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Detlefsen AJ, Paulukinas RD, Penning TM. Germline Mutations in Steroid Metabolizing Enzymes: A Focus on Steroid Transforming Aldo-Keto Reductases. Int J Mol Sci 2023; 24:1873. [PMID: 36768194 PMCID: PMC9915212 DOI: 10.3390/ijms24031873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 01/15/2023] [Accepted: 01/16/2023] [Indexed: 01/20/2023] Open
Abstract
Steroid hormones synchronize a variety of functions throughout all stages of life. Importantly, steroid hormone-transforming enzymes are ultimately responsible for the regulation of these potent signaling molecules. Germline mutations that cause dysfunction in these enzymes cause a variety of endocrine disorders. Mutations in SRD5A2, HSD17B3, and HSD3B2 genes that lead to disordered sexual development, salt wasting, and other severe disorders provide a glimpse of the impacts of mutations in steroid hormone transforming enzymes. In a departure from these established examples, this review examines disease-associated germline coding mutations in steroid-transforming members of the human aldo-keto reductase (AKR) superfamily. We consider two main categories of missense mutations: those resulting from nonsynonymous single nucleotide polymorphisms (nsSNPs) and cases resulting from familial inherited base pair substitutions. We found mutations in human AKR1C genes that disrupt androgen metabolism, which can affect male sexual development and exacerbate prostate cancer and polycystic ovary syndrome (PCOS). Others may be disease causal in the AKR1D1 gene that is responsible for bile acid deficiency. However, given the extensive roles of AKRs in steroid metabolism, we predict that with expanding publicly available data and analysis tools, there is still much to be uncovered regarding germline AKR mutations in disease.
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Affiliation(s)
- Andrea J. Detlefsen
- Department of Biochemistry & Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ryan D. Paulukinas
- Department of Systems Pharmacology & Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center of Excellence in Environmental Toxicology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Trevor M. Penning
- Department of Systems Pharmacology & Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center of Excellence in Environmental Toxicology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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Haas CB, Hsu L, Lampe JW, Wernli KJ, Lindström S. Cross-ancestry Genome-wide Association Studies of Sex Hormone Concentrations in Pre- and Postmenopausal Women. Endocrinology 2022; 163:6534466. [PMID: 35192695 PMCID: PMC8962449 DOI: 10.1210/endocr/bqac020] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Indexed: 11/19/2022]
Abstract
OBJECTIVE Concentrations of circulating sex hormones have been associated with a variety of diseases in women and are strongly influenced by menopausal status. We investigated the genetic architectures of circulating concentrations of estradiol, testosterone, and SHBG by menopausal status in women of European and African ancestry. METHODS Using data on 229 966 women from the UK Biobank, we conducted genome-wide association studies (GWASs) of circulating concentrations of estradiol, testosterone, and SHBG in premenopausal and postmenopausal women. We tested for evidence of heterogeneity of genetic effects by menopausal status and genetic ancestry. We conducted gene-based enrichment analyses to identify tissues in which genes with GWAS-enriched signals were expressed. RESULTS We identified 4 loci (5q35.2, 12q14.3, 19q13.42, 20p12.3) that were associated with detectable concentrations of estradiol in both pre- and postmenopausal women of European ancestry. Heterogeneity analysis identified 1 locus for testosterone (7q22.1) in the CYP3A7 gene and 1 locus that was strongly associated with concentrations of SHBG in premenopausal women only (10q15.1) near the AKR1C4 gene. Gene-based analysis of testosterone revealed evidence of enrichment of GWAS signals in genes expressed in adipose tissue for postmenopausal women. We did not find any evidence of ancestry-specific genetic effects for concentrations of estradiol, testosterone, or SHBG. CONCLUSIONS We identified specific loci that showed genome-wide significant evidence of heterogeneity by menopausal status for testosterone and SHBG. We also observed support for a more prominent role of genetic variants located near genes expressed in adipose tissue in determining testosterone concentrations among postmenopausal women.
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Affiliation(s)
- Cameron B Haas
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
- Correspondence: Cameron B. Haas, PhD, MPH, Hans Rosling Population Health Building, 3980 15th Ave NE, Box 351619, Seattle, WA 98195, USA.
| | - Li Hsu
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Johanna W Lampe
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Karen J Wernli
- Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101, USA
| | - Sara Lindström
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
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Sarnowski C, Cousminer DL, Franceschini N, Raffield LM, Jia G, Fernández-Rhodes L, Grant SFA, Hakonarson H, Lange LA, Long J, Sofer T, Tao R, Wallace RB, Wong Q, Zirpoli G, Boerwinkle E, Bradfield JP, Correa A, Kooperberg CL, North KE, Palmer JR, Zemel BS, Zheng W, Murabito JM, Lunetta KL. Large trans-ethnic meta-analysis identifies AKR1C4 as a novel gene associated with age at menarche. Hum Reprod 2021; 36:1999-2010. [PMID: 34021356 PMCID: PMC8213450 DOI: 10.1093/humrep/deab086] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 03/12/2021] [Indexed: 12/25/2022] Open
Abstract
STUDY QUESTION Does the expansion of genome-wide association studies (GWAS) to a broader range of ancestries improve the ability to identify and generalise variants associated with age at menarche (AAM) in European populations to a wider range of world populations? SUMMARY ANSWER By including women with diverse and predominantly non-European ancestry in a large-scale meta-analysis of AAM with half of the women being of African ancestry, we identified a new locus associated with AAM in African-ancestry participants, and generalised loci from GWAS of European ancestry individuals. WHAT IS KNOWN ALREADY AAM is a highly polygenic puberty trait associated with various diseases later in life. Both AAM and diseases associated with puberty timing vary by race or ethnicity. The majority of GWAS of AAM have been performed in European ancestry women. STUDY DESIGN, SIZE, DURATION We analysed a total of 38 546 women who did not have predominantly European ancestry backgrounds: 25 149 women from seven studies from the ReproGen Consortium and 13 397 women from the UK Biobank. In addition, we used an independent sample of 5148 African-ancestry women from the Southern Community Cohort Study (SCCS) for replication. PARTICIPANTS/MATERIALS, SETTING, METHODS Each AAM GWAS was performed by study and ancestry or ethnic group using linear regression models adjusted for birth year and study-specific covariates. ReproGen and UK Biobank results were meta-analysed using an inverse variance-weighted average method. A trans-ethnic meta-analysis was also carried out to assess heterogeneity due to different ancestry. MAIN RESULTS AND THE ROLE OF CHANCE We observed consistent direction and effect sizes between our meta-analysis and the largest GWAS conducted in European or Asian ancestry women. We validated four AAM loci (1p31, 6q16, 6q22 and 9q31) with common genetic variants at P < 5 × 10-7. We detected one new association (10p15) at P < 5 × 10-8 with a low-frequency genetic variant lying in AKR1C4, which was replicated in an independent sample. This gene belongs to a family of enzymes that regulate the metabolism of steroid hormones and have been implicated in the pathophysiology of uterine diseases. The genetic variant in the new locus is more frequent in African-ancestry participants, and has a very low frequency in Asian or European-ancestry individuals. LARGE SCALE DATA N/A. LIMITATIONS, REASONS FOR CAUTION Extreme AAM (<9 years or >18 years) were excluded from analysis. Women may not fully recall their AAM as most of the studies were conducted many years later. Further studies in women with diverse and predominantly non-European ancestry are needed to confirm and extend these findings, but the availability of such replication samples is limited. WIDER IMPLICATIONS OF THE FINDINGS Expanding association studies to a broader range of ancestries or ethnicities may improve the identification of new genetic variants associated with complex diseases or traits and the generalisation of variants from European-ancestry studies to a wider range of world populations. STUDY FUNDING/COMPETING INTEREST(S) Funding was provided by CHARGE Consortium grant R01HL105756-07: Gene Discovery For CVD and Aging Phenotypes and by the NIH grant U24AG051129 awarded by the National Institute on Aging (NIA). The authors have no conflict of interest to declare.
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Affiliation(s)
- C Sarnowski
- Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - D L Cousminer
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - N Franceschini
- Department of Epidemiology, University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - L M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - G Jia
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - L Fernández-Rhodes
- Department of Biobehavioral Health, College of Health and Human Development, Pennsylvania State University, University Park, PA, USA
| | - S F A Grant
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Endocrinology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - H Hakonarson
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Pulmonary Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - L A Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - J Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - T Sofer
- Departments of Medicine and of Biostatistics, Harvard University, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA
| | - R Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - R B Wallace
- University of Iowa College of Public Health, Iowa City, IA, USA
| | - Q Wong
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - G Zirpoli
- Slone Epidemiology Center at Boston University, Boston, MA, USA
- Section of Hematology/Oncology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - E Boerwinkle
- Human Genetic Center and Department of Epidemiology, The University of Texas School of Public Health, Houston, TX, USA
| | - J P Bradfield
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Quantinuum Research, LLC, Wayne, PA, USA
| | - A Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Pediatrics, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Population Health Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - C L Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - K E North
- Department of Epidemiology, University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, NC, USA
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
| | - J R Palmer
- Slone Epidemiology Center at Boston University, Boston, MA, USA
- Section of Hematology/Oncology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - B S Zemel
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Gastroenterology, Hepatology and Nutrition, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - W Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - J M Murabito
- National Heart Lung and Blood Institute and Boston University’s Framingham Heart Study, Framingham, MA, USA
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - K L Lunetta
- Boston University School of Public Health, Boston, MA, USA
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Lee E, Luo J, Schumacher FR, Van Den Berg D, Wu AH, Stram DO, Bernstein L, Ursin G. Growth factor genes and change in mammographic density after stopping combined hormone therapy in the California Teachers Study. BMC Cancer 2018; 18:1072. [PMID: 30400783 PMCID: PMC6220514 DOI: 10.1186/s12885-018-4981-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Accepted: 10/21/2018] [Indexed: 11/24/2022] Open
Abstract
Background The contribution of genetic polymorphisms to the large inter-individual variation in mammographic density (MD) changes following starting and stopping use of estrogen and progestin combined therapy (EPT) has not been well-studied. Previous studies have shown that circulating levels of insulin-like growth factors are associated with MD and cross-talk between estrogen signaling and growth factors is necessary for cell proliferation in the breast. We evaluated single nucleotide polymorphisms (SNPs) in growth factor genes in association with MD changes after women stop EPT use. Methods We genotyped 191 SNPs in 13 growth factor pathway genes in 284 non-Hispanic white California Teachers Study participants who previously used EPT and collected their mammograms before and after quitting EPT. Percent MD was assessed using a computer-assisted method. Change in percent MD was calculated by subtracting percent MD of an ‘off-EPT’ mammogram from percent MD of an ‘on-EPT’ (i.e. baseline) mammogram. We used multivariable linear regression analysis to investigate the association between SNPs and change in percent MD. We calculated P-values corrected for multiple testing within a gene (Padj). Results Rs1983210 in INHA and rs35539615 in IGFBP1/3 showed the strongest associations. Per minor allele of rs1983210, the absolute change in percent MD after stopping EPT use decreased by 1.80% (a difference in absolute change in percent MD) (Padj= 0.021). For rs35539615, change in percent MD increased by 1.79% per minor allele (Padj= 0.042). However, after applying a Bonferroni correction for the number of genes tested, these associations were no longer statistically significant. Conclusions Genetic variation in growth factor pathway genes INHA and IGFBP1/3 may predict longitudinal MD change after women quit EPT. The observed differences in EPT-associated changes in percent MD in association with these genetic polymorphisms are modest but may be clinically significant considering that the magnitude of absolute increase in percent MD reported from large clinical trials of EPT ranged from 3% to 7%. Electronic supplementary material The online version of this article (10.1186/s12885-018-4981-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Eunjung Lee
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, 90089, USA.
| | - Jianning Luo
- Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, 91010, USA
| | - Fredrick R Schumacher
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - David Van Den Berg
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, 90089, USA
| | - Anna H Wu
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, 90089, USA
| | - Daniel O Stram
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, 90089, USA
| | - Leslie Bernstein
- Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, 91010, USA
| | - Giske Ursin
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, 90089, USA.,Department of Nutrition, University of Oslo, Oslo, Norway.,Cancer Registry of Norway, Oslo, Norway
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Alshogran OY. Pharmacogenetics of aldo-keto reductase 1C (AKR1C) enzymes. Expert Opin Drug Metab Toxicol 2017; 13:1063-1073. [PMID: 28871815 DOI: 10.1080/17425255.2017.1376648] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- Osama Y. Alshogran
- Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, Jordan
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6
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Kallionpää RA, Uusitalo E, Peltonen J. Association of Catechol-O-methyltransferase polymorphism Val158Met and mammographic density: A meta-analysis. Gene 2017; 624:34-42. [PMID: 28473194 DOI: 10.1016/j.gene.2017.04.049] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Accepted: 04/30/2017] [Indexed: 10/19/2022]
Abstract
OBJECTIVES The Val158Met polymorphism in catechol-O-methyltransferase (COMT) enzyme reduces the methylation of catechol estrogens, which may affect mammographic density. High mammographic density is a known risk factor of breast cancer. Our aim was to perform meta-analysis of the effect of COMT Val158Met polymorphism on mammographic density. METHODS Original studies reporting data on mammographic density, stratified by the presence of COMT Val158Met polymorphism, were identified and combined using genetic models Met/Val vs. Val/Val, Met/Met vs. Val/Val, Val/Met+Met/Met vs. Val/Val (dominant model) and Met/Met vs. Val/Met+Val/Val (recessive model). Subgroup analyses by breast cancer status, menopausal status and use of hormone replacement therapy (HRT) were also performed. RESULTS Eight studies were included in the meta-analysis. The overall effect in percent mammographic density was -1.41 (CI -2.86 to 0.05; P=0.06) in the recessive model. Exclusion of breast cancer patients increased the effect size to -1.93 (CI -3.49 to -0.37; P=0.02). The results suggested opposite effect of COMT Val158Met for postmenopausal users of HRT versus premenopausal women or postmenopausal non-users of HRT. CONCLUSIONS COMT Val158Met polymorphism may be associated with mammographic density at least in healthy women. Menopausal status and HRT should be taken into account in future studies to avoid masking of the underlying effects.
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Affiliation(s)
- Roope A Kallionpää
- Department of Cell Biology and Anatomy, University of Turku, Kiinamyllynkatu 10, 20520 Turku, Finland.
| | - Elina Uusitalo
- Department of Cell Biology and Anatomy, University of Turku, Kiinamyllynkatu 10, 20520 Turku, Finland
| | - Juha Peltonen
- Department of Cell Biology and Anatomy, University of Turku, Kiinamyllynkatu 10, 20520 Turku, Finland
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Rudolph A, Fasching PA, Behrens S, Eilber U, Bolla MK, Wang Q, Thompson D, Czene K, Brand JS, Li J, Scott C, Pankratz VS, Brandt K, Hallberg E, Olson JE, Lee A, Beckmann MW, Ekici AB, Haeberle L, Maskarinec G, Le Marchand L, Schumacher F, Milne RL, Knight JA, Apicella C, Southey MC, Kapuscinski MK, Hopper JL, Andrulis IL, Giles GG, Haiman CA, Khaw KT, Luben R, Hall P, Pharoah PDP, Couch FJ, Easton DF, Dos-Santos-Silva I, Vachon C, Chang-Claude J. A comprehensive evaluation of interaction between genetic variants and use of menopausal hormone therapy on mammographic density. Breast Cancer Res 2015; 17:110. [PMID: 26275715 PMCID: PMC4537547 DOI: 10.1186/s13058-015-0625-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2015] [Accepted: 07/29/2015] [Indexed: 02/02/2023] Open
Abstract
INTRODUCTION Mammographic density is an established breast cancer risk factor with a strong genetic component and can be increased in women using menopausal hormone therapy (MHT). Here, we aimed to identify genetic variants that may modify the association between MHT use and mammographic density. METHODS The study comprised 6,298 postmenopausal women from the Mayo Mammography Health Study and nine studies included in the Breast Cancer Association Consortium. We selected for evaluation 1327 single nucleotide polymorphisms (SNPs) showing the lowest P-values for interaction (P int) in a meta-analysis of genome-wide gene-environment interaction studies with MHT use on risk of breast cancer, 2541 SNPs in candidate genes (AKR1C4, CYP1A1-CYP1A2, CYP1B1, ESR2, PPARG, PRL, SULT1A1-SULT1A2 and TNF) and ten SNPs (AREG-rs10034692, PRDM6-rs186749, ESR1-rs12665607, ZNF365-rs10995190, 8p11.23-rs7816345, LSP1-rs3817198, IGF1-rs703556, 12q24-rs1265507, TMEM184B-rs7289126, and SGSM3-rs17001868) associated with mammographic density in genome-wide studies. We used multiple linear regression models adjusted for potential confounders to evaluate interactions between SNPs and current use of MHT on mammographic density. RESULTS No significant interactions were identified after adjustment for multiple testing. The strongest SNP-MHT interaction (unadjusted P int <0.0004) was observed with rs9358531 6.5kb 5' of PRL. Furthermore, three SNPs in PLCG2 that had previously been shown to modify the association of MHT use with breast cancer risk were found to modify also the association of MHT use with mammographic density (unadjusted P int <0.002), but solely among cases (unadjusted P int SNP×MHT×case-status <0.02). CONCLUSIONS The study identified potential interactions on mammographic density between current use of MHT and SNPs near PRL and in PLCG2, which require confirmation. Given the moderate size of the interactions observed, larger studies are needed to identify genetic modifiers of the association of MHT use with mammographic density.
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Affiliation(s)
- Anja Rudolph
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, D-69120, Heidelberg, Germany.
| | - Peter A Fasching
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany.
- David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, CA, USA.
| | - Sabine Behrens
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, D-69120, Heidelberg, Germany.
| | - Ursula Eilber
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, D-69120, Heidelberg, Germany.
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Deborah Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Judith S Brand
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Jingmei Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | | | | | | | - Emily Hallberg
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
| | - Janet E Olson
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
| | - Adam Lee
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA.
| | - Matthias W Beckmann
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany.
| | - Arif B Ekici
- Institute of Human Genetics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany.
| | - Lothar Haeberle
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany.
| | | | | | - Fredrick Schumacher
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
| | - Roger L Milne
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia.
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
| | - Julia A Knight
- Prosserman Centre for Health Research, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Canada.
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.
| | - Carmel Apicella
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
| | - Melissa C Southey
- Department of Pathology, The University of Melbourne, Melbourne, Australia.
| | - Miroslav K Kapuscinski
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
| | - Irene L Andrulis
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Canada.
- Department of Molecular Genetics, University of Toronto, Toronto, Canada.
| | - Graham G Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia.
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
| | - Kay-Tee Khaw
- MRC Centre for Nutritional Epidemiology in Cancer Prevention and Survival (CNC), University of Cambridge, Cambridge, UK.
| | - Robert Luben
- Clinical Gerontology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
| | - Isabel Dos-Santos-Silva
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
| | - Celine Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, D-69120, Heidelberg, Germany.
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Lee E, Luo J, Su YC, Lewinger JP, Schumacher FR, Van Den Berg D, Wu AH, Bernstein L, Ursin G. Hormone metabolism pathway genes and mammographic density change after quitting estrogen and progestin combined hormone therapy in the California Teachers Study. Breast Cancer Res 2014; 16:477. [PMID: 25499601 PMCID: PMC4318222 DOI: 10.1186/s13058-014-0477-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2013] [Accepted: 11/11/2014] [Indexed: 01/07/2023] Open
Abstract
INTRODUCTION Mammographic density (MD) is a strong biomarker of breast cancer risk. MD increases after women start estrogen plus progestin therapy (EPT) and decreases after women quit EPT. A large interindividual variation in EPT-associated MD change has been observed, but few studies have investigated genetic predictors of the EPT-associated MD change. Here, we evaluate the association between polymorphisms in hormone metabolism pathway genes and MD changes when women quit EPT. METHODS We collected mammograms before and after women quit EPT and genotyped 405 tagging single nucleotide polymorphisms (SNPs) in 30 hormone metabolism pathway genes in 284 non-Hispanic white participants of the California Teachers Study (CTS). Participants were ages 49 to 71 years at time of mammography taken after quitting EPT. We assessed percent MD using a computer-assisted method. MD change was calculated by subtracting MD of an 'off-EPT' mammogram from MD of an 'on-EPT' (that is baseline) mammogram. Linear regression analysis was used to investigate the SNP-MD change association, adjusting for the baseline 'on-EPT' MD, age and BMI at time of baseline mammogram, and time interval and BMI change between the two mammograms. An overall pathway and gene-level summary was obtained using the adaptive rank truncated product (ARTP) test. We calculated 'P values adjusted for correlated tests (P(ACT))' to account for multiple testing within a gene. RESULTS The strongest associations were observed for rs7489119 in SLCO1B1, and rs5933863 in ARSC. SLCO1B1 and ARSC are involved in excretion and activation of estrogen metabolites of EPT, respectively. MD change after quitting was 4.2% smaller per minor allele of rs7489119 (P = 0.0008; P(ACT) = 0.018) and 1.9% larger per minor allele of rs5933863 (P = 0.013; P(ACT) = 0.025). These individual SNP associations did not reach statistical significance when we further used Bonferroni correction to consider the number of tested genes. The pathway level summary ARTP P value was not statistically significant. CONCLUSIONS Data from this longitudinal study of EPT quitters suggest that genetic variation in two hormone metabolism pathway genes, SLCO1B1 and ARSC, may be associated with change in MD after women stop using EPT. Larger longitudinal studies are needed to confirm our findings.
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Affiliation(s)
- Eunjung Lee
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, 1441 Eastlake Avenue, Los Angeles, CA, 90089, USA.
| | - Jianning Luo
- Department of Population Sciences, Beckman Research Institute, City of Hope, 1500 East Duarte Road, Duarte, CA, 91010, USA.
| | - Yu-Chen Su
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, 1441 Eastlake Avenue, Los Angeles, CA, 90089, USA.
| | - Juan Pablo Lewinger
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, 1441 Eastlake Avenue, Los Angeles, CA, 90089, USA.
| | - Fredrick R Schumacher
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, 1441 Eastlake Avenue, Los Angeles, CA, 90089, USA.
| | - David Van Den Berg
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, 1441 Eastlake Avenue, Los Angeles, CA, 90089, USA.
| | - Anna H Wu
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, 1441 Eastlake Avenue, Los Angeles, CA, 90089, USA.
| | - Leslie Bernstein
- Department of Population Sciences, Beckman Research Institute, City of Hope, 1500 East Duarte Road, Duarte, CA, 91010, USA.
| | - Giske Ursin
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, 1441 Eastlake Avenue, Los Angeles, CA, 90089, USA.
- Department of Nutrition, University of Oslo, PB 1046 Blindern, 0317, Oslo, Norway.
- Cancer Registry of Norway, PB 5313 Majorstuen, 0304, Oslo, Norway.
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Ellingjord-Dale M, Grotmol T, Lee E, Van Den Berg DJ, Hofvind S, Couto E, Sovio U, Dos-Santos-Silva I, Ursin G. Breast cancer susceptibility variants and mammographic density phenotypes in norwegian postmenopausal women. Cancer Epidemiol Biomarkers Prev 2014; 23:1752-63. [PMID: 25002657 DOI: 10.1158/1055-9965.epi-13-1212] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Mammographic density (MD) is one of the strongest known breast cancer risk factors. Twin studies have suggested that a large part of the variation in MD is genetically determined. We hypothesized that breast cancer susceptibility variants may affect MD, and that their effects may be modified by nongenetic factors. METHODS We assessed MD, using a computer-assisted method, on 2,348 postmenopausal Caucasian women (50-69 years) who participated in the Norwegian Breast Cancer Screening Program (NBCSP) in 2004 or 2006-07. We used linear regression (additive models) to determine the association between each SNP and MD, adjusting for age, body mass index (BMI), and study. We evaluated MD associations with 17 established breast cancer SNPs, overall, and by strata defined by non-genetic factors. RESULTS Two variants, 6q25.1-rs9383938 and TXNRD2-rs8141691, were statistically significantly associated with percent MD (P = 0.019 and 0.03, respectively), with the 6q25.1-rs9383938 association being consistent with the SNP effect on breast cancer risk. The effect of 6q25.1-rs3734805 on percent MD varied between parous and nulliparous women (Pinteraction = 0.02), whereas the effects of 9q31.2-rs865686 and MRPS30:FGF10-rs4415084 differed across strata of BMI (Pinteraction = 0.01 and 0.005, respectively). There was no evidence of effect modification by estrogen and progestin therapy use or alcohol consumption. CONCLUSION This study provides novel evidence of shared genetic risk factors between MD and breast cancer and of possible MD genetic-environmental interactions. IMPACT Although the results may be chance findings, they nevertheless highlight the need to investigate interactions with nongenetic factors in studies on the genetics of MD.
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Affiliation(s)
| | | | - Eunjung Lee
- University of Southern California, Los Angeles, California
| | | | | | - Elisabeth Couto
- Norwegian Knowledge Centre for the Health Services, Health Economic and Drug Unit, Oslo, Norway
| | - Ulla Sovio
- University of Cambridge, Cambridge, United Kingdom
| | | | - Giske Ursin
- University of Oslo, Oslo, Norway. Cancer Registry of Norway, Oslo, Norway.
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Yang L, Zhang J, Zhang S, Dong W, Lou X, Liu S. Quantitative evaluation of aldo-keto reductase expression in hepatocellular carcinoma (HCC) cell lines. GENOMICS PROTEOMICS & BIOINFORMATICS 2013; 11:230-40. [PMID: 23584128 PMCID: PMC4357791 DOI: 10.1016/j.gpb.2013.04.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2013] [Revised: 03/31/2013] [Accepted: 04/07/2013] [Indexed: 12/03/2022]
Abstract
The involvement of aldo–keto reductases (AKRs) in tumorigenesis is widely reported, but their roles in the pathological process are not generally recognized due to inconsistent measurements of their expression. To overcome this problem, we simultaneously employed real-time PCR to examine gene expression and multiple reaction monitoring (MRM) of mass spectrometry (MS) to examine the protein expression of AKRs in five different hepatic cell lines. These include one relatively normal hepatic cell line, L-02, and four hepatocellular carcinoma (HCC) cell lines, HepG2, HuH7, BEL7402 and SMMC7721. The results of real-time PCR showed that expression of genes encoding the AKR1C family members rather than AKR1A and AKR1B was associated with tumor, and most of genes encoding AKRs were highly expressed in HuH7. Similar observations were obtained through MRM. Different from HuH7, the protein abundance of AKR1A and AKR1B was relatively consistent among the other four hepatic cell lines, while protein expression of AKR1C varied significantly compared to L-02. Therefore, we conclude that the abundant distribution of AKR1C proteins is likely to be associated with liver tumorigenesis, and the AKR expression status in HuH7 is completely different from other liver cancer cell lines. This study, for the first time, provided both overall and quantitative information regarding the expression of AKRs at both mRNA and protein levels in hepatic cell lines. Our observations put the previous use of AKRs as a biomarker into question since it is only consistent with our data from HuH7. Furthermore, the data presented herein demonstrated that quantitative evaluation and comparisons within a protein family at both mRNA and protein levels were feasible using current techniques.
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Affiliation(s)
- Lei Yang
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
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11
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Ellingjord-Dale M, Lee E, Couto E, Ozhand A, Qureshi S, Hofvind S, Van Den Berg DJ, Akslen LA, Grotmol T, Ursin G. Polymorphisms in hormone metabolism and growth factor genes and mammographic density in Norwegian postmenopausal hormone therapy users and non-users. Breast Cancer Res 2012; 14:R135. [PMID: 23095343 PMCID: PMC4053113 DOI: 10.1186/bcr3337] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2012] [Accepted: 08/30/2012] [Indexed: 01/10/2023] Open
Abstract
INTRODUCTION Mammographic density (MD) is one of the strongest known breast cancer risk factors. Estrogen and progestin therapy (EPT) has been associated with increases in MD. Dense breast tissue is characterized by increased stromal tissue and (to a lesser degree) increased numbers of breast epithelial cells. It is possible that genetic factors modify the association between EPT and MD, and that certain genetic variants are particularly important in determining MD in hormone users. We evaluated the association between MD and 340 tagging single nucleotide polymorphisms (SNPs) from about 30 candidate genes in hormone metabolism/growth factor pathways among women who participated in the Norwegian Breast Cancer Screening Program (NBCSP) in 2004. METHODS We assessed MD on 2,036 postmenopausal women aged 50 to 69 years using a computer-assisted method (Madena, University of Southern California) in a cross-sectional study. We used linear regression to determine the association between each SNP and MD, adjusting for potential confounders. The postmenopausal women were stratified into HT users (EPT and estrogen-only) and non-users (never HT). RESULTS For current EPT users, there was an association between a variant in the prolactin gene (PRL; rs10946545) and MD (dominant model, Bonferroni-adjusted P (Pb) = 0.0144). This association remained statistically significant among current users of norethisterone acetate (NETA)-based EPT, a regimen common in Nordic countries. Among current estrogen-only users (ET), there was an association between rs4670813 in the cytochrome P450 gene (CYP1B1) and MD (dominant model, Pb = 0.0396). In never HT users, rs769177 in the tumor necrosis factor (TNF) gene and rs1968752 in the region of the sulfotransferase gene (SULT1A1/SULT1A2), were significantly associated with MD (Pb = 0.0202; Pb = 0.0349). CONCLUSIONS We found some evidence that variants in the PRL gene were associated with MD in current EPT and NETA users. In never HT users, variants in the TNF and SULT1A1/SULT1A2 genes were significantly associated with MD. These findings may suggest that several genes in the hormone metabolism and growth factor pathways are implicated in determining MD.
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12
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Johansson AGM, Nikamo P, Schalling M, Landén M. Polymorphisms in AKR1C4 and HSD3B2 and differences in serum DHEAS and progesterone are associated with paranoid ideation during mania or hypomania in bipolar disorder. Eur Neuropsychopharmacol 2012; 22:632-40. [PMID: 22356824 DOI: 10.1016/j.euroneuro.2012.01.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2011] [Revised: 12/30/2011] [Accepted: 01/17/2012] [Indexed: 10/28/2022]
Abstract
Paranoia is commonly a mood-incongruent psychotic symptom of mania which may be related to dopamine dysregulation. Progesterone and its metabolite allopregnanolone (ALLO) have been found in animals to antagonize the effects of dopamine. We therefore examined serum progesterone, its endogenous antagonist DHEAS and polymorphisms of the genes coding for certain steroidogenetic enzymes (AKR1C4, HSD3B2, and SRD5A1) in 64 males and 96 females with bipolar 1 or 2 disorder with or without paranoid ideation during mood elevation. Euthymic morning serum progesterone, DHEAS and cortisol concentrations were measured in males and in premenopausal women who were in follicular phase and not taking oral contraceptives. In women only, SNPs in AKR1C4 reduced the likelihood of having exhibited paranoid ideation by circa 60%. The haplotype of all 4 SNPs in the AKR1C4 gene reduced the risk of exhibiting paranoia by 80% (OR 0.19, 95% CI 0.06-0.61, p=0.05). A history of paranoid ideation was not, however, related to progesterone or DHEAS concentration. Serum DHEAS and progesterone concentrations were lower in men who had shown paranoid ideation during mania/hypomania compared with those who had not (F=7.30, p=0.006) however this was not coupled to polymorphisms in the selected genes. The ancestral G in rs4659174 in HSD3B2 was in men associated with a lower risk of paranoid ideation (likelihood ratio χ(2) 3.97, p=0.046, OR 0.31 (95% CI 0.10-0.96)) but did not correlate with hormone concentrations. Hence, gene variants in the steroidogenetic pathway and steroids concentration differences may be involved in the susceptibility to paranoia during mood elevation.
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Affiliation(s)
- Anette G M Johansson
- Division of Psychiatry, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
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13
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Hein R, Abbas S, Seibold P, Salazar R, Flesch-Janys D, Chang-Claude J. Polymorphism Thr160Thr in SRD5A1, involved in the progesterone metabolism, modifies postmenopausal breast cancer risk associated with menopausal hormone therapy. Breast Cancer Res Treat 2011; 131:653-61. [PMID: 21947678 DOI: 10.1007/s10549-011-1772-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2011] [Accepted: 09/05/2011] [Indexed: 12/30/2022]
Abstract
Menopausal hormone therapy (MHT) is associated with an increased breast cancer risk in postmenopausal women, with combined estrogen-progestagen therapy posing a greater risk than estrogen monotherapy. However, few studies focused on potential effect modification of MHT-associated breast cancer risk by genetic polymorphisms in the progesterone metabolism. We assessed effect modification of MHT use by five coding single nucleotide polymorphisms (SNPs) in the progesterone metabolizing enzymes AKR1C3 (rs7741), AKR1C4 (rs3829125, rs17134592), and SRD5A1 (rs248793, rs3736316) using a two-center population-based case-control study from Germany with 2,502 postmenopausal breast cancer patients and 4,833 matched controls. An empirical-Bayes procedure that tests for interaction using a weighted combination of the prospective and the retrospective case-control estimators as well as standard prospective logistic regression were applied to assess multiplicative statistical interaction between polymorphisms and duration of MHT use with regard to breast cancer risk assuming a log-additive mode of inheritance. No genetic marginal effects were observed. Breast cancer risk associated with duration of combined therapy was significantly modified by SRD5A1_rs3736316, showing a reduced risk elevation in carriers of the minor allele (p (interaction,empirical-Bayes) = 0.006 using the empirical-Bayes method, p (interaction,logistic regression) = 0.013 using logistic regression). The risk associated with duration of use of monotherapy was increased by AKR1C3_rs7741 in minor allele carriers (p (interaction,empirical-Bayes) = 0.083, p (interaction,logistic regression) = 0.029) and decreased in minor allele carriers of two SNPs in AKR1C4 (rs3829125: p (interaction,empirical-Bayes) = 0.07, p (interaction,logistic regression) = 0.021; rs17134592: p (interaction,empirical-Bayes) = 0.101, p (interaction,logistic regression) = 0.038). After Bonferroni correction for multiple testing only SRD5A1_rs3736316 assessed using the empirical-Bayes method remained significant. Postmenopausal breast cancer risk associated with combined therapy may be modified by genetic variation in SRD5A1. Further well-powered studies are, however, required to replicate our finding.
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Affiliation(s)
- R Hein
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
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14
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Dumas I, Diorio C. Polymorphisms in genes involved in the estrogen pathway and mammographic density. BMC Cancer 2010; 10:636. [PMID: 21092186 PMCID: PMC3000407 DOI: 10.1186/1471-2407-10-636] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2010] [Accepted: 11/22/2010] [Indexed: 11/18/2022] Open
Abstract
Background Single nucleotide polymorphisms (SNPs) in genes involved in the estrogen pathway appear to be associated with breast cancer risk and possibly with mammographic density (MD), but little is known of these associations among premenopausal women. This study examines the association of 11 polymorphisms in five estrogen-related genes (estrogen receptors alpha and beta (ERα, ERβ), 17β-hydroxysteroid dehydrogenase 1 (HSD17B1), catechol-O-methyltransferase (COMT), cytochrome P450 1B1 (CYP1B1)) with premenopausal MD. Effect modification of four estrogen-related factors (parity, age at menarche, hormonal derivatives use and body mass index (BMI)) on this relation is also assessed. Methods Polymorphisms were genotyped in 741 premenopausal Caucasian women whose MD was measured in absolute density (AD, cm2) and percent density using a computer-assisted method. Multivariate linear models were used to examine the associations (Ptrend) and interactions (Pi). Results None of the SNPs showed a statistically significant association with AD. However, each additional rare allele of rs1056836 CYP1B1 was associated with a reduction in AD among nulliparous women (Ptrend = 0.004), while no association was observed among parous women (Ptrend = 0.62; Pi = 0.02). An increase in the number of rare alleles of the HSD17B1 SNP (rs598126 and rs2010750) was associated with an increase in AD among women who never used hormonal derivatives (Ptrend = 0.06 and Ptrend = 0.04, respectively), but with a decrease in AD among past hormonal derivatives users (Ptrend = 0.04; Pi = 0.02 and Ptrend = 0.08; Pi = 0.01, respectively). Moreover, a negative association of rs598126 HSD17B1 SNP with AD was observed among women with higher BMI (>median) (Ptrend = 0.01; Pi = 0.02). A negative association between an increased number of rare alleles of COMT rs4680 SNP and AD was limited to women who never used hormonal derivatives (Ptrend = 0.02; Pi = 0.03) or with late age at menarche (>median) (Ptrend = 0.03; Pi = 0.02). No significant association was observed between polymorphisms in the ERα or ERβ genes and AD. Similar results, although less significant, were observed when MD was assessed in percent density. Conclusion SNPs located in CYP1B1, COMT or HSD17B1 genes seem to be associated with MD in some strata of estrogen-related factors. Our findings suggest that modifying effects of estrogen-related factors should be considered when evaluating associations of polymorphisms in estrogen-related genes with premenopausal mammographic density.
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Affiliation(s)
- Isabelle Dumas
- Université Laval, Département de médecine sociale et préventive, Quebec City, QC, Canada
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15
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Li J, Eriksson L, Humphreys K, Czene K, Liu J, Tamimi RM, Lindström S, Hunter DJ, Vachon CM, Couch FJ, Scott CG, Lagiou P, Hall P. Genetic variation in the estrogen metabolic pathway and mammographic density as an intermediate phenotype of breast cancer. Breast Cancer Res 2010; 12:R19. [PMID: 20214802 PMCID: PMC2879563 DOI: 10.1186/bcr2488] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2009] [Revised: 03/01/2010] [Accepted: 03/09/2010] [Indexed: 01/01/2023] Open
Abstract
Introduction Several studies have examined the effect of genetic variants in genes involved in the estrogen metabolic pathway on mammographic density, but the number of loci studied and the sample sizes evaluated have been small and pathways have not been evaluated comprehensively. In this study, we evaluate the association between mammographic density and genetic variants of the estrogen metabolic pathway. Methods A total of 239 SNPs in 34 estrogen metabolic genes were studied in 1,731 Swedish women who participated in a breast cancer case-control study, of which 891 were cases and 840 were controls. Film mammograms of the medio-lateral oblique view were digitalized and the software Cumulus was used for computer-assisted semi-automated thresholding of mammographic density. Generalized linear models controlling for possible confounders were used to evaluate the effects of SNPs on mammographic density. Results found to be nominally significant were examined in two independent populations. The admixture maximum likelihood-based global test was performed to evaluate the cumulative effect from multiple SNPs within the whole metabolic pathway and three subpathways for androgen synthesis, androgen-to-estrogen conversion and estrogen removal. Results Genetic variants of genes involved in estrogen metabolism exhibited no appreciable effect on mammographic density. None of the nominally significant findings were validated. In addition, global analyses on the overall estrogen metabolic pathway and its subpathways did not yield statistically significant results. Conclusions Overall, there is no conclusive evidence that genetic variants in genes involved in the estrogen metabolic pathway are associated with mammographic density in postmenopausal women.
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Affiliation(s)
- Jingmei Li
- Karolinska Institutet, Department of Medical Epidemiology and Biostatistics, Stockholm, Sweden.
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McTiernan A, Chlebowski RT, Martin C, Peck JD, Aragaki A, Pisano ED, Wang CY, Johnson KC, Manson JE, Wallace RB, Vitolins MZ, Heiss G. Conjugated equine estrogen influence on mammographic density in postmenopausal women in a substudy of the women's health initiative randomized trial. J Clin Oncol 2009; 27:6135-43. [PMID: 19901118 DOI: 10.1200/jco.2008.21.7166] [Citation(s) in RCA: 52] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
PURPOSE Increased mammographic density is associated with increased breast cancer risk and reduced sensitivity of screening mammography and is related to hormone exposure. However, the effects of conjugated equine estrogens (CEEs) alone on mammographic density in diverse racial/ethnic populations are not established. We examined the effect of CEE alone on mammographic density in a subsample of the Women's Health Initiative (WHI) clinical trial participants. PATIENTS AND METHODS In the WHI trial, women were randomly assigned to daily CEE 0.625 mg or placebo. The effect of CEE on mammographic percent density was determined over 1 and 2 years in a stratified random sample of 435 racially and ethnically diverse participants from 15 of 40 WHI clinics. RESULTS Use of CEE resulted in mean increase in mammographic percent density of 1.6 percentage points (95% CI, 0.8 to 2.4) at year 1 compared with a mean decrease of 1.0 percentage point (95% CI, -1.7 to -0.4) in the placebo group (P < .001). The effect persisted for 2 years, with a mean increase of 1.7 percentage points (95% CI, 0.7 to 2.7) versus a mean decrease of 1.2 percentage points (95% CI, -1.8 to -0.5; P < .001) in the hormone and placebo groups, respectively. These effects were greater in women age 60 to 79 years (P = .03 for interaction across age). CONCLUSION Use of CEE results in a modest but statistically significant increase in mammographic density that is sustained over at least a 2-year period. The clinical significance of the CEE effect on mammographic density remains to be determined.
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Affiliation(s)
- Anne McTiernan
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, M4-B874, PO Box 19024, Seattle, WA 98019, USA.
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Crandall CJ, Sehl ME, Crawford SL, Gold EB, Habel LA, Butler LM, Sowers MR, Greendale GA, Sinsheimer JS. Sex steroid metabolism polymorphisms and mammographic density in pre- and early perimenopausal women. Breast Cancer Res 2009; 11:R51. [PMID: 19630952 PMCID: PMC2750112 DOI: 10.1186/bcr2340] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2009] [Revised: 07/08/2009] [Accepted: 07/27/2009] [Indexed: 12/02/2022] Open
Abstract
Introduction We examined the association between mammographic density and single-nucleotide polymorphisms (SNPs) in genes encoding CYP1A1, CYP1B1, aromatase, 17β-HSD, ESR1, and ESR2 in pre- and early perimenopausal white, African-American, Chinese, and Japanese women. Methods The Study of Women's Health Across the Nation is a longitudinal community-based cohort study. We analyzed data from 451 pre- and early perimenopausal participants of the ancillary SWAN Mammographic Density study for whom we had complete information regarding mammographic density, genotypes, and covariates. With multivariate linear regression, we examined the relation between percentage mammographic breast density (outcome) and each SNP (primary predictor), adjusting for age, race/ethnicity, parity, cigarette smoking, and body mass index (BMI). Results After multivariate adjustment, the CYP1B1 rs162555 CC genotype was associated with a 9.4% higher mammographic density than the TC/TT genotype (P = 0.04). The CYP19A1 rs936306 TT genotype was associated with 6.2% lower mammographic density than the TC/CC genotype (P = 0.02). The positive association between CYP1A1 rs2606345 and mammographic density was significantly stronger among participants with BMI greater than 30 kg/m2 than among those with BMI less than 25 kg/m2 (Pinteraction = 0.05). Among white participants, the ESR1 rs2234693 CC genotype was associated with a 7.0% higher mammographic density than the CT/TT genotype (P = 0.01). Conclusions SNPs in certain genes encoding sex steroid metabolism enzymes and ESRs were associated with mammographic density. Because the encoded enzymes and ESR1 are expressed in breast tissue, these SNPs may influence breast cancer risk by altering mammographic density.
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Affiliation(s)
- Carolyn J Crandall
- Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, UCLA Medicine/GIM, 911 Broxton Ave, 1st floor, Los Angeles, CA 90024, USA.
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Abstract
Mammographic density (MD) reflects variations in fat, stromal and epithelial tissues that are thought to be regulated by several genes. High MD is an established risk factor for breast cancer; therefore, genes that regulate MD may indirectly influence breast cancer. These genes might also be fewer in number and easier to identify than those for breast cancer risk outside of inherited predisposition syndromes. In this Perspective, we review the limited genetic studies of MD and propose future directions.
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Affiliation(s)
- Linda E Kelemen
- Department of Population Health Research, Alberta Cancer Board, 1,331 29th Street North West, Calgary, Alberta T2N 4N2, Canada
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Tamimi RM, Cox D, Kraft P, Colditz GA, Hankinson SE, Hunter DJ. Breast cancer susceptibility loci and mammographic density. Breast Cancer Res 2008; 10:R66. [PMID: 18681954 PMCID: PMC2575539 DOI: 10.1186/bcr2127] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2008] [Revised: 07/15/2008] [Accepted: 08/05/2008] [Indexed: 12/26/2022] Open
Abstract
Introduction Recently, the Breast Cancer Association Consortium (BCAC) conducted a multi-stage genome-wide association study and identified 11 single nucleotide polymorphisms (SNPs) associated with breast cancer risk. Given the high degree of heritability of mammographic density and its strong association with breast cancer, it was hypothesised that breast cancer susceptibility loci may also be associated with breast density and provide insight into the biology of breast density and how it influences breast cancer risk. Methods We conducted an analysis in the Nurses' Health Study (n = 1121) to assess the relation between 11 breast cancer susceptibility loci and mammographic density. At the time of their mammogram, 217 women were premenopausal and 904 women were postmenopausal. We used generalised linear models adjusted for covariates to determine the mean percentage of breast density according to genotype. Results Overall, no association between the 11 breast cancer susceptibility loci and mammographic density was seen. Among the premenopausal women, three SNPs (rs12443621 [TNRc9/LOC643714], rs3817198 [lymphocyte-specific protein-1] and rs4666451) were marginally associated with mammographic density (p < 0.10). All three of these SNPs showed an association that was consistent with the direction in which these alleles influence breast cancer risk. The difference in mean percentage mammographic density comparing homozygous wildtypes to homozygous variants ranged from 6.3 to 8.0%. None of the 11 breast cancer loci were associated with postmenopausal breast density. Conclusion Overall, breast cancer susceptibility loci identified through a genome-wide association study do not appear to be associated with breast cancer risk.
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Affiliation(s)
- Rulla M Tamimi
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA.
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Bains OS, Takahashi RH, Pfeifer TA, Grigliatti TA, Reid RE, Riggs KW. Two Allelic Variants of Aldo-Keto Reductase1A1Exhibit Reduced in Vitro Metabolism of Daunorubicin. Drug Metab Dispos 2008; 36:904-10. [DOI: 10.1124/dmd.107.018895] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
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Tamimi RM, Cox DG, Kraft P, Pollak MN, Haiman CA, Cheng I, Freedman ML, Hankinson SE, Hunter DJ, Colditz GA. Common genetic variation in IGF1, IGFBP-1, and IGFBP-3 in relation to mammographic density: a cross-sectional study. Breast Cancer Res 2007; 9:R18. [PMID: 17300730 PMCID: PMC1851377 DOI: 10.1186/bcr1655] [Citation(s) in RCA: 62] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2006] [Revised: 02/02/2007] [Accepted: 02/14/2007] [Indexed: 12/12/2022] Open
Abstract
Introduction Mammographic density is one of the strongest risk factors for breast cancer and is believed to represent epithelial and stromal proliferation. Because of the high heritability of breast density, and the role of the insulin-like growth factor (IGF) pathway in cellular proliferation and breast development, we examined the association between common genetic variation in this pathway and mammographic density. Methods We conducted a cross-sectional analysis among controls (n = 1,121) who were between the ages of 42 and 78 years at mammography, from a breast cancer case-control study nested within the Nurses' Health Study cohort. At the time of mammography, 204 women were premenopausal and 917 were postmenopausal. We genotyped 29 haplotype-tagging SNPs demonstrated to capture common genetic variation in IGF1, IGF binding protein (IGFBP)-1, and IGFBP-3. Results Common haplotype patterns in three of the four haplotype blocks spanning the gene encoding IGF1 were associated with mammographic density. Haplotype patterns in block 1 (p = 0.03), block 3 (p = 0.009), and block 4 (p = 0.007) were associated with mammographic density, whereas those in block 2 were not. None of the common haplotypes in the three haplotype blocks spanning the genes encoding IGFBP-1/IGFBP-3 were significantly associated with mammographic density. Two haplotype-tagging SNPs in IGF1, rs1520220 and rs2946834, showed a strong association with mammographic density. Those with the homozygous variant genotype for rs1520220 had a mean percentage mammographic density of 19.6% compared with those with the homozygous wild-type genotype, who had a mean percentage mammographic density of 27.9% (p for trend < 0.0001). Those that were homozygous variant for rs2946834 had a mean percentage mammographic density of 23.2% compared with those who were homozygous wild-type with a mean percentage mammographic density of 28.2% (p for trend = 0.0004). Permutation testing demonstrated that results as strong as these are unlikely to occur by chance (p = 0.0005). Conclusion Common genetic variation in IGF1 is strongly associated with percentage mammographic density.
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Affiliation(s)
- Rulla M Tamimi
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA 02115, USA
- Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
| | - David G Cox
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA 02115, USA
- Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
- Department of Biostatics, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
| | - Michael N Pollak
- Department of Medicine and Oncology, McGill University, 3755 Cote Ste-Catherine Road, Montreal, Quebec H3T 1E2, Canada
| | - Christopher A Haiman
- Keck School of Medicine, University of Southern California, 1441 Eastlake Avenue, Los Angeles, CA 90089, USA
| | - Iona Cheng
- Department of Epidemiology and Biostatistics, University of California, 513 Parnassus Avenue S966B, San Francisco, CA 94143, USA
| | - Matthew L Freedman
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, 7 Cambridge Center, Cambridge MA 02142, USA
| | - Susan E Hankinson
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA 02115, USA
- Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
| | - David J Hunter
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA 02115, USA
- Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
- Department of Surgery, Washington University School of Medicine, Campus Box 8100 660, S. Euclid Avenue, St. Louis, MO 63110 USA
| | - Graham A Colditz
- Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
- Department of Surgery, Washington University School of Medicine, Campus Box 8100 660, S. Euclid Avenue, St. Louis, MO 63110 USA
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Abstract
Aldo-keto reductases (AKRs) are soluble NAD(P)(H) oxidoreductases that primarily reduce aldehydes and ketones to primary and secondary alcohols, respectively. The ten known human AKR enzymes can turnover a vast range of substrates, including drugs, carcinogens, and reactive aldehydes. They play central roles in the metabolism of these agents, and this can lead to either their bioactivation or detoxication. AKRs are Phase I drug metabolizing enzymes for a variety of carbonyl-containing drugs and are implicated in cancer chemotherapeutic drug resistance. They are involved in tobacco-carcinogenesis because they activate polycyclic aromatic trans-dihydrodiols to yield reactive and redox active o-quinones, but they also catalyze the detoxication of nicotine derived nitrosamino ketones. They also detoxify reactive aldehydes formed from exogenous toxicants, e.g., aflatoxin, endogenous toxicants, and those formed from the breakdown of lipid peroxides. AKRs are stress-regulated genes and play a central role in the cellular response to osmotic, electrophilic, and oxidative stress.
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Affiliation(s)
- Yi Jin
- Department of Pharmacology, Center of Excellence in Environmental Toxicology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
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Steiner AZ, Xiang M, Mack WJ, Shoupe D, Felix JC, Lobo RA, Hodis HN. Unopposed estradiol therapy in postmenopausal women: results from two randomized trials. Obstet Gynecol 2007; 109:581-7. [PMID: 17329508 DOI: 10.1097/01.aog.0000251518.56369.eb] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE To estimate the rates of endometrial hyperplasia, bleeding episodes, and interventions among menopausal women receiving unopposed oral estradiol or placebo therapy with ultrasound monitoring over 3 years. METHODS Two-hundred eighteen healthy women with intact uteri enrolled in the Estrogen in the Prevention of Atherosclerosis Trial (EPAT) or the Women's Estrogen-Progestin Lipid-Lowering Hormone Atherosclerosis Regression Trial (WELL-HART) were randomly assigned to either 1 mg of micronized 17beta-estradiol (n=96) or placebo (n=122) daily for up to 3 years in a double-blind fashion. Patients were followed with annual measurement of endometrial thickness using transvaginal ultrasonography. Logistic regression was used to identify predictors of uterine bleeding and endometrial biopsy. RESULTS Over the study periods, nine women (9.4% of patients, 95% confidence interval [CI] 3.6-15.2%) in the estradiol group developed hyperplasia. Eight of the nine cases (88.9%) of hyperplasia were simple without atypia. Women receiving estradiol were more likely than those receiving placebo to have at least one episode of uterine bleeding (67% versus 11% at 3 years, respectively, P<.001). Women in the estradiol group were also more likely to have an endometrial biopsy (48% versus 4% at 3 years, P<.001). Among women on estradiol, obesity (body mass index [BMI] greater than 30 kg/m(2)) significantly increased the odds of uterine bleeding compared with normal-weight patients (BMI 25 or less) (OR 3.7, 95% CI 1.2-11.8). CONCLUSION Short-term, unopposed estradiol therapy with gynecologic monitoring may be an option for the treatment of menopausal symptoms. Menopausal women choosing estradiol therapy, especially if obese, should anticipate uterine bleeding and the possibility of an endometrial biopsy. CLINICAL TRIAL REGISTRATION Clinicaltrials.gov, www.clinicaltrials.gov, NCT 00000559 and NCT 00115024. LEVEL OF EVIDENCE I.
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Affiliation(s)
- Anne Z Steiner
- Department of Obstetrics and Gynecology, University of Southern California, Keck School of Medicine, Los Angeles, California 90033, USA
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Breast density and polymorphisms in genes coding for CYP1A2 and COMT: the Multiethnic Cohort. BMC Cancer 2007; 7:30. [PMID: 17295924 PMCID: PMC1800856 DOI: 10.1186/1471-2407-7-30] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2006] [Accepted: 02/12/2007] [Indexed: 11/22/2022] Open
Abstract
Background Mammographic density is a strong predictor of breast cancer risk and is increased by hormone replacement therapy (HRT). Some associations with genetic polymorphisms in enzymes involved in estrogen metabolism have been described. This cross-sectional analysis examined the relation between mammographic density and the CYP1A2*1F and COMT Val58 Met polymorphisms among 332 breast cancer cases and 254 controls in the Hawaii component of the Multiethnic Cohort. Methods Mammographic density, before diagnosis in cases, was quantified by using a validated computer-assisted method. Blood samples were genotyped by standard PCR/RFLP methods. Adjusted mean percent density was calculated by genotype using mixed models with the unstructured covariance option. Results A positive association between the C allele in the CYP1A2*1F gene and percent density, but not the dense area, was suggested (p = 0.11). The relation was limited to controls (p = 0.045), postmenopausal women not using HRT (p = 0.08), and normal weight subjects (p = 0.046). We did not observe any relation between the COMT Val58 Met polymorphism and breast density. Conclusion The lack of an association between the CYP1A2 genotype and the size of the dense areas suggests an effect on the non-dense, i.e., fatty breast tissue. The discrepancies among studies may be due to differential susceptibility; changes in enzyme activity as a result of the CYP1A2*1F polymorphism may influence breast tissue differently depending on hormonal status. Larger studies with the ability to look at interactions would be useful to elucidate the influence of genetic variation in CYP1A2 and COMT on the risk of developing breast cancer.
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Conner P. Breast response to menopausal hormone therapy--aspects on proliferation, apoptosis and mammographic density. Ann Med 2007; 39:28-41. [PMID: 17364449 DOI: 10.1080/07853890601039842] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
Abstract
Breast cancer is the major malignancy among women in the Western world. The breast is clearly a target organ for sex steroid hormones and hormonal treatments have been associated with an increased risk of breast cancer. The balance between proliferation and apoptosis is important for breast cell homeostasis. Mammographic breast density has been identified as a strong and independent risk factor for breast cancer. It seems clear that there is a difference between various hormonal treatments with regard to their effects on breast density and cell proliferation. Also, not all women respond similarly to the same treatment. Combined estrogen and progestogen therapy generally will enhance density and proliferation more than treatment with estrogen alone. Certain constitutional and hormonal factors appear to be predictive of breast reactivity. Older women with a low body mass index respond more strongly to treatment. Estrogen levels have a positive and androgens a negative association to increase in density and proliferation. A combination of increased proliferation and decreased apoptosis could be one mechanism to explain the excess risk of breast cancer during combined estrogen/progestogen treatment. Tibolone seems to have less impact on breast response than conventional hormone therapy. Efforts should be made to identify those women with an adverse response to treatment as well as therapeutic principles with the least possible influence on the breast.
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Affiliation(s)
- Peter Conner
- Department of Obstetrics and Gynecology, Karolinska University Hospital, Stockholm, Sweden.
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Warren R, Skinner J, Sala E, Denton E, Dowsett M, Folkerd E, Healey CS, Dunning A, Doody D, Ponder B, Luben RN, Day NE, Easton D. Associations among mammographic density, circulating sex hormones, and polymorphisms in sex hormone metabolism genes in postmenopausal women. Cancer Epidemiol Biomarkers Prev 2006; 15:1502-8. [PMID: 16896040 DOI: 10.1158/1055-9965.epi-05-0828] [Citation(s) in RCA: 67] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Mammographic density and serum sex hormone levels are important risk factors for breast cancer, but their associations with one another are unclear. We studied these phenotypes, together with single nucleotide polymorphisms (SNP) in genes related to sex hormone metabolism, in a cross-sectional study of 1,413 postmenopausal women from the European Prospective Investigation into Cancer and Nutrition-Norfolk. All women were >1 year postmenopausal and had not taken hormone replacement therapy for >3 months before sampling. Serum levels of 7 sex hormones [estradiol, testosterone, sex hormone-binding globulin (SHBG), androstenedione, 17-OH-progesterone, estrone, and estrone sulfate] and 15 SNPs in the CYP17, CYP19, EDH17B2, SHBG, COMT, and CYP1B1 genes were studied. Mammograms nearest in time to the blood sampling were identified through the national breast screening program and visually assessed by three radiologists using the Boyd six-category and Wolfe four-category scales. We found a weak positive association between mammographic density and SHBG levels (P = 0.09) but no association with any other hormones. None of the SNPs, including those shown previously to be associated with estradiol or SHBG, showed significant associations with density. We conclude that mammographic density is largely independent of postmenopausal steroid hormone levels, indicating that these risk factors have, to a large extent, an independent etiology and suggesting that they may be independent predictors of breast cancer risk.
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Affiliation(s)
- Ruth Warren
- Department of Radiology, University of Cambridge, United Kingdom.
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Nonneman DJ, Wise TH, Ford JJ, Kuehn LA, Rohrer GA. Characterization of the aldo-keto reductase 1C gene cluster on pig chromosome 10: possible associations with reproductive traits. BMC Vet Res 2006; 2:28. [PMID: 16970816 PMCID: PMC1586007 DOI: 10.1186/1746-6148-2-28] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2006] [Accepted: 09/13/2006] [Indexed: 01/07/2023] Open
Abstract
Background The rate of pubertal development and weaning to estrus interval are correlated and affect reproductive efficiency of swine. Quantitative trait loci (QTL) for age of puberty, nipple number and ovulation rate have been identified in Meishan crosses on pig chromosome 10q (SSC10) near the telomere, which is homologous to human chromosome 10p15 and contains an aldo-keto reductase (AKR) gene cluster with at least six family members. AKRs are tissue-specific hydroxysteroid dehydrogenases that interconvert weak steroid hormones to their more potent counterparts and regulate processes involved in development, homeostasis and reproduction. Because of their location in the swine genome and their implication in reproductive physiology, this gene cluster was characterized and evaluated for effects on reproductive traits in swine. Results Screening the porcine CHORI-242 BAC library with a full-length AKR1C4 cDNA identified 7 positive clones and sample sequencing of 5 BAC clones revealed 5 distinct AKR1C genes (AKR1CL2 and AKR1C1 through 4), which mapped to 126–128 cM on SSC10. Using the IMpRH7000rad and IMNpRH212000rad radiation hybrid panels, these 5 genes mapped between microsatellite markers SWR67 and SW2067. Comparison of sequence data with the porcine BAC fingerprint map show that the cluster of genes resides in a 300 kb region. Twelve SNPs were genotyped in gilts observed for age at first estrus and ovulation rate from the F8 and F10 generations of one-quarter Meishan descendants of the USMARC resource population. Age at puberty, nipple number and ovulation rate data were analyzed for association with genotypes by MTDFREML using an animal model. One SNP, a phenylalanine to isoleucine substitution in AKR1C2, was associated with age of puberty (p = 0.07) and possibly ovulation rate (p = 0.102). Two SNP in AKR1C4 were significantly associated with nipple number (p ≤ 0.03) and another possibly associated with age at puberty (p = 0.09). Conclusion AKR1C genotypes were associated with nipple number as well as possible effects on age at puberty and ovulation rate. The estimated effects of AKR1C genotypes on these traits suggest that the SNPs are in incomplete linkage disequilibrium with the causal mutations that affect reproductive traits in swine. Further investigations are necessary to identify these mutations and understand how these AKR1C genes affect these important reproductive traits. The nucleotide sequence data reported have been submitted to GenBank and assigned accession numbers [GenBank:DQ474064–DQ474068, GenBank:DQ494488–DQ494490 and GenBank:DQ487182–DQ487184].
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Affiliation(s)
- Dan J Nonneman
- USDA-ARS, U.S. Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | - Tommy H Wise
- USDA-ARS, U.S. Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | - J Joe Ford
- USDA-ARS, U.S. Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | - Larry A Kuehn
- USDA-ARS, U.S. Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
| | - Gary A Rohrer
- USDA-ARS, U.S. Meat Animal Research Center, Clay Center, Nebraska, 68933, USA
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van Duijnhoven FJB, Peeters PHM, Warren RML, Bingham SA, Uitterlinden AG, van Noord PAH, Monninkhof EM, Grobbee DE, van Gils CH. Influence of estrogen receptor alpha and progesterone receptor polymorphisms on the effects of hormone therapy on mammographic density. Cancer Epidemiol Biomarkers Prev 2006; 15:462-7. [PMID: 16537702 DOI: 10.1158/1055-9965.epi-05-0754] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Postmenopausal hormone therapy increases mammographic density, a strong breast cancer risk factor, but effects vary across women. We investigated whether the effect of hormone therapy use is modified by polymorphisms in the estrogen receptor (ESR1) and progesterone receptor (PGR) genes in the Dutch Prospect-EPIC and the English EPIC-Norfolk cohorts. Information on hormone therapy use was obtained through questionnaires at recruitment and after 5 years. Blood samples were collected and consecutive mammograms were available through breast cancer screening programs. For 795 hormone therapy users, one mammogram before and a second mammogram during hormone therapy use was included. For 781 never hormone therapy users, mammograms with similar time intervals were included. Mammographic density was assessed using a computer-assisted method. Changes in density were analyzed using linear regression. A statistically significant difference in percentage density change between hormone therapy users and never users was seen in women with the ESR1 PvuII Pp or pp genotype (2.24%; P < 0.01), but not in those with the PP genotype (0.90%; P = 0.47). Similarly, effects of hormone therapy on percentage density were observed in women with the ESR1 XbaI Xx or xx genotype (2.20%; P < 0.01), but not in those with the XX genotype (-0.65%; P = 0.70). Also, effects were seen in women with the PGR +331 GG genotype (2.04%; P < 0.01), but not in those with the GA or AA genotype (0.98%; P = 0.53). The PGR PROGINS polymorphism did not seem to make women more susceptible to the effects of hormone therapy use. In conclusion, our results suggest that specific polymorphisms in the ESR1 and PGR genes may make women more susceptible to the effects of hormone therapy use on mammographic density.
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Affiliation(s)
- Fränzel J B van Duijnhoven
- Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, Mail-drop Str. 6.131, P.O. Box 85500, 3508 GA Utrecht, the Netherlands
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McTiernan A, Martin CF, Peck JD, Aragaki AK, Chlebowski RT, Pisano ED, Wang CY, Brunner RL, Johnson KC, Manson JE, Lewis CE, Kotchen JM, Hulka BS. Estrogen-plus-progestin use and mammographic density in postmenopausal women: Women's Health Initiative randomized trial. J Natl Cancer Inst 2005; 97:1366-76. [PMID: 16174858 DOI: 10.1093/jnci/dji279] [Citation(s) in RCA: 191] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Increased mammographic density reduces the sensitivity of screening mammography, is associated with increased breast cancer risk, and may be hormone related. We assessed the effect of estrogen-plus-progestin therapy on mammographic density. METHODS In a racially and ethnically diverse ancillary study of the Women's Health Initiative, we examined data from 413 postmenopausal women who had been randomly assigned to receive daily combined conjugated equine estrogens (0.625 mg) plus medroxyprogesterone acetate (i.e., progestin; 2.5 mg) (n = 202) or daily placebo (n = 211). We assessed the effect of estrogen plus progestin on measured mammographic percent density and abnormal findings over a 1-year and 2-year period. All tests of statistical significance were two-sided and were based on F tests or t tests from mixed-effects models. RESULTS Mean mammographic percent density increased by 6.0% at year 1, compared with baseline, in the estrogen-plus-progestin group but decreased by 0.9% in the placebo group (difference = 6.9%, 95% confidence interval [CI] = 5.3% to 8.5%; P < .001). The mean changes in mammographic density persisted but were attenuated slightly after 2 years, with an absolute increase of 4.9% in the estrogen-plus-progestin group and a decrease of 0.8% in the placebo group (difference = 5.7%, 95% CI = 4.3% to 7.3%; P < .001). These effects were consistent across racial/ethnic groups but were higher among women aged 70-79 years in the estrogen-plus-progestin group (mean increase at year 1 = 11.6%) than in the placebo group (mean decrease at year 1 = 0.1%) (difference of the means = 11.7%, 95% CI = 8.2% to 15.4%; P < .001, comparing across age groups). At year 1, women who were adherent to treatment in the estrogen-plus-progestin group had a mean increase in density of 7.7% (95% CI = 5.9% to 9.5%), and women in the placebo group had a mean decrease in density of 1.1% (95% CI = 0.3% to 1.9%). Use of estrogen plus progestin was associated with an increased risk of having an abnormal mammogram at year 1 (relative risk = 3.9, 95% CI = 1.5 to 10.2; P = .003), compared with placebo, that was not explained by an increase in density. CONCLUSIONS Use of up to 2 years of estrogen plus progestin was associated with increases in mammographic density.
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Affiliation(s)
- Anne McTiernan
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98019, USA.
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