Prognostic peripheral blood biomarkers at ICU admission predict COVID-19 clinical outcomes.

The COVID-19 pandemic continues to challenge the capacities of hospital ICUs which currently lack the ability to identify prospectively those patients who may require extended management. In this study of 90 ICU COVID-19 patients, we evaluated serum levels of four cytokines (IL-1ß, IL-6, IL-10 and TNFα) as well as standard clinical and laboratory measurements. On 42 of these patients (binned into Initial and Replication Cohorts), we further performed CyTOF-based deep immunophenotyping of peripheral blood mononuclear cells with a panel of 38 antibodies. All measurements and patient samples were taken at time of ICU admission and retrospectively linked to patient clinical outcomes through statistical approaches. These analyses resulted in the definition of a new measure of patient clinical outcome: patients who will recover after short ICU stays (< 6 days) and those who will subsequently die or recover after long ICU stays (≥6 days). Based on these clinical outcome categories, we identified blood prognostic biomarkers that, at time of ICU admission, prospectively distinguish, with 91% sensitivity and 91% specificity (positive likelihood ratio 10.1), patients in the two clinical outcome groups. This is achieved through a tiered evaluation of serum IL-10 and targeted immunophenotyping of monocyte subsets, specifically, CD11clow classical monocytes. Both immune biomarkers were consistently elevated ( ≥15 pg/ml and ≥2.7 x107/L for serum IL-10 and CD11clow classical monocytes, respectively) in those patients who will subsequently die or recover after long ICU stays. This highly sensitive and specific prognostic test could prove useful in guiding clinical resource allocation.

The need to streamline approval processes for clinical research in Canada: CMAJ

Lumia et al discuss Murthy and colleagues' commentary highlighting the need to improve Canada's current research infrastructure to support national clinical research studies. Murthy and colleagues note Canada's limited ability to rapidly conduct high-priority research, hindered by the need for separate data-sharing agreements and ethics review at each participating hospital site. They experienced long delays (6 mo to more than 1 yr) in receiving ethics and institutional approvals to conduct our low-risk, multisite observational study evaluating the long-term effects of COVID-19. The main factors that contributed to approval delays included the establishment and approval of data-sharing agreements at each of our 11 study sites (across 6 provinces) and separate, full-board ethics review at 5 study sites. Differences in local requirements for information technology and online security, collection of personal health data, recruitment processes, and data storage and retention also contributed to approval delays.

Prognostic peripheral blood biomarkers at ICU admission predict COVID-19 clinical outcomes

The COVID-19 pandemic continues to challenge the capacities of hospital ICUs which currently lack the ability to identify prospectively those patients who may require extended management. In this study of 90 ICU COVID-19 patients, we evaluated serum levels of four cytokines (IL-1β, IL-6, IL-10 and TNFα) as well as standard clinical and laboratory measurements. On 42 of these patients (binned into Initial and Replication Cohorts), we further performed CyTOF-based deep immunophenotyping of peripheral blood mononuclear cells with a panel of 38 antibodies. All measurements and patient samples were taken at time of ICU admission and retrospectively linked to patient clinical outcomes through statistical approaches. These analyses resulted in the definition of a new measure of patient clinical outcome: patients who will recover after short ICU stays (< 6 days) and those who will subsequently die or recover after long ICU stays (≥6 days). Based on these clinical outcome categories, we identified blood prognostic biomarkers that, at time of ICU admission, prospectively distinguish, with 91% sensitivity and 91% specificity (positive likelihood ratio 10.1), patients in the two clinical outcome groups. This is achieved through a tiered evaluation of serum IL-10 and targeted immunophenotyping of monocyte subsets, specifically, CD11clow classical monocytes. Both immune biomarkers were consistently elevated ( ≥15 pg/ml and ≥2.7 x107/L for serum IL-10 and CD11clow classical monocytes, respectively) in those patients who will subsequently die or recover after long ICU stays. This highly sensitive and specific prognostic test could prove useful in guiding clinical resource allocation.

Pulmonary rehabilitation in a postcoronavirus disease 2019 world: feasibility, challenges, and solutions.

PURPOSE OF REVIEW: Pulmonary rehabilitation improves clinical outcomes in patients with chronic obstructive pulmonary disease (COPD). Traditional centre-based (in-person) pulmonary rehabilitation was largely shut down in response to the COVID-19 pandemic, forcing many centres to rapidly shift to remote home-based programs in the form of telerehabilitation (tele-pulmonary rehabilitation). This review summarizes the recent evidence for the feasibility and effectiveness of remote pulmonary rehabilitation programs, and their implications for the delivery of pulmonary rehabilitation in a postpandemic world. RECENT FINDINGS: A number of innovative adaptations to pulmonary rehabilitation in response to COVID-19 have been reported, and the evidence supports tele-pulmonary rehabilitation as a viable alternative to traditional centre-based pulmonary rehabilitation. However, these studies also highlight the challenges that must be surmounted in order to see its widespread adoption. SUMMARY: There are outstanding questions regarding the optimal model for tele-pulmonary rehabilitation. In the post-COVID-19 world, a 'hybrid' model may be more desirable, with some components held in person and others via telehealth technology. This would be determined by the infrastructure and expertise of individual centres, and the needs of their patients. In order to achieve a truly patient-centred pulmonary rehabilitation program, high-quality studies addressing these outstanding questions, as well as multidisciplinary collaboration, are required.

The impact of lockdown timing on COVID-19 transmission across US counties.

BACKGROUND: Many countries have implemented lockdowns to reduce COVID-19 transmission. However, there is no consensus on the optimal timing of these lockdowns to control community spread of the disease. Here we evaluated the relationship between timing of lockdowns, along with other risk factors, and the growth trajectories of COVID-19 across 3,112 counties in the US. METHODS: We ascertained dates for lockdowns and implementation of various non-pharmaceutical interventions at a county level and merged these data with those of US census and county-specific COVID-19 daily cumulative case counts. We then applied a Functional Principal Component (FPC) analysis on this dataset to generate FPC scores, which were used as a surrogate variable to describe the trajectory of daily cumulative case counts for each county. We used machine learning methods to identify risk factors including the timing of lockdown that significantly influenced the FPC scores. FINDINGS: We found that the first eigen-function accounted for most (>92%) of the variations in the daily cumulative case counts. The impact of lockdown timing on the total daily case count of a county became significant beginning approximately 7 days prior to that county reporting at least 5 cumulative cases of COVID-19. Delays in lockdown implementation after this date led to a rapid acceleration of COVID-19 spread in the county over the first ~50 days from the date with at least 5 cumulative cases, and higher case counts across the entirety of the follow-up period. Other factors such as total population, median family income, Gini index, median age, and within-county mobility also had a substantial effect. When adjusted for all these factors, the timing of lockdowns was the most significant risk factor associated with the county-specific daily cumulative case counts. INTERPRETATION: Lockdowns are an effective way of controlling the spread of COVID-19 in communities. Significant delays in lockdown cause a dramatic increase in the cumulative case counts. Thus, the timing of the lockdown relative to the case count is an important consideration in controlling the pandemic in communities. FUNDING: The study period is from June 2020 to July 2021. Dr. Xuekui Zhang is a Tier 2 Canada Research Chairs (Grant No. 950231363) and funded by Natural Sciences and Engineering Research Council of Canada (Grant No. RGPIN201704722). Dr. Li Xing is funded by Natural Sciences and Engineering Research Council of Canada (Grant Number: RGPIN 202103530). This research was enabled in part by support provided by WestGrid (www.westgrid.ca) and Compute Canada (www.computecanada.ca). The computing resource is provided by Compute Canada Resource Allocation Competitions #3495 (PI: Xuekui Zhang) and #1551 (PI: Li Xing). Dr. Don Sin is a Tier 1 Canada Research Chair in COPD and holds the de Lazzari Family Chair at the Heart Lung Innovation, Vancouver, Canada.

COPD and the risk of poor outcomes in COVID-19: A systematic review and meta-analysis.

BACKGROUND: Patients with chronic obstructive pulmonary disease (COPD) are highly susceptible from respiratory exacerbations from viral respiratory tract infections. However, it is unclear whether they are at increased risk of COVID-19 pneumonia or COVID-19-related mortality. We aimed to determine whether COPD is a risk factor for adverse COVID-19 outcomes including hospitalization, severe COVID-19, or death. METHODS: Following the PRISMA guidelines, we performed a systematic review of COVID-19 clinical studies published between November 1st, 2019 and January 28th, 2021 (PROSPERO ID: CRD42020191491). We included studies that quantified the number of COPD patients, and reported at least one of the following outcomes stratified by COPD status: hospitalization; severe COVID-19; ICU admission; mechanical ventilation; acute respiratory distress syndrome; or mortality. We meta-analyzed the results of individual studies to determine the odds ratio (OR) of these outcomes in patients with COPD compared to those without COPD. FINDINGS: Fifty-nine studies met the inclusion criteria, and underwent data extraction. Most studies were retrospective cohort studies/case series of hospitalized patients. Only four studies examined the effects of COPD on COVID-19 outcomes as their primary endpoint. In aggregate, COPD was associated with increased odds of hospitalization (OR 4.23, 95% confidence interval [CI] 3.65-4.90), ICU admission (OR 1.35, 95% CI 1.02-1.78), and mortality (OR 2.47, 95% CI 2.18-2.79). INTERPRETATION: Having a clinical diagnosis of COPD significantly increases the odds of poor clinical outcomes in patients with COVID-19. COPD patients should thus be considered a high-risk group, and targeted for preventative measures and aggressive treatment for COVID-19 including vaccination.

Microchip RT-PCR Detection of Nasopharyngeal SARS-CoV-2 Samples.

Fast, accurate, and reliable diagnostic tests are critical for controlling the spread of the coronavirus disease 2019 (COVID-19) associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The current gold standard for testing is real-time PCR; however, during the current pandemic, supplies of testing kits and reagents have been limited. We report the validation of a rapid (30 minutes), user-friendly, and accurate microchip real-time PCR assay for detection of SARS-CoV-2 from nasopharyngeal swab RNA extracts. Microchips preloaded with COVID-19 primers and probes for the N gene accommodate 1.2-µL reaction volumes, lowering the required reagents by 10-fold compared with tube-based real-time PCR. We validated our assay using contrived reference samples and 21 clinical samples from patients in Canada, determining a limit of detection of 1 copy per reaction. The microchip real-time PCR provides a significantly lower resource alternative to the Centers for Disease Control and Prevention-approved real-time RT-PCR assays with comparable sensitivity, showing 100% positive and negative predictive agreement of clinical samples.

Pulmonary Rehabilitation in a Post-COVID-19 World: Telerehabilitation as a New Standard in Patients with COPD.

Pulmonary rehabilitation (PR) is effective in reducing symptoms and improving health status, and exercise tolerance of patients with chronic obstructive pulmonary disease (COPD). The coronavirus disease 19 (COVID-19) pandemic has greatly impacted PR programs and their delivery to patients. Owing to fears of viral transmission and resultant outbreaks of COVID-19, institution-based PR programs have been forced to significantly reduce enrolment or in some cases completely shut down during the pandemic. As a majority of COPD patients are elderly and have multiple co-morbidities including cardiovascular disease and diabetes, they are notably susceptible to severe complications of COVID-19. As such, patients have been advised to stay at home and avoid social contact to the maximum extent possible. This has increased patients' vulnerability to physical deconditioning, depression, and social isolation. To address this major gap in care, some traditional hospital or clinic-centered PR programs have converted some or all of their learning contents to home-based telerehabilitation during the pandemic. There are, however, some significant barriers to this approach that have impeded its implementation in the community. These include variable access and use of technology (by patients), a lack of standardization of methods and tools for evaluation of the program, and inadequate training and resources for health professionals in optimally delivering telerehabilitation to patients. There is a pressing need for high-quality studies on these modalities of PR to enable the successful implementation of PR at home and via teleconferencing technologies. Here, we highlight the importance of telerehabilitation of patients with COPD in the post-COVID world and discuss various strategies for clinical implementation.

Multi-omics highlights ABO plasma protein as a causal risk factor for COVID-19.

SARS-CoV-2 is responsible for the coronavirus disease 2019 (COVID-19) and the current health crisis. Despite intensive research efforts, the genes and pathways that contribute to COVID-19 remain poorly understood. We, therefore, used an integrative genomics (IG) approach to identify candidate genes responsible for COVID-19 and its severity. We used Bayesian colocalization (COLOC) and summary-based Mendelian randomization to combine gene expression quantitative trait loci (eQTLs) from the Lung eQTL (n = 1,038) and eQTLGen (n = 31,784) studies with published COVID-19 genome-wide association study (GWAS) data from the COVID-19 Host Genetics Initiative. Additionally, we used COLOC to integrate plasma protein quantitative trait loci (pQTL) from the INTERVAL study (n = 3,301) with COVID-19 loci. Finally, we determined any causal associations between plasma proteins and COVID-19 using multi-variable two-sample Mendelian randomization (MR). The expression of 18 genes in lung and/or blood co-localized with COVID-19 loci. Of these, 12 genes were in suggestive loci (PGWAS < 5 × 10-05). LZTFL1, SLC6A20, ABO, IL10RB and IFNAR2 and OAS1 had been previously associated with a heightened risk of COVID-19 (PGWAS < 5 × 10-08). We identified a causal association between OAS1 and COVID-19 GWAS. Plasma ABO protein, which is associated with blood type in humans, demonstrated a significant causal relationship with COVID-19 in the MR analysis; increased plasma levels were associated with an increased risk of COVID-19 and, in particular, severe COVID-19. In summary, our study identified genes associated with COVID-19 that may be prioritized for future investigations. Importantly, this is the first study to demonstrate a causal association between plasma ABO protein and COVID-19.

ACE inhibition and cardiometabolic risk factors, lung ACE2 and TMPRSS2 gene expression, and plasma ACE2 levels: a Mendelian randomization study.

Angiotensin-converting enzyme 2 (ACE2) and serine protease TMPRSS2 have been implicated in cell entry for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19). The expression of ACE2 and TMPRSS2 in the lung epithelium might have implications for the risk of SARS-CoV-2 infection and severity of COVID-19. We use human genetic variants that proxy angiotensin-converting enzyme (ACE) inhibitor drug effects and cardiovascular risk factors to investigate whether these exposures affect lung ACE2 and TMPRSS2 gene expression and circulating ACE2 levels. We observed no consistent evidence of an association of genetically predicted serum ACE levels with any of our outcomes. There was weak evidence for an association of genetically predicted serum ACE levels with ACE2 gene expression in the Lung eQTL Consortium (p = 0.014), but this finding did not replicate. There was evidence of a positive association of genetic liability to type 2 diabetes mellitus with lung ACE2 gene expression in the Gene-Tissue Expression (GTEx) study (p = 4 × 10-4) and with circulating plasma ACE2 levels in the INTERVAL study (p = 0.03), but not with lung ACE2 expression in the Lung eQTL Consortium study (p = 0.68). There were no associations of genetically proxied liability to the other cardiometabolic traits with any outcome. This study does not provide consistent evidence to support an effect of serum ACE levels (as a proxy for ACE inhibitors) or cardiometabolic risk factors on lung ACE2 and TMPRSS2 expression or plasma ACE2 levels.

Gene expression network analysis provides potential targets against SARS-CoV-2.

Cell entry of SARS-CoV-2, the novel coronavirus causing COVID-19, is facilitated by host cell angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). We aimed to identify and characterize genes that are co-expressed with ACE2 and TMPRSS2, and to further explore their biological functions and potential as druggable targets. Using the gene expression profiles of 1,038 lung tissue samples, we performed a weighted gene correlation network analysis (WGCNA) to identify modules of co-expressed genes. We explored the biology of co-expressed genes using bioinformatics databases, and identified known drug-gene interactions. ACE2 was in a module of 681 co-expressed genes; 10 genes with moderate-high correlation with ACE2 (r > 0.3, FDR < 0.05) had known interactions with existing drug compounds. TMPRSS2 was in a module of 1,086 co-expressed genes; 31 of these genes were enriched in the gene ontology biologic process 'receptor-mediated endocytosis', and 52 TMPRSS2-correlated genes had known interactions with drug compounds. Dozens of genes are co-expressed with ACE2 and TMPRSS2, many of which have plausible links to COVID-19 pathophysiology. Many of the co-expressed genes are potentially targetable with existing drugs, which may accelerate the development of COVID-19 therapeutics.