A dry cough. Loss of smell. Diarrhea. A fever. All of these were considered as possible symptoms associated with SARS-CoV-2 infection, along with the complete absence of symptoms. Lacking adequate testing capacity, many areas in the United States are being forced to assign their limited testing to only those who appear to have COVID-19 symptoms. But given the difficulty of determining which symptoms actually indicate a likely infection, those are tough decisions to make.
The bewildering array of symptoms also raises questions about why people react so differently to the same virus.
Figuring out what’s going on in the midst of a pandemic is an incredible challenge. We’re going to look at some preliminary reports on one way to do this — not because the results are likely to hold up as more research comes in, but because it reveals some of the ways researchers are using to try to understand the virus’ infection.
Symptom or coincidence?
Currently, the CDC website lists a variety of symptoms associated with COVID-19. Some of these are what you would expect from a viral infection of the lungs: fever and chills, cough, shortness of breath, and a sore throat. But there are also some less obvious ones, such as headaches, muscle aches and loss of sense of smell.
Lists like this are usually created by aggregating medical reports as doctors take and update a person’s symptoms as they are admitted and treated. But the lack of testing poses significant problems for this effort. First, we struggle to understand how many people are infected without medical care. The arrival of the pandemic also coincided with flu season and the onset of seasonal allergies, which can cause an overlapping set of symptoms.
Finally, the list of symptoms is usually a product of the patient’s own memory, as he is asked to describe the onset of the problems. Reminders can be problematic, as the need for medical care itself can improve recall of symptoms that would otherwise be ignored. Widespread awareness of symptom lists like the CDCs can serve the same purpose.
To complicate matters, some problems seem to affect a relatively small subset of infected people. Several reports have linked SARS-CoV-2 to the formation of blood clots, possibly due to the infection of the lining of blood vessels. Similar things apply to the gastrointestinal symptoms. And the receptor the virus uses to enter cells is also found in the kidneys, which could potentially explain why some hospitalized patients need dialysis. Why some patients appear vulnerable to severe symptoms while others have an asymptomatic infection remains unclear.
Figuring out what’s going on with some of this will eventually require a lot of lab work – we need to find out if the virus can reproduce in kidney cells and investigate the nature of, say, kidney damage. But another group of researchers has been looking for ways to understand the onset of COVID-19 symptoms in real time.
What happens when?
Two recent concept papers have described the first results of a collaboration between health researchers from Harvard and King’s College London. They teamed up with an application development company to put together a simple application for mobile devices called COVID Symptom Tracker that asks its users a series of questions on a daily basis. These focus on known symptoms of COVID-19 (and may be updated as that list grows), as well as any test results and treatments received.
This approach has some drawbacks. The users are self-selected and have smartphones, which probably means a younger population. And the app only asks about the symptoms that the developers enabled. But the approach trades these limitations for some key benefits. The first is just scale. Between the US and the UK, the app already had 2.2 million users before the end of March. The second is that it does not suffer from recall bias – people enter their symptoms as soon as they occur, before they know they are associated with a positive diagnosis. Later, the early symptoms and even treatments may be correlated with the patient’s results.
How are you? A concept describing the application provides an initial analysis of the users. It turned out that people were usually tested after they reported coughing and/or fatigue, but these weren’t really strongly linked to the test coming back positive. The same was true if someone had diarrhea but no other symptoms. Instead, positive diagnoses increased when coughing and/or fatigue was accompanied by diarrhea or loss of smell. The results even suggested that loss of smell was more common than fever in those who would eventually test positive for the virus.
Last week, the team posted a follow-up concept looking at the characteristics associated with these symptoms. It does this by looking at a population of twins in the UK who have volunteered to participate in health research. A number of them (just over 2,500) have used the application, and the researchers have used that to try and find out if genetics can influence the symptoms people experience.
The problem here is that not enough of them have been diagnosed to do any kind of analysis. So the researchers didn’t correlate anything with actual SARS-CoV-2 infections; instead, they correlated it with a prediction of a positive diagnosis, as determined in their earlier draft script. That is clearly the greatest weakness of this work. The second is that it covered an extremely short period of time: March 25 to April 3.
Given these warnings, you should take the results with a whole salt flat. But there are some interesting potential results that seem worth tracking with longer-term tracking. They suggest there is a significant genetic component to who is likely to receive a COVID-19 diagnosis, with a likely value of 50 percent genetically (although the error range was from 30 to 80 percent). In addition, many symptoms also appeared to be genetically related, including fever, fatigue, loss of smell and diarrhea. Others, such as coughing, chest pain, and abdominal pain, were not.
While this study won’t change our understanding in its current form, it does provide an interesting model for how a higher-quality study would work — that’s one possible reason for publishing a draft publicly in the first place. And it’s clear that eventually this research could be what we’re looking for, because there’s no reason why we couldn’t end up testing every participant and getting a clearer picture of what’s going on. In the longer term, rather than relying on twins, we may also want to do genome-wide studies with unrelated individuals, which could expand the study population significantly.
While this study shouldn’t be seen as much more than a hint of what’s possible, something is clearly affecting the body’s response to this virus in different individuals. Genetics is a reasonable candidate for one of the influences there.