Evidence map›Paper›PMID 35403707›Full record

ArticleInternational journal of cancer2022

Mendelian randomization analyses of 23 known and suspected risk factors and biomarkers for breast cancer overall and by molecular subtypes.

Fa Chen, Wanqing Wen, Jirong Long, Xiang Shu, Yaohua Yang, Xiao-Ou Shu, Wei Zheng

Open access · greenAbstract read
In one paragraph

Article in International journal of cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 3 pooled it
11.2field-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

36 citing papers in PubMed, 3 syntheses or guidelines pooled it, 59 citations in OpenAlex.

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  10. Causal Effects of Breast Cancer Risk Factors across Hormone Receptor Breast Cancer Subtypes: A Two-Sample Mendelian Randomization Study.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
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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

7 authors at 2 institutions in 2 countries.

Fa ChenDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Wanqing WenDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Jirong LongDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Xiang ShuDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Yaohua YangDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Xiao-Ou ShuDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID 0000-0002-0711-8314
Wei ZhengDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID 0000-0003-1226-070X
Vanderbilt University Medical Center · USFujian Medical University · CN

Funding

Integrating genomic and transcriptomic data to identify breast cancer susceptibility genesR01CA235553 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI LONG, JIRONG, ZHENG, WEI · 2019 to 2024
$3.3M
Uncovering Roles of Metabolites in Colorectal Cancer EtiologyR00CA230205 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI SHU, XIANG · 2020 to 2022
$888k
NCI NIH HHS R00 CA230205NCI NIH HHS R01 CA235553
6 · The paper itself

Abstract

Many risk factors have been identified for breast cancer. The potential causality for some of them remains uncertain, and few studies have comprehensively investigated these associations by molecular subtypes. We performed a two-sample Mendelian randomization (MR) study to evaluate potential causal associations of 23 known and suspected risk factors and biomarkers with breast cancer risk overall and by molecular subtypes using data from the Breast Cancer Association Consortium. The inverse-variance weighted method was used to estimate odds ratios (OR) and 95% confidence interval (CI) for association of each trait with breast cancer risk. Significant associations with breast cancer risk were found for 15 traits, including age at menarche, age at menopause, body mass index, waist-to-hip ratio, height, physical activity, cigarette smoking, sleep duration, and morning-preference chronotype, and six blood biomarkers (estrogens, insulin-like growth factor-1, sex hormone-binding globulin [SHBG], telomere length, HDL-cholesterol and fasting insulin). Noticeably, an increased circulating SHBG was associated with a reduced risk of estrogen receptor (ER)-positive cancer (OR = 0.83, 95% CI: 0.73-0.94), but an elevated risk of ER-negative (OR = 1.12, 95% CI: 0.93-1.36) and triple negative cancer (OR = 1.19, 95% CI: 0.92-1.54) (P

Indexed as

Breast NeoplasmsMendelian Randomization AnalysisBiomarkersFemaleGenome-Wide Association StudyHumansInsulinPolymorphism, Single NucleotideRisk FactorsBiomarkersInsulinbreast cancercausal inferenceepidemiologyMendelian randomizationmolecular subtypesrisk factors

Identifiers

PMID35403707
PMCPMC9177773
OpenAlexW4223467638

What OpenQuestion holds

Textmetadata
LicenceTDM
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.