Skip to main content
  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

AACR logo

  • Register
  • Log in
  • My Cart
Advertisement

Main menu

  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CEBP Focus Archive
    • Meeting Abstracts
    • Progress and Priorities
    • Collections
      • COVID-19 & Cancer Resource Center
      • Disparities Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Informing Public Health Policy
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

User menu

  • Register
  • Log in
  • My Cart

Search

  • Advanced search
Cancer Epidemiology, Biomarkers & Prevention
Cancer Epidemiology, Biomarkers & Prevention
  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CEBP Focus Archive
    • Meeting Abstracts
    • Progress and Priorities
    • Collections
      • COVID-19 & Cancer Resource Center
      • Disparities Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Informing Public Health Policy
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

Research Articles

Val158Met Polymorphism in Catechol-O-methyltransferase Gene Associated with Risk Factors for Breast Cancer

Chi-Chen Hong, Henry J. Thompson, Cheng Jiang, Geoffrey L. Hammond, David Tritchler, Martin Yaffe and Norman F. Boyd
Chi-Chen Hong
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Henry J. Thompson
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Cheng Jiang
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Geoffrey L. Hammond
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David Tritchler
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Martin Yaffe
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Norman F. Boyd
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI:  Published September 2003
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Fig. 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig. 1.

    COMT genotype and mammographic features. Values are least square means (±95% CI). All of the analyses are adjusted for age and ethnicity. In each genotype group, the number of subjects (n) are as follows: A, premenopausal group *1/*1, n = 45; group *1/*2, n = 98; group *2/*2, n = 38; B, postmenopausal group *1/*1, n = 46; group *1/*2, n = 79; group *2/*2, n = 46. a, b, ab, genotypes not sharing the same superscripts are significantly different, i.e., a and b are significantly different, but a and ab (or b and ab) are not significantly different (Bonferroni t test, P < 0.016). Embedded Image, group *1/*1; □, group *1/*2; Embedded Image, group *2/*2.

  • Fig. 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig. 2.

    COMT genotype and anthropometric variables. Values are least square means (95% CI), and all of the analyses are adjusted for age and ethnicity. 1 Premenopausal subjects (n) of group *1/*1, n = 45; group *1/*2, n = 98; group *2/*2, n = 38 [n = 37 for subscapular skinfold (C)]. 2 Results (premenopausal) are further adjusted for GH, IGF-1, and IGFBP-3. A, BMI analyses are also adjusted for WHR; B, WHR analyses are also adjusted for BMI; C, subscapular skinfold analyses are also adjusted for BMI and WHR. Premenopausal group *1/*1, n = 44; group *1/*2, n = 96; group *2/*2, n = 37, except for subscapular skinfold (C), n = 36. 3 Postmenopausal group *1/*1, n = 46 except for subscapular skinfold (C), n = 45; group *1/*2, n = 79; group *2/*2, n = 46. 4 Postmenopausal group *1/*1, n = 42 except for subscapular skinfold (C), n = 41; group *1/*2, n = 69; group *2/*2, n = 43. a, b, ab, genotypes not sharing the same superscripts are significantly different, i.e. a and b are significantly different, but a and ab (or b and ab) are not significantly different (Bonferroni t test, P < 0.016). Embedded Image, group *1/*1; □, group *1/*2; Embedded Image, group *2/*2.

  • Fig. 3.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig. 3.

    COMT genotype and percentage breast density adjusted individually and in combination for the GH-IGF-I axis, body size, and hormones. Values are least square means (± 95% CIs). Number of subjects in each genotype group: premenopausal group *1/*1, n = 44 for all analyses except age and ethnicity adjusted, for which n = 45; group *1/*2, n = 96 for all analyses except age and ethnicity adjusted, in which n = 98; group *2/*2, n = 37 in all analyses except age and ethnicity adjusted, in which n = 38. Postmenopausal group *1/*1, n = 42 in all analyses except age and ethnicity adjusted, in which n = 46; group *1/*2, n = 69 in all analyses except age and ethnicity adjusted, in which n = 79; group *2/*2, n = 43 in all analyses except age and ethnicity adjusted, in which n = 46. The three categories of variables are mutually adjusted (see results section, COMT Genotype, Body Size, Hormones, Growth Factors, and Mammographic Density for explanation). GH analyses (GH) adjusted for age, GH, IGF-1, and IGFBP-3. Body size analyses (BS) adjusted for age, BMI, and WHR. Hormones analyses (Horm) adjusted for age, FSH, and progesterone. a, b, ab, genotypes not sharing the same superscripts are significantly different, i.e. a and b are significantly different, but a and ab (or b and ab) are not significantly different (Bonferroni t test, P < 0.016). Embedded Image, group *1/*1; □, group *1/*2; Embedded Image, group *2/*2.

Tables

  • Figures
  • Table 1

    Selected characteristics of study subjects by menopausal status

    Mean (SD)
    CaucasianaEast AsianbJewishcOtherd
    Pre n = 155Pre n = 5Pre n = 11Pre n = 10
    Post n = 141Post n = 9Post n = 5Post n = 15
    Premenopausal
     Risk factors
      Age, yr44.7 (4.7)47.4 (4.2)45.6 (3.0)45.5 (4.6)
      Height, cm163.8 (6.1)155.2 (6.3)161.7 (5.1)162.1 (10.4)
      Weight, kg68.25 (16.2)57.08 (5.9)60.32 (10.6)67.2 (15.3)
      BMI, kg/m225.4 (6.0)23.6 (1.2)23.0 (3.6)25.6 (5.5)
      Waist:Hip ratio0.75 (0.06)0.75 (0.04)0.73 (0.07)0.75 (0.06)
      Age at menarche, yr12.7 (1.4)12.6 (2.7)12.2 (0.6)13.8 (1.4)
      Age at first birth, yr28.1 (5.8)33.3 (6.7)29.5 (2.7)24.4 (7.9)
      No. of live births1.4 (1.2)1.2 (1.1)1.9 (1.4)1.8 (1.3)
      Mammographic density, %e28.0 (22.7)49.7 (15.5)37.0 (24.1)22.1 (17.5)
     Pituitary hormones and growth factors
      Prolactin, μg/liter16.3 (11.4)22.0 (15.6)12.8 (7.5)25.2 (20.9)
      GH, μg/liter1.7 (2.4)2.6 (4.5)2.5 (2.4)3.6 (6.2)
      IGF-1, μg/liter155.9 (35.8)149.0 (33.7)141 (35.0)143.6 (23.5)
      IGFBP-3, mg/liter2.7 (0.5)2.6 (0.3)2.7 (0.6)2.6 (0.5)
     Sex hormones
      Estradiol, pmol/liter321.2 (219.3)172.4 (115.8)239.2 (164.6)361.5 (165.6)
      Free estradiol, %2.2 (0.7)1.9 (0.6)1.9 (0.8)2.3 (0.6)
      SHBG, nmol/liter55.6 (26.1)63.6 (21.9)65.6 (27.8)49.1 (20.3)
      Progesterone, nmol/liter28.9 (22.7)30.0 (31.4)29.3 (21.6)31.6 (20.0)
      FSH, IU/liter9.3 (15.3)20.7 (25.9)10.3 (20.1)7.2 (8.5)
    Postmenopausal
     Risk factors
      Age, yr56.1 (4.7)54.3 (3.3)53.7 (2.3)56.3 (4.1)
      Height, cm164.9 (6.6)157.1 (4.7)164.7 (4.4)162.2 (6.5)
      Weight, kg71.7 (16.9)56.4 (8.2)69.0 (16.6)65.3 (14.4)
      BMI, kg/m226.4 (6.1)23.0 (3.9)25.5 (6.2)24.8 (5.2)
      Waist:Hip ratio0.76 (0.08)0.77 (0.07)0.78 (0.10)0.79 (0.06)
      Age at menarche, yr13.1 (1.6)12.9 (1.5)12.7 (2.3)12.9 (2.2)
      Age at first birth, yr26.0 (5.2)33.2 (7.1)23.0 (3.3)29.7 (8.1)
      No. of live births1.7 (1.5)1.3 (1.4)2.2 (1.5)1.2 (1.2)
      Mammographic density,e %21.3 (19.4)50.7 (11.5)26.6 (24.3)30.5 (21.6)
     Pituitary hormones and growth factors
      Prolactin, μg/liter9.7 (5.6)8.8 (3.7)7.7 (3.1)10.4 (3.4)
      GH, μg/liter1.6 (2.6)1.5 (2.4)0.5 (0.4)0.7 (0.8)
      IGF-1, μg/liter128.2 (33.2)137.2 (38.1)133.5 (32.2)142.9 (41.8)
      IGFBP-3, mg/liter2.8 (0.5)2.8 (0.5)3.0 (0.5)2.8 (0.6)
     Sex hormones
      Estradiol, pmol/liter49.7 (98.8)46.4 (42.4)26.3 (10.2)46.9 (32.2)
      Free estradiol, %2.5 (0.6)2.2 (0.7)2.3 (0.6)2.5 (0.5)
      SHBG, nmol/liter42.5 (22.7)52.1 (26.1)48.3 (20.1)41.7 (16.8)
      Progesterone, nmol/liter1.7 (1.1)1.7 (0.7)1.6 (1.2)2.1 (0.9)
      FSH, IU/liter72.1 (30.7)71.1 (23.2)72.1 (11.1)71.7 (31.3)
    • a Premenopausal (Pre): n = 107 for age at first birth; n = 153 for GH; n = 154 for IGF-1, IGFBP-3, and free estradiol. Postmenopausal (Post): n = 104 for age at first birth; n = 127 for GH; n = 140 for IGF-1, IGFBP-3, free estradiol; n = 119 for total estradiol.

    • b Pre: n = 3 for age at first birth. Post: n = 6 for age at first birth; n = 7 for GH; n = 8 for total estradiol, free estradiol, and SHBG.

    • c Pre: n = 8 for age at first birth; n = 10 for GH. Post: n = 5 for age at first birth.

    • d Pre: n = 8 for age at first birth. Post: n = 10 for age at first birth.

    • e Proportion of breast area occupied by dense tissue.

  • Table 2

    COMT genotype and allele frequency distribution

    nCOMT genotype distributionaAllele frequency
    *1/*1*1/*2*2/*2COMT*1COMT*2
    Premenopausal
     All women1814598380.520.48
     Caucasian1553886310.520.48
     East Asian52210.600.40
     Jewish112540.410.59
     Other103520.550.45
    Postmenopausal
     All women1714679460.500.50
     Caucasian1412871420.450.55
     East Asian97200.890.11
     Jewish62220.500.50
     Other159420.730.27
    • a COMT*1/*1 is associated with the high-activity phenotype, *1/*2 with the intermediate-activity phenotype, and *2/*2 with the low-activity phenotype.

  • Table 3

    COMT genotype, sex hormones, and growth factors

    Values are least square means (95% CI), and all of the models are adjusted for age and ethnicity. Results provided in italics have been further adjusted for BMI and WHR.a,b,ab

    PremenopausalPostmenopausal
    GenotypeFPGenotypeFP
    *1/*1 n = 45c*1/*2 n = 98d*2/*2 n = 38e*1/*1 n = 46f*1/*2 n = 79g*2/*2 n = 46h
    Sex hormones
     Total estradiol282.2 (209.9–365.3)237.8 (180.1–303.4)257.6 (185.5–341.5)0.880.4230.4 (24.6–38.4)32.2 (25.9–41.4)30.4 (24.6–38.4)0.380.68
      (pmol/liter) 291.0 (217.5–375.3) 241.5 (183.4–307.6) 242.7 (171.9–325.8) 1.11 0.33 30.7 (26.2–35.7) 33.9 (28.4–41.2) 32.9 (27.3–40.4) 0.58 0.56
     Free estradiol (%)2.02 (1.73–2.27)2.19 (197–2.40)2.21 (1.94–2.45)1.280.282.58 (2.38–2.76)2.37 (2.15–2.57)2.40 (2.16–2.62)1.900.15
    2.14 (1.89–2.36) 2.23 (2.03–2.41) 2.13 (1.57–2.36) 0.62 0.54 2.57 (2.41–2.72) 2.40 (2.22–2.57) 2.53 (2.34–2.70) 2.16 0.12
     SHBG (nmol/liter)j62.3 (52.2–73.2)55.5 (47.1–64.6)54.5 (44.6–65.4)1.280.2839.6 (32.7–47.0)46.0 (37.9–54.9)46.8 (37.6–56.9)1.390.25
    57.9 (48.8–67.8) 54.0 (46.3–62.4) 58.2 (48.5–68.8) 0.67 0.51 39.9 (34.0–46.4) 45.3 (38.2–53.0) 42.1 (34.6–50.4) 1.16 0.32
     Progesterone (nmol/liter)k36.8 (29.2–45.4)a25.0 (19.5–31.2)b20.8 (14.9–27.7)b9.170.00021.5 (1.2–1.8)1.6 (1.3–2.0)1.6 (1.3–2.0)0.440.65
    34.5 (27.3–42.5) a 24.3 (19.1–30.2) b 21.4 (15.6–28.1) b 6.81 0.001 1.5 (1.2–1.8) 1.6 (1.3–2.0) 1.6 (1.3–2.0) 0.32 0.73
     FSH (IU/liter)l6.8 (5.2–9.0)a6.2 (4.9–7.9)ab4.8 (3.6–6.4)b2.980.0564.1 (55.9–73.5)61.0 (53.1–69.9)73.0 (61.2–87.0)2.690.07
    6.4 (4.9–8.5) 6.0 (4.8–7.6) 4.9 (3.7–6.5) 1.61 0.20 63.8 (55.9–72.9) 61.2 (53.0–70.6) 69.5 (59.4–81.3) 1.56 0.21
    Growth factors
     Prolactin (μg/liter)16.1 (13.0–20.0)14.3 (11.8–17.4)16.0 (12.6–20.2)0.970.388.0 (6.9–9.3)8.7 (7.4–10.1)8.3 (6.9–9.9)0.490.61
    16.0 (12.9–19.8) 14.3 (11.8–17.3) 15.7 (12.5–19.7) 0.87 0.42 8.0 (6.9–9.2) 8.5 (7.3–9.9) 7.9 (6.7–9.4) 0.52 0.60
     GH (μg/liter)m1.41 (0.85–2.34)0.86 (0.56–1.33)0.96 (0.56–1.64)2.240.110.46 (0.30–0.72)0.46 (0.29–0.72)0.53 (0.32–0.88)0.220.80
    1.29 (0.78–2.11) 0.82 (0.53–1.25) 1.06 (0.62–1.81) 2.18 0.12 0.45 (0.29–0.69) 0.44 (0.28–0.69) 0.47 (0.29–0.78) 0.06 0.94
     IGF-1 (μg/liter)n159.0 (147.5–170.9)a150.2 (140.5–160.1)a136.9 (125.8–148.4)b6.250.002129.0 (119.2–139.2)132.9 (122.5–143.7)134.5 (122.9–146.6)0.400.67
    156.2 (145.4–167.3) a 148.6 (139.6–157.8) a 139.9 (129.2–151.1) b 3.51 0.03 129.0 (119.4–139.0) 134.3 (123.7–145.3) 132.2 (120.9–144.1) 0.44 0.65
     IGFBP-3 mg/litero2.53 (2.37–2.70)a2.66 (2.52–2.80)ab2.79 (2.61–2.97)b3.830.022.77 (2.62–2.92)2.85 (2.70–3.01)2.73 (2.56–2.91)1.270.28
    2.58 (2.42–2.73) 2.68 (2.55–2.82) 2.73 (2.56–2.90) 1.70 0.19 2.76 (2.61–2.91) 2.82 (2.63–3.02) 2.72 (2.55–2.90) 0.80 0.45
    • a,b,ab Genotypes not sharing the same superscripts are significantly different, i.e., a and b are significantly different, but a and ab (or b and ab) are not significantly different (Bonferroni t test, P < 0.016).

    • c n = 44 for free estradiol, GH, IGF-1, and IGFBP-3.

    • d n = 97 for total estradiol, SHBG, and GH.

    • e n = 37 for total estradiol, SHBG, GH, IGF-1, and IGFBP-3.

    • f n = 43 for total estradiol and SHBG; n = 44 for free estradiol and FSH; n = 42 for GH, IGF-1, and IGFBP-3.

    • g n = 62 for total estradiol and SHBG; n = 69 for GH, IGF-1, and IGFBP-3.

    • h n = 40 for total estradiol and SHBG; n = 43 for GH, IGF-1, and IGFBP-3.

    • i Adjusted for SHBG.

    • j Adjusted for total estradiol levels.

    • k Models adjusted for FSH.

    • l Adjusted for progesterone levels in premenopausal women and for free estradiol values in postmenopausal women.

    • m Adjusted for IGF-1 and IGFBP-3.

    • n Adjusted for GH and IGFBP-3.

    • o Adjusted for GH and IGF-1.

PreviousNext
Back to top
Cancer Epidemiology Biomarkers & Prevention: 12 (9)
September 2003
Volume 12, Issue 9
  • Table of Contents

Sign up for alerts

View this article with LENS

Open full page PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for sharing this Cancer Epidemiology, Biomarkers & Prevention article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Val158Met Polymorphism in Catechol-O-methyltransferase Gene Associated with Risk Factors for Breast Cancer
(Your Name) has forwarded a page to you from Cancer Epidemiology, Biomarkers & Prevention
(Your Name) thought you would be interested in this article in Cancer Epidemiology, Biomarkers & Prevention.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Val158Met Polymorphism in Catechol-O-methyltransferase Gene Associated with Risk Factors for Breast Cancer
Chi-Chen Hong, Henry J. Thompson, Cheng Jiang, Geoffrey L. Hammond, David Tritchler, Martin Yaffe and Norman F. Boyd
Cancer Epidemiol Biomarkers Prev September 1 2003 (12) (9) 838-847;

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Val158Met Polymorphism in Catechol-O-methyltransferase Gene Associated with Risk Factors for Breast Cancer
Chi-Chen Hong, Henry J. Thompson, Cheng Jiang, Geoffrey L. Hammond, David Tritchler, Martin Yaffe and Norman F. Boyd
Cancer Epidemiol Biomarkers Prev September 1 2003 (12) (9) 838-847;
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF
Advertisement

Related Articles

Cited By...

More in this TOC Section

  • Gallstones and Gallbladder Cancer
  • Additive Effects of Aristolochic Acid and Arsenic in UTUC
  • Provider Lifestyle Discussions
Show more Research Articles
  • Home
  • Alerts
  • Feedback
  • Privacy Policy
Facebook   Twitter   LinkedIn   YouTube   RSS

Articles

  • Online First
  • Current Issue
  • Past Issues

Info for

  • Authors
  • Subscribers
  • Advertisers
  • Librarians

About Cancer Epidemiology, Biomarkers & Prevention

  • About the Journal
  • Editorial Board
  • Permissions
  • Submit a Manuscript
AACR logo

Copyright © 2021 by the American Association for Cancer Research.

Cancer Epidemiology, Biomarkers & Prevention
eISSN: 1538-7755
ISSN: 1055-9965

Advertisement