EAACI guidelines on environmental science in allergic diseases and asthma - Leveraging artificial intelligence and machine learning to develop a causality model in exposomics

Unraveling the Molecular Landscape of Neutrophil Extracellular Traps in Severe Asthma: Identification of Biomarkers and Molecular Clusters

Neutrophil extracellular traps (NETs) play a central role in chronic airway diseases. However, the precise genetic basis linking NETs to the development of severe asthma remains elusive. This study aims to unravel the molecular characterization of NET-related genes (NRGs) in severe asthma and to reliably identify relevant molecular clusters and biomarkers. We analyzed RNA-seq data from the Gene Expression Omnibus database. Interaction analysis revealed fifty differentially expressed NRGs (DE-NRGs). Subsequently, the non-negative matrix factorization algorithm categorized samples from severe asthma patients. A machine learning algorithm then identified core NRGs that were highly associated with severe asthma. DE-NRGs were correlated and subjected to protein-protein interaction analysis. Unsupervised consensus clustering of the core gene expression profiles delineated two distinct clusters (C1 and C2) characterizing severe asthma. Functional enrichment highlighted immune-related pathways in the C2 cluster. Core gene selection included the Boruta algorithm, support vector machine, and least absolute contraction and selection operator algorithms. Diagnostic performance was assessed by receiver operating characteristic curves. This study addresses the molecular characterization of NRGs in adult severe asthma, revealing distinct clusters based on DE-NRGs. Potential biomarkers (TIMP1 and NFIL3) were identified that may be important for early diagnosis and treatment of severe asthma.

Opportunities and challenges with artificial intelligence in allergy and immunology: a bibliometric study

Introduction

The fields of allergy and immunology are increasingly recognizing the transformative potential of artificial intelligence (AI). Its adoption is reshaping research directions, clinical practices, and healthcare systems. However, a systematic overview identifying current statuses, emerging trends, and future research hotspots is lacking.

Methods

This study applied bibliometric analysis methods to systematically evaluate the global research landscape of AI applications in allergy and immunology. Data from 3,883 articles published by 21,552 authors across 1,247 journals were collected and analyzed to identify leading contributors, prevalent research themes, and collaboration patterns.

Results

Analysis revealed that the USA and China are currently leading in research output and scientific impact in this domain. AI methodologies, especially machine learning (ML) and deep learning (DL), are predominantly applied in drug discovery and development, disease classification and prediction, immune response modeling, clinical decision support, diagnostics, healthcare system digitalization, and medical education. Emerging trends indicate significant movement toward personalized medical systems integration.

Discussion

The findings demonstrate the dynamic evolution of AI in allergy and immunology, highlighting the broadening scope from basic diagnostics to comprehensive personalized healthcare systems. Despite advancements, critical challenges persist, including technological limitations, ethical concerns, and regulatory frameworks that could potentially hinder further implementation and integration.

Conclusion

AI holds considerable promise for advancing allergy and immunology globally by enhancing healthcare precision, efficiency, and accessibility. Addressing existing technological, ethical, and regulatory challenges will be crucial to fully realizing its potential, ultimately improving global health outcomes and patient well-being.

Exposomics: a review of methodologies, applications, and future directions in molecular medicine

The exposome is the measure of all the exposures of an individual in a lifetime and how those exposures relate to health. Exposomics is the emerging field of research to measure and study the totality of the exposome. Exposomics can assist with molecular medicine by furthering our understanding of how the exposome influences cellular and molecular processes such as gene expression, epigenetic modifications, metabolic pathways, and immune responses. These molecular alterations can aid as biomarkers for the diagnosis, disease prediction, early detection, and treatment and offering new avenues for personalized medicine. Advances in high throughput omics and other technologies as well as increased computational analytics is enabling comprehensive measurement and sophisticated analysis of the exposome to elucidate their cumulative and combined impacts on health, which can enable individuals, communities, and policymakers to create programs, policies, and protections that promote healthier environments and people. This review provides an overview of the potential role of exposomics in molecular medicine, covering its history, methodologies, current research and applications, and future directions.

EAACI Guidelines on Environmental Science for Allergy and Asthma-Recommendations on the Impact of Indoor Air Pollutants on the Risk of New-Onset Asthma and on Asthma-Related Outcomes

The EAACI Guidelines used the GRADE approach to evaluate the impact of major indoor air pollutants (dampness and mould, cleaning agents, volatile organic compounds and pesticides) on the risk of new-onset asthma and on asthma-related outcomes. The guideline also acknowledges the synergies among indoor air pollutants and other components of the indoor exposome (allergens, viruses, endotoxins). Very low to low certainty of evidence was found for the association between exposure to indoor pollutants and increased risk of new-onset asthma and asthma worsening. Only for mould exposure there was moderate certainty of evidence for new-onset asthma. Due to the quality of evidence, conditional recommendations were formulated on the risk of exposure to all indoor pollutants. Recommendations are provided for prevention, patient care and mitigation in a framework supporting rational decisions for healthcare professionals and patients to individualize and improve asthma management. For policymakers and regulators this evidence-informed guideline supports setting legally binding standards and goals for indoor air quality at international, national and local levels. Asthma management counselled by the current EAACI guidelines can improve asthma-related outcomes but community and governmental measures for improved indoor air quality are needed to achieve significant impact.

An Overview of Climate Changes and Its Effects on Health: From Mechanisms to One Health

Human activities, primarily the burning of fossil fuels, widespread deforestation, soil erosion or machine-intensive farming methods, manufacturing, food processing, mining, construction, and the iron, cement, steel, and chemicals industries, have been the main drivers of the observed increase in Earth's average surface temperature and climate change. Rising global temperatures, extreme weather events, ecosystems disruption, agricultural impacts, water scarcity, problems in access to good quality water, food and housing, and profound environmental disruptions such as biodiversity loss and extreme pollution are expected to steeply increase the prevalence and severity of acute and chronic diseases. Its long-term effects cannot be adequately predicted or mitigated without a comprehensive understanding of the adaptive ecosystems. Studying the complex interaction between environmental aggressors and the resilient adaptive responses requires the exposomic and the One Health approaches. The problem is broad and affects the whole ecosystem, plants, pets, and animals in addition to humans. The central role of the epithelial barrier, microbiome, and diet as key pillars for an adaptive tolerogenic immune response should be explored for increasing resilience at the individual level. A radical change in mindset worldwide, with sustainable solutions and adaptive strategies and climate resilience and health equity policies at their center, should be achieved quickly through increased awareness based on solid scientific data.

Monkeypox 2024 outbreak: Fifty essential questions and answers

As the world still vividly recalls the previous monkeypox (mpox) outbreak that impacted over 120 countries worldwide with more than 99,000 cases in 2022, we are now facing a second wave of infections from the monkeypox virus (MPXV), characterized by an exponential increase in cases. The current 2024 outbreak has already recorded more than 20,000 cases in Africa, marking a dramatic escalation compared to previous outbreaks. The predominance of the newly identified clade Ib variant, first detected in the Democratic Republic of the Congo (DRC) and now identified across multiple African nations and beyond, underscores its enhanced transmissibility and potential for international spread, evidenced by cases in Sweden and Thailand. The World Health Organization (WHO) declared on August 14, 2024, the current mpox outbreak a Public Health Emergency of International Concern (PHEIC), calling for heightened global public health measures. The ongoing pattern of unusual, frequent, and extensive outbreaks of mpox with potential global implications poses significant questions. This review addresses, in the format of 50 questions and answers, the 2024 mpox outbreak, detailing its characteristics, epidemiological data, and impact compared to previous outbreaks. It comprehensively explores critical questions related to MPXV virological characteristics, immunological response, clinical manifestations, epidemiology, diagnostics, and available treatments. The review also documents the significant and evolving challenges posed by the current mpox outbreak, highlighting its scale, spread, and public health response.

Artificial intelligence applications for immunology laboratory: image analysis and classification study of IIF photos

Artificial intelligence (AI) is increasingly being used in medicine to enhance the speed and accuracy of disease diagnosis and treatment. AI-based image analysis is expected to play a crucial role in future healthcare facilities and laboratories, offering improved precision and cost-effectiveness. As technology advances, the requirement for specialized software knowledge to utilize AI applications is diminishing. Our study will examine the advantages and challenges of employing AI-based image analysis in the field of immunology and will investigate whether physicians without software expertise can use MS Azure Portal for ANA IIF test classification and image analysis. This is the first study to perform Hep-2 image analysis using MS Azure Portal. We will also assess the potential for AI applications to aid physicians in interpreting ANA IIF results in immunology laboratories. The study was designed in four stages by two specialists. Stage 1: creation of an image library, Stage 2: finding an artificial intelligence application, Stage 3: uploading images and training artificial intelligence, Stage 4: performance analysis of the artificial intelligence application. In the first training, the average pattern identification accuracy for 72 testing images was 81.94%. After the second training, this accuracy increased to 87.5%. Patterns Precision improved from 71.42 to 79.96% after the second training. As a result, the number of correctly identified patterns and their accuracy increased with the second training process. Artificial intelligence-based image analysis shows promising potential. This technology is expected to become essential in healthcare facility laboratories, offering higher accuracy rates and lower costs.

The Use of Artificial Intelligence to Analyze the Exposome in the Development of Chronic Diseases: A Review of the Current Literature

The “Exposome” is a concept that indicates the set of exposures to which a human is subjected during their lifetime. These factors influence the health state of individuals and can drive the development of Noncommunicable Diseases (NCDs). Artificial Intelligence (AI) allows one to analyze large amounts of data in a short time. As such, several authors have used AI to study the relationship between exposome and chronic diseases. Under such premises, this study reviews the use of AI in analyzing the exposome to understand its role in the development of chronic diseases, focusing on how AI can identify patterns in exposure-related data and support prevention strategies. To achieve this, we carried out a search on multiple databases, including PubMed, ScienceDirect, and SCOPUS, from 1 January 2019 to 31 May 2023, using the MeSH terms (exposome) and (‘Artificial Intelligence’ OR ‘Machine Learning’ OR ‘Deep Learning’) to identify relevant studies on this topic. After completing the identification, screening, and eligibility assessment, a total of 18 studies were included in this literature review. According to the search, most authors used supervised or unsupervised machine learning models to study multiple exposure factors’ role in the risk of developing cardiovascular, metabolic, and chronic respiratory diseases. In some more recent studies, authors also used deep learning. Furthermore, the exposome analysis is useful to study the risk of developing neuropsychiatric disorders or evaluating pregnancy outcomes and child growth. Understanding the role of the exposome is pivotal to overcome the classic concept of a single exposure/disease. The application of AI allows one to analyze multiple environmental risks and their combined effects on health conditions. In the future, AI could be helpful in the prevention of chronic diseases, providing new diagnostic, therapeutic, and follow-up strategies.

Contemporary Concise Review 2023: Asthma

Asthma research and management needs to meet the priorities of the end user-patients, carers and clinicians. A better understanding of the natural history of asthma and the progression of disease has highlighted the importance of early identification of patients with asthma and the potential role of early intervention. Management of mild asthma requires a consistent approach with the same detail and consideration used when managing severe disease. Evidence around treatable traits approaches continues to evolve, supporting the role of a personalized medicine in asthma. Oral corticosteroid (OCS) stewardship continues to be an urgent issue in asthma management. Strategies to taper OCS doses and the implementation of biologic therapies for their steroid sparing benefits will be important steps to address this problem. The concept of remission in asthma provides an ambitious target and treatment outcome.

Research integrity in the era of artificial intelligence: Challenges and responses

The application of artificial intelligence (AI) technologies in scientific research has significantly enhanced efficiency and accuracy but also introduced new forms of academic misconduct, such as data fabrication and text plagiarism using AI algorithms. These practices jeopardize research integrity and can mislead scientific directions. This study addresses these challenges, underscoring the need for the academic community to strengthen ethical norms, enhance researcher qualifications, and establish rigorous review mechanisms. To ensure responsible and transparent research processes, we recommend the following specific key actions: Development and enforcement of comprehensive AI research integrity guidelines that include clear protocols for AI use in data analysis and publication, ensuring transparency and accountability in AI-assisted research. Implementation of mandatory AI ethics and integrity training for researchers, aimed at fostering an in-depth understanding of potential AI misuses and promoting ethical research practices. Establishment of international collaboration frameworks to facilitate the exchange of best practices and development of unified ethical standards for AI in research. Protecting research integrity is paramount for maintaining public trust in science, making these recommendations urgent for the scientific community consideration and action.

EAACI guidelines on environmental science for allergy and asthma: The impact of short-term exposure to outdoor air pollutants on asthma-related outcomes and recommendations for mitigation measures

The EAACI Guidelines on the impact of short-term exposure to outdoor pollutants on asthma-related outcomes provide recommendations for prevention, patient care and mitigation in a framework supporting rational decisions for healthcare professionals and patients to individualize and improve asthma management and for policymakers and regulators as an evidence-informed reference to help setting legally binding standards and goals for outdoor air quality at international, national and local levels. The Guideline was developed using the GRADE approach and evaluated outdoor pollutants referenced in the current Air Quality Guideline of the World Health Organization as single or mixed pollutants and outdoor pesticides. Short-term exposure to all pollutants evaluated increases the risk of asthma-related adverse outcomes, especially hospital admissions and emergency department visits (moderate certainty of evidence at specific lag days). There is limited evidence for the impact of traffic-related air pollution and outdoor pesticides exposure as well as for the interventions to reduce emissions. Due to the quality of evidence, conditional recommendations were formulated for all pollutants and for the interventions reducing outdoor air pollution. Asthma management counselled by the current EAACI guidelines can improve asthma-related outcomes but global measures for clean air are needed to achieve significant impact.

Saccharomyces boulardii alleviates allergic asthma by restoring gut microbiota and metabolic homeostasis via up-regulation of METTL3 in an m6A-dependent manner

BACKGROUND

Allergic asthma is a heterogeneous disease and new strategies are needed to prevent or treat this disease. Studies have shown that probiotic interventions are effective in preventing asthma. Here, we investigated the impact of Saccharomyces boulardii (S. boulardii) on ovalbumin (OVA)-induced allergic asthma in mice, as well as the underlying mechanisms.

METHODS

First, we constructed a mouse asthma model using OVA and given S. boulardii intervention. Next, we measured N6-methyladenosine (m6A) levels in lung injury tissues. 16 s rRNA was employed to identify different gut microbiota in fecal samples. The analysis of differential metabolites in feces was performed by non-targeted metabolomics. Pearson correlation coefficient was utilized to analyze correlation between gut microbiota, metabolites and methyltransferase-like 3 (METTL3). Finally, we collected mouse feces treated by OVA and S. boulardii intervention for fecal microbiota transplantation (FMT) and interfered with METTL3.

RESULTS

S. boulardii improved inflammation and oxidative stress and alleviated lung damage in asthmatic mice. In addition, S. boulardii regulated m6A modification levels in asthmatic mice. 16 s rRNA sequencing showed that S. boulardii remodeled gut microbiota homeostasis in asthmatic mice. Non-targeted metabolomics analysis showed S. boulardii restored metabolic homeostasis in asthmatic mice. There was a correlation between gut microbiota, differential metabolites, and METTL3 analyzed by Pearson correlation. Additionally, through FMT and interference of METTL3, we found that gut microbiota mediated the up-regulation of METTL3 by S. boulardii improved inflammation and oxidative stress in asthmatic mice, and alleviated lung injury.

CONCLUSIONS

S. boulardii alleviated allergic asthma by restoring gut microbiota and metabolic homeostasis via up-regulation of METTL3 in an m6A-dependent manner.

Impact of climate change on immune responses and barrier defense

Climate change is not just jeopardizing the health of our planet but is also increasingly affecting our immune health. There is an expanding body of evidence that climate-related exposures such as air pollution, heat, wildfires, extreme weather events, and biodiversity loss significantly disrupt the functioning of the human immune system. These exposures manifest in a broad range of stimuli, including antigens, allergens, heat stress, pollutants, microbiota changes, and other toxic substances. Such exposures pose a direct and indirect threat to our body's primary line of defense, the epithelial barrier, affecting its physical integrity and functional efficacy. Furthermore, these climate-related environmental stressors can hyperstimulate the innate immune system and influence adaptive immunity-notably, in terms of developing and preserving immune tolerance. The loss or failure of immune tolerance can instigate a wide spectrum of noncommunicable diseases such as autoimmune conditions, allergy, respiratory illnesses, metabolic diseases, obesity, and others. As new evidence unfolds, there is a need for additional research in climate change and immunology that covers diverse environments in different global settings and uses modern biologic and epidemiologic tools.

Hot topics in allergen immunotherapy, 2023: Current status and future perspective

The importance of allergen immunotherapy (AIT) is multifaceted, encompassing both clinical and quality-of-life improvements and cost-effectiveness in the long term. Key mechanisms of allergen tolerance induced by AIT include changes in memory type allergen-specific T- and B-cell responses towards a regulatory phenotype with decreased Type 2 responses, suppression of allergen-specific IgE and increased IgG1 and IgG4, decreased mast cell and eosinophil numbers in allergic tissues and increased activation thresholds. The potential of novel patient enrolment strategies for AIT is taking into account recent advances in biomarkers discoveries, molecular allergy diagnostics and mobile health applications contributing to a personalized approach enhancement that can increase AIT efficacy and compliance. Artificial intelligence can help manage and interpret complex and heterogeneous data, including big data from omics and non-omics research, potentially predict disease subtypes, identify biomarkers and monitor patient responses to AIT. Novel AIT preparations, such as synthetic compounds, innovative carrier systems and adjuvants, are also of great promise. Advances in clinical trial models, including adaptive, complex and hybrid designs as well as real-world evidence, allow more flexibility and cost reduction. The analyses of AIT cost-effectiveness show a clear long-term advantage compared to pharmacotherapy. Important research questions, such as defining clinical endpoints, biomarkers of patient selection and efficacy, mechanisms and the modulation of the placebo effect and alternatives to conventional field trials, including allergen exposure chamber studies are still to be elucidated. This review demonstrates that AIT is still in its growth phase and shows immense development prospects.

Age-related differences in IgE between childhood and adulthood allergic asthma: Analysis of NHANES 2005-2006

Background

Asthma exhibits varying clinical features in children and adults. However, previous studies have mainly focused on the clinical significance of immunoglobulin E (IgE) in the diagnosis and treatment of asthma, disregarding the characteristics of IgE and its relevant factors.

Objective

This study aimed to gain a better understanding of the differences in the characteristics of IgE between childhood and adulthood allergic asthma (AA).

Methods

Patients with AA from the 2005 to 2006 National Health and Nutrition Examination Survey (NHANES) were divided into 3 groups based on their current age and onset age of AA: childhood AA (Group 1), childhood-onset adult AA (Group 2), and adulthood-onset AA (Group 3). Intragroup analysis and intergroup comparison were carried out, focusing on the characteristics and relevant factors of IgE, as well as the clinical relevance of total IgE (total IgE, tIgE) and allergen-specific IgE (allergen-specific IgE, sIgE).

Results

A total of 424 patients were analyzed, including 187 with childhood AA, 132 with childhood-onset adult AA, and 105 with adulthood-onset AA. The concentration of tIgE was found to be higher in Group 1 (268.0, 118.0-686.0 kU/L) than in Group 2 (224.0, 78.0-494.0 kU/L) and Group 3 (165.0, 74.4-350.5 kU/L). The sensitization rates did not differ between Group 1 and Group 2 but were higher compared with Group 3, particularly for Alternaria-sIgE (50.3% and 46.2% vs 15.2%) and Aspergillus-sIgE (43.9% and 37.1% vs 16.2%). In Group 1, there was a negative correlation between pollen-sIgEs and indoor allergens, but this correlation was not commonly observed in Group 2 and Group 3. On the other hand, in Group 1, environmental chemicals such as phthalates, polyaromatic hydrocarbons, trihalomethanes, and phenols showed a positive correlation with IgE. However, a greater number of chemicals was observed in Group 2 and Group 3, including cotinine, metals, trihalomethanes, phthalates, phenols, and other volatile organic compounds (VOCs). Furthermore, in Group 1, IgE was positively correlated with asthma-related issues such as emergency visits, absenteeism, limited activities, and medication needs. These correlations were less common in Group 2 and Group 3, particularly in Group 3.

Conclusions

There are notable differences in the characteristics and environmental factors of IgE among childhood AA, childhood-onset adult AA, and adulthood-onset AA. Additionally, IgE plays a more significant role in childhood AA due to its higher concentration, fewer relevant environmental chemicals and greater clinical relevance. This may partially explain the age-related features of asthma.

Nomenclature of allergic diseases and hypersensitivity reactions: Adapted to modern needs: An EAACI position paper

The exponential growth of precision diagnostic tools, including omic technologies, molecular diagnostics, sophisticated genetic and epigenetic editing, imaging and nano-technologies and patient access to extensive health care, has resulted in vast amounts of unbiased data enabling in-depth disease characterization. New disease endotypes have been identified for various allergic diseases and triggered the gradual transition from a disease description focused on symptoms to identifying biomarkers and intricate pathogenetic and metabolic pathways. Consequently, the current disease taxonomy has to be revised for better categorization. This European Academy of Allergy and Clinical Immunology Position Paper responds to this challenge and provides a modern nomenclature for allergic diseases, which respects the earlier classifications back to the early 20th century. Hypersensitivity reactions originally described by Gell and Coombs have been extended into nine different types comprising antibody- (I-III), cell-mediated (IVa-c), tissue-driven mechanisms (V-VI) and direct response to chemicals (VII). Types I-III are linked to classical and newly described clinical conditions. Type IVa-c are specified and detailed according to the current understanding of T1, T2 and T3 responses. Types V-VI involve epithelial barrier defects and metabolic-induced immune dysregulation, while direct cellular and inflammatory responses to chemicals are covered in type VII. It is notable that several combinations of mixed types may appear in the clinical setting. The clinical relevance of the current approach for allergy practice will be conferred in another article that will follow this year, aiming at showing the relevance in clinical practice where various endotypes can overlap and evolve over the lifetime.

Novel, computational IgE-clustering in a population-based cross-sectional study: Mapping the allergy burden

BACKGROUND

Even though the prevalence of allergies is increasing, population-based data are still scarce. As a read-out for chronic inflammatory information, new methods are needed to integrate individual biological measurements and lifestyle parameters to mitigate the consequences and costs of allergic burden for society.

METHODS

More than 480.000 data points were collected from 1462 Luxembourg adults during the representative, cross-sectional European Health Examination Survey, spanning health and lifestyle reports. Deep IgE-profiles based on unsupervised clustering were correlated with data of the health survey.

FINDINGS

42.6% of the participants reported a physician-diagnosed allergy and 44% were found to be IgE-positive to at least one allergen or extract. The main sensitization sources were tree pollens followed by grass pollens and mites (52.4%, 51.8% and 40.3% of sensitized participants respectively), suggesting seasonal as well as perennial burden. The youngest group of participants (25-34 years old) showed the highest burden of sensitization, with 18.2% of them having IgE to 10 or more allergen groups. Unsupervised clustering revealed that the biggest cluster of 24.4% of participants was also the one with the highest medical need, marked by their multi-sensitization to respiratory sources.

INTERPRETATION

Our novel approach to analyzing large biosample datasets together with health information allows the measurement of the chronic inflammatory disease burden in the general population and led to the identification of the most vulnerable groups in need of better medical care.

Artificial Intelligence Chatbots in Allergy and Immunology Practice: Where Have We Been and Where Are We Going?

Artificial intelligence (AI) is rapidly becoming a valuable tool in healthcare, providing clinicians with a new AI lens perspective for patient care, diagnosis, and treatment. This article explores the potential applications, benefits, and challenges of AI chatbots in clinical settings, with a particular emphasis on ChatGPT 4.0 (OpenAI - Chat generative pretrained transformer 4.0), especially in the field of allergy and immunology. AI chatbots have shown considerable promise in various medical domains, including radiology and dermatology, by improving patient engagement, diagnostic accuracy, and personalized treatment plans. ChatGPT 4.0, developed by OpenAI, is good at understanding and replying to prompts in a way that makes sense. However, it is critical to address the potential biases, data privacy issues, ethical considerations, and the need for verification of AI-generated findings. When used responsibly, AI chatbots can significantly enhance clinical practice in allergy and immunology. However, there are still challenges in using this technology that require ongoing research and collaboration between AI developers and medical specialists. To this end, the ChatGPT 4.0 platform has the potential to enhance patient engagement, improve diagnostic accuracy, and provide personalized treatment plans in allergy and immunology practice. However, limitations and risks must be addressed to ensure their safe and effective use in clinical practice.