title: Increased genomic burden of germline copy number variants is associated with early onset breast cancer: Australian breast cancer family registry.
abstract: Women with breast cancer who have multiple affected relatives are more likely to have inherited genetic risk factors for the disease. All the currently known genetic risk factors for breast cancer account for less than half of the average familial risk. Furthermore, the genetic factor(s) underlying an increased cancer risk for many women from multiple-case families remain unknown. Rare genomic duplications and deletions, known as copy number variants (CNVs), cover more than 10% of a human genome, are often not assessed in studies of genetic predisposition, and could account for some of the so-called "missing heritability".
  
  
  
  We carried out a hypothesis-generating case-control study of breast cancer diagnosed before age 40 years (200 cases, 293 controls) using population-based cases from the Australian Breast Cancer Family Study. Genome-wide scanning for CNVs was performed using the Human610-Quad BeadChip and fine-mapping was conducted using PennCNV.
  
  
  
  We identified deletions overlapping two known cancer susceptibility genes, (BRCA1 and BLM), and a duplication overlapping SMARCB1, associated with risk. The number of deletions across the genome was 1.5-fold higher for cases than controls (P = 10-16), and 2-fold higher when only rare deletions overlapping genes (frequency <1%) were assessed (P = 5 × 10-4). Association tests of CNVs, followed by experimental validation of CNV calls, found deletions overlapping the OR4C11 and OR4P4 genes were associated with breast cancer (P = 0.02 and P = 0.03, respectively).
  
  
  
  These results suggest rare CNVs might have a role in breast cancer susceptibility, at least for disease at a young age.
authors.affiliation: Mackenzie Cancer Research Group, Department of Pathology, University of Otago, Christchurch, New Zealand.
authors.forename: Logan C
authors.initials: LC
authors.lastname: Walker
authors.affiliation: Biostatistics and Computational Biology Unit, University of Otago, Christchurch, New Zealand.
authors.forename: John F
authors.initials: JF
authors.lastname: Pearson
authors.affiliation: Mackenzie Cancer Research Group, Department of Pathology, University of Otago, Christchurch, New Zealand.
authors.forename: George A R
authors.initials: GA
authors.lastname: Wiggins
authors.affiliation: Cancer Epidemiology Centre, The Cancer Council Victoria, Melbourne, Australia.
authors.forename: Graham G
authors.initials: GG
authors.lastname: Giles
authors.affiliation: Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia. j.hopper@unimelb.edu.au.
authors.forename: John L
authors.initials: JL
authors.lastname: Hopper
authors.affiliation: Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Melbourne, Victoria, Australia.
authors.forename: Melissa C
authors.initials: MC
authors.lastname: Southey
mesh_terms: D017668:Age of Onset; D001315:Australia / Q000453:epidemiology; D001943:Breast Neoplasms / Q000175:diagnosis / Q000453:epidemiology* / Q000235:genetics*; D016022:Case-Control Studies; D019295:Computational Biology / Q000379:methods; D056915:DNA Copy Number Variations; D005260:Female; D005787:Gene Frequency; D056726:Genetic Association Studies; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D023281:Genomics / Q000379:methods; D005854:Germ Cells / Q000378:metabolism*; D006801:Humans; D012042:Registries
keywords: Breast cancer; Copy number variants; Early onset; Genome-wide association analysis; Inherited susceptibility