AUTHOR=Gao Feng , Yao Yu , Zhang Yiwei , Tian Jun 

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

JOURNAL=Frontiers in Genetics

VOLUME=Volume 10 - 2019

YEAR=2019

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2019.00827

DOI=10.3389/fgene.2019.00827

ISSN=1664-8021

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 aetiology of OA. Here, we integrated the GWAS into pathway analysis to identify novel osteoarthritis 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 non-coding mutations. We then conducted an eQTLs analysis and found that 165 of these 187 genetic variants could significantly regulate the expression of nearby genes. Third, we identified that OA susceptibility genes corresponding 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, TGF-beta signaling pathway is the most significant signal (P = 5.98E-05) and is the only pathway after the BH multiple test adjustment with 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 understand the genomic aetiology of OA.