ABSTRACT
BackgroundSARS-CoV-2 viral entry may disrupt angiotensin II (Ang II) homeostasis in part via ACE2 downregulation, potentially contributing to COVID-19 induced lung injury. Preclinical models of viral pneumonias that utilize ACE2 demonstrate Ang II type 1 receptor (AT1R) blockade mitigates lung injury, though observational COVID-19 data addressing the effect of AT1R blockade remain mixed. MethodsMulticenter, blinded, placebo-controlled randomized trial of losartan (50 mg PO twice daily for 10 days) versus placebo. Hospitalized patients with COVID-19 and a respiratory sequential organ failure assessment score of at least 1 and not already taking a renin-angiotensin-aldosterone system (RAAS) inhibitor were eligible. The primary outcome was the imputed partial pressure of oxygen to fraction of inspired oxygen (PaO2/FiO2) ratio at 7 days. Secondary outcomes included ordinal COVID-19 severity, oxygen, ventilator, and vasopressor-free days, and mortality. Losartan pharmacokinetics (PK) and RAAS components [Ang II, angiotensin-(1-7) (Ang-(1-7)), ACE, ACE2] were measured in a subgroup of participants. FindingsFrom April 2020 - February 2021, 205 participants were randomized, 101 to losartan and 104 to placebo. Compared to placebo, losartan did not significantly affect PaO2/FiO2 ratio at 7 days [difference of -24.8 (95% -55.6 to 6.1; p=0.12)]. Losartan did not improve any secondary clinical outcome, but worsened vasopressor-free days. PK data were consistent with appropriate steady-state concentrations, but we observed no significant effect of losartan on RAAS components. InterpretationInitiation of orally administered losartan to hospitalized patients with COVID-19 and acute lung injury does not improve PaO2 / FiO2 ratio at 7 days. These data may have implications for ongoing clinical trials. Trial RegistrationLosartan for Patients With COVID-19 Requiring Hospitalization (NCT04312009), https://clinicaltrials.gov/ct2/show/NCT04312009
ABSTRACT
With no known treatments or vaccine, COVID-19 presents a major threat, particularly to older adults, who account for the majority of severe illness and deaths. The age-related susceptibility is partly explained by increased comorbidities including dementia and type II diabetes [1]. While it is unclear why these diseases predispose risk, we hypothesize that increased biological age, rather than chronological age, may be driving disease-related trends in COVID-19 severity with age. To test this hypothesis, we applied our previously validated biological age measure (PhenoAge) [2] composed of chronological age and nine clinical chemistry biomarkers to data of 347,751 participants from a large community cohort in the United Kingdom (UK Biobank), recruited between 2006 and 2010. Other data included disease diagnoses (to 2017), mortality data (to 2020), and the UK national COVID-19 test results (to May 31, 2020) [3]. Accelerated aging 10-14 years prior to the start of the COVID-19 pandemic was associated with test positivity (OR=1.15 per 5-year acceleration, 95% CI: 1.08 to 1.21, p=3.2x10-6) and all-cause mortality with test-confirmed COVID-19 (OR=1.25, per 5-year acceleration, 95% CI: 1.09 to 1.44, p=0.002) after adjustment for demographics including current chronological age and pre-existing diseases or conditions. The corresponding areas under the curves were 0.669 and 0.803, respectively. Biological aging, as captured by PhenoAge, is a better predictor of COVID-19 severity than chronological age, and may inform risk stratification initiatives, while also elucidating possible underlying mechanisms, particularly those related to inflammaging.
ABSTRACT
The global COVID-19 pandemic has led to an urgent need for scalable methods for clinical diagnostics and viral tracking. Next generation sequencing technologies have enabled large-scale genomic surveillance of SARS-CoV-2 as thousands of isolates are being sequenced around the world and deposited in public data repositories. A number of methods using both short- and long-read technologies are currently being applied for SARS-CoV-2 sequencing, including amplicon approaches, metagenomic methods, and sequence capture or enrichment methods. Given the small genome size, the ability to sequence SARS-CoV-2 at scale is limited by the cost and labor associated with making sequencing libraries. Here we describe a low-cost, streamlined, all amplicon-based method for sequencing SARS-CoV-2, which bypasses costly and time-consuming library preparation steps. We benchmark this tailed amplicon method against both the ARTIC amplicon protocol and sequence capture approaches and show that an optimized tailed amplicon approach achieves comparable amplicon balance, coverage metrics, and variant calls to the ARTIC v3 approach and represents a cost-effective and highly scalable method for SARS-CoV-2 sequencing.
ABSTRACT
The COVID-19 global pandemic is an unprecedented health emergency. Insufficient access to testing has hampered effective public health interventions and patient care management in a number of countries. Furthermore, the availability of regulatory-cleared reagents has challenged widespread implementation of testing. We rapidly developed a qRT-PCR SARS-CoV-2 detection assay using a 384-well format and tested its analytic performance across multiple nucleic acid extraction kits. Our data shows robust analytic accuracy on residual clinical biospecimens. Limit of detection sensitivity and specificity was confirmed with currently available commercial reagents. Our methods and results provide valuable information for other high-complexity laboratories seeking to develop effective, local, laboratory-developed procedures with high-throughput capability to detect SARS-CoV-2.
