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Your search keyword '"Nguyen-Viet, Tuan Anh"' showing total 4 results
Start Over Author "Nguyen-Viet, Tuan Anh" Journal nature genetics
4 results on '"Nguyen-Viet, Tuan Anh"'

1. Multi-trait analysis of genome-wide association summary statistics using MTAG

Author

Turley, Patrick, Walters, Raymond K, Maghzian, Omeed, Okbay, Aysu, Lee, James J, Fontana, Mark Alan, Nguyen-Viet, Tuan Anh, Wedow, Robbee, Zacher, Meghan, Furlotte, Nicholas A, 23andMe Research Team, Social Science Genetic Association Consortium, Magnusson, Patrik, Oskarsson, Sven, Johannesson, Magnus, Visscher, Peter M, Laibson, David, Cesarini, David, Neale, Benjamin M, and Benjamin, Daniel J

Subjects
Biological Sciences, Genetics, Human Genome, Algorithms, Data Interpretation, Statistical, Datasets as Topic, Depression, Diagnostic Self Evaluation, Genetic Association Studies, Genome-Wide Association Study, Health, Humans, Meta-Analysis as Topic, Multifactorial Inheritance, Neuroticism, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, 23andMe Research Team, Social Science Genetic Association Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

We introduce multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (N eff = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). As compared to the 32, 9, and 13 genome-wide significant loci identified in the single-trait GWAS (most of which are themselves novel), MTAG increases the number of associated loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.

Published
2018

2. Author Correction: Multi-trait analysis of genome-wide association summary statistics using MTAG

Author

Turley, Patrick, Walters, Raymond K., Maghzian, Omeed, Okbay, Aysu, Lee, James J., Fontana, Mark Alan, Nguyen-Viet, Tuan Anh, Wedow, Robbee, Zacher, Meghan, Furlotte, Nicholas A., 23andMe Research Team, Social Science Genetic Association Consortium, Magnusson, Patrik, Oskarsson, Sven, Johannesson, Magnus, Visscher, Peter M., Laibson, David, Cesarini, David, Neale, Benjamin M., and Benjamin, Daniel J.

Published
2019
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3. Publisher Correction: Multi-trait analysis of genome-wide association summary statistics using MTAG

Author

Turley, Patrick, Walters, Raymond K., Maghzian, Omeed, Okbay, Aysu, Lee, James J., Fontana, Mark Alan, Nguyen-Viet, Tuan Anh, Wedow, Robbee, Zacher, Meghan, Furlotte, Nicholas A., 23andMe Research Team, Social Science Genetic Association Consortium, Magnusson, Patrik, Oskarsson, Sven, Johannesson, Magnus, Visscher, Peter M., Laibson, David, Cesarini, David, Neale, Benjamin M., and Benjamin, Daniel J.

Published
2019
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4. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

Author

Lee, James J., Wedow, Robbee, Okbay, Aysu, Kong, Edward, Maghzian, Omeed, Zacher, Meghan, Nguyen-Viet, Tuan Anh, Bowers, Peter, Sidorenko, Julia, Karlsson Linnér, Richard, Fontana, Mark Alan, Kundu, Tushar, Lee, Chanwook, Li, Hui, Li, Ruoxi, Royer, Rebecca, Timshel, Pascal N., Walters, Raymond K., Willoughby, Emily A., Yengo, Loïc, Alver, Maris, Bao, Yanchun, Clark, David W., Day, Felix R., Furlotte, Nicholas A., Joshi, Peter K., Kemper, Kathryn E., Kleinman, Aaron, Langenberg, Claudia, Mägi, Reedik, Trampush, Joey W., Verma, Shefali Setia, Wu, Yang, Lam, Max, Zhao, Jing Hua, Zheng, Zhili, Boardman, Jason D., Campbell, Harry, Freese, Jeremy, Harris, Kathleen Mullan, Hayward, Caroline, Herd, Pamela, Kumari, Meena, Lencz, Todd, Luan, Jian’an, Malhotra, Anil K., Metspalu, Andres, Milani, Lili, Ong, Ken K., Perry, John R. B., Porteous, David J., Ritchie, Marylyn D., Smart, Melissa C., Smith, Blair H., Tung, Joyce Y., Wareham, Nicholas J., Wilson, James F., Beauchamp, Jonathan P., Conley, Dalton C., Esko, Tõnu, Lehrer, Steven F., Magnusson, Patrik K. E., Oskarsson, Sven, Pers, Tune H., Robinson, Matthew R., Thom, Kevin, Watson, Chelsea, Chabris, Christopher F., Meyer, Michelle N., Laibson, David I., Yang, Jian, Johannesson, Magnus, Koellinger, Philipp D., Turley, Patrick, Visscher, Peter M., Benjamin, Daniel J., and Cesarini, David

Abstract

Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11–13% of the variance in educational attainment and 7–10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.

Published
2018
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