Genome-wide association and HLA fine-mapping studies identify risk loci and genetic pathways underlying allergic rhinitis

Allergic rhinitis is the most common clinical presentation of allergy, affecting 400 million people worldwide, with increasing incidence in westernized countries1,2. To elucidate the genetic architecture and understand the underlying disease mechanisms, we carried out a meta-analysis of allergic rhinitis in 59,762 cases and 152,358 controls of European ancestry and identified a total of 41 risk loci for allergic rhinitis, including 20 loci not previously associated with allergic rhinitis, which were confirmed in a replication phase of 60,720 cases and 618,527 controls. Functional annotation implicated genes involved in various immune pathways, and fine mapping of the HLA region suggested amino acid variants important for antigen binding. We further performed genome-wide association study (GWAS) analyses of allergic sensitization against inhalant allergens and nonallergic rhinitis, which suggested shared genetic mechanisms across rhinitis-related traits. Future studies of the identified loci and genes might identify novel targets for treatment and prevention of allergic rhinitis

Rhinitis associated with asthma is distinct from rhinitis alone: TARIA‐MeDALL hypothesis

Asthma, rhinitis, and atopic dermatitis (AD) are interrelated clinical phenotypes that partly overlap in the human interactome. The concept of “one-airway-one-disease,” coined over 20 years ago, is a simplistic approach of the links between upper- and lower-airway allergic diseases. With new data, it is time to reassess the concept. This article reviews (i) the clinical observations that led to Allergic Rhinitis and its Impact on Asthma (ARIA), (ii) new insights into polysensitization and multimorbidity, (iii) advances in mHealth for novel phenotype definitions, (iv) confirmation in canonical epidemiologic studies, (v) genomic findings, (vi) treatment approaches, and (vii) novel concepts on the onset of rhinitis and multimorbidity. One recent concept, bringing together upper- and lower-airway allergic diseases with skin, gut, and neuropsychiatric multimorbidities, is the “Epithelial Barrier Hypothesis.” This review determined that the “one-airway-one-disease” concept does not always hold true and that several phenotypes of disease can be defined. These phenotypes include an extreme “allergic” (asthma) phenotype combining asthma, rhinitis, and conjunctivitis.info:eu-repo/semantics/publishedVersio

De Irradiatione vel Linguis Angelorum, Deo Duce, Præside Dn. Johanne Eberhardo Schwelingio, J. U. D. ... Publicè disputabit Johannes Michael Jungius, Hanoviâ-Wetteravus, Phil. Studiosus, Autor ac Respondens, Ad diem XXIV. labentis Septemb. horis locoq, ordinariis.

DE IRRADIATIONE VEL LINGUIS ANGELORUM, DEO DUCE, PRÆSIDE DN. JOHANNE EBERHARDO SCHWELINGIO, J. U. D. ... PUBLICÈ DISPUTABIT JOHANNES MICHAEL JUNGIUS, HANOVIÂ-WETTERAVUS, PHIL. STUDIOSUS, AUTOR AC RESPONDENS, AD DIEM XXIV. LABENTIS SEPTEMB. HORIS LOCOQ, ORDINARIIS. De Irradiatione vel Linguis Angelorum, Deo Duce, Præside Dn. Johanne Eberhardo Schwelingio, J. U. D. ... Publicè disputabit Johannes Michael Jungius, Hanoviâ-Wetteravus, Phil. Studiosus, Autor ac Respondens, Ad diem XXIV. labentis Septemb. horis locoq, ordinariis. ([1]) Titelseite ([1]) Widmung ([2]) ... Magni, omni cultu & officiorum genere dignissimi ([3]) Thesen ([5]) Mantissa (14) Beiträge (15

Aortic Dissection Dataset and Segmentations

This dataset consists of a type B Aortic Dissection (AD) CTA collection with true and false lumen expert annotations. It can be used for the development of AI-based algorithms for an automatic segmentation of ADs.For a review about the detection, segmentation, simulation and visualization of Aortic Dissections, please see:Pepe A, Li J, Rolf-Pissarczyk M, Gsaxner C, Chen X, Holzapfel GA, Egger J. Detection, segmentation, simulation and visualization of aortic dissections: A review. Medical image analysis. 2020 Oct 1;65:101773.Cite as:[1] Christian Mayer, Antonio Pepe, Sophie Hossain, Barbara Karner, Melanie Arnreiter, Jens Kleesiek, Johannes Schmid, Michael Janisch, Hannes Deutschmann, Michael Fuchsjäger, Daniel Zimpfer, Jan Egger, Heinrich Mächler. Aortic Dissection Dataset and Segmentations. figshare, 2024. DOI: 10.6084/m9.figshare.22269091[2] Christian Mayer, Antonio Pepe, Sophie Hossain, Barbara Karner, Melanie Arnreiter, Jens Kleesiek, Johannes Schmid, Michael Janisch, Hannes Deutschmann, Michael Fuchsjäger, Daniel Zimpfer, Jan Egger, Heinrich Mächler. Type B Aortic Dissection CTA Collection with True and False Lumen Expert Annotations for the Development of AI-based Algorithms. Scientific Data, Nature Portfolio 2024.</p