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. © 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.
Original languageEnglish
Pages (from-to)56-73
Number of pages18
JournalNat. Genet.
Volume52
Issue number1
DOIs
Publication statusPublished - 2020

Keywords

  • transcription factor
  • tumor marker
  • apoptosis
  • Article
  • binding site
  • breast cancer
  • cancer risk
  • chromatin
  • controlled study
  • female
  • gene expression
  • gene linkage disequilibrium
  • gene mapping
  • gene ontology
  • genetic variability
  • genome-wide association study
  • genomics
  • human
  • human cell
  • human tissue
  • immune system
  • MCF-7 cell line
  • priority journal
  • quantitative trait locus
  • Bayes theorem
  • breast tumor
  • chromosomal mapping
  • genetic predisposition
  • genetics
  • procedures
  • regulatory sequence
  • risk factor
  • single nucleotide polymorphism
  • Bayes Theorem
  • Biomarkers, Tumor
  • Breast Neoplasms
  • Chromosome Mapping
  • Female
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study
  • Humans
  • Linkage Disequilibrium
  • Polymorphism, Single Nucleotide
  • Quantitative Trait Loci
  • Regulatory Sequences, Nucleic Acid
  • Risk Factors

Fingerprint Dive into the research topics of 'Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes: Nature Genetics'. Together they form a unique fingerprint.

Cite this