Evidence map›Paper›PMID 36928917›Full record

SynthesisHuman molecular genetics2023

Cross-cancer pleiotropic analysis identifies three novel genetic risk loci for colorectal cancer.

Jing Sun, Lijuan Wang, Xuan Zhou, Lidan Hu, Shuai Yuan, Zilong Bian, Jie Chen, Yingshuang Zhu, Susan M Farrington, Harry Campbell and 5 more

Open access · greenAbstract readMeta-Analysis
In one paragraph

Synthesis in Human molecular genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.8field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 7 institutions in 3 countries.

Jing SunDepartment of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China.
Lijuan WangDepartment of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China.
Xuan ZhouDepartment of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China.
Lidan HuThe Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China.
Shuai YuanUnit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm 171 77, Sweden.
Zilong BianDepartment of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China.
Jie ChenDepartment of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China.
Yingshuang ZhuColorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Susan M FarringtonCancer Research UK Edinburgh Centre, Medical Research Council Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK.
Harry CampbellCentre for Global Health, Usher Institute, University of Edinburgh, Edinburgh EH8 9AG, UK.
Kefeng DingColorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Dongfeng ZhangDepartment of Epidemiology and Health Statistics, The School of Public Health of Qingdao University, Qingdao 266071, China.
Malcolm G DunlopCancer Research UK Edinburgh Centre, Medical Research Council Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK.
Evropi TheodoratouCentre for Global Health, Usher Institute, University of Edinburgh, Edinburgh EH8 9AG, UK.
Xue LiDepartment of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China.
Second Affiliated Hospital of Zhejiang University · CNEdinburgh Cancer Research · GBUniversity of Edinburgh · GBZhejiang University · CNChildren's Hospital of Zhejiang University · CNKarolinska Institutet · SEQingdao University · CN

Funding

Cancer Research UK 18927Cancer Research UK 22804Cancer Research UK C348/A12076Medical Research Council MC_PC_U127527198Medical Research Council MC_U127527198Medical Research Council MC_UU_00007/1
6 · The paper itself

Abstract

backgroundTo understand the shared genetic basis between colorectal cancer (CRC) and other cancers and identify potential pleiotropic loci for compensating the missing genetic heritability of CRC.

methodsWe conducted a systematic genome-wide pleiotropy scan to appraise associations between cancer-related genetic variants and CRC risk among European populations. Single nucleotide polymorphism (SNP)-set analysis was performed using data from the UK Biobank and the Study of Colorectal Cancer in Scotland (10 039 CRC cases and 30 277 controls) to evaluate the overlapped genetic regions for susceptibility of CRC and other cancers. The variant-level pleiotropic associations between CRC and other cancers were examined by CRC genome-wide association study meta-analysis and the pleiotropic analysis under composite null hypothesis (PLACO) pleiotropy test. Gene-based, co-expression and pathway enrichment analyses were performed to explore potential shared biological pathways. The interaction between novel genetic variants and common environmental factors was further examined for their effects on CRC.

resultsGenome-wide pleiotropic analysis identified three novel SNPs (rs2230469, rs9277378 and rs143190905) and three mapped genes (PIP4K2A, HLA-DPB1 and RTEL1) to be associated with CRC. These genetic variants were significant expressions quantitative trait loci in colon tissue, influencing the expression of their mapped genes. Significant interactions of PIP4K2A and HLA-DPB1 with environmental factors, including smoking and alcohol drinking, were observed. All mapped genes and their co-expressed genes were significantly enriched in pathways involved in carcinogenesis.

conclusionOur findings provide an important insight into the shared genetic basis between CRC and other cancers. We revealed several novel CRC susceptibility loci to help understand the genetic architecture of CRC.

Indexed as

Colorectal NeoplasmsGenome-Wide Association StudyAlcohol DrinkingGenetic LociGenetic Predisposition to DiseaseHumansPhosphotransferases (Alcohol Group Acceptor)Polymorphism, Single NucleotideQuantitative Trait LociRiskPhosphotransferases (Alcohol Group Acceptor)PIP4K2A protein, human

Identifiers

PMID36928917
PMCPMC10244225
OpenAlexW4327575252

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.