ArticleQuantitative biology (Beijing, China)2021
Transcriptome-wide association studies: a view from Mendelian randomization.
Article in Quantitative biology (Beijing, China), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 54 citations in OpenAlex.
- Pooled it
- A Review of Statistical Methods for Identifying Trait-Relevant Tissues and Cell Types.Frontiers in genetics · 2020Pooled it
- FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies.PLoS genetics · 2026Article
- Conditionally Significant eQTL and TWAS Analyses Identify MsRD26 as a Major Candidate Positive Regulator of Salt Tolerance in Medicago sativa L.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- CIT-Lasso: a scalable approach beyond guilty by association for identifying causal variants from genome-wide summary statistics.Genome biology · 2026Article
- Plasma GDF15 affects long-term dementia risk and alters neuroimmune signaling.Science advances · 2026Article
- FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies.bioRxiv : the preprint server for biology · 2026Article
- Evaluating the causal effect of circulating proteome on the risk of Juvenile idiopathic arthritis: an omics pipeline study.Pediatric rheumatology online journal · 2025Article
- Article
- Linking plant genes to arthropod community dynamics: current progress and future challenges.Plant & cell physiology · 2025Review
- Multi-Ancestry Transcriptome-Wide Association Studies of Cognitive Function, White Matter Hyperintensity, and Alzheimer's Disease.International journal of molecular sciences · 2025Article
- Proteome-wide association studies for blood lipids and comparison with transcriptome-wide association studies.HGG advances · 2025Article
- Identification of novel proteins for coronary artery disease by integrating GWAS data and human plasma proteomes.Heliyon · 2024Article
- TIPS: a novel pathway-guided joint model for transcriptome-wide association studies.Briefings in bioinformatics · 2024Article
- The goldmine of GWAS summary statistics: a systematic review of methods and tools.BioData mining · 2024Article
- Article
- Integrative analysis reveals novel insights into juvenile idiopathic arthritis pathogenesis and shared molecular pathways with associated traits.Frontiers in genetics · 2024Article
- Potential biomarkers for predicting the risk of thyroid cancer in immunosenescence: a population-based and externally validated multi omics study.Frontiers in oncology · 2024Article
- Translation of genome-wide association study: from genomic signals to biological insights.Frontiers in genetics · 2024Review
- Transcriptome-wide association analyses reveal the impact of regulatory variants on rice panicle architecture and causal gene regulatory networks.Nature communications · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Background: Genome-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 mechanisms underlying variant-trait associations. Specifically, TWAS integrate GWAS with expression mapping studies based on a common set of variants and aim to identify genes whose GReX is associated with the phenotype. Various methods have been developed for performing TWAS and/or similar integrative analysis. Each such method has a different modeling assumption and many were initially developed to answer different biological questions. Consequently, it is not straightforward to understand their modeling property from a theoretical perspective. Results: We present a technical review on thirteen TWAS methods. Importantly, we show that these methods can all be viewed as two-sample Mendelian randomization (MR) analysis, which has been widely applied in GWASs for examining the causal effects of exposure on outcome. Viewing different TWAS methods from an MR perspective provides us a unique angle for understanding their benefits and pitfalls. We systematically introduce the MR analysis framework, explain how features of the GWAS and expression data influence the adaptation of MR for TWAS, and re-interpret the modeling assumptions made in different TWAS methods from an MR angle. We finally describe future directions for TWAS methodology development. Conclusions: We hope that this review would serve as a useful reference for both methodologists who develop TWAS methods and practitioners who perform TWAS analysis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.