ArticlePLoS genetics2023
On the interpretation of transcriptome-wide association studies.
Article in PLoS genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 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.
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Who cites it
22 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- The Genetic Architecture of the Human Corpus Callosum and its Subregions.Nature communications · 2025Pooled it
- Multiomic integration analysis identifies atherogenic metabolites mediating between novel immune genes and cardiovascular risk.Genome medicine · 2024Pooled it
- Hippocampal transcriptome-wide association study and pathway analysis of mitochondrial solute carriers in Alzheimer's disease.Translational psychiatry · 2024Pooled it
- Genomic dimensions deconstruct the clinical heterogeneity of bipolar disorder.Research square · 2026Article
- Review
- Functionally informed cis and trans proteome-wide association studies prioritize disease-critical genes.Research square · 2026Article
- Functionally informed cis and trans proteome-wide association studies prioritize disease-critical genes.medRxiv : the preprint server for health sciences · 2026Article
- Methods for Prioritizing Causal Genes in Molecular Studies of Human Disease: The State of the Art.Genetic epidemiology · 2026Review
- Improving isoform-level eQTL and integrative genetic analyses of breast cancer risk with long-read RNA transcript assemblies.bioRxiv : the preprint server for biology · 2026Article
- A gene-specific variance-control approach corrects polygenicity-driven inflation observed in transcriptome-wide association studies.American journal of human genetics · 2026Article
- Psoriasis risk allele function in activated Th1/17 cells with "memory" to antigen exposure.PloS one · 2026Article
- TransferTWAS: A transfer learning framework for cross-tissue transcriptome-wide association study.American journal of human genetics · 2025Article
- Genetic analysis of psychosis Biotypes: shared Ancestry-adjusted polygenic risk and unique genomic associations.Molecular psychiatry · 2025Article
- Integrative genomics sheds light on the immunogenetics of tuberculosis in cattle.Communications biology · 2025Article
- Cross-Trait Genome-Wide Association Study Identifies Shared Genetic Risk Loci Between COPD and Five Autoimmune Diseases.International journal of chronic obstructive pulmonary disease · 2025Article
- Genetic Analysis of Psychosis Biotypes: Shared Ancestry-Adjusted Polygenic Risk and Unique Genomic Associations.medRxiv : the preprint server for health sciences · 2024Article
- Pervasive polygenicity of complex traits inflates false positive rates in transcriptome-wide association studies.bioRxiv : the preprint server for biology · 2024Article
- Unveiling the Genetic Mechanism of Meat Color in Pigs through GWAS, Multi-Tissue, and Single-Cell Transcriptome Signatures Exploration.International journal of molecular sciences · 2024Article
- Predicting the genetic component of gene expression using gene regulatory networks.Bioinformatics advances · 2024Article
- Proteome-wide Mendelian randomization in global biobank meta-analysis reveals multi-ancestry drug targets for common diseases.Cell genomics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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 genetic relationship between gene expression and a phenotype, but this interpretation is not consistent with the null hypothesis that is evaluated in the traditional TWAS framework. In this study we provide a mathematical outline of this TWAS framework, and elucidate what interpretations are warranted given the null hypothesis it actually tests. We then use both simulations and real data analysis to assess the implications of misinterpreting TWAS results as indicative of a genetic relationship between gene expression and the phenotype. Our simulation results show considerably inflated type 1 error rates for TWAS when interpreted this way, with 41% of significant TWAS associations detected in the real data analysis found to have insufficient statistical evidence to infer such a relationship. This demonstrates that in current implementations, TWAS cannot reliably be used to investigate genetic relationships between gene expression and a phenotype, but that local genetic correlation analysis can serve as a potential alternative.
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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 Socratic graph.