Results 11 to 20 of about 40,064,637 (293)

Probabilistic fine-mapping of transcriptome-wide association studies [PDF]

Nature Genetics, 2019
Transcriptome-wide association studies using predicted expression have identified thousands of genes whose locally regulated expression is associated with complex traits and diseases.
Kichaev, Gleb, Pasaniuc, Bogdan, Gleb Kichaev, Huwenbo Shi, Malika K. Freund, Gusev, Alexander, Bogdan Pasaniuc, Ruth Johnson, Shi, Huwenbo, Freund, Malika K, Johnson, Ruth, Nicholas Mancuso, Alexander Gusev, Mancuso, Nicholas   +13 more
core   +6 more sources

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

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

Genetic Epidemiology, 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 ...
Ellberg, Carolina,, Borg, Åke,, EMBRACE Collaborators, Olsson, Håkan,, GC-HBOC Study Collaborators, Feng, Helian,, Lund University., GEMO Study Collaborators   +7 more
core   +21 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

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

PLOS Genetics, 2021
Abstract 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. Results from TWAS analyses are often interpreted as indicating a geneticrelationship between gene expression and a ...
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
Abstract Many 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 ...
Grinberg, Nastasiya F, Wallace, Chris
openaire   +2 more sources

Assigning function to genome wide association study variants associated with complex gastrointestinal disease [PDF]

, 2009
PhDThe genome‐wide association study era has identified numerous loci associated with many common polygenic diseases. The next challenge is to identify the functional consequences of these variants and elicit how they impact on disease risk.
Heap, Graham Alastair Richard
core   +4 more sources

Proteome-Wide Association Studies for Blood Lipids and Comparison with Transcriptome-Wide Association Studies [PDF]

Human Genetics and Genomics Advances, 2023
Abstract Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWAS) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological
Daiwei Zhang, Boran Gao, Qidi Feng, Ani Manichaikul, Gina M. Peloso, Russell P. Tracy, Peter Durda, Kent D. Taylor, Yongmei Liu, W. Craig Johnson, Stacey Gabriel, Namrata Gupta, Joshua D. Smith, Francois Aguet, Kristin G. Ardlie, Thomas W. Blackwell, Robert E. Gerszten, Stephen S. Rich, Jerome I. Rotter, Laura J. Scott, Xiang Zhou, Seunggeun Lee   +21 more
openaire   +5 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