Early immune factors associated with the development of post-acute sequelae of SARS-CoV-2 infection in hospitalized and non-hospitalized individuals.

Background: Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can lead to post-acute sequelae of SARS-CoV-2 (PASC) that can persist for weeks to years following initial viral infection. Clinical manifestations of PASC are heterogeneous and often involve multiple organs. While many hypotheses have been made on the mechanisms of PASC and its associated symptoms, the acute biological drivers of PASC are still unknown. Methods: We enrolled 494 patients with COVID-19 at their initial presentation to a hospital or clinic and followed them longitudinally to determine their development of PASC. From 341 patients, we conducted multi-omic profiling on peripheral blood samples collected shortly after study enrollment to investigate early immune signatures associated with the development of PASC. Results: During the first week of COVID-19, we observed a large number of differences in the immune profile of individuals who were hospitalized for COVID-19 compared to those individuals with COVID-19 who were not hospitalized. Differences between individuals who did or did not later develop PASC were, in comparison, more limited, but included significant differences in autoantibodies and in epigenetic and transcriptional signatures in double-negative 1 B cells, in particular. Conclusions: We found that early immune indicators of incident PASC were nuanced, with significant molecular signals manifesting predominantly in double-negative B cells, compared with the robust differences associated with hospitalization during acute COVID-19. The emerging acute differences in B cell phenotypes, especially in double-negative 1 B cells, in PASC patients highlight a potentially important role of these cells in the development of PASC.

Distinct temporal trajectories and risk factors for Post-acute sequelae of SARS-CoV-2 infection.

Background: The understanding of Post-acute sequelae of SARS-CoV-2 infection (PASC) can be improved by longitudinal assessment of symptoms encompassing the acute illness period. To gain insight into the various disease trajectories of PASC, we assessed symptom evolution and clinical factors associated with the development of PASC over 3 months, starting with the acute illness period. Methods: We conducted a prospective cohort study to identify parameters associated with PASC. We performed cluster and case control analyses of clinical data, including symptomatology collected over 3 months following infection. Results: We identified three phenotypic clusters associated with PASC that could be characterized as remittent, persistent, or incident based on the 3-month change in symptom number compared to study entry: remittent (median; min, max: -4; -17, 3), persistent (-2; -14, 7), or incident (4.5; -5, 17) (p = 0.041 remittent vs. persistent, p < 0.001 remittent vs. incident, p < 0.001 persistent vs. incident). Despite younger age and lower hospitalization rates, the incident phenotype had a greater number of symptoms (15; 8, 24) and a higher proportion of participants with PASC (63.2%) than the persistent (6; 2, 9 and 52.2%) or remittent clusters (1; 0, 6 and 18.7%). Systemic corticosteroid administration during acute infection was also associated with PASC at 3 months [OR (95% CI): 2.23 (1.14, 4.36)]. Conclusion: An incident disease phenotype characterized by symptoms that were absent during acute illness and the observed association with high dose steroids during acute illness have potential critical implications for preventing PASC.

Multi-omic profiling reveals early immunological indicators for identifying COVID-19 Progressors.

We sought to better understand the immune response during the immediate post-diagnosis phase of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by identifying molecular associations with longitudinal disease outcomes. Multi-omic analyses identified differences in immune cell composition, cytokine levels, and cell subset-specific transcriptomic and epigenomic signatures between individuals on a more serious disease trajectory (Progressors) as compared to those on a milder course (Non-progressors). Higher levels of multiple cytokines were observed in Progressors, with IL-6 showing the largest difference. Blood monocyte cell subsets were also skewed, showing a comparative decrease in non-classical CD14-CD16+ and intermediate CD14+CD16+ monocytes. In lymphocytes, the CD8+ T effector memory cells displayed a gene expression signature consistent with stronger T cell activation in Progressors. These early stage observations could serve as the basis for the development of prognostic biomarkers of disease risk and interventional strategies to improve the management of severe COVID-19. BACKGROUND: Much of the literature on immune response post-SARS-CoV-2 infection has been in the acute and post-acute phases of infection. TRANSLATIONAL SIGNIFICANCE: We found differences at early time points of infection in approximately 160 participants. We compared multi-omic signatures in immune cells between individuals progressing to needing more significant medical intervention and non-progressors. We observed widespread evidence of a state of increased inflammation associated with progression, supported by a range of epigenomic, transcriptomic, and proteomic signatures. The signatures we identified support other findings at later time points and serve as the basis for prognostic biomarker development or to inform interventional strategies.

Multi-omic Profiling Reveals Early Immunological Indicators for Identifying COVID-19 Progressors.

The pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to a rapid response by the scientific community to further understand and combat its associated pathologic etiology. A focal point has been on the immune responses mounted during the acute and post-acute phases of infection, but the immediate post-diagnosis phase remains relatively understudied. We sought to better understand the immediate post-diagnosis phase by collecting blood from study participants soon after a positive test and identifying molecular associations with longitudinal disease outcomes. Multi-omic analyses identified differences in immune cell composition, cytokine levels, and cell subset-specific transcriptomic and epigenomic signatures between individuals on a more serious disease trajectory (Progressors) as compared to those on a milder course (Non-progressors). Higher levels of multiple cytokines were observed in Progressors, with IL-6 showing the largest difference. Blood monocyte cell subsets were also skewed, showing a comparative decrease in non-classical CD14-CD16+ and intermediate CD14+CD16+ monocytes. Additionally, in the lymphocyte compartment, CD8+ T effector memory cells displayed a gene expression signature consistent with stronger T cell activation in Progressors. Importantly, the identification of these cellular and molecular immune changes occurred at the early stages of COVID-19 disease. These observations could serve as the basis for the development of prognostic biomarkers of disease risk and interventional strategies to improve the management of severe COVID-19.

Supervised Machine Learning with CITRUS for Single Cell Biomarker Discovery.

CITRUS is a supervised machine learning algorithm designed to analyze single cell data, identify cell populations, and identify changes in the frequencies or functional marker expression patterns of those populations that are significantly associated with an outcome. The algorithm is a black box that includes steps to cluster cell populations, characterize these populations, and identify the significant characteristics. This chapter describes how to optimize the use of CITRUS by combining it with upstream and downstream data analysis and visualization tools.

Morphological profiling using machine learning reveals emergent subpopulations of interferon-γ-stimulated mesenchymal stromal cells that predict immunosuppression.

BACKGROUND: Although a preponderance of pre-clinical data demonstrates the immunosuppressive potential of mesenchymal stromal cells (MSCs), significant heterogeneity and lack of critical quality attributes (CQAs) based on immunosuppressive capacity likely have contributed to inconsistent clinical outcomes. This heterogeneity exists not only between MSC lots derived from different donors, tissues and manufacturing conditions, but also within a given MSC lot in the form of functional subpopulations. We therefore explored the potential of functionally relevant morphological profiling (FRMP) to identify morphological subpopulations predictive of the immunosuppressive capacity of MSCs derived from multiple donors, manufacturers and passages. METHODS: We profiled the single-cell morphological response of MSCs from different donors and passages to the functionally relevant inflammatory cytokine interferon (IFN)-γ. We used the machine learning approach visual stochastic neighbor embedding (viSNE) to identify distinct morphological subpopulations that could predict suppression of activated CD4+ and CD8+ T cells in a multiplexed quantitative assay. RESULTS: Multiple IFN-γ-stimulated subpopulations significantly correlated with the ability of MSCs to inhibit CD4+ and CD8+ T-cell activation and served as effective CQAs to predict the immunosuppressive capacity of additional manufactured MSC lots. We further characterized the emergence of morphological heterogeneity following IFN-γ stimulation, which provides a strategy for identifying functional subpopulations for future single-cell characterization and enrichment techniques. DISCUSSION: This work provides a generalizable analytical platform for assessing functional heterogeneity based on single-cell morphological responses that could be used to identify novel CQAs and inform cell manufacturing decisions.

Multivariate Computational Analysis of Gamma Delta T Cell Inhibitory Receptor Signatures Reveals the Divergence of Healthy and ART-Suppressed HIV+ Aging.

Even with effective viral control, HIV-infected individuals are at a higher risk for morbidities associated with older age than the general population, and these serious non-AIDS events (SNAEs) track with plasma inflammatory and coagulation markers. The cell subsets driving inflammation in aviremic HIV infection are not yet elucidated. Also, whether ART-suppressed HIV infection causes premature induction of the inflammatory events found in uninfected elderly or if a novel inflammatory network ensues when HIV and older age co-exist is unclear. In this study we measured combinational expression of five inhibitory receptors (IRs) on seven immune cell subsets and 16 plasma markers from peripheral blood mononuclear cells (PBMC) and plasma samples, respectively, from a HIV and Aging cohort comprised of ART-suppressed HIV-infected and uninfected controls stratified by age (≤35 or ≥50 years old). For data analysis, multiple multivariate computational algorithms [cluster identification, characterization, and regression (CITRUS), partial least squares regression (PLSR), and partial least squares-discriminant analysis (PLS-DA)] were used to determine if immune parameter disparities can distinguish the subject groups and to investigate if there is a cross-impact of aviremic HIV and age on immune signatures. IR expression on gamma delta (γδ) T cells exclusively separated HIV+ subjects from controls in CITRUS analyses and secretion of inflammatory cytokines and cytotoxic mediators from γδ T cells tracked with TIGIT expression among HIV+ subjects. Also, plasma markers predicted the percentages of TIGIT+ γδ T cells in subjects with and without HIV in PSLR models, and a PLS-DA model of γδ T cell IR signatures and plasma markers significantly stratified all four of the subject groups (uninfected younger, uninfected older, HIV+ younger, and HIV+ older). These data implicate γδ T cells as an inflammatory driver in ART-suppressed HIV infection and provide evidence of distinct "inflamm-aging" processes with and without ART-suppressed HIV infection.

Concentrations of 6-thioguanine nucleotide correlate with trough levels of infliximab in patients with inflammatory bowel disease on combination therapy.

BACKGROUND & AIMS: In patients with inflammatory bowel diseases, the combination of infliximab and thiopurines (such as 6-thioguanine) is more effective treatment than monotherapy. We assessed the correlation between serum levels of 6-thioguanine (6-TGN) and infliximab levels or antibodies to infliximab (ATI). METHODS: We performed a cross-sectional study of 72 patients receiving maintenance therapy with infliximab and a thiopurine for inflammatory bowel disease at the Crohn's and Colitis Center of the University of Miami, FL. We collected clinical, endoscopic, and biochemical data, and levels of thiopurine metabolites. The primary outcomes were trough level of infliximab and the presence of ATI. RESULTS: Levels of 6-TGN correlated with those of infliximab (ρ, 0.53; P < .0001). The cut-off point of 6-TGN that best predicted a higher level of infliximab was 125 pmol/8 × 10(8) red blood cells (RBCs) (area under receiver operating characteristic, 0.86; P < .001). Patients in the lowest quartile of 6-TGN had infliximab levels that were similar to patients on no thiopurines (4.3 vs. 4.8 mcg/mL, respectively; P = .8). An infliximab level of 8.3 mcg/mL or greater was associated with mucosal healing. Only 8 patients (11%) had detectable ATI. Patients with 6-TGN levels less than 125 pmol/8 × 10(8) RBCs were significantly more likely to have ATI (odds ratio, 1.3; 95% confidence interval, 2.3-72.5; P < .01). CONCLUSIONS: Although 6-TGN levels of greater than 230 pmol/8 × 10(8) RBCs have been associated with improved outcomes in patients on monotherapy, a level of 6-thioguanine of 125 pmol/8 × 10(8) RBCs or greater may be adequate to achieve therapeutic levels of infliximab. In the long term, this may minimize the toxicity for patients on combination therapy.

Genetic ancestry influences asthma susceptibility and lung function among Latinos.

BACKGROUND: Childhood asthma prevalence and morbidity varies among Latinos in the United States, with Puerto Ricans having the highest and Mexicans the lowest. OBJECTIVE: To determine whether genetic ancestry is associated with the odds of asthma among Latinos, and secondarily whether genetic ancestry is associated with lung function among Latino children. METHODS: We analyzed 5493 Latinos with and without asthma from 3 independent studies. For each participant, we estimated the proportion of African, European, and Native American ancestry using genome-wide data. We tested whether genetic ancestry was associated with the presence of asthma and lung function among subjects with and without asthma. Odds ratios (OR) and effect sizes were assessed for every 20% increase in each ancestry. RESULTS: Native American ancestry was associated with lower odds of asthma (OR = 0.72, 95% CI: 0.66-0.78, P = 8.0 × 10(-15)), while African ancestry was associated with higher odds of asthma (OR = 1.40, 95% CI: 1.14-1.72, P = .001). These associations were robust to adjustment for covariates related to early life exposures, air pollution, and socioeconomic status. Among children with asthma, African ancestry was associated with lower lung function, including both pre- and post-bronchodilator measures of FEV1 (-77 ± 19 mL; P = 5.8 × 10(-5) and -83 ± 19 mL; P = 1.1 x 10(-5), respectively) and forced vital capacity (-100 ± 21 mL; P = 2.7 × 10(-6) and -107 ± 22 mL; P = 1.0 x 10(-6), respectively). CONCLUSION: Differences in the proportions of genetic ancestry can partially explain disparities in asthma susceptibility and lung function among Latinos.

Genome-wide association study and admixture mapping identify different asthma-associated loci in Latinos: the Genes-environments & Admixture in Latino Americans study.

BACKGROUND: Asthma is a complex disease with both genetic and environmental causes. Genome-wide association studies of asthma have mostly involved European populations, and replication of positive associations has been inconsistent. OBJECTIVE: We sought to identify asthma-associated genes in a large Latino population with genome-wide association analysis and admixture mapping. METHODS: Latino children with asthma (n = 1893) and healthy control subjects (n = 1881) were recruited from 5 sites in the United States: Puerto Rico, New York, Chicago, Houston, and the San Francisco Bay Area. Subjects were genotyped on an Affymetrix World Array IV chip. We performed genome-wide association and admixture mapping to identify asthma-associated loci. RESULTS: We identified a significant association between ancestry and asthma at 6p21 (lowest P value: rs2523924, P < 5 × 10(-6)). This association replicates in a meta-analysis of the EVE Asthma Consortium (P = .01). Fine mapping of the region in this study and the EVE Asthma Consortium suggests an association between PSORS1C1 and asthma. We confirmed the strong allelic association between SNPs in the 17q21 region and asthma in Latinos (IKZF3, lowest P value: rs90792, odds ratio, 0.67; 95% CI, 0.61-0.75; P = 6 × 10(-13)) and replicated associations in several genes that had previously been associated with asthma in genome-wide association studies. CONCLUSIONS: Admixture mapping and genome-wide association are complementary techniques that provide evidence for multiple asthma-associated loci in Latinos. Admixture mapping identifies a novel locus on 6p21 that replicates in a meta-analysis of several Latino populations, whereas genome-wide association confirms the previously identified locus on 17q21.

A genome-wide association study of bronchodilator response in Latinos implicates rare variants.

BACKGROUND: The primary rescue medication to treat acute asthma exacerbation is the short-acting ß2-adrenergic receptor agonist; however, there is variation in how well a patient responds to treatment. Although these differences might be due to environmental factors, there is mounting evidence for a genetic contribution to variability in bronchodilator response (BDR). OBJECTIVE: To identify genetic variation associated with bronchodilator drug response in Latino children with asthma. METHODS: We performed a genome-wide association study (GWAS) for BDR in 1782 Latino children with asthma using standard linear regression, adjusting for genetic ancestry and ethnicity, and performed replication studies in an additional 531 Latinos. We also performed admixture mapping across the genome by testing for an association between local European, African, and Native American ancestry and BDR, adjusting for genomic ancestry and ethnicity. RESULTS: We identified 7 genetic variants associated with BDR at a genome-wide significant threshold (P < 5 × 10(-8)), all of which had frequencies of less than 5%. Furthermore, we observed an excess of small P values driven by rare variants (frequency, <5%) and by variants in the proximity of solute carrier (SLC) genes. Admixture mapping identified 5 significant peaks; fine mapping within these peaks identified 2 rare variants in SLC22A15 as being associated with increased BDR in Mexicans. Quantitative PCR and immunohistochemistry identified SLC22A15 as being expressed in the lung and bronchial epithelial cells. CONCLUSION: Our results suggest that rare variation contributes to individual differences in response to albuterol in Latinos, notably in SLC genes that include membrane transport proteins involved in the transport of endogenous metabolites and xenobiotics. Resequencing in larger, multiethnic population samples and additional functional studies are required to further understand the role of rare variation in BDR.

Case-control admixture mapping in Latino populations enriches for known asthma-associated genes.

BACKGROUND: Polymorphisms in more than 100 genes have been associated with asthma susceptibility, yet much of the heritability remains to be explained. Asthma disproportionately affects different racial and ethnic groups in the United States, suggesting that admixture mapping is a useful strategy to identify novel asthma-associated loci. OBJECTIVE: We sought to identify novel asthma-associated loci in Latino populations using case-control admixture mapping. METHODS: We performed genome-wide admixture mapping by comparing levels of local Native American, European, and African ancestry between children with asthma and nonasthmatic control subjects in Puerto Rican and Mexican populations. Within candidate peaks, we performed allelic tests of association, controlling for differences in local ancestry. RESULTS: Between the 2 populations, we identified a total of 62 admixture mapping peaks at a P value of less than 10(-3) that were significantly enriched for previously identified asthma-associated genes (P= .0051). One of the peaks was statistically significant based on 100 permutations in the Mexican sample (6q15); however, it was not significant in Puerto Rican subjects. Another peak was identified at nominal significance in both populations (8q12); however, the association was observed with different ancestries. CONCLUSION: Case-control admixture mapping is a promising strategy for identifying novel asthma-associated loci in Latino populations and implicates genetic variation at 6q15 and 8q12 regions with asthma susceptibility. This approach might be useful for identifying regions that contribute to both shared and population-specific differences in asthma susceptibility.

Race, ethnicity and social class and the complex etiologies of asthma.

Asthma is a common but complex respiratory disease caused by the interaction of genetic and environmental factors. Significant racial and ethnic disparities in prevalence, mortality and drug response have been described. These disparities may be explained by racial and ethnic-specific variation in genetic, environmental, social and psychological risk factors. In addition, race, ethnicity and social class are important proxies for unmeasured factors that influence health outcomes. Herein, we review salient differences in the etiologies of asthma by race, ethnicity and social class, and argue for their continued use as variables in asthma research.

Development of a homogeneous, fluorescence resonance energy transfer-based in vitro recruitment assay for peroxisome proliferator-activated receptor delta via selection of active LXXLL coactivator peptides.

The peroxisome proliferator-activated receptors (PPARs) are nuclear receptors activated by fatty acids and their metabolites. The PPARdelta subtype is believed to be involved in lipoprotein regulation and may have a role in reverse cholesterol transport. While the range of biological roles of PPARdelta still remains unclear, it is of therapeutic interest in cardiovascular diseases. Here we report a homogeneous in vitro assay for studying ligand activation of PPARdelta. We surveyed a panel of peptides containing the LXXLL motifs derived from coactivator protein sequences. Peptides with the best response were used to develop a sensitive and homogeneous recruitment assay for PPARdelta. The optimized assay has a signal-to-background ratio of about 8:1 and an assay quality parameter Z'-factor value of 0.8. The assay signal generated is stable for hours to even overnight. This simple recruitment assay can provide agonist and/or antagonist information that cannot be assessed by receptor-binding assay, and can be used for characterization and screening of ligands that modulate the activation of PPARdelta.