Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2010 Mar 19:3:9.
doi: 10.1186/1755-8794-3-9.

Genotypes and haplotypes in the insulin-like growth factors, their receptors and binding proteins in relation to plasma metabolic levels and mammographic density

Margarethe Biong  1 , Inger T Gram, Ilene Brill, Fredrik Johansen, Hiroko K Solvang, Grethe I G Alnaes, Toril Fagerheim, Yngve Bremnes, Stephen J Chanock, Laurie Burdett, Meredith Yeager, Giske Ursin, Vessela N Kristensen
Affiliations

Genotypes and haplotypes in the insulin-like growth factors, their receptors and binding proteins in relation to plasma metabolic levels and mammographic density

Margarethe Biong et al. BMC Med Genomics. .

Abstract

Background: Increased mammographic density is one of the strongest independent risk factors for breast cancer. It is believed that one third of breast cancers are derived from breasts with more than 50% density. Mammographic density is affected by age, BMI, parity, and genetic predisposition. It is also greatly influenced by hormonal and growth factor changes in a woman's life cycle, spanning from puberty through adult to menopause. Genetic variations in genes coding for hormones and growth factors involved in development of the breast are therefore of great interest. The associations between genetic polymorphisms in genes from the IGF pathway on mammographic density and circulating levels of IGF1, its binding protein IGFBP3, and their ratio in postmenopausal women are reported here.

Methods: Samples from 964 postmenopausal Norwegian women aged 55-71 years were collected as a part of the Tromsø Mammography and Breast Cancer Study. All samples were genotyped for 25 SNPs in IGF1, IGF2, IGF1R, IGF2R, IGFALS and IGFBP3 using Taqman (ABI). The main statistical analyses were conducted with the PROC HAPLOTYPE procedure within SAS/GENETICS (SAS 9.1.3).

Results: The haplotype analysis revealed six haploblocks within the studied genes. Of those, four had significant associations with circulating levels of IGF1 or IGFBP3 and/or mammographic density. One haplotype variant in the IGF1 gene was found to be associated with mammographic density. Within the IGF2 gene one haplotype variant was associated with levels of both IGF1 and IGFBP3. Two haplotype variants in the IGF2R were associated with the level of IGF1. Both variants of the IGFBP3 haplotype were associated with the IGFBP3 level and indicate regulation in cis.

Conclusion: Polymorphisms within the IGF1 gene and related genes were associated with plasma levels of IGF1, IGFBP3 and mammographic density in this study of postmenopausal women.

PubMed Disclaimer

Similar articles

See all similar articles

Cited by

  • Genetic variants improve breast cancer risk prediction on mammograms.
    Liu J, Page D, Nassif H, Shavlik J, Peissig P, McCarty C, Onitilo AA, Burnside E. Liu J, et al. AMIA Annu Symp Proc. 2013 Nov 16;2013:876-85. eCollection 2013. AMIA Annu Symp Proc. 2013. PMID: 24551380 Free PMC article.
  • An intergenic risk locus containing an enhancer deletion in 2q35 modulates breast cancer risk by deregulating IGFBP5 expression.
    Wyszynski A, Hong CC, Lam K, Michailidou K, Lytle C, Yao S, Zhang Y, Bolla MK, Wang Q, Dennis J, Hopper JL, Southey MC, Schmidt MK, Broeks A, Muir K, Lophatananon A, Fasching PA, Beckmann MW, Peto J, Dos-Santos-Silva I, Sawyer EJ, Tomlinson I, Burwinkel B, Marme F, Guénel P, Truong T, Bojesen SE, Nordestgaard BG, González-Neira A, Benitez J, Neuhausen SL, Brenner H, Dieffenbach AK, Meindl A, Schmutzler RK, Brauch H; GENICA Network; Nevanlinna H, Khan S, Matsuo K, Ito H, Dörk T, Bogdanova NV, Lindblom A, Margolin S, Mannermaa A, Kosma VM; kConFab Investigators; Australian Ovarian Cancer Study Group; Wu AH, Van Den Berg D, Lambrechts D, Wildiers H, Chang-Claude J, Rudolph A, Radice P, Peterlongo P, Couch FJ, Olson JE, Giles GG, Milne RL, Haiman CA, Henderson BE, Dumont M, Teo SH, Wong TY, Kristensen V, Zheng W, Long J, Winqvist R, Pylkäs K, Andrulis IL, Knight JA, Devilee P, Seynaeve C, García-Closas M, Figueroa J, Klevebring D, Czene K, Hooning MJ, van den Ouweland AM, Darabi H, Shu XO, Gao YT, Cox A, Blot W, Signorello LB, Shah M, Kang D, Choi JY, Hartman M, Miao H, Hamann U, Jakubowska A, Lubinski J, Sangrajrang S, McKay J, Toland AE, Yannoukakos D, Shen CY, Wu PE, Swerdlow A, Or… See abstract for full author list ➔ Wyszynski A, et al. Hum Mol Genet. 2016 Sep 1;25(17):3863-3876. doi: 10.1093/hmg/ddw223. Epub 2016 Jul 11. Hum Mol Genet. 2016. PMID: 27402876 Free PMC article.
  • Genetic architecture of mammographic density as a risk factor for breast cancer: a systematic review.
    Khorshid Shamshiri A, Alidoust M, Hemmati Nokandei M, Pasdar A, Afzaljavan F. Khorshid Shamshiri A, et al. Clin Transl Oncol. 2023 Jun;25(6):1729-1747. doi: 10.1007/s12094-022-03071-8. Epub 2023 Jan 13. Clin Transl Oncol. 2023. PMID: 36639603
  • The role of the insulin-like growth factor-1 system in breast cancer.
    Christopoulos PF, Msaouel P, Koutsilieris M. Christopoulos PF, et al. Mol Cancer. 2015 Feb 15;14:43. doi: 10.1186/s12943-015-0291-7. Mol Cancer. 2015. PMID: 25743390 Free PMC article. Review.
  • New genetic variants improve personalized breast cancer diagnosis.
    Liu J, Page D, Peissig P, McCarty C, Onitilo AA, Trentham-Dietz A, Burnside E. Liu J, et al. AMIA Jt Summits Transl Sci Proc. 2014 Apr 7;2014:83-9. eCollection 2014. AMIA Jt Summits Transl Sci Proc. 2014. PMID: 25717406 Free PMC article.
See all "Cited by" articles

References

    1. Harvey JA, Bovbjerg VE. Quantitative assessment of mammographic breast density: relationship with breast cancer risk. Radiology. 2004;230:29–41. doi: 10.1148/radiol.2301020870. - DOI - PubMed
    1. Boyd NF, Rommens JM, Vogt K, Lee V, Hopper JL, Yaffe MJ. Mammographic breast density as an intermediate phenotype for breast cancer. Lancet Oncol. 2005;6:798–808. doi: 10.1016/S1470-2045(05)70390-9. - DOI - PubMed
    1. Byrne C, Schairer C, Wolfe J, Parekh N, Salane M, Brinton LA. Mammographic features and breast cancer risk: effects with time, age, and menopause status. J Natl Cancer Inst. 1995;87:1622–1629. doi: 10.1093/jnci/87.21.1622. - DOI - PubMed
    1. Byrne C, Schairer C, Brinton LA, Wolfe J, Parekh N, Salane M. Effects of mammographic density and benign breast disease on breast cancer risk (United States) Cancer Causes Control. 2001;12:103–110. doi: 10.1023/A:1008935821885. - DOI - PubMed
    1. Byrne C. Studying mammographic density: implications for understanding breast cancer. J Natl Cancer Inst. 1997;89:531–533. doi: 10.1093/jnci/89.8.531. - DOI - PubMed

Publication types

MeSH terms

Substances