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

Research output: Contribution to journalJournal articleResearchpeer-review

  1. Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses

    Research output: Contribution to journalJournal articleResearchpeer-review

  2. Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson’s disease

    Research output: Contribution to journalJournal articleResearchpeer-review

  3. Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing

    Research output: Contribution to journalJournal articleResearchpeer-review

  4. Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer

    Research output: Contribution to journalJournal articleResearchpeer-review

  1. Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women

    Research output: Contribution to journalJournal articleResearchpeer-review

  2. Cytoplasmic mRNPs revisited: Singletons and condensates

    Research output: Contribution to journalJournal articleResearchpeer-review

  • GEMO Study Collaborators
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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.

Original languageEnglish
JournalNature Genetics
Volume52
Issue number1
Pages (from-to)56-73
Number of pages18
ISSN1061-4036
DOIs
Publication statusPublished - Jan 2020

ID: 59351842