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1.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-20202820

RESUMEN

Introductory paragraphParticular host and environmental factors influence susceptibility to severe COVID-19. We analyzed RNA-sequencing data from bronchial epithelial brushings - a relevant tissue for SARS-CoV-2 infection - obtained from three cohorts of uninfected individuals, and investigated how non-genetic and genetic factors affect the regulation of host genes implicated in COVID-19. We found that ACE2 expression was higher in relation to active smoking, obesity, and hypertension that are known risk factors of COVID-19 severity, while an association with interferon-related inflammation was driven by the truncated, non-binding ACE2 isoform. We discovered that expression patterns of a suppressed airway immune response to early SARS-CoV-2 infection, compared to other viruses, are similar to patterns associated with obesity, hypertension, and cardiovascular disease, which may thus contribute to a COVID-19-susceptible airway environment. eQTL mapping identified regulatory variants for genes implicated in COVID-19, some of which had pheWAS evidence for their potential role in respiratory infections. These data provide evidence that clinically relevant variation in the expression of COVID-19-related genes is associated with host factors, environmental exposures, and likely host genetic variation.

2.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-20155382

RESUMEN

RationaleCOVID-19-associated respiratory failure offers the unprecedented opportunity to evaluate the differential host response to a uniform pathogenic insult. Prior studies of Acute Respiratory Distress Syndrome (ARDS) have identified subphenotypes with differential outcomes. Understanding whether there are distinct subphenotypes of severe COVID-19 may offer insight into its pathophysiology. ObjectivesTo identify and characterize distinct subphenotypes of COVID-19 critical illness defined by the post-intubation trajectory of Sequential Organ Failure Assessment (SOFA) score. MethodsIntubated COVID-19 patients at two hospitals in New York city were leveraged as development and validation cohorts. Patients were grouped into mild, intermediate, and severe strata by their baseline post-intubation SOFA. Hierarchical agglomerative clustering was performed within each stratum to detect subphenotypes based on similarities amongst SOFA score trajectories evaluated by Dynamic Time Warping. Statistical tests defined trajectory subphenotype predictive markers. Measurements and Main ResultsDistinct worsening and recovering subphenotypes were identified within each stratum, which had distinct 7-day post-intubation SOFA progression trends. Patients in the worsening suphenotypes had a higher mortality than those in the recovering subphenotypes within each stratum (mild stratum, 29.7% vs. 10.3%, p=0.033; intermediate stratum, 29.3% vs. 8.0%, p=0.002; severe stratum, 53.7% vs. 22.2%, p<0.001). Worsening and recovering subphenotypes were replicated in the validation cohort. Routine laboratory tests, vital signs, and respiratory variables rather than demographics and comorbidities were predictive of the worsening and recovering subphenotypes. ConclusionsThere are clear worsening and recovering subphenotypes of COVID-19 respiratory failure after intubation, which are more predictive of outcomes than baseline severity of illness. Organ dysfunction trajectory may be well suited as a surrogate for research in COVID-19 respiratory failure. At a Glance CommentaryO_ST_ABSScientific Knowledge on the SubjectC_ST_ABSCOVID-19 associated respiratory failure leads to a significant risk of morbidity and mortality. It is clear that there is heterogeneity in the viral-induced host response leading to differential outcomes, even amongst those treated with mechanical ventilation. There are many studies of COVID-19 disease which use intubation status as an outcome or an inclusion criterion. However, there is less understanding of the post intubation course in COVID-19. What This Study Adds to the FieldWe have developed and validated a novel subphenotyping model based on post-intubation organ dysfunction trajectory in COVID-19 patients. Specifically, we identified clear worsening and recovering organ dysfunction trajectory subphenotypes, which are more predictive of outcomes than illness severity at baseline. Dynamic inflammatory markers and ventilator variables rather than baseline severity of illness, demographics and comorbidities differentiate the worsening and recovering subphenotypes. Trajectory subphenotypes offer a potential road map for understanding the evolution of critical illness in COVID-19.

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