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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.
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Details
1 University of Bristol, MRC Integrative Epidemiology Unit, Bristol, UK (GRID:grid.5337.2) (ISNI:0000 0004 1936 7603)
2 University of Bristol, MRC Integrative Epidemiology Unit, Bristol, UK (GRID:grid.5337.2) (ISNI:0000 0004 1936 7603); University of Bristol, Department of Population Health Sciences, Bristol Medical School, Bristol, UK (GRID:grid.5337.2) (ISNI:0000 0004 1936 7603); University Hospitals Bristol and University of Bristol, National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, Bristol, UK (GRID:grid.410421.2) (ISNI:0000 0004 0380 7336)
3 Baylor College of Medicine, Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan, Comprehensive Cancer Centre, Houston, USA (GRID:grid.39382.33) (ISNI:0000 0001 2160 926X)
4 Stanford University, Department of Epidemiology and Population Health, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956)
5 University of Bristol, MRC Integrative Epidemiology Unit, Bristol, UK (GRID:grid.5337.2) (ISNI:0000 0004 1936 7603); Brain Tumour Research Centre, Bristol, UK (GRID:grid.5337.2)