Ultrasensitive monitoring of SARS-CoV-2-specific antibody responses based on a digital approach reveals one week of IgG seroconversion.

COVID-19 is still unfolding, while many people have been vaccinated. In comparison to nucleic acid testing (NAT), antibody-based immunoassays are faster and more convenient. However, its application has been hampered by its lower sensitivity and the existing fact that by traditional immunoassays, the measurable seroconversion time of pathogen-specific antibodies, such as IgM or IgG, lags far behind that of nucleic acids. Herein, by combining the single molecule array platform (Simoa), RBD, and a previously identified SARS-CoV-2 S2 protein derivatized 12-aa peptide (S2-78), we developed and optimized an ultrasensitive assay (UIM-COVID-19 assay). Sera collected from three sources were tested, i.e., convalescents, inactivated virus vaccine-immunized donors and wild-type authentic SARS-CoV-2-infected rhesus monkeys. The sensitivities of UIM-COVID-19 assays are 100-10,000 times higher than those of conventional flow cytometry, which is a relatively sensitive detection method at present. For the established UIM-COVID-19 assay using RBD as a probe, the IgG and IgM seroconversion times after vaccination were 7.5 and 8.6 days vs. 21.4 and 24 days for the flow cytometry assay, respectively. In addition, using S2-78 as a probe, the UIM-COVID-19 assay could differentiate COVID-19 patients (convalescents) from healthy people and patients with other diseases, with AUCs ranging from 0.85-0.95. In summary, the UIM-COVID-19 we developed here is a promising ultrasensitive biodetection strategy that has the potential to be applied for both immunological studies and diagnostics.

Trajectories of Neurologic Recovery 12 Months After Hospitalization for COVID-19: A Prospective Longitudinal Study.

BACKGROUND AND OBJECTIVE: Little is known about trajectories of recovery 12 months after hospitalization for severe COVID-19. METHODS: We conducted a prospective, longitudinal cohort study of patients with and without neurologic complications during index hospitalization for COVID-19 from March 10, 2020, to May 20, 2020. Phone follow-up batteries were performed at 6 and 12 months after COVID-19 onset. The primary 12-month outcome was the modified Rankin Scale (mRS) score comparing patients with or without neurologic complications using multivariable ordinal analysis. Secondary outcomes included activities of daily living (Barthel Index), telephone Montreal Cognitive Assessment (t-MoCA), and Quality of Life in Neurologic Disorders (Neuro-QoL) batteries for anxiety, depression, fatigue, and sleep. Changes in outcome scores from 6 to 12 months were compared using nonparametric paired-samples sign test. RESULTS: Twelve-month follow-up was completed in 242 patients (median age 65 years, 64% male, 34% intubated during hospitalization) and 174 completed both 6- and 12-month follow-up. At 12 months, 197/227 (87%) had ≥1 abnormal metric: mRS >0 (75%), Barthel Index <100 (64%), t-MoCA ≤18 (50%), high anxiety (7%), depression (4%), fatigue (9%), or poor sleep (10%). Twelve-month mRS scores did not differ significantly among those with (n = 113) or without (n = 129) neurologic complications during hospitalization after adjusting for age, sex, race, pre-COVID-19 mRS, and intubation status (adjusted OR 1.4, 95% CI 0.8-2.5), although those with neurologic complications had higher fatigue scores (T score 47 vs 44; p = 0.037). Significant improvements in outcome trajectories from 6 to 12 months were observed in t-MoCA scores (56% improved, median difference 1 point; p = 0.002) and Neuro-QoL anxiety scores (45% improved; p = 0.003). Nonsignificant improvements occurred in fatigue, sleep, and depression scores in 48%, 48%, and 38% of patients, respectively. Barthel Index and mRS scores remained unchanged between 6 and 12 months in >50% of patients. DISCUSSION: At 12 months after hospitalization for severe COVID-19, 87% of patients had ongoing abnormalities in functional, cognitive, or Neuro-QoL metrics and abnormal cognition persisted in 50% of patients without a history of dementia/cognitive abnormality. Only fatigue severity differed significantly between patients with or without neurologic complications during index hospitalization. However, significant improvements in cognitive (t-MoCA) and anxiety (Neuro-QoL) scores occurred in 56% and 45% of patients, respectively, between 6 and 12 months. These results may not be generalizable to those with mild or moderate COVID-19.

Single-Cell Transcriptomic Profiling of MAIT Cells in Patients With COVID-19.

Background: Mucosal-associated invariant T (MAIT) cells are considered to participate of the host immune response against acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection; however, single-cell transcriptomic profiling of MAIT cells in patients with COVID-19 remains unexplored. Methods: We performed single-cell RNA sequencing analyses on peripheral MAIT cells from 13 patients with COVID-19 and 5 healthy donors. The transcriptional profiles of MAIT cells, together with assembled T-cell receptor sequences, were analyzed. Flow cytometry analysis was also performed to investigate the properties of MAIT cells. Results: We identified that differentially expressed genes (DEGs) of MAIT cells were involved in myeloid leukocyte activation and lymphocyte activation in patients with COVID-19. In addition, in MAIT cells from severe cases, more DEGs were enriched in adaptive cellular and humoral immune responses compared with those in moderate cases. Further analysis indicated that the increase of cell cytotoxicity (killing), chemotaxis, and apoptosis levels in MAIT cells were consistent with disease severity and displayed the highest levels in patients with severe disease. Interestingly, flow cytometry analysis showed that the frequencies of pyroptotic MAIT cells, but not the frequencies of apoptotic MAIT cells, were increased significantly in patients with COVID-19, suggesting pyroptosis is one of leading causes of MAIT cell deaths during SARS-CoV-2 infection. Importantly, there were more clonal expansions of MAIT cells in severe cases than in moderate cases. Conclusions: The results of the present study suggest that MAIT cells are likely to be involved in the host immune response against SARS-CoV-2 infection. Simultaneously, the transcriptomic data from MAIT cells provides a deeper understanding of the immune pathogenesis of the disease.

Individualized model for predicting COVID-19 deterioration in patients with cancer: A multicenter retrospective study.

The 2019 novel coronavirus has spread rapidly around the world. Cancer patients seem to be more susceptible to infection and disease deterioration, but the factors affecting the deterioration remain unclear. We aimed to develop an individualized model for prediction of coronavirus disease (COVID-19) deterioration in cancer patients. The clinical data of 276 cancer patients diagnosed with COVID-19 in 33 designated hospitals of Hubei, China from December 21, 2019 to March 18, 2020, were collected and randomly divided into a training and a validation cohort by a ratio of 2:1. Cox stepwise regression analysis was carried out to select prognostic factors. The prediction model was developed in the training cohort. The predictive accuracy of the model was quantified by C-index and time-dependent area under the receiver operating characteristic curve (t-AUC). Internal validation was assessed by the validation cohort. Risk stratification based on the model was carried out. Decision curve analysis (DCA) were used to evaluate the clinical usefulness of the model. We found age, cancer type, computed tomography baseline image features (ground glass opacity and consolidation), laboratory findings (lymphocyte count, serum levels of C-reactive protein, aspartate aminotransferase, direct bilirubin, urea, and d-dimer) were significantly associated with symptomatic deterioration. The C-index of the model was 0.755 in the training cohort and 0.779 in the validation cohort. The t-AUC values were above 0.7 within 8 weeks both in the training and validation cohorts. Patients were divided into two risk groups based on the nomogram: low-risk (total points ≤ 9.98) and high-risk (total points > 9.98) group. The Kaplan-Meier deterioration-free survival of COVID-19 curves presented significant discrimination between the two risk groups in both training and validation cohorts. The model indicated good clinical applicability by DCA curves. This study presents an individualized nomogram model to individually predict the possibility of symptomatic deterioration of COVID-19 in patients with cancer.

Semiparametric Bayesian inference for the transmission dynamics of COVID-19 with a state-space model.

The outbreak of Coronavirus Disease 2019 (COVID-19) is an ongoing pandemic affecting over 200 countries and regions. Inference about the transmission dynamics of COVID-19 can provide important insights into the speed of disease spread and the effects of mitigation policies. We develop a novel Bayesian approach to such inference based on a probabilistic compartmental model using data of daily confirmed COVID-19 cases. In particular, we consider a probabilistic extension of the classical susceptible-infectious-recovered model, which takes into account undocumented infections and allows the epidemiological parameters to vary over time. We estimate the disease transmission rate via a Gaussian process prior, which captures nonlinear changes over time without the need of specific parametric assumptions. We utilize a parallel-tempering Markov chain Monte Carlo algorithm to efficiently sample from the highly correlated posterior space. Predictions for future observations are done by sampling from their posterior predictive distributions. Performance of the proposed approach is assessed using simulated datasets. Finally, our approach is applied to COVID-19 data from six states of the United States: Washington, New York, California, Florida, Texas, and Illinois. An R package BaySIR is made available at https://github.com/tianjianzhou/BaySIR for the public to conduct independent analysis or reproduce the results in this paper.

Human umbilical cord-derived mesenchymal stem cell therapy in patients with COVID-19: a phase 1 clinical trial.

No effective drug treatments are available for coronavirus disease 2019 (COVID-19). Host-directed therapies targeting the underlying aberrant immune responses leading to pulmonary tissue damage, death, or long-term functional disability in survivors require clinical evaluation. We performed a parallel assigned controlled, non-randomized, phase 1 clinical trial to evaluate the safety of human umbilical cord-derived mesenchymal stem cells (UC-MSCs) infusions in the treatment of patients with moderate and severe COVID-19 pulmonary disease. The study enrolled 18 hospitalized patients with COVID-19 (n = 9 for each group). The treatment group received three cycles of intravenous infusion of UC-MSCs (3 × 107 cells per infusion) on days 0, 3, and 6. Both groups received standard COVID-treatment regimens. Adverse events, duration of clinical symptoms, laboratory parameters, length of hospitalization, serial chest computed tomography (CT) images, the PaO2/FiO2 ratio, dynamics of cytokines, and IgG and IgM anti-SARS-CoV-2 antibodies were analyzed. No serious UC-MSCs infusion-associated adverse events were observed. Two patients receiving UC-MSCs developed transient facial flushing and fever, and one patient developed transient hypoxia at 12 h post UC-MSCs transfusion. Mechanical ventilation was required in one patient in the treatment group compared with four in the control group. All patients recovered and were discharged. Our data show that intravenous UC-MSCs infusion in patients with moderate and severe COVID-19 is safe and well tolerated. Phase 2/3 randomized, controlled, double-blinded trials with long-term follow-up are needed to evaluate the therapeutic use of UC-MSCs to reduce deaths and improve long-term treatment outcomes in patients with serious COVID-19.

Single-cell landscape of immunological responses in patients with COVID-19.

In coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the relationship between disease severity and the host immune response is not fully understood. Here we performed single-cell RNA sequencing in peripheral blood samples of 5 healthy donors and 13 patients with COVID-19, including moderate, severe and convalescent cases. Through determining the transcriptional profiles of immune cells, coupled with assembled T cell receptor and B cell receptor sequences, we analyzed the functional properties of immune cells. Most cell types in patients with COVID-19 showed a strong interferon-α response and an overall acute inflammatory response. Moreover, intensive expansion of highly cytotoxic effector T cell subsets, such as CD4+ effector-GNLY (granulysin), CD8+ effector-GNLY and NKT CD160, was associated with convalescence in moderate patients. In severe patients, the immune landscape featured a deranged interferon response, profound immune exhaustion with skewed T cell receptor repertoire and broad T cell expansion. These findings illustrate the dynamic nature of immune responses during disease progression.

Single-cell landscape of immunological responses in COVID-19 patients (preprint)

In COVID-19 caused by SARS-CoV-2 infection, the relationship between disease severity and the host immune response is not fully understood. Here we performed single-cell RNA sequencing in peripheral blood samples of five healthy donors and 13 COVID-19 patients including moderate, severe and convalescent cases. Through determining the transcriptional profiles of immune cells, coupled with assembled T cell receptor and B cell receptor sequences, we analyzed the functional properties of immune cells. Most cell types in COVID-19 patients showed a strong interferon-alpha response, and an overall acute inflammatory response. Moreover, intensive expansion of highly cytotoxic effector T cell subsets, such as CD4+ Effector-GNLY (Granulysin), CD8+ Effector-GNLY and NKT CD160, was associated with convalescence in moderate patients. In severe patients, the immune landscape featured a deranged interferon response, profound immune exhaustion with skewed T cell receptor repertoire and broad T cell expansion. These findings illustrate the dynamic nature of immune responses during the disease progression.

Immunological and inflammatory profiles in mild and severe cases of COVID-19.

COVID-19 is associated with 5.1% mortality. Although the virological, epidemiological, clinical, and management outcome features of COVID-19 patients have been defined rapidly, the inflammatory and immune profiles require definition as they influence pathogenesis and clinical expression of COVID-19. Here we show lymphopenia, selective loss of CD4+ T cells, CD8+ T cells and NK cells, excessive T-cell activation and high expression of T-cell inhibitory molecules are more prominent in severe cases than in those with mild disease. CD8+ T cells in patients with severe disease express high levels of cytotoxic molecules. Histochemical studies of lung tissue from one fatality show sub-anatomical distributions of SARS-CoV-2 RNA and massive infiltration of T cells and macrophages. Thus, aberrant activation and dysregulation of CD8+ T cells occur in patients with severe COVID-19 disease, an effect that might be for pathogenesis of SARS-CoV-2 infection and indicate that immune-based targets for therapeutic interventions constitute a promising treatment for severe COVID-19 patients.

Omics-Driven Systems Interrogation of Metabolic Dysregulation in COVID-19 Pathogenesis.

The coronavirus disease 2019 (COVID-19) pandemic presents an unprecedented threat to global public health. Herein, we utilized a combination of targeted and untargeted tandem mass spectrometry to analyze the plasma lipidome and metabolome in mild, moderate, and severe COVID-19 patients and healthy controls. A panel of 10 plasma metabolites effectively distinguished COVID-19 patients from healthy controls (AUC = 0.975). Plasma lipidome of COVID-19 resembled that of monosialodihexosyl ganglioside (GM3)-enriched exosomes, with enhanced levels of sphingomyelins (SMs) and GM3s, and reduced diacylglycerols (DAGs). Systems evaluation of metabolic dysregulation in COVID-19 was performed using multiscale embedded differential correlation network analyses. Using exosomes isolated from the same cohort, we demonstrated that exosomes of COVID-19 patients with elevating disease severity were increasingly enriched in GM3s. Our work suggests that GM3-enriched exosomes may partake in pathological processes related to COVID-19 pathogenesis and presents the largest repository on the plasma lipidome and metabolome distinct to COVID-19.

Expansion of myeloid-derived suppressor cells in patients with severe coronavirus disease (COVID-19).

SARS-CoV-2 is associated with a 3.4% mortality rate in patients with severe disease. The pathogenesis of severe cases remains unknown. We performed an in-depth prospective analysis of immune and inflammation markers in two patients with severe COVID-19 disease from presentation to convalescence. Peripheral blood from 18 SARS-CoV-2-infected patients, 9 with severe and 9 with mild COVID-19 disease, was obtained at admission and analyzed for T-cell activation profile, myeloid-derived suppressor cells (MDSCs) and cytokine profiles. MDSC functionality was tested in vitro. In four severe and in four mild patients, a longitudinal analysis was performed daily from the day of admission to the early convalescent phase. Early after admission severe patients showed neutrophilia, lymphopenia, increase in effector T cells, a persisting higher expression of CD95 on T cells, higher serum concentration of IL-6 and TGF-ß, and a cytotoxic profile of NK and T cells compared with mild patients, suggesting a highly engaged immune response. Massive expansion of MDSCs was observed, up to 90% of total circulating mononuclear cells in patients with severe disease, and up to 25% in the patients with mild disease; the frequency decreasing with recovery. MDSCs suppressed T-cell functions, dampening excessive immune response. MDSCs decline at convalescent phase was associated to a reduction in TGF-ß and to an increase of inflammatory cytokines in plasma samples. Substantial expansion of suppressor cells is seen in patients with severe COVID-19. Further studies are required to define their roles in reducing the excessive activation/inflammation, protection, influencing disease progression, potential to serve as biomarkers of disease severity, and new targets for immune and host-directed therapeutic approaches.

Incidence rate, clinical course and risk factor for recurrent PCR positivity in discharged COVID-19 patients in Guangzhou, China: a prospective cohort study (preprint)

Background: The phenomenon of COVID-19 patients tested positive for SARS-CoV-2 after discharge (redetectable as positive, RP) emerged globally. The data of incidence rate and risk factors for RP event and the clinical features of RP patients may provide recommendations for virus containment and discharge assessment for COVID-19. Methods: The baseline included 285 adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Guangzhou Eighth People's Hospital. We started the Observation on Jan 20, 2020, and acquired all their definite clinical outcome (becoming RP or keeping normal during post-discharge surveillance) by Mar 10, 2020. The dynamic clinical data of patients during observation were prospectively collected and analyzed. Univariate and multivariate-adjusted logistic regression were used to explore the risk factors related to RP events in COVID-19 patients. Results: By March 10, 27 (9.5%) discharged patients had tested positive for SARS-CoV-2 in their nasopharyngeal swab after a median duration of 7·0 days (IQR 5·0-8·0). Age, sex, epidemiological history, clinical symptoms and underlying diseases were similar between RP and non-RP patients (p>0.05). Compared to first admission, RP patients generally had milder clinical symptoms, lower viral load, shorter length of stay and improved pulmonary conditions at readmission (p<0.05). Elder RP patients (≥ 60 years old) were more likely to be symptomatic compared to younger patients (7/8, 87.5% vs. 3/19, 18.8%, p=0.001) at readmission. A prolonged duration of viral shedding (>10 days) during the first hospitalization [adjusted odds ratio [aOR]: 5.82, 95% confidence interval [CI]: 2.50-13.57 for N gene; aOR: 9.64, 95% CI: 3.91-23.73 for ORF gene] and higher Ct value (ORF) in the third week of the first hospitalization (aOR: 0.69; 95% CI: 0.50-0.95) were associated with RP events. Conclusions: RP events occurred in nearly 10% of COVID-19 patients which deserves globally attention. During hospitalization, patients’ low efficiency of viral clearance was a risk factor for RP event. Elderly RP patients were more likely to develop clinical symptoms. To reduce the possibility of reinfection and readmission during the management of COVID-19, more rigorously monitoring on patients’ viral load should be carried out especially in elder patients and later stage of hospitalization.