Advertisement for orthosearch.org.uk
Results 1 - 3 of 3
Results per page:
Bone & Joint Research
Vol. 6, Issue 10 | Pages 572 - 576
1 Oct 2017
Wang W Huang S Hou W Liu Y Fan Q He A Wen Y Hao J Guo X Zhang F

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


Bone & Joint Research
Vol. 6, Issue 7 | Pages 439 - 445
1 Jul 2017
Sekimoto T Ishii M Emi M Kurogi S Funamoto T Yonezawa Y Tajima T Sakamoto T Hamada H Chosa E

Objectives

We have previously investigated an association between the genome copy number variation (CNV) and acetabular dysplasia (AD). Hip osteoarthritis is associated with a genetic polymorphism in the aspartic acid repeat in the N-terminal region of the asporin (ASPN) gene; therefore, the present study aimed to investigate whether the CNV of ASPN is involved in the pathogenesis of AD.

Methods

Acetabular coverage of all subjects was evaluated using radiological findings (Sharp angle, centre-edge (CE) angle, acetabular roof obliquity (ARO) angle, and minimum joint space width). Genomic DNA was extracted from peripheral blood leukocytes. Agilent’s region-targeted high-density oligonucleotide tiling microarray was used to analyse 64 female AD patients and 32 female control subjects. All statistical analyses were performed using EZR software (Fisher’s exact probability test, Pearson’s correlation test, and Student’s t-test).


Bone & Joint Research
Vol. 5, Issue 7 | Pages 314 - 319
1 Jul 2016
Xiao X Hao J Wen Y Wang W Guo X Zhang F

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.