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Science’s COVID-19 reporting is supported by the Pulitzer Center and the Heising-Simons Foundation.
Researchers have used CRISPR gene-editing technology to come up with a test that detects the pandemic coronavirus in just 5 minutes. The diagnostic doesn’t require expensive lab equipment to run and could potentially be deployed at doctor’s offices, schools, and office buildings.
“It looks like they have a really rock-solid test,” says Max Wilson, a molecular biologist at the University of California (UC), Santa Barbara. “It’s really quite elegant.”
CRISPR diagnostics are just one way researchers are trying to speed coronavirus testing. The new test is the fastest CRISPR-based diagnostic yet. In May, for example, two teams reported creating CRISPR-based coronavirus tests that could detect the virus in about an hour, much faster than the 24 hours needed for conventional coronavirus diagnostic tests.CRISPR tests work by identifying a sequence of RNA—about 20 RNA bases long—that is unique to SARS-CoV-2. They do so by creating a “guide” RNA that is complementary to the target RNA sequence and, thus, will bind to it in solution. When the guide binds to its target, the CRISPR tool’s Cas13 “scissors” enzyme turns on and cuts apart any nearby single-stranded RNA. These cuts release a separately introduced fluorescent particle in the test solution. When the sample is then hit with a burst of laser light, the released fluorescent particles light up, signaling the presence of the virus. These initial CRISPR tests, however, required researchers to first amplify any potential viral RNA before running it through the diagnostic to increase their odds of spotting a signal. That added complexity, cost, and time, and put a strain on scarce chemical reagents. Now, researchers led by Jennifer Doudna, who won a share of this year’s Nobel Prize in Chemistry yesterday for her co-discovery of CRISPR, report creating a novel CRISPR diagnostic that doesn’t amplify coronavirus RNA. Instead, Doudna and her colleagues spent months testing hundreds of guide RNAs to find multiple guides that work in tandem to increase the sensitivity of the test.
That’s still not as good as the conventional coronavirus diagnostic setup, which uses expensive lab-based machines to track the virus down to one virus per microliter, says Melanie Ott, a virologist at UC San Francisco who helped lead the project with Doudna. However, she says, the new setup was able to accurately identify a batch of five positive clinical samples with perfect accuracy in just 5 minutes per test, whereas the standard test can take 1 day or more to return results.
The new test has another key advantage, Wilson says: quantifying a sample’s amount of virus. When standard coronavirus tests amplify the virus’ genetic material in order to detect it, this changes the amount of genetic material present—and thus wipes out any chance of precisely quantifying just how much virus is in the sample.
By contrast, Ott’s and Doudna’s team found that the strength of the fluorescent signal was proportional to the amount of virus in their sample. That revealed not just whether a sample was positive, but also how much virus a patient had. That information can help doctors tailor treatment decisions to each patient’s condition, Wilson says.
Doudna and Ott say they and their colleagues are now working to validate their test setup and are looking into how to commercialize it.
Most significant article published in the Society of Evolution, Medicine and Public Health won Prize: polygenic scores, polygenic adaptation, and human phenotypic differences
Reporter: Aviva Lev-Ari, PhD, RN
UPDATED on 8/30/2020
Analysis of polygenic risk score usage and performance in diverse human populations
A historical tendency to use European ancestry samples hinders medical genetics research, including the use of polygenic scores, which are individual-level metrics of genetic risk. We analyze the first decade of polygenic scoring studies (2008–2017, inclusive), and find that 67% of studies included exclusively European ancestry participants and another 19% included only East Asian ancestry participants. Only 3.8% of studies were among cohorts of African, Hispanic, or Indigenous peoples. We find that predictive performance of European ancestry-derived polygenic scores is lower in non-European ancestry samples (e.g. African ancestry samples: t = −5.97, df = 24, p = 3.7 × 10−6), and we demonstrate the effects of methodological choices in polygenic score distributions for worldwide populations. These findings highlight the need for improved treatment of linkage disequilibrium and variant frequencies when applying polygenic scoring to cohorts of non-European ancestry, and bolster the rationale for large-scale GWAS in diverse human populations.
You might be interested in the paper “interpreting polygenic scores, polygenic adaptation, and human phenotypic differences” by N. Rosenberg, M. Edge, J. Pritchard, and M. Feldman, published in Evolution, Medicine and Public Health (2019). Rosenberg and Pritchard are my former PhD students, both full professors at Stanford, and M.Edge is a student of Rosenberg.
It is my pleasure in my role as President of the International Society for Evolution, Medicine and Public Health to inform you that your 2019 EMPH article, “Interpreting polygenic scores, polygenic adaptation, and human phenotypic differences” has won The George C. Williams Prize which is awarded each year to the first author of the most significant article published in the Society’s flagship journal, Evolution, Medicine and Public Health.
The Prize recognizes the contributions of George C. Williams to evolutionary medicine and aims to encourage and highlight important research in this growing field. It includes $5,000 and an invitation to present at the online lecture series, Club EvMed. The Prize is made possible by donations from Doris Williams, Randolph Nesse, and other supporters of EMPH.
Recent analyses of polygenic scores have opened new discussions concerning the genetic basis and evolutionary significance of differences among populations in distributions of phenotypes. Here, we highlight limitations in research on polygenic scores, polygenic adaptation and population differences. We show how genetic contributions to traits, as estimated by polygenic scores, combine with environmental contributions so that differences among populations in trait distributions need not reflect corresponding differences in genetic propensity. Under a null model in which phenotypes are selectively neutral, genetic propensity differences contributing to phenotypic differences among populations are predicted to be small. We illustrate this null hypothesis in relation to health disparities between African Americans and European Americans, discussing alternative hypotheses with selective and environmental effects. Close attention to the limitations of research on polygenic phenomena is important for the interpretation of their relationship to human population differences.
We are currently witnessing a surge in public interest in the intersection of evolutionary genetics with such topics as cognitive phenotypes, disease, race and heritability of human traits [1–7]. This attention emerges partly from recent advances in genomics, including the introduction of polygenic scores—the aggregation of estimated effects of genome-wide variants to predict the contribution of a person’s genome to a phenotypic trait [8–10]—and a new focus on polygenic adaptations, namely adaptations that have occurred by natural selection on traits influenced by many genes [11–13].
Theories involving natural selection have long been applied in the scientific literature to explain mean phenotypic differences among human populations [14–16]. Although new tools for statistical analysis of polygenic variation and polygenic adaptation provide opportunities for studying human evolution and the genetic basis of traits, they also generate potential for misinterpretation. In the past, public attention to research on human variation and its possible evolutionary basis has often been accompanied by claims that are not justified by the research findings [17]. Recognizing pitfalls in the interpretation of new research on human variation is therefore important for advancing discussions on associated sensitive and controversial topics.
The contribution of polygenic score distributions to phenotype distributions. Two populations are considered, populations 1 (red) and 2 (blue). Each population has a distribution of genetic propensities, which are treated as accurately estimated in the form of polygenic scores (left). The genetic propensity distribution and an environment distribution sum to produce a phenotype distribution (right). All plots have the same numerical scale. (A) Environmental differences amplify an underlying difference in genetic propensities. (B) Populations differ in their phenotypes despite having no differences in genetic propensity distributions. (C) Environmental differences obscure a difference in genetic propensities opposite in direction to the difference in phenotype means. (D) Similarity in phenotype distributions is achieved despite a difference in genetic propensity distributions by an intervention that reduces the environmental contribution for individuals with polygenic scores above a threshold. (E) Within populations, heritability is high, so that genetic variation explains the majority of phenotypic variation; however, the difference between populations is explained by an environmental difference. Panels (A–C and E) present independent normal distributions for genotype and environment that sum to produce normal distributions for phenotype. In (D), (genotype, environment) pairs are simulated from independent normal distributions and a negative constant—reflecting the effect of a medication or other intervention—is added to environmental contributions associated with simulated genotypic values that exceed a threshold
Summary
These limitations illustrate that much of the complexity embedded in use of polygenic scores—the effects of the environment on phenotype and its relationship to genotype, the proportion of variance explained, and the peculiarities of the underlying GWAS data that have been used to estimate effect sizes—is obscured by the apparent simplicity of the single values computed for each individual for each phenotype. Consequently, in using polygenic scores to describe genomic contributions to traits, particularly traits for which the total contribution of genetic variation to trait variation, as measured by heritability, is low—but even if it is high (Fig. 1E)—a difference in polygenic scores between populations provides little information about potential genetic bases for trait differences between those populations.
Unlike heritability, which ranges from 0 to 1 and therefore makes it obvious that the remaining contribution to phenotypic variation is summarized by its difference from 1, the limited explanatory role of genetics is not embedded in the nature of the polygenic scores themselves. Although polygenic scores encode knowledge about specific genetic correlates of trait variation, they do not change the conceptual framework for genetic and environmental contribution to population differences. Attributions of phenotypic differences among populations to genetic differences should therefore be treated with as much caution as similar genetic attributions from heritability in the pre-genomic era.
National Public Radio interview with Dr. Anthony Fauci on his optimism on a COVID-19 vaccine by early 2021
Reporter: Stephen J. Williams, PhD
Below I am giving a link to an important interview by NPR’s Judy Woodruff with Dr. Anthony Fauci on his thoughts regarding the recent spikes in cases, the potential for a COVID-19 vaccine by next year, and promising therapeutics in the pipeline. The interview link is given below however I will summarize a few of the highlights of the interview.
Some notes on the interview
Judy Woodruff began her report with some up to date news regarding the recent spike and that Miami Florida has just ordered the additional use of facemasks. She asked Dr. Anthony Fauci, head of the National Institute of Allergy and Infectious Diseases (NIAD), about if the measures currently in use are enough to bring this spike down. Dr. Fauci said that we need to reboot our efforts, mainly because people are not doing three things which could have prevented this spike mainly
We have to use the tests we have out there efficiently and effectively And we have to get them out to the right people who can do the proper identification, isolation, and do proper contract tracing and need to test more widely in a surveillance way to get a feel of the extent and penetrance of this community spread. there needs to be support and money for these testing labs
We have a problem and we need to admit and own it but we need to do the things we know are effective to turn this thing around.
On Vaccines
“May be later this year”
His response to Merck’s CEO Ken Frazer who said officials are giving false hop if they say ‘end of year’ but Dr. Fauci disagrees. He says a year end goal is not outlandish.
What we have been doing is putting certain things in line with each other in an unprecedented way.
Dr. Fauci went on to say that, in the past yes, it took a long time, even years to develop a vaccine but now they have been able to go from sequence of virus to a vaccine development program in days, which is unheard of. Sixty two days later we have gone into phase 1 trials. the speed at which this is occurring is so much faster. He says that generally it would take a couple of years to get a neutralizing antibody but we are already there. Another candidate will be undergoing phase 3 trials by end of this month (July 2020).
He is “cautiously optimistic” that we will have one or more vaccines to give to patients by end of year because given the amount of cases it will be able to get a handle on safety and efficacy by late fall.
Now he says the game changer is that the government is working with companies to ramp up the production of doses of the candidate vaccines so when we find which one works we will have ample doses on hand. He is worried about the anti vaccine movement derailing vaccine testing and vaccinations but says if we keep on informing the public we can combat this.
Going back to school
Dr. Fauci is concerned for the safety of the vulnerable in schools, including students and staff. He wants the US to get down to a reasonable baseline of cases but in the US that baseline after the first wave was still significantly higher than in most countries, where the baseline was more like tens of cases not hundreds of cases.
For more information on COVID-19 Please go to our Coronavirus Portal at
The Wide Variability in Reported COVID-19 Epidemiologic Data May Suggest That Personalized Omic Testing May Be Needed to Identify At-Risk Populations
Curator: Stephen J. Williams, PhD
I constantly check the Youtube uploads from Dr. John Campbell, who is a wonderful immunologist and gives daily reports on new findings on COVID-19 from the scientific literature. His reporting is extremely insightful and easily understandable. This is quite a feat as it seems the scientific field has been inundated with a plethora of papers, mostly reported clinical data from small retrospective studies, and many which are being put on preprint servers, and not peer reviewed.
It has become a challenge for many scientists, already inundated with expanding peer reviewed literature in their own fields, as well as the many requests to review papers, to keep up with all these COVID related literature. Especially when it is up to the reader to do their own detailed peer review. So many thanks to people like Dr. Campbell who is an expert in his field for doing this.
However the other day he had posted a video which I found a bit disturbing, as a central theme of the video was that many expert committee could not find any reliable epidemiologic study concerning transmission or even incidence of the disease. In all studies, as Dr. Campell alluded to, there is such a tremendous variability in the reported statistics, whether one is looking at percentage of people testing positive who are symptomatic, the percentage of asymptomatic which may be carriers, the transmission of the disease, and even the percentage of people who recover.
With all the studies being done it would appear that, even if a careful meta analysis were done using all available studies, and assuming their validity before peer review, that there would be a tighter consensus on some of these metrics of disease spread, incidence and prevalence.
Below is the video from Dr. Campbell and the topic is on percentage of asymptomatic carriers of the COVID-19 virus. This was posted last week but later in this post there will be updated information and views by the WHO on this matter as well as other literature (which still shows to my point that this wide variability in reported data may be adding to the policy confusion with respect to asymptomatic versus symptomatic people and why genetic testing might be needed to further discriminate these cohorts of people.
“There is not a single reliable study to determine the number of asymptomatic infections”
And this is very troubling as this means there is no reliable testing resulting in any meaningful data.
As Dr. Campell says
” This is not good enough. There needs to be some sort of coordinated research program it seems all ad hoc”
A few other notes from post and Oxford Center for Evidence Based Medicine:
Symptom based screening will miss a lot of asymptomatic and presymptomatic cases
Some asymptomatic cases will become symptomatic over next week (these people were technically presymptomatic but do we know the %?)
We need a population based antibody screening program
An Italian study of all 3,000 people in city of Vo’Euganeo revealed that 50-75% of those who tested positive were asymptomatic and authors concluded that asymptomatic represents “a formidable source of infection”; Dr. Campbell feels this was a reliable study
Another study from a Washington state nursing facility showed while 56% of positive cases were asymptomatic, 75% of these asymptomatic developed symptoms within a week. Symptom based screening missed half of cases.
Other studies do not follow-up on the positive cases to determine in presymptomatic
It also appears discrepancies between data from different agencies (like CDC, WHO) on who is shedding virus as different tests used (PCR vs antibody)
Recent Studies Conflict Concerning Asymptomatic, Presymtomatic and Viral Transmission
‘We don’t actually have that answer yet’: WHO clarifies comments on asymptomatic spread of Covid-19
From StatNews
A top World Health Organization official clarified on Tuesday that scientists have not determined yet how frequently people with asymptomatic cases of Covid-19 pass the disease on to others, a day after suggesting that such spread is “very rare.”
The clarification comes after the WHO’s original comments incited strong pushback from outside public health experts, who suggested the agency had erred, or at least miscommunicated, when it said people who didn’t show symptoms were unlikely to spread the virus.
Maria Van Kerkhove, the WHO’s technical lead on the Covid-19 pandemic, made it very clear Tuesday that the actual rates of asymptomatic transmission aren’t yet known.
Some of the confusion boiled down to the details of what an asymptomatic infection actually is, and the different ways the term is used. While some cases of Covid-19 are fully asymptomatic, sometimes the word is also used to describe people who haven’t started showing symptoms yet, when they are presymptomatic. Research has shown that people become infectious before they start feeling sick, during that presymptomatic period.
At one of the WHO’s thrice-weekly press briefings Monday, Van Kerkhove noted that when health officials review cases that are initially reported to be asymptomatic, “we find out that many have really mild disease.” There are some infected people who are “truly asymptomatic,” she said, but countries that are doing detailed contact tracing are “not finding secondary transmission onward” from those cases. “It’s very rare,” she said.
Therefore the problems have been in coordinating the testing results, which types of tests conducted, and the symptomology results. As Dr. Campbell previously stated it appears more ‘ad hoc’ than coordinated research program. In addition, defining the presymptomatic and measuring this group have been challenging.
However, an alternative explanation to the wide variability in the data may be we need to redefine the cohorts of patients we are evaluating and the retrospective data we are collecting. It is feasible that sub groups, potentially defined by genetic background may be identified and data re-evaluated based on personalized omic data, in essence creating new cohorts based on biomarker data.
From a Perspective in The Lancet about a worldwide proteomic effort (COVID-19 MS Coalition) to discover biomarkers related to COVID19 infection risk, by identifying COVID-related antigens.
The COVID-19 MS Coalition is a collective mass spectrometry effort that will provide molecular level information on SARS-CoV-2 in the human host and reveal pathophysiological and structural information to treat and minimise COVID-19 infection. Collaboration with colleagues at pace involves sharing of optimised methods for sample collection and data generation, processing and formatting for maximal information gain. Open datasets will enable ready access to this valuable information by the computational community to help understand antigen response mechanisms, inform vaccine development, and enable antiviral drug design. As countries across the world increase widespread testing to confirm SARS-CoV-2 exposure and assess immunity, mass spectrometry has a significant role in fighting the disease. Through collaborative actions, and the collective efforts of the COVID-19 MS Coalition, a molecular level quantitative understanding of SARS-CoV-2 and its effect will benefit all.
In an ACS Perspective below, Morteza Mahmoudi suggests a few possible nanobased technologies (i.e., protein corona sensor array and magnetic levitation) that could discriminate COVID-19-infected people at high risk of death while still in the early stages of infection.
Emerging Biomolecular Testing to Assess the Risk of Mortality from COVID-19 Infection
Lancet Oncol. 2020 Mar; 21(3): 335–337. Published online 2020 Feb 14. doi: 10.1016/S1470-2045(20)30096-6
PMCID: PMC7159000
The National Clinical Research Center for Respiratory Disease and the National Health Commission of the People’s Republic of China collaborated to establish a prospective cohort to monitor COVID-19 cases in China. As on Jan31, 20202007 cases have been collected and analyzed with confirmed COVID-19 infection in these cohorts.
Results: 18 or 1% of COVID-19 cases had a history of cancer (the overall average cancer incidence in the overall China population is 0.29%) {2015 statistics}. It appeared that cancer patients had an observable higher risk of COVID related complications upon hospitalization. However, this was a higher risk compared with the general population. There was no comparison between cancer patients not diagnosed with COVID-19 and an assessment of their risk of infection. Interestingly those who were also cancer survivors showed an increased incidence of COVID related severe complications compared to the no cancer group.
Although this study could have compared the risk within a cancer group, the authors still felt the results warranted precautions when dealing with cancer patients and issued recommendations including:
Postponing of adjuvant chemotherapy or elective surgery for stable cancer should be considered
Stronger personal protection for cancer patients
More intensive surveillance or treatment should be considered when patients with cancer are infected, especially in older patients
Further studies will need to address the risk added by specific types of chemotherapy: cytolytic versus immunotherapy e.g.
Preparedness for COVID-19 in the oncology community in Africa
Africa has a heterogeneity of cultures, economies and disease patterns however fortunately it is one of the last countries to be hit by the COVID-19 pandemic, which allows some time for preparation by the African nations. The authors note that with Africa’s previous experiences with epidemics, namely ebola and cholera, Africa should be prepared for this pandemic.
However, as a result of poor economic discipline, weak health systems, and poor health-seeking behaviors across the continent, outcomes could be dismal. Poverty, low health literacy rates, and cultural practices that negatively affect cancer outcomes will result in poor assimilation of COVID-19 containment strategies in Africa.”
In general African oncologists are following COVID-19 guidelines from other high-income countries, but as this writer acknowledges in previous posts, there was a significant lag from first cases in the United States to the concrete formulation of guidelines for both oncologists and patients with regard to this pandemic. African oncologist are delaying the start of adjuvant therapies and switching more to oral therapies and rethink palliative care.
However the authors still have many more questions than answers, however even among countries that have dealt with this pandemic before Africa (like Italy and US), oncologists across the globe still have not been able to answer questions like: what if my patient develops a fever, what do I do during a period of neutropenia, to their satisfaction or the satisfaction of the patient. These are questions even oncologists who are dealing in COVID hotspots are still trying to answer including what constitutes a necessary surgical procedure? As I have highlighted in recent posts, oncologists in New York have all but shut down all surgical procedures and relying on liquid biopsies taken in the at-home setting. But does Africa have this capability of access to at home liquid biopsy procedures?
In addition, as I had just highlighted in a recent posting, there exists extreme cancer health disparities across the African continent, as well as the COVID responses. In West Africa, COVID-19 protocols are defined at individual institutions. This is more like the American system where even NCI designated centers were left to fashion some of their own guidelines initially, although individual oncologists had banded together to do impromptu meetings to discuss best practices. However this is fine for big institutions, but as in the US, there is a large rural population on the African continent with geographical barriers to these big centers. Elective procedures have been cancelled and small number of patients are seen by day. This remote strategy actually may be well suited for African versus more developed nations, as highlighted in a post I did about mobile health app use in oncology, as this telemedicine strategy is rather new among US oncologists (reference my posts with the Town Hall meetings).
The situation is more complicated in South Africa where they are dealing with an HIV epidemic, where about 8 million are infected with HIV. Oncology services here are still expecting to run at full capacity as the local hospitals deal with the first signs of the COVID outbreak. In Sudan, despite low COVID numbers, cancer centers have developed contingency plans. and are deferring new referrals except for emergency cases. Training sessions for staff have been developed.
For more articles in this online open access journal on Cancer and COVID-19 please see our
We investigated SARS-CoV-2 potential tropism by surveying expression of viral entry-associated genes in single-cell RNA-sequencing data from multiple tissues from healthy human donors. We co-detected these transcripts in specific respiratory, corneal and intestinal epithelial cells, potentially explaining the high efficiency of SARS-CoV-2 transmission. These genes are co-expressed in nasal epithelial cells with genes involved in innate immunity, highlighting the cells’ potential role in initial viral infection, spread and clearance. The study offers a useful resource for further lines of inquiry with valuable clinical samples from COVID-19 patients and we provide our data in a comprehensive, open and user-friendly fashion at www.covid19cellatlas.org.
To further characterize specific epithelial cell types expressing ACE2, we evaluated ACE2 expression within the lung and airway epithelium. We found that, despite a low level of expression overall, ACE2 was expressed in multiple epithelial cell types across the airway, as well as in alveolar epithelial type II cells in the parenchyma, consistently with previous studies9,10,11. Notably, nasal epithelial cells, including two previously described clusters of goblet cells and one cluster of ciliated cells, show the highest expression among all investigated cells in the respiratory tree (Fig. 1b). We confirmed enriched ACE2 expression in nasal epithelial cells in an independent scRNA-seq study that includes nasal brushings and biopsies. The results were consistent; we found the highest expression of ACE2 in nasal secretory cells (equivalent to the two goblet cell clusters in the previous dataset) and ciliated cells (Fig. 1b).
In addition, scRNA-seq data from an in vitro epithelial regeneration system from nasal epithelial cells corroborated the expression of ACE2 in goblet/secretory cells and ciliated cells in air–liquid interface cultures (Extended Data Fig. 1). Notably, the differentiating cells in the air–liquid interface acquire progressively more ACE2 (Extended Data Fig. 1). The results also suggest that this in vitro culture system may be biologically relevant for the study of SARS-CoV-2 pathogenesis.
Coronavirus Entry Genes Highly Expressed in Two Nasal Epithelial Cell Types
This story has been updated to include information on a related study appearing in Cell.
NEW YORK – Two types of cells inside the nose express high levels of the genes encoding proteins the SARS-CoV-2 uses to enter cells, suggesting they are the likely entry points for the virus.
SARS-CoV-2, the virus that causes COVID-19, uses its spike protein to bind to cellular receptors in the human body. The virus relies on the ACE2 receptor protein and the TMPRSS2 protease to enter cells, but which cells are initially infected has been unclear.
An international team of researchers used single-cell RNA sequencing datasets put together by the Human Cell Atlas consortium to search for cell types that express both the ACE2 and TMPRSS2 genes. As they reported in Nature Medicine Thursday, they found a number of cells in different organs express the genes encoding these proteins, but they homed in on cells of the respiratory system, especially goblet cells and ciliated cells in the nose.
“Mucus-producing goblet cells and ciliated cells in the nose had the highest levels of both these [genes], of all cells in the airways,” first author Waradon Sungnak from the Wellcome Sanger Institute said in a statement. “This makes these cells the most likely initial infection route for the virus.”
Using the Human Cell Atlas dataset, Sungnak and his colleagues analyzed ACE2 and TMPRSS2 expression in a range of tissues, including not only respiratory tissue — previous analyses using immunohistochemistry had detected both ACE2 and TMPRSS2 in the nasal and bronchial epithelium — but also tissue from the eyes, digestive tract, muscle, and more.
ACE2 gene expression was generally low across the datasets analyzed, while TMPRSS2 was more broadly expressed, the researchers found. This suggested that ACE2 expression might be the limiting factor for viral entry in initial infections.
However, ACE2 was expressed in a number of epithelial cell types of respiratory tissues, and its expression was particularly high among goblet cells and ciliated cells of the nose. The researchers confirmed this finding using data from two other scRNA-seq studies.
Other genes often co-expressed alongside ACE2 in the respiratory system included ones involved in carbohydrate metabolism — possibly due to their role in goblet cell mucin synthesis — and those involved in innate and antiviral immune functions.
The ACE2 and TMPRSS2 genes were also expressed outside of the respiratory system, including by cells of the cornea and the lining of the intestine, which the researchers noted is in line with some clinical reports suggesting fecal shedding of the virus.
Where these viral entry receptor genes are expressed in the respiratory system could influence how transmissible a virus is. The researchers compared the tissue expression patterns of these viral receptor genes to those of receptor genes used by other coronaviruses and influenza viruses. The receptors used by highly infectious viruses like influenza were expressed more in the upper airway, while receptors for less infectious viruses like MERSCoV were expressed in the lower airway. This indicated to the researchers that the spatial distribution of the viral receptors may influence how transmissible a virus is.
“This is the first time these particular cells in the nose have been associated with COVID-19,” study co-author Martijn Nawijn from the University Medical Center Groningen and the HCA Lung Biological Network said in a statement. “The location of these cells on the surface of the inside of the nose make them highly accessible to the virus, and also may assist with transmission to other people.”
Another study that appeared as a preprint at Cell also used single-cell RNA-sequencing datasets from humans, nonhuman primates, and mice to examine where cells expressing both the ACE2 and TMPRSS2 genes are located. Those researchers, led by the Broad Institute’s Jose Ordovas-Montanes, found both genes were expressed among type II pneumocytes and ileal absorptive enterocytes as well as among nasal goblet secretory cells.
Sungnak, W., Huang, N., Bécavin, C. et al. SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes. Nat Med (2020). https://doi.org/10.1038/s41591-020-0868-6
AAAS Science Podcast: Why some diseases are seasonal and some are not: Coronaviruses and more
Reporter: Stephen J. Williams, PhD
The following podcast from the American Association for Advancement of Science (AAAS) discusses the seasonality of some viruses while other viruses are able to manifest themselves in different seasons over the globe.
The coronavirus pandemic has affected almost every country in every continent however, after months of the novel advent of novel COVID-19 cases, it has become apparent that the varied clinical responses in this epidemic (and outcomes) have laid bare some of the strong and weak aspects in, both our worldwide capabilities to respond to infectious outbreaks in a global coordinated response and in individual countries’ response to their localized epidemics.
Some nations, like Israel, have initiated a coordinated government-private-health system wide action plan and have shown success in limiting both new cases and COVID-19 related deaths. After the initial Wuhan China outbreak, China closed borders and the government initiated health related procedures including the building of new hospitals. As of writing today, Wuhan has experienced no new cases of COVID-19 for two straight days.
However, the response in the US has been perplexing and has highlighted some glaring problems that have been augmented in this crisis, in the view of this writer. In my view, which has been formulated after social discussion with members in the field ,these issues can be centered on three major areas of deficiencies in the United States that have hindered a rapid and successful response to this current crisis and potential future crises of this nature.
The mistrust or misunderstanding of science in the United States
Lack of communication and connection between patients and those involved in the healthcare industry
Socio-geographical inequalities within the US healthcare system
1. The mistrust or misunderstanding of science in the United States
For the past decade, anyone involved in science, whether directly as active bench scientists, regulatory scientists, scientists involved in science and health policy, or environmental scientists can attest to the constant pressure to not only defend their profession but also to defend the entire scientific process and community from an onslaught of misinformation, mistrust and anxiety toward the field of science. This can be seen in many of the editorials in scientific publications including the journal Science and Scientific American (as shown below)
Boston rally coincides with annual American Association for the Advancement of Science (AAAS) conference and is a precursor to the March for Science in Washington, D.C.
Responding to the troubling suppression of science under the Trump administration, thousands of scientists, allies, and frontline communities are holding a rally in Boston’s Copley Square on Sunday.
“Science serves the common good,” reads the call to action. “It protects the health of our communities, the safety of our families, the education of our children, the foundation of our economy and jobs, and the future we all want to live in and preserve for coming generations.”
It continues:
But it’s under attack—both science itself, and the unalienable rights that scientists help uphold and protect.
From the muzzling of scientists and government agencies, to the immigration ban, the deletion of scientific data, and the de-funding of public science, the erosion of our institutions of science is a dangerous direction for our country. Real people and communities bear the brunt of these actions.
The rally was planned to coincide with the annual American Association for the Advancement of Science (AAAS) conference, which draws thousands of science professionals, and is a precursor to the March for Science in Washington, D.C. and in cities around the world on April 22.
However, some feel that scientists are being too sensitive and that science policy and science-based decision making may not be under that much of a threat in this country. Yet even as some people think that there is no actual war on science and on scientists they realize that the public is not engaged in science and may not be sympathetic to the scientific process or trust scientists’ opinions.
Certainly, opponents of genetically modified crops, vaccinations that are required for children and climate science have become louder and more organized in recent times. But opponents typically live in separate camps and protest single issues, not science as a whole, said science historian and philosopher Roberta Millstein of the University of California, Davis. She spoke at a standing-room only panel session at the American Association for the Advancement of Science’s annual meeting, held in Washington, D.C. All the speakers advocated for a scientifically informed citizenry and public policy, and most discouraged broadly applied battle-themed rhetoric.
In general, it appears to be a major misunderstanding by the public of the scientific process, and principles of scientific discovery, which may be the fault of miscommunication by scientists or agendas which have the goals of subverting or misdirecting public policy decisions from scientific discourse and investigation.
This can lead to an information vacuum, which, in this age of rapid social media communication,
can quickly perpetuate misinformation.
This perpetuation of misinformation was very evident in a Twitter feed discussion with Dr. Eric Topol, M.D. (cardiologist and Founder and Director of the Scripps Research Translational Institute) on the US President’s tweet on the use of the antimalarial drug hydroxychloroquine based on President Trump referencing a single study in the International Journal of Antimicrobial Agents. The Twitter thread became a sort of “scientific journal club” with input from international scientists discussing and critiquing the results in the paper.
Please note that when we scientists CRITIQUE a paper it does not mean CRITICIZE it. A critique is merely an in depth analysis of the results and conclusions with an open discussion on the paper. This is part of the normal peer review process.
Below is the original Tweet by Dr. Eric Topol as well as the ensuing tweet thread
I reviewed the cited paperhttps://t.co/E4Iw7GpVh6 an open-label, non=randomized study The endpoint was viral PCR (mostly + or -, many ND) by nasopharyngeal swab. 6 of the 36 people were asymptomatic. 6 with pneumonia (LRTI) 6 people received "H + A" pic.twitter.com/KBjR1QcZRV
Eric – a huge issue here is they only report data on 20 of the 26 patients, and of the 6 – all deteriorated! Six hydroxychloroquine-treated patients were lost in follow-up: they worsened and weee sent to the ICU! They need to do last observation carried forward for those.
OMG, do you realize none of the patients in the treatment arm were definitive positives to start with? They were all in the "gray zone". JFC, this study was worse than I thought when I skimmed it the first time!
Within the tweet thread it was discussed some of the limitations or study design flaws of the referenced paper leading the scientists in this impromptu discussion that the study could not reasonably conclude that hydroxychloroquine was not a reliable therapeutic for this coronavirus strain.
The lesson:The public has to realizeCRITIQUE does not mean CRITICISM.
Scientific discourse has to occur to allow for the proper critique of results. When this is allowed science becomes better, more robust, and we protect ourselves from maybe heading down an incorrect path, which may have major impacts on a clinical outcome, in this case.
2. Lack of communication and connection between patients and those involved in the healthcare industry
In normal times, it is imperative for the patient-physician relationship to be intact in order for the physician to be able to communicate proper information to their patient during and after therapy/care. In these critical times, this relationship and good communication skills becomes even more important.
Recently, I have had multiple communications, either through Twitter, Facebook, and other social media outlets with cancer patients, cancer advocacy groups, and cancer survivorship forums concerning their risks of getting infected with the coronavirus and how they should handle various aspects of their therapy, whether they were currently undergoing therapy or just about to start chemotherapy. This made me realize that there were a huge subset of patients who were not receiving all the information and support they needed; namely patients who are immunocompromised.
These are patients represent
cancer patient undergoing/or about to start chemotherapy
Patients taking immunosuppressive drugs: organ transplant recipients, patients with autoimmune diseases, multiple sclerosis patients
Patients with immunodeficiency disorders
These concerns prompted me to write a posting curating the guidance from National Cancer Institute (NCI) designated cancer centers to cancer patients concerning their risk to COVID19 (which can be found here).
Surprisingly, there were only 14 of the 51 US NCI Cancer Centers which had posted guidance (either there own or from organizations like NCI or the National Cancer Coalition Network (NCCN). Most of the guidance to patients had stemmed from a paper written by Dr. Markham of the Fred Hutchinson Cancer Center in Seattle Washington, the first major US city which was impacted by COVID19.
Also I was surprised at the reactions to this posting, with patients and oncologists enthusiastic to discuss concerns around the coronavirus problem. This led to having additional contact with patients and oncologists who, as I was surprised, are not having these conversations with each other or are totally confused on courses of action during this pandemic. There was a true need for each party, both patients/caregivers and physicians/oncologists to be able to communicate with each other and disseminate good information.
Last night there was a Tweet conversation on Twitter #OTChat sponsored by @OncologyTimes. A few tweets are included below
The Lesson: Rapid Communication of Vital Information in times of stress is crucial in maintaining a good patient/physician relationship and preventing Misinformation.
3. Socio-geographical Inequalities in the US Healthcare System
It has become very clear that the US healthcare system is fractioned and multiple inequalities (based on race, sex, geography, socio-economic status, age) exist across the whole healthcare system. These inequalities are exacerbated in times of stress, especially when access to care is limited.
Some of the passengers had to be extricated from the wrecked cars. Many of the passengers and local residents helped first responders during the rescue operation. Five local hospitals treated the injured. The derailment disrupted train service for several days.
What was not reported was the difficulties that first responders, namely paramedics had in finding an emergency room capable of taking on the massive load of patients. In the years prior to this accident, several hospitals, due to monetary reasons, had to close their emergency rooms or reduce them in size. In addition only two in Philadelphia were capable of accepting gun shot victims (Temple University Hospital was the closest to the derailment but one of the emergency rooms which would accept gun shot victims. This was important as Temple University ER, being in North Philadelphia, is usually very busy on any given night. The stress to the local health system revealed how one disaster could easily overburden many hospitals.
Over the past decade many hospitals, especially rural hospitals, have been shuttered or consolidated into bigger health systems. The graphic below shows this
Note the huge swath of hospital closures in the midwest, especially in rural areas. This has become an ongoing problem as the health care system deals with rising costs.
Lesson:Epidemic Stresses an already stressed out US healthcare system
Science 07 Jun 2019:
Vol. 364, Issue 6444, pp. 941-942
DOI: 10.1126/science.aaw8299
Precision medicine is at a crossroads. Progress toward its central goal, to address persistent health inequities, will depend on enrolling populations in research that have been historically underrepresented, thus eliminating longstanding exclusions from such research (1). Yet the history of ethical violations related to protocols for inclusion in biomedical research, as well as the continued misuse of research results (such as white nationalists looking to genetic ancestry to support claims of racial superiority), continue to engender mistrust among these populations (2). For precision medicine research (PMR) to achieve its goal, all people must believe that there is value in providing information about themselves and their families, and that their participation will translate into equitable distribution of benefits. This requires an ethics of inclusion that considers what constitutes inclusive practices in PMR, what goals and values are being furthered through efforts to enhance diversity, and who participates in adjudicating these questions. The early stages of PMR offer a critical window in which to intervene before research practices and their consequences become locked in (3).
Initiatives such as the All of Us program have set out to collect and analyze health information and biological samples from millions of people (1). At the same time, questions of trust in biomedical research persist. For example, although the recent assertions of white nationalists were eventually denounced by the American Society of Human Genetics (4), the misuse of ancestry testing may have already undermined public trust in genetic research.
There are also infamous failures in research that included historically underrepresented groups, including practices of deceit, as in the Tuskegee Syphilis Study, or the misuse of samples, as with the Havasupai tribe (5). Many people who are being asked to give their data and samples for PMR must not only reconcile such past research abuses, but also weigh future risks of potential misuse of their data.
To help assuage these concerns, ongoing PMR studies should open themselves up to research, conducted by social scientists and ethicists, that examines how their approaches enhance diversity and inclusion. Empirical studies are needed to account for how diversity is conceptualized and how goals of inclusion are operationalized throughout the life course of PMR studies. This is not limited to selection and recruitment of populations but extends to efforts to engage participants and communities, through data collection and measurement, and interpretations and applications of study findings. A commitment to transparency is an important step toward cultivating public trust in PMR’s mission and practices.
From Inclusion to Inclusive
The lack of diverse representation in precision medicine and other biomedical research is a well-known problem. For example, rare genetic variants may be overlooked—or their association with common, complex diseases can be misinterpreted—as a result of sampling bias in genetics research (6). Concentrating research efforts on samples with largely European ancestry has limited the ability of scientists to make generalizable inferences about the relationships among genes, lifestyle, environmental exposures, and disease risks, and thereby threatens the equitable translation of PMR for broad public health benefit (7).
However, recruiting for diverse research participation alone is not enough. As with any push for “diversity,” related questions arise about how to describe, define, measure, compare, and explain inferred similarities and differences among individuals and groups (8). In the face of ambivalence about how to represent population variation, there is ample evidence that researchers resort to using definitions of diversity that are heterogeneous, inconsistent, and sometimes competing (9). Varying approaches are not inherently problematic; depending on the scientific question, some measures may be more theoretically justified than others and, in many cases, a combination of measures can be leveraged to offer greater insight (10). For example, studies have shown that American adults who do not self-identify as white report better mental and physical health if they think others perceive them as white (11, 12).
The benefit of using multiple measures of race and ancestry also extends to genetic studies. In a study of hypertension in Puerto Rico, not only did classifications based on skin color and socioeconomic status better predict blood pressure than genetic ancestry, the inclusion of these sociocultural measures also revealed an association between a genetic polymorphism and hypertension that was otherwise hidden (13). Thus, practices that allow for a diversity of measurement approaches, when accompanied by a commitment to transparency about the rationales for chosen approaches, are likely to benefit PMR research more than striving for a single gold standard that would apply across all studies. These definitional and measurement issues are not merely semantic. They also are socially consequential to broader perceptions of PMR research and the potential to achieve its goals of inclusion.
Study Practices, Improve Outcomes
Given the uncertainty and complexities of the current, early phase of PMR, the time is ripe for empirical studies that enable assessment and modulation of research practices and scientific priorities in light of their social and ethical implications. Studying ongoing scientific practices in real time can help to anticipate unintended consequences that would limit researchers’ ability to meet diversity recruitment goals, address both social and biological causes of health disparities, and distribute the benefits of PMR equitably. We suggest at least two areas for empirical attention and potential intervention.
First, we need to understand how “upstream” decisions about how to characterize study populations and exposures influence “downstream” research findings of what are deemed causal factors. For example, when precision medicine researchers rely on self-identification with U.S. Census categories to characterize race and ethnicity, this tends to circumscribe their investigation of potential gene-environment interactions that may affect health. The convenience and routine nature of Census categories seemed to lead scientists to infer that the reasons for differences among groups were self-evident and required no additional exploration (9). The ripple effects of initial study design decisions go beyond issues of recruitment to shape other facets of research across the life course of a project, from community engagement and the return of results to the interpretation of study findings for human health.
Second, PMR studies are situated within an ecosystem of funding agencies, regulatory bodies, disciplines, and other scholars. This partly explains the use of varied terminology, different conceptual understandings and interpretations of research questions, and heterogeneous goals for inclusion. It also makes it important to explore how expectations related to funding and regulation influence research definitions of diversity and benchmarks for inclusion.
For example, who defines a diverse study population, and how might those definitions vary across different institutional actors? Who determines the metrics that constitute successful inclusion, and why? Within a research consortium, how are expectations for data sharing and harmonization reconciled with individual studies’ goals for recruitment and analysis? In complex research fields that include multiple investigators, organizations, and agendas, how are heterogeneous, perhaps even competing, priorities negotiated? To date, no studies have addressed these questions or investigated how decisions facilitate, or compromise, goals of diversity and inclusion.
The life course of individual studies and the ecosystems in which they reside cannot be easily separated and therefore must be studied in parallel to understand how meanings of diversity are shaped and how goals of inclusion are pursued. Empirically “studying the studies” will also be instrumental in creating mechanisms for transparency about how PMR is conducted and how trade-offs among competing goals are resolved. Establishing open lines of inquiry that study upstream practices may allow researchers to anticipate and address downstream decisions about how results can be interpreted and should be communicated, with a particular eye toward the consequences for communities recruited to augment diversity. Understanding how scientists negotiate the challenges and barriers to achieving diversity that go beyond fulfilling recruitment numbers is a critical step toward promoting meaningful inclusion in PMR.
Transparent Reflection, Cultivation of Trust
Emerging research on public perceptions of PMR suggests that although there is general support, questions of trust loom large. What we learn from studies that examine on-the-ground approaches aimed at enhancing diversity and inclusion, and how the research community reflects and responds with improvements in practices as needed, will play a key role in building a culture of openness that is critical for cultivating public trust.
Cultivating long-term, trusting relationships with participants underrepresented in biomedical research has been linked to a broad range of research practices. Some of these include the willingness of researchers to (i) address the effect of history and experience on marginalized groups’ trust in researchers and clinicians; (ii) engage concerns about potential group harms and risks of stigmatization and discrimination; (iii) develop relationships with participants and communities that are characterized by transparency, clear communication, and mutual commitment; and (iv) integrate participants’ values and expectations of responsible oversight beyond initial informed consent (14). These findings underscore the importance of multidisciplinary teams that include social scientists, ethicists, and policy-makers, who can identify and help to implement practices that respect the histories and concerns of diverse publics.
A commitment to an ethics of inclusion begins with a recognition that risks from the misuse of genetic and biomedical research are unevenly distributed. History makes plain that a multitude of research practices ranging from unnecessarily limited study populations and taken-for-granted data collection procedures to analytic and interpretive missteps can unintentionally bolster claims of racial superiority or inferiority and provoke group harm (15). Sustained commitment to transparency about the goals, limits, and potential uses of research is key to further cultivating trust and building long-term research relationships with populations underrepresented in biomedical studies.
As calls for increasing diversity and inclusion in PMR grow, funding and organizational pathways must be developed that integrate empirical studies of scientific practices and their rationales to determine how goals of inclusion and equity are being addressed and to identify where reform is required. In-depth, multidisciplinary empirical investigations of how diversity is defined, operationalized, and implemented can provide important insights and lessons learned for guiding emerging science, and in so doing, meet our ethical obligations to ensure transparency and meaningful inclusion.
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