ArticleInternational journal of cancer2022
A transcriptome-wide association study identifies novel candidate susceptibility genes for prostate cancer risk.
Article in International journal of cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.
- Pooled it
- Genetically Predicted Blood DNA Methylation Reveals Putative Regulatory Signals Associated with ALS Risk.medRxiv : the preprint server for health sciences · 2026Article
- Transcriptome-wide association study of prostate cancer in the Chinese population.Asian journal of urology · 2026Article
- Large-scale integration of omics and electronic health records to identify potential risk protein biomarkers and therapeutic drugs for cancer prevention.American journal of human genetics · 2026Article
- Proteome-wide association study of prostate cancer risk across populations.Nature communications · 2025Article
- Integrating Single-Cell Transcriptome-Wide Mendelian Randomization and Differentially Expressed Gene Analyses to Prioritize Dynamic Immune-Related Drug Targets for Cancers.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Cross-tissue transcriptome-wide association studies identify genetic susceptibility genes for prostate cancer.BMC cancer · 2025Article
- A Transcriptome-Wide Association Study Identifies Candidate Susceptibility Loci and Genes for Lung Cancer Risk.Cancer medicine · 2025Article
- Causal Relationship Between Blood Metabolites and Prostate Cancer Risk: A Two-Sample Mendelian Randomization Study.Molecular carcinogenesis · 2025Article
- Integrating Multi-Omics Data to Uncover Prostate Tissue DNA Methylation Biomarkers and Target Genes for Prostate Cancer Risk.Molecular carcinogenesis · 2025Article
- Multiome-wide Association Studies: Novel Approaches for Understanding Diseases.Genomics, proteomics & bioinformatics · 2024Review
- A proteome-wide association study identifies putative causal proteins for breast cancer risk.British journal of cancer · 2024Article
- Transcriptome-wide association analysis identifies candidate susceptibility genes for prostate-specific antigen levels in men without prostate cancer.HGG advances · 2024Article
- Development of a Longitudinal Prostate Cancer Transcriptomic and Clinical Data Linkage.JAMA network open · 2024Article
- Associations between genetically predicted plasma protein levels and Alzheimer's disease risk: a study using genetic prediction models.Alzheimer's research & therapy · 2024Article
- Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma.GigaScience · 2024Article
- The role of NOP58 in prostate cancer progression through SUMOylation regulation and drug response.Frontiers in pharmacology · 2024Article
- A transcriptome-wide association study identified susceptibility genes for hepatocellular carcinoma in East Asia.Gastroenterology report · 2024Article
- Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants.Nature genetics · 2023Article
- Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects.Human molecular genetics · 2023Article
Corrections and comments
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Authors and funding
15 authors at 10 institutions in 5 countries.
Funding
Abstract
A large proportion of heritability for prostate cancer risk remains unknown. Transcriptome-wide association study combined with validation comparing overall levels will help to identify candidate genes potentially playing a role in prostate cancer development. Using data from the Genotype-Tissue Expression Project, we built genetic models to predict normal prostate tissue gene expression using the statistical framework PrediXcan, a modified version of the unified test for molecular signatures and Joint-Tissue Imputation. We applied these prediction models to the genetic data of 79 194 prostate cancer cases and 61 112 controls to investigate the associations of genetically determined gene expression with prostate cancer risk. Focusing on associated genes, we compared their expression in prostate tumor vs normal prostate tissue, compared methylation of CpG sites located at these loci in prostate tumor vs normal tissue, and assessed the correlations between the differentiated genes' expression and the methylation of corresponding CpG sites, by analyzing The Cancer Genome Atlas (TCGA) data. We identified 573 genes showing an association with prostate cancer risk at a false discovery rate (FDR) ≤ 0.05, including 451 novel genes and 122 previously reported genes. Of the 573 genes, 152 showed differential expression in prostate tumor vs normal tissue samples. At loci of 57 genes, 151 CpG sites showed differential methylation in prostate tumor vs normal tissue samples. Of these, 20 CpG sites were correlated with expression of 11 corresponding genes. In this TWAS, we identified novel candidate susceptibility genes for prostate cancer risk, providing new insights into prostate cancer genetics and biology.
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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.