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Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes


Fachal, L; Aschard, H; Beesley, J; Barnes, DR; ALLEN, J; Kar, S; Pooley, KA; Dennis, J; Michailidou, K; Turman, C; Soucy, P; Lemacon, A; Lush, M; Tyrer, JP; Ghoussaini, M; Moradi Marjaneh, M; Jiang, X; Gemo Study Collaborators,; Embrace Collaborators,; K ConFab Investigators,; Hebon Investigators,; Abctb Investigators,; includes Lindeman, GJ; Visvader, JE; Scott, C
2020-01
Nature Genetics
Journal Article
52
1
56-73
Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
NPG
Cancer Biology and Stem Cells
10.1038/s41588-019-0537-1
31911677
Refer to copyright notice on published article.

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Creation Date 2020-05-04 11:46:50 Last Modified 2020-05-04 01:56:27