Evidence map›Paper›PMID 32493226›Full record

SynthesisBMC cancer2020

Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study.

A E Howell, J W Robinson, R E Wootton, A McAleenan, S Tsavachidis, Q T Ostrom, M Bondy, G Armstrong, C Relton, P Haycock and 3 more

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 3 pooled it
–field-weighted citation impact
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

16 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  8. Novel insights into rosacea's role in cancer risk: A Mendelian randomization approach.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 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

13 authors.

A E HowellBrain Tumour Research Centre, Institute of Clinical Neurosciences, University of Bristol, Bristol, UK.
J W RobinsonBrain Tumour Research Centre, Institute of Clinical Neurosciences, University of Bristol, Bristol, UK.
R E WoottonMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
A McAleenanPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
S TsavachidisSection of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, UK.
Q T OstromSection of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, UK.
M BondySection of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, UK.
G ArmstrongSection of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, UK.
C ReltonMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
P HaycockMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
R M MartinMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
J ZhengMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK. Jie.zheng@bristol.ac.uk.
K M KurianBrain Tumour Research Centre, Institute of Clinical Neurosciences, University of Bristol, Bristol, UK. Kathreena.kurian@bristol.ac.uk.

Funding

Cancer Research UK 19169Cancer Research UK 20138Cancer Research UK C18281/A19169Cancer Research UK C52724/A20138Medical Research Council MC_UU_00011/4
6 · The paper itself

Abstract

backgroundWhilst epidemiological studies have provided evidence of associations between certain risk factors and glioma onset, inferring causality has proven challenging. Using Mendelian randomization (MR), we assessed whether associations of 36 reported glioma risk factors showed evidence of a causal relationship.

methodsWe performed a systematic search of MEDLINE from inception to October 2018 to identify candidate risk factors and conducted a meta-analysis of two glioma genome-wide association studies (5739 cases and 5501 controls) to form our exposure and outcome datasets. MR analyses were performed using genetic variants to proxy for candidate risk factors. We investigated whether risk factors differed by subtype diagnosis (either glioblastoma (n = 3112) or non-glioblastoma (n = 2411)). MR estimates for each risk factor were determined using multiplicative random effects inverse-variance weighting (IVW). Sensitivity analyses investigated potential pleiotropy using MR-Egger regression, the weighted median estimator, and the mode-based estimator. To increase power, trait-specific polygenic risk scores were used to test the association of a genetically predicated increase in each risk factor with glioma onset.

resultsOur systematic search identified 36 risk factors that could be proxied using genetic variants. Using MR, we found evidence that four genetically predicted traits increased risk of glioma, glioblastoma or non-glioblastoma: longer leukocyte telomere length, liability to allergic disease, increased alcohol consumption and liability to childhood extreme obesity (> 3 standard deviations from the mean). Two traits decreased risk of non-glioblastoma cancers: increased low-density lipoprotein cholesterol (LDLc) and triglyceride levels. Our findings were similar across sensitivity analyses that made allowance for pleiotropy (genetic confounding).

conclusionsOur comprehensive investigation provides evidence of a causal link between both genetically predicted leukocyte telomere length, allergic disease, alcohol consumption, childhood extreme obesity, and LDLc and triglyceride levels, and glioma. The findings from our study warrant further research to uncover mechanisms that implicate these traits in glioma onset.

Indexed as

Cholesterol, LDLGenetic Predisposition to DiseaseGenome-Wide Association StudyGliomaHumansHypersensitivityMendelian Randomization AnalysisObesityPolymorphism, Single NucleotideRisk FactorsTelomere HomeostasisTriglyceridesCholesterol, LDLTriglyceridesCausal inferenceGliomaMendelian randomizationRisk factorSystematic search

Identifiers

PMID32493226
PMCPMC7268455

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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.