Projects / Programmes source: ARIS

Genomic approach to neurodegenerative diseases

Research activity

Code Science Field Subfield
3.05.00  Medical sciences  Human reproduction   

Code Science Field
B790  Biomedical sciences  Clinical genetics 
Neurodegenerative diseases, Huntington's disease, genomics, genetic biomarker, expression profile
Evaluation (rules)
source: COBISS
Researchers (18)
no. Code Name and surname Research area Role Period No. of publicationsNo. of publications
1.  04041  PhD Jurček Dimec  Computer science and informatics  Researcher  2008  101 
2.  20006  Paula Duff    Technical associate  2007 - 2008 
3.  11373  PhD Dimitar Hristovski  Computer science and informatics  Researcher  2005  146 
4.  26061  PhD Helena Jaklič  Human reproduction  Researcher  2005 - 2008  36 
5.  26484  PhD Andrej Kastrin  Medical sciences  Junior researcher  2005 - 2008  146 
6.  10693  PhD Jan Kobal  Neurobiology  Researcher  2005 - 2008  144 
7.  23434  PhD Luca Lovrečić  Human reproduction  Researcher  2005 - 2008  164 
8.  15356  PhD Igor Medica  Human reproduction  Researcher  2005 - 2008  49 
9.  10458  PhD Borut Peterlin  Human reproduction  Head  2005 - 2008  833 
10.  11252  PhD Danijel Petrovič  Cardiovascular system  Researcher  2005 - 2008  313 
11.  28621  Bernarda Prosenc  Human reproduction  Technical associate  2007 - 2008 
12.  21133  MSc Gorazd Rudolf  Human reproduction  Researcher  2005 - 2008  51 
13.  23076  Andrej Stegnar    Technical associate  2005 - 2008 
14.  15149  PhD Nataša Teran  Human reproduction  Researcher  2005 - 2008  96 
15.  12245  Alenka Veble  Human reproduction  Researcher  2005 - 2008  70 
16.  17837  PhD Gaj Vidmar  Systems and cybernetics  Researcher  2006 - 2007  545 
17.  26331  Marija Volk  Human reproduction  Researcher  2006 - 2008  83 
18.  19449  PhD Branko Zorn  Human reproduction  Researcher  2005 - 2008  307 
Organisations (2)
no. Code Research organisation City Registration number No. of publicationsNo. of publications
1.  0312  University Medical Centre Ljubljana  Ljubljana  5057272000  76,701 
2.  0381  University of Ljubljana, Faculty of Medicine  Ljubljana  1627066  47,547 
All neurodegenerative diseases are characterized by progressive degeneration of neurons which cannot be monitered in vivo. The degeneration itself begins long before the symptoms develop and this symptomless time period of the disease gives us an important opportunity for therapeutic intervention in the sense of delaying the progress of the disease. To evaluate the stage of neurodegeneration, more detailed knowledge of pathogenesis is needed and specific and sensitive biomarkers, also. A neurodegenerative disease where we are able to identify the patients before the symptoms start, is Huntington's disease (HD). One of the recently widely accepted hypothesis explains HD pathogenesis in relation to transcriptional deregulation, which has been shown in central nervous system and muscle tissue in cell and animal models of HD. Since mutant huntigtin and related transcriptional factors show ubiquitous distribution in all tissues, we postulate that transcriptional impairments in HD may also exist in peripheral blood and that we will find differences in expression profiles of carriers of HD mutation compared to healthy control subjects. With use of statistics and bioinformatics to analyze the differences in global gene expression of HD mutation carriers compared to healthy control subject, we expect to find specific genetic biomarkers. Biomarkers would enable us to better understand pathogenesis of HD, to speculate about start and progression of HD and in the future also to evaluate response to potential new treatments. In relation to overlap of clinical symptoms and some known pathogenetic pathways in neurodegenerative disorders, we speculate that it is possible to find more specific genetic biomarkers characteristic of different neurodegenerative disorders. In order to test this hypothesis we plan to generate database of expression changes in selected neurodegenerative disorders (HD, Alzheimer's disease, Parkinson's disease, spinocerecellar ataxia). We will try to identify common biomarkers with use of data mining and literature-based discovery.
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