Results 11 to 20 of about 92,622 (257)

Transcriptome-wide association study identifies susceptibility genes for rheumatoid arthritis [PDF]

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   +3 more sources

Multi-ethnic transcriptome-wide association study of prostate cancer.

PLoS ONE, 2020
The genetic risk for prostate cancer has been governed by a few rare variants with high penetrance and over 150 commonly occurring variants with lower impact on risk; however, most of these variants have been identified in studies containing exclusively ...
Peter N Fiorica, Ryan Schubert, John D Morris, Mohammed Abdul Sami, Heather E Wheeler   +4 more
doaj   +4 more sources

Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes [PDF]

Human Genomics, 2019
Background While genome-wide association studies (GWAS) of multiple myeloma (MM) have identified variants at 23 regions influencing risk, the genes underlying these associations are largely unknown. To identify candidate causal genes at these regions and
Molly Went, Ben Kinnersley, Amit Sud, David C. Johnson, Niels Weinhold, Asta Försti, Mark van Duin, Giulia Orlando, Jonathan S. Mitchell, Rowan Kuiper, Brian A. Walker, Walter M. Gregory, Per Hoffmann, Graham H. Jackson, Markus M. Nöthen, Miguel Inacio da Silva Filho, Hauke Thomsen, Annemiek Broyl, Faith E. Davies, Unnur Thorsteinsdottir, Markus Hansson, Martin Kaiser, Pieter Sonneveld, Hartmut Goldschmidt, Kari Stefansson, Kari Hemminki, Björn Nilsson, Gareth J. Morgan, Richard S. Houlston   +28 more
doaj   +5 more sources

On the interpretation of transcriptome-wide association studies [PDF]

PLOS Genetics, 2021
AbstractTranscriptome-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. Results from TWAS analyses are often interpreted as indicating a geneticrelationship between gene expression and a phenotype, but this ...
de Leeuw, Christiaan, Werme, Josefin, Savage, Jeanne E., Peyrot, Wouter J., Posthuma, Danielle   +4 more
openaire   +6 more sources

Multi-tissue transcriptome-wide association studies [PDF]

Genetic Epidemiology, 2020
AbstractMany genetic mutations affecting phenotypes are presumed to do so via altering gene expression in particular cells or tissues, but identifying the specific genes involved has been challenging. A transcriptome-wide association study (TWAS) attempts to identify disease associated genes by first learning a predictive model on an eQTL dataset and ...
Grinberg, Nastasiya F, Wallace, Chris
openaire   +2 more sources

Statistical power of transcriptome‐wide association studies

Genetic Epidemiology, 2022
AbstractTranscriptome‐Wide Association Studies (TWASs) have become increasingly popular in identifying genes (or other endophenotypes or exposures) associated with complex traits. In TWAS, one first builds a predictive model for gene expressions using an expression quantitative trait loci (eQTL) data set in stage 1, then tests the association between ...
Ruoyu He, Haoran Xue, Wei Pan
openaire   +2 more sources

Network regression analysis in transcriptome-wide association studies

BMC Genomics, 2022
Abstract Background Transcriptome-wide association studies (TWASs) have shown great promise in interpreting the findings from genome-wide association studies (GWASs) and exploring the disease mechanisms, by integrating GWAS and eQTL mapping studies. Almost all TWAS methods only focus on one gene at a time, with exception
Jin, Xiuyuan, Zhang, Liye, Ji, Jiadong, Ju, Tao, Zhao, Jinghua, Yuan, Zhongshang   +5 more
openaire   +4 more sources

MOSTWAS: Multi-Omic Strategies for Transcriptome-Wide Association Studies [PDF]

PLOS Genetics, 2020
Traditional predictive models for transcriptome-wide association studies (TWAS) consider only single nucleotide polymorphisms (SNPs) local to genes of interest and perform parameter shrinkage with a regularization process. These approaches ignore the effect of distal-SNPs or other molecular effects underlying the SNP-gene association.
Arjun Bhattacharya, Yun Li, Michael I. Love   +2 more
openaire   +6 more sources

Transcriptome-wide association study identifies genes associated with bladder cancer risk. [PDF]

Sci Rep
AbstractGenome-wide association studies (GWAS) have detected several susceptibility variants for urinary bladder cancer, but how gene regulation affects disease development remains unclear. To extend GWAS findings, we conducted a transcriptome-wide association study (TWAS) using PrediXcan to predict gene expression levels in whole blood using genome ...
Li S, Gui J, Karagas MR, Passarelli MN.
europepmc   +4 more sources

Some statistical consideration in transcriptome‐wide association studies [PDF]

Genetic Epidemiology, 2019
Abstract The methodology of transcriptome‐wide association studies (TWAS) has become popular in integrating a reference expression quantitative trait (eQTL) data set with an independent main GWAS data set to identify (putatively) causal genes, shedding mechanistic insights to biological pathways from genetic variants to a GWAS trait ...
Haoran Xue, Wei Pan
openaire   +3 more sources