Genetic risk, incident stroke, and the benefits of adhering to a healthy lifestyle: cohort study of 306 473 UK Biobank participants

Rutten-Jacobs, Loes C.A.; Larsson, Susanna C.; Malik, Rainer; Rannikmäe, Kristiina; Sudlow, Cathie; Dichgans, Martin; Markus, Hugh S.; Traylor, Matthew

doi:10.1136/bmj.k4168

Cited by 206 publications

(210 citation statements)

References 32 publications

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“…Recent work has highlighted the potential of genomic risk scores (GRS) for risk prediction of common diseases [21][22][23][24] . Genomic risk prediction has a notable advantage over established risk factors as it could be used to infer risk of disease from birth, thus allowing the initiation of preventive strategies before conventional risk factors manifest and their discriminative capacity begins to emerge.…”

Section: Introductionmentioning

confidence: 99%

“…For stroke, a recent 90-SNP GRS derived from the MEGASTROKE GWAS metaanalysis 4 showed that genetic and lifestyle factors are independently associated with incident stroke 24 , and that even among individuals with high GRS, lifestyle factors had a large impact on risk, implying that risk could be reduced in those with high genetic predisposition for stroke. However, in contrast to GRSs for other cardiovascular diseases like coronary artery disease (CAD) [21][22][23] , the predictive power of previous GRS for stroke has been limited [25][26][27] , likely because of limited genetic data for stroke and the well-known heterogeneity of the stroke phenotype 4,7 .…”

Section: Introductionmentioning

confidence: 99%

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Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke

Abraham

Malik

Yonova-Doing

et al. 2019

Preprint

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Recent genome-wide association studies in stroke have enabled the generation of genomic risk scores (GRS) but the predictive power of these GRS has been modest in comparison to established stroke risk factors. Here, using a meta-scoring approach, we developed a metaGRS for ischaemic stroke (IS) and analysed this score in the UK Biobank (n=395,393; 3075 IS events by age 75). The metaGRS hazard ratio for IS (1.26, 95% CI 1.22-1.31 per standard deviation increase of the score) doubled that of previous GRS, enabling the identification of a subset of individuals at monogenic levels of risk: individuals in the top 0.25% of metaGRS had a three-fold increased risk of IS. The metaGRS was similarly or more predictive when compared to established risk factors, such as family history, blood pressure, body mass index and smoking status. For participants within accepted guideline levels for established stroke risk factors, we found substantial variation in incident stroke rates across genomic risk backgrounds. We further estimated combinations of reductions needed in modifiable risk factors for individuals with different levels of genomic risk and suggest that, for individuals with high metaGRS, achieving currently recommended risk factor levels may be insufficient to mitigate risk.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke

Abraham

Malik

Yonova-Doing

et al. 2019

Preprint

Self Cite

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“…The whole-genome approach to G-C interaction also sets this study apart from G-C interaction studies using a candidate gene approach which only focused on genetic variants with large phenotypic effects (e.g. [13][14][15] ). In these studies, variants might be missed if they contribute to GxE interaction and their effects depend on lifestyle factors.…”

Section: Discussionmentioning

confidence: 99%

“…To date, G-C interaction estimates for cardiovascular traits are based on a limited number of genetic variants [13][14][15][16][17][18][19][20] ; therefore they are likely underestimated. R-C interaction has been largely neglected, leading to potential confounding between G-C and R-C interactions, in the presence of genuine R-C interaction 10 .…”

Section: Introductionmentioning

confidence: 99%

A Whole-Genome Approach Discovers Novel Genetic and Non-Genetic Variance Components Modulated by Lifestyle for Cardiovascular Health

Zhou

Werf

Carson‐Chahhoud

et al. 2019

Preprint

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Both genetic and non-genetic factors can predispose individuals to cardiovascular risk. Finding ways to alter these predispositions is important for cardiovascular disease (CVD) prevention. Here, we use a novel whole-genome framework to estimate genetic and non-genetic effects on-hence their predispositions to-cardiovascular risk and determine whether they vary with respect to lifestyle factors. We performed analyses on the Atherosclerosis Risk in Communities Study (ARIC, N=6,180) and validated findings using the UK Biobank (UKBB, N=14,076-34,538). Cardiovascular risk was measured using 23 traits in the ARIC and eight traits in the UKBB, such as body mass index (BMI), resting heart rate, white blood cell count and blood pressure; and lifestyle factors included information on physical activity, smoking, alcohol consumption and dietary intake. Physical activity altered both genetic and non-genetic effects on heart rate and BMI, genetic effects on HDL cholesterol level, and nongenetic effects on waist-to-hip ratio. Alcohol consumption altered both genetic and non-genetic effects on BMI, while smoking altered non-genetic effects on heart rate, pulse pressure, and white blood cell count. In addition, saturated fat intake modified genetic effects on BMI, and total daily energy intake modified non-genetic effects on waist-to-hip ratio. These results highlight the relevance of lifestyle changes for CVD prevention. We also stratified individuals according to their genetic predispositions and showed notable differences in the effects of lifestyle on cardiovascular risk across stratified groups, implying the need for individualizing lifestyle changes for CVD prevention. Finally, we showed that neglecting lifestyle modulation of genetic and nongenetic effects will on average reduce SNP heritability estimates of cardiovascular traits by a small yet significant amount, primarily owing to overestimation of residual variance. Thus, current SNP heritability estimates for cardiovascular traits, which commonly do not consider modulating effects of lifestyle covariates, are likely underestimated.

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“…Excessive alcohol use, smoking, and lack of physical activity are typical risk factors of lifestyle, which may contribute to adiposity, fatty deposition in the liver and increased all-cause mortality [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Combined Effects of Lifestyle Risk Factors on Fatty Liver Index

Nivukoski

Niemelä

Bloigu

et al. 2020

Preprint

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Background: Factors of lifestyle may have a major impact on liver-related morbidity and mortality.We examined independent and joint effects of lifestyle risk factors on fatty liver index (FLI), a biomarker of hepatic steatosis, in a population-based cross-sectional national health survey. Methods:The study included 12,368 participants (5,784 men, 6,584 women) aged 25-74 years.Quantitative estimates of alcohol use, smoking, adiposity and physical activity were used to establish a total score of risk factors, with higher scores indicating an unhealthier lifestyle. FLI was calculated based on an algorithm including body mass index, waist circumference, serum gammaglutamyltransferase and triglycerides. Results:The occurrence of FLI ≥ 60% indicating fatty liver increased from 2.4% in men with zero risk factors to 81.9% in those with a total risk score of 7-8 (p < 0.0005 for linear trend) and in women from 0% to 73.5% (p < 0.0005). The most striking individual impacts on the likelihood for FLI above 60% were observed for physical inactivity (p < 0.0005 for both genders) and alcohol consumption (p < 0.0005 for men). Interestingly, coffee consumption was also found to increase with increasing risk factor scores (p < 0.0005 for linear trend in both genders). Conclusions:The data indicates that unfavorable combinations of lifestyle risk factors lead to a high likelihood of hepatic steatosis. Use of FLI as a diagnostic tool may benefit the assessment of interventions aimed at maintaining a healthy lifestyle and prevention of liver-related morbidity. BackgroundExcessive alcohol use, smoking, and lack of physical activity are typical risk factors of lifestyle, which may contribute to adiposity, fatty deposition in the liver and increased all-cause mortality [1][2][3][4].Furthermore, several risk factors are often present concomitantly in the same individual [5,6]. Recent studies have concluded that simultaneous adherence to multiple healthy lifestyle factors could significantly prolong life expectancy suggesting substantial therapeutic implications for interventions focusing on basic lifestyle factors [1,7,8].In current societies, hepatic steatosis is a highly common manifestation of health problems driven by behavioral factors. Building of too much fat in the liver may lead to a wide variety of clinical

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Genetic risk, incident stroke, and the benefits of adhering to a healthy lifestyle: cohort study of 306 473 UK Biobank participants

Cited by 206 publications

References 32 publications

Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke

Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke

A Whole-Genome Approach Discovers Novel Genetic and Non-Genetic Variance Components Modulated by Lifestyle for Cardiovascular Health

Combined Effects of Lifestyle Risk Factors on Fatty Liver Index

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