ArticleOrphanet journal of rare diseases2016
Common disease signatures from gene expression analysis in Huntington's disease human blood and brain.
Article in Orphanet journal of rare diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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22 citing papers in PubMed, 36 citations in OpenAlex.
- Design and evaluation of semantically-valid negative samples integration techniques for scalable semi-automated drug repurposing prediction pipelines in rare disease research.BMC bioinformatics · 2026Article
- Commentary: a review of technical considerations for planning an RNA-Sequencing experiment.BMC genomics · 2025Review
- 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.Journal of neuroinflammation · 2024Article
- Temporal changes of gene expression in health, schizophrenia, bipolar disorder, and major depressive disorder.Schizophrenia (Heidelberg, Germany) · 2024Article
- Leukocyte Telomere Length as Potential Biomarker of HD Progression: A Follow-Up Study.International journal of molecular sciences · 2022Article
- A Glimpse of Molecular Biomarkers in Huntington's Disease.International journal of molecular sciences · 2022Review
- Huntington Disease Gene Expression Signatures in Blood Compared to Brain of YAC128 Mice as Candidates for Monitoring of Pathology.Molecular neurobiology · 2022Article
- Amygdala DCX and blood Cdk14 are implicated as cross-species indicators of individual differences in fear, extinction, and resilience to trauma exposure.Molecular psychiatry · 2022Article
- Blood and brain gene expression signatures of chronic intermittent ethanol consumption in mice.PLoS computational biology · 2022Article
- Systemic manifestation and contribution of peripheral tissues to Huntington's disease pathogenesis.Ageing research reviews · 2021Review
- Statistical method for modeling sequencing data from different technologies in longitudinal studies with application to Huntington disease.Biometrical journal. Biometrische Zeitschrift · 2021Article
- Integrated Systems Analysis Explores Dysfunctional Molecular Modules and Regulatory Factors in Children with Autism Spectrum Disorder.Journal of molecular neuroscience : MN · 2021Article
- Weighted Gene Coexpression Network Analysis Reveals Essential Genes and Pathways in Bipolar Disorder.Frontiers in psychiatry · 2021Article
- Single-nucleus RNA-seq identifies Huntington disease astrocyte states.Acta neuropathologica communications · 2020Article
- RNA Sequencing of Human Peripheral Blood Cells Indicates Upregulation of Immune-Related Genes in Huntington's Disease.Frontiers in neurology · 2020Article
- Longitudinal expression changes are weak correlates of disease progression in Huntington's disease.Brain communications · 2020Article
- Genetic variants in humanin nuclear isoform gene regions show no association with coronary artery disease.BMC research notes · 2019Article
- Identification of putative regulatory regions and transcription factors associated with intramuscular fat content traits.BMC genomics · 2018Article
- Transcriptional profiling and biomarker identification reveal tissue specific effects of expanded ataxin-3 in a spinocerebellar ataxia type 3 mouse model.Molecular neurodegeneration · 2018Article
- Integrated approach reveals diet, APOE genotype and sex affect immune response in APP mice.Biochimica et biophysica acta. Molecular basis of disease · 2018Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHuntington's disease (HD) is a devastating brain disorder with no effective treatment or cure available. The scarcity of brain tissue makes it hard to study changes in the brain and impossible to perform longitudinal studies. However, peripheral pathology in HD suggests that it is possible to study the disease using peripheral tissue as a monitoring tool for disease progression and/or efficacy of novel therapies. In this study, we investigated if blood can be used to monitor disease severity and progression in brain. Since previous attempts using only gene expression proved unsuccessful, we compared blood and brain Huntington's disease signatures in a functional context.
methodsMicroarray HD gene expression profiles from three brain regions were compared to the transcriptome of HD blood generated by next generation sequencing. The comparison was performed with a combination of weighted gene co-expression network analysis and literature based functional analysis (Concept Profile Analysis). Uniquely, our comparison of blood and brain datasets was not based on (the very limited) gene overlap but on the similarity between the gene annotations in four different semantic categories: "biological process", "cellular component", "molecular function" and "disease or syndrome".
resultsWe identified signatures in HD blood reflecting a broad pathophysiological spectrum, including alterations in the immune response, sphingolipid biosynthetic processes, lipid transport, cell signaling, protein modification, spliceosome, RNA splicing, vesicle transport, cell signaling and synaptic transmission. Part of this spectrum was reminiscent of the brain pathology. The HD signatures in caudate nucleus and BA4 exhibited the highest similarity with blood, irrespective of the category of semantic annotations used. BA9 exhibited an intermediate similarity, while cerebellum had the least similarity. We present two signatures that were shared between blood and brain: immune response and spinocerebellar ataxias.
conclusionsOur results demonstrate that HD blood exhibits dysregulation that is similar to brain at a functional level, but not necessarily at the level of individual genes. We report two common signatures that can be used to monitor the pathology in brain of HD patients in a non-invasive manner. Our results are an exemplar of how signals in blood data can be used to represent brain disorders. Our methodology can be used to study disease specific signatures in diseases where heterogeneous tissues are involved in the pathology.
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