Integrating Genome-Wide Association Studies With Pathway Analysis and Gene Expression Analysis Highlights Novel Osteoarthritis Risk Pathways and Genes

Abstract

Osteoarthritis (OA) is the most common degenerative joint disorder worldwide. To identify more genetic signals, genome-wide association study (GWAS) has been widely used and elucidated some OA susceptibility genes. However, these susceptibility genes could only explain only a small part of heritability of OA. It is suggested that the identification of disease-related pathways may contribute to understand the genomic etiology of OA. Here, we integrated the GWAS into pathway analysis to identify novel OA risk pathways. In this study, we first selected 187 independent genetic variants identified by GWAS (P < 1.00E−05) and found that most of these genetic variants are noncoding mutations. We then conducted an expression quantitative trait loci analysis and found that 165 of these 187 genetic variants could significantly regulate the expression of nearby genes. Third, we identified OA susceptibility genes corresponding to these genetic variants, conducted a pathway analysis, and identified novel OA-related KEGG pathways, GO biological processes, GO molecular functions, and GO cellular components. In KEGG database, transforming growth factor β signaling pathway is the most significant signal (P = 5.98E−05) and is the only pathway after the BH multiple-test adjustment with false discovery rate (FDR) = 0.02. In GO database, we identified 24 statistically significant GO biological processes, one statistically significant GO molecular function, and five statistically significant GO cellular components (FDR < 0.05). These signals are related with chondrocyte differentiation and development, which are all known biological pathways associated with OA. Finally, we conducted an OA case–control gene expression analysis to evaluate the differential expression of these OA risk genes. Using an OA case–control gene expression analysis, we showed that 44 risk genes were suggestively differentially expressed in OA cases compared with controls (P < 0.05). Three genes, WWP2, COG5, and MAPT, were statistically differentially expressed in OA cases compared with controls (P < 0.05/122 = 4.10E−04). Hence, our findings may contribute to understanding the genomic etiology of OA.

Integrated Approaches to Identify miRNA Biomarkers Associated with Cognitive Dysfunction in Multiple Sclerosis Using Text Mining, Gene Expression, Pathways, and GWAS

“…miRSNPs have functional consequences for autoimmune diseases including MS [ 31 ]. Statistical approaches and meta-analysis of neurological diseases A recent study showed that miRSNPs have an expression quantitative trait locus (eQTL) effect on genes reported in GWAS [ 33 ], and the number of miRSNPs associated with human diseases keep increasing [ 34 , 35 ]; A recent study integrated GWAS with pathways to report novel risk pathways and genes [ 36 ]. We believe that the existing analysis on MS cognitive dysfunction can reveal the pathways and genes with common risks that are associated with the cognitive dysfunction in MS.…”