Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Metanálise da relação entre espessura de toicinho e variáveis corporais e reprodutivas de porcas gestantes e lactantes Meta-analysis of relation among backfat thickness, body and reproductive variables of gestating and lactating sows

Um estudo de metanálise avaliou a relação entre a espessura de toicinho e as variáveis de condição corporal de porcas gestantes e lactantes. A base de dados contemplou 14 artigos publicados de 2000 a 2006 em revistas indexadas. A metanálise foi realizada através de análises gráfica, de correlação e de variância. A correlação da espessura de toicinho (ET) com o peso vivo foi de 0,16 (P<0,01), com a massa protéica de 0,48 (P<0,01) e com a concentração de leptina de 0,88 (P<0,01). A correlação da variação da espessura de toicinho na lactação (ETl) com o peso vivo foi de -0,21 (P<0,01), com variação do peso vivo na lactação de 0,34 (P<0,01) e com variação da massa lipídica na lactação de 0,70 (P<0,01). A correlação entre a ET e o número de leitões nascidos vivos foi de 0,46 (P<0,01), e entre a ETl e o PV dos leitões aos sete dias foi de 0,95 (P<0,01). A ET foi influenciada pelo peso vivo e pela massa protéica na gestação, enquanto a ETl é influenciada pela variação do peso vivo e pela massa lipídica na lactação. As concentrações de leptina ao parto estão correlacionadas positivamente com a ET. A ET é influenciada pelo número total de leitões nascidos vivos e pelo peso vivo dos leitões ao nascimento, enquanto a ETl é influenciada pelo peso vivo dos leitões aos sete dias e pelo ganho de peso vivo da leitegada. Há relação significativa entre espessura de toicinho e variáveis de condição corporal de porcas gestantes e lactantes.<br>A meta-analysis was carried out to evaluate the association between backfat thickness and sow body condition in gestation and lactation. The database assembled 14 publications from 2000 to 2006. The meta-analysis was accomplished by graphical analysis, correlation, and analysis of variance. The correlation between backfat thickness (BT) and body weight was 0.16 (P<0.01), with protein mass was 0.48 (P<0.01) and leptin concentration was 0.88 (P<0.01). The correlation between the backfat variation during and in lactation (VBTl) and body weight was -0.21 (P<0.01), with body weight variation in lactation was 0.34 (P<0.01) and with fat mass variation in lactation was 0.70 (P<0.01). The correlation between BT and born alive litter size was 0.46 (P<0.01), between VBTl and piglets body weight at seven days of age was 0.95 (P<0.01). In the gestation, the BD was influenced by the body weight and protein mass. However, in lactation the VBTl was influenced by the body weight variation and fat mass. The leptin concentration at farrowing was positively correlated with backfat depth. The BT was influenced by born alive litter size and piglets birth weight. The VBTl was influenced by piglets weight at seven days old and litter weight gain. In conclusion, there is a significant relation between backfat thickness and body variables of the sows in gestation and lactation