Evidence map›Paper›PMID 39565278›Full record

SynthesisHuman molecular genetics2025

Brain multi-omic Mendelian randomisation to identify novel drug targets for gliomagenesis.

Zak A Thornton, Lily J Andrews, Huiling Zhao, Jie Zheng, Lavinia Paternoster, Jamie W Robinson, Kathreena M Kurian

Abstract readMeta-Analysis
In one paragraph

Synthesis in Human molecular genetics, 2025. 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
–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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
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.

Zak A ThorntonMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom.ORCID 0000-0001-9275-7198
Lily J AndrewsMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom.
Huiling ZhaoMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom.
Jie ZhengMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom.ORCID 0000-0002-4265-6695
Lavinia PaternosterMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom.
Jamie W RobinsonMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom.
Kathreena M KurianMRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom.

Funding

Cancer Research UK C18281/A30905Cancer Research UK C30758/A29791Innovate 10027624National Institute for Health and Care Research Bristol Biomedical Research Centre NIHR203315National Institute for Health and Social Care Research (NIHR) Leeds Biomedical Research Centre (BRC) NIHR203331Southmead Hospital Charitable Funds: Brain tumour bank and research fund 8036UK Medical Research Council Integrative Epidemiology Unit at the University of Bristol MC_UU_00011/1
6 · The paper itself

Abstract

backgroundGenetic variants associated with molecular traits that are also associated with liability to glioma can provide causal evidence for the identification and prioritisation of drug targets.

methodsWe performed comprehensive two-sample Mendelian randomisation (Wald ratio and/or IVW) and colocalisation analyses of molecular traits on glioma. Instrumentable traits (QTLs P < 5 × 10-8) were identified amongst 11 985 gene expression measures, 13 285 splicing isoforms and 10 198 protein abundance measures, derived from 15 brain regions. Glioma summary-level data was extracted from a genome-wide association meta-analysis of 12 496 cases and 18 190 controls.

resultsWe found evidence for causal effect of 22 molecular traits (across 18 genes/proteins) on glioma risk. Thirteen molecular traits have been previously linked with glioma risk and five were novel; HBEGF (5q31.3) expression and all glioma [OR 1.36 (95%CI 1.19-1.55); P = 4.41 × 10-6]; a CEP192 (18p11.21) splice isoform and glioblastoma [OR 4.40 (95%CI 2.28-8.48); P = 9.78 × 10-4]; a FAIM (3q22.3) splice isoform and all glioma [OR 2.72-3.43; P = 1.03 × 10-5 to 1.09 × 10-5]; a SLC8A1 (2p22.1) splice isoform and all glioma [OR 0.37 (95%CI 0.24-0.56; P = 5.72 × 10-6]; D2HGDH (2q37.3) protein and all glioma [OR 0.86 (95%CI 0.80-0.92); P = 5.94 × 10-6)].

conclusionsWe provide robust causal evidence for prioritising genes and their protein products in glioma research. Our results highlight the importance of alternative splicing as a mechanism in gliomagenesis and as an avenue for exploration of drug targets.

Indexed as

Brain NeoplasmsGliomaBrainGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMendelian Randomization AnalysisMultiomicsPolymorphism, Single NucleotideQuantitative Trait Locie/s/pQTLgliomaMendelian randomisationmolecular traitsquantitative trait loci

Identifiers

PMID39565278
PMCPMC11780873

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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.