Plasma immune signatures can predict rejection-free survival in the first year after pediatric liver transplantation.

BACKGROUND & AIMS: After pediatric liver transplantation (pLT), children undergo life-long immunosuppression since reliable biomarkers for the assessment of rejection probability are scarce. In the multicenter (n = 7) prospective clinical cohort "ChilSFree" study, we aimed to characterize longitudinal dynamics of soluble and cellular immune mediators during the first year after pLT and identify early biomarkers associated with outcome. METHODS: Using a Luminex-based multiplex technique paired with flow cytometry, we characterized longitudinal dynamics of soluble immune mediators (SIMs, n = 50) and immune cells in the blood of 244 patients at eight visits over 1 year: before, and 7/14/21/28 days and 3/6/12 months after pLT. RESULTS: The unsupervised clustering of patients based on SIM profiles revealed six unique SIM signatures associated with clinical outcome. From three signatures linked to improved outcome, one was associated with 1-year-long rejection-free survival and stable graft function and was characterized by low levels of pro-inflammatory SIMs (CXCL8/9/10/12, CCL7, SCGF-ß, sICAM-1), and high levels of regenerative (SCF, TNF-ß) and pro-apoptotic (TRAIL) SIMs (all, p <0.001, fold change >100). Of note, this SIM signature appeared 2 weeks after pLT and remained stable over the entire year, pointing towards its potential as a novel early biomarker for minimizing or weaning immunosuppression. In the blood of these patients, a higher frequency of CD56bright natural killer cells (p <0.01), a known hallmark also associated with operationally tolerant pLT patients, was detected. The concordance of the model for prediction of rejection based on identified SIM signatures was 0.715, and 0.795, in combination with living-related transplantation as a covariate, respectively. CONCLUSIONS: SIM blood signatures may enable the non-invasive and early assessment of rejection risks in the first year after pLT, paving the way for improved clinical management. IMPACT AND IMPLICATIONS: ChilSFree represents the largest pediatric liver transplant (pLT) cohort with paired longitudinal data on soluble immune mediators (SIMs) and immune phenotyping in the first year after pLT. SIM signatures allow for the selection of rejection-free patients 2 weeks after pLT independently of patient diagnosis, sex, or age. The SIM signatures may enable the non-invasive and early assessment of rejection risks, paving the way for minimization or withdrawal of immunosuppression after pLT.

Estimating the relative importance of epidemiological and behavioural parameters for epidemic mpox transmission: a modelling study.

BACKGROUND: Many European countries experienced outbreaks of mpox in 2022, and there was an mpox outbreak in 2023 in the Democratic Republic of Congo. There were many apparent differences between these outbreaks and previous outbreaks of mpox; the recent outbreaks were observed in men who have sex with men after sexual encounters at common events, whereas earlier outbreaks were observed in a wider population with no identifiable link to sexual contacts. These apparent differences meant that data from previous outbreaks could not reliably be used to parametrise infectious disease models during the 2022 and 2023 mpox outbreaks, and modelling efforts were hampered by uncertainty around key transmission and immunity parameters. METHODS: We developed a stochastic, discrete-time metapopulation model for mpox that allowed for sexual and non-sexual transmission and the implementation of non-pharmaceutical interventions, specifically contact tracing and pre- and post-exposure vaccinations. We calibrated the model to case data from Berlin and used Sobol sensitivity analysis to identify parameters that mpox transmission is especially sensitive to. We also briefly analysed the sensitivity of the effectiveness of non-pharmaceutical interventions to various efficacy parameters. RESULTS: We found that variance in the transmission probabilities due to both sexual and non-sexual transmission had a large effect on mpox transmission in the model, as did the level of immunity to mpox conferred by a previous smallpox vaccination. Furthermore, variance in the number of pre-exposure vaccinations offered was the dominant contributor to variance in mpox dynamics in men who have sex with men. If pre-exposure vaccinations were not available, both the accuracy and timeliness of contact tracing had a large impact on mpox transmission in the model. CONCLUSIONS: Our results are valuable for guiding epidemiological studies for parameter ascertainment and identifying key factors for success of non-pharmaceutical interventions.

The impact of inaccurate assumptions about antibody test accuracy on the parametrisation and results of infectious disease models of epidemics.

The parametrisation of infectious disease models is often done based on epidemiological studies that use diagnostic and serology tests to establish disease prevalence or seroprevalence in the population being modelled. During outbreaks of an emerging infectious disease, tests are often used, both for disease control and epidemiological studies, before studies evaluating their accuracy in the population have concluded, with assumptions made about accuracy parameters like sensitivity and specificity. In this simulation study, we simulated such an outbreak, based on the case study of COVID-19, and found that inaccurate parametrisation of infectious disease models due to assumptions about antibody test accuracy in a seroprevalence study can cause modelling results that inform public health decisions to be inaccurate; for example, in our simulation setup, assuming that antibody test specificity was 0.99 instead of 0.90 when it was in fact 0.90 led to an average relative difference of 0.78 in model-projected peak hospitalisations, even when test sensitivity and all other parameters were accurately characterised. We therefore suggest that methods to speed up test evaluation studies are vitally important in the public health response to an emerging outbreak.

Sexual Contact Patterns in High-Income Countries-A Comparative Analysis Using Data From Germany, the United Kingdom, and the United States.

Sexual contact patterns determine the spread of sexually transmitted infections and are a central input parameter for mathematical models in this field. We evaluated the importance of country-specific sexual contact pattern parametrization for high-income countries with similar cultural backgrounds by comparing data from two independent studies (HaBIDS and SBG) in Germany, a country without systematic sexual contact pattern data, with data from the National Survey of Sexual Attitudes and Lifestyles (Natsal) in the UK, and the National Survey of Family Growth (NSFG) in the US, the two longest running sexual contact studies in high-income countries. We investigated differences in the distribution of the reported number of opposite-sex partners, same-sex partners and both-sex partners using weighted negative binomial regression adjusted for age and sex (as well as stratified by age). In our analyses, UK and US participants reported a substantially higher number of lifetime opposite-sex sexual partners compared to both German studies. The difference in lifetime partners was caused by a higher proportion of individuals with many partners in the young age group (<24 years) in the UK and the US. Partner acquisition in older age groups was similar. The number of same-sex partners was similar across countries, while there was heterogeneity in the reported experience with partners from both sexes, consistent with the differences observed for opposite-sex sexual partners. These patterns can lead to substantially different dynamics of sexually transmitted infections across ages, and have strong impact on the results of modeling studies.