ABSTRACT
Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte-macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).
Subject(s)
COVID-19 , Critical Illness , Genetic Predisposition to Disease , Genetic Variation , Genome-Wide Association Study , Humans , COVID-19/genetics , Genetic Predisposition to Disease/genetics , Genotype , Phenotype , Genetic Variation/genetics , Whole Genome Sequencing , Transcriptome , Monocytes/metabolism , rab GTP-Binding Proteins/genetics , Genotyping TechniquesABSTRACT
OBJECTIVES: Evaluating whether meteorological and geographical variables could be associated with the severity of COVID-19 in Spain. METHODS: An ecological study was performed to analyze the influence of meteorological and geographical factors in hospital admissions and deaths due to COVID-19 in the 52 provinces of Spain (24 coastal and 28 inland regions), during the first three pandemic waves. Medical and mortality data were collected from the CarlosIII Health Institute (ISCIII) and meteorological variables were requested to the Spanish State Meteorological Agency (AEMET). RESULTS: Regarding the diagnosed cases it is remarkable that the percentage of patients hospitalized for COVID-19 was lower in the coastal provinces than in the inland ones (8.7±2.6% vs. 11.5±2.6%; P=9.9×10-5). Furthermore, coastal regions registered a lower percentage of mortality than inland regions (2.0±0.6% vs. 3.1±0.8%; P=1.7×10-5). Mean air temperature was inversely correlated both with COVID-19 hospitalizations (Rho: -0.59; P=3.0×10-6) and mortality (Rho: -0.70; P=5.3×10-9). In those provinces with a mean air temperature <10°C mortality by COVID-19 was twice that of those with >16°C. Finally, we found an association between mortality and the location of the province (coastal/inland), altitude, patient age and the average air temperature; the latter was inversely and independently correlated with mortality (non-standardized ß coeff.: -0.24; 95%CI: -0.31 to -0.16; P=2.38×10-8). CONCLUSIONS: The average air temperature was inversely associated with COVID-19 mortality in our country during the first three waves of the pandemic.
ABSTRACT
Objectives Evaluating whether meteorological and geographical variables could be associated with the severity of COVID-19 in Spain. Methods An ecological study was performed to analyze the influence of meteorological and geographical factors in hospital admissions and deaths due to COVID-19 in the 52 provinces of Spain (24 coastal and 28 inland regions), during the first three pandemic waves. Medical and mortality data were collected from the Carlos III Health Institute (ISCIII) and meteorological variables were requested to the Spanish State Meteorological Agency (AEMET). Results Regarding the diagnosed cases it is remarkable that the percentage of patients hospitalized for COVID-19 was lower in the coastal provinces than in the inland ones (8.7 ± 2.6% vs. 11.5 ± 2.6%;p = 9.9 × 10−5). Furthermore, coastal regions registered a lower percentage of mortality than inland regions (2.0 ± 0.6% vs. 3.1 ± 0.8%;p = 1.7 × 10−5). Mean air temperature was inversely correlated both with COVID-19 hospitalizations (Rho: −0.59;p = 3.0 × 10-6) and mortality (Rho: −0.70;p = 5.3 × 10−9). In those provinces with a mean air temperature <10 °C mortality by COVID-19 was twice that of those with >16 °C. Finally, we found an association between mortality and the location of the province (coastal/inland), altitude, patient age and the average air temperature;the latter was inversely and independently correlated with mortality (non standardised B coeff.: −0.24;IC 95%: −0.31 to −0.16;p = 2.38 × 10−8). Conclusions The average air temperature was inversely associated with COVID-19 mortality in our country during the first three waves of the pandemic.
ABSTRACT
Objectives: Evaluating whether meteorological and geographical variables could be associated with the severity of COVID-19 in Spain. Methods: An ecological study was performed to analyze the influence of meteorological and geographical factors in hospital admissions and deaths due to COVID-19 in the 52 provinces of Spain (24 coastal and 28 inland regions), during the first three pandemic waves. Medical and mortality data were collected from the Carlos III Health Institute (ISCIII) and meteorological variables were requested to the Spanish State Meteorological Agency (AEMET). Results: Regarding the diagnosed cases it is remarkable that the percentage of patients hospitalized for COVID-19 was lower in the coastal provinces than in the inland ones (8.7 ± 2.6% vs. 11.5 ± 2.6%; p = 9.9 × 10-5). Furthermore, coastal regions registered a lower percentage of mortality than inland regions (2.0 ± 0.6% vs. 3.1 ± 0.8%; p = 1.7 × 10-5). Mean air temperature was inversely correlated both with COVID-19 hospitalizations (Rho: -0.59; p = 3.0 × 10-6) and mortality (Rho: -0.70; p = 5.3 × 10-9). In those provinces with a mean air temperature <10 °C mortality by COVID-19 was twice that of those with >16 °C. Finally, we found an association between mortality and the location of the province (coastal/inland), altitude, patient age and the average air temperature; the latter was inversely and independently correlated with mortality (non standardised B coeff.: -0.24; IC 95%: -0.31 to -0.16; p = 2.38 × 10-8). Conclusions: The average air temperature was inversely associated with COVID-19 mortality in our country during the first three waves of the pandemic.
Objetivos: Evaluar si factores meteorológicos y geográficos pudieron relacionarse con la gravedad de la COVID-19 en España. Métodos: Estudio ecológico, a escala provincial, que analiza la influencia de factores meteorológicos y geográficos en la hospitalización y mortalidad por COVID-19 en las 52 provincias españolas (24 costeras y 28 del interior), durante las tres primeras olas. Los datos de hospitalizaciones y mortalidad se obtuvieron del Instituto de Salud Carlos III (ISCIII). Los datos epidemiológicos del Instituto Nacional Estadística (INE) y la Red Nacional de Vigilancia Epidemiológica (RENAVE). Las variables meteorológicas de la Agencia estatal de meteorología (AEMET). Resultados: El porcentaje de pacientes hospitalizados por COVID-19, del total de personas infectadas, fue inferior en las provincias costeras que en las del interior peninsular (8,7 ± 2,6% vs. 11,5 ± 2,6%; p = 9,9 × 10−5). De igual manera la costa registró menor porcentaje de mortalidad que el interior peninsular (2,0 ± 0,6% vs. 3,1 ± 0,8%; p = 1,7 × 10−5). La temperatura media correlacionó negativamente con la hospitalización (Rho: −0,59; p = 3,0 × 10−6) y la mortalidad por COVID-19 (Rho: −0,70; p = 5,3 × 10−9). Las provincias con una temperatura media <10 °C duplicaron la mortalidad por COVID respecto a las de >16 °C. La mortalidad se relacionó con la localización provincial (costa/interior), la altitud, la edad de la población y la temperatura media, siendo esta última la variable asociada de manera independiente (Coef. B no estandarizado: −0,24; IC 95%: −0,31 a −0,16; p = 2,38 × 10−8). Conclusiones: La mortalidad por COVID-19 durante las tres primeras olas de la pandemia en nuestro país se asoció inversamente con la temperatura media.
ABSTRACT
Objetivos: Evaluar si factores meteorológicos y geográficos pudieron relacionarse con la gravedad de la COVID-19 en España. Métodos: Estudio ecológico, a escala provincial, que analiza la influencia de factores meteorológicos y geográficos en la hospitalización y mortalidad por COVID-19 en las 52 provincias españolas (24 costeras y 28 del interior), durante las tres primeras olas. Los datos de hospitalizaciones y mortalidad se obtuvieron del Instituto de Salud Carlos III (ISCIII). Los datos epidemiológicos del Instituto Nacional Estadística (INE) y la Red Nacional de Vigilancia Epidemiológica (RENAVE). Las variables meteorológicas de la Agencia estatal de meteorología (AEMET). Resultados: El porcentaje de pacientes hospitalizados por COVID-19, del total de personas infectadas, fue inferior en las provincias costeras que en las del interior peninsular (8,7±2,6% vs. 11,5 ±2,6%;p=9,9x10-5). De igual manera la costa registró menor porcentaje de mortalidad que el interior peninsular (2,0±0,6% vs. 3,1±0,8%;p=1,7x10-5). La temperatura media correlacionó negativamente con la hospitalización (Rho: -0,59;p=3,0x10-6) y la mortalidad por COVID-19 (Rho: -0,70;p=5,3x10-9). Las provincias con una temperatura media <10ºC duplicaron la mortalidad por COVID respecto a las de >16ºC. La mortalidad se relacionó con la localización provincial (costa/interior), la altitud, la edad de la población y la temperatura media, siendo esta última la variable asociada de manera independiente (Coef. B no estandarizado: -0,24;IC 95%: -0,31 a -0,16;p=2,38x10-8). Conclusiones: La mortalidad por COVID-19 durante las tres primeras olas de la pandemia en nuestro país se asoció inversamente con la temperatura media.
ABSTRACT
Introducción: La obesidad es considerada un factor de riesgo en casos graves de la COVID-19, habiendo sido analizada mediante el índice de masa corporal (IMC), estimador que no correlaciona adecuadamente con el porcentaje de grasa corporal (GC). El objetivo de este estudio ha sido analizar la fracción atribuible poblacional a la GC en formas graves de COVID-19 atendiendo al IMC y al CUN-BAE. Material y métodos: Estudio multicéntrico observacional de prevalencia. Se recogió información sociodemográfica, antecedentes personales, IMC y CUN-BAE, de casos positivos SARS-CoV-2, de las provincias de León y La Rioja. Mediante modelos de regresión logística se calcularon odds ratio con sus respectivos intervalos de confianza del 95% ajustando por edad y antecedentes personales, así como la fracción atribuible poblacional a la GC. Resultados: Participaron 785 pacientes, 123 (15,7%) fueron graves. Se detectaron como factores de riesgo la edad, la obesidad (tanto por IMC como por CUN-BAE) y los antecedentes personales. Un 51,6% de casos graves podrían ser atribuidos a un exceso de IMC y un 61,4% a exceso GC estimada según CUN-BAE, observándose una mayor infraestimación del riesgo en mujeres. Conclusiones: El exceso de GC, es un factor de riesgo para formas graves de la COVID-19 junto con la edad avanzada y la presencia de enfermedades cardiovasculares, respiratorias crónicas u oncohematológicas. El IMC infraestima el riesgo, especialmente en mujeres, siendo el CUN-BAE el predictor seleccionado por su mejor estimación del porcentaje de GC.
ABSTRACT
PURPOSE: To determine whether a 6-day course of methylprednisolone (MP) improves outcome in patients with severe SARS-CoV2 (Corona Virus Disease 2019 [COVID-19]). METHODS: The study was a multicentric open-label trial of COVID-19 patients who were aged ≥â¯18 years, receiving oxygen without mechanical ventilation, and with evidence of systemic inflammatory response who were assigned to standard of care (SOC) or SOC plus intravenous MP (40â¯mg bid for 3 days followed by 20â¯mg bid for 3 days). The primary outcome was a composite of death, admission to the intensive care unit, or requirement for noninvasive ventilation. Both intention-to-treat (ITT) and per protocol (PP) analyses were performed. RESULTS: A total of 91 patients were screened, and 64 were randomized (mean age70⯱ 12 years). In the ITT analysis, 14 of 29 patients (48%) in the SOC group and 14 of 35 (40%) in the MP group suffered the composite endpoint (40% versus 20% in patients under 72 years and 67% versus 48% in those over 72 years; pâ¯= 0.25). In the PP analysis, patients on MP had a significantly lower risk of experiencing the composite endpoint (age-adjusted risk ratio 0.42; 95% confidence interval, CI 0.20-0.89; pâ¯= 0.043). CONCLUSION: The planned sample size was not achieved, and our results should therefore be interpreted with caution. The use of MP had no significant effect on the primary endpoint in ITT analysis; however, the PP analysis showed a beneficial effect due to MP, which consistent with other published trials support the use of glucocorticoids in severe cases of COVID-19.