Risk-associated and pathway-based method to detect association with Alzheimer's disease

Jeffrey Mitchel, Laszlo Prokai, Youping Deng, Fan Zhang, Robert Clinton Barber

Research output: Contribution to journalEditorialResearch

Abstract

Genes do not function alone but through complex biological pathways in complex diseases such as Alzheimer's disease (AD). Unravelling these intricate pathways is essential to understanding biological mechanisms of the AD. Based on the integrated pathway analysis database (IPAD), we developed a pathway-based method to detect association with the AD. First, we performed risk associated allele analysis to determine if a major or minor allele is associated with risk. Then we performed pathway-disease association analysis to identify 133 AD-associated pathways. Lastly, we performed pathway-patient association analysis to investigate the patient's association and distribution among the 133 pathways. We found five AD-associated pathways that have the highest association with patients. We present a pathway-based method to detect AD-associated pathways from GWAS data. Our pathway-based analysis not only provides a technique to identify disease-associated pathways, but also help determine the pathway-patient association.

Original languageEnglish
JournalInternational Journal of Computational Biology and Drug Design
Volume11
Issue number1-2
DOIs
StatePublished - 1 Jan 2018

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Alzheimer Disease
Alleles
Genome-Wide Association Study
Databases
Genes

Keywords

  • Alzheimer's disease
  • Biomarker discovery
  • Pathway analysis

Cite this

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title = "Risk-associated and pathway-based method to detect association with Alzheimer's disease",
abstract = "Genes do not function alone but through complex biological pathways in complex diseases such as Alzheimer's disease (AD). Unravelling these intricate pathways is essential to understanding biological mechanisms of the AD. Based on the integrated pathway analysis database (IPAD), we developed a pathway-based method to detect association with the AD. First, we performed risk associated allele analysis to determine if a major or minor allele is associated with risk. Then we performed pathway-disease association analysis to identify 133 AD-associated pathways. Lastly, we performed pathway-patient association analysis to investigate the patient's association and distribution among the 133 pathways. We found five AD-associated pathways that have the highest association with patients. We present a pathway-based method to detect AD-associated pathways from GWAS data. Our pathway-based analysis not only provides a technique to identify disease-associated pathways, but also help determine the pathway-patient association.",
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Risk-associated and pathway-based method to detect association with Alzheimer's disease. / Mitchel, Jeffrey; Prokai, Laszlo; Deng, Youping; Zhang, Fan; Barber, Robert Clinton.

In: International Journal of Computational Biology and Drug Design, Vol. 11, No. 1-2, 01.01.2018.

Research output: Contribution to journalEditorialResearch

TY - JOUR

T1 - Risk-associated and pathway-based method to detect association with Alzheimer's disease

AU - Mitchel, Jeffrey

AU - Prokai, Laszlo

AU - Deng, Youping

AU - Zhang, Fan

AU - Barber, Robert Clinton

PY - 2018/1/1

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N2 - Genes do not function alone but through complex biological pathways in complex diseases such as Alzheimer's disease (AD). Unravelling these intricate pathways is essential to understanding biological mechanisms of the AD. Based on the integrated pathway analysis database (IPAD), we developed a pathway-based method to detect association with the AD. First, we performed risk associated allele analysis to determine if a major or minor allele is associated with risk. Then we performed pathway-disease association analysis to identify 133 AD-associated pathways. Lastly, we performed pathway-patient association analysis to investigate the patient's association and distribution among the 133 pathways. We found five AD-associated pathways that have the highest association with patients. We present a pathway-based method to detect AD-associated pathways from GWAS data. Our pathway-based analysis not only provides a technique to identify disease-associated pathways, but also help determine the pathway-patient association.

AB - Genes do not function alone but through complex biological pathways in complex diseases such as Alzheimer's disease (AD). Unravelling these intricate pathways is essential to understanding biological mechanisms of the AD. Based on the integrated pathway analysis database (IPAD), we developed a pathway-based method to detect association with the AD. First, we performed risk associated allele analysis to determine if a major or minor allele is associated with risk. Then we performed pathway-disease association analysis to identify 133 AD-associated pathways. Lastly, we performed pathway-patient association analysis to investigate the patient's association and distribution among the 133 pathways. We found five AD-associated pathways that have the highest association with patients. We present a pathway-based method to detect AD-associated pathways from GWAS data. Our pathway-based analysis not only provides a technique to identify disease-associated pathways, but also help determine the pathway-patient association.

KW - Alzheimer's disease

KW - Biomarker discovery

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