Literature DB >> 33504897

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

Jamie W Robinson1, Richard M Martin2,3,4, Jie Zheng2, Kathreena M Kurian5,6, Spiridon Tsavachidis7, Amy E Howell2, Caroline L Relton2, Georgina N Armstrong8, Melissa Bondy8.   

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.

Entities:  

Year:  2021        PMID: 33504897      PMCID: PMC7840943          DOI: 10.1038/s41598-021-82169-5

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  4 in total

1.  Identification of differentially expressed genes in human gliomas by DNA microarray and tissue chip techniques.

Authors:  S L Sallinen; P K Sallinen; H K Haapasalo; H J Helin; P T Helén; P Schraml; O P Kallioniemi; J Kononen
Journal:  Cancer Res       Date:  2000-12-01       Impact factor: 12.701

2.  A benchmark of gene expression tissue-specificity metrics.

Authors:  Nadezda Kryuchkova-Mostacci; Marc Robinson-Rechavi
Journal:  Brief Bioinform       Date:  2017-03-01       Impact factor: 11.622

3.  The MR-Base platform supports systematic causal inference across the human phenome.

Authors:  Gibran Hemani; Jie Zheng; Benjamin Elsworth; Tom R Gaunt; Philip C Haycock; Kaitlin H Wade; Valeriia Haberland; Denis Baird; Charles Laurin; Stephen Burgess; Jack Bowden; Ryan Langdon; Vanessa Y Tan; James Yarmolinsky; Hashem A Shihab; Nicholas J Timpson; David M Evans; Caroline Relton; Richard M Martin; George Davey Smith
Journal:  Elife       Date:  2018-05-30       Impact factor: 8.140

Review 4.  Use of Mendelian Randomization for Identifying Risk Factors for Brain Tumors.

Authors:  Amy Elizabeth Howell; Jie Zheng; Philip C Haycock; Alexandra McAleenan; Caroline Relton; Richard M Martin; Kathreena M Kurian
Journal:  Front Genet       Date:  2018-11-12       Impact factor: 4.599

  4 in total
  2 in total

1.  Identifying causal genes for depression via integration of the proteome and transcriptome from brain and blood.

Authors:  Yue-Ting Deng; Ya-Nan Ou; Bang-Sheng Wu; Yu-Xiang Yang; Yan Jiang; Yu-Yuan Huang; Yi Liu; Lan Tan; Qiang Dong; John Suckling; Fei Li; Jin-Tai Yu
Journal:  Mol Psychiatry       Date:  2022-03-16       Impact factor: 13.437

Review 2.  The Scaffold Protein PICK1 as a Target in Chronic Pain.

Authors:  Andreas Toft Sørensen; Joscha Rombach; Ulrik Gether; Kenneth Lindegaard Madsen
Journal:  Cells       Date:  2022-04-07       Impact factor: 7.666

  2 in total

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