The NOS1AP gene rs10494366 common genetic variant does not modify the risk of sudden cardiac death in users of digoxin.

AIMS: Common genetic variations in the nitric oxide synthase-1 adaptor protein (NOS1AP) gene are associated with QT-interval prolongation. In a previous study, we observed an association between the rs10494366 variant of this gene and an increased QT-interval shortening in digoxin users. As QT-interval shortening is a risk factor for sudden cardiac death (SCD), in this study, we investigated whether the association between digoxin use and risk of SCD differs in participants with different NOS1AP rs10494366 genotypes. METHODS: We included 11 377 individuals from the prospective population-based cohort of the Rotterdam Study. We used Cox proportional hazard regression analysis with digoxin as time-dependent exposure to estimate the associations between current digoxin use and the risk of SCD among different rs10494366 genotype groups in the adjusted models. We also studied whether such an association was dose-dependent, comparing high dosage (≥ 0.250 mg), moderate dosage (0.125 mg ≤ dose< 0.250 mg) and low dosage (< 0.125 mg) digoxin users with non-users. RESULTS: The median baseline age of the total study population was 62 (interquartile range [IQR] 58-71) years. The cumulative incidence of SCD was 4.1% (469 cases), and among them, 74 (15.7%) individuals were current digoxin users at the time of death, during a median follow-up of 11.5 (IQR 6.5-17) years. Current digoxin users had an increased risk of SCD (multivariable adjusted model hazard ratio [HR]: 3.07; 95% confidence interval [CI]: 2.38-3.98), with no significant differences between the three genotype groups. The adjusted HRs were 4.03 [95% CI: 1.98-8.21] in the minor homozygous GG, 3.46 [95% CI: 2.37-5.04] in the heterozygous TG and 2.56 [95%CI: 1.70-3.86] in the homozygous TT genotype groups. Compared to low- and moderate-dose, high-dose digoxin users with GG genotype had the highest risk of SCD (HR: 5.61 [95% CI: 1.34-23.47]). CONCLUSIONS: Current use of digoxin is associated with a significantly increased risk of SCD. The NOS1AP gene rs10494366 variant did not modify the digoxin-associated risk of SCD in a population of European ancestry.

Respiratory syncytial virus vaccination during pregnancy for improving infant outcomes.

BACKGROUND: Respiratory syncytial virus (RSV) is a major cause of lower respiratory tract infections (LRTIs) in infants. Maternal RSV vaccination is a preventive strategy of great interest, as it could have a substantial impact on infant RSV disease burden. In recent years, the clinical development of maternal RSV vaccines has advanced rapidly. OBJECTIVES: To assess the efficacy and safety of maternal respiratory syncytial virus (RSV) vaccination for preventing RSV disease in infants. SEARCH METHODS: We searched Cochrane Pregnancy and Childbirth's Trials Register and two other trials registries on 21 October 2022. We updated the search on 27 July 2023, when we searched MEDLINE, Embase, CENTRAL, CINAHL, and two trials registries. Additionally, we searched the reference lists of retrieved studies and conference proceedings. There were no language restrictions on our searches. SELECTION CRITERIA: We included randomised controlled trials (RCTs) comparing maternal RSV vaccination with placebo or no intervention in pregnant women of any age. The primary outcomes were hospitalisation with clinically confirmed or laboratory-confirmed RSV disease in infants. The secondary outcomes covered adverse pregnancy outcomes (intrauterine growth restriction, stillbirth, and maternal death) and adverse infant outcomes (preterm birth, congenital abnormalities, and infant death). DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods and assessed the certainty of evidence using the GRADE approach. MAIN RESULTS: We included six RCTs (25 study reports) involving 17,991 pregnant women. The intervention was an RSV pre-F protein vaccine in four studies, and an RSV F protein nanoparticle vaccine in two studies. In all studies, the comparator was a placebo (saline, formulation buffer, or sterile water). We judged four studies at overall low risk of bias and two studies at overall high risk (mainly due to selection bias). All studies were funded by pharmaceutical companies. Maternal RSV vaccination compared with placebo reduces infant hospitalisation with laboratory-confirmed RSV disease (risk ratio (RR) 0.50, 95% confidence interval (CI) 0.31 to 0.82; 4 RCTs, 12,216 infants; high-certainty evidence). Based on an absolute risk with placebo of 22 hospitalisations per 1000 infants, our results represent 11 fewer hospitalisations per 1000 infants from vaccinated pregnant women (15 fewer to 4 fewer). No studies reported infant hospitalisation with clinically confirmed RSV disease. Maternal RSV vaccination compared with placebo has little or no effect on the risk of congenital abnormalities (RR 0.96, 95% CI 0.88 to 1.04; 140 per 1000 with placebo, 5 fewer per 1000 with RSV vaccination (17 fewer to 6 more); 4 RCTs, 12,304 infants; high-certainty evidence). Maternal RSV vaccination likely has little or no effect on the risk of intrauterine growth restriction (RR 1.32, 95% CI 0.75 to 2.33; 3 per 1000 with placebo, 1 more per 1000 with RSV vaccination (1 fewer to 4 more); 4 RCTs, 12,545 pregnant women; moderate-certainty evidence). Maternal RSV vaccination may have little or no effect on the risk of stillbirth (RR 0.81, 95% CI 0.38 to 1.72; 3 per 1000 with placebo, no difference with RSV vaccination (2 fewer to 3 more); 5 RCTs, 12,652 pregnant women). There may be a safety signal warranting further investigation related to preterm birth. This outcome may be more likely with maternal RSV vaccination, although the 95% CI includes no effect, and the evidence is very uncertain (RR 1.16, 95% CI 0.99 to 1.36; 6 RCTs, 17,560 infants; very low-certainty evidence). Based on an absolute risk of 51 preterm births per 1000 infants from pregnant women who received placebo, there may be 8 more per 1000 infants from pregnant women with RSV vaccination (1 fewer to 18 more). There was one maternal death in the RSV vaccination group and none in the placebo group. Our meta-analysis suggests that RSV vaccination compared with placebo may have little or no effect on the risk of maternal death (RR 3.00, 95% CI 0.12 to 73.50; 3 RCTs, 7977 pregnant women; low-certainty evidence). The effect of maternal RSV vaccination on the risk of infant death is very uncertain (RR 0.81, 95% CI 0.36 to 1.81; 6 RCTs, 17,589 infants; very low-certainty evidence). AUTHORS' CONCLUSIONS: The findings of this review suggest that maternal RSV vaccination reduces laboratory-confirmed RSV hospitalisations in infants. There are no safety concerns about intrauterine growth restriction and congenital abnormalities. We must be careful in drawing conclusions about other safety outcomes owing to the low and very low certainty of the evidence. The evidence available to date suggests RSV vaccination may have little or no effect on stillbirth, maternal death, and infant death (although the evidence for infant death is very uncertain). However, there may be a safety signal warranting further investigation related to preterm birth. This is driven by data from one trial, which is not fully published yet. The evidence base would be much improved by more RCTs with substantial sample sizes and well-designed observational studies with long-term follow-up for assessment of safety outcomes. Future studies should aim to use standard outcome measures, collect data on concomitant vaccines, and stratify data by timing of vaccination, gestational age at birth, race, and geographical setting.

Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People With Type 2 Diabetes.

OBJECTIVE: To identify genetic risk factors for incident cardiovascular disease (CVD) among people with type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: We conducted a multiancestry time-to-event genome-wide association study for incident CVD among people with T2D. We also tested 204 known coronary artery disease (CAD) variants for association with incident CVD. RESULTS: Among 49,230 participants with T2D, 8,956 had incident CVD events (event rate 18.2%). We identified three novel genetic loci for incident CVD: rs147138607 (near CACNA1E/ZNF648, hazard ratio [HR] 1.23, P = 3.6 × 10-9), rs77142250 (near HS3ST1, HR 1.89, P = 9.9 × 10-9), and rs335407 (near TFB1M/NOX3, HR 1.25, P = 1.5 × 10-8). Among 204 known CAD loci, 5 were associated with incident CVD in T2D (multiple comparison-adjusted P < 0.00024, 0.05/204). A standardized polygenic score of these 204 variants was associated with incident CVD with HR 1.14 (P = 1.0 × 10-16). CONCLUSIONS: The data point to novel and known genomic regions associated with incident CVD among individuals with T2D.

Machine learning-based models to predict the conversion of normal blood pressure to hypertension within 5-year follow-up.

BACKGROUND: Factors contributing to the development of hypertension exhibit significant variations across countries and regions. Our objective was to predict individuals at risk of developing hypertension within a 5-year period in a rural Middle Eastern area. METHODS: This longitudinal study utilized data from the Fasa Adults Cohort Study (FACS). The study initially included 10,118 participants aged 35-70 years in rural districts of Fasa, Iran, with a follow-up of 3,000 participants after 5 years using random sampling. A total of 160 variables were included in the machine learning (ML) models, and feature scaling and one-hot encoding were employed for data processing. Ten supervised ML algorithms were utilized, namely logistic regression (LR), support vector machine (SVM), random forest (RF), Gaussian naive Bayes (GNB), linear discriminant analysis (LDA), k-nearest neighbors (KNN), gradient boosting machine (GBM), extreme gradient boosting (XGB), cat boost (CAT), and light gradient boosting machine (LGBM). Hyperparameter tuning was performed using various combinations of hyperparameters to identify the optimal model. Synthetic Minority Over-sampling Technology (SMOTE) was used to balance the training data, and feature selection was conducted using SHapley Additive exPlanations (SHAP). RESULTS: Out of 2,288 participants who met the criteria, 251 individuals (10.9%) were diagnosed with new hypertension. The LGBM model (determined to be the optimal model) with the top 30 features achieved an AUC of 0.67, an f1-score of 0.23, and an AUC-PR of 0.26. The top three predictors of hypertension were baseline systolic blood pressure (SBP), gender, and waist-to-hip ratio (WHR), with AUCs of 0.66, 0.58, and 0.63, respectively. Hematuria in urine tests and family history of hypertension ranked fourth and fifth. CONCLUSION: ML models have the potential to be valuable decision-making tools in evaluating the need for early lifestyle modification or medical intervention in individuals at risk of developing hypertension.

Machine-learning algorithms in screening for type 2 diabetes mellitus: Data from Fasa Adults Cohort Study.

INTRODUCTION: The application of machine learning (ML) is increasingly growing in biomedical sciences. This study aimed to evaluate factors associated with type 2 diabetes mellitus (T2DM) and compare the performance of ML methods in identifying individuals with the disease in an Iranian setting. METHODS: Using the baseline data from Fasa Adult Cohort Study (FACS) and in a sex-stratified manner, we studied factors associated with T2DM by applying seven different ML methods including Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbours (KNN), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGB) and Bagging classifier (BAG). We further compared the performance of these methods; for each algorithm, accuracy, precision, sensitivity, specificity, F1 score, and Area Under Curve (AUC) were calculated. RESULTS: 10,112 participants were recruited between 2014 and 2016, of whom 1246 had T2DM at baseline. 4566 (45%) participants were males, aged between 35 and 70 years. For males, age, sugar consumption, and history of hospitalization were the most weighted variables regarding their importance in screening for T2DM using the GBM model, respectively; these variables were sugar consumption, urine blood, and age for females. GBM outperformed other models for both males and females with AUC of 0.75 (0.69-0.82) and 0.76 (0.71-0.80), and F1 score of 0.33 (0.27-0.39) and 0.42 (0.38-0.46), respectively. GBM also showed a sensitivity of 0.24 (0.19-0.29) and a specificity of 0.98 (0.96-1.0) in males and a sensitivity of 0.38 (0.34-0.42) and specificity of 0.92 (0.89-0.95) in females. Notably, close performance characteristics were detected among other ML models. CONCLUSIONS: GBM model might achieve better performance in screening for T2DM in a south Iranian population.

A Federated Database for Obesity Research: An IMI-SOPHIA Study.

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.

Statin Use and Coronary Artery Calcification: a Systematic Review and Meta-analysis of Observational Studies and Randomized Controlled Trials.

PURPOSE OF REVIEW: This review aimed to determine the association between statin use and coronary artery calcification (CAC), as detected by computed tomography in the general population, in previously published observational studies (OSs) and randomized controlled trials (RCTs). RECENT FINDINGS: A systematic search until February 2022 identified 41 relevant studies, comprising 29 OSs and 12 RCTs. We employed six meta-analysis models, stratifying studies based on design and effect metrics. For cohort studies, the pooled ß of the association with CAC quantified by the Agatston score was 0.11 (95% CI = 0.05; 0.16), with an average follow-up time per person (AFTP) of 3.68 years. Cross-sectional studies indicated a pooled odds ratio of 2.11 (95% CI = 1.61; 2.78) for the presence of CAC. In RCTs, the pooled standardized mean differences (SMDs) for CAC, quantified by Agatston score or volume, over and AFTP of 1.25 years were not statistically significant (SMD = - 0.06, 95% CI = - 0.19; 0.06 and SMD = 0.26, 95% CI = - 0.66; 1.19), but significantly different (p-value = 0.04). Meta-regression and subgroup analyses did not show any significant differences in pooled estimates across covariates. The effect of statins on CAC differs across study designs. OSs demonstrate associations between statin use and higher CAC scores and presence while being prone to confounding by indication. Effects from RCTs do not reach statistical significance and vary depending on the quantification method, hampering drawing conclusions. Further investigations are required to address the limitations inherent in each approach.

Are maternal vaccines effective and safe for mothers and infants? A systematic review and meta-analysis of randomised controlled trials.

INTRODUCTION: Maternal vaccination is a promising strategy to reduce the burden of vaccine-preventable diseases for mothers and infants. We aimed to provide an up-to-date overview of the efficacy and safety of all available maternal vaccines. METHODS: We searched PubMed, Embase, CENTRAL and ClinicalTrials.gov on 1 February 2022, for phase III and IV randomised controlled trials (RCTs) that compared maternal vaccination against any pathogen with placebo or no vaccination. Primary outcomes were laboratory-confirmed or clinically confirmed disease in mothers and infants. Secondary safety outcomes included intrauterine growth restriction, stillbirth, maternal death, preterm birth, congenital malformations and infant death. Random effects meta-analysis were used to calculate pooled risk ratio's (RR). Quality appraisal was performed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE). RESULTS: Six RCTs on four maternal vaccines, influenza, tetanus, diphtheria and pertussis (Tdap), pneumococcal and respiratory syncytial virus (RSV) were eligible. The overall risk of bias and certainty of evidence varied from low to high. Maternal influenza vaccination significantly reduced the number of laboratory-confirmed influenza cases (RR 0.58, 95% CI 0.42 to 0.79, event rate 57 vs 98, 2 RCTs, n=6003, I2=0%), and clinically confirmed influenza cases in mothers (RR 0.88, 95% CI 0.78 to 0.99, event rate 418 vs 472, 2 RCTs, n=6003, I2=0%), and laboratory-confirmed influenza in infants (RR 0.66, 95% CI 0.52 to 0.85, event rate 98 vs 148, 2 RCTs, n=5883, I2=0%), although this was not significant for clinically confirmed influenza in infants (RR 0.99, 95% CI 0.94 to 1.05, event rate 1371 vs 1378, 2 RCTs, n=5883, I2=0%). No efficacy data were available on maternal Tdap vaccination. Maternal pneumococcal vaccination did not reduce laboratory-confirmed and clinically confirmed middle ear disease (RR 0.49, 95% CI 0.24 to 1.02, event rate 9 vs 18, 1 RCT, n=133 and RR 0.88 95% CI 0.69 to 1.12, event rate 42 vs 47, 1 RCT, n=133, respectively), and clinically confirmed lower-respiratory tract infection (LRTI) (RR 1.08, 95% CI 0.82 to 1.43, event rate 18 vs 34, 1 RCT, n=70) in infants. Maternal RSV vaccination did not reduce laboratory-confirmed RSV LRTI in infants (RR 0.75, 95% CI 0.56 to 1.01, event rate 103 vs 71, 1 RCT, n=4527). There was no evidence of a significant effect of any of the maternal vaccines on the reported safety outcomes. CONCLUSIONS: The few RCTs with low event rates suggest that, depending on the type of maternal vaccine, the vaccine might effectively prevent disease and within its size does not show safety concerns in mothers and infants. PROSPERO REGISTRATION NUMBER: CRD42021235115.

Gene-environment interactions and the effect on obesity risk in low and middle-income countries: a scoping review.

Background: Obesity represents a major and preventable global health challenge as a complex disease and a modifiable risk factor for developing other non-communicable diseases. In recent years, obesity prevalence has risen more rapidly in low- and middle-income countries (LMICs) compared to high-income countries (HICs). Obesity traits are shown to be modulated by an interplay of genetic and environmental factors such as unhealthy diet and physical inactivity in studies from HICs focused on populations of European descent; however, genetic heterogeneity and environmental differences prevent the generalisation of study results to LMICs. Primary research investigating gene-environment interactions (GxE) on obesity in LMICs is limited but expanding. Synthesis of current research would provide an overview of the interactions between genetic variants and environmental factors that underlie the obesity epidemic and identify knowledge gaps for future studies. Methods: Three databases were searched systematically using a combination of keywords such as "genes", "obesity", "LMIC", "diet", and "physical activity" to find all relevant observational studies published before November 2022. Results: Eighteen of the 1,373 articles met the inclusion criteria, of which one was a genome-wide association study (GWAS), thirteen used a candidate gene approach, and five were assigned as genetic risk score studies. Statistically significant findings were reported for 12 individual SNPs; however, most studies were small-scale and without replication. Conclusion: Although the results suggest significant GxE interactions on obesity in LMICs, updated robust statistical techniques with more precise and standardised exposure and outcome measurements are necessary for translatable results. Future research should focus on improved quality replication efforts, emphasising large-scale and long-term longitudinal study designs using multi-ethnic GWAS.

Bi-Directional Interactions between Glucose-Lowering Medications and Gut Microbiome in Patients with Type 2 Diabetes Mellitus: A Systematic Review.

Background: Although common drugs for treating type 2 diabetes (T2D) are widely used, their therapeutic effects vary greatly. The interaction between the gut microbiome and glucose-lowering drugs is one of the main contributors to the variability in T2D progression and response to therapy. On the one hand, glucose-lowering drugs can alter gut microbiome components. On the other hand, specific gut microbiota can influence glycemic control as the therapeutic effects of these drugs. Therefore, this systematic review assesses the bi-directional relationships between common glucose-lowering drugs and gut microbiome profiles. Methods: A systematic search of Embase, Web of Science, PubMed, and Google Scholar databases was performed. Observational studies and randomised controlled trials (RCTs), published from inception to July 2023, comprising T2D patients and investigating bi-directional interactions between glucose-lowering drugs and gut microbiome, were included. Results: Summarised findings indicated that glucose-lowering drugs could increase metabolic-healthy promoting taxa (e.g., Bifidobacterium) and decrease harmful taxa (e.g., Bacteroides and Intestinibacter). Our findings also showed a significantly different abundance of gut microbiome taxa (e.g., Enterococcus faecium (i.e., E. faecium)) in T2D patients with poor compared to optimal glycemic control. Conclusions: This review provides evidence for glucose-lowering drug and gut microbiome interactions, highlighting the potential of gut microbiome modulators as co-adjuvants for T2D treatment.

Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus.

BACKGROUND: Type 2 diabetes mellitus (T2D) confers a two- to three-fold increased risk of cardiovascular disease (CVD). However, the mechanisms underlying increased CVD risk among people with T2D are only partially understood. We hypothesized that a genetic association study among people with T2D at risk for developing incident cardiovascular complications could provide insights into molecular genetic aspects underlying CVD. METHODS: From 16 studies of the Cohorts for Heart & Aging Research in Genomic Epidemiology (CHARGE) Consortium, we conducted a multi-ancestry time-to-event genome-wide association study (GWAS) for incident CVD among people with T2D using Cox proportional hazards models. Incident CVD was defined based on a composite of coronary artery disease (CAD), stroke, and cardiovascular death that occurred at least one year after the diagnosis of T2D. Cohort-level estimated effect sizes were combined using inverse variance weighted fixed effects meta-analysis. We also tested 204 known CAD variants for association with incident CVD among patients with T2D. RESULTS: A total of 49,230 participants with T2D were included in the analyses (31,118 European ancestries and 18,112 non-European ancestries) which consisted of 8,956 incident CVD cases over a range of mean follow-up duration between 3.2 and 33.7 years (event rate 18.2%). We identified three novel, distinct genetic loci for incident CVD among individuals with T2D that reached the threshold for genome-wide significance (P<5.0×10-8): rs147138607 (intergenic variant between CACNA1E and ZNF648) with a hazard ratio (HR) 1.23, 95% confidence interval (CI) 1.15 - 1.32, P=3.6×10-9, rs11444867 (intergenic variant near HS3ST1) with HR 1.89, 95% CI 1.52 - 2.35, P=9.9×10-9, and rs335407 (intergenic variant between TFB1M and NOX3) HR 1.25, 95% CI 1.16 - 1.35, P=1.5×10-8. Among 204 known CAD loci, 32 were associated with incident CVD in people with T2D with P<0.05, and 5 were significant after Bonferroni correction (P<0.00024, 0.05/204). A polygenic score of these 204 variants was significantly associated with incident CVD with HR 1.14 (95% CI 1.12 - 1.16) per 1 standard deviation increase (P=1.0×10-16). CONCLUSIONS: The data point to novel and known genomic regions associated with incident CVD among individuals with T2D.

Exploring Metabolomic Patterns in Type 2 Diabetes Mellitus and Response to Glucose-Lowering Medications-Review.

The spectrum of information related to precision medicine in diabetes generally includes clinical data, genetics, and omics-based biomarkers that can guide personalized decisions on diabetes care. Given the remarkable progress in patient risk characterization, there is particular interest in using molecular biomarkers to guide diabetes management. Metabolomics is an emerging molecular approach that helps better understand the etiology and promises the identification of novel biomarkers for complex diseases. Both targeted or untargeted metabolites extracted from cells, biofluids, or tissues can be investigated by established high-throughput platforms, like nuclear magnetic resonance (NMR) and mass spectrometry (MS) techniques. Metabolomics is proposed as a valuable tool in precision diabetes medicine to discover biomarkers for diagnosis, prognosis, and management of the progress of diabetes through personalized phenotyping and individualized drug-response monitoring. This review offers an overview of metabolomics knowledge as potential biomarkers in type 2 diabetes mellitus (T2D) diagnosis and the response to glucose-lowering medications.

The healthy beverage index is not associated with insulin resistance, prediabetes and type 2 diabetes risk in the Rotterdam Study.

PURPOSE: Whether beverage quality affects changes in glycaemic traits and type 2 diabetes (T2D) risk is unknown. We examined associations of a previously developed Healthy Beverage Index (HBI) with insulin resistance, and risk of prediabetes and T2D. METHODS: We included 6769 participants (59% female, 62.0 ± 7.8 years) from the Rotterdam Study cohort free of diabetes at baseline. Diet was assessed using food-frequency questionnaires at baseline. The HBI included 10 components (energy from beverages, meeting fluid requirements, water, coffee and tea, low-fat milk, diet drinks, juices, alcohol, full-fat milk, and sugar-sweetened beverages), with a total score ranging from 0 to 100. A higher score represents a healthier beverage pattern. Data on study outcomes were available from 1993 to 2015. Multivariable linear mixed models and Cox proportional-hazards regression models were used to examine associations of the HBI (per 10 points increment) with two measurements of HOMA-IR (a proxy for insulin resistance), and risk of prediabetes and T2D. RESULTS: During follow-up, we documented 1139 prediabetes and 784 T2D cases. Mean ± SD of the HBI was 66.8 ± 14.4. Higher HBI score was not associated with HOMA-IR (ß: 0.003; 95% CI - 0.007, 0.014), or with risk of prediabetes (HR: 1.01; 95% CI 0.97, 1.06), or T2D (HR: 1.01; 95% CI 0.96, 1.07). CONCLUSION: Our findings suggest no major role for overall beverage intake quality assessed with the HBI in insulin resistance, prediabetes and T2D incidence. The HBI may not be an adequate tool to assess beverage intake quality in our population.

COVID-19 Vaccine Safety Monitoring Studies in Low- and Middle-Income Countries (LMICs)-A Systematic Review of Study Designs and Methods.

BACKGROUND: Post-marketing vaccine safety surveillance aims to monitor and quantify adverse events following immunization in a population, but little is known about their implementation in low- and middle-income countries (LMICs). We aimed to synthesize methodological approaches used to assess adverse events following COVID-19 vaccination in LMICs. METHODS: For this systematic review, we searched articles published from 1 December 2019 to 18 February 2022 in main databases, including MEDLINE and Embase. We included all peer-reviewed observational COVID-19 vaccine safety monitoring studies. We excluded randomized controlled trials and case reports. We extracted data using a standardized extraction form. Two authors assessed study quality using the modified Newcastle-Ottawa Quality Assessment Scale. All findings were summarized narratively using frequency tables and figures. RESULTS: Our search found 4254 studies, of which 58 were eligible for analysis. Many of the studies included in this review were conducted in middle-income countries, with 26 studies (45%) in lower-middle-income and 28 (48%) in upper-middle-income countries. More specifically, 14 studies were conducted in the Middle East region, 16 in South Asia, 8 in Latin America, 8 in Europe and Central Asia, and 4 in Africa. Only 3% scored 7-8 points (good quality) on the Newcastle-Ottawa Scale methodological quality assessment, while 10% got 5-6 points (medium). About 15 studies (25.9%) used a cohort study design and the rest were cross-sectional. In half of them (50%), vaccination data were gathered from the participants' self-reporting methods. Seventeen studies (29.3%) used multivariable binary logistic regression and three (5.2%) used survival analyses. Only 12 studies (20.7%) performed model diagnostics and validity checks (e.g., the goodness of fit, identification of outliers, and co-linearity). CONCLUSIONS: Published studies on COVID-19 vaccine safety surveillance in LMICs are limited in number and the methods used do not often address potential confounders. Active surveillance of vaccines in LMICs are needed to advocate vaccination programs. Implementing training programs in pharmacoepidemiology in LMICs is essential.

Heart Rate Variability and Incident Type 2 Diabetes in General Population.

CONTEXT: Hyperglycemia and autonomic dysfunction are bidirectionally related. OBJECTIVE: We investigated the association of longitudinal evolution of heart rate variability (HRV) with incident type 2 diabetes (T2D) among the general population. METHODS: We included 7630 participants (mean age 63.7 years, 58% women) from the population-based Rotterdam Study who had no history of T2D and atrial fibrillation at baseline and had repeated HRV assessments at baseline and during follow-up. We used joint models to assess the association between longitudinal evolution of heart rate and different HRV metrics (including the heart rate-corrected SD of the normal-to-normal RR intervals [SDNNc], and root mean square of successive RR-interval differences [RMSSDc]) with incident T2D. Models were adjusted for cardiovascular risk factors. Bidirectional Mendelian randomization (MR) using summary-level data was also performed. RESULTS: During a median follow-up of 8.6 years, 871 individuals developed incident T2D. One SD increase in heart rate (hazard ratio [HR] 1.20; 95% CI, 1.09-1.33), and log(RMSSDc) (HR 1.16; 95% CI, 1.01-1.33) were independently associated with incident T2D. The HRs were 1.54 (95% CI, 1.08-2.06) for participants younger than 62 years and 1.15 (95% CI, 1.01-1.31) for those older than 62 years for heart rate (P for interaction <.001). Results from bidirectional MR analyses suggested that HRV and T2D were not significantly related to each other. CONCLUSION: Autonomic dysfunction precedes development of T2D, especially among younger individuals, while MR analysis suggests no causal relationship. More studies are needed to further validate our findings.

Safety of COVID-19 Vaccines Among the Paediatric Population: Analysis of the European Surveillance Systems and Pivotal Clinical Trials.

BACKGROUND AND OBJECTIVES: The European Medicine Agency extended the use of Comirnaty, Spikevax, and Nuvaxovid in paediatrics; thus, these vaccines require additional real-world safety evidence. Herein, we aimed to monitor the safety of COVID-19 vaccines through Covid-19 Vaccine Monitor (CVM) and EudraVigilance surveillance systems and the published pivotal clinical trials. METHODS: In a prospective cohort of vaccinees aged between 5 and 17 years, we measured the frequency of commonly reported (local/systemic solicited) and serious adverse drug events (ADRs) following the first and second doses of COVID-19 vaccines in Europe using data from the CVM cohort until April 2022. The results of previous pivotal clinical trials and data in the EudraVigilance were also analysed. RESULTS: The CVM study enrolled 658 first-dose vaccinees (children aged 5-11 years; n = 250 and adolescents aged 12-17 years; n = 408). Local/systemic solicited ADRs were common, whereas serious ADRs were uncommon. Among Comirnaty first and second dose recipients, 28.8% and 17.1% of children and 54.2% and 52.2% of adolescents experienced at least one ADR, respectively; injection-site pain (29.2% and 20.7%), fatigue (16.1% and 12.8%), and headache (22.1% and 19.3%) were the most frequent local and systemic ADRs. Results were consistent but slightly lower than in pivotal clinical trials. Reporting rates in Eudravigilance were lower by a factor of 1000. CONCLUSIONS: The CVM study showed high frequencies of local solicited reactions after vaccination but lower rates than in pivotal clinical trials. Injection-site pain, fatigue, and headache were the most commonly reported ADRs for clinical trials, but higher than spontaneously reported data.

C-reactive protein partially mediates the inverse association between coffee consumption and risk of type 2 diabetes: The UK Biobank and the Rotterdam study cohorts.

BACKGROUND: Coffee is among the most consumed beverages worldwide. Coffee consumption has been associated with lower risk of type 2 diabetes mellitus (T2D), but underlying mechanisms are not well understood. We aimed to study the role of classic and novel-T2D biomarkers with anti- or pro-inflammatory activity in the association between habitual coffee intake and T2D risk. Furthermore, we studied differences by coffee types and smoking status in this association. METHODS: Using two large population-based cohorts, the UK-Biobank (UKB; n = 145,368) and the Rotterdam Study (RS; n = 7111), we investigated associations of habitual coffee consumption with incident T2D and repeated measures of insulin resistance (HOMA-IR), using Cox proportional hazards and mixed effect models, respectively. Additionally, we studied associations between coffee and subclinical inflammation biomarkers including C-reactive protein (CRP) and IL-13, and adipokines, such as adiponectin and leptin, using linear regression models. Next, we performed formal causal mediation analyses to investigate the role of coffee-associated biomarkers in the association of coffee with T2D. Finally, we evaluated effect modification by coffee type and smoking. All models were adjusted for sociodemographic, lifestyle and health-related factors. RESULTS: During a median follow-up of 13.9 (RS) and 7.4 (UKB) years, 843 and 2290 incident T2D cases occurred, respectively. A 1 cup/day increase in coffee consumption was associated with 4% lower T2D risk (RS, HR = 0.96 [95%CI 0.92; 0.99], p = 0.045; UKB, HR = 0.96 [0.94; 0.98], p < 0.001), with lower HOMA-IR (RS, log-transformed ß = -0.017 [-0.024;-0.010], p < 0.001), and with lower CRP (RS, log-transformed ß = -0.014 [-0.022;-0.005], p = 0.002; UKB, ß = -0.011 [-0.012;-0.009], p < 0.001). We also observed associations of higher coffee consumption with higher serum adiponectin and IL-13 concentrations, and with lower leptin concentrations. Coffee-related CRP levels partially mediated the inverse association of coffee intake with T2D incidence (average mediation effect RS ß = 0.105 (0.014; 0.240), p = 0.016; UKB ß = 6.484 (4.265; 9.339), p < 0.001), with a proportion mediated by CRP from 3.7% [-0.012%; 24.4%] (RS) to 9.8% [5,7%; 25.8%] (UKB). No mediation effect was observed for the other biomarkers. Coffee-T2D and coffee-CRP associations were generally stronger among consumers of ground (filtered or espresso) coffee and among never and former smokers. CONCLUSIONS: Lower subclinical inflammation may partially mediate the beneficial association between coffee consumption and lower T2D risk. Consumers of ground coffee and non-smokers may benefit the most. KEYWORDS (MESH TERMS): coffee consumptions; diabetes mellitus, type 2; inflammation; adipokines; biomarkers; mediation analysis; follow-up studies.

Associations of baseline glycemic status and its transitions with cognitive and physical functioning decline.

OBJECTIVE: Evidence about the decline of cognition and physical function across glycemic status (normoglycemia, prediabetes, and diabetes) is inconsistent. We evaluated longitudinal changes in cognition and physical function according to glycemic status and also different glycemic transitions. STUDY DESIGN: Population-based cohort study. METHODS: 9307 participants (mean age 59.7 years, 53.7 % women) were included from the China Health and Retirement Longitudinal Study (2011-2018). Global cognition (assessed by orientation, memory, and executive function) and physical function (calculated as the sum of impaired basic and instrumental activities of daily living) were assessed in each wave. The glycemic status was assessed in waves 2011 and 2015. Diabetes was defined as fasting blood glucose ≥7.0 mmol/L, HbA1c ≥6.5 %, self-reported diabetes, or glucose-lowering medication use. Prediabetes was defined as fasting blood glucose 5.6-6.9 mmol/L or an HbA1c of 5.7-6.4 %. RESULTS: Compared with normoglycemia, baseline diabetes was associated with a faster decline in orientation (-0.018 SD/year, 95%CI -0.032, -0.004) and a faster increase in physical function score (0.082 /year, 95%CI 0.038, 0.126). We did not observe any effect of prediabetes on the changing rate of cognition and physical function. Progression from normoglycemia to diabetes between waves 2011 and 2015 was associated with a significantly faster decline in global cognition, memory, executive function, and physical function compared with stable normoglycemia. CONCLUSIONS: Baseline diabetes was associated with accelerated decline of cognition and physical function. Associations with prediabetes were not observed, suggesting an important short diagnostic window when diabetes presents de novo.

Four missense genetic variants in CUBN are associated with higher levels of eGFR in non-diabetes but not in diabetes mellitus or its subtypes: A genetic association study in Europeans.

Aim: Rare genetic variants in the CUBN gene encoding the main albumin-transporter in the proximal tubule of the kidneys have previously been associated with microalbuminuria and higher urine albumin levels, also in diabetes. Sequencing studies in isolated proteinuria suggest that these variants might not affect kidney function, despite proteinuria. However, the relation of these CUBN missense variants to the estimated glomerular filtration rate (eGFR) is largely unexplored. We hereby broadly examine the associations between four CUBN missense variants and eGFRcreatinine in Europeans with Type 1 (T1D) and Type 2 Diabetes (T2D). Furthermore, we sought to deepen our understanding of these variants in a range of single- and aggregate- variant analyses of other kidney-related traits in individuals with and without diabetes mellitus. Methods: We carried out a genetic association-based linear regression analysis between four CUBN missense variants (rs141640975, rs144360241, rs45551835, rs1801239) and eGFRcreatinine (ml/min/1.73 m2, CKD-EPIcreatinine(2012), natural log-transformed) in populations with T1D (n ~ 3,588) or T2D (n ~ 31,155) from multiple European studies and in individuals without diabetes from UK Biobank (UKBB, n ~ 370,061) with replication in deCODE (n = 127,090). Summary results of the diabetes-group were meta-analyzed using the fixed-effect inverse-variance method. Results: Albeit we did not observe associations between eGFRcreatinine and CUBN in the diabetes-group, we found significant positive associations between the minor alleles of all four variants and eGFRcreatinine in the UKBB individuals without diabetes with rs141640975 being the strongest (Effect=0.02, PeGFR_creatinine=2.2 × 10-9). We replicated the findings for rs141640975 in the Icelandic non-diabetes population (Effect=0.026, PeGFR_creatinine=7.7 × 10-4). For rs141640975, the eGFRcreatinine-association showed significant interaction with albuminuria levels (normo-, micro-, and macroalbuminuria; p = 0.03). An aggregated genetic risk score (GRS) was associated with higher urine albumin levels and eGFRcreatinine. The rs141640975 variant was also associated with higher levels of eGFRcreatinine-cystatin C (ml/min/1.73 m2, CKD-EPI2021, natural log-transformed) and lower circulating cystatin C levels. Conclusions: The positive associations between the four CUBN missense variants and eGFR in a large population without diabetes suggests a pleiotropic role of CUBN as a novel eGFR-locus in addition to it being a known albuminuria-locus. Additional associations with diverse renal function measures (lower cystatin C and higher eGFRcreatinine-cystatin C levels) and a CUBN-focused GRS further suggests an important role of CUBN in the future personalization of chronic kidney disease management in people without diabetes.

Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease.

The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.