Atopic phenotypes and their implication in the atopic march

Čustović, Adnan; Custovic, Darije; Bukvić, Blaženka Kljaić; Fontanella, Sara; Haider, Sadia

doi:10.1080/1744666x.2020.1816825

Cited by 42 publications

(53 citation statements)

References 69 publications

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“…The term AEDS , for atopic eczema/dermatitis syndrome has also been proposed 7 . The ‘atopic’ qualifier originally represented a link with type I hypersensitivity, 8 but atopic sensitization itself was shown to be heterogeneous 9,10 . Recent studies have emphasized the need for a consensus terminology 2,6,11 and warned that ambiguity could jeopardize treatment reimbursement, patient education, as well as data mining.…”

Section: Introductionmentioning

confidence: 99%

Atopic dermatitis or eczema? Consequences of ambiguity in disease name for biomedical literature mining

Frainay

Pitarch

Filippi

et al. 2021

Clin Experimental Allergy

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Background Biomedical research increasingly relies on computational approaches to extract relevant information from large corpora of publications. Objective To investigate the consequence of the ambiguity between the use of terms “Eczema” and “Atopic Dermatitis” (AD) from the Information Retrieval perspective, and its impact on meta‐analyses, systematic reviews and text mining. Methods Articles were retrieved by querying the PubMed using terms ‘eczema’ (D003876) and “dermatitis, atopic” (D004485). We used machine learning to investigate the differences between the contexts in which each term is used. We used a decision tree approach and trained model to predict if an article would be indexed with eczema or AD tags. We used text‐mining tools to extract biological entities associated with eczema and AD, and investigated the discrepancy regarding the retrieval of key findings according to the terminology used. Results Atopic dermatitis query yielded more articles related to veterinary science, biochemistry, cellular and molecular biology; the eczema query linked to public health, infectious disease and respiratory system. Medical Subject Headings terms associated with “AD” or “Eczema” differed, with an agreement between the top 40 lists of 52%. The presence of terms related to cellular mechanisms, especially allergies and inflammation, characterized AD literature. The metabolites mentioned more frequently than expected in articles with AD tag differed from those indexed with eczema. Fewer enriched genes were retrieved when using eczema compared to AD query. Conclusions and Clinical Relevance There is a considerable discrepancy when using text mining to extract bio‐entities related to eczema or AD. Our results suggest that any systematic approach (particularly when looking for metabolites or genes related to the condition) should be performed using both terms jointly. We propose to use decision tree learning as a tool to spot and characterize ambiguity, and provide the source code for disambiguation at https://github.com/cfrainay/ResearchCodeBase.

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Section: Introductionmentioning

confidence: 99%

Atopic dermatitis or eczema? Consequences of ambiguity in disease name for biomedical literature mining

Frainay

Pitarch

Filippi

et al. 2021

Clin Experimental Allergy

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“…The study of the course of the condition, including its onset, persistence, and flare-ups, and the design of personalized treatment strategies would be greatly aided by additional longitudinal data. Previous studies have showcased the benefit and need of such data 21,42,43 and new smartphone apps could facilitate the collection of data outside of a clinical visit. The sharing of data is also crucial, as AD is a complex disease that cannot be fully characterized in a single study.…”

Section: Discussionmentioning

confidence: 99%

Data-driven research on eczema: systematic characterization of the field and recommendations for the future

Duverdier

Čustović

Tanaka

2022

Preprint

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Background: The past decade has seen a substantial rise in the employment of modern data-driven methods to study atopic dermatitis (AD) / eczema. Objective: To summarise the past and future of data-driven AD research, and identify areas in the field that would benefit from the application of these methods. Methods: We retrieved the publications that applied multivariate statistics (MS), artificial intelligence (AI, including machine learning-ML), and Bayesian statistics (BS) to AD and eczema research from the SCOPUS database over the last 50 years. We conducted a bibliometric analysis to highlight the publication trends and conceptual knowledge structure of the field, and applied topic modelling to retrieve the key topics in the literature. Results: Five key themes of data-driven research on AD and eczema were identified: (1) allergic co-morbidities, (2) image analysis and classification, (3) disaggregation, (4) quality of life, and (5) risk factors and prevalence. ML&AI methods mapped to studies investigating quality of life, prevalence, risk factors, allergic co-morbidities and disaggregation of AD/eczema, but seldom in studies of therapies. MS was employed evenly between the topics, particularly in studies on risk factors and prevalence. BS was focused on three key topics: treatment, risk factors and allergy. The use of AD or eczema terms was not uniform, with studies applying ML&AI methods using the term eczema more often. Within MS, papers using cluster and factor analysis were often only identified with the term AD. In contrast, those using logistic regression and latent class/transition models were "eczema" papers. Conclusions: Research areas that could benefit from the application of data-driven methods include the study of the pathogenesis of the condition and related risk factors, its disaggregation into validated subtypes, and personalized severity management and prognosis. We highlight Bayesian statistics as a new and promising approach in AD and eczema research.

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“…However, only approximately 7% of children with any atopic disease manifestation follow this path during childhood. 112 Genetic factors have a major role in atopic disposition. For example, mutations in the gene coding for the protein filaggrin, linked to epidermal and mucosal homeostasis, predispose to eczema.…”

Section: Case Food Allergymentioning

confidence: 99%

Immunological resilience and biodiversity for prevention of allergic diseases and asthma

Haahtela

Alenius

Lehtimäki

et al. 2021

Allergy

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Increase of allergic conditions has occurred at the same pace with the Great Acceleration, which stands for the rapid growth rate of human activities upon earth from 1950s. Changes of environment and lifestyle along with escalating urbanization are acknowledged as the main underlying causes. Secondary (tertiary) prevention for better disease control has advanced considerably with innovations for oral immunotherapy and effective treatment of inflammation with corticosteroids, calcineurin inhibitors, and biological medications. Patients are less disabled than before. However, primary prevention has remained a dilemma. Factors predicting allergy and asthma risk have proven complex: Risk factors increase the risk, while protective factors counteract them. Interaction of human body with environmental biodiversity with micro-organisms and biogenic compounds as well as the central role of epigenetic adaptation in immune homeostasis have given new insight. Allergic diseases are good indicators of the twisted relation to environment. In various non-communicable diseases, the protective mode of the immune system indicates low-grade inflammation without apparent cause. Giving microbes, pro-and prebiotics, has shown some promise in prevention and treatment. The real-world public health programme in Finland (2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018) emphasized nature relatedness and protective factors for immunological resilience, instead of avoidance. The nationwide action mitigated the allergy burden, but in the lack of controls, primary preventive effect remains to be proven. The first results of controlled biodiversity interventions are promising. In the fast urbanizing world, new approaches are called for allergy prevention, which also has a major cost saving potential.

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Atopic phenotypes and their implication in the atopic march

Cited by 42 publications

References 69 publications

Atopic dermatitis or eczema? Consequences of ambiguity in disease name for biomedical literature mining

Atopic dermatitis or eczema? Consequences of ambiguity in disease name for biomedical literature mining

Data-driven research on eczema: systematic characterization of the field and recommendations for the future

Immunological resilience and biodiversity for prevention of allergic diseases and asthma

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