Results 31 to 40 of about 345,542 (371)
Dissecting the genetic heterogeneity of gastric cancerResearch in context
EBioMedicine, 2023 Summary: Background: Gastric cancer (GC) is clinically heterogenous according to location (cardia/non-cardia) and histopathology (diffuse/intestinal). We aimed to characterize the genetic risk architecture of GC according to its subtypes.
Timo Hess +133 more
doaj +1 more source
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. In this work, we show that linkage disequilibrium induces significant gene-trait associations at non-causal genes as a function of the expression quantitative trait loci ...
Nicholas Mancuso +6 more
openaire +4 more sources
Proteome-Wide Association Studies for Blood Lipids and Comparison with Transcriptome-Wide Association Studies [PDF]
Human Genetics and Genomics Advances, 2023 AbstractBlood 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.
Daiwei Zhang +21 more
openaire +5 more sources
Journal of Translational Medicine, 2022 Background Genome-wide association studies (GWAS) have revealed numerous loci associated with stroke. However, the underlying mechanisms at these loci in the pathogenesis of stroke and effective stroke drug targets are elusive.
Bang-Sheng Wu +7 more
doaj +1 more source
Identifying causal genes for migraine by integrating the proteome and transcriptome
The Journal of Headache and Pain, 2023 Background While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine.
Shuang-jie Li +19 more
doaj +1 more source
Journal of Animal Science and Biotechnology, 2023 Background A detailed understanding of genetic variants that affect beef merit helps maximize the efficiency of breeding for improved production merit in beef cattle.
Wentao Cai +11 more
semanticscholar +1 more source
Opportunities and challenges for transcriptome-wide association studies [PDF]
Nature Genetics, 2019 Transcriptome-wide association studies (TWAS) integrate genome-wide association studies (GWAS) and gene expression datasets to identify gene-trait associations. In this Perspective, we explore properties of TWAS as a potential approach to prioritize causal genes at GWAS loci, by using simulations and case studies of literature-curated candidate causal ...
Michael Wainberg +14 more
openaire +4 more sources
Transcriptome‐wide association studies: a view from Mendelian randomization
Quantitative Biology, 2021 BackgroundGenome‐wide association studies (GWASs) have identified thousands of genetic variants that are associated with many complex traits. However, their biological mechanisms remain largely unknown. Transcriptome‐wide association studies (TWAS) have been recently proposed as an invaluable tool for investigating the potential gene regulatory ...
Huanhuan, Zhu, Xiang, Zhou
openaire +2 more sources
Multi-trait transcriptome-wide association studies with probabilistic Mendelian randomization [PDF]
The American Journal of Human Genetics, 2021 A transcriptome-wide association study (TWAS) integrates data from genome-wide association studies and gene expression mapping studies for investigating the gene regulatory mechanisms underlying diseases. Existing TWAS methods are primarily univariate in nature, focusing on analyzing one outcome trait at a time.
Lu, Liu +4 more
openaire +2 more sources
Diabetologia, 2023 Aims/hypothesis This study aimed to assess the causal relationship between visceral obesity and type 2 diabetes and subsequently to screen visceral adipose tissue (VAT)-specific targets for type 2 diabetes.
Haibo Tang +8 more
semanticscholar +1 more source