Health registries improve our knowledge, support optimising care organisation and quality, and support the implementation of personalised medicine. While many registries collect data in the field of allergy and immunology worldwide, only few registries are dedicated to anaphylaxis. Despite a growing scientific interest in anaphylaxis over the past decade, current knowledge on severe anaphylaxis is insufficient, with many unresolved questions regarding risk factors, impact of cofactors, specific aspects in childhood, details related to trigger and the most appropriate therapeutic strategies. There is a clear need for health registries dedicated to severe anaphylaxis to address these gaps. This article aims first to present the rationale for creating a new registry dedicated to severe anaphylaxis by defining and describing health registries and related challenges in the field of anaphylaxis worldwide and in France, identifying knowledge gaps in severe anaphylaxis, and second to present the objectives of the new French anaphylaxis registry, named Severe Anaphylaxis in France nEtwork (SAFE). In 2026, the French professional council for allergy, in partnership with key allergy stakeholders in France, notably the Société française d'allergologie (the French allergy society), will inaugurate the SAFE registry in order to provide inputs on severe anaphylaxis, integrating all involved caregivers, including emergency care, anaesthesia and intensive care, paediatrics, research structures and patient associations.

OBJECTIVE:The French Society of Anaesthesia and Intensive Care (SFAR) and the French Society of Allergology (SFA) have collaborated to propose guidelines for the diagnosis and management of perioperative immediate hypersensitivity reactions (IHR). DESIGN:A group of 23 French experts from the SFAR and the SFA was assembled. Any potential conflicts of interest were officially declared at the outset of the recommendations development process, which was conducted independently of any industry funding. The authors used the GRADE (Grading of Recommendations Assessment, Development and Evaluation) methodology to assess the level of evidence in the literature. METHODS:4 fields were defined: 1) Diagnostic assessment of perioperative IHR reactions; 2) Risk factors for perioperative IHR reactions; 3) Treatment in scheduled and emergency situations and; 4) Treatment of perioperative IHR reactions. For each field, the aim of the recommendations was to answer questions formulated by the experts according to the PICO model ("Population, Intervention, Comparison, Outcome"). Based on these questions, an extensive literature search covering the last 24 years was carried out using predefined keywords according to the PRISMA recommendations. The level of evidence was analysed using the GRADE method. The recommendations were formulated using the GRADE method, then voted on by all the experts using the GRADE grid method. RESULTS:The experts' summary work and the application of the GRADE method resulted in 70 recommendations concerning 31 questions. After 3 rounds of voting and several amendments, strong agreement was reached on 70 recommendations. Of these recommendations, 6 have a high level of evidence (6 GRADE 1), 16 have a low level of evidence (16 GRADE 2) and 48 are expert opinions. Finally, for 1 question, no recommendation could be made. CONCLUSION:There was strong agreement among the experts to formulate recommendations aimed at providing a benchmark for the diagnosis and management of perioperative IHR.

BACKGROUND:COVID-19 exhibits a variety of symptoms and may lead to multi-organ failure and death. This clinical complexity is exacerbated by significant immune dysregulation affecting nearly all cells of the innate and adaptive immune system. Granulocytes, including eosinophils, are affected by SARS-CoV-2. OBJECTIVES:Eosinophil responses remain poorly understood despite early recognition of eosinopenia as a hallmark feature of COVID-19 severity. RESULTS:The heterogeneous nature of eosinophil responses categorizes them as dual-function cells with contradictory effects. Eosinophil activation can suppress virus-induced inflammation by releasing type 2 cytokines like IL-13 and granular proteins with antiviral action such as eosinophil-derived neurotoxins and eosinophil cationic protein, and also by acting as antigen-presenting cells. In contrast, eosinophil accumulation in the lungs can induce tissue damage triggered by cytokines or hormones like IFN-γ and leptin. Additionally, they can affect adaptive immune functions by interacting with T cells through direct formation of membrane complexes or soluble mediator action. Individuals with allergic disorders who have elevated levels of eosinophils in tissues and blood, such as asthma, do not appear to be at an increased risk of developing severe COVID-19 following SARS-CoV-2 infection. However, the SARS-CoV-2 vaccine appears to be associated with complications and eosinophilic infiltrate-induced immunopathogenicity, which can be mitigated by corticosteroid, anti-histamines and anti-IL-5 therapy and avoided by modifying adjuvants or excipients. CONCLUSION:This review highlights the importance of eosinophils in COVID-19 and contributes to a better understanding of their role during natural infection and vaccination.

The study and applications of artificial intelligence (AI) in healthcare have developed rapidly over the last decade. In the field of allergy, which is characterized by the heterogeneity of pathologies and the role of complex immunological and environmental factors, there is a requirement for tools capable of processing voluminous and multidimensional data. AI, notably through machine learning, deep learning and natural language processing, facilitates the analysis of these data. The high prevalence of allergies (30% of the population in 2025 and 50% in 2050) requires significant opportunities for AI to enhance and personalize diagnosis. These technologies, integrated into clinical decision, support professionals in diagnosis, endotype definition and biomarker research. This literature review, conducted by the e-health and artificial intelligence working group (GTESIA) of the French Society of Allergy (SFA), aims to address the current issues and proposals on AI specific to the specialty. The review presents a selection of the most promising methods and elucidates the potential for AI integration into the complex, multidisciplinary care pathway of allergy patients. (c) 2025 l'Academie nationale de medecine. Published by Elsevier Masson SAS. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Severe asthma and allergic bronchopulmonary aspergillosis (ABPA) do not rarely coexist and share several similarities in terms of pathobiological background, together with overlapping clinical manifestations, misleading the correct diagnosis. Within that scenario, severe asthma with fungal sensitization (SAFS) further complicates the correct pheno-endotyping, which still needs to be recognized in the light of the greater burden and higher risk of irreversible damage related to ABPA and SAFS when compared to asthma alone. The identification of pathobiological drivers underlying different conditions remains challenging; in fact, available biomarkers, although accurate when related to each specific condition, do not always fully support a clear-cut differential diagnosis. The opportunity for innovative targeted treatments, although needing further evidence, should further stimulate a precise endo-phenotyping of severe asthma patients presenting some hallmarks of fungal-related dis-immunity to provide them the best standard of care for preventing disease evolution and achieving complete remission. This review provides a comparative outline of the recent advances in terms of pathophysiology, clinical manifestations, biomarkers, and management of asthma and ABPA, including a focus on SAFS, with the aim of updating the practical approach to those conditions and supporting their correct recognition.

Diagnostic criteria of allergic bronchopulmonary aspergillosis have been updated in 2024. The use of molecular fungal allergens could complement these essential criteria for allergic bronchopulmonary aspergillosis to improve its diagnosis. This French pilot study was conducted to determine optimal Aspergillus fumigatus (A. fumigatus)-specific IgE (A. fumigatus-IgE) and molecular allergen (rAsp)-IgE cut-off values in routine practice and to confirmed the allergic bronchopulmonary aspergillosis diagnostic strategy using IgE tests described in medical algorithms. A. fumigatus-IgE and rAsp-IgE showed robust discrimination capabilities between allergic bronchopulmonary aspergillosis and A. fumigatus sensitisation (AUROC > 0.80). Their optimal local cutoffs outperformed those recommended, particularly A. fumigatus-IgE (≥ 2.64 kUA/L) and Asp f1-IgE (≥ 2.65 kUA/L) and could improve the diagnostic of allergic bronchopulmonary aspergillosis.

The complexity and diversity of the immune response in patients with asthma, chronic obstructive pulmonary disease (COPD), and asthma-COPD overlap present significant challenges for disease management. Relying on a limited number of biomarkers and clinical data is insufficient to fully reveal the immunopathogenesis of these diseases. However, in vitro technologies such as cell analysis, cytokine investigation, and nucleic acid sequencing have provided new insights into the underlying mechanisms of these diseases, leading to the discovery of several biomarkers—including cell degranulation, cell function, secreted cytokines, and single nucleotide polymorphisms—that have potential clinical implications. This paper reviews the immunopathogenesis in asthma, chronic obstructive pulmonary disease, and asthma-COPD overlap and examines the applications of recent in vitro models to detect candidate biomarkers that could enhance diagnostic precision, predict severity, monitor treatments, and develop new treatment strategies. A deeper understanding of the immune response in these diseases, along with the integration of in vitro models into clinical practice, could greatly improve the management of these respiratory diseases, making approaches more personalized and efficient.

BACKGROUND:Allergen chip (AC) technologies are a powerful tool for simultaneous analysis of hundreds of allergens, generating a comprehensive sensitization landscape for precision medicine in allergy. These considerable data require extensive knowledge for translation into clinically relevant conclusion. OBJECTIVE:To harness machine learning for AC interpretation in daily practice, we set out to establish a nationwide open database of AC, demographic, and clinical information and to submit it to an international crowdsourced machine learning competition to generate a predictive allergy classification algorithm. METHODS:The project consortium defined 20 clinical variables and 5 demographic factors for retrospective collection in conjunction with AC IgE data (2014-23) from 11 French university hospitals. The dataset was processed to tag confirmed allergy, grade of severity, and culprit allergen identification associated with AC data and submitted to the data challenge. RESULTS:Data were collected for 4271 patients, yielding a dataset with over 700,000 specific IgE data points. Sensitization was present in 3579 patients (84%). Allergy was confirmed in 2236 patients (53%) and excluded in 1076 patients, with the remaining 959 being missing outcome data (allergy diagnosis labels). The competition attracted 292 data scientists who submitted 3135 algorithms. The highest F scores ranged from 0.780 to 0.786. The database was subsequently made available as open source. CONCLUSIONS:We present a nationwide open allergy database designed to enable the development of predictive algorithms. This scalable framework, integrating clinical data with machine learning techniques, paves the way for data-driven AC use and interpretation by allergists.

Tryptase is currently the most specific mast cell biomarker available in clinical laboratories. Tryptase levels in the peripheral blood contribute to the diagnostic, prognostic, and therapeutic evaluation of the following 3 clinical categories: (1) immediate hypersensitivity reactions, including the life-threatening systemic form known as anaphylaxis; (2) clonal mast cell diseases and other myeloid malignancies, also as a biomarker for efficacy of chemotherapeutic agents targeting mast cell survival; and (3) hereditary α-tryptasemia, a genetic trait found in 4% to 8% of general population associated to increased risk of severe immediate hypersensitivity reactions. Rapidly evolving pathophysiology knowledge and management guidelines affect tryptase use in clinical practice, explaining the need for frequent updates. Such updates often lack context on the pathophysiology and methods regarding mast cells and tryptase, thus hampering the practicing clinician's ability to get the full picture from tryptase test results. Here, we provide the practicing physician with the 2025 state-of-the-art recommendations on tryptase use and interpretation in clinical practice, also exposing their basic, clinical, and technical foundations. Successive additions to mast cell and tryptase research are summarized and revisited in light of today's knowledge. The review sections are titled to reflect matter-of-fact questions arising in clinical practice. Currently unmet needs of tryptase use and selected lines of ongoing research expected to influence clinical practice in the near future are also presented.

Eosinophils are innate immune cells with central roles in allergy, parasitic diseases and multiple inflammatory conditions. Moreover, their role in host-pathogen interactions has been well characterized. However, the role of eosinophils during fungal infection is poorly defined. In this study, we delineate the importance of eosinophils during C. albicans systemic infections. C. albicans is promptly phagocytosed by human eosinophils, but growing hyphae escape this mechanism by releasing the fungal toxin candidalysin, which causes eosinophil membrane damage and cell death. Concomitantly, eosinophil mediators, notably major basic protein 1 (MBP-1), released during cytolysis, inhibits C. albicans growth and viability. Moreover, systemic candidiasis in genetic (Δdbl/GATA) or anti-IL-5-mediated depletion of eosinophils results in increased fungal burden and decreased survival. We here identified CD48 as a major receptor of eosinophils and possibly of other immune cells involved in the recognition of C. albicans via agglutinin-like sequence 6 (Als6). CD48 is important for protection in a model of systemic candidiasis as shown in CD48-/- mice and it binds clinical isolates of C. albicans. In conclusion, we have defined a protective role for eosinophils in vitro and in mouse C. albicans infections through CD48/Als6 host-pathogen interaction axis.

Chronic rhinosinusitis (CRS) with nasal polyps (CRSwNP) mainly expresses type-2 endotype, featuring eosinophils as a main player in the inflammatory process. Prolonged eosinophilia in the tissues of asthma and CRSwNP patients has been associated with structural changes, leading to fixed airflow obstruction in asthma and nasal polyposis in CRSwNP. This suggests that eosinophils may belong to different subgroups playing distinct roles in pathogenesis. Recent studies highlight the roles of inflammatory eosinophils (iEOS) in driving inflammation and tissue damage, whereas tissue-resident eosinophils (rEOS) maintain homeostasis and tissue repair in the airway. Therefore, understanding both roles of eosinophil subpopulations is crucial for better CRSwNP management, including enhancing the diagnosis accuracy, predicting recurrence, and optimizing treatment strategies.

Prérequis/Contexte Baseline serum tryptase (bST) levels depend of age, sex, and other genetic, sociodemographic, lifestyle, and health determinants. Elevated bST levels have been associated with higher risk and severity of various hypersensitivity reactions, and can suggest an underlying clonal mast cell disorders. While historic bST reference values have been recently questioned, defining age- and sex-specific bST reference intervals (RIs) could improve diagnosis, risk evaluation, and clinical decision-making in mast cell-related disorders and allergy. Objectifs To determine and validate age- and sex-specific RIs for bST from infancy to old age. Méthodes A training cohort, consisting of 21,216 bST values obtained through a nation-wide ambulatory community-based clinical database, was used to compare five indirect methods to establish bST RIs. The most accurate was selected, and applied to modelize the bST distribution in each age- and sex-group. Next, lifelong sex-dependent bST RIs were established using sequential linear models. Finally, a validation cohort consisting in 572 HαT – teenagers from a population-based birth cohort was used to confirm the robustness of age- and sex-specific bST RIs. Résultats/Discussions Independently of age and sex, the reference median and 95th percentile were 4.6 and 8.4μg/L, respectively. The levels of bST were lower in females, especially in teenagers and young adults. Tryptase concentrations decreased during childhood, then increased slowly from puberty until old age. In the validation cohort, 4.9% (28/572) participants presented bST values above their age- and sex-specific 95th reference percentile. Conclusion This study establishes and validates age- and sex-specific bST reference intervals in the pediatric, adult, and elderly population. It also proposes a decisional algorithm and an online tool for daily clinical practice.

L’étude et les applications de l’intelligence artificielle (IA) en santé se sont rapidement développées au cours de la dernière décennie. En allergologie, domaine marqué par l’hétérogénéité des pathologies et le rôle de facteurs immunologiques et environnementaux complexes nécessitent des outils capables de traiter des données volumineuses et multidimensionnelles. L’IA, notamment par le biais du machine learning, du deep learning et du traitement du langage naturel, facilite l’analyse de ces données. Les allergies ayant une prévalence élevée (30 % de la population en 2025 et 50 % en 2050), l’IA offre des opportunités majeures pour améliorer et personnaliser le diagnostic. Ces technologies, intégrées au sein de systèmes d’aide à la décision clinique peuvent notamment soutenir les professionnels dans le diagnostic, la définition des endotypes et la recherche de biomarqueurs. Cette revue de littérature du groupe de travail e-santé et intelligence artificielle (GTESIA) de la Société française d’allergologie (SFA) expose les questions et propositions actuelles sur l’IA spécifiques à la spécialité. Nous présentons une sélection des méthodes les plus prometteuses et précisons comment l’IA peut s’intégrer dans le parcours de soin complexe et multidisciplinaire des patients allergiques.

Background: Dynamic measurement of serum acute (sAT) and baseline (sBT) tryptase confirms mast cell degranulation during systemic hypersensitivity reactions, provided timing and interpretation are appropriate. The current consensus formula requires sAT greater than a personalized cutoff value [sAT > (1.2 × sBT) + 2]. Only a few studies have investigated its diagnostic performance in children. Objective: We assessed the diagnostic accuracy of the consensus formula and alternative algorithms for interpreting tryptase levels in pediatric patients with suspected anaphylaxis. Methods: Medical records of suspected anaphylaxis referred to the pediatric emergency department of the University Hospitals of Marseille (France) from 2011 to 2020 were retrospectively reviewed. Clinical and laboratory data, including total tryptase and allergy evaluations, were collected. Anaphylaxis was defined as a sudden-onset, perceived life-threatening systemic reaction at the time of physician assessment. Inclusion criteria were suspected anaphylaxis and at least one tryptase determination. The diagnostic performance of the consensus formula was compared to 5 alternative tryptase interpretation algorithms. Results: Among 315 patients (median age, 7.8 years; 317 emergency department visits), 175 (55%) were categorized as cases. Food-induced anaphylaxis was diagnosed in 82%, and 92 (52.6%) had two or more tryptase determinations. The highest diagnostic performance was achieved by the sAT/sBT ratio. A cutoff for sAT/sBT ratio of >1.74 yielded 66.7% sensitivity, 90.0% specificity, 96.8% positive predictive value, and 24.3% negative predictive value. The retrospective study design was a major limitation. Conclusion: Compared to the current consensus formula, a sAT/sBT ratio above 1.74 may enhance the diagnostic performance of dynamic tryptase measurement in children with suspected anaphylaxis.