Evidence map›Paper›PMID 35361153›Full record

ArticleBMC cancer2022

Causal relationship between genetically predicted depression and cancer risk: a two-sample bi-directional mendelian randomization.

Guang-Li Zhu, Cheng Xu, Kai-Bin Yang, Si-Qi Tang, Ling-Long Tang, Lei Chen, Wen-Fei Li, Yan-Ping Mao, Jun Ma

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 2 pooled it
14.6field-weighted citation impact, top 1% 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

43 citing papers in PubMed, 2 syntheses or guidelines pooled it, 74 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

9 authors at 1 institution in 1 country.

Guang-Li Zhu *Department of Radiation Oncology, Sun Yat-Sen University Cancer Center State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, 510060, Guangzhou, PR China.
Cheng Xu *Department of Radiation Oncology, Sun Yat-Sen University Cancer Center State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, 510060, Guangzhou, PR China.
Kai-Bin Yang *Department of Radiation Oncology, Sun Yat-Sen University Cancer Center State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, 510060, Guangzhou, PR China.
Si-Qi TangDepartment of Radiation Oncology, Sun Yat-Sen University Cancer Center State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, 510060, Guangzhou, PR China.
Ling-Long TangDepartment of Radiation Oncology, Sun Yat-Sen University Cancer Center State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, 510060, Guangzhou, PR China.
Lei ChenDepartment of Radiation Oncology, Sun Yat-Sen University Cancer Center State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, 510060, Guangzhou, PR China.
Wen-Fei LiDepartment of Radiation Oncology, Sun Yat-Sen University Cancer Center State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, 510060, Guangzhou, PR China.
Yan-Ping MaoDepartment of Radiation Oncology, Sun Yat-Sen University Cancer Center State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, 510060, Guangzhou, PR China.
Jun MaDepartment of Radiation Oncology, Sun Yat-Sen University Cancer Center State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, 510060, Guangzhou, PR China. majun2@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-1137-9349
Sun Yat-sen University · CN

Funding

key-area research and development program of guangdong province 2019B020230002Medical Research Council MC_PC_17228Medical Research Council MC_QA137853natural science foundation of guangdong province 2017A030312003overseas expertise introduction project for discipline innovation B14035
6 · The paper itself

Abstract

backgroundDepression has been reported to be associated with some types of cancer in observational studies. However, the direction and magnitude of the causal relationships between depression and different types of cancer remain unclear.

methodsWe performed the two-sample bi-directional mendelian randomization with the publicly available GWAS summary statistics to investigate the causal relationship between the genetically predicted depression and the risk of multiple types of cancers, including ovarian cancer, breast cancer, lung cancer, glioma, pancreatic cancer, lymphoma, colorectal cancer, thyroid cancer, bladder cancer, and kidney cancer. The total sample size varies from 504,034 to 729,150. Causal estimate was calculated by inverse variance weighted method. We also performed additional sensitivity tests to evaluate the validity of the causal relationship.

resultsAfter correction for heterogeneity and horizontal pleiotropy, we only detected suggestive evidence for the causality of genetically predicted depression on breast cancer (OR = 1.09, 95% CI: 1.03-1.15, P = 0.0022). The causal effect of depression on breast cancer was consistent in direction and magnitude in the sensitivity analysis. No evidence of causal effects of depression on other types of cancer and reverse causality was detected.

conclusionsThe result of this study suggests a causative effect of genetically predicted depression on specific type of cancer. Our findings emphasize the importance of depression in the prevention and treatment of breast cancer.

Indexed as

Breast NeoplasmsLung NeoplasmsCausalityDepressionFemaleHumansMendelian Randomization AnalysisCancerCausalityDepressionGWASMendelian randomization

Identifiers

PMID35361153
PMCPMC8973550
OpenAlexW4220750454

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.