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Browsing by Author "Wang, Zhiping"
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Item Evaluation of the Genetic Basis of Familial Aggregation of Pacemaker Implantation by a Large Next Generation Sequencing Panel(Public Library of Science (PloS), 2015) Celestino-Soper, Patrícia B. S.; Doytchinova, Anisiia; Steiner, Hillel A.; Uradu, Andrea; Lynnes, Ty C.; Groh, William J.; Miller, John M.; Lin, Hai; Gao, Hongyu; Wang, Zhiping; Liu, Yunlong; Chen, Peng-Sheng; Vatta, Matteo; Department of Medical and Molecular Genetics, IU School of MedicineBACKGROUND: The etiology of conduction disturbances necessitating permanent pacemaker (PPM) implantation is often unknown, although familial aggregation of PPM (faPPM) suggests a possible genetic basis. We developed a pan-cardiovascular next generation sequencing (NGS) panel to genetically characterize a selected cohort of faPPM. MATERIALS AND METHODS: We designed and validated a custom NGS panel targeting the coding and splicing regions of 246 genes with involvement in cardiac pathogenicity. We enrolled 112 PPM patients and selected nine (8%) with faPPM to be analyzed by NGS. RESULTS: Our NGS panel covers 95% of the intended target with an average of 229x read depth at a minimum of 15-fold depth, reaching a SNP true positive rate of 98%. The faPPM patients presented with isolated cardiac conduction disease (ICCD) or sick sinus syndrome (SSS) without overt structural heart disease or identifiable secondary etiology. Three patients (33.3%) had heterozygous deleterious variants previously reported in autosomal dominant cardiac diseases including CCD: LDB3 (p.D117N) and TRPM4 (p.G844D) variants in patient 4; TRPM4 (p.G844D) and ABCC9 (p.V734I) variants in patient 6; and SCN5A (p.T220I) and APOB (p.R3527Q) variants in patient 7. CONCLUSION: FaPPM occurred in 8% of our PPM clinic population. The employment of massive parallel sequencing for a large selected panel of cardiovascular genes identified a high percentage (33.3%) of the faPPM patients with deleterious variants previously reported in autosomal dominant cardiac diseases, suggesting that genetic variants may play a role in faPPM.Item Genome-Wide Mapping and Interrogation of the Nmp4 Antianabolic Bone Axis(Oxford University Press, 2015-09) Childress, Paul; Stayrook, Keith R.; Alvarez, Marta B.; Wang, Zhiping; Shao, Yu; Hernandez-Buquer, Selene; Mack, Justin K.; Grese, Zachary R.; He, Yongzheng; Horan, Daniel; Pavalko, Fredrick M.; Warden, Stuart J.; Robling, Alexander G.; Yang, Feng-Chun; Allen, Matthew R.; Krishnan, Venkatesh; Liu, Yunlong; Bidwell, Joseph P.; Department of Anatomy & Cell Biology, IU School of MedicinePTH is an osteoanabolic for treating osteoporosis but its potency wanes. Disabling the transcription factor nuclear matrix protein 4 (Nmp4) in healthy, ovary-intact mice enhances bone response to PTH and bone morphogenetic protein 2 and protects from unloading-induced osteopenia. These Nmp4(-/-) mice exhibit expanded bone marrow populations of osteoprogenitors and supporting CD8(+) T cells. To determine whether the Nmp4(-/-) phenotype persists in an osteoporosis model we compared PTH response in ovariectomized (ovx) wild-type (WT) and Nmp4(-/-) mice. To identify potential Nmp4 target genes, we performed bioinformatic/pathway profiling on Nmp4 chromatin immunoprecipitation sequencing (ChIP-seq) data. Mice (12 w) were ovx or sham operated 4 weeks before the initiation of PTH therapy. Skeletal phenotype analysis included microcomputed tomography, histomorphometry, serum profiles, fluorescence-activated cell sorting and the growth/mineralization of cultured WT and Nmp4(-/-) bone marrow mesenchymal stem progenitor cells (MSPCs). ChIP-seq data were derived using MC3T3-E1 preosteoblasts, murine embryonic stem cells, and 2 blood cell lines. Ovx Nmp4(-/-) mice exhibited an improved response to PTH coupled with elevated numbers of osteoprogenitors and CD8(+) T cells, but were not protected from ovx-induced bone loss. Cultured Nmp4(-/-) MSPCs displayed enhanced proliferation and accelerated mineralization. ChIP-seq/gene ontology analyses identified target genes likely under Nmp4 control as enriched for negative regulators of biosynthetic processes. Interrogation of mRNA transcripts in nondifferentiating and osteogenic differentiating WT and Nmp4(-/-) MSPCs was performed on 90 Nmp4 target genes and differentiation markers. These data suggest that Nmp4 suppresses bone anabolism, in part, by regulating IGF-binding protein expression. Changes in Nmp4 status may lead to improvements in osteoprogenitor response to therapeutic cues.Item A modulated empirical Bayes model for identifying topological and temporal estrogen receptor α regulatory networks in breast cancer.(BioMed Central, 2011-05-09) Shen, Changyu; Huang, Yiwen; Liu, Yunlong; Wang, Guohua; Zhao, Yuming; Wang, Zhiping; Teng, Mingxiang; Wang, Yadong; Flockhart, David A.; Skaar, Todd C.; Yan, Pearlly; Nephew, Kenneth P.; Huang, Tim Hm; Li, LangBACKGROUND: Estrogens regulate diverse physiological processes in various tissues through genomic and non-genomic mechanisms that result in activation or repression of gene expression. Transcription regulation upon estrogen stimulation is a critical biological process underlying the onset and progress of the majority of breast cancer. Dynamic gene expression changes have been shown to characterize the breast cancer cell response to estrogens, the every molecular mechanism of which is still not well understood. RESULTS: We developed a modulated empirical Bayes model, and constructed a novel topological and temporal transcription factor (TF) regulatory network in MCF7 breast cancer cell line upon stimulation by 17β-estradiol stimulation. In the network, significant TF genomic hubs were identified including ER-alpha and AP-1; significant non-genomic hubs include ZFP161, TFDP1, NRF1, TFAP2A, EGR1, E2F1, and PITX2. Although the early and late networks were distinct (<5% overlap of ERα target genes between the 4 and 24 h time points), all nine hubs were significantly represented in both networks. In MCF7 cells with acquired resistance to tamoxifen, the ERα regulatory network was unresponsive to 17β-estradiol stimulation. The significant loss of hormone responsiveness was associated with marked epigenomic changes, including hyper- or hypo-methylation of promoter CpG islands and repressive histone methylations. CONCLUSIONS: We identified a number of estrogen regulated target genes and established estrogen-regulated network that distinguishes the genomic and non-genomic actions of estrogen receptor. Many gene targets of this network were not active anymore in anti-estrogen resistant cell lines, possibly because their DNA methylation and histone acetylation patterns have changed.Item Non-compartment model to compartment model pharmacokinetics transformation meta-analysis – a multivariate nonlinear mixed model(BMC, 2010-05-28) Wang, Zhiping; Kim, Seongho; Quinney, Sara K.; Zhou, Jihao; Li, Lang; Medicine, School of MedicineBackground To fulfill the model based drug development, the very first step is usually a model establishment from published literatures. Pharmacokinetics model is the central piece of model based drug development. This paper proposed an important approach to transform published non-compartment model pharmacokinetics (PK) parameters into compartment model PK parameters. This meta-analysis was performed with a multivariate nonlinear mixed model. A conditional first-order linearization approach was developed for statistical estimation and inference. Results Using MDZ as an example, we showed that this approach successfully transformed 6 non-compartment model PK parameters from 10 publications into 5 compartment model PK parameters. In simulation studies, we showed that this multivariate nonlinear mixed model had little relative bias (<1%) in estimating compartment model PK parameters if all non-compartment PK parameters were reported in every study. If there missing non-compartment PK parameters existed in some published literatures, the relative bias of compartment model PK parameter was still small (<3%). The 95% coverage probabilities of these PK parameter estimates were above 85%. Conclusions This non-compartment model PK parameter transformation into compartment model meta-analysis approach possesses valid statistical inference. It can be routinely used for model based drug development.Item A Study of Alterations in DNA Epigenetic Modifications (5mC and 5hmC) and Gene Expression Influenced by Simulated Microgravity in Human Lymphoblastoid Cells.(PLOS, 2016) Chowdhury, Basudev; Seetharam, Arun; Wang, Zhiping; Liu, Yunlong; Lossie, Amy C.; Thimmapuram, Jyothi; Irudayaraj, Joseph; Department of Medical & Molecular Genetics, IU School of MedicineCells alter their gene expression in response to exposure to various environmental changes. Epigenetic mechanisms such as DNA methylation are believed to regulate the alterations in gene expression patterns. In vitro and in vivo studies have documented changes in cellular proliferation, cytoskeletal remodeling, signal transduction, bone mineralization and immune deficiency under the influence of microgravity conditions experienced in space. However microgravity induced changes in the epigenome have not been well characterized. In this study we have used Next-generation Sequencing (NGS) to profile ground-based “simulated” microgravity induced changes on DNA methylation (5-methylcytosine or 5mC), hydroxymethylation (5-hydroxymethylcytosine or 5hmC), and simultaneous gene expression in cultured human lymphoblastoid cells. Our results indicate that simulated microgravity induced alterations in the methylome (~60% of the differentially methylated regions or DMRs are hypomethylated and ~92% of the differentially hydroxymethylated regions or DHMRs are hyperhydroxymethylated). Simulated microgravity also induced differential expression in 370 transcripts that were associated with crucial biological processes such as oxidative stress response, carbohydrate metabolism and regulation of transcription. While we were not able to obtain any global trend correlating the changes of methylation/ hydroxylation with gene expression, we have been able to profile the simulated microgravity induced changes of 5mC over some of the differentially expressed genes that includes five genes undergoing differential methylation over their promoters and twenty five genes undergoing differential methylation over their gene-bodies. To the best of our knowledge, this is the first NGS-based study to profile epigenomic patterns induced by short time exposure of simulated microgravity and we believe that our findings can be a valuable resource for future explorations.