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Landau T, Gamrasni K, Levin A, Barlev Y, Sanders O, Benor S, Brandwein M. Development of a predictive model for pediatric atopic dermatitis: A retrospective cross-sectional nationwide database study. Ann Allergy Asthma Immunol 2024; 133:325-334.e5. [PMID: 38901543 DOI: 10.1016/j.anai.2024.06.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 05/09/2024] [Accepted: 06/06/2024] [Indexed: 06/22/2024]
Abstract
BACKGROUND The rise in prevalence of atopic dermatitis (AD) has been correlated with numerous elements of the exposome, modern-day lifestyle, and familial history. The combined analysis of familial history and other risk elements may allow us to understand the driving factors behind the development of AD. OBJECTIVE To develop prediction models to assess the risk of developing AD using a large and diverse cohort (N = 77,525) and easily assessed risk factors. METHODS We analyzed electronic medical record data from Leumit Health System. Documented predictive factors include sex, season of birth, environment (urban/rural), socioeconomic status, household smoking, diagnosed skin conditions, number of siblings, a paternal, maternal, or sibling history of an atopic condition, and antibiotic prescriptions during pregnancy or after birth. Predictive models were trained and validated on the data set. RESULTS Medium (odds ratio [OR] 2.04, CI 1.92-2.17, P < .001) and high (OR 2.13, CI 1.95-2.34, P < .001) socioeconomic status, a previous diagnosis of contact dermatitis (OR 2.57, CI 2.37-2.78, P < .001), presence of siblings with an AD diagnosis (OR 2.21, CI 2.04-2.40, P < .001), and the percentage of siblings with any atopic condition (OR 2.58, CI 2.09-3.17, P < .001) drove risk for AD in a logistic regression model. A random forest prediction model with a sensitivity of 61% and a specificity of 84% was developed. Generalized mixed models accounting for the random effect of familial relationships boasted an area under the curve of 0.98. CONCLUSION Predictive modeling using noninvasive and accessible inputs is a powerful tool to stratify risk for developing AD.
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Affiliation(s)
| | | | - Alex Levin
- MYOR Diagnostics Ltd, Zichron Yaakov, Israel
| | - Yotam Barlev
- MYOR Diagnostics Ltd, Zichron Yaakov, Israel; Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Oliver Sanders
- Department of Pediatrics, Hadassah University Medical Center, Jerusalem, Israel
| | - Shira Benor
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Leumit Health Services, Tel Aviv, Israel; Allergy and Clinical Immunology Unit, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
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Nakamura T, Nakano T, Simpson A, Kono M, Curtin JA, Kobayashi T, Murray CS, Akiyama M, Imanishi M, Mikuriya M, Custovic A, Shimojo N. Trajectories of egg sensitization in childhood: Two birth cohorts in Asia and Europe. Allergy 2024. [PMID: 39087444 DOI: 10.1111/all.16264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 06/18/2024] [Accepted: 06/23/2024] [Indexed: 08/02/2024]
Abstract
BACKGROUND Hen's egg exposure through impaired skin barrier is considered a major mechanism of sensitization to eggs. However, the impact of filaggrin (FLG) gene loss-of-function mutations on the natural history of egg sensitization lacks consensus among studies. OBJECTIVE To evaluate the association between the natural course of egg sensitization and FLG mutations. METHODS We used Japanese and the UK birth cohorts (CHIBA and MAAS) to identify the longitudinal patterns of egg sensitization until mid-school age and examined the relationship between the identified patterns and FLG mutations. Sensitization was assessed using egg white-specific IgE levels or skin prick tests (SPTs). Egg allergy was confirmed by parental reports and sensitization. Latent class growth analysis identified longitudinal patterns. RESULTS Three similar patterns of egg sensitization (persistent, early-onset remitting, and no/low grade classes) were identified in both cohorts, with differing prevalence estimates. The proportion of children with egg allergy in the persistent class at 7 or 8 years of age was 23% (CHIBA) and 20% (MAAS). Consistently in both cohorts, FLG mutations were significantly associated only with the persistent class. Children with FLG mutations had an approximately four-fold increased risk of being in the persistent sensitization class (RRRs: 4.3, 95%C.I. (1.2-16.0), p = .03 in CHIBA; 4.3 (1.3-14.7), p = .02 in MAAS). CONCLUSION FLG loss-of-function mutations are associated with persistent egg sensitization in both Japanese and European ethnicities, and the mutations might be a potential biomarker for identifying the risk of persistent egg sensitization/allergy in early infancy. Future studies should incorporate oral food challenges to confirm this relationship.
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Affiliation(s)
| | - Taiji Nakano
- Department of Pediatrics, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Angela Simpson
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Michihiro Kono
- Department of Dermatology and Plastic Surgery, Akita University Graduate School of Medicine, Akita, Japan
- Department of Dermatology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - John A Curtin
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Tomoko Kobayashi
- Department of Dermatology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Clare S Murray
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Masashi Akiyama
- Department of Dermatology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | | | | | - Adnan Custovic
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Naoki Shimojo
- Department of Pediatrics, Graduate School of Medicine, Chiba University, Chiba, Japan
- Center for Preventive Medical Sciences, Chiba University, Chiba, Japan
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3
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Custovic A, Custovic D, Fontanella S. Understanding the heterogeneity of childhood allergic sensitization and its relationship with asthma. Curr Opin Allergy Clin Immunol 2024; 24:79-87. [PMID: 38359101 PMCID: PMC10906203 DOI: 10.1097/aci.0000000000000967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2024]
Abstract
PURPOSE OF REVIEW To review the current state of knowledge on the relationship between allergic sensitization and asthma; to lay out a roadmap for the development of IgE biomarkers that differentiate, in individual sensitized patients, whether their sensitization is important for current or future asthma symptoms, or has little or no relevance to the disease. RECENT FINDINGS The evidence on the relationship between sensitization and asthma suggests that some subtypes of allergic sensitization are not associated with asthma symptoms, whilst others are pathologic. Interaction patterns between IgE antibodies to individual allergenic molecules on component-resolved diagnostics (CRD) multiplex arrays might be hallmarks by which different sensitization subtypes relevant to asthma can be distinguished. These different subtypes of sensitization are associated amongst sensitized individuals at all ages, with different clinical presentations (no disease, asthma as a single disease, and allergic multimorbidity); amongst sensitized preschool children with and without lower airway symptoms, with different risk of subsequent asthma development; and amongst sensitized patients with asthma, with differing levels of asthma severity. SUMMARY The use of machine learning-based methodologies on complex CRD data can help us to design better diagnostic tools to help practising physicians differentiate between benign and clinically important sensitization.
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Affiliation(s)
- Adnan Custovic
- National Heart and Lung Institute, Imperial College London, London, UK
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Jacobson ME, Seshadri RS, Morimoto R, Grinich E, Haag C, Nguyen K, Simpson EL. Early intervention and disease modification in atopic dermatitis-the current state of the field and barriers to progress. J Eur Acad Dermatol Venereol 2024; 38:665-672. [PMID: 38063244 DOI: 10.1111/jdv.19699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 10/24/2023] [Indexed: 03/26/2024]
Abstract
Atopic dermatitis (AD) is a highly prevalent chronic inflammatory skin disease representing a major source of global disability burden. Disease-modifying therapies are showing promise in chronic inflammatory disorders such as rheumatoid arthritis and Crohn's disease with method and timing of initial treatment impacting long-term disease outcomes. Whether disease-modifying therapies, specifically those used as an early interventional approach, impacts disease course and comorbidity development in AD is not well-understood. We reviewed the progress in disease modification strategies, emphasizing early intervention approaches in common (or proto-typical) inflammatory diseases. Although more common in other fields, disease modification approaches are becoming increasingly investigated in dermatology, though studies in AD are lacking. Despite significant limitations in ongoing and completed studies, early data are promising and suggest that both the choice and timing of early intervention approach can affect long-term disease course and comorbidity development. To best improve AD patient outcomes, more research is needed to further explore the impact of early disease-modifying therapies. Future studies should focus on identifying the most effective approaches and extend the early results to a more inclusive set of comorbidities and longer-term outcomes.
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Affiliation(s)
- M E Jacobson
- Department of Dermatology, Oregon Health and Science University, Portland, Oregon, USA
| | - R S Seshadri
- Department of Dermatology, Oregon Health and Science University, Portland, Oregon, USA
| | - R Morimoto
- Department of Dermatology, Oregon Health and Science University, Portland, Oregon, USA
| | - E Grinich
- Department of Dermatology, Oregon Health and Science University, Portland, Oregon, USA
| | - C Haag
- Department of Dermatology, Oregon Health and Science University, Portland, Oregon, USA
| | - K Nguyen
- Department of Dermatology, Oregon Health and Science University, Portland, Oregon, USA
| | - E L Simpson
- Department of Dermatology, Oregon Health and Science University, Portland, Oregon, USA
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5
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Haider S, Granell R, Curtin JA, Holloway JW, Fontanella S, Hasan Arshad S, Murray CS, Cullinan P, Turner S, Roberts G, Simpson A, Custovic A. Identification of eczema clusters and their association with filaggrin and atopic comorbidities: analysis of five birth cohorts. Br J Dermatol 2023; 190:45-54. [PMID: 37935633 PMCID: PMC10733627 DOI: 10.1093/bjd/ljad326] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 06/23/2023] [Indexed: 11/09/2023]
Abstract
BACKGROUND Longitudinal modelling of the presence/absence of current eczema through childhood has identified similar phenotypes, but their characteristics often differ between studies. OBJECTIVES To demonstrate that a more comprehensive description of longitudinal pattern of symptoms may better describe trajectories than binary information on eczema presence. METHODS We derived six multidimensional variables of eczema spells from birth to 18 years of age (including duration, temporal sequencing and the extent of persistence/recurrence). Spells were defined as consecutive observations of eczema separated by no eczema across 5 epochs in five birth cohorts: infancy (first year); early childhood (age 2-3 years); preschool/early school age (4-5 years); middle childhood (8-10 years); adolescence (14-18 years). We applied Partitioning Around Medoids clustering on these variables to derive clusters of the temporal patterns of eczema. We then investigated the stability of the clusters, within-cluster homogeneity and associated risk factors, including FLG mutations. RESULTS Analysis of 7464 participants with complete data identified five clusters: (i) no eczema (51.0%); (ii) early transient eczema (21.6%); (iii) late-onset eczema (LOE; 8.1%); (iv) intermittent eczema (INT; 7.5%); and (v) persistent eczema (PE; 11.8%). There was very-high agreement between the assignment of individual children into clusters when using complete or imputed (n = 15 848) data (adjusted Rand index = 0.99; i.e. the clusters were very stable). Within-individual symptom patterns across clusters confirmed within-cluster homogeneity, with consistent patterns of symptoms among participants within each cluster and no overlap between the clusters. Clusters were characterized by differences in associations with risk factors (e.g. parental eczema was associated with all clusters apart from LOE; sensitization to inhalant allergens was associated with all clusters, with the highest risk in the PE cluster). All clusters apart from LOE were associated with FLG mutations. Of note, the strongest association was for PE [relative risk ratio (RRR) 2.70, 95% confidence interval (CI) 2.24-3.26; P < 0.001] followed by INT (RRR 2.29, 95% CI 1.82-2.88; P < 0.001). CONCLUSIONS Clustering of multidimensional variables identified stable clusters with different genetic architectures. Using multidimensional variables may capture eczema development and derive stable and internally homogeneous clusters. However, deriving homogeneous symptom clusters does not necessarily mean that these are underpinned by completely unique mechanisms.
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Affiliation(s)
- Sadia Haider
- National Heart and Lung Institute, Imperial College London, UK
- NIHR Imperial Biomedical Research Centre (BRC), London, UK
| | - Raquel Granell
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - John A Curtin
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Research Unit, Manchester University NHS Foundation Trust, Manchester, UK
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust, Southampton, UK
| | - Sara Fontanella
- National Heart and Lung Institute, Imperial College London, UK
- NIHR Imperial Biomedical Research Centre (BRC), London, UK
| | - Syed Hasan Arshad
- NIHR Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust, Southampton, UK
- David Hide Asthma and Allergy Research Centre, Newport, Isle of Wight, UK
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Clare S Murray
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Research Unit, Manchester University NHS Foundation Trust, Manchester, UK
| | - Paul Cullinan
- National Heart and Lung Institute, Imperial College London, UK
| | - Stephen Turner
- Royal Aberdeen Children’s Hospital, NHS Grampian, Aberdeen, UK
- Child Health, University of Aberdeen, Aberdeen, UK
| | - Graham Roberts
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust, Southampton, UK
- David Hide Asthma and Allergy Research Centre, Newport, Isle of Wight, UK
| | - Angela Simpson
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Research Unit, Manchester University NHS Foundation Trust, Manchester, UK
| | - Adnan Custovic
- National Heart and Lung Institute, Imperial College London, UK
- NIHR Imperial Biomedical Research Centre (BRC), London, UK
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van Breugel M, Fehrmann RSN, Bügel M, Rezwan FI, Holloway JW, Nawijn MC, Fontanella S, Custovic A, Koppelman GH. Current state and prospects of artificial intelligence in allergy. Allergy 2023; 78:2623-2643. [PMID: 37584170 DOI: 10.1111/all.15849] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 07/08/2023] [Accepted: 07/31/2023] [Indexed: 08/17/2023]
Abstract
The field of medicine is witnessing an exponential growth of interest in artificial intelligence (AI), which enables new research questions and the analysis of larger and new types of data. Nevertheless, applications that go beyond proof of concepts and deliver clinical value remain rare, especially in the field of allergy. This narrative review provides a fundamental understanding of the core concepts of AI and critically discusses its limitations and open challenges, such as data availability and bias, along with potential directions to surmount them. We provide a conceptual framework to structure AI applications within this field and discuss forefront case examples. Most of these applications of AI and machine learning in allergy concern supervised learning and unsupervised clustering, with a strong emphasis on diagnosis and subtyping. A perspective is shared on guidelines for good AI practice to guide readers in applying it effectively and safely, along with prospects of field advancement and initiatives to increase clinical impact. We anticipate that AI can further deepen our knowledge of disease mechanisms and contribute to precision medicine in allergy.
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Affiliation(s)
- Merlijn van Breugel
- Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- Groningen Research Institute for Asthma and COPD (GRIAC), University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- MIcompany, Amsterdam, the Netherlands
| | - Rudolf S N Fehrmann
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | | | - Faisal I Rezwan
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
- Department of Computer Science, Aberystwyth University, Aberystwyth, UK
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
- National Institute for Health and Care Research Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust, Southampton, UK
| | - Martijn C Nawijn
- Groningen Research Institute for Asthma and COPD (GRIAC), University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- Department of Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Sara Fontanella
- National Heart and Lung Institute, Imperial College London, London, UK
- National Institute for Health and Care Research Imperial Biomedical Research Centre (BRC), London, UK
| | - Adnan Custovic
- National Heart and Lung Institute, Imperial College London, London, UK
- National Institute for Health and Care Research Imperial Biomedical Research Centre (BRC), London, UK
| | - Gerard H Koppelman
- Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- Groningen Research Institute for Asthma and COPD (GRIAC), University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
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Abuabara K, Langan SM. Atopic dermatitis across the life course. Br J Dermatol 2022; 188:709-717. [PMID: 36715326 DOI: 10.1093/bjd/ljac072] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 10/13/2022] [Accepted: 10/22/2022] [Indexed: 01/22/2023]
Abstract
Atopic dermatitis, the most common chronic inflammatory skin disease, can occur at any age, and patterns of disease activity vary over time. Both prevalence and incidence are highest in infancy and early childhood, followed by a second peak in older adulthood. Birth cohort studies from European countries following children through adolescence have identified subgroups of patients with early-onset persistent disease, early-onset resolving disease, and later-onset disease. Parental history of atopy and genetic factors are among the most consistent predictors of more persistent disease. Studies have begun to examine whether molecular markers differ by age group, although longitudinal data are lacking. Breastfeeding, probiotics and skin-directed therapies such as emollients have been investigated as potential preventive measures, but randomized trials have not found consistent long-term benefit. Future research should focus on patterns of disease activity beyond early adulthood and the role of treatments on long-term disease activity.
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Affiliation(s)
- Katrina Abuabara
- Program for Clinical Research, Department of Dermatology, University of California, San Francisco School of Medicine (UCSF), San Francisco, CA, USA
| | - Sinéad M Langan
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
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Haider S, Fontanella S, Ullah A, Turner S, Simpson A, Roberts G, Murray CS, Holloway JW, Curtin JA, Cullinan P, Arshad SH, Hurault G, Granell R, Custovic A. Evolution of Eczema, Wheeze, and Rhinitis from Infancy to Early Adulthood: Four Birth Cohort Studies. Am J Respir Crit Care Med 2022; 206:950-960. [PMID: 35679320 PMCID: PMC9802000 DOI: 10.1164/rccm.202110-2418oc] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 06/09/2022] [Indexed: 01/07/2023] Open
Abstract
Rationale: The relationship between eczema, wheeze or asthma, and rhinitis is complex, and epidemiology and mechanisms of their comorbidities is unclear. Objectives: To investigate within-individual patterns of morbidity of eczema, wheeze, and rhinitis from birth to adolescence/early adulthood. Methods: We investigated onset, progression, and resolution of eczema, wheeze, and rhinitis using descriptive statistics, sequence mining, and latent Markov modeling in four population-based birth cohorts. We used logistic regression to ascertain if early-life eczema or wheeze, or genetic factors (filaggrin [FLG] mutations and 17q21 variants), increase the risk of multimorbidity. Measurements and Main Results: Single conditions, although the most prevalent, were observed significantly less frequently than by chance. There was considerable variation in the timing of onset/remission/persistence/intermittence. Multimorbidity of eczema+wheeze+rhinitis was rare but significantly overrepresented (three to six times more often than by chance). Although infantile eczema was associated with subsequent multimorbidity, most children with eczema (75.4%) did not progress to any multimorbidity pattern. FLG mutations and rs7216389 were not associated with persistence of eczema/wheeze as single conditions, but both increased the risk of multimorbidity (FLG by 2- to 3-fold, rs7216389 risk variant by 1.4- to 1.7-fold). Latent Markov modeling revealed five latent states (no disease/low risk, mainly eczema, mainly wheeze, mainly rhinitis, multimorbidity). The most likely transition to multimorbidity was from eczema state (0.21). However, although this was one of the highest transition probabilities, only one-fifth of those with eczema transitioned to multimorbidity. Conclusions: Atopic diseases fit a multimorbidity framework, with no evidence for sequential atopic march progression. The highest transition to multimorbidity was from eczema, but most children with eczema (more than three-quarters) had no comorbidities.
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Affiliation(s)
| | | | | | - Stephen Turner
- Royal Aberdeen Children’s Hospital National Health Service Grampian Aberdeen, Aberdeen, United Kingdom
- Child Health, University of Aberdeen, Aberdeen, United Kingdom
| | - Angela Simpson
- Division of Immunology, Immunity to Infection and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester Academic Health Science Centre, and Manchester University National Health Service Foundation Trust, Manchester, United Kingdom
| | - Graham Roberts
- Human Development and Health and
- National Institute for Health and Care Research Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
- David Hide Asthma and Allergy Research Centre, Isle of Wight, United Kingdom; and
| | - Clare S. Murray
- Division of Immunology, Immunity to Infection and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester Academic Health Science Centre, and Manchester University National Health Service Foundation Trust, Manchester, United Kingdom
| | - John W. Holloway
- Human Development and Health and
- National Institute for Health and Care Research Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - John A. Curtin
- Division of Immunology, Immunity to Infection and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester Academic Health Science Centre, and Manchester University National Health Service Foundation Trust, Manchester, United Kingdom
| | | | - Syed Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
- National Institute for Health and Care Research Southampton Biomedical Research Centre, University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
- David Hide Asthma and Allergy Research Centre, Isle of Wight, United Kingdom; and
| | - Guillem Hurault
- Faculty of Engineering, Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Raquel Granell
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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Duverdier A, Custovic A, Tanaka RJ. Data-driven research on eczema: Systematic characterization of the field and recommendations for the future. Clin Transl Allergy 2022; 12:e12170. [PMID: 35686200 PMCID: PMC9172212 DOI: 10.1002/clt2.12170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 05/23/2022] [Accepted: 05/25/2022] [Indexed: 11/26/2022] Open
Abstract
Background The past decade has seen a substantial rise in the employment of modern data-driven methods to study atopic dermatitis (AD)/eczema. The objective of this study is 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 treatment response, 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 personalised severity management and prognosis. We highlight BS as a new and promising approach in AD and eczema research.
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Affiliation(s)
- Ariane Duverdier
- Department of ComputingImperial College LondonLondonUK
- Department of BioengineeringImperial College LondonLondonUK
- UKRI Centre for Doctoral Training in AI for HealthcareImperial College LondonLondonUK
| | - Adnan Custovic
- National Heart and Lung InstituteImperial College LondonLondonUK
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10
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Venter C, Palumbo MP, Sauder KA, Glueck DH, O'Mahony L, Yang I, Davidson EJ, Brough HA, Holloway JW, Fleischer DM, Ben-Abdallah M, Dabelea D. Associations between child filaggrin mutations and maternal diet with the development of allergic diseases in children. Pediatr Allergy Immunol 2022; 33:e13753. [PMID: 35338739 PMCID: PMC9621095 DOI: 10.1111/pai.13753] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 01/12/2022] [Accepted: 02/16/2022] [Indexed: 12/16/2022]
Abstract
BACKGROUND Filaggrin (FLG) loss-of-function mutations in children and maternal diet in pregnancy have been implicated in child allergy outcomes. This paper studies the questions: "do FLG mutations modify the effect of maternal diet on the odds of development of allergic diseases?" and "which factor leads to the highest rate of diagnosis allergic diseases over time, maternal diet, or FLG mutations?". METHODS Exact logistic regressions studied effect modification. Cox proportional hazard models compared the rate of allergic disease development in three groups (N = 624): (1) children with FLG mutation, (2) children without FLG mutation whose mothers did not eat an allergy preventive diet, and (3) children without FLG mutation whose mothers ate an allergy preventive diet. Maternal diet was classified using a validated index. RESULTS Cox models showed the development of atopic dermatitis, asthma, and wheeze was significantly higher for children in group 1 versus 3 (HR = 2.40 [1.32, 4.37], HR = 2.29 [1.05, 4.97], and HR 2.10 [1.004, 4.38], respectively), but not significantly higher for children in group 1 versus 2 (HR = 1.30 [0.74, 2.29], HR = 1.27 [0.61, 2.63], and HR = 1.29 [0.65, 2.58], respectively). Development of allergic rhinitis was significantly higher for group 1 versus 2 and 3 (1 vs. 2: HR = 2.29 [1.10, 4.76]; 1 vs. 3: HR = 3.21 [1.46, 7.08]). There was no significant effect modification for any outcome. CONCLUSION Children with FLG mutation had similar risk of atopic dermatitis, asthma, and wheeze as children without an FLG mutation whose mothers did not eat an allergy preventive diet during pregnancy. Child FLG mutation did not modify the effect of maternal diet. The results suggest that maternal diet in pregnancy, a modifiable risk factor, could be a target for preventive interventions.
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Affiliation(s)
- Carina Venter
- Section of Allergy & Immunology, Department of Pediatrics, Children's Hospital Colorado, University of Colorado School of Medicine, Aurora, Colorado, USA.,Children's Hospital Colorado, Aurora, Colorado, USA
| | - Michaela P Palumbo
- Lifecourse Epidemiology of Adiposity and Diabetes Center, University of Colorado Anschutz Medical Campus, University of Colorado Denver, Aurora, Colorado, USA
| | - Katherine A Sauder
- Lifecourse Epidemiology of Adiposity and Diabetes Center, University of Colorado Anschutz Medical Campus, University of Colorado Denver, Aurora, Colorado, USA.,Department of Pediatrics, University of Colorado School of Medicine, University of Colorado Denver, Aurora, Colorado, USA
| | - Deborah H Glueck
- Lifecourse Epidemiology of Adiposity and Diabetes Center, University of Colorado Anschutz Medical Campus, University of Colorado Denver, Aurora, Colorado, USA.,Department of Pediatrics, University of Colorado School of Medicine, University of Colorado Denver, Aurora, Colorado, USA
| | - Liam O'Mahony
- Departments of Medicine and Microbiology, APC Microbiome Ireland, University College Cork, Cork, Ireland
| | - Ivana Yang
- Department of Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA.,Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado, USA
| | - Elizabeth J Davidson
- Department of Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Helen A Brough
- Paediatric Allergy Group, Department Women and Children's Health, School of Life Course Sciences, King's College London, London, UK.,Paediatric Allergy Group, School of Immunology and Microbial Sciences, King's College London, London, UK.,Children's Allergy Service, Evelina Children's Hospital, Guy's and St, Thomas's NHS Foundation Trust, London, UK
| | - John W Holloway
- Faculty of Medicine, Human Development and Health, University of Southampton, Southampton, UK
| | - David M Fleischer
- Section of Allergy & Immunology, Department of Pediatrics, Children's Hospital Colorado, University of Colorado School of Medicine, Aurora, Colorado, USA.,Children's Hospital Colorado, Aurora, Colorado, USA
| | - Miriam Ben-Abdallah
- Department of Pediatrics, University of Colorado School of Medicine, University of Colorado Denver, Aurora, Colorado, USA
| | - Dana Dabelea
- Lifecourse Epidemiology of Adiposity and Diabetes Center, University of Colorado Anschutz Medical Campus, University of Colorado Denver, Aurora, Colorado, USA.,Department of Pediatrics, University of Colorado School of Medicine, University of Colorado Denver, Aurora, Colorado, USA.,Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado, USA
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11
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Kotsapas C, Nicolaou N, Haider S, Kerry G, Turner PJ, Murray CS, Simpson A, Custovic A. Early-life predictors and risk factors of peanut allergy, and its association with asthma in later-life: Population-based birth cohort study. Clin Exp Allergy 2022; 52:646-657. [PMID: 35108754 PMCID: PMC9303430 DOI: 10.1111/cea.14103] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 01/25/2022] [Accepted: 01/27/2022] [Indexed: 12/01/2022]
Abstract
BACKGROUND Understanding risk factors for peanut allergy (PA) is essential to develop effective preventive measures. OBJECTIVE To ascertain associates and predictors of PA, and the relationship between PA and asthma severity. METHODS In a population-based birth cohort, we investigated the association between objectively confirmed PA with early-life environmental exposures, filaggrin (FLG)-loss-of-function mutations and other atopic disease. We then examined the association of PA with longitudinal trajectories of sensitisation, wheeze and allergic comorbidities, which were previously derived using machine learning. Finally, we ascertained the relationship between PA and asthma severity. RESULTS PA was confirmed in 30/959 participants with evaluable data. In the multivariate analysis, eczema in infancy (OR=4.4, 95% CI 1.5-13.2, p=0.007), egg sensitisation at age 3 years (OR=9.7, 95% CI 3.3-29.9, p<0.001) and early-life cat ownership (OR=3.0, 95% CI 1.1-8.4, p=0.04) were independent associates of PA. In the stratified analysis among 700 participants with genetic information, in children with early-life eczema there was no difference in FLG mutations between children with and without PA (3/18 [16.7%] vs. 42/220 [19.1%], p=1.00). In contrast, among children without eczema, those with PA were almost 8-times more likely to have FLG mutations (2/6 [33.3%] vs. 27/456 [5.9%], p=0.049). We observed associations between PA and multiple allergic sensitisation profiles derived using machine learning, with ~60-fold increase in risk amongst individuals assigned to multiple early sensitisation. PA was significantly associated with persistent wheeze (but not other wheeze phenotypes), and with trajectories of atopic disease characterised by co-morbid persistent eczema and wheeze (but not with transient phenotypes). Children with PA were more likely to have asthma, but among asthmatics we found no evidence of an association between PA and asthma severity. CONCLUSIONS Peanut allergy is associated with multiple IgE-sensitisation and early-onset persistent eczema and wheeze. FLG loss-of-function mutations were associated with peanut allergy in children without eczema.
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Affiliation(s)
| | - Nicolaos Nicolaou
- University of Nicosia Medical School, Cyprus.,Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, and Manchester Academic Health Science Centre and NIHR Biomedical Research Centre, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Sadia Haider
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Gina Kerry
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, and Manchester Academic Health Science Centre and NIHR Biomedical Research Centre, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Paul J Turner
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Clare S Murray
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, and Manchester Academic Health Science Centre and NIHR Biomedical Research Centre, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Angela Simpson
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, and Manchester Academic Health Science Centre and NIHR Biomedical Research Centre, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Adnan Custovic
- National Heart and Lung Institute, Imperial College London, London, UK
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12
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Sinikumpu SP, Huilaja L. Challenges of multidimensional atopic dermatitis. Br J Dermatol 2021; 186:208-209. [PMID: 34817860 DOI: 10.1111/bjd.20874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 10/22/2021] [Indexed: 12/01/2022]
Affiliation(s)
- S-P Sinikumpu
- PEDEGO Research Unit, University of Oulu, Department of Dermatology and Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | - L Huilaja
- PEDEGO Research Unit, University of Oulu, Department of Dermatology and Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
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