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151. Arsenic and the Epigenome: Inter-individual differences in arsenic metabolism related to distinct patterns of DNA methylation

Author

Bailey, Kathryn A., Wu, Michael C., Ward, William O., Smeester, Lisa, Rager, Julia E., García-Vargas, Gonzalo, Del Razo, Luz-Maria, Drobná, Zuzana, Stýblo, Miroslav, and Fry, Rebecca C.

Subjects
Epigenomics, Male, Arsenic Poisoning, Diabetes Mellitus, Leukocytes, Humans, Female, DNA Methylation, Article, Biomarkers, Arsenic, Epigenesis, Genetic, Genome-Wide Association Study
Abstract

Biotransformation of inorganic arsenic (iAs) is one of the factors that determines the character and magnitude of the diverse detrimental health effects associated with chronic iAs exposure, but it is unknown how iAs biotransformation may impact the epigenome. Here, we integrated analyses of genome-wide, gene-specific promoter DNA methylation levels of peripheral blood leukocytes (PBLs) with urinary arsenical concentrations of subjects from a region of Mexico with high levels of iAs in drinking water. These analyses revealed dramatic differences in DNA methylation profiles associated with concentrations of specific urinary metabolites of arsenic. The majority of individuals in this study had positive indicators of arsenic-related disease, namely pre-diabetes mellitus or diabetes mellitus. Methylation patterns of genes with known associations to diabetes mellitus were associated with urinary concentrations of specific iAs metabolites. Future studies will determine whether these DNA methylation profiles provide mechanistic insight into the development of iAs-associated disease, predict disease risk, and/or serve as biomarkers of iAs exposure in humans.

Published
2013

152. Salivary proteins associated with hyperglycemia in diabetes: a proteomic analysis

Author

Baxter, Sarah Schwartz, Byrd, Warren C., Offenbacher, Steven, Carlson, Jim, Howard-Williams, Escher L., Buse, John B., Wu, Michael C., Border, Michael B., Urrutia, Eugene, Bencharit, Sompop, Kohltfarber, Heidi, and Mayo, Mary Virginia

Abstract

Effective monitoring of glucose levels is necessary for patients to achieve greater control over their diabetes. However, only about a quarter of subjects with diabetes who requires close serum glucose monitoring, regularly check their serum glucose daily. One of the potential barriers to patient compliance is the blood sampling requirement. Saliva and its protein contents can be altered in subjects with diabetes, possibly due to changes in glycemic control. We propose here that salivary proteomes of subjects with diabetes may be different based on their glycemic control as reflected in A1C levels. A total of 153 subjects with type 1 or 2 diabetes were recruited. Subjects in each type of diabetes were divided into 5 groups based on their A1C levels; 10. To examine the global proteomic changes associated with A1C, the proteomic profiling of pooled saliva samples from each group was created using label-free quantitative proteomics. Similar proteomic analysis for individual subjects (N=4, for each group) were then applied to examine proteins that may be less abundant in pooled samples. Principle component analysis (PCA) and cluster analysis (p

Published
2013
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153. Identification of Driver Genes in Hepatocellular Carcinoma by Exome Sequencing

Author

Zhao, Xiaobei, Savich, Gleb L., Jeck, William R., Li, Jinyu, Powers, Scott, Chen, Kui, Wu, Michael C., Getz, Gad, Lawrence, Michael S., Selitsky, Sara R., Tan, Ting-Xu, Fischer, Sandra, Cleary, Sean P., Guindi, Maha, Ghanekar, Anand, Chiang, Derek Y., Parker, Joel S., and Kim, Hyeja

Abstract

Genetic alterations in specific driver genes lead to disruption of cellular pathways and are critical events in the instigation and progression of hepatocellular carcinoma. As a prerequisite for individualized cancer treatment, we sought to characterize the landscape of recurrent somatic mutations in hepatocellular carcinoma. We performed whole exome sequencing on 87 hepatocellular carcinomas and matched normal adjacent tissues to anaverage coverage of 59x. The overall mutation rate was roughly 2 mutations per Mb, with a median of 45 non-synonymous mutations that altered the amino acid sequence (range 2 to 381). We found recurrent mutations in several genes with high transcript levels: TP53 (18%), CTNNB1 (10%), KEAP1 (8%), C16orf62 (8%), MLL4(7%) and RAC2 (5%). Significantly affected gene families include the nucleotide-binding domain and leucine rich repeat containing family, calcium channel subunits, and histone methyltransferases. In particular, the MLL family of methyltransferases for histone H3 lysine 4 were mutated in 20% of tumors.

Published
2013
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154. Arsenic and the Epigenome: Inter-individual differences in arsenic metabolism related to distinct patterns of DNA methylation

Author

Ward, William O., Wu, Michael C., Bailey, Kathryn A., Smeester, Lisa, Drobná, Zuzana, Stýblo, Miroslav, García-Vargas, Gonzalo, Rager, Julia E., and Del Razo, Luz-Maria

Abstract

Biotransformation of inorganic arsenic (iAs) is one of the factors that determines the character and magnitude of the diverse detrimental health effects associated with chronic iAs exposure, but it is unknown how iAs biotransformation may impact the epigenome. Here, we integrated analyses of genome-wide, gene-specific promoter DNA methylation levels of peripheral blood leukocytes (PBLs) with urinary arsenical concentrations of subjects from a region of Mexico with high levels of iAs in drinking water. These analyses revealed dramatic differences in DNA methylation profiles associated with concentrations of specific urinary metabolites of arsenic. The majority of individuals in this study had positive indicators of arsenic-related disease, namely pre-diabetes mellitus or diabetes mellitus. Methylation patterns of genes with known associations to diabetes mellitus were associated with urinary concentrations of specific iAs metabolites. Future studies will determine whether these DNA methylation profiles provide mechanistic insight into the development of iAs-associated disease, predict disease risk, and/or serve as biomarkers of iAs exposure in humans.

Published
2013
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155. The Value of Statistical or Bioinformatics Annotation for Rare Variant Association with Quantitative Trait

Author

Wu, Michael C., Li, Yun, Byrnes, Andrea E., Li, Mingyao, and Wright, Fred A.

Abstract

In the past few years, a plethora of methods for rare variant association with phenotype have been proposed. These methods aggregate information from multiple rare variants across genomic region(s), but there is little consensus as to which method is most effective. The weighting scheme adopted when aggregating information across variants is one of the primary determinants of effectiveness. Here we present a systematic evaluation of multiple weighting schemes through a series of simulations intended to mimic large sequencing studies of a quantitative trait. We evaluate existing phenotype-independent and -dependent methods, as well as weights estimated by penalized regression approaches including Lasso, Elastic Net and SCAD. We find that the difference in power between phenotype-dependent schemes is negligible when high quality functional annotations are available. When functional annotations are unavailable or incomplete, all methods suffer from power loss; however, the variable selection methods outperform the others at the cost of increased computational time. Therefore, in the absence of good annotation, we recommend variable selection methods (which can be viewed as “statistical annotation”) on top regions implicated by a phenotype independent weighting scheme. Further, once a region is implicated, variable selection can help to identify potential causal SNPs for biological validation. These findings are supported by an analysis of a high coverage targeted sequencing study of 1898 individuals.

Published
2013
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169. A novel copy number variants kernel association test with application to autism spectrum disorders studies.

Author

Xiang Zhan, Girirajan, Santhosh, Ni Zhao, Wu, Michael C., and Ghosh, Debashis

Subjects
AUTISM spectrum disorders, ASSOCIATION tests, DNA copy number variations, NEURODEVELOPMENTAL treatment, INTELLECTUAL disabilities, SCHIZOPHRENIA, ETIOLOGY of diseases
Abstract

Motivation: Copy number variants (CNVs) have been implicated in a variety of neurodevelopmental disorders, including autism spectrum disorders, intellectual disability and schizophrenia. Recent advances in high-throughput genomic technologies have enabled rapid discovery of many genetic variants including CNVs. As a result, there is increasing interest in studying the role of CNVs in the etiology of many complex diseases. Despite the availability of an unprecedented wealth of CNV data, methods for testing association between CNVs and disease-related traits are still underdeveloped due to the low prevalence and complicated multi-scale features of CNVs. Results: We propose a novel CNV kernel association test (CKAT) in this paper. To address the low prevalence, CNVs are first grouped into CNV regions (CNVR). Then, taking into account the multiscale features of CNVs, we first design a single-CNV kernel which summarizes the similarity between two CNVs, and next aggregate the single-CNV kernel to a CNVR kernel which summarizes the similarity between two CNVRs. Finally, association between CNVR and disease-related traits is assessed by comparing the kernel-based similarity with the similarity in the trait using a score test for variance components in a random effect model. We illustrate the proposed CKAT using simulations and show that CKAT is more powerful than existing methods, while always being able to control the type I error. We also apply CKAT to a real dataset examining the association between CNV and autism spectrum disorders, which demonstrates the potential usefulness of the proposed method. [ABSTRACT FROM AUTHOR]

Published
2016
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172. Goodness-of-fit test for nonparametric regression models: Smoothing spline ANOVA models as example.

Author

Teran Hidalgo, Sebastian J., Wu, Michael C., Engel, Stephanie M., and Kosorok, Michael R.

Subjects
*ANALYSIS of variance, *REGRESSION analysis, *NONPARAMETRIC statistics, *P-value (Statistics), *DATA analysis
Abstract

Nonparametric regression models do not require the specification of the functional form between the outcome and the covariates. Despite their popularity, the amount of diagnostic statistics, in comparison to their parametric counterparts, is small. We propose a goodness-of-fit test for nonparametric regression models with linear smoother form. In particular, we apply this testing framework to smoothing spline ANOVA models. The test can consider two sources of lack-of-fit: whether covariates that are not currently in the model need to be included, and whether the current model fits the data well. The proposed method derives estimated residuals from the model. Then, statistical dependence is assessed between the estimated residuals and the covariates using the HSIC. If dependence exists, the model does not capture all the variability in the outcome associated with the covariates, otherwise the model fits the data well. The bootstrap is used to obtain p -values. Application of the method is demonstrated with a neonatal mental development data analysis. We demonstrate correct type I error as well as power performance through simulations. [ABSTRACT FROM AUTHOR]

Published
2018
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178. Abstract 4598: Identification of driver genes in hepatocellular carcinoma by exome sequencing.

Author

Cleary, Sean P., primary, Jeck, William R., additional, Zhao, Xiaobei, additional, Selitsky, Sara R., additional, Savich, Gleb L., additional, Tan, Ting-Xu, additional, Wu, Michael C., additional, Getz, Gad, additional, Lawrence, Michael S., additional, Parker, Joel S., additional, Li, Jinyu, additional, Powers, Scott, additional, Kim, Hyeja, additional, Fischer, Sandra E., additional, Guindi, Maha, additional, Ghanekar, Anand, additional, and Chiang, Derek Y., additional

Published
2013
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179. Cytochrome P450-derived eicosanoids and vascular dysfunction in coronary artery disease patients

Author

Schuck, Robert N., primary, Theken, Katherine N., additional, Edin, Matthew L., additional, Caughey, Melissa, additional, Bass, Almasa, additional, Ellis, Kyle, additional, Tran, Bryant, additional, Steele, Savanna, additional, Simmons, Brian P., additional, Lih, Fred B., additional, Tomer, Kenneth B., additional, Wu, Michael C., additional, Hinderliter, Alan L., additional, Stouffer, George A., additional, Zeldin, Darryl C., additional, and Lee, Craig R., additional

Published
2013
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182. Salivary proteins associated with hyperglycemia in diabetes: a proteomic analysis

Author

Bencharit, Sompop, primary, Baxter, Sarah Schwartz, additional, Carlson, Jim, additional, Byrd, Warren C., additional, Mayo, Mary Virginia, additional, Border, Michael B., additional, Kohltfarber, Heidi, additional, Urrutia, Eugene, additional, Howard-Williams, Escher L., additional, Offenbacher, Steven, additional, Wu, Michael C., additional, and Buse, John B., additional

Published
2013
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183. Test for Rare Variants by Environment Interactions in Sequencing Association Studies.

Author

Lin, Xinyi, Lee, Seunggeun, Wu, Michael C., Wang, Chaolong, Chen, Han, Li, Zilin, and Lin, Xihong

Subjects
ADIPONECTIN, ERROR rates, KERNEL operating systems, REGRESSION analysis, ANALYSIS of covariance
Abstract

We consider in this article testing rare variants by environment interactions in sequencing association studies. Current methods for studying the association of rare variants with traits cannot be readily applied for testing for rare variants by environment interactions, as these methods do not effectively control for the main effects of rare variants, leading to unstable results and/or inflated Type 1 error rates. We will first analytically study the bias of the use of conventional burdenbased tests for rare variants by environment interactions, and show the tests can often be invalid and result in inflated Type 1 error rates. To overcome these difficulties, we develop the interaction sequence kernel association test (iSKAT) for assessing rare variants by environment interactions. The proposed test iSKAT is optimal in a class of variance component tests and is powerful and robust to the proportion of variants in a gene that interact with environment and the signs of the effects. This test properly controls for the main effects of the rare variants using weighted ridge regression while adjusting for covariates. We demonstrate the performance of iSKAT using simulation studies and illustrate its application by analysis of a candidate gene sequencing study of plasma adiponectin levels. [ABSTRACT FROM AUTHOR]

Published
2016
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185. Evaluation of cytochrome P450-derived eicosanoids in humans with stable atherosclerotic cardiovascular disease

Author

Theken, Katherine N., primary, Schuck, Robert N., additional, Edin, Matthew L., additional, Tran, Bryant, additional, Ellis, Kyle, additional, Bass, Almasa, additional, Lih, Fred B., additional, Tomer, Kenneth B., additional, Poloyac, Samuel M., additional, Wu, Michael C., additional, Hinderliter, Alan L., additional, Zeldin, Darryl C., additional, Stouffer, George A., additional, and Lee, Craig R., additional

Published
2012
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186. Maternal Tobacco Smoke Exposure Relates To Epigenetic Changes In Fetal Cord Blood: A Genome-Wide Methylation Study

Author

Joubert, Bonnie R., primary, Haberg, Siri E., additional, Nilsen, Roy M., additional, Wang, Xuting, additional, Bell, Douglas A., additional, Wu, Michael C., additional, Cupul-Uicab, Lea A., additional, Midttun, O., additional, Vollset, Stein Emil, additional, Ueland, Per M., additional, Nystad, Wenche, additional, Peddada, Shyamal D., additional, and London, Stephanie, additional

Published
2012
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189. Intracorneal and Intraocular Invasion of Ocular Surface Squamous Neoplasia after Intraocular Surgery:Report of Two Cases and Review of the Literature

Author

Murillo, Juan C., Galor, Anat, Wu, Michael C., Kye, Natasha K., Wong, James, Ahmed, Ibrahim O., Joag, Madhura, Shalabi, Nabeel, Lahners, William, Dubovy, Sander, and Karp, Carol L.

Abstract

Purpose:The aim of this paper was to describe 2 cases of ocular surface squamous neoplasia (OSSN) of the conjunctiva with intracorneal and intraocular extension following intraocular surgery. Methods:We conducted a clinical pathological retrospective case series. Results:Case 1 underwent cataract surgery in the setting of an unnoticed adjacent OSSN. An excisional biopsy with cryotherapy and intraoperative mitomycin C was subsequently performed, confirming OSSN. The patient had two recurrences treated topically with resolution. While the conjunctiva remained clear, a corneal haze emanating from the cataract incision site was noted. Penetrating keratoplasty (PK) for this haze revealed midstromal infiltrative carcinoma. Case 2 had a history of herpes simplex keratitis that ultimately required corneal grafts. Fifteen years later, he developed an OSSN treated with excisional biopsy and had clear margins. Eight months later, he presented with a recurrence of his OSSN and was treated briefly with topical interferon for 4 weeks; however, he developed an infectious keratitis with a corneal perforation requiring another PK. Four months after PK, low-grade inflammation was noted. Cytology of the anterior chamber aspirate revealed neoplastic squamous cells. Another PK was then performed. Pathology confirmed extensive intraocular neoplasia. Limited exenteration was performed. Conclusion:Patients with a history of OSSN may be at increased risk of neoplastic intraocular extension following intraocular surgery.

Published
2017
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190. Reader Reaction: A note on testing and estimation in marker‐set association study using semiparametric quantile regression kernel machine.

Author

Wu, Michael C. and Zhan, Xiang

Subjects
*QUANTILE regression, *KERNEL operating systems, *PERMUTATIONS, *NUMERICAL calculations, *GENETIC markers
Abstract

Summary: Kong et al. (2016, Biometrics 72, 364–371) presented a quantile regression kernel machine (QRKM) test for robust analysis of genetic marker‐set association studies. A potential limitation of QRKM is the permutation‐based test design may be unscalable for the massive sizes of modern datasets. In this article, we present an alternative strategy for p‐value calculation of QRKM, which is capable of speeding up the QRKM testing procedure dramatically while maintaining the same testing performance as QRKM. The effectiveness of our approach is demonstrated via simulation studies. [ABSTRACT FROM AUTHOR]

Published
2018
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196. Cervical Multilevel Intraspinal Stem Cell Therapy

Author

Raore, Bethwel, primary, Federici, Thais, additional, Taub, Jason, additional, Wu, Michael C., additional, Riley, Jonathan, additional, Franz, Colin K., additional, Kliem, Michele A., additional, Snyder, Brooke, additional, Feldman, Eva L., additional, Johe, Karl, additional, and Boulis, Nicholas M., additional

Published
2011
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198. Variation in folate pathway genes contributes to risk of congenital heart defects among individuals with Down syndrome

Author

Locke, Adam E., primary, Dooley, Kenneth J., additional, Tinker, Stuart W., additional, Cheong, Soo Yeon, additional, Feingold, Eleanor, additional, Allen, Emily G., additional, Freeman, Sallie B., additional, Torfs, Claudine P., additional, Cua, Clifford L., additional, Epstein, Michael P., additional, Wu, Michael C., additional, Lin, Xihong, additional, Capone, George, additional, Sherman, Stephanie L., additional, and Bean, Lora J.H., additional

Published
2010
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199. Genome-Wide Analysis of Survival in Early-Stage Non–Small-Cell Lung Cancer

Author

Huang, Yen-Tsung, primary, Heist, Rebecca S., additional, Chirieac, Lucian R., additional, Lin, Xihong, additional, Skaug, Vidar, additional, Zienolddiny, Shanbeh, additional, Haugen, Aage, additional, Wu, Michael C., additional, Wang, Zhaoxi, additional, Su, Li, additional, Asomaning, Kofi, additional, and Christiani, David C., additional

Published
2009
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