Annals of Indian Academy of Neurology
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Year : 2013  |  Volume : 16  |  Issue : 1  |  Page : 72-74

Physiological genomics analysis for Alzheimer's disease

Wiwanitkit House, Bangkhae, Bangkok, Thailand

Correspondence Address:
Viroj Wiwanitkit
Wiwanitkit House, Bangkhae, Bangkok-10160
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0972-2327.107711

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Alzheimer's disease is a common kind of dementia. This disorder can be detected in all countries around the world. This neurological disorder affects millions of population and becomes an important concern in modern neurology. There are many researches on the pathogenesis of Alzheimer's disease. Although it has been determined for a long time, there is no clear-cut that this is a case with genetic disorder or not. A physiological genomics is a new application that is useful for track function to genes within the human genome and can be applied for answering the problem of underlying pathobiology of complex diseases. The physiogenomics can be helpful for study of systemic approach on the pathophysiology, and genomics might provide useful information to better understand the pathogenesis of Alzheimer's disease. The present advent in genomics technique makes it possible to trace for the underlying genomics of disease. In this work, physiological genomics analysis for Alzheimer's disease was performed. The standard published technique is used for assessment. According to this work, there are 20 identified physiogenomics relationship on several chromosomes. Considering the results, the HADH2 gene on chromosome X, APBA1 gene on chromosome 9, AGER gene on chromosome 6, GSK3B gene on chromosome 3, CDKHR1 gene on chromosome 17, APPBP1 gene on chromosome 16, APBA2 gene on chromosome 15, GAL gene on chromosome 11, and APLP2 gene on chromosome 11 have the highest physiogenomics score (9.26) while the CASP3 gene on chromosome 4 and the SNCA gene on chromosome 4 have the lowest physiogenomics score (7.44). The results from this study confirm that Alzheimer's disease has a polygenomic origin.

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