Background: This study compares the severity of SARS-CoV-2 infections caused by Alpha, Delta or Omicron variants in periods of co-circulation in Spain, and estimates the variant-specific association of vaccination with severe disease. Methods: SARS-CoV-2 infections notified to the national epidemiological surveillance network with information on genetic variant and vaccination status were considered cases if they required hospitalisation or controls otherwise. Alpha and Delta were compared during June-July 2021; and Delta and Omicron during December 2021-January 2022. Adjusted odds ratios (aOR) were estimated using logistic regression, comparing variant and vaccination status between cases and controls. Results: We included 5,345 Alpha and 11,974 Delta infections in June-July and 5,272 Delta and 10,578 Omicron in December-January. Unvaccinated cases of Alpha (aOR: 0.57; 95% CI: 0.46-0.69) or Omicron (0.28; 0.21-0.36) had lower probability of hospitalisation vs. Delta. Complete vaccination reduced hospitalisation, similarly for Alpha (0.16; 0.13-0.21) and Delta (June-July: 0.16; 0.14-0.19; December-January: 0.36; 0.30-0.44) but lower from Omicron (0.63; 0.53-0.75) and individuals aged 65+ years. Conclusion: Results indicate higher intrinsic severity of the Delta variant, compared with Alpha or Omicron, with smaller differences among vaccinated individuals. Nevertheless, vaccination was associated to reduced hospitalisation in all groups. (c) 2022 The Authors. Published by Elsevier Espan a, S.L.U. on behalf of Sociedad Espan ola de Enfermedades Infecciosas y Microbiolog & imath;a Cl & imath;nica. This is an open access article under the CC BY-NC-ND

Human health risk assessment of chemical mixtures is complex due to the almost infinite number of possible combinations of chemicals to which people are exposed to on a daily basis. Human biomonitoring (HBM) approaches can provide inter alia information on the chemicals that are in our body at one point in time. Network analysis applied to such data may provide insight into real-life mixtures by visualizing chemical exposure patterns. The identification of groups of more densely correlated biomarkers, so-called “communities”, within these networks highlights which combination of substances should be considered in terms of real-life mixtures to which a population is exposed. We applied network analyses to HBM datasets from Belgium, Czech Republic, Germany, and Spain, with the aim to explore its added value for exposure and risk assessment. The datasets varied in study population, study design, and chemicals analysed. Sensitivity analysis was performed to address the influence of different approaches to standardise for creatinine content of urine. Our approach demonstrates that network analysis applied to HBM data of highly varying origin provides useful information with regards to the existence of groups of biomarkers that are densely correlated. This information is relevant for regulatory risk assessment, as well as for the design of relevant mixture exposure experiments.

Arsenic (As) is a toxic metalloid widely distributed in the environment. Chronic exposure to As has been associated with the development of several types of cancer. However, its role in prostate cancer (PC) remains unclear. To evaluate the relationship between As exposure and the risk of PC, considering different clinical tumour classifications and genetic susceptibility, and to compare biomarkers that may reflect distinct exposure windows. We included 345 incident cases and 468 controls with available data on both urinary and toenail As concentrations within the MCC-Spain project. Toenail and urinary As levels were measured using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES), respectively. Genetic susceptibility was assessed using a polygenic risk score (PRS) based on Single-Nucleotide Polymorphisms. Associations between As exposure and PC were examined using mixed-effects and multinomial logistic regression models. Higher toenail As concentrations were associated with increased risk of PC [odds ratio (OR) comparing the fourth to first quartile: 1.94; 95 % confidence interval (CI):1.23-3.06]. Stratified analyses by tumor classification showed consistent risk increases for advanced and aggressive tumors [ISUP3-5 Relative risk ratio (RRR) quartile 4vs.1: 2.86 (1.16-7.06); AJCC IIB-IV RRR: 2.58 (1.48-4.50); cT2-cT4 RRR: 3.05 (1.55-5.99)]. No clear association was found with urinary As concentrations. Interaction analyses showed no evidence of effect modification by PRS. Elevated toenail As levels were associated with an increased risk of PC, especially in advanced disease, suggesting that toenails represent a more reliable biomarker for assessing long-term As exposure.

Toenails are commonly used as biomarkers of exposure to zinc (Zn), but there is scarce information about their relationship with sources of exposure to Zn. To investigate the main determinants of toenail Zn, including selected sources of environmental exposure to Zn and individual genetic variability in Zn metabolism. We determined toenail Zn by inductively coupled plasma mass spectrometry in 3,448 general population controls from the MultiCase-Control study MCC-Spain. We assessed dietary and supplement Zn intake using food frequency questionnaires, residential proximity to Zn-emitting industries and residential topsoil Zn levels through interpolation methods. We constructed a polygenic score of genetic variability based on 81 single nucleotide polymorphisms in genes involved in Zn metabolism. Geometric mean ratios of toenail Zn across categories of each determinant were estimated from multivariate linear regression models on log-transformed toenail Zn. Geometric mean toenail Zn was 104.1 µg/g in men and 100.3 µg/g in women. Geometric mean toenail Zn levels were 7 % lower (95 % confidence interval 1-13 %) in men older than 69 years and those in the upper tertile of fibre intake, and 9 % higher (3-16 %) in smoking men. Women residing within 3 km from Zn-emitting industries had 4 % higher geometric mean toenail Zn levels (0-9 %). Dietary Zn intake and polygenic score were unrelated to toenail Zn. Overall, the available determinants only explained 9.3 % of toenail Zn variability in men and 4.8 % in women. Sociodemographic factors, lifestyle, diet, and environmental exposure explained little of the individual variability of toenail Zn in the study population. The available genetic variants related to Zn metabolism were not associated with toenail Zn.