Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Ergebnis 21 von 7013

Details

Autor(en) / Beteiligte
Titel
Huntington's disease biomarker progression profile identified by transcriptome sequencing in peripheral blood
Ist Teil von
  • European journal of human genetics : EJHG, 2015-10, Vol.23 (10), p.1349-1356
Ort / Verlag
England: Nature Publishing Group
Erscheinungsjahr
2015
Link zum Volltext
Quelle
MEDLINE
Beschreibungen/Notizen
  • With several therapeutic approaches in development for Huntington's disease, there is a need for easily accessible biomarkers to monitor disease progression and therapy response. We performed next-generation sequencing-based transcriptome analysis of total RNA from peripheral blood of 91 mutation carriers (27 presymptomatic and, 64 symptomatic) and 33 controls. Transcriptome analysis by DeepSAGE identified 167 genes significantly associated with clinical total motor score in Huntington's disease patients. Relative to previous studies, this yielded novel genes and confirmed previously identified genes, such as H2AFY, an overlap in results that has proven difficult in the past. Pathway analysis showed enrichment of genes of the immune system and target genes of miRNAs, which are downregulated in Huntington's disease models. Using a highly parallelized microfluidics array chip (Fluidigm), we validated 12 of the top 20 significant genes in our discovery cohort and 7 in a second independent cohort. The five genes (PROK2, ZNF238, AQP9, CYSTM1 and ANXA3) that were validated independently in both cohorts present a candidate biomarker panel for stage determination and therapeutic readout in Huntington's disease. Finally we suggest a first empiric formula predicting total motor score from the expression levels of our biomarker panel. Our data support the view that peripheral blood is a useful source to identify biomarkers for Huntington's disease and monitor disease progression in future clinical trials.

Weiterführende Literatur

Empfehlungen zum selben Thema automatisch vorgeschlagen von bX