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B16 Common disease signatures from gene expression analysis in huntington’s disease human blood and brain
  1. Eleni Mina1,
  2. Willeke van Roon-Mom1,
  3. Kristina Hettne1,
  4. Erik W van Zwet2,
  5. Jelle J Goeman2,
  6. Christian Neri3,4,
  7. Peter AC ’t Hoen1,
  8. Barend Mons1,
  9. Marco Roos1
  1. 1Department of Human Genetics, Leiden University Medical Centre, Leiden, The Netherlands
  2. 2Department of Medical Statistics and Bioinformatics, Leiden University Medical Centre, Leiden, The Netherlands
  3. 3CNRS, UMR 8256, Laboratory of Neuronal Cell Biology and Pathology, Institute of Biology Paris-Seine, Paris, France
  4. 4Sorbonnes Universites, University Pierre and Marie Curie (UPMC) Univ Paris 06, Paris, France


Background The peripheral pathology in Huntington’s disease (HD) suggests that it is possible to study such a brain disease using peripheral tissue as a monitoring tool for disease progression and/or efficacy of novel therapies.

Aims We investigated if blood can be used to monitor disease severity and progression in brain, by comparing blood and brain HD signatures in a functional context.

Methods Microarray 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. Uniquely, our comparison of blood and brain datasets was based on the similarity between the gene annotations in four different semantic categories: “biological process”, “cellular component”, “molecular function” and “disease or syndrome”.

Results We identified signatures in HD blood reflecting a broad pathophysiological spectrum, including among others alterations in the immune response, sphingolipid biosynthetic processes, RNA splicing, vesicle transport and cell signalling. 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, the immune response and genes involved in spinocerebellar ataxias.

Conclusions Our 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.

  • blood biomarkers
  • literature mining
  • gene coexpression

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