Cell adhesion molecules contribute to Alzheimer's disease: multiple pathway analyses of two genome-wide association studies.
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.
Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, China. liuguiyou1981@163.com
Guiyou
G
Liu
Yongshuai
Y
Jiang
Ping
P
Wang
Rennan
R
Feng
Nan
N
Jiang
Xiaoyun
X
Chen
Hui
H
Song
Zugen
Z
Chen
D000465:Algorithms; D000544:Alzheimer Disease / Q000235:genetics / Q000503:physiopathology*; D015815:Cell Adhesion Molecules / Q000235:genetics / Q000502:physiology*; D057225:Data Mining; D030541:Databases, Genetic; D039721:Diagnostic and Statistical Manual of Mental Disorders; D005260:Female; D005602:France; D020022:Genetic Predisposition to Disease / Q000235:genetics; D055106:Genome-Wide Association Study; D006801:Humans; D008297:Male; D020641:Polymorphism, Single Nucleotide; D015203:Reproducibility of Results; D015398:Signal Transduction / Q000235:genetics* / Q000502:physiology*
D015815:Cell Adhesion Molecules