Phenome-wide Mendelian randomisation analysis of 378,142 cases reveals risk factors for eight common cancers

Molly Went (), Amit Sud, Charlie Mills, Abi Hyde, Richard Culliford, Philip Law, Jayaram Vijayakrishnan, Ines Gockel, Carlo Maj, Johannes Schumacher, Claire Palles, Martin Kaiser and Richard Houlston
Additional contact information
Molly Went: The Institute of Cancer Research
Amit Sud: The Institute of Cancer Research
Charlie Mills: The Institute of Cancer Research
Abi Hyde: The Institute of Cancer Research
Richard Culliford: The Institute of Cancer Research
Philip Law: The Institute of Cancer Research
Jayaram Vijayakrishnan: The Institute of Cancer Research
Ines Gockel: University Hospital of Leipzig
Carlo Maj: University Hospital of Marburg
Johannes Schumacher: University Hospital of Marburg
Claire Palles: University of Birmingham
Martin Kaiser: The Institute of Cancer Research
Richard Houlston: The Institute of Cancer Research

Nature Communications, 2024, vol. 15, issue 1, 1-12

Abstract: Abstract For many cancers there are only a few well-established risk factors. Here, we use summary data from genome-wide association studies (GWAS) in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to identify potentially causal relationships for over 3,000 traits. Our outcome datasets comprise 378,142 cases across breast, prostate, colorectal, lung, endometrial, oesophageal, renal, and ovarian cancers, as well as 485,715 controls. We complement this analysis by systematically mining the literature space for supporting evidence. In addition to providing supporting evidence for well-established risk factors (smoking, alcohol, obesity, lack of physical activity), we also find sex steroid hormones, plasma lipids, and telomere length as determinants of cancer risk. A number of the molecular factors we identify may prove to be potential biomarkers. Our analysis, which highlights aetiological similarities and differences in common cancers, should aid public health prevention strategies to reduce cancer burden. We provide a R/Shiny app to visualise findings.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-024-46927-z Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-46927-z

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-46927-z

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().