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

被引:4
|
作者
Went, Molly [1 ]
Sud, Amit [1 ,2 ,3 ,4 ,5 ]
Mills, Charlie [1 ]
Hyde, Abi [1 ,6 ]
Culliford, Richard [1 ]
Law, Philip [1 ]
Vijayakrishnan, Jayaram [1 ]
Gockel, Ines [7 ]
Maj, Carlo [8 ]
Schumacher, Johannes [8 ]
Palles, Claire [9 ]
Kaiser, Martin [1 ,10 ]
Houlston, Richard [1 ]
机构
[1] Inst Canc Res, Div Genet & Epidemiol, London, England
[2] Dana Farber Canc Inst, Dept Med Oncol, Boston, MA USA
[3] Broad Inst MIT & Harvard, Cambridge, MA USA
[4] Harvard Med Sch, Boston, MA USA
[5] Univ Oxford, Nuffield Dept Med, Ctr Immuno Oncol, Oxford, England
[6] Univ Cambridge, Dept Engn, Cambridge, England
[7] Univ Hosp Leipzig, Dept Visceral Transplant Thorac & Vasc Surg, Leipzig, Germany
[8] Univ Hosp Marburg, Ctr Human Genet, Marburg, Germany
[9] Univ Birmingham, Inst Canc & Genom Sci, Birmingham, W Midlands, England
[10] Royal Marsden Hosp NHS Fdn Trust, London, England
基金
美国国家卫生研究院; 英国惠康基金; 瑞典研究理事会; 加拿大健康研究院; 英国医学研究理事会;
关键词
ENDOGENOUS SEX-HORMONES; SUSCEPTIBILITY LOCI; IDENTIFICATION; INSTRUMENTS; METAANALYSIS; ASSOCIATION; MORTALITY; WOMEN;
D O I
10.1038/s41467-024-46927-z
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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页数:12
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