Dataset Information

Hormone treatment, estrogen receptor polymorphisms and mortality: a prospective cohort study.

ABSTRACT: BACKGROUND: The association between hormone treatment (HT) and mortality remains controversial. This study aimed to determine whether the risk of mortality associated with HT use varies depending on the specific characteristics of treatment and genetic variability in terms of the estrogen receptor. METHODOLOGY/PRINCIPAL FINDINGS: A prospective, population-based study of 5135 women aged 65 years and older who were recruited from three cities in France and followed over six years. Detailed information related to HT use was obtained and five estrogen receptor polymorphisms were genotyped. The total follow-up was 25,436 person-years and during this time 352 women died. Cancer (36.4%) and cardiovascular disease (19.3%) were the major causes of death. Cox proportional hazards models adjusted for age, education, centre, living situation, comorbidity, depression, physical and mental incapacities, indicated no significant association between HT and mortality, regardless of the type or duration of treatment, or the age at initiation. However, the association between HT and all-cause or cancer-related mortality varied across women, with significant interactions identified with three estrogen receptor polymorphisms (p-values?=?0.004 to 0.03) in adjusted analyses. Women carrying the C allele of ESR1 rs2234693 had a decreased risk of all-cause mortality with HT (HR: 0.42, 95% CI: 0.18-0.97), while in stark contrast, those homozygous for the T allele had a significantly increased risk of cancer-related mortality (HR: 3.18, 95% CI: 1.23-8.20). The findings were similar for ESR1 rs9340799 and ESR2 rs1271572. CONCLUSIONS/SIGNIFICANCE: The risk of mortality was not associated with HT duration, type or age at initiation. It was however not equal across all women, with some women appearing genetically more vulnerable to the effects of HT in terms of their estrogen receptor genotype. These findings, if confirmed in another independent study, may help explain the differential susceptibility of women to the beneficial or adverse effects of HT.

SUBMITTER: Ryan J

PROVIDER: S-EPMC3311587 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Hormone treatment, estrogen receptor polymorphisms and mortality: a prospective cohort study.

Ryan Joanne J Canonico Marianne M Carcaillon Laure L Carrière Isabelle I Scali Jacqueline J Dartigues Jean-Francois JF Dufouil Carole C Ritchie Karen K Scarabin Pierre-Yves PY Ancelin Marie-Laure ML

PloS one 20120323 3

<h4>Background</h4>The association between hormone treatment (HT) and mortality remains controversial. This study aimed to determine whether the risk of mortality associated with HT use varies depending on the specific characteristics of treatment and genetic variability in terms of the estrogen receptor.<h4>Methodology/principal findings</h4>A prospective, population-based study of 5135 women aged 65 years and older who were recruited from three cities in France and followed over six years. Det ...[more]

PMID: 22457817

Similar Datasets

Project description:BackgroundThe estrogen receptors alpha and beta (ESR1, ESR2) have been implicated in adiposity, lipid metabolism and feeding behaviour. In this report we analyse ESR1 and ESR2 gene single nucleotide polymorphisms (SNPs) for association with obesity. We also relate adipose tissue ESR1 mRNA levels and ESR1 SNPs to adipocyte lipolysis and lipogenesis phenotypes.Methods23 ESR1 and 11 ESR2 tag-SNPs, covering most of the common haplotype variation in each gene according to HAPMAP data, were analysed by Chi2 for association with obesity in a cohort comprising 705 adults with severe obesity and 402 lean individuals. Results were replicated in a cohort comprising 837 obese and 613 lean subjects. About 80% of both cohorts comprised women and 20% men. Adipose tissue ESR1 mRNA was quantified in 122 women and related to lipolysis and lipogenesis by multiple regression. ESR1 SNPs were analysed for association with adipocyte lipolysis and lipogenesis phenotypes in 204 obese women by simple regression.ResultsNo ESR1 SNP was associated with obesity. Five ESR2 SNPs displayed nominal significant allelic association with obesity in women and one in men. The two ESR2 SNPs associated with obesity with nominal P value < 0.01 were genotyped in a second cohort where no association with obesity was observed. There was an inverse correlation between ESR1 mRNA levels in abdominal subcutaneous (sc) adipose tissue and basal lipolysis, as well as responsiveness to adrenoceptor agonists independent of age and BMI (P value 0.009-0.045). ESR1 rs532010 was associated with lipolytic sensitivity to noradrenaline (nominal P value 0.012), and ESR1 rs1884051 with responsiveness to the non-selective beta-adrenoceptor agonist isoprenaline (nominal P value 0.05). These associations became non-significant after Bonferroni correction.ConclusionESR1 gene alleles are unlikely to be a major cause of obesity in women. A minor importance of ESR2 on severe obesity cannot be excluded. The inverse correlation between ESR1 mRNA levels and lipolytic responsiveness to adrenoceptor agonists implies that low adipose tissue ESR1 levels attenuate catecholamine resistance in sc fat cells of obese women hereby contributing to loss of sc and gain of visceral fat. There is no evidence for a genetic impact of ESR1 on lipolysis or lipogenesis.

Project description:IntroductionAssociations of hormone-receptor positive breast cancer with excess adiposity are reasonably well characterized; however, uncertainty remains regarding the association of body mass index (BMI) with hormone-receptor negative malignancies, and possible interactions by hormone replacement therapy (HRT) use.MethodsWithin the European EPIC cohort, Cox proportional hazards models were used to describe the relationship of BMI, waist and hip circumferences with risk of estrogen-receptor (ER) negative and progesterone-receptor (PR) negative (n = 1,021) and ER+PR+ (n = 3,586) breast tumors within five-year age bands. Among postmenopausal women, the joint effects of BMI and HRT use were analyzed.ResultsFor risk of ER-PR- tumors, there was no association of BMI across the age bands. However, when analyses were restricted to postmenopausal HRT never users, a positive risk association with BMI (third versus first tertile HR = 1.47 (1.01 to 2.15)) was observed. BMI was inversely associated with ER+PR+ tumors among women aged ?49 years (per 5 kg/m2 increase, HR = 0.79 (95%CI 0.68 to 0.91)), and positively associated with risk among women ?65 years (HR = 1.25 (1.16 to 1.34)). Adjusting for BMI, waist and hip circumferences showed no further associations with risks of breast cancer subtypes. Current use of HRT was significantly associated with an increased risk of receptor-negative (HRT current use compared to HRT never use HR: 1.30 (1.05 to 1.62)) and positive tumors (HR: 1.74 (1.56 to 1.95)), although this risk increase was weaker for ER-PR- disease (Phet = 0.035). The association of HRT was significantly stronger in the leaner women (BMI ?22.5 kg/m2) than for more overweight women (BMI ?25.9 kg/m2) for, both, ER-PR- (HR: 1.74 (1.15 to 2.63)) and ER+PR+ (HR: 2.33 (1.84 to 2.92)) breast cancer and was not restricted to any particular HRT regime.ConclusionsAn elevated BMI may be positively associated with risk of ER-PR- tumors among postmenopausal women who never used HRT. Furthermore, postmenopausal HRT users were at an increased risk of ER-PR- as well as ER+PR+ tumors, especially among leaner women. For hormone-receptor positive tumors, but not for hormone-receptor negative tumors, our study confirms an inverse association of risk with BMI among young women of premenopausal age. Our data provide evidence for a possible role of sex hormones in the etiology of hormone-receptor negative tumors.

Dataset Information

Hormone treatment, estrogen receptor polymorphisms and mortality: a prospective cohort study.

Publications

Hormone treatment, estrogen receptor polymorphisms and mortality: a prospective cohort study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets