Objectives. The molecular mechanism of rheumatoid arthritis (RA) remains elusive. We conducted a protein-protein interaction network-based integrative analysis of genome-wide association studies (GWAS) and gene expression profiles of RA. Methods. We first performed a dense search of RA-associated gene modules by integrating a large GWAS meta-analysis dataset (containing 5539 RA patients and 20 169 healthy controls), protein interaction network and gene expression profiles of RA synovium and peripheral blood mononuclear cells (PBMCs). Gene ontology (GO) enrichment analysis was conducted by DAVID. The protein association networks of gene modules were generated by STRING. Results. For RA synovium, the top-ranked gene module is HLA-A, containing TAP2, HLA-A, HLA-C, TAPBP and LILRB1 genes. For RA PBMCs, the top-ranked gene module is GRB7, consisting of HLA-DRB5, HLA-DRA, GRB7, CD63 and KIT genes. Functional enrichment analysis identified three significant GO terms for RA synovium, including antigen processing and presentation of peptide antigen via major histocompatibility complex class I (false discovery rate (FDR) = 4.86 × 10 – 4), antigen processing and presentation of peptide antigen (FDR = 2.33 × 10 – 3) and eukaryotic translation initiation factor 4F complex (FDR = 2.52 × 10 – 2). Conclusion. This study reported several RA-associated gene modules and their functional association networks. Cite this article: X. Xiao, J. Hao, Y. Wen, W. Wang, X. Guo, F. Zhang. Genome-wide association studies and gene expression profiles of rheumatoid arthritis: an analysis. Bone Joint Res 2016;5:314–319. DOI: 10.1302/2046-3758.57.2000502

Heterotopic ossification (HO) is lamellar bone formation that occurs within tissues that do not normally have properties of ossification. The pathoaetiology of HO is poorly understood. We conducted a genome wide association study to better understand the genetic architecture of HO.

891 patients of European descent (410 HO cases) following THA for primary osteoarthritis were recruited from the UK. HO was assessed from plain AP radiographs of the pelvis. Genomic DNA was extracted, genotyped using the Illumina 610 beadchip and referenced using the 1000 Genome Project panel. HO susceptibility case-control analysis and an evaluation of disease severity in those with HO was undertaken using SNPTESTv2.3.0 on>10 million variants. We tested variants most strongly associated with HO in an independent UK THA replication cohort comprising 209 cases and 211 controls. The datasets were meta-analysed using PLINK.

In the discovery cohort 70 signals with an index variant at p<9×10–5 were suggestively associated with HO susceptibility. The strongest signal lay just downstream of the gene ARHGAP18 (rs59084763, effect allele frequency (EAF) 0.19, OR1.87 [1.48–2.38], p=2.48×10–8), the second strongest signal lay within the long non-coding (LNC) RNA gene CASC20 (rs11699612, EAF 0.25, OR1.73 [1.1.40–2.16, p=9.3×10–8). In the discovery cohort 73 signals with an index variant at p<9×10–5 were associated with HO severity. At replication, 12 of the leading 14 susceptibility signals showed a concordant direction of allelic effect and 5 replicated at nominal significance. Following meta-analysis, the lead replicating susceptibility signal was the CASC20 variant rs11699612 (p=2.71×10–11).

We identify consistent replicating association of variation within the LNC RNA CASC20 with HO susceptibility after THA. Although the function of CASC20 is currently unknown, possible mechanisms include transcriptional, post-transcriptional and epigenetic regulation of downstream target genes. The work presented here provides new avenues for the development of novel predictive and therapeutic approaches towards HO.

Objectives. Several genome-wide association studies (GWAS) of bone mineral density (BMD) have successfully identified multiple susceptibility genes, yet isolated susceptibility genes are often difficult to interpret biologically. The aim of this study was to unravel the genetic background of BMD at pathway level, by integrating BMD GWAS data with genome-wide expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (meQTLs) data. Method. We employed the GWAS datasets of BMD from the Genetic Factors for Osteoporosis Consortium (GEFOS), analysing patients’ BMD. The areas studied included 32 735 femoral necks, 28 498 lumbar spines, and 8143 forearms. Genome-wide eQTLs (containing 923 021 eQTLs) and meQTLs (containing 683 152 unique methylation sites with local meQTLs) data sets were collected from recently published studies. Gene scores were first calculated by summary data-based Mendelian randomisation (SMR) software and meQTL-aligned GWAS results. Gene set enrichment analysis (GSEA) was then applied to identify BMD-associated gene sets with a predefined significance level of 0.05. Results. We identified multiple gene sets associated with BMD in one or more regions, including relevant known biological gene sets such as the Reactome Circadian Clock (GSEA p-value = 1.0 × 10. -4. for LS and 2.7 × 10. -2. for femoral necks BMD in eQTLs-based GSEA) and insulin-like growth factor receptor binding (GSEA p-value = 5.0 × 10. -4. for femoral necks and 2.6 × 10. -2. for lumbar spines BMD in meQTLs-based GSEA). Conclusion. Our results provided novel clues for subsequent functional analysis of bone metabolism, and illustrated the benefit of integrating eQTLs and meQTLs data into pathway association analysis for genetic studies of complex human diseases. Cite this article: W. Wang, S. Huang, W. Hou, Y. Liu, Q. Fan, A. He, Y. Wen, J. Hao, X. Guo, F. Zhang. Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density. Bone Joint Res 2017;6:572–576

Objectives

In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis.