COVID-19: disease pathways and gene expression changes predict methylprednisolone can improve outcome in severe cases

Gene set correlation enrichment analysis for interpreting and annotating gene expression profiles

Pathway analysis, including nontopology-based (non-TB) and topology-based (TB) methods, is widely used to interpret the biological phenomena underlying differences in expression data between two phenotypes. By considering dependencies and interactions between genes, TB methods usually perform better than non-TB methods in identifying pathways that include closely relevant or directly causative genes for a given phenotype. However, most TB methods may be limited by incomplete pathway data used as the reference network or by difficulties in selecting appropriate reference networks for different research topics. Here, we propose a gene set correlation enrichment analysis method, Gscore, based on an expression dataset-derived coexpression network to examine whether a differentially expressed gene (DEG) list (or each of its DEGs) is associated with a known gene set. Gscore is better able to identify target pathways in 89 human disease expression datasets than eight other state-of-the-art methods and offers insight into how disease-wide and pathway-wide associations reflect clinical outcomes. When applied to RNA-seq data from COVID-19-related cells and patient samples, Gscore provided a means for studying how DEGs are implicated in COVID-19-related pathways. In summary, Gscore offers a powerful analytical approach for annotating individual DEGs, DEG lists, and genome-wide expression profiles based on existing biological knowledge.

Comparison of corticosteroids types, dexamethasone, and methylprednisolone in patients hospitalized with COVID-19: A systematic review and network meta-analysis

Background

COVID-19 is associated with severe pneumonia lung damage, acute respiratory distress syndrome (ARDS), and mortality. In this study, we aimed to compare corticosteroids' effect on the mortality risk in patients hospitalized with COVID-19.

Methods

PubMed, Web of Science, Scopus, Cochrane Library, and Embase, were searched using a predesigned search strategy. Randomized controlled trials (RCTs) that had compared the corticosteroid drugs were included. The hazard ratio (HR) with a 95% confidence interval (CI) was used to summarize the effect size from the network meta-analysis (NMA).

Results

Out of 329 retrieved references, 12 RCTs with 11,455 participants met the eligibility criteria in this review. The included RCTs formed one network with six treatments. In addition, five treatments in two RCTs were not connected to the network. Methylprednisolone + usual care (UC) versus UC decreased the risk of death by 0.65 (95% CI: 0.47, 0.90). Among treatments in the network the highest P-score (0.89) was related to Methylprednisolone + UC.

Conclusion

Based on the results of this NMA it seems Methylprednisolone + UC to be the best treatment option in patients with COVID-ARDS and COVID pneumonia.

A novel approach for predicting upstream regulators (PURE) that affect gene expression

External factors such as exposure to a chemical, drug, or toxicant (CDT), or conversely, the lack of certain chemicals can cause many diseases. The ability to identify such causal CDTs based on changes in the gene expression profile is extremely important in many studies. Furthermore, the ability to correctly infer CDTs that can revert the gene expression changes induced by a given disease phenotype is a crucial step in drug repurposing. We present an approach for Predicting Upstream REgulators (PURE) designed to tackle this challenge. PURE can correctly infer a CDT from the measured expression changes in a given phenotype, as well as correctly identify drugs that could revert disease-induced gene expression changes. We compared the proposed approach with four classical approaches as well as with the causal analysis used in Ingenuity Pathway Analysis (IPA) on 16 data sets (1 rat, 5 mouse, and 10 human data sets), involving 8 chemicals or drugs. We assessed the results based on the ability to correctly identify the CDT as indicated by its rank. We also considered the number of false positives, i.e. CDTs other than the correct CDT that were reported to be significant by each method. The proposed approach performed best in 11 out of the 16 experiments, reporting the correct CDT at the very top 7 times. IPA was the second best, reporting the correct CDT at the top 5 times, but was unable to identify the correct CDT at all in 5 out of the 16 experiments. The validation results showed that our approach, PURE, outperformed some of the most popular methods in the field. PURE could effectively infer the true CDTs responsible for the observed gene expression changes and could also be useful in drug repurposing applications.

Identification of shared biological features in four different lung cell lines infected with SARS-CoV-2 virus through RNA-seq analysis

The COVID-19 pandemic caused by SARS-CoV-2 has resulted in millions of confirmed cases and deaths worldwide. Understanding the biological mechanisms of SARS-CoV-2 infection is crucial for the development of effective therapies. This study conducts differential expression (DE) analysis, pathway analysis, and differential network (DN) analysis on RNA-seq data of four lung cell lines, NHBE, A549, A549.ACE2, and Calu3, to identify their common and unique biological features in response to SARS-CoV-2 infection. DE analysis shows that cell line A549.ACE2 has the highest number of DE genes, while cell line NHBE has the lowest. Among the DE genes identified for the four cell lines, 12 genes are overlapped, associated with various health conditions. The most significant signaling pathways varied among the four cell lines. Only one pathway, "cytokine-cytokine receptor interaction", is found to be significant among all four cell lines and is related to inflammation and immune response. The DN analysis reveals considerable variation in the differential connectivity of the most significant pathway shared among the four lung cell lines. These findings help to elucidate the mechanisms of SARS-CoV-2 infection and potential therapeutic targets.

Theory and Practice of Glucocorticoids in COVID-19: Getting to the Heart of the Matter-A Critical Review and Viewpoints

Prolonged, low-dose glucocorticoids (GCs) have shown the highest efficacy among pharmacological and non-pharmacological treatments for COVID-19. Despite the World Health Organization's recommendation against their use at the beginning of the pandemic, GCs at a dose equivalent to dexamethasone 6 mg/day for 10 days are now indicated in all COVID-19 cases who require respiratory support. However, the efficacy of the intervention depends on the timing of initiation, the dose, and other individual factors. Indeed, patients treated with similar GC protocols often experience different outcomes, which do not always correlate with the presence of comorbidities or with the severity of respiratory involvement at baseline. This prompted us to critically review the literature on the rationale, pharmacological principles, and clinical evidence that should guide GC treatment. Based on these data, the best treatment protocol probably involves an initial bolus dose to saturate the glucocorticoid receptors, followed by a continuous infusion to maintain constant plasma levels, and eventually a slow tapering to interruption. Methylprednisolone has shown the highest efficacy among different GC molecules, most likely thanks to its higher ability to penetrate the lung. Decreased tissue sensitivity to glucocorticoids is thought to be the main mechanism accounting for the lower response to the treatment in some individuals. We do not have a readily available test to identify GC resistance; therefore, to address inter-individual variability, future research should aim at investigating clinical, physiological, and laboratory markers to guide a personalized GC treatment approach.

A systematic review and meta-analysis of glucocorticoids treatment in severe COVID-19: methylprednisolone versus dexamethasone

OBJECTIVE

The preferred agent of glucocorticoids in the treatment of patients with severe COVID-19 is still controversial. This study aimed to compare the efficacy and safety of methylprednisolone and dexamethasone in the treatment of patients with severe COVID-19.

METHODS

By searching the electronic literature database including PubMed, Cochrane Central Register of Controlled Trials, and Web of Science, the clinical studies comparing methylprednisolone and dexamethasone in the treatment of severe COVID-19 were selected according to the inclusion criteria and exclusion criteria. Relevant data were extracted and literature quality was assessed. The primary outcome was short-term mortality. The secondary outcomes were the rates of ICU admission and mechanical ventilation, PaO₂/FiO₂ ratio, plasma levels of C-reactive protein (CRP), ferritin, and neutrophil/lymphocyte ratio, hospital stay, and the incidence of severe adverse events. Statistical pooling applied the fixed or random effects model and reported as risk ratio (RR) or mean difference (MD) with the corresponding 95% confidence interval (CI). Meta-analysis was performed using Review Manager 5.1.0.

RESULTS

Twelve clinical studies were eligible, including three randomized controlled trials (RCTs) and nine non-RCTs. A total of 2506 patients with COVID-19 were analyzed, of which 1242 (49.6%) received methylprednisolone and 1264 (50.4%) received dexamethasone treatment. In general, the heterogeneity across studies was significant, and the equivalent doses of methylprednisolone were higher than that of dexamethasone. Our meta-analysis showed that methylprednisolone treatment in severe COVID-19 patients was related to significantly reduced plasma ferritin and neutrophil/lymphocyte ratio compared with dexamethasone, and that no significant difference in other clinical outcomes between the two groups was found. However, subgroup analyses of RCTs demonstrated that methylprednisolone treatment was associated with reduced short-term mortality, and decreased CRP level compared with dexamethasone. Moreover, subgroup analyses observed that severe COVID-19 patients treated with a moderate dose (2 mg/kg/day) of methylprednisolone were related to a better prognosis than those treated with dexamethasone.

CONCLUSIONS

This study showed that compared with dexamethasone, methylprednisolone could reduce the systemic inflammatory response in severe COVID-19, and its effect was equivalent to that of dexamethasone on other clinical outcomes. It should be noted that the equivalent dose of methylprednisolone used was higher. Based on the evidence of subgroup analyses of RCTs, methylprednisolone, preferably at a moderate dose, has an advantage over dexamethasone in the treatment of patients with severe COVID-19.

Effective holistic characterization of small molecule effects using heterogeneous biological networks

The two most common reasons for attrition in therapeutic clinical trials are efficacy and safety. We integrated heterogeneous data to create a human interactome network to comprehensively describe drug behavior in biological systems, with the goal of accurate therapeutic candidate generation. The Computational Analysis of Novel Drug Opportunities (CANDO) platform for shotgun multiscale therapeutic discovery, repurposing, and design was enhanced by integrating drug side effects, protein pathways, protein-protein interactions, protein-disease associations, and the Gene Ontology, and complemented with its existing drug/compound, protein, and indication libraries. These integrated networks were reduced to a "multiscale interactomic signature" for each compound that describe its functional behavior as vectors of real values. These signatures are then used for relating compounds to each other with the hypothesis that similar signatures yield similar behavior. Our results indicated that there is significant biological information captured within our networks (particularly via side effects) which enhance the performance of our platform, as evaluated by performing all-against-all leave-one-out drug-indication association benchmarking as well as generating novel drug candidates for colon cancer and migraine disorders corroborated via literature search. Further, drug impacts on pathways derived from computed compound-protein interaction scores served as the features for a random forest machine learning model trained to predict drug-indication associations, with applications to mental disorders and cancer metastasis highlighted. This interactomic pipeline highlights the ability of Computational Analysis of Novel Drug Opportunities to accurately relate drugs in a multitarget and multiscale context, particularly for generating putative drug candidates using the information gleaned from indirect data such as side effect profiles and protein pathway information.

Safety and efficacy of methylprednisolone versus dexamethasone in critically ill patients with COVID-19 acute respiratory distress syndrome: a retrospective study

Background

Corticosteroids (CSs), specifically dexamethasone (DEX), are the treatment of choice for severe acute respiratory distress syndrome (ARDS) due to COVID-19 pneumonia (CARDS). However, data from both ARDS and relatively small CARDS clinical trials have suggested improved outcomes with methylprednisolone (MP) versus DEX. The objective of this retrospective cohort study was to compare the safety and effectiveness of MP and DEX in critically ill CARDS patients.

Methods

The study cohort included CARDS patients admitted to a tertiary referral intensive care unit (ICU) between April and September 2020 who received at least 5 days of CSs for CARDS.

Results

The cohort was notable for a high severity of illness (overall, 88.5% of patients required mechanical ventilation and 16% required vasopressors on admission). The DEX group (n = 62) was significantly older with a higher illness severity [Sequential Organ Failure Assessment (SOFA) 6 (4.75-8) versus 4.5 (3-7), p = 0.008], while the MP group (n = 51) received significantly more loading doses [19 (37.3%) versus 4 (6.5%), p < 0.0001]. MP was associated with a shorter time to intubation and more rapid progression to mortality [days to death: 18 (15-23) versus 27 (15-34), p = 0.026]. After correction for baseline imbalances in age and SOFA score, DEX was associated with improved mortality at 90 days compared with MP [hazard ratio (HR) = 0.43, 95% confidence interval (CI) = 0.23-0.80, p = 0.008]. However, there were no differences between rates of secondary infections during hospitalization or insulin requirements at 7 and 14 days.

Conclusion

In this cohort of critically ill CARDS, choice of CS was associated with mortality but not adverse event profile, and thus warrants further investigation.

Effects of different doses of methylprednisolone therapy on acute respiratory distress syndrome: results from animal and clinical studies

Background

The optimal dose of glucocorticoids for acute respiratory distress syndrome (ARDS) is uncertain. This study aimed to evaluate the effects of different doses of methylprednisolone on sepsis-induced acute lung injury (ALI) rats and a cohort of moderate and severe ARDS patients.

Methods

ALI rats, challenged with lipopolysaccharide, were randomly received intraperitoneal injection of normal saline (model group) and different doses of methylprednisolone (0.5, 2, 8 mg/kg, named as low-, moderate- and high-dose group, respectively) for 5 days. The body weight changes of rats, inflammatory factors in bronchoalveolar lavage fluid (BALF), lung wet/dry ratio, histopathological score, and the mRNA expressions of glucocorticoid receptor α (GRα), GRβ and nuclear factor-κB (NF-κB) were measured. Forty moderate and severe ARDS patients were treated with standard of care or plus different doses of methylprednisolone (40, 80, 120 mg/day, named as low-, moderate- and high-dose group, respectively) for 5 days. Clinical outcomes were PaO₂/FiO₂ ratio and C-reactive protein (CRP) level at day 5, intubation rate, hospital stay, 28-day mortality, and adverse events rate.

Results

In animal experiment, different doses of methylprednisolone could increase the body weight of rats, and reduce inflammatory factors in BALF and the degree of lung injury compared with model group. The efficacy of methylprednisolone at moderate-dose was better than that at low-dose, but was equivalent to that at high-dose, which was consistent with the differential changes in the mRNA expression of GRα, GRβ and NF-κB. In clinical study, the moderate-dose group was associated with higher PaO₂/FiO₂ ratio and lower CRP level. No significant difference in other clinical outcomes among groups was detected.

Conclusions

This study showed that the efficacy of methylprednisolone in ARDS treatment was not always dose-dependent due to the differential regulation of related receptors. The moderate-dose of methylprednisolone may be the potential optimal dose for ARDS treatment, which needs to be further verified by larger clinical trials.

The roles of methylprednisolone treatment in patients with COVID-19: A systematic review and meta-analysis

The roles of methylprednisolone in treatment of patients with COVID-19 remain unclear. The aim of this study was to evaluate the efficacy and safety of methylprednisolone in treatment of COVID-19 patients. PubMed, Cochrane and Web of Science were searched for studies comparing methylprednisolone and no glucocorticoids treatment in patients with COVID-19. Statistical pooling was reported as risk ratio (RR) or mean difference (MD) with corresponding 95 % confidence interval (CI). Thirty-three studies were eligible, including 5 randomized trials and 28 observational studies. Meta-analysis showed that compared with no glucocorticoids, methylprednisolone in treatment of COVID-19 patients was associated with reduced short-term mortality (RR 0.73; 95% CI 0.60-0.89), less need for ICU admission (RR 0.77; 95% CI 0.66-0.91) and mechanical ventilation (RR 0.69; 95% CI 0.57-0.84), increased 28-day ventilator-free days (MD 2.81; 95% CI 2.64-2.97), without increasing risk of secondary infections (RR 1.04; 95% CI 0.82-1.32), but could prolong duration of viral shedding (MD 1.03; 95% CI 0.25-1.82). Subgroup analyses revealed that low-dose (≤2mg/kg/day) methylprednisolone treatment for ≤ 7 days in severe COVID-19 patients was associated with relatively better clinical outcomes, without increasing duration of viral shedding. Compared with no glucocorticoids, methylprednisolone treatment in COVID-19 patients is associated with reduced short-term mortality and better clinical outcomes, without increasing secondary infections, but could slightly prolong duration of viral shedding. Patients with severe COVID-19 are more likely to benefit from short-term low-dose methylprednisolone treatment (1-2 mg/kg/day for ≤ 7 days).

Mechanism of Caspase-1 Inhibition by Four Anti-inflammatory Drugs Used in COVID-19 Treatment

The inflammatory protease caspase-1 is associated with the release of cytokines. An excessive number of cytokines (a “cytokine storm”) is a dangerous consequence of COVID-19 infection and has been indicated as being among the causes of death by COVID-19. The anti-inflammatory drug colchicine (which is reported in the literature to be a caspase-1 inhibitor) and the corticosteroid drugs, dexamethasone and methylprednisolone, are among the most effective active compounds for COVID-19 treatment. The SERM raloxifene has also been used as a repurposed drug in COVID-19 therapy. In this study, inhibition of caspase-1 by these four compounds was analyzed using computational methods. Our aim was to see if the inhibition of caspase-1, an important biomolecule in the inflammatory response that triggers cytokine release, could shed light on how these drugs help to alleviate excessive cytokine production. We also measured the antioxidant activities of dexamethasone and colchicine when scavenging the superoxide radical using cyclic voltammetry methods. The experimental findings are associated with caspase-1 active site affinity towards these compounds. In evaluating our computational and experimental results, we here formulate a mechanism for caspase-1 inhibition by these drugs, which involves the active site amino acid Cys285 residue and is mediated by a transfer of protons, involving His237 and Ser339. It is proposed that the molecular moiety targeted by all of these drugs is a carbonyl group which establishes a S(Cys285)–C(carbonyl) covalent bond.

"MATH+" Multi-Modal Hospital Treatment Protocol for COVID-19 Infection: Clinical and Scientific Rationale

In December 2019, coronavirus disease 2019 (COVID-19), a severe respiratory illness caused by the new coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China. The greatest impact that COVID-19 had was on intensive care units (ICUs), given that approximately 20% of hospitalized cases developed acute respiratory failure (ARF) requiring ICU admission. Based on the assumption that COVID-19 represented a viral pneumonia and no anti-coronaviral therapy existed, nearly all national and international health care societies recommended "supportive care only" avoiding other therapies outside of randomized controlled trials, with a specific prohibition against the use of corticosteroids in treatment. However, early studies of COVID-19-associated ARF reported inexplicably high mortality rates, with frequent prolonged durations of mechanical ventilation (MV), even from centers expert in such supportive care strategies. These reports led the authors to form a clinical expert panel called the Front-Line COVID-19 Critical Care Alliance (www.flccc.net). The panel collaboratively reviewed the emerging clinical, radiographic, and pathological reports of COVID-19 while initiating multiple discussions among a wide clinical network of front-line clinical ICU experts from initial outbreak areas in China, Italy, and New York. Based on the shared early impressions of "what was working and what wasn't working", the increasing medical journal publications and the rapidly accumulating personal clinical experiences with COVID-19 patients, a treatment protocol was created for the hospitalized patients based on the core therapies of methylprednisolone, ascorbic acid, thiamine, heparin and non-antiviral co-interventions (MATH+). This manuscript reviews the scientific and clinical rationale behind MATH+ based on published in-vitro, pre-clinical, and clinical data in support of each medicine, with a special emphasis of studies supporting their use in the treatment of patients with viral syndromes and COVID-19 specifically.

Low- Versus High-Dose Methylprednisolone in Adult Patients With Coronavirus Disease 2019: Less Is More

Background

Corticosteroids use in severe coronavirus disease 2019 (COVID-19) improves survival; however, the optimal dose is not established. We aim to evaluate clinical outcomes in patients with severe COVID-19 receiving high-dose corticosteroids (HDC) versus low-dose corticosteroids (LDC).

Methods

This was a quasi-experimental study conducted at a large, quaternary care center in Michigan. A corticosteroid dose change was implemented in the standardized institutional treatment protocol on November 17, 2020. All patients admitted with severe COVID-19 that received corticosteroids were included. Consecutive patients in the HDC group (September 1 to November 15, 2020) were compared to the LDC group (November 30, 2020 to January 20, 2021). High-dose corticosteroids was defined as 80 mg of methylprednisolone daily in 2 divided doses, and LDC was defined as 32–40 mg of methylprednisolone daily in 2 divided doses. The primary outcome was all-cause 28-day mortality. Secondary outcomes included progression to mechanical ventilation, hospital length of stay (LOS), discharge on supplemental oxygen, and corticosteroid-associated adverse events.

Results

Four-hundred seventy patients were included: 218 (46%) and 252 (54%) in the HDC and LDC groups, respectively. No difference was observed in 28-day mortality (14.5% vs 13.5%, P = .712). This finding remained intact when controlling for additional variables (odds ratio, 0.947; confidence interval, 0.515–1.742; P = .861). Median hospital LOS was 6 and 5 days in the HDC and LDC groups, respectively (P < .001). No differences were noted in any of the other secondary outcomes.

Conclusions

Low-dose methylprednisolone had comparable outcomes including mortality to high-dose methylprednisolone for the treatment of severe COVID-19.

Do high-dose corticosteroids improve outcomes in hospitalized COVID-19 patients?

Coronavirus disease 2019 (COVID-19) is characterized by dysregulated hyperimmune response and steroids have been shown to decrease mortality. However, whether higher dosing of steroids results in better outcomes has been debated. This was a retrospective observation of COVID-19 admissions between March 1, 2020, and March 10, 2021. Adult patients (≥18 years) who received more than 10 mg daily methylprednisolone equivalent dosing (MED) within the first 14 days were included. We excluded patients who were discharged or died within 7 days of admission. We compared the standard dose of steroids (<40 mg MED) versus the high dose of steroids (>40 mg MED). Inverse probability weighted regression adjustment (IPWRA) was used to examine whether higher dose steroids resulted in improved outcomes. The outcomes studied were in-hospital mortality, rate of acute kidney injury (AKI) requiring hemodialysis, invasive mechanical ventilation (IMV), hospital-associated infections (HAI), and readmissions. Of the 1379 patients meeting study criteria, 506 received less than 40 mg of MED (median dose 30 mg MED) and 873 received more than or equal to 40 mg of MED (median dose 78 mg MED). Unadjusted in-hospital mortality was higher in patients who received high-dose corticosteroids (40.7% vs. 18.6%, p < 0.001). On IPWRA, the use of high-dose corticosteroids was associated with higher odds of death (odds ratio [OR] 2.14; 95% confidence interval [CI] 1.45-3.14, p < 0.001) but not with the development of HAI, readmissions, or requirement of IMV. High-dose corticosteroids were associated with lower rates of AKI requiring hemodialysis (OR 0.33; 95% CI 0.18-0.63). In COVID-19, corticosteroids more than or equal to 40 mg MED were associated with higher in-hospital mortality.

Rapid Identification of Druggable Targets and the Power of the PHENotype SIMulator for Effective Drug Repurposing in COVID-19

The current, rapidly diversifying pandemic has accelerated the need for efficient and effective identification of potential drug candidates for COVID-19. Knowledge on host-immune response to SARS-CoV-2 infection, however, remains limited with very few drugs approved to date. Viable strategies and tools are rapidly arising to address this, especially with repurposing of existing drugs offering significant promise. Here we introduce a systems biology tool, the PHENotype SIMulator, which - by leveraging available transcriptomic and proteomic databases - allows modeling of SARS-CoV-2 infection in host cells in silico to i) determine with high sensitivity and specificity (both > 96%) the viral effects on cellular host-immune response, resulting in a specific cellular SARS-CoV-2 signature and ii) utilize this specific signature to narrow down promising repurposable therapeutic strategies. Powered by this tool, coupled with domain expertise, we have identified several potential COVID-19 drugs including methylprednisolone and metformin, and further discern key cellular SARS-CoV-2-affected pathways as potential new druggable targets in COVID-19 pathogenesis.