Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes

Molly Went,Asta Försti,Jonathan S Mitchell,Björn Nilsson,David C Johnson,Walter M Gregory,Markus M Nöthen,Brian A Walker,Markus Hansson,Hartmut Goldschmidt,Hauke Thomsen,Martin Kaiser,Miguel Inácio Da Silva Filho ,Annemiek Broyl,Unnur Þorsteinsdóttir ,Mark Van Duin,Rowan Kuiper,Ben Kinnersley,Niels Weinhold,Kari Hemminki,Gareth J Morgan,Faith E Davies,Per Hoffmann,Graham Jackson ,Pieter Sonneveld,Kári Stefánsson ,Amit Sud,Giulia Orlando,Richard S Houlston

doi:10.1186/s40246-019-0231-5

Abstract

BackgroundWhile genome-wide association studies (GWAS) of multiple myeloma (MM) have identified variants at 23 regions influencing risk, the genes underlying these associations are largely unknown. To identify candidate causal genes at these regions and search for novel risk regions, we performed a multi-tissue transcriptome-wide association study (TWAS).ResultsGWAS data on 7319 MM cases and 234,385 controls was integrated with Genotype-Tissue Expression Project (GTEx) data assayed in 48 tissues (sample sizes, N = 80–491), including lymphocyte cell lines and whole blood, to predict gene expression. We identified 108 genes at 13 independent regions associated with MM risk, all of which were in 1 Mb of known MM GWAS risk variants. Of these, 94 genes, located in eight regions, had not previously been considered as a candidate gene for that locus.ConclusionsOur findings highlight the value of leveraging expression data from multiple tissues to identify candidate genes responsible for GWAS associations which provide insight into MM tumorigenesis. Among the genes identified, a number have plausible roles in MM biology, notably APOBEC3C, APOBEC3H, APOBEC3D, APOBEC3F, APOBEC3G, or have been previously implicated in other malignancies. The genes identified in this TWAS can be explored for follow-up and validation to further understand their role in MM biology.

Highlights

While genome-wide association studies (GWAS) of multiple myeloma (MM) have identified variants at 23 regions influencing risk, the genes underlying these associations are largely unknown
We identify 108 genes at 13 loci associated with MM risk and provide additional evidence of a potential role for a number of genes dysregulated in MM tumorigenesis
We evaluated the association between predicted gene expression levels and MM risk using MetaXcan with summary statistics for GWAS SNPs in 7319 MM cases and 234,385 controls

Summary

Introduction

While genome-wide association studies (GWAS) of multiple myeloma (MM) have identified variants at 23 regions influencing risk, the genes underlying these associations are largely unknown. To identify candidate causal genes at these regions and search for novel risk regions, we performed a multi-tissue transcriptome-wide association study (TWAS). Went et al Human Genomics (2019) 13:37 genome, they are enriched for variants correlated with gene expression levels [4, 5] Exploiting this characteristic, the integration of GWAS signals with expression quantitative trait loci (eQTLs) has implicated ELL2 and CDCA7L as the risk genes likely to be responsible for the 5q15 and 7p15.3 MM associations, respectively [6,7,8,9]. The high frequency of eQTLs coupled with linkage disequilibrium (LD) across regions can, make disentangling the risk genes from spurious co-localization at the same region problematic

Objectives

Methods

Results

Discussion

Conclusion