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

Author(s): 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;
Details: Publication Year 2020-01,Volume 52,Issue #1,Page 56-73
Journal Title: Nature Genetics
Publication Type: Journal Article
Abstract: 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.
Publisher: NPG
Research Division(s): Cancer Biology And Stem Cells
PubMed ID: 31911677
Publisher's Version: https://doi.org/10.1038/s41588-019-0537-1
Open Access at Publisher's Site: http://www.ncbi.nlm.nih.gov/pmc/articles/pmc6974400/
Terms of Use/Rights Notice: Refer to copyright notice on published article.

Creation Date: 2020-05-04 11:46:50

Last Modified: 2020-05-04 01:56:27