High rates of SARS-CoV-2 infection in pregnant Ugandan women and association with stunting in infancy (preprint)

Background: SARS-CoV-2 has been well studied in resource-rich areas but many questions remain about effects of infection in African populations, particularly in vulnerable groups such as pregnant women. Methods: We describe SARS-CoV-2 immunoglobulin (Ig) G and IgM antibody responses and clinical outcomes in mother-infant dyads enrolled in malaria chemoprevention trials in Uganda. Results: From December 2020 to February 2022, among 400 unvaccinated pregnant women, serologic assessments revealed that 128 (32%) were seronegative for anti-SARS-CoV-2 IgG and IgM at enrollment and delivery, 80 (20%) were infected either prior to or early in pregnancy, and 192 (48%) were infected or re-infected with SARS-CoV-2 during pregnancy. We observed preferential binding of plasma IgG to Wuhan-Hu-1-like antigens in individuals seroconverting up to early 2021, and to Delta variant antigens in a subset of individuals in mid-2021. Breadth of IgG binding to all variants improved over time. No participants experienced severe respiratory illness during the study. SARS-CoV-2 infection in early pregnancy was associated with lower median length-for-age Z-score at age 3 months compared with no infection or late pregnancy infection (-1.54 versus -0.37 and -0.51, p=0.009). Conclusion: Pregnant Ugandan women experienced high levels of SARS-CoV-2 infection without severe respiratory illness. Variant-specific serology testing demonstrated evidence of antibody affinity maturation at the population level. Early gestational SARS-CoV-2 infection was associated with shorter stature in early infancy.

TNFα-producing CD4+ T cells dominate the SARS-CoV-2-specific T cell response in COVID-19 outpatients and are associated with durable antibodies (preprint)

SARS-CoV-2-specific CD4+ T cells are likely important in immunity against COVID-19, but our understanding of CD4+ longitudinal dynamics following infection and specific features that correlate with the maintenance of neutralizing antibodies remains limited. We characterized SARS-CoV-2-specific CD4+ T cells in a longitudinal cohort of 109 COVID-19 outpatients. The quality of the SARS-CoV-2-specific CD4+ response shifted from cells producing IFN{gamma} to TNF+ from five days to four months post-enrollment, with IFN{gamma}-IL21-TNF+ CD4+ T cells the predominant population detected at later timepoints. Greater percentages of IFN{gamma}-IL21-TNF+ CD4+ T cells on day 28 correlated with SARS-CoV-2 neutralizing antibodies measured seven months post-infection ({rho}=0.4, P=0.01). mRNA vaccination following SARS-CoV-2 infection boosted both IFN{gamma} and TNF producing, spike protein-specific CD4+ T cells. These data suggest that SARS-CoV-2-specific, TNF-producing CD4+ T cells may play an important role in antibody maintenance following COVID-19.

Early immune responses have long-term associations with clinical, virologic, and immunologic outcomes in patients with COVID-19 (preprint)

The great majority of SARS-CoV-2 infections are mild and uncomplicated, but some individuals with initially mild COVID-19 progressively develop more severe symptoms. Furthermore, mild to moderate infections are an important contributor to ongoing transmission. There remains a critical need to identify host immune biomarkers predictive of clinical and virologic outcomes in SARS-CoV-2-infected patients. Leveraging longitudinal samples and data from a clinical trial of Peginterferon Lambda for treatment of SARS-CoV-2 infected outpatients, we used host proteomics and transcriptomics to characterize the trajectory of the immune response in COVID-19 patients within the first 2 weeks of symptom onset. We define early immune signatures, including plasma levels of RIG-I and the CCR2 ligands (MCP1, MCP2 and MCP3), associated with control of oropharyngeal viral load, the degree of symptom severity, and immune memory (including SARS-CoV-2-specific T cell responses and spike (S) protein-binding IgG levels). We found that individuals receiving BNT162b2 (Pfizer-BioNTech) vaccine had similar early immune trajectories to those observed in this natural infection cohort, including the induction of both inflammatory cytokines (e.g. MCP1) and negative immune regulators (e.g. TWEAK). Finally, we demonstrate that machine learning models using 8-10 plasma protein markers measured early within the course of infection are able to accurately predict symptom severity, T cell memory, and the antibody response post-infection.

Early immune responses have long-term associations with clinical, virologic, and immunologic outcomes in patients with COVID-19 (preprint)

The great majority of SARS-CoV-2 infections are mild and uncomplicated, but some individuals with initially mild COVID-19 progressively develop more severe symptoms. Furthermore, there is substantial heterogeneity in SARS-CoV-2-specific memory immune responses following infection. There remains a critical need to identify host immune biomarkers predictive of clinical and immunologic outcomes in SARS-CoV-2-infected patients. Leveraging longitudinal samples and data from a clinical trial in SARS-CoV-2 infected outpatients, we used host proteomics and transcriptomics to characterize the trajectory of the immune response in COVID-19 patients within the first 2 weeks of symptom onset. We identify early immune signatures, including plasma RIG-I levels, early interferon signaling, and related cytokines (CXCL10, MCP1, MCP-2 and MCP-3) associated with subsequent disease progression, control of viral shedding, and the SARS-CoV-2 specific T cell and antibody response measured up to 7 months after enrollment. We found that several biomarkers for immunological outcomes are shared between individuals receiving BNT162b2 (Pfizer–BioNTech) vaccine and COVID-19 patients. Finally, we demonstrate that machine learning models using 7-10 plasma protein markers measured early within the course of infection are able to accurately predict disease progression, T cell memory, and the antibody response post-infection in a second, independent dataset.