Genome-wide Association Study Identified TIMP2 Genetic Variant with Susceptibility to Osteoarthritis

Osteoarthritis (OA) is the most common degenerative joint disorder in the elderly population. To identify OA-associated genetic variants and candidate genes, we conducted a genome-wide association study (GWAS). A total 3,793 samples (476 cases: wrist + knee and 3317 controls) from a community-based epidemiological study were genotyped using the Affymetrix SNP 5.0. An intronic SNP (rs4789934) in the TIMP2 (tissue inhibitor of metalloproteinase-2) showed the most significance with OA (odd ratio [OR] = 2.06, 95% confidence interval [CI] = 1.52-2.81, p = 4.01 x 10(-6)). Furthermore, a polymorphism (rs1352677) in the NKAIN2 (Na+/K+ transporting ATPase interacting 2) was suggestively associated with OA (OR = 1.43, CI = 1.22-1.66, p = 7.01 x 10(-6)). The present study provides new insights into the identification of genetic predisposing factors for OA.

FCAnalyzer: A Functional Clustering Analysis Tool for Predicted Transcription Regulatory Elements and Gene Ontology Terms

Numerous studies have reported that genes with similar expression patterns are co-regulated. From gene expression data, we have assumed that genes having similar expression pattern would share similar transcription factor binding sites (TFBSs). These function as the binding regions for transcription factors (TFs) and thereby regulate gene expression. In this context, various analysis tools have been developed. However, they have shortcomings in the combined analysis of expression patterns and significant TFBSs and in the functional analysis of target genes of significantly overrepresented putative regulators. In this study, we present a web-based A Functional Clustering Analysis Tool for Predicted Transcription Regulatory Elements and Gene Ontology Terms (FCAnalyzer). This system integrates microarray clustering data with similar expression patterns, and TFBS data in each cluster. FCAnalyzer is designed to perform two independent clustering procedures. The first process clusters gene expression profiles using the K-means clustering method, and the second process clusters predicted TFBSs in the upstream region of previously clustered genes using the hierarchical biclustering method for simultaneous grouping of genes and samples. This system offers retrieved information for predicted TFBSs in each cluster using Match(TM) in the TRANSFAC database. We used gene ontology term analysis for functional annotation of genes in the same cluster. We also provide the user with a combinatorial TFBS analysis of TFBS pairs. The enrichment of TFBS analysis and GO term analysis is statistically by the calculation of P values based on Fisher's exact test, hypergeometric distribution and Bonferroni correction. FCAnalyzer is a web-based, user-friendly functional clustering analysis system that facilitates the transcriptional regulatory analysis of co-expressed genes. This system presents the analyses of clustered genes, significant TFBSs, significantly enriched TFBS combinations, their target genes and TFBS-TF pairs.