32 results on '"Zhao, Sihai D"'
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2. Capturing patterns of variation unique to a specific dataset
- Author
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Tu, Robin, Foss, Alexander H., and Zhao, Sihai D.
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Computer Science - Machine Learning ,Statistics - Methodology - Abstract
Capturing patterns of variation present in a dataset is important in exploratory data analysis and unsupervised learning. Contrastive dimension reduction methods, such as contrastive principal component analysis (cPCA), find patterns unique to a target dataset of interest by contrasting with a carefully chosen background dataset representing unwanted or uninteresting variation. However, such methods typically require a tuning parameter that governs the level of contrast, and it is unclear how to choose this parameter objectively. Furthermore, it is frequently of interest to contrast against multiple backgrounds, which is difficult to accomplish with existing methods. We propose unique component analysis (UCA), a tuning-free method that identifies low-dimensional representations of a target dataset relative to one or more comparison datasets. It is computationally efficient even with large numbers of features. We show in several experiments that UCA with a single background dataset achieves similar results compared to cPCA with various tuning parameters, and that UCA with multiple individual background datasets is superior to both cPCA with any single background data and cPCA with a pooled background dataset.
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- 2021
3. Nonparametric empirical Bayes and maximum likelihood estimation for high-dimensional data analysis
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Dicker, Lee H. and Zhao, Sihai D.
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Statistics - Methodology - Abstract
Nonparametric empirical Bayes methods provide a flexible and attractive approach to high-dimensional data analysis. One particularly elegant empirical Bayes methodology, involving the Kiefer-Wolfowitz nonparametric maximum likelihood estimator (NPMLE) for mixture models, has been known for decades. However, implementation and theoretical analysis of the Kiefer-Wolfowitz NPMLE are notoriously difficult. A fast algorithm was recently proposed that makes NPMLE-based procedures feasible for use in large-scale problems, but the algorithm calculates only an approximation to the NPMLE. In this paper we make two contributions. First, we provide upper bounds on the convergence rate of the approximate NPMLE's statistical error, which have the same order as the best known bounds for the true NPMLE. This suggests that the approximate NPMLE is just as effective as the true NPMLE for statistical applications. Second, we illustrate the promise of NPMLE procedures in a high-dimensional binary classification problem. We propose a new procedure and show that it vastly outperforms existing methods in experiments with simulated data. In real data analyses involving cancer survival and gene expression data, we show that it is very competitive with several recently proposed methods for regularized linear discriminant analysis, another popular approach to high-dimensional classification.
- Published
- 2014
4. Sure screening for estimating equations in ultra-high dimensions
- Author
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Zhao, Sihai D. and Li, Yi
- Subjects
Statistics - Methodology - Abstract
As the number of possible predictors generated by high-throughput experiments continues to increase, methods are needed to quickly screen out unimportant covariates. Model-based screening methods have been proposed and theoretically justified, but only for a few specific models. Model-free screening methods have also recently been studied, but can have lower power to detect important covariates. In this paper we propose EEScreen, a screening procedure that can be used with any model that can be fit using estimating equations, and provide unified results on its finite-sample screening performance. EEScreen thus generalizes many recently proposed model-based and model-free screening procedures. We also propose iEEScreen, an iterative version of EEScreen, and show that it is closely related to a recently studied boosting method for estimating equations. We show via simulations for two different estimating equations that EEScreen and iEEScreen are useful and flexible screening procedures, and demonstrate our methods on data from a multiple myeloma study.
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- 2011
5. Power of testing for exposure effects under incomplete mediation.
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Zhou, Ruixuan R., Zucker, David M., and Zhao, Sihai D.
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DNA analysis ,SMOKING ,NULL hypothesis ,DNA methylation ,GENE expression ,CIGARETTE smoke ,NICOTINE - Abstract
Mediation analysis studies situations where an exposure may affect an outcome both directly and indirectly through intervening variables called mediators. It is frequently of interest to test for the effect of the exposure on the outcome, and the standard approach is simply to regress the latter on the former. However, it seems plausible that a more powerful test statistic could be achieved by also incorporating the mediators. This would be useful in cases where the exposure effect size might be small, which for example is common in genomics applications. Previous work has shown that this is indeed possible under complete mediation, where there is no direct effect. In most applications, however, the direct effect is likely nonzero. In this paper we study linear mediation models and find that under certain conditions, power gain is still possible under this incomplete mediation setting for testing the null hypothesis that there is neither a direct nor an indirect effect. We study a class of procedures that can achieve this performance and develop their application to both low- and high-dimensional mediators. We then illustrate their performances in simulations as well as in an analysis using DNA methylation mediators to study the effect of cigarette smoking on gene expression. [ABSTRACT FROM AUTHOR]
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- 2024
- Full Text
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6. Deep evolutionary conservation of autism-related genes
- Author
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Shpigler, Hagai Y., Saul, Michael C., Corona, Frida, Block, Lindsey, Ahmed, Amy Cash, Zhao, Sihai D., and Robinson, Gene E.
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- 2017
7. Identification and targeting of microbial putrescine acetylation in bloodstream infections
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Mayers, Jared R., primary, Varon, Jack, additional, Zhou, Ruixuan R., additional, Daniel-Ivad, Martin, additional, Beaulieu, Courtney, additional, Bholse, Amrisha, additional, Glasser, Nathaniel R., additional, Lichtenauer, Franziska M., additional, Ng, Julie, additional, Pinilla Vera, Mayra, additional, Huttenhower, Curtis, additional, Perrella, Mark A., additional, Clish, Clary B., additional, Zhao, Sihai D., additional, Baron, Rebecca M., additional, and Balskus, Emily P., additional
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- 2023
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8. Power of testing for exposure effects under incomplete mediation
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Zhou, Ruixuan R., primary, Zucker, David M., additional, and Zhao, Sihai D., additional
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- 2023
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9. Supplementary File 3 from Bayesian Machine Learning Enables Identification of Transcriptional Network Disruptions Associated with Drug-Resistant Prostate Cancer
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Blatti, Charles, primary, de la Fuente, Jesús, primary, Gao, Huanyao, primary, Marín-Goñi, Irene, primary, Chen, Zikun, primary, Zhao, Sihai D., primary, Tan, Winston, primary, Weinshilboum, Richard, primary, Kalari, Krishna R., primary, Wang, Liewei, primary, and Hernaez, Mikel, primary
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- 2023
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10. Supplementary File 2 from Bayesian Machine Learning Enables Identification of Transcriptional Network Disruptions Associated with Drug-Resistant Prostate Cancer
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Blatti, Charles, primary, de la Fuente, Jesús, primary, Gao, Huanyao, primary, Marín-Goñi, Irene, primary, Chen, Zikun, primary, Zhao, Sihai D., primary, Tan, Winston, primary, Weinshilboum, Richard, primary, Kalari, Krishna R., primary, Wang, Liewei, primary, and Hernaez, Mikel, primary
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- 2023
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11. Supplementary File 1 from Bayesian Machine Learning Enables Identification of Transcriptional Network Disruptions Associated with Drug-Resistant Prostate Cancer
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Blatti, Charles, primary, de la Fuente, Jesús, primary, Gao, Huanyao, primary, Marín-Goñi, Irene, primary, Chen, Zikun, primary, Zhao, Sihai D., primary, Tan, Winston, primary, Weinshilboum, Richard, primary, Kalari, Krishna R., primary, Wang, Liewei, primary, and Hernaez, Mikel, primary
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- 2023
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12. Data from Bayesian Machine Learning Enables Identification of Transcriptional Network Disruptions Associated with Drug-Resistant Prostate Cancer
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Blatti, Charles, primary, de la Fuente, Jesús, primary, Gao, Huanyao, primary, Marín-Goñi, Irene, primary, Chen, Zikun, primary, Zhao, Sihai D., primary, Tan, Winston, primary, Weinshilboum, Richard, primary, Kalari, Krishna R., primary, Wang, Liewei, primary, and Hernaez, Mikel, primary
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- 2023
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13. Supplementary File 4 from Bayesian Machine Learning Enables Identification of Transcriptional Network Disruptions Associated with Drug-Resistant Prostate Cancer
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Blatti, Charles, primary, de la Fuente, Jesús, primary, Gao, Huanyao, primary, Marín-Goñi, Irene, primary, Chen, Zikun, primary, Zhao, Sihai D., primary, Tan, Winston, primary, Weinshilboum, Richard, primary, Kalari, Krishna R., primary, Wang, Liewei, primary, and Hernaez, Mikel, primary
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- 2023
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14. High-dimensional classification via nonparametric empirical Bayes and maximum likelihood inference
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DICKER, LEE H. and ZHAO, SIHAI D.
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- 2016
15. Bayesian machine learning enables identification of transcriptional network disruptions associated with drug-resistant prostate cancer
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Blatti, Charles, primary, de la Fuente, Jesús, additional, Gao, Huanyao, additional, Marín-Goñi, Irene, additional, Chen, Zikun, additional, Zhao, Sihai D., additional, Tan, Winston, additional, Weinshilboum, Richard, additional, Kalari, Krishna R., additional, Wang, Liewei, additional, and Hernaez, Mikel, additional
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- 2023
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16. Comprehensive Genomic Characterization of Long Non-coding RNAs across Human Cancers
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Yan, Xiaohui, Hu, Zhongyi, Feng, Yi, Hu, Xiaowen, Yuan, Jiao, Zhao, Sihai D., Zhang, Youyou, Yang, Lu, Shan, Weiwei, He, Qun, Fan, Lingling, Kandalaft, Lana E., Tanyi, Janos L., Li, Chunsheng, Yuan, Chao-Xing, Zhang, Dongmei, Yuan, Huiqing, Hua, Keqin, Lu, Yiling, Katsaros, Dionyssios, Huang, Qihong, Montone, Kathleen, Fan, Yi, Coukos, George, Boyd, Jeff, Sood, Anil K., Rebbeck, Timothy, Mills, Gordon B., Dang, Chi V., and Zhang, Lin
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- 2015
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17. A Functional Genomic Approach Identifies FAL1 as an Oncogenic Long Noncoding RNA that Associates with BMI1 and Represses p21 Expression in Cancer
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Hu, Xiaowen, Feng, Yi, Zhang, Dongmei, Zhao, Sihai D., Hu, Zhongyi, Greshock, Joel, Zhang, Youyou, Yang, Lu, Zhong, Xiaomin, Wang, Li-Ping, Jean, Stephanie, Li, Chunsheng, Huang, Qihong, Katsaros, Dionyssios, Montone, Kathleen T., Tanyi, Janos L., Lu, Yiling, Boyd, Jeff, Nathanson, Katherine L., Li, Hongzhe, Mills, Gordon B., and Zhang, Lin
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- 2014
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18. More Powerful Genetic Association Testing via a New Statistical Framework for Integrative Genomics
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Zhao, Sihai D. and Cai, T. Tony
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- 2014
19. Identification of transcriptional network disruptions in drug-resistant prostate cancer with TraRe
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Blatti, Charles, primary, de la Fuente, Jesús, additional, Gao, Huanyao, additional, Marín, Irene, additional, Chen, Zikun, additional, Zhao, Sihai. D., additional, Tan, Winston, additional, Weinshilbaum, Richard, additional, Kalari, Krishna R., additional, Wang, Liewei, additional, and Hernaez, Mikel, additional
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- 2022
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20. Neck Dissection After Chemoradiotherapy: Timing and Complications
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Goguen, Laura A., Chapuy, Claudia I., Li, Yi, Zhao, Sihai D., and Annino, Donald J.
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- 2010
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21. Integrated Analysis of Genetic Ancestry and Genomic Alterations across Cancers
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Yuan, Jiao, primary, Hu, Zhongyi, additional, Mahal, Brandon A., additional, Zhao, Sihai D., additional, Kensler, Kevin H., additional, Pi, Jingjiang, additional, Hu, Xiaowen, additional, Zhang, Youyou, additional, Wang, Yueying, additional, Jiang, Junjie, additional, Li, Chunsheng, additional, Zhong, Xiaomin, additional, Montone, Kathleen T., additional, Guan, Guoqiang, additional, Tanyi, Janos L., additional, Fan, Yi, additional, Xu, Xiaowei, additional, Morgan, Mark A., additional, Long, Meixiao, additional, Zhang, Yuzhen, additional, Zhang, Rugang, additional, Sood, Anil K., additional, Rebbeck, Timothy R., additional, Dang, Chi V., additional, and Zhang, Lin, additional
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- 2018
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22. Cross‐species systems analysis of evolutionary toolkits of neurogenomic response to social challenge
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Saul, Michael C., primary, Blatti, Charles, additional, Yang, Wei, additional, Bukhari, Syed A., additional, Shpigler, Hagai Y., additional, Troy, Joseph M., additional, Seward, Christopher H., additional, Sloofman, Laura, additional, Chandrasekaran, Sriram, additional, Bell, Alison M., additional, Stubbs, Lisa, additional, Robinson, Gene E., additional, Zhao, Sihai D., additional, and Sinha, Saurabh, additional
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- 2018
- Full Text
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23. Genetic Reduction in Left Ventricular Protein Kinase C-α and Adverse Ventricular Remodeling in Human Subjects
- Author
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Hu, Ray, primary, Morley, Michael P., additional, Brandimarto, Jeffrey, additional, Tucker, Nathan R., additional, Parsons, Victoria A., additional, Zhao, Sihai D., additional, Meder, Benjamin, additional, Katus, Hugo A., additional, Rühle, Frank, additional, Stoll, Monika, additional, Villard, Eric, additional, Cambien, François, additional, Lin, Honghuang, additional, Smith, Nicholas L., additional, Felix, Janine F., additional, Vasan, Ramachandran S., additional, van der Harst, Pim, additional, Newton-Cheh, Christopher, additional, Li, Jin, additional, Kim, Cecilia E., additional, Hakonarson, Hakon, additional, Hannenhalli, Sridhar, additional, Ashley, Euan A., additional, Moravec, Christine S., additional, Tang, W.H. Wilson, additional, Maillet, Marjorie, additional, Molkentin, Jeffery D., additional, Ellinor, Patrick T., additional, Margulies, Kenneth B., additional, and Cappola, Thomas P, additional
- Published
- 2018
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24. Genetic sharing and heritability of paediatric age of onset autoimmune diseases.
- Author
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Li, Yun R, Zhao, Sihai D, Li, Jin, Bradfield, Jonathan P, Mohebnasab, Maede, Steel, Laura, Kobie, Julie, Abrams, Debra J, Mentch, Frank D, Glessner, Joseph T, Guo, Yiran, Wei, Zhi, Connolly, John J, Cardinale, Christopher J, Bakay, Marina, Li, Dong, Maggadottir, S Melkorka, Thomas, Kelly A, Qui, Haijun, Chiavacci, Rosetta M, Kim, Cecilia E, Wang, Fengxiang, Snyder, James, Flatø, Berit, Førre, Øystein, Denson, Lee A, Thompson, Susan D, Becker, Mara L, Guthery, Stephen L, Latiano, Anna, Perez, Elena, Resnick, Elena, Strisciuglio, Caterina, Staiano, Annamaria, Miele, Erasmo, Silverberg, Mark S, Lie, Benedicte A, Punaro, Marilynn, Russell, Richard K, Wilson, David C, Dubinsky, Marla C, Monos, Dimitri S, Annese, Vito, Munro, Jane E, Wise, Carol, Chapel, Helen, Cunningham-Rundles, Charlotte, Orange, Jordan S, Behrens, Edward M, Sullivan, Kathleen E, Kugathasan, Subra, Griffiths, Anne M, Satsangi, Jack, Grant, Struan FA, Sleiman, Patrick MA, Finkel, Terri H, Polychronakos, Constantin, Baldassano, Robert N, Luning Prak, Eline T, Ellis, Justine A, Li, Hongzhe, Keating, Brendan J, Hakonarson, Hakon, Li, Yun R, Zhao, Sihai D, Li, Jin, Bradfield, Jonathan P, Mohebnasab, Maede, Steel, Laura, Kobie, Julie, Abrams, Debra J, Mentch, Frank D, Glessner, Joseph T, Guo, Yiran, Wei, Zhi, Connolly, John J, Cardinale, Christopher J, Bakay, Marina, Li, Dong, Maggadottir, S Melkorka, Thomas, Kelly A, Qui, Haijun, Chiavacci, Rosetta M, Kim, Cecilia E, Wang, Fengxiang, Snyder, James, Flatø, Berit, Førre, Øystein, Denson, Lee A, Thompson, Susan D, Becker, Mara L, Guthery, Stephen L, Latiano, Anna, Perez, Elena, Resnick, Elena, Strisciuglio, Caterina, Staiano, Annamaria, Miele, Erasmo, Silverberg, Mark S, Lie, Benedicte A, Punaro, Marilynn, Russell, Richard K, Wilson, David C, Dubinsky, Marla C, Monos, Dimitri S, Annese, Vito, Munro, Jane E, Wise, Carol, Chapel, Helen, Cunningham-Rundles, Charlotte, Orange, Jordan S, Behrens, Edward M, Sullivan, Kathleen E, Kugathasan, Subra, Griffiths, Anne M, Satsangi, Jack, Grant, Struan FA, Sleiman, Patrick MA, Finkel, Terri H, Polychronakos, Constantin, Baldassano, Robert N, Luning Prak, Eline T, Ellis, Justine A, Li, Hongzhe, Keating, Brendan J, and Hakonarson, Hakon
- Abstract
Autoimmune diseases (AIDs) are polygenic diseases affecting 7-10% of the population in the Western Hemisphere with few effective therapies. Here, we quantify the heritability of paediatric AIDs (pAIDs), including JIA, SLE, CEL, T1D, UC, CD, PS, SPA and CVID, attributable to common genomic variations (SNP-h(2)). SNP-h(2) estimates are most significant for T1D (0.863±s.e. 0.07) and JIA (0.727±s.e. 0.037), more modest for UC (0.386±s.e. 0.04) and CD (0.454±0.025), largely consistent with population estimates and are generally greater than that previously reported by adult GWAS. On pairwise analysis, we observed that the diseases UC-CD (0.69±s.e. 0.07) and JIA-CVID (0.343±s.e. 0.13) are the most strongly correlated. Variations across the MHC strongly contribute to SNP-h(2) in T1D and JIA, but does not significantly contribute to the pairwise rG. Together, our results partition contributions of shared versus disease-specific genomic variations to pAID heritability, identifying pAIDs with unexpected risk sharing, while recapitulating known associations between autoimmune diseases previously reported in adult cohorts.
- Published
- 2015
25. Genetic sharing and heritability of paediatric age of onset autoimmune diseases
- Author
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Li, Yun R., primary, Zhao, Sihai D., additional, Li, Jin, additional, Bradfield, Jonathan P., additional, Mohebnasab, Maede, additional, Steel, Laura, additional, Kobie, Julie, additional, Abrams, Debra J., additional, Mentch, Frank D., additional, Glessner, Joseph T., additional, Guo, Yiran, additional, Wei, Zhi, additional, Connolly, John J., additional, Cardinale, Christopher J., additional, Bakay, Marina, additional, Li, Dong, additional, Maggadottir, S. Melkorka, additional, Thomas, Kelly A., additional, Qui, Haijun, additional, Chiavacci, Rosetta M., additional, Kim, Cecilia E., additional, Wang, Fengxiang, additional, Snyder, James, additional, Flatø, Berit, additional, Førre, Øystein, additional, Denson, Lee A., additional, Thompson, Susan D., additional, Becker, Mara L., additional, Guthery, Stephen L., additional, Latiano, Anna, additional, Perez, Elena, additional, Resnick, Elena, additional, Strisciuglio, Caterina, additional, Staiano, Annamaria, additional, Miele, Erasmo, additional, Silverberg, Mark S., additional, Lie, Benedicte A., additional, Punaro, Marilynn, additional, Russell, Richard K., additional, Wilson, David C., additional, Dubinsky, Marla C., additional, Monos, Dimitri S., additional, Annese, Vito, additional, Munro, Jane E., additional, Wise, Carol, additional, Chapel, Helen, additional, Cunningham-Rundles, Charlotte, additional, Orange, Jordan S., additional, Behrens, Edward M., additional, Sullivan, Kathleen E., additional, Kugathasan, Subra, additional, Griffiths, Anne M., additional, Satsangi, Jack, additional, Grant, Struan F. A., additional, Sleiman, Patrick M. A., additional, Finkel, Terri H., additional, Polychronakos, Constantin, additional, Baldassano, Robert N., additional, Luning Prak, Eline T., additional, Ellis, Justine A., additional, Li, Hongzhe, additional, Keating, Brendan J., additional, and Hakonarson, Hakon, additional
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- 2015
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26. Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases
- Author
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Li, Yun R, primary, Li, Jin, additional, Zhao, Sihai D, additional, Bradfield, Jonathan P, additional, Mentch, Frank D, additional, Maggadottir, S Melkorka, additional, Hou, Cuiping, additional, Abrams, Debra J, additional, Chang, Diana, additional, Gao, Feng, additional, Guo, Yiran, additional, Wei, Zhi, additional, Connolly, John J, additional, Cardinale, Christopher J, additional, Bakay, Marina, additional, Glessner, Joseph T, additional, Li, Dong, additional, Kao, Charlly, additional, Thomas, Kelly A, additional, Qiu, Haijun, additional, Chiavacci, Rosetta M, additional, Kim, Cecilia E, additional, Wang, Fengxiang, additional, Snyder, James, additional, Richie, Marylyn D, additional, Flatø, Berit, additional, Førre, Øystein, additional, Denson, Lee A, additional, Thompson, Susan D, additional, Becker, Mara L, additional, Guthery, Stephen L, additional, Latiano, Anna, additional, Perez, Elena, additional, Resnick, Elena, additional, Russell, Richard K, additional, Wilson, David C, additional, Silverberg, Mark S, additional, Annese, Vito, additional, Lie, Benedicte A, additional, Punaro, Marilynn, additional, Dubinsky, Marla C, additional, Monos, Dimitri S, additional, Strisciuglio, Caterina, additional, Staiano, Annamaria, additional, Miele, Erasmo, additional, Kugathasan, Subra, additional, Ellis, Justine A, additional, Munro, Jane E, additional, Sullivan, Kathleen E, additional, Wise, Carol A, additional, Chapel, Helen, additional, Cunningham-Rundles, Charlotte, additional, Grant, Struan F A, additional, Orange, Jordan S, additional, Sleiman, Patrick M A, additional, Behrens, Edward M, additional, Griffiths, Anne M, additional, Satsangi, Jack, additional, Finkel, Terri H, additional, Keinan, Alon, additional, Prak, Eline T Luning, additional, Polychronakos, Constantin, additional, Baldassano, Robert N, additional, Li, Hongzhe, additional, Keating, Brendan J, additional, and Hakonarson, Hakon, additional
- Published
- 2015
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27. Cross‐species systems analysis of evolutionary toolkits of neurogenomic response to social challenge.
- Author
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Saul, Michael C., Blatti, Charles, Yang, Wei, Bukhari, Syed A., Shpigler, Hagai Y., Troy, Joseph M., Seward, Christopher H., Sloofman, Laura, Chandrasekaran, Sriram, Bell, Alison M., Stubbs, Lisa, Robinson, Gene E., Zhao, Sihai D., and Sinha, Saurabh
- Subjects
TRANSCRIPTOMES ,STICKLEBACKS ,GENE expression in fishes ,TRANSCRIPTION factors ,NEURAL transmission ,SYSTEM analysis - Abstract
Social challenges like territorial intrusions evoke behavioral responses in widely diverging species. Recent work has showed that evolutionary "toolkits"—genes and modules with lineage‐specific variations but deep conservation of function—participate in the behavioral response to social challenge. Here, we develop a multispecies computational‐experimental approach to characterize such a toolkit at a systems level. Brain transcriptomic responses to social challenge was probed via RNA‐seq profiling in three diverged species—honey bees, mice and three‐spined stickleback fish—following a common methodology, allowing fair comparisons across species. Data were collected from multiple brain regions and multiple time points after social challenge exposure, achieving anatomical and temporal resolution substantially greater than previous work. We developed statistically rigorous analyses equipped to find homologous functional groups among these species at the levels of individual genes, functional and coexpressed gene modules, and transcription factor subnetworks. We identified six orthogroups involved in response to social challenge, including groups represented by mouse genes Npas4 and Nr4a1, as well as common modulation of systems such as transcriptional regulators, ion channels, G‐protein‐coupled receptors and synaptic proteins. We also identified conserved coexpression modules enriched for mitochondrial fatty acid metabolism and heat shock that constitute the shared neurogenomic response. Our analysis suggests a toolkit wherein nuclear receptors, interacting with chaperones, induce transcriptional changes in mitochondrial activity, neural cytoarchitecture and synaptic transmission after social challenge. It shows systems‐level mechanisms that have been repeatedly co‐opted during evolution of analogous behaviors, thus advancing the genetic toolkit concept beyond individual genes. Across distantly related species, social challenge modulates nuclear receptor signal transduction‐related molecules. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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28. Genetic Reduction in Left Ventricular Protein Kinase C-α and Adverse Ventricular Remodeling in Human Subjects
- Author
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Hu, Ray, Morley, Michael P., Brandimarto, Jeffrey, Tucker, Nathan R., Parsons, Victoria A., Zhao, Sihai D., Meder, Benjamin, Katus, Hugo A., Rühle, Frank, Stoll, Monika, Villard, Eric, Cambien, François, Lin, Honghuang, Smith, Nicholas L., Felix, Janine F., Vasan, Ramachandran S., van der Harst, Pim, Newton-Cheh, Christopher, Li, Jin, Kim, Cecilia E., Hakonarson, Hakon, Hannenhalli, Sridhar, Ashley, Euan A., Moravec, Christine S., Tang, W.H. Wilson, Maillet, Marjorie, Molkentin, Jeffery D., Ellinor, Patrick T., Margulies, Kenneth B., and Cappola, Thomas P
- Abstract
Supplemental Digital Content is available in the text.
- Published
- 2018
- Full Text
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29. Genetic sharing and heritability of paediatric age of onset autoimmune diseases
- Author
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Jin Li, Patrick M. A. Sleiman, Rosetta M. Chiavacci, Dimitri S. Monos, Fengxiang Wang, Zhi Wei, Jane E Munro, Edward M. Behrens, Carol Wise, Kathleen E. Sullivan, Jack Satsangi, Jordan S. Orange, Sihai Dave Zhao, Subramaniam Kugathasan, Maede Mohebnasab, Vito Annese, Elena S. Resnick, Charlotte Cunningham-Rundles, Eline T. Luning Prak, Constantin Polychronakos, Christopher J. Cardinale, Haijun Qui, Kelly A. Thomas, David C. Wilson, Cecilia E. Kim, Yiran Guo, Marina Bakay, Julie Kobie, Brendan J. Keating, Elena E. Perez, Frank D. Mentch, Marla Dubinsky, Richard K Russell, Hakon Hakonarson, Stephen L. Guthery, Berit Flatø, Justine A. Ellis, Susan D. Thompson, Struan F.A. Grant, Øystein Førre, James Snyder, Benedicte A. Lie, Marilynn Punaro, Erasmo Miele, Yun Li, Mara L. Becker, Debra J. Abrams, S. Melkorka Maggadottir, Annamaria Staiano, Caterina Strisciuglio, Lee A. Denson, Terri H. Finkel, John Connolly, Dong Li, Hongzhe Li, Helen Chapel, Robert N. Baldassano, Anne M. Griffiths, Anna Latiano, Mark S. Silverberg, Jonathan P. Bradfield, Laura Steel, Joseph T. Glessner, Li, Yun R., Zhao, Sihai D., Li, Jin, Bradfield, Jonathan P., Mohebnasab, Maede, Steel, Laura, Kobie, Julie, Abrams, Debra J., Mentch, Frank D., Glessner, Joseph T., Guo, Yiran, Wei, Zhi, Connolly, John J., Cardinale, Christopher J., Bakay, Marina, Li, Dong, Maggadottir, S. Melkorka, Thomas, Kelly A., Qui, Haijun, Chiavacci, Rosetta M., Kim, Cecilia E., Wang, Fengxiang, Snyder, Jame, Flatø, Berit, Førre, Oystein, Denson, Lee A., Thompson, Susan D., Becker, Mara L., Guthery, Stephen L., Latiano, Anna, Perez, Elena, Resnick, Elena, Strisciuglio, Caterina, Staiano, Annamaria, Miele, Erasmo, Silverberg, Mark S., Lie, Benedicte A., Punaro, Marilynn, Russell, Richard K., Wilson, David C., Dubinsky, Marla C., Monos, Dimitri S., Annese, Vito, Munro, Jane E., Wise, Carol, Chapel, Helen, Cunningham Rundles, Charlotte, Orange, Jordan S., Behrens, Edward M., Sullivan, Kathleen E., Kugathasan, Subra, Griffiths, Anne M., Satsangi, Jack, Grant, Struan F. A., Sleiman, Patrick M. A., Finkel, Terri H., Polychronakos, Constantin, Baldassano, Robert N., Luning Prak, Eline T., Ellis, Justine A., Li, Hongzhe, Keating, Brendan J., and Hakonarson, Hakon
- Subjects
Male ,Adolescent ,Population ,European Continental Ancestry Group ,General Physics and Astronomy ,Genome-wide association study ,Biology ,Major histocompatibility complex ,Inflammatory bowel disease ,Autoimmune Disease ,Polymorphism, Single Nucleotide ,General Biochemistry, Genetics and Molecular Biology ,White People ,Article ,Autoimmune Diseases ,03 medical and health sciences ,Physics and Astronomy (all) ,0302 clinical medicine ,medicine ,Humans ,Genetic Predisposition to Disease ,Age of Onset ,education ,Child ,030304 developmental biology ,030203 arthritis & rheumatology ,Genetics ,0303 health sciences ,education.field_of_study ,Multidisciplinary ,Biochemistry, Genetics and Molecular Biology (all) ,Chemistry (all) ,Case-control study ,General Chemistry ,Heritability ,medicine.disease ,3. Good health ,Rheumatoid arthritis ,Case-Control Studies ,Child, Preschool ,biology.protein ,Female ,Age of onset ,Case-Control Studie ,Genome-Wide Association Study ,Human - Abstract
Autoimmune diseases (AIDs) are polygenic diseases affecting 7–10% of the population in the Western Hemisphere with few effective therapies. Here, we quantify the heritability of paediatric AIDs (pAIDs), including JIA, SLE, CEL, T1D, UC, CD, PS, SPA and CVID, attributable to common genomic variations (SNP-h2). SNP-h2 estimates are most significant for T1D (0.863±s.e. 0.07) and JIA (0.727±s.e. 0.037), more modest for UC (0.386±s.e. 0.04) and CD (0.454±0.025), largely consistent with population estimates and are generally greater than that previously reported by adult GWAS. On pairwise analysis, we observed that the diseases UC-CD (0.69±s.e. 0.07) and JIA-CVID (0.343±s.e. 0.13) are the most strongly correlated. Variations across the MHC strongly contribute to SNP-h2 in T1D and JIA, but does not significantly contribute to the pairwise rG. Together, our results partition contributions of shared versus disease-specific genomic variations to pAID heritability, identifying pAIDs with unexpected risk sharing, while recapitulating known associations between autoimmune diseases previously reported in adult cohorts., Autoimmune diseases are genetically complex disorders that affect up to 10% of the Western population. Here Li et al. quantify the heritability of a range of autoimmune diseases in the largest paediatric cohort examined to date, illustrating that genetic and non-genetic components variably contribute to the susceptibility of each disease.
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- 2015
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30. Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases
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Marina Bakay, Diana Chang, Kelly A. Thomas, Jack Satsangi, Sihai Dave Zhao, Cuiping Hou, Carol Wise, Dong Li, Feng Gao, Anne M. Griffiths, Brendan J. Keating, Jane E Munro, Jin Li, Berit Flatø, Øystein Førre, Marla Dubinsky, Benedicte A. Lie, Charlotte Cunningham-Rundles, Erasmo Miele, Debra J. Abrams, Elena S. Resnick, Edward M. Behrens, Haijun Qiu, Marilynn Punaro, Anna Latiano, Alon Keinan, David C. Wilson, Christopher J. Cardinale, John Connolly, Lee A. Denson, Mark S. Silverberg, Subra Kugathasan, Jonathan P. Bradfield, Dimitri S. Monos, Fengxiang Wang, Richard K Russell, Annamaria Staiano, Hakon Hakonarson, Caterina Strisciuglio, Justine A. Ellis, Stephen L. Guthery, Hongzhe Li, Terri H. Finkel, Helen Chapel, Marylyn D Richie, James Snyder, S. Melkorka Maggadottir, Elena E. Perez, Rosetta M. Chiavacci, Kathleen E. Sullivan, Struan F.A. Grant, Robert N. Baldassano, Jordan S. Orange, Eline T. Luning Prak, Vito Annese, Constantin Polychronakos, Cecilia E. Kim, Yiran Guo, Frank D. Mentch, Susan D. Thompson, Charlly Kao, Yun Li, Mara L. Becker, Zhi Wei, Joseph T. Glessner, Patrick M. A. Sleiman, Li, Yun R., Li, Jin, Zhao, Sihai D., Bradfield, Jonathan P., Mentch, Frank D., Maggadottir, S. Melkorka, Hou, Cuiping, Abrams, Debra J., Chang, Diana, Gao, Feng, Guo, Yiran, Wei, Zhi, Connolly, John J., Cardinale, Christopher J., Bakay, Marina, Glessner, Joseph T., Li, Dong, Kao, Charlly, Thomas, Kelly A., Qiu, Haijun, Chiavacci, Rosetta M., Kim, Cecilia E., Wang, Fengxiang, Snyder, Jame, Richie, Marylyn D., Flatø, Berit, Førre, Øystein, Denson, Lee A., Thompson, Susan D., Becker, Mara L., Guthery, Stephen L., Latiano, Anna, Perez, Elena, Resnick, Elena, Russell, Richard K., Wilson, David C., Silverberg, Mark S., Annese, Vito, Lie, Benedicte A., Punaro, Marilynn, Dubinsky, Marla C., Monos, Dimitri S., Strisciuglio, Caterina, Staiano, Annamaria, Miele, Erasmo, Kugathasan, Subra, Ellis, Justine A., Munro, Jane E., Sullivan, Kathleen E., Wise, Carol A., Chapel, Helen, Cunningham Rundles, Charlotte, Grant, Struan F. A., Orange, Jordan S., Sleiman, Patrick M. A., Behrens, Edward M., Griffiths, Anne M., Satsangi, Jack, Finkel, Terri H., Keinan, Alon, Prak, Eline T. Luning, Polychronakos, Constantin, Baldassano, Robert N., Li, Hongzhe, Keating, Brendan J., and Hakonarson, Hakon
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Candidate gene ,Population ,Quantitative Trait Loci ,Single-nucleotide polymorphism ,Genome-wide association study ,Quantitative trait locus ,Autoimmune Disease ,Polymorphism, Single Nucleotide ,General Biochemistry, Genetics and Molecular Biology ,Autoimmune Diseases ,Risk Factors ,Humans ,Medicine ,education ,Child ,Genetic association ,Genetics ,education.field_of_study ,Biochemistry, Genetics and Molecular Biology (all) ,business.industry ,Risk Factor ,Medicine (all) ,General Medicine ,Genetic architecture ,Expression quantitative trait loci ,Immunology ,business ,Genome-Wide Association Study ,Human - Abstract
Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ(2) meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico-replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases.
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- 2015
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31. Identification and targeting of microbial putrescine acetylation in bloodstream infections.
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Mayers JR, Varon J, Zhou RR, Daniel-Ivad M, Beaulieu C, Bholse A, Glasser NR, Lichtenauer FM, Ng J, Vera MP, Huttenhower C, Perrella MA, Clish CB, Zhao SD, Baron RM, and Balskus EP
- Abstract
The growth of antimicrobial resistance (AMR) has highlighted an urgent need to identify bacterial pathogenic functions that may be targets for clinical intervention. Although severe bacterial infections profoundly alter host metabolism, prior studies have largely ignored alterations in microbial metabolism in this context. Performing metabolomics on patient and mouse plasma samples, we identify elevated levels of bacterially-derived N -acetylputrescine during gram-negative bloodstream infections (BSI), with higher levels associated with worse clinical outcomes. We discover that SpeG is the bacterial enzyme responsible for acetylating putrescine and show that blocking its activity reduces bacterial proliferation and slows pathogenesis. Reduction of SpeG activity enhances bacterial membrane permeability and results in increased intracellular accumulation of antibiotics, allowing us to overcome AMR of clinical isolates both in culture and in vivo. This study highlights how studying pathogen metabolism in the natural context of infection can reveal new therapeutic strategies for addressing challenging infections., Competing Interests: DECLARATION OF INTERESTS The authors declare no competing interests.
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- 2023
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32. Neck dissection after chemoradiotherapy: timing and complications.
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Goguen LA, Chapuy CI, Li Y, Zhao SD, and Annino DJ
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- Adult, Aged, Carcinoma, Squamous Cell drug therapy, Carcinoma, Squamous Cell pathology, Carcinoma, Squamous Cell radiotherapy, Combined Modality Therapy, Female, Head and Neck Neoplasms drug therapy, Head and Neck Neoplasms pathology, Head and Neck Neoplasms radiotherapy, Humans, Lymphatic Metastasis, Male, Middle Aged, Postoperative Complications, Proportional Hazards Models, Regression Analysis, Retrospective Studies, Survival Rate, Treatment Outcome, Carcinoma, Squamous Cell surgery, Head and Neck Neoplasms surgery, Neck Dissection methods
- Abstract
Objectives: To determine the incidence of postchemoradiotherapy (post-CRT) neck dissection (ND) complications; to ascertain whether timing (< 12 vs ≥ 12 weeks) from CRT to ND or other factors are associated with increased complications; and to determine whether ND timing influences disease control or survival., Design: Ten-year retrospective analysis., Setting: Tertiary care center., Patients: One hundred five patients with head and neck cancer undergoing ND after CRT., Main Outcome Measures: Complications and survival variables compared between groups undergoing ND less than 12 weeks (less-than-12-weeks ND group) and 12 weeks or more (12-weeks-or-more ND group) after CRT., Results: Sixty-seven NDs were performed less than 12 weeks and 38 were performed 12 weeks or more after CRT. Patient characteristics, treatment, and ND pathology results were comparable between the 2 ND groups. The incidence of complications between the less-than-12-weeks and the 12-weeks-or-more ND groups included major wound complications in 8 of 67 (11.9%) vs 1 of 38 (2.6%; P = .15), minor wound complications in 11 of 67 (16.4%) vs 4 of 38 (10.5%; P = .56), airway complications in 7 of 67 (10.4%) vs 2 of 38 (5.3%; P = .48), and systemic complications in 9 of 67 (13.4%) vs 2 of 38 (5.3%; P = .32). The number of patients with at least 1 complication was significantly smaller in the 12-weeks-or-more ND group (P = .04). Multivariate analysis showed that radical ND was significantly associated with an increased number of complications, and higher radiation doses approached significance (P = .05). Induction chemotherapy was associated with fewer wound complications (P = .01). There were no significant differences in overall survival (P = .82), progression-free survival (P = .77), or regional relapse (P = .54) between groups. Positive ND findings were associated with diminished progression-free and overall survival., Conclusion: These findings indicate that ND can be safely performed 12 weeks or more after CRT without adversely affecting surgical complications or survival variables.
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- 2010
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