AllergoOncology: Biomarkers and refined classification for research in the allergy and glioma nexus-A joint EAACI-EANO position paper.

Epidemiological studies have explored the relationship between allergic diseases and cancer risk or prognosis in AllergoOncology. Some studies suggest an inverse association, but uncertainties remain, including in IgE-mediated diseases and glioma. Allergic disease stems from a Th2-biased immune response to allergens in predisposed atopic individuals. Allergic disorders vary in phenotype, genotype and endotype, affecting their pathophysiology. Beyond clinical manifestation and commonly used clinical markers, there is ongoing research to identify novel biomarkers for allergy diagnosis, monitoring, severity assessment and treatment. Gliomas, the most common and diverse brain tumours, have in parallel undergone changes in classification over time, with specific molecular biomarkers defining glioma subtypes. Gliomas exhibit a complex tumour-immune interphase and distinct immune microenvironment features. Immunotherapy and targeted therapy hold promise for primary brain tumour treatment, but require more specific and effective approaches. Animal studies indicate allergic airway inflammation may delay glioma progression. This collaborative European Academy of Allergy and Clinical Immunology (EAACI) and European Association of Neuro-Oncology (EANO) Position Paper summarizes recent advances and emerging biomarkers for refined allergy and adult-type diffuse glioma classification to inform future epidemiological and clinical studies. Future research is needed to enhance our understanding of immune-glioma interactions to ultimately improve patient prognosis and survival.

Digitally-enabled, person-centred care (PCC) in allergen immunotherapy: An ARIA-EAACI Position Paper.

In rhinitis and asthma, several mHealth apps have been developed but only a few have been validated. However, these apps have a high potential for improving person-centred care (PCC), especially in allergen immunotherapy (AIT). They can provide support in AIT initiation by selecting the appropriate patient and allergen shared decision-making. They can also help in (i) the evaluation of (early) efficacy, (ii) early and late stopping rules and (iii) the evaluation of (carried-over) efficacy after cessation of the treatment course. Future perspectives have been formulated in the first report of a joint task force (TF)-Allergic Rhinitis and Its Impact on Asthma (ARIA) and the European Academy of Allergy and Clinical Immunology (EAACI)-on digital biomarkers. The TF on AIT now aims to (i) outline the potential of the clinical applications of mHealth solutions, (ii) express their current limitations, (iii) make proposals regarding further developments for both clinical practice and scientific purpose and (iv) suggest which of the tools might best comply with the purpose of digitally-enabled PCC in AIT.

Working with companies that manufacture breastmilk substitutes: An EAACI position paper.

Breastmilk is the optimal source of nutrition for infants and should ideally be provided exclusively for the first 6 months of life, and alongside complementary food until 2 years of life. However, there are circumstances where a breastmilk substitute (BMS) may be required. This includes maternal and/or child conditions or personal preference. Whilst these circumstances should never be used as an opportunity to promote BMS, healthcare professionals (HCPs) need to have the knowledge of suitable alternatives and should always be guided by scientific and health motives when recommending a BMS. The Task Force 'Milk Formula Industry Sponsorship' from the European Academy of Allergy and Clinical Immunology (EAACI), provides with this publication recommendations for EAACI interactions with the BMS manufacturers and how this will be supervised.

Asthma and rhinitis control in adolescents and young adults: A real-world MASK-air study.

BACKGROUND: In allergic rhinitis and asthma, adolescents and young adult patients are likely to differ from older patients. We compared adolescents, young adults and adults on symptoms, control levels, and medication adherence. METHODS: In a cross-sectional study (2015-2022), we assessed European users of the MASK-air mHealth app of three age groups: adolescents (13-18 years), young adults (18-26 years), and adults (>26 years). We compared them on their reported rhinitis and asthma symptoms, use and adherence to rhinitis and asthma treatment and app adherence. Allergy symptoms and control were assessed by means of visual analogue scales (VASs) on rhinitis or asthma, the combined symptom-medication score (CSMS), and the electronic daily control score for asthma (e-DASTHMA). We built multivariable regression models to compare symptoms or medication accounting for potential differences in demographic characteristics and baseline severity. RESULTS: We assessed 965 adolescent users (15,252 days), 4595 young adults (58,161 days), and 15,154 adult users (258,796 days). Users of all three age groups displayed similar app adherence. In multivariable models, age groups were not found to significantly differ in their adherence to rhinitis or asthma medication. These models also found that adolescents reported lower VAS on global allergy, ocular, and asthma symptoms (as well as lower CSMS) than young adults and adults. CONCLUSIONS: Adolescents reported a better rhinitis and asthma control than young adults and adults, even though similar medication adherence levels were observed across age groups. These results pave the way for future studies on understanding how adolescents control their allergic diseases.

Creation of a pandemic memory by tracing COVID-19 infections and immunity in Luxembourg (CON-VINCE).

BACKGROUND: During the COVID-19 pandemic swift implementation of research cohorts was key. While many studies focused exclusively on infected individuals, population based cohorts are essential for the follow-up of SARS-CoV-2 impact on public health. Here we present the CON-VINCE cohort, estimate the point and period prevalence of the SARS-CoV-2 infection, reflect on the spread within the Luxembourgish population, examine immune responses to SARS-CoV-2 infection and vaccination, and ascertain the impact of the pandemic on population psychological wellbeing at a nationwide level. METHODS: A representative sample of the adult Luxembourgish population was enrolled. The cohort was followed-up for twelve months. SARS-CoV-2 RT-qPCR and serology were conducted at each sampling visit. The surveys included detailed epidemiological, clinical, socio-economic, and psychological data. RESULTS: One thousand eight hundred sixty-five individuals were followed over seven visits (April 2020-June 2021) with the final weighted period prevalence of SARS-CoV-2 infection of 15%. The participants had similar risks of being infected regardless of their gender, age, employment status and education level. Vaccination increased the chances of IgG-S positivity in infected individuals. Depression, anxiety, loneliness and stress levels increased at a point of study when there were strict containment measures, returning to baseline afterwards. CONCLUSION: The data collected in CON-VINCE study allowed obtaining insights into the infection spread in Luxembourg, immunity build-up and the impact of the pandemic on psychological wellbeing of the population. Moreover, the study holds great translational potential, as samples stored at the biobank, together with self-reported questionnaire information, can be exploited in further research. TRIAL REGISTRATION: Trial registration number: NCT04379297, 10 April 2020.

Venom Component Allergen IgE Measurement in the Diagnosis and Management of Insect Sting Allergy.

Accurate identification of allergy-eliciting stinging insect(s) is essential to ensuring effective management of Hymenoptera venom-allergic individuals with venom-specific immunotherapy. Diagnostic testing using whole-venom extracts with skin tests and serologic-based analyses remains the first level of discrimination for honeybee versus vespid venom sensitization in patients with a positive clinical history. As a second-level evaluation, serologic testing using molecular venom allergens can further discriminate genuine sensitization (honeybee venom: Api m 1, 3, 4, and 10 vs yellow jacket venom/Polistes dominula venom Ves v 1/Pol d 1 and Ves v 5/Pol d 5) from interspecies cross-reactivity (hyaluronidases [Api m 2, Ves v 2, and Pol d 2] and dipeptidyl peptidases IV [Api m 5, Ves v 3, and Pol d 3]). Clinical laboratories use a number of singleplex, oligoplex, and multiplex immunoassays that employ both extracted whole-venom and molecular venom allergens (highlighted earlier) for confirmation of allergic venom sensitization. Established quantitative singleplex autoanalyzers have general governmental regulatory clearance worldwide for venom-allergic patient testing with maximally achievable analytical sensitivity (0.1 kUA/L) and confirmed reproducibility (interassay coefficient of variation <10%). Emerging oligoplex and multiplex (fixed-panel) assays conserve on serum and are more cost-effective, but they need regulatory clearance in some countries and are prone to higher rates of detecting asymptomatic sensitization. Ultimately, the patient's clinical history, combined with proof of sensitization, is the final arbiter in the diagnosis of Hymenoptera venom allergy.

Gut microbial factors predict disease severity in a mouse model of multiple sclerosis.

Gut bacteria are linked to neurodegenerative diseases but the risk factors beyond microbiota composition are limited. Here we used a pre-clinical model of multiple sclerosis (MS), experimental autoimmune encephalomyelitis (EAE), to identify microbial risk factors. Mice with different genotypes and complex microbiotas or six combinations of a synthetic human microbiota were analysed, resulting in varying probabilities of severe neuroinflammation. However, the presence or relative abundances of suspected microbial risk factors failed to predict disease severity. Akkermansia muciniphila, often associated with MS, exhibited variable associations with EAE severity depending on the background microbiota. Significant inter-individual disease course variations were observed among mice harbouring the same microbiota. Evaluation of microbial functional characteristics and host immune responses demonstrated that the immunoglobulin A coating index of certain bacteria before disease onset is a robust individualized predictor of disease development. Our study highlights the need to consider microbial community networks and host-specific bidirectional interactions when aiming to predict severity of neuroinflammation.

Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality.

Tools for predicting COVID-19 outcomes enable personalized healthcare, potentially easing the disease burden. This collaborative study by 15 institutions across Europe aimed to develop a machine learning model for predicting the risk of in-hospital mortality post-SARS-CoV-2 infection. Blood samples and clinical data from 1286 COVID-19 patients collected from 2020 to 2023 across four cohorts in Europe and Canada were analyzed, with 2906 long non-coding RNAs profiled using targeted sequencing. From a discovery cohort combining three European cohorts and 804 patients, age and the long non-coding RNA LEF1-AS1 were identified as predictive features, yielding an AUC of 0.83 (95% CI 0.82-0.84) and a balanced accuracy of 0.78 (95% CI 0.77-0.79) with a feedforward neural network classifier. Validation in an independent Canadian cohort of 482 patients showed consistent performance. Cox regression analysis indicated that higher levels of LEF1-AS1 correlated with reduced mortality risk (age-adjusted hazard ratio 0.54, 95% CI 0.40-0.74). Quantitative PCR validated LEF1-AS1's adaptability to be measured in hospital settings. Here, we demonstrate a promising predictive model for enhancing COVID-19 patient management.