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

Asymptotic properties of pivotal sampling with application to spatial sampling

Unequal probability sampling without replacement is commonly used for sample selection. To produce estimators with associated condence intervals, some basic statistical properties like consistency and asymptotic normality of the Horvitz-Thompson estimator are desirable. These properties have been mainly studied for large entropy sampling designs. On the other hand, spatial sampling designs rather make use of sampling algorithms which take into account the order of units in the population, like systematic sampling or pivotal sampling. So far, the statistical properties of such procedures have not been investigated. In this work, we study the asymptotic properties of the pivotal sampling design. Under mild assumptions, we prove that the Horvitz-Thompson estimator is asymptotically normally distributed and that a conservative variance estimator can always be computed. We also introduce a general spatial sampling design which is spatially balanced, which possesses good statistical properties and which is computationally very ecient, even for large databases

Asymptotic properties of pivotal sampling with application to spatial sampling

Unequal probability sampling without replacement is commonly used for sample selection. To produce estimators with associated condence intervals, some basic statistical properties like consistency and asymptotic normality of the Horvitz-Thompson estimator are desirable. These properties have been mainly studied for large entropy sampling designs. On the other hand, spatial sampling designs rather make use of sampling algorithms which take into account the order of units in the population, like systematic sampling or pivotal sampling. So far, the statistical properties of such procedures have not been investigated. In this work, we study the asymptotic properties of the pivotal sampling design. Under mild assumptions, we prove that the Horvitz-Thompson estimator is asymptotically normally distributed and that a conservative variance estimator can always be computed. We also introduce a general spatial sampling design which is spatially balanced, which possesses good statistical properties and which is computationally very ecient, even for large databases

Inference under pivotal sampling: Properties, variance estimation, and application to tesselation for spatial sampling

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Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infection rates

Contento L, Castelletti N, Raimúndez E, et al. Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infection rates. medRxiv. 2021

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

Nakayama M, Marchi H, Dmitrieva AM, et al. 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. Frontiers in Microbiology. 2023;13: 957830.**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 infectionin vitrowere 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 retainedin vitrowhen 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

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

Reinkemeyer C, Khazaei Y, Weigert M, et al. The Prospective COVID-19 Post-Immunization Serological Cohort in Munich (KoCo-Impf): Risk Factors and Determinants of Immune Response in Healthcare Workers. Viruses. 2023;15(7): 1574.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

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

Pritsch M, Radon K, Bakuli A, et al. Prevalence and Risk Factors of Infection in the Representative COVID-19 Cohort Munich. International journal of environmental research and public health. 2021;18(7): 3572.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

A Serology Strategy for Epidemiological Studies Based on the Comparison of the Performance of Seven Different Test Systems - The Representative COVID-19 Cohort Munich

Olbrich L, Castelletti N, Schälte Y, et al. A Serology Strategy for Epidemiological Studies Based on the Comparison of the Performance of Seven Different Test Systems - The Representative COVID-19 Cohort Munich. bioRxiv. 2021.Background - Serosurveys are essential to understand SARS-CoV-2 exposure and enable population-level surveillance, but currently available tests need further in-depth evaluation. We aimed to identify testing-strategies by comparing seven seroassays in a population-based cohort. Methods - We analysed 6,658 samples consisting of true-positives (n=193), true-negatives (n=1,091), and specimens of unknown status (n=5,374). For primary testing, we used Euroimmun-Anti-SARS-CoV-2-ELISA-IgA/IgG and Roche-Elecsys-Anti-SARS-CoV-2; and virus-neutralisation, GeneScript®cPass™, VIRAMED-SARS-CoV-2-ViraChip®, and Mikrogen- recom Line-SARS-CoV-2-IgG, including common-cold CoVs, for confirmatory testing. Statistical modelling generated optimised assay cut-off-thresholds. Findings - Sensitivity of Euroimmun-anti-S1-IgA was 64.8%, specificity 93.3%; 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 titres remained stable for at least 90-120 days after RT-PCR-positivity. Of true-positives with positive RT-PCR (<30 days), 6.7% did not mount detectable seroresponses. Virus-neutralisation was 73.8% sensitive, 100.0% specific (1:10 dilution). Neutralisation surrogate tests (GeneScript®cPass™, Mikrogen- recom Line-RBD) were >94.9% sensitive, >98.1% specific. Seasonality had limited effects; cross-reactivity with common-cold CoVs 229E and NL63 in SARS-CoV-2 true-positives was significant. Conclusion - Optimised cut-offs improved test performances of several tests. Non-reactive serology in true-positives was uncommon. For epidemiological purposes, confirmatory testing with virus-neutralisation may be replaced with GeneScript®cPass™ or recom Line-RBD. Head-to-head comparisons given here aim to contribute to the refinement of testing-strategies for individual and public health use