Genome-Wide Association Study and Transcriptome of Japanese Patients with Developmental Dysplasia of the Hip Demonstrates an Association with the Ferroptosis Signaling Pathway.

This study examined the association between developmental dysplasia of the hip (DDH) and disease-associated loci in a Japanese cohort. A genome-wide association study (GWAS) of 238 Japanese patients with DDH and 2044 healthy individuals was performed. As a replicate, GWAS was also conducted on the UK Biobank data with 3315 cases and matched 74,038 controls. Gene set enrichment analyses (GSEAs) of both the genetics and transcriptome of DDH were performed. Transcriptome analysis of cartilage specimens from DDH-associated osteoarthritis and femoral neck fractures was performed as a control. Most of the lead variants were very low-frequency ones in the UK, and variants in the Japanese GWAS could not be replicated with the UK GWAS. We assigned DDH-related candidate variants to 42 and 81 genes from the Japanese and UK GWASs, respectively, using functional mapping and annotation. GSEA of gene ontology, disease ontology, and canonical pathways identified the most enriched pathway to be the ferroptosis signaling pathway, both in the Japanese gene set as well as the Japanese and UK merged set. Transcriptome GSEA also identified significant downregulation of genes in the ferroptosis signaling pathway. Thus, the ferroptosis signaling pathway may be associated with the pathogenic mechanism of DDH.

A whole-genome transcriptome analysis of articular chondrocytes in secondary osteoarthritis of the hip.

OBJECTIVE: To date, exhaustive gene expression analyses of chondrocytes in hip osteoarthritis (OA) have yielded specific gene expression patterns. No study has reported on the exhaustive transcriptome of secondary hip OA based on acetabular dysplasia in a Japanese population, while previous reports have focused on primary or idiopathic hip OA in Caucasian populations. This study aims to search for specific gene expression patterns of secondary hip OA chondrocytes by transcriptome analysis. DESIGN: Human articular cartilage was obtained from femoral heads following hemiarthroplasty for femoral neck fracture (N = 8; non-OA) and total hip arthroplasty for secondary hip OA (N = 12). Total RNA was extracted from the articular cartilage and submitted for microarray analysis. The obtained data were used to perform gene expression analysis, GO enrichment analysis and pathway analysis and were compared with data from primary hip OA in Caucasian populations in the literature. RESULTS: We identified 888 upregulated (fold change: FC ≥ 2) and 732 downregulated (FC ≤ 0.5) genes in hip OA versus non-OA chondrocytes, respectively. Only 10% of upregulated genes were common between the secondary and primary OA. The newly found genes prominently overexpressed in the secondary hip OA chondrocytes were DPT, IGFBP7, and KLF2. Pathway analysis revealed extracellular matrix (ECM)-receptor interaction as an OA-related pathway, which was similar to previous reports in primary hip OA. CONCLUSIONS: This is the first study to report the genome-wide transcriptome of secondary hip OA chondrocytes and demonstrates new potential OA-related genes. Gene expression patterns were different between secondary and primary hip OA, although the results of pathway and functional analysis were similar.

Pretreatment prediction of interferon-alfa efficacy in chronic hepatitis C patients.

BACKGROUND & AIMS: Interferon has been used widely to treat patients with chronic hepatitis C infections. Prediction of interferon efficacy before treatment has been performed mainly by using viral information, such as viral load and genotype. This information has allowed the successful prediction of sustained responders (SR) and non-SRs, which includes transient responders (TR) and nonresponders (NR). In the current study we examined whether liver messenger RNA expression profiles also can be used to predict interferon efficacy. METHODS: RNA was isolated from 69 liver biopsy samples from patients receiving interferon monotherapy and was analyzed on a complementary DNA microarray. Of these 69 samples, 31 were used to develop an algorithm for predicting interferon efficacy, and 38 were used to validate the precision of the algorithm. We also applied our methodology to the prediction of the efficacy of interferon/ribavirin combination therapy using an additional 56 biopsy samples. RESULTS: Our microarray analysis combined with the algorithm was 94% successful at predicting SR/TR and NR patients. A validation study confirmed that this algorithm can predict interferon efficacy with 95% accuracy and a P value of less than .00001. Similarly, we obtained a 93% prediction efficacy and a P value of less than .0001 for patients receiving combination therapy. CONCLUSIONS: By using only host data from the complementary DNA microarray we are able to successfully predict SR/TR and NR patients for interferon therapy. Therefore, this technique can help determine the appropriate treatment for hepatitis C patients.

A low-density cDNA microarray with a unique reference RNA: pattern recognition analysis for IFN efficacy prediction to HCV as a model.

We have designed and established a low-density (295 genes) cDNA microarray for the prediction of IFN efficacy in hepatitis C patients. To obtain a precise and consistent microarray data, we collected a data set from three spots for each gene (mRNA) and using three different scanning conditions. We also established an artificial reference RNA representing pseudo-inflammatory conditions from established hepatocyte cell lines supplemented with synthetic RNAs to 48 inflammatory genes. We also developed a novel algorithm that replaces the standard hierarchical-clustering method and allows handling of the large data set with ease. This algorithm utilizes a standard space database (SSDB) as a key scale to calculate the Mahalanobis distance (MD) from the center of gravity in the SSDB. We further utilized sMD (divided by parameter k: MD/k) to reduce MD number as a predictive value. The efficacy prediction of conventional IFN mono-therapy was 100% for non-responder (NR) vs. transient responder (TR)/sustained responder (SR) (P < 0.0005). Finally, we show that this method is acceptable for clinical application.