scholarly journals Characterization of the human ABO genotypes and their association to common inflammatory and cardiovascular disease in the UK Biobank

2021 ◽  
Author(s):  
Julia Höglund ◽  
Torgny Karlsson ◽  
Therese Johansson ◽  
Weronica E. Ek ◽  
Åsa Johansson
Keyword(s):  
Cardiovascular Disease ◽  
Uk Biobank ◽  
The Uk ◽  
Abo Genotypes

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 >400,000 participants were used as training set and >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 >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 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.

Association of Lichen Planus with Cardiovascular Disease: A Combined Analysis in the UK Biobank and All of Us Study

2021 ◽  
Author(s):  
Audrey C. Leasure ◽  
Julian N. Acosta ◽  
Lauren H. Sansing ◽  
Kevin N. Sheth ◽  
Jeffrey M. Cohen ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Lichen Planus ◽  
Uk Biobank ◽  
Combined Analysis ◽  
The Uk

scholarly journals Associations of discretionary screen time with mortality, cardiovascular disease and cancer are attenuated by strength, fitness and physical activity: findings from the UK Biobank study

BMC Medicine ◽  
2018 ◽  
Vol 16 (1) ◽  
Author(s):  
Carlos A. Celis-Morales ◽  
Donald M. Lyall ◽  
Lewis Steell ◽  
Stuart R. Gray ◽  
Stamatina Iliodromiti ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cardiovascular Disease ◽  
Screen Time ◽  
Uk Biobank ◽  
The Uk

scholarly journals Phenotypic and genetic characterization of lower LDL-C and increased type-2 diabetes risk in the UK Biobank

2020 ◽  
Author(s):  
Ada Admin ◽  
Yann C. Klimentidis ◽  
Amit Arora ◽  
Michelle Newell ◽  
Jin Zhou ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Uk Biobank ◽  
Alcoholic Fatty Liver ◽  
Genome Wide ◽  
Using Data ◽  
Underlying Mechanisms ◽  
Phenotypic And Genetic Characterization ◽  
The Uk

Although hyperlipidemia is traditionally considered a risk factor for type-2 diabetes (T2D), evidence has emerged from statin trials and candidate gene investigations suggesting that lower LDL-C increases T2D risk. We thus sought to more comprehensively examine the phenotypic and genotypic relationships of LDL-C with T2D. Using data from the UK Biobank, we found that levels of circulating LDL-C were negatively associated with T2D prevalence (OR=0.41[0.39, 0.43] per mmol/L unit of LDL-C), despite positive associations of circulating LDL-C with HbA1c and BMI. We then performed the first genome-wide exploration of variants simultaneously associated with lower circulating LDL-C and increased T2D risk, using data on LDL-C from the UK Biobank (n=431,167) and the GLGC consortium (n=188,577), and T2D from the DIAGRAM consortium (n=898,130). We identified 31 loci associated with lower circulating LDL-C and increased T2D, capturing several potential mechanisms. Seven of these loci have previously been identified for this dual phenotype, and 9 have previously been implicated in non-alcoholic fatty liver disease. These findings extend our current understanding of the higher T2D risk among individuals with low circulating LDL-C, and of the underlying mechanisms, including those responsible for the diabetogenic effect of LDL-C-lowering medications.

scholarly journals Rare Genetic Variation Underlying Human Diseases and Traits: Results from 200,000 Individuals in the UK Biobank

2020 ◽  
Author(s):  
Sean J. Jurgens ◽  
Seung Hoan Choi ◽  
Valerie N. Morrill ◽  
Mark Chaffin ◽  
James P. Pirruccello ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Genetic Variation ◽  
Exome Sequencing ◽  
Human Diseases ◽  
Disease Genes ◽  
Uk Biobank ◽  
Novel Genes ◽  
Pathogenic Variants ◽  
Rare Genetic Variation ◽  
The Uk

AbstractBackgroundMany human diseases are known to have a genetic contribution. While genome-wide studies have identified many disease-associated loci, it remains challenging to elucidate causal genes. In contrast, exome sequencing provides an opportunity to identify new disease genes and large-effect variants of clinical relevance. We therefore sought to determine the contribution of rare genetic variation in a curated set of human diseases and traits using a unique resource of 200,000 individuals with exome sequencing data from the UK Biobank.Methods and ResultsWe included 199,832 participants with a mean age of 68 at follow-up. Exome-wide gene-based tests were performed for 64 diseases and 23 quantitative traits using a mixed-effects model, testing rare loss-of-function and damaging missense variants. We identified 51 known and 23 novel associations with 26 diseases and traits at a false-discovery-rate of 1%. There was a striking risk associated with many Mendelian disease genes including: MYPBC3 with over a 100-fold increased odds of hypertrophic cardiomyopathy, PKD1 with a greater than 25-fold increased odds of chronic kidney disease, and BRCA2, BRCA1, ATM and PALB2 with 3 to 10-fold increased odds of breast cancer. Notable novel findings included an association between GIGYF1 and type 2 diabetes (OR 5.6, P=5.35×10−8), elevated blood glucose, and lower insulin-like-growth-factor-1 levels. Rare variants in CCAR2 were also associated with diabetes risk (OR 13, P=8.5×10−8), while COL9A3 was associated with cataract (OR 3.4, P=6.7×10−8). Notable associations for blood lipids and hypercholesterolemia included NR1H3, RRBP1, GIGYF1, SCGN, APH1A, PDE3B and ANGPTL8. A number of novel genes were associated with height, including DTL, PIEZO1, SCUBE3, PAPPA and ADAMTS6, while BSN was associated with body-mass-index. We further assessed putatively pathogenic variants in known Mendelian cardiovascular disease genes and found that between 1.3 and 2.3% of the population carried likely pathogenic variants in known cardiomyopathy, arrhythmia or hypercholesterolemia genes.ConclusionsLarge-scale population sequencing identifies known and novel genes harboring high-impact variation for human traits and diseases. A number of novel findings, including GIGYF1,represent interesting potential therapeutic targets. Exome sequencing at scale can identify a meaningful proportion of the population that carries a pathogenic variant underlying cardiovascular disease.

scholarly journals Transthyretin-stabilizing mutation T119M is not associated with protection against vascular disease or death in the UK Biobank

2019 ◽  
Author(s):  
Margaret M. Parker ◽  
Simina Ticau ◽  
James Butler ◽  
David Erbe ◽  
Madeline Merkel ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Cerebrovascular Disease ◽  
Vascular Disease ◽  
Prospective Cohort ◽  
Proportional Hazards ◽  
Disease Diagnosis ◽  
Cox Proportional Hazards ◽  
Uk Biobank ◽  
The Uk ◽  
Large Prospective Cohort

AbstractBackgroundDestabilized transthyretin (TTR) can result in the progressive, fatal disease transthyretin-mediated (ATTR) amyloidosis. A stabilizing TTR mutation, T119M, is the basis for a therapeutic strategy to reduce destabilized TTR. Recently, T119M was associated with extended lifespan and lower risk of cerebrovascular disease in a Danish cohort. We aimed to determine whether this finding could be replicated in the UK Biobank.MethodsTTR T119M carriers were identified in the UK Biobank, a large prospective cohort of ∼500,000 individuals. Association between T119M genotype and inpatient diagnosis of vascular disease, cardiovascular disease, cerebrovascular disease, and mortality was analyzed.ResultsFrequency of T119M within the white UK Biobank population (n=337,148) was 0.4%. Logistic regression comparing T119M carriers to non-carriers found no association between T119M and vascular disease (odds ratio [OR]=1.08; p=.27), cardiovascular disease (OR=1.08; p=.31), cerebrovascular disease (OR=1.1; p=.42), or death (OR=1.2; p=.06). Cox proportional hazards regression showed similar results (hazard ratio>1, p>.05). Age at death and vascular disease diagnosis were similar between T119M carriers and non-carriers (p=.12 and p=.38, respectively).ConclusionsThere was no association between the TTR T119M genotype and risk of vascular disease or death in a large prospective cohort study, indicating that TTR tetramer stabilization through T119M is not protective in this setting.

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