Atopic comorbidities associated with chronic spontaneous urticaria: a case-control analysis of the All of Us research program

Cortes JA, Adjei-Frimpong NA, Fakhouri SK, Delacqua F, Oldenburg R. JEADV Clin Prac. Published online October 8, 2025. doi:10.1002/jvc2.70181

ABSTRACT

Background

Chronic spontaneous urticaria (CSU) is a mast cell-driven condition defined by recurrent wheals and/or angioedema lasting over 6 weeks without an identifiable trigger. Though CSU is known to co-occur with atopic diseases and share Th2-dominant immunologic pathways, prior studies have not adequately addressed these relationships in diverse populations.

Objectives

To examine associations between CSU and atopic comorbidities in the All of Us (AoU) research program, a diverse, nationwide National Institutes of Health cohort focused on increasing enrollment from historically underrepresented groups.

Methods

We conducted a matched, case-control study of AoU participants aged ≧ 18 years enrolled between May 6, 2018 and October 1, 2023. CSU cases were identified using SNOMED codes 51611005 and 42265009. Controls were matched 4:1 by age, sex, race, ethnicity, and smoking status.

Montelukast: risk of mental disorders vs. efficacy–a meta-analysis

Sobczak M and Pawliczak R (2025)  Front. Pharmacol. 16:1659852. doi: 10.3389/fphar.2025.1659852

Abstract

Background: Montelukast, a selective leukotriene receptor antagonist, is widely used in the treatment of bronchial asthma and allergic rhinitis (AR). Although it is a well-tolerated drug, there are reports of possible central nervous system side effects, including, for example, mood changes and suicidal thoughts. Therefore, we conducted a meta-analysis to test the effects of montelukast on the mental health of patients taking montelukast and to test its effectiveness in treating asthma and AR.

Methods: PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials databases were searched to find articles of control-compared randomized clinical trials, which investigated the efficacy of montelukast treatment as well as articles about mental disorders after this treatment. The relative risk with 95% confidence interval (CI) and the standardized mean difference with 95% CI were calculated to compare the effect. A random effects model was used to calculate effect sizes.

Risk of (A) anxiety, (B) depression and (C) suicidal and self-injurious
behaviors,nonfatal self-harm or completed suicides after montelukast
treatmentcompared to control.

Results: Our meta-analysis was based on 4 studies (mental health analysis) and 19 studies (efficacy analysis). We indicated that montelukast treatment was associated with a higher risk of anxiety by 11% (RR = 1.11; 95% CI [1.06; 1.16]; p < 0.0001, I2 = 0%) without differences between subgroups.

Can artificial intelligence improve the diagnosis and management of patients with eosinophilic esophagitis?

Issa IA, Youssef O, Issa T. World J Gastroenterol. 2025 Oct 14;31(38):110999. doi: 10.3748/wjg.v31.i38.110999. 

Abstract

Eosinophilic esophagitis (EoE) is a chronic, immune-mediated condition leading to esophageal inflammation and a range of symptomatic complications if inadequately managed. Recent epidemiological trends indicate a significant increase in EoE prevalence, complicating patient care amid diagnostic challenges associated with conventional methods such as endoscopy and histopathological analysis. This review explores the promise of artificial intelligence (AI) and deep learning models in enhancing the diagnosis and management of EoE, addressing the limitations of traditional approaches including inter-observer variability, invasiveness, and delays in diagnosis. By synthesizing findings from peer-reviewed studies, we demonstrate that AI algorithms exhibit high diagnostic accuracy in recognizing subtle endoscopic features and quantifying eosinophilic tissue infiltration. Moreover, these technologies can streamline workflows, reduce dependency on manual assessments, and enhance personalized care strategies. 

Summary of artificial intelligence methodologies applicable
to eosinophilic esophagitis diagnosis.

Despite the potential benefits, challenges regarding the integration of AI into clinical practice remain, including issues of algorithmic bias, data privacy, and the need for robust validation across diverse healthcare settings.

Family dermatology life quality index (F-DLQI): German validation and applicability to parents of infants and toddlers with dermatological conditions

Traxler, J., da Silva Burger, N., Augustin, M. et al.  Eur J Pediatr 184, 703 (2025). https://doi.org/10.1007/s00431-025-06494-x

Abstract

Parents of children with skin conditions face an additional caregiving burden and significant health-related quality of life (HRQoL) impairments. This study aimed to (1) test the psychometric properties of the German version of the Family Dermatology Life Quality Index (F-DLQI) in parents of infants and toddlers with any dermatological diagnosis and (2) examine the associations between the parents’ and their children’s HRQoL. Parents (n = 126) of 0- to 4-year-old children with any skin disease filled in the F-DLQI and an instrument assessing their children’s HRQoL, the Infants and Toddlers Dermatology Quality of Life questionnaire (InToDermQoL). 

Descriptive statistics of the F-DLQI at baseline
and follow-up (T1, n = 126)

The attending physician provided clinical information. Internal consistency, 2-week test–retest reliability, measurement error, and known-groups validity across severity levels of the F-DLQI were examined. Associations between the parents’ and their children’s HRQoL were tested using regression analysis. Internal consistency and test–retest reliability of the F-DLQI were good (Cronbach’s α = 0.896, ICC = 0.867), and construct validity was confirmed. Parents’ HRQoL (F-DLQI) and children’s current complaints as reported by their parents, but not physician-rated disease severity, were associated with children’s HRQoL.

Association of allergen signatures with individualized allergic phenotypes

Kim D, Cho HJ, Kim CH, Rha MS. Allergol Int. 2025 Oct 15:S1323-8930(25)00109-1. doi: 10.1016/j.alit.2025.09.003.

Abstract

Background

Allergen sensitization patterns are heterogeneous, and their clinical relevance is often obscured by extensive cross-reactivity. We applied non-negative matrix factorization (NMF) to disentangle overlapping immunoglobulin E (IgE) signals and define clinically meaningful allergen signatures in a large Korean cohort.

Methods

We analyzed 45,065 patients who underwent multiplex allergen testing (35 inhalants and food components) between 2010 and 2025. Class-scaled specific IgE values (0–6) were factorized by NMF (k = 4). Signature weights were related to asthma, allergic rhinitis, and atopic dermatitis using multivariable logistic regression and to peripheral eosinophil counts and total IgE using age- and sex-adjusted linear models.

Results

Top allergen loadings for each non-negative matrix
factorization signature.

Four signatures—mite, grass/weed, pet, and tree—explained 77.7 % of the variance in sensitization. The mite signature predominated (57.6 % of patients) and was strongly associated with allergic rhinitis (adjusted OR: 7.21, 95 % CI: 5.66–9.16), as well as marked increases in eosinophils and total IgE.

AI, Health, and Health Care Today and Tomorrow The JAMA Summit Report on Artificial Intelligence

Angus DC, Khera R, Lieu T, et al. AI,  JAMA. Published online October 13, 2025. doi:10.1001/jama.2025.18490

Abstract

Importance  Artificial intelligence (AI) is changing health and health care on an unprecedented scale. Though the potential benefits are massive, so are the risks. The JAMA Summit on AI discussed how health and health care AI should be developed, evaluated, regulated, disseminated, and monitored.

Observations  Health and health care AI is wide-ranging, including clinical tools (eg, sepsis alerts or diabetic retinopathy screening software), technologies used by individuals with health concerns (eg, mobile health apps), tools used by health care systems to improve business operations (eg, revenue cycle management or scheduling), and hybrid tools supporting both business operations (eg, documentation and billing) and clinical activities (eg, suggesting diagnoses or treatment plans). Many AI tools are already widely adopted, especially for medical imaging, mobile health, health care business operations, and hybrid functions like scribing outpatient visits. All these tools can have important health effects (good or bad), but these effects are often not quantified because evaluations are extremely challenging or not required, in part because many are outside the US Food and Drug Administration’s regulatory oversight. A major challenge in evaluation is that a tool’s effects are highly dependent on the human-computer interface, user training, and setting in which the tool is used.

Efficacy of different allergen-specific immunotherapies for the treatment of allergic rhinitis in children and adults: an umbrella review

He Y, Liu X, Zhou B, Dai T.  Front Immunol. 2025 Sep 25;16:1658826. doi: 10.3389/fimmu.2025.1658826. 

Objective: The aim of this study was to summarize the therapeutic efficacy of various allergen immunotherapy (AIT) in the treatment of allergic rhinitis (AR) among different populations and for different allergens.

Methods: Systematic reviews or meta-analyses related to the efficacy of AIT in the treatment of AR until October 2024 were retrieved from PubMed, Web of Science, Embase, and Cochrane Library. Each study was independently evaluated by two investigators in accordance with the inclusion and exclusion criteria. The methodological quality was assessed using AMSTAR 2, and the quality of evidence was evaluated by the GRADE system.

Forest plot of the efficacy of SLIT in AR patients allergic to HDM.
[(A) Symptom scores. (B) Medication scores].

Results: A total of 16 SRs/Mas were included. The methodological quality was evaluated by AMSTAR 2, with 5 rated as “low” and the remainder as “very low”. The quality of the evidence was assessed using the GRADE system.

The Global Patient Perspective on Uncontrolled Moderate-to-Severe Asthma: Reducing Delays in Diagnosis and Treatment

Rance K, Young B, McCreary G et al. Adv Ther. 2025 Oct 6. doi: 10.1007/s12325-025-03346-w. 

Abstract

Introduction: Uncontrolled asthma greatly affects quality of life globally and highlights unmet medical needs. Despite advances in treatment and care, many patients still experience delayed diagnoses, poor symptom control, and a reliance on emergency care. The Global Allergy and Airways Patient Platform (GAAPP) surveyed patients with moderate-to-severe uncontrolled asthma to assess their care experiences.

Methods: The GAAPP Time Clock Survey is a cross-sectional, online, multilingual survey of adults living in Brazil, Germany, Italy, Japan, Saudi Arabia, the United Arab Emirates, and the US. The survey examined diagnosis, symptoms, treatment outcomes, challenges in self-management, and timelines for care coordination.

Respondents’ Symptom Report Self-reported frequency
of common asthma symptoms, including cough,
shortness of breath, mucus production, wheezing,
chest tightness, and rescue inhaler use

Results: A total of 1401 individuals with self-reported asthma using combination inhaler therapy and experiencing symptoms were enrolled in this study. Among these participants, 56% reported waiting more than 1 month to undergo pulmonary function testing for diagnosis.