteins is not a transmembrane domain. We propose renaming the C-terminal cysteine-rich domain as cysteine-rich palmitoylated domain. Loss of the palmitoyltransferase Erf2 leads to partial degradation of Ybr016w (Cpp1), whereas in the absence of the palmitoyltransferase Akr1, members of this family are completely degraded. For Cpp1, we show that this degradation occurs via the proteasome in an Rsp5-dependent manner, but is not exclusively due to a lack of Cpp1 palmitoylation.

Advances in microfluidic chips targeting toxic aggregation proteins for neurodegenerative diseases

Neurodegenerative diseases (NDs) are characterized by nervous system damage, often influenced by genetic and aging factors. Pathological analysis frequently reveals the presence of aggregated toxic proteins. The intricate and poorly understood origins of these diseases have hindered progress in early diagnosis and drug development. The development of novel in-vitro and in-vivo models could enhance our comprehension of ND mechanisms and facilitate clinical treatment advancements. Microfluidic chips are employed to establish three-dimensional culture conditions, replicating the human ecological niche and creating a microenvironment conducive to neuronal cell survival. The incorporation of mechatronic controls unifies the chip, cells, and culture medium optimizing living conditions for the cells. This study provides a comprehensive overview of microfluidic chip applications in drug and biomarker screening for neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, Huntington's disease, multiple sclerosis, and amyotrophic lateral sclerosis. Our Lab-on-a-Chip system releases toxic proteins to simulate the pathological characteristics of neurodegenerative diseases, encompassing β-amyloid, α-synuclein, huntingtin, TAR DNA-binding protein 43, and Myelin Basic Protein. Investigating molecular and cellular interactions in vitro can enhance our understanding of disease mechanisms while minimizing harmful protein levels and can aid in screening potential therapeutic agents. We anticipate that our research will promote the utilization of microfluidic chips in both fundamental research and clinical applications for neurodegenerative diseases.

A Comprehensive Bioinformatics Approach to Identify Molecular Signatures and Key Pathways for the Huntington Disease

Huntington disease (HD) is a degenerative brain disease caused by the expansion of CAG (cytosine-adenine-guanine) repeats, which is inherited as a dominant trait and progressively worsens over time possessing threat. Although HD is monogenetic, the specific pathophysiology and biomarkers are yet unknown specifically, also, complex to diagnose at an early stage, and identification is restricted in accuracy and precision. This study combined bioinformatics analysis and network-based system biology approaches to discover the biomarker, pathways, and drug targets related to molecular mechanism of HD etiology. The gene expression profile data sets GSE64810 and GSE95343 were analyzed to predict the molecular markers in HD where 162 mutual differentially expressed genes (DEGs) were detected. Ten hub genes among them (DUSP1, NKX2-5, GLI1, KLF4, SCNN1B, NPHS1, SGK2, PITX2, S100A4, and MSX1) were identified from protein-protein interaction (PPI) network which were mostly expressed as down-regulated. Following that, transcription factors (TFs)-DEGs interactions (FOXC1, GATA2, etc), TF-microRNA (miRNA) interactions (hsa-miR-340, hsa-miR-34a, etc), protein-drug interactions, and disorders associated with DEGs were predicted. Furthermore, we used gene set enrichment analysis (GSEA) to emphasize relevant gene ontology terms (eg, TF activity, sequence-specific DNA binding) linked to DEGs in HD. Disease interactions revealed the diseases that are linked to HD, and the prospective small drug molecules like cytarabine and arsenite was predicted against HD. This study reveals molecular biomarkers at the RNA and protein levels that may be beneficial to improve the understanding of molecular mechanisms, early diagnosis, as well as prospective pharmacologic targets for designing beneficial HD treatment.

Screening of potential biomarkers of system lupus erythematosus based on WGCNA and machine learning algorithms

Systemic lupus erythematosus (SLE) is an autoimmune disease involving multiple systems. Its recurrent episodes and fluctuating disease courses have a severe impact on patients. Biomarkers to predict disease prognosis and remission are still lacking in SLE. We downloaded the GSE50772 dataset from the Gene Expression Omnibus database and identified differentially expressed genes (DEGs) between SLE and healthy controls. Weighted gene co-expression network analysis was used to identify key gene modules and corresponding genes in SLE. The overlapped genes in DEGs and key modules are used as key genes for subsequent analysis. These key genes were analyzed using 3 machine learning algorithms, including the least absolute shrinkage and selection operator, support vector machine recursive elimination, and random forest algorithms. The overlapped genes were obtained as potential biomarkers for further analysis, investigating and validating the potential biomarkers' possible functions, regulatory mechanisms, diagnostic value, and expression levels. And finally studied the differences between groups in level of immune cell infiltration and explored the relationship between potential biomarkers and immunity. A total of 234 overlapped genes in DEGs and key modules are used as key genes for subsequent analysis. After taking the intersection of the key genes obtained by 3 algorithms, we got 4 potential biomarkers (ARID2, CYSTM1, DDIT3, and RNASE1) with high diagnostic values. Finally, further immune infiltration analysis showed differences in various immune cells in the SLE and healthy control samples. ARID2, CYSTM1, DDIT3, and RNASE1 can affect the immune function of SLE patients. ARID2, CYSTM1, DDIT3, and RNASE1 could be used as immune-related potential biomarkers and therapeutic or diagnostic targets for further research.

Therapeutic Potential of Targeting Prokineticin Receptors in Diseases

The prokineticins (PKs) were discovered approximately 20 years ago as small peptides inducing gut contractility. Today, they are established as angiogenic, anorectic, and proinflammatory cytokines, chemokines, hormones, and neuropeptides involved in variety of physiologic and pathophysiological pathways. Their altered expression or mutations implicated in several diseases make them a potential biomarker. Their G-protein coupled receptors, PKR1 and PKR2, have divergent roles that can be therapeutic target for treatment of cardiovascular, metabolic, and neural diseases as well as pain and cancer. This article reviews and summarizes our current knowledge of PK family functions from development of heart and brain to regulation of homeostasis in health and diseases. Finally, the review summarizes the established roles of the endogenous peptides, synthetic peptides and the selective ligands of PKR1 and PKR2, and nonpeptide orthostatic and allosteric modulator of the receptors in preclinical disease models. The present review emphasizes the ambiguous aspects and gaps in our knowledge of functions of PKR ligands and elucidates future perspectives for PK research. SIGNIFICANCE STATEMENT: This review provides an in-depth view of the prokineticin family and PK receptors that can be active without their endogenous ligand and exhibits "constitutive" activity in diseases. Their non- peptide ligands display promising effects in several preclinical disease models. PKs can be the diagnostic biomarker of several diseases. A thorough understanding of the role of prokineticin family and their receptor types in health and diseases is critical to develop novel therapeutic strategies with safety concerns.

Blood transcriptome sequencing identifies biomarkers able to track disease stages in spinocerebellar ataxia type 3

Transcriptional dysregulation has been described in spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD), an autosomal dominant ataxia caused by a polyglutamine expansion in the ataxin-3 protein. As ataxin-3 is ubiquitously expressed, transcriptional alterations in blood may reflect early changes that start before clinical onset and might serve as peripheral biomarkers in clinical and research settings. Our goal was to describe enriched pathways and report dysregulated genes, which can track disease onset, severity or progression in carriers of the ATXN3 mutation (pre-ataxic subjects and patients). Global dysregulation patterns were identified by RNA sequencing of blood samples from 40 carriers of ATXN3 mutation and 20 controls and further compared with transcriptomic data from post-mortem cerebellum samples of MJD patients and controls. Ten genes-ABCA1, CEP72, PTGDS, SAFB2, SFSWAP, CCDC88C, SH2B1, LTBP4, MEG3 and TSPOAP1-whose expression in blood was altered in the pre-ataxic stage and simultaneously, correlated with ataxia severity in the overt disease stage, were analysed by quantitative real-time PCR in blood samples from an independent set of 170 SCA3/MJD subjects and 57 controls. Pathway enrichment analysis indicated the Gαi signalling and the oestrogen receptor signalling to be similarly affected in blood and cerebellum. SAFB2, SFSWAP and LTBP4 were consistently dysregulated in pre-ataxic subjects compared to controls, displaying a combined discriminatory ability of 79%. In patients, ataxia severity was associated with higher levels of MEG3 and TSPOAP1. We propose expression levels of SAFB2, SFSWAP and LTBP4 as well as MEG3 and TSPOAP1 as stratification markers of SCA3/MJD progression, deserving further validation in longitudinal studies and in independent cohorts.

Cerebrospinal Fluid Protein Biomarker Discovery in CLN3

Syndromic CLN3-Batten is a fatal, pediatric, neurodegenerative disease caused by variants in CLN3, which encodes the endolysosomal transmembrane CLN3 protein. No approved treatment for CLN3 is currently available. The protracted and asynchronous disease presentation complicates the evaluation of potential therapies using clinical disease progression parameters. Biomarkers as surrogates to measure the progression and effect of potential therapeutics are needed. We performed proteomic discovery studies using cerebrospinal fluid (CSF) samples from 28 CLN3-affected and 32 age-similar non-CLN3 individuals. Proximal extension assay (PEA) of 1467 proteins and untargeted data-dependent mass spectrometry [MS; MassIVE FTP server (ftp://MSV000090147@massive.ucsd.edu)] were used to generate orthogonal lists of protein marker candidates. At an adjusted p-value of <0.1 and threshold CLN3/non-CLN3 fold-change ratio of 1.5, PEA identified 54 and MS identified 233 candidate biomarkers. Some of these (NEFL, CHIT1) have been previously linked with other neurologic conditions. Others (CLPS, FAM217B, QRICH2, KRT16, ZNF333) appear to be novel. Both methods identified 25 candidate biomarkers, including CHIT1, NELL1, and ISLR2 which had absolute fold-change ratios >2. NELL1 and ISLR2 regulate axonal development in neurons and are intriguing new candidates for further investigation in CLN3. In addition to identifying candidate proteins for CLN3 research, this study provides a comparison of two large-scale proteomic discovery methods in CSF.

Genome-wide functional characterization of Canavalia rosea cysteine-rich trans-membrane module (CrCYSTM) genes to reveal their potential protective roles under extreme abiotic stress

Cysteine-rich transmembrane module (CYSTM) proteins constitute small molecular protein families and have been identified across eukaryotes, including yeast, humans, and several plant species. Plant CYSTMs play vital roles in growth regulation, development, phytohormone signal transduction, pathogen defense, environmental stress response, and even heavy metal binding and detoxification. Canavalia rosea (Sw.) DC is a perennial halophyte with great semi-arid and saline-alkali tolerance. In this study, the CrCYSTM family including 10 members were identified in the C. rosea genome, with the purpose of clarifying the possible roles of CrCYSTMs in C. rosea plants development and stress resistance. The phylogenetic relationships, exon-intron structure, domain structure, chromosomal localization, and putative cis-acting elements in promoter regions were predicted and analyzed. Transcriptome analysis combined with quantitative reverse transcription PCR showed that different CrCYSTM members exhibited varied expression patterns in different tissues and under different abiotic stress challenges. In addition, several CrCYSTMs were cloned and functionally characterized for their roles in abiotic stress tolerance with yeast expression system. Overall, these findings provide a foundation for functionally characterizing plant CYSTMs to unravel their possible roles in the adaptation of C. rosea to tropical coral reefs. Our results also lay the foundation for further research on the roles of plant CYSTM genes in abiotic stress signaling, especially for heavy metal detoxification.

The YBR056W-A and Its Ortholog YDR034W-B of S. cerevisiae Belonging to CYSTM Family Participate in Manganese Stress Overcoming

The CYSTM (cysteine-rich transmembrane module) protein family comprises small molecular cysteine-rich tail-anchored membrane proteins found in many eukaryotes. The Saccharomyces cerevisiae strains carrying the CYSTM genes YDRO34W-B and YBR056W-A (MNC1) fused with GFP were used to test the expression of these genes under different stresses. The YBR056W-A (MNC1) and YDR034W-B genes are expressed under stress conditions caused by the toxic concentrations of heavy metal ions, such as manganese, cobalt, nickel, zinc, cuprum, and 2.4-dinitrophenol uncoupler. The expression level of YDR034W-B was higher than that of YBR056W-A under alkali and cadmium stresses. The Ydr034w-b-GFP and Ybr056w-a-GFP proteins differ in the cellular localization: Ydr034w-b-GFP was mainly observed in the plasma membrane and vacuolar membrane, while Ybr056w-a-GFP was observed in the cytoplasm, probably in intracellular membranes. The null-mutants in both genes demonstrated decreased cell concentration and lytic phenotype when cultivated in the presence of excess manganese. This allows for speculations about the involvement of Mnc1 and Ydr034w-b proteins in manganese stress overcoming.

A standardised protocol for blood and cerebrospinal fluid collection and processing for biomarker research in ataxia

The European Spinocerebellar Ataxia Type 3/Machado-Joseph Disease Initiative (ESMI) is a consortium established with the ambition to set up the largest European longitudinal trial-ready cohort of Spinocerebellar Ataxia Type 3/Machado-Joseph Disease (SCA3/MJD), the most common autosomal dominantly inherited ataxia worldwide. A major focus of ESMI has been the identification of SCA3/MJD biomarkers to enable future interventional studies. As biosample collection and processing variables significantly impact the outcomes of biomarkers studies, biosampling procedures standardisation was done previously to study visit initiation. Here, we describe the ESMI consensus biosampling protocol, developed within the scope of ESMI, that ultimately might be translated to other neurodegenerative disorders, particularly ataxias, being the first step to protocol harmonisation in the field.

An in silico study to find potential effective circRNAs in the progression of Huntington's disease

Objectives

Huntington's disease (HD) is identified as a progressive genetic disorder caused by a mutation in the Huntington gene. Although the pathogenesis of this disease has not been fully understood, investigations have demonstrated the role of various genes and non-coding RNAs in the disease progression. In this study, we aimed to discover the potential promising circRNAs which can bind to miRNAs of HD.

Materials and Methods

We used several bioinformatics tools such as ENCORI, Cytoscape, circBase, Knime, and Enrichr to collect possible circRNAs and then evaluate their connections with target miRNAs to reach this goal. We also found the probable relationship between parental genes of these circRNAs and the disease progress.

Results

According to the data collected, more than 370 thousand circRNA-miRNA interactions were found for 57 target miRNAs. Several of circRNAs were spliced out of parental genes involved in the etiology of HD. Some of them need to be further investigated to elucidate their role in this neurodegenerative disease.

Conclusion

This in silico investigation highlights the potential role of circRNAs in the progression of HD and opens up new horizons for drug discovery as well as diagnostic approaches for the disease.

Current Diagnostic Methods and Non-Coding RNAs as Possible Biomarkers in Huntington’s Disease

Whether as a cause or a symptom, RNA transcription is recurrently altered in pathologic conditions. This is also true for non-coding RNAs, with regulatory functions in a variety of processes such as differentiation, cell identity and metabolism. In line with their increasingly recognized roles in cellular pathways, RNAs are also currently evaluated as possible disease biomarkers. They could be informative not only to follow disease progression and assess treatment efficacy in clinics, but also to aid in the development of new therapeutic approaches. This is especially important for neurological and genetic disorders, where the administration of appropriate treatment during the disease prodromal stage could significantly delay, if not halt, disease progression. In this review we focus on the current status of biomarkers in Huntington’s Disease (HD), a fatal hereditary and degenerative disease condition. First, we revise the sources and type of wet biomarkers currently in use. Then, we explore the feasibility of different RNA types (miRNA, ncRNA, circRNA) as possible biomarker candidates, discussing potential advantages, disadvantages, sources of origin and the ongoing investigations on this topic.

Circulating U13 Small Nucleolar RNA as a Potential Biomarker in Huntington's Disease: A Pilot Study

Plasma small RNAs have been recently explored as biomarkers in Huntington’s disease (HD). We performed an exploratory study on nine HD patients, eight healthy subjects (HS), and five psychiatric patients (PP; to control for iatrogenic confounder effects) through an Affymetrix-Gene-Chip-miRNA-Array. We validated the results in an independent population of 23 HD, 15 pre-HD, 24 PP, 28 Alzheimer’s disease (AD) patients (to control the disease-specificity) and 22 HS through real-time PCR. The microarray results showed higher levels of U13 small nucleolar RNA (SNORD13) in HD patients than controls (fold change 1.54, p = 0.003 HD vs. HS, and 1.44, p = 0.0026 HD vs. PP). In the validation population, a significant increase emerged with respect to both pre-HD and the control groups (p < 0.0001). SNORD13 correlated with the status of the mutant huntingtin carrier (r = 0.73; p < 0.001) and the disease duration (r = 0.59; p = 0.003). The receiver operating characteristic (ROC) curve analysis showed the high accuracy of SNORD13 in discriminating HD patients from other groups (AUC = 0.963). An interactome and pathway analysis on SNORD13 revealed enrichments for factors relevant to HD pathogenesis. We report the unprecedented finding of a potential disease-specific role of SNORD13 in HD. It seems to peripherally report a ‘tipping point’ in the pathogenic cascade at the neuronal level.

A Glimpse of Molecular Biomarkers in Huntington's Disease

Huntington's disease (HD) is a devastating neurodegenerative disorder that is caused by an abnormal expansion of CAG repeats in the Huntingtin (HTT) gene. Although the main symptomatology is explained by alterations at the level of the central nervous system, predominantly affecting the basal ganglia, a peripheral component of the disease is being increasingly acknowledged. Therefore, the manifestation of the disease is complex and variable among CAG expansion carriers, introducing uncertainty in the appearance of specific signs, age of onset and severity of disease. The monogenic nature of the disorder allows a precise diagnosis, but the use of biomarkers with prognostic value is still needed to achieve clinical management of the patients in an individual manner. In addition, we need tools to evaluate the patient's response to potential therapeutic approaches. In this review, we provide a succinct summary of the most interesting molecular biomarkers that have been assessed in patients, mostly obtained from body fluids such as cerebrospinal fluid, peripheral blood and saliva.

Multiple Criteria Optimization (MCO): A gene selection deterministic tool in RStudio

Identifying genes with the largest expression changes (gene selection) to characterize a given condition is a popular first step to drive exploration into molecular mechanisms and is, therefore, paramount for therapeutic development. Reproducibility in the sciences makes it necessary to emphasize objectivity and systematic repeatability in biological and informatics analyses, including gene selection. With these two characteristics in mind, in previous works our research team has proposed using multiple criteria optimization (MCO) in gene selection to analyze microarray datasets. The result of this effort is the MCO algorithm, which selects genes with the largest expression changes without user manipulation of neither informatics nor statistical parameters. Furthermore, the user is not required to choose either a preference structure among multiple measures or a predetermined quantity of genes to be deemed significant a priori. This implies that using the same datasets and performance measures (PMs), the method will converge to the same set of selected differentially expressed genes (repeatability) despite who carries out the analysis (objectivity). The present work describes the development of an open-source tool in RStudio to enable both: (1) individual analysis of single datasets with two or three PMs and (2) meta-analysis with up to five microarray datasets, using one PM from each dataset. The capabilities afforded by the code include license-free portability and the possibility to carry out analyses via modest computer hardware, such as personal laptops. The code provides affordable, repeatable, and objective detection of differentially expressed genes from microarrays. It can be used to analyze other experiments with similar experimental comparative layouts, such as microRNA arrays and protein arrays, among others. As a demonstration of the capabilities of the code, the analysis of four publicly-available microarray datasets related to Parkinson´s Disease (PD) is presented here, treating each dataset individually or as a four-way meta-analysis. These MCO-supported analyses made it possible to identify MMP9 and TUBB2A as potential PD genetic biomarkers based on their persistent appearance across each of the case studies. A literature search confirmed the importance of these genes in PD and indeed as PD biomarkers, which evidences the code´s potential.

Antimicrobial peptide gene expression in Atlantic salmon (Salmo salar) seven days post-challenge with Neoparamoeba perurans

Amoebic gill disease in teleost fish is caused by the marine parasite Neoparamoeba perurans. To date, the role of antimicrobial peptides β-defensins and cathelicidins in this infection have not been explored. Using a high-throughput microfluidics quantitative polymerase chain reaction system (Biomark HD™ by Fluidigm), this study aimed to: firstly, to investigate organ-specific expression of antimicrobial peptide genes β-defensin-1, -3 and -4 and cathelicidin 2 in healthy Atlantic salmon; secondly, to compare the expression of these antimicrobial peptide genes in healthy versus asymptomatic Atlantic salmon seven days post-challenge with Neoparamoeba perurans. Results from this study indicate expression of the β-defensin and cathelicidin genes in the selected organs from healthy Atlantic salmon. Furthermore, a statistically significant upregulation of β-defensins -3 and -4 and cathelicidin 2 was detected in gill of parasite-challenged salmon. The upregulated cathelicidin and β-defensin genes in gill could indicate novel potential roles in innate immune responses to Neoparamoeba perurans.

Huntington Disease Gene Expression Signatures in Blood Compared to Brain of YAC128 Mice as Candidates for Monitoring of Pathology

While the genetic cause of Huntington disease (HD) is known since 1993, still no cure exists. Therapeutic development would benefit from a method to monitor disease progression and treatment efficacy, ideally using blood biomarkers. Previously, HD-specific signatures were identified in human blood representing signatures in human brain, showing biomarker potential. Since drug candidates are generally first screened in rodent models, we aimed to identify HD signatures in blood and brain of YAC128 HD mice and compare these with previously identified human signatures. RNA sequencing was performed on blood withdrawn at two time points and four brain regions from YAC128 and control mice. Weighted gene co-expression network analysis was used to identify clusters of co-expressed genes (modules) associated with the HD genotype. These HD-associated modules were annotated via text-mining to determine the biological processes they represented. Subsequently, the processes from mouse blood were compared with mouse brain, showing substantial overlap, including protein modification, cell cycle, RNA splicing, nuclear transport, and vesicle-mediated transport. Moreover, the disease-associated processes shared between mouse blood and brain were highly comparable to those previously identified in human blood and brain. In addition, we identified HD blood-specific pathology, confirming previous findings for peripheral pathology in blood. Finally, we identified hub genes for HD-associated blood modules and proposed a strategy for gene selection for development of a disease progression monitoring panel.

Nuclear and cytoplasmic huntingtin inclusions exhibit distinct biochemical composition, interactome and ultrastructural properties

Despite the strong evidence linking the aggregation of the Huntingtin protein (Htt) to the pathogenesis of Huntington's disease (HD), the mechanisms underlying Htt aggregation and neurodegeneration remain poorly understood. Herein, we investigated the ultrastructural properties and protein composition of Htt cytoplasmic and nuclear inclusions in mammalian cells and primary neurons overexpressing mutant exon1 of the Htt protein. Our findings provide unique insight into the ultrastructural properties of cytoplasmic and nuclear Htt inclusions and their mechanisms of formation. We show that Htt inclusion formation and maturation are complex processes that, although initially driven by polyQ-dependent Htt aggregation, also involve the polyQ and PRD domain-dependent sequestration of lipids and cytoplasmic and cytoskeletal proteins related to HD dysregulated pathways; the recruitment and accumulation of remodeled or dysfunctional membranous organelles, and the impairment of the protein quality control and degradation machinery. We also show that nuclear and cytoplasmic Htt inclusions exhibit distinct biochemical compositions and ultrastructural properties, suggesting different mechanisms of aggregation and toxicity.

Single-cell Transcriptional Changes in Neurodegenerative Diseases

In recent decades, our understanding of the molecular changes involved in neurodegenerative diseases has been transformed. Single-cell RNA sequencing and single-nucleus RNA sequencing technologies have been applied to provide cellular and molecular details of the brain at the single-cell level. This has expanded our knowledge of the central nervous system and provided insights into the molecular vulnerability of brain cell types and underlying mechanisms in neurodegenerative diseases. In this review, we highlight the recent advances and findings related to neurodegenerative diseases using these cutting-edge technologies.

Circulating hsa-miR-323b-3p in Huntington's Disease: A Pilot Study

The momentum of gene therapy in Huntington's disease (HD) deserves biomarkers from easily accessible fluid. We planned a study to verify whether plasma miRNome may provide useful peripheral “reporter(s)” for the management of HD patients. We performed an exploratory microarray study of whole non-coding RNA profiles in plasma from nine patients with HD and 13 matched controls [eight healthy subjects (HS) and five psychiatric patients (PP) to minimize possible iatrogenic impact on the profile of non-coding RNAs]. We found an HD-specific signature: downregulation of hsa-miR-98 (fold change, −1.5, p = 0.0338 HD vs. HS, and fold change, 1.5, p = 0.0045 HD vs. PP) and upregulation of hsa-miR-323b-3p (fold change, 1.5, p = 0.0007 HD vs. HS, and fold change, 1.5, p = 0.0111 HD vs. PP). To validate this result in an independent cohort, we quantify by digital droplet PCR (ddPCR) the presence of the two microRNA in the plasma of 33 HD patients and 49 matched controls (25 HS and 24 PP patients). We were able to confirm that hsa-miR-323b-3p was upregulated in HD and premanifest HD vs. HS and PP: the median values (first–third quartile) were 4.1 (0.9–10.53) and 5.8 (1.9–10.70) vs. 0.69 (0.3–2.75) and 1.4 (0.78–2.70), respectively, p < 0.05. No significant difference was found for hsa-miR-98. To evaluate the biological plausibility of the hsa-miR-323b-3p as a component of the disease pathophysiology, we performed a bioinformatic analysis based on its targetome and the huntingtin (HTT) interactome. We found a statistically significant overconnectivity between the targetome of hsa-miR-323b-3p and the HTT interactome (p = 1.48e−08). Furthermore, there was a significant transcription regulation of the HTT interactome by the miR-323b-3p targetome (p = 0.02). The availability of handy, reproducible, and minimally invasive biomarkers coming from peripheral miRNome may be valuable to characterize the illness progression, to indicate new therapeutic targets, and to monitor the effect of disease-modifying treatments. Our data deserve further studies with larger sample size and longitudinal design.

Statistical method for modeling sequencing data from different technologies in longitudinal studies with application to Huntington disease

Advancement of gene expression measurements in longitudinal studies enables the identification of genes associated with disease severity over time. However, problems arise when the technology used to measure gene expression differs between time points. Observed differences between the results obtained at different time points can be caused by technical differences. Modeling the two measurements jointly over time might provide insight into the causes of these different results. Our work is motivated by a study of gene expression data of blood samples from Huntington disease patients, which were obtained using two different sequencing technologies. At time point 1, DeepSAGE technology was used to measure the gene expression, with a subsample also measured using RNA‐Seq technology. At time point 2, all samples were measured using RNA‐Seq technology. Significant associations between gene expression measured by DeepSAGE and disease severity using data from the first time point could not be replicated by the RNA‐Seq data from the second time point. We modeled the relationship between the two sequencing technologies using the data from the overlapping samples. We used linear mixed models with either DeepSAGE or RNA‐Seq measurements as the dependent variable and disease severity as the independent variable. In conclusion, (1) for one out of 14 genes, the initial significant result could be replicated with both technologies using data from both time points; (2) statistical efficiency is lost due to disagreement between the two technologies, measurement error when predicting gene expressions, and the need to include additional parameters to account for possible differences.

Nervous system regulated by POZ domain Krüppel-like zinc finger (POK) family transcription repressor RP58

The POZ domain Krüppel-like zinc finger transcription repressor (POK family) contains many important molecules, including RP58, Bcl6 and PLZF. They function as transcription repressors via chromatin remodelling and histone deacetylation and are known to be involved in the development and tumourigenesis of various organs. Furthermore, they are important in the formation and function of the nervous system. This review summarizes the role of the POK family transcription repressors in the nervous system. We particularly targeted Rp58 (also known as Znf238, Znp238 and Zbtb18), a sequence-specific transcriptional repressor that is strongly expressed in developing glutamatergic projection neurons in the cerebral cortex. It regulates various physiological processes, including neuronal production, neuronal migration and neuronal maturation. Human studies suggest that reduced RP58 levels are involved in cognitive function impairment and brain tumour formation. This review particularly focuses on the mechanisms underlying RP58-mediated neuronal development and function. LINKED ARTICLES: This article is part of a themed issue on Neurochemistry in Japan. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v178.4/issuetoc.

RNA Sequencing of Human Peripheral Blood Cells Indicates Upregulation of Immune-Related Genes in Huntington's Disease

Huntington's disease (HD) is an autosomal dominantly inherited neurodegenerative disorder caused by a trinucleotide repeat expansion in the Huntingtin gene. As disease-modifying therapies for HD are being developed, peripheral blood cells may be used to indicate disease progression and to monitor treatment response. In order to investigate whether gene expression changes can be found in the blood of individuals with HD that distinguish them from healthy controls, we performed transcriptome analysis by next-generation sequencing (RNA-seq). We detected a gene expression signature consistent with dysregulation of immune-related functions and inflammatory response in peripheral blood from HD cases vs. controls, including induction of the interferon response genes, IFITM3, IFI6 and IRF7. Our results suggest that it is possible to detect gene expression changes in blood samples from individuals with HD, which may reflect the immune pathology associated with the disease.

Crucial transcripts predict response to initial immunoglobulin treatment in acute Kawasaki disease

Although intravenous immunoglobulin (IVIG) can effectively treat Kawasaki disease (KD), 10–20% of KD patients show no beneficial clinical response. Developing reliable criteria to discriminate non-responders is important for early planning of appropriate regimens. To predict the non-responders before IVIG treatment, gene expression dataset of 110 responders and 61 non-responders was obtained from Gene Expression Omnibus. After weighted gene co-expression network analysis, we found that modules positively correlated with the non-responders were mainly associated with myeloid cell activation. Transcripts up-regulated in the non-responders, IL1R2, GK, HK3, C5orf32, CXCL16, NAMPT and EMILIN2, were proven to play key roles via interaction with other transcripts in co-expression network. The crucial transcripts may affect the clinical response to IVIG treatment in acute KD. And these transcripts may serve as biomarkers and therapeutic targets for precise diagnosis and treatment of the non-responders.

Longitudinal expression changes are weak correlates of disease progression in Huntington's disease

Huntington's disease is a severe but slowly progressive hereditary illness for which only symptomatic treatments are presently available. Clinical measures of disease progression are somewhat subjective and may require years to detect significant change. There is a clear need to identify more sensitive, objective and consistent measures to detect disease progression in Huntington's disease clinical trials. Whereas Huntington's disease demonstrates a robust and consistent gene expression signature in the brain, previous studies of blood cell RNAs have lacked concordance with clinical disease stage. Here we utilized longitudinally collected samples from a well-characterized cohort of control, Huntington's disease-at-risk and Huntington's disease subjects to evaluate the possible correlation of gene expression and disease status within individuals. We interrogated these data in both cross-sectional and longitudinal analyses. A number of changes in gene expression showed consistency within this study and as compared to previous reports in the literature. The magnitude of the mean disease effect over 2 years' time was small, however, and did not track closely with motor symptom progression over the same time period. We therefore conclude that while blood-derived gene expression indicators can be of value in understanding Huntington's disease pathogenesis, they are insufficiently sensitive to be of use as state biomarkers.

Evaluation of blood gene expression levels in facioscapulohumeral muscular dystrophy patients

Facioscapulohumeral muscular dystrophy (FSHD) is caused by the expression of DUX4 in skeletal muscles. A number of therapeutic approaches are being developed to antagonize the events preceding and following DUX4 expression that leads to muscular dystrophy. Currently, the possibility to evaluate treatment response in clinical trials is hampered by the lack of objective molecular biomarkers connecting the disease cause to clinical performance. In this study we employed RNA-seq to examine gene expression in PAXgene tubes obtained from two independent cohorts of FSHD patients. Analysis of gene expression profiles did not lead to the identification of genes or pathways differentially expressed in FSHD patients, or associated with disease severity. In particular, we did not find evidence that the DUX4 and PAX7 signatures were differentially expressed. On the other hand, we were able to improve patient classification by including single genes or groups of genes in classification models. The best classifier was ROPN1L, a gene known to be expressed in testis, coincidentally the typical location of DUX4 expression. These improvements in patient classification hold the potential to enrich the FSHD clinical trial toolbox.

Annexin A3 in sepsis: novel perspectives from an exploration of public transcriptome data

According to publicly available transcriptome datasets, the abundance of Annexin A3 (ANXA3) is robustly increased during the course of sepsis; however, no studies have examined the biological significance or clinical relevance of ANXA3 in this pathology. Here we explored this interpretation gap and identified possible directions for future research. Based on reference transcriptome datasets, we found that ANXA3 expression is restricted to neutrophils, is upregulated in vitro after exposure to plasma obtained from septic patients, and is associated with adverse clinical outcomes. Secondly, an increase in ANXA3 transcript abundance was also observed in vivo, in the blood of septic patients in multiple independent studies. ANXA3 is known to mediate calcium-dependent granules-phagosome fusion in support of microbicidal activity in neutrophils. More recent work has also shown that ANXA3 enhances proliferation and survival of tumour cells via a Caspase-3-dependent mechanism. And this same molecule is also known to play a critical role in regulation of apoptotic events in neutrophils. Thus, we posit that during sepsis ANXA3 might either play a beneficial role, by facilitating microbial clearance and resolution of the infection; or a detrimental role, by prolonging neutrophil survival, which is known to contribute to sepsis-mediated organ damage.

Inflammation in Huntington's disease: A few new twists on an old tale

Huntington's disease (HD) is a neurodegenerative disease characterized by prominent loss of neurons in the striatum and cortex. Traditionally research in HD has focused on brain changes as they cause progressive motor dysfunction, cognitive decline and psychiatric disorders. The discovery that huntingtin protein (HTT) and its mutated form (mHTT) are expressed not only in the brain but also in different organs and tissues paved the way for the hypothesis that HD might affect regions beyond the central nervous system (CNS). Besides pathological deposition of mHTT, other mechanisms, including inflammation, seem to underlie HD pathogenesis and progression. Altered inflammation can be evidenced even before the onset of classical symptoms of HD. Herein, we will discuss current pre-clinical and clinical evidence on immune/inflammatory changes in peripheral organs during HD development and progression. The understanding of the impact of inflammation on peripheral organs may open new venues for the development of novel therapeutic targets in HD.

Mitochondrial biology and the identification of biomarkers of Huntington's disease

Apart from finding novel compounds for treating Huntington's disease (HD) an important challenge at present consists in finding reliable read-outs or biomarkers that reflect key biological processes involved in HD pathogenesis. The core elements of HD biology, for example, HTT RNA levels or protein species can serve as biomarker, as could measures from biological systems or pathways in which Huntingtin plays an important role. Here we review the evidence for the involvement of mitochondrial biology in HD. The most consistent findings pertain to mitochondrial quality control, for example, fission/fusion. However, a convincing mitochondrial signature with biomarker potential is yet to emerge. This requires more research including in peripheral sources of human material, such as blood, or skeletal muscle.

Systematic metabolic analysis of potential target, therapeutic drug, diagnostic method and animal model applicability in three neurodegenerative diseases

Considerable evidence suggests that metabolic abnormalities are associated with neurodegenerative diseases. This study aimed to conduct a systematic metabolic analysis of Alzheimer’s disease (AD), Parkinson’s disease (PD) and Huntington’s disease (HD). Human and mouse model microarray datasets were downloaded from the Gene Expression Omnibus database. The metabolic genes and pathways were collected from the Recon 3D human metabolic model. Drug and target information was obtained from the DrugBank database. This study identified ATP1A1, ATP6V1G2, GOT1, HPRT1, MAP2K1, PCMT1 and PLK2 as key metabolic genes that were downregulated in AD, PD and HD. We screened 57 drugs that target these genes, such as digoxin, ouabain and diazoxide. This study constructed multigene diagnostic models for AD, PD and HD by using metabolic gene expression profiles in blood, all models showed high accuracy (AUC > 0.8) both in the experimental and validation sets. Furthermore, analysis of animal models showed that there was almost no consistency among the metabolic changes between mouse models and human diseases. This study systematically revealed the metabolic damage among AD, PD, and HD and uncovered the differences between animal models and human diseases. This information may be helpful for understanding the metabolic mechanisms and drug development for neurodegenerative diseases.

A six‑gene support vector machine classifier contributes to the diagnosis of pediatric septic shock

Septic shock is induced by an uncontrolled inflammatory immune response to pathogens and the survival rate of patients with pediatric septic shock (PSS) is particularly low, with a mortality rate of 25‑50%. The present study explored the mechanisms of PSS using four microarray datasets (GSE26378, GSE26440, GSE13904 and GSE4607) that were obtained from the Gene Expression Omnibus database. Based on the MetaDE package, the consistently differentially expressed genes (DEGs) in the four datasets were screened. Using the WGCNA package, the disease‑associated modules and genes were identified. Subsequently, the optimal feature genes were further selected using the caret package. Finally, a support vector machine (SVM) classifier based on the optimal feature genes was built using the e1071 package. Initially, there were 2,699 consistent DEGs across the four datasets. From the 10 significantly stable modules across the datasets, four stable modules (including the magenta, purple, turquoise and yellow modules), in which the consistent DEGs were significantly enriched (P<0.05), were further screened. Subsequently, six optimal feature genes (including cysteine rich transmembrane module containing 1, S100 calcium binding protein A9, solute carrier family 2 member 14, stomatin, uridine phosphorylase 1 and utrophin) were selected from the genes in the four stable modules. Additionally, an effective SVM classifier was constructed based on the six optimal genes. The SVM classifier based on the six optimal genes has the potential to be applied for PSS diagnosis. This may improve the accuracy of early PSS diagnosis and suggest possible molecular targets for interventions.

Epigenetic mechanisms of neurodegenerative diseases and acute brain injury

Epigenetic modifications are emerging as major players in the pathogenesis of neurodegenerative disorders and susceptibility to acute brain injury. DNA and histone modifications act together with non-coding RNAs to form a complex gene expression machinery that adapts the brain to environmental stressors and injury response. These modifications influence cell-level operations like neurogenesis and DNA repair to large, intricate processes such as brain patterning, memory formation, motor function and cognition. Thus, epigenetic imbalance has been shown to influence the progression of many neurological disorders independent of aberrations in the genetic code. This review aims to highlight ways in which epigenetics applies to several commonly researched neurodegenerative diseases and forms of acute brain injury as well as shed light on the benefits of epigenetics-based treatments.

aTEMPO: Pathway-Specific Temporal Anomalies for Precision Therapeutics

Dynamic processes are inherently important in disease, and identifying disease-related disruptions of normal dynamic processes can provide information about individual patients. We have previously characterized individuals' disease states via pathway-based anomalies in expression data, and we have identified disease-correlated disruption of predictable dynamic patterns by modeling a virtual time series in static data. Here we combine the two approaches, using an anomaly detection model and virtual time series to identify anomalous temporal processes in specific disease states. We demonstrate that this approach can informatively characterize individual patients, suggesting personalized therapeutic approaches.

Transcriptional correlates of the pathological phenotype in a Huntington's disease mouse model

Huntington disease (HD) is a fatal neurodegenerative disorder without a cure that is caused by an aberrant expansion of CAG repeats in exon 1 of the huntingtin (HTT) gene. Although a negative correlation between the number of CAG repeats and the age of disease onset is established, additional factors may contribute to the high heterogeneity of the complex manifestation of symptoms among patients. This variability is also observed in mouse models, even under controlled genetic and environmental conditions. To better understand this phenomenon, we analysed the R6/1 strain in search of potential correlates between pathological motor/cognitive phenotypical traits and transcriptional alterations. HD-related genes (e.g., Penk, Plk5, Itpka), despite being downregulated across the examined brain areas (the prefrontal cortex, striatum, hippocampus and cerebellum), exhibited tissue-specific correlations with particular phenotypical traits that were attributable to the contribution of the brain region to that trait (e.g., striatum and rotarod performance, cerebellum and feet clasping). Focusing on the striatum, we determined that the transcriptional dysregulation associated with HD was partially exacerbated in mice that showed poor overall phenotypical scores, especially in genes with relevant roles in striatal functioning (e.g., Pde10a, Drd1, Drd2, Ppp1r1b). However, we also observed transcripts associated with relatively better outcomes, such as Nfya (CCAAT-binding transcription factor NF-Y subunit A) plus others related to neuronal development, apoptosis and differentiation. In this study, we demonstrated that altered brain transcription can be related to the manifestation of HD-like symptoms in mouse models and that this can be extrapolated to the highly heterogeneous population of HD patients.

Age-associated bimodal transcriptional drift reduces intergenic disparities in transcription

This study addressed the question of how well the quantitative transcriptome structure established in early life is maintained and how consistently it appears with increasing age, and if there is age-associated alteration of gene expression (A₃GE), how much influence the Huntington’s disease (HD) genotype exerts on it. We examined 285 exonic sequences of 175 genes using targeted PCR sequencing in skeletal muscle, brain, and splenic CD4+ T cells of wild-type and HD mice. In contrast to the muscle and brain, T cells exhibited large A₃GE, suggesting a strong contribution to functional decline of the organism. This A₃GE was markedly intensified in age-matched HD T cells, which exhibited accelerated aging as determined by reduced telomere length. Regression analysis suggested that gene expression levels change at a rate of approximately 3% per month with age. We found a bimodal relationship in A₃GE in T cells in that weakly expressed genes in young mice were increasingly transcribed in older animals whereas highly expressed genes in the young were decreasingly expressed with age. This bimodal transcriptional drift in the T cell transcriptome data causes the differences in transcription rate between genes to progressively reduce with age.

Peripheral blood gene expression reveals an inflammatory transcriptomic signature in Friedreich's ataxia patients

Transcriptional changes in Friedreich's ataxia (FRDA), a rare and debilitating recessive Mendelian neurodegenerative disorder, have been studied in affected but inaccessible tissues-such as dorsal root ganglia, sensory neurons and cerebellum-in animal models or small patient series. However, transcriptional changes induced by FRDA in peripheral blood, a readily accessible tissue, have not been characterized in a large sample. We used differential expression, association with disability stage, network analysis and enrichment analysis to characterize the peripheral blood transcriptome and identify genes that were differentially expressed in FRDA patients (n = 418) compared with both heterozygous expansion carriers (n = 228) and controls (n = 93 739 individuals in total), or were associated with disease progression, resulting in a disease signature for FRDA. We identified a transcriptional signature strongly enriched for an inflammatory innate immune response. Future studies should seek to further characterize the role of peripheral inflammation in FRDA pathology and determine its relevance to overall disease progression.

Transcriptomic Biomarkers for Huntington's Disease: Are Gene Expression Signatures in Whole Blood Reliable Biomarkers?

Huntington's disease (HD) is a severe neurodegenerative disorder manifesting as progressive impairment of motor function, cognitive decline, psychiatric symptoms, and immunological and endocrine dysfunction. We explored the consistency of blood transcriptomic biomarkers in HD based on a novel Slovene patient cohort and expert review of previous studies. HumanHT-12 v4 BeadChip microarrays were performed on the whole blood samples of a cohort of 23 HD mutation carriers and 23 controls to identify differentially expressed (DE) transcripts. In addition, we performed an expert review of DE transcripts identified in comparable HD studies from whole blood, to identify any consistent signature of HD. In the Slovene cohort, we identified 740 DE transcripts (p < 0.01 and a false discovery rate (FDR) of <0.1) of which 414 were downregulated and 326 were upregulated. Pathway analyses of DE transcripts showed enrichment for pathways involved in systemic, rather than neural processes in HD. With an expert review of comparable studies, we have further identified 15 DE transcripts shared by 3 studies. We suggest transcriptomic changes in blood reflect systemic changes in HD pathogenesis, rather than being a direct result of the neuropathological processes in the central nervous system during HD progression, and thus, have limited value as disease biomarkers.

Identification of potential blood biomarkers for Parkinson's disease by gene expression and DNA methylation data integration analysis

BACKGROUND

Blood-based gene expression or epigenetic biomarkers of Parkinson's disease (PD) are highly desirable. However, accuracy and specificity need to be improved, and methods for the integration of gene expression with epigenetic data need to be developed in order to make this feasible.

METHODS

Whole blood gene expression data and DNA methylation data were downloaded from Gene Expression Omnibus (GEO) database. A linear model was used to identify significantly differentially expressed genes (DEGs) and differentially methylated genes (DMGs) according to specific gene regions 5'-C-phosphate-G-3' (CpGs) or all gene regions CpGs in PD. Gene set enrichment analysis was then applied to DEGs and DMGs. Subsequently, data integration analysis was performed to identify robust PD-associated blood biomarkers. Finally, the random forest algorithm and a leave-one-out cross validation method were performed to construct classifiers based on gene expression data integrated with methylation data.

RESULTS

Eighty-five (85) significantly hypo-methylated and upregulated genes in PD patients compared to healthy controls were identified. The dominant hypo-methylated regions of these genes were significantly different. Some genes had a single dominant hypo-methylated region, while others had multiple dominant hypo-methylated regions. One gene expression classifier and two gene methylation classifiers based on all or dominant methylation-altered region CpGs were constructed. All have a good prediction power for PD.

CONCLUSIONS

Gene expression and methylation data integration analysis identified a blood-based 53-gene signature, which could be applied as a biomarker for PD.

RNA Related Pathology in Huntington's Disease

This chapter summarises research investigating the expression of huntingtin sense and anti-sense transcripts, the effect of the mutation on huntingtin processing as well as the more global effect of the mutation on the coding and non-coding transcriptomes. The huntingtin gene is ubiquitously expressed, although expression levels vary between tissues and cell types. A SNP that affects NF-ĸB binding in the huntingtin promoter modulates the expression level of huntingtin transcripts and is associated with the age of disease onset. Incomplete splicing between exon 1 and exon 2 has been shown to result in the expression of a small polyadenylated mRNA that encodes the highly pathogenic exon 1 huntingtin protein. This occurs in a CAG-repeat length dependent manner in all full-length mouse models of HD as well as HD patient post-mortem brains and fibroblasts. An antisense transcript to huntingtin is generated that contains a CUG repeat that is expanded in HD patients. In myotonic dystrophy, expanded CUG repeats form RNA foci in cell nuclei that bind specific proteins (e.g. MBL1). Short, pure CAG RNAs of approximately 21 nucleotides that have been processed by DICER can inhibit the translation of other CAG repeat containing mRNAs. The HD mutation affects the transcriptome at the level of mRNA expression, splicing and the expression of non-coding RNAs. Finally, expanded repetitive stretched of nucleotides can lead to RAN translation, in which the ribosome translates from the expanded repeat in all possible reading frames, producing proteins with various poly-amino acid tracts. The extent to which these events contribute to HD pathogenesis is largely unknown.

Transcriptome analysis reveals candidate genes involved in splay leg syndrome in piglets

Splay leg is frequently observed in newborn piglets and leads to economic loss as well as welfare concerns. However, the etiology and pathogenesis of splay leg syndrome in piglets are still poorly understood. The aims of this paper were to characterize changes in the transcriptome of splay leg piglets and identify candidate genes responsible for this disease. We chose three splay leg piglets and their healthy full sibs, and constructed six RNA libraries using skeletal muscle samples from both groups and identified the differentially expressed genes between the two groups using RNA-seq. A total of 555 differentially expressed genes were identified, of which 216 were up-regulated and 339 genes were down-regulated in the splay leg group relative to the healthy group. In addition, 321 significantly enriched GO terms and 12 significantly enriched KEGG pathways were identified. FBXO32 is one of the ten most differentially expressed genes in our experiment, and it is regulated by the significantly enriched pathway (PI3K-Akt). The overexpression of FBXO32 which leads to the process of muscle atrophy might be responsible for congenital splay leg in piglets. The result of this study could help improve understanding of the molecular mechanism of congenital splay leg syndrome.

Transcriptional profiling and biomarker identification reveal tissue specific effects of expanded ataxin-3 in a spinocerebellar ataxia type 3 mouse model

Background

Spinocerebellar ataxia type 3 (SCA3) is a progressive neurodegenerative disorder caused by expansion of the polyglutamine repeat in the ataxin-3 protein. Expression of mutant ataxin-3 is known to result in transcriptional dysregulation, which can contribute to the cellular toxicity and neurodegeneration. Since the exact causative mechanisms underlying this process have not been fully elucidated, gene expression analyses in brains of transgenic SCA3 mouse models may provide useful insights.

Methods

Here we characterised the MJD84.2 SCA3 mouse model expressing the mutant human ataxin-3 gene using a multi-omics approach on brain and blood. Gene expression changes in brainstem, cerebellum, striatum and cortex were used to study pathological changes in brain, while blood gene expression and metabolites/lipids levels were examined as potential biomarkers for disease.

Results

Despite normal motor performance at 17.5 months of age, transcriptional changes in brain tissue of the SCA3 mice were observed. Most transcriptional changes occurred in brainstem and striatum, whilst cerebellum and cortex were only modestly affected. The most significantly altered genes in SCA3 mouse brain were Tmc3, Zfp488, Car2, and Chdh. Based on the transcriptional changes, α-adrenergic and CREB pathways were most consistently altered for combined analysis of the four brain regions. When examining individual brain regions, axon guidance and synaptic transmission pathways were most strongly altered in striatum, whilst brainstem presented with strongest alterations in the pi-3 k cascade and cholesterol biosynthesis pathways. Similar to other neurodegenerative diseases, reduced levels of tryptophan and increased levels of ceramides, di- and triglycerides were observed in SCA3 mouse blood.

Conclusions

The observed transcriptional changes in SCA3 mouse brain reveal parallels with previous reported neuropathology in patients, but also shows brain region specific effects as well as involvement of adrenergic signalling and CREB pathway changes in SCA3. Importantly, the transcriptional changes occur prior to onset of motor- and coordination deficits.

Electronic supplementary material

The online version of this article (10.1186/s13024-018-0261-9) contains supplementary material, which is available to authorized users.

Genome-Scale Brain Metabolic Networks as Scaffolds for the Systems Biology of Neurodegenerative Diseases: Mapping Metabolic Alterations

Systems-based investigation of diseases requires integrated analysis of cellular networks and high-throughput data of gene products. The use of genome-scale metabolic networks for such integration has led to the elucidation of cellular mechanisms for several cell types from microorganisms to plants. It has become easier and cheaper to generate high-throughput data over years in the form of transcriptome, proteome and metabolome. This has tremendously improved the quality and quantity of information extracted from such data enabling the documentation of active pathways and reactions in cell metabolism. A number of omics-based datasets for several neurodegenerative diseases are now available in public repositories. This increases the potential of using genome-scale brain metabolic networks as a scaffold for this type of data to map metabolic alterations for the purpose of elucidating disease mechanisms and for the diagnosis and treatment of such disorders. This chapter first reviews omics data collected for neurodegenerative diseases to map their effect on metabolism. Later, the potential for genome-scale metabolic modeling of such data is reviewed and discussed in light of recently reconstructed brain metabolic networks at genome-scale.

Point-of-Care Devices Using Disease Biomarkers To Diagnose Neurodegenerative Disorders

Neurodegenerative disorders such as Alzheimer's, Parkinson's, and Huntington's diseases are highly prevalent and immensely destructive to the health and well-being of individuals and their families across the globe. Neurodegenerative diseases are characterized by the gradual loss of neural tissue in the central nervous system. Clearly, early diagnosis of the onset of neurodegeneration is vital and beneficial. Current diagnostic methods rely heavily on symptoms or autopsy results, thus overlooking early diagnosis, the only opportunity for amelioration. However, appropriately selected and used biomarker diagnostics provide a solution. This article reviews the development and application of biomarker-related diagnostics for neurodegenerative disease with specific recommendations for point-of-care (POC) methodology. These advantageous approaches may offer a solution to existing obstacles and limitations to neurodegenerative disease treatment.

Therapy development in Huntington disease: From current strategies to emerging opportunities

Huntington disease (HD) is a progressive autosomal dominant neurodegenerative disorder in which patients typically present with uncontrolled involuntary movements and subsequent cognitive decline. In 1993, a CAG trinucleotide repeat expansion in the coding region of the huntingtin (HTT) gene was identified as the cause of this disorder. This extended CAG repeat results in production of HTT protein with an expanded polyglutamine tract, leading to pathogenic HTT protein conformers that are resistant to protein turnover, culminating in cellular toxicity and neurodegeneration. Research into the mechanistic basis of HD has highlighted a role for bioenergetics abnormalities stemming from mitochondrial dysfunction, and for synaptic defects, including impaired neurotransmission and excitotoxicity. Interference with transcription regulation may underlie the mitochondrial dysfunction. Current therapies for HD are directed at treating symptoms, as there are no disease-modifying therapies. Commonly prescribed drugs for involuntary movement control include tetrabenazine, a potent and selective inhibitor of vesicular monoamine transporter 2 that depletes synaptic monoamines, and olanzapine, an atypical neuroleptic that blocks the dopamine D2 receptor. Various drugs are used to treat non-motor features. The HD therapeutic pipeline is robust, as numerous efforts are underway to identify disease-modifying treatments, with some small compounds and biological agents moving into clinical trials. Especially encouraging are dosage reduction strategies, including antisense oligonucleotides, and molecules directed at transcription dysregulation. Given the depth and breadth of current HD drug development efforts, there is reason to believe that disease-modifying therapies for HD will emerge, and this achievement will have profound implications for the entire neurotherapeutics field.

Transcriptome profile of yeast reveals the essential role of PMA2 and uncharacterized gene YBR056W-A (MNC1) in adaptation to toxic manganese concentration

Adaptation of S. cerevisiae to toxic concentrations of manganese provides a physiological model of heavy metal homeostasis. Transcriptome analysis of adapted yeast cells reveals upregulation of cell wall and plasma membrane proteins including membrane transporters. The gene expression in adapted cells differs from that of cells under short-term toxic metal stress. Among the most significantly upregulated genes are PMA2, encoding an ortholog of Pma1 H⁺-ATPase of the plasma membrane, and YBR056W-A, encoding a putative membrane protein Mnc1 that belongs to the CYSTM family and presumably chelates manganese at the cell surface. We demonstrate that these genes are essential for the adaptation to toxic manganese concentration and propose an extended scheme of manganese detoxification in yeast.

Age-associated chromatin relaxation is enhanced in Huntington's disease mice

Expansion of polyglutamine stretch in the huntingtin (HTT) protein is a major cause of Huntington's disease (HD). The polyglutamine part in HTT interacts with various proteins implicated in epigenetic regulation of genes, suggesting that mutant HTT may disturb the integrity of the epigenetic system. Here, we used a PCRseq-based method to examine expression profile of 395 exonic segments from 260 “epi-driver” genes in splenic T lymphocytes from aged HD mice. We identified 67 exonic segments differentially expressed between young and aged HD mice, most of them upregulated in the aged. Polycomb-repressive complex (PRC)-regulated genes (PRGs) were markedly upregulated in aged HD mice, consistent with downregulation of PRC genes. Epi-driver gene categories of lysine-methylation, lysine-demethylation, arginine-methylation, and PRG showed differential age-associated changes between HD and control. Analyzing the pattern of change in epi-driver gene expressions hinted at an enhanced shift in HD chromatin to a more accessible state with age, which was experimentally demonstrated by DNase-I-hypersensitivity sequencing showing increased chromatin accessibility in HD cells compared to control. We suggest the global change can potentially relieve chromatin-induced repression of many genes, and the unintended expressions of some detrimental proteins could alter T cell function to a greater degree in aged HD mice.

Adhesion Regulating Molecule 1 Mediates HAP40 Overexpression-Induced Mitochondrial Defects

Striatal neuron death in Huntington's disease is associated with abnormal mitochondrial dynamics and functions. However, the mechanisms for this mitochondrial dysregulation remain elusive. Increased accumulation of Huntingtin-associated protein 40 (HAP40) has been shown to be associated with Huntington's disease. However, the link between increased HAP40 and Huntington's disease remains largely unknown. Here we show that HAP40 overexpression causes mitochondrial dysfunction and reduces cell viability in the immortalized mouse striatal neurons. HAP40-associated mitochondrial dysfunction is associated with reduction of adhesion regulating molecule 1 (ADRM1) protein. Consistently, depletion of ADRM1 by shRNAs impaired mitochondrial functions and increased mitochondrial fragmentation in mouse striatal cells. Moreover, reducing ADRM1 levels enhanced activity of fission factor dynamin-related GTPase protein 1 (Drp1) via increased phosphorylation at serine 616 of Drp1 (Drp1^Ser616). Restoring ADRM1 protein levels was able to reduce HAP40-induced ROS levels and mitochondrial fragmentation and improved mitochondrial functions and cell viability. Moreover, reducing Drp1 activity by Drp1 inhibitor, Mdivi-1, ameliorates both HAP40 overexpression- and ADRM1 depletion-induced mitochondrial dysfunction. Taken together, our studies suggest that HAP40-mediated reduction of ADRM1 alters the mitochondrial fission activity and results in mitochondrial fragmentation and mitochondrial dysfunction.

Modern Genome Editing Technologies in Huntington's Disease Research

The development of new revolutionary technologies for directed gene editing has made it possible to thoroughly model and study NgAgo human diseases at the cellular and molecular levels. Gene editing tools like ZFN, TALEN, CRISPR-based systems, NgAgo and SGN can introduce different modifications. In gene sequences and regulate gene expression in different types of cells including induced pluripotent stem cells (iPSCs). These tools can be successfully used for Huntington's disease (HD) modeling, for example, to generate isogenic cell lines bearing different numbers of CAG repeats or to correct the mutation causing the disease. This review presents common genome editing technologies and summarizes the progress made in using them in HD and other hereditary diseases. Furthermore, we will discuss prospects and limitations of genome editing in understanding HD pathology.

Huntington's Disease: Calcium Dyshomeostasis and Pathology Models

Huntington's disease (HD) is a severe inherited neurodegenerative disorder characterized by motor dysfunction, cognitive decline, and mental impairment. At the molecular level, HD is caused by a mutation in the first exon of the gene encoding the huntingtin protein. The mutation results in an expanded polyglutamine tract at the N-terminus of the huntingtin protein, causing the neurodegenerative pathology. Calcium dyshomeostasis is believed to be one of the main causes of the disease, which underlies the great interest in the problem among experts in molecular physiology. Recent studies have focused on the development of animal and insect HD models, as well as patient-specific induced pluripotent stem cells (HD-iPSCs), to simulate the disease's progression. Despite a sesquicentennial history of HD studies, the issues of diagnosis and manifestation of the disease have remained topical. The present review addresses these issues.