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D08 A Holistic Network Analysis Of Gene Expression Data In Huntington’s Disease Patients Reveals A Common Signature Of Transcriptional Dysregulation
  1. A Neueder,
  2. GP Bates
  1. King’s College London, 8th Floor Tower Wing, Guy’s Hospital, SE1 9RT London, UK

Abstract

Background Huntington’s disease (HD) belongs to the group of poly-glutamine repeat expansion diseases, which is the most common form of inherited neurodegenerative diseases. Transcriptional dysregulation, or a global change in gene expression is a hallmark of many neurodegenerative diseases. For HD there is some evidence in patients and mouse models that these changes already occur in the prodromal stage, which could make them useful to define disease progression on a molecular level, or even as potential biomarkers for therapeutics.

Aim Here, we used weighted gene correlation network analysis (WGCNA) to study the transcriptional dysregulation in HD.

Methods We constructed and compared networks for 4 different brain regions of patient samples and analysed their preservation in gene expression datasets of other diseases, as well as in mouse models of HD. We furthermore constructed consensus networks of HD and various other diseases to highlight commonly changed pathways.

Results We identified a very similar signature of transcriptional dysregulation in 3 brain areas of HD patients, including the cerebellum, which is in general less affected by pathological changes.

KeyWords
  • transcriptional dysregulation
  • weighted gene correlation network analysis
  • biomarker

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