Implication of the Immune System in Alzheimer's Disease: Evidence from Genome-Wide Pathway Analysis

Lambert, Jean‐Charles; Grenier‐Boley, Benjamin; Chouraki, Vincent; Heath, Simon; Zélénika, Diana; Fiévet, Nathalie; Hannequin, Didier; Pasquier, Florence; Hanon, Olivier; Brice, Alexis; Epelbaum, Jacques; Berr, Claudine; Dartigues, Jean‐François; Tzourio, Christophe; Campion, Dominique; Lathrop, Mark; Amouyel, Philippe

doi:10.3233/jad-2010-100018

Cited by 133 publications

(135 citation statements)

References 37 publications

(34 reference statements)

Supporting

Mentioning

119

Contrasting

Order By: Relevance

“…A large proportion of AD heritability has yet to be explained. Fortunately, the existing large-scale GWAS datasets provide strong support for the investigation of AD mechanisms using pathway analysis methods [4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Integrating Genome-Wide Association Study and Brain Expression Data Highlights Cell Adhesion Molecules and Purine Metabolism in Alzheimer’s Disease

Zhang

Liao

et al. 2014

Mol Neurobiol

View full text Add to dashboard Cite

Alzheimer's disease (AD) is the most common neurodegenerative disease in the elderly. Recently, genome-wide association studies (GWAS) have been used to investigate AD pathogenesis. However, a large proportion of AD heritability has yet to be explained. We previously identified the cell adhesion molecule (CAM) pathway as a consistent signal in two AD GWAS. However, it is unclear whether CAM is present in the Genetic and Environmental Risk for Alzheimer's Disease Consortium (GERAD) GWAS and brain expression GWAS. Meanwhile, we think integrating AD GWAS and AD brain expression datasets may provide complementary information to identify important pathways involved in AD. Here, we conducted a systems analysis using (1) KEGG pathways, (2) large-scale AD GWAS from GERAD (n = 11,789), (3) two brain expression GWAS datasets (n = 399) from the AD cerebellum and temporal cortex, and (4) previous results from pathway analysis of AD GWAS. Our results indicate that (1) CAM is a consistent signal in five AD GWAS; (2) CAM is the most significant signal in AD; (3) we confirmed previous AD risk pathways related to immune system and diseases, and cardiovascular disease, etc.; and (4) we highlighted the purine metabolism pathway in AD for the first time. We believe that our results may advance our understanding of AD mechanisms and will be very informative for future genetic studies in AD.

show abstract

Section: Introductionmentioning

confidence: 99%

Integrating Genome-Wide Association Study and Brain Expression Data Highlights Cell Adhesion Molecules and Purine Metabolism in Alzheimer’s Disease

Zhang

Liao

et al. 2014

Mol Neurobiol

View full text Add to dashboard Cite

show abstract

“…6 GSA methods were first introduced in the context of gene expression (microarray) data analysis [10][11][12] but have since been extended to other data types, in particular to SNP data from GWAS. [13][14][15] GSA for GWAS has recently been used to investigate many common diseases including breast cancer, 16 Alzheimer's disease, 17 multiple sclerosis, 18 bone mineral density, 19 hypertension, type 1 and 2 diabetes, and coronary artery disease. 20 Such studies are leading to novel insights into the etiology of common diseases and possible relationships between diseases that were not detected using the individual SNP analysis approach.…”

Section: Introductionmentioning

confidence: 99%

Gene set analysis of SNP data: benefits, challenges, and future directions

2011

View full text Add to dashboard Cite

The last decade of human genetic research witnessed the completion of hundreds of genome-wide association studies (GWASs). However, the genetic variants discovered through these efforts account for only a small proportion of the heritability of complex traits. One explanation for the missing heritability is that the common analysis approach, assessing the effect of each singlenucleotide polymorphism (SNP) individually, is not well suited to the detection of small effects of multiple SNPs. Gene set analysis (GSA) is one of several approaches that may contribute to the discovery of additional genetic risk factors for complex traits. Complex phenotypes are thought to be controlled by networks of interacting biochemical and physiological pathways influenced by the products of sets of genes. By assessing the overall evidence of association of a phenotype with all measured variation in a set of genes, GSA may identify functionally relevant sets of genes corresponding to relevant biomolecular pathways, which will enable more focused studies of genetic risk factors. This approach may thus contribute to the discovery of genetic variants responsible for some of the missing heritability. With the increased use of these approaches for the secondary analysis of data from GWAS, it is important to understand the different GSA methods and their strengths and weaknesses, and consider challenges inherent in these types of analyses. This paper provides an overview of GSA, highlighting the key challenges, potential solutions, and directions for ongoing research.

show abstract

“…This is in general a complicated task as there is no gold standard and available databases may lack sufficient detail 36 and accordance in the pathway composition. 50 Consequently, it is possible that some relevant genetic variation is not covered in the present study.…”

Section: Discussionmentioning

confidence: 79%

Human longevity and variation in DNA damage response and repair: study of the contribution of sub-processes using competitive gene-set analysis

Debrabant

Soerensen

Flachsbart³

et al. 2014

Eur J Hum Genet

View full text Add to dashboard Cite

DNA-damage response and repair are crucial to maintain genetic stability, and are consequently considered central to aging and longevity. Here, we investigate whether this pathway overall associates to longevity, and whether specific sub-processes are more strongly associated with longevity than others. Data were applied on 592 SNPs from 77 genes involved in nine sub-processes: DNA-damage response, base excision repair (BER), nucleotide excision repair, mismatch repair, non-homologous end-joining, homologous recombinational repair (HRR), RecQ helicase activities (RECQ), telomere functioning and mitochondrial DNA processes. The study population was 1089 long-lived and 736 middle-aged Danes. A self-contained set-based test of all SNPs displayed association with longevity (P-value ¼ 9.9 Â 10 À5 ), supporting that the overall pathway could affect longevity. Investigation of the nine sub-processes using the competitive gene-set analysis by Wang et al indicated that BER, HRR and RECQ associated stronger with longevity than the respective remaining genes of the pathway (P-values ¼ 0.004-0.048). For HRR and RECQ, only one gene contributed to the significance, whereas for BER several genes contributed. These associations did, however, generally not pass correction for multiple testing. Still, these findings indicate that, of the entire pathway, variation in BER might influence longevity the most. These modest sized P-values were not replicated in a German sample. This might, though, be due to differences in genotyping procedures and investigated SNPs, potentially inducing differences in the coverage of gene regions. Specifically, five genes were

show abstract

Implication of the Immune System in Alzheimer's Disease: Evidence from Genome-Wide Pathway Analysis

Cited by 133 publications

References 37 publications

Integrating Genome-Wide Association Study and Brain Expression Data Highlights Cell Adhesion Molecules and Purine Metabolism in Alzheimer’s Disease

Integrating Genome-Wide Association Study and Brain Expression Data Highlights Cell Adhesion Molecules and Purine Metabolism in Alzheimer’s Disease

Gene set analysis of SNP data: benefits, challenges, and future directions

Human longevity and variation in DNA damage response and repair: study of the contribution of sub-processes using competitive gene-set analysis

Contact Info

Product

Resources

About