Mining and mapping of protein-protein interaction associated with dementia and related diseases
Dementia is a multi-causal syndrome caused by various types of neurodegenerative diseases. Symptoms of dementia include short memory, muscle contraction, poor judgement and it is the effect caused by gradual brain cell death. There is a need to understand the fundamental causes of this syndrome as d...
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| 格式: | Thesis |
| 语言: | English |
| 出版: |
2013
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| 主题: | |
| 在线阅读: | http://eprints.utm.my/id/eprint/33224/5/LeeSheauChenMFBSK2013.pdf |
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| 总结: | Dementia is a multi-causal syndrome caused by various types of neurodegenerative diseases. Symptoms of dementia include short memory, muscle contraction, poor judgement and it is the effect caused by gradual brain cell death. There is a need to understand the fundamental causes of this syndrome as dementia is historically well-documented with new cases increasing steadily every year yet it is still incurable. In this study, protein-protein interaction in diseases that have been shown to be associated with dementia such as Alzheimer's disease, Parkinson's disease, and Huntington's disease were mined and mapped. Results indicated that, nine proteins are found to be interconnected between four different diseases. Six out of nine proteins that belong to Fatal Familial Insomnia are also found in Creutzfeldt-Jakob disease. Although Alzheimer’s disease has the most complex interaction map, only two proteins coexist in Frontotemporal Dementia and one protein in Creutzfeldt-Jakob disease. The interaction data of diabetes, hypertension and hypercholesterolemia were also mapped by adding into the map and seven proteins were found to be associated with Alzheimer’s disease and two proteins with Parkinson’s disease. The interconnector proteins were examined in gene co-expression database and some of the functional interactions were found to interact physically. Proteins that interact physically will initiate a reaction while functional interaction shows co-expression of some proteins on a specific location at a time. These results demonstrated how the combination of the protein-protein interaction data and functional interaction data obtained from gene coexpression database was useful to predict their possible relationship, in which the functional interactions are potentially interacting physically. This study allowed the prediction of protein-protein interaction through the combination of functional interaction and physical interaction as a methodology in proteomic studies. |
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