Han-Kyul Kim, Ji-One Kang, Ji Eun Lim, Tae-Woong Ha, Hae Un Jung, Won Jun Lee, Dong Jun Kim, Eun Ju Baek, Ian M. Adcock, Kian Fan Chung, Tae-Bum Kim, Bermseok Oh
{"title":"哮喘发病年龄和肺功能的遗传差异:聚类分析","authors":"Han-Kyul Kim, Ji-One Kang, Ji Eun Lim, Tae-Woong Ha, Hae Un Jung, Won Jun Lee, Dong Jun Kim, Eun Ju Baek, Ian M. Adcock, Kian Fan Chung, Tae-Bum Kim, Bermseok Oh","doi":"10.1002/clt2.12282","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>The extent of differences between genetic risks associated with various asthma subtypes is still unknown. To better understand the heterogeneity of asthma, we employed an unsupervised method to identify genetic variants specifically associated with asthma subtypes. Our goal was to gain insight into the genetic basis of asthma.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>In this study, we utilized the UK Biobank dataset to select asthma patients (All asthma, <i>n</i> = 50,517) and controls (<i>n</i> = 283,410). We excluded 14,431 individuals who had no information on predicted values of forced expiratory volume in one second percent (FEV1%) and onset age, resulting in a final total of 36,086 asthma cases. We conducted k-means clustering based on asthma onset age and predicted FEV1% using these samples (<i>n</i> = 36,086). Cluster-specific genome-wide association studies were then performed, and heritability was estimated via linkage disequilibrium score regression. To further investigate the pathophysiology, we conducted eQTL analysis with GTEx and gene-set enrichment analysis with FUMA.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Clustering resulted in four distinct clusters: early onset asthma<sup>normalLF</sup> (early onset with normal lung function, <i>n</i> = 8172), early onset asthma<sup>reducedLF</sup> (early onset with reduced lung function, <i>n</i> = 8925), late-onset asthma<sup>normalLF</sup> (late-onset with normal lung function, <i>n</i> = 12,481), and late-onset asthma<sup>reducedLF</sup> (late-onset with reduced lung function, <i>n</i> = 6508). Our GWASs in four clusters and in All asthma sample identified 5 novel loci, 14 novel signals, and 51 cluster-specific signals. Among clusters, early onset asthma<sup>normalLF</sup> and late-onset asthma<sup>reducedLF</sup> were the least correlated (<i>r</i><sub><i>g</i></sub> = 0.37). Early onset asthma<sup>reducedLF</sup> showed the highest heritability explained by common variants (<i>h</i><sup><i>2</i></sup> = 0.212) and was associated with the largest number of variants (71 single nucleotide polymorphisms). Further, the pathway analysis conducted through eQTL and gene-set enrichment analysis showed that the worsening of symptoms in early onset asthma correlated with lymphocyte activation, pathogen recognition, cytokine receptor activation, and lymphocyte differentiation.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Our findings suggest that early onset asthma<sup>reducedLF</sup> was the most genetically predisposed cluster, and that asthma clusters with reduced lung function were genetically distinct from clusters with normal lung function. Our study revealed the genetic variation between clusters that were segmented based on onset age and lung function, providing an important clue for the genetic mechanism of asthma heterogeneity.</p>\n </section>\n </div>","PeriodicalId":10334,"journal":{"name":"Clinical and Translational Allergy","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/clt2.12282","citationCount":"0","resultStr":"{\"title\":\"Genetic differences according to onset age and lung function in asthma: A cluster analysis\",\"authors\":\"Han-Kyul Kim, Ji-One Kang, Ji Eun Lim, Tae-Woong Ha, Hae Un Jung, Won Jun Lee, Dong Jun Kim, Eun Ju Baek, Ian M. Adcock, Kian Fan Chung, Tae-Bum Kim, Bermseok Oh\",\"doi\":\"10.1002/clt2.12282\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>The extent of differences between genetic risks associated with various asthma subtypes is still unknown. To better understand the heterogeneity of asthma, we employed an unsupervised method to identify genetic variants specifically associated with asthma subtypes. Our goal was to gain insight into the genetic basis of asthma.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>In this study, we utilized the UK Biobank dataset to select asthma patients (All asthma, <i>n</i> = 50,517) and controls (<i>n</i> = 283,410). We excluded 14,431 individuals who had no information on predicted values of forced expiratory volume in one second percent (FEV1%) and onset age, resulting in a final total of 36,086 asthma cases. We conducted k-means clustering based on asthma onset age and predicted FEV1% using these samples (<i>n</i> = 36,086). Cluster-specific genome-wide association studies were then performed, and heritability was estimated via linkage disequilibrium score regression. To further investigate the pathophysiology, we conducted eQTL analysis with GTEx and gene-set enrichment analysis with FUMA.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>Clustering resulted in four distinct clusters: early onset asthma<sup>normalLF</sup> (early onset with normal lung function, <i>n</i> = 8172), early onset asthma<sup>reducedLF</sup> (early onset with reduced lung function, <i>n</i> = 8925), late-onset asthma<sup>normalLF</sup> (late-onset with normal lung function, <i>n</i> = 12,481), and late-onset asthma<sup>reducedLF</sup> (late-onset with reduced lung function, <i>n</i> = 6508). Our GWASs in four clusters and in All asthma sample identified 5 novel loci, 14 novel signals, and 51 cluster-specific signals. Among clusters, early onset asthma<sup>normalLF</sup> and late-onset asthma<sup>reducedLF</sup> were the least correlated (<i>r</i><sub><i>g</i></sub> = 0.37). Early onset asthma<sup>reducedLF</sup> showed the highest heritability explained by common variants (<i>h</i><sup><i>2</i></sup> = 0.212) and was associated with the largest number of variants (71 single nucleotide polymorphisms). Further, the pathway analysis conducted through eQTL and gene-set enrichment analysis showed that the worsening of symptoms in early onset asthma correlated with lymphocyte activation, pathogen recognition, cytokine receptor activation, and lymphocyte differentiation.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>Our findings suggest that early onset asthma<sup>reducedLF</sup> was the most genetically predisposed cluster, and that asthma clusters with reduced lung function were genetically distinct from clusters with normal lung function. Our study revealed the genetic variation between clusters that were segmented based on onset age and lung function, providing an important clue for the genetic mechanism of asthma heterogeneity.</p>\\n </section>\\n </div>\",\"PeriodicalId\":10334,\"journal\":{\"name\":\"Clinical and Translational Allergy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2023-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/clt2.12282\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical and Translational Allergy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/clt2.12282\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ALLERGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical and Translational Allergy","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/clt2.12282","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ALLERGY","Score":null,"Total":0}
Genetic differences according to onset age and lung function in asthma: A cluster analysis
Background
The extent of differences between genetic risks associated with various asthma subtypes is still unknown. To better understand the heterogeneity of asthma, we employed an unsupervised method to identify genetic variants specifically associated with asthma subtypes. Our goal was to gain insight into the genetic basis of asthma.
Methods
In this study, we utilized the UK Biobank dataset to select asthma patients (All asthma, n = 50,517) and controls (n = 283,410). We excluded 14,431 individuals who had no information on predicted values of forced expiratory volume in one second percent (FEV1%) and onset age, resulting in a final total of 36,086 asthma cases. We conducted k-means clustering based on asthma onset age and predicted FEV1% using these samples (n = 36,086). Cluster-specific genome-wide association studies were then performed, and heritability was estimated via linkage disequilibrium score regression. To further investigate the pathophysiology, we conducted eQTL analysis with GTEx and gene-set enrichment analysis with FUMA.
Results
Clustering resulted in four distinct clusters: early onset asthmanormalLF (early onset with normal lung function, n = 8172), early onset asthmareducedLF (early onset with reduced lung function, n = 8925), late-onset asthmanormalLF (late-onset with normal lung function, n = 12,481), and late-onset asthmareducedLF (late-onset with reduced lung function, n = 6508). Our GWASs in four clusters and in All asthma sample identified 5 novel loci, 14 novel signals, and 51 cluster-specific signals. Among clusters, early onset asthmanormalLF and late-onset asthmareducedLF were the least correlated (rg = 0.37). Early onset asthmareducedLF showed the highest heritability explained by common variants (h2 = 0.212) and was associated with the largest number of variants (71 single nucleotide polymorphisms). Further, the pathway analysis conducted through eQTL and gene-set enrichment analysis showed that the worsening of symptoms in early onset asthma correlated with lymphocyte activation, pathogen recognition, cytokine receptor activation, and lymphocyte differentiation.
Conclusions
Our findings suggest that early onset asthmareducedLF was the most genetically predisposed cluster, and that asthma clusters with reduced lung function were genetically distinct from clusters with normal lung function. Our study revealed the genetic variation between clusters that were segmented based on onset age and lung function, providing an important clue for the genetic mechanism of asthma heterogeneity.
期刊介绍:
Clinical and Translational Allergy, one of several journals in the portfolio of the European Academy of Allergy and Clinical Immunology, provides a platform for the dissemination of allergy research and reviews, as well as EAACI position papers, task force reports and guidelines, amongst an international scientific audience.
Clinical and Translational Allergy accepts clinical and translational research in the following areas and other related topics: asthma, rhinitis, rhinosinusitis, drug hypersensitivity, allergic conjunctivitis, allergic skin diseases, atopic eczema, urticaria, angioedema, venom hypersensitivity, anaphylaxis, food allergy, immunotherapy, immune modulators and biologics, animal models of allergic disease, immune mechanisms, or any other topic related to allergic disease.