scholarly journals Consumption of coffee and tea and risk of developing stroke, dementia, and poststroke dementia: A cohort study in the UK Biobank

PLoS Medicine ◽  
2021 ◽  
Vol 18 (11) ◽  
pp. e1003830
Author(s):  
Yuan Zhang ◽  
Hongxi Yang ◽  
Shu Li ◽  
Wei-dong Li ◽  
Yaogang Wang
Keyword(s):  
Cohort Study ◽  
Lower Risk ◽  
Smoking Status ◽  
Density Lipoprotein ◽  
Tea Consumption ◽  
Uk Biobank ◽  
Daily Consumption ◽  
History Of ◽  
Poststroke Dementia ◽  
The Uk

Background Previous studies have revealed the involvement of coffee and tea in the development of stroke and dementia. However, little is known about the association between the combination of coffee and tea and the risk of stroke, dementia, and poststroke dementia. Therefore, we aimed to investigate the associations of coffee and tea separately and in combination with the risk of developing stroke and dementia. Methods and findings This prospective cohort study included 365,682 participants (50 to 74 years old) from the UK Biobank. Participants joined the study from 2006 to 2010 and were followed up until 2020. We used Cox proportional hazards models to estimate the associations between coffee/tea consumption and incident stroke and dementia, adjusting for sex, age, ethnicity, qualification, income, body mass index (BMI), physical activity, alcohol status, smoking status, diet pattern, consumption of sugar-sweetened beverages, high-density lipoprotein (HDL), low-density lipoprotein (LDL), history of cancer, history of diabetes, history of cardiovascular arterial disease (CAD), and hypertension. Coffee and tea consumption was assessed at baseline. During a median follow-up of 11.4 years for new onset disease, 5,079 participants developed dementia, and 10,053 participants developed stroke. The associations of coffee and tea with stroke and dementia were nonlinear (P for nonlinear <0.01), and coffee intake of 2 to 3 cups/d or tea intake of 3 to 5 cups/d or their combination intake of 4 to 6 cups/d were linked with the lowest hazard ratio (HR) of incident stroke and dementia. Compared with those who did not drink tea and coffee, drinking 2 to 3 cups of coffee and 2 to 3 cups of tea per day was associated with a 32% (HR 0.68, 95% CI, 0.59 to 0.79; P < 0.001) lower risk of stroke and a 28% (HR, 0.72, 95% CI, 0.59 to 0.89; P = 0.002) lower risk of dementia. Moreover, the combination of coffee and tea consumption was associated with lower risk of ischemic stroke and vascular dementia. Additionally, the combination of tea and coffee was associated with a lower risk of poststroke dementia, with the lowest risk of incident poststroke dementia at a daily consumption level of 3 to 6 cups of coffee and tea (HR, 0.52, 95% CI, 0.32 to 0.83; P = 0.007). The main limitations were that coffee and tea intake was self-reported at baseline and may not reflect long-term consumption patterns, unmeasured confounders in observational studies may result in biased effect estimates, and UK Biobank participants are not representative of the whole United Kingdom population. Conclusions We found that drinking coffee and tea separately or in combination were associated with lower risk of stroke and dementia. Intake of coffee alone or in combination with tea was associated with lower risk of poststroke dementia.

Associations of BMI and Serum Urate with Developing Dementia: A Prospective Cohort Study

2020 ◽  
Vol 105 (12) ◽  
pp. e4688-e4698
Author(s):  
Zhi Cao ◽  
Chenjie Xu ◽  
Hongxi Yang ◽  
Shu Li ◽  
Fusheng Xu ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Cohort Study ◽  
Lower Risk ◽  
Serum Urate ◽  
Healthy Weight ◽  
Uk Biobank ◽  
Health Records ◽  
Increased Risk ◽  
The Uk

Abstract Context Recent studies have suggested that a higher body mass index (BMI) and serum urate levels were associated with a lower risk of developing dementia. However, these reverse relationships remain controversial, and whether serum urate and BMI confound each other is not well established. Objectives To investigate the independent associations of BMI and urate, as well as their interaction with the risk of developing dementia. Design and Settings We analyzed a cohort of 502 528 individuals derived from the UK Biobank that included people aged 37–73 years for whom BMI and urate were recorded between 2006 and 2010. Dementia was ascertained at follow-up using electronic health records. Results During a median of 8.1 years of follow-up, a total of 2138 participants developed dementia. People who were underweight had an increased risk of dementia (hazard ratio [HR] = 1.91, 95% confidence interval [CI]: 1.24–2.97) compared with people of a healthy weight. However, the risk of dementia continued to fall as weight increased, as those who were overweight and obese were 19% (HR = 0.81, 95%: 0.73–0.90) and 22% (HR = 0.78, 95% CI: 0.68–0.88) were less likely to develop dementia than people of a healthy weight. People in the highest quintile of urate were also associated with a 25% (HR = 0.75, 95% CI: 0.64–0.87) reduction in the risk of developing dementia compared with those who were in the lowest quintile. There was a significant multiplicative interaction between BMI and urate in relation to dementia (P for interaction = 0.004), and obesity strengthens the protective effect of serum urate on the risk of dementia. Conclusion Both BMI and urate are independent predictors of dementia, and there are inverse monotonic and dose-response associations of BMI and urate with dementia.

scholarly journals Walking pace improves all-cause and cardiovascular mortality risk prediction: A UK Biobank prognostic study

2019 ◽  
Vol 27 (10) ◽  
pp. 1036-1044 ◽  
Author(s):  
Stavroula Argyridou ◽  
Francesco Zaccardi ◽  
Melanie J Davies ◽  
Kamlesh Khunti ◽  
Thomas Yates
Keyword(s):  
Risk Factors ◽  
Risk Prediction ◽  
Cardiovascular Mortality ◽  
Smoking Status ◽  
Density Lipoprotein ◽  
Uk Biobank ◽  
All Cause Mortality ◽  
Lifestyle Measures ◽  
European Society Of Cardiology ◽  
The Uk

Aims The purpose of this study was to quantify and rank the prognostic relevance of dietary, physical activity and physical function factors in predicting all-cause and cardiovascular mortality in comparison with the established risk factors included in the European Society of Cardiology Systematic COronary Risk Evaluation (SCORE). Methods We examined the predictive discrimination of lifestyle measures using C-index and R2 in sex-stratified analyses adjusted for: model 1, age; model 2, SCORE variables (age, smoking status, systolic blood pressure, total and high-density lipoprotein cholesterol). Results The sample comprised 298,829 adults (median age, 57 years; 53.5% women) from the UK Biobank free from cancer and cardiovascular disease at baseline. Over a median follow-up of 6.9 years, there were 2174 and 3522 all–cause and 286 and 796 cardiovascular deaths in women and men, respectively. When added to model 1, self-reported walking pace improved C-index in women and men by 0.013 (99% CI: 0.007–0.020) and 0.022 (0.017–0.028) respectively for all-cause mortality; and by 0.023 (0.005–0.042) and 0.034 (0.020–0.048) respectively for cardiovascular mortality. When added to model 2, corresponding values for women and men were: 0.008 (0.003–0.012) and 0.013 (0.009–0.017) for all-cause mortality; and 0.012 (–0.001–0.025) and 0.024 (0.013–0.035) for cardiovascular mortality. Other lifestyle factors did not consistently improve discrimination across models and outcomes. The pattern of results for R2 mirrored those for C-index. Conclusion A simple self-reported measure of walking pace was the only lifestyle variable found to improve risk prediction for all-cause and cardiovascular mortality when added to established risk factors.

scholarly journals Remote history of VTE is associated with severe COVID‐19 in middle and older age: UK Biobank cohort study

2021 ◽  
Author(s):  
Jana J Anderson ◽  
Frederick K Ho ◽  
Claire L Niedzwiedz ◽  
S. Vittal Katikireddi ◽  
Carlos Celis‐Morales ◽  
...  
Keyword(s):  
Cohort Study ◽  
Older Age ◽  
Uk Biobank ◽  
History Of

scholarly journals Machine Learning Prediction of Biomarkers from SNPs and of Disease Risk from Biomarkers in the UK Biobank

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 991
Author(s):  
Erik Widen ◽  
Timothy G. Raben ◽  
Louis Lello ◽  
Stephen D. H. Hsu
Keyword(s):  
Disease Risk ◽  
Smoking Status ◽  
Glycated Haemoglobin ◽  
European Ancestry ◽  
Risk Scores ◽  
Common Disease ◽  
Atherosclerotic Cardiovascular Disease ◽  
Uk Biobank ◽  
Lipoprotein A ◽  
The Uk

We use UK Biobank data to train predictors for 65 blood and urine markers such as HDL, LDL, lipoprotein A, glycated haemoglobin, etc. from SNP genotype. For example, our Polygenic Score (PGS) predictor correlates ∼0.76 with lipoprotein A level, which is highly heritable and an independent risk factor for heart disease. This may be the most accurate genomic prediction of a quantitative trait that has yet been produced (specifically, for European ancestry groups). We also train predictors of common disease risk using blood and urine biomarkers alone (no DNA information); we call these predictors biomarker risk scores, BMRS. Individuals who are at high risk (e.g., odds ratio of >5× population average) can be identified for conditions such as coronary artery disease (AUC∼0.75), diabetes (AUC∼0.95), hypertension, liver and kidney problems, and cancer using biomarkers alone. Our atherosclerotic cardiovascular disease (ASCVD) predictor uses ∼10 biomarkers and performs in UKB evaluation as well as or better than the American College of Cardiology ASCVD Risk Estimator, which uses quite different inputs (age, diagnostic history, BMI, smoking status, statin usage, etc.). We compare polygenic risk scores (risk conditional on genotype: PRS) for common diseases to the risk predictors which result from the concatenation of learned functions BMRS and PGS, i.e., applying the BMRS predictors to the PGS output.

scholarly journals Clinical laboratory tests and five-year incidence of major depressive disorder: a prospective cohort study of 433,890 participants from the UK Biobank

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Michael Wainberg ◽  
Stefan Kloiber ◽  
Breno Diniz ◽  
Roger S. McIntyre ◽  
Daniel Felsky ◽  
...  
Keyword(s):  
Public Health ◽  
Major Depressive Disorder ◽  
Cohort Study ◽  
Confidence Interval ◽  
Depressive Disorder ◽  
Blood Cell ◽  
Biological Processes ◽  
Uk Biobank ◽  
Major Depressive ◽  
The Uk

AbstractPrevention of major depressive disorder (MDD) is a public health priority. Identifying biomarkers of underlying biological processes that contribute to MDD onset may help address this public health need. This prospective cohort study encompassed 383,131 white British participants from the UK Biobank with no prior history of MDD, with replication in 50,759 participants of other ancestries. Leveraging linked inpatient and primary care records, we computed adjusted odds ratios for 5-year MDD incidence among individuals with values below or above the 95% confidence interval (<2.5th or >97.5th percentile) on each of 57 laboratory measures. Sensitivity analyses were performed across multiple percentile thresholds and in comparison to established reference ranges. We found that indicators of liver dysfunction were associated with increased 5-year MDD incidence (even after correction for alcohol use and body mass index): elevated alanine aminotransferase (AOR = 1.35, 95% confidence interval [1.16, 1.58]), aspartate aminotransferase (AOR = 1.39 [1.19, 1.62]), and gamma glutamyltransferase (AOR = 1.52 [1.31, 1.76]) as well as low albumin (AOR = 1.28 [1.09, 1.50]). Similar observations were made with respect to endocrine dysregulation, specifically low insulin-like growth factor 1 (AOR = 1.34 [1.16, 1.55]), low testosterone among males (AOR = 1.60 [1.27, 2.00]), and elevated glycated hemoglobin (HbA1C; AOR = 1.23 [1.05, 1.43]). Markers of renal impairment (i.e. elevated cystatin C, phosphate, and urea) and indicators of anemia and macrocytosis (i.e. red blood cell enlargement) were also associated with MDD incidence. While some immune markers, like elevated white blood cell and neutrophil count, were associated with MDD (AOR = 1.23 [1.07, 1.42]), others, like elevated C-reactive protein, were not (AOR = 1.04 [0.89, 1.22]). The 30 significant associations validated as a group in the multi-ancestry replication cohort (Wilcoxon p = 0.0005), with a median AOR of 1.235. Importantly, all 30 significant associations with extreme laboratory test results were directionally consistent with an increased MDD risk. In sum, markers of liver and kidney dysfunction, growth hormone and testosterone deficiency, innate immunity, anemia, macrocytosis, and insulin resistance were associated with MDD incidence in a large community-based cohort. Our results support a contributory role of diverse biological processes to MDD onset.

A prospective study of coffee and tea consumption and the risk of glioma in the UK Biobank

2020 ◽  
Vol 129 ◽  
pp. 123-131 ◽  
Author(s):  
Jordan H. Creed ◽  
Stephanie A. Smith-Warner ◽  
Travis A. Gerke ◽  
Kathleen M. Egan
Keyword(s):  
Prospective Study ◽  
Tea Consumption ◽  
Uk Biobank ◽  
The Uk ◽  
A Prospective Study

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 Caffeinated Coffee and Tea Consumption, Genetic Variation and Cognitive Function in the UK Biobank

2020 ◽  
Vol 150 (8) ◽  
pp. 2164-2174
Author(s):  
Marilyn C Cornelis ◽  
Sandra Weintraub ◽  
Martha Clare Morris
Keyword(s):  
Genetic Variation ◽  
Cognitive Function ◽  
Poor Performance ◽  
Sociodemographic Factors ◽  
Caffeine Intake ◽  
Tea Consumption ◽  
Uk Biobank ◽  
Trail Making ◽  
Caffeine Metabolism ◽  
The Uk

ABSTRACT Background Coffee and tea are the major contributors of caffeine in the diet. Evidence points to the premise that caffeine may benefit cognition. Objective We examined the associations of habitual regular coffee or tea and caffeine intake with cognitive function whilst additionally accounting for genetic variation in caffeine metabolism. Methods We included white participants aged 37–73 y from the UK Biobank who provided biological samples and completed touchscreen questionnaires regarding sociodemographic factors, medical history, lifestyle, and diet. Habitual caffeine-containing coffee and tea intake was self-reported in cups/day and used to estimate caffeine intake. Between 97,369 and 445,786 participants with data also completed ≥1 of 7 self-administered cognitive functioning tests using a touchscreen system (2006–2010) or on home computers (2014). Multivariable regressions were used to examine the association between coffee, tea, or caffeine intake and cognition test scores. We also tested interactions between coffee, tea, or caffeine intake and a genetic-based caffeine-metabolism score (CMS) on cognitive function. Results After multivariable adjustment, reaction time, Pairs Matching, Trail Making test B, and symbol digit substitution, performance significantly decreased with consumption of 1 or more cups of coffee (all tests P-trend &lt; 0.0001). Tea consumption was associated with poor performance on all tests (P-trend &lt; 0.0001). No statistically significant CMS × tea, CMS × coffee, or CMS × caffeine interactions were observed. Conclusions Our findings, based on the participants of the UK Biobank, provide little support for habitual consumption of regular coffee or tea and caffeine in improving cognitive function. On the contrary, we observed decrements in performance with intakes of these beverages which may be a result of confounding. Whether habitual caffeine intake affects cognitive function therefore remains to be tested.

scholarly journals Predicting the effect of statins on cancer risk using genetic variants from a Mendelian randomization study in the UK Biobank

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Paul Carter ◽  
Mathew Vithayathil ◽  
Siddhartha Kar ◽  
Rahul Potluri ◽  
Amy M Mason ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Cancer Risk ◽  
Genetic Variants ◽  
Ldl Cholesterol ◽  
Human Genetics ◽  
Density Lipoprotein ◽  
Lipid Lowering ◽  
Uk Biobank ◽  
Standard Deviation Increase ◽  
The Uk

Laboratory studies have suggested oncogenic roles of lipids, as well as anticarcinogenic effects of statins. Here we assess the potential effect of statin therapy on cancer risk using evidence from human genetics. We obtained associations of lipid-related genetic variants with the risk of overall and 22 site-specific cancers for 367,703 individuals in the UK Biobank. In total, 75,037 individuals had a cancer event. Variants in the HMGCR gene region, which represent proxies for statin treatment, were associated with overall cancer risk (odds ratio [OR] per one standard deviation decrease in low-density lipoprotein [LDL] cholesterol 0.76, 95% confidence interval [CI] 0.65–0.88, p=0.0003) but variants in gene regions representing alternative lipid-lowering treatment targets (PCSK9, LDLR, NPC1L1, APOC3, LPL) were not. Genetically predicted LDL-cholesterol was not associated with overall cancer risk (OR per standard deviation increase 1.01, 95% CI 0.98–1.05, p=0.50). Our results predict that statins reduce cancer risk but other lipid-lowering treatments do not. This suggests that statins reduce cancer risk through a cholesterol independent pathway.

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