An integrated cell atlas of the lung in health and disease.

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1+ profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas.

Anti-SARS-CoV2 antibody levels predict outcome in diabetic patients with COVID-19: a prospective cohort study (preprint)

Diabetic patients constitute one of the most vulnerable subgroups in COVID-19. Despite high vaccination rates, a correlate of protection to advise vaccination strategies for novel SARS-CoV2 variants of concern and lower mortality in this high-risk group is still missing. It is further unclear what antibody levels provide protection and whether pre-existing organ damage affects this threshold. To address these gaps, we conducted a prospective multicenter cohort study on 1152 patients with COVID-19 from five hospitals. Patients were classified by diabetes and vaccination status. Anti-SARS-CoV-2-spike-antibodies, creatinine and NTproBNP were measured on hospital admission. Pre-specified endpoints were all-cause in-hospital-mortality, ICU admission, endotracheal intubation, and oxygen administration. Propensity score matching was applied to increase comparability. We observed significantly lower anti-SARS-CoV2-spike-antibodies in diabetic non-survivors compared to survivors (mean, 95%CI; 351U/ml, 106–595 vs. 1123, 968–1279, p < 0.001). Mortality risk increased two-fold with each standard deviation-decrease of antibody levels (aHR 1.988, 95%CI 1.229–3.215, p = 0.005). Diabetic patients requiring oxygen administration, endotracheal intubation and ICU admission had significantly lower antibody levels than those who did not (p < 0.001, p = 0.046, p = 0.011). While diabetic patients had significantly worse outcomes than non-diabetic patients, the differences were less pronounced compared to propensity-score-matched non-diabetic patients. Anti-SARS-CoV2 spike antibodies on hospital admission are inversely associated with oxygen administration, endotracheal intubation, intensive care and in-hospital mortality in diabetic COVID-19 patients. Pre-existing comorbidities may have a greater impact on outcome than diabetes status alone.

Pressure overload induces ISG15 to facilitate adverse ventricular remodeling and promote heart failure.

Inflammation promotes adverse ventricular remodeling, a common antecedent of heart failure. Here, we set out to determine how inflammatory cells affect cardiomyocytes in the remodeling heart. Pathogenic cardiac macrophages induced an IFN response in cardiomyocytes, characterized by upregulation of the ubiquitin-like protein IFN-stimulated gene 15 (ISG15), which posttranslationally modifies its targets through a process termed ISGylation. Cardiac ISG15 is controlled by type I IFN signaling, and ISG15 or ISGylation is upregulated in mice with transverse aortic constriction or infused with angiotensin II; rats with uninephrectomy and DOCA-salt, or pulmonary artery banding; cardiomyocytes exposed to IFNs or CD4+ T cell-conditioned medium; and ventricular tissue of humans with nonischemic cardiomyopathy. By nanoscale liquid chromatography-tandem mass spectrometry, we identified the myofibrillar protein filamin-C as an ISGylation target. ISG15 deficiency preserved cardiac function in mice with transverse aortic constriction and led to improved recovery of mouse hearts ex vivo. Metabolomics revealed that ISG15 regulates cardiac amino acid metabolism, whereas ISG15 deficiency prevented misfolded filamin-C accumulation and induced cardiomyocyte autophagy. In sum, ISG15 upregulation is a feature of pathological ventricular remodeling, and protein ISGylation is an inflammation-induced posttranslational modification that may contribute to heart failure development by altering cardiomyocyte protein turnover.

Genetic and environmental contributions to the subjective burden of social isolation during the COVID-19 pandemic.

BACKGROUND: Feelings of loneliness and the burden of social isolation were among the most striking consequences of widespread containment measures, such as "social distancing", during the COVID-19 pandemic. Because of the potential impact on people's health, there has been increased interest in understanding the mechanisms and factors that contributed to feelings of loneliness and the burdens of social isolation. However, in this context, genetic predisposition has been largely ignored as an important factor. This is problematic because some of the phenotypic associations observed to date may in fact be genetic. The aim of this study is, therefore, to examine the genetic and environmental contributions to the burden of social isolation at two time points during the pandemic. In addition, we examine whether risk factors identified in previous studies explain genetic or environmental contributions to the burden of social isolation. METHODS: The present study is based on a genetically sensitive design using data from the TwinLife panel study, which surveyed a large sample of adolescent and young adult twins during the first (N = 798) and the second (N = 2520) lockdown in Germany. RESULTS: We find no substantive differences in genetic and environmental contributions to social isolation burden over the course of the pandemic. However, we find the determinants highlighted as important in previous studies can explain only a small proportion of the observed variance in the burden of social isolation and mainly explained genetic contributions. CONCLUSIONS: While some of the observed associations appear to be genetic, our findings underscore the need for further research, as the causes of individual differences in burden of social isolation remain unclear.

Evaluation of SARS-CoV-2 antibody levels on hospital admission as a correlate of protection against mortality.

BACKGROUND: Millions of people have now been vaccinated against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, it is still unclear which antibody levels provide protection against mortality. It is further unknown whether measuring antibody concentrations on hospital admission allows for identifying patients with a high risk of mortality. OBJECTIVES: To evaluate whether anti-SARS-CoV2-spike antibodies on hospital admission predict in-hospital mortality in patients with coronavirus disease 2019. METHODS: We conducted a prospective, multicentre cohort study on 1152 hospitalized patients who tested positive for SARS-CoV-2 with a polymerase chain reaction-based assay. Patients were classified by vaccination status. Anti-SARS-CoV-2 spike antibodies were determined on hospital admission. The investigated end point was in-hospital mortality for any cause. RESULTS: Spike antibodies on hospital admission were significantly lower in non-survivors in both non-vaccinated (73 U/ml, 95%CI 0-164 vs. 175 U/ml, 95%CI 124-235, p = 0.002) and vaccinated patients (1056 U/ml, 95%CI 701-1411 vs. 1668 U/ml, 95%CI 1580-1757, p < 0.001). Further, spike antibodies were significantly lower in fully vaccinated and boostered patients who died compared to those who survived (mean 883 U/ml, 95%CI 406-1359 vs. 1292 U/ml, 95%CI 1152-1431, p = 0.017 and 1485 U/ml, 95%CI 836-2133 vs. 2050 U/ml, 95%CI 1952-2149, p = 0.036). Patients infected with the currently prevailing Omicron variant were three times more likely to die if spike antibodies were <1200 U/ml (OR 3.458, 95%CI 1.562-7.656, p = 0.001). After adjusting for potential confounders, this value increased to an aOR of 4.079 (95%CI 1.809-9.198, p < 0.001). CONCLUSION: Anti-SARS-CoV2 spike-antibody levels on hospital admission are inversely associated with in-hospital mortality. Hospitalized patients with lower antibody levels have a higher risk of mortality.

Effectiveness of a one-week inpatient multimodal pain treatment program for patients with rheumatologic diseases and musculoskeletal pain - a single center observational study

Background: Multimodal rheumatologic complex treatment (MRCT) is a treatment concept for patients with rheumatologic diseases requiring acute inpatient care suffering from exacerbated pain and/or functional impairment. A rheumatologist directs the treatment program including multimodal assessments and treatment from three of the following: ergotherapy, physiotherapy, pain medicine and cognitive behavioural treatment. Objective(s): To evaluate the effectiveness of a one-week inpatient MRCT on musculoskeletal pain and function of patients with rheumatologic disorders. Method(s): 59 consecutive patients were entered into a program of multimodal treatment courses from January 2021 until December 2021. Two patients were excluded for evaluation (one patient acquired COVID-19 during hospitalization and one patient was excluded due to missing data). Pain was assessed via visual analogue scale (VAS) and functional impairment via the "Funktionsfragebogen Hanover (FFbH)" and the "Health Assessment Questionnaire (HAQ)" at admission, at discharge and at 12 weeks of follow up. Paired t-test analyses for all treatment episodes were performed. Result(s): The mean treatment duration (days, +/-SD) was 8.1 +/- 0.8. Mean age (years, +/-SD) of the 57 patients treated in the MRCT program was 57.2 +/- 12.5, with 72% female and 28% male patients. Of all patients, 40% had an underlying inflammatory disorder, 60% a non - inflammatory rheumatic disease. 23% of all patients had "back pain", 14% "spondyloarthritis" and 11% "rheumatoid arthritis". VAS (pain) mean at admission was 6.9 +/- 1.0 (SD), HAQ mean 0.57 +/- 0.23 (SD) and FFbH mean 81.44 +/- 7.95 (SD), respectively. Significant improvements in VAS, HAQ and FFbH were demonstrated at discharge, with a mean improvement of VAS of -2.86 (95% CI: -3.07 to -2.64, P value: <0.0001), a mean improvement of HAQ of -0.24 (95% CI: -0.28 to -0.20, P value: <0.0001) and a mean improvement of FFbH of 5.38 (95% CI: 3.78 to 6.98, P value: <0.0001). Follow up assessment at week 12 was recorded in 22 patients (39%) with a significant mean improvement in VAS of -2.23 (95% CI: -2.98 to - 1.48), P value <0.0001). Conclusion(s): Significant improvement of pain and function was demonstrated at discharge and at week 12 in patients with rheumatologic diseases and musculoskeletal pain completing a one-week inpatient multimodal interprofessional treatment program. A multimodal therapeutic approach may provide an effective treatment strategy superior to unimodal standard management.

Early Prediction of COVID-19 Patient Survival by Targeted Plasma Multi-Omics and Machine Learning.

The recent surge of coronavirus disease 2019 (COVID-19) hospitalizations severely challenges healthcare systems around the globe and has increased the demand for reliable tests predictive of disease severity and mortality. Using multiplexed targeted mass spectrometry assays on a robust triple quadrupole MS setup which is available in many clinical laboratories, we determined the precise concentrations of hundreds of proteins and metabolites in plasma from hospitalized COVID-19 patients. We observed a clear distinction between COVID-19 patients and controls and, strikingly, a significant difference between survivors and nonsurvivors. With increasing length of hospitalization, the survivors' samples showed a trend toward normal concentrations, indicating a potential sensitive readout of treatment success. Building a machine learning multi-omic model that considers the concentrations of 10 proteins and five metabolites, we could predict patient survival with 92% accuracy (area under the receiver operating characteristic curve: 0.97) on the day of hospitalization. Hence, our standardized assays represent a unique opportunity for the early stratification of hospitalized COVID-19 patients.

An Update on MRMAssayDB: A Comprehensive Resource for Targeted Proteomics Assays in the Community.

Precise multiplexed quantification of proteins in biological samples can be achieved by targeted proteomics using multiple or parallel reaction monitoring (MRM/PRM). Combined with internal standards, the method achieves very good repeatability and reproducibility enabling excellent protein quantification and allowing longitudinal and cohort studies. A laborious part of performing such experiments lies in the preparation steps dedicated to the development and validation of individual protein assays. Several public repositories host information on targeted proteomics assays, including NCI's Clinical Proteomic Tumor Analysis Consortium assay portals, PeptideAtlas SRM Experiment Library, SRMAtlas, PanoramaWeb, and PeptideTracker, with all offering varying levels of details. We introduced MRMAssayDB in 2018 as an integrated resource for targeted proteomics assays. The Web-based application maps and links the assays from the repositories, includes comprehensive up-to-date protein and sequence annotations, and provides multiple visualization options on the peptide and protein level. We have extended MRMAssayDB with more assays and extensive annotations. Currently it contains >828 000 assays covering >51 000 proteins from 94 organisms, of which >17 000 proteins are present in >2400 biological pathways, and >48 000 mapping to >21 000 Gene Ontology terms. This is an increase of about four times the number of assays since introduction. We have expanded annotations of interaction, biological pathways, and disease associations. A newly added visualization module for coupled molecular structural annotation browsing allows the user to interactively examine peptide sequence and any known PTMs and disease mutations, and map all to available protein 3D structures. Because of its integrative approach, MRMAssayDB enables a holistic view of suitable proteotypic peptides and commonly used transitions in empirical data. Availability: http://mrmassaydb.proteincentre.com.

Single-cell RNA sequencing reveals ex vivo signatures of SARS-CoV-2-reactive T cells through 'reverse phenotyping'.

The in vivo phenotypic profile of T cells reactive to severe acute respiratory syndrome (SARS)-CoV-2 antigens remains poorly understood. Conventional methods to detect antigen-reactive T cells require in vitro antigenic re-stimulation or highly individualized peptide-human leukocyte antigen (pHLA) multimers. Here, we use single-cell RNA sequencing to identify and profile SARS-CoV-2-reactive T cells from Coronavirus Disease 2019 (COVID-19) patients. To do so, we induce transcriptional shifts by antigenic stimulation in vitro and take advantage of natural T cell receptor (TCR) sequences of clonally expanded T cells as barcodes for 'reverse phenotyping'. This allows identification of SARS-CoV-2-reactive TCRs and reveals phenotypic effects introduced by antigen-specific stimulation. We characterize transcriptional signatures of currently and previously activated SARS-CoV-2-reactive T cells, and show correspondence with phenotypes of T cells from the respiratory tract of patients with severe disease in the presence or absence of virus in independent cohorts. Reverse phenotyping is a powerful tool to provide an integrated insight into cellular states of SARS-CoV-2-reactive T cells across tissues and activation states.

Direct and Precise Measurement of Bevacizumab Levels in Human Plasma Based on Controlled Methionine Oxidation and Multiple Reaction Monitoring.

Bevacizumab is a monoclonal antibody which targets vascular endothelial growth factor A (VEGF-A) and is used to treat various cancers and recently COVID-19. The dosage recommendations for bevacizumab are determined on the basis of body weight, and the drug is administered after defined time intervals, when it is presumed to still be above its minimum effective serum concentration. Interindividual and disease-stage-related variations in bevacizumab catabolism, however, can affect the proper dosing of patients, resulting in plasma concentrations which may not be within the optimal therapeutic window for the drug. Therapeutic drug monitoring (TDM) enables the assessment of patients' serum concentrations and allows personalized dosing which has the potential to improve efficacy and reduce side effects. While TMD is often performed using ligand-based assays, mass spectrometry (MS)-based TDM offers improved specificity. Here, we present a robust multiple reaction monitoring (MRM)-MS-based TDM method for the precise quantification of bevacizumab plasma concentrations, based on the controlled oxidation of the methionine-containing peptide, STAYLQMNSLR. The assay shows good linearity (r 2 = 0.9951), robustness, and precision (CVs < 20%) for the quantification of bevacizumab, with a lower limit of quantification (S/N > 10) of 1.8 µg/mL of plasma, without the need for enrichment and requiring less than 1 µL of plasma and less than 6 h from sampling to result.

Mass-Spectrometric Detection of SARS-CoV-2 Virus in Scrapings of the Epithelium of the Nasopharynx of Infected Patients via Nucleocapsid N Protein.

The detection of viral RNA by polymerase chain reaction (PCR) is currently the main diagnostic tool for COVID-19 ( Eurosurveillance 2019, 25 (3), 1). The PCR-based test, however, shows limited sensitivity, especially in the early and late stages of disease development ( Nature 2020, 581, 465-469; J. Formosan Med. Assoc. 2020, 119 (6) 1123), and is relatively time-consuming. Fast and reliable complementary methods for detecting the viral infection would be of help in the current pandemic conditions. Mass spectrometry is one of such possibilities. We have developed a mass-spectrometry-based method for the detection of the SARS CoV-2 virus in nasopharynx epithelial swabs based on the detection of the viral nucleocapsid N protein. Our approach shows confident identification of the N protein in patient samples, even those with the lowest viral loads, and a much simpler preparation procedure. Our main protocol consists of virus inactivation by heating and the addition of isopropanol and tryptic digestion of the proteins sedimented from the swabs followed by MS analysis. A set of unique peptides, produced as a result of proteolysis of the nucleocapsid phosphoprotein of SARS-CoV-2, is detected. The obtained results can further be used to create fast parallel mass-spectrometric approaches for the detection of the virus in the nasopharyngeal mucosa, saliva, sputum and other physiological fluids.

Single-cell RNA sequencing reveals in vivo signatures of SARS-CoV-2-reactive T cells through 'reverse phenotyping' (preprint)

The in vivo phenotypic profile of T cells reactive to severe acute respiratory syndrome (SARS)-CoV-2 antigens remains poorly understood. Conventional methods to detect antigen-reactive T cells require in vitro antigenic re-stimulation or highly individualized peptide-human leukocyte antigen (pHLA) multimers. Here, we used single-cell RNA sequencing to identify and profile SARS-CoV-2-reactive T cells from Coronavirus Disease 2019 (COVID-19) patients. To do so, we induced transcriptional shifts by antigenic stimulation in vitro and took advantage of natural T cell receptor (TCR) sequences of clonally expanded T cells as barcodes for reverse phenotyping. This allowed identification of SARS-CoV-2-reactive TCRs and revealed phenotypic effects introduced by antigen-specific stimulation. We characterized transcriptional signatures of currently and previously activated SARS-CoV-2-reactive T cells, and showed correspondence with phenotypes of T cells from the respiratory tract of patients with severe disease in the presence or absence of virus in independent cohorts. Reverse phenotyping is a powerful tool to provide an integrated insight into cellular states of SARS-CoV-2-reactive T cells across tissues and activation states.

Mass Spectrometric detection of SARS-CoV-2 virus in scrapings of the epithelium of the nasopharynx of infected patients via Nucleocapsid N protein (preprint)

Detection of viral RNA by PCR is currently the main diagnostic tool for COVID-19 [1]. The PCR-based test, however, shows limited sensitivity, especially at early and late stages of the disease development [2,3], and is relatively time consuming. Fast and reliable complementary methods for detecting the viral infection would be of help in the current pandemia conditions. Mass-spectrometry is one of such possibilities. We have developed a mass-spectrometry based method for the detection of the SARS CoV-2 virus in nasopharynx epithelial swabs, based on the detection of the viral nucleocapsid N protein. The N protein of the SARS-COV-2 virus, the most abundant protein in the virion, is the best candidate for mass-spectrometric detection of the infection, and MS-based detection of several peptides from the SARS-COoV-2 nucleoprotein has been reported earlier by the Sinz group [4]. Our approach shows confident identification of the N protein in patient samples even with the lowest viral loads and a much simpler preparation procedure. Our main protocol consists of virus inactivation by heating and adding of isopropanol, and tryptic digestion of the proteins sedimented from the swabs followed by MS analysis. A set of unique peptides, produced as a result of proteolysis of the nucleocapsid phosphoprotein of SARS-CoV-2, is detected. The obtained results can further be used to create fast parallel mass-spectrometric approaches for the detection of the virus in the nasopharyngeal mucosa, saliva, sputum and other physiological fluids.