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BackgroundIn 2022, a global monkeypox virus (MPXV) clade II epidemic occurred mainly among men who have sex with men. Until early 1980s, European smallpox vaccination programmes were part of worldwide smallpox eradication efforts. Having received smallpox vaccine > 20 years ago may provide some cross-protection against MPXV.AimTo assess the effectiveness of historical smallpox vaccination against laboratory-confirmed mpox in 2022 in Europe.MethodsEuropean countries with sufficient data on case vaccination status and historical smallpox vaccination coverage were included. We selected mpox cases born in these countries during the height of the national smallpox vaccination campaigns (latest 1971), male, with date of onset before 1 August 2022. We estimated vaccine effectiveness (VE) and corresponding 95% CI for each country using logistic regression as per the Farrington screening method. We calculated a pooled estimate using a random effects model.ResultsIn Denmark, France, the Netherlands and Spain, historical smallpox vaccination coverage was high (80-90%) until the end of the 1960s. VE estimates varied widely (40-80%, I2 = 82%), possibly reflecting different booster strategies. The pooled VE estimate was 70% (95% CI: 23-89%).ConclusionOur findings suggest residual cross-protection by historical smallpox vaccination against mpox caused by MPXV clade II in men with high uncertainty and heterogeneity. Individuals at high-risk of exposure should be offered mpox vaccination, following national recommendations, regardless of prior smallpox vaccine history, until further evidence becomes available. There is an urgent need to conduct similar studies in sub-Saharan countries currently affected by the MPXV clade I outbreak.

Background: Whether cardiovascular (CV) disease risk factors and biomarkers associate differentially with heart failure (HF) risk in men and women is unclear., Objectives: The purpose of this study was to evaluate sex-specific associations of CV risk factors and biomarkers with incident HF., Methods: The analysis was performed using data from 4 community-based cohorts with 12.5 years of follow-up. Participants (recruited between 1989 and 2002) were free of HF at baseline. Biomarker measurements included natriuretic peptides, cardiac troponins, plasminogen activator inhibitor-1, D-dimer, fibrinogen, C-reactive protein, sST2, galectin-3, cystatin-C, and urinary albumin-to-creatinine ratio., Results: Among 22,756 participants (mean age 60 ± 13 years, 53% women), HF occurred in 2,095 participants (47% women). Age, smoking, type 2 diabetes mellitus, hypertension, body mass index, atrial fibrillation, myocardial infarction, left ventricular hypertrophy, and left bundle branch block were strongly associated with HF in both sexes (p < 0.001), and the combined clinical model had good discrimination in men (C-statistic = 0.80) and in women (C-statistic = 0.83). The majority of biomarkers were strongly and similarly associated with HF in both sexes. The clinical model improved modestly after adding natriuretic peptides in men (ΔC-statistic = 0.006; likelihood ratio chi-square = 146; p < 0.001), and after adding cardiac troponins in women (ΔC-statistic = 0.003; likelihood ratio chi-square = 73; p < 0.001)., Conclusions: CV risk factors are strongly and similarly associated with incident HF in both sexes, highlighting the similar importance of risk factor control in reducing HF risk in the community. There are subtle sex-related differences in the predictive value of individual biomarkers, but the overall improvement in HF risk estimation when included in a clinical HF risk prediction model is limited in both sexes., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

We tested whether DNA-methylation profiles account for inter-individual variation in body mass index (BMI) and height and whether they predict these phenotypes over and above genetic factors. Genetic predictors were derived from published summary results from the largest genome-wide association studies on BMI (n ∼ 350,000) and height (n ∼ 250,000) to date. We derived methylation predictors by estimating probe-trait effects in discovery samples and tested them in external samples. Methylation profiles associated with BMI in older individuals from the Lothian Birth Cohorts (LBCs, n = 1,366) explained 4.9% of the variation in BMI in Dutch adults from the LifeLines DEEP study (n = 750) but did not account for any BMI variation in adolescents from the Brisbane Systems Genetic Study (BSGS, n = 403). Methylation profiles based on the Dutch sample explained 4.9% and 3.6% of the variation in BMI in the LBCs and BSGS, respectively. Methylation profiles predicted BMI independently of genetic profiles in an additive manner: 7%, 8%, and 14% of variance of BMI in the LBCs were explained by the methylation predictor, the genetic predictor, and a model containing both, respectively. The corresponding percentages for LifeLines DEEP were 5%, 9%, and 13%, respectively, suggesting that the methylation profiles represent environmental effects. The differential effects of the BMI methylation profiles by age support previous observations of age modulation of genetic contributions. In contrast, methylation profiles accounted for almost no variation in height, consistent with a mainly genetic contribution to inter-individual variation. The BMI results suggest that combining genetic and epigenetic information might have greater utility for complex-trait prediction., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Tools for the prediction of atrial fibrillation (AF) may identify high-risk individuals more likely to benefit from preventive interventions and serve as a benchmark to test novel putative risk factors., Methods and Results: Individual-level data from 3 large cohorts in the United States (Atherosclerosis Risk in Communities [ARIC] study, the Cardiovascular Health Study [CHS], and the Framingham Heart Study [FHS]), including 18 556 men and women aged 46 to 94 years (19% African Americans, 81% whites) were pooled to derive predictive models for AF using clinical variables. Validation of the derived models was performed in 7672 participants from the Age, Gene and Environment-Reykjavik study (AGES) and the Rotterdam Study (RS). The analysis included 1186 incident AF cases in the derivation cohorts and 585 in the validation cohorts. A simple 5-year predictive model including the variables age, race, height, weight, systolic and diastolic blood pressure, current smoking, use of antihypertensive medication, diabetes, and history of myocardial infarction and heart failure had good discrimination (C-statistic, 0.765; 95% CI, 0.748 to 0.781). Addition of variables from the electrocardiogram did not improve the overall model discrimination (C-statistic, 0.767; 95% CI, 0.750 to 0.783; categorical net reclassification improvement, -0.0032; 95% CI, -0.0178 to 0.0113). In the validation cohorts, discrimination was acceptable (AGES C-statistic, 0.664; 95% CI, 0.632 to 0.697 and RS C-statistic, 0.705; 95% CI, 0.664 to 0.747) and calibration was adequate., Conclusion: A risk model including variables readily available in primary care settings adequately predicted AF in diverse populations from the United States and Europe.

Hypertension is an important determinant of cardiovascular morbidity and mortality and has a substantial heritability, which is likely of polygenic origin. The aim of this study was to assess to what extent multiple common genetic variants contribute to blood pressure regulation in both adults and children and to assess overlap in variants between different age groups, using genome-wide profiling. Single nucleotide polymorphism sets were defined based on a meta-analysis of genome-wide association studies on systolic blood pressure and diastolic blood pressure performed by the Cohort for Heart and Aging Research in Genome Epidemiology (n=29 136), using different P value thresholds for selecting single nucleotide polymorphisms. Subsequently, genetic risk scores for systolic blood pressure and diastolic blood pressure were calculated in an independent adult population (n=2072) and a child population (n=1034). The explained variance of the genetic risk scores was evaluated using linear regression models, including sex, age, and body mass index. Genetic risk scores, including also many nongenome-wide significant single nucleotide polymorphisms, explained more of the variance than scores based only on very significant single nucleotide polymorphisms in adults and children. Genetic risk scores significantly explained ≤1.2% (P=9.6*10(-8)) of the variance in adult systolic blood pressure and 0.8% (P=0.004) in children. For diastolic blood pressure, the variance explained was similar in adults and children (1.7% [P=8.9*10(-10)] and 1.4% [P=3.3*10(-5)], respectively). These findings suggest the presence of many genetic loci with small effects on blood pressure regulation both in adults and children, indicating also a (partly) common polygenic regulation of blood pressure throughout different periods of life.

Chronic kidney disease (CKD) has a heritable component and is an important global public health problem because of its high prevalence and morbidity. We conducted genome-wide association studies (GWAS) to identify susceptibility loci for glomerular filtration rate, estimated by serum creatinine (eGFRcrea) and cystatin C (eGFRcys), and CKD (eGFRcrea < 60 ml/min/1.73 m(2)) in European-ancestry participants of four population-based cohorts (ARIC, CHS, FHS, RS; n = 19,877; 2,388 CKD cases), and tested for replication in 21,466 participants (1,932 CKD cases). We identified significant SNP associations (P < 5 × 10(-8)) with CKD at the UMOD locus, with eGFRcrea at UMOD, SHROOM3 and GATM-SPATA5L1, and with eGFRcys at CST and STC1. UMOD encodes the most common protein in human urine, Tamm-Horsfall protein, and rare mutations in UMOD cause mendelian forms of kidney disease. Our findings provide new insights into CKD pathogenesis and underscore the importance of common genetic variants influencing renal function and disease.

Background: Hyperuricaemia, a highly heritable trait, is a key risk factor for gout. We aimed to identify novel genes associated with serum uric acid concentration and gout., Methods: Genome-wide association studies were done for serum uric acid in 7699 participants in the Framingham cohort and in 4148 participants in the Rotterdam cohort. Genome-wide significant single nucleotide polymorphisms (SNPs) were replicated in white (n=11 024) and black (n=3843) individuals who took part in the study of Atherosclerosis Risk in Communities (ARIC). The SNPs that reached genome-wide significant association with uric acid in either the Framingham cohort (p<5.0 x 10(-8)) or the Rotterdam cohort (p<1.0 x 10(-7)) were evaluated with gout. The results obtained in white participants were combined using meta-analysis., Findings: Three loci in the Framingham cohort and two in the Rotterdam cohort showed genome-wide association with uric acid. Top SNPs in each locus were: missense rs16890979 in SLC2A9 (p=7.0 x 10(-168) and 2.9 x 10(-18) for white and black participants, respectively); missense rs2231142 in ABCG2 (p=2.5 x 10(-60) and 9.8 x 10(-4)), and rs1165205 in SLC17A3 (p=3.3 x 10(-26) and 0.33). All SNPs were direction-consistent with gout in white participants: rs16890979 (OR 0.59 per T allele, 95% CI 0.52-0.68, p=7.0 x 10(-14)), rs2231142 (1.74, 1.51-1.99, p=3.3 x 10(-15)), and rs1165205 (0.85, 0.77-0.94, p=0.002). In black participants of the ARIC study, rs2231142 was direction-consistent with gout (1.71, 1.06-2.77, p=0.028). An additive genetic risk score of high-risk alleles at the three loci showed graded associations with uric acid (272-351 mumol/L in the Framingham cohort, 269-386 mumol/L in the Rotterdam cohort, and 303-426 mumol/L in white participants of the ARIC study) and gout (frequency 2-13% in the Framingham cohort, 2-8% in the Rotterdam cohort, and 1-18% in white participants in the ARIC study)., Interpretation: We identified three genetic loci associated with uric acid concentration and gout. A score based on genes with a putative role in renal urate handling showed a substantial risk for gout.