Common disease signatures from gene expression analysis in Huntington's disease human blood and brain

TYROBP/DAP12 knockout in Huntington's disease Q175 mice cell-autonomously decreases microglial expression of disease-associated genes and non-cell-autonomously mitigates astrogliosis and motor deterioration

INTRODUCTION

Huntington's disease (HD) is a fatal neurodegenerative disorder caused by an expansion of the CAG trinucleotide repeat in the Huntingtin gene (HTT). Immune activation is abundant in the striatum of HD patients. Detection of active microglia at presymptomatic stages suggests that microgliosis is a key early driver of neuronal dysfunction and degeneration. Recent studies showed that deletion of Tyrobp, a microglial protein, ameliorates neuronal dysfunction in Alzheimer's disease amyloidopathy and tauopathy mouse models while decreasing components of the complement subnetwork.

OBJECTIVE

While TYROBP/DAP12-mediated microglial activation is detrimental for some diseases such as peripheral nerve injury, it is beneficial for other diseases. We sought to determine whether the TYROBP network is implicated in HD and whether Tyrobp deletion impacts HD striatal function and transcriptomics.

METHODS

To test the hypothesis that Tyrobp deficiency would be beneficial in an HD model, we placed the Q175 HD mouse model on a Tyrobp-null background. We characterized these mice with a combination of behavioral testing, immunohistochemistry, transcriptomic and proteomic profiling. Further, we evaluated the gene signature in isolated Q175 striatal microglia, with and without Tyrobp.

RESULTS

Comprehensive analysis of publicly available human HD transcriptomic data revealed that the TYROBP network is overactivated in the HD putamen. The Q175 mice showed morphologic microglial activation, reduced levels of post-synaptic density-95 protein and motor deficits at 6 and 9 months of age, all of which were ameliorated on the Tyrobp-null background. Gene expression analysis revealed that lack of Tyrobp in the Q175 model does not prevent the decrease in the expression of striatal neuronal genes but reduces pro-inflammatory pathways that are specifically active in HD human brain, including genes identified as detrimental in neurodegenerative diseases, e.g. C1q and members of the Ccr5 signaling pathway. Integration of transcriptomic and proteomic data revealed that astrogliosis and complement system pathway were reduced after Tyrobp deletion, which was further validated by immunofluorescence analysis.

CONCLUSIONS

Our data provide molecular and functional support demonstrating that Tyrobp deletion prevents many of the abnormalities in the HD Q175 mouse model, suggesting that the Tyrobp pathway is a potential therapeutic candidate for Huntington's disease.

Temporal changes of gene expression in health, schizophrenia, bipolar disorder, and major depressive disorder

The molecular events underlying the development, manifestation, and course of schizophrenia, bipolar disorder, and major depressive disorder span from embryonic life to advanced age. However, little is known about the early dynamics of gene expression in these disorders due to their relatively late manifestation. To address this, we conducted a secondary analysis of post-mortem prefrontal cortex datasets using bioinformatics and machine learning techniques to identify differentially expressed gene modules associated with aging and the diseases, determine their time-perturbation points, and assess enrichment with expression quantitative trait loci (eQTL) genes. Our findings revealed early, mid, and late deregulation of expression of functional gene modules involved in neurodevelopment, plasticity, homeostasis, and immune response. This supports the hypothesis that multiple hits throughout life contribute to disease manifestation rather than a single early-life event. Moreover, the time-perturbed functional gene modules were associated with genetic loci affecting gene expression, highlighting the role of genetic factors in gene expression dynamics and the development of disease phenotypes. Our findings emphasize the importance of investigating time-dependent perturbations in gene expression before the age of onset in elucidating the molecular mechanisms of psychiatric disorders.

Leukocyte Telomere Length as Potential Biomarker of HD Progression: A Follow-Up Study

The identification of biomarkers for neurodegenerative disorders such as Huntington’s disease (HD) is crucial for monitoring disease progression and therapeutic trial outcomes, especially in the pre-manifest disease stage (pre-HD). In a previous study, we observed that leukocyte telomere length (LTL) was strongly correlated with the estimated time to clinical onset in pre-HD subjects. To validate this hypothesis, we designed a follow-up study in which we analyzed LTL in 45 pre-HD stage subjects at baseline (T0) and then again after clinical onset at follow-up (T1); the follow-up interval was about 3 years, and the CAG range was 39–51 repeats; 90 peripheral blood mononuclear cell samples (PBMCs) were obtained from the Enroll-HD biorepository. In pre-HD subjects at T0, LTL was significantly reduced by 22% compared to the controls and by 14% from T0 at T1. No relationship was observed between the LTL and CAG numbers in subjects carrying different CAG repeats at T0 and at T1, suggesting that LTL reduction occurs independently of CAG number in pre-HD subjects. ROC curve analysis was used to test the validity of LTL as a potential biomarker of HD progression and showed that LTL measurement is extremely accurate in discriminating pre-HD subjects from the controls and even pre-HD from manifest HD, thus yielding a robust prognostic value in pre-HD subjects.

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.

Amygdala DCX and blood Cdk14 are implicated as cross-species indicators of individual differences in fear, extinction, and resilience to trauma exposure

Doublecortin (DCX) has long been implicated in, and employed as a marker for, neurogenesis, yet little is known about its function in non-neurogenic brain regions, including the amygdala. This study sought first to explore, in rodents, whether fear learning and extinction modulate amygdala DCX expression and, second, to assess the utility of peripheral DCX correlates as predictive biomarkers of trauma response in rodents and humans. Pavlovian conditioning was found to alter DCX protein levels in mice 24 h later, resulting in higher DCX expression associated with enhanced learning in paradigms examining both the acquisition and extinction of fear (p < 0.001). This, in turn, is associated with differences in freezing on subsequent fear expression tests, and the same relationship between DCX and fear extinction was replicated in rats (p < 0.001), with higher amygdala DCX levels associated with more rapid extinction of fear. RNAseq of amygdala and blood from mice identified 388 amygdala genes that correlated with DCX (q < 0.001) and which gene ontology analyses revealed were significantly over-represented for neurodevelopmental processes. In blood, DCX-correlated genes included the Wnt signaling molecule Cdk14 which was found to predict freezing during both fear acquisition (p < 0.05) and brief extinction protocols (p < 0.001). High Cdk14 measured in blood immediately after testing was also associated with less freezing during fear expression testing (p < 0.01). Finally, in humans, Cdk14 expression in blood taken shortly after trauma was found to predict resilience in males for up to a year post-trauma (p < 0.0001). These data implicate amygdala DCX in fear learning and suggest that Cdk14 may serve as a predictive biomarker of trauma response.

Blood and brain gene expression signatures of chronic intermittent ethanol consumption in mice

Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heterogeneous set of behavioral signs and symptoms. There are no laboratory tests that provide direct objective evidence for diagnosis. Microarray and RNA-Seq technologies enable genome-wide transcriptome profiling at low costs and provide an opportunity to identify biomarkers to facilitate diagnosis, prognosis, and treatment of patients. However, access to brain tissue in living patients is not possible. Blood contains cellular and extracellular RNAs that provide disease-relevant information for some brain diseases. We hypothesized that blood gene expression profiles can be used to diagnose AUD. We profiled brain (prefrontal cortex, amygdala, and hypothalamus) and blood gene expression levels in C57BL/6J mice using RNA-seq one week after chronic intermittent ethanol (CIE) exposure, a mouse model of alcohol dependence. We found a high degree of preservation (rho range: [0.50, 0.67]) between blood and brain transcript levels. There was small overlap between blood and brain DEGs, and considerable overlap of gene networks perturbed after CIE related to cell-cell signaling (e.g., GABA and glutamate receptor signaling), immune responses (e.g., antigen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logistic regression, random forest, and partial least squares discriminant analysis), which were highly accurate at predicting alcohol dependence status (maximum AUC: 90.1%). These results suggest that gene expression profiles from peripheral blood samples contain a biological signature of alcohol dependence that can discriminate between CIE and Air subjects.

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.

Systemic manifestation and contribution of peripheral tissues to Huntington's disease pathogenesis

Huntington disease (HD) is an autosomal dominant neurodegenerative disease that is caused by expansion of cytosine/adenosine/guanine repeats in the huntingtin (HTT) gene, which leads to a toxic, aggregation-prone, mutant HTT-polyQ protein. Beyond the well-established mechanisms of HD progression in the central nervous system, growing evidence indicates that also peripheral tissues are affected in HD and that systemic signaling originating from peripheral tissues can influence the progression of HD in the brain. Herein, we review the systemic manifestation of HD in peripheral tissues, and the impact of systemic signaling on HD pathogenesis. Mutant HTT induces a body wasting syndrome (cachexia) primarily via its activity in skeletal muscle, bone, adipose tissue, and heart. Additional whole-organism effects induced by mutant HTT include decline in systemic metabolic homeostasis, which stems from derangement of pancreas, liver, gut, hypothalamic-pituitary-adrenal axis, and circadian functions. In addition to spreading via the bloodstream and a leaky blood brain barrier, HTT-polyQ may travel long distance via its uptake by neurons and its axonal transport from the peripheral to the central nervous system. Lastly, signaling factors that are produced and/or secreted in response to therapeutic interventions such as exercise or in response to mutant HTT activity in peripheral tissues may impact HD. In summary, these studies indicate that HD is a systemic disease that is influenced by intertissue signaling and by the action of pathogenic HTT in peripheral tissues. We propose that treatment strategies for HD should include the amelioration of HD symptoms in peripheral tissues. Moreover, harnessing signaling between peripheral tissues and the brain may provide a means for reducing HD progression in the central nervous system.

Weighted Gene Coexpression Network Analysis Reveals Essential Genes and Pathways in Bipolar Disorder

Bipolar disorder (BD) is a major and highly heritable mental illness with severe psychosocial impairment, but its etiology and pathogenesis remains unclear. This study aimed to identify the essential pathways and genes involved in BD using weighted gene coexpression network analysis (WGCNA), a bioinformatic method studying the relationships between genes and phenotypes. Using two available BD gene expression datasets (GSE5388, GSE5389), we constructed a gene coexpression network and identified modules related to BD. The analyses of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways were performed to explore functional enrichment of the candidate modules. A protein-protein interaction (PPI) network was further constructed to identify the potential hub genes. Ten coexpression modules were identified from the top 5,000 genes in 77 samples and three modules were significantly associated with BD, which were involved in several biological processes (e.g., the actin filament-based process) and pathways (e.g., MAPK signaling). Four genes (NOTCH1, POMC, NGF, and DRD2) were identified as candidate hub genes by PPI analysis and CytoHubba. Finally, we carried out validation analyses in a separate dataset, GSE12649, and verified NOTCH1 as a hub gene and the involvement of several biological processes such as actin filament-based process and axon development. Taken together, our findings revealed several candidate pathways and genes (NOTCH1) in the pathogenesis of BD and call for further investigation for their potential research values in BD diagnosis and treatment.

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.

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.

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.

Integrated Systems Analysis Explores Dysfunctional Molecular Modules and Regulatory Factors in Children with Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a genetic neurodevelopmental disorder involving multiple genes that occurs in early childhood, and a number of risk genes have been reported in previous studies. However, the molecular mechanism of the polygenic regulation leading to pathological changes in ASD remains unclear. First, we identified 8 dysregulated gene coexpression modules by analyzing blood transcriptome data from 96 children with ASD and 42 controls. These modules are rich in ASD risk genes and function related to metabolism, immunity, neurodevelopment, and signaling. The regulatory factors of each module including microRNA (miRNA) and transcription factors (TFs) were subsequently predicted based on transcriptional and posttranscriptional regulation. We identified a set of miRNAs that regulate metabolic and immune modules, as well as transcription factors that cause dysregulation of the modules, and we constructed a coregulatory network between the regulatory factors and modules. Our work reveals dysfunctional modules in children with ASD, elucidates the role of miRNA and transcription factor dysregulation in the pathophysiology of ASD, and helps us to further understand the underlying molecular mechanism of ASD.

Single-nucleus RNA-seq identifies Huntington disease astrocyte states

Huntington Disease (HD) is an inherited movement disorder caused by expanded CAG repeats in the Huntingtin gene. We have used single nucleus RNASeq (snRNASeq) to uncover cellular phenotypes that change in the disease, investigating single cell gene expression in cingulate cortex of patients with HD and comparing the gene expression to that of patients with no neurological disease. In this study, we focused on astrocytes, although we found significant gene expression differences in neurons, oligodendrocytes, and microglia as well. In particular, the gene expression profiles of astrocytes in HD showed multiple signatures, varying in phenotype from cells that had markedly upregulated metallothionein and heat shock genes, but had not completely lost the expression of genes associated with normal protoplasmic astrocytes, to astrocytes that had substantially upregulated glial fibrillary acidic protein (GFAP) and had lost expression of many normal protoplasmic astrocyte genes as well as metallothionein genes. When compared to astrocytes in control samples, astrocyte signatures in HD also showed downregulated expression of a number of genes, including several associated with protoplasmic astrocyte function and lipid synthesis. Thus, HD astrocytes appeared in variable transcriptional phenotypes, and could be divided into several different “states”, defined by patterns of gene expression. Ultimately, this study begins to fill the knowledge gap of single cell gene expression in HD and provide a more detailed understanding of the variation in changes in gene expression during astrocyte “reactions” to the disease.

Dual and multi-targeted nanoparticles for site-specific brain drug delivery

In recent years, nanomedicines have emerged as a promising method for central nervous system drug delivery, enabling the drugs to overcome the blood-brain barrier and accumulate preferentially in the brain. Despite the current success of brain-targeted nanomedicines, limitations still exist in terms of the targeting specificity. Based on the molecular mechanism, the exact cell populations and subcellular organelles where the injury occurs and the drugs take effect have been increasingly accepted as a more specific target for the next generation of nanomedicines. Dual and multi-targeted nanoparticles integrate different targeting functionalities and have provided a paradigm for precisely delivering the drug to the pathological site inside the brain. The targeting process often involves the sequential or synchronized navigation of the targeting moieties, which allows highly controlled drug delivery compared to conventional targeting strategies. Herein, we focus on the up-to-date design of pathological site-specific nanoparticles for brain drug delivery, highlighting the dual and multi-targeting strategies that were employed and their impact on improving targeting specificity and therapeutic effects. Furthermore, the background discussion of the basic properties of a brain-targeted nanoparticle and the common lesion features classified by neurological pathology are systematically summarized.

Genetic variants in humanin nuclear isoform gene regions show no association with coronary artery disease

Objective

Coronary artery disease contributes to noncommunicable disease deaths worldwide. In order to make preventive methods more accurate, we need to know more about the development and progress of this pathology, including the genetic aspects. Humanin is a small peptide known for its cytoprotective and anti-apoptotic properties. Our study looked for genomic associations between humanin-like nuclear isoform genes and coronary artery disease using CARDIoGRAMplusC4D Consortium data.

Results

Lookup from meta-analysis datasets gave single nucleotide polymorphisms in all 13 humanin-like nuclear isoform genes with the lowest P value for rs6151662 from the MTRNR2L2 gene including the 50 kb flanking region in both directions (P-value = 0.0037). Within the gene region alone the top variant was rs78083998 from the MTRNR2L13 region (meta-analysis P-value = 0.042). None of the found associations were statistically significant after correction for multiple testing. Lookup for expression trait loci in these gene regions gave no statistically significant variants.

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.

Leukocyte telomere shortening in Huntington's disease

Huntington's disease (HD) is an autosomal dominant neurodegenerative disease caused by an expanded CAG repeat. Though symptom onset commonly occurs at midlife and inversely correlates with the CAG repeat expansion, age at clinical onset and progression rate are variable. In the present study we investigated the relationship between leukocyte telomere length (LTL) and HD development. LTL was measured by real-time PCR in manifest HD patients (HD, n = 62), pre-manifest HD patients (pre-HD, n = 38), and age-matched controls (n = 76). Significant LTL differences were observed between the three groups (p < .0001), with LTL values in the order: HD < pre-HD < controls. The relationship between LTL and age was different in the three groups. An inverse relationship between mean LTL and CAG repeat number was found in the pre-HD (p = .03). The overall data seem to indicate that after age 30 years, LT begins to shorten markedly in pre-HD patients according to CAG number and increasing age, up to the values observed in HD. This very suggestive picture allowed us to hypothesize that in pre-manifest HD, LTL could be a measure of time to clinical HD onset. The possible use of LTL as a reliable biomarker to track HD development and progression was evaluated and discussed.

Identification of putative regulatory regions and transcription factors associated with intramuscular fat content traits

Background

Integration of high throughput DNA genotyping and RNA-sequencing data allows for the identification of genomic regions that control gene expression, known as expression quantitative trait loci (eQTL), on a whole genome scale. Intramuscular fat (IMF) content and carcass composition play important roles in metabolic and physiological processes in mammals because they influence insulin sensitivity and consequently prevalence of metabolic diseases such as obesity and type 2 diabetes. However, limited information is available on the genetic variants and mechanisms associated with IMF deposition in mammals. Thus, our hypothesis was that eQTL analyses could identify putative regulatory regions and transcription factors (TFs) associated with intramuscular fat (IMF) content traits.

Results

We performed an integrative eQTL study in skeletal muscle to identify putative regulatory regions and factors associated with intramuscular fat content traits. Data obtained from skeletal muscle samples of 192 animals was used for association analysis between 461,466 SNPs and the transcription level of 11,808 genes. This yielded 1268 cis- and 10,334 trans-eQTLs, among which we identified nine hotspot regions that each affected the expression of > 119 genes. These putative regulatory regions overlapped with previously identified QTLs for IMF content. Three of the hotspots respectively harbored the transcription factors USF1, EGR4 and RUNX1T1, which are known to play important roles in lipid metabolism. From co-expression network analysis, we further identified modules significantly correlated with IMF content and associated with relevant processes such as fatty acid metabolism, carbohydrate metabolism and lipid metabolism.

Conclusion

This study provides novel insights into the link between genotype and IMF content as evident from the expression level. It thereby identifies genomic regions of particular importance and associated regulatory factors. These new findings provide new knowledge about the biological processes associated with genetic variants and mechanisms associated with IMF deposition in mammals.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4871-y) contains supplementary material, which is available to authorized users.

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.

Integrated approach reveals diet, APOE genotype and sex affect immune response in APP mice

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder that is influenced by genetic and environmental risk factors, such as inheritance of ε4 allele of APOE (APOE4), sex and diet. Here, we examined the effect of high fat diet (HFD) on amyloid pathology and expression profile in brains of AD model mice expressing human APOE isoforms (APP/E3 and APP/E4 mice). APP/E3 and APP/E4 mice were fed HFD or Normal diet for 3months. We found that HFD significantly increased amyloid plaques in male and female APP/E4, but not in APP/E3 mice. To identify differentially expressed genes and gene-networks correlated to diet, APOE isoform and sex, we performed RNA sequencing and applied Weighted Gene Co-expression Network Analysis. We determined that the immune response network with major hubs Tyrobp/DAP12, Csf1r, Tlr2, C1qc and Laptm5 correlated significantly and positively to the phenotype of female APP/E4-HFD mice. Correspondingly, we found that in female APP/E4-HFD mice, microglia coverage around plaques, particularly of larger size, was significantly reduced. This suggests altered containment of the plaque growth and sex-dependent vulnerability in response to diet. The results of our study show concurrent impact of diet, APOE isoform and sex on the brain transcriptome and AD-like phenotype.

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.

Dissecting the Molecular Mechanisms of Neurodegenerative Diseases through Network Biology

Neurodegenerative diseases are rarely caused by a mutation in a single gene but rather influenced by a combination of genetic, epigenetic and environmental factors. Emerging high-throughput technologies such as RNA sequencing have been instrumental in deciphering the molecular landscape of neurodegenerative diseases, however, the interpretation of such large amounts of data remains a challenge. Network biology has become a powerful platform to integrate multiple omics data to comprehensively explore the molecular networks in the context of health and disease. In this review article, we highlight recent advances in network biology approaches with an emphasis in brain-networks that have provided insights into the molecular mechanisms leading to the most prevalent neurodegenerative diseases including Alzheimer’s (AD), Parkinson’s (PD) and Huntington’s diseases (HD). We discuss how integrative approaches using multi-omics data from different tissues have been valuable for identifying biomarkers and therapeutic targets. In addition, we discuss the challenges the field of network medicine faces toward the translation of network-based findings into clinically actionable tools for personalized medicine applications.

Huntington's disease blood and brain show a common gene expression pattern and share an immune signature with Alzheimer's disease

There is widespread transcriptional dysregulation in Huntington's disease (HD) brain, but analysis is inevitably limited by advanced disease and postmortem changes. However, mutant HTT is ubiquitously expressed and acts systemically, meaning blood, which is readily available and contains cells that are dysfunctional in HD, could act as a surrogate for brain tissue. We conducted an RNA-Seq transcriptomic analysis using whole blood from two HD cohorts, and performed gene set enrichment analysis using public databases and weighted correlation network analysis modules from HD and control brain datasets. We identified dysregulated gene sets in blood that replicated in the independent cohorts, correlated with disease severity, corresponded to the most significantly dysregulated modules in the HD caudate, the most prominently affected brain region, and significantly overlapped with the transcriptional signature of HD myeloid cells. High-throughput sequencing technologies and use of gene sets likely surmounted the limitations of previously inconsistent HD blood expression studies. Our results suggest transcription is disrupted in peripheral cells in HD through mechanisms that parallel those in brain. Immune upregulation in HD overlapped with Alzheimer's disease, suggesting a common pathogenic mechanism involving macrophage phagocytosis and microglial synaptic pruning, and raises the potential for shared therapeutic approaches.

Whole genome grey and white matter DNA methylation profiles in dorsolateral prefrontal cortex

The brain's neocortex is anatomically organized into grey and white matter, which are mainly composed by neuronal and glial cells, respectively. The neocortex can be further divided in different Brodmann areas according to their cytoarchitectural organization, which are associated with distinct cortical functions. There is increasing evidence that brain development and function are governed by epigenetic processes, yet their contribution to the functional organization of the neocortex remains incompletely understood. Herein, we determined the DNA methylation patterns of grey and white matter of dorsolateral prefrontal cortex (Brodmann area 9), an important region for higher cognitive skills that is particularly affected in various neurological diseases. For avoiding interindividual differences, we analyzed white and grey matter from the same donor using whole genome bisulfite sequencing, and for validating their biological significance, we used Infinium HumanMethylation450 BeadChip and pyrosequencing in ten and twenty independent samples, respectively. The combination of these analysis indicated robust grey-white matter differences in DNA methylation. What is more, cell type-specific markers were enriched among the most differentially methylated genes. Interestingly, we also found an outstanding number of grey-white matter differentially methylated genes that have previously been associated with Alzheimer's, Parkinson's, and Huntington's disease, as well as Multiple and Amyotrophic lateral sclerosis. The data presented here thus constitute an important resource for future studies not only to gain insight into brain regional as well as grey and white matter differences, but also to unmask epigenetic alterations that might underlie neurological and neurodegenerative diseases.