| Title: | Pan-cancer and cross-population genome-wide association studies dissect shared genetic backgrounds underlying carcinogenesis |
| Journal: | Nature Communications |
| Published: | 20 Jun 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37340002/ |
| DOI: | https://doi.org/10.1038/s41467-023-39136-7 |
| URL: | https://www.nature.com/articles/s41467-023-39136-7.pdf |
| Citations: | 8 (8 in last 2 years) as of 8 Aug 2024 |
Publication 7790
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
Integrating genomic data of multiple cancers allows de novo cancer grouping and elucidating the shared genetic basis across cancers. Here, we conduct the pan-cancer and cross-population genome-wide association study (GWAS) meta-analysis and replication studies on 13 cancers including 250,015 East Asians (Biobank Japan) and 377,441 Europeans (UK Biobank). We identify ten cancer risk variants including five pleiotropic associations (e.g., rs2076295 at DSP on 6p24 associated with lung cancer and rs2525548 at TRIM4 on 7q22 nominally associated with six cancers). Quantifying shared heritability among the cancers detects positive genetic correlations between breast and prostate cancer across populations. Common genetic components increase the statistical power, and the large-scale meta-analysis of 277,896 breast/prostate cancer cases and 901,858 controls identifies 91 newly genome-wide significant loci. Enrichment analysis of pathways and cell types reveals shared genetic backgrounds across said cancers. Focusing on genetically correlated cancers can contribute to enhancing our insights into carcinogenesis.11 Authors
- Go Sato
- Yuya Shirai
- Shinichi Namba
- Ryuya Edahiro
- Kyuto Sonehara
- Tsuyoshi Hata
- Mamoru Uemura
- Koichi Matsuda
- Yuichiro Doki
- Hidetoshi Eguchi
- Yukinori Okada
1 Application
| Application ID | Title |
|---|---|
| 47821 | Trans-ethnic GWAS meta-analysis and exploration of trait-relevant genetic architecture. |
Enabling scientific discoveries that improve human health