Incremento del riesgo cardiovascular en pacientes con COVID-19 a corto y largo plazo

Si bien la COVID-19 es una enfermedad dominantemente y los síntomas respiratorios tienden a ser la presentación clínica inicial, la evidencia acumulada ha sugerido que esta entidad clínica está estrechamente asociada con complicaciones cardiovasculares. Aunado a esto, aunque inicialmente se evidenció que las complicaciones cardiovasculares forman parte de la presentación aguda de la COVID-19, se dispone de datos limitados a largo plazo de las complicaciones posteriores a la misma. Hoy en día algunos estudios soportan que este tipo de complicaciones pueden persistir después de la resolución de la infección, evidenciándose la necesidad de un mayor entendimiento de las implicaciones a corto y largo plazo de la infección por SARS-CoV-2. El objetivo de esta revisión sintetizar la evidencia actual de las complicaciones cardiovasculares a corto y largo plazo de la COVID-19.Alternate :Although COVID-19 is a predominantly respiratory disease, and respiratory symptoms tend to be the initial clinical presentation, accumulated evidence suggests this clinical entity is closely related to cardiovascular complications. In addition, although cardiovascular complications have been an early observation of the acute presentation of COVID-19, limited data is available regarding the long-term complications in this respect. At present, some studies suggest that the risk for this type of complications may persist after the resolution of the infection, highlighting the need for a greater understanding of the implication of the SARS-CoV-2 infection in the short and long term. The objective of this review is to synthesize current evidence on the short-term and long-term cardiovascular complications of COVID-19.

In Silico Analyses of Immune System Protein Interactome Network, Single-Cell RNA Sequencing of Human Tissues, and Artificial Neural Networks Reveal Potential Therapeutic Targets for Drug Repurposing Against COVID-19 (preprint)

There is pressing urgency to better understand the immunological underpinnings of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2) in order to identify potential therapeutic targets and drugs that allow treating patients effectively. To fill in this gap, we performed in silico analyses of immune system protein interactome network, single-cell RNA sequencing of human tissues, and artificial neural networks to reveal potential therapeutic targets for drug repurposing against COVID-19. As results, the high-confidence protein interactome network was conformed by 1,588 nodes between immune system proteins and human proteins physically associated with SARS-CoV-2. Subsequently, we screened all these nodes in ACE2 and TMPRSS2 co-expressing cells according to the Alexandria Project, finding 75 potential therapeutic targets significantly overexpressed (Z score > 2) in nasal goblet secretory cells, lung type II pneumocytes, and ileal absorptive enterocytes of patients with several immunopathologies. Then, we performed fully connected deep neural networks to find the best multitask classification model to predict the activity of 10,672 drugs for 25 of the 75 aforementioned proteins. On one hand, we obtained 45 approved drugs, 16 compounds under investigation, and 35 experimental compounds with the highest area under the receiver operating characteristic (AUROCs) for 15 immune system proteins. On the other hand, we obtained 4 approved drugs, 9 compounds under investigation, and 16 experimental compounds with the highest multi-target affinities for 9 immune system proteins. In conclusion, computational structure-based drug discovery focused on immune system proteins is imperative to select potential drugs that, after being effectively analyzed in cell lines and clinical trials, these can be considered for treatment of complex symptoms of COVID-19 patients, and for co-therapies with drugs directly targeting SARS-CoV-2.