Metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes.

Spatially resolved metabolomics enables the investigation of tumoral metabolites in situ. Inter- and intratumor heterogeneity are key factors associated with patient outcomes. Adrenocortical carcinoma (ACC) is an exceedingly rare tumor associated with poor survival. Its clinical prognosis is highly variable, but the contributions of tumor metabolic heterogeneity have not been investigated thus far to our knowledge. An in-depth understanding of tumor heterogeneity requires molecular feature-based identification of tumor subpopulations associated with tumor aggressiveness. Here, using spatial metabolomics by high-mass resolution MALDI Fourier transform ion cyclotron resonance mass spectrometry imaging, we assessed metabolic heterogeneity by de novo discovery of metabolic subpopulations and Simpson's diversity index. After identification of tumor subpopulations in 72 patients with ACC, we additionally performed a comparison with 25 tissue sections of normal adrenal cortex to identify their common and unique metabolic subpopulations. We observed variability of ACC tumor heterogeneity and correlation of high metabolic heterogeneity with worse clinical outcome. Moreover, we identified tumor subpopulations that served as independent prognostic factors and, furthermore, discovered 4 associated anticancer drug action pathways. Our research may facilitate comprehensive understanding of the biological implications of tumor subpopulations in ACC and showed that metabolic heterogeneity might impact chemotherapy.

The representative COVID-19 cohort Munich (KoCo19): from the beginning of the pandemic to the Delta virus variant.

BACKGROUND: Population-based serological studies allow to estimate prevalence of SARS-CoV-2 infections despite a substantial number of mild or asymptomatic disease courses. This became even more relevant for decision making after vaccination started. The KoCo19 cohort tracks the pandemic progress in the Munich general population for over two years, setting it apart in Europe. METHODS: Recruitment occurred during the initial pandemic wave, including 5313 participants above 13 years from private households in Munich. Four follow-ups were held at crucial times of the pandemic, with response rates of at least 70%. Participants filled questionnaires on socio-demographics and potential risk factors of infection. From Follow-up 2, information on SARS-CoV-2 vaccination was added. SARS-CoV-2 antibody status was measured using the Roche Elecsys® Anti-SARS-CoV-2 anti-N assay (indicating previous infection) and the Roche Elecsys® Anti-SARS-CoV-2 anti-S assay (indicating previous infection and/or vaccination). This allowed us to distinguish between sources of acquired antibodies. RESULTS: The SARS-CoV-2 estimated cumulative sero-prevalence increased from 1.6% (1.1-2.1%) in May 2020 to 14.5% (12.7-16.2%) in November 2021. Underreporting with respect to official numbers fluctuated with testing policies and capacities, becoming a factor of more than two during the second half of 2021. Simultaneously, the vaccination campaign against the SARS-CoV-2 virus increased the percentage of the Munich population having antibodies, with 86.8% (85.5-87.9%) having developed anti-S and/or anti-N in November 2021. Incidence rates for infections after (BTI) and without previous vaccination (INS) differed (ratio INS/BTI of 2.1, 0.7-3.6). However, the prevalence of infections was higher in the non-vaccinated population than in the vaccinated one. Considering the whole follow-up time, being born outside Germany, working in a high-risk job and living area per inhabitant were identified as risk factors for infection, while other socio-demographic and health-related variables were not. Although we obtained significant within-household clustering of SARS-CoV-2 cases, no further geospatial clustering was found. CONCLUSIONS: Vaccination increased the coverage of the Munich population presenting SARS-CoV-2 antibodies, but breakthrough infections contribute to community spread. As underreporting stays relevant over time, infections can go undetected, so non-pharmaceutical measures are crucial, particularly for highly contagious strains like Omicron.

The Prospective COVID-19 Post-Immunization Serological Cohort in Munich (KoCo-Impf): Risk Factors and Determinants of Immune Response in Healthcare Workers.

Antibody studies analyze immune responses to SARS-CoV-2 vaccination and infection, which is crucial for selecting vaccination strategies. In the KoCo-Impf study, conducted between 16 June and 16 December 2021, 6088 participants aged 18 and above from Munich were recruited to monitor antibodies, particularly in healthcare workers (HCWs) at higher risk of infection. Roche Elecsys® Anti-SARS-CoV-2 assays on dried blood spots were used to detect prior infections (anti-Nucleocapsid antibodies) and to indicate combinations of vaccinations/infections (anti-Spike antibodies). The anti-Spike seroprevalence was 94.7%, whereas, for anti-Nucleocapsid, it was only 6.9%. HCW status and contact with SARS-CoV-2-positive individuals were identified as infection risk factors, while vaccination and current smoking were associated with reduced risk. Older age correlated with higher anti-Nucleocapsid antibody levels, while vaccination and current smoking decreased the response. Vaccination alone or combined with infection led to higher anti-Spike antibody levels. Increasing time since the second vaccination, advancing age, and current smoking reduced the anti-Spike response. The cumulative number of cases in Munich affected the anti-Spike response over time but had no impact on anti-Nucleocapsid antibody development/seropositivity. Due to the significantly higher infection risk faced by HCWs and the limited number of significant risk factors, it is suggested that all HCWs require protection regardless of individual traits.

Socioeconomic and risk-related drivers of compliance with measures to prevent SARS-CoV-2 infection: evidence from the Munich-based KoCo19 study.

OBJECTIVES: Although a growing share of the population in many countries has been vaccinated against the SARS-CoV-2 virus to different degrees, social distancing and hygienic non-pharmaceutical interventions still play a substantial role in containing the pandemic. The goal of this study was to investigate which factors are correlated with a higher compliance with these regulations in the context of a cohort study in the city of Munich, southern Germany, during the summer of 2020, i.e. after the first lockdown phase. METHODS: Using self-reported compliance with six regulations and personal hygiene rules (washing hands, avoiding touching face, wearing a mask, keeping distance, avoiding social gatherings, avoiding public spaces) we extracted two compliance factor scores, namely compliance with personal hygiene measures and compliance with social distancing regulations. Using linear and logistic regressions, we estimated the correlation of several socio-demographic and risk perception variables with both compliance scores. RESULTS: Risk aversion proved to be a consistent and significant driver of compliance across all compliance behaviors. Furthermore, being female, being retired and having a migration background were positively associated with compliance with personal hygiene regulations, whereas older age was related with a higher compliance with social distancing regulations. Generally, socioeconomic characteristics were not related with compliance, except for education, which was negatively related with compliance with personal hygiene measures. CONCLUSIONS: Our results suggest that for a targeted approach to improve compliance with measures to prevent SARS-CoV-2 infection, special attention should be given to younger, male and risk-prone individuals.

Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infectious contacts.

Mathematical models have been widely used during the ongoing SARS-CoV-2 pandemic for data interpretation, forecasting, and policy making. However, most models are based on officially reported case numbers, which depend on test availability and test strategies. The time dependence of these factors renders interpretation difficult and might even result in estimation biases. Here, we present a computational modelling framework that allows for the integration of reported case numbers with seroprevalence estimates obtained from representative population cohorts. To account for the time dependence of infection and testing rates, we embed flexible splines in an epidemiological model. The parameters of these splines are estimated, along with the other parameters, from the available data using a Bayesian approach. The application of this approach to the official case numbers reported for Munich (Germany) and the seroprevalence reported by the prospective COVID-19 Cohort Munich (KoCo19) provides first estimates for the time dependence of the under-reporting factor. Furthermore, we estimate how the effectiveness of non-pharmaceutical interventions and of the testing strategy evolves over time. Overall, our results show that the integration of temporally highly resolved and representative data is beneficial for accurate epidemiological analyses.

Quantitative proteomics of differentiated primary bronchial epithelial cells from chronic obstructive pulmonary disease and control identifies potential novel host factors post-influenza A virus infection.

Background: Chronic obstructive pulmonary disease (COPD) collectively refers to chronic and progressive lung diseases that cause irreversible limitations in airflow. Patients with COPD are at high risk for severe respiratory symptoms upon influenza virus infection. Airway epithelial cells provide the first-line antiviral defense, but whether or not their susceptibility and response to influenza virus infection changes in COPD have not been elucidated. Therefore, this study aimed to compare the susceptibility of COPD- and control-derived airway epithelium to the influenza virus and assess protein changes during influenza virus infection by quantitative proteomics. Materials and methods: The presence of human- and avian-type influenza A virus receptor was assessed in control and COPD lung sections as well as in fully differentiated primary human bronchial epithelial cells (phBECs) by lectin- or antibody-based histochemical staining. PhBECs were from COPD lungs, including cells from moderate- and severe-stage diseases, and from age-, sex-, smoking, and history-matched control lung specimens. Protein profiles pre- and post-influenza virus infection in vitro were directly compared using quantitative proteomics, and selected findings were validated by qRT-PCR and immunoblotting. Results: The human-type influenza receptor was more abundant in human airways than the avian-type influenza receptor, a property that was retained in vitro when differentiating phBECs at the air-liquid interface. Proteomics of phBECs pre- and post-influenza A virus infection with A/Puerto Rico/8/34 (PR8) revealed no significant differences between COPD and control phBECs in terms of flu receptor expression, cell type composition, virus replication, or protein profile pre- and post-infection. Independent of health state, a robust antiviral response to influenza virus infection was observed, as well as upregulation of several novel influenza virus-regulated proteins, including PLSCR1, HLA-F, CMTR1, DTX3L, and SHFL. Conclusion: COPD- and control-derived phBECs did not differ in cell type composition, susceptibility to influenza virus infection, and proteomes pre- and post-infection. Finally, we identified novel influenza A virus-regulated proteins in bronchial epithelial cells that might serve as potential targets to modulate the pathogenicity of infection and acute exacerbations.

Head-to-head evaluation of seven different seroassays including direct viral neutralisation in a representative cohort for SARS-CoV-2.

A number of seroassays are available for SARS-CoV-2 testing; yet, head-to-head evaluations of different testing principles are limited, especially using raw values rather than categorical data. In addition, identifying correlates of protection is of utmost importance, and comparisons of available testing systems with functional assays, such as direct viral neutralisation, are needed.We analysed 6658 samples consisting of true-positives (n=193), true-negatives (n=1091), and specimens of unknown status (n=5374). For primary testing, we used Euroimmun-Anti-SARS-CoV-2-ELISA-IgA/IgG and Roche-Elecsys-Anti-SARS-CoV-2. Subsequently virus-neutralisation, GeneScriptcPass, VIRAMED-SARS-CoV-2-ViraChip, and Mikrogen-recomLine-SARS-CoV-2-IgG were applied for confirmatory testing. Statistical modelling generated optimised assay cut-off thresholds. Sensitivity of Euroimmun-anti-S1-IgA was 64.8%, specificity 93.3% (manufacturer's cut-off); for Euroimmun-anti-S1-IgG, sensitivity was 77.2/79.8% (manufacturer's/optimised cut-offs), specificity 98.0/97.8%; Roche-anti-N sensitivity was 85.5/88.6%, specificity 99.8/99.7%. In true-positives, mean and median Euroimmun-anti-S1-IgA and -IgG titres decreased 30/90 days after RT-PCR-positivity, Roche-anti-N titres decreased significantly later. Virus-neutralisation was 80.6% sensitive, 100.0% specific (≥1:5 dilution). Neutralisation surrogate tests (GeneScriptcPass, Mikrogen-recomLine-RBD) were >94.9% sensitive and >98.1% specific. Optimised cut-offs improved test performances of several tests. Confirmatory testing with virus-neutralisation might be complemented with GeneScriptcPassTM or recomLine-RBD for certain applications. Head-to-head comparisons given here aim to contribute to the refinement of testing strategies for individual and public health use.

From first to second wave: follow-up of the prospective COVID-19 cohort (KoCo19) in Munich (Germany).

BACKGROUND: In the 2nd year of the COVID-19 pandemic, knowledge about the dynamics of the infection in the general population is still limited. Such information is essential for health planners, as many of those infected show no or only mild symptoms and thus, escape the surveillance system. We therefore aimed to describe the course of the pandemic in the Munich general population living in private households from April 2020 to January 2021. METHODS: The KoCo19 baseline study took place from April to June 2020 including 5313 participants (age 14 years and above). From November 2020 to January 2021, we could again measure SARS-CoV-2 antibody status in 4433 of the baseline participants (response 83%). Participants were offered a self-sampling kit to take a capillary blood sample (dry blood spot; DBS). Blood was analysed using the Elecsys® Anti-SARS-CoV-2 assay (Roche). Questionnaire information on socio-demographics and potential risk factors assessed at baseline was available for all participants. In addition, follow-up information on health-risk taking behaviour and number of personal contacts outside the household (N = 2768) as well as leisure time activities (N = 1263) were collected in summer 2020. RESULTS: Weighted and adjusted (for specificity and sensitivity) SARS-CoV-2 sero-prevalence at follow-up was 3.6% (95% CI 2.9-4.3%) as compared to 1.8% (95% CI 1.3-3.4%) at baseline. 91% of those tested positive at baseline were also antibody-positive at follow-up. While sero-prevalence increased from early November 2020 to January 2021, no indication of geospatial clustering across the city of Munich was found, although cases clustered within households. Taking baseline result and time to follow-up into account, men and participants in the age group 20-34 years were at the highest risk of sero-positivity. In the sensitivity analyses, differences in health-risk taking behaviour, number of personal contacts and leisure time activities partly explained these differences. CONCLUSION: The number of citizens in Munich with SARS-CoV-2 antibodies was still below 5% during the 2nd wave of the pandemic. Antibodies remained present in the majority of SARS-CoV-2 sero-positive baseline participants. Besides age and sex, potentially confounded by differences in behaviour, no major risk factors could be identified. Non-pharmaceutical public health measures are thus still important.

Prevalence and Risk Factors of Infection in the Representative COVID-19 Cohort Munich.

Given the large number of mild or asymptomatic SARS-CoV-2 cases, only population-based studies can provide reliable estimates of the magnitude of the pandemic. We therefore aimed to assess the sero-prevalence of SARS-CoV-2 in the Munich general population after the first wave of the pandemic. For this purpose, we drew a representative sample of 2994 private households and invited household members 14 years and older to complete questionnaires and to provide blood samples. SARS-CoV-2 seropositivity was defined as Roche N pan-Ig ≥ 0.4218. We adjusted the prevalence for the sampling design, sensitivity, and specificity. We investigated risk factors for SARS-CoV-2 seropositivity and geospatial transmission patterns by generalized linear mixed models and permutation tests. Seropositivity for SARS-CoV-2-specific antibodies was 1.82% (95% confidence interval (CI) 1.28-2.37%) as compared to 0.46% PCR-positive cases officially registered in Munich. Loss of the sense of smell or taste was associated with seropositivity (odds ratio (OR) 47.4; 95% CI 7.2-307.0) and infections clustered within households. By this first population-based study on SARS-CoV-2 prevalence in a large German municipality not affected by a superspreading event, we could show that at least one in four cases in private households was reported and known to the health authorities. These results will help authorities to estimate the true burden of disease in the population and to take evidence-based decisions on public health measures.

Radiation Response of Human Cardiac Endothelial Cells Reveals a Central Role of the cGAS-STING Pathway in the Development of Inflammation.

Radiation-induced inflammation leading to the permeability of the endothelial barrier may increase the risk of cardiovascular disease. The aim of this study was to investigate potential mechanisms in vitro at the level of the proteome in human coronary artery endothelial cells (HCECest2) that were exposed to radiation doses of 0, 0.25, 0.5, 2.0 and 10 Gy (60Co-γ). Proteomics analysis was performed using mass spectrometry in a label-free data-independent acquisition mode. The data were validated using bioinformatics and immunoblotting. The low- and moderate-dose-irradiated samples (0.25 Gy, 0.5 Gy) showed only scarce proteome changes. In contrast, an activation of DNA-damage repair, inflammation, and oxidative stress pathways was seen after the high-dose treatments (2 and 10 Gy). The level of the DNA damage response protein DDB2 was enhanced early at the 10 Gy dose. The expression of proteins belonging to the inflammatory response or cGAS-STING pathway (STING, STAT1, ICAM1, ISG15) increased in a dose-dependent manner, showing the strongest effects at 10 Gy after one week. This study suggests a connection between the radiation-induced DNA damage and the induction of inflammation which supports the inhibition of the cGAS-STING pathway in the prevention of radiation-induced cardiovascular disease.