Serum Uric Acid and Coronary Heart Disease in 9,458 Incident Cases and 155,084 Controls: Prospective Study and Meta-Analysis

BACKGROUND: It has been suggested throughout the past fifty years that serum uric acid concentrations can help predict the future risk of coronary heart disease (CHD), but the epidemiological evidence is uncertain. METHODS AND FINDINGS: We report a “nested” case-control comparison within a prospective study in Reykjavik, Iceland, using baseline values of serum uric acid in 2,456 incident CHD cases and in 3,962 age- and sex-matched controls, plus paired serum uric acid measurements taken at baseline and, on average, 12 y later in 379 participants. In addition, we conducted a meta-analysis of 15 other prospective studies in eight countries conducted in essentially general populations. Compared with individuals in the bottom third of baseline measurements of serum uric acid in the Reykjavik study, those in the top third had an age- and sex-adjusted odds ratio for CHD of 1.39 (95% confidence interval [CI], 1.23–1.58) which fell to 1.12 (CI, 0.97–1.30) after adjustment for smoking and other established risk factors. Overall, in a combined analysis of 9,458 cases and 155,084 controls in all 16 relevant prospective studies, the odds ratio was 1.13 (CI, 1.07–1.20), but it was only 1.02 (CI, 0.91–1.14) in the eight studies with more complete adjustment for possible confounders. CONCLUSIONS: Measurement of serum uric acid levels is unlikely to enhance usefully the prediction of CHD, and this factor is unlikely to be a major determinant of the disease in general populations

Antihypertensive medication uses and serum ACE2 levels

The current coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is associated with major respiratory failure where the old and those with an underlying chronic disease are at highest risk of mortality1. Several factors have been proposed that may be underlying the higher mortality rates in these high-risk groups. The most frequent comorbidities associated with COVID-19 related mortality are clinical hypertension and type 2 diabetes (T2D)2,3. Although lower survival can simply be attributed to the frailty of this population, it has been suggested that administration of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) may affect the susceptibility to COVID-19 related outcomes by upregulating ACE24. It is well known that ACE2 is the cellular receptor that COVID-19 and other SARS coronaviruses bind to for entering the host cell5

Body weight changes and longitudinal associations with cognitive decline among community-dwelling older adults.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadIntroduction: We aim to investigate the longitudinal associations between changes in body weight (BW) and declines in cognitive function and risk of mild cognitive impairment (MCI)/dementia among cognitively normal individuals 65 years or older. Methods: Data from the Age Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik Study) including 2620 participants, were examined using multiple logistic regression models. Cognitive function included speed of processing (SP), executive function (EF), and memory function (MF). Changes in BW were classified as; weight loss (WL), weight gain (WG), and stable weight (SW). Results: Mean follow-up time was 5.2 years and 61.3% were stable weight. Participants who experienced WL (13.4%) were significantly more likely to have declines in MF and SP compared to the SW group. Weight changes were not associated with EF. WL was associated with a higher risk of MCI, while WG (25.3%) was associated with a higher dementia risk, when compared to SW. Discussion: Significant BW changes in older adulthood may indicate impending changes in cognitive function. Keywords: APOE ε4; body weight changes; cognitive function; dementia; executive function; memory function; mild cognitive impairment; nutrition; speed of processing.Foundation of St. Josefs Hospital Icelandic Gerontological Research Center, National Universit

A New Panel-Estimated GFR, Including beta(2)-Microglobulin and beta-Trace Protein and Not Including Race, Developed in a Diverse Population

RATIONALE AND OBJECTIVE: GFR estimation based on creatinine and cystatin C (eGFR(cr-cys)) is more accurate than eGFR based on either creatinine or cystatin C alone (eGFR(cr) or eGFR(cys)), but the inclusion of creatinine in eGFR(cr-cys) requires specification of a person’s race. Beta-2-microglobulin (B2M) and beta-trace protein (BTP) are alternative filtration markers that appear to be less influenced by race than creatinine. STUDY DESIGN: Study of diagnostic test accuracy. SETTING AND PARTICIPANTS: Development in pooled population of seven studies with 5017 participants with and without chronic kidney disease. External validation in a pooled population of seven other studies with 2245 participants. TESTS COMPARED: Panel eGFR using B2M and BTP in addition to cystatin C (three-marker panel) or creatinine and cystatin C (four-marker panel) with and without age and sex or race. OUTCOMES: GFR measured as the urinary clearance of iothalamate, plasma clearance of iohexol, or plasma clearance of Cr-EDTA RESULTS: Mean measured GFR was 58.1 and 83.2 ml/min/1.73m(2) and the proportion of blacks was 38.6% and 24.0%, in the development and validation populations, respectively. In development, addition of age and sex improved the performance of all equations compared to equations without age and sex, but addition of race did not further improve the performance. In validation, the four-marker panels were more accurate than the three-marker panels (p<0.001). The three-marker panel without race was more accurate than eGFR(cys) [1- P(30) of 15.6 vs 17.4% (p=0.014)], and the four-marker panel without race was as accurate as eGFR(cr-cys) [1- P(30) of 8.6 vs 9.4% (p=0.17)]. Results were generally consistent across subgroups. LIMITATIONS: No representation of participants with severe comorbid illness and from geographic areas outside of North America and Europe. CONCLUSIONS: The four-marker panel eGFR is as accurate as eGFR(cr-cys), without requiring specification of race. A more accurate race-free eGFR could be an important advance

Population assessment of future trajectories in coronary heart disease mortality.

Background: Coronary heart disease (CHD) mortality rates have been decreasing in Iceland since the 1980s, largely reflecting improvements in cardiovascular risk factors. The purpose of this study was to predict future CHD mortality in Iceland based on potential risk factor trends. Methods and findings: The previously validated IMPACT model was used to predict changes in CHD mortality between 2010 and 2040 among the projected population of Iceland aged 25–74. Calculations were based on combining: i) data on population numbers and projections (Statistics Iceland), ii) population risk factor levels and projections (Refine Reykjavik study), and iii) effectiveness of specific risk factor reductions (published meta-analyses). Projections for three contrasting scenarios were compared: 1) If the historical risk factor trends of past 30 years were to continue, the declining death rates of past decades would level off, reflecting population ageing. 2) If recent trends in risk factors (past 5 years) continue, this would result in a death rate increasing from 49 to 70 per 100,000. This would reflect a recent plateau in previously falling cholesterol levels and recent rapid increases in obesity and diabetes prevalence. 3) Assuming that in 2040 the entire population enjoys optimal risk factor levels observed in low risk cohorts, this would prevent almost all premature CHD deaths before 2040. Conclusions: The potential increase in CHD deaths with recent trends in risk factor levels is alarming both for Iceland and probably for comparable Western populations. However, our results show considerable room for reducing CHD mortality. Achieving the best case scenario could eradicate premature CHD deaths by 2040. Public health policy interventions based on these predictions may provide a cost effective means of reducing CHD mortality in the future

Coding and regulatory variants are associated with serum protein levels and disease.

Circulating proteins can be used to diagnose and predict disease-related outcomes. A deep serum proteome survey recently revealed close associations between serum protein networks and common disease. In the current study, 54,469 low-frequency and common exome-array variants were compared to 4782 protein measurements in the serum of 5343 individuals from the AGES Reykjavik cohort. This analysis identifies a large number of serum proteins with genetic signatures overlapping those of many diseases. More specifically, using a study-wide significance threshold, we find that 2021 independent exome array variants are associated with serum levels of 1942 proteins. These variants reside in genetic loci shared by hundreds of complex disease traits, highlighting serum proteins' emerging role as biomarkers and potential causative agents of a wide range of diseases

Clinical significance of cerebral microbleeds on MRI

__Background:__ Cerebral microbleeds can confer a high risk of intracerebral hemorrhage, ischemic stroke, death and dementia, but estimated risks remain imprecise and often conflicting. We investigated the association between cerebral microbleeds presence and these outcomes in a large meta-analysis of all published cohorts including: ischemic stroke/TIA, memory clinic, “high risk” elderly populations, and healthy individuals in population-based studies. __Methods:__ Cohorts (with > 100 participants) that assessed cerebral microbleeds presence on MRI, with subsequent follow-up (≥3 months) were identified. The association between cerebral microbleeds and each of the outcomes (ischemic stroke, intracerebral hemorrhage, death, and dementia) was quantified using random effects models of (a) unadjusted crude odds ratios and (b) covariate-adjusted hazard rations. Results: We identified 31 cohorts (n = 20,368): 19 ischemic stroke/TIA (n = 7672), 4 memory clinic (n = 1957), 3 high risk elderly (n = 1458) and 5 population-based cohorts (n = 11,722). Cerebral microbleeds were associated with an increased risk of ischemic stroke (OR: 2.14; 95% CI: 1.58–2.89 and adj-HR: 2.09; 95% CI: 1.71–2.57), but the relative increase in future intracerebral hemorrhage risk was greater (OR: 4.65; 95% CI: 2.68–8.08 and adj-HR: 3.93; 95% CI: 2.71–5.69). Cerebral microbleeds were an independent predictor of all-cause mortality (adj-HR: 1.36; 95% CI: 1.24–1.48). In three population-based studies, cerebral microbleeds were independently associated with incident dementia (adj-HR: 1.35; 95% CI: 1.00–1.82). Results were overall consistent in analyses stratified by different populations, but with different degrees of heterogeneity. __Conclusions:__ Our meta-analysis shows that cerebral microbleeds predict an increased risk of stroke, death, and dementia and provides up-to-date effect sizes across different clinical settings. These pooled estimates can inform clinical decisions and trials, further supporting cerebral microbleeds role as biomarkers of underlying subclinical brain pathology in research and clinical settings

Natriuretic peptides and integrated risk assessment for cardiovascular disease. an individual-participant-data meta-analysis

BACKGROUND: Guidelines for primary prevention of cardiovascular diseases focus on prediction of coronary heart disease and stroke. We assessed whether or not measurement of N-terminal-pro-B-type natriuretic peptide (NT-proBNP) concentration could enable a more integrated approach than at present by predicting heart failure and enhancing coronary heart disease and stroke risk assessment. METHODS: In this individual-participant-data meta-analysis, we generated and harmonised individual-participant data from relevant prospective studies via both de-novo NT-proBNP concentration measurement of stored samples and collection of data from studies identified through a systematic search of the literature (PubMed, Scientific Citation Index Expanded, and Embase) for articles published up to Sept 4, 2014, using search terms related to natriuretic peptide family members and the primary outcomes, with no language restrictions. We calculated risk ratios and measures of risk discrimination and reclassification across predicted 10 year risk categories (ie, <5%, 5% to <7·5%, and ≥7·5%), adding assessment of NT-proBNP concentration to that of conventional risk factors (ie, age, sex, smoking status, systolic blood pressure, history of diabetes, and total and HDL cholesterol concentrations). Primary outcomes were the combination of coronary heart disease and stroke, and the combination of coronary heart disease, stroke, and heart failure. FINDINGS: We recorded 5500 coronary heart disease, 4002 stroke, and 2212 heart failure outcomes among 95 617 participants without a history of cardiovascular disease in 40 prospective studies. Risk ratios (for a comparison of the top third vs bottom third of NT-proBNP concentrations, adjusted for conventional risk factors) were 1·76 (95% CI 1·56-1·98) for the combination of coronary heart disease and stroke and 2·00 (1·77-2·26) for the combination of coronary heart disease, stroke, and heart failure. Addition of information about NT-proBNP concentration to a model containing conventional risk factors was associated with a C-index increase of 0·012 (0·010-0·014) and a net reclassification improvement of 0·027 (0·019-0·036) for the combination of coronary heart disease and stroke and a C-index increase of 0·019 (0·016-0·022) and a net reclassification improvement of 0·028 (0·019-0·038) for the combination of coronary heart disease, stroke, and heart failure. INTERPRETATION: In people without baseline cardiovascular disease, NT-proBNP concentration assessment strongly predicted first-onset heart failure and augmented coronary heart disease and stroke prediction, suggesting that NT-proBNP concentration assessment could be used to integrate heart failure into cardiovascular disease primary prevention

Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: a pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction &gt; 5.0×10−8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD