Evidence map›Paper›PMID 33504897›Full record

ArticleScientific reports2021

Transcriptome-wide Mendelian randomization study prioritising novel tissue-dependent genes for glioma susceptibility.

Jamie W Robinson, Richard M Martin, Spiridon Tsavachidis, Amy E Howell, Caroline L Relton, Georgina N Armstrong, Melissa Bondy, Jie Zheng, Kathreena M Kurian

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 25% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 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 5 institutions in 2 countries.

Jamie W Robinson *MRC Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK. jamie.robinson@bristol.ac.uk.
Richard M Martin *MRC Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK.
Spiridon TsavachidisDepartment of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan, Comprehensive Cancer Centre, Baylor College of Medicine, Houston, TX, 77030, USA.
Amy E HowellMRC Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK.
Caroline L ReltonMRC Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK.
Georgina N ArmstrongDepartment of Epidemiology and Population Health, Stanford University, Stanford, CA, 94305, USA.
Melissa BondyDepartment of Epidemiology and Population Health, Stanford University, Stanford, CA, 94305, USA.
Jie Zheng *MRC Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK.
Kathreena M Kurian *MRC Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK. kathreena.kurian@bristol.ac.uk.
MRC Epidemiology Unit · GBStanford University · USBaylor College of Medicine · USNIHR Bristol Biomedical Research Centre · GBUniversity of Bristol · GB

Funding

Cancer Research UK 29019Cancer Research UK C18281/A19169Medical Research Council MC_UU_00011/4Medical Research Council MC_UU_12013/1Medical Research Council MC_UU_12013/2
6 · The paper itself

Abstract

Genome-wide association studies (GWAS) have discovered 27 loci associated with glioma risk. Whether these loci are causally implicated in glioma risk, and how risk differs across tissues, has yet to be systematically explored. We integrated multi-tissue expression quantitative trait loci (eQTLs) and glioma GWAS data using a combined Mendelian randomisation (MR) and colocalisation approach. We investigated how genetically predicted gene expression affects risk across tissue type (brain, estimated effective n = 1194 and whole blood, n = 31,684) and glioma subtype (all glioma (7400 cases, 8257 controls) glioblastoma (GBM, 3112 cases) and non-GBM gliomas (2411 cases)). We also leveraged tissue-specific eQTLs collected from 13 brain tissues (n = 114 to 209). The MR and colocalisation results suggested that genetically predicted increased gene expression of 12 genes were associated with glioma, GBM and/or non-GBM risk, three of which are novel glioma susceptibility genes (RETREG2/FAM134A, FAM178B and MVB12B/FAM125B). The effect of gene expression appears to be relatively consistent across glioma subtype diagnoses. Examining how risk differed across 13 brain tissues highlighted five candidate tissues (cerebellum, cortex, and the putamen, nucleus accumbens and caudate basal ganglia) and four previously implicated genes (JAK1, STMN3, PICK1 and EGFR). These analyses identified robust causal evidence for 12 genes and glioma risk, three of which are novel. The correlation of MR estimates in brain and blood are consistently low which suggested that tissue specificity needs to be carefully considered for glioma. Our results have implicated genes yet to be associated with glioma susceptibility and provided insight into putatively causal pathways for glioma risk.

Indexed as

Genetic Predisposition to DiseaseGenome-Wide Association StudyGliomaHumansMendelian Randomization AnalysisPolymorphism, Single NucleotideQuantitative Trait LociTranscriptome

Identifiers

PMID33504897
PMCPMC7840943
OpenAlexW3121052573

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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.