Despite relentlessly battering the world with uncertainty after uncertainty, some pieces of conventional wisdom about COVID-19 have remained unchanged since early on in the pandemic. One is the observation that more men die of the disease than women, despite having comparable rates of infection. This has sparked a deluge of research articles and news coverage (including by The Scientist) trying to parse out why this trend exists and what it could mean.
In August 2020, researchers from Yale University published one of the first studies to report differences in the immune response between men and women with COVID-19. This study generated a flurry of both public and scientific interest, and has already been cited in more than 400 publications. However, it also elicited a recent response article in Nature challenging the statistical robustness of the results and expressing concern at the original paper’s suggestion that the findings might guide sex-specific treatment and vaccination regimens in the future. The response and subsequent counter-response open a window into fundamental questions about how sex and gender influence biological outcomes.
In the original study, researchers led by Yale immunologist Akiko Iwasaki measured nearly 200 immune parameters—including circulating cytokines and immune cell subsets—either at baseline (upon admittance to the hospital with COVID-19) or as the infection progressed, and found a number of differences. At baseline, they saw higher levels of the proinflammatory cytokines interleukin-8 (IL-8) and IL-18 in male participants (whose sex was determined by medical records or from the Yale IMPACT study database), while females had higher numbers of activated CD8+ T cells, our bodies’ most skilled antiviral weapons, leading the authors to conclude that these differences might underlie the striking difference in COVID-19 mortality between the sexes.
The team also found a number of innate immune factors that were present only in females but not males who had progressed to severe disease, and an association in males between poor T cell responses and worse outcomes. The authors conclude that inherent biological differences in the immune response to SARS-CoV-2 between males and females could merit tailored vaccinations and treatments—ones that aim to boost the T cell response in male patients, for example, or that dampen the innate inflammatory response associated with worse disease in females.
The authors of the response paper (which was peer-reviewed) reanalyzed the data from the Yale paper and, after correcting for age and BMI, reported finding no differences in IL-8 and IL-18 levels, nor many of the other reported differences, between male and female patients as the disease progressed. They did identify three immune parameters in their reanalysis that they say could represent true sex differences in this cohort: male patients had higher baseline numbers of immune cells known as nonclassical monocytes than females, as well as higher levels of the chemokine CCL5 as the infection progressed, while female patients had higher numbers of activated T cells at baseline. Statistical analysis aside, though, the authors of the response paper argue that there are problems with trying to pin sex-associated differences solely on biology.
“Biological sex differences are the only causal model considered in the study,” they write. “While it is plausible that sex-related biological variables may have a role in explaining sex disparities in COVID-19, strong evidence not cited by the researchers suggests a large role for social and other variables in producing the sex differences they seek to explain.”
“Of course, people talked about demographic differences in [things] like occupational factors,” says Yale immunologist Takehiro Takahashi, the first author of last year’s paper. But, he adds, he and his colleagues were convinced from previous studies—including of infections with SARS-CoV-1 and other viruses—that “both sexes are very different in terms of immune responses.”
Indeed, while his group’s paper was the first of its kind for COVID-19, the study is far from alone in ascribing differences in immune response to biological sex. For instance, in a recent retrospective analysis of data from five hospitals near Washington, DC, Johns Hopkins University viral immunologist Sabra Klein and her colleagues found that markers of inflammation were higher in male patients who had been hospitalized for COVID-19 than in hospitalized female patients. After parsing out the effects of other factors that may differ between the sexes—including comorbidities, body-mass index, smoking, and alcohol use—the researchers concluded that this difference in the inflammatory response had the biggest effect on the sex disparity in COVID-19 outcomes.
Sex and the immune system
A large body of research has uncovered numerous ways in which differing biology between the sexes might undergird worse COVID-19 outcomes for men. For example, Toll-like receptor 7 (TLR7), an important sensor cells use to detect single-stranded viral RNA, is encoded on the X chromosome. Normally, in people with two Xs, only one chromosome serves as a template for gene expression while the other is silenced in a process called X inactivation. However, many X-encoded genes, including the one for TLR7, are not fully silenced, meaning that cells might get a double dose of those proteins. This has led researchers to believe that females may have higher levels of TLR7 than males and thus a potential advantage at nipping viral infections in the bud, says immunologist Susan Kovats, who studies sex differences in the immune response to influenza in mice at the Oklahoma Medical Research Foundation. Additionally, she adds, “women and female mice tend to make more [antiviral] type I interferon” than men and male mice, potentially giving females another edge in clearing viral infections before they get out of control.
Kovats also notes that multiple immune cells express sex hormone receptors, many of which move to the nucleus to control gene expression after binding their hormone. For instance, her group has found that lung-resident immune cells called type 2 innate lymphoid cells (ILCs) express high levels of androgen receptors. These cells are important for repairing lung tissue during and after infection, but during influenza, their function is suppressed in female mice—which have lower levels of androgens than males. This leads to more tissue damage and increased morbidity in females than in males.
Animal studies have also shown that there are some sex differences in the response to infections with coronaviruses, Takahashi says. “For example, in the mouse model of SARS-CoV-1, if you infect mice with that virus, males succumb to death more than females.” Takahashi explains that that difference disappears if female mice have had their ovaries removed or are treated with drugs to block the estrogen receptor, suggesting that the protective phenotype is driven by hormonal sex differences.
Animal research on SARS-CoV-2 similarly suggests there may also be biological reasons for differences in outcomes between males and females. For example, a study that infected transgenic mice expressing human ACE2 with SARS-CoV-2 showed that at a lower infectious dose, 40 percent of the female mice survived while all the males died—although more female mice than males died when the dose was 10-fold higher. Another study using Syrian hamsters showed that males experienced more lung damage than females during SARS-CoV-2 infection.
When it comes to humans, Kovats says, the massive genetic diversity within the population makes it difficult to tease out true differences between groups unless the sample size is large, and so far, many have been relatively small. The Yale paper had 98 study participants. Of the difference in outcomes between the genders, she says, “Is that the difference in the immune response? Or is there some other sort of social factor happening?” Or, she asks, is there a biological but non-immunological explanation—such as levels of expression of the ACE2 receptor, which SARS-CoV-2 uses to attach to and infect cells and which may be controlled by testosterone signaling?
Since Takahashi’s paper came out, there have been a few others in humans that compared the immune responses of males and females with COVID-19 (each of these studies report classifying patients’ sex from their medical records), and their results broadly align with those of the Yale-led team. In a study of 36 Chinese COVID-19 patients, the researchers found that male patients had more circulating CD8+ T cells and monocytes and fewer CD4+ T cells (known as “helper T cells”) than females. In Klein’s retrospective analysis of more than 2,600 patients, she and her colleagues found that when assessed across all ages, males had a significantly higher neutrophil-to-lymphocyte ratio, and more inflammatory markers such as IL-6, ferritin, and C-reactive protein, while females had more B and T cells. Another study of more than 3,000 patients in China also found more B and T cells in females, who showed a quicker onset of neutralizing antibodies, while males had higher levels of neutrophils, C-reactive protein, and IL-6.
While Klein agrees with the authors of the response paper that there may have been some over-interpretation of the results in the initial paper, she notes that the reanalysis underscores one striking difference between males and females that remained significant: that females had more CD8+ T cells during SARS-CoV-2 infection. “What the [response piece] told me was, ‘Wow. That T cell response? That’s conserved,’” regardless of who analyzes the data, she says.
Takahashi says his group is now working on follow-up studies, including looking at sex-specific differences in the manifestations of long COVID, which seems to disproportionately affect women and may be rooted in the same mechanisms that drive autoimmune diseases. About the criticisms of the August 2020 paper, he says, “What we intended to say is that in the long run, this study could be a preview of other larger studies that would lead to more insight into the sex difference in immune responses.” And while those future studies could inform potential sex-specific strategies to fight COVID-19, he adds, “we didn’t mean that our study itself has the statistical strength to say that kind of thing.”
Looking closer at social variables
Some researchers argue that differences in immune parameters such as T cells or cytokines that align with biological sex aren’t necessarily rooted in sex. “Just because something is biologically measured and differs between men and women doesn’t mean that innate sex is driving outcome,” says Heather Shattuck-Heidorn, a biologist and feminist scholar at the University of Southern Maine and the lead author of the response paper.
For instance, she explains, prior coronavirus epidemics and the 1918 influenza pandemic had sex differences in outcomes, with men having higher mortality rates. But, says Shattuck-Heidorn, later analyses showed that “it wasn’t that sex was driving those disparities.” Rather, it was things that varied by sex, such as smoking rates or rates of tuberculosis—which was associated with the crowded factory or military conditions men were more likely to experience—that likely caused worse outcomes.
Additionally, the blanket assumption that men are more vulnerable, she says, “can hide how there’s groups of women that are very, very vulnerable to poor COVID outcomes,” underscoring the need to look at how social factors such as race, occupation, gender roles, and access to healthcare factor into the disparities.
In her own research using official public health data from Georgia and Michigan (where gender was recorded by each state’s public health department), Shattuck-Heidorn and her colleagues have found that while men are more likely to die of COVID-19 than women within their own racial groups, Black women are not only much more likely to die than white women, they are more likely to die than white and Asian or Pacific Islander men. In fact, she says the disparity within sex between white women and Black women is much larger than the sex disparity between white men and white women.
Shattuck-Heidorn adds that while these findings are not evidence that there are no biological sex-linked contributions, they suggest that any such mechanisms are working in tandem with social factors such as access to healthcare, smoking and alcohol use, type of occupation, and hand-washing or wearing a mask—behaviors that can influence disease susceptibility. “If [the cause of the sex disparity in COVID-19 outcomes] was as simple as aspects on our chromosomes—which people have proposed—or levels of estrogen or something like that, it’s hard to understand why it would vary so wildly across time and place and between different racial groups.”
Renée Adams, a financial economist at Oxford University who noted huge international variations in the disparity between men and women dying of COVID-19 early on in the pandemic, agrees. In a preprint she posted in May 2020, she notes that as of that April, women made up only 19 percent of COVID-19 deaths in Thailand, while they constituted 50 percent in Portugal. “If it’s a biological factor—if women and men are really different—they should die at the same rate in each country,” she tells The Scientist. But this wasn’t the case.
Adams found that relative female mortality to COVID-19 was higher in countries where more women were part of the full-time workforce—suggesting that instead of (or in addition to) bona fide biological differences between males and females, health outcomes depended on variation in likelihood of exposure. She says people need to be very careful any time they say women are different from men (not only in the context of COVID-19), because it means that women and men will be treated differently—which, in her view, inherently creates more inequality. For example, if a country sees that males have a higher COVID-19 mortality rate, public health policies might prioritize a sick male’s care over a female’s simply because of sex, when they really should be prioritizing those at greater risk because of their occupations and other social factors that influence infection rate and severity, she says. “Whenever you further inequality instead of reducing it, that’s always a problem.”
Adams advises that healthcare facilities ask admitted patients not just about their allergies and the medications they’re taking, but also about social factors: What line of work are they in? How many people do they share a home with? How do they get to work? Questions like these might help doctors assess risk of specific types of illness or infection, especially during the pandemic, to ensure those at the greatest risk receive appropriate care, she says. “If you don’t have the data or you don’t ask those questions, then you obviously can’t tailor the policy or take the social factors into account.”
Shattuck-Heidorn notes another major gap in COVID-19 data perpetuated by not asking enough questions: namely, representation of transgender and nonbinary people in the data. She says that with a few exceptions, most states don’t even have a place to record information about gender identity in their COVID-19 case and fatality reports.
In not collecting data on trans and nonbinary people, “you make them invisible,” she says—researchers can’t even ask questions about these groups of people. Some states say their data is separated by sex, while others say it’s by gender, but she says it’s often unclear as to whether they’re recording sex assigned at birth or gender identity. In fact, she says, few states release COVID-19 mortality data that specify age, sex, and race, making it harder to tease out the socioeconomic effects perpetuating disparities.
Klein says she thinks one answer is for researchers to publish more fine-grained data, rather than picking sides. “What we need to do is have more and more people disaggregating their data—whether that’s the primary goal of their research or not,” she says. That way, every time people are looking at differences between populations, they can check for the differences reported by other researchers.
She notes that often, in drug trials and other clinical studies, the first table gives the breakdown of “what proportion of subjects were male, female, Black, white, Asian, ‘other,’ Hispanic, Latino, non-Latino—but then you go to Table Two where all the data are, and that disappears”—that is, the authors don’t break down their results according to these demographic categories. People get uncomfortable with issues of sex and race, and while researchers may be concerned that disaggregating their data could invite over-interpretation or open a political can of worms, Klein argues that if the prevailing sentiment is, “It’s too messy. I don’t want to get into this,” no one can know if differences between groups exist or not.