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

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 pathwaypatient association.

[1]  I. Mook‐Jung,et al.  Acute ER stress regulates amyloid precursor protein processing through ubiquitin-dependent degradation , 2015, Scientific Reports.

[2]  C. Behl,et al.  Protein Homeostasis, Aging and Alzheimer’s Disease , 2012, Molecular Neurobiology.

[3]  Margaret A. Pericak-Vance,et al.  Genome-Wide Association Meta-analysis of Neuropathologic Features of Alzheimer's Disease and Related Dementias , 2014, PLoS genetics.

[4]  William E. Balch,et al.  Integration of endoplasmic reticulum signaling in health and disease , 1999, Nature Medicine.

[5]  M. Folstein,et al.  Clinical diagnosis of Alzheimer's disease , 1984, Neurology.

[6]  Daniel S. Himmelstein,et al.  Understanding multicellular function and disease with human tissue-specific networks , 2015, Nature Genetics.

[7]  Kazuhiro Nagata,et al.  Protein folding and quality control in the ER. , 2012, Cold Spring Harbor perspectives in biology.

[8]  Keith S. Sheppard,et al.  Discovery of novel variants in genotyping arrays improves genotype retention and reduces ascertainment bias , 2012, BMC Genomics.

[9]  Kazuhiko Yanai,et al.  Pathobiology of Alzheimer's disease and biomarker development. , 2010, Nihon yakurigaku zasshi. Folia pharmacologica Japonica.

[10]  Daniele Ghezzi,et al.  Mitochondrial dysfunction in Parkinson disease: evidence in mutant PARK2 fibroblasts , 2015, Front. Genet..

[11]  Muin J Khoury,et al.  A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes , 2013, European Journal of Human Genetics.

[12]  Lars Bertram,et al.  The genetics of Alzheimer's disease. , 2012, Progress in molecular biology and translational science.

[13]  C. Lendon,et al.  A common biological mechanism in cancer and Alzheimer's disease? , 2009, Current Alzheimer research.

[14]  Dominique Drouin,et al.  Toward an Alzheimer's disease diagnosis via high-resolution blood gene expression , 2010, Alzheimer's & Dementia.

[15]  Lihua Zhang,et al.  Parkin promotes intracellular Abeta1-42 clearance. , 2009, Human molecular genetics.

[16]  R. Petersen Mild cognitive impairment as a diagnostic entity , 2004, Journal of internal medicine.

[17]  Springer-Verlag Italia Genome-wide pathway analysis of a genome-wide association study on Alzheimer's disease , 2015 .

[18]  Fan Zhang,et al.  IPAD: the Integrated Pathway Analysis Database for Systematic Enrichment Analysis , 2012, BMC Bioinformatics.

[19]  Francisco Vives,et al.  Analysis of the genetic variability in Parkinson's disease from Southern Spain , 2016, Neurobiology of Aging.

[20]  C. Putterman,et al.  Neuropsychiatric Lupus, the Blood Brain Barrier, and the TWEAK/Fn14 Pathway , 2013, Front. Immunol..