Integrative Pathway-Based Approach for Genome-Wide Association Studies: Identification of New Pathways for Rheumatoid Arthritis and Type 1 Diabetes

Büchel, Finja; Mittag, Florian; Wrzodek, Clemens; Zell, Andreas; Gasser, Thomas; Sharma, Manu

doi:10.1371/journal.pone.0078577

Cited by 9 publications

(12 citation statements)

References 38 publications

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“…We found the majority of these 33 pathways are related to immune system ( n =17), infectious diseases ( n =8), cellular processes ( n =3). Among these pathways, there are 24 pathways to be found respectively as RA-related pathways in the pervious published studies [ 2 , 21 , 23 , 24 ]. There are 18 pathways to be identified by SNP dataset and 10 novel pathways which were not reported in pervious literatures.…”

Section: Resultsmentioning

confidence: 99%

Integrative analysis of genome-wide association studies and gene expression analysis identifies pathways associated with rheumatoid arthritis

Zhang

et al. 2016

Oncotarget

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Rheumatoid arthritis (RA) is a complex and systematic autoimmune disease, which is usually influenced by both genetic and environmental factors. Pathway analyses based on a single data type such as microarray data or SNP data have successfully revealed some biology pathways associated with RA. However, we found that the pathway analysis based on a single data type only provide limited understanding about the pathogenesis of RA. Gene-disease association is usually caused by many ways, such as genotype, gene expression and so on. Therefore, the integrative analysis method combining multiple levels of evidence can more precisely and comprehensively identify the pathway associations. In this study, we performed a pathway analysis by integrating GWAS and gene expression analysis to detect the RA-related pathways. The integrative analysis identified 28 pathways associated with RA. Among these pathways, 18 pathways were also found by both GWAS and gene expression analysis, 7 pathways are novel RA-related pathways, such as B cell receptor signaling pathway, Toll-like receptor signaling pathway, Fc gamma R-mediated phagocytosis and so on. Compared with pathway analyses using only one type genomic data, we found integrative analysis can increase the power to identify the real associations and provided more stable and accurate results. We believe these results will contribute to perform future genetic studies in RA pathogenesis and may promote the development of new therapeutic strategies by targeting these pathways.

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Section: Resultsmentioning

confidence: 99%

Integrative analysis of genome-wide association studies and gene expression analysis identifies pathways associated with rheumatoid arthritis

Zhang

et al. 2016

Oncotarget

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“…In these pathways, six risk pathways were reported to be associated with RA in previous literatures. 6,17,18,20 This indicated that this method is effective on identifying the RA-risk pathways.…”

Section: Consistency Analysis Of Two Permutation Methodsmentioning

confidence: 87%

“…All 19 pathways had been proven to be RA-related risk pathways in the literatures. 6,7,[16][17][18]21 The results also indicated that it was effective and feasible to use all SNP to identify risk pathways.…”

Section: Consistency Analysis Of Two Permutation Methodsmentioning

confidence: 90%

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Pathway-based association analysis of two genome-wide screening data identifies rheumatoid arthritis-related pathways

Jiang

et al. 2014

Genes Immun

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The pathways can explain molecular mechanisms of complex diseases from the perspective of biology function. We carried out a genome-wide pathway-based association analysis to identify the risk pathways of rheumatoid arthritis (RA). First, we performed two genome-wide association studies using two RA data sets from GAW16 (Genetic Analysis Workshop 16) and the Wellcome Trust Case Control Consortium, and obtained risk P-value for each single-nucleotide polymorphism (SNP). Next, we mapped all the SNPs to genome-wide autosomal genes and calculated gene-wise risk values by minimum P-value method. We calculated the KEGG (Kyoto Encyclopedia of Gene and Genomes) pathway risk scores according to Fisher combination method and identified the significant pathways by permutation test. At last, we merged the results from the two pathway-based genome-wide association analyses to identify the high-risk pathways, which were found in both the data sets. The results showed that there were nine pathways, focal adhesion pathway, extracellular matrix-receptor interaction pathway, calcium signaling pathway, dopaminergic synapse pathway, long-term potentiation pathway, retrograde endocannabinoid signaling pathway, glutamatergic synapse pathway, cholinergic synapse pathway and morphine addiction pathway, associated with susceptibility to RA. Among these pathways, four pathways were reported as RA-risk pathways in the previous literatures. We also inferred that other five pathways may be related to RA. Further researches of these pathways will help us to understand the molecular mechanisms of RA.

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“…A promising direction is to perform unbiased, large-scale integrative studies of multi -omics data as the molecular interplay among these axes remains largely underexplored. These integrative approaches have already demonstrated a potential to dissect the complexity and to identify the underlying regulators of other complex diseases such as Alzeheimer's disease (82), type I diabetes (83), and breast cancer (84) and may provide a useful strategy to fulfill these unmet needs.…”

Section: Resultsmentioning

confidence: 99%

Linking childhood allergic asthma phenotypes with endotype through integrated systems biology: current evidence and research needs

Choi

Song

Zhang

2017

Reviews on Environmental Health

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Abstract Asthma and other complex diseases results from a complex web of interactions involving inflammation, immunity, cell cycle, apoptosis, and metabolic perturbations across multiple organ systems. The extent to which various degrees of the age at onset, symptom severity, and the natural progression of the disease reflect multiple disease subtypes, influenced by unique process of development remains unknown. One of the most critical challenges to our understanding stems from incomplete understanding of the mechanisms. Within this review, we focus on the phenotypes of childhood allergic asthma as the basis to better understand the endotype for quantitative define subtypes of asthma. We highlight some of the known mechanistic pathways associated with the key hallmark events before the asthma onset. In particular, we examine how the recent advent of multiaxial -omics technologies and systems biology could help to clarify our current understanding of the pathway. We review how a large volume of molecular, genomic data generated by multiaxial technologies could be digested to identify cogent pathophysiologic molecular networks. We highlight some recent successes in application of these technologies within the context of other disease conditions for therapeutic interventions. We conclude by summarizing the research needs for the predictive value of preclinical biomarkers.

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Integrative Pathway-Based Approach for Genome-Wide Association Studies: Identification of New Pathways for Rheumatoid Arthritis and Type 1 Diabetes

Cited by 9 publications

References 38 publications

Integrative analysis of genome-wide association studies and gene expression analysis identifies pathways associated with rheumatoid arthritis

Integrative analysis of genome-wide association studies and gene expression analysis identifies pathways associated with rheumatoid arthritis

Pathway-based association analysis of two genome-wide screening data identifies rheumatoid arthritis-related pathways

Linking childhood allergic asthma phenotypes with endotype through integrated systems biology: current evidence and research needs

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