Six low-penetrance SNPs for the estimation of breast cancer heritability: A family-based study in Caucasian Italian patients

De Summa,Simona; Graziano,Francesca; Pilato,Brunella; Pinto,Rosamaria; Danza,Katia; Lacalamita,Rosanna; Serratì,Simona; Sambiasi,Domenico; Grassi,Mario; Tommasi,Stefania

doi:10.3892/ol.2017.6725

Six low-penetrance SNPs for the estimation of breast cancer heritability: A family-based study in Caucasian Italian patients

Authors:
- Simona De Summa
- Francesca Graziano
- Brunella Pilato
- Rosamaria Pinto
- Katia Danza
- Rosanna Lacalamita
- Simona Serratì
- Domenico Sambiasi
- Mario Grassi
- Stefania Tommasi
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Affiliations: Molecular Genetics Laboratory, IRCCS, Istituto Tumori ‘Giovanni Paolo II’, I‑70124 Bari, Italy, Department of Brain and Behavioral Sciences, Section of Biostatistics, NeuroPhysiology and Psychiatry, Unit of Medical Statistics and Genomics, University of Pavia, I‑27100 Pavia, Italy, Familial Hereditary Cancer Study Unit, IRCCS, Istituto Tumori ‘Giovanni Paolo II’, I‑70124 Bari, Italy
Published online on: August 4, 2017 https://doi.org/10.3892/ol.2017.6725
Pages: 4384-4390

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Abstract

Breast cancer is a malignancy with a strong heritable component. Genetic counseling has been principally focused on families carrying high-penetrance breast cancer 1/2, early onset genes. Current modeling suggests that the majority of the unexplained fraction of familial risk is likely to be explained by a polygenic model. The aim of the present study was to estimate the heritability (h2) of breast cancer susceptibility through the analysis of 6 single nucleotide polymorphisms (SNPs), nuclear mitotic apparatus protein 1, cyclin D1, cytochrome C oxidase copper chaperone, fibroblast growth factor receptor 2, TOX high mobility group box family member 3 and solute carrier family 4 member 7. These 6 SNPs, previously identified by genome‑wide association studies, were considered to evaluate the additive and common environmental components that contribute to the development of breast cancer in nuclear (pedigrees including only first degree relationships) and in extended families (with at most third degree relationships). A total of 22 extended pedigrees, subsequently split into 52 nuclear pedigrees were analyzed. An example of splitting process from extended to nuclear pedigree is shown in Fig. 1. Firstly, an underline latent continuous trait (Y*) using breast cancer status and information of 6 breast cancer‑associated SNPs was calculated. This novel trait summarized the susceptibility of breast cancer in each individual. Secondly, the h2 of Y* was estimated using an additive polygenic‑common environment‑unique error model. h2 was evaluated in extended and immediate pedigrees, obtaining comparable results. h2 accounts for ~40% of the total phenotypic variance, indicating a fairly strong additive genetic effect of breast cancer susceptibility. The present study indicated the importance of the evaluation and consideration of these six SNPs, which can be used as instrumental variables in order to obtain improved genetic models that are useful for h2 analysis.

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1	International Agency for Research on Cancer. http://globocan.iarc.frAccessed. November 15–2015.
2	Colditz GA, Willett WC, Hunter DJ, Stampfer MJ, Manson JE, Hennekens CH and Rosner BA: Family history, age, and risk of breast cancer. Prospective data from the Nurses' Health Study. JAMA. 270:338–343. 1993. View Article : Google Scholar : PubMed/NCBI
3	Slattery ML, Berry TD and Kerber RA: Is survival among women diagnosed with breast cancer influenced by family history of breast cancer? Epidemiology. 4:543–548. 1993. View Article : Google Scholar : PubMed/NCBI
4	Pharoah PD, Day NE, Duffy S, Easton DF and Ponder BA: Family history and the risk of breast cancer: A systematic review and meta-analysis. Int J Cancer. 71:800–809. 1997. View Article : Google Scholar : PubMed/NCBI
5	Bevier M, Sundquist K and Hemminki K: Risk of breast cancer in families of multiple affected women and men. Breast Cancer Res Treat. 132:723–728. 2012. View Article : Google Scholar : PubMed/NCBI
6	Thompson D and Easton D: The genetic epidemiology of breast cancer genes. J Mammary Gland Biol Neoplasia. 9:221–236. 2004. View Article : Google Scholar : PubMed/NCBI
7	Chenevix-Trench G, Milne RL, Antoniou AC, Couch FJ, Easton DF and Goldgar DE: An international initiative to identify genetic modifiers of cancer risk in BRCA1 and BRCA2 mutation carriers: The Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA). Breast Cancer Res. 9:1042007. View Article : Google Scholar : PubMed/NCBI
8	Breast Cancer Association Consortium: Commonly studied single-nucleotide polymorphisms and breast cancer: Results from the Breast Cancer Association Consortium. J Natl Cancer Inst. 98:1382–1396. 2006. View Article : Google Scholar : PubMed/NCBI
9	Sawyer S, Mitchell G, McKinley J, Chenevix-Trench G, Beesley J, Chen XQ, Bowtell D, Trainer AH, Harris M, Lindeman GJ and James PA: A role for common genomic variants in the assessment of familial breast cancer. J Clin Oncol. 30:4330–4336. 2012. View Article : Google Scholar : PubMed/NCBI
10	Visscher PM, Hill WG and Wray NR: Heritability in the genomics era-concepts and misconceptions. Nat Rev Genet. 9:255–266. 2008. View Article : Google Scholar : PubMed/NCBI
11	Ahmed S, Thomas G, Ghoussaini M, Healey CS, Humphreys MK, Platte R, Morrison J, Maranian M, Pooley KA, Luben R, et al: Newly discovered breast cancer susceptibility loci on 3p24 and 17q23.2. Nat Genet. 41:585–590. 2009. View Article : Google Scholar : PubMed/NCBI
12	Easton DF, Pooley KA, Dunning AM, Pharoah PD, Thompson D, Ballinger DG, Struewing JP, Morrison J, Field H, Luben R, et al: Genome-wide association study identifies novel breast cancer susceptibility loci. Nature. 447:1087–1093. 2007. View Article : Google Scholar : PubMed/NCBI
13	Turnbull C, Ahmed S, Morrison J, Pernet D, Renwick A, Maranian M, Seal S, Ghoussaini M, Hines S, Healey CS, et al: Genome-wide association study identifies five new breast cancer susceptibility loci. Nat Genet. 42:504–507. 2010. View Article : Google Scholar : PubMed/NCBI
14	Stacey SN, Manolescu A, Sulem P, Rafnar T, Gudmundsson J, Gudjonsson SA, Masson G, Jakobsdottir M, Thorlacius S, Helgason A, et al: Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor-positive breast cancer. Nat Genet. 39:865–869. 2007. View Article : Google Scholar : PubMed/NCBI
15	Claus EB, Risch N and Thompson WD: The calculation of breast cancer risk for women with a first degree family history of ovarian cancer. Breast Cancer Res Treat. 28:115–120. 1993. View Article : Google Scholar : PubMed/NCBI
16	Claus EB, Risch N and Thompson WD: Autosomal dominant inheritance of early-onset breast cancer. Implications for risk prediction. Cancer. 73:643–651. 1994. View Article : Google Scholar : PubMed/NCBI
17	Gail MH, Brinton LA, Byar DP, Corle DK, Green SB, Schairer C and Mulvihill JJ: Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst. 81:1879–1886. 1989. View Article : Google Scholar : PubMed/NCBI
18	Parmigiani G, Berry D and Aguilar O: Determining carrier probabilities for breast cancer-susceptibility genes BRCA1 and BRCA2. Am J Hum Genet. 62:145–158. 1998. View Article : Google Scholar : PubMed/NCBI
19	Berry DA, Iversen ES Jr, Gudbjartsson DF, Hiller EH, Garber JE, Peshkin BN, Lerman C, Watson P, Lynch HT, Hilsenbeck SG, et al: BRCAPRO validation, sensitivity of genetic testing of BRCA1/BRCA2 and prevalence of other breast cancer susceptibility genes. J Clin Oncol. 20:2701–2712. 2002. View Article : Google Scholar : PubMed/NCBI
20	Gail MH: Discriminatory accuracy from single-nucleotide polymorphisms in models to predict breast cancer risk. J Natl Cancer Inst. 100:1037–1041. 2008. View Article : Google Scholar : PubMed/NCBI
21	Gail MH: Value of adding single-nucleotide polymorphism genotypes to a breast cancer risk model. J Natl Cancer Inst. 101:959–963. 2009. View Article : Google Scholar : PubMed/NCBI
22	Sobin LH: TNM, sixth edition: New developments in general concepts and rules. Semin Surg Oncol. 21:19–22. 2003. View Article : Google Scholar : PubMed/NCBI
23	Tommasi S, Crapolicchio A, Lacalamita R, Bruno M, Monaco A, Petroni S, Schittulli F, Longo S, Digennaro M, Calistri D, et al: BRCA1 mutations and polymorphisms in a hospital-based consecutive series of breast cancer patients from Apulia, Italy. Mutat Res. 578:395–405. 2005. View Article : Google Scholar : PubMed/NCBI
24	Team R.C.D: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. 2005.
25	Benchek PH and Morris NJ: How meaningful are heritability estimates of liability? Hum Genet. 132:1351–1360. 2013. View Article : Google Scholar : PubMed/NCBI
26	Muthén LK and Muthén B: Mplus User's Guide. 6th. CA, Muthén & Muthén, Los Angeles: 2010
27	Almasy L and Blangero J: Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet. 62:1198–1211. 1998. View Article : Google Scholar : PubMed/NCBI
28	Neale M and Cardon L: Methodology for genetic studies of twins and families. Kluwer Academic Publishers B.V.Dordrecht; The Netherlands: 1992, View Article : Google Scholar
29	Familial breast cancer: Collaborative reanalysis of individual data from 52 epidemiological studies including 58,209 women with breast cancer and 101,986 women without the disease. Lancet. 358:1389–1399. 2001. View Article : Google Scholar : PubMed/NCBI
30	Antoniou A, Pharoah PD, Narod S, Risch HA, Eyfjord JE, Hopper JL, Loman N, Olsson H, Johannsson O, Borg A, et al: Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case Series unselected for family history: A combined analysis of 22 studies. Am J Hum Genet. 72:1117–1130. 2003. View Article : Google Scholar : PubMed/NCBI
31	Smith P, McGuffog L, Easton DF, Mann GJ, Pupo GM, Newman B, Chenevix-Trench G kConFab Investigators, Szabo C, Southey M, et al: A genome wide linkage search for breast cancer susceptibility genes. Genes Chromosomes Cancer. 45:646–655. 2006. View Article : Google Scholar : PubMed/NCBI
32	Hunter DJ, Kraft P, Jacobs KB, Cox DG, Yeager M, Hankinson SE, Wacholder S, Wang Z, Welch R, Hutchinson A, et al: A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer. Nat Genet. 39:870–874. 2007. View Article : Google Scholar : PubMed/NCBI
33	Cox A, Dunning AM, Garcia-Closas M, Balasubramanian S, Reed MW, Pooley KA, Scollen S, Baynes C, Ponder BA, Chanock S, et al: A common coding variant in CASP8 is associated with breast cancer risk. Nat Genet. 39:352–358. 2007. View Article : Google Scholar : PubMed/NCBI
34	Zhang B, Beeghly-Fadiel A, Long J and Zheng W: Genetic variants associated with breast-cancer risk: Comprehensive research synopsis, meta-analysis, and epidemiological evidence. Lancet Oncol. 12:477–488. 2011. View Article : Google Scholar : PubMed/NCBI
35	Antoniou AC, Pharoah PP, Smith P and Easton DF: The BOADICEA model of genetic susceptibility to breast and ovarian cancer. Br J Cancer. 91:1580–1590. 2004.PubMed/NCBI