Zobrazeno 1 - 10
of 289
pro vyhledávání: '"Hae Kyung, Im"'
Predicting molecular mechanisms of hereditary diseases by using their tissue‐selective manifestation
Autor:
Eyal Simonovsky, Moran Sharon, Maya Ziv, Omry Mauer, Idan Hekselman, Juman Jubran, Ekaterina Vinogradov, Chanan M Argov, Omer Basha, Lior Kerber, Yuval Yogev, Ayellet V Segrè, Hae Kyung Im, GTEx Consortium, Ohad Birk, Lior Rokach, Esti Yeger‐Lotem
Publikováno v:
Molecular Systems Biology, Vol 19, Iss 8, Pp 1-20 (2023)
Abstract How do aberrations in widely expressed genes lead to tissue‐selective hereditary diseases? Previous attempts to answer this question were limited to testing a few candidate mechanisms. To answer this question at a larger scale, we develope
Externí odkaz:
https://doaj.org/article/2f83bd8335064584b8465fdd36d265bc
Autor:
Matthew Dapas, Yu Lin Lee, William Wentworth-Sheilds, Hae Kyung Im, Carole Ober, Nathan Schoettler
Publikováno v:
HGG Advances, Vol 4, Iss 4, Pp 100233- (2023)
Summary: In this study we examined how genetic risk for asthma associates with different features of the disease and with other medical conditions and traits. Using summary statistics from two multi-ancestry genome-wide association studies of asthma,
Externí odkaz:
https://doaj.org/article/b483245297dc4def9cf3fdbd83a46d29
Autor:
Daniel S. Araujo, Chris Nguyen, Xiaowei Hu, Anna V. Mikhaylova, Chris Gignoux, Kristin Ardlie, Kent D. Taylor, Peter Durda, Yongmei Liu, George Papanicolaou, Michael H. Cho, Stephen S. Rich, Jerome I. Rotter, Hae Kyung Im, Ani Manichaikul, Heather E. Wheeler
Publikováno v:
HGG Advances, Vol 4, Iss 4, Pp 100216- (2023)
Summary: Transcriptome prediction models built with data from European-descent individuals are less accurate when applied to different populations because of differences in linkage disequilibrium patterns and allele frequencies. We hypothesized that
Externí odkaz:
https://doaj.org/article/e5378247f4d847d8b11fd367f8966c80
Autor:
Gengjie Jia, Xue Zhong, Hae Kyung Im, Nathan Schoettler, Milton Pividori, D. Kyle Hogarth, Anne I. Sperling, Steven R. White, Edward T. Naureckas, Christopher S. Lyttle, Chikashi Terao, Yoichiro Kamatani, Masato Akiyama, Koichi Matsuda, Michiaki Kubo, Nancy J. Cox, Carole Ober, Andrey Rzhetsky, Julian Solway
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-19 (2022)
Asthma is a heterogeneous, complex syndrome that arises in individuals with various genetic and exposure variations. Here, the authors show that disease comorbidity patterns can serve as a surrogate for these variations, and identify asthma endotypes
Externí odkaz:
https://doaj.org/article/c0bc253f917a42f192232de999a0a2e9
Autor:
Selene M. Clay, Nathan Schoettler, Andrew M. Goldstein, Peter Carbonetto, Matthew Dapas, Matthew C. Altman, Mario G. Rosasco, James E. Gern, Daniel J. Jackson, Hae Kyung Im, Matthew Stephens, Dan L. Nicolae, Carole Ober
Publikováno v:
Genome Medicine, Vol 14, Iss 1, Pp 1-16 (2022)
Abstract Background Genome-wide association studies of asthma have revealed robust associations with variation across the human leukocyte antigen (HLA) complex with independent associations in the HLA class I and class II regions for both childhood-o
Externí odkaz:
https://doaj.org/article/5ad2bffb561c45329d8d724aa87835f6
Autor:
Yanyu Liang, Milton Pividori, Ani Manichaikul, Abraham A. Palmer, Nancy J. Cox, Heather E. Wheeler, Hae Kyung Im
Publikováno v:
Genome Biology, Vol 23, Iss 1, Pp 1-18 (2022)
Abstract Background Polygenic risk scores (PRS) are valuable to translate the results of genome-wide association studies (GWAS) into clinical practice. To date, most GWAS have been based on individuals of European-ancestry leading to poor performance
Externí odkaz:
https://doaj.org/article/e3337e1e5c4347f3b11f5555781e0b82
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-11 (2021)
Methods for eQTL mapping from total and allele-specific gene expression typically are too computationally heavy to apply to large scale studies. Here, the authors describe a computationally efficient method to identify eQTLs, fine-map and predict exp
Externí odkaz:
https://doaj.org/article/851a2e4e25024f928fc9e3810b60b5e9
Autor:
Alvaro N. Barbeira, Rodrigo Bonazzola, Eric R. Gamazon, Yanyu Liang, YoSon Park, Sarah Kim-Hellmuth, Gao Wang, Zhuoxun Jiang, Dan Zhou, Farhad Hormozdiari, Boxiang Liu, Abhiram Rao, Andrew R. Hamel, Milton D. Pividori, François Aguet, GTEx GWAS Working Group, Lisa Bastarache, Daniel M. Jordan, Marie Verbanck, Ron Do, GTEx Consortium, Matthew Stephens, Kristin Ardlie, Mark McCarthy, Stephen B. Montgomery, Ayellet V. Segrè, Christopher D. Brown, Tuuli Lappalainen, Xiaoquan Wen, Hae Kyung Im
Publikováno v:
Genome Biology, Vol 22, Iss 1, Pp 1-24 (2021)
Abstract The resources generated by the GTEx consortium offer unprecedented opportunities to advance our understanding of the biology of human diseases. Here, we present an in-depth examination of the phenotypic consequences of transcriptome regulati
Externí odkaz:
https://doaj.org/article/84ae6dd57bee4833929e3d4586a1d87a
Autor:
Yuhua Zhang, Corbin Quick, Ketian Yu, Alvaro Barbeira, The GTEx Consortium, Francesca Luca, Roger Pique-Regi, Hae Kyung Im, Xiaoquan Wen
Publikováno v:
Genome Biology, Vol 21, Iss 1, Pp 1-26 (2020)
Abstract We propose a new computational framework, probabilistic transcriptome-wide association study (PTWAS), to investigate causal relationships between gene expressions and complex traits. PTWAS applies the established principles from instrumental
Externí odkaz:
https://doaj.org/article/72e4c9693846493a8015b5059f85754c
Autor:
Yuan He, Surya B. Chhetri, Marios Arvanitis, Kaushik Srinivasan, François Aguet, Kristin G. Ardlie, Alvaro N. Barbeira, Rodrigo Bonazzola, Hae Kyung Im, GTEx Consortium, Christopher D. Brown, Alexis Battle
Publikováno v:
Genome Biology, Vol 21, Iss 1, Pp 1-25 (2020)
Abstract Genetic regulation of gene expression, revealed by expression quantitative trait loci (eQTLs), exhibits complex patterns of tissue-specific effects. Characterization of these patterns may allow us to better understand mechanisms of gene regu
Externí odkaz:
https://doaj.org/article/4732b96b2dc2477bb07ba28215a5d6f7