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As the biomedical community produces datasets that are increasingly complex and high dimensional, there is a need for more sophisticated computational tools to extract biological insights. We present Multiscale PHATE, a method that sweeps through all levels of data granularity to learn abstracted biological features directly predictive of disease outcome. Built on a coarse-graining process called diffusion condensation, Multiscale PHATE learns a data topology that can be analyzed at coarse resolutions for high-level summarizations of data and at fine resolutions for detailed representations of subsets. We apply Multiscale PHATE to a coronavirus disease 2019 (COVID-19) dataset with 54 million cells from 168 hospitalized patients and find that patients who die show CD16(hi)CD66b(lo) neutrophil and IFN-γ(+) granzyme B(+) Th17 cell responses. We also show that population groupings from Multiscale PHATE directly fed into a classifier predict disease outcome more accurately than naive featurizations of the data. Multiscale PHATE is broadly generalizable to different data types, including flow cytometry, single-cell RNA sequencing (scRNA-seq), single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq), and clinical variables.

The impact of coronavirus disease 2019 (COVID-19) mRNA vaccination on pregnancy and fertility has become a major topic of public interest. We investigated two of the most widely propagated claims to determine 1) whether COVID-19 mRNA vaccination of mice during early pregnancy is associated with an increased incidence of birth defects or growth abnormalities, and 2) whether COVID-19 mRNA-vaccinated human volunteers exhibit elevated levels of antibodies to the human placental protein syncytin-1. Using a mouse model, we found that intramuscular COVID-19 mRNA vaccination during early pregnancy at gestational age E7.5 did not lead to differences in fetal size by crown-rump length or weight at term, nor did we observe any gross birth defects. In contrast, injection of the TLR3 agonist and double-stranded RNA mimic polyinosinic-polycytidylic acid, or poly(I:C), impacted growth in utero leading to reduced fetal size. No overt maternal illness following either vaccination or poly(I:C) exposure was observed. We also found that term fetuses from vaccinated murine pregnancies exhibit high circulating levels of anti-Spike and anti-RBD antibodies to SARS-CoV-2 consistent with maternal antibody status, indicating transplacental transfer. Finally, we did not detect increased levels of circulating anti-syncytin-1 antibodies in a cohort of COVID-19 vaccinated adults compared to unvaccinated adults by ELISA. Our findings contradict popular claims associating COVID-19 mRNA vaccination with infertility and adverse neonatal outcomes.

Efficient quantitative assays for measurement of viral replication and infectivity are indispensable for future endeavors to develop prophylactic or therapeutic antiviral drugs or vaccines against SARS-CoV-2. We developed a SARS-CoV-2 cell-cell transmission assay that provides a rapid and quantitative readout to assess SARS-CoV-2 spike hACE2 interaction in the absence of pseudotyped particles or live virus. We established two well-behaved stable cell lines, which demonstrated a remarkable correlation with standard cell-free viral pseudotyping for inhibition by convalescent sera, small-molecule drugs, and murine anti-spike monoclonal antibodies. The assay is rapid, reliable, and highly reproducible, without a requirement for any specialized research reagents or laboratory equipment and should be easy to adapt for use in most investigative and clinical settings. It can be effectively used or modified for high-throughput screening for compounds and biologics that interfere with virus-cell binding and entry to complement other neutralization assays currently in use.

The COVID-19 pandemic has affected more than 20 million people worldwide with mortality exceeding 800,000 patients. Risk factors associated with severe disease and mortality include advanced age, hypertension, diabetes, and obesity. Each of these risk factors pathologically disrupts the lipidome, including immunomodulatory eicosanoids and docosanoids lipid mediators (LM). We hypothesized that dysregulation of LMs may be a defining feature of the severity of COVID-19. By examining LMs and polyunsaturated fatty acid precursor lipids in serum from hospitalized COVID-19 patients, we demonstrate that moderate and severe disease are separated by specific differences in abundance of immune-regulatory and pro-inflammatory LMs. This difference in LM balance corresponded with decreased LM products of ALOX12 and COX2 and an increase LMs products of ALOX5 and cytochrome p450. Given the important immune regulatory role of LMs, these data provide mechanistic insight into an immuno-lipidomic imbalance in severe COVID-19.

The COVID-19 pandemic has affected more than 10 million people worldwide with mortality exceeding3 half a million patients. Risk factors associated with severe disease and mortality include advanced age,4 hypertension, diabetes, and obesity.1 Clear mechanistic understanding of how these comorbidities5 converge to enable severe infection is lacking. Notably each of these risk factors pathologically disrupts6 the lipidome and this disruption may be a unifying feature of severe COVID-19.1-7 Here we provide the first in depth interrogation of lipidomic changes, including structural-lipids as well as the eicosanoids and docosanoids lipid mediators (LMs), that mark COVID-19 disease severity. Our data reveal that progression from moderate to severe disease is marked by a loss of specific immune regulatory LMs and increased pro-inflammatory species. Given the important immune regulatory role of LMs, these data provide mechanistic insight into the immune balance in COVID-19 and potential targets for therapy with currently approved pharmaceuticals.8

A growing body of evidence indicates sex differences in the clinical outcomes of coronavirus disease 2019 (COVID-19)1-4. However, whether immune responses against SARS-CoV-2 differ between sexes, and whether such differences explain male susceptibility to COVID-19, is currently unknown. In this study, we examined sex differences in viral loads, SARS-CoV-2-specific antibody titers, plasma cytokines, as well as blood cell phenotyping in COVID-19 patients. By focusing our analysis on patients with mild to moderate disease who had not received immunomodulatory medications, our results revealed that male patients had higher plasma levels of innate immune cytokines and chemokines including IL-8, IL-18, and CCL5, along with more robust induction of non-classical monocytes. In contrast, female patients mounted significantly more robust T cell activation than male patients during SARS-CoV-2 infection, which was sustained in old age. Importantly, we found that a poor T cell response negatively correlated with patients’ age and was predictive of worse disease outcome in male patients, but not in female patients. Conversely, higher innate immune cytokines in female patients associated with worse disease progression, but not in male patients. These findings reveal a possible explanation underlying observed sex biases in COVID-19, and provide important basis for the development of sex-based approach to the treatment and care of men and women with COVID-19.

Rationale and Objective Acute kidney injury (AKI) is common in patients with COVID-19 and associated with poor outcomes. Urinary biomarkers have been associated with adverse kidney outcomes in other settings and may provide additional prognostic information in patients with COVID-19. We investigated the association between urinary biomarkers with adverse kidney outcomes among patients hospitalized with COVID-19. Study Design Prospective cohort study. Setting and Participants Patients hospitalized with COVID-19 (n=153) at 2 academic medical centers between April and June 2020. Exposures 19 urinary biomarkers of injury, inflammation, and repair. Outcomes Composite of KDIGO stage 3 AKI, requirement for dialysis, or death within 60 days of hospital admission. We also compared various kidney biomarker levels in the setting of COVID-19 versus other common AKI settings. Analytic Approach Time-varying Cox proportional hazards regression to associate biomarker level with composite outcome. Results Out of 153 patients, 24 (15.7%) experienced the primary outcome. Two-fold higher levels of neutrophil gelatinase-associated lipocalin (NGAL) (HR: 1.34; 95% CI: 1.14-1.57), monocyte chemoattractant protein (MCP-1) (HR: 1.42; 95% CI: 1.09-1.84), and kidney injury molecule-1 (KIM-1) (HR: 2.03; 95% CI: 1.38-2.99) were associated with highest risk of sustaining primary composite outcome. Higher epidermal growth factor (EGF) levels were associated with a lower risk of the primary outcome (HR 0.61; 95% CI: 0.47-0.79). Individual biomarkers provided moderate discrimination and biomarker combinations improved discrimination for the primary outcome. The degree of kidney injury by biomarker level in COVID-19 was comparable to other settings of clinical AKI. There was evidence of subclinical AKI in COVID-19 patients based on elevated injury biomarker level in patients without clinical AKI defined by serum creatinine. Limitations Small sample size with low number of composite outcome events. Conclusion Urinary biomarkers are associated with adverse kidney outcomes in patients hospitalized with COVID-19 and may provide valuable information to monitor kidney disease progression and recovery., Graphical abstract