Results 41 to 50 of about 8,166 (222)

Integrating Transcriptome-Wide Association Study and mRNA Expression Profiling Identifies Novel Genes Associated With Osteonecrosis of the Femoral Head

Frontiers in Genetics, 2021
ObjectiveThis study aims to identify novel candidate genes associated with osteonecrosis of the femoral head (ONFH).MethodsA transcriptome-wide association study (TWAS) was performed by integrating the genome-wide association study dataset of ...
Mei Ma, Peilin Li, Li Liu, Shiqiang Cheng, Bolun Cheng, Chu Jun Liang, Sijia Tan, Wenyu Li, Yan Wen, Xiong Guo, Cuiyan Wu   +10 more
doaj   +1 more source

Exploring Contraindicated Medications and Corresponding Targeted Genes for Migraine Through Integrated Genetic Approaches. [PDF]

Brain Behav
To systematically identify risk medications for migraine and its subtypes, we integrated GWAS data for 23 medications with GWASs of migraine and its subtypes to conduct causal inference. We then combined plasma eQTLs with drug‐target databases to map putative targets of the risk medications and validated causal relationships using colocalization and ...
Wang N, Liang W, Wen Z, Liao W, Xie Z, Zhou Z, Yang Z, Ju X, Zhou H, Huang C.   +9 more
europepmc   +2 more sources

A transcriptome-wide association study of uterine fibroids to identify potential genetic markers and toxic chemicals

PLoS ONE, 2022
Uterine fibroid is one of the most prevalent benign tumors in women, with high socioeconomic costs. Although genome-wide association studies (GWAS) have identified several loci associated with uterine fibroid risks, they could not successfully interpret ...
Gayeon Kim, Gyuyeon Jang, Jaeseung Song, Daeun Kim, Sora Lee, Jong Wha J. Joo, Wonhee Jang   +6 more
doaj   +2 more sources

On the interpretation of transcriptome-wide association studies.

PLoS Genetics, 2023
Transcriptome-wide association studies (TWAS) aim to detect relationships between gene expression and a phenotype, and are commonly used for secondary analysis of genome-wide association study (GWAS) results.
Christiaan de Leeuw, Josefin Werme, Jeanne E Savage, Wouter J Peyrot, Danielle Posthuma   +4 more
doaj   +1 more source

TIGAR-V2: Efficient TWAS tool with nonparametric Bayesian eQTL weights of 49 tissue types from GTEx V8

HGG Advances, 2022
Summary: Standard transcriptome-wide association study (TWAS) methods first train gene expression prediction models using reference transcriptomic data and then test the association between the predicted genetically regulated gene expression and ...
Randy L. Parrish, Greg C. Gibson, Michael P. Epstein, Jingjing Yang   +3 more
doaj   +1 more source

Transcriptome-wide association study of breast cancer risk by estrogen-receptor status [PDF]

, 2020
Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations ...
ABCTB Investigators, ABCTB Investigators, Abu-Full, Zomoroda, Aittomäki, Kristiina, Andrulis, Irene L, Anton-Culver, Hoda, Antoniou, Antonis C, Arason, Adalgeir, Arndt, Volker, Aronson, Kristan J, Arun, Banu K, Asseryanis, Ella, Auer, Paul L, Azzollini, Jacopo, Balmaña, Judith, Barkardottir, Rosa B, Barnes, Daniel R, Barrowdale, Daniel, BCFR Investigators, BCFR Investigators, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Białkowska, Katarzyna, Blanco, Ana, Blomqvist, Carl, Boeckx, Bram, Bogdanova, Natalia V, Bojesen, Stig E, Bolla, Manjeet K, Bonanni, Bernardo, Borg, Ake, Brauch, Hiltrud, Brenner, Hermann, Briceno, Ignacio, Broeks, Annegien, Brüning, Thomas, Burwinkel, Barbara, Cai, Qiuyin, Caldés, Trinidad, Caligo, Maria A, Campa, Daniele, Campbell, Ian, Canisius, Sander, Carter, Brian D, Carter, Jonathan, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Chenevix-Trench, Georgia, Christiansen, Hans, Chung, Wendy K, Claes, Kathleen BM, Clarke, Christine L, Couch, Fergus J, Cox, Angela, Cross, Simon S, Cybulski, Cezary, Czene, Kamila, Daly, Mary B, de la Hoya, Miguel, De Leeneer, Kim, Dennis, Joe, Devilee, Peter, Diez, Orland, Domchek, Susan M, Dos-Santos-Silva, Isabel, Dunning, Alison M, Dwek, Miriam, Dörk, Thilo, Easton, Douglas F, Eccles, Diana M, Ejlertsen, Bent, Ellberg, Carolina, EMBRACE Collaborators, EMBRACE Collaborators, Engel, Christoph, Eriksson, Mikael, Fasching, Peter A, Feng, Helian, Fletcher, Olivia, Flyger, Henrik, Fostira, Florentia, Friedman, Eitan, Fritschi, Lin, Frost, Debra, Gabrielson, Marike, Ganz, Patricia A, Gapstur, Susan M, Garber, Judy, García-Closas, Montserrat, García-Sáenz, José A, Gaudet, Mia M, GC-HBOC study Collaborators, GC-HBOC study Collaborators, GEMO Study Collaborators, GEMO Study Collaborators, Giles, Graham G, Glendon, Gord, Godwin, Andrew K, Goldberg, Mark S, Goldgar, David E, González-Neira, Anna, Greene, Mark H, Gronwald, Jacek, Gusev, Alexander, Guénel, Pascal, Haiman, Christopher A, Hake, Christopher, Hall, Per, Hamann, Ute, He, Wei, HEBON Investigators, Heyworth, Jane, Hogervorst, Frans BL, Hollestelle, Antoinette, Hooning, Maartje J, Hoover, Robert N, Hopper, John L, Huang, Guanmengqian, Hulick, Peter J, Humphreys, Keith, Imyanitov, Evgeny N, Isaacs, Claudine, Jakimovska, Milena, Jakubowska, Anna, James, Paul, Janavicius, Ramunas, Jankowitz, Rachel C, Jiang, Xia, John, Esther M, Johnson, Nichola, Joseph, Vijai, Jung, Audrey, Kapoor, Pooja M, Karlan, Beth Y, Khusnutdinova, Elza, Kiiski, Johanna I, Konstantopoulou, Irene, Kraft, Peter, Kristensen, Vessela N, Laitman, Yael, Lambrechts, Diether, Lazaro, Conxi, Leroux, Dominique, Leslie, Goska, Lester, Jenny, Lesueur, Fabienne, Lindor, Noralane, Lindström, Sara, Lo, Wing-Yee, Long, Jirong, Loud, Jennifer T, Lubiński, Jan, Makalic, Enes, Mannermaa, Arto, Manoochehri, Mehdi, Manoukian, Siranoush, Margolin, Sara, Martens, John WM, Martinez, Maria E, Matricardi, Laura, Maurer, Tabea, Mavroudis, Dimitrios, McGuffog, Lesley, Meindl, Alfons, Menon, Usha, Michailidou, Kyriaki, Miller, Austin, Milne, Roger L, Montagna, Marco, Moreno, Fernando, Moserle, Lidia, Mulligan, Anna M, Muranen, Taru A, Nathanson, Katherine L, Neuhausen, Susan L, Nevanlinna, Heli, Nevelsteen, Ines, Nielsen, Finn C, Nikitina-Zake, Liene, OCGN Investigators, OCGN Investigators, Offit, Kenneth, Olah, Edith, Olopade, Olufunmilayo I, Olsson, Håkan, Osorio, Ana, Papp, Janos, Park-Simon, Tjoung-Won, Parsons, Michael T, Pasaniuc, Bogdan, Pedersen, Inge S, Peixoto, Ana, Peterlongo, Paolo, Peto, Julian, Pharoah, Paul DP, Phillips, Kelly-Anne, Plaseska-Karanfilska, Dijana, Poppe, Bruce, Pradhan, Nisha, Prajzendanc, Karolina, Presneau, Nadege, Punie, Kevin, Pylkäs, Katri, Radice, Paolo, Rantala, Johanna, Rashid, Muhammad Usman, Rennert, Gad, Risch, Harvey A, Robson, Mark, Romero, Atocha, Saloustros, Emmanouil, Sandler, Dale P, Santos, Catarina, Sawyer, Elinor J, Schmidt, Daniel F, Schmidt, Marjanka K, Schmutzler, Rita K, Schoemaker, Minouk J, Scott, Rodney J, Sharma, Priyanka, Shu, Xiao-Ou, Simard, Jacques, Singer, Christian F, Skytte, Anne-Bine, Soucy, Penny, Southey, Melissa C, Spinelli, John J, Spurdle, Amanda B, Stone, Jennifer, Swerdlow, Anthony J, Tapper, William J, Taylor, Jack A, Teixeira, Manuel R, Terry, Mary Beth, Teulé, Alex, Thomassen, Mads, Thull, Darcy L, Thöne, Kathrin, Tischkowitz, Marc, Toland, Amanda E, Tollenaar, Rob AEM, Torres, Diana, Truong, Thérèse, Tung, Nadine, Vachon, Celine M, van Asperen, Christi J, van den Ouweland, Ans MW, van Rensburg, Elizabeth J, Vega, Ana, Vieiro-Balo, Paula, Viel, Alessandra, Wang, Qin, Wappenschmidt, Barbara, Weinberg, Clarice R, Weitzel, Jeffrey N, Wendt, Camilla, Winqvist, Robert, Wu, Lang, Yang, Xiaohong R, Yannoukakos, Drakoulis, Zheng, Wei, Ziogas, Argyrios   +264 more
core   +17 more sources

webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study

Nucleic Acids Res., 2021
The development of transcriptome-wide association studies (TWAS) has enabled researchers to better identify and interpret causal genes in many diseases.
Chen Cao, Jianhua Wang, Devin Kwok, Feifei Cui, Zilong Zhang, Da Zhao, Mulin Jun Li, Q. Zou   +7 more
semanticscholar   +1 more source

Transcriptome-wide association study identifies susceptibility genes for rheumatoid arthritis

Arthritis Research & Therapy, 2021
Objective To identify rheumatoid arthritis (RA)-associated susceptibility genes and pathways through integrating genome-wide association study (GWAS) and gene expression profile data. Methods A transcriptome-wide association study (TWAS) was conducted by
Cuiyan Wu, Sijian Tan, Li Liu, Shiqiang Cheng, Peilin Li, Wenyu Li, Huan Liu, Feng’e Zhang, Sen Wang, Yujie Ning, Yan Wen, Feng Zhang   +11 more
doaj   +1 more source

Transcriptome‐wide association and prediction for carotenoids and tocochromanols in fresh sweet corn kernels

The Plant Genome, 2022
Sweet corn (Zea mays L.) is consistently one of the most highly consumed vegetables in the United States, providing a valuable opportunity to increase nutrient intake through biofortification.
Jenna Hershberger, Ryokei Tanaka, Joshua C. Wood, Nicholas Kaczmar, Di Wu, John P. Hamilton, Dean DellaPenna, C. Robin Buell, Michael A. Gore   +8 more
doaj   +1 more source

Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution [PDF]

, 2017
We show that epigenome- and transcriptome-wide association studies (EWAS and TWAS) are prone to significant inflation and bias of test statistics, an unrecognized phenomenon introducing spurious findings if left unaddressed.
't Hoen, P.-B. (Peter-Bram), 't Hoen, P.A.C. (Peter A.C.), Arindrarto, W. (Wibowo), Beekman, M. (Marian), Berg, L.H. (Leonard) van den, Bonder, M.J. (Marc), Boomsma, D.I. (Dorret), Bot, J.J. (Jan), Breggen, R. (Ruud) van der, Deelen, J. (Joris), Deelen, P. (Patrick), Dijk, F. (Freerk) van, Dongen, J. (Jenny) van, Duijn, C.M. (Cornelia) van, Franke, L. (Lude), Greevenbroek, M.M. van, Heemst, D. (Diana) van, Heijmans, B.T. (Bastiaan), Hofman, B., Hottenga, J.J. (Jouke Jan), Isaacs, A.J. (Aaron), Iterson, M. (Maarten) van, Jansen, R., Jhamai, P.M. (Mila), Kallen, C.J. van der, Kielbasa, S.M. (Szymon M.), Lakenberg, N. (Nico), Luijk, R. (René), Mei, S. (Shan), Meurs, J.B.J. (Joyce) van, Moed, H. (Heleen), Nooren, I. (Irene), Pool, R. (Reńe), Rooij, J.G.J. (Jeroen) van, Schalkwijk, C.G. (Casper), Slagboom, P.E. (Eline), Stehouwer, C.D. (Coen), Suchiman, H.E.D. (Eka), Swertz, M.A. (Morris A.), Tigchelaar, E.F. (Ettje F.), Uitterlinden, A.G. (André), van 't Hof, P. (Peter), Van Galen, M. (Michiel), Veldink, J.H. (Jan), Verbiest, M.M.P.J. (Michael), Verkerk, M. (Marijn), Vermaat, M. (Martijn), Wijmenga, C. (Cisca), Zhernakova, A. (Alexandra), Zhernakova, S. (Sasha), Zwet, E.W. (Erik) van   +50 more
core   +1 more source