Evidence map›Paper›PMID 35237847›Full record

ArticleArchives of toxicology2022

Genetic variants in choline metabolism pathway are associated with the risk of bladder cancer in the Chinese population.

Zhichao Han, Jingjing Gu, Junyi Xin, Hanting Liu, Yanling Wu, Mulong Du, Haiyan Chu, Yadong Liu, Zhengdong Zhang

Abstract read
PubMed Publisher
In one paragraph

Article in Archives of toxicology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 41% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
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  4. The Effects ofAnimals : an open access journal from MDPI · 2024
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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

9 authors at 3 institutions in 2 countries.

Zhichao Han *Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China.
Jingjing Gu *Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China.
Junyi XinJiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China.
Hanting LiuJiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China.
Yanling WuJiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China.
Mulong DuJiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China.
Haiyan ChuJiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China.
Yadong LiuDepartment of Urology, The Yancheng School of Clinical Medicine of Nanjing Medical University (The Third People's Hospital of Yancheng), NO. 2 Xindu West Road, Yancheng, 224001, China. liuyadong@njmu.edu.cn.
Zhengdong ZhangJiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China. drzdzhang@njmu.edu.cn.ORCID http://orcid.org/0000-0002-6730-9251
Nanjing Institute of Environmental Sciences · CNMinistry of Education · KRYancheng Third People's Hospital · CN

Funding

National Natural Science Foundation of China 82130096
6 · The paper itself

Abstract

Choline metabolism alteration is considered as a metabolic hallmark in cancer, reflecting the complex interactions between carcinogenic signaling pathways and cancer metabolism, but little is known about whether genetic variants in the metabolism pathway contribute to the susceptibility of bladder cancer. Herein, a case-control study comprising 580 patients and 1,101 controls was carried out to analyze the association of bladder cancer with genetic variants on candidate genes involved in the choline metabolism pathway using unconditional logistic regression. Gene expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were applied for differential gene expression analysis. Cox regression was also applied to estimate the role of candidate genes on bladder cancer prognosis. Our results demonstrated that C allele of rs6810830 in ENPP6 was a significant protective allele of bladder cancer, compared to the T allele [Odds ratio (OR) = 0.74, 95% confidence interval (CI) = 0.64-0.86, P = 7.14 × 10

Indexed as

Urinary Bladder NeoplasmsCase-Control StudiesChinaCholineFemaleGenetic Predisposition to DiseaseHumansMalePolymorphism, Single NucleotideCholineBladder cancerCholine metabolismGenetic variantsMolecular epidemiologySusceptibility

Identifiers

PMID35237847
OpenAlexW4214936519

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.