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14 results on '"Schadt, Eric"'

1. Management of de novo metastatic hormone-sensitive prostate cancer: A comprehensive report of a single-center experience

Author

Guin, Sunny, primary, Liaw, Bobby K., additional, Jun, Tomi, additional, Ayers, Kristin, additional, Patel, Bonny, additional, O’Connell, Timmy, additional, Deitz, Matthew, additional, Klein, Michael, additional, Mullaney, Tommy, additional, Prentice, Tony, additional, Newman, Scott, additional, Fink, Marc, additional, Zhou, Xiang, additional, Schadt, Eric E., additional, Chen, Rong, additional, and Oh, William K., additional

Published
2022
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2. Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers

Author

Pereira, Elena, primary, Camacho-Vanegas, Olga, additional, Anand, Sanya, additional, Sebra, Robert, additional, Catalina Camacho, Sandra, additional, Garnar-Wortzel, Leopold, additional, Nair, Navya, additional, Moshier, Erin, additional, Wooten, Melissa, additional, Uzilov, Andrew, additional, Chen, Rong, additional, Prasad-Hayes, Monica, additional, Zakashansky, Konstantin, additional, Beddoe, Ann Marie, additional, Schadt, Eric, additional, Dottino, Peter, additional, and Martignetti, John A., additional

Published
2015
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4. Predictive Genes in Adjacent Normal Tissue Are Preferentially Altered by sCNV during Tumorigenesis in Liver Cancer and May Rate Limiting

Author

Lamb, John R., primary, Zhang, Chunsheng, additional, Xie, Tao, additional, Wang, Kai, additional, Zhang, Bin, additional, Hao, Ke, additional, Chudin, Eugene, additional, Fraser, Hunter B., additional, Millstein, Joshua, additional, Ferguson, Mark, additional, Suver, Christine, additional, Ivanovska, Irena, additional, Scott, Martin, additional, Philippar, Ulrike, additional, Bansal, Dimple, additional, Zhang, Zhan, additional, Burchard, Julja, additional, Smith, Ryan, additional, Greenawalt, Danielle, additional, Cleary, Michele, additional, Derry, Jonathan, additional, Loboda, Andrey, additional, Watters, James, additional, Poon, Ronnie T. P., additional, Fan, Sheung T., additional, Yeung, Chun, additional, Lee, Nikki P. Y., additional, Guinney, Justin, additional, Molony, Cliona, additional, Emilsson, Valur, additional, Buser-Doepner, Carolyn, additional, Zhu, Jun, additional, Friend, Stephen, additional, Mao, Mao, additional, Shaw, Peter M., additional, Dai, Hongyue, additional, Luk, John M., additional, and Schadt, Eric E., additional

Published
2011
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5. Identification of Genes and Networks Driving Cardiovascular and Metabolic Phenotypes in a Mouse F2 Intercross

Author

Derry, Jonathan M. J., primary, Zhong, Hua, additional, Molony, Cliona, additional, MacNeil, Doug, additional, Guhathakurta, Debraj, additional, Zhang, Bin, additional, Mudgett, John, additional, Small, Kersten, additional, El Fertak, Lahcen, additional, Guimond, Alain, additional, Selloum, Mohammed, additional, Zhao, Wenqing, additional, Champy, Marie France, additional, Monassier, Laurent, additional, Vogt, Tom, additional, Cully, Doris, additional, Kasarskis, Andrew, additional, and Schadt, Eric E., additional

Published
2010
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10. Uncovering the Genetic Landscape for Multiple Sleep-Wake Traits

Author

Winrow, Christopher J., primary, Williams, Deanna L., additional, Kasarskis, Andrew, additional, Millstein, Joshua, additional, Laposky, Aaron D., additional, Yang, He S., additional, Mrazek, Karrie, additional, Zhou, Lili, additional, Owens, Joseph R., additional, Radzicki, Daniel, additional, Preuss, Fabian, additional, Schadt, Eric E., additional, Shimomura, Kazuhiro, additional, Vitaterna, Martha H., additional, Zhang, Chunsheng, additional, Koblan, Kenneth S., additional, Renger, John J., additional, and Turek, Fred W., additional

Published
2009
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11. Concept, Design and Implementation of a Cardiovascular Gene-Centric 50 K SNP Array for Large-Scale Genomic Association Studies

Author

Keating, Brendan J., primary, Tischfield, Sam, additional, Murray, Sarah S., additional, Bhangale, Tushar, additional, Price, Thomas S., additional, Glessner, Joseph T., additional, Galver, Luana, additional, Barrett, Jeffrey C., additional, Grant, Struan F. A., additional, Farlow, Deborah N., additional, Chandrupatla, Hareesh R., additional, Hansen, Mark, additional, Ajmal, Saad, additional, Papanicolaou, George J., additional, Guo, Yiran, additional, Li, Mingyao, additional, DerOhannessian, Stephanie, additional, de Bakker, Paul I. W., additional, Bailey, Swneke D., additional, Montpetit, Alexandre, additional, Edmondson, Andrew C., additional, Taylor, Kent, additional, Gai, Xiaowu, additional, Wang, Susanna S., additional, Fornage, Myriam, additional, Shaikh, Tamim, additional, Groop, Leif, additional, Boehnke, Michael, additional, Hall, Alistair S., additional, Hattersley, Andrew T., additional, Frackelton, Edward, additional, Patterson, Nick, additional, Chiang, Charleston W. K., additional, Kim, Cecelia E., additional, Fabsitz, Richard R., additional, Ouwehand, Willem, additional, Price, Alkes L., additional, Munroe, Patricia, additional, Caulfield, Mark, additional, Drake, Thomas, additional, Boerwinkle, Eric, additional, Reich, David, additional, Whitehead, A. Stephen, additional, Cappola, Thomas P., additional, Samani, Nilesh J., additional, Lusis, A. Jake, additional, Schadt, Eric, additional, Wilson, James G., additional, Koenig, Wolfgang, additional, McCarthy, Mark I., additional, Kathiresan, Sekar, additional, Gabriel, Stacey B., additional, Hakonarson, Hakon, additional, Anand, Sonia S., additional, Reilly, Muredach, additional, Engert, James C., additional, Nickerson, Deborah A., additional, Rader, Daniel J., additional, Hirschhorn, Joel N., additional, and FitzGerald, Garret A., additional

Published
2008
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12. Magnitude of Stratification in Human Populations and Impacts on Genome Wide Association Studies.

Author

Ke Hao, Chudin, Eugene, Greenawalt, Danielle, and Schadt, Eric E.

Subjects
GENOMES, POPULATION, CAUCASIAN race, AFRICAN Americans, HISPANIC Americans, GENE expression, RNA, LIVER, TISSUES
Abstract

Genome-wide association studies (GWAS) may be biased by population stratification (PS). We conducted empirical quantification of the magnitude of PS among human populations and its impact on GWAS. Liver tissues were collected from 979, 59 and 49 Caucasian Americans (CA), African Americans (AA) and Hispanic Americans (HA), respectively, and genotyped using Illumina650Y (Ilmn650Y) arrays. RNA was also isolated and hybridized to Agilent whole-genome gene expression arrays. We propose a new method (i.e., hgdp-eigen) for detecting PS by projecting genotype vectors for each sample to the eigenvector space defined by the Human Genetic Diversity Panel (HGDP). Further, we conducted GWAS to map expression quantitative trait loci (eQTL) for the ∼40,000 liver gene expression traits monitored by the Agilent arrays. HGDP-eigen performed similarly to the conventional self-eigen methods in capturing PS. However, leveraging the HGDP offered a significant advantage in revealing the origins, directions and magnitude of PS. Adjusting for eigenvectors had minor impacts on eQTL detection rates in CA. In contrast, for AA and HA, adjustment dramatically reduced association findings. At an FDR = 10%, we identified 65 eQTLs in AA with the unadjusted analysis, but only 18 eQTLs after the eigenvector adjustment. Strikingly, 55 out of the 65 unadjusted AA eQTLs were validated in CA, indicating that the adjustment procedure significantly reduced GWAS power. A number of the 55 AA eQTLs validated in CA overlapped with published disease associated SNPs. For example, rs646776 and rs10903129 have previously been associated with lipid levels and coronary heart disease risk, however, the rs10903129 eQTL was missed in the eigenvector adjusted analysis. [ABSTRACT FROM AUTHOR]

Published
2010
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13. Uncovering the Genetic Landscape for Multiple Sleep- Wake Traits.

Author

,4Winrow, Christopher J., Williams, Deanna L., Kasarskis, Andrew, Millstein, Joshua, Laposky, Aaron D., Yang, He S., Mrazek, Karrie, Zhou, Lili, Owens, Joseph R., Radzicki, Daniel, Preuss, Fabian, Schadt, Eric E., Shimomura, Kazuhiro, Vitaterna, Martha H., Chunsheng Zhang, Koblan, Kenneth S., Renger, John J., and Turek, Fred W.

Subjects
SLEEP physiology, GENETIC regulation, CHROMOSOME abnormalities, LOCUS (Genetics), CELL nuclei
Abstract

Despite decades of research in defining sleep-wake properties in mammals, little is known about the nature or identity of genes that regulate sleep, a fundamental behaviour that in humans occupies about one-third of the entire lifespan. While genome-wide association studies in humans and quantitative trait loci (QTL) analyses in mice have identified candidate genes for an increasing number of complex traits and genetic diseases, the resources and time-consuming process necessary for obtaining detailed quantitative data have made sleep seemingly intractable to similar large-scale genomic approaches. Here we describe analysis of 20 sleep-wake traits from 269 mice from a genetically segregating population that reveals 52 significant QTL representing a minimum of 20 genomic loci. While many (28) QTL affected a particular sleep-wake trait (e.g., amount of wake) across the full 24-hr day, other loci only affected a trait in the light or dark period while some loci had opposite effects on the trait during the light vs. dark. Analysis of a dataset for multiple sleep-wake traits led to previously undetected interactions (including the differential genetic control of number and duration of REM bouts), as well as possible shared genetic regulatory mechanisms for seemingly different unrelated sleep-wake traits (e.g., number of arousals and REM latency). Construction of a Bayesian network for sleep-wake traits and loci led to the identification of subnetworks of linkage not detectable in smaller data sets or limited single-trait analyses. For example, the network analyses revealed a novel chain of causal relationships between the chromosome 17@29cM QTL, total amount of wake, and duration of wake bouts in both light and dark periods that implies a mechanism whereby overall sleep need, mediated by this locus, in turn determines the length of each wake bout. Taken together, the present results reveal a complex genetic landscape underlying multiple sleep-wake traits and emphasize the need for a systems biology approach for elucidating the full extent of the genetic regulatory mechanisms of this complex and universal behavior. [ABSTRACT FROM AUTHOR]

Published
2009
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14. Fine-mapping, gene expression and splicing analysis of the disease associated LRRK2 locus.

Author

Trabzuni D, Ryten M, Emmett W, Ramasamy A, Lackner KJ, Zeller T, Walker R, Smith C, Lewis PA, Mamais A, de Silva R, Vandrovcova J, Hernandez D, Nalls MA, Sharma M, Garnier S, Lesage S, Simon-Sanchez J, Gasser T, Heutink P, Brice A, Singleton A, Cai H, Schadt E, Wood NW, Bandopadhyay R, Weale ME, Hardy J, and Plagnol V

Subjects
Brain metabolism, Brain pathology, Crohn Disease genetics, Exons, Genetic Association Studies, Humans, Leprosy, Leucine-Rich Repeat Serine-Threonine Protein Kinase-2, Male, Parkinson Disease genetics, Polymorphism, Single Nucleotide, RNA, Messenger genetics, RNA, Messenger metabolism, Alternative Splicing, Gene Expression Profiling, Gene Expression Regulation, Protein Serine-Threonine Kinases genetics, Quantitative Trait Loci
Abstract

Association studies have identified several signals at the LRRK2 locus for Parkinson's disease (PD), Crohn's disease (CD) and leprosy. However, little is known about the molecular mechanisms mediating these effects. To further characterize this locus, we fine-mapped the risk association in 5,802 PD and 5,556 controls using a dense genotyping array (ImmunoChip). Using samples from 134 post-mortem control adult human brains (UK Human Brain Expression Consortium), where up to ten brain regions were available per individual, we studied the regional variation, splicing and regulation of LRRK2. We found convincing evidence for a common variant PD association located outside of the LRRK2 protein coding region (rs117762348, A>G, P = 2.56×10(-8), case/control MAF 0.083/0.074, odds ratio 0.86 for the minor allele with 95% confidence interval [0.80-0.91]). We show that mRNA expression levels are highest in cortical regions and lowest in cerebellum. We find an exon quantitative trait locus (QTL) in brain samples that localizes to exons 32-33 and investigate the molecular basis of this eQTL using RNA-Seq data in n = 8 brain samples. The genotype underlying this eQTL is in strong linkage disequilibrium with the CD associated non-synonymous SNP rs3761863 (M2397T). We found two additional QTLs in liver and monocyte samples but none of these explained the common variant PD association at rs117762348. Our results characterize the LRRK2 locus, and highlight the importance and difficulties of fine-mapping and integration of multiple datasets to delineate pathogenic variants and thus develop an understanding of disease mechanisms.

Published
2013
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