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Aims We examined associations of obesity with incident cardiovascular outcomes and cardiovascular magnetic resonance (CMR) phenotypes, integrating information from body mass index (BMI) and waist-to-hip ratio (WHR). Then, we used multiple mediation to define the role of obesity-related cardiac remodelling in driving obesity-outcome associations, independent of cardiometabolic diseases. Methods and results In 491 606 UK Biobank participants, using Cox proportional hazard models, greater obesity (higher WHR, higher BMI) was linked to significantly greater risk of incident ischaemic heart disease, atrial fibrillation (AF), heart failure (HF), all-cause mortality, and cardiovascular disease (CVD) mortality. In combined stratification by BMI and WHR thresholds, elevated WHR was associated with greater risk of adverse outcomes at any BMI level. Individuals with overweight BMI but normal WHR had weaker disease associations. In the subset of participants with CMR (n = 31 107), using linear regression, greater obesity was associated with higher left ventricular (LV) mass, greater LV concentricity, poorer LV systolic function, lower myocardial native T1, larger left atrial (LA) volumes, poorer LA function, and lower aortic distensibility. Of note, higher BMI was linked to higher, whilst greater WHR was linked to lower LV end-diastolic volume (LVEDV). In Cox models, greater LVEDV and LV mass (LVM) were linked to increased risk of CVD, most importantly HF and an increased LA maximal volume was the key predictive measure of new-onset AF. In multiple mediation analyses, hypertension and adverse LV remodelling (higher LVM, greater concentricity) were major independent mediators of the obesity–outcome associations. Atrial remodelling and native T1 were additional mediators in the associations of obesity with AF and HF, respectively. Conclusions We demonstrate associations of obesity with adverse cardiovascular phenotypes and their significant independent role in mediating obesity–outcome relationships. In addition, our findings support the integrated use of BMI and WHR to evaluate obesity-related cardiovascular risk.

Aim This study examined sex-based differences in associations of vascular risk factors with incident cardiovascular events in the UK Biobank. Methods Baseline participant demographic, clinical, laboratory, anthropometric, and imaging characteristics were collected. Multivariable Cox regression was used to estimate independent associations of vascular risk factors with incident myocardial infarction (MI) and ischaemic stroke for men and women. Women-to-men ratios of hazard ratios (RHRs), and related 95% confidence intervals, represent the relative effect-size magnitude by sex. Results Among the 363 313 participants (53.5% women), 8 470 experienced MI (29.9% women) and 7 705 experienced stroke (40.1% women) over 12.66 [11.93, 13.38] years of prospective follow-up. Men had greater risk factor burden and higher arterial stiffness index at baseline. Women had greater age-related decline in aortic distensibility. Older age [RHR: 1.02 (1.01–1.03)], greater deprivation [RHR: 1.02 (1.00–1.03)], hypertension [RHR: 1.14 (1.02–1.27)], and current smoking [RHR: 1.45 (1.27–1.66)] were associated with a greater excess risk of MI in women than men. Low-density lipoprotein cholesterol was associated with excess MI risk in men [RHR: 0.90 (0.84–0.95)] and apolipoprotein A (ApoA) was less protective for MI in women [RHR: 1.65 (1.01–2.71)]. Older age was associated with excess risk of stroke [RHR: 1.01 (1.00–1.02)] and ApoA was less protective for stroke in women [RHR: 2.55 (1.58–4.14)]. Conclusion Older age, hypertension and smoking appeared stronger drivers of cardiovascular disease in women, whereas lipid metrics appeared stronger risk determinants for men. These findings highlight the importance of sex-specific preventive strategies and suggest priority targets for intervention in men and women.

Background: Biological heart age estimation can provide insights into cardiac aging. However, existing studies do not consider differential aging across cardiac regions.Purpose: To estimate biological age of the left ventricle (LV), right ventricle (RV), myocardium, left atrium, and right atrium using magnetic resonance imaging radiomics phenotypes and to investigate determinants of aging by cardiac region.Study type: Cross-sectional.Population: A total of 18,117 healthy UK Biobank participants including 8338 men (mean age = 64.2 ± 7.5) and 9779 women (mean age = 63.0 ± 7.4).Field Strength/Sequence: A 1.5 T/balanced steady-state free precession.Assessment: An automated algorithm was used to segment the five cardiac regions, from which radiomic features were extracted. Bayesian ridge regression was used to estimate biological age of each cardiac region with radiomics features as predictors and chronological age as the output. The “age gap” was the difference between biological and chronological age. Linear regression was used to calculate associations of age gap from each cardiac region with socioeconomic, lifestyle, body composition, blood pressure and arterial stiffness, blood biomarkers, mental well-being, multiorgan health, and sex hormone exposures (n = 49).Statistical Test: Multiple testing correction with false discovery method (threshold = 5%).Results: The largest model error was with RV and the smallest with LV age (mean absolute error in men: 5.26 vs. 4.96 years). There were 172 statistically significant age gap associations. Greater visceral adiposity was the strongest correlate of larger age gaps, for example, myocardial age gap in women (Beta = 0.85, P = 1.69 × 10−26). Poor mental health associated with large age gaps, for example, “disinterested” episodes and myocardial age gap in men (Beta = 0.25, P = 0.001), as did a history of dental problems (eg LV in men Beta = 0.19, P = 0.02). Higher bone mineral density was the strongest associate of smaller age gaps, for example, myocardial age gap in men (Beta = −1.52, P = 7.44 × 10−6).Data Conclusion: This work demonstrates image-based heart age estimation as a novel method for understanding cardiac aging.

Aims We evaluated the associations of left atrial (LA) structure and function with prevalent and incident cardiovascular disease (CVD), independent of left ventricular (LV) metrics, in 25 896 UK Biobank participants. Methods and results We estimated the association of cardiovascular magnetic resonance (CMR) metrics [LA maximum volume (LAV), LA ejection fraction (LAEF), LV mass : LV end-diastolic volume ratio (LVM : LVEDV), global longitudinal strain, and LV global function index (LVGFI)] with vascular risk factors (hypertension, diabetes, high cholesterol, and smoking), prevalent and incident CVDs [atrial fibrillation (AF), stroke, ischaemic heart disease (IHD), myocardial infarction], all-cause mortality, and CVD mortality. We created uncorrelated CMR variables using orthogonal principal component analysis rotation. All five CMR metrics were simultaneously entered into multivariable regression models adjusted for sex, age, ethnicity, deprivation, education, body size, and physical activity. Lower LAEF was associated with diabetes, smoking, and all the prevalent and incident CVDs. Diabetes, smoking, and high cholesterol were associated with smaller LAV. Hypertension, IHD, AF (incident and prevalent), incident stroke, and CVD mortality were associated with larger LAV. LV and LA metrics were both independently informative in associations with prevalent disease, however LAEF showed the most consistent associations with incident CVDs. Lower LVGFI was associated with greater all-cause and CVD mortality. In secondary analyses, compared with LVGFI, LV ejection fraction showed similar but less consistent disease associations. Conclusion LA structure and function measures (LAEF and LAV) demonstrate significant associations with key prevalent and incident cardiovascular outcomes, independent of LV metrics. These measures have potential clinical utility for disease discrimination and outcome prediction.

BackgroundChronic liver disease (CLD) and cardiovascular diseases (CVD) share common risk factors; the former is associated with a two-fold greater incidence of CVD. With most CLD being preventable/modifiable, early identification of at high-risk individuals is crucial. Using data from the UK Biobank imaging sub-study, we tested the hypothesis that early signs of liver disease (measured by iron corrected T1-mapping (cT1)) is associated with an increased risk of major cardiovascular events.MethodsLiver disease activity (cT1) and fat (PDFF) were measured using LiverMultiScan® from images acquired between January-2016 and February-2020 in the UK Biobank imaging sub-study. Multivariable Cox regression was used to explore associations between liver cT1 (MRI) andprimary CVD outcomes(coronary artery disease, atrial fibrillation, embolism/vascular events, heart failure and stroke), as well as CVDhospitalisationandall-cause mortality. Other liver blood biomarkers (AST, ALT, AST/ALT ratio, FIB4), general metabolism biomarkers (CRP, HbA1c, systolic blood pressure (SBP), total cholesterol), and demographics were also included. Subgroup analysis was conducted in those without metabolic syndrome (MetS= at least 3 of these traits: a large waist, high triglycerides, low HDL cholesterol, increased SBP, or elevated HbA1c)Results33,616 participants in the UK Biobank imaging sub-study (65 years, mean BMI 26kg/m2, mean HbA1c 35mmol/mol) had complete MRI liver data with linked clinical outcomes [median time to major CVD event onset: 1.4 years (range:0.002-5.1); follow-up: 2.5 years (range:1.1-5.2)]. Liver disease activity (cT1), but not liver fat (PDFF), was associated with a higher risk of any major CVD event [HR(CI) 1.14(1.03-1.26), p=0.008], AF [1.30 (1.12-1.5), pConclusionLiver disease activity, as measured with MRI-derived biomarker cT1, was independently associated with a higher risk of new onset CVD events and all-cause mortality. This association occurred even without pre-existing impairment of metabolic health and was independent of FIB4 or liver fat content. cT1 was identified as a major predictor of adverse CVD outcomes.

Elevated vascular disease risk associates with poorer cognitive function, but the mechanism for this link is poorly understood. A leading theory, the structural-functional model argues that vascular risk may drive adverse cardiac remodelling, which in turn leads to chronic cerebral hypoperfusion and subsequent brain structural damage. This model predicts that variation in heart and brain structure should associate with both greater vascular risk and lower cognitive function. This study tests that prediction in a large sample of the UK Biobank (N=11,962). We assemble and summarise vascular risk factors, cardiac magnetic resonance radiomics, brain structural and diffusion MRI indices, and cognitive assessment. We also extract ‘heart-brain axes’ capturing the covariation in heart and brain structure. Many heart and brain measures partially explain the vascular risk – cognitive function association, like left ventricular end-diastolic volume and grey matter volume. Notably, a heart-brain axis, capturing correlation between lower myocardial intensity, lower grey matter volume, and poorer thalamic white matter integrity, completely mediates the association, supporting the structural-functional model. Our findings also complicate this theory by finding that brain structural variation cannot completely explain the heart structure – cognitive function association. Our results broadly offer evidence for the structural functional hypothesis, identify imaging biomarkers for this association by considering covariation in heart and brain structure, and generate novel hypotheses about how cardiovascular risk may link to cognitive function.

Background Coronavirus disease 2019 (COVID-19) disproportionately affects older people. Observational studies suggest indolent cardiovascular involvement after recovery from acute COVID-19. However, these findings may reflect pre-existing cardiac phenotypes. Aims We tested the association of baseline cardiovascular magnetic resonance (CMR) phenotypes with incident COVID-19. Methods We studied UK Biobank participants with CMR imaging and COVID-19 testing. We considered left and right ventricular (LV, RV) volumes, ejection fractions, and stroke volumes, LV mass, LV strain, native T1, aortic distensibility, and arterial stiffness index. COVID-19 test results were obtained from Public Health England. Co-morbidities were ascertained from self-report and hospital episode statistics (HES). Critical care admission and death were from HES and death register records. We investigated the association of each cardiovascular measure with COVID-19 test result in multivariable logistic regression models adjusting for age, sex, ethnicity, deprivation, body mass index, smoking, diabetes, hypertension, high cholesterol, and prior myocardial infarction. Results We studied 310 participants (n = 70 positive). Median age was 63.8 [57.5, 72.1] years; 51.0% (n = 158) were male. 78.7% (n = 244) were tested in hospital, 3.5% (n = 11) required critical care admission, and 6.1% (n = 19) died. In fully adjusted models, smaller LV/RV end-diastolic volumes, smaller LV stroke volume, and poorer global longitudinal strain were associated with significantly higher odds of COVID-19 positivity. Discussion We demonstrate association of pre-existing adverse CMR phenotypes with greater odds of COVID-19 positivity independent of classical cardiovascular risk factors. Conclusions Observational reports of cardiovascular involvement after COVID-19 may, at least partly, reflect pre-existing cardiac status rather than COVID-19 induced alterations.

Background We examined whether the greater severity of coronavirus disease 2019 (COVID-19) amongst men and Black, Asian and Minority Ethnic (BAME) individuals is explained by cardiometabolic, socio-economic or behavioural factors. Methods We studied 4510 UK Biobank participants tested for COVID-19 (positive, n = 1326). Multivariate logistic regression models including age, sex and ethnicity were used to test whether addition of (1) cardiometabolic factors [diabetes, hypertension, high cholesterol, prior myocardial infarction, smoking and body mass index (BMI)]; (2) 25(OH)-vitamin D; (3) poor diet; (4) Townsend deprivation score; (5) housing (home type, overcrowding) or (6) behavioural factors (sociability, risk taking) attenuated sex/ethnicity associations with COVID-19 status. Results There was over-representation of men and BAME ethnicities in the COVID-19 positive group. BAME individuals had, on average, poorer cardiometabolic profile, lower 25(OH)-vitamin D, greater material deprivation, and were more likely to live in larger households and in flats/apartments. Male sex, BAME ethnicity, higher BMI, higher Townsend deprivation score and household overcrowding were independently associated with significantly greater odds of COVID-19. The pattern of association was consistent for men and women; cardiometabolic, socio-demographic and behavioural factors did not attenuate sex/ethnicity associations. Conclusions In this study, sex and ethnicity differential pattern of COVID-19 was not adequately explained by variations in cardiometabolic factors, 25(OH)-vitamin D levels or socio-economic factors. Factors which underlie ethnic differences in COVID-19 may not be easily captured, and so investigation of alternative biological and genetic susceptibilities as well as more comprehensive assessment of the complex economic, social and behavioural differences should be prioritised.

Objectives Evaluation of the feasibility of using cardiovascular magnetic resonance (CMR) radiomics in the prediction of incident atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), and stroke using machine learning techniques. Methods We identified participants from the UK Biobank who experienced incident AF, HF, MI, or stroke during the continuous longitudinal follow-up. The CMR indices and the vascular risk factors (VRFs) as well as the CMR images were obtained for each participant. Three-segmented regions of interest (ROIs) were computed: right ventricle cavity, left ventricle (LV) cavity, and LV myocardium in end-systole and end-diastole phases. Radiomics features were extracted from the 3D volumes of the ROIs. Seven integrative models were built for each incident cardiovascular disease (CVD) as an outcome. Each model was built with VRF, CMR indices, and radiomics features and a combination of them. Support vector machine was used for classification. To assess the model performance, the accuracy, sensitivity, specificity, and AUC were reported. Results AF prediction model using the VRF+CMR+Rad model (accuracy: 0.71, AUC 0.76) obtained the best result. However, the AUC was similar to the VRF+Rad model. HF showed the most significant improvement with the inclusion of CMR metrics (VRF+CMR+Rad: 0.79, AUC 0.84). Moreover, adding only the radiomics features to the VRF reached an almost similarly good performance (VRF+Rad: accuracy 0.77, AUC 0.83). Prediction models looking into incident MI and stroke reached slightly smaller improvement. Conclusions Radiomics features may provide incremental predictive value over VRF and CMR indices in the prediction of incident CVDs. Key Points • Prediction of incident atrial fibrillation, heart failure, stroke, and myocardial infarction using machine learning techniques. • CMR radiomics, vascular risk factors, and standard CMR indices will be considered in the machine learning models. • The experiments show that radiomics features can provide incremental predictive value over VRF and CMR indices in the prediction of incident cardiovascular diseases.

ObjectivesTo evaluate incident cardiovascular outcomes and imaging phenotypes in UK Biobank participants with previous cancer.MethodsCancer and cardiovascular disease (CVD) diagnoses were ascertained using health record linkage. Participants with cancer history (breast, lung, prostate, colorectal, uterus, haematological) were propensity matched on vascular risk factors to non-cancer controls. Competing risk regression was used to calculate subdistribution HRs (SHRs) for associations of cancer history with incident CVD (ischaemic heart disease (IHD), non-ischaemic cardiomyopathy (NICM), heart failure (HF), atrial fibrillation/flutter, stroke, pericarditis, venous thromboembolism (VTE)) and mortality outcomes (any CVD, IHD, HF/NICM, stroke, hypertensive disease) over 11.8±1.7 years of prospective follow-up. Linear regression was used to assess associations of cancer history with left ventricular (LV) and left atrial metrics.ResultsWe studied 18 714 participants (67% women, age: 62 (IQR: 57–66) years, 97% white ethnicities) with cancer history, including 1354 individuals with cardiovascular magnetic resonance. Participants with cancer had high burden of vascular risk factors and prevalent CVDs. Haematological cancer was associated with increased risk of all incident CVDs considered (SHRs: 1.92–3.56), larger chamber volumes, lower ejection fractions, and poorer LV strain. Breast cancer was associated with increased risk of selected CVDs (NICM, HF, pericarditis and VTE; SHRs: 1.34–2.03), HF/NICM death, hypertensive disease death, lower LV ejection fraction, and lower LV global function index. Lung cancer was associated with increased risk of pericarditis, HF, and CVD death. Prostate cancer was linked to increased VTE risk.ConclusionsCancer history is linked to increased risk of incident CVDs and adverse cardiac remodelling independent of shared vascular risk factors.

ObjectiveTo examine associations of birth weight with clinical and imaging indicators of cardiovascular health and evaluate mechanistic pathways in the UK Biobank.MethodsCompeting risk regression was used to estimate associations of birth weight with incident myocardial infarction (MI) and mortality (all-cause, cardiovascular disease, ischaemic heart disease, MI), over 7–12 years of longitudinal follow-up, adjusting for age, sex, deprivation, maternal smoking/hypertension and maternal/paternal diabetes. Mediation analysis was used to evaluate the role of childhood growth, adulthood obesity, cardiometabolic diseases and blood biomarkers in mediating the birth weight–MI relationship. Linear regression was used to estimate associations of birth weight with left ventricular (LV) mass-to-volume ratio, LV stroke volume, global longitudinal strain, LV global function index and left atrial ejection fraction.Results258 787 participants from white ethnicities (61% women, median age 56 (49, 62) years) were studied. Birth weight had a non-linear relationship with incident MI, with a significant inverse association below an optimal threshold of 3.2 kg (subdistribution HR: 1.15 (1.08 to 1.22), p=6.0×10–5) and attenuation to the null above this threshold. The birth weight–MI effect was mediated through hypertension (8.4%), glycated haemoglobin (7.0%), C reactive protein (6.4%), high-density lipoprotein (5.2%) and high cholesterol (4.1%). Birth weight–mortality associations were statistically non-significant after Bonferroni correction. In participants with cardiovascular magnetic resonance (n=19 314), lower birth weight was associated with adverse LV remodelling (greater concentricity, poorer function).ConclusionsLower birth weight was associated with greater risk of incident MI and unhealthy LV phenotypes; effects were partially mediated through cardiometabolic disease and systemic inflammation. These findings support consideration of birth weight in risk prediction and highlight actionable areas for disease prevention.

Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): British Heart Foundation Clinical Research Training Fellowship No. FS/17/81/33318 European Union’s Horizon 2020 research and innovation programme under grant agreement No 825903 (euCanSHare project). Background Multiple epidemiological studies link greater red and processed meat consumption with poorer cardiovascular outcomes. However, the impact of these exposures on directly measured cardiovascular phenotypes has not been examined in large cohorts. Limited existing studies suggest that the observed associations may be mediated by cardiometabolic diseases and/or novel mechanisms acting via the heart-gut axes. However, few studies systematically examine potential confounding and mediating mechanisms. Purpose We assessed, in the UK Biobank, the association between meat intake and cardiovascular structure and function incorporating a comprehensive range of confounders and mediators. Methods We studied 19,408 participants with cardiovascular magnetic resonance (CMR) data. We determined average daily red and processed meat intake using food frequency questionnaires. We used oily fish as a comparator linked to favourable cardiac health. We considered conventional CMR measures (ventricular volumes, left ventricular mass, ejection fraction, stroke volume), novel CMR radiomics features (shape, texture), and arterial stiffness metrics (arterial stiffness index, aortic distensibility). Multivariable linear regression models were used to investigate associations between meat/fish intake and cardiovascular phenotypes, adjusting for age, sex, deprivation, educational level, smoking, alcohol intake, and exercise. In separate models, we investigated the mediating role of cardiometabolic morbidities. Results Higher intake of red and processed meat was associated with an adverse overall pattern of right and left ventricular remodelling, poorer cardiac function, and higher arterial stiffness. Conversely, higher oily fish intake was associated with a healthy cardiovascular phenotype (better ventricular function, greater arterial compliance). Radiomics analysis showed association of the different dietary habits with unique overall geometry of the ventricles and myocardial texture. These associations were partially mediated by cardiometabolic morbidities. Conclusions Higher red and processed meat consumption is associated with adverse cardiovascular phenotypes. These relationships are not fully explained by mediation through cardiometabolic morbidities suggesting importance of alternative disease pathways. Understanding these potential novel disease mechanisms is important for optimising cardiovascular disease prevention strategies.

BackgroundWe examined whether the greater severity of coronavirus disease 2019 (COVID-19) amongst men and non-White ethnicities is explained by cardiometabolic, socio-economic, or behavioural factors.MethodsWe studied 4,510 UK Biobank participants tested for COVID-19 (positive, n = 1,326). Multivariate logistic regression models including age, sex, and ethnicity were used to test whether addition of: 1)cardiometabolic factors (diabetes, hypertension, high cholesterol, prior myocardial infarction, smoking, BMI); 2)25(OH)-vitamin D; 3)poor diet; 4)Townsend deprivation score; 5)housing (home type, overcrowding); or 6)behavioural factors (sociability, risk taking) attenuated sex/ethnicity associations with COVID-19 status.ResultsThere was over-representation of men and non-White ethnicities in the COVID-19 positive group. Non-Whites had, on average, poorer cardiometabolic profile, lower 25(OH)-vitamin D, greater material deprivation, and were more likely to live in larger households and flats/apartments. Male sex, non-White ethnicity, higher BMI, Townsend deprivation score, and household overcrowding were independently associated with significantly greater odds of COVID-19. The pattern of association was consistent for men and women; cardiometabolic, socio-demographic and behavioural factors did not attenuate sex/ethnicity associations.ConclusionsSex and ethnicity differential pattern of COVID-19 is not adequately explained by variations in cardiometabolic factors, 25(OH)-vitamin D levels, or socio-economic factors. Investigation of alternative biological pathways and different genetic susceptibilities is warranted.

Background: Cardiometabolic morbidity and medications, specifically Angiotensin Converting Enzyme inhibitors (ACEi) and Angiotensin Receptor Blockers (ARBs), have been linked with adverse outcomes from coronavirus disease 2019 (COVID-19). This study aims to investigate factors associated with COVID-19 positivity for the first 669 UK Biobank participants; compared with individuals who tested negative, and with the untested, presumed negative, rest of the population. Methods: We studied 1,474 participants from the UK Biobank who had been tested for COVID-19. Given UK testing policy, this implies a hospital setting, suggesting at least moderate to severe symptoms. We considered the following exposures: age, sex, ethnicity, body mass index (BMI), diabetes, hypertension, hypercholesterolaemia, ACEi/ARB use, prior myocardial infarction (MI), and smoking. We undertook comparisons between: 1) COVID-19 positive and COVID-19 tested negative participants; and 2) COVID-19 tested positive and the remaining participants (tested negative plus untested, n=501,837). Logistic regression models were used to investigate univariate and mutually adjusted associations. Results: Among participants tested for COVID-19, non-white ethnicity, male sex, and greater BMI were independently associated with COVID-19 positive result. Non-white ethnicity, male sex, greater BMI, diabetes, hypertension, prior MI, and smoking were independently associated with COVID-19 positivity compared to the remining cohort (test negatives plus untested). However, similar associations were observed when comparing those who tested negative for COVID-19 with the untested cohort; suggesting that these factors associate with general hospitalisation rather than specifically with COVID-19. Conclusions: Among participants tested for COVID-19 with presumed moderate to severe symptoms in a hospital setting, non-white ethnicity, male sex, and higher BMI are associated with a positive result. Other cardiometabolic morbidities confer increased risk of hospitalisation, without specificity for COVID-19. Notably, ACE/ARB use did not associate with COVID-19 status.