title: Continuing difficulties in interpreting CNV data: lessons from a genome-wide CNV association study of Australian HNPCC/lynch syndrome patients.
abstract: BACKGROUND
  Hereditary non-polyposis colorectal cancer (HNPCC)/Lynch syndrome (LS) is a cancer syndrome characterised by early-onset epithelial cancers, especially colorectal cancer (CRC) and endometrial cancer. The aim of the current study was to use SNP-array technology to identify genomic aberrations which could contribute to the increased risk of cancer in HNPCC/LS patients.
  
  
  METHODS
  Individuals diagnosed with HNPCC/LS (100) and healthy controls (384) were genotyped using the Illumina Human610-Quad SNP-arrays. Copy number variation (CNV) calling and association analyses were performed using Nexus software, with significant results validated using QuantiSNP. TaqMan Copy-Number assays were used for verification of CNVs showing significant association with HNPCC/LS identified by both software programs.
  
  
  RESULTS
  We detected copy number (CN) gains associated with HNPCC/LS status on chromosome 7q11.21 (28% cases and 0% controls, Nexus; p =3.60E-20 and QuantiSNP; p < 1.00E-16) and 16p11.2 (46% in cases, while a CN loss was observed in 23% of controls, Nexus; p = 4.93E-21 and QuantiSNP; p = 5.00E-06) via in silico analyses. TaqMan Copy-Number assay was used for validation of CNVs showing significant association with HNPCC/LS. In addition, CNV burden (total CNV length, average CNV length and number of observed CNV events) was significantly greater in cases compared to controls.
  
  
  CONCLUSIONS
  A greater CNV burden was identified in HNPCC/LS cases compared to controls supporting the notion of higher genomic instability in these patients. One intergenic locus on chromosome 7q11.21 is possibly associated with HNPCC/LS and deserves further investigation. The results from this study highlight the complexities of fluorescent based CNV analyses. The inefficiency of both CNV detection methods to reproducibly detect observed CNVs demonstrates the need for sequence data to be considered alongside intensity data to avoid false positive results.
authors.affiliation: School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW, Australia. Bente.Talseth-Palmer@newcastle.edu.au
authors.forename: Bente A
authors.initials: BA
authors.lastname: Talseth-Palmer
authors.forename: Elizabeth G
authors.initials: EG
authors.lastname: Holliday
authors.forename: Tiffany-Jane
authors.initials: TJ
authors.lastname: Evans
authors.forename: Mark
authors.initials: M
authors.lastname: McEvoy
authors.forename: John
authors.initials: J
authors.lastname: Attia
authors.forename: Desma M
authors.initials: DM
authors.lastname: Grice
authors.forename: Amy L
authors.initials: AL
authors.lastname: Masson
authors.forename: Cliff
authors.initials: C
authors.lastname: Meldrum
authors.forename: Allan
authors.initials: A
authors.lastname: Spigelman
authors.forename: Rodney J
authors.initials: RJ
authors.lastname: Scott
mesh_terms: D000483:Alleles; D001315:Australia; D002897:Chromosomes, Human, Pair 7; D003123:Colorectal Neoplasms, Hereditary Nonpolyposis / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D056915:DNA Copy Number Variations; D004260:DNA Repair; D005787:Gene Frequency; D056426:Genetic Loci; D015894:Genome, Human; D055106:Genome-Wide Association Study; D042822:Genomic Instability; D005838:Genotype; D006801:Humans; D020641:Polymorphism, Single Nucleotide; D012307:Risk Factors; D012984:Software