COVID-19 Phenotypes Research Articles

Overview of Antiviral Drug Therapy for COVID-19: Where Do We Stand?

The vaccine weapon has resulted in being essential in fighting the COVID-19 outbreak, but it is not fully preventing infection due to an alarming spreading of several identified variants of concern. In fact, the recent emergence of variants has pointed out how the SARS-CoV-2 pandemic still represents a global health threat. Moreover, oral antivirals also develop resistance, supporting the need to find new targets as therapeutic tools. However, cocktail therapy is useful to reduce drug resistance and maximize vaccination efficacy. Natural products and metal-drug-based treatments have also shown interesting antiviral activity, representing a valid contribution to counter COVID-19 outbreak. This report summarizes the available evidence which supports the use of approved drugs and further focuses on significant clinical trials that have investigated the safety and efficacy of repurposing drugs and new molecules in different COVID-19 phenotypes. To date, there are many individuals vulnerable to COVID-19 exhibiting severe symptoms, thus characterizing valid therapeutic strategies for better management of the disease is still a challenge.

Latent class analysis: an innovative approach for identification of clinical and laboratory markers of disease severity among COVID-19 patients admitted to the intensive care unit

ObjectiveThe aim of this study was to identify clinical and laboratory phenotype distribution patterns and their usefulness as prognostic markers in COVID-19 patients admitted to the intensive care unit (ICU) at Tygerberg Hospital, Cape Town. Methods and resultsA latent class analysis (LCA) model was applied in a prospective, observational cohort study. Data from 343 COVID-19 patients were analysed. Two distinct phenotypes (1 and 2) were identified, comprising 68.46% and 31.54% of patients, respectively. The phenotype 2 patients were characterized by increased coagulopathy markers (D-dimer, median value 1.73 ng/L vs 0.94 ng/L; p < 0.001), end-organ dysfunction (creatinine, median value 79 µmol/L vs 69.5 µmol/L; p < 0.003), under-perfusion markers (lactate, median value 1.60 mmol/L vs 1.20 mmol/L; p < 0.001), abnormal cardiac function markers (median N‐terminal pro‐brain natriuretic peptide (NT-proBNP) 314 pg/ml vs 63.5 pg/ml; p < 0.001 and median high‐sensitivity cardiac troponin (Hs-TropT) 39 ng/L vs 12 ng/L; p < 0.001), and acute inflammatory syndrome (median neutrophil-to-lymphocyte ratio 15.08 vs 8.68; p < 0.001 and median monocyte value 0.68 × 109/L vs 0.45 × 109/L; p < 0.001). ConclusionThe identification of COVID-19 phenotypes and sub-phenotypes in ICU patients could help as a prognostic marker in the day-to-day management of COVID-19 patients admitted to the ICU.

Does ACE2 mediate the detrimental effect of exposures related to COVID-19 risk: A Mendelian randomization investigation.

Adiposity, smoking, and lower socioeconomic position (SEP) increase COVID-19 risk while the association of vitamin D, blood pressure, and glycemic traits in COVID-19 risk were less clear. Whether angiotensin-converting enzyme 2 (ACE2), the key receptor for SARS-CoV-2, mediates these associations has not been investigated. We conducted a Mendelian randomization study to assess the role of these exposures in COVID-19 and mediation by ACE2. We extracted genetic variants strongly related to various exposures (vitamin D, blood pressure, glycemic traits, smoking, adiposity, and educational attainment [SEP proxy]), and ACE2 cis-variants from genome-wide association studies (GWAS, n ranged from 28 204 to 3 037 499) and applied them to GWAS summary statistics of ACE2 (n = 28 204) and COVID-19 (severe, hospitalized, and susceptibility, n ≤ 2 942 817). We used inverse variance weighted as the main analyses, with MR-Egger and weighted median as sensitivity analyses. Mediation analyses were performed based on product of coefficient method. Higher adiposity, lifetime smoking index, and lower educational attainment were consistently associated with higher risk of COVID-19 phenotypes while there was no strong evidence for an association of other exposures in COVID-19 risk. ACE2 partially mediates the detrimental effects of body mass index (ranged from 4.3% to 8.2%), waist-to-hip ratio (ranged from 11.2% to 16.8%), and lower educational attainment (ranged from 4.0% to 7.5%) in COVID-19 phenotypes while ACE2 did not mediate the detrimental effect of smoking. We provided genetic evidence that reducing ACE2 could partly lower COVID-19 risk amongst people who were overweight/obese or of lower SEP.

Causal associations between obstructive sleep apnea and COVID-19: A bidirectional Mendelian randomization study

BackgroundsThe COVID-19 pandemic has caused significant impact on human health. Whether obstructive sleep apnea (OSA) increases the risk of COVID-19 remains unclear. We sought to clarify this issue using two-sample Mendelian randomization (TSMR) analysis in large cohorts. MethodsBidirectional two-sample Mendelian randomization (MR) was used to evaluate the potential causality between OSA and COVID-19 by selecting single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) from genome-wide association studies (GWAS). The inverse-variance weighted (IVW) method was selected as the main approach for data analysis to estimate the possible causal effects. Alternative methods such as MR-Egger, the MR pleiotropy residual sum and outlier (MR-PRESSO), and leave-one-out analysis methods were implemented as sensitivity analysis approaches to ensure the robustness of the results. ResultsAll forward MR analyses consistently indicated the absence of a causal relationship between OSA and any COVID-19 phenotype. In the reverse MR analysis, the IVW mode demonstrated that severe respiratory confirmed COVID-19 was correlated with a 4.9% higher risk of OSA (OR, 1.049; 95%CI, 1.018–1.081; P = 0.002), consistent in MR-PRESSO (OR = 1.049, 95%CI 1.018–1.081, P = 0.004), weighted median (OR = 1.048, 95%CI 1.003–1.095, P = 0.035), and MR-Egger (OR = 1.083, 95%CI 1.012–1.190, P = 0.041) methods. ConclusionsThere is no significant evidence supporting a causal association between OSA and any COVID phenotype, while we identified potential evidence for a causal effect of severe COVID-19 on an increased risk of OSA.

Integrated network-based multiple computational analyses for identification of co-expressed candidate genes associated with neurological manifestations of COVID-19

‘Tripartite network’ (TN) and ‘combined gene network’ (CGN) were constructed and their hub-bottleneck and driver nodes (44 genes) were evaluated as ‘target genes’ (TG) to identify 21 ‘candidate genes’ (CG) and their relationship with neurological manifestations of COVID-19. TN was developed using neurological symptoms of COVID-19 found in literature. Under query genes (TG of TN), co-expressed genes were identified using pair-wise mutual information to genes available in RNA-Seq autopsy data of frontal cortex of COVID-19 victims. CGN was constructed with genes selected from TN and co-expressed in COVID-19. TG and their connecting genes of respective networks underwent functional analyses through findings of their enrichment terms and pair-wise ‘semantic similarity scores’ (SSS). A new integrated ‘weighted harmonic mean score’ was formulated assimilating values of SSS and STRING-based ‘combined score’ of the selected TG-pairs, which provided CG-pairs with properties of CGs as co-expressed and ‘indispensable nodes’ in CGN. Finally, six pairs sharing seven ‘prevalent CGs’ (ADAM10, ADAM17, AKT1, CTNNB1, ESR1, PIK3CA, FGFR1) showed linkages with the phenotypes (a) directly under neurodegeneration, neurodevelopmental diseases, tumour/cancer and cellular signalling, and (b) indirectly through other CGs under behavioural/cognitive and motor dysfunctions. The pathophysiology of ‘prevalent CGs’ has been discussed to interpret neurological phenotypes of COVID-19.

A new approach to modeling pre-symptomatic incidence and transmission time of imported COVID-19 cases evolving with SARS-CoV-2 variants.

There is paucity of the statistical model that is specified for data on imported COVID-19 cases with the unique global information on infectious properties of SARS-CoV-2 variant different from local outbreak data used for estimating transmission and infectiousness parameters via the established epidemic models. To this end, a new approach with a four-state stochastic model was proposed to formulate these well-established infectious parameters with three new parameters, including the pre-symptomatic incidence rate, the median of pre-symptomatic transmission time (MPTT) to symptomatic state, and the incidence (proportion) of asymptomatic cases using imported COVID-19 data. We fitted the proposed stochastic model to empirical data on imported COVID-19 cases from D614G to Omicron with the corresponding calendar periods according to the classification GISAID information on the evolution of SARS-CoV-2 variant between March 2020 and Jan 2022 in Taiwan. The pre-symptomatic incidence rate was the highest for Omicron followed by Alpha, Delta, and D614G. The MPTT (in days) increased from 3.45 (first period) ~ 4.02 (second period) of D614G until 3.94–4.65 of VOC Alpha but dropped to 3.93–3.49 of Delta and 2 days (only first period) of Omicron. The proportion of asymptomatic cases increased from 29% of D-614G period to 59.2% of Omicron. Modeling data on imported cases across strains of SARS-CoV-2 not only bridges the link between the underlying natural infectious properties elucidated in the previous epidemic models and different disease phenotypes of COVID-19 but also provides precision quarantine and isolation policy for border control in the face of various emerging SRAS-CoV-2 variants globally.

Predicting the Kinetic Coordination of Immune Response Dynamics in SARS-CoV-2 Infection: Implications for Disease Pathogenesis

A calibrated mathematical model of antiviral immune response to SARS-CoV-2 infection is developed. The model considers the innate and antigen-specific responses to SARS-CoV-2 infection. Recently published data sets from human challenge studies with SARS-CoV-2 were used for parameter evaluation. The calibration of the mathematical model of SARS-CoV-2 infection is based on combining the parameter guesses from our earlier study of influenza A virus infection, some recent quantitative models of SARS-CoV-2 infection and clinical data-based parameter estimation of a subset of the model parameters. Hence, the calibrated mathematical model represents a theoretical exploration type of study, i.e., ‘in silico patient’ with mild-to-moderate severity phenotype, rather than a completely validated quantitative model of COVID-19 with respect to all its state-space variables. Understanding the regulation of multiple intertwined reaction components of the immune system is necessary for linking the kinetics of immune responses with the clinical phenotypes of COVID-19. Consideration of multiple immune reaction components in a single calibrated mathematical model allowed us to address some fundamental issues related to the pathogenesis of COVID-19, i.e., the sensitivity of the peak viral load to the parameters characterizing the antiviral specific response components, the kinetic coordination of the individual innate and adaptive immune responses, and the factors favoring a prolonged viral persistence. The model provides a tool for predicting the infectivity of patients, i.e., the amount of virus which is transmitted via droplets from the person infected with SARS-CoV-2, depending on the time of infection. The thresholds for variations of the innate and adaptive response parameters which lead to a prolonged persistence of SARS-CoV-2 due to the loss of a kinetic response synchrony/coordination between them were identified.

The Role of Lung Ultrasound in SARS-CoV-19 Pneumonia Management.

Purpose: We aimed to assess the role of lung ultrasound (LUS) in the diagnosis and prognosis of SARS-CoV-2 pneumonia, by comparing it with High Resolution Computed Tomography (HRCT). Patients and methods: All consecutive patients with laboratory-confirmed SARS-CoV-2 infection and hospitalized in COVID Centers were enrolled. LUS and HRCT were carried out on all patients by expert operators within 48–72 h of admission. A four-level scoring system computed in 12 regions of the chest was used to categorize the ultrasound imaging, from 0 (absence of visible alterations with ultrasound) to 3 (large consolidation and cobbled pleural line). Likewise, a semi-quantitative scoring system was used for HRCT to estimate pulmonary involvement, from 0 (no involvement) to 5 (>75% involvement for each lobe). The total CT score was the sum of the individual lobar scores and ranged from 0 to 25. LUS scans were evaluated according to a dedicated scoring system. CT scans were assessed for typical findings of COVID-19 pneumonia (bilateral, multi-lobar lung infiltration, posterior peripheral ground glass opacities). Oxygen requirement and mortality were also recorded. Results: Ninety-nine patients were included in the study (male 68.7%, median age 71). 40.4% of patients required a Venturi mask and 25.3% required non-invasive ventilation (C-PAP/Bi-level). The overall mortality rate was 21.2% (median hospitalization 30 days). The median ultrasound thoracic score was 28 (IQR 20–36). For the CT evaluation, the mean score was 12.63 (SD 5.72), with most of the patients having LUS scores of 2 (59.6%). The bivariate correlation analysis displayed statistically significant and high positive correlations between both the CT and composite LUS scores and ventilation, lactates, COVID-19 phenotype, tachycardia, dyspnea, and mortality. Moreover, the most relevant and clinically important inverse proportionality in terms of P/F, i.e., a decrease in P/F levels, was indicative of higher LUS/CT scores. Inverse proportionality P/F levels and LUS and TC scores were evaluated by univariate analysis, with a P/F–TC score correlation coefficient of −0.762, p < 0.001, and a P/F–LUS score correlation coefficient of −0.689, p < 0.001. Conclusions: LUS and HRCT show a synergistic role in the diagnosis and disease severity evaluation of COVID-19.

The osteo-metabolic phenotype of COVID-19: an update.

ContextIn the multifaceted COVID-19 clinical scenario characterized by a multi-system disorder with negative implications not only on respiratory function but also on cardiac, hematological, neurological and endocrine-metabolic systems, a distinctive osteo-metabolic phenotype with an independent influence on disease severity and recovery of patients affected was early reported.AimTo summarize and update the main evidences regarding the distinct components of this phenotype in acute and Long COVID-19, reinforcing its clinical relevance and discussing the main pathophysiological and clinical-therapeutic implications of the most recent reported findings.ResultsThis emerging phenotype is characterized by a widespread acute hypocalcemia and hypovitaminosis D with an impaired compensatory parathyroid hormone response, and a high prevalence of skeletal complications such as vertebral fractures. The clinical relevance of this osteo-metabolic phenotype on acute COVID-19 is well characterized, and novel seminal evidences are progressively highlighting its importance also in predicting patient’s long-term outcomes and Long COVID-19 occurrence.ConclusionsThese findings reinforced the central role of a multidisciplinary team, including endocrinologists, in evaluating these patients for a proactive search of each aspect of the osteo-metabolic phenotype components since they may represent suitable therapeutic targets to prevent SARS-CoV-2 infection, poor COVID-19 outcomes, Long COVID-19 occurrence and even possibly better responses to COVID-19 vaccination.

COVID-19 and Thyroid Function: A Bi-Directional Two-Sample Mendelian Randomization Study.

Background: Thyroid dysfunction has been observed among some patients with coronavirus disease (COVID-19). It is unclear whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (or its severity) leads to the development of thyroid dysfunction, or vice versa. In this study, we examined the bi-directional causal relationship between host genetic liability to three COVID-19 phenotypes (including SARS-CoV-2 infection, hospitalized and severe COVID-19) and three thyroid dysfunction traits (including hyperthyroidism, hypothyroidism, and autoimmune thyroid disease [AITD]) and three continuous traits of thyroid hormones (including thyrotropin [TSH] and free thyroxine [fT4] within reference range, and TSH in full range). Methods: Summary statistics from the largest available meta-analyses of human genome-wide association studies were retrieved for the following variables: SARS-CoV-2 infection (n = 1,348,701), COVID-19 hospitalization (n = 1,557,411), severe COVID-19 (n = 1,059,456), hyperthyroidism (n = 51,823), hypothyroidism (n = 53,423), AITD (n = 755,406), TSH within reference range (n = 54,288), fT4 within reference range (n = 49,269), and TSH in full range (n = 119,715). Using a two-sample Mendelian randomization (MR) approach, the inverse-variance weighted (IVW) method was adopted as the main MR analysis. Weighted median, contamination mixture, MR-Egger, and MR pleiotropy residual sum and outlier (MR-PRESSO) methods were applied as sensitivity analyses. Results: Host genetic susceptibility to SARS-CoV-2 infection was causally associated with hypothyroidism in the main IVW analysis (per doubling in prevalence of SARS-CoV-2 infection, odds ratio [OR] = 1.335; 95% confidence interval [CI]: 1.167-1.526; p = 2.4 × 10-5, surpassing the Bonferroni multiple-testing threshold). Similar causal estimates were observed in the sensitivity analyses (weighted median: OR = 1.296; CI: 1.066-1.575; p = 9 × 10-3; contamination mixture: OR = 1.356; CI: 1.095-1.818; p = 0.013; MR-Egger: OR = 1.712; CI: 1.202-2.439; p = 2.92 × 10-3, and MR-PRESSO: OR = 1.335; CI: 1.156-1.542; p = 5.73 × 10-4). Host genetic liability to hospitalized or severe COVID-19 was not associated with thyroid dysfunction or thyroid hormone levels. In the reverse direction, there was no evidence to suggest that genetic predisposition to thyroid dysfunction or genetically determined thyroid hormone levels altered the risk of the COVID-19 outcomes. Conclusions: This bi-directional MR study supports that host response to SARS-CoV-2 viral infection plays a role in the causal association with increased risk of hypothyroidism. Long-term follow-up studies are needed to confirm the expected increased hypothyroidism risk.

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

BackgroundUpdatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework.MethodsIn this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status.FindingsAmong 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1.InterpretationOur analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources.FundingBritish Heart Foundation Data Science Centre, led by Health Data Research UK.

Vertebral fractures at hospitalization predict impaired respiratory function during follow-up of COVID-19 survivors

Morphometric vertebral fractures (VFs) have been recently reported as an important component of the endocrine phenotype of COVID-19 and emerging data show negative respiratory sequelae at long-term follow-up in COVID-19 survivors. The aim of this study was to evaluate the impact of VFs on respiratory function in COVID-19 survivors. We included patients referred to our Hospital Emergency Department and re-evaluated during follow-up. VFs were detected on lateral chest X-rays on admission using a qualitative and semiquantitative assessment and pulmonary function tests were obtained by Jaeger-MasterScreen-Analyzer Unit 6 months after discharge. Fifty patients were included. Median age was 66 years and 66% were males. No respiratory function data were available at COVID-19 diagnosis. VFs were detected in 16 (32%) patients. No differences between fractured and non-fractured patients regarding age and sex were observed. Although no difference was observed between VF and non-VF patient groups in the severity of pneumonia as assessed by Radiological-Assessment-of-Lung-Edema score at admission, (5 vs. 6, p = 0.69), patients with VFs were characterized as compared to those without VFs by lower Forced Vital Capacity (FVC, 2.9 vs. 3.6 L, p = 0.006; 85% vs. 110% of predicted, respectively, p = 0.001), Forced Expiratory Volume 1st s (FEV1, 2.2 vs. 2.8 L, p = 0.005; 92% vs. 110% of predicted, respectively, p = 0.001) and Diffusing Capacity of the Lungs for Carbon Monoxide (DLCO 5.83 vs. 6.98 mmol/min/kPa, p = 0.036, 59% vs. 86.3% of predicted, respectively, p = 0.043) at 6-month follow up. VFs, expression of the endocrine phenotype of the disease, appear to influence medium-term impaired respiratory function of COVID-19 survivors which may significantly influence their recovery. Therefore, our findings suggest that a VFs assessment at baseline may help in identifying patients needing a more intensive respiratory follow-up and patients showing persistent respiratory impairment without evidence of pulmonary disease may benefit from VFs assessment to preventing the vicious circle of further fractures and respiratory deterioration.

Expediting knowledge acquisition by a web framework for Knowledge Graph Exploration and Visualization (KGEV): case studies on COVID-19 and Human Phenotype Ontology

BackgroundKnowledges graphs (KGs) serve as a convenient framework for structuring knowledge. A number of computational methods have been developed to generate KGs from biomedical literature and use them for downstream tasks such as link prediction and question answering. However, there is a lack of computational tools or web frameworks to support the exploration and visualization of the KG themselves, which would facilitate interactive knowledge discovery and formulation of novel biological hypotheses.MethodWe developed a web framework for Knowledge Graph Exploration and Visualization (KGEV), to construct and visualize KGs in five stages: triple extraction, triple filtration, metadata preparation, knowledge integration, and graph database preparation. The application has convenient user interface tools, such as node and edge search and filtering, data source filtering, neighborhood retrieval, and shortest path calculation, that work by querying a backend graph database. Unlike other KGs, our framework allows fast retrieval of relevant texts supporting the relationships in the KG, thus allowing human reviewers to judge the reliability of the knowledge extracted.ResultsWe demonstrated a case study of using the KGEV framework to perform research on COVID-19. The COVID-19 pandemic resulted in an explosion of relevant literature, making it challenging to make full use of the vast and heterogenous sources of information. We generated a COVID-19 KG with heterogenous information, including literature information from the CORD-19 dataset, as well as other existing knowledge from eight data sources. We showed the utility of KGEV in three intuitive case studies to explore and query knowledge on COVID-19. A demo of this web application can be accessed at http://covid19nlp.wglab.org. Finally, we also demonstrated a turn-key adaption of the KGEV framework to study clinical phenotypic presentation of human diseases by Human Phenotype Ontology (HPO), illustrating the versatility of the framework.ConclusionIn an era of literature explosion, the KGEV framework can be applied to many emerging diseases to support structured navigation of the vast amount of newly published biomedical literature and other existing biological knowledge in various databases. It can be also used as a general-purpose tool to explore and query gene-phenotype-disease-drug relationships interactively.

Neutrophils in COVID-19: Not Innocent Bystanders.

Unusually for a viral infection, the immunological phenotype of severe COVID-19 is characterised by a depleted lymphocyte and elevated neutrophil count, with the neutrophil-to-lymphocyte ratio correlating with disease severity. Neutrophils are the most abundant immune cell in the bloodstream and comprise different subpopulations with pleiotropic actions that are vital for host immunity. Unique neutrophil subpopulations vary in their capacity to mount antimicrobial responses, including NETosis (the generation of neutrophil extracellular traps), degranulation and de novo production of cytokines and chemokines. These processes play a role in antiviral immunity, but may also contribute to the local and systemic tissue damage seen in acute SARS-CoV-2 infection. Neutrophils also contribute to complications of COVID-19 such as thrombosis, acute respiratory distress syndrome and multisystem inflammatory disease in children. In this Progress review, we discuss the anti-viral and pathological roles of neutrophils in SARS-CoV-2 infection, and potential therapeutic strategies for COVID-19 that target neutrophil-mediated inflammatory responses.

Fulminant onset COVID-19: predictors and outcome

PurposeDuring COVID-19 infection, organ dysfunction such as respiratory failure tends to occur towards the second week of illness; however, in a subset, there may be rapid onset of organ dysfunction...

Germline rare variants of lectin pathway genes predispose to asymptomatic SARS-CoV-2 infection in elderly individuals

PurposeEmerging evidence suggest that infection-dependent hyperactivation of complement system (CS) may worsen COVID-19 outcome. We investigated the role of predicted high impact rare variants — referred as qualifying variants (QVs) — of CS genes in predisposing asymptomatic COVID-19 in elderly individuals, known to be more susceptible to severe disease. MethodsExploiting exome sequencing data and 56 CS genes, we performed a gene-based collapsing test between 164 asymptomatic subjects (aged ≥60 years) and 56,885 European individuals from the Genome Aggregation Database. We replicated this test comparing the same asymptomatic individuals with 147 hospitalized patients with COVID-19. ResultsWe found an enrichment of QVs in 3 genes (MASP1, COLEC11, and COLEC10), which belong to the lectin pathway, in the asymptomatic cohort. Analyses of complement activity in serum showed decreased activity of lectin pathway in asymptomatic individuals with QVs. Finally, we found allelic variants associated with asymptomatic COVID-19 phenotype and with a decreased expression of MASP1, COLEC11, and COLEC10 in lung tissue. ConclusionThis study suggests that genetic rare variants can protect from severe COVID-19 by mitigating the activity of lectin pathway and prothrombin. The genetic data obtained through ES of 786 asymptomatic and 147 hospitalized individuals are publicly available at http://espocovid.ceinge.unina.it/

Insights into Cardiovascular Defects and Cardiac Epigenome in the Context of COVID-19.

Although few in number, studies on epigenome of the heart of COVID-19 patients show that epigenetic signatures such as DNA methylation are significantly altered, leading to changes in expression of several genes. It contributes to pathogenic cardiac phenotypes of COVID-19, e.g., low heart rate, myocardial edema, and myofibrillar disarray. DNA methylation studies reveal changes which likely contribute to cardiac disease through unknown mechanisms. The incidence of severe COVID-19 disease, including hospitalization, requiring respiratory support, morbidity, and mortality, is disproportionately higher in individuals with co-morbidities. This poses unprecedented strains on the global healthcare system. While their underlying conditions make patients more susceptible to severe COVID-19 disease, strained healthcare systems, lack of adequate support, or sedentary lifestyles from ongoing lockdowns have proved detrimental to their underlying health conditions, thus pushing them to severe risk of congenital heart disease (CHD) itself. Prophylactic vaccines against COVID-19 have ushered new hope for CHD. A common connection between COVID-19 and CHD is SARS-CoV-2’s host receptor ACE2, because ACE2 regulates and protects organs, including the heart, in various ways. ACE2 is a common therapeutic target against cardiovascular disease and COVID-19 which damages organs. Hence, this review explores the above regarding CHDs, cardiovascular damage, and cardiac epigenetics, in COVID-19 patients.

COVID-19 Phenotypes and Comorbidity: A Data-Driven, Pattern Recognition Approach Using National Representative Data from the United States.

The aim of our study was to determine COVID-19 syndromic phenotypes in a data-driven manner using the survey results based on survey results from Carnegie Mellon University’s Delphi Group. Monthly survey results (>1 million responders per month; 320,326 responders with a certain COVID-19 test status and disease duration <30 days were included in this study) were used sequentially in identifying and validating COVID-19 syndromic phenotypes. Logistic Regression-weighted multiple correspondence analysis (LRW-MCA) was used as a preprocessing procedure, in order to weigh and transform symptoms recorded by the survey to eigenspace coordinates, capturing a total variance of >75%. These scores, along with symptom duration, were subsequently used by the Two Step Clustering algorithm to produce symptom clusters. Post-hoc logistic regression models adjusting for age, gender, and comorbidities and confirmatory linear principal components analyses were used to further explore the data. Model creation, based on August’s 66,165 included responders, was subsequently validated in data from March–December 2020. Five validated COVID-19 syndromes were identified in August: 1. Afebrile (0%), Non-Coughing (0%), Oligosymptomatic (ANCOS); 2. Febrile (100%) Multisymptomatic (FMS); 3. Afebrile (0%) Coughing (100%) Oligosymptomatic (ACOS); 4. Oligosymptomatic with additional self-described symptoms (100%; OSDS); 5. Olfaction/Gustatory Impairment Predominant (100%; OGIP). Our findings indicate that the COVID-19 spectrum may be undetectable when applying current disease definitions focusing on respiratory symptoms alone.

Clinico-Radiological-Pathologic Profile and Outcomes of Lung Transplant in Post–COVID-19 Phenotype: A Single Center Experience

BackgroundLung transplantation (LTx) has come as hope for select patients with post-COVID acute respiratory distress syndrome (ARDS). It has a different phenotype with unique challenges. We aimed to bring out our experience with and outcomes of LTx for post-COVID ARDS.MethodsThis study is retrospective case series from a single center in India. All the patients with post-COVID end stage lung disease (ESLD) who underwent bilateral LTx between 1st May 2020 and 30th August 2021 were included. LTx was performed following no improvement with optimal medical management with adequate time provided for recovery. Information relating to demographics, comorbidities, pretransplant status, perioperative parameters, gross and histopathological findings of explanted lungs, posttransplant morbidity, and mortality were analyzed.ResultsThis study included 23 patients. The median age of the patients in this study was 42 years and 20 participants were men (87%). The mean duration of intensive care unit stay was 15.83 ± 6.61 days. Mortality was observed among 8 participants (34.78%). Mean survival time was 34.54 weeks. Among the 8 patients who expired, the cause of death was sepsis for 6 patients (75.0%), neurologic cerebrovascular accident for 1 patient (12.5%), and cytomegalovirus for 1 patient (12.5%). All the deaths were reported in primary graft dysfunction grade 2 & 3 category. No rejections were observed on first and third month surveillance biopsies.ConclusionsLTx is the definitive option for survival in select patients with severe post–COVID-19–associated ESLD. This study brings out various challenges involved in such phenotypes and also observations in postoperative recovery.

The impact of shifting demographics, variants of concern and vaccination on outcomes during the first 3 COVID-19 waves in Alberta and Ontario: a retrospective cohort study.

Background:In Canada, published outcome data for COVID-19 come largely from the first 2 waves of the pandemic. We examined changes in demographics and 30-day outcomes after SARS-CoV-2 infection during the first 3 pandemic waves in Alberta and Ontario; for wave 3, we compared outcomes between those infected with a variant of concern and those infected with the original “wild-type” SARS-CoV-2.Methods:We conducted a population-based retrospective cohort study using linked health care data sets in Alberta and Ontario. We identified all-cause hospitalizations or deaths within 30 days after a positive result on a reverse transcription polymerase chain reaction test for SARS-CoV-2 in individuals of any age between Mar. 1, 2020, and June 30, 2021, with genomic confirmation of variants of concern. We compared outcomes in wave 3 (February 2021 to June 2021) with outcomes in waves 1 and 2 combined (March 2020 to January 2021) after adjusting for age, sex and Charlson Comorbidity Index score. Using wave 3 data only, we compared outcomes by vaccination status and whether or not the individual was infected with a variant of concern.Results:Compared to those infected with SARS-CoV-2 during waves 1 and 2 (n = 372 070), we found a shift toward a younger and healthier demographic in those infected during wave 3 (n = 359 079). In wave 3, patients were more likely to be hospitalized (adjusted odds ratio [aOR] 1.57, 95% confidence interval [CI] 1.46–1.70) but had a shorter length of hospital stay (median 6 days v. 7 days, p < 0.001) and lower 30-day mortality (aOR 0.73, 95% CI 0.65–0.81). The 217 892 patients in wave 3 who were infected with a variant of concern (83.5% confirmed to have the Alpha variant, 1.7% confirmed to have the Delta variant) had a higher risk of death (Alpha: aOR 1.29, 95% CI 1.16–1.44; Delta: aOR 2.05, 95% CI 1.49–2.82) and hospitalization (Alpha: aOR 1.59, 95% CI 1.53–1.66; Delta: aOR 1.88, 95% CI 1.64–2.15) than those infected with wild-type SARS-CoV-2.Interpretation:We observed a shift among those infected with SARS-CoV-2 toward younger patients with fewer comorbidities, a shorter length of hospital stay and lower mortality risk as the pandemic evolved in Alberta and Ontario; however, infection with a variant of concern was associated with a substantially higher risk of hospitalization or death. As variants of concern emerge, ongoing monitoring of disease expression and outcomes among vaccinated and unvaccinated individuals is important to understand the phenotypes of COVID-19 and the anticipated burdens for the health care system.