Xiao-Wei Zhu

Meta-analysis of Atherogenic Index of Plasma and other lipid parameters in relation to risk of type 2 diabetes mellitus

AIMSnDiabetic dyslipidemia is one of important complication of type 2 diabetes mellitus (T2DM). Blood lipid parameters (e.g., triglyceride, TG; total cholesterol, TC; high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; Atherogenic Index of Plasma defined as lg(TG/HDL-C), AIP), are important indexes in predicting risk of T2DM. This study performed comprehensive meta-analyses to evaluate the powers of these indexes, especially for AIP, on predicting risk of T2DM.nnnMETHODSnWe searched PubMed Database, China National Knowledge Infrastructure (CNKI) and Wanfang Database in February 2014 to identify eligible studies. Case-control studies that have mean baseline values of AIP were included. Random-effect models were used to pool the summary standardized mean difference (SMD) in meta-analysis.nnnRESULTSnFifteen eligible studies, with a total sample size of 4010, were included in meta-analysis. All these studies reported positive associations between AIP and T2DM. Moreover, the SMD for the AIP is 1.78 (95% confidence interval (CI): 1.04-2.52), which is higher than for other parameters (TG: 0.93, 95% CI: 0.78-1.09; TC: 0.46, 95% CI: 0.21-0.71; HDL-C: -0.89, 95% CI: -1.18 to -0.60; and LDL-C: 0.44, 95% CI: 0.11-0.77). Meta-analysis of association between BMI and T2DM gave a SMD of 0.85 (95% CI: 0.38 to 1.32).nnnCONCLUSIONSnThe results suggest that lipid parameters have ability to reflect the risk of T2DM, but AIP may be more closely associated with the risk of T2DM. The current results suggest AIP may be used as a simple, easily calculated parameter in assessing the risk of T2DM.

Integrative multi-omics analysis revealed SNP-lncRNA-mRNA (SLM) networks in human peripheral blood mononuclear cells

Long non-coding RNAs (lncRNAs) serve as important controller of cellular functions via regulating RNA transcription, degradation and translation. However, what are the regulation patterns of lncRNAs on downstream mRNA and how the upstream genetic variants regulate lncRNAs are largely unknown. We first performed a comprehensive expression quantitative trait locus (eQTL) analysis (MatrixeQTL package, R) using genome-wide lncRNA expression and SNP genotype data from human peripheral blood mononuclear cells (PBMCs) of 43 unrelated individuals. Subsequently, multi-omics integrative network analysis was applied to construct SNP-lncRNA-mRNA (SLM) interaction networks. The causal inference test (CIT) was used to identify lncRNA-mediated (epi-) genetic regulation on mRNA expressions. Our eQTL analysis detected 707 pairs of cis-effect associations (pxa0<xa05.64E−06) and 6657 trans-effect associations (pxa0<xa03.51E−08), respectively. We also found that top significant cis-eSNPs were enriched around the lncRNA transcription start site regions, and that enrichment patterns of cis-eSNPs differs among different lncRNA sizes (small, medium and large).The constructed SLM interaction networks (1 primary networks and four small separate networks) showed various complex interaction patterns. Especially, the in-depth CIT detected 50 significant lncRNA-mediated SLM trios, and some hotspots (e.g., SNPs: rs926370, rs7716167 and rs16880521; lncRNAs: HIT000061975 and ENST00000579057.1). This study represents the first effort of dissecting the SLM interaction patterns in PBMCs by multi-omics integrative network analysis and causal inference test for clearing the regulation chain. The results provide novel insights into the regulation patterns of lncRNA, and may facilitate investigations of PBMC-related immune physiological process and immunological diseases in the future.

Identification and evaluation of lncRNA and mRNA integrative modules in human peripheral blood mononuclear cells.

AIMnTo identify sets of functionally related long noncoding RNAs (lncRNAs) and mRNAs and to evaluate the importance of lncRNAs in an lncRNA-mRNA network.nnnMETHODSnWe carried out weighted gene co-expression network analysis and enrichment analyses to identify functional modules of co-expressed lncRNAs and mRNAs in human peripheral blood mononuclear cells of 43 females.nnnRESULTSnWe identified seven modules and found hub lncRNAs in each module. Four of the seven modules had significant gene ontology enrichments. Some of the hub lncRNAs (e.g., SSX8, UCA1, HOXA-AS2, STARD4-AS1 and PCBP1-AS1) have known functions related with diseases such as cancers.nnnCONCLUSIONnWe identified seven biologically important lncRNA and mRNA integrative modules in females and showed that lncRNAs might play important roles in lncRNA-mRNA co-expression modules.

Correlation analyses revealed global microRNA-mRNA expression associations in human peripheral blood mononuclear cells.

MicroRNAs (miRNAs) can regulate gene expression through binding to complementary sites in the 3′-untranslated regions of target mRNAs, which will lead to existence of correlation in expression between miRNA and mRNA. However, the miRNA–mRNA correlation patterns are complex and remain largely unclear yet. To establish the global correlation patterns in human peripheral blood mononuclear cells (PBMCs), multiple miRNA–mRNA correlation analyses and expression quantitative trait locus (eQTL) analysis were conducted in this study. We predicted and achieved 861 miRNA–mRNA pairs (65 miRNAs, 412 mRNAs) using multiple bioinformatics programs, and found global negative miRNA–mRNA correlations in PBMC from all 46 study subjects. Among the 861 pairs of correlations, 19.5% were significant (Pxa0<xa00.05) and ~70% were negative. The correlation network was complex and highlighted key miRNAs/genes in PBMC. Some miRNAs, such as hsa-miR-29a, hsa-miR-148a, regulate a cluster of target genes. Some genes, e.g., TNRC6A, are regulated by multiple miRNAs. The identified genes tend to be enriched in molecular functions of DNA and RNA binding, and biological processes such as protein transport, regulation of translation and chromatin modification. The results provided a global view of the miRNA–mRNA expression correlation profile in human PBMCs, which would facilitate in-depth investigation of biological functions of key miRNAs/mRNAs and better understanding of the pathogenesis underlying PBMC-related diseases.

Relative abundance of mature myostatin rather than total myostatin is negatively associated with bone mineral density in Chinese

Myostatin is mainly secreted by skeletal muscle and negatively regulates skeletal muscle growth. However, the roles of myostatin on bone metabolism are still largely unknown. Here, we recruited two large populations containing 6308 elderly Chinese and conducted comprehensive statistical analyses to evaluate the associations among lean body mass (LBM), plasma myostatin, and bone mineral density (BMD). Our data revealed that total myostatin in plasma was mainly determined by LBM. The relative abundance of mature myostatin (mature/total) was significantly lower in high versus low BMD subjects. Moreover, the relative abundance of mature myostatin was positively correlated with bone resorption marker. Finally, we carried out in vitro experiments and found that myostatin has inhibitory effects on the proliferation and differentiation of human osteoprogenitor cells. Taken together, our results have demonstrated that the relative abundance of mature myostatin in plasma is negatively associated with BMD, and the underlying functional mechanism for the association is most likely through inhibiting osteoblastogenesis and promoting osteoclastogenesis.

Functional mechanisms for type 2 diabetes-associated genetic variants

AIMSnType 2 diabetes (T2D) is a complex endocrine and metabolic disorder, characterized by hyperglycemia due to insulin resistance and relative lack of insulin. Several recent studies have identified a large number of genetic loci associated with T2D without exploring functional mechanisms underlying the associations. This study established integrative analyses to detect the functional mechanisms for T2D-related associations.nnnMETHODSnBased on the public available datasets and resources, this study performed integrative analyses (gene relationships among implicated loci (GRAIL), expression quantitative trait loci (eQTL) analysis, differential gene expression analysis and functional prediction analysis) to detect the molecular functional mechanisms underlying the associations.nnnRESULTSnTwo single nucleotide polymorphisms (SNPs) (rs7593730, rs2439312) have been found to act as cis-effect regulators of two corresponding eQTL genes (RBMS1, NRG1) among 252 selected (P<E-4) genetic associations that were archived in the public databases. These two non-HLA genes were also differentially expressed in T2D-related cell groups. The two SNPs were predicted as regulatory sites by utilizing online prediction tools.nnnCONCLUSIONSnThis study detected potential regulatory mechanisms underlying the associations between T2D and two identified SNPs. Integrative analysis can be used to provide suggestive clues for the molecular functional mechanisms in T2D.

The distribution and functional relevance analysis of runs of homozygosity (ROHs) in Chinese Han female population

Extended homozygosity is a genomic region in which the copies inherited from parents are identical, and has obvious inter-individual differences in length and frequency. Runs of homozygosity (ROHs), regarded as a type of structure variations, may have potential capacity in regulating gene transcription. To learn more about the genome-wide distribution of ROH regions in humans and understand the potential roles, this study applied ROH-based approach to quantify and characterize ROHs in 41 Chinese Han female subjects, and test potential associations between ROHs and mRNA expressions by eQTL analysis to ascertain whether ROHs are relevant to gene transcription in peripheral blood mononuclear cellsxa0(PBMCs). 10,884 ROH regions were identified in human genome. The average cumulative length of ROH regions was 217,250xa0±xa020,241xa0kb. The number of core segments in each chromosome generally matched the total length of corresponding chromosome, i.e., the longer the chromosome, the more the core segments. Genes located in the core regions of ROH were significantly enriched in multiple basic metabolism pathways. A total of 226 cis-eQTLs and 178 trans-eQTLs were identified. The cis-effect size was mainly concentrated atxa0±xa00.5; and the trans-effect size was mainly concentrated at −1.5 and 1.0. Genes with eQTL effects were significantly enriched in functions related to protein binding, cytosol, nucleoplasm, nuclear membrane, protein binding and citrate metabolic process. This study described comprehensive distributions and characteristics of ROH in Han female Chinese, and recognized the significant role of ROH associated with gene transcription in humanxa0PBMC.

Detection of lncRNA-mRNA interaction modules by integrating eQTL with weighted gene co-expression network analysis

One major function of lncRNA is to regulate the expression of mRNA, but the patterns of their interactions were largely unknown. We attempted to construct lncRNA-mRNA interaction modules at a genome-wide scale. We performed a genome-wide lncRNA-mRNA eQTL analysis in peripheral blood mononuclear cells of 43 individuals, followed by weighted gene co-expression network analysis and functional enrichment analysis which sought to detect functional modules. There were 4627 significant cis lnc-eQTL pairs (Pu2009<u20091.4u2009×u200910−6) and 1,587,128 significant trans lnc-eQTL pairs (Pu2009<u20093.46u2009×u200910−9). We detected 11 eQTL modules for the lnc-eQTL networks. Among them, five modules showed significant enrichments in GO terms, and three modules showed significant enrichments in specific KEGG pathways (e.g., Toll-like receptor, PI3K-Akt, NF-kappa B, and TNF signaling pathways). lncRNA-protein interaction analysis showed that some well-known functional lncRNAs (HOTAIR, CCDC26, RHPN1-AS1, WT1-AS, and TCL6) in the eQTL module interacted with genes in focal adhesion and PI3K-Akt signaling pathway. We identified biologically functional lncRNA-mRNA interaction modules by integrating eQTL and weighted gene co-expression network analysis. Integrative analysis of lncRNA and mRNA data by applying eQTL analysis and weighted gene co-expression network analysis methods could be helpful for functional annotation of lncRNAs.

Multiple correlation analyses revealed complex relationship between DNA methylation and mRNA expression in human peripheral blood mononuclear cells

DNA methylation is an important regulator on the mRNA expression. However, a genome-wide correlation pattern between DNA methylation and mRNA expression in human peripheral blood mononuclear cells (PBMCs) is largely unknown. The comprehensive relationship between mRNA and DNA methylation was explored by using four types of correlation analyses and a genome-wide methylation-mRNA expression quantitative trait locus (eQTL) analysis in PBMCs in 46 unrelated female subjects. An enrichment analysis was performed to detect biological function for the detected genes. Single pair correlation coefficient (rT1) between methylation level and mRNA is moderate (−0.63–0.62) in intensity, and the negative and positive correlations are nearly equal in quantity. Correlation analysis on each gene (T4) found 60.1% genes showed correlations between mRNA and gene-based methylation at Pxa0<xa00.05 and more than 5.96% genes presented very strong correlation (RT4xa0>xa00.8). Methylation sites have regulation effects on mRNA expression in eQTL analysis, with more often observations in region of transcription start site (TSS). The genes under significant methylation regulation both in correlation analysis and eQTL analysis tend to cluster to the categories (e.g., transcription, translation, regulation of transcription) that are essential for maintaining the basic life activities of cells. Our findings indicated that DNA methylation has predictive regulation effect on mRNA with a very complex pattern in PBMCs. The results increased our understanding on correlation of methylation and mRNA and also provided useful clues for future epigenetic studies in exploring biological and disease-related regulatory mechanisms in PBMC.

Rheumatoid arthritis–associated DNA methylation sites in peripheral blood mononuclear cells

Objectives To identify novel DNA methylation sites significant for rheumatoid arthritis (RA) and comprehensively understand their underlying pathological mechanism. Methods We performed (1) genome-wide DNA methylation and mRNA expression profiling in peripheral blood mononuclear cells from RA patients and health controls; (2) correlation analysis and causal inference tests for DNA methylation and mRNA expression data; (3) differential methylation genes regulatory network construction; (4) validation tests of 10 differential methylation positions (DMPs) of interest and corresponding gene expressions; (5) correlation between PARP9 methylation and its mRNA expression level in Jurkat cells and T cells from patients with RA; (6) testing the pathological functions of PARP9 in Jurkat cells. Results A total of 1046 DNA methylation positions were associated with RA. The identified DMPs have regulatory effects on mRNA expressions. Causal inference tests identified six DNA methylation–mRNA–RA regulatory chains (eg, cg00959259-PARP9-RA). The identified DMPs and genes formed an interferon-inducible gene interaction network (eg, MX1, IFI44L, DTX3L and PARP9). Key DMPs and corresponding genes were validated their differences in additional samples. Methylation of PARP9 was correlated with mRNA level in Jurkat cells and T lymphocytes isolated from patients with RA. The PARP9 gene exerted significant effects on Jurkat cells (eg, cell cycle, cell proliferation, cell activation and expression of inflammatory factor IL-2). Conclusions This multistage study identified an interferon-inducible gene interaction network associated with RA and highlighted the importance of PARP9 gene in RA pathogenesis. The results enhanced our understanding of the important role of DNA methylation in pathology of RA.