Associations of Combined Genetic and Lifestyle Risks With Incident Cardiovascular Disease and Diabetes in the UK Biobank Study

Said, M. Abdullah; Verweij, Niek; Harst, Pim van der

doi:10.1001/jamacardio.2018.1717

Cited by 409 publications

(311 citation statements)

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“…Cox regression analysis was performed to investigate the association between different sedentary behaviours and new-onset CAD events. CAD was defined based on ICD-9 and ICD-10 codes, together with operation codes and self-reported data on myocardial infarction, other ischaemic heart disease and history of coronary artery bypass grafting or percutaneous coronary intervention as performed previously 44 . Three Cox regression models were used to investigate the association of leisure sedentary television watching, leisure computer use and driving with CAD; potential confounders were selected per prior epidemiological analyses 8 .…”

Section: Methodsmentioning

confidence: 99%

“…Smoking status was defined as ideal (never smoked or quit >12 months ago), intermediate (quit smoking ≤12 months ago) or poor (current smoker). Physical activity was based on questionnaires concerning do-ityourself and exercise activities using guidelines for ideal cardiovascular health and according to previous research 44 . In short, physical activity was defined as ideal if participants had ≥150 min/week moderate or ≥75 min/week vigorous or 150 min/ week mixed (moderate and vigorous) activity.…”

Section: Methodsmentioning

confidence: 99%

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Genome-wide association studies and Mendelian randomization analyses for leisure sedentary behaviours

et al. 2020

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Leisure sedentary behaviours are associated with increased risk of cardiovascular disease, but whether this relationship is causal is unknown. The aim of this study is to identify genetic determinants associated with leisure sedentary behaviours and to estimate the potential causal effect on coronary artery disease (CAD). Genome wide association analyses of leisure television watching, leisure computer use and driving behaviour in the UK Biobank identify 145, 36 and 4 genetic loci (P < 1×10 −8 ), respectively. High genetic correlations are observed between sedentary behaviours and neurological traits, including education and body mass index (BMI). Two-sample Mendelian randomization (MR) analysis estimates a causal effect between 1.5 hour increase in television watching and CAD (OR 1.44, 95%CI 1.25-1.66, P = 5.63 × 10 −07 ), that is partially independent of education and BMI in multivariable MR analyses. This study finds independent observational and genetic support for the hypothesis that increased sedentary behaviour by leisure television watching is a risk factor for CAD.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Genome-wide association studies and Mendelian randomization analyses for leisure sedentary behaviours

et al. 2020

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“…Previous studies have shown that age, male sex, hypertension, DM, valvular heart disease, heart failure, coronary artery disease, CKD, in ammatory disease, obstructive sleep apnoea syndrome and smoking are common risk factors for AF and ischaemic stroke [9,11,12]. Potential risk factors, such as obesity and metabolic syndrome, contribute to the development of AF and atrial cardiomyopathy through a variety of mechanisms [13]. The Framingham Heart Study [14] pointed out that the lifetime risk of AF was approximately 20% with an optimal risk pro le, lower than that with a high-risk pro le (38.4%).…”

Section: Discussionmentioning

confidence: 99%

Relationship Among Atrial Fibrillation, CHADS2 Score and Ischaemic Stroke in Patients With Coronary Artery Disease: A Propensity Score Matching Study

Shi

Liu

Wang

et al. 2020

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Objective: The purpose of this study was to investigate the relationship among atrial fibrillation (AF), CHADS2 score and ischaemic stroke in patients with coronary artery disease.Methods: A total of 2335 patients with coronary artery disease were included. They were divided into a nonischaemic stroke group (n=1997) and an ischaemic stroke group (n=388). Propensity score matching (PSM) was used to match ischaemic stroke patients with nonischaemic stroke patients in a 1:4 ratio. The relationship between AF, CHADS2 score and ischaemic stroke was evaluated using a univariate generalized linear model in different age, body mass index, and coronary artery disease subgroups. Univariate and multivariate generalized linear models were used to evaluate the relationship between AF and ischaemic stroke in different models.Results: Compared with the nonischaemic stroke group, the rate of AF (8.81% vs. 14.20%, P=0.002) in the ischaemic stroke group was higher. The proportion of patients with ischaemic stroke was significantly different between the AF group and the non-AF group (19.04% vs. 28.74%, P=0.003). With increasing CHADS2 score, the incidence of AF gradually increased (P for trend <0.001). With increasing AF burden, the rate of ischaemic stroke increased continuously (P for trend <0.001). Subgroup analysis showed that the trend towards increased stroke risk in the AF group was consistent across the various subgroups. Multivariate analysis demonstrated that paroxysmal and nonparoxysmal AF were not associated with ischaemic stroke compared with the absence of AF.Conclusion: After adjusting for confounding factors, the correlation between AF and ischaemic stroke decreased. Atherosclerotic factors may play an important role in ischaemic stroke in patients with coronary heart disease.

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“…1 In order to improve established risk scores, a detailed battery of questionnaires, genetics, biochemical analyses and imaging is currently applied in large cohorts involving 200,000 individuals (German National Cohort) 20 or in the UK Biobank Study involving >500,000 individuals. 21,22 This will certainly improve the definition of individual risk beyond the established cardiovascular risk factors and first results have been presented. [21][22][23] However, importantly, this knowledge will have to be integrated into lifestyle preventive strategies.…”

mentioning

confidence: 99%

“…21,22 This will certainly improve the definition of individual risk beyond the established cardiovascular risk factors and first results have been presented. [21][22][23] However, importantly, this knowledge will have to be integrated into lifestyle preventive strategies. Characterization of ''basic'' biomarkers with prognostic potential to predict high-risk patients will have to be added by the identification of ''modifiable biomarkers'', which characteristically change by intervention strategies and predict efficacy of intervention.…”

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confidence: 99%

Research in preventive cardiology: Quo vadis?

Halle

2020

Eur J Prev Cardiolog

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In the current position statement of the European Association of Preventive Cardiology of the European Society of Cardiology, 1 Massimo Piepoli et al. update the 2016 practice guidelines on primary prevention. 2 Recently, the American Heart Association and American College of Cardiology have also revised their primary prevention guidelines, 3,4 which emphasizes increasing importance and awareness of the topic of preventive cardiology, worldwide. However, despite the ubiquitous expert opinion of the key cardio-protective effects of a healthy lifestyle characterized by healthy nutrition (e.g. polyunsaturated fatty acids, vegetables, legumes, low content of salt and saturated fatty acids), non-smoking, maintaining a normal body weight (body mass index between 20 and 25 kg/m 2), low alcohol consumption and daily physical activity (30 min of moderate physical activity), 1,4-6 clinical research remains rather scarce, particularly with respect to randomized controlled intervention trials. So far, most data supporting the beneficial effects of a healthy lifestyle on cardiovascular disease have been retrieved from epidemiological cohort studies, 7-13 whereas numbers of large randomized controlled trials in preventive medicine confirming epidemiological hypotheses are low and significantly less compared to pharmacological intervention trials. Most of the intervention studies on the effects of lifestyle intervention are proof of concept studies involving less than 500 patients. Larger intervention trials enrolling more than 1000 individuals or patients, numbers comparable to pharmacological studies in cardiology, are very limited and confined to three trials overallthe Diabetes Prevention Program in Prediabetes (Diabetes Prevention Program, n ¼ 3234 overweight, prediabetic individuals randomized to metformin, lifestyle or usual care, follow-up 2.8 years) 14 ; the Look AHEAD (Action for Health in Diabetes) trial in type 2 diabetes (n ¼ 5145 overweight type 2 diabetes patients, randomized to lifestyle or usual care, 10-year followup) 15 ; and the HF ACTION (Heart Failure and A Controlled Trial Investigating Outcomes of exercise traiNing trial) (n ¼ 2331, exercise training versus usual care, three-year follow-up) 16 in patients with heart

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Associations of Combined Genetic and Lifestyle Risks With Incident Cardiovascular Disease and Diabetes in the UK Biobank Study

Cited by 409 publications

References 48 publications

Genome-wide association studies and Mendelian randomization analyses for leisure sedentary behaviours

Genome-wide association studies and Mendelian randomization analyses for leisure sedentary behaviours

Relationship Among Atrial Fibrillation, CHADS2 Score and Ischaemic Stroke in Patients With Coronary Artery Disease: A Propensity Score Matching Study

Research in preventive cardiology: Quo vadis?

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