Literature DB >> 24311777

Genetic heterogeneity of asthma phenotypes identified by a clustering approach.

Valérie Siroux1, Juan R González, Emmanuelle Bouzigon, Ivan Curjuric, Anne Boudier, Medea Imboden, Josep Maria Anto, Ivo Gut, Deborah Jarvis, Mark Lathrop, Ernst Reidar Omenaas, Isabelle Pin, Mathias Wjst, Florence Demenais, Nicole Probst-Hensch, Manolis Kogevinas, Francine Kauffmann.   

Abstract

The aim of the study was to identify genetic variants associated with refined asthma phenotypes enabling multiple features of the disease to be taken into account. Latent class analysis (LCA) was applied in 3001 adults ever having asthma recruited in the frame of three epidemiological surveys (the European Community Respiratory Health Survey (ECRHS), the Swiss Study on Air Pollution and Lung Disease in Adults (SAPALDIA) and the Epidemiological Study on the Genetics and Environment of Asthma (EGEA)). 14 personal and phenotypic characteristics, gathered from questionnaires and clinical examination, were used. A genome-wide association study was conducted for each LCA-derived asthma phenotype, compared to subjects without asthma (n=3474). The LCA identified four adult asthma phenotypes, mainly characterised by disease activity, age of asthma onset and atopic status. Associations of genome-wide significance (p<1.25 × 10(-7)) were observed between "active adult-onset nonallergic asthma" and rs9851461 flanking CD200 (3q13.2) and between "inactive/mild nonallergic asthma" and rs2579931 flanking GRIK2 (6q16.3). Borderline significant results (2.5 × 10(-7) < p <8.2 × 10(-7)) were observed between three single nucleotide polymorphisms (SNPs) in the ALCAM region (3q13.11) and "active adult-onset nonallergic asthma". These results were consistent across studies. 15 SNPs identified in previous genome-wide association studies of asthma have been replicated with at least one asthma phenotype, most of them with the "active allergic asthma" phenotype. Our results provide evidence that a better understanding of asthma phenotypic heterogeneity helps to disentangle the genetic heterogeneity of asthma.

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Year:  2013        PMID: 24311777     DOI: 10.1183/09031936.00032713

Source DB:  PubMed          Journal:  Eur Respir J        ISSN: 0903-1936            Impact factor:   16.671


  16 in total

1.  Multimorbidity medications and poor asthma prognosis.

Authors:  Sébastien Chanoine; Margaux Sanchez; Isabelle Pin; Sofia Temam; Nicole Le Moual; Agnès Fournier; Christophe Pison; Jean Bousquet; Pierrick Bedouch; Marie-Christine Boutron-Ruault; Raphaëlle Varraso; Valérie Siroux
Journal:  Eur Respir J       Date:  2018-04-12       Impact factor: 16.671

2.  Allergic Endotypes and Phenotypes of Asthma.

Authors:  Nicole Akar-Ghibril; Thomas Casale; Adnan Custovic; Wanda Phipatanakul
Journal:  J Allergy Clin Immunol Pract       Date:  2020-02

3.  IRAK-M Associates with Susceptibility to Adult-Onset Asthma and Promotes Chronic Airway Inflammation.

Authors:  Yi Liu; Mingqiang Zhang; Lili Lou; Lun Li; Youming Zhang; Wei Chen; Weixun Zhou; Yan Bai; Jinming Gao
Journal:  J Immunol       Date:  2019-01-07       Impact factor: 5.422

4.  IL-13 and FOXO3 genes polymorphisms regulate IgE levels in asthmatic patients.

Authors:  Amer Imraish; Tuqa Abu-Thiab; Malek Zihlif
Journal:  Biomed Rep       Date:  2021-04-13

5.  Treatment options in type-2 low asthma.

Authors:  Timothy S C Hinks; Stewart J Levine; Guy G Brusselle
Journal:  Eur Respir J       Date:  2021-01-21       Impact factor: 16.671

6.  Subtypes of asthma based on asthma control and severity: a latent class analysis.

Authors:  Elina M S Mäkikyrö; Maritta S Jaakkola; Jouni J K Jaakkola
Journal:  Respir Res       Date:  2017-01-23

7.  Prevalence and Geographic Distribution Pattern of Asthma in Tehran by ECRHS.

Authors:  Hooman Sharifi; Mostafa Ghanei; Makan Sadr; Habib Emami; Atefeh Fakharian; Zahra Hessami; Mahshid Aryanpur; Hamidreza Jamaati; Mohammad Reza Masjedi
Journal:  Tanaffos       Date:  2016

8.  Childhood wheezing, asthma, allergy, atopy, and lung function: different socioeconomic patterns for different phenotypes.

Authors:  Bruna Galobardes; Raquel Granell; Jonathan Sterne; Rachael Hughes; Cilia Mejia-Lancheros; George Davey Smith; John Henderson
Journal:  Am J Epidemiol       Date:  2015-10-06       Impact factor: 4.897

Review 9.  Phenotypes, Risk Factors, and Mechanisms of Adult-Onset Asthma.

Authors:  Pinja Ilmarinen; Leena E Tuomisto; Hannu Kankaanranta
Journal:  Mediators Inflamm       Date:  2015-10-11       Impact factor: 4.711

Review 10.  Artificial Intelligence and Machine Learning in Chronic Airway Diseases: Focus on Asthma and Chronic Obstructive Pulmonary Disease.

Authors:  Yinhe Feng; Yubin Wang; Chunfang Zeng; Hui Mao
Journal:  Int J Med Sci       Date:  2021-06-01       Impact factor: 3.738

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