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

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

In: Human Genomics, 13 (2019), Nr. 37. pp. 1-8. ISSN 1479-7364

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Download (1MB) | Lizenz: Creative Commons LizenzvertragTranscriptome-wide association study of multiple myeloma identifies candidate susceptibility genes by Went, Molly ; Kinnersley, Ben ; Sud, Amit ; Johnson, David C. ; Weinhold, Niels ; Försti, Asta ; van Duin, Mark ; Orlando, Giulia ; Mitchell, Jonathan S. ; Kuiper, Rowan ; Walker, Brian A. ; Gregory, Walter M. ; Hoffmann, Per ; Jackson, Graham H. ; Nöthen, Markus M. ; da Silva Filho, Miguel Inacio ; Thomsen, Hauke ; Broyl, Annemiek ; Davies, Faith E. ; Thorsteinsdottir, Unnur ; Hansson, Markus ; Kaiser, Martin ; Sonneveld, Pieter ; Goldschmidt, Hartmut ; Stefansson, Kari ; Hemminki, Kari ; Nilsson, Björn ; Morgan, Gareth J. ; Houlston, Richard S. underlies the terms of Creative Commons Attribution 4.0

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Abstract

Background: 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).

Results: GWAS 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.

Conclusions: Our 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.

Item Type: Article
Journal or Publication Title: Human Genomics
Volume: 13
Number: 37
Publisher: Henry Stewart Publ.
Place of Publication: London
Date Deposited: 28 Aug 2019 08:53
Date: 2019
ISSN: 1479-7364
Page Range: pp. 1-8
Faculties / Institutes: Service facilities > German Cancer Research Center (DKFZ)
Medizinische Fakultät Heidelberg > Medizinische Universitäts-Klinik und Poliklinik
Subjects: 610 Medical sciences Medicine
Uncontrolled Keywords: Genome-wide association study, Gene expression, Multiplemyeloma, Transcriptome-wide association study
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