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Cell adhesion molecules contribute to Alzheimer’s disease: multiple pathway analyses of two genome‐wide association studies
Author(s) -
Liu Guiyou,
Jiang Yongshuai,
Wang Ping,
Feng Rennan,
Jiang Nan,
Chen Xiaoyun,
Song Hui,
Chen Zugen
Publication year - 2012
Publication title -
journal of neurochemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.75
H-Index - 229
eISSN - 1471-4159
pISSN - 0022-3042
DOI - 10.1111/j.1471-4159.2011.07547.x
Subject(s) - kegg , computational biology , hypergeometric distribution , genome wide association study , test statistic , biology , false discovery rate , encyclopedia , statistic , biological pathway , genetics , gene , bioinformatics , computer science , gene ontology , statistical hypothesis testing , single nucleotide polymorphism , gene expression , mathematics , statistics , genotype , library science
J. Neurochem. (2012) 120 , 190–198. Abstract Alzheimer’s disease (AD) is a kind of complex neurological disorder. The complex genetic architecture of AD makes genetic analysis difficult. Fortunately, a pathway‐based method to study the existing genome‐wide association studies datasets has been applied into AD. However, no shared Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway was reported. In this study, we performed multiple pathway analyses of French AD genome‐wide association studies dataset (discovery dataset, n = 7360, 2032 cases and 5328 controls) and Pfizer dataset (validation dataset, n = 2220, 1034 cases and 1186 controls). First, we performed multiple pathway analyses by Hypergeometric test, improved gene set enrichment analysis (IGSEA) and Z‐statistic test in KEGG. Using Hypergeometric test, we identified 54 and 25 significant pathways ( p < 0.05) in discovery dataset and validation dataset, respectively. Using IGSEA method, we identified three significant pathways in both discovery and validation datasets, respectively. Using Z ‐statistic test, we identified 19 significant pathways in validation dataset. Among the significant pathways, cell adhesion molecules (CAM) pathway was identified to be the only consistent signal emerging across multiple analyses in KEGG. After permutation and multiple testing corrections, CAM pathway was significant with p = 2.40E−05 (Hypergeometric test) and p = 3.00E−03 (IGSEA) in discovery dataset. In validation dataset, CAM pathway was significant with p = 1.84E−06 (Hypergeometric test), p = 1.00E−02 (IGSEA) and p = 2.81E−03 ( Z ‐statistic test). We replicated the association by multiple pathway analyses in Gene Ontology using Hypergeometric test (WebGestalt), modified Fisher’s exact test (DAVID) and Binomial test (PANTHER). Our findings provided further evidence on the association between CAM pathway and AD susceptibility, which would be helpful to study the genetic mechanisms of AD and may significantly assist in the development of therapeutic strategies.