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Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma.
(2018-09-13)
Genome-wide association studies (GWAS) have transformed our understanding of susceptibility to multiple myeloma (MM), but much of the heritability remains unexplained. We report a new GWAS, a meta-analysis with previous ...
Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes.
(BMC, 2019-08-20)
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 ...
Genetic correlation between multiple myeloma and chronic lymphocytic leukaemia provides evidence for shared aetiology.
(NATURE PUBLISHING GROUP, 2018-12-21)
The clustering of different types of B-cell malignancies in families raises the possibility of shared aetiology. To examine this, we performed cross-trait linkage disequilibrium (LD)-score regression of multiple myeloma ...
Capture Hi-C identifies putative target genes at 33 breast cancer risk loci.
(NATURE PUBLISHING GROUP, 2018-03-12)
Genome-wide association studies (GWAS) have identified approximately 100 breast cancer risk loci. Translating these findings into a greater understanding of the mechanisms that influence disease risk requires identification ...
A genome-wide association study identifies risk loci for childhood acute lymphoblastic leukemia at 10q26.13 and 12q23.1.
(NATURE PUBLISHING GROUP, 2017-03-01)
Genome-wide association studies (GWASs) have shown that common genetic variation contributes to the heritable risk of childhood acute lymphoblastic leukemia (ALL). To identify new susceptibility loci for the largest subtype ...
Multiple myeloma risk variant at 7p15.3 creates an IRF4-binding site and interferes with CDCA7L expression.
(NATURE PUBLISHING GROUP, 2016-11-24)
Genome-wide association studies have identified several risk loci for multiple myeloma (MM); however, the mechanisms by which they influence MM are unknown. Here by using genetic association data and functional characterization, ...
Assessing the effect of obesity-related traits on multiple myeloma using a Mendelian randomisation approach.
(NATURE PUBLISHING GROUP, 2017-06-16)