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Mechanistic link between SARS-CoV-2 infection and increased risk of stroke using 3D printed models and human endothelial cells
Reporter: Adina Hazan, PhD
Kaneko, et al. from UCLA aimed to explore why SARS-CoV-2 infection is associated with an increased rate of cerebrovascular events, including
ischemic stroke and
intracerebral hemorrhage
While some suggested mechanisms include an overall systemic inflammatory response including increasing circulating cytokines and leading to a prothrombotic state, this may be only a partial answer. A SARS-CoV-2 specific mechanism could be likely, considering that both angiotensin-converting enzyme-2 (ACE2), the receptor necessary for SARS-CoV-2 to gain entry into the cell, and SARS-CoV-2 RNA have been reportedly detected in the human brain postmortem.
One of the difficulties in studying vasculature mechanisms is that the inherent 3D shape and blood flow subject this tissue to different stressors, such as flow, that could be critically relevant during inflammation. To accurately study the effect of SARS-CoV-2 on the vasculature of the brain, the team generated 3D models of the human middle cerebral artery during intracranial artery stenosis using data from CT (computed tomography) angiography. This data was then exported with important factors included such as
shear stress during perfusion,
streamlines, and
flow velocity to be used to fabricate 3D models.
These tubes were then coated with endothelial cells isolated and sorted from normal human brain tissue resected during surgery. In doing so, this model could closely mimic the cellular response of the vasculature of the human brain.
Surprisingly, without this 3D tube, human derived brain endothelial cells displayed very little expression of ACE2 or, TMPRSS2 (transmembrane protease 2), a necessary cofactor for SARS-COV-2 viral entry.
Interestingly,
horizontal shear stress increased the expression of ACE2 and
increased the binding of spike protein to ACE2, especially within the stenotic portion of the 3D model.
By exposing the endothelial cells to liposomes expressing the SARS-CoV-2 spike protein, they also were able to explore key upregulated genes in the exposed cells, in which they found that
“binding of SARS-CoV-2 S protein triggered 83 unique genes in human brain endothelial cells”.
This included many inflammatory signals, some of which have been previously described as associated with SARS-COV-2, and others whose effects are unknown. This may provide an important foundation for exploring potential therapeutic targets in patients susceptible to cerebrovascular events.
Overall, this study shows important links between the
mechanisms of SARS-CoV-2 and the
increase in ischemic events in these patients. It also has important implications for
treatment for SARS-CoV-2, as high blood pressure and atherosclerosis may be increasing ACE2 expression in patients, providing the entry port for viral particles into brain endothelia.
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?
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
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