Xiong Guo

Genome-wide association study identifies ITPR2 as a susceptibility gene for Kashin-Beck disease in Han Chinese.

Kashin‐Beck disease (KBD) is a chronic osteochondropathy, the pathogenesis of which remains elusive. The aim of this study was to identify susceptibility genes for KBD by conducting a 2‐stage genome‐wide association study (GWAS).

Integrative meta-analysis of differentially expressed genes in osteoarthritis using microarray technology

The aim of the present study was to identify differentially expressed (DE) genes in patients with osteoarthritis (OA), and biological processes associated with changes in gene expression that occur in this disease. Using the INMEX (integrative meta-analysis of expression data) software tool, a meta-analysis of publicly available microarray Gene Expression Omnibus (GEO) datasets of OA was performed. Gene ontology (GO) enrichment analysis was performed in order to detect enriched functional attributes based on gene-associated GO terms. Three GEO datasets, containing 137 patients with OA and 52 healthy controls, were included in the meta-analysis. The analysis identified 85 genes that were consistently differentially expressed in OA (30 genes were upregulated and 55 genes were downregulated). The upregulated gene with the lowest P-value (P=5.36E-07) was S-phase kinase-associated protein 2, E3 ubiquitin protein ligase (SKP2). The downregulated gene with the lowest P-value (P=4.42E-09) was Proline rich 5 like (PRR5L). Among the 210 GO terms that were associated with the set of DE genes, the most significant two enrichments were observed in the GO categories of Immune response, with a P-value of 0.000129438, and Immune effectors process, with a P-value of 0.000288619. The current meta-analysis identified genes that were consistently DE in OA, in addition to biological pathways associated with changes in gene expression that occur during OA, which may provide insight into the molecular mechanisms underlying the pathogenesis of this disease.

Integrating genome-wide association study and expression quantitative trait locus study identifies multiple genes and gene sets associated with schizophrenia

&NA; Schizophrenia is a serious mental disease with high heritability. To better understand the genetic basis of schizophrenia, we conducted a large scale integrative analysis of genome‐wide association study (GWAS) and expression quantitative trait loci (eQTLs) data. GWAS summary data was derived from a published GWAS of schizophrenia, containing 9394 schizophrenia patients and 12,462 healthy controls. The eQTLs dataset was obtained from an eQTLs meta‐analysis of 5311 subjects, containing 923,021 cis‐eQTLs for 14,329 genes and 4732 trans‐eQTLs for 2612 genes. Genome‐wide single gene expression association analysis was conducted by SMR software. The SMR analysis results were further subjected to gene set enrichment analysis (GSEA) to identify schizophrenia associated gene sets. SMR detected 49 genes significantly associated with schizophrenia. The top five significant genes were CRELD2 (p value = 1.65 × 10−11), DIP2B (p value = 3.94 × 10−11), ZDHHC18 (p value = 1.52 × 10−10) and ZDHHC5 (p value = 7.45 × 10−10), C11ORF75 (p value = 3.70 × 10−9). GSEA identified 80 gene sets with p values <0.01. The top five significant gene sets were COWLING_MYCN_TARGETS (p value <0.001) and CHR16P11 (p value <0.001), ACTACCT_MIR196A_MIR196B (p value = 0.002), CELLULAR_COMPONENT_DISASSEMBLY (p value = 0.002) and GRAESSMANN_RESPONSE_TO_MC_AND_DOXORUBICIN_DN (p value = 0.002). Our results provide useful information for revealing the genetic basis of schizophrenia. HighlightsThe first large scale integrative study of GWAS and eQTLs was conducted for schizophrenia.SMR analysis identified 49 significant genes, whose expression levels were related to schizophrenia.Enrichment analysis detected 80 gene sets significantly associated with schizophrenia.Our results expand the understanding of the genetic mechanism of schizophrenia.

Diagnostic value of circulating microRNAs for osteosarcoma in Asian populations: a meta-analysis.

A large number of studies have provided new insights into the diagnostic value of circulating microRNAs (miRNA) for osteosarcoma (OS), one of the most common primary malignancies in adolescents. However, inconsistent conclusions on the diagnostic performance of various kinds of miRNAs have been made. To assess the true diagnostic value of circulating miRNA for the early detection of OS in this meta-analysis, multiple databases, including PubMed, EMBASE, Web of Science, Chinese National Knowledge Infrastructurexa0(CNKI), and Technology of Chongqingxa0(VIP), were carefully searched for available studies up to October 30, 2015. The quality of each study was scored using the quality assessment of diagnostic accuracy studies-2 (QUADAS-2). Sensitivity and specificity was pooled using a random-effects model. Positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the curve (AUC) were used to measure the diagnostic values. Subgroup and meta-regression analyses were used to find potential sources of heterogeneity. Publication bias was tested with the Deeks’ funnel plot asymmetry test. Eight articles with 741 OS patients and 479 healthy controls were finally included in this meta-analysis. The pooled estimations indicated circulating miRNAs has a high accuracy for diagnosing OS, with sensitivity of 0.94, specificity of 0.80, PLR of 4.75, NLR of 0.07, DOR of 69, and AUC of 0.94. In addition, subgroup and meta-regression analyses revealed that the expression patterns of miRNAs obtained from plasma are more credible diagnostic biomarkers than those from serum. In conclusion, as noninvasive biomarkers, circulating miRNAs have a promising future for the diagnosis of OS in Asian populations.

Tissue-specific pathway association analysis using genome-wide association study summaries

Motivation: Pathway association analysis has made great achievements in elucidating the genetic basis of human complex diseases. However, current pathway association analysis approaches fail to consider tissue-specificity. Results: We developed a tissue-specific pathway interaction enrichment analysis algorithm (TPIEA). TPIEA was applied to two large Caucasian and Chinese genome-wide association study summary datasets of bone mineral density (BMD). TPIEA identified several significant pathways for BMD [false discovery rate (FDR)u2009<u20090.05], such as KEGG FOCAL ADHESION and KEGG AXON GUIDANCE, which had been demonstrated to be involved in the development of osteoporosis. We also compared the performance of TPIEA and classical pathway enrichment analysis, and TPIEA presented improved performance in recognizing disease relevant pathways. TPIEA may help to fill the gap of classic pathway association analysis approaches by considering tissue specificity. Availability and Implementation: The online web tool of TPIEA is available at https://sourceforge.net/projects/tpieav1/files. Contact: fzhxjtu@mail.xjtu.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.

Selenium and Iodine Levels in Subjects with Kashin-Beck Disease: a Meta-analysis

Kashin-Beck disease (KBD) is an endemic, degenerative osteoarthropathy, and particularly seen in China. A deficiency of selenium and iodine is implicated as the main etiological factor for KBD. This meta-analysis aimed to evaluate the differences in the selenium and iodine levels between patients with KBD and healthy individuals. Eligible articles published before March 6, 2015 were searched from four electronic databases. Data extraction and quality assessment of included studies were performed by two independent reviewers. Results were summarized as standardized mean difference (SMD) with 95xa0% confidence intervals (CIs). Cohen’s d test was used to estimate the difference of the effect size between patients with KBD and healthy controls. A total of 26 cross-sectional studies were included in the meta-analysis. The pooled SMD showed that the whole blood selenium (Cohen’s dxa0=xa04.39, Pxa0<xa00.001), serum selenium (Cohen’s dxa0=xa02.42, Pxa0=xa00.015), hair selenium (Cohen’s dxa0=xa05.46, Pxa0<xa00.001), and urinary selenium (Cohen’s dxa0=xa04.16, Pxa0<xa00.001) levels were significantly lower in patients with KBD than that in healthy controls. There was no significant difference of plasma selenium (Cohen’s dxa0=xa00.08, Pxa0=xa00.936) and urinary iodine (Cohen’s dxa0=xa00.33, Pxa0=xa00.744) levels between subjects with KBD and healthy controls. In conclusion, the levels of selenium, but not iodine were significantly lower in subjects with KBD than that in healthy controls. Selenium deficiency might be associated with the risk of KBD.

Long noncoding RNA expression profile reveals lncRNAs signature associated with extracellular matrix degradation in kashin-beck disease

Kashin-Beck disease (KBD) is a deformative, endemic osteochondropathy involving degeneration and necrosis of growth plates and articular cartilage. The pathogenesis of KBD is related to gene expression and regulation mechanisms, but long noncoding RNAs (lncRNAs) in KBD have not been investigated. In this study, we identified 316 up-regulated and 631 down-regulated lncRNAs (≥xa02-fold change) in KBD chondrocytes using microarray analysis, of which more than three-quarters were intergenic lncRNAs and antisense lncRNAs. We also identified 232 up-regulated and 427 down-regulated mRNAs (≥xa02-fold change). A lncRNA-mRNA correlation analysis combined 343 lncRNAs and 292 mRNAs to form 509 coding-noncoding gene co-expression networks (CNC networks). Eleven lncRNAs were predicted to have cis-regulated target genes, including NAV2 (neuron navigator 2), TOX (thymocyte selection-associated high mobility group box), LAMA4 (laminin, alpha 4), and DEPTOR (DEP domain containing mTOR-interacting protein). The differentially expressed mRNAs in KBD significantly contribute to biological events associated with the extracellular matrix. Meanwhile, 34 mRNAs and 55 co-expressed lncRNAs constituted a network that influences the extracellular matrix. In the network, FBLN1 and LAMA 4 were the core genes with the highest significance. These novel findings indicate that lncRNAs may play a role in extracellular matrix destruction in KBD.

Genome-wide DNA methylation profiling of articular cartilage reveals significant epigenetic alterations in Kashin-Beck disease and osteoarthritis

OBJECTIVEnTo determine genome-wide DNA methylation profiles of knee cartilage from patients with Kashin-Beck disease (KBD) and osteoarthritis (OA).nnnMETHODnKnee cartilage was collected from 14 grade III KBD patients, 5 primary OA patients and 13 healthy subjects. The genome-wide methylation profiles of 5 KBD cartilage, 5 OA cartilage and 5 normal cartilage were determined by Illumina HumanMethylation450 array. Illumina Methylation Analyzer package was employed for identifying differentially methylated CpG sites. Functional annotation and enrichment analysis of differentially methylated genes (DMG) were conducted using GeneRIF database, Ingenuity Pathway Analysis (IPA) and The Database for Annotation, Visualization and Integrated Discovery (DAVID). Mass spectrometry (MS) and immunohistochemistry (IHC) were conducted to validate the functional relevance of identified KBD associated gene.nnnRESULTSnWe identified a total of 1212 differentially methylated CpG sites in KBD vs Normal, annotated to 264 hypermethylated and 368 hypomethylated genes. Comparing the DNA methylation profiles of KBD vs Normal and OA vs Normal detected overlap of 367 differentially methylated CpG sites (annotated to 182 genes) as well as 845 KBD-specific differentially methylated CpG sites (annotated to 471 unique genes). MS and IHC confirmed the hypermethylation status and decreased protein expression of HAPLN1 gene in KBD cartilage.nnnCONCLUSIONnOur data implicate epigenetic dysregulation of a host of genes in KBD and OA. Furthermore, we observed common causal epigenetic changes shared by KBD and OA.

Population-based comparative analysis of differentially expressed genes between Kashin–Beck disease grades I and II

Objectives: To identify the differences and similarities of differentially expressed genes in peripheral blood mononuclear cells (PBMCs) between Kashin–Beck disease (KBD) grades I and II. Method: In total, 100 patients with KBD and 100 healthy controls were selected from a KBD endemic area and divided into 100 pairs of KBD vs. controls (50 pairs of patients with KBD grade I and healthy controls, 50 pairs of patients with KBD grade II and healthy controls). RNA was isolated from KBD PBMCs and healthy control PBMCs. Microarray analysis was conducted to identify differentially expressed genes in the different stages of KBD. The microarray data obtained were further confirmed using quantitative real-time polymerase chain reaction (qRT-PCR). Results: In total, eight differentially expressed genes in KBD grade I and 69 differentially expressed genes in KBD grade II were identified. Among these genes, six common genes were differentially expressed in both stages of the disease. The expression ratios of four common genes differed significantly between KBD grades I and II. Based on the expression ratios of the four genes, linear discriminant analysis (LDA) correctly classified the KBD grade (I or II) with 81% accuracy. Conclusions: The similarities and differences of differentially expressed genes in PBMCs of patients with different stages of KBD may play an important role in the pathogenesis of the early phase of KBD. Additionally, six common genes may be considered blood-based genetic biomarkers for the detection and treatment of KBD.

Genome-wide association studies and gene expression profiles of rheumatoid arthritis: An analysis

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.