Suchergebnisse

The heterogenous distribution of both COVID-19 incidence and mortality in Catalonia (Spain) during the firsts moths of the pandemic suggests that differences in baseline risk factors across regions might play a relevant role in modulating the outcome of the pandemic. This paper investigates the associations between both COVID-19 incidence and mortality and air pollutant concentration levels, and screens the potential effect of the type of agri-food industry and the overall land use and cover (LULC) at area level. ; Quim Zaldo-Aubanell was supported by AGAUR FI fellowship (DOGC num. 7720, of5.10.2018). Marc Saez was partially financed by the SUPERA COVID19 Fund, from SAUN: SantanderUniversidades, CRUE and CSIC, and by the COVID-19 Competitive Grant Program from PfizerGlobal Medical Grants. E. David Pino acknowledge the support of the Spanish government projectCGL2016-75996-R (MICINN) The funding sources did not participate in the design or conduct of thestudy, the collection, management, analysis, or interpretation of the data, or the preparation, review,or approval of the manuscript. ; Postprint (published version)

The heterogenous distribution of both COVID-19 incidence and mortality in Catalonia (Spain) during the firsts moths of the pandemic suggests that differences in baseline risk factors across regions might play a relevant role in modulating the outcome of the pandemic. This paper investigates the associations between both COVID-19 incidence and mortality and air pollutant concentration levels, and screens the potential effect of the type of agri-food industry and the overall land use and cover (LULC) at area level. We used a main model with demographic, socioeconomic and comorbidity covariates highlighted in previous research as important predictors. This allowed us to take a glimpse of the independent effect of the explanatory variables when controlled for the main model covariates. Our findings are aligned with previous research showing that the baseline features of the regions in terms of general health status, pollutant concentration levels (here NO and PM ), type of agri-food industry, and type of land use and land cover have modulated the impact of COVID-19 at a regional scale. This study is among the first to explore the associations between COVID-19 and the type of agri-food industry and LULC data using a population-based approach. The results of this paper might serve as the basis to develop new research hypotheses using a more comprehensive approach, highlighting the inequalities of regions in terms of risk factors and their response to COVID-19, as well as fostering public policies towards more resilient and safer environments. ; Quim Zaldo-Aubanell was supported by AGAUR FI fellowship (DOGC num. 7720, of 5.10.2018). Marc Saez was partially financed by the SUPERA COVID19 Fund, from SAUN: Santander Universidades, CRUE and CSIC, and by the COVID-19 Competitive Grant Program from Pfizer Global Medical Grants. E. David Pino acknowledge the support of the Spanish government project CGL2016-75996-R (MICINN) The funding sources did not participate in the design or conduct of the study, the collection, management, analysis, or interpretation of the data, or the preparation, review, or approval of the manuscript.

The heterogenous distribution of both COVID-19 incidence and mortality in Catalonia (Spain) during the firsts moths of the pandemic suggests that differences in baseline risk factors across regions might play a relevant role in modulating the outcome of the pandemic. This paper investigates the associations between both COVID-19 incidence and mortality and air pollutant concentration levels, and screens the potential effect of the type of agri-food industry and the overall land use and cover (LULC) at area level. We used a main model with demographic, socioeconomic and comorbidity covariates highlighted in previous research as important predictors. This allowed us to take a glimpse of the independent effect of the explanatory variables when controlled for the main model covariates. Our findings are aligned with previous research showing that the baseline features of the regions in terms of general health status, pollutant concentration levels (here NO2 and PM10), type of agri-food industry, and type of land use and land cover have modulated the impact of COVID-19 at a regional scale. This study is among the first to explore the associations between COVID-19 and the type of agri-food industry and LULC data using a population-based approach. The results of this paper might serve as the basis to develop new research hypotheses using a more comprehensive approach, highlighting the inequalities of regions in terms of risk factors and their response to COVID-19, as well as fostering public policies towards more resilient and safer environments ; Quim Zaldo-Aubanell was supported by AGAUR FI fellowship (DOGC num. 7720, of 5.10.2018). Marc Saez was partially financed by the SUPERA COVID19 Fund, from SAUN: Santander Universidades, CRUE and CSIC, and by the COVID-19 Competitive Grant Program from Pfizer Global Medical Grants. E. David Pino acknowledge the support of the Spanish government project CGL2016-75996-R (MICINN)

Risk prediction tools cannot identify most individuals at high coronary artery disease (CAD) risk. Oxidized low-density lipoproteins (oxLDLs) and microRNAs are actively involved in atherosclerosis. Our aim was to examine the association of CAD and oxLDLs-induced microRNAs, and to assess the microRNAs predictive capacity of future CAD events. Human endothelial and vascular smooth muscle cells were treated with oxidized/native low-density lipoproteins, and microRNA expression was analyzed. Differentially expressed and CAD-related miRNAs were examined in serum samples from (1) a case-control study with 476 myocardial infarction (MI) patients and 487 controls, and (2) a case-cohort study with 105 incident CAD cases and 455 randomly-selected cohort participants. MicroRNA expression was analyzed with custom OpenArray plates, log rank tests and Cox regression models. Twenty-one microRNAs, two previously undescribed (hsa-miR-193b-5p and hsa-miR-1229-5p), were up- or down-regulated upon cell treatment with oxLDLs. One of the 21, hsa-miR-122-5p, was also upregulated in MI cases (fold change = 4.85). Of the 28 CAD-related microRNAs tested, 11 were upregulated in MI cases -1 previously undescribed (hsa-miR-16-5p)-, and 1/11 was also associated with CAD incidence (adjusted hazard ratio = 0.55 (0.35-0.88)) and improved CAD risk reclassification, hsa-miR-143-3p. We identified 2 novel microRNAs modulated by oxLDLs in endothelial cells, 1 novel microRNA upregulated in AMI cases compared to controls, and one circulating microRNA that improved CAD risk classification. ; This work was supported by the Spain's Ministry of Science and Innovation (Madrid, Spain), co-financed with European Union European Regional Development Funds –ERDF- (FIS-CP12/03287, FIS-14/00449, FIS-PI081327, INTRASALUD PI11/01801, PI15/00064, IJCI-2016-29393 to DdG-C, CIBERCV (CB16/11/00229, 00246, 00403), CIBERESP CB06/02/0029, CIBEROBN CB06/03/0028); the Spain's ministry of Economy and Competiveness (Madrid, Spain) (BFU2016-75360-R); the BBVA Foundation (Bilbao, Spain) (PR-16-BIO-CAR-0041); the Health Departament of the Generalitat de Catalunya (Barcelona, Spain) through the Agència de Gestió d'Ajuts Universitaris de Recerca de Catalunya (AGAUR) (Barcelona, Spain) (2017SGR222), the Strategic Plan for research and health innovation (PERIS) (Barcelona, Spain) (SLT006/17/00234, SLT002/16/00145, SLT006/17/00029 to IRD); and by the Junta de Castilla y León (Valladolid, Spain) (VA114P17). CIBERs of Pathophysiology of Obesity and Nutrition (CIBEROBN), Cardiovascular Diseases (CIBERCV), and Epidemiology (CIBERESP) are initiatives of the Instituto de Salud Carlos III, Madrid, Spain.