以全基因轉錄體及基因環境交互作用探討RSV對氣喘發作的影響

Genome-wide integrative analysis to identify genetic targets for RSV latent infection on asthma exacerbations

蔡靜慧(Ching-Hui Tsai)

指導教授 ： 盧子彬 ； 李永凌

國立臺灣大學/公共衛生學院/流行病學與預防醫學研究所/博士(2020年)

https://doi.org/10.6342/NTU202001249

摘要

背景及目的：
呼吸道融合病毒(Respiratory syncytial virus, RSV)是造成人類呼吸道感染的主因，並且與氣喘發作有關。然而，並非所有氣喘孩童在感染RSV後，均會發生氣喘發作的症狀，孩童本身的基因對氣喘發作嚴重程度也有貢獻。因此，本研究目的將結合RSV感染、全基因體基因表現及全基因體基因型資料，探討影響氣喘發作的標的基因。

方法：
以Gene Expression Omnibus (GEO)資料庫進行RSV感染的轉錄體資料的統合分析，討論RSV感染的顯著基因及生物路徑，以數量性狀基因座(expression quantitative trait loci, eQTL)分析，搜尋潛在影響RSV感染顯著基因的單一核苷酸多型性(single nucleotide polymorphisms, SNPs)，於台灣孩童氣喘研究聯盟(Taiwanese Consortium of Childhood Asthma Study, TCCAS)中，利用以基因為基礎的邏輯式回歸篩選氣喘發作的基因，並於獨立族群(Childhood Asthma Management Program, CAMP)驗證，最後進行基因、RSV感染與氣喘發作的交互作用分析。

結果：
利用RSV感染的轉錄體資料進行統合分析後，發現352個顯著表現基因(FDR<0.05)。利用38,123個SNPs進行與氣喘發作的相關性分析，我們發現11個SNPs位於GADD45A、GYPB、MS4A3、NFE2、RNASE3、EPB41L3、CEACAM6及CEACAM3等8個基因與氣喘發作有顯著相關(FDR<0.05)，並也經過獨立族群驗證，其中rs7251960 (CEACAM3)會修飾RSV感染對氣喘發作的風險(p for interaction <0.05)。在肺部組織中，rs7251960的核苷酸變異與CEACAM3 基因表達量有顯著相關(p for trend=1.2×10-7)。利用兩個獨立的族群資料分析，發現相對於非氣喘發作者，氣喘發作者的鼻腔黏膜CEACAM3 基因表現量較低。

結論：
GADD45A、GYPB、MS4A3、NFE2、RNASE3、EPB41L3、CEACAM6及CEACAM3是影響氣喘發作的基因。rs7251960是影響CEACAM3基因表現的數量性狀基因座，且CEACAM3 基因表現量與氣喘發作有顯著相關，CEACAM3可修飾RSV潛在感染對於氣喘發作的影響。

關鍵字

孩童 ； 氣喘 ； 統合分析 ； 整合式分析 ； 基因環境交互作用

並列摘要

Background:
Respiratory syncytial virus (RSV) is a major cause of human respiratory infections and is associated with asthma exacerbations, the symptoms of which include nocturnal wheezing and severe wheezing causing limited speech. Nevertheless, not all children exposed to RSV develop asthma symptoms, possibly because genes modulate the effects of RSV on asthma exacerbations.

Objective:
The purpose of this study was to identify genes that modulate the effect of RSV latent infection on asthma exacerbations on a genome-wide scale.

Methods:
We performed an in silico meta-analysis to investigate differentially expressed genes (DEGs) of RSV infection from Gene Expression Omnibus (GEO) datasets. Expression quantitative trait loci (eQTL) methods were applied to select single nucleotide polymorphisms (SNPs) that were associated with DEGs. SNPs located in the gene range ± 5 kb were included. Gene-based analysis was used to identify SNPs that were significantly associated with asthma exacerbations in the Taiwanese Consortium of Childhood Asthma Study (TCCAS) and validation was attempted in an independent cohort, the Childhood Asthma Management Program (CAMP). Gene-RSV interaction analyses were performed to investigate the association between the interaction of SNPs and RSV latent infection on asthma exacerbations.

Results:
A total of 352 significant DEGs were found by meta-analysis of RSV-related genes. We used 38,123 SNPs related to DEGs to investigate the genetic main effects on asthma exacerbations. We found that eight RSV-related genes (GADD45A, GYPB, MS4A3, NFE2, RNASE3, EPB41L3, CEACAM6 and CEACAM3) were significantly associated with asthma exacerbations in TCCAS and also validated in CAMP. In TCCAS, rs7251960 (CEACAM3) significantly modulated the effect of RSV latent infection on asthma exacerbations (FDR<0.05). The rs7251960 variants were associated with CEACAM3 mRNA expression in lung tissue (p for trend=1.2×10-7). CEACAM3 mRNA was reduced in nasal mucosa from subjects with asthma exacerbations in two independent datasets.

Conclusion:
GADD45A, GYPB, MS4A3, NFE2, RNASE3, EPB41L3, CEACAM6 and CEACAM3 are potential markers of asthma exacerbations. rs7251960 is an eQTL for CEACAM3, and CEACAM3 mRNA expression is reduced in subjects experiencing asthma exacerbations. CEACAM3 may be a modulator of RSV latent infection on asthma exacerbations.

並列關鍵字

children ； asthma ； meta-analysis ； integrative analysis ； gene-environment interaction

參考文獻

1. CDC. Centers for Disease Control and Prevention. Vital signs: asthma prevalence, disease characteristics, and self-management education: United States, 2001–2009. MMWR Morb Mortal Wkly Rep 2011;60:547-52.

2. Silverstein MD, Mair JE, Katusic SK, Wollan PC, O'Connell E J, Yunginger JW. School attendance and school performance: a population-based study of children with asthma. J Pediatr 2001;139:278-83.

3. Spee-van der Wekke J, Meulmeester JF, Radder JJ, Verloove-Vanhorick SP. School absence and treatment in school children with respiratory symptoms in The Netherlands: data from the Child Health Monitoring System. J Epidemiol Community Health 1998;52:359-63.

4. Weiss KB, Sullivan SD. Socio-economic burden of asthma, allergy, and other atopic illnesses. Pediatr Allergy Immunol 1994;5:7-12.

5. Calsbeek H, Morren M, Bensing J, Rijken M. Knowledge and attitudes towards genetic testing: a two year follow-up study in patients with asthma, diabetes mellitus and cardiovascular disease. J Genet Couns 2007;16:493-504.