Stroke Risk After COVID-19 Bivalent Vaccination Among US Older Adults.

Importance: In January 2023, the US Centers for Disease Control and Prevention and the US Food and Drug Administration noted a safety concern for ischemic stroke among adults aged 65 years or older who received the Pfizer-BioNTech BNT162b2; WT/OMI BA.4/BA.5 COVID-19 bivalent vaccine. Objective: To evaluate stroke risk after administration of (1) either brand of the COVID-19 bivalent vaccine, (2) either brand of the COVID-19 bivalent plus a high-dose or adjuvanted influenza vaccine on the same day (concomitant administration), and (3) a high-dose or adjuvanted influenza vaccine. Design, Setting, and Participants: Self-controlled case series including 11 001 Medicare beneficiaries aged 65 years or older who experienced stroke after receiving either brand of the COVID-19 bivalent vaccine (among 5 397 278 vaccinated individuals). The study period was August 31, 2022, through February 4, 2023. Exposures: Receipt of (1) either brand of the COVID-19 bivalent vaccine (primary) or (2) a high-dose or adjuvanted influenza vaccine (secondary). Main Outcomes and Measures: Stroke risk (nonhemorrhagic stroke, transient ischemic attack, combined outcome of nonhemorrhagic stroke or transient ischemic attack, or hemorrhagic stroke) during the 1- to 21-day or 22- to 42-day risk window after vaccination vs the 43- to 90-day control window. Results: There were 5 397 278 Medicare beneficiaries who received either brand of the COVID-19 bivalent vaccine (median age, 74 years [IQR, 70-80 years]; 56% were women). Among the 11 001 beneficiaries who experienced stroke after receiving either brand of the COVID-19 bivalent vaccine, there were no statistically significant associations between either brand of the COVID-19 bivalent vaccine and the outcomes of nonhemorrhagic stroke, transient ischemic attack, nonhemorrhagic stroke or transient ischemic attack, or hemorrhagic stroke during the 1- to 21-day or 22- to 42-day risk window vs the 43- to 90-day control window (incidence rate ratio [IRR] range, 0.72-1.12). Among the 4596 beneficiaries who experienced stroke after concomitant administration of either brand of the COVID-19 bivalent vaccine plus a high-dose or adjuvanted influenza vaccine, there was a statistically significant association between vaccination and nonhemorrhagic stroke during the 22- to 42-day risk window for the Pfizer-BioNTech BNT162b2; WT/OMI BA.4/BA.5 COVID-19 bivalent vaccine (IRR, 1.20 [95% CI, 1.01-1.42]; risk difference/100 000 doses, 3.13 [95% CI, 0.05-6.22]) and a statistically significant association between vaccination and transient ischemic attack during the 1- to 21-day risk window for the Moderna mRNA-1273.222 COVID-19 bivalent vaccine (IRR, 1.35 [95% CI, 1.06-1.74]; risk difference/100 000 doses, 3.33 [95% CI, 0.46-6.20]). Among the 21 345 beneficiaries who experienced stroke after administration of a high-dose or adjuvanted influenza vaccine, there was a statistically significant association between vaccination and nonhemorrhagic stroke during the 22- to 42-day risk window (IRR, 1.09 [95% CI, 1.02-1.17]; risk difference/100 000 doses, 1.65 [95% CI, 0.43-2.87]). Conclusions and Relevance: Among Medicare beneficiaries aged 65 years or older who experienced stroke after receiving either brand of the COVID-19 bivalent vaccine, there was no evidence of a significantly elevated risk for stroke during the days immediately after vaccination.

High Variability of Body Mass Index Is Independently Associated With Incident Heart Failure.

BACKGROUND: Heart failure (HF) is a serious condition with increasing prevalence, high morbidity, and increased mortality. Obesity is an established risk factor for HF. Fluctuation in body mass index (BMI) has shown a higher risk of cardiovascular outcomes. We investigated the association between BMI variability and incident HF. METHODS AND RESULTS: In the UK Biobank, we established a prospective cohort after excluding participants with prevalent HF or cancer at enrollment. A total of 99 368 White participants with ≥3 BMI measures during >2 years preceding enrollment were included, with a median follow-up of 12.5 years. The within-participant variability of BMI was evaluated using standardized SD and coefficient of variation. The association of BMI variability with incident HF was assessed using Fine and Gray's competing risk model, adjusting for confounding factors and participant-specific rate of BMI change. Higher BMI variability measured in both SD and coefficient of variation was significantly associated with higher risk in HF incidence (SD: hazard ratio [HR], 1.05 [95% CI, 1.03-1.08], P<0.0001; coefficient of variation: HR, 1.07 [95% CI, 1.04-1.10], P<0.0001). CONCLUSIONS: Longitudinal health records capture BMI fluctuation, which independently predicts HF incidence.

High Variability of Body Mass Index Independently Associated with Incident Heart Failure.

Background: Heart failure (HF) is a serious condition with increasing prevalence, high morbidity, and increased mortality. Obesity is an established risk factor for cardiovascular diseases, including HF. Fluctuation in body mass index (BMI) has shown a higher risk of cardiovascular outcomes. We investigated the association between BMI variability and incident HF. Methods: In the UK Biobank, we established a prospective cohort after excluding participants with prevalent HF or cancer at enrollment. A total of 99,368 White (British, Irish, and any other white background) participants with ≥ 3 BMI measures during > 2 years preceding enrollment were included, with a median follow-up of 12.5 years. The within-participant variability of BMI was evaluated using standardized standard deviation (SD) and coefficient of variation (CV). The association of BMI variability with incident HF was assessed using Fine and Gray's competing risk model, and adjusted for age, sex, smoking history, alcohol consumption, diabetes, hypertension, history of heart attack, stroke, atrial fibrillation, lipids, estimated glomerular filtration rate and mean BMI per individual. Results: In the fully adjusted model, higher BMI variability measured in both SD and CV were significantly associated with higher risk in HF incidence (SD: Hazard Ratio [HR] 1.05, 95% Confidence Interval [CI] 1.02 - 1.07, p = 0.0002; CV: HR 1.06, 95% CI 1.04 - 1.09, p < 0.0001). Conclusions: Longitudinal health records capture BMI fluctuation, which independently predicts HF incidence. Integration of long-term BMI and other routinely measured health factors may improve risk prediction of HF and other cardiovascular outcomes.

Crosstalk between Host Genome and Metabolome among People with HIV in South Africa.

Genome-wide association studies (GWAS) of circulating metabolites have revealed the role of genetic regulation on the human metabolome. Most previous investigations focused on European ancestry, and few studies have been conducted among populations of African descent living in Africa, where the infectious disease burden is high (e.g., human immunodeficiency virus (HIV)). It is important to understand the genetic associations of the metabolome in diverse at-risk populations including people with HIV (PWH) living in Africa. After a thorough literature review, the reported significant gene−metabolite associations were tested among 490 PWH in South Africa. Linear regression was used to test associations between the candidate metabolites and genetic variants. GWAS of 154 plasma metabolites were performed to identify novel genetic associations. Among the 29 gene−metabolite associations identified in the literature, we replicated 10 in South Africans with HIV. The UGT1A cluster was associated with plasma levels of biliverdin and bilirubin; SLC16A9 and CPS1 were associated with carnitine and creatine, respectively. We also identified 22 genetic associations with metabolites using a genome-wide significance threshold (p-value < 5 × 10−8). In a GWAS of plasma metabolites in South African PWH, we replicated reported genetic associations across ancestries, and identified novel genetic associations using a metabolomics approach.