Results 1 to 10 of about 8,166 (222)

A large-scale transcriptome-wide association study (TWAS) of 10 blood cell phenotypes reveals complexities of TWAS fine-mapping. [PDF]

Genet Epidemiol, 2022
AbstractHematological measures are important intermediate clinical phenotypes for many acute and chronic diseases and are highly heritable. Although genome‐wide association studies (GWAS) have identified thousands of loci containing trait‐associated variants, the causal genes underlying these associations are often uncertain.
Tapia AL, Rowland BT, Rosen JD, Preuss M, Young K, Graff M, Choquet H, Couper DJ, Buyske S, Bien SA, Jorgenson E, Kooperberg C, Loos RJF, Morrison AC, North KE, Yu B, Reiner AP, Li Y, Raffield LM.   +18 more
europepmc   +9 more sources

Brain transcriptome wide association study (TWAS) implicates 8 genes across 6 loci in Alzheimer’s disease [PDF]

Alzheimer's & Dementia, 2020
AbstractBackgroundAlzheimer’s disease (AD), an incurable neurodegenerative disease, currently affects 1.75% of the United States population, with projected growth to 3.46% by 2050. Common genetic variation linked transcript expression differences which confer AD‐risk isl necessary to elucidate AD mechanism and develop therapeutic interventions.
Jake Gockley, Kelsey S. Montgomery, William L. Poehlman, Yue Liu, Ekaterina S. Gerasimov, Anna K. Greenwood, Aliza P. Wingo, Thomas S. Wingo, Lara M. Mangravite, Benjamin A. Logsdon   +9 more
semanticscholar   +3 more sources

UTMOST, a single and cross-tissue TWAS (Transcriptome Wide Association Study), reveals new ASD (Autism Spectrum Disorder) associated genes [PDF]

Translational Psychiatry, 2021
Abstract Autism spectrum disorders (ASD) is a complex neurodevelopmental disorder that may significantly impact on the affected individual’s life. Common variation (SNPs) could explain about 50% of ASD heritability.
Cristina Rodriguez‐Fontenla, Ángel Carracedo   +1 more
semanticscholar   +6 more sources

A large-scale transcriptome-wide association study (TWAS) of ten blood cell phenotypes reveals complexities of TWAS fine-mapping [PDF]

bioRxiv, 2021
AbstractHematological measures are important intermediate clinical phenotypes for many acute and chronic diseases. Hematological measures are highly heritable, and although genome-wide association studies (GWAS) have identified thousands of loci containing trait-associated variants, the causal genes underlying these associations are often uncertain. To
Amanda L. Tapia, Bryce Rowland, Jonathan D. Rosen, Michael Preuß, Kris Young, Misa Graff, Hélène Choquet, David Couper, Steven Buyske, Stephanie A. Bien, Eric Jorgenson, Charles Kooperberg, Ruth J. F. Loos, Alanna C. Morrison, Kari E. North, Bing Yu, Alexander P. Reiner, Yun Li, Laura M. Raffield   +18 more
semanticscholar   +3 more sources

TWAS atlas 2.0: an updated data resource for transcriptome-wide association studies. [PDF]

Nucleic Acids Res
Abstract Transcriptome-wide association studies (TWAS), which combine large-scale GWAS and expression quantitative trait loci (eQTL) datasets to predict gene expression levels and identify trait-related genes, have recently been applied across many traits.
Gao H, Bu C, Zheng S, Mai J, Wang J, Tang R, Fan Z, Zeng J, Li J, Xiao J.   +9 more
europepmc   +3 more sources

SR-TWAS: leveraging multiple reference panels to improve transcriptome-wide association study power by ensemble machine learning [PDF]

Nature Communications
Multiple reference panels of a given tissue or multiple tissues often exist, and multiple regression methods could be used for training gene expression imputation models for transcriptome-wide association studies (TWAS). To leverage expression imputation models (i.e., base models) trained with multiple reference panels, regression methods, and tissues,
Randy L. Parrish, Aron S. Buchman, Shinya Tasaki, Yanling Wang, Denis Avey, Jishu Xu, Philip L. De Jager, David A. Bennett, Michael P. Epstein, Jingjing Yang   +9 more
semanticscholar   +5 more sources

Abstract 30: Cross-cancer cross-tissue transcriptome-wide association study (TWAS) of 11 cancers identifies 56 novel genes [PDF]

Cancer Research, 2020
Abstract Although cancer is a heterogeneous disease, there are shared hallmark mechanisms across multiple tumor types. Because of this, identifying genes associated with multiple cancer types has the potential to shed light on general oncogenic mechanisms.
Helian Feng, Arunabha Majumdar, Bogdan Paşaniuc, Hongjie Chen, Sara Lindström, Jeroen R. Huyghe, Stephanie L. Schmit, Tracy A. O’Mara, Deborah J. Thompson, Stuart MacGregor, Paul Brennan, James McKay, Richard S. Houlston, Beatrice Melin, Christopher I. Amos, Anne E. Cus, Mark M. Iles, Siddhartha Kar, Paul D.P. Pharoah, Rayjean J. Hung, Peter Kraft, Peter Kraft   +21 more
semanticscholar   +3 more sources

TWAS Atlas: a curated knowledgebase of transcriptome-wide association studies [PDF]

Nucleic Acids Research, 2022
Abstract Transcriptome-wide association studies (TWASs), as a practical and prevalent approach for detecting the associations between genetically regulated genes and traits, are now leading to a better understanding of the complex mechanisms of genetic variants in regulating various diseases and traits.
Mingming Lu, Yadong Zhang, Fengchun Yang, Jialin Mai, Qianwen Gao, Xiaowei Xu, Hongyu Kang, Li Hou, Yunfei Shang, Qiheng Qain, Jie Liu, Meiye Jiang, Hao Zhang, Congfan Bu, Jinyue Wang, Zhewen Zhang, Zaichao Zhang, Jingyao Zeng, Jiao Li, Jingfa Xiao   +19 more
openalex   +3 more sources

TWAS-GKF: a novel method for causal gene identification in transcriptome-wide association studies with knockoff inference [PDF]

Bioinformatics
Abstract Motivation Transcriptome-wide association study (TWAS) aims to identify trait-associated genes regulated by significant variants to explore the underlying biological mechanisms at a tissue-specific level.
Anqi Wang, Peixin Tian, Yan Zhang
openalex   +3 more sources

UTMOST, A Novel Single And Cross-Tissue TWAS (Transcriptome Wide Association Study), Reveals New ASD (Autism Spectrum Disorder) Associated Genes [PDF]

, 2020
ABSTRACTBackgroundASD is a complex neurodevelopmental disorder which may significantly impact on the affected individual’s life. Common variation (SNPs) could explain about 50% of ASD heritability. Despite this fact and the large size of the last GWAS meta-analysis, it is believed that hundreds of risk genes in ASD have yet to be discovered.
Cristina Rodriguez-Fontenla, Angel Carracedo   +1 more
openalex   +2 more sources