| Backgrounds:Bronchial asthma is a chronic respiratory disease with a high incidence and may cause serious harm to health.Genetic factors play an important role in the development of asthma.Linkage analysis,candidate gene research,and genome-wide association studies have found hundreds of asthma-related genetic variations.These researches are mainly carried out in European and American populations,due to disease heterogeneity,differences of genetic background and other factors,the results are inconsistent and a large fraction of heritability remains unexplained,especially in Chinese population.Exploring genetic susceptibility loci of asthma patients in Chinese Han population,and further constructing a genetic stratified model are of great significance,not only for the exploration of genetic mechanisms of asthma but also for early prevention.Objective:This study intends to apply high-throughput sequencing technology to detect genetic variation in Chinese Han patients with asthma,explore the correlation between different variants（including both common and rare variants）and asthma,perform population verification and further construct a genetic risk stratification model.Methods:Firstly,211 asthma-associated genes were selected by systemically reviewing the literatures and databases.Then a Discovery Cohort of 284 asthma cases and 205 healthy controls were included and targeted next-generation sequencing was performed based on the Ion Torrent platform.The sequencing results were analyzed and screened with bioinformatics methods.Sanger sequencing was performed for validation,burden tests were performed for rare variants,association analysis was performed for common variants.In the second stage,Mass ARRAY genotyping method was applied to verify the novel asthma-related common variants and other 35 reported asthma associated SNPs in a Replication Cohort of 664 asthma cases and 650 healthy controls.After combining the data from the two cohorts,association analysis and subgroup analysis based on asthma onset age were performed,genetic risk stratified models were further constructed based on the polygenic risk score.Results:We identified 18 potential functional loss of function variants in 21/284（7.4%）asthma cases after screening and verification,including 10 nonsense variants and 8 frameshift variants.With burden tests,10 genes were found to have a higher burden of rare variants in asthma group.We revealed 23 SNPs associated with the risk of asthma in the Discovery Cohort.In the Replication Cohort,14 SNPs were nominally associated with asthma（P<0.05）,7 SNPs were modestly significant after multiple test adjustment(P<9.1×10-4).After merging the data from two stages,17 SNPs were nominally significant,9 were modestly significant,and2 SNPs（ALOX5,rs28395865;ALOX5,rs4987105）reached genome-wide significance(P<5×10-8)in the Combined Cohort.Subgroup analysis revealed more variants were associated with childhood-onset asthma,compared to adolescent or young adult-onset group and adult-onset group.We constructed two risk stratification models based on polygenic risk score:model 1,high risk（risk score>14）and middle risk（risk score 10～14）subjects had 7.2-fold(95%CI:4.895-10.648,P=2.071×10-23)and 2.3-fold(95%CI:1.872-2.828,P=1.905×10-15)risk of developing asthma compared with low risk（risk score<10）subjects,respectively;model 2,high risk（risk score>8）and middle risk（risk score 4～8）subjects had 6.1-fold(95%CI:3.623-10.156,P=7.086×10-12)and 2.0-fold(95%CI:1.621-2.423,P=2.624×10-11)risk of developing asthma compared with low risk（risk score<4）subjects,respectively.Conclusion:This is a first comprehensive study using targeted resequencing approach to assess the role of both common and rare variants of candidate genes for asthma risk in Chinese Han population.We identified novel genetic risk for asthma susceptibility,and constructed genetic risk models for asthma.These findings provide new evidence for further elucidating the pathogenesis and assessing the genetic risk of asthma.Further independent cohort replication and functional exploration are needed. |
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