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Imaging-defined atherosclerosis represents an intermediate phenotype of atherosclerotic cardiovascular disease (ASCVD). Genome-wide association studies (GWAS) on directly measured coronary plaques using coronary computed tomography angiography (CCTA) are scarce. In the so far largest population-based cohort with CCTA data, we performed a GWAS on coronary plaque burden as determined by the segment involvement score (SIS) in 24,811 European individuals. We identified 20 significant independent genetic markers for SIS, three of which were found in loci not implicated in ASCVD before. Further GWAS on coronary artery calcification showed similar results to that of SIS, whereas a GWAS on ultrasound-assessed carotid plaques identified both shared and non-shared loci with SIS. In two-sample Mendelian randomization studies using SIS-associated markers in UK Biobank and CARDIoGRAMplusC4D, one extra coronary segment with atherosclerosis corresponded to 1.8-fold increased odds of myocardial infarction. This GWAS data can aid future studies of causal pathways in ASCVD.

Background: Although SARS-CoV-2 vaccination was a critical component to mitigate impact of the pandemic, it also brought specific challenges related to adverse drug reactions (ADRs) when large cohorts of healthcare workers were vaccinated.

Methods and findings: This study reports solicited ADRs and IgG anti-SARS-CoV-2 levels from 3805 healthcare workers in Sweden following primary immunization during 2021. Differences in systemic reactions at a level where study participants needed sick-leave or rescheduling of work shifts differed substantially between vaccine regimens, ranging from 12 % (Comirnaty) to 48 % (heterologous vaccination with Vaxzevria/Spikevax). Multivariable linear regression showed that the anti-S IgG response was dependent on vaccine label and that higher age and increased time from vaccination significantly correlated with lower antibody titers. Multivariable logistic regression models describing the risk for each ADR category in relation to vaccine label, age, sex, anti-S IgG levels post vaccination and time from vaccination showed vaccine label-dependent statistically significant differences in adjusted odds ratios for wide range of ADR categories, as high as OR 10 (95 % CI 7.6-13.5) for fever and chills when comparing Vaxzevria to Comirnaty. Among the mRNA vaccines, use of Spikevax (compared to Comirnaty) correlated with a statistically significant 1.3 to 3.5-fold increase in adjusted ORs for several ADR categories.

Conclusions: Based on a large cohort of health workers, our study confirms that adverse reactions after COVID-19 vaccination can lead to a substantial amount of missed work shifts, potentially causing organizational-level disturbances in staffing. There are significant differences in ADR frequencies related to vaccine type, age and sex, at overall levels not observed for other commonly used vaccines for adults.

Aim: Habitual physical activity (PA) affects metabolism and homeostasis in various tissues and organs. However, detailed knowledge of associations between PA and cardiovascular disease (CVD) risk markers is limited. We sought to identify associations between accelerometer-assessed PA classes and 183 proteomic and 154 metabolomic CVD-related biomarkers.

Method: We utilized cross-sectional data from the main SCAPIS cohort (n = 4647, median age: 57.5 yrs, 50.5% female) as a discovery sample and the SCAPIS pilot cohort (n = 910, median age: 57.5 yrs, 50.3% female) as a validation sample. PA was assessed via hip-worn accelerometers, while plasma concentrations of proteomic biomarkers were measured using Olink CVD II and III panels. Metabolomic markers were assessed using the Nightingale NMR platform. We evaluated associations between four PA classes (moderate-to-vigorous PA [MVPA], low-intensity PA [LIPA], sedentary [SED], and prolonged SED [prolSED]) and biomarkers, controlling for potential confounders and applying a false discovery rate of 5% using multiple linear regressions.

Results: A total of eighty-five metabolomic markers and forty-three proteomic markers were validated and found to be significantly associated with one or more PA classes. LIPA and SED markers demonstrated significant mirroring or opposing relations to biomarkers, while prolSED mainly shared relations with SED. Notably, HDL species were predominantly negatively associated with SED, whereas LDL species were positively associated with SED and negatively associated with MVPA. Among the proteomic markers, eighteen were uniquely associated with MVPA (among those Interleukin - 6 [IL6] and Growth/differentiation factor 15 [GDF15] both negatively related), seven with SED (among those Metalloproteinase inhibitor 4 [TIMP4] and Tumor necrosis factor receptor 2 [TNFR2], both positively related), and eight were related to both SED/prolSED (among those Lipoprotein lipase [LPL] negatively related to SED and leptin [LEP] positively related to SED) and MVPA (with LPL positively related to MVPA and LEP negatively related to MVPA).

Conclusion: Our findings suggest the existence of specific associations between PA classes and metabolomic and cardiovascular protein biomarkers in a middle-aged population. Beyond validation of previous results, we identified new associations. This multitude of connections between PA and CVD-related markers may help elucidate the previously observed relationship between PA and CVD. The identified cross-sectional associations could inform the design of future experimental studies, serving as important outcome measures.

Aims/Hypothesis: The potential impact of childhood bereavement-a severe psychological stressor-on childhood type 1 diabetes development remains unclear. Here, we aimed to bridge this knowledge gap and assess whether bereavement characteristics influenced any impact.

Methods: We conducted a register-based cohort study encompassing 3,598,159 children born in Sweden between 1987 and 2020. Childhood bereavement was defined as the death of a biological mother, father or sibling. Diagnosis of type 1 diabetes in childhood (<18 years) was ascertained through the National Patient Register. We applied a Cox proportional hazards regression model to investigate the impact of childhood bereavement on type 1 diabetes, while adjusting for potential confounders (including parental type 1 diabetes status, country of birth and demographic characteristics).

Results: During follow-up, 86,226 children (2.4%) lost a family member, and 18,817 children (0.52%) were diagnosed with type 1 diabetes (median age at onset 9.1 years). We did not detect any overall association between childhood bereavement and type 1 diabetes (adjusted HR 1.04; 95% CI 0.93, 1.17). We found no influence of age at loss, cause of death, familial relationship to the deceased, and time since loss.

Conclusions/Interpretation: In this large population-based Swedish study, we observed no evidence supporting a link between childhood bereavement and type 1 diabetes.

Background

How cardiovascular diseases (CVD) predispose to a higher risk of fragility fractures is not well understood. Both contribute to significant components of disease burden and health expenditure. Poor bone quality, central obesity, sarcopenia, falls, and low grip strength are independent risk factors for hip and other fragility fractures and also for CVD and early death.

Methods

We used proteomics and a cohort design combined with Mendelian randomisation analysis to understand shared mechanisms for developing CVD and fragility fractures, two significant sources of disease burden and health expenditure. We primarily aimed to discover and replicate the association of 274 cardio-metabolic-related proteins with future rates of hip and any fracture in two separate population-based cohorts, with a total of 12,314 women and men.

Findings

The average age at baseline was 68 years in the discovery cohort of women and 74 years in the mixed-sex replication cohort. During 100,619 person-years of follow-up, 2168 had any fracture, and 538 had a hip fracture. Our analysis resulted in 24 cardiometabolic proteins associated with fracture risk: 20 with hip fracture, 9 with any fracture, and 5 with both. The associations remained even if protein concentrations were measured from specimens taken during preclinical stages of cardio-metabolic diseases, and 19 associations remained after adjustment for bone mineral density. Twenty-two of the proteins were associated with total body fat mass or lean body mass. Mendelian randomisation (MR) analysis supported causality since genetically predicted levels of SOST (Sclerostin), CCDC80 (Coiled-coil domain-containing protein 80), NT-proBNP (N-terminal prohormone brain natriuretic peptide), and BNP (Brain natriuretic peptide) were associated with risk of hip fracture. MR analysis also revealed a possible negative impact on bone mineral density (BMD) by genetically predicted higher levels of SOST, CCDC80, and TIMP4 (Metalloproteinase inhibitor 4). The MR association with BMD was positive for PTX3 (Pentraxin-related protein) and SPP1 (Osteopontin). Genetically predicted higher concentrations of SOST and lower concentrations of SPP1 also conferred a higher risk of falls and lowered grip strength. The genetically determined concentration of nine proteins influenced fat mass, and one influenced lean body mass.

Interpretation

These data reveal biological links between cardiovascular diseases and fragility fractures. The proteins should be further evaluated as shared targets for developing pharmacological interventions to prevent fractures and cardiovascular disease.