Genomic Characterization of SARS-CoV-2 Isolated from Patients with Distinct Disease Outcomes in Mexico.

The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has shown a wide spectrum of clinical manifestations ranging from asymptomatic infections to severe disease and death. Pre-existing medical conditions and age have been mainly linked to the development of severe disease; however, the potential association of viral genetic characteristics with different clinical conditions remains unclear. SARS-CoV-2 variants with increased transmissibility were detected early in the pandemics, and several variants with potential relevance for public health are currently circulating around the world. In this study, we characterized 57 complete SARS-CoV-2 genomes during the exponential growth phase of the early epidemiological curve in Mexico, in April 2020. Patients were categorized under distinct disease severity outcomes: mild disease or ambulatory care, severe disease or hospitalized, and deceased. To reduce bias related to risk factors, the patients were less than 60 years old and with no diagnosed comorbidities A trait-association phylogenomic approach was used to explore genotype-phenotype associations, represented by the co-occurrence of mutations, disease severity outcome categories, and clusters of Mexican sequences. Phylogenetic results revealed a higher genomic diversity compared to the initial viruses detected during the early stage of the local epidemic. We identified a total of 90 single nucleotide variants compared to the Wuhan-Hu-1 genome, including 54 nonsynonymous mutations. We did not find evidence for the co-occurrence of mutations associated with specific disease outcomes. Therefore, in the group of patients studied, disease severity was likely mainly driven by the host genetic background and other demographic factors. IMPORTANCE The genetic association of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) with different clinical conditions remains unclear and needs further investigation. In this study, we characterized 57 complete SARS-CoV-2 genomes from patients in Mexico with distinct disease severity outcomes: mild disease or ambulatory care, severe disease or hospitalized, and deceased. To reduce bias related to risk factors the patients were less than 60 years old and with no diagnosed comorbidities. We did not find evidence for the co-occurrence of mutations associated with specific disease outcomes. Therefore, in the group of patients studied, disease severity was likely mainly driven by the host genetic background and other demographic factors.

Chronic anticoagulation is not associated with a reduced risk of acute kidney injury in hospitalised Covid-19 patients.

BACKGROUND: Coronavirus-19 (COVID-19) has been declared a global pandemic by the World Health Organisation. Severe disease typically presents with respiratory failure but Acute Kidney Injury (AKI) and a hypercoagulable state can also occur. Early reports suggest that thrombosis may be linked with AKI. We studied the development of AKI and outcomes of patients with COVID-19 taking chronic anticoagulation therapy. METHODS: Electronic records were reviewed for all adult patients admitted to Manchester University Foundation Trust Hospitals between March 10 and April 302,020 with a diagnosis of COVID-19. Patients with end-stage kidney disease were excluded. AKI was classified as per KDIGO criteria. RESULTS: Of the 1032 patients with COVID-19 studied,164 (15.9%) were taking anticoagulant therapy prior to admission. There were similar rates of AKI between those on anticoagulants and those not anticoagulated (23.8% versus 19.7%) with no difference in the severity of AKI or requirement of renal replacement therapy between groups (1.2% versus 3.5%). Risk factors for AKI included hypertension, pre-existing renal disease and male sex. There was a higher mortality in those taking anticoagulant therapy (40.2% versus 30%). Patients taking anticoagulants were less likely to be admitted to the Intensive Care Unit (8.5% versus 17.4%) and to receive mechanical ventilation (42.9% versus 78.1%). CONCLUSION: Patients on chronic anticoagulant therapy did not have a reduced incidence or severity of AKI suggesting that AKI is unlikely to be thrombotic in nature. Therapeutic anticoagulation is currently still under investigation in randomised controlled studies to determine whether it has a potential role in COVID-19 treatment.

Association of Sickle Cell Trait with Risk and Mortality of COVID-19: Results from the United Kingdom Biobank.

Sickle cell trait (SCT) carriers inherit one copy of the Glu6Val mutation in the hemoglobin gene and is particularly common in Black individuals (5-10%). Considering the roles of hemoglobin in immune responses and the higher risk for coronavirus disease (COVID-19) among Black individuals, we tested whether Black SCT carriers were at increased risk for COVID-19 infection and mortality according to the United Kingdom Biobank. Among Black individuals who were tested for COVID-19, we found similar infection rates among SCT carriers (14/72; 19.7%) and noncarriers (167/791; 21.1%), but higher COVID-19 mortality rates among SCT carriers (4/14; 28.6%) than among noncarriers (21/167; 12.6%) (odds ratio [OR], 3.04; 95% confidence interval [CI], 0.69-11.82; P = 0.12). Notably, SCT carriers with preexisting diabetes had significantly higher COVID-19 mortality (4/4; 100%) than those without diabetes (0/10; 0%; (OR, 90.71; 95% CI, 5.66-infinite; P = 0.0005). These findings suggest that Black SCT carriers with preexisting diabetes are at disproportionally higher risk for COVID-19 mortality. Confirmation by larger studies is warranted.

Biological Aging Predicts Vulnerability to COVID-19 Severity in UK Biobank Participants.

BACKGROUND: Age and disease prevalence are the 2 biggest risk factors for Coronavirus disease 2019 (COVID-19) symptom severity and death. We therefore hypothesized that increased biological age, beyond chronological age, may be driving disease-related trends in COVID-19 severity. METHODS: Using the UK Biobank England data, we tested whether a biological age estimate (PhenoAge) measured more than a decade prior to the COVID-19 pandemic was predictive of 2 COVID-19 severity outcomes (inpatient test positivity and COVID-19-related mortality with inpatient test-confirmed COVID-19). Logistic regression models were used with adjustment for age at the pandemic, sex, ethnicity, baseline assessment centers, and preexisting diseases/conditions. RESULTS: Six hundred and thirteen participants tested positive at inpatient settings between March 16 and April 27, 2020, 154 of whom succumbed to COVID-19. PhenoAge was associated with increased risks of inpatient test positivity and COVID-19-related mortality (ORMortality = 1.63 per 5 years, 95% CI: 1.43-1.86, p = 4.7 × 10-13) adjusting for demographics including age at the pandemic. Further adjustment for preexisting diseases/conditions at baseline (ORM = 1.50, 95% CI: 1.30-1.73 per 5 years, p = 3.1 × 10-8) and at the early pandemic (ORM = 1.21, 95% CI: 1.04-1.40 per 5 years, p = .011) decreased the association. CONCLUSIONS: PhenoAge measured in 2006-2010 was associated with COVID-19 severity outcomes more than 10 years later. These associations were partly accounted for by prevalent chronic diseases proximate to COVID-19 infection. Overall, our results suggest that aging biomarkers, like PhenoAge may capture long-term vulnerability to diseases like COVID-19, even before the accumulation of age-related comorbid conditions.

Decomposing Differences in Coronavirus disease 2019-related Case-Fatality Rates across Seventeen Nations.

As of 1 November 2020, estimated case-fatality rates associated with coronavirus disease 2019 are not uniformly patterned across the world and differ substantially in magnitude. Given the global spatial heterogeneity in case-fatality rates, we applied the Blinder-Oaxaca regression decomposition technique to identify how putative sociodemographic, structural, and environmental sources influence variation in case-fatality rates. We show that compositional and associational differences in country-level risk factors explain a substantial proportion of the coronavirus disease 2019-related case-fatality rate gap across nations. Asian countries fair better vis-à-vis case-fatality rate differences mainly due to variation in returns to sociodemographic, structural, and environmental sources among their citizens, relative to those who share similar attributes but live in Europe or North America. The variation in case-fatality rate is driven by Asian populations being better able to buffer the harmful effects of the very risk factors purported to exacerbate the risk of coronavirus disease 2019-related death. The dire circumstances in which we find ourselves demand better understanding of how preexisting conditions across countries contribute to observed disparities in case-fatality rates.

Preexisting Comorbidities Predicting COVID-19 and Mortality in the UK Biobank Community Cohort.

BACKGROUND: Hospitalized COVID-19 patients tend to be older and frequently have hypertension, diabetes, or coronary heart disease, but whether these comorbidities are true risk factors (ie, more common than in the general older population) is unclear. We estimated associations between preexisting diagnoses and hospitalized COVID-19 alone or with mortality, in a large community cohort. METHODS: UK Biobank (England) participants with baseline assessment 2006-2010, followed in hospital discharge records to 2017 and death records to 2020. Demographic and preexisting common diagnoses association tested with hospitalized laboratory-confirmed COVID-19 (March 16 to April 26, 2020), alone or with mortality, in logistic models. RESULTS: Of 269 070 participants aged older than 65, 507 (0.2%) became COVID-19 hospital inpatients, of which 141 (27.8%) died. Common comorbidities in hospitalized inpatients were hypertension (59.6%), history of fall or fragility fractures (29.4%), coronary heart disease (21.5%), type 2 diabetes (type 2, 19. 9%), and asthma (17.6%). However, in models adjusted for comorbidities, age group, sex, ethnicity, and education, preexisting diagnoses of dementia, type 2 diabetes, chronic obstructive pulmonary disease, pneumonia, depression, atrial fibrillation, and hypertension emerged as independent risk factors for COVID-19 hospitalization, the first 5 remaining statistically significant for related mortality. Chronic kidney disease and asthma were risk factors for COVID-19 hospitalization in women but not men. CONCLUSIONS: There are specific high-risk preexisting comorbidities for COVID-19 hospitalization and related deaths in community-based older men and women. These results do not support simple age-based targeting of the older population to prevent severe COVID-19 infections.