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BACKGROUNDPatients hospitalized for COVID-19 exhibit diverse clinical outcomes, with outcomes for some individuals diverging over time even though their initial disease severity appears similar to that of other patients. A systematic evaluation of molecular and cellular profiles over the full disease course can link immune programs and their coordination with progression heterogeneity.METHODSWe performed deep immunophenotyping and conducted longitudinal multiomics modeling, integrating 10 assays for 1,152 Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) study participants and identifying several immune cascades that were significant drivers of differential clinical outcomes.RESULTSIncreasing disease severity was driven by a temporal pattern that began with the early upregulation of immunosuppressive metabolites and then elevated levels of inflammatory cytokines, signatures of coagulation, formation of neutrophil extracellular traps, and T cell functional dysregulation. A second immune cascade, predictive of 28-day mortality among critically ill patients, was characterized by reduced total plasma Igs and B cells and dysregulated IFN responsiveness. We demonstrated that the balance disruption between IFN-stimulated genes and IFN inhibitors is a crucial biomarker of COVID-19 mortality, potentially contributing to failure of viral clearance in patients with fatal illness.CONCLUSIONOur longitudinal multiomics profiling study revealed temporal coordination across diverse omics that potentially explain the disease progression, providing insights that can inform the targeted development of therapies for patients hospitalized with COVID-19, especially those who are critically ill.TRIAL REGISTRATIONClinicalTrials.gov NCT04378777.FUNDINGNIH (5R01AI135803-03, 5U19AI118608-04, 5U19AI128910-04, 4U19AI090023-11, 4U19AI118610-06, R01AI145835-01A1S1, 5U19AI062629-17, 5U19AI057229-17, 5U19AI125357-05, 5U19AI128913-03, 3U19AI077439-13, 5U54AI142766-03, 5R01AI104870-07, 3U19AI089992-09, 3U19AI128913-03, and 5T32DA018926-18); NIAID, NIH (3U19AI1289130, U19AI128913-04S1, and R01AI122220); and National Science Foundation (DMS2310836).

The glycosylation of IgG plays a critical role during human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, activating immune cells and inducing cytokine production. However, the role of IgM N-glycosylation has not been studied during human acute viral infection. The analysis of IgM N-glycosylation from healthy controls and hospitalized coronavirus disease 2019 (COVID-19) patients reveals increased high-mannose and sialylation that correlates with COVID-19 severity. These trends are confirmed within SARS-CoV-2-specific immunoglobulin N-glycan profiles. Moreover, the degree of total IgM mannosylation and sialylation correlate significantly with markers of disease severity. We link the changes of IgM N-glycosylation with the expression of Golgi glycosyltransferases. Lastly, we observe antigen-specific IgM antibody-dependent complement deposition is elevated in severe COVID-19 patients and modulated by exoglycosidase digestion. Taken together, this work links the IgM N-glycosylation with COVID-19 severity and highlights the need to understand IgM glycosylation and downstream immune function during human disease.

Vaccination to prevent infectious disease is one of the most successful public health interventions ever developed. And yet, variability in individual vaccine effectiveness suggests that a better mechanistic understanding of vaccine-induced immune responses could improve vaccine design and efficacy. We have previously shown that protective antibody levels could be elicited in a subset of recipients with only a single dose of the hepatitis B virus (HBV) vaccine and that a wide range of antibody levels were elicited after three doses. The immune mechanisms responsible for this vaccine response variability is unclear. Using single cell RNA sequencing of sorted innate immune cell subsets, we identified two distinct myeloid dendritic cell subsets (NDRG1-expressing mDC2 and CDKN1C-expressing mDC4), the ratio of which at baseline (pre-vaccination) correlated with the immune response to a single dose of HBV vaccine. Our results suggest that the participants in our vaccine study were in one of two different dendritic cell dispositional states at baseline - an NDRG2-mDC2 state in which the vaccine elicited an antibody response after a single immunization or a CDKN1C-mDC4 state in which the vaccine required two or three doses for induction of antibody responses. To explore this correlation further, genes expressed in these mDC subsets were used for feature selection prior to the construction of predictive models using supervised canonical correlation machine learning. The resulting models showed an improved correlation with serum antibody titers in response to full vaccination. Taken together, these results suggest that the propensity of circulating dendritic cells toward either activation or suppression, their "dispositional endotype" at pre-vaccination baseline, could dictate response to vaccination.

BackgroundVaccination remains one of the most effective means of reducing the burden of infectious diseases globally. Improving our understanding of the molecular basis for effective vaccine response is of paramount importance if we are to ensure the success of future vaccine development efforts.MethodsWe applied cutting edge multi-omics approaches to extensively characterize temporal molecular responses following vaccination with hepatitis B virus (HBV) vaccine. Data were integrated across cellular, epigenomic, transcriptomic, proteomic, and fecal microbiome profiles, and correlated to final HBV antibody titres.ResultsUsing both an unsupervised molecular-interaction network integration method (NetworkAnalyst) and a data-driven integration approach (DIABLO), we uncovered baseline molecular patterns and pathways associated with more effective vaccine responses to HBV. Biological associations were unravelled, with signalling pathways such as JAK-STAT and interleukin signalling, Toll-like receptor cascades, interferon signalling, and Th17 cell differentiation emerging as important pre-vaccination modulators of response.ConclusionThis study provides further evidence that baseline cellular and molecular characteristics of an individual's immune system influence vaccine responses, and highlights the utility of integrating information across many parallel molecular datasets.

Fibrotic interstitial lung diseases (ILDs) result from excessive deposition of extracellular matrix (ECM) proteins in the lung, causing irreversible damage to the lung architecture. Clinical management of ILDs differs depending on the diagnosis, but differentiation between subtypes can be difficult and better clinical biomarkers are needed. In this study, we use a 166-gene NanoString assay to investigate whether there are ILD subtype-specific transcripts in whole blood. We identified one transcript, killer cell lectin like receptor 1 (KLRF1), as differentially expressed between idiopathic pulmonary fibrosis (IPF) and systemic sclerosis-associated ILD (SSc-ILD), and identified two transcripts (VCAN, LTK) associated with IPF expression against other ILD subtypes. These findings were validated by examining their expression in ILD lung, with KLRF1 expression significantly higher in SSc-ILD compared to IPF and hypersensitivity pneumonitis (HP) samples. Taken together, this pilot study provides support for the use of the peripheral transcriptome in identifying diagnostic biomarkers of ILD with biological relevance. [ABSTRACT FROM AUTHOR]

Rationale: The factors that lead to poor pulmonary exacerbation (PEx) outcomes in individuals with cystic fibrosis (CF) are still being investigated; however, delayed diagnosis and treatment are likely contributory. Identifying individuals at imminent risk of PEx could enable closer monitoring and/or earlier initiation of therapies to improve outcomes. Objectives: The goal of this study was to develop blood-based biomarkers that associate with imminent PEx risk in individuals with CF. Methods: We examined the whole-blood transcriptome and 55 inflammatory proteins from plasma and serum on 72 blood samples from 53 individuals with CF. Biomarker candidate genes and proteins were selected from 14 individuals with CF with paired stable and PEx visits (cohort 1). The biomarker candidates were then estimated and tested to classify individuals with CF who would experience a PEx within 4 months of a stable clinic visit or not (cohort 2). Results: A 16-gene panel and 9-protein panel were identified that could distinguish paired stable and PEx visits (area under the receiver operating characteristic curve [AUC] ± standard error = 0.83 ± 0.28 and 0.92 ± 0.18, respectively). These two panels also demonstrated strong performance in classifying individuals with CF who would experience a PEx within 4 months of a clinically stable visit or not (16-gene panel: AUC = 0.88; 9-protein panel: AUC = 0.83). In comparison, serum calprotectin and clinical variables (i.e., sex, precent predicted forced expiratory volume in 1 s, and the number of IV antibiotics in the preceding year) had AUCs of 0.75 and 0.71, respectively. Conclusions: Blood-based mRNA and protein biomarkers demonstrated strong performance in classifying individuals with CF at risk of imminent PEx. If the findings from this study can be validated, there is the potential to use blood biomarkers to enable more personalized disease activity monitoring in CF. [ABSTRACT FROM AUTHOR]

Previously incarcerated youth reintegrating into their communities face many challenges. This study provided visual entry into the lives of three youth through the use of Photovoice methodology. Participants included three males, two Latinos and one White non-Latino, who had successfully been reentered into their communities for at least four months. During the eight-week program, participants photographed images of importance to them in their homes and communities. These were discussed and ultimately shared through a community photo exhibit. The resulting themes, related to their perceived supports and challenges to successful reentry, are presented with implications for supporting youth in their community reintegration.

Over the past few decades, diversity and multiculturalism have received considerable attention in the field of psychology. While there have been notable efforts to ensure these important areas are addressed in undergraduate psychology training, little is known about this undertaking. The present study examined how diversity and multiculturalism were addressed in the course titles and course descriptions of 200 undergraduate, psychology programs across North America and their corresponding general education programs. Analyses revealed that while most undergraduate psychology programs offered diversity or multicultural courses, very few programs required these courses. Moreover, when these courses were offered, they typically examined diversity or multiculturalism in a singular fashion, giving very little attention to the intersectionality that exists among cultural factors. With respect to the institutions' general education programs, we found that while some institutions had a multicultural awareness requirement, few offered or required psychology-based diversity or multicultural courses of their psychology students. Implications of these finding are considered, and several recommendations and resources for improving undergraduate psychology programs are provided.

Understanding the epidemiology of long COVID and emerging variants has significant public-health implications as physical interventions and restrictions that help limit viral spread are eased globally. Here, we provide rationales for the necessity of updating current vaccines to improve protection against omicron and emerging variants, as well as more research into understanding the epidemiology and mechanisms of long COVID. [ABSTRACT FROM AUTHOR]

The Expanded Program for Immunization Consortium – Human Immunology Project Consortium study aims to employ systems biology to identify and characterize vaccine-induced biomarkers that predict immunogenicity in newborns. Key to this effort is the establishment of the Data Management Core (DMC) to provide reliable data and bioinformatic infrastructure for centralized curation, storage, and analysis of multiple de-identified "omic" datasets. The DMC established a cloud-based architecture using Amazon Web Services to track, store, and share data according to National Institutes of Health standards. The DMC tracks biological samples during collection, shipping, and processing while capturing sample metadata and associated clinical data. Multi-omic datasets are stored in access-controlled Amazon Simple Storage Service (S3) for data security and file version control. All data undergo quality control processes at the generating site followed by DMC validation for quality assurance. The DMC maintains a controlled computing environment for data analysis and integration. Upon publication, the DMC deposits finalized datasets to public repositories. The DMC architecture provides resources and scientific expertise to accelerate translational discovery. Robust operations allow rapid sharing of results across the project team. Maintenance of data quality standards and public data deposition will further benefit the scientific community. [ABSTRACT FROM AUTHOR]