Covid Linked To Disorder That Causes Sudden Vision Loss, Study Says

Authors: Zachary Snowdon Smith Forbes 

Covid-19 infection is linked to eye conditions called retinal vascular occlusions—blockages of blood vessels in the eye that can cause vision loss—according to a study published Thursday by JAMA Ophthalmology that threw light on one of several little-understood long-term effects of the virus.


The first condition, called retinal artery occlusions, can cause sudden blurring or loss of vision in one eye, and was found to have increased 29.9% in the period two to 26 weeks after Covid-19 diagnosis compared to the period 26 to two weeks before diagnosis, researchers concluded.

The second condition, retinal vein occlusions, causes similar symptoms to retinal artery occlusions and was even more strongly associated with Covid-19, with a 47% increase in the period two to 26 weeks after Covid-19 diagnosis compared to the period 26 to two weeks before diagnosis, according to the study.

The strong association between Covid-19 and retinal vein occlusions seems to confirm previous research suggesting that Covid-19 generally affects veins more severely than arteries, researchers said—a finding that could help guide treatment approaches for Covid-19 patients.

Even following Covid-19 infection, retinal vascular occlusions remained rare, with retinal artery occlusions affecting about 1 in 333,333 patients and retinal vein occlusions affecting about 1 in 81,967 patients during the period two to 26 weeks after they were diagnosed.

Researchers did not find that Covid-19 patients who were hospitalized were more likely to experience retinal vascular occlusions than those who were not hospitalized.

The study included 432,515 patients without a history of retinal vascular occlusions more than six months prior to their Covid-19 diagnosis, and who were diagnosed with the virus between January 20, 2020 and May 31, 2021.


Retinal vascular occlusions are caused when blood clots or fat deposits block blood vessels in the retina, the part of the eye that receives light and transmits images to the brain. These occlusions may cause damage ranging from slight vision impairments to whole-eye vision loss. Retinal artery occlusion is linked to diabetes, high blood pressure, elevated levels of fat in blood and various disorders affecting the heart or the carotid artery, according to the National Library of Medicine’s MedlinePlus service. Retinal vein occlusion is linked to diabetes, high blood pressure, fatty buildup in the arteries and eye disorders like glaucoma. Outcomes are variable: while many patients regain a degree of vision, there are no reliable treatments for whole-eye vision loss due to a retinal vascular occlusion. These occlusions may indicate the presence of clots or fat deposits elsewhere in the body, warning of a risk of stroke, according to Johns Hopkins Medicine.


Though Covid-19’s immediate symptoms have been well documented, scientists have struggled to understand the longer-term effects of the virus. A study published Monday by JAMA Neurology determined that the long-term smell loss reported by some Covid-19 patients is tied to damage to the olfactory bulb, the part of the brain that processes smells. Covid-19 has also been associated with a range of vascular issues such as inflammation of the heart muscle or the sac containing the heart. Some researchers have concluded that much of the damage caused by the coronavirus is not directly inflicted by the virus itself, but by infection symptoms like inflammation, the New York Times reports. The authors of the JAMA Ophthalmology study suggested a similar interpretation, theorizing that the initial vascular damage caused by Covid-19 infection might make some people more vulnerable to a pre-existing risk of retinal vascular occlusions.


It’s possible that the JAMA Ophthalmology study underestimated the risk of retinal vascular occlusions among severely ill patients because those patients’ conditions may have prevented them from informing healthcare staff of vision changes, researchers said.


Further research would be necessary to establish a cause-and-effect relationship between Covid-19 infection and retinal vascular occlusions, researchers said. The JAMA Ophthalmology study established only an association between the two conditions.

Could tiny blood clots cause long COVID’s puzzling symptoms?

Scientists debate evidence for a micro-clot hypothesis that has some people pursuing potentially risky treatments

Authors: Cassandra Willyard Nature 608, 662-664 (2022)doi:

When Lara Hawthorne, an illustrator in Bristol, UK, began developing strange symptoms after having COVID-19, she hoped that they weren’t due to the virus. Her initial illness had been mild. “I’ve been triple vaccinated. I felt quite protected,” she says. But months later, she was still sick with a variety of often debilitating symptoms: earaches, tinnitus, congestion, headaches, vertigo, heart palpitations, muscle pain and more. On some days, Hawthorne felt so weak that she could not get out of bed. When she finally saw her physician, the diagnosis was what she had been dreading: long COVID.

Unable to find relief, she became increasingly desperate. After reading an opinion piece in The Guardian newspaper about how blood clots might be to blame for long COVID symptoms, Hawthorne contacted a physician in Germany who is treating people with blood thinners and a procedure to filter the blood. She hasn’t heard back yet — rumour has it that people stay on the waiting list for months — but if she has the opportunity to head there for these unproven treatments, she probably will. “I don’t want to wait on my health when I’m feeling so dreadful,” she says.

Researchers are baffled by long COVID: hundreds of studies have tried to unpick its mechanism, without much success. Now some scientists, and an increasing number of people with the condition, have been lining up behind the as-yet-unproven hypothesis that tiny, persistent clots might be constricting blood flow to vital organs, resulting in the bizarre constellation of symptoms that people experience.

Heart disease after COVID: what the data say

Proponents of the idea (#teamclots, as they sometimes refer to themselves on Twitter) include Etheresia Pretorius, a physiologist at Stellenbosch University in South Africa, and Douglas Kell, a systems biologist at the University of Liverpool, UK, who led the first team to visualize micro-clots in the blood of people with long COVID. They say that the evidence implicating micro-clots is undeniable, and they want trials of the kinds of anticoagulant treatment that Hawthorne is considering. Pretorius penned the Guardian article that caught Hawthorne’s attention.

But many haematologists and COVID-19 researchers worry that enthusiasm for the clot hypothesis has outpaced the data. They want to see larger studies and stronger causal evidence. And they are concerned about people seeking out unproven, potentially risky treatments.

When it comes to long COVID, “we’ve now got little scattered of bits of evidence”, says Danny Altmann, an immunologist at Imperial College London. “We’re all scuttling to try and put it together in some kind of consensus. We’re so far away from that. It’s very unsatisfying.”

Cascade of clots

Pretorius and Kell met about a decade ago. Pretorius had been studying the role of iron in clotting and neglected to cite some of Kell’s research. When he reached out, they began chatting. “We had a Skype meeting and then we decided to work together,” Pretorius says. They observed odd, dense clots that resist breaking down for years in people with a variety of diseases. The research led them to develop the theory that some molecules — including iron, proteins or bits of bacterial cell wall — might trigger these abnormal clots.

Blood clotting is a complex process, but one of the key players is a cigar-shaped, soluble protein called fibrinogen, which flows freely in the bloodstream. When an injury occurs, cells release the enzyme thrombin, which cuts fibrinogen into an insoluble protein called fibrin. Strands of fibrin loop and criss-cross, creating a web that helps to form a clot and stop the bleeding.

Under a microscope, this web typically resembles “a nice plate of spaghetti”, Kell says. But the clots that the team has identified in many inflammatory conditions look different. They’re “horrible, gunky, dark”, Kell says, “such as you might get if you half-boiled the spaghetti and let it all stick together.” Research by Kell, Pretorius and their colleagues suggests that the fibrin has misfolded1, creating a gluey, ‘amyloid’ version of itself. It doesn’t take much misfolding to seed disaster, says Kell. “If the first one changes its conformation, all the others have to follow suit”, much like prions, the infectious misfolded proteins that cause conditions such as Creutzfeldt–Jakob disease.

Long-COVID treatments: why the world is still waiting

Pretorius first saw these strange, densely matted clots in the blood of people with a clotting disorder2, but she and Kell have since observed the phenomenon in a range of conditions1 — diabetes, Alzheimer’s disease and Parkinson’s disease, to name a few. But the idea never gained much traction, until now.

When the pandemic hit in 2020, Kell and Pretorius applied their methods almost immediately to people who had been infected with SARS-CoV-2. “We thought to look at clotting in COVID, because that is what we do,” Pretorius says. Their assay uses a special dye that fluoresces when it binds to amyloid proteins, including misfolded fibrin. Researchers can then visualize the glow under a microscope. The team compared plasma samples from 13 healthy volunteers, 15 people with COVID-19, 10 people with diabetes and 11 people with long COVID3. For both long COVID and acute COVID-19, Pretorius says, the clotting “was much more than we have previously found in diabetes or any other inflammatory disease”. In another study4, they looked at the blood of 80 people with long COVID and found micro-clots in all of the samples.

So far, Pretorius, Kell and their colleagues are the only group that has published results on micro-clots in people with long COVID.

But in unpublished work, Caroline Dalton, a neuroscientist at Sheffield Hallam University’s Biomolecular Sciences Research Centre, UK, has replicated the results. She and her colleagues used a slightly different method, involving an automated microscopy imaging scanner, to count the number of clots in blood. The team compared 3 groups of about 25 individuals: people who had never knowingly had COVID-19, those who had had COVID-19 and recovered, and people with long COVID. All three groups had micro-clots, but those who had never had COVID-19 tended to have fewer, smaller clots, and people with long COVID had a greater number of larger clots. The previously infected group fell in the middle. The team’s hypothesis is that SARS-CoV-2 infection creates a burst of micro-clots that go away over time. In individuals with long COVID, however, they seem to persist.

Dalton has also found that fatigue scores seem to correlate with micro-clot counts, at least in a few people. That, says Dalton, “increases confidence that we are measuring something that is mechanistically linked to the condition”.

In many ways, long COVID resembles another disease that has defied explanation: chronic fatigue syndrome, also known as myalgic encephalomyelitis (ME/CFS). Maureen Hanson, who directs the US National Institutes of Health (NIH) ME/CFS Collaborative Research Center at Cornell University in Ithaca, New York, says that Pretorius and Kell’s research has renewed interest in a 1980s-era hypothesis about abnormal clots contributing to symptoms. Pretorius, Kell and colleagues found amyloid clots in the blood of people with ME/CFS, but the amount was much lower than what they’ve found in people with long COVID5. So clotting is probably only a partial explanation for ME/CFS, Pretorius says.

Micro-clot mysteries

Where these micro-clots come from isn’t entirely clear. But Pretorius and Kell think that the spike protein, which SARS-CoV-2 uses to enter cells, might be the trigger in people with long COVID. When they added the spike protein to plasma from healthy volunteers in the laboratory, that alone was enough to prompt formation of these abnormal clots6.

Bits of evidence hint that the protein might be involved. In a preprint7 posted in June, researchers from Harvard University in Boston, Massachusetts, reported finding the spike protein in the blood of people with long COVID. Another paper8 from a Swedish group showed that certain peptides in the spike can form amyloid strands on their own, at least in a test tube. It’s possible that these misfolded strands provide a kind of template, says Sofie Nyström, a protein chemist at Linköping University in Sweden and an author of the paper.

Micrographs of platelet poor plasma of a healthy volunteer showing few microclots,and post-COVID-19 infection showing microclots
Micro-clots (green) in a study participant before SARS-CoV-2 infection (left four panels) and in the same person after they developed long COVID (right four panels).Credit: E. Pretorius et al./Cardiovasc. Diabetol. (CC BY 4.0)

A California-based group found that fibrin can actually bind to the spike. In a 2021 preprint9, it reported that when the two proteins bind, fibrin ramps up inflammation and forms clots that are harder to degrade. But how all these puzzle pieces fit together isn’t yet clear.

If the spike protein is the trigger for abnormal clots, that raises the question of whether COVID-19 vaccines, which contain the spike or instructions for making it, can induce them as well. There’s currently no direct evidence implicating spike from vaccines in forming clots, but Pretorius and Kell have received a grant from the South African Medical Research Council to study the issue. (Rare clotting events associated with the Oxford–AstraZeneca vaccine are thought to happen through a different mechanism (Nature 596, 479–481; 2021).)

Raising safety concerns about the vaccines can be uncomfortable, says Per Hammarström, a protein chemist at Linköping University and Nyström’s co-author. “We don’t want to be over-alarmist, but at the same time, if this is a medical issue, at least in certain people, we have to address that.” Gregory Poland, director of the Mayo Clinic’s vaccine research group in Rochester, Minnesota, agrees that it’s an important discussion. “My guess is that spike and the virus will turn out to have a pretty impressive list of pathophysiologies,” he says. “How much of that may or may not be true for the vaccine, I don’t know.”

Dearth of data

Many researchers find it plausible and intriguing that micro-clots could be contributing to long COVID. And the hypothesis does seem to fit with other data that have emerged on clotting. Researchers already know that people with COVID-19, especially severe disease, are more likely to develop clots. The virus can infect cells lining the body’s 100,000 kilometres of blood vessels, causing inflammation and damage that triggers clotting.

Those clots can have physiological effects. Danny Jonigk, a pathologist at Hanover Medical School in Germany, and his colleagues looked at tissue samples from people who died of COVID-19. They found micro-clots and saw that the capillaries had split, forming new branches to try to keep oxygen-rich blood flowing10. The downside was that the branching introduces turbulence into the flow that can give rise to fresh clots.

How common is long COVID? Why studies give different answers

Several other labs have found signs that, in some people, this tendency towards clotting persists months after the initial infection. James O’Donnell, a haematologist and clotting specialist at Trinity College Dublin, and his colleagues found11 that about 25% of people who are recovering from COVID-19 have signs of increased clotting that are “quite marked and unusual”, he says.

What is less clear is whether this abnormal clotting response is actually to blame for any of the symptoms of long COVID, “or is it just, you know, another unusual phenomenon associated with COVID?” O’Donnell says.

Alex Spyropoulos, a haematologist at the Feinstein Institutes for Medical Research in New York City, says the micro-clot hypothesis presents “a very elegant mechanism”. But he argues that much more work is needed to tie the lab markers to clinical symptoms. “What’s a little bit disturbing is that these authors and others make huge leaps of faith,” Spyropoulos says.

Jeffrey Weitz, a haematologist and clotting specialist at McMaster University in Hamilton, Canada, points out that the method Pretorius’s team is using to identify micro-clots “isn’t a standard technique at all”. He adds: “I’d like to see confirmation from other investigators.” Micro-clots are difficult to detect. Pathologists can spot them in tissue samples, but haematologists tend to look for markers of abnormal clotting rather than the clots themselves.

Other, larger studies of long COVID have failed to find signs of clotting. Michael Sneller, an infectious-disease specialist, and his colleagues at the NIH in Bethesda, Maryland, thoroughly examined 189 people who had been infected with SARS-CoV-2, some with lingering symptoms and some without, and 120 controls12. They did not specifically look for micro-clots. But if micro-clots had been clogging the capillaries, Sneller says, they should have seen some evidence — tissue damage in capillary-rich organs such as the lungs and kidneys, for example. Micro-clots might also damage red blood cells, leading to anaemia. But Sneller and his colleagues found no signs of this in any of the lab tests.

The four most urgent questions about long COVID

Kell and Pretorius argue that just because this study didn’t find any evidence of micro-clots doesn’t mean they aren’t there. One of the key issues with long COVID is that “every single test comes back within the normal ranges”, Pretorius says. “You have desperately ill patients with no diagnostic method.” She hopes that other researchers will read their papers and attempt to replicate their results. “Then we can have a discussion,” she says. The ultimate causal proof, she adds, would be people with long COVID feeling better after receiving anticoagulant therapies.

There is some limited evidence of this. In an early version of a preprint, posted in December 2021, Kell, Pretorius and other researchers, including physician Gert Jacobus Laubscher at Stellenbosch University, reported that 24 people who had long COVID and were treated with a combination of two antiplatelet therapies and an anticoagulant experienced some relief13. Participants reported that their main symptoms resolved and that they became less fatigued. They also had fewer micro-clots. Pretorius and Kell are working to gather more data before they try to formally publish these results. But other physicians are already using these medications to treat people with long COVID. Some are even offering a dialysis-like procedure that filters fibrinogen and other inflammatory molecules from the blood. To O’Donnell, such treatment feels premature. He accepts that some people with long COVID are prone to clots, but leaping from a single small study to treating a vast number of people is “just not going to wash in 2022 in my book”, he says. Sneller agrees. “Anticoagulating somebody is not a benign thing. You basically are interfering with the blood’s ability to clot,” he says, which could make even minor injuries life-threatening.

Kell says he’s tired of waiting for a consensus on how to treat long COVID. “These people are in terrible pain. They are desperately unwell,” he says. Altmann understands that frustration. He gets e-mails almost daily, asking: “Where are the drug trials? Why does it take so long?” But even in the midst of a pandemic, he argues, researchers have to follow the process. “I’m not rubbishing anybody’s data. I’m just saying we’re not there yet,” he says. “Let’s join up the dots and do this properly.”


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Consequences of COVID-19 for the Pancreas

Authors: Urszula Abramczyk,1,*Maciej Nowaczyński,2Adam Słomczyński,2Piotr Wojnicz,2Piotr Zatyka,2 and Aleksandra Kuzan1 Int J Mol Sci. 2022 Jan; 23(2): 864.Published online 2022 Jan 13. doi: 10.3390/ijms23020864


Although coronavirus disease 2019 (COVID-19)-related major health consequences involve the lungs, a growing body of evidence indicates that COVID-19 is not inert to the pancreas either. This review presents a summary of the molecular mechanisms involved in the development of pancreatic dysfunction during the course of COVID-19, the comparison of the effects of non-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on pancreatic function, and a summary of how drugs used in COVID-19 treatment may affect this organ. It appears that diabetes is not only a condition that predisposes a patient to suffer from more severe COVID-19, but it may also develop as a consequence of infection with this virus. Some SARS-CoV-2 inpatients experience acute pancreatitis due to direct infection of the tissue with the virus or due to systemic multiple organ dysfunction syndrome (MODS) accompanied by elevated levels of amylase and lipase. There are also reports that reveal a relationship between the development and treatment of pancreatic cancer and SARS-CoV-2 infection. It has been postulated that evaluation of pancreatic function should be increased in post-COVID-19 patients, both adults and children.

1. Effects of Severe Acute Respiratory Syndrome-Related Coronavirus (SARS-CoV) and Middle East Respiratory Syndrome-Related Coronavirus (MERS-CoV) on the Pancreas

Coronaviruses are enveloped, single- and positive-stranded RNA viruses that infect birds and mammals. In humans, coronaviruses cause respiratory tract infection, usually the common cold, but they can also cause severe respiratory illness including severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), caused by severe acute respiratory syndrome-related coronavirus (SARS-CoV) and Middle East respiratory syndrome-related coronavirus (MERS-CoV), respectively [1]. Coronaviruses tend to cause epidemics and even pandemics. The first coronavirus pandemic was the SARS outbreak in 2002–2003 [2]. With the experience gained during the SARS pandemic, it was possible to more quickly identify subsequent outbreaks of the MERS epidemic in 2012 [3]. The pathomechanism of both viruses is very similar—they even both use transmembrane protease serine 2 (TMPRSS2), except SARS-CoV uses angiotensin-converting enzyme 2 (ACE2) as its receptor, whereas MERS uses dipeptidyl peptidase-4 (DPP4) [4,5]. Moreover, there is a difference in terms of the severity and frequency of symptoms, which was observed in MERS patients as more frequent hospitalization in the intensive care unit (ICU) compared to SARS patients [2] (Table 1). Diabetes was one of the significant and independent predictors for developing severe SARS-CoV and MERS-CoV [6,7,8]. In MERS, no viral antigen was detected in any tissue other than pneumocytes [7], despite multiple organ dysfunction syndrome in critically ill patients. In SARS-CoV, the presence of the virus was detected not only in respiratory epithelial cells, but also in small intestinal and colonic epithelial cells, in which it also revealed replication features [9]. It is known that the ACE2 receptor is also present in tissues such as the heart, kidney, and pancreas [8,9]. According to some authors, the presence of the receptor is sufficient for tissue entry and pathogenic activity, although other researchers do not support this thesis [9,10]. Yang et al. were some of the first researchers who hypothesized that SARS coronavirus enters islets using ACE2 as its receptor and damages islets causing acute diabetes [8]. Yang’s study revealed that SARS-CoV had a much higher affinity for pancreatic islet cells than for pancreatic exocrine cells, which was consistent with the hyperglycemia observed in some patients and rarely reported acute pancreatitis (AP) [8]. Furthermore, insulin-dependent diabetes mellitus (IDDM) and high fasting blood glucose values were observed in some inpatients [8]. A 3-year follow-up revealed that both abnormalities were transient, which may be indicative of only temporary damage to the pancreatic islets [8]. However, another reason (different from that given by Young et al.) for high fasting blood glucose value in patients may result from increased stress hormones release. Cortisol, catecholamines, growth hormone, and glucagon, which are released during infection, fever, and trauma, can lead to hyperglycemia to the same degree as SARS-CoV can [11]. No information was found in the literature about a direct impact of the MERS virus on the pancreas or on glycemia during or after infection. This may be due to an insufficiently detailed analysis of the available data during previous studies that oscillated primarily, for laboratory tests, between complete blood count (CBC), lactate dehydrogenase (LDH), urea, and creatinine analysis. A summary of SARS-CoV, MERS, and SARS-CoV-2 is shown in Table 1.Table 1. The summary of characteristics of SARS and MERS coronaviruses. Dipeptidyl peptidase-4 (DPP4), transmembrane protease serine 2 (TMPRSS2), hospitalization in the intensive care unit (ICU), and cathepsin L (CTSL).


In 2019, a new coronavirus named SARS-CoV-2 was identified, causing COVID-19. This virus has many characteristics that are analogous to SARS-CoV, for example, ACE2 is also used as its receptor [12]. Patients with diabetes are among those with the most severe forms of COVID-19 and related mortality; insights from recent experience can guide future management [17], particularly for the consequences on the pancreas. As the COVID-19 pandemic has been ongoing for nearly two years, this study aims to collect data concerning the impact of SARS-CoV-2 on the pancreas and analyze them to estimate the future health consequences of COVID-19 in populations.

2. Pancreatic Damage during Diabetes Mellitus and COVID-19

Pancreas tissue damage may cause to the lack of control over normal blood glucose levels in the body. Type 1 diabetes (T1D) is caused by insulin deficiency due to βcell dysfunction of immunologic or idiopathic cause. In contrast, β pancreatic cells in type 2 diabetes (T2D) become depleted over time due to compensatory insulin secretion caused by insulin resistance. There is also type 3 diabetes (T3D), which is described as diabetes associated with the development of Alzheimer’s disease [18]. It should not be confused with type 3c (pancreatogenic) diabetes, which relates to the exocrine and digestive functions of the pancreas. The issue concerning the impairing effect of hyperglycemia (glucotoxicity) on the secretory function of the islets of Langerhans has also been increasingly raised. In addition to endocrine dysfunction, some diabetic patients may also develop moderate exocrine pancreatic insufficiency (EPI), in which pancreatic enzyme secretion is impaired. EPI can be observed in almost all patients with type 3c (pancreatogenic) diabetes (secondary to pancreatic pathology), whereas the prevalence of this dysfunction in patients with T1D or T2D is 40% and 27%, respectively [19].With the ongoing SARS-CoV-2 pandemic, patients with reduced normal pancreatic function are at high risk for COVID-19 requiring hospitalization. In particular, elevated blood glucose levels in patient with and without diabetes makes them at high risk of mortality [20]. Hyperglycemia impairs the immune response (e.g., by reducing the activity of macrophages and polymorphonuclear leukocytes), which in addition influences the excessive cytokine response, and thus has a strong proinflammatory effect.The receptors for ACE2, which are also present in the pancreas, are a target of SARS-CoV-2 in the body, which may result in acute failure of both the islets of Langerhans and exocrine cells [15]. Infection-induced, transient β cell dysfunction may cause an uncontrolled hyperglycemic state, especially in patients whose pancreas is already affected by diabetes mellitus. Persistent hyperglycemia usually predisposes to severe COVID-19 and to viral infection complicated by secondary infections. The aforementioned risk can be found in T1D, T2D, and gestational diabetes mellitus (GDM). In T2D patients, the much more frequent coexistence of other risk factors such as atherosclerosis, hypertension, and obesity should be taken into consideration, which usually implies a worse prognosis for the course of COVID-19 [21,22]. In GDM, SARS-CoV-2 infection not only increases the risk of more severe course of the disease in a patient, but may also result in diabetic fetopathy or, in more advanced pregnancies, increase the risk of future pathologies involving glucose metabolism (such as T2D) in a child [23].

3. Pancreatic Damage in Patients without Pre-Existing Diabetes Infected with SARS-CoV-2

It has been postulated that, either by direct invasion of pancreatic cells by the virus or by indirect mechanisms described below, SARS-CoV-2 has a destructive effect on the pancreas and can lead to insulin deficiency and development of T1D [24].If the hypothesis that SARS-CoV-2 infection causes hyperglycemia is true, increased statistics of new T1D cases should be observed. Indeed, there are publications that describe such a phenomenon. For instance, Unsworth et al. and Kamrath et al. describe an increase in new-onset T1D in children during the COVID-19 pandemic [16,25]. Although pancreatic β cell damage induced transient hyperglycemia in SARS-CoV, it is still unclear whether β cell damage is transient or permanent in SARS-CoV-2 [22]. This information appears to be of great importance because COVID-19 in children is frequently considered “harmless”. Therefore, it is reasonable to sensitize parents to the fact that the consequences of COVID-19 may be potentially dangerous for their children.Below you will find the proposed molecular mechanisms that may participate in pancreatic damage that causes carbohydrate metabolism disorders.

4. Etiology Associated with ACE2, TMPRSS2, and Na+/H+ Exchanger

As previously mentioned, SARS-CoV infection of host cells is facilitated by ACE2, but also by the transmembrane protease serine 2 (TMPRSS2) and other host cell proteases such as cathepsin L (CTSL) [13].ACE2 is an enzyme that is expressed to varying degrees in most cells of the human body [14,26,27]. This enzyme catalyzes the conversion of angiotensin II to angiotensin 1–7, taking part in the maintenance of body homeostasis by influencing the regulation of blood pressure and water–electrolyte balance through the renin–angiotensin–aldosterone (RAA) system [28]. Moreover, ACE2/angiotensin (1–7) stimulates insulin secretion, reduces insulin resistance, and increases pancreatic βcell survival [27,28].In addition to the key role it plays in maintaining body homeostasis, ACE2 is now also the best-studied target for SARS-CoV-2 S glycoprotein, enabling infection of host cells [27,29]. ACE2 in the pancreas is expressed mainly within the pericytes of pancreatic microvessels and to a lesser extent on the surface of the islets of Langerhans, including pancreatic β cells [30]. SARS-CoV-2 shows 10–20 times more activity against ACE2 than SARS-CoV, which significantly increases the infectivity of SARS-CoV-2 [31,32]. Furthermore, studies indicate that SARS-CoV may also downregulate ACE2 expression in cells. This causes an imbalance between ACE and ACE2, consequently leading to blood pressure disorders and systemic inflammation [27,33,34]. Due to the 79% genetic similarity between SARS-CoV and SARS-CoV-2 [35], it is speculated that ACE2 expression may also be downregulated during SARS-CoV-2 infection, causing i.a. MODS observed in COVID-19 [27].During cell infection by SARS-CoV-2, in addition to the role played by ACE2, it is also appropriate to consider the significant pathogenic role of TMPRSS2 that is necessary for the preparation of S glycoprotein by its cleavage, thereby enabling fusion of the virus with the host cell [36,37]. The S1 and S2 domains can be distinguished in the SARS-CoV-2 S glycoprotein. The S1 domain is involved in binding to the ACE2 receptor and then TMPRSS2 intersects with the S protein, including at the boundary of the S1 and S2 domains and within the S2 domain, which enables the virus–cell fusion [38,39]. According to studies, TMPRSS2 expression is significantly increased in obese patients, which may contribute to the poorer prognosis that is observed during COVID-19 in this patient group [40]. Moreover, obese patients are frequently already burdened with problems such as insulin resistance at baseline, while the presence of ACE2 and TMPRSS2 within the pancreas as a binding site for SARS-CoV-2 may exacerbate insulin resistance causing problems in terms of diabetes management in COVID-19 patients.There are also other mechanisms by which COVID-19 may affect the development of hyperglycemia. It is reported that the virus may also affect the glucose regulation through the Na+/H+ exchanger and lactate pathways. The mechanism is that angiotensin II, which accumulates during infection, contributes to insulin resistance and—by activating the Na+/H+ exchanger in the pancreas—it leads to hypoxia and extracellular acidification, which, through the accumulation of calcium and sodium ions in the cells and the production of reactive oxygen species, damages pancreatic tissue [41]. Simultaneously, the concentration of lactate increases, which in COVID-19 infection is intensively released, among other things, from adipose tissue, and then monocarboxylate transporters transport lactate and H+ ion inward in the cell, which increases Na+/H+ exchanger activation, further disrupting pancreatic homeostasis [41].

5. The Etiology Associated with a Systemic Proinflammatory Environment, Immune System Aggression, and Production of Novel Autoantigens

A broad spectrum of proinflammatory cytokines, such as IL-2, IL-6, IL-7, IL-8, interferon-γ, and Tumor Necrosis Factor α (TNF-α), is released during, in particular severe, COVID-19 infection [42,43,44]. Based on current studies, it is reasonable to suspect that these cytokines are released in response to the binding of the virus to ACE2 receptors that are also located in the pancreas [9,42]. The cause of pancreatic damage during COVID-19 is the cytokine storm that plays a key role in this case, because in both acute pancreatitis (AP) and severe COVID-19, elevated levels of the aforementioned interleukins are associated with the severity of these both disease entities. Particular attention should be paid to IL-6, because it is suspected to play a key role in the pathogenesis of AP as well as acute respiratory distress syndrome (ARDS) that is the most common and most severe clinical manifestation of COVID-19. In COVID-19-induced ARDS, IL-6 levels are correlated with disease-related mortality [45,46,47]. At the same time, high IL-6 levels correlate with an increased risk of developing severe pancreatitis [48,49].The production of neutralizing antibodies is also an important response of the body in the course of COVID-19 [50,51,52]. It has been observed that early seroconversion and very high antibody titers occur in patients with severe SARS-CoV-2 infection [53,54]. The available literature details a mechanism called antibody-dependent enhancement (ADE), which is associated with a pathological response of the immune system [53]. ADE exploits the existence of FcRS receptors located on various cells of the immune system, for example, macrophages and B lymphocytes [53]. This relationship may lead to a likely bypass of the classical viral infection pathway by ACE2, and virus–antibody complexes may stimulate macrophages to overproduce cytokines including significant IL-6 [53,55].Molecular mimicry may be also one of potential causes of pancreatic cell damage [56]. There are similarities in the protein structure of the virus and β-pancreatic cells, which may induce cross-reactivity and lead to autoimmunity [56]. Furthermore, viral infection may also lead to increased cytokine secretion by surrounding dendritic cells and activation of naive T cells in genetically predisposed individuals [56].

6. Pancreatitis in COVID-19

Although the impact of the discussed coronavirus-induced disease on exocrine function is not fully understood, available literature is not able to unambiguously determine whether the tissue damage leading to AP occurs as a result of direct SARS-CoV-2 infection [57] or as a result of systemic MODS with increased levels of amylase and lipase [42]. Liu et al.’s study involving 121 COVID-19 patients with a mean age of 57 years and a variable course of infection proved above-normal levels of amylase and lipase in 1–2% of patients with moderate COVID-19 infection and in 17% of patients with severe COVID-19 infection. This may support the hypothesis that SARS-CoV-2-induced disease has a destructive effect not only on the endocrine portion of this gland, but also on the exocrine one [15].However, elevated levels of pancreatic enzymes in question do not have to mean the destruction of pancreatic cells—after all, such a situation may occur during kidney failure or diarrhea in the course of COVID-19. Furthermore, there remains the question of the effect of drugs administered during SARS-CoV-2 infection on changes in pancreatic function [42], discussed further in this article.According to the International Association of Pancreatology (IAP) and the American Pancreatic Association (APA), the diagnosis of AP is based on meeting two out of three of the following criteria: clinical (epigastric pain), laboratory (serum amylase or lipase > 3 × upper limit of normal), and/or imaging criteria (computed tomography, magnetic resonance imaging, ultrasound) [58]. Pancreatic lipase is considered as a potential marker of SARS-CoV-2 severity with concomitant AP. In Hemant Goyal et al.’s study, as many as 11.7% out of 756 COVID-19 patients had hyperlipidemia and they were three times more likely to have severe COVID-19 [59]. Those with higher lipase levels—17% out of 83 patients—required hospitalization [60]. However, it is difficult to distinguish whether these patients required hospitalization for severe systemic COVID-19 infection or for pancreatitis in the course of COVID-19 infection.AP in the course of COVID-19 was analyzed in different age groups; however, some studies only involve children [61]. Compared to pancreatic islet cells, cells of the exocrine pancreatic ducts are more abundant in ACE2 and TMPRSS2 that are necessary for the virus to penetrate the cell [62]. Infection of these cells may be one of the causes of AP [63]. Infections, both bacterial and viral, are one of the causes of AP. The definitive mechanism of how viral infections affect pancreatic cells is not known; however, a study by Maria K Smatti et al. found that there is infection of pancreatic islet cells and replication of the virus within them, ultimately resulting in autoimmune reactions that eventually affect both diabetes and AP in a negative way [64]. For non-SARS-CoV-2 patients, the etiology of AP is known and confirmed in most cases, although 69% of those undergoing infection do not have definite etiology of AP while meeting the AP-Atlanta criteria for diagnosis [65].Hegyi et al. show the mechanism of MODS formation during COVID-19 infection and AP [66]. This is lipotoxicity, involving an interstitial increase in pancreatic lipase levels, which leads to the breakdown of triacylglycerols contained in adipose tissue cells and the release of unsaturated fatty acids. These in turn exert a toxic effect on mitochondria causing the release of cytokines, which results in a cytokine storm.There is also a hypothesis, which claims that AP can develop because of blood circulatory centralization resulting from uncontrolled cytokine storm created by SARS-CoV-2 infection [67]. There exist reports that say that pancreatic ischemia may be the cause of different degrees of acute pancreatitis [68,69]. This statement can be supported by the reports that state that pancreatic blood reperfusion inhibits the development of AP and accelerate pancreas recovery [70].Another mechanism of developing AP during COVID-19 may be a coagulation cascade activation caused by active inflammatory process due to SARS-CoV-2 infection [71]. The ongoing inflammatory process causes not only hemostasis imbalance for blood clotting, but it also leads to intensification of coagulation by removing epithelial cell protein C receptor (EPCR) from epithelial by the means of inflammatory mediators and thrombin [71]. This means that both processes intensify each other. Simultaneously, it was proved that COVID-19 predisposes patients to venous thromboembolism resulting from excessive inflammation, platelet activation, and endothelial dysfunction [72]. It is also important to notice that AP is inherently connected with a coagulation cascade activation, increased fibrinolysis and, hence, higher level of D-dimers [73]. Acute pancreatitis severity may depend on hemostasis imbalance; local coagulation results in mild AP whereas, in more severe AP cases, the imbalance may lead to development of disseminated intravascular coagulation (DIC) [74]. These observations have been supported by the results of experimental studies showing that the inhibition of coagulation reduces the development of AP [75,76,77] and exhibits therapeutic effect in this disease [78,79]. Additionally it is worth noticing that infection-related hyperglycemia has powerful inflammation-promoting effects on the organism (especially when organism is under stress), thus increasing the number of inflammatory mediators [74]. Unfortunately, it is impossible to decide which process is dominant in causing AP in COVID-19 patients: local inflammation caused by SARS-CoV-2 or systemic hemostasis imbalance.Clinical reports on low molecular weight heparin (LMWH) treatment in AP seem to emphasize a more significant role of hemostasis imbalance in causing AP [74,80,81]. Heparin is extremely significant in the treatment of COVID19 patients due to its properties, mainly its similarity to heparan sulphate, which appears in a respiratory tract, its interactions with SARS-CoV-2 S protein, leading to viral adhesion inhibiting to the cell membrane [82], and its anti-inflammatory effects. Thanks to these properties, heparin may not only show its therapeutic effect as the anticoagulant, but also its protective role in acute pancreatitis or respiratory inflammations [83,84,85].

7. Drugs Used against SARS-CoV-2 Infection (Glucocorticoids, Lopinavir, Ritonavir, Remedesivir, Interferon-β1 (IFN-β1), and Azithromycin) Induce Pancreatic β Cell Damage

Statistical analyses revealed a significantly higher incidence of AP with the concomitant systemic use of glucocorticosteroids (GCS) [86]. In one study analyzing the development of drug-induced AP, dexamethasone, was classified as type IB—there was one case report in which administration of this drug-induced AP occurred; however, other causes of pancreatitis such as alcohol consumption could not be excluded [87]. Other GCS such as hydrocortisone, prednisone, and prednisolone were used in patients with mild to moderate AP; however, they cannot be classified into any group because they are frequently used together with other drugs that cause AP [86,87]. However, it has been determined that GCS independently increase the risk of AP, and patients with residual AP risk factors during GCS treatment should be more monitored for the development of AP [23]. Javier A. Cienfuegos et al. additionally observed that one of mechanisms of AP formation in COVID-19 patients may be GCS administered at the time of admission to the ICU with severe respiratory failure [88]. Because GCS were used in severe COVID-19 cases, it is difficult to say what true reason for AP was—either a severe course of COVID-19 or GCS application or both.GCS are used in the treatment of many diseases due to their immunosuppressive and anti-inflammatory nature. They induce diabetes in previously healthy patients as well as significantly exacerbate diabetes in diabetic patients [89,90]. Diabetes develops in these patients likely due to pancreatic β cell dysfunction, decreased insulin secretion, and increased insulin resistance in other tissues, which may depend on the timing and the dose of GCS used [89,91]. Long-acting or intermediate-acting insulin alone or combined with short-acting insulin should be used during the treatment [90]. At the same time, no advantage was found over the use of oral hypoglycemics [92]. Certainly, patients after long-term GCS therapy will need further observation for diabetes.Lopinavir/ritonavir was classified in the previously mentioned study as a type IV drug—medications reported with little information [87]. Both drugs are included in the group of antiretrovirals that act as protease inhibitors, and they are primarily used for HIV infection. Although Lopinavir is an active drug, it is not used alone. There have been reports about the occurrence of AP during the use of protease inhibitors in question, which is also described in the Summary of Product Characteristics (SmPC) of products approved by Committee for Medicinal Products for Human Use (CHMP). It has been proved that the use of lopinavir/ritonavir causes hyperglycemia [93,94].Remdesivir is an adenosine analogue with antiviral activity. There are single reports about the occurrence of pancreatitis as a result of the use of the aforementioned medication [95,96]. At the same time, it should be noted that other nucleoside-derivative drugs may cause pancreatitis [97].The current state of knowledge does not clearly indicate the therapeutic benefit of interferon-β in the treatment of COVID-19 patients [98,99]. To date, only single cases suggesting induction of pancreatitis by interferon-β have been reported. Based on this, Badalov et al. classified interferon into type III [87].There are few reports about the development of AP due to the use of azithromycin [100]. In the previously mentioned study by Badalov et al., two macrolide antibiotics were classified as type II and III. Unfortunately, there are no direct data concerning azithromycin. Interestingly, there were cases of patients with concomitant symptoms of AP and viral pneumonia caused by SARS-CoV-2 who were treated with azithromycin, which resulted in complete resolution of symptoms for both conditions [96,101]. Based on available data, the risk of azithromycin-induced AP is low.There is no clear evidence that azithromycin affects blood glucose levels in humans. However, it is known for its prokinetic effects, which may be helpful in patients who suffer from diabetic gastroparesis [102]). The incidence of hypo- and hyperglycemic episodes was not proved to be significant for azithromycin [103]; however, the risk of dysglycemia is emphasized [94]. In the SmPC, where azithromycin is the main ingredient, it is not possible to establish a causal relationship between the occurrence of pancreatitis and taking medications (Zithromax) based on the available data. In contrast, glycemic disturbances were not indicated as side effects (Zithromax) [104].Hydroxychloroquine has been extensively promoted for COVID-19 due to its anti-inflammatory and antiviral action; yet, the use of this agent in diabetes deserves particular attention for its documented hypoglycemic action, and its benefit on COVID-19 is controversial, although there is large usage [105].Table 2 shows a comparison of the side effects of medications in question.Table 2. Side effects of medications used in SARS-CoV-2 infection in the area of pancreatic effects and hyperglycemia.


8. COVID-19, Pancreas, and Glycation

In T2D diabetics, oxidative stress leading to pancreatic damage may be stimulated by, among other things, the intense glycation that accompanies hyperglycemia [24]. Glycation is a non-enzymatic process involving reducing sugar and amino groups of proteins, which contributes to the formation of advanced glycation end products (AGEs). These products have significantly altered biochemical properties relative to the substrates, including proteins that have altered conformation, increased rigidity, resistance to proteolysis, etc. [106,107].Part of the pathomechanism involved in facilitating coronavirus infection in diabetics may be due to glycation of ACE2 and SARS-CoV-2 spike protein [108,109].An interesting hypothesis is that COVID-19 has a worse prognosis in patients with intense glycation, and thus high tissue AGE content. Glycated hemoglobin (HbA1c) is a commonly used diagnostic tool that estimates intensity of glycation. The parameter is not only a marker of long-term persistent hyperglycemia, but an active participant in immune processes, as HbA1c levels are associated with NK cell activity [110].Zhang et al.’s retrospective cohort study concerning COVID-19 patients revealed that glycated hemoglobin correlates negatively with saturation (SaO2) and positively with C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and fibrinogen (Fbg). It was concluded that determination of HbA1c levels may be helpful in assessing inflammation, hypercoagulability, and prognosis of COVID-19 patients [111].According to the meta-analysis by Chen et al. (2020), Hba1c levels were slightly higher in patients with severe COVID-19 compared to patients with mild COVID-19; however, this correlation was not statistically significant. However, it is of great importance to note that only two studies analyzing HbA1c in COVID-19 patients were included in this analysis because only these studies were available in May 2020 [112].Glycation plays its physiological effects not only directly by changing the properties of various proteins, but also indirectly through various receptors. RAGE is the most common receptor for AGEs. Binding of RAGE to its ligands activates a proinflammatory response primarily by mitogen-activated protein kinase (MAPK) and nuclear factor κβ (NFκβ) pathways. This interaction was proved to be significant in the pathogenesis of cancer, diabetes mellitus, and other inflammatory disorders [113]. RAGE was found to be expressed in the pancreas, and S100P-derived RAGE antagonistic peptide (RAP) reduces pancreatic tumor growth and metastasis [113]. The implications of this fact may also apply to the etiology and treatment of COVID-19. It has been postulated that targeting RAGE by various antagonists of this receptor may inhibit damage to various organs including the pancreas [114].

9. COVID-19 vs. Pancreatic Cancer

Immunosuppression as a treatment effect, elevated cytokine levels, altered expression of receptors for SARS-CoV-2, and a prothrombotic state in patients with various types of cancer may exacerbate the effects of COVID-19 [115].Focusing on pancreatic cancer, it can be observed that the pathomechanism of both diseases—COVID-19 and tumorigenesis in the pancreas—overlap in several molecular mechanisms. As mentioned above, SARS-CoV-2 infection of host cells is facilitated by ACE-2, TMPRSS2, and CTSL. Cathepsin L is upregulated in a wide variety of cancers, including pancreatic adenocarcinoma [13]. TMPRSS2 upregulation in pancreatic cancers is moderate, whereas ACE-2 is overexpressed in some cancers, including pancreatic carcinomas [115]. Interestingly, ACE2 upregulation seems to be associated with favorable survival in pancreatic cancer [116], and it is known that SARS-CoV-2 reduces ACE2 expression [22]. Furthermore, the above-mentioned RAGE may also participate in both pancreatic cancer development and SARS-CoV-2 infection. RAGE facilitates neutrophil extracellular trap (NET) formation in pancreatic cancer [117]. In conclusion, pancreatic cancer predisposes to an increased risk of COVID-19 and its more severe course, and coronavirus infection may contribute to pancreatic cancer.It also seems important how the COVID-19 epidemic has affected the treatment of patients with pancreatic cancer of SARS-CoV-2-independent etiology. According to the study by Pergolini et al., care of patients with pancreatic cancer can be disrupted or delayed, particularly in the context of treatment selection, postoperative course, and outpatient care [118].A separate issue is how patients after pancreatoduodenectomy respond to SARS-CoV-2 infection. A case series reported by Bacalbasa reveal that patients who develop SARS-CoV-2 infection postoperatively require re-admission in the ICU and a longer hospital stay; however, these infections are not fatal [119]. Although the analysis was performed on single cases, it is concluded that these results are an argument to perform elective oncological surgeries [119].There are also reports that chemotherapy in pancreatic cancer patients who become ill between treatment series can be successfully completed after a complete cure of the infection [120]. Guidelines for, e.g., prioritization and treatment regimens regarding pancreatic cancer treatment in the era of the pandemic, are developed and described, for example, by Catanese et al. or Jones et al. [121,122].

10. Conclusions

Evidence shows that SARS-CoV-2 infection contributes to damage within the pancreas. The mechanisms that are involved in this include but are not limited to direct cytopathic effect of SARS-CoV-2 replication and systemic and local inflammatory response [123]. At the current state of knowledge, it is certain that the virus attacks the endocrine portion of the pancreas as well as, to a much lesser extent, the exocrine portion. It has been shown that a bidirectional relationship between COVID-19 and diabetes exists; indeed, diabetes is associated with COVID-19 severity and mortality but, at the same time, patients with COVID-19 have shown new onset of diabetes [124]. SARS-CoV-2 virus infection not only directly affects glycemic levels, but also exacerbates already existing hyperglycemia through its negative impact on the functional competence of the islets of Langerhans. It cannot be excluded that the real cause of exocrine dysfunction of this gland is the negative effect of the drugs used for treatment of the infection. As the pandemic progresses, special attention should be given to the evaluation of chronic and acute pancreatic diseases, including pancreatic cancer, so that faster diagnosis enables faster implementation of treatment.

Author Contributions

Conceptualization, A.K.; investigation, U.A., M.N., A.S., P.W., P.Z. and A.K.; resources, U.A., M.N., A.S., P.W., P.Z. and A.K.; writing—original draft preparation, U.A., M.N., A.S., P.W., P.Z. and A.K.; visualization, U.A.; supervision, A.K. All authors have read and agreed to the published version of the manuscript.


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Covid infection associated with a greater likelihood of Type 2 diabetes, according to review of patient records

Authors: Lenny Bernstein – March 21, 2022 The Washington Post

People who had covid-19 were at greater risk of developing Type 2 diabetes within a year than those who managed to avoid the coronavirus, according to a large review of patient records released Monday.

The finding is true even for people who had less severe or asymptomatic forms of coronavirus infection, though the chances of developing new-onset diabetes were greater as the severity of covid symptoms increased, according to researchers who reviewed the records of more than 181,000 Department of Veterans Affairs patients diagnosed with coronavirus infections between March 1, 2020, and Sept. 30, 2021.

Their data was compared to the medical records of more than 4.1 million VA patients who were not infected during the same period and another 4.28 million who received medical care from VA in 2018 and 2019. This kind of study cannot prove cause and effect, but it showed a strong association between the two diseases.

Overall, the researchers calculated that people diagnosed with covid-19, the disease caused by the coronavirus, were 46 percent more likely to develop Type 2 diabetes for the first time or be prescribed medication to control their blood sugar. The research was released Monday in the Lancet Diabetes & Endocrinology, a medical journal.

Put another way, 2 in 100 covid patients were more likely to develop Type 2 diabetes, a condition in which the pancreas makes insufficient amounts of the hormone insulin, leaving blood sugar levels poorly controlled. Type 2 diabetes can cause damage to kidneys, nerves, blood vessels and the heart, among its other effects.

The results have implications for the more than 471 million people known to have been infected during the pandemic, nearly 80 million of them in the United States, and especially for people suffering from long-haul covid.

“For the broader public, if you’ve had covid-19, you need to pay attention to your blood sugar,” said Ziyad Al-Aly, chief of research and development at VA St. Louis Health Care System, who led the review.

Previous smaller studies and physicians who have treated covid patients have noted an apparent increase in new diabetes diagnoses associated with coronavirus infection. But Al-Aly said his review was the largest consideration of the issue and looked at the greatest length of time after the acute phase of an infection — from 31 days after infection to a median of nearly one year per patient.

VA patients tend to be older than the general population, with more White people and males. But Al-Aly said the large numbers of people involved made him confident that his findings were applicable to the public.

“The risk was evident in all subgroups,” including women, racial minorities, younger people and people with different body mass indexes, he said.

More than 99 percent of the infected VA patients developed Type 2 diabetes, as opposed to Type 1, a condition in which insulin-producing cells in the pancreas stop producing the hormone entirely. Al-Aly speculated that the cells’ reduced efficiency may be caused by inflammation, produced either by the virus itself or the body’s response to it.

“Taken together,” the researchers wrote, “current evidence suggests that diabetes is a facet of the multifaceted long covid syndrome and that post-acute care strategies of people with covid-19 should include identification and management of diabetes.”

SARS-CoV-2 infects human pancreatic β cells and elicits β cell impairment

aUTHORS: Chien-Ting Wu,1,13Peter V. Lidsky,2,13Yinghong Xiao,2,13Ivan T. Lee,3,4,5,13Ran Cheng,1,6,13Tsuguhisa Nakayama,5,7,13Sizun Jiang,3,13Janos Demeter,1Romina J. Bevacqua,8Charles A. Chang,8,9,10,11Robert L. Whitener,8Anna K. Stalder,12Bokai Zhu,3Han Chen,3

Cell Metab. 2021 Aug 3; 33(8): 1565–1576.e5.Published online 2021 May18. doi: 10.1016/j.cmet.2021.05.013 :  PMC8130512PMID: 34081912


Emerging evidence points toward an intricate relationship between the pandemic of coronavirus disease 2019 (COVID-19) and diabetes. While preexisting diabetes is associated with severe COVID-19, it is unclear whether COVID-19 severity is a cause or consequence of diabetes. To mechanistically link COVID-19 to diabetes, we tested whether insulin-producing pancreatic β cells can be infected by SARS-CoV-2 and cause β cell depletion. We found that the SARS-CoV-2 receptor, ACE2, and related entry factors (TMPRSS2, NRP1, and TRFC) are expressed in β cells, with selectively high expression of NRP1. We discovered that SARS-CoV-2 infects human pancreatic β cells in patients who succumbed to COVID-19 and selectively infects human islet β cells in vitro. We demonstrated that SARS-CoV-2 infection attenuates pancreatic insulin levels and secretion and induces β cell apoptosis, each rescued by NRP1 inhibition. Phosphoproteomic pathway analysis of infected islets indicates apoptotic β cell signaling, similar to that observed in type 1 diabetes (T1D). In summary, our study shows SARS-CoV-2 can directly induce β cell killing.Keywords: SARS-CoV-2, COVID-19, ACE2, type 1 diabetes, neuropilin 1, phosphoproteomics, apoptosis, SARS-CoV-2 spike protein, insulin, pancreatic beta cell


Coronavirus disease 2019 (COVID-19) is an ongoing pandemic infection caused by the positive-sense RNA virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (Zhu et al., 2020b). Although initial studies focused on lung injury and cardiovascular manifestations (Yang et al., 2020Zheng et al., 2020), other organ dysfunctions have been observed, notably in the kidney, pancreas, intestine, and olfactory epithelia (Fang et al., 2020Giacomelli et al., 2020Lamers et al., 2020Puelles et al., 2020). With regard to diabetes, several recent clinical studies suggested a significant increase in new-onset hyperglycemia, diabetic ketoacidosis (DKA), and diabetes in patients with COVID-19 (Chee et al., 2020Ebekozien et al., 2020Hollstein et al., 2020Naguib et al., 2021Rubino et al., 2020Singh and Singh, 2020Unsworth et al., 2020), although some studies question the statistical significance of the effect (Boddu et al., 2020). Conceptually, β cell damage could be a consequence of direct virally induced cell death or T cell autoreactivity. Therefore, the clinical association between COVID-19 and diabetes raises the first question of whether SARS-CoV-2 can infect pancreatic islet endocrine cells, particularly insulin-secreting β cells, and cause cell death or dysfunction to initiate diabetes. The binding of SARS-CoV-2 to the host cell membrane is mediated primarily by the interaction between the viral spike glycoprotein (S) and its main entry host receptor, angiotensin-converting enzyme 2 (ACE2) (Hoffmann et al., 2020). Accordingly, many recent studies have focused on analyzing the expression levels of ACE2 in pancreatic endocrine cells. Recent RNA and protein expression studies suggested low ACE2 expression levels in α, β, and δ cells in the pancreas, leading some to postulate that SARS-CoV-2 is unable to infect β cells (Arda et al., 2016Baron et al., 2016Blodgett et al., 2015Coate et al., 2020Kusmartseva et al., 2020Segerstolpe et al., 2016). However, these characterizations are incomplete, and a more direct evaluation of cellular SARS-CoV-2 tropism is needed. Here, we suggest that the clinical severity of diabetes in patients with COVID-19 may be notably influenced by showing direct viral infection of endocrine cells, particularly β cells.Go to:


Pancreatic β cells selectively express SARS-CoV-2 entry factor proteins

Recently published studies have been discordant in terms of whether the SARS-CoV-2 receptor, ACE2, is present within insulin-secreting β cells of the pancreas (Coate et al., 2020Kusmartseva et al., 2020). While technical differences can explain the discrepancies, several of the studies found low levels of ACE2 mRNA expression in pancreatic islets, leading to speculation that SARS-CoV-2 is unable to infect β cells. However, SARS-CoV-2 entry is thought to be not only mediated by ACE2 but also by transmembrane serine protease 2 (TMPRSS2), neuropilin 1 (NRP1) (Cantuti-Castelvetri et al., 2020Daly et al., 2020), and transferrin receptor (TFRC) (Tang et al., 2020). We first evaluated the mRNA expression level of ACE2TMPRSS2NRP1TFRC, and FURIN in three previously published single-cell RNA sequencing (RNA-seq) datasets (Arda et al., 2016Blodgett et al., 2015Kim et al., 2020) in order to assess their expression within the two major pancreatic islet cell populations: insulin-secreting β cells and glucagon-secreting α cells (Figures S1A–S1C). We observed that ACE2 and TMPRSS2 transcripts, while expressed at low levels, are nonetheless readily measurable within both β cells and α cells. Additionally, the transcripts of other SARS-CoV-2 entry factors, NRP1TFRC, and FURIN, are expressed abundantly in pancreatic islets. We next investigated the protein expression of these SARS-CoV-2 entry factors by co-staining ACE2 (Lee et al., 2020), TMPRSS2 (Suárez-Fariñas et al., 2021), NRP1 (Cantuti-Castelvetri et al., 2020Daly et al., 2020), and TFRC (Haberger et al., 2020) in combination with insulin (INS), a β cell marker, or glucagon (GLU), an α cell marker, in pancreatic autopsy samples from 5 non-COVID-19 donors negative for COVID-19 (by PCR test). The characteristics of these donors are summarized in Table 1 . Consistent with recent mRNA work, ACE2 and TMPRSS2 were generally expressed within β cells and α cells but at low protein levels (Figures 1 A and S1D) (Coate et al., 2020Kusmartseva et al., 2020). Strikingly, we found robust NRP1 and TFRC protein expression within β cells, but not α cells, suggesting a potential mechanism for SARS-CoV-2 tropism for β cells (Figures 1A and S1D). For orthogonal confirmation of this result, we utilized a different anti-NRP1 antibody to confirm the NRP1 expression in the pancreas and arrived at the same conclusion (Figure S2A). Pre-incubation of the anti-NRP1 and anti-TFRC antibodies with the immunizing peptides drastically reduced staining in the pancreas, further validating the specificity of the result (Figures S2B and S2C). To further explore this, we compared the differential protein expression of SARS-CoV-2 entry factors within β cells and α cells. Similar to the mRNA data, no major differences in ACE2 and TMPRSS2 protein expression were observed between β cells and α cells (Figure 1B), suggesting that the expression levels of these receptors are unlikely to be singularly responsible for a propensity for SARS-CoV-2 to infect β cells. Importantly, though, NRP1 and TFRC proteins were significantly increased in β cells as compared with α cells (Figure 1B). NRP1 and TFRC were recently found to facilitate ACE2-mediated SARS-CoV-2 entry (Cantuti-Castelvetri et al., 2020Daly et al., 2020Tang et al., 2020), whereas stable SARS-CoV-2 spike-ACE2 interactions depended on both NRP1 and TFRC. These results indicate that β cells contain the necessary molecular components for SARS-CoV-2 viral entry and that the higher expression of NRP1 and TFRC entry factors may in part explain the tropism of SARS-CoV-2 for β cells.

Table 1

Non-COVID-19 pancreatic tissue donor characteristics

DonorGenderAgeBMIDiabetesCause of deathCOVID-19
1male7826noacute cardiac arrestnegative
2male5029noadvanced cancernegative
3male8218noleft-sided cardiac failurenegative
4female8624nocombined hemorrhagic and cardiogenic shocknegative
5male8128.4noprogressing coronary insufficiencynegative

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Open in a separate windowFigure 1

SARS-CoV-2-associated receptors are expressed in pancreatic β cells

(A) Representative double immunofluorescence staining of ACE2, TMPRSS2, NRP1, and TFRC with the β cell marker, insulin (INS), and α cell marker, glucagon (GLU), in the normal human pancreas, donor 1. See Table 1.

(B) Quantification of ACE2, TMPRSS2, NRP1, and TFRC in β cells (INS +) and α cells (GLU +) from a normal pancreas. No statistically significant changes in ACE2 and TMPRSS2 expression were detected between β and α cells. NRP1 and TFRC expression was statistically significantly higher in β cells compared with α cells. Rabbit anti-NRP1 (Abcam, ab81321, 1:200) and mouse anti-TFRC (Thermo Fisher, # 13-6800, 1:200) were used for the experiments shown here.

Error bars represent mean ± SD (~10–15 islets from the pancreas of 5 non-COVID-19 donors; see Table 1). ∗∗p < 0.001, one-way ANOVA with Tukey’s post-test. Each dot represents one donor. Scale bars, 5 μm (A) and 2 μm (insets). See also Figures S1 and S2 and Table 1.

SARS-CoV-2 infects β cells ex vivo and requires NRP1

To test our hypothesis regarding the increased tropism of SARS-CoV-2 for pancreatic β cells, we isolated human islets from healthy donors and infected them with SARS-CoV-2 ex vivo. The characteristics of the islet donors are summarized in Table 2 . Two or 6 dpi, infected pancreatic islets were fixed and stained with antibodies against the SARS-CoV-2 nucleocapsid protein (NP) in combination with antibodies against cell-type-specific markers: insulin (β cells), glucagon (α cells), somatostatin (δ cells), or CD31 (endothelial cells). Interestingly, SARS-CoV-2 NP was primarily observed in insulin-positive β cells at both 2 and 6 dpi (Figures 2A, 2C, and 2D), indicating preferential infection of β cells by SARS-CoV-2. Similar results were obtained using an antibody raised against the SARS-CoV-2 spike protein (SP) (Figures 2B–2D). In contrast, the presence of SARS-CoV-2 was notably lower in other pancreatic cell types, namely α and δ cells, and endothelial cells (Figures 2A–2D). These results strongly support the increased susceptibility of human pancreatic β cells for SARS-CoV-2.

Table 2

Non-COVID-19 pancreatic islet donor characteristics

DonorGenderAgeBMIDiabetesCause of deathCOVID-19Islet RRID
5male3531.3nohead traumanegativeSAMN16191825
8male3725nohead traumanegativeUNOS ID: AHJX486
9female5327.4nocerebrovascular/strokenegativeUNOS ID: AHK2444
11female4423.8nocerebrovascular/strokenegativeUNOS ID: AIA3480
12male6225.9nohead traumanegativeSAMN17928660

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SARS-CoV-2 preferentially infects β cells of human pancreatic islets ex vivo

(A–D) Mock-treated or SARS-CoV-2-infected human pancreatic islets were stained after 2 or 6 dpi. (A) Representative double immunofluorescence staining of SARS-CoV-2 nucleocapsid protein (NP) in combination with β cell marker, insulin (INS); ɑ cell marker, glucagon (GLU); δ cell marker, somatostatin (SST); and endothelial cell marker (CD31).

(B) Representative double immunofluorescence staining of SARS-CoV-2 spike protein (SP) in combination with a similar combination of markers as (A). The nuclei were stained using DAPI (blue) as a counterstain.

(C) Quantified percentages of SARS-CoV-2 NP and SP within α, β, δ, and endothelial cells of pancreatic islets. Around 40% to 60% NP and SP staining, respectively, are present within β cells.

(D) Quantified percentages of SARS-CoV-2 NP- and SP-positive α, β, δ, and endothelial cells.

(C and D) Error bars represent mean ± SD (~500–1,000 cells were quantified from healthy isolated human islets from donors 1–5; see Table 2).

(E) Representative double immunofluorescence staining of SARS-CoV-2 NP in combination with insulin after pre-treating islets with dimethyl sulfoxide (DMSO) or 100 μM EG00229 for 1 h before infection with SARS-CoV-2. Islets were fixed at 2 dpi and stained for SARS-CoV-2 NP and β cell marker, insulin (INS). Quantification of the percentages of β cells containing NP-positive β cells (right).

Error bars represent mean ± SD (~500–1,000 cells were quantified from healthy isolated human islets from donors 10–13; see Table 2). p < 0.05, two-tailed Student’s t test. Each dot represents one donor. Scale bars, 5 μm (A, B, and E) and 2 μm (insets). See also Table 2.

Given the selectively high expression of NRP1 in β cells, we hypothesized that inhibition of NRP1 would be sufficient to block infection, even if other co-receptors were important. It has been shown that the treatment of the small molecule EG00229, a selective NRP1 antagonist, reduced the efficiency of SARS-CoV-2 infection in vitro (Daly et al., 2020). Here, we also found that incubation of ex vivo pancreatic islets with EG00229 notably reduced the efficiency of SARS-CoV-2 infection (Figure 2E). This result supports a critical role of NRP1 protein in the increased tropism of SARS-CoV-2 for pancreatic β cells. Additional studies will be needed to further establish the relationship between levels of NRP1 and the levels of other viral receptors and the efficiency of infection.

SARS-CoV-2 infects β cells in subjects with COVID-19

Next, we determined whether SARS-CoV-2 tropism for β cells is also observed in patients with COVID-19. We obtained pancreatic autopsy samples from 9 patients who died from severe COVID-19-related complications. The characteristics of these patients are summarized in Table 3 . Histological analysis revealed lipomatosis, fibrosis, or autolysis in some of the samples, whereas acute or chronic pancreatitis was not observed in any patient (Table 1), tending to exclude that broad pancreatic damage is a universal feature. The pancreas of 7 out of 9 of these patients had SARS-CoV-2 viral positivity as measured by RT-PCR. We observed SARS-CoV-2 NP staining selective to insulin-positive β cells in 4 of 7 patients, while the remaining 3 pancreatic samples and healthy control samples were negative for NP staining (Figure 3 A). The specificity of the anti-NP antibody was validated through peptide blocking assays (Figure S2D). The 3 negative samples (staining not shown) from patients with COVID-19 had extensive autolysis/atrophy (Table 3), which may explain the lack of NP signal due to rapid proteolysis of tissue by digestive enzymes. As an orthogonal confirmation of our observations of viral presence in β cells, we performed in situ hybridization (ISH) using a validated SARS-CoV-2 spike mRNA probe in combination with an antibody targeting insulin on the four positive SARS-CoV-2-infected human pancreatic tissues (see Figures S3A and S3B for SARS-CoV-2 probe validation) (Lee et al., 2020). Similar to the NP staining results, SARS-CoV-2 spike transcripts were detected in β cells of these autopsied pancreatic islets (Figure 3B). These results confirm SARS-CoV-2 tropism for β cells, supporting a model in which SARS-CoV-2 infects and replicates in β cells to induce pancreatic dysfunction, thus leading to hyperglycemia or diabetes.

Table 3

COVID-19 patient characteristics, pancreas viral load, percentage of NP+ islets, and histological analysis

PatientAgeBMIDiabetesViral load PCR (mean)Ct values (ORF, S, N)NP-positive islets (%)Histological analysis
16735no2933/32/354well preserved, mild fibrosis
28526type II10835/35/3531mild fibrosis, lipomatosis, and autolysis
39523no2434/33/335well preserved, lipomatosis, and mild fibrosis
47124no1535/35/indet12mild lipomatosis and autolysis
58828no631/32/320extensive atrophy, lipomatosis, and moderate fibrosis
68530no1138/37/360extensive autolysis
75847no1638/35/360extensive autolysis
86629noindeterminateindeterminate0mild lipomatosis, fibrosis, autolysis
95430noindeterminateindeterminate0extensive autolysis

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Pancreatic autopsies were obtained from 9 patients who died from COVID-19-related complications. The pancreas of 7 out of 9 of these patients had SARS-CoV-2 viral positivity by RT-PCR. Ct values of RT-PCR targeting three different SARS-CoV-2 genomic regions (ORF1ab, spike [S], and nucleocapsid [N]) are shown. Ct values of the pancreas from patients 8 and 9 were between 37 and 40 and therefore considered “indeterminate” and not positive. The percentages of the nucleocapsid (NP)-positive islets by immunofluorescence staining as described in the manuscript are also shown for each patient sample. Pancreas from patients 5–7 did not have NP positivity, possibly due to extensive autolysis/atrophy. Histological analysis was performed by a board-certified pathologist (M.S.M.).

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Open in a separate windowFigure 3

SARS-CoV-2 infects pancreatic β cells of patients with COVID-19

(A) Representative double immunofluorescence staining of pancreatic islets from patients with COVID-19 and healthy controls using antibodies against SARS-CoV-2 NP and INS.

(B) Representative multiplexed images of in situ hybridization against the SARS-CoV-2 spike mRNA, in combination with immunofluorescence staining of insulin (INS). SARS-CoV-2 spike mRNA expression (red dots) was detected within pancreatic β cells. The nuclei were stained using DAPI (blue) as a counterstain.

Scale bars, 5 μm (A and B) and 2 μm (insets). See also Figure S3 and Table 3.

We next investigated whether ACE2 and NRP1 are differentially expressed in the pancreatic β cells of patients with COVID-19 compared with non-COVID-19 donors as a potential explanation for why β cells are more susceptible to viral infection. ACE2 expression remained low in individuals with COVID-19 with no statistically significant difference compared with non-COVID-19 donors (Figures S3C and S3D). Conversely, NRP1 expression is upregulated in patients with COVID-19 compared with non-COVID-19 donors (Figures S3C and S3D). These results support a potential role of NRP1 in β cell susceptibility of viral infection. However, it is also possible that this is due to the increased NRP1 expression in the organ caused by SARS-CoV-2 infection, which in turn causes the cells to be more susceptible to infection. Further research is needed to establish the generality and mechanism by which SARS-CoV-2 may require either (1) preexisting or (2) virally induced upregulation of NRP1 levels.

SARS-CoV-2 infection suppresses insulin secretion and kills β cells ex vivo

To determine whether SARS-CoV-2 infection affected pancreatic islet function, we quantified the insulin content and glucose-stimulated insulin secretion (GSIS), a functional assay for β cell insulin release, in infected islets. We observed a dramatic decrease in insulin content and GSIS in SARS-CoV-2-infected human islets, compared with mock-treated islets (Figures 4A and 4B). Notably, this effect is partially reversed upon treatment with the NRP1 antagonist EG00229 (Figure S3E). In type 1 diabetes (T1D), virus-induced β cell damage can be a result of either virus-triggered cell death or immune-mediated loss of infected pancreatic β cell mass. Previous reports of SARS-CoV-1/2-induced apoptosis in ACE2-expressing A549 and Vero E6 cells (Diemer et al., 2008Li et al., 2020Zhu et al., 2020a) suggested a similar mechanism of virus-mediated cell death in pancreatic β cells ex vivo. To this end, we performed the terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay on SARS-CoV-2-infected human islets 6 dpi. TUNEL signal was significantly increased in infected β cells, compared with mock-infected β cells (Figures 4C and 4D). Since SARS-CoV-2 also infects a small number of other cells, such as α cells, a population that accounts for the second-largest number of cells in the islet, we next investigated whether SARS-CoV-2 infection can cause apoptosis of α cells (Figure S3F). The increased TUNEL signal in infected α cells suggests that viral infection-induced cell death was agnostic to cell type, although the percentage of β cells undergoing apoptosis was higher due to higher susceptibility. SARS-CoV-2 spike protein treatment was sufficient to induce apoptosis in β cells, as indicated by an increase in TUNEL signal (Figures 4E and 4F). This observation is consistent with past findings that SARS-CoV-1 SP can induce apoptosis in Vero E6 cells (Chow et al., 2005). Altogether, these results support a model in which SARS-CoV-2-induced β cell apoptosis leads to dysregulation in insulin production and secretion.

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Figure 4

SARS-CoV-2 infection interferes with insulin content/secretion and induces β cell apoptosis

(A–F) Pancreatic islet functionality was analyzed by insulin content, glucose-stimulated insulin secretion (GSIS), and TUNEL staining ex vivo.

(A) Insulin content is decreased in SARS-CoV-2-infected islets compared with mock-treated islets.

(B) GSIS is decreased in SARS-CoV-2-infected islets compared with mock-treated islets.

(A and B) Error bars represent mean ± SD (data were collected from 7 healthy isolated human islets, donors 2–8; see Table 2). p < 0.05, two-tailed Student’s t test.

(C) Representative staining of β cell apoptosis by in situ TUNEL and DAPI staining in β cells (INS) of mock- or SARS-CoV-2-treated human islets. DNase-treated sections were used as a positive control in the TUNEL assay.

(D and F) Quantification of the percentages of islets containing TUNEL-positive β cells. Error bars represent mean ± SD (~500–1,000 cells were quantified from each of 3–5 separate healthy isolated human islets, donors 1–5 [D] and 7–9 [F]; see Table 2).

(E) Representative staining of β cell apoptosis by in situ TUNEL and DAPI staining in β cells (INS) of mock-treated versus SARS-CoV-2-SP-treated human islets.

p < 0.05, ∗∗p < 0.01, two-tailed Student’s t test. Scale bars, 5 μm (C and E). See also Figures S3–S5 and Tables 2S1S2, and S3.

Given the central role of regulatory kinases in the control of apoptosis, we next asked whether the binding of SARS-CoV-2 to its receptors is sufficient to trigger apoptosis-related signaling pathways independent of additional cellular stress as a result of viral infection and replication. We first leveraged assaying global phosphoproteomics to determine potential kinase regulatory roles of the SARS-CoV-2 SP, which directly binds the viral receptors. Isolated human islets were incubated with SARS-CoV-2 SP from SARS-CoV-2 for 15 or 30 min in parallel with vehicle control treatment. Cells were then harvested, and extracts were prepared for phosphoproteomic mass spectrometry and analysis of signaling (Figure S4A). We employed a substrate-based kinase activity prediction model to determine the activity levels of specific kinases from this large-scale phosphoproteomic data. This analysis is based on the underlying assumption that the activity levels of upstream kinases can be inferred through the measured abundance of known downstream target phosphorylation events (Hernandez-Armenta et al., 2017). Using kinase set enrichment analysis (KSEA) (Drake et al., 2012Ochoa et al., 2016), we were able to assign an enrichment score (ES) value (weighted Kolmogorov-Smirnov statistic; STAR Methods) to each kinase to reflect its activity in a manner analogous to that of gene set enrichment analysis (GSEA) (Subramanian et al., 2005). Differential expression of phosphosites in the 15- and 30-min SARS-CoV-2 SP-treated human islets was calculated by comparing them to vehicle control, and KSEA was performed using a kinase-substrate database created using PhosphoSitePlus (Hornbeck et al., 2015) and NetworKin (Linding et al., 2008).

Quantification of the activity of 67 kinases (Figure S4B; Tables S1 and S2) revealed an upregulation of stress-response MAP kinases, including JNK/p38 (MAPK8/11) (Wada and Penninger, 2004) and cytoskeleton reorganizing p21-activated kinases (PAK) (Manser et al., 1994), which are two classic pathways triggering cell death by the apoptosis pathways. Additionally, multiple members of the protein kinase C (PKC) family were downregulated in response to SARS-CoV-2 SP treatment. Through pathway analysis using gene ontology (GO) biological process over-representation analysis (ORA), apoptosis emerged as a recurring top hit (Figures S4C and S5A–S5D; Table S3) as early as 30 min post-SARS-CoV-2 spike protein incubation. Apoptotic kinases, including PAK, were upregulated, as was activation of GSK3β and the proapoptotic kinase JNK1, both previously linked to apoptosis in β cells (Dhanasekaran and Reddy, 2008Guo et al., 2016Tournier et al., 2000) (Figures S5E–S5I).

To understand whether the same pathways were activated by a viral infection, we repeated the phosphoproteomics analysis on cells infected with SARS-CoV-2 (24 h post-infection) to measure the activity levels of specific kinases triggered by the virus. As with SARS-CoV-2 SP treatment, we also observed upregulation of JNK and PAK in SARS-CoV-2-infected islet cells (Figure S4B). As before, GO analysis pointed to apoptosis and programmed cell death as the most significantly enriched categories (Figure S4D). To validate that JNK and PAK are indeed activated in virus-infected islets, we co-stained phosphorylated JNK1/2 (pJNK1/2) and phosphorylated PAK1/2 (pPAK1/2) in combination with the SARS-CoV-2 SP in infected pancreatic islets. Our results confirm that pJNK1/2 and pPAK1/2 were primarily observed in SARS-CoV-2 SP-positive cells at 24 h post-infection (Figure S4E), confirming that the SARS-CoV-2 infection induces the activation of JNK and PAK. The kinase activities induced by SARS-CoV-2 SP and SARS-CoV-2 infection support a mechanism through which SARS-CoV-2 induces apoptosis via the JNK-MAPK apoptosis pathway, allowing a potential window for therapeutic intervention.Go to:


Emerging clinical reports have noted a significant increase in new-onset hyperglycemia, DKA, and diabetes in patients with COVID-19. Understanding how SARS-CoV-2 affects the normal function of the pancreas is an urgent unmet need with fundamental healthcare implications. In this study, we discovered that SARS-CoV-2 preferentially infects β cells in isolated human pancreatic islets ex vivo and in patients who succumbed to COVID-19. Building on recent studies that identified low-level ACE2 expression in pancreatic islets (Fignani et al., 2020Kusmartseva et al., 2020), we observed that ACE2 as well as TMPRSS2 are indeed modestly expressed in β cells. Importantly, we uncover the selective expression of other critical SARS-CoV-2 entry factors, NRP1 and TFRC, in β cells. We propose that this enrichment of NRP1, and possibly TFRC, is a potential mechanism underlying SARS-CoV-2 tropism for β cells. Further studies incorporating more robust reagents, such as well-validated antibodies, will be needed to better understand the additional roles of other factors implicated in SARS-CoV-2 entry, including TMPRSS4, Furin, and heparan sulfate (Clausen et al., 2020). Heparan sulfate, in particular, has been shown to be highly expressed in pancreatic β cells and plays an important role in regulating β cell survival (Simeonovic et al., 2018Ziolkowski et al., 2012) and would be another leading candidate in determining SARS-CoV-2 tropism for β cells.

Of note, while we found SARS-CoV-2 localization within β cells from 4 autopsied patients, SARS-CoV-2 NP was not detected in pancreatic islets from 3 autopsied patient samples from a separate report (Kusmartseva et al., 2020). This discrepancy is likely due to the issue that pancreatic tissues are highly prone to autolysis, resulting in the rapid proteolysis of proteins due to the abundance of digestive enzymes. Indeed, we also did not detect SARS-CoV-2 NP signal in 3 out of 7 pancreas tissues with extensive pathologist-verified autolysis/atrophy, further suggesting the importance of rapid tissue preservation and documentation during COVID-19 autopsies. For these samples, we were able to confirm viral genomic expression by ISH in β cells as evidence of viral infection. Finally, we showed that SARS-CoV-2 infection leads to dysregulation of insulin homeostasis, induction of apoptosis-associated signaling pathways, along with cell apoptosis, mainly in β cells. These key observations support a mechanism through which SARS-CoV-2 can directly drive β cell damage to cause clinical T1D linked to hyperglycemia. These effects of the virus are not mutually exclusive with the possibility that SARS-CoV-2 can also induce autoimmune-mediated β cell destruction and is the subject of further investigation. Nonetheless, at least our microscopic histological observations do not suggest ongoing insulitis. Additional limitations of our study are the small sample size of pancreas samples from patients with COVID-19 and the lack of pancreas from children due to challenges in procuring these tissues. Moreover, since we utilized the pancreas from patients who succumbed to severe COVID-19, we are unable to generalize the SARS-CoV-2 β cell tropism to all patients with COVID-19, particularly those with mild COVID-19 due to the invasiveness of such a biopsy. Indeed, only a minority of patients with COVID-19 develop hyperglycemia, DKA, or T1D (Chee et al., 2020Ebekozien et al., 2020Hollstein et al., 2020Naguib et al., 2021Rubino et al., 2020Singh and Singh, 2020Unsworth et al., 2020).

Although we identify a mechanism explaining β cell-selective cell death, many details of how the virus migrates to the pancreas in patients with severe COVID-19 remain unclear. We suspect that following the initial infection of the upper airway and secondary expansion of the virus to the lungs, viral particles can be taken up by the vasculature and propagated to vascularized organs including the pancreas, kidney, and brain. From there, the route of vascular exit and viral entry to the tissue itself may require additional steps or preconditions to favor viral attack of secondary tissues like the pancreas. It would be of value to evaluate patient records to determine the time of onset of COVID-19-induced pneumonia, marking severe lung infection, compared with the evolution of hyperglycemia as a marker of pancreatic damage and a diabetes-like effect on insulin secretion.

While this manuscript was under review, Müller and colleagues (Ulm University Medical Center, Germany) reported that SARS-CoV-2 infects human pancreatic endocrine cells ex vivo and in vivo and interferes with β cell functions ex vivo (Müller et al., 2021). While the general findings are similar to ours, there are some important key discrepancies. First, inconsistent with previous studies, these authors found that ACE2 and TMPRSS2 expression are higher in β cells than ɑ and δ cells. We and others found that ACE2 and TMPRSS2 expression are low in islets (Figure 1) (Coate et al., 2020Kusmartseva et al., 2020) both at the mRNA and protein levels. Furthermore, we identified the expression of two other SARS-CoV-2 entry receptors, NRP1 and TFRC, to be higher in β cells than ɑ cells (Figure 1). NRP1 expression, and not ACE2, was found to be upregulated in patients with COVID-19 compared with non-COVID-19 donors (Figure S3). Treatment of human islets with an NRP1 inhibitor reduces infection by SARS-CoV-2 and partially rescues GSIS in the islets, showing the critical role of NRP1 for enabling SARS-CoV-2 infection. Second, although the authors confirmed that SARS-CoV-2 infects β cells by staining pancreatic tissue sections from COVID-19 autopsies, the authors did not find β cells to be selectively infected by the SARS-CoV-2, but rather a large number of endocrine cells were infected in isolated islets. In contrast, we found that β cells are more susceptible to SARS-CoV-2 infection. Finally, the authors measured apoptosis via cleaved caspase-3 staining at 3 dpi and found no increased apoptosis in infected islets at 3 dpi. Our results indicate a significant increase in apoptotic β cells in infected islets at 2 and 6 dpi (Figure 4). This is further confirmed through phosphoproteomic analysis and subsequent identification of the specific upregulated kinases involved in apoptotic processes in isolated pancreatic islet post-SARS-CoV-2 SP treatment or virus infection (Figures S4 and S5).

There are a number of variations between our studies, one of which is the source of the SARS-CoV-2 used. Although we used the same SARS-CoV-2 D614G variant, the source is quite different. The clinically isolated virus used by Müller et al. originated from the Amsterdam University, Netherlands (010V-03903), while the clinical virus strain used in this paper was from UCSF, United States (CA-UCSF-0001C). Further studies are required to determine whether these different virus strains may affect pathological outcomes. In addition, our source of human islets is different. Our human islets are from patients of United States origin and may reflect different ethnicities. Given the scale of the ongoing epidemic, our findings emphasize the urgent need for the development of therapies to prevent COVID-19-induced diabetes, here informed through a combination of ex vivo tissue culture models, retrospective autopsy samples, and unbiased phosphoproteomic analysis.

Limitations of study

There are expected limitations to this study. First, the localization and quantification of pancreatic ACE2, TMPRSS2, NRP1, and TFRC are largely based on ex vivo and in situ analyses of protein (IHC and IF) expression in pancreatic tissues from a limited cohort of healthy or COVID-19 subjects. The histological analysis of these pancreatic tissue sections can only provide approximate predictions for ACE2, TMPRSS2, NRP1, and TFRC protein expression in isolated islets and islet cells and a general signature for their susceptibility to in vitro SARS-CoV-2 infection. This limitation is improved by our ability to infect human islet ex vivo and reconstitute several critical aspects of viral infection and pathogenesis, increasing our confidence in the results. For this study, we could not directly translate our ex vivo observations of the dramatic decrease in insulin content and GSIS in SARS-CoV-2-infected human islets to the COVID-19 clinical samples in this study, as the insulin and blood glucose levels of these patients were not measured. Additional studies correlating patient serum markers of islet secretion of insulin, glucose levels, and COVID-19 status would be of considerable benefit to better understand virus effects on patients with typical versus severe COVID-19 disease.

Finally, phosphoproteomics was performed across the entire population of islet cell types, since single-cell phosphoproteomics is currently technically challenging. Therefore, we are unable to deconvolute any diversity of signaling pathways caused by the treatment of SARS-CoV-2 SP or SARS-CoV-2 infection in individual cell types in this study. Given the measured selectivity of infection in β cells and preponderance of β cells, we can reasonably estimate that the strong effects we observe reflect β cell alterations, rather than bystander effects.Go to:


Key resources table

Rabbit anti-SARS-CoV-2-NPGeneTexCat# GTX135361; RRID: AB_2887484
Mouse anti-SARS-CoV-2-NPThermo FisherCat# MA1-7403; RRID: AB_1018420
Mouse anti-SARS-CoV-2-SPGeneTexCat# GTX632604; RRID: AB_2864418
Rabbit anti-ACE2AbcamCat# ab15348; RRID: AB_301861
Mouse anti-TMPRSS2MilliporeCat# MABF2158
Mouse anti-NRP1Santa CruzCat# sc-5307; RRID: AB_2282634
Rabbit anti-NRP1AbcamCat# ab81321; RRID: AB_1640739
Rabbit anti-NRP1AtlasCat# HPA030278; RRID: AB_10601976
Mouse anti-TFRCThermo FisherCat# 13-6800; RRID: AB_2533029
Rabbit anti-TFRCAtlasCat# HPA028598; RRID: AB_10601599
Mouse anti-InsulinCell SignalingCat# 8138S; RRID: AB_10949314
Mouse anti-InsulinSanta CruzCat# sc-8033; RRID: AB_627285
Rabbit anti-glucagonProteinTechCat# 15954-1-AP; RRID: AB_2878200
Mouse anti-glucagonAbcamCat# ab10988; RRID: AB_297642
Mouse-somatostatinSanta CruzCat# sc-55565; RRID: AB_831726
Mouse-somatostatinSanta CruzCat# sc-74556; RRID: AB_2271061
Mouse anti-CD31BDCat# 550389; RRID: AB_2252087
Mouse anti-CD31NovusCat# NBP2-47785; RRID: AB_2864381
Rabbit anti- Phospho-JNK1/2Cell SignalingCat# 4668T
Rabbit anti- Phospho-PAK1/2Cell SignalingCat# 2601S; RRID: AB_330220
Bacterial and virus strains
SARS-CoV-2Joe DeRisi Lab, UCSFSARS-CoV-2/human/USA/CA-UCSF-0001C/2020
Biological samples
Human pancreatic isletsIntegrated Islet Distribution Program (IIDP)Table 2
Chemicals, peptides, and recombinant proteins
DMSOSigma-AldrichCat# 276855
EG00229Sigma-AldrichCat# SML1367
DAPIBio TrendCat# 40043
Pen/StrepThermo FisherCat# 15140163
ParaformaldehydeAlfaAesarCat# 433689M
Normal Donkey SerumJackson ImmunoResearchCat# 017-000-121
NP40SigmaCat# 11332473001
The unrelated mock peptide: KKHKNQRSRKKHKNQRSRGenscriptN/A
The NRP1 peptide for blocking assayAbcamCat# ab189308
The TFRC peptide for blocking assay: DQARSAFSNLFGGEPLSYTRFSLARQGenScriptN/A
The SARS-CoV-2 NP peptide for blocking assay: STGSNQNGERSGARSKGenScriptN/A
BSASigmaCat# A6003-25G
1X PBSCorningCat# 46-013-CM
Triton X-100USBCat# 22686
OCT compoundVWRCat# 25608-930
SaponinSigma-AldrichCat# S7900
Fluoromount-GSouthernBiotechCat# 0100-01
Dako Target Retrieval Solution, pH 9DAKO AgilentCat# S236784-2
ProLong Gold Antifade mounting medium with DAPIThermo FisherCat# P36931
HoechstThermo FisherCat# 33342
GlutaMaxlifeCat# 35050-079
Critical commercial assays
Human insulin ELISA kitMercodiaCat# 10-1113-01
In Situ Cell Death Detection Kit, TMR redSigma-AldrichCat# 12156792910
TaqMan 2019-nCoV Control Kit v1Thermo FisherCat# A47533
RNAscope Multiplex Fluorescent Reagent Kit v2Bio-TechneCat# 323100
TSA Cyanine 3Akoya BiosciencesCat# NEL744001KT
High-Select Fe-NTA Phosphopeptide Enrichment KitThermo ScientificCat# A32992
Deposited data
RNA-seq data for FACS purified human alpha and beta cells (Blodgett et al., 2015)NCBI Gene Expression OmnibusGEO: GSE67543
RNA-seq data for FACS purified human alpha and beta cells (Arda et al., 2016)NCBI Gene Expression OmnibusGEO: GSE57973
RNA-seq data for FACS purified human alpha, beta, and delta cells (Kim et al., 2020)NCBI Gene Expression OmnibusGEO: GSE143889
Phosphoproteomics data of SARS-CoV-2 infected and Spike protein treated human pancreatic isletsThis paperPRIDE: PXD025629
SARS-CoV-2 spike mRNABio-TechneCat# 848561
Software and algorithms
Zen blackCarl Zeiss

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Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Peter Jackson (

Materials availability

This study did not generate new unique reagents.

Data and code availability

The analysis code used to support the findings of this study are available at

Experimental model and subject details

Human pancreas tissue collection

De-identified human pancreatic islets were obtained from adult organ donors without a history of diabetes or glucose intolerance. Islets were procured through the Integrated Islet Distribution Program, Alberta Diabetes Institute IsletCore, and the International Institute for the Advancement of Medicine. SARS-CoV-2 infected pancreas tissue was obtained during autopsy and processed as previously described (Menter et al., 2020); the procedure was approved by the ethics commission of Northern Switzerland (EKNZ; study ID: 2020-00969). All patients with COVID-19 or their relatives consented to the use of tissue for research purposes. The characteristics of the autopsy and islet donors are summarized in Tables 1​,2,2, and ​and33.

Method details

Virus production, islet infection, and drug treatment

A549 cells stably expressing ACE2 under CMV promoter were infected with SARS-CoV-2 clinical isolate of the pandemic D614G variant (SARS-CoV-2/human/USA/CA-UCSF-0001C/2020, kindly provided by Sara Sunshine and Joe DeRisi) with MOI ~0.05 in MEM medium supplemented with 2% FBS and penicillin/streptavidin (Gibco). 3 days after infection, the medium was collected and cleared from cell debris by centrifugation at 3,000 g for 10 min at 4 C. The virus titers were measured by plaque assay. To infect the islets, 100 ul of virus suspension (5-10×106 PFU per ml) was added to 1 ml of the pancreatic islet culture and incubated at 37°C for the indicated time. Small molecules were dissolved in DMSO (276855, Sigma-Aldrich). Islets were first treated with 100 μM EG00229 (SML1367, Sigma-Aldrich) or DMSO for 1 hour before infection with SARS-CoV-2. Islets were fixed at 2 dpi.

Immunofluorescence immunohistochemistry (IF IHC) of cryosections

For cryosections, isolated human islets were fixed in 4% paraformaldehyde in 1X PBS for 1 h, embedded in collagen I (Becton-Dickinson, San Jose, CA, USA) 4% (wt/vol.) and then fixed on ice in 4% paraformaldehyde in 1X PBS for another 20 min, followed by three 5 min washes with 1X PBS and equilibration in 30% sucrose/1X PBS overnight. Tissue specimens were processed for OCT-embedded, 6-μm cryosections.

Cryosections were blocked with 5% normal donkey serum (017-000-121, Jackson ImmunoResearch) in IF buffer (3% BSA and 0.4% saponin in PBS; for all else: 3% BSA and 0.1% NP-40 in PBS) at room temperature for 1 hour. Samples were incubated with primary antibody in IF buffer at room temperature for overnight at 4°C, followed by 5 washes with IF buffer. Samples were then incubated with fluorescent-labeled secondary antibody at room temperature for 1 hour, followed by a 5 min incubation with 4’,6-dia-midino-2-phenylindole (DAPI) in PBS at room temperature for 5min and 3 washes with IF buffer. Coverslips were mounted with Fluoromount-G (0100-01, SouthernBiotech) onto glass slides followed by image acquisition.

Immunofluorescence immunohistochemistry (IF IHC) of FFPE sections

Sections were cut to 4 μm thickness onto frosted glass slides at the Stanford University Histology Service Center and University Hospital Basel. H&E-stained sections were obtained from each formalin-fixed paraffin-embedded (FFPE) block. Deparaffinization, rehydration, and heat-induced epitope retrieval (HIER) were performed on a ST4020 small linear stainer (Leica). For deparaffinization, slides were baked at 70 °C for 1 h, followed by rehydration in descending concentrations of ethanol (100% twice, 95% twice, 80%, 70%, ddH2O twice; each step for 3 min). Washes were performed using a Leica ST4020 Linear Stainer (Leica Biosystems, Wetzlar, Germany) programmed to three dips per wash for 30 s each. HIER was performed in a Lab VisionTM PT module (Thermo Fisher) using Dako Target Retrieval Solution, pH 9 (S236784-2, DAKO Agilent) at 97 °C for 10 min and cooled down to 65 °C. After further cooling to room temperature for 30 min, slides were washed for 5-10 min three times in Tris-Buffered Saline (TBS), containing 0.1% Tween 20 (Cell Marque; TBS-T). Sections were then blocked in 5% normal donkey serum ((D9663, Sigma-Aldrich) in TBS-T at room temperature for 1 h, followed by incubation with primary antibodies in the blocking solution. After one overnight incubation of primary antibodies in 4 °C, sections were washed three times with TBS-T and stained with the appropriate secondary antibodies in PBS with 3% bovine serum albumin, 0.4% saponin, and 0.02% sodium azide at room temperature for 1 h. Following this, sections were washed three times with TBS-T and mounted with ProLong Gold Antifade mounting medium with DAPI (Invitrogen). Hoechst (33342, Thermo) was also used in the second to last TBS-T wash for additional nuclear staining. For the peptide blocking assay, the NRP1 (Abcam, ab81321), TFRC (Thermo, # 13-6800), and SARS-CoV-2 NP (GeneTex, GTX135361) antibodies were preincubated with a 20-fold molar excess of the immunizing peptide or an unrelated mock peptide for 3 hours with rotation at room temperature immediately before primary antibody staining. The peptides used are described below.


For detection of SARS-CoV-2, RNA was first isolated from formalin-fixed and paraffin embedded pancreas tissue by using the Maxwell RSC RNA FFPE Kit (Promega, Madison, WI, USA) according to the manufacturer’s protocol. Afterwards, TaqMan reverse transcription polymerase chain reaction (RT-PCR) was performed by using the TaqMan 2019-nCoV Control Kit v1 (A47533, ThermoFisher Scientific) to target three different viral genomic regions (ORF1ab, S and N) and the human RPPH1 gene (RNAse-P). According to the manufacturer’s protocol, a Cт value below 37 in at least two out of three viral genomic regions was considered positive. A case was considered negative if Cт values were above 40. Values between 37 and 40 were considered indeterminate and the assay was repeated. Samples were always run as duplicates.

Antibodies and reagents

Antibodies used include the following: rabbit anti-SARS-CoV-2-NP (GeneTex, GTX135361, 1:2,000), mouse anti-SARS-CoV-2-NP (Thermo Fisher, MA1-7403, 1:200), mouse anti-SARS-CoV-2-SP (GeneTex, GTX632604, 1:500), rabbit anti-ACE2 (Abcam, ab15348, 1:200), mouse anti-TMPRSS2 (Millipore, MABF2158, 1:200), mouse anti-NRP1 (Santa Cruz, sc-5307, 1:200), rabbit anti-NRP1 (Abcam, ab81321, 1:200), rabbit anti-NRP1 (Atlas, HPA030278, 1:200), mouse anti-TFRC (Thermo Fisher, # 13-6800, 1:200), rabbit anti-TFRC (Atlas, HPA028598, 1:200), mouse anti-Insulin (Cell Signaling, 8138S, 1:4,000), mouse anti-Insulin (Santa Cruz, sc-8033, 1:1,000), rabbit anti-glucagon (ProteinTech, 15954-1-AP, 1:3,000), mouse anti-glucagon (Abcam, ab10988, 1:4,000), mouse-somatostatin (Santa Cruz, sc-55565, 1:6,000), mouse-somatostatin (Santa Cruz, sc-74556, 1:2,000), mouse anti-CD31 (BD, 550389, 1:100), mouse anti-CD31 (Novus, NBP2-47785, 1:200), rabbit anti- Phospho-JNK1/2 (Cell Signaling, 4668T, 1:100), and rabbit anti- Phospho-PAK1/2 (Cell Signaling, 2601S, 1:100). Spike protein (BPS Bioscience, 100688) was used in the apoptosis experiment in Figures 4E and 4F. The immunizing peptides for the peptide blocking assay were NRP1 (Abcam, ab189308), TFRC (custom synthesized through GenScript using sequences provided in confidence by Thermo Fisher), and SARS-CoV-2 NP (custom synthesized through GenScript using sequences provided in confidence by GeneTex). The sequence of the unrelated mock peptide used for the peptide blocking assay was KKHKNQRSRKKHKNQRSR (Genscript).

In situ hybridization staining

Rehydration and HIER of tissue sections were performed as described above and in Lee et al. (2020). After cooling to room temperature, slides were washed for 2 × 2 min ddH2O before a 15 min H2O2 block at 40 °C (322335, Bio-Techne). Slides were then washed for 2 × 2 min ddH2O before an overnight hybridization at 40 °C with probes against the SARS-CoV-2 spike mRNA (848561, Bio-Techne). Amplification of the ISH probes was performed the next day according to manufacturer’s protocol (323100, Bio-Techne), with the final deposition of Cyanine 3 for SARS-CoV-2 spike mRNA probe targets (NEL744001KT, Akoya Biosciences). Slides were then processed as described above for IF IHC staining for mouse anti-insulin (Cell Signaling, 8138S, 1:4000).


Fluorescence-immunolabeled images were acquired using a Zeiss AxioImager Z1 microscope or a Marianas spinning disk confocal (SDC) microscopy (Intelligent Imaging Innovations). Post-imaging processing was performed using ZEN (Carl Zeiss). Final figures were organized using Adobe Illustrator.

In vitro insulin secretion assays

GSIS was performed 6 days post infection. Batches of 25 islets were used for in vitro secretion assays. Islets were incubated at a glucose concentration of 2.8 mM for 1 h as an initial equilibration period. Subsequently, islets were incubated at 2.8 mM glucose concentration for 1 h. Supernatant was taken and stored for insulin quantification. Islets were incubated at 16.7 mM glucose concentration for another 1 h. Supernatant was taken and stored for insulin quantification. Islets were then lysed in an acid-ethanol solution (1.5% HCL in 75% ethanol) to extract the total cellular insulin or glucagon content. Secreted human insulin in the supernatants and islet lysates were quantified using a human insulin ELISA kit (Mercodia). Secreted insulin levels were divided by total insulin content and presented as a percentage of total insulin content and normalized to values obtained at 2.8 mM glucose. All secretion assays were carried out in RPMI 1640 (Gibco) and the above-mentioned glucose concentrations.

TUNEL staining

Cellular apoptosis was measured by TUNEL staining according to the manufacturer’s instructions (Roche, Berlin, Germany). The proportion of TUNEL-positive nuclei in pancreatic β cell was determined through image analysis of the cryosections. The number of TUNEL-positive cells in pancreatic islets was counted under an Everest deconvolution workstation (Intelligent Imaging Innovations) equipped with a Zeiss AxioImager Z1 microscope and a CoolSnapHQ cooled CCD camera (Roper Scientific).

Phosphopeptide shotgun proteomics

Isolated human islet cells were treated with SARS-CoV-2 spike protein for 15, 30 minutes or with vehicle (water) for 30 minutes. Cells were harvested, lysed, reduce, and alkylated using 100 μl of lysis buffer (6M Guanidine Hydrochloride, 100 mM Tris-HCl pH 8.0, 10 mM TCEP, 10 mM CAA) and boiled 60°C for 1 hour. Proteins were precipitated by adding 100 μl methanol, vortexed, 50 μl chloroform, vortexed, 100 μl water, vortexed, and centrifuged at 13,000g for 2 minutes. The top aqueous layer was removed, 200 μl of methanol was added, vortexed, and centrifuged at 13,000g for 3 minutes. Methanol was removed and dried proteins were resuspended using 200mM HEPES pH 8.5. Proteins were digested using Trypsin/Lys-C overnight at 37°C 250 RPM. Sample was acidified using TFA and cleaned using stage tips. Stage tips were created using 5 layers of C18 filters packed into a P200 tip. The stage tips were activated using methanol, equilibrated twice with equilibration buffer (5% ACN, 0.5% TFA). Sample were bound, washed twice with equilibration buffer, and eluted using elution buffer (50% ACN, 0.1% FA). Eluted samples were dried using a Speed-Vac and resuspended using Binding/Wash Buffer in High-Select Fe-NTA Phosphopeptide Enrichment Kit (Thermo Scientific, A32992). The peptides were enriched for phosphopeptides according to the manufacturer’s instructions. Eluted samples were eluted and resuspended using Solution A (2% ACN, 0.1% FA).

Samples were analyzed using the timsTOF Pro (Bruker Daltonics) (Meier et al., 2018), an ion-mobility spectrometry quadrupole time of flight mass spectrometer. Specifically, a nanoElute (Bruker Daltonics) high pressure nanoflow system was connected to the timsTOF Pro. Peptides were delivered to a reversed phase analytical column (10 cm x 75 μm i.d., Bruker 1866154). Liquid chromatography was performed at 50 °C and peptides were separated on the analytical column using a 48 min gradient (solvent A: 2% ACN, 0.1% FA; solvent B: 0.1% FA, in ACN) at a flow rate of 500 nl/min. A linear gradient from 2-35 % B was applied for 45 min, followed by a step to 95% B for 1.5 min and 3 min of washing at 95% B. The timsTOF Pro was operated in PASEF mode with the following settings: Mass Range 100 to 1700m/z, 1/K0 Start 0.85 V·s/cm2, End 1.3 V·s/cm2, Ramp time 100ms, Lock Duty Cycle to 100%, Capillary Voltage 1700, Dry Gas 3 l/min, Dry Temp 200°C, PASEF settings: 4 MS/MS, charge range 0-5, active exclusion for 0.04 min, Scheduling Target intensity 20000, Intensity threshold 500, CID collision energy 10eV.

For analysis, Bruker raw data files were processed using Byonic software (Protein Metrics) to identify peptides and proteins using the NCBI Homo sapiens refseq protein database. Data were searched with 20 ppm error tolerance for precursor and 40 ppm for fragment ions using QTOF/HCD fragmentation type. Besides standard variable modifications, we searched for S/T/Y phosphorylation and set 1 % FDR for protein identifications.

Kinase set enrichment analysis (KSEA Analysis)

Counts for phosphosites between two technical replicates were summed after the total counts per sample were normalized to the median of total counts. The counts were then log2-transformed and quantile normalized. Batch correction was done using ComBat function from the sva package from Bioconductor and the log2-transformation was undone to obtain the counts for differential expression analysis. Differential expression analysis was conducted with the msms.glm.pois function from the msmsTests package from Bioconductor (Josep Gregori, Alex Sanchez and Josep Villanueva (2020). msmsTests: LC-MS/MS Differential Expression Tests. R package version 1.26.0.). KSEA was calculated with the ksea function from ksea package from GitHub (David Ochoa (2020). ksea: Kinase Activity Prediction based in Quantitative Phosphoproteomic Data. R package version 0.1.2.) using a kinase substrate database created from PhosphositePlus (Hornbeck et al., 2015) and NetworKin (Linding et al., 2008). p-values were adjusted using Benjamini-Hochberg procedure. GO ORA was conducted using enrichGO function from the clusterProfiler package from Bioconductor (Yu et al., 2012) and the database package from Bioconductor (Marc Carlson (2020). Genome wide annotation for Human. R package version 3.11.4.).

Quantification and statistical analysis

For signal quantification, samples were stained simultaneously in batch with the primary antibodies (ex. ACE2, TMPRSS2, NRP1, TFRC, insulin, glucagon as described above) using the same master mixes and identical incubation times under similar staining conditions described above. Exposure times under confocal microscopy were identical for the quantified samples. Quantification was performed using a custom script developed in the FIJI package of ImageJ as previously described (Lee et al., 2020). Briefly, a binary mask was created by thresholding the insulin and glucagon channels using selected cutoff values to generate a comprehensive outline of each channel. Insulin- and glucagon-positive regions were segmented using continuity of high signal regions on a binary mask. Finally, the signals of proteins of interest within the segmented regions were computed. While the experimenters were not strictly blinded to the samples, all sample processing, staining, and data acquisition were performed in parallel under identical conditions without regard to the specific identity of the samples. Quantification used a custom script developed in the FIJI package of ImageJ as previously described (Lee et al., 2020). Experimental sample sizes were not predetermined given the exploratory nature of the work and the limited availability of tissue specimens. No pancreatic samples were excluded from experimentation/analyses unless otherwise stated in the manuscript (see Table 3). Mann-Whitney U test was used when the data were not normally distributed by Shapiro-Wilk normality test and were not at equal variance by F-test. When the normal distribution and equal variance were confirmed, Student’s t test were used. Kruskal-Wallis test and post-hoc Dunn’s multiple comparison test were used for comparisons of more than two groups. Analyses were performed with GraphPad Prism 6.0 (GraphPad Software, La Jolla, CA) software and IBM SPSS Statistics version 23 (IBM, Armonk, NY).Go to:


The authors acknowledge members of the Kim laboratory, especially Jonathan Lam and Dr. Sangbin Park, for helpful discussions and assistance with islet experiments. We thank the Stanford Diabetes Research Center/Stanford Islet Research Core (supported by # P30DK116074). We thank the Stanford Diabetes Research Center/Stanford Islet Research Core (SDRC/SIRC), Alberta Diabetes Institute Islet (ADI) Research Core, IIDP, NDRI, and IIAM for islet and/or pancreas procurement, and especially the organ donors and their families. This work was supported by the National Institutes of Health R01DK127665 (P.K.J.), R01HD085901 (P.K.J.), R01GM121565 (P.K.J.), P30DK116074 (P.K.J.), R01AI149672-01 (G.P.N.), and U54-CA209971 (G.P.N.); Stanford Diabetes Research Center (SDRC) Pilot and Feasibility Research grant (P.K.J.); the Fast Grant Funding for COVID-19 Science (P.K.J. and G.P.N.); the Botnar Research Centre for Child Health Emergency Response to COVID-19 grant (S.J., M.S.M., G.P.N., and A.T.); a Bill and Melinda Gates Foundation COVID-19 Pilot Award (S.J. and G.P.N.); the Rachford & Carlotta A. Harris Endowed Chair (G.P.N.); California Institute for Regenerative Medicine (DISC2-09637) (J.V.N.); Defense Advanced Research Project Agency (HR001118S0037-PREPARE-FP-001) (J.V.N.); the Operndorf Foundation (J.V.N.); Stanford Respond. Innovate. Scale. Empower (RISE) COVID-19 crisis response trainee seed grant (C.-T.W., R.C., I.T.L., S.J., and T.N.); Stanford Translational Research and Applied Medicine (TRAM) pilot grant (I.T.L.); Thrasher Research Fund Early Career Award (I.T.L.); Stanford Maternal and Child Health Research Institute (MCHRI) Clinical (MD) Trainee Support Award (I.T.L., Ernest and Amelia Gallo endowed postdoctoral fellow); Leukemia & Lymphoma Society Career Development Program (S.J.); Cellular and Molecular Biology Training grant (NIH 5 T32 GM007276) (R.C.); and the Swiss National Science Foundation (SNSF; grant no. 320030_189275) (M.S.M.).

Author contributions

C.-T.W. conceived and coordinated the study. C.-T.W., P.V.L., Y.X., I.T.L., R.C., S.J., and T.N. designed and performed the experiments. C.-T.W., I.T.L., and T.N. performed the microscopy imaging. P.V.L. and Y.X. made virus and infected isolated human pancreatic islets. I.T.L., S.J., A.K.S., A.T., and M.S.M. obtained patient consent, and collected, processed, banked, and/or evaluated the human samples. R.C. and J.D. performed phosphopeptide shotgun proteomics. C.-T.W., I.T.L., R.C., J.D., T.N., and S.J. analyzed the data. C.-T.W., T.N., and S.J. conducted statistical analyses. R.J.B., R.L.W., and C.A.C. provided isolated pancreatic islets. B.Z. and H.C. assisted in experiments. Y.G. contributed novel tools that enabled the analysis. C.-T.W. and T.N. prepared the final figures. C.-T.W., I.T.L., S.J., and R.C. wrote the manuscript with contributions by P.V.L., J.V.N., A.T., M.S.M., and P.K.J. The co-first authors, C.-T.W., P.V.L., Y.X., I.T.L., R.C., S.J., and T.N. contributed equally and have the right to list their name first in their CV. Funding and supervision were provided by P.K.J. All authors reviewed and agreed with the content of this manuscript.

Declaration of interests

The authors declare no competing interests.Go to:


Published: May 18, 2021Go to:


Supplemental information can be found online at to:

Supplemental information

Document S1. Figures S1–S5:Click here to view.(22M, pdf)Table S1. Phosphoproteomic data, related to Figures 4 and S4:

Contains raw count of filtered phosphoproteomic data and fold change analysis of phosphosites for human islet cells treated with purified Spike protein (PhosphoSpike) or SARS-CoV-2 (PhosphoSars). Unfiltered phosphoproteomic raw count data is also included (UnfilteredPhospho).Click here to view.(5.6M, xlsx)Table S2. Predicted kinase activity, related to Figures 4 and S4:

Kinase activity as predicted by KSEA of various kinases in human islet cells treated with purified Spike protein (KSEA.Spike) or SARS-CoV-2 (KSEA.Sars). Kinase activity is reported as ES as calculated by weighted Kolmogorov-Smirnov statistics.Click here to view.(22K, xlsx)Table S3. Gene ontology pathway analysis, related to Figures 4 and S5:

Gene ontology enrichments for upregulated/downregulated kinases upon treatment by Spike protein or SARS-CoV-2.Click here to view.(397K, xlsx)Document S2. Article plus supplemental information:Click here to view.(26M, pdf)Go to:


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Hyperglycemia in Acute COVID-19 is Characterized by Adipose Tissue Dysfunction and Insulin Resistance

Authors: Reiterer MRajan MGómez-Banoy NLau JDGomez-Escobar LGGilani AAlvarez-Mulett SSholle ETChandar VBram YHoffman KRubio-Navarro AUhl SShukla APGoyal PtenOever BRAlonso LCSchwartz RESchenck EJSafford MM


COVID-19 has proven to be a metabolic disease resulting in adverse outcomes in individuals with diabetes or obesity. Patients infected with SARS-CoV-2 and hyperglycemia suffer from longer hospital stays, higher risk of developing acute respiratory distress syndrome (ARDS), and increased mortality compared to those who do not develop hyperglycemia. Nevertheless, the pathophysiological mechanism(s) of hyperglycemia in COVID-19 remains poorly characterized. Here we show that insulin resistance rather than pancreatic beta cell failure is the prevalent cause of hyperglycemia in COVID-19 patients with ARDS, independent of glucocorticoid treatment. A screen of protein hormones that regulate glucose homeostasis reveals that the insulin sensitizing adipokine adiponectin is reduced in hyperglycemic COVID-19 patients. Hamsters infected with SARS-CoV-2 also have diminished expression of adiponectin. Together these data suggest that adipose tissue dysfunction may be a driver of insulin resistance and adverse outcomes in acute COVID-19.

The deadly COVID-19 pandemic is underscored by the high morbidity and mortality rates seen in certain vulnerable populations, including patients with diabetes mellitus (DM), obesity, cardiovascular disease, and advanced age, with the latter associated with many chronic cardiometabolic diseases 14 . Hyperglycemia with or without a history of DM is a strong predictor of in-hospital adverse outcomes, portending a 7-fold higher mortality compared to patients with well-controlled blood glucose levels 5 . Hyperglycemia may be seen as a biomarker that predicts poor prognosis. A retrospective study that compared hyperglycemic patients that were treated with insulin against those who were not showed increased mortality in those receiving insulin 6 . However, it remains unclear whether insulin treatment is a surrogate for increased hyperglycemia and overall morbidity, or whether it is an actual causative factor for death. There is thus uncertainty regarding specific treatments for hyperglycemia in acute COVID-19 7 .

Despite our early recognition of the association between hyperglycemia and perilous outcomes, the pathophysiological mechanisms that underlie hyperglycemia in COVID-19 remain undefined 8,9 . Hypotheses have included a broad range of pathologies from direct infection of islets leading to beta cell failure (BCF) and to inflammation and glucocorticoids leading to insulin resistance (IR). Although COVID-19 is primarily a respiratory tract infection, SARS-CoV-2 is known to infect other cell types and often leads to extrapulmonary consequences 10,11 ACE2 and other entry receptors for SARS-CoV-2 can be expressed on pancreatic islet cells and endocrine cells differentiated from human pluripotent stem cells are permissive to infection 12 . Early reports of unexpected diabetic ketoacidosis (DKA) in COVID-19 patients fuelled concerns for a novel form of acute onset beta cell failure. For example, one case described a patient with new onset diabetic ketoacidosis (DKA) who was found to be autoantibody negative for type 1 DM (T1DM) but showed evidence of prior SARS-CoV-2 infection based on serology results, suggesting the possibility of pancreatic beta cell dysfunction or destruction as a result of COVID-19 13 . However, given the high rates of COVID-19 during this pandemic coupled with low background rates of new onset T1DM, the connection between these two events in this case could be “true, true, and unrelated.” Recent studies disagree on whether ACE2 is expressed on pancreatic beta cells or whether the SARS-CoV-2 virus is found in pancreatic beta cells of deceased individuals with COVID-19 1416 . Conversely, the well-known connection between obesity and insulin resistance might lead to impaired immunity and more severe SARS-CoV-2 infection 17 . In fact, population level studies have reported higher risk of complications in obese patients with COVID-19 1820 . Viral infection may lead to systemic insulin resistance and worsened hyperglycemia. In sum, despite much attention, the pathophysiology of hyperglycemia in COVID-19 remains unknown.

Dexamethasone substantially reduces mortality in patients with severe COVID-19 infection requiring oxygen or invasive mechanical ventilation 21 . Glucocorticoids can also provoke hyperglycemia by inducing insulin resistance and beta cell dysfunction. The widespread usage of dexamethasone in severe SARS-CoV-2 infection is sure to exacerbate both the incidence and severity of hyperglycemia in COVID-19.

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