Obesity is an established risk factor for several common chronic diseases such as breast and colorectal cancer, metabolic and cardiovascular diseases; however, the biological basis for these ...relationships is not fully understood. To explore the association of obesity with these conditions, we investigated peripheral blood leucocyte (PBL) DNA methylation markers for adiposity and their contribution to risk of incident breast and colorectal cancer and myocardial infarction.
DNA methylation profiles (Illumina Infinium
HumanMethylation450 BeadChip) from 1941 individuals from four population-based European cohorts were analysed in relation to body mass index, waist circumference, waist-hip and waist-height ratio within a meta-analytical framework. In a subset of these individuals, data on genome-wide gene expression level, biomarkers of glucose and lipid metabolism were also available. Validation of methylation markers associated with all adiposity measures was performed in 358 individuals. Finally, we investigated the association of obesity-related methylation marks with breast, colorectal cancer and myocardial infarction within relevant subsets of the discovery population.
We identified 40 CpG loci with methylation levels associated with at least one adiposity measure. Of these, one CpG locus (cg06500161) in ABCG1 was associated with all four adiposity measures (P = 9.07×10
to 3.27×10
) and lower transcriptional activity of the full-length isoform of ABCG1 (P = 6.00×10
), higher triglyceride levels (P = 5.37×10
) and higher triglycerides-to-HDL cholesterol ratio (P = 1.03×10
). Of the 40 informative and obesity-related CpG loci, two (in IL2RB and FGF18) were significantly associated with colorectal cancer (inversely, P < 1.6×10
) and one intergenic locus on chromosome 1 was inversely associated with myocardial infarction (P < 1.25×10
), independently of obesity and established risk factors.
Our results suggest that epigenetic changes, in particular altered DNA methylation patterns, may be an intermediate biomarker at the intersection of obesity and obesity-related diseases, and could offer clues as to underlying biological mechanisms.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
ObjectivesUncertainty about the benefit of (high-intensity) statins for women remains due to under-representation of women in primary prevention trials and scarcity of sex-stratified data. This study ...evaluates the sex-specific relation between statin treatment and survival and the additional benefit of high-intensity statins.MethodsElectronic health record data from 47 801 patients (17 008 statin users and 30 793 non-users) without prior cardiovascular disease were extracted from thirteen Dutch outpatient cardiology clinics. Patients prescribed statins at baseline were propensity-score matched to those eligible for statin therapy (low-density lipoprotein >2.5 mmol/L) without a statin prescription. Statins were divided into low-intensity and high-intensity according to Dutch guidelines. Mortality data were obtained via linkage to the national mortality registry. Cox regression was used to evaluate the relationship between statin prescription and intensity and all-cause and cardiovascular mortality.ResultsPropensity score matching created a cohort of 8631 statin users and 8631 non-users. 35% of women and 28% of men received a low-intensity statin. The beneficial effect of statins on both all-cause and cardiovascular mortality was stronger in women (HR 0.66, 95% CI 0.58 to 0.74 and HR 0.55, 95% CI 0.39 to 0.71, respectively) than in men (HR 0.89, 95% CI 0.81 to 0.95 and HR 0.93, 95% CI 0.77 to 1.08, respectively). High-intensity statins conferred modest protection against all-cause mortality (HR 0.94, 95% CI 0.88 to 1.00) and cardiovascular mortality (HR 0.86, 95% CI 0.74 to 0.98) in both sexes.ConclusionsThe protective effect of primary prevention statins was stronger in women than men for both all-cause and cardiovascular mortality. High-intensity statins conferred a modest additional benefit in both sexes. Statins seem to be effective regardless of treatment intensity, especially in women.
BACKGROUND Timing of natural menopause has great implications for fertility and women's health. Age at natural menopause (ANM) is largely influenced by genetic factors. In the past decade, several ...genetic studies have been conducted to identify genes in ANM, which can help us unravel the biological pathways underlying this trait and the associated infertility and health risks. After providing an overview of the results of the genetic studies performed so far, we give recommendations for future studies in identifying genetic factors involved in determining the variation in timing of natural menopause. METHODS The electronic databases of Pubmed and Embase were systematically searched until September 2009 for genetic studies on ANM, using relevant keywords on the subject. Additional papers identified through hand search were also included. RESULTS Twenty-eight papers emerged from our literature search. A number of genetic regions and variants involved in several possible pathways underlying timing of ANM were identified, including two possible interesting regions (9q21.3 and chromosome 8 at 26 cM) in linkage analyses. Recent genome-wide association studies have identified two genomic regions (19q13.42 and 20p12.3), containing two promising candidate genes (BRKS1 and MCM). In the candidate gene association studies on ANM, very few consistent associations were found. CONCLUSION A number of genetic variants have been discovered in association with ANM, although the overall results have been rather disappointing. We have described possible new strategies for future genetic studies to identify more genetic loci involved in the variation in menopausal age.
Can additional genetic variants for circulating anti-Müllerian hormone (AMH) levels be identified through a genome-wide association study (GWAS) meta-analysis including a large sample of ...premenopausal women?
We identified four loci associated with AMH levels at P < 5 × 10-8: the previously reported MCM8 locus and three novel signals in or near AMH, TEX41 and CDCA7.
AMH is expressed by antral stage ovarian follicles in women, and variation in age-specific circulating AMH levels has been associated with disease outcomes. However, the physiological mechanisms underlying these AMH-disease associations are largely unknown.
We performed a GWAS meta-analysis in which we combined summary statistics of a previous AMH GWAS with GWAS data from 3705 additional women from three different cohorts.
In total, we included data from 7049 premenopausal female participants of European ancestry. The median age of study participants ranged from 15.3 to 48 years across cohorts. Circulating AMH levels were measured in either serum or plasma samples using different ELISA assays. Study-specific analyses were adjusted for age at blood collection and population stratification, and summary statistics were meta-analysed using a standard error-weighted approach. Subsequently, we functionally annotated GWAS variants that reached genome-wide significance (P < 5 × 10-8). We also performed a gene-based GWAS, pathway analysis and linkage disequilibrium score regression and Mendelian randomization (MR) analyses.
We identified four loci associated with AMH levels at P < 5 × 10-8: the previously reported MCM8 locus and three novel signals in or near AMH, TEX41 and CDCA7. The strongest signal was a missense variant in the AMH gene (rs10417628). Most prioritized genes at the other three identified loci were involved in cell cycle regulation. Genetic correlation analyses indicated a strong positive correlation among single nucleotide polymorphisms for AMH levels and for age at menopause (rg = 0.82, FDR = 0.003). Exploratory two-sample MR analyses did not support causal effects of AMH on breast cancer or polycystic ovary syndrome risk, but should be interpreted with caution as they may be underpowered and the validity of genetic instruments could not be extensively explored.
The full AMH GWAS summary statistics will made available after publication through the GWAS catalog (https://www.ebi.ac.uk/gwas/).
Whilst this study doubled the sample size of the most recent GWAS, the statistical power is still relatively low. As a result, we may still lack power to identify more genetic variants for AMH and to determine causal effects of AMH on, for example, breast cancer. Also, follow-up studies are needed to investigate whether the signal for the AMH gene is caused by reduced AMH detection by certain assays instead of actual lower circulating AMH levels.
Genes mapped to the MCM8, TEX41 and CDCA7 loci are involved in the cell cycle and processes such as DNA replication and apoptosis. The mechanism underlying their associations with AMH may affect the size of the ovarian follicle pool. Altogether, our results provide more insight into the biology of AMH and, accordingly, the biological processes involved in ovarian ageing.
Nurses' Health Study and Nurses' Health Study II were supported by research grants from the National Institutes of Health (CA172726, CA186107, CA50385, CA87969, CA49449, CA67262, CA178949). The UK Medical Research Council and Wellcome (217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the listed authors, who will serve as guarantors for the contents of this article. A comprehensive list of grants funding is available on the ALSPAC website (http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf). Funding for the collection of genotype and phenotype data used here was provided by the British Heart Foundation (SP/07/008/24066), Wellcome (WT092830M and WT08806) and UK Medical Research Council (G1001357). M.C.B., A.L.G.S. and D.A.L. work in a unit that is funded by the University of Bristol and UK Medical Research Council (MC_UU_00011/6). M.C.B.'s contribution to this work was funded by a UK Medical Research Council Skills Development Fellowship (MR/P014054/1) and D.A.L. is a National Institute of Health Research Senior Investigator (NF-0616-10102). A.L.G.S. was supported by the study of Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases (H2020-SC1-2019-Single-Stage-RTD, project ID 874739). The Doetinchem Cohort Study was financially supported by the Ministry of Health, Welfare and Sports of the Netherlands. The funder had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Ansh Labs performed the AMH measurements for the Doetinchem Cohort Study free of charge. Ansh Labs was not involved in the data analysis, interpretation or reporting, nor was it financially involved in any aspect of the study. R.M.G.V. was funded by the Honours Track of MSc Epidemiology, University Medical Center Utrecht with a grant from the Netherlands Organization for Scientific Research (NWO) (022.005.021). The Study of Women's Health Across the Nation (SWAN) has grant support from the National Institutes of Health (NIH), DHHS, through the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR) and the NIH Office of Research on Women's Health (ORWH) (U01NR004061; U01AG012505, U01AG012535, U01AG012531, U01AG012539, U01AG012546, U01AG012553, U01AG012554, U01AG012495). The SWAN Genomic Analyses and SWAN Legacy have grant support from the NIA (U01AG017719). The Generations Study was funded by Breast Cancer Now and the Institute of Cancer Research (ICR). The ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent official views of the funders. The Sister Study was funded by the Intramural Research Program of the National Institutes of Health (NIH), National Institute of Environmental Health Sciences (Z01-ES044005 to D.P.S.); the AMH assays were supported by the Avon Foundation (02-2012-065 to H.B. Nichols and D.P.S.). The breast cancer genome-wide association analyses were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the 'Ministère de l'Économie, de la Science et de l'Innovation du Québec' through Genome Québec and grant PSR-SIIRI-701, The National Institutes of Health (U19 CA148065, X01HG007492), Cancer Research UK (C1287/A10118, C1287/A16563, C1287/A10710) and The European Union (HEALTH-F2-2009-223175 and H2020 633784 and 634935). All studies and funders are listed in Michailidou et al. (Nature, 2017). F.J.M.B. has received fees and grant support from Merck Serono and Ferring BV. D.A.L. has received financial support from several national and international government and charitable funders as well as from Medtronic Ltd and Roche Diagnostics for research that is unrelated to this study. N.S. is scientific consultant for Ansh Laboratories. The other authors declare no competing interests.
Women have historically been underrepresented in cardiovascular clinical trials, resulting in a lack of sex-specific data. This is especially problematic in two situations, namely those where ...diseases manifest differently in women and men and those where biological differences between the sexes might affect the efficacy and/or safety of medication. There is therefore a pressing need for datasets with proper representation of women to address questions related to these situations. Clinical care data could fit this bill nicely because of their unique broad scope across both patient groups and clinical measures. This perspective piece presents the potential of clinical care data in sex differences research and discusses current challenges clinical care data-based research faces. It also suggests strategies to reduce the effect of these limitations, and explores whether clinical care data alone will be sufficient to close evidence gaps or whether a more comprehensive approach is needed.
The aim of our study was to relate four modifiable lifestyle factors (smoking status, body mass index, physical activity and diet) to health expectancy, using quality-adjusted life years (QALYs) in a ...prospective cohort study. Data of the prospective EPIC-NL study were used, including 33,066 healthy men and women aged 20-70 years at baseline (1993-7), followed until 31-12-2007 for occurrence of disease and death. Smoking status, body mass index, physical activity and adherence to a Mediterranean-style diet (excluding alcohol) were investigated separately and combined into a healthy lifestyle score, ranging from 0 to 4. QALYs were used as summary measure of healthy life expectancy, combining a person's life expectancy with a weight for quality of life when having a chronic disease. For lifestyle factors analyzed separately the number of years living longer in good health varied from 0.12 year to 0.84 year, after adjusting for covariates. A combination of the four lifestyle factors was positively associated with higher QALYs (P-trend <0.0001). A healthy lifestyle score of 4 compared to a score of 0 was associated with almost a 2 years longer life in good health (1.75 QALYs 95% CI 1.37, 2.14).
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Evidence suggests an etiologic role for inflammation in ovarian carcinogenesis and heterogeneity between tumor subtypes and anthropometric indices. Prospective studies on circulating inflammatory ...markers and epithelial invasive ovarian cancer (EOC) have predominantly investigated overall risk; data characterizing risk by tumor characteristics (histology, grade, stage, dualistic model of ovarian carcinogenesis) and anthropometric indices are sparse.
We conducted a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort to evaluate C-reactive protein (CRP), IL6, and EOC risk by tumor characteristics. A total of 754 eligible EOC cases were identified; two controls (n = 1,497) were matched per case. We used multivariable conditional logistic regression to assess associations.
CRP and IL6 were not associated with overall EOC risk. However, consistent with prior research, CRP >10 versus CRP ≤1 mg/L was associated with higher overall EOC risk OR, 1.67 (1.03-2.70). We did not observe significant associations or heterogeneity in analyses by tumor characteristics. In analyses stratified by waist circumference, inflammatory markers were associated with higher risk among women with higher waist circumference; no association was observed for women with normal waist circumference e.g., IL6: waist ≤80: ORlog2, 0.97 (0.81-1.16); waist >88: ORlog2, 1.78 (1.28-2.48), Pheterogeneity ≤ 0.01.
Our data suggest that high CRP is associated with increased risk of overall EOC, and that IL6 and CRP may be associated with EOC risk among women with higher adiposity.
Our data add to global evidence that ovarian carcinogenesis may be promoted by an inflammatory milieu.
DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ...ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (
= 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of
< 7.94 × 10
. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely
, and
. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. SIGNIFICANCE: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.
The New York Heart Association (NYHA) functional class has extensively been used for risk stratification in patients suspected of heart failure, although its prognostic value differs between sexes ...and disease entities. Functional exercise capacity might explain the association between NYHA functional class and survival, and can serve as an objective proxy for the subjective nature of the NYHA classification. Therefore, we assessed whether sex-differences in exercise capacity explain the association between NYHA functional class and survival in patients suspected of cardiovascular disease.BackgroundThe New York Heart Association (NYHA) functional class has extensively been used for risk stratification in patients suspected of heart failure, although its prognostic value differs between sexes and disease entities. Functional exercise capacity might explain the association between NYHA functional class and survival, and can serve as an objective proxy for the subjective nature of the NYHA classification. Therefore, we assessed whether sex-differences in exercise capacity explain the association between NYHA functional class and survival in patients suspected of cardiovascular disease.Electronic health record data from 7259 patients with cardiovascular symptoms, a documented NYHA functional class and cardiac stress electrocardiogram (ECG), was analysed. Follow-up for all-cause mortality was obtained through linkage with Statistics Netherlands. A sex-stratified mediation analysis was performed to assess to what extent the proportional heart rate and -workload during ECG stress testing explain the association between NYHA functional class and survival.MethodsElectronic health record data from 7259 patients with cardiovascular symptoms, a documented NYHA functional class and cardiac stress electrocardiogram (ECG), was analysed. Follow-up for all-cause mortality was obtained through linkage with Statistics Netherlands. A sex-stratified mediation analysis was performed to assess to what extent the proportional heart rate and -workload during ECG stress testing explain the association between NYHA functional class and survival.In men, increments in NYHA functional class were related to higher all-cause mortality in a dose-response manner (NYHA II vs III/IV: hazard ratio HR 1.59 vs 3.64, referenced to NYHA I), whilst in women those classified as NYHA functional class II and III/IV had a similar higher mortality risk (HR 1.49 vs 1.41). Sex-stratified mediation analysis showed that the association between NYHA and survival was mostly explained by proportional workload during stress ECG (men vs women: 22.9%, 95% CI: 18.9%-27.3% vs 40.3%, 95% CI: 28.5%-68.6%) and less so by proportional heart rate (men vs women: 2.5%, 95% CI: 1.3%-4.3% vs 8.0%, 95% CI: 4.1%-18.1%). Post-hoc analysis showed that NYHA classification explained a minor proportion of the association between proportional workload and all-cause mortality (men vs women: 15.1%, 95% CI: 12.0%-18.3% vs 4.4%, 95% CI: 1.5%-7.4%).ResultsIn men, increments in NYHA functional class were related to higher all-cause mortality in a dose-response manner (NYHA II vs III/IV: hazard ratio HR 1.59 vs 3.64, referenced to NYHA I), whilst in women those classified as NYHA functional class II and III/IV had a similar higher mortality risk (HR 1.49 vs 1.41). Sex-stratified mediation analysis showed that the association between NYHA and survival was mostly explained by proportional workload during stress ECG (men vs women: 22.9%, 95% CI: 18.9%-27.3% vs 40.3%, 95% CI: 28.5%-68.6%) and less so by proportional heart rate (men vs women: 2.5%, 95% CI: 1.3%-4.3% vs 8.0%, 95% CI: 4.1%-18.1%). Post-hoc analysis showed that NYHA classification explained a minor proportion of the association between proportional workload and all-cause mortality (men vs women: 15.1%, 95% CI: 12.0%-18.3% vs 4.4%, 95% CI: 1.5%-7.4%).This study showed a significant mediation in both sexes on the association between NYHA functional class and all-cause mortality by proportional workload, but the effect explained by NYHA classification on the association between survival and proportional workload is small. This implies that NYHA classification is not a sole representation of a patient's functional capacity, but might also incude other aspects of the patient's overall health status.ConclusionsThis study showed a significant mediation in both sexes on the association between NYHA functional class and all-cause mortality by proportional workload, but the effect explained by NYHA classification on the association between survival and proportional workload is small. This implies that NYHA classification is not a sole representation of a patient's functional capacity, but might also incude other aspects of the patient's overall health status.
Higher age-specific circulating anti-Müllerian hormone (AMH) levels have been linked to a lower risk of cardiometabolic outcomes. However, whether AMH has a casual role in the etiology of these ...diseases is unknown. The objective of this study was therefore to explore if circulating AMH levels have a causal effect on risk of coronary artery disease (CAD), ischemic stroke and type 2 diabetes (T2D) in women, using a two-sample Mendelian randomization (MR) approach.BackgroundHigher age-specific circulating anti-Müllerian hormone (AMH) levels have been linked to a lower risk of cardiometabolic outcomes. However, whether AMH has a casual role in the etiology of these diseases is unknown. The objective of this study was therefore to explore if circulating AMH levels have a causal effect on risk of coronary artery disease (CAD), ischemic stroke and type 2 diabetes (T2D) in women, using a two-sample Mendelian randomization (MR) approach.We used four single nucleotide polymorphisms (SNPs) from the most recent AMH GWAS meta-analysis as instrumental variables. Summary-level data for CAD (n = 149,752; 11,802 cases), ischemic stroke (n = 17,541; 4678 cases) and T2D (n = 464,389; 30,052 cases) were extracted from the UK Biobank, the Stroke Genetics Network, and DIAMANTE consortia, respectively. To assess the presence of potential pleiotropy we tested the association of the four AMH SNPs, both individually and combined in a weighted genetic risk score, with a range of cardiovascular risk factors and intermediate traits using UK Biobank data.MethodsWe used four single nucleotide polymorphisms (SNPs) from the most recent AMH GWAS meta-analysis as instrumental variables. Summary-level data for CAD (n = 149,752; 11,802 cases), ischemic stroke (n = 17,541; 4678 cases) and T2D (n = 464,389; 30,052 cases) were extracted from the UK Biobank, the Stroke Genetics Network, and DIAMANTE consortia, respectively. To assess the presence of potential pleiotropy we tested the association of the four AMH SNPs, both individually and combined in a weighted genetic risk score, with a range of cardiovascular risk factors and intermediate traits using UK Biobank data.MR estimates, i.e., inverse variance-weighted odds ratios ( OR IVW ), did not support a causal effect of circulating AMH levels on CAD ( OR IVW = 1.13, 95% CI: 0.95-1.35), ischemic stroke ( OR IVW = 1.11, 95% CI: 0.83-1.49), and T2D ( OR IVW = 0.98, 95% CI: 0.87-1.10). After adjustment for multiple testing, we observed associations between genetically predicted AMH and age at menopause, and age at menarche, but not with intermediate traits on the causal pathway between AMH and cardiometabolic health, such as atherosclerosis or glucose levels.ResultsMR estimates, i.e., inverse variance-weighted odds ratios ( OR IVW ), did not support a causal effect of circulating AMH levels on CAD ( OR IVW = 1.13, 95% CI: 0.95-1.35), ischemic stroke ( OR IVW = 1.11, 95% CI: 0.83-1.49), and T2D ( OR IVW = 0.98, 95% CI: 0.87-1.10). After adjustment for multiple testing, we observed associations between genetically predicted AMH and age at menopause, and age at menarche, but not with intermediate traits on the causal pathway between AMH and cardiometabolic health, such as atherosclerosis or glucose levels.This study does not provide evidence for a causal effect of circulating AMH levels on CAD, ischemic stroke and T2D in women, although weak instrument bias cannot be excluded.ConclusionsThis study does not provide evidence for a causal effect of circulating AMH levels on CAD, ischemic stroke and T2D in women, although weak instrument bias cannot be excluded.
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