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Our take —

The clinical trial of the Pfizer/BioNTech vaccine showed that the vaccine is almost 95% effective in preventing COVID-19 1-2 weeks following administration of the second dose of the vaccine. With vaccine shortages and high SARS-CoV-2 infection rates world-wide, many have proposed postponing the second dose of the vaccine to expand the number of people getting their first dose to curb viral spread. This study shows that the Pfizer/BioNTech vaccine may be 85% effective in preventing symptomatic cases of COVID-19 15-28 days after following administration of first dose. Further studies are needed to determine the long-term protection after the first dose of the vaccine.

Study design

Case-Control, Prospective Cohort

Study population and setting

The study analyzed the SARS-CoV-2 infection rate among health care workers in The Sheba Medical Center, the largest hospital in Israel, after vaccination with Pfizer/BioNTech BNT162b2 vaccine. By the end of the study, among 9109 health care workers eligible for the vaccine, 7214 (79%) had received at least one dose and 6037 (66%) had received both doses of the vaccine. Most (91%) of the fully vaccinated workers received their second dose 21 or 22 days following the first dose. SARS-CoV-2 infection was detected through daily required symptom reporting and/or contact tracing followed by PCR lab diagnosis.

Summary of Main Findings

The study found that the vaccine reduced the infection rate (both symptomatic and asymptomatic) from 7.4/10,000 person-days in the unvaccinated group to 5.5/10,000 person-days (30% reduction) and 3/10,000 (75% reduction) on days 1-14 and 15-28 after administration of the first dose of the vaccine, respectively. The symptomatic cases were also reduced by 47% (2.8/10,000 person-days) and 85% (1.2/10,000 person-days) on days 1-14 and 15-28 after administration of the first dose of the vaccine, respectively, compared to the unvaccinated group (5/10,000 person-days).

Study Strengths

The study included 9109 health care workers with daily reporting of SARS-CoV-2 symptoms and contact tracing followed by same-day molecular diagnosis of the infection. This allowed for relatively high quality data. The high rate of SARS-CoV-2 infection in Israel at the time in which this study was conducted permitted detection of differences in infection rates among different groups tested in this study.

Limitations

One of the main limitations of this study is that it included health care workers only. This group has a higher exposure rate relative to the general population. The study also analyzed Pfize/BioNTech vaccine protection for up to 28 days after the first dose. Longer follow up to determine the protection level for one dose relative to two dases of the vaccine. For the effectiveness estimate of the window 15-28 days after vaccination, person-time from vaccinated individuals who had not been infected through 14 days were compared to all person-time contributed by unvaccinated individuals. It is possible that this could induce a selection bias that could overestimate effectiveness during this time window.

Value added

This study showed that Pfizer/BioNTech (BNT162b2) vaccine may provide up to 85% protection against symptomatic infection of COVID19 15-28 days after the first dose of the vaccine.

Our take —

This genome-wide association study among people primarily of European ancestry compared over two thousand critically ill COVID-19 patients to controls from several population-based cohorts. The authors replicated an association between severe illness and a genetic variant on Chromosome 3 (at 3p21.31) previously observed in other studies, and identified novel associations between several other genes and severe COVID-19. A Mendelian randomization study provided some evidence that severe COVID-19 is linked with lower IFNAR2 expression (involved in the antiviral defense mechanism of type I interferon signaling, the suppression of which has been previously implicated in severe COVID-19) and higher TYK2 expression (which may promote inflammatory lung injury). The study used population-based controls with no prior positive SARS-CoV-2 test, which makes unmeasured confounding likely. The results, if replicated elsewhere using non-critically ill COVID-19 patients as controls, may lead to development of therapeutic approaches to stimulate interferon activity and suppress harmful inflammation.

Study design

Case-Control, Other

Study population and setting

This was a genome-wide association study (GWAS) comparing genetic variants from 2,244 critically ill COVID-19 patients from 208 UK intensive care units to variants from ancestry-matched controls (5:1) in UK Biobank, a large population-based cohort. Potential controls were excluded if they had any record of a positive test for SARS-CoV-2. Ancestry was inferred using principal components analysis with a population reference from the 1000 Genomes Project. GWAS was performed separately by ancestry group. Tests for association with COVID-19 status were performed via multivariable logistic regression with the covariates sex, age, residential deprivation score, and the first 10 genomic principal components. Replication was attempted using a meta-analysis of data from the COVID-19 Host Genetics Initiative (2,415 hospitalized COVID-19 cases; 477,741 population-based controls). Two-sample Mendelian randomization was employed to assess the causal effects of RNA expression of several genes on the risk of severe COVID-19. The authors additionally performed a transcriptome-wide association study (TWAS) testing for links between GWAS results and tissue-specific (lung and whole blood) gene expression.

Summary of Main Findings

There were 15 independent associations between genetic variations and COVID-19 case status that had genome-wide significance (p < 5 x 10−8); of these, 8 were validated in GWAS using additional sources of population-based controls and thus included in replication analysis. Five of the 8 associations were replicated with statistical significance; these were found in loci on chr3 at 3p21.31 (odds ratio (OR): 2.14, p= 4.77 x 10-30), chr12 near the OAS gene cluster (OR: 1.59, p 1.65 x 10^−8), near TYK2 on chr19 (OR: 1.40, p: 2.3 10^−8), in DPP9 on chr19 (OR: 1.36, p 3.98 x 10^−8), and on chr21 containing the gene IFNAR2 (OR: 1.28, p 4.99 x 10^−8). A list of target genes was assessed in Mendelian randomization for possible effects on severe COVID-19; low expression of IFNAR2 showed statistically significant association with severe disease. Transcriptome-wide Mendelian randomization on unselected genes yielded no significant associations after adjustment for multiple tests; the smallest p-value (0.00049) was observed for an association between higher expression of TYK2 and severe disease. Both the IFNAR2 and TYK2 associations were replicated with statistical significance in an external dataset. In TWAS results, five genes had genome-wide differences in expected expression between cases and controls: CCR2, CCR3, CXCR6, and MTA2B from lung tissue; and OAS3 from whole blood.

Study Strengths

The COVID-19 cases were drawn from an existing network of ICUs in the UK and thus represented a well-defined group of critically ill patients, which better represents the outcome of interest (severe disease) than other methods of case selection (e.g., all hospitalized cases). The authors attempted to replicate their results using multiple independent control groups.

Limitations

Control groups were drawn from population-based cohorts that differed from COVID-19 cases with respect to ancestry, demographic variables, and comorbidities; this may have introduced confounding of the variant-outcome associations. For example, if controls were less likely to have been exposed to SARS-CoV-2 than cases due to occupational or sociodemographic differences, effect estimates would be biased. This confounding is likely given the observed genetic correlations with educational attainment. Moreover, potential controls with any prior positive SARS-CoV-2 test were excluded, further confusing the contrast between cases and controls (i.e., cases had critical illness, whereas controls may not have ever been exposed to SARS-CoV-2). The study population of critically ill COVID-19 cases was not well described and its characteristics were not reported in detail, which limits interpretation of the observed associations. One of the assumptions of Mendelian randomization (that the genetic variant can only influence the outcome through the exposure of interest) appears to have been violated in the results for IFNAR2, which may have biased the effect estimate in an unknown direction. Finally, the study population was predominantly of European ancestry, limiting generalizability of results.

Value added

This GWAS confirms prior evidence for associations between genetic variants and severe disease, and adds novel evidence for associations that are amenable to replication in future analyses and may provide the basis for therapeutic interventions.

Our take —

In this study of 154 patients with asymptomatic or severe COVID-19 in India, individuals with severe COVID-19 (defined as ICU admission) had lower vitamin D levels and were more likely to have vitamin D deficiency. Those with vitamin D deficiency were more likely to die than those without deficiency. However, caution is warranted as these findings do not provide evidence that vitamin D supplementation can prevent severe COVID-19, results were not adjusted for any potential confounders (including age), and vitamin D levels were measured after illness onset. Further research regarding this relationship is warranted.

Study design

Case-Control, Prospective Cohort

Study population and setting

This observational study at the M.L.B. Medical College in Jhansi, India was designed to evaluate the association between vitamin D and COVID-19 disease severity. Individuals aged 30-60 years with PCR-confirmed COVID-19 starting were consecutively enrolled for 6 weeks starting on June 5, 2020. Patients were included if they were asymptomatic at admission and remained so until their discharge (Day 12) or if they required ICU admission due to severe COVID-19 disease, defined as clinical pneumonia with respiratory rate >30 or oxygen levels <90%, signs of multi-organ impairment, or laboratory evidence of coagulation abnormalities. Vitamin D levels were estimated from Serum 25 (OH)D, and levels <20 ng/mL were considered as vitamin D deficiency. Participants were followed until death or discharge alive from the hospital.

Summary of Main Findings

In total, 154 patients were included: 91 were asymptomatic (53% male; mean age: 42 years) and 63 had severe COVID-19 (67% male, mean age: 51 years). The mean concentration of 25 (OH)D was higher among asymptomatic cases (mean: 27.9 ng/mL, 32% with vitamin D deficiency), compared to those with severe disease (mean: 14.4 ng/mL, 97% with vitamin D deficiency). Serum inflammatory markers, such as IL-6, ferritin, and TNF-alpha, were also associated with vitamin D deficiency. Regardless of symptom severity at enrollment, those with vitamin D deficiency were more likely to die (19/90 [21%] vs. 2/64 [3%]).

Study Strengths

This was a prospective cohort study with completed follow-up of included participants.

Limitations

No adjusted analyses were presented, and confounding is likely due to differences in age and comorbidities between asymptomatic and severely ill COVID-19 patients (older age is a known risk factor for vitamin D deficiency). The timing of vitamin D measurement relative to SARS-CoV-2 infection is not reported. Temporality between vitamin D levels and COVID-19 severity cannot be established; it is unknown whether vitamin D deficiency is a cause or consequence of severe disease. The sample size was relatively small and did not include patients with moderate disease (symptoms but not requiring ICU admission), which limits generalizability and inhibits inferences about any potential dose-response relationship between vitamin D levels and COVID-19 severity.

Value added

This is one of the first studies examining the relationship between Vitamin D and COVID-19 disease severity.

Our take —

This preliminary study suggests that using artificial intelligence on cough recordings can be a low-cost, rapid method for COVID-19 screening, especially in resource-limited settings and as a supplement to other screening techniques such as symptom questionnaires and temperature checks. Further work needs to be done to validate the accuracy of the diagnostic algorithm for COVID-19 identification in the general population and whether it has value over other established low-cost screening methods.

Study design

Case-Control; Other

Study population and setting

This study included 5,320 participants from across the world who submitted forced-cough data between April to May 2020 on a website and agreed to participate in the study to train a machine learning model to detect COVID-19 through cough recordings. Using online submission of cough recordings from various browsers and devices, all COVID-19 positive cases collected (n = 2,660, determined by either testing, or physician or self-assessment) and the same number of randomly selected negative cases (determined negative by the same methods) were included. 80% of the total cohort were used in a training set, and the remaining 20% for validation. Sensitivity, specificity, and diagnostic accuracy were estimated.

Summary of Main Findings

The artificial intelligence-based COVID-19 screening tool achieved a reported sensitivity of 98.5% (eg. the model correctly identified 98.5% of positive cases as positive) and specificity of 94.2% (eg. correctly identified 94.2% of negative cases as negative), achieving an overall accuracy of 98.5%. In asymptomatic subjects, it achieved a reported sensitivity of 100% and specificity of 83.2%.

Study Strengths

Cough recordings were collected from various devices and platforms, across a variety of symptomatic groups, to generate the artificial intelligence-based model for identifying COVID-19. Advanced, robust convolutional neural networks featuring modules previously shown to be successful in diagnosing Alzheimer’s disease from audio voice recordings were used to train the model which may yield to stronger diagnostic ability.

Limitations

Participant recruitment was based on self-selection and online-based volunteering which is prone to selection bias and could potentially limit the value of this artificial intelligence tool in the general population. Additionally, this study did not report the performance of the AI to detect COVID-19 within specific subject (e.g. racial, gender, age) and recording device subgroups, which could lead to variability in the value of this tool in different populations. Lastly, the bulk of COVID-19 “cases” used to train the model and evaluate its accuracy were from self-assessment (59%) or doctor assessment (28%), versus results from (undefined) “official” tests (13%), so it is unknown what proportion of the cohort’s COVID-19 status were correctly assigned. Validation of this artificial intelligence-based COVID-19 detection tool in the general population and on verified COVID-19 cases and non-cases is necessary to further gauge its value.

Value added

This was a preliminary study that developed and evaluated the performance of an artificial intelligence-based model using recorded coughs to identify COVID-19 cases. The reported diagnostic accuracy was high (98.5%) with an 100% asymptomatic detection rate. This study proposes an alternative low-cost and rapid screening method for evaluating COVID-19 using artificial intelligence.

Our take —

Variations in immune response are suspected to underlie some COVID-19 disease outcomes. In this important study, about 10% of patients with severe COVID-19 pneumonia had neutralizing IgG auto-antibodies to type I interferons, which were not present in any patients with mild SARS-CoV-2 infection. Production of auto-antibodies inhibited the ability of type I interferons to fight SARS-CoV-2 infection in vitro, and appeared to precede disease in patients. Individuals producing auto-antibodies were nearly all (94%) male. These results suggest a mechanism contributing to severe disease in a sizable minority of patients, which may be X-chromosome-linked, and they may lead to screening and therapeutic implications if replicated elsewhere.

Study design

Case series, case-control

Study population and setting

This study included 987 patients hospitalized with severe “life-threatening COVID-19 pneumonia” (defined as pneumonia with critical disease involving any organ system, requiring ICU admission) from multiple cohorts in several countries, along with 663 patients with SARS-CoV-2 infection with mild or no symptoms, and 1,127 healthy controls. Plasma and serum samples were obtained from participants, and these samples were tested for the presence of IgG auto-antibodies (Ab) against the type I interferons (IFNs) IFN-ɑ2 and IFN-ω. The authors tested whether these auto-Ab were neutralizing in vitro using plasma from patients with auto-Ab and healthy controls. A subset of samples from patients with auto-Ab to IFN-ɑ2 (n=22) were tested for the presence of auto-Ab to all 15 type I IFNs. Another subset of samples from patients with auto-Ab to IFN-ɑ2 (n=8) were tested to determine if they impaired the ability of IFN-ɑ2 to block SARS-CoV-2 infection in vitro. Finally, plasma concentrations of all 15 type I IFNs were measured among patients who had auto-Ab to these type I IFNs (n=41).

Summary of Main Findings

Among the 987 patients with severe COVID-19 pneumonia, 135 (13.7%) had IgG auto-Ab to IFN-ɑ2 and/or IFN-ω; these were also present in the two available samples from patients prior to SARS-CoV-2 infection. The prevalence of these auto-Ab against type I IFNs was estimated to be 0.33% (95% CI: 0.015% to 0.67%) in the healthy controls. In vitro, these antibodies were neutralizing for at least one type I IFN in 101 patients (10.1%), 95 (94%) of whom were male. All of the tested patients with auto-Ab to IFN-ɑ2 also had auto-Ab to all 13 type I INFs. The 8 plasma samples tested from patients with auto-Ab to IFN-ɑ2 were able to block the ability of IFN-ɑ2 to protect against infection from SARS-CoV-2 in vitro. Among the 41 patients tested who had auto-Ab to all 13 type I IFNs, 40 had no detectable levels of any type I INFs, and one had low levels. Among individuals with neutralizing auto-Ab against type I INFs, there was a predominance of males (94%), which was higher than the proportion of men among severe COVID-19 patients without these Ab (75%) and among those with mild or no symptoms (28%). One of the 7 women with auto-Ab to type I INFs had a condition in which cells activate only one X chromosome, providing evidence for X chromosome linkage.

Study Strengths

This study considered evidence at multiple levels (prevalence in cases and controls, neutralizing effect in vitro, effect on ability of IFN-ɑ2 to block SARS-CoV-2 infection in vitro, plasma type I INF concentrations). The study population was large and included from diverse ethnicities and nationalities.

Limitations

Only two samples were available from patients before SARS-CoV-2 infection, which limits the ability to conclude with certainty that auto-Ab production was not a consequence of severe disease. Demographic and clinical characteristics of patients and controls were not well described. Methods for selecting asymptomatic or paucisymptomatic controls were unclear.

Value added

This, along with an accompanying study in the same journal (Zhang et al.), is an important and novel piece of evidence; it is among the first to identify underlying variations in immune response that may cause severe COVID-19.

Our take —

A subset (3.5%) of 659 patients with severe COVID-19 pneumonia had uncommon genetic variants that suppress the type I interferon response to SARS-CoV-2 infection; none had previous severe viral illness. Some of these mutations are known to increase susceptibility to influenza, while others were not previously identified. This study, along with an accompanying study in the same journal, suggests that some people may have inborn deficiencies in their immune response that render them more susceptible to severe disease should they become infected with SARS-CoV-2. More research is necessary to determine if provision of type I interferons could improve outcomes in these patients.

Study design

Case series, Case control

Study population and setting

This study included 659 patients with severe COVID-19 pneumonia who were admitted to the ICU from four cohorts in France, Italy, and the United States (mean age 51.8 years, range 0.1 to 99 years, 74.5% male). Patients with Kawasaki-like disease were excluded. A control group of 534 individuals with mild laboratory-confirmed or suspected SARS-CoV-2 infection was also enrolled. The authors sequenced the genomes of participants from whole blood, with the aim of identifying monogenic inborn errors (primary immunodeficiency) of SARS-CoV-2 immunity that were associated with severe COVID-19. In particular, the authors tested the hypothesis that errors of TLR3- and IRF7-dependent type I interferon (INF) immunity were associated with severe COVID-19, by comparing the frequency of variants at 13 loci known to be mutated in patients with severe influenza pneumonia (or connected to three core genes dictating susceptibility to pneumonia) between cases and controls. Cells from patients with the identified variants were then tested in vitro for their effects on type I INF production after stimulation with SARS-CoV-2. Finally, blood concentrations of the 13 types of IFN-ɑ were measured in 10 patients with the identified mutations.

Summary of Main Findings

Four patients had biallelic variants of IRF7 or IFNAR1, while 113 patients had an additional 113 monoallelic variants at 12 loci; 9 of these variants were predicted to be loss-of-function (pLOF). Compared to controls, patients with severe COVID-19 were enriched in the pLOF variants at the 13 loci associated with influenza susceptibility. Of the 118 total variants, the authors tested 113 in overexpression systems, and 24 (carried by 23 patients) were found to be deleterious. In all, 23 of the 659 patients (3.5%) carried a deficiency at one of eight loci among the 13 loci tested. In vitro stimulation with SARS-CoV-2 of cells from patients with selected genotypes found those with autosomal recessive IRF7 deficiency had impaired production of type I INF by plasmacytoid dendritic cells, and deficiencies of TLR3 or IFNAR1 impaired fibroblast-intrinsic type I INF immunity to SARS-CoV-2. Ten of the 23 patients with the identified mutations had blood samples available, and among them, IFN-ɑ levels were all below 1 pg/mL, much lower than previously published measures in other patients with severe COVID-19.

Study Strengths

This was a multi-level study; variants that were enriched in the patient population were tested for responses to SARS-CoV-2 in vitro, and concentrations of IFN-ɑ were measured in blood samples from a subset of patients. Patients were from multiple countries and were of multiple ethnicities.

Limitations

Although it is biologically plausible, this study cannot establish that impaired INF type I production is responsible for severe COVID-19 among the subset of patients with the identified mutations. Patient demographic and clinical characteristics were not well described. Concentrations of IFN-ɑ were only measured in blood samples from 10 patients, all of whom had variants at the loci investigated; this limits possible inference.

Value added

This carefully conducted study suggests a mechanism for inborn susceptibility to severe COVID-19 among a subset of the population.

Our take —

This case-control study aimed to assess community and close contact exposures associated with COVID-19. This study included 154 cases and 160 controls who presented with symptoms to healthcare facilities within a US network who were tested for SARS-COV-2. COVID-19 cases were 2.4 times more likely to have reported dining at a restaurant in the 2 weeks preceding illness onset than controls. No differences between cases and controls were observed among several other community exposures. These findings should be interpreted in the context of several limitations, especially that controls were not positive for SAR-CoV-2, but they may have been infected with a pathogen with similar transmission characteristics. Although reported mask use in public spaces was high amongst both cases and controls, cases were nearly 3 times more likely to have a known COVID-19 contact many of which would have been contacts in private spaces without masks and cases were significantly higher amongst those attending restaurants where masks were not used by participants. This study suggests that restaurants may be a greater exposure risk than other community activities that do not involve eating or drinking where mask use is uncommon.

Study design

Case-Control

Study population and setting

This case-control study aimed to assess community and close contact exposures associated with COVID-19. This study included adults who were symptomatic and tested for COVID-19 the first time at one of 11 Influenza Vaccine Effectiveness in the Critically Ill (IVY) Network sites across the U.S. between the period of July 1 to 29, 2020. The study included 154 cases and 160 controls. Cases were defined as individuals with evidence of SARS-CoV-2 RNA by RT-PCR in one the networks sites and were selected by random sampling of confirmed patients within a specific time period. Controls were symptomatic individuals from the network sites who tested negative for SARS-CoV-2. Multiple controls were randomly selected for each case, matching on age, sex, and study site. Information on demographic characteristics, medical history, exposure history, community activities, and mask wearing was collected through structured retrospective interviews with participants.

Summary of Main Findings

Close contact with one or more persons with known COVID-19 was reported by 42% of cases and 14% of controls. Cases were more likely to have reported dining at a restaurant in the 2 weeks preceding illness onset than were controls (adjusted odds ratio [aOR] 2.4; 95% CI 1.5–3.8), even after restricting the analysis to participants without a known close contact to be confirmed with SARS-Cov-2 (aOR 2.8, 95% CI 1.9–4.3). Restricted analysis also suggests that cases were more likely than control to have reported going to a bar/coffee shop (aOR 3.9, 95% CI 1.5–10.1) in the 2 weeks preceding illness onset. No differences between cases and controls were observed among those who reported shopping; gatherings with ≤10 persons in a home; going to an office setting; going to a salon; gatherings with >10 persons in a home; going to a gym; using public transportation; or attending church/religious gatherings.

Study Strengths

This study attempts to differentiate between different community activity exposure risks.

Limitations

These findings should be interpreted in the context of several limitations. Authors attempted to match cases and controls at a ratio of 1:2; however, due to ineligibility or refusal to participate the matching ratio was not possible, and matching based on age and sex was not maintained. Those who agreed to participate may differ from those who did not. Participation as well as recall of exposures may have been influenced by symptom severity, and therefore the results may be subject to bias. Controls included individuals who presented at the health facility and reported symptoms, however, did not test positive for COVID-19. These patients may have illness due to another pathogen with similar exposure risks and modes of transmission. Therefore, it may be difficult to differentiate between exposure risks between cases and controls. Finally, a significant limitation was that data were not able to distinguish between indoor and outdoor dining and indoor/outdoor bar/coffee shop attendance.

Value added

This study suggests that the restaurant environment may a particular concern for risk of exposure to SARS-CoV-2 compared to other community activities that do not involve removing masks alongside being in shared indoor spaces.

Our take —

This was a retrospective study considering serial laboratory measurements from patients who had received PCR testing for SARS-CoV-2 infection at Mayo Clinic hospitals in Minnesota, Arizona, and Florida between February 15 to May 28, 2020. At the time of PCR testing for SARS-CoV-2 infection, patients who tested positive had higher mean plasma fibrinogen levels (n=51) and lower mean platelet counts (n=39) than patients who tested negative (n=233 and 649, respectively). Over the next 10 days after diagnosis, mean fibrinogen levels declined, consistent with the resolution of acute phase response, and mean platelet counts increased to levels that were higher, on average, than those among controls. Among a wider group of 2,232 patients testing positive for SARS-CoV-2, 101 (4.5%) experienced a thrombotic event within 30 days of diagnosis; 53 of these patients experienced deep vein thrombosis. Mean platelet counts and trajectories were not associated with thrombotic events, and disseminated intravascular coagulation (DIC) was rare. Although the sample was not large and selection bias was likely, this study improves the picture of coagulopathy associated with COVID-19.

Study design

Case-Control

Study population and setting

This retrospective study considered serial laboratory measurements from patients who had received PCR testing for SARS-CoV-2 infection at Mayo Clinic hospitals in Minnesota, Arizona, and Florida between February 15 to May 28, 2020. Analysis was restricted to patients who had at least three serial observations from one of 194 laboratory tests. The study included 246 patients with PCR confirmed SARS-CoV-2 infection (mean age 61 years, 56% male) and 13,666 patients who tested negative (mean age 64 years, 52% male), 2,460 of whom were selected as controls via propensity matching (using age, gender, race, anticoagulation/antiplatelet medication use, history of coagulopathies, and hospitalization status prior to PCR testing). Differences in laboratory measurements of coagulation-related markers were assessed between the two groups at pre-specified time intervals centered around the date of PCR testing. The broader cohort of 2,232 patients who tested positive for SARS-CoV-2 was used for a supplementary analysis of thrombotic events: a neural network was used to classify clinical “sentiment” from electronic medical records regarding diagnosis of coagulopathies as “yes” (confirmed diagnosis), “no” (diagnosis ruled out), “maybe,” and “other” (alternate context, e.g., family history of disease).

Summary of Main Findings

Across nine windows of time defined relative to the date of PCR testing, there were 130 comparisons (66 unique laboratory values) that significantly differed between those testing positive and negative for SARS-CoV-2 infection (at a Cohen’s D > 0.35 and a Benjamini-Hochberg-adjusted p-value < 0.05). Relative to controls with available measurements, mean plasma fibrinogen levels were higher in patients with SARS-CoV-2 infection at the time of PCR testing (529 vs. 361 mg/dL, p<0.01); this difference waned and resolved over the next 7 days. Mean pre-diagnosis platelet counts were lower in the positive group relative to controls (185 vs. 226 x 109/L, with thrombocytopenia observed in 29% of those with SARS-CoV-2 infection vs. 21% without) but increased over the next 10 days to levels that were significantly higher than those in controls. In the full cohort of 2,232 patients with a positive SARS-CoV-2 result, 101 (4.5%) experienced a clinically diagnosed thrombotic phenotype within 30 days after the PCR test; 53 of these patients had a deep vein thrombosis. The main analytic cohort of 246 SARS-CoV-2-positive patients with serial laboratory measurements contained 76 of the 101 patients with thrombosis. Among this group, platelet counts at SARS-CoV-2 diagnosis were not associated with subsequent development of thrombosis, and the degree of mean platelet increases over the next 10 days was similarly unassociated with thrombosis. Five of the 2,232 (0.2%) in the full cohort of SARS-CoV-2-positive patients exhibited symptoms consistent with disseminated intravascular coagulation (DIC).

Study Strengths

This study employed serial measurements of coagulation markers in patients infected with SARS-CoV-2, and compared trajectories to those observed in propensity-matched controls who were similar on average with respect to several determinants of coagulopathy.

Limitations

The sample of patients testing positive for SARS-CoV-2 with serial coagulation marker measurements was small, and most were white (63%), making it difficult to generalize to the broader population of COVID-19 patients. Those with serial measurements available are likely different from the wider population; for example, they probably represent more severe disease and are at higher risk for thrombotic events. The occurrence of thrombotic events among the control group of patients testing negative for SARS-CoV-2 was not reported, preventing any inference about the role of SARS-CoV-2 infection in thrombosis. The timing of PCR testing may have varied considerably with respect to the date of infection or symptom onset, which could have muddied the observed trends and comparisons. Finally, there may have been additional unmeasured determinants of serial testing that were related to the probability of experiencing coagulopathy; if so, results could be biased in an unpredictable manner. Analysis of laboratory markers was limited to individuals with available measurements, which were often a small subset of cases and controls. This selection likely undermines any benefit of propensity-score matching for control of confounding. Controls were selected at the time of their first negative SARS-CoV-2 test, as long as they did not have a positive test later, whereas cases were selected at the time of their first positive test, regardless of how many negative tests they had previously. This means that individuals with more testing for COVID-19 would be more likely to be selected as cases.

Value added

This study is one of the few published longitudinal analyses of coagulopathy in COVID-19 that also considered a control group of comparable patients who tested negative for SARS-CoV-2.

Our take —

Immune responses to COVID-19 are not well understood, but evidence suggests that they may be crucial to patient outcomes. This analysis considered a very large number of immune responses to COVID-19 among hospitalized patients, noting considerable heterogeneity in responses, but identifying several broad patterns. Most patients showed a strong plasmablast response, and subgroups of patients exhibited B cell and T cell activation and proliferation that persisted for at least 7 days. Although the authors identified three “immunotypes” associated with disease severity, more studies are required to determine whether these immune response clusters are present in the broader population of COVID-19 patients.

Study design

Case-Control

Study population and setting

This study included blood samples from 125 hospitalized patients (median age 60 years, 51% male, 68% African-American) with laboratory-confirmed COVID-19 at the University of Pennsylvania (collected 1-3 days after admission and 7 days after admission for those who remained hospitalized), along with samples from 36 non-hospitalized patients who had recovered from COVID-19, and from 60 healthy donors. Flow cytometry was used to analyze peripheral blood mononuclear cells (PBMCs) with respect to a large number of immunological markers.

Summary of Main Findings

Among the 125 hospitalized patients, 83% had cardiovascular comorbidities, 30% required mechanical ventilation, and 14% died. Most hospitalized patients had elevated concentrations of inflammatory biomarkers such as CRP, d-dimer, and ferritin; troponin levels were also commonly elevated. Nearly half of hospitalized patients were clinically lymphopenic, but most had normal monocyte, eosinophil, and basophil counts. In principal components analysis of 193 immune parameters, the immune profile of hospitalized patients was clearly distinct from that in recovered and healthy donors, while recovered and healthy donors exhibited overlap. Approximately 80% of hospitalized patients exhibited CD8+ T cell activation above the levels seen in the control groups. There was a heterogeneous degree of CD4+ T cell response, with some distinct proliferating subpopulations of CD4+ T cells. In a subset of 8 SARS-CoV-2-negative blood samples, inflammatory cytokines and chemokines were elevated. Naive B cell counts were similar in hospitalized patients relative to controls, but there were significant changes in B cell subpopulation frequencies that did not appear to be related to systemic inflammation. Approximately two-thirds of hospitalized patients exhibited significantly elevated plasmablast (PB) frequency; declines in memory B cell frequencies and loss of CXCR5 expression were also commonly seen. In a subset of patients hospitalized for at least 7 days (n=48), changes in T cell and B cell responses between admission and day 7 were highly heterogeneous. More severe disease was associated with lower frequencies of CD4+ and CD8+ T cells, but there were no significant associations between temporal changes in B or T cell response and clinical severity. The authors used Uniform Manifold Approximation and Projection (UMAP) to identify clusters of immune response and correlate them with clinical outcomes; they defined three “immunotypes” having varying correlations with disease severity.

Study Strengths

The primary strengths of this study are the very large number of immune parameters considered, and the detailed manner in which variations in these parameters was assessed.

Limitations

Patients providing samples for analysis (n=125) were not large in number, and were limited to a single institution. Little information was provided about patient selection and eligibility criteria. Clusters of immune response observed, and their correlation with clinical severity, may not be generalizable to other populations. Although analyses attempted to adjust for age, sex, and race, they did not appear to adjust for comorbidities. In addition to comorbidity data, there may be other uncontrolled confounding variables associated with both immune parameters and clinical outcomes, such as (for example) cigarette smoking.

Value added

This study provided highly detailed measurements of a wide variety of immune responses to COVID-19, and outlined some broad patterns worthy of further research.

Our take —

This case-control study from Spain and Italy, available as a preprint and thus not yet peer reviewed, provides the first large-scale evidence of host genetic influence in severe COVID-19 disease, and identifies biological targets for further investigation. This analysis was only conducted in European populations, however these genetic variants do not vary widely between ancestries, and therefore should be similar across populations. Furthermore this study does not support a biological explanation for racial/ethnic disparities in COVID-19 morbidity and mortality both within the United States and globally. Finally, replication studies are needed with better control definitions and clinical characterizations to clarify the role of human genetics in COVID-19 severity, instead of overall frailty.

Study design

Case-Control

Study population and setting

A total of 1,610 patients with severe COVID-19 defined by hospitalization with respiratory failure were recruited from seven medical centers in Spain and Italy, and compared to 2,205 randomly selected blood donors. Population based-controls were significantly younger than cases; data were unavailable regarding pre-existing comorbidities or other relevant risk factors for COVID-19.

Summary of Main Findings

A genome-wide association study (GWAS) estimated the association between ~8 million single nucleotide polymorphisms (SNPs) across the human genome, adjusting for population substructure, age, and sex separately by country and then combined with a fixed-effects meta-analysis. Two regions were identified and met the threshold of genome-wide significance (P<10^-8): a region on chromosome 3 upstream of a solute carrier (SLC6A209) and a region on chromosome 9 overlapping the ABO blood group gene. Further analyses found a protective effect for blood group O, and an elevated risk for A positive individuals.

Study Strengths

By limiting cases to those hospitalized with documented COVID-19, the analysis is more likely to capture the host genetics underlying severe disease sequelae.

Limitations

This study uses population controls that are not documented to be exposed or tested for COVID-19, which could dilute the true effect size. Additionally, the combination of different age distributions in cases and controls (controls being significantly younger), and the lack of availability of additional clinical information such as comorbidities, makes the association inference unclear. The associated genetic regions may reflect a COVID-19-specific morbidity, an existing co-morbidity, or generally poorer health in an older population.

Value added

This study provides evidence that genetic variants may be partially responsible for differences in COVID-19 severity.