Feeds:
Posts
Comments

Archive for the ‘number of asymptomatic infections’ Category

Epidemiological measurement on COVID-19 pandemic may have statistical biases which might affect next variant responses

Reporter: Stephen J. Williams Ph.D.

Source: https://www.science.org/doi/10.1126/science.abi6602

From the jounal Science

Tackling the pandemic with (biased) data

CHRISTINA PAGEL AND CHRISTIAN A. YATESSCIENCE•22 Oct 2021•Vol 374, Issue 6566•pp. 403-404•DOI: 10.1126/science.abi66027,757

Accurate and near real-time data about the trajectory of the COVID-19 pandemic have been crucial in informing mitigation policies. Because choosing the right mitigation policies relies on an accurate assessment of the current state of the local epidemic, the potential ramifications of misinterpreting data are serious. Each data source has inherent biases and pitfalls in interpretation. The more data sources that are interpreted in combination, the easier it is to detect genuine changes in an epidemic. Recently, in many countries, this has involved disentangling the varying impact of rising but heterogeneous vaccination rates, relaxation of mitigations, and the emergence of new variants such as Delta.The exact data collected and their accuracy will vary by country. Typical data common to many countries are numbers of tests, confirmed cases, hospital and intensive care unit (ICU) admissions and occupancy, deaths, and vaccinations (1). Many countries additionally sequence a proportion of new positive tests to identify and track emerging variants. Some countries also now collect and publish data on infections, hospitalizations, and deaths by vaccination status (e.g., Israel and the UK). Stratifying all available data by different demographic factors (e.g., age, location, measures of deprivation, and ethnicity) is crucial for understanding patterns of spread, potential impact of policies, and efficacy of vaccines (age, timing of breakthrough infections, and prevalent variants).It is also necessary to be aware of what data are not being collected. For example, persistent symptoms of COVID-19 (Long Covid) were recognized as a long-term adverse outcome by the autumn of 2020. However, no simple diagnostic test has been associated with the up to 200 different reported symptoms (2). Counting Long Covid relies on a clinical diagnosis, based on a history of having had COVID-19 and a failure to fully recover, with development of some characteristic symptoms and with no obvious alternative cause (3). These features make it very difficult to measure routinely, and so it rarely is. As a result, Long Covid is often neglected in decision-making. Failure to account for the disease load associated with Long Covid may lead to an unnecessary long-term societal health burden.The feedback between different types of outcomes, different severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, different mitigation policies (including vaccination), and individual risks (a combination of exposure and clinical risk) is complex and must be factored into both interpretation of data and the development of policy. Using all available data to quantify transmission is crucial to ensuring rapid and effective responses to early phases of renewed exponential growth and to evaluating mitigation measures. Relying too much on a single data source, or without disaggregating data, risks fundamentally misunderstanding the state of the epidemic.The inherent biases and lags in data are particularly important to understand from the point of view of policy-makers. Because of the natural time scales of COVID-19 disease progression (see the figure), policy changes can take several weeks to show up in the data. Purely reactive policy-making is likely to be ineffective. When cases are rising, increases in hospital admissions and deaths will follow. When a new variant is outcompeting existing strains, it is likely to become dominant without action to suppress. The precautionary principle suggests acting early and emphatically. Conversely, when releasing restrictions, governments must wait long enough to assess them before continuing with re-opening.The most up-to-date indicator of the state of the epidemic is typically the number of confirmed cases, as ascertained through testing of both symptomatic individuals and those tested frequently regardless of symptoms. Symptom-based testing is likely to pick up more adults and fewer younger individuals (4). Infections in children are harder to detect: children are more likely to be asymptomatic than adults, are harder to administer tests to (particularly young children), are often exposed to other viruses with similar symptoms, and can present with symptoms that are atypical in adults (e.g., abdominal pain or nausea). Children under 12 are not routinely offered the COVID-19 vaccination, and their mixing in schools provides ongoing opportunities for the virus to circulate, so it will be important for countries to track infections in children as accurately as possible. Other testing biases include accessibility, reporting lags, and the ability to act lawfully upon receiving a positive result. Substantial changes in the number of people seeking tests may further confound case figures (5). Case positivity rates may provide a more accurate reflection of the state of the epidemic (6) but are dependent on the mix of symptomatic and asymptomatic people being tested.SARS-CoV-2 variants have been an important driver of local epidemics in 2021. The four main SARS-CoV-2 variants of concern, to date, are B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma), and B.1.617.2 (Delta). Some have been more transmissible (Alpha), some have substantial resistance to previous infection or vaccines (Beta), and some have elements of both (Gamma and Delta) (7). Currently, the high transmissibility of Delta combined with some immune evasion has made it the world’s dominant variant. Determining which variants pose a substantial threat is difficult and takes time, particularly when many variants cocirculate. This is especially true for situations in which a dominant variant is declining, and a new one growing. While the declining variant remains dominant, its decrease masks increases in the new variant because case numbers remain unchanged or fall overall. Only when a new variant becomes dominant does its growth become apparent in aggregated case data, by which time it is, by definition, too late to contain its spread. This dynamic has been observed across the world with Delta over the latter half of 2021.With multiple variants circulating, there are, effectively, multiple epidemics occurring in parallel, and they must be tracked separately. This typically requires the availability of sequencing data, which is unfortunately limited in most countries. Sequencing takes time and so is typically a few weeks out of date. These lags, and the uncertainty in sampling, can lead to hesitancy in acting. The rapid path to dominance of the Delta variant in the UK highlights the need for action when a quickly growing variant represents a few percent (or less) of overall cases.Hospital admissions or occupancy data do not suffer the same biases associated with testing behaviors and provide unequivocal evidence of widespread transmission, its geography, and demographics. However, hospital admissions lag infections more than reported cases do, rendering these data less useful for proactive decision-making. Hospital data are also biased toward older people, who are more likely to suffer severe COVID-19, and now, unvaccinated populations. ICU occupancy data show a younger age profile than admissions because younger patients have a better chance of benefitting from the invasive treatment procedures (8).Deaths are the most lagged indicator, typically occurring 3 or more weeks after infection and with an additional lag in registration and reporting. Death data should never be used to inform real-time policy decisions. Instead, death figures can act as an eventual measure of the success of a country’s epidemic strategy and implementation. The age distribution of those who eventually die from COVID-19 is different from other metrics of the epidemic—skewed furthest toward older age groups (9). Those with clinical risk factors (such as immunodeficiency, obesity, or existing lung conditions), high exposure (health care workers and low-income workers), and the unvaccinated are overrepresented in COVID-19 deaths.In countries with high vaccination rates, vaccination has had a substantial impact—reducing COVID-19 cases, hospitalizations, and deaths. However, when looking at the raw numbers in highly vaccinated populations, it can be the case that more fully vaccinated people are dying of COVID-19 than unvaccinated. If these raw statistics are misinterpreted—or worse, deliberately misused—they can damage vaccine confidence. More vaccinated people may die than unvaccinated because such a high proportion of people are vaccinated (10). This does not mean vaccines are not effective at preventing death. Looking at the rates of death in vaccinated and unvaccinated individuals separately within age groups demonstrates that vaccines provide considerable protection against severe disease and death. This example illustrates how important it is to curate and manage the way in which data are presented.

COVID-19 progressionAn approximate timeline from infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to various outcomes. When current infections show up in different data sources depends on this timeline. Collecting data for Long Covid, asymptomatic infection, and vaccine history will improve understanding of the pandemic.GRAPHIC: N. CARY/SCIENCE

Each country has established its own vaccination priority lists and dosing schedules to best achieve its goals (1112). Each of these strategies will manifest differently in the data. Additionally, many countries are using multiple vaccines in tandem and administer them differently for different demographics. Some countries are vaccinating adolescents, and others are not or not offering them the full approved dose. Most vaccines require two doses, spaced between 3 and 12 weeks apart, except for the Johnson & Johnson single-dose vaccine. This matters, particularly as variants spread, because different vaccines have different effectiveness after one and two doses, different timelines to full effectiveness, and different effectiveness against variants (13).Data published on the vaccination delivery itself must thus go beyond the raw numbers of people vaccinated. Vaccine uptake must be reported by whether fully or partially (one-dose in a two-dose regimen) vaccinated and using the whole population as a denominator. It is vital to disaggregate vaccine data by age, gender, and ethnicity as well as location so that it is possible, for example, to understand the impact of deprivation on vaccine coverage or vaccine hesitancy in particular demographics. When interpreting vaccination data, it is important to remember that there is also a lag between delivery and the build-up of immunity.Data on reinfection and post-vaccination (breakthrough) infection are also important to determine the relative benefits of infection-mediated and vaccine-mediated immunity and the length of protection offered. Studies that show those who were immunized earlier were acquiring COVID-19 with higher rates than those vaccinated more recently may suggest waning vaccine protection (14). Such studies have already prompted vaccine booster programs in some countries. However, any study that suggests waning immunity must be extremely careful to ensure that the “early” and “recent” subgroups are properly controlled. Differences in prior exposure, affluence, education level, age, and other demographic factors between these cohorts may be enough to explain the disparities in SARS-CoV-2 infection rates, even in the absence of waning immunity. Waning immunity must also be reported separately for different outcomes; for example, there might be waning in terms of preventing symptomatic infection but far less or none in preventing death (15). Additionally, there are ethical concerns about mass booster programs in high-income countries while many lower-income countries have been unable to procure vaccines.Moving into the vaccination era, reported cases, hospitalizations, and deaths should also be disaggregated by vaccination status (and by which vaccine), which will be easier in countries where national linked datasets exist. Additionally, incorporating Long Covid into routine reporting and policy-making is crucial. Consistent diagnostic criteria and well-controlled studies will be vital to this effort. These elusive data will be of critical importance to navigate our way successfully out of the pandemic.

Acknowledgments

C.P. and C.A.Y. are both members of Independent SAGE: www.independentsage.org.

References and Notes

1M. Roser et al., Our World in Data (2021); https://bit.ly/3kepLgw.GO TO REFERENCEGOOGLE SCHOLAR2H. E. Davis et al., E. Clin. Med.38, 101019 (2021).GO TO REFERENCEGOOGLE SCHOLAR3M. Sivan, S. Taylor, BMJ371, m4938 (2020).GO TO REFERENCECROSSREFPUBMEDGOOGLE SCHOLAR4S. M. Moghadas et al., Proc. Natl. Acad. Sci. U.S.A.117, 17513 (2020).GO TO REFERENCECROSSREFPUBMEDGOOGLE SCHOLAR5J. Wise, BMJ370, m3678 (2020).GO TO REFERENCECROSSREFPUBMEDGOOGLE SCHOLAR6D. Dowdy, G. D’Souza, COVID-19 Testing: Understanding the “Percent Positive” (2020); https://bit.ly/3CeN8wl.GO TO REFERENCEGOOGLE SCHOLAR7C. E. Gómez et al., Vaccines (Basel)9, 243 (2021).CROSSREFPUBMEDGOOGLE SCHOLAR8A. B. Docherty et al., BMJ369, 1985 (2020).GO TO REFERENCECROSSREFPUBMEDGOOGLE SCHOLAR9Office for National Statistics, Deaths registered weekly in England and Wales by age and sex: covid-19 (2021); https://bit.ly/3Ci2obS.

For articles on Issues of Bias in Science on this Open Access Journal see

From @Harvardmed Center for Bioethics: The Medical Ethics of the Corona Virus Crisis

Live Notes from @HarvardMed Bioethics: Authors Jerome Groopman, MD & Pamela Hartzband, MD, discuss Your Medical Mind

Read Full Post »

Nir Hacohen and Marcia Goldberg, Researchers at MGH and the Broad Institute identify protein “signature” of severe COVID-19

Curator and Reporter: Aviva Lev-Ari, PhD, RN

Longitudinal proteomic analysis of plasma from patients with severe COVID-19 reveal patient survival-associated signatures, tissue-specific cell death, and cell-cell interactions

Open AccessPublished:April 30, 2021DOI:https://doi.org/10.1016/j.xcrm.2021.100287

Highlights

  • 16% of COVID-19 patients display an atypical low-inflammatory plasma proteome
  • Severe COVID-19 is associated with heterogeneous plasma proteomic responses
  • Death of virus-infected lung epithelial cells is a key feature of severe disease
  • Lung monocyte/macrophages drive T cell activation, together promoting epithelial damage

Summary

Mechanisms underlying severe COVID-19 disease remain poorly understood. We analyze several thousand plasma proteins longitudinally in 306 COVID-19 patients and 78 symptomatic controls, uncovering immune and non-immune proteins linked to COVID-19. Deconvolution of our plasma proteome data using published scRNAseq datasets reveals contributions from circulating immune and tissue cells. Sixteen percent of patients display reduced inflammation yet comparably poor outcomes. Comparison of patients who died to severely ill survivors identifies dynamic immune cell-derived and tissue-associated proteins associated with survival, including exocrine pancreatic proteases. Using derived tissue-specific and cell type-specific intracellular death signatures, cellular ACE2 expression, and our data, we infer whether organ damage resulted from direct or indirect effects of infection. We propose a model in which interactions among myeloid, epithelial, and T cells drive tissue damage. These datasets provide important insights and a rich resource for analysis of mechanisms of severe COVID-19 disease.

Graphical Abstract

Figure thumbnail fx1

Image Source: DOI: https://doi.org/10.1016/j.xcrm.2021.100287

https://www.cell.com/cell-reports-medicine/fulltext/S2666-3791(21)00115-4

The quest to identify mechanisms that might be contributing to death in COVID-19: Why do some patients die from this disease, while others — who appear to be just as ill do not?

Researchers at Massachusetts General Hospital (MGH) and the Broad Institute of MIT and Harvard have identified the protein “signature” of severe COVID-19

Interest was to develop methods for studying human immune responses to infections, which they had applied to the condition known as bacterial sepsis. The three agreed to tackle this new problem with the goal of understanding how the human immune system responds to SARS-CoV-2, the novel pathogen that causes COVID-19.

How scientists launched a study in days to probe COVID-19’s unpredictability

Collecting these specimens required a large team of collaborators from many departments, which worked overtime for five weeks to amass blood samples from 306 patients who tested positive for COVID-19, as well as from 78 patients with similar symptoms who tested negative for the coronavirus.

Alexandra-Chloé Villani

Credit : Alexandra-Chloé VillaniResearch associates at Mass General who worked countless hours to process blood samples for the COVID Acute Cohort Study (from left to right: Anna Gonye, Irena Gushterova, and Tom Lasalle)By Leah Eisenstadt

https://www.broadinstitute.org/news/how-scientists-launched-study-days-probe-covid-19%E2%80%99s-unpredictability

As the COVID-19 surge began in March, Mass General and Broad researchers worked around the clock to begin learning why some patients fare worse with the disease than others

Protein signatures in the blood

https://www.broadinstitute.org/news/researchers-identify-protein-%E2%80%9Csignature%E2%80%9D-severe-covid-19

The study found that most patients with COVID-19 have a consistent protein signature, regardless of disease severity; as would be expected, their bodies mount an immune response by producing proteins that attack the virus. “But we also found a small subset of patients with the disease who did not demonstrate the pro-inflammatory response that is typical of other COVID-19 patients,” Filbin said, yet these patients were just as likely as others to have severe disease. Filbin, who is also an assistant professor of emergency medicine at Harvard Medical School (HMS), noted that patients in this subset tended to be older people with chronic diseases, who likely had weakened immune systems.

Among other revelations, this showed that the most prevalent severity-associated protein, a pro-inflammatory protein called interleukin-6 (IL-6) rose steadily in patients who died, while it rose and then dropped in those with severe disease who survived. Early attempts by other groups to treat COVID-19 patients experiencing acute respiratory distress with drugs that block IL-6 were disappointing, though more recent studies show promise in combining these medications with the steroid dexamethasone.

Hacohen, who is a professor of medicine at HMS and director of the Broad’s Cell Circuits Program:

“You can ask which of the many thousands of proteins that are circulating in your blood are associated with the actual outcome,” he said, “and whether there is a set of proteins that tell us something.”

Goldberg, who is a professor of emergency medicine at HMS:

They are highly likely to be useful in figuring out some of the underlying mechanisms that lead to severe disease and death in COVID-19,” she said, noting her gratitude to the patients involved in the study. Their samples are already being used to study other aspects of COVID-19, such as identifying the qualities of antibodies that patients form against the virus.

SOURCES

Original Research

Filbin MR, Mehta A, et al. Longitudinal proteomic analysis of plasma from patients with severe COVID-19 reveal patient survival-associated signatures, tissue-specific cell death, and cell-cell interactionsCell Reports Medicine. Online April 30, 2021. DOI: 10.1016/j.xcrm.2021.100287.

Adapted from a press release originally issued by Massachusetts General Hospital.

https://www.broadinstitute.org/news/researchers-identify-protein-%E2%80%9Csignature%E2%80%9D-severe-covid-19

https://www.cell.com/cell-reports-medicine/fulltext/S2666-3791(21)00115-4

Read Full Post »

Thriving Vaccines and Research: Weizmann Institute Coronavirus Research Development

Reporter: Amandeep Kaur, B.Sc., M.Sc.

In early February, Prof. Eran Segal updated in one of his tweets and mentioned that “We say with caution, the magic has started.”

The article reported that this statement by Prof. Segal was due to decreasing cases of COVID-19, severe infection cases and hospitalization of patients by rapid vaccination process throughout Israel. Prof. Segal emphasizes in another tweet to remain cautious over the country and informed that there is a long way to cover and searching for scientific solutions.

A daylong webinar entitled “COVID-19: The epidemic that rattles the world” was a great initiative by Weizmann Institute to share their scientific knowledge about the infection among the Israeli institutions and scientists. Prof. Gideon Schreiber and Dr. Ron Diskin organized the event with the support of the Weizmann Coronavirus Response Fund and Israel Society for Biochemistry and Molecular Biology. The speakers were invited from the Hebrew University of Jerusalem, Tel-Aviv University, the Israel Institute for Biological Research (IIBR), and Kaplan Medical Center who addressed the molecular structure and infection biology of the virus, treatments and medications for COVID-19, and the positive and negative effect of the pandemic.

The article reported that with the emergence of pandemic, the scientists at Weizmann started more than 60 projects to explore the virus from different range of perspectives. With the help of funds raised by communities worldwide for the Weizmann Coronavirus Response Fund supported scientists and investigators to elucidate the chemistry, physics and biology behind SARS-CoV-2 infection.

Prof. Avi Levy, the coordinator of the Weizmann Institute’s coronavirus research efforts, mentioned “The vaccines are here, and they will drastically reduce infection rates. But the coronavirus can mutate, and there are many similar infectious diseases out there to be dealt with. All of this research is critical to understanding all sorts of viruses and to preempting any future pandemics.”

The following are few important projects with recent updates reported in the article.

Mapping a hijacker’s methods

Dr. Noam Stern-Ginossar studied the virus invading strategies into the healthy cells and hijack the cell’s systems to divide and reproduce. The article reported that viruses take over the genetic translation system and mainly the ribosomes to produce viral proteins. Dr. Noam used a novel approach known as ‘ribosome profiling’ as her research objective and create a map to locate the translational events taking place inside the viral genome, which further maps the full repertoire of viral proteins produced inside the host.

She and her team members grouped together with the Weizmann’s de Botton Institute and researchers at IIBR for Protein Profiling and understanding the hijacking instructions of coronavirus and developing tools for treatment and therapies. Scientists generated a high-resolution map of the coding regions in the SARS-CoV-2 genome using ribosome-profiling techniques, which allowed researchers to quantify the expression of vital zones along the virus genome that regulates the translation of viral proteins. The study published in Nature in January, explains the hijacking process and reported that virus produces more instruction in the form of viral mRNA than the host and thus dominates the translation process of the host cell. Researchers also clarified that it is the misconception that virus forced the host cell to translate its viral mRNA more efficiently than the host’s own translation, rather high level of viral translation instructions causes hijacking. This study provides valuable insights for the development of effective vaccines and drugs against the COVID-19 infection.

Like chutzpah, some things don’t translate

Prof. Igor Ulitsky and his team worked on untranslated region of viral genome. The article reported that “Not all the parts of viral transcript is translated into protein- rather play some important role in protein production and infection which is unknown.” This region may affect the molecular environment of the translated zones. The Ulitsky group researched to characterize that how the genetic sequence of regions that do not translate into proteins directly or indirectly affect the stability and efficiency of the translating sequences.

Initially, scientists created the library of about 6,000 regions of untranslated sequences to further study their functions. In collaboration with Dr. Noam Stern-Ginossar’s lab, the researchers of Ulitsky’s team worked on Nsp1 protein and focused on the mechanism that how such regions affect the Nsp1 protein production which in turn enhances the virulence. The researchers generated a new alternative and more authentic protocol after solving some technical difficulties which included infecting cells with variants from initial library. Within few months, the researchers are expecting to obtain a more detailed map of how the stability of Nsp1 protein production is getting affected by specific sequences of the untranslated regions.

The landscape of elimination

The article reported that the body’s immune system consists of two main factors- HLA (Human Leukocyte antigen) molecules and T cells for identifying and fighting infections. HLA molecules are protein molecules present on the cell surface and bring fragments of peptide to the surface from inside the infected cell. These peptide fragments are recognized and destroyed by the T cells of the immune system. Samuels’ group tried to find out the answer to the question that how does the body’s surveillance system recognizes the appropriate peptide derived from virus and destroy it. They isolated and analyzed the ‘HLA peptidome’- the complete set of peptides bound to the HLA proteins from inside the SARS-CoV-2 infected cells.

After the analysis of infected cells, they found 26 class-I and 36 class-II HLA peptides, which are present in 99% of the population around the world. Two peptides from HLA class-I were commonly present on the cell surface and two other peptides were derived from coronavirus rare proteins- which mean that these specific coronavirus peptides were marked for easy detection. Among the identified peptides, two peptides were novel discoveries and seven others were shown to induce an immune response earlier. These results from the study will help to develop new vaccines against new coronavirus mutation variants.

Gearing up ‘chain terminators’ to battle the coronavirus

Prof. Rotem Sorek and his lab discovered a family of enzymes within bacteria that produce novel antiviral molecules. These small molecules manufactured by bacteria act as ‘chain terminators’ to fight against the virus invading the bacteria. The study published in Nature in January which reported that these molecules cause a chemical reaction that halts the virus’s replication ability. These new molecules are modified derivates of nucleotide which integrates at the molecular level in the virus and obstruct the works.

Prof. Sorek and his group hypothesize that these new particles could serve as a potential antiviral drug based on the mechanism of chain termination utilized in antiviral drugs used recently in the clinical treatments. Yeda Research and Development has certified these small novel molecules to a company for testing its antiviral mechanism against SARS-CoV-2 infection. Such novel discoveries provide evidences that bacterial immune system is a potential repository of many natural antiviral particles.

Resolving borderline diagnoses

Currently, Real-time Polymerase chain reaction (RT-PCR) is the only choice and extensively used for diagnosis of COVID-19 patients around the globe. Beside its benefits, there are problems associated with RT-PCR, false negative and false positive results and its limitation in detecting new mutations in the virus and emerging variants in the population worldwide. Prof. Eran Elinavs’ lab and Prof. Ido Amits’ lab are working collaboratively to develop a massively parallel, next-generation sequencing technique that tests more effectively and precisely as compared to RT-PCR. This technique can characterize the emerging mutations in SARS-CoV-2, co-occurring viral, bacterial and fungal infections and response patterns in human.

The scientists identified viral variants and distinctive host signatures that help to differentiate infected individuals from non-infected individuals and patients with mild symptoms and severe symptoms.

In Hadassah-Hebrew University Medical Center, Profs. Elinav and Amit are performing trails of the pipeline to test the accuracy in borderline cases, where RT-PCR shows ambiguous or incorrect results. For proper diagnosis and patient stratification, researchers calibrated their severity-prediction matrix. Collectively, scientists are putting efforts to develop a reliable system that resolves borderline cases of RT-PCR and identify new virus variants with known and new mutations, and uses data from human host to classify patients who are needed of close observation and extensive treatment from those who have mild complications and can be managed conservatively.

Moon shot consortium refining drug options

The ‘Moon shot’ consortium was launched almost a year ago with an initiative to develop a novel antiviral drug against SARS-CoV-2 and was led by Dr. Nir London of the Department of Chemical and Structural Biology at Weizmann, Prof. Frank von Delft of Oxford University and the UK’s Diamond Light Source synchroton facility.

To advance the series of novel molecules from conception to evidence of antiviral activity, the scientists have gathered support, guidance, expertise and resources from researchers around the world within a year. The article reported that researchers have built an alternative template for drug-discovery, full transparency process, which avoids the hindrance of intellectual property and red tape.

The new molecules discovered by scientists inhibit a protease, a SARS-CoV-2 protein playing important role in virus replication. The team collaborated with the Israel Institute of Biological Research and other several labs across the globe to demonstrate the efficacy of molecules not only in-vitro as well as in analysis against live virus.

Further research is performed including assaying of safety and efficacy of these potential drugs in living models. The first trial on mice has been started in March. Beside this, additional drugs are optimized and nominated for preclinical testing as candidate drug.

Source: https://www.weizmann.ac.il/WeizmannCompass/sections/features/the-vaccines-are-here-and-research-abounds

Other related articles were published in this Open Access Online Scientific Journal, including the following:

Identification of Novel genes in human that fight COVID-19 infection

Reporter: Amandeep Kaur, B.Sc., M.Sc. (ept. 5/2021)

https://pharmaceuticalintelligence.com/2021/04/19/identification-of-novel-genes-in-human-that-fight-covid-19-infection/

Fighting Chaos with Care, community trust, engagement must be cornerstones of pandemic response

Reporter: Amandeep Kaur, B.Sc., M.Sc. (ept. 5/2021)

https://pharmaceuticalintelligence.com/2021/04/13/fighting-chaos-with-care/

T cells recognize recent SARS-CoV-2 variants

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2021/03/30/t-cells-recognize-recent-sars-cov-2-variants/

Need for Global Response to SARS-CoV-2 Viral Variants

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2021/02/12/need-for-global-response-to-sars-cov-2-viral-variants/

Mechanistic link between SARS-CoV-2 infection and increased risk of stroke using 3D printed models and human endothelial cells

Reporter: Adina Hazan, PhD

https://pharmaceuticalintelligence.com/2020/12/28/mechanistic-link-between-sars-cov-2-infection-and-increased-risk-of-stroke-using-3d-printed-models-and-human-endothelial-cells/

Read Full Post »

Why Do Some COVID-19 Patients Infect Many Others, Whereas Most Don’t Spread the Virus At All?

Guest Reporter: Jason S Zielonka, MD

One of the key parameters in COVID-19 pandemic epidemiology has been to define the spread metrics, basically identifying how a host spreads the virus to uninfected individuals. The pattern of spread can impact how and which preventative measures such as social distancing and hand washing can impact spread patterns. In particular, two metrics, the average number of new patients infected by each host (the reproduction number, R) and a factor representing the tendency to cluster (the dispersion factor, k) can be used to describe and model the spread of a virus quite well. Higher values of R mean more people are infected by a single host, i.e, the disease is more contagious; lower values of k mean that a host infects a larger number of new patients, i.e., the disease is more clustered.

The reproduction number, R, for SARS-CoV-2, without social distancing, is about 3. But this is an average, taken over an aggregate of patients. For most individuals, R is zero, i.e., most patients do not transmit the virus to others. For comparison, SARS and MERS, both coronaviruses, had R > 3 and the 1918 influenza pandemic had R >> 3. So what determines viral spread and how can we use that information to treat and eradicate SARS-CoV-2?

In 2005, by modeling the Chinese SARS outbreak and comparing the model to the real-world data, Lloyd-Smith and co-authors were able to determine that SARS had a k of about 0.16. MERS, in 2012, was estimated to have k around 0.25; the 1918 pandemic, by contrast, had a k of 1, meaning it had very little cluster effect. The current modeling indicates that k for SARS-CoV-2 is not conclusive, but it appears higher than k for either SARS or MERS.

This work has provided insights into some of the factors influencing cluster spread, which can be controlled in a more specific way than quarantining an entire population. There will be individual variance, but we know that people are particularly infectious over a certain time period; that certain activities are more conducive to droplet formation and wider spread, and that being outdoors rather than in confined and noisy indoor locations leads to less spread. This can all lead to better, faster and more tolerable approaches to either future pandemics or to a recurrence of SARS-CoV-2.

SOURCE

https://www.sciencemag.org/news/2020/05/why-do-some-covid-19-patients-infect-many-others-whereas-most-don-t-spread-virus-all

Read Full Post »

Sex Differences in Immune Responses that underlie COVID-19 Disease Outcomes

Reporter: Aviva Lev-Ari, PhD, RN and Irina Robu, PhD COVID-19 is a non-discriminatory virus, it can infect anyone from young to old, but it seems that older men are twice more susceptible to it and most likely to become severely sick and die in comparison to women of the same age. Researchers from Yale university, published an article suggesting that men, particularly those over the age of 60 may need to depend more on vaccines to protect themselves from infection. According to their research published in Nature in August 2020, known sex differences between men and women pose challenges to the immune system. Women mount faster and stronger immune responses, possibly because their bodies are equipped to fight pathogens that threaten unborn or newborn children. Over time, an immune system in a constant state of high alert can be harmful. The findings underline the necessity for companies developing coronavirus vaccines to analyze their data by sex and may influence decisions about dosing. Dr. Iwasaki’s team from Yale  analyzed immune responses in 17 men and 22 women who were admitted to the hospital soon after they were infected with the coronavirus. The investigators collected blood, nasopharyngeal swabs, saliva, urine and stool from the patients every three to seven days. The researchers also analyzed data from an additional 59 men and women who did not meet those criteria. Over all, the scientists found, the women’s bodies produced more T cells, which can kill and stop the infection from spreading. Men on the other hand presented  a much weaker activation of T cells and that delay was linked to how sick the men became. The older the men, the weaker their T cell responses. Even though the study provided some more information about why men become sicker when diagnosed with coronavirus than women,  it did not offer a clear reason for the differences between men and women. SOURCE https://www.nature.com/articles/s41586-020-2700-3
Article

This is an unedited manuscript that has been accepted for publication. Nature Research are providing this early version of the manuscript as a service to our authors and readers. The manuscript will undergo copyediting, typesetting and a proof review before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers apply.

Sex differences in immune responses that underlie COVID-19 disease outcomes

Abstract

A growing body of evidence indicates sex differences in the clinical outcomes of coronavirus disease 2019 (COVID-19)1–5. However, whether immune responses against SARS-CoV-2 differ between sexes, and whether such differences explain male susceptibility to COVID-19, is currently unknown. In this study, we examined sex differences in
  • viral loads,
  • SARS-CoV-2-specific antibody titers,
  • plasma cytokines, as well as
  • blood cell phenotyping in COVID-19 patients.
By focusing our analysis on patients with moderate disease who had not received immunomodulatory medications, our results revealed that
  • male patients had higher plasma levels of innate immune cytokines such as IL-8 and IL-18 along with more robust induction of non-classical monocytes. In contrast,
  • female patients mounted significantly more robust T cell activation than male patients during SARS-CoV-2 infection, which was sustained in old age.
  • Importantly, we found that a poor T cell response negatively correlated with patients’ age and was associated with worse disease outcome in male patients, but not in female patients.
  • Conversely, higher innate immune cytokines in female patients associated with worse disease progression, but not in male patients.
  • These findings reveal a possible explanation underlying observed sex biases in COVID-19, and provide an important basis for the development of
  • a sex-based approach to the treatment and care of men and women with COVID-19.

Author information

Affiliations

Consortia

Corresponding author

Correspondence to Akiko Iwasaki.

Read Full Post »

Online Event: Vaccine matters: Can we cure coronavirus? An AAAS Webinar on COVID19: 8/12/2020

Reporter: Stephen J. Williams. PhD

Source: Online Event

Top on the world’s want list right now is a coronavirus vaccine. There is plenty of speculation about how and when this might become a reality, but clear answers are scarce.Science/AAAS, the world’s leading scientific organization and publisher of the Science family of journals, brings together experts in the field of coronavirus vaccine research to answer the public’s most pressing questions: What vaccines are being developed? When are we likely to get them? Are they safe? And most importantly, will they work?

link: https://view6.workcast.net/AuditoriumAuthenticator.aspx?cpak=1836435787247718&pak=8073702641735492

Presenters

Presenter
Speaker: Sarah Gilbert, Ph.D.

University of Oxford
Oxford, UK
View Bio

Presenter
Speaker: Kizzmekia Corbett, Ph.D.

National Institute of Allergy and Infectious Diseases, NIH
Bethesda, MD
View Bio

Presenter
Speaker: Kathryn M. Edwards, M.D.

Vanderbilt Vaccine Research Program
Nashville, TN
View Bio

Presenter
Speaker: Jon Cohen

Science/AAAS
San Diego, CA
View Bio

Presenter
Moderator: Sean Sanders, Ph.D.

Science/AAAS
Washington, DC
View Moderator Bio

Read Full Post »

50,008 views
Apr 22, 2020

496K subscribers

Dmitry Korkin is a professor of bioinformatics and computational biology at Worcester Polytechnic Institute, where he specializes in bioinformatics of complex disease, computational genomics, systems biology, and biomedical data analytics. I came across Dmitry’s work when in February his group used the viral genome of the COVID-19 to reconstruct the 3D structure of its major viral proteins and their interactions with human proteins, in effect creating a structural genomics map of the coronavirus and making this data open and available to researchers everywhere. We talked about the biology of COVID-19, SARS, and viruses in general, and how computational methods can help us understand their structure and function in order to develop antiviral drugs and vaccines.
This conversation is part of the Artificial Intelligence podcast.
Support this podcast by signing up with these sponsors: – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w
EPISODE LINKS: Dmitry’s Website: http://korkinlab.org/ Dmitry’s Twitter: https://twitter.com/dmkorkin
Dmitry’s Paper that we discuss: https://bit.ly/3eKghEM
INFO:
Podcast website: https://lexfridman.com/ai
Apple Podcasts: https://apple.co/2lwqZIr
OUTLINE: 0:00 – Introduction 2:33 – Viruses are terrifying and fascinating 6:02 – How hard is it to engineer a virus? 10:48 – What makes a virus contagious? 29:52 – Figuring out the function of a protein 53:27 – Functional regions of viral proteins 1:19:09 – Biology of a coronavirus treatment 1:34:46 – Is a virus alive? 1:37:05 – Epidemiological modeling 1:55:27 – Russia 2:02:31 – Science bobbleheads 2:06:31 – Meaning of life
CONNECT: – Subscribe to this YouTube channel
– Support on Patreon: https://www.patreon.com/lexfridman
SOURCE

Read Full Post »

Recent Grim COVID-19 Statistics in U.S. and Explanation from Dr. John Campbell: Why We Need to be More Proactive

Reporter: Stephen J. Williams, Ph.D.

In case you have not been following the excellent daily YouTube sessions on COVID-19 by Dr. John Campbell I am posting his latest video on how grim the statistics have become and the importance of using proactive measures (like consistent use of facial masks, proper social distancing) instead of relying on reactive measures (e.g. lockdowns after infection spikes).  In addition, below the video are some notes from his presentation and some links to sites discussed within the video.

 

Notes from the video:

  • approaching 5 million confirmed cases in US however is probably an underestimation
  • 160,00 deaths as of 8/08/2020

From the University of Washington Institute for Health Metrics and Evaluation in Seattle WA

  • 295,000 US COVID-19 related deaths estimated by December 1, 2020
  • however if 95% of people in US consistently and properly wear masks could save 66,000 lives
  • however this will mean a remaining 228,271 deaths which is a depressing statistic
  • Dr. John Campbell agrees with Dr. Christopher Murray, director of the Institute for Health Metrics that “people’s inconsistent use of these measures (face masks, social distancing) is a serious problem”
  • States with increasing transmission like Colorado, Idaho, Kansas, Kentucky, Mississippi, Missouri, Ohio, Oklahoma, Oregon, and Virginia are suggested to have a lockdown when death rate reaches 8 deaths per million population however it seems we should be also focusing on population densities rather than geographic states
  • Dr. Campbell and Dr. Murray stress more proactive measures than reactive ones like lockdowns
  • if mask usage were to increase to 95% usage reimposition to shutdown could be delayed 6 to 8 weeks

 

New IHME COVID-19 Forecasts See Nearly 300,000 Deaths by December 1

SEATTLE (August 6, 2020) – America’s COVID-19 death toll is expected to reach nearly 300,000 by December 1; however, consistent mask-wearing beginning today could save about 70,000 lives, according to new data from the Institute for Health Metrics and Evaluation (IHME) at the University of Washington’s School of Medicine.The US forecast totals 295,011 deaths by December. As of today, when, thus far, 158,000 have died, IHME is projecting approximately 137,000 more deaths. However, starting today, if 95% of the people in the US were to wear masks when leaving their homes, that total number would decrease to 228,271 deaths, a drop of 49%. And more than 66,000 lives would be saved.Masks and other protective measures against transmission of the virus are essential to staying COVID-free, but people’s inconsistent use of those measures is a serious problem, said IHME Director Dr. Christopher Murray.

“We’re seeing a rollercoaster in the United States,” Murray said. “It appears that people are wearing masks and socially distancing more frequently as infections increase, then after a while as infections drop, people let their guard down and stop taking these measures to protect themselves and others – which, of course, leads to more infections. And the potentially deadly cycle starts over again.”

Murray noted that there appear to be fewer transmissions of the virus in Arizona, California, Florida, and Texas, but deaths are rising and will continue to rise for the next week or two. The drop in infections appears to be driven by the combination of local mandates for mask use, bar and restaurant closures, and more responsible behavior by the public.

“The public’s behavior had a direct correlation to the transmission of the virus and, in turn, the numbers of deaths,” Murray said. “Such efforts to act more cautiously and responsibly will be an important aspect of COVID-19 forecasting and the up-and-down patterns in individual states throughout the coming months and into next year.”

Murray said that based on cases, hospitalizations, and deaths, several states are seeing increases in the transmission of COVID-19, including Colorado, Idaho, Kansas, Kentucky, Mississippi, Missouri, Ohio, Oklahoma, Oregon, and Virginia.

“These states may experience increasing cases for several weeks and then may see a response toward more responsible behavior,” Murray said.

In addition, since July 15, several states have added mask mandates. IHME’s statistical analysis suggests that mandates with no penalties increase mask wearing by 8 percentage points. But mandates with penalties increase mask wearing by 15 percentage points.

“These efforts, along with media coverage and public information efforts by state and local health agencies and others, have led to an increase in the US rate of mask wearing by about 5 percentage points since mid-July,” Murray said. Mask-wearing increases have been larger in states with larger epidemics, he said.

IHME’s model assumes that states will reimpose a series of mandates, including non-essential business closures and stay-at-home orders, when the daily death rate reaches 8 per million. This threshold is based on data regarding when states and/or communities imposed mandates in March and April, and implies that many states will have to reimpose mandates.

As a result, the model suggests which states will need to reimpose mandates and when:

  • August – Arizona, Florida, Mississippi, and South Carolina
  • September – Georgia and Texas
  • October – Colorado, Kansas, Louisiana, Missouri, Nevada, North Carolina, and Oregon.
  • November – Alabama, Arkansas, California, Iowa, New Mexico, Oklahoma, Utah, Washington, and Wisconsin.

However, if mask use is increased to 95%, the re-imposition of stricter mandates could be delayed 6 to 8 weeks on average.

Source: http://www.healthdata.org/news-release/new-ihme-covid-19-forecasts-see-nearly-300000-deaths-december-1

 

Read Full Post »

Is SARS-COV2 Hijacking the Complement and Coagulation Systems?

Reporter: Stephen J. Williams, PhD

In a recent Nature Medicine paper “Immune complement and coagulation dysfunction in adverse outcomes of SARS-CoV-2 infection” Ramlall et al. demonstrate, in a retrospective study, that a significant number of patients presenting SARS-CoV2 complications had prior incidences of macular degeneration and coagulation disorders and these previous indications are risk factors for COVID-related complications.

 

Abstract

Understanding the pathophysiology of SARS-CoV-2 infection is critical for therapeutic and public health strategies. Viral–host interactions can guide discovery of disease regulators, and protein structure function analysis points to several immune pathways, including complement and coagulation, as targets of coronaviruses. To determine whether conditions associated with dysregulated complement or coagulation systems impact disease, we performed a retrospective observational study and found that history of macular degeneration (a proxy for complement-activation disorders) and history of coagulation disorders (thrombocytopenia, thrombosis and hemorrhage) are risk factors for SARS-CoV-2-associated morbidity and mortality—effects that are independent of age, sex or history of smoking. Transcriptional profiling of nasopharyngeal swabs demonstrated that in addition to type-I interferon and interleukin-6-dependent inflammatory responses, infection results in robust engagement of the complement and coagulation pathways. Finally, in a candidate-driven genetic association study of severe SARS-CoV-2 disease, we identified putative complement and coagulation-associated loci including missense, eQTL and sQTL variants of critical complement and coagulation regulators. In addition to providing evidence that complement function modulates SARS-CoV-2 infection outcome, the data point to putative transcriptional genetic markers of susceptibility. The results highlight the value of using a multimodal analytical approach to reveal determinants and predictors of immunity, susceptibility and clinical outcome associated with infection.

Introduction

As part of a separate study, the authors mapped over 140 cellular proteins that are structurally mimicked by coronaviruses (CoVs) and identified complement and coagulation pathways as targets of this strategy across all CoV strains4. The complement system is a critical defense against pathogens, including viruses5 and when dysregulated (by germline variants or acquired through age-related effects or excessive tissue damage) can contribute to pathologies mediated by inflammation5,6,7.

“So, virally encoded structural mimics of complement and coagulation factors may contribute to CoV-associated immune-mediated pathology and indicate sensitivities in antiviral defenses.”

 

Methods and Results

  • Between 1 February 2020 and 25 April 2020, 11,116 patients presented to New York-Presbyterian/Columbia University Irving Medical Center with suspected SARS-CoV-2 infection, of which 6,398 tested positive
  • Electronic health records (EHRs) were used to define sex, age and smoking history status as well as histories of macular degeneration, coagulatory disorders (thrombocytopenia, thrombosis and hemorrhage), hypertension, type 2 diabetes (T2D), coronary artery disease (CAD) and obesity (see Methods). A Python algorithm was used to analyze all confounders.
  • identified 88 patients with history of macular degeneration, 4 with complement deficiency disorders and 1,179 with coagulatory disorders).
  • observed a 35% mortality rate among patients that were put on mechanical ventilation and that 31% of deceased patients had been on mechanical respiration.
  • patients with AMD (a proxy for complement activation disorders) and coagulation disorders (thrombocytopenia, thrombosis and hemorrhage) were at significantly increased risk of adverse clinical outcomes (including mechanical respiration and death) following SARS-CoV-2 infection
  • 650 NP swabs from control and SARS-CoV-2-infected patients who presented to Weill-Cornell Medical Center were evaluated by RNA-Seq. Gene set enrichment analysis (GSEA) of Hallmark gene sets found that SARS-CoV-2 infection (as defined by presence of SARS-CoV-2 RNA and stratified into ‘positive’, ‘low’, ‘medium’ or ‘high’ based on viral load; induces genes related to pathways with known immune modulatory functions (Fig. 2a). Moreover, among the most enriched gene sets, SARS-CoV-2 infection induces robust activation of the complement cascade (false discovery rate (FDR) P < 0.001), with increasing enrichment and significance with viral load (FDR P < 0.0001).
  • KEGG Pathway Analysis revealed KEGG_Complement_and_Coagulation_Cascades’, ‘GO_Coagulation’ and ‘Reactome_initial_triggering_of_complement’ to be significantly enriched in expression profiles of SARS-CoV-2-infected samples
  • conducted a candidate-driven study to evaluate whether genetic variation within a 60-Kb window around 102 genes with known roles in regulating complement or coagulation cascades (2,888 genetic variants fulfill this criteria of the 805,426 profiled in the UK Biobank) is associated with poor SARS-CoV-2 clinical outcome
  • identified 11 loci representing seven genes with study-wide significance. A variant of coagulation factor III (F3), variant rs72729504, was found to be associated with increased risk of adverse clinical outcome associated with SARS-CoV-2 infection. The analysis also identified that four variants previously reported to be associated with AMD (rs45574833, rs61821114, rs61821041 and rs12064775)15predispose carriers to hospitalization following SARS-CoV-2 infection

As authors state:

“Among the implications, the data warrant heightened public health awareness for the most vulnerable individuals and further investigation into an existing menu of complement and coagulation targeting therapies that were recently shown to be beneficial in a small cohort of patients with SARS-CoV-2 infection.” 26,27.

 

References

Ramlall, V., Thangaraj, P.M., Meydan, C. et al. Immune complement and coagulation dysfunction in adverse outcomes of SARS-CoV-2 infection. Nat Med (2020). https://doi.org/10.1038/s41591-020-1021-2

 

4.

Lasso, G., Honig, B. & Shapira, S. D. A sweep of earth’s virome reveals host-guided viral protein structural mimicry; with implications for human disease. Preprint at bioRxiv https://doi.org/10.1101/2020.06.18.159467 (2020).

 

SUMMARY

Viruses deploy an array of genetically encoded strategies to coopt host machinery and support viral replicative cycles. Molecular mimicry, manifested by structural similarity between viral and endogenous host proteins, allow viruses to harness or disrupt cellular functions including nucleic acid metabolism and modulation of immune responses. Here, we use protein structure similarity to scan for virally encoded structure mimics across thousands of catalogued viruses and hosts spanning broad ecological niches and taxonomic range, including bacteria, plants and fungi, invertebrates and vertebrates. Our survey identified over 6,000,000 instances of structural mimicry, the vast majority of which (>70%) cannot be discerned through protein sequence. The results point to molecular mimicry as a pervasive strategy employed by viruses and indicate that the protein structure space used by a given virus is dictated by the host proteome. Interrogation of proteins mimicked by human-infecting viruses points to broad diversification of cellular pathways targeted via structural mimicry, identifies biological processes that may underly autoimmune disorders, and reveals virally encoded mimics that may be leveraged to engineer synthetic metabolic circuits or may serve as targets for therapeutics. Moreover, the manner and degree to which viruses exploit molecular mimicry varies by genome size and nucleic acid type, with ssRNA viruses circumventing limitations of their small genomes by mimicking human proteins to a greater extent than their large dsDNA counterparts. Finally, we identified over 140 cellular proteins that are mimicked by CoV, providing clues about cellular processes driving the pathogenesis of the ongoing COVID-19 pandemic.

 

26.

Risitano, A. M. Complement as a target in COVID-19?. Nat. Rev. Immunol. 20, 343–344 (2020).

 

27.

Mastaglio, S. et al. The first case of COVID-19 treated with the complement C3 inhibitor AMY-101. Clin. Immunol. 215, 108450 (2020).

 

28.

Polubriaginof, F. C. G. et al. Challenges with quality of race and ethnicity data in observational databases. J. Am. Med. Inf. Assoc. 26, 730–736 (2019).

 

Read Full Post »

via Key Immune System Genes Identified to Explain High COVID Deaths and Spread in Northern Italy Versus Fewer Cases and Deaths in the South

Read Full Post »

Older Posts »

%d bloggers like this: