scholarly journals Women’s reproductive factors and incident cardiovascular disease in the UK Biobank

Heart ◽  
2018 ◽  
Vol 104 (13) ◽  
pp. 1069-1075 ◽  
Author(s):  
Sanne AE Peters ◽  
Mark Woodward
Keyword(s):  
Cardiovascular Disease ◽  
Reproductive Factors ◽  
Age At First Birth ◽  
Uk Biobank ◽  
First Birth ◽  
Early Menopause ◽  
Early Menarche ◽  
History Of ◽  
The Uk ◽  
The Relationship

BackgroundStudies have suggested that women’s reproductive factors are associated with the risk of cardiovascular disease (CVD); however, findings are mixed. We assessed the relationship between reproductive factors and incident CVD in the UK Biobank.MethodsBetween 2006 and 2010, the UK Biobank recruited over 500 000 participants aged 40–69 years across the UK. During 7 years of follow-up, 9054 incident cases of CVD (34% women), 5782 cases of coronary heart disease (CHD) (28% women), and 3489 cases of stroke (43% women) were recorded among 267 440 women and 215 088 men without a history of CVD at baseline. Cox regression models yielded adjusted hazard ratios (HRs) for CVD, CHD and stroke associated with reproductive factors.ResultsAdjusted HRs (95% CI) for CVD were 1.10 (1.01 to 1.30) for early menarche (<12 years), 0.97 (0.96 to 0.98) for each year increase in age at first birth, 1.04 (1.00 to 1.09) for each miscarriage, 1.14 (1.02 to 1.28) for each stillbirth, and 1.33 (1.19 to 1.49) for early menopause (<47 years). Hysterectomy without oophorectomy or with previous oophorectomy had adjusted HRs of 1.16 (1.06 to 1.28) and 2.30 (1.20 to 4.43) for CVD. Each additional child was associated with a HR for CVD of 1.03 (1.00 to 1.06) in women and 1.03 (1.02 to 1.05) in men.ConclusionsEarly menarche, early menopause, earlier age at first birth, and a history of miscarriage, stillbirth or hysterectomy were each independently associated with a higher risk of CVD in later life. The relationship between the number of children and incident CVD was similar for men and women.

Abstract MP63: Established Cardiovascular Disease Risk Factors Mediate The Relationship Between Hypertensive Disorders In First Pregnancy And Maternal Cardiovascular Disease

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Jennifer J Stuart ◽  
Lauren J Tanz ◽  
Eric B Rimm ◽  
Donna Spiegelman ◽  
Stacey A Missmer ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Chronic Hypertension ◽  
Cvd Risk Factors ◽  
First Birth ◽  
Cvd Risk ◽  
Hypertensive Disorders ◽  
Increased Risk ◽  
History Of ◽  
The Relationship

Introduction: Women with a history of hypertensive disorders in pregnancy (HDP; gestational hypertension [GHTN] or preeclampsia) have an increased risk of CVD risk factors and events compared to women with normotensive pregnancies. However, the extent to which the relationship between HDP and CVD events is mediated by established CVD risk factors is less clear. Hypothesis: We hypothesized that a large proportion of the HDP-CVD relationship would be mediated by subsequent CVD risk factors — chronic hypertension (CHTN), type 2 diabetes (T2D), hypercholesterolemia, and BMI. Methods: Parous women free of prior CVD events, CHTN, T2D, and hypercholesterolemia at first birth in the Nurses’ Health Study II comprised the analytic sample (n=57,974). Pregnancy history was retrospectively reported in 2009. Women were followed for confirmed CVD events (coronary heart disease [non-fatal or fatal MI, fatal CHD] or stroke [non-fatal or fatal]) from first birth through 2015. Potential mediators were self-reported on biennial questionnaires. We used Cox proportional hazards models to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the relationship between HDP in first pregnancy (preeclampsia or GHTN vs. normotension [ref]) and CVD, adjusting for age, race/ethnicity, parental education, family history of CVD before age 60, and pre-pregnancy risk factors (e.g., smoking, diet, and BMI). To evaluate the proportion of the HDP-CVD association that was jointly mediated by the CVD risk factors we used the difference method, comparing a model including these four factors to a model without them. Results: Nine percent of women (n=5,306) had a history of HDP in first pregnancy (preeclampsia: 6.3%; GHTN: 2.9%). CVD events occurred in 650 women with normotension in first pregnancy, 30 with GHTN, and 81 with preeclampsia. Adjusting for pre-pregnancy confounders, women with HDP in first pregnancy had a 63% higher rate of incident CVD (CI: 1.33-2.00) compared to women with normotension in first pregnancy; in particular, the strongest association was observed between preeclampsia and CHD (HR=2.18, CI: 1.62-2.93). The overall HDP-CVD association was largely mediated by the group of four CVD risk factors (HDP: proportion mediation [PM]=65%, CI: 35-87; preeclampsia: PM=57%, CI: 21-87; GHTN: PM=99%, CI: inestimable). All CVD risk factors contributed to mediation, but chronic hypertension accounted for the largest proportion. Conclusions: While approximately 40% of the association between preeclampsia and CVD remained unexplained, almost all the increased risk of CVD conferred by a history of GHTN was jointly accounted for by the development of established risk factors postpartum. Screening for CHTN, T2D, hypercholesterolemia, and overweight/obesity after pregnancy may be especially helpful in CVD prevention among women with a history of HDP.

A model of lifetime health outcomes in cardiovascular disease based on clinical trials and large cohorts

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
R Wu ◽  
C Williams ◽  
I Schlackow ◽  
J Zhou ◽  
J Emberson ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cardiovascular Disease ◽  
Life Expectancy ◽  
Remaining Life ◽  
Uk Biobank ◽  
Cvd Risk ◽  
Micro Simulation ◽  
History Of ◽  
Remaining Life Expectancy ◽  
The Uk

Abstract Background and purpose Cardiovascular disease (CVD) risk of individuals depends on their socio-demographic characteristics, clinical risk factors, and treatments, and strongly influences their quality of life and survival. Individual-based long-term disease models, which aim to more accurately calculate the lifetime consequences, can help to target treatments, develop disease management programmes, and assess the value of new therapies. We present a new micro-simulation CVD model. Methods This micro-simulation model was developed using individual participant data from the Cholesterol Treatment Trialists' collaboration (CTT: 118,000 participants; 15 trials) and calibrated (with added socioeconomic deprivation, ethnicity, physical activity, mental illness, cancer and incident diabetes) in the UK Biobank cohort (UKB: 502,000 participants). Parametric survival models estimated risks of key endpoints (myocardial infarction (MI), stroke, coronary revascularisation (CRV), diabetes, cancer and vascular (VD) and nonvascular death (NVD) using participants' age, sex, ethnicity, physical activity, socioeconomic deprivation, smoking history, lipids, blood pressure, creatinine, previous cardiovascular diseases, diabetes, mental illness and cancer at entry and non-fatal incidents of the key endpoints during follow-up. The model integrates the risk equations and enables annual projection of endpoints and survival over individuals' lifetimes. The model was used to project remaining life expectancy across UK Biobank participants. Results Nonfatal cardiovascular events and age were the major determinants of CVD risk and, together with incident diabetes and cancer, of individuals' survival. The cumulative incidence of the key endpoints predicted by the CTT-UKB model corresponded well to their observed incidence in the UK Biobank cohort, overall (Figure 1) and in categories of participants by age, sex, prior CVD and CVD risk. Predicted remaining life expectancy across UK Biobank participants without history of CVD ranged between 22 and 43 years in men and between 24 and 46 years in women, depending on their age and CVD risk (Figure 2). Among UK Biobank participants with history of CVD, depending on their age, predicted remaining life expectancy ranged from 20 to 32 years in men and from 26 to 38 years in women. Conclusion This new lifetime CVD model accurately predicts morbidity and mortality in a large UK population cohort. It will be made available to provide individualised projections of expected lifetime health outcomes and benefits of treatments. FUNDunding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): UK National Institute for Health Research (NIHR) Health Technology Assessment (HTA) Programme, UK Medical Research Council (MRC), British Heart Foundation Figure 1. Predicted (in black) versus observed (95% CI; in red) incidence of major clinical outcomes in the UK Biobank. Figure 2. Predicted remaining life expectancy of participants in UK Biobank cohort, by age and CVD risk or previous CVD at entry. QRISK, a 10-year CVD risk scoring algorithm for people without previous CVD, recommended for use in the UK National Health Service.

Abstract 15887: Clonal Hematopoiesis Links Premature Menopause to Cardiovascular Disease

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Michael C Honigberg ◽  
Seyedeh Zekavat ◽  
Abhishek Niroula ◽  
Gabirel K Griffin ◽  
Alexander G Bick ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Strong Association ◽  
Premature Menopause ◽  
Uk Biobank ◽  
Clonal Hematopoiesis ◽  
Age Related ◽  
Cardiovascular Disease In Women ◽  
History Of ◽  
Artery Disease ◽  
The Uk

Introduction: Premature menopause is an independent risk factor for cardiovascular disease in women, but mechanisms underlying this association remain unclear. Clonal hematopoiesis of indeterminate potential (CHIP), the age-related expansion of hematopoietic cells with leukemogenic mutations, is associated with accelerated atherosclerosis. Whether premature menopause is associated with CHIP is unknown. Methods: We included postmenopausal women from the UK Biobank (N=11,509) aged 40-70 years with whole exome sequences and from the Women’s Health Initiative (WHI, N=8,111) aged 50-79 years with whole genome sequences. Premature menopause was defined as natural or surgical menopause occurring before age 40 years. Co-primary outcomes were the presence of (1) any CHIP and (2) CHIP with variant allele fraction (VAF) >0.1. Logistic regression tested the association of premature menopause with CHIP, adjusted for age, race, the first 10 principal components, smoking, diabetes mellitus, and hormone therapy use. Results: Across cohorts, prevalence of CHIP in women with vs. without a history of premature menopause was 8.8% vs. 5.5% (P<0.001), respectively. After multivariable adjustment, premature menopause was independently associated with CHIP, driven by associations with natural premature menopause (OR for all CHIP: 1.73, 95% CI 1.23-2.44; OR for CHIP with VAF >0.1: 1.91, 95% CI 1.30-2.80; Figure ). In gene-specific analyses, DNMT3A CHIP had a strong association with natural premature menopause but no association with surgical premature menopause. Among postmenopausal middle-aged women in the UK Biobank and WHI, CHIP was independently associated with incident coronary artery disease (meta-analyzed HR 1.52, 95% CI 1.17-1.99). Conclusions: Premature menopause, especially natural premature menopause, is independently associated with CHIP. CHIP may contribute to the excess cardiovascular risk associated with premature menopause.

scholarly journals Variation in VKORC1 Is Associated with Vascular Dementia

2021 ◽  
Vol 80 (3) ◽  
pp. 1329-1337
Author(s):  
Jure Mur ◽  
Daniel L. McCartney ◽  
Daniel I. Chasman ◽  
Peter M. Visscher ◽  
Graciela Muniz-Terrera ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Vascular Dementia ◽  
Genetic Variant ◽  
Warfarin Dose ◽  
Uk Biobank ◽  
Parental History ◽  
Genome Wide ◽  
History Of ◽  
First Time ◽  
The Relationship

Background: The genetic variant rs9923231 (VKORC1) is associated with differences in the coagulation of blood and consequentially with sensitivity to the drug warfarin. Variation in VKORC1 has been linked in a gene-based test to dementia/Alzheimer’s disease in the parents of participants, with suggestive evidence for an association for rs9923231 (p = 1.8×10–7), which was included in the genome-wide significant KAT8 locus. Objective: Our study aimed to investigate whether the relationship between rs9923231 and dementia persists only for certain dementia sub-types, and if those taking warfarin are at greater risk. Methods: We used logistic regression and data from 238,195 participants from UK Biobank to examine the relationship between VKORC1, risk of dementia, and the interplay with warfarin use. Results: Parental history of dementia, APOE variant, atrial fibrillation, diabetes, hypertension, and hypercholesterolemia all had strong associations with vascular dementia (p < 4.6×10–6). The T-allele in rs9923231 was linked to a lower warfarin dose (βperT - allele = –0.29, p < 2×10–16) and risk of vascular dementia (OR = 1.17, p = 0.010), but not other dementia sub-types. However, the risk of vascular dementia was not affected by warfarin use in carriers of the T-allele. Conclusion: Our study reports for the first time an association between rs9923231 and vascular dementia, but further research is warranted to explore potential mechanisms and specify the relationship between rs9923231 and features of vascular dementia.

Advanced cardiometabolic & inflammatory markers for prediction of cardiovascular disease and cancer

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
D Radenkovic ◽  
S.C Chawla ◽  
G Botta ◽  
A Boli ◽  
M.B Banach ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Risk Score ◽  
Cancer Incidence ◽  
Risk Function ◽  
Patient Characteristics ◽  
Risk Scores ◽  
Uk Biobank ◽  
Training Set ◽  
All Cause Mortality ◽  
The Uk

Abstract   The two leading causes of mortality worldwide are cardiovascular disease (CVD) and cancer. The annual total cost of CVD and cancer is an estimated $844.4 billion in the US and is projected to double by 2030. Thus, there has been an increased shift to preventive medicine to improve health outcomes and development of risk scores, which allow early identification of individuals at risk to target personalised interventions and prevent disease. Our aim was to define a Risk Score R(x) which, given the baseline characteristics of a given individual, outputs the relative risk for composite CVD, cancer incidence and all-cause mortality. A non-linear model was used to calculate risk scores based on the participants of the UK Biobank (= 502548). The model used parameters including patient characteristics (age, sex, ethnicity), baseline conditions, lifestyle factors of diet and physical activity, blood pressure, metabolic markers and advanced lipid variables, including ApoA and ApoB and lipoprotein(a), as input. The risk score was defined by normalising the risk function by a fixed value, the average risk of the training set. To fit the non-linear model &gt;400,000 participants were used as training set and &gt;45,000 participants were used as test set for validation. The exponent of risk function was represented as a multilayer neural network. This allowed capturing interdependent behaviour of covariates, training a single model for all outcomes, and preserving heterogeneity of the groups, which is in contrast to CoxPH models which are traditionally used in risk scores and require homogeneous groups. The model was trained over 60 epochs and predictive performance was determined by the C-index with standard errors and confidence intervals estimated with bootstrap sampling. By inputing the variables described, one can obtain personalised hazard ratios for 3 major outcomes of CVD, cancer and all-cause mortality. Therefore, an individual with a risk Score of e.g. 1.5, at any time he/she has 50% more chances than average of experiencing the corresponding event. The proposed model showed the following discrimination, for risk of CVD (C-index = 0.8006), cancer incidence (C-index = 0.6907), and all-cause mortality (C-index = 0.7770) on the validation set. The CVD model is particularly strong (C-index &gt;0.8) and is an improvement on a previous CVD risk prediction model also based on classical risk factors with total cholesterol and HDL-c on the UK Biobank data (C-index = 0.7444) published last year (Welsh et al. 2019). Unlike classically-used CoxPH models, our model considers correlation of variables as shown by the table of the values of correlation in Figure 1. This is an accurate model that is based on the most comprehensive set of patient characteristics and biomarkers, allowing clinicians to identify multiple targets for improvement and practice active preventive cardiology in the era of precision medicine. Figure 1. Correlation of variables in the R(x) Funding Acknowledgement Type of funding source: None

scholarly journals Comment on the Relationship Between Common Variant Schizophrenia Liability and Number of Offspring in the UK Biobank

2019 ◽  
Vol 176 (7) ◽  
pp. 573-574 ◽  
Author(s):  
Rebecca B. Lawn ◽  
Hannah M. Sallis ◽  
Amy E. Taylor ◽  
Robyn E. Wootton ◽  
George Davey Smith ◽  
...  
Keyword(s):  
Common Variant ◽  
Uk Biobank ◽  
The Uk ◽  
The Relationship

scholarly journals Hormonal and reproductive factors and risk of upper gastrointestinal cancers in men: A prospective cohort study within the UK Biobank

2018 ◽  
Vol 143 (4) ◽  
pp. 831-841
Author(s):  
Úna C. Mc Menamin ◽  
Andrew T. Kunzmann ◽  
Michael B. Cook ◽  
Brian T. Johnston ◽  
Liam J. Murray ◽  
...  
Keyword(s):  
Cohort Study ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Reproductive Factors ◽  
Uk Biobank ◽  
Gastrointestinal Cancers ◽  
The Uk ◽  
Upper Gastrointestinal

scholarly journals Coffee Consumption and Cardiovascular Diseases: A Mendelian Randomization Study

Nutrients ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 2218
Author(s):  
Shuai Yuan ◽  
Paul Carter ◽  
Amy M. Mason ◽  
Stephen Burgess ◽  
Susanna C. Larsson
Keyword(s):  
Cardiovascular Disease ◽  
Cardiovascular Diseases ◽  
Intracerebral Hemorrhage ◽  
Genetic Variants ◽  
Odds Ratio ◽  
Observational Studies ◽  
Mendelian Randomization ◽  
Coffee Consumption ◽  
Uk Biobank ◽  
The Uk

Coffee consumption has been linked to a lower risk of cardiovascular disease in observational studies, but whether the associations are causal is not known. We conducted a Mendelian randomization investigation to assess the potential causal role of coffee consumption in cardiovascular disease. Twelve independent genetic variants were used to proxy coffee consumption. Summary-level data for the relations between the 12 genetic variants and cardiovascular diseases were taken from the UK Biobank with up to 35,979 cases and the FinnGen consortium with up to 17,325 cases. Genetic predisposition to higher coffee consumption was not associated with any of the 15 studied cardiovascular outcomes in univariable MR analysis. The odds ratio per 50% increase in genetically predicted coffee consumption ranged from 0.97 (95% confidence interval (CI), 0.63, 1.50) for intracerebral hemorrhage to 1.26 (95% CI, 1.00, 1.58) for deep vein thrombosis in the UK Biobank and from 0.86 (95% CI, 0.50, 1.49) for subarachnoid hemorrhage to 1.34 (95% CI, 0.81, 2.22) for intracerebral hemorrhage in FinnGen. The null findings remained in multivariable Mendelian randomization analyses adjusted for genetically predicted body mass index and smoking initiation, except for a suggestive positive association for intracerebral hemorrhage (odds ratio 1.91; 95% CI, 1.03, 3.54) in FinnGen. This Mendelian randomization study showed limited evidence that coffee consumption affects the risk of developing cardiovascular disease, suggesting that previous observational studies may have been confounded.

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