RESUMO
Infection by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) leads to multi-organ failure associated with a cytokine storm and septic shock. The virus evades the mitochondrial production of interferons through its N protein and, from that moment on, it hijacks the functions of these organelles. The aim of this study was to show how the virus kidnaps the mitochondrial machinery for its benefit and survival, leading to alterations of serum parameters and to nitrosative stress (NSS). In a prospective cohort of 15 postmortem patients who died from COVID-19, six markers of mitochondrial function (COX II, COX IV, MnSOD, nitrotyrosine, Bcl-2 and caspase-9) were analyzed by the immune colloidal gold technique in samples from the lung, heart, and liver. Biometric laboratory results from these patients showed alterations in hemoglobin, platelets, creatinine, urea nitrogen, glucose, C-reactive protein, albumin, D-dimer, ferritin, fibrinogen, Ca²âº, Kâº, lactate and troponin. These changes were associated with alterations in the mitochondrial structure and function. The multi-organ dysfunction present in COVID-19 patients may be caused, in part, by damage to the mitochondria that results in an inflammatory state that contributes to NSS, which activates the sepsis cascade and results in increased mortality in COVID-19 patients.
Assuntos
COVID-19/patologia , Mitocôndrias/patologia , Estresse Nitrosativo/fisiologia , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , SARS-CoV-2RESUMO
Dipeptidyl peptidase-4 (DPP4) can influence lipid homeostasis and atherosclerosis progression. We aimed to assess the association of DPP4 gene polymorphisms with hypoalphalipoproteinemia and DPP4 serum levels, in a cohort of Mexican individuals. Five DPP4 polymorphisms (rs12617336, rs12617656, rs1558957, and rs3788979, and rs17574) were genotyped in 748 participants with and 745 without hypoalphalipoproteinemia. The associations were evaluated using logistic regression analyses. Under inheritance models adjusted for confounding variables, the rs12617336 (OR = 0.22, P heterozygote = 0.001) and rs17574 (OR = 0.78, P additive = 0.022; OR = 0.73, P dominant = 0.012; OR = 0.73, P heterozygote = 0.017; OR = 0.72, P codominant 1 = 0.014) minor alleles were associated with a low risk of hypoalphalipoproteinemia. After the correction for multiple comparisons, the associations were marginal except the association of the rs12617336 that remaining significant. Additionally, both DPP4 minor alleles were associated with protection for the presence of insulin resistance (IR) (OR = 0.17, P heterozygote = 0.019 for rs12617336 and OR = 0.75, P additive = 0.049 for rs17574). The rs12617336 minor allele was also associated with a low risk of hyperinsulinemia (OR = 0.11, P heterozygote = 0.006). Differences in DPP4 levels were observed in individuals with rs17574 genotypes, the rs17574 GG genotype individuals had the lowest levels. Our data suggest that rs12617336 and rs17574 DPP4 minor alleles could be envisaged as protective genetic markers for hypoalphalipoproteinemia, IR, and hyperinsulinemia. The rs17574 GG genotype was associated with the lowest DPP4 levels.
RESUMO
Objetivos: Establecer la precisión diagnóstica por tomografía computarizada (TC) de la probabilidad de neumopatía por enfermedad por coronavirus 2019 (COVID-19), dada por el sistema de inteligencia artificial (IA) diseñado por Siemens, y el resultado de la evaluación cualitativa CO-RADS (COVID-19 Reporting and Data System) con el estándar de referencia reacción en cadena de la polimerasa transcriptasa inversa (RT-PCR), entregando así la experiencia de nuestra institución. Métodos: Se realizó un estudio observacional, comparativo y retrolectivo en 192 pacientes adultos con sospecha de infección por coronavirus 2 del síndrome respiratorio agudo grave (SARS-CoV-2) que contaban con prueba PCR. Se obtuvo la información de precisión diagnóstica luego de comparar el estándar de referencia (RT- PCR) con el CO-RADS realizado por los observadores y la probabilidad de COVID-19 que arrojaron las imágenes de TC mediante la IA. Resultados: La comparación de la probabilidad de COVID-19 obtenida por la IA vs. la RT-PCR para SARS-CoV- 2 generó un AUC ROC de 0.774 (IC: 0.69-0.81) con p = 0.0001. La probabilidad de COVID-19 tuvo una precisión aceptable, con un buen valor predictivo positivo del 87.80%, pero con un pobre valor predictivo negativo del 58.80%. La variable CO-RADS vs. PCR obtuvo una mayor precisión con valores de sensibilidad y especificidad del 91.80 y 88.7% respectivamente. Conclusión: La comparación entre los resultados obtenidos por la IA y por la variable CO-RADS mostró mayor efectividad en esta última, sin embargo se logró documentar el alto impacto que tiene el sistema de cuantificación automática en la evaluación de estos pacientes, ya que permite agilizar la valoración del radiólogo y funciona como complemento en casos de dudas diagnósticas.