This thesis demonstrates the application of bioinformatics to investigate the mechanisms that are implicated in Huntington’s Disease (HD). HD is an inherited neurodegenerative disorder and although... Show moreThis thesis demonstrates the application of bioinformatics to investigate the mechanisms that are implicated in Huntington’s Disease (HD). HD is an inherited neurodegenerative disorder and although the cause of the disease is known since 1993 we are still lacking a cure or treatment that can effectively treat the symptoms of HD. In order to tackle such a complicated case study, we followed a multidisciplinary approach to exploit the expertise and knowledge of people with diverse scientific background (chapter 2). This blend of disciplines facilitates constant collaboration between bioinformaticians, wet lab technicians, biologists, computer engineers and data scientists. A collaborative eScience model is proposed as a way to combine state-of-the-art computation analysis and laboratory work (chapter 3). At the same time, we explored methods to preserve the results, materials and methods involved in the experiment to increase the reproducibility and reusability of our research (chapter 4). In chapter 5 we identified disease signatures in blood that are functionally similar to signatures in brain. These are proposed as candidate biomarkers to be used as a monitoring tool for the state of the disease in brain, but also as a means to determine whether a treatment is successful or not. Show less
Mastrokolias, A.; Pool, R.; Mina, E.; Hettne, K.M.; Duijn, E. van; Mast, R.C. van der; ... ; Roon-Mom, W. van 2016
Introduction Metabolic changes have been frequently associated with Huntington's disease (HD). At the same time peripheral blood represents aminimally invasive sampling avenue with little distress... Show moreIntroduction Metabolic changes have been frequently associated with Huntington's disease (HD). At the same time peripheral blood represents aminimally invasive sampling avenue with little distress to Huntington's disease patients especially when brain or other tissue samples are difficult to collect.Objectives We investigated the levels of 163 metabolites in HD patient and control serum samples in order to identify disease related changes. Additionally, we integrated the metabolomics data with our previously published next generation sequencing-based gene expression data from the same patients in order to interconnect the metabolomics changes with transcriptional alterations. Methods This analysis was performed using targeted metabolomics and flow injection electrospray ionization tandem mass spectrometry in 133 serum samples from 97 Huntington's disease patients (29 pre-symptomatic and 68 symptomatic) and 36 controls.Results By comparing HD mutation carriers with controls we identified 3 metabolites significantly changed in HD (serine and threonine and one phosphatidylcholine-PC ae C36:0) and an additional 8 phosphatidylcholines (PC aa C38:6, PC aa C36:0, PC ae C38:0, PC aa C38:0, PC ae C38:6, PC ae C42:0, PC aa C36:5 and PC ae C36:0) that exhibited a significant association with disease severity. Using workflow based exploitation of pathway databases and by integrating our metabolomics data with our gene expression data from the same patients we identified 4 deregulated phosphatidylcholine metabolism related genes (ALDH1B1, MBOAT1, MTRR and PLB1) that showed significant association with the changes in metabolite concentrations.Conclusion Our results support the notion that phosphatidylcholine metabolism is deregulated in HD blood and that these metabolite alterations are associated with specific gene expression changes. Show less
