Mitigating COVID-19 Mortality and Morbidity in China's Aging Population: A Focus on Available Medications and Future Developments.

The COVID-19 pandemic, often referred to as the geropandemic, has put immense pressure on global healthcare systems worldwide, leading to a rush in the development and approval of medications for the treatment of the viral infection. Clinical trials on efficacy and safety had a limited spectrum on inclusion and endpoints because of the urgent need for fast results. The chronologically and biologically aged population is especially at risk for severe or lethal disease, as well as treatment-associated toxicity. In China, the growing elderly population segment has been a focus in public health measurements of COVID-19, guiding towards herd immunity with a mild variant, thus minimizing overall deaths and morbidity. While the COVID-19 pandemic has now been reclassified and the virus weakened, there is a clear need for novel therapies to protect the elderly. This paper reviews the current safety and efficacy of available COVID-19 medications in China, with a specific focus on 3CL protease inhibitors and the aging population. The current COVID wave in China has demonstrated a significant impact on the elderly and the need for new drugs that are effective at low doses and can be used alone, without harmful side effects, generation of viral resistance, and drug-drug interactions. The rush to develop and approve COVID-19 medications has brought up important questions about the balance between speed and caution, resulting in a pipeline of novel therapies now moving through clinical trials, including third-generation 3CL protease inhibitors. A majority of those therapeutics are being developed in China.

Application of the PHENotype SIMulator for rapid identification of potential candidates in effective COVID-19 drug repurposing

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 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 specific cellular SARS-CoV-2 signatures and ii) utilize these cell-specific signatures to identify promising repurposable therapeutics. Powered by this tool, coupled with domain expertise, we identify several potential COVID-19 drugs including methylprednisolone and metformin, and further discern key cellular SARS-CoV-2-affected pathways as potential druggable targets in COVID-19 pathogenesis. Graphical abstract Application of the PHENotype SIMulator: By modeling human host-cell infection with a pathogen in silico - in this case SARS-CoV-2 - we can acquire a cell-specific viral signature and formulate multiple drug repurposing hypotheses;(I) logFold Changes (logFCs) of Differentially Expressed Genes (DEGs) arising from transcriptomic genome wide expression analysis of infected vs. baseline uninfected cells are used to represent a virus in the meta-pathway;(II) we run the PHENSIM simulation by upregulating the viral node and collect all perturbation values computed by PHENSIM for pathway endpoints to define a cell-specific pathogen signature. (III) The same process is applied to expression data arising from whole transcriptome-wide expression analysis of drug treated vs. mock-treated cell lines, yielding a cell-specific drug signature. This process is iterated for each drug we wish to test and collected in a database of drug signatures. (IV) Finally, a Pearson correlation analysis between the pathogen and each drug signature is utilized to score repurposing candidates.Image 1

Application of the PHENotype SIMulator for rapid identification of potential candidates in effective COVID-19 drug repurposing.

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 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 specific cellular SARS-CoV-2 signatures and ii) utilize these cell-specific signatures to identify promising repurposable therapeutics. Powered by this tool, coupled with domain expertise, we identify several potential COVID-19 drugs including methylprednisolone and metformin, and further discern key cellular SARS-CoV-2-affected pathways as potential druggable targets in COVID-19 pathogenesis.

Clinical trials for COVID-19 should include sex as a variable

The number of COVID-19 cases appears to be comparable between men and women, but the severity of disease and death is two times greater for men than for women. History, including the 1918 influenza pandemic, warned us that male biases in COVID-19 could occur. In this Viewpoint, we focus on biological explanations, with a forward look at why clinicians and biomedical researchers should consider sex as a biological variable that will affect treatment outcomes for COVID-19. There is a long history of not analyzing or reporting differences between women and men in the prophylactic or therapeutic treatment of infectious diseases. We seek to reverse this trend and call on investigators developing and testing therapeutic and prophylactic approaches for COVID-19 to design studies that are inclusive of male versus female differences in drug responses, immunotherapies, vaccines, and nonpharmacological interventions.

Increased Pace of Aging in COVID-Related Mortality.

Identifying prognostic biomarkers and risk stratification for COVID-19 patients is a challenging necessity. One of the core survival factors is patient age. However, chronological age is often severely biased due to dormant conditions and existing comorbidities. In this retrospective cohort study, we analyzed the data from 5315 COVID-19 patients (1689 lethal cases) admitted to 11 public hospitals in New York City from 1 March 2020 to 1 December. We calculated patients' pace of aging with BloodAge-a deep learning aging clock trained on clinical blood tests. We further constructed survival models to explore the prognostic value of biological age compared to that of chronological age. A COVID-19 score was developed to support a practical patient stratification in a clinical setting. Lethal COVID-19 cases had higher predicted age, compared to non-lethal cases (Δ = 0.8-1.6 years). Increased pace of aging was a significant risk factor of COVID-related mortality (hazard ratio = 1.026 per year, 95% CI = 1.001-1.052). According to our logistic regression model, the pace of aging had a greater impact (adjusted odds ratio = 1.09 ± 0.00, per year) than chronological age (1.04 ± 0.00, per year) on the lethal infection outcome. Our results show that a biological age measure, derived from routine clinical blood tests, adds predictive power to COVID-19 survival models.

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.

The potential of rapalogs to enhance resilience against SARS-CoV-2 infection and reduce the severity of COVID-19.

COVID-19 disproportionately affects older people, with likelihood of severe complications and death mirroring that of other age-associated diseases. Inhibition of the mechanistic target of rapamycin complex 1 (mTORC1) has been shown to delay or reverse many age-related phenotypes, including declining immune function. Rapamycin (sirolimus) and rapamycin derivatives are US Food and Drug Administration-approved inhibitors of mTORC1 with broad clinical utility and well established dosing and safety profiles. Based on preclinical and clinical evidence, a strong case can be made for immediate large-scale clinical trials to assess whether rapamycin and other mTORC1 inhibitors can prevent COVID-19 infection in these populations and also to determine whether these drugs can improve outcomes in patients with severe COVID-19.

ANERGY TO SYNERGY-THE ENERGY FUELING THE RXCOVEA FRAMEWORK.

We write to introduce our novel group formed to confront some of the issues raised by the COVID-19 pandemic. Information about the group, which we named "cure COVid for Ever and for All" (RxCOVEA), its dynamic membership (changing regularly), and some of its activities-described in more technical detail for expert perusal and commentary-are available upon request.

Towards Precision Medicine: Inclusion of Sex and Gender Aspects in COVID-19 Clinical Studies-Acting Now before It Is Too Late-A Joint Call for Action.

The COVID-19 global pandemic is accelerating investigations for effective vaccines and repurposable validated therapeutics [...].