Integrated genomics analysis highlights important SNPs and genes implicated in moderate-to-severe asthma based on GWAS and eQTL datasets.
Integrated genomics analysis highlights important SNPs and genes implicated in moderate-to-severe asthma based on GWAS and eQTL datasets.
复制标题
DOI：
10.1186/s12890-020-01303-7
复制
发表时间：
2020-10-16
影响因子：
3.1
通讯作者：
Zhou L
中科院分区：
文献类型：
--
作者：
Dong Z;Ma Y;Zhou H;Shi L;Ye G;Yang L;Liu P;Zhou L
重度哮喘是一种慢性疾病，导致不成比例的疾病发病率和死亡率。自2007年以来，许多全基因组关联研究（GWAS）已经记录了大量与哮喘相关的遗传变异和相关基因。然而，这些已鉴定的变异体参与哮喘或严重哮喘风险的分子机制在很大程度上仍然未知。在本研究中，我们系统地整合了3个独立的表达数量性状基因座（eQTL）数据（N = 1977）和一个大规模的GWAS汇总数据（N = 30，810）的中重度哮喘，通过使用Sherlock Bayesian分析，以确定是否表达相关的变异导致严重哮喘的风险。此外，我们进行了各种生物信息学分析，包括途径富集分析、PPI网络富集分析、计算机排列分析、DEG分析和共表达分析，以优先考虑与严重哮喘相关的重要基因。在发现阶段，我们通过使用Sherlock Bayesian分析确定了1129个与中重度哮喘相关的重要基因。通过MAGMA基因分析，228个基因被显著复制。这228个复制基因在17个生物学途径中富集，包括抗原加工和呈递（校正P = 4.30 × 10− 6）、I型糖尿病（校正P = 7.09 × 10− 5）和哮喘（校正P = 1.72 × 10− 3）。通过一系列生物信息学分析，我们突出了11个重要基因，如GNGT 2，TLR 6和TTC 19，作为与中重度/重度哮喘相关的真实风险基因。在GNGT 2基因中，rs 17637472有3个eSNPs（PeQTL = 2.98 × 10− 8，PGWAS = 3.40 × 10− 8），rs11265180（PeQTL = 6.0 × 10− 6和PGWAS = 1.99 × 10− 3）和rs 1867087（PeQTL = 1.0 × 10− 4和PGWAS = 1.84 × 10− 5）。此外，与轻中度哮喘相比，GNGT 2在重度哮喘中显著表达（P = 0.045），并且Gngt 2在溶媒和各种糖皮质激素之间显示出显著不同的表达模式（Anova P = 1.55 × 10− 6）。我们目前的研究提供了多方面的证据，支持这11个被鉴定的基因是严重哮喘发病机制中的重要候选基因。
Severe asthma is a chronic disease contributing to disproportionate disease morbidity and mortality. From the year of 2007, many genome-wide association studies (GWAS) have documented a large number of asthma-associated genetic variants and related genes. Nevertheless, the molecular mechanism of these identified variants involved in asthma or severe asthma risk remains largely unknown. In the current study, we systematically integrated 3 independent expression quantitative trait loci (eQTL) data (N = 1977) and a large-scale GWAS summary data of moderate-to-severe asthma (N = 30,810) by using the Sherlock Bayesian analysis to identify whether expression-related variants contribute risk to severe asthma. Furthermore, we performed various bioinformatics analyses, including pathway enrichment analysis, PPI network enrichment analysis, in silico permutation analysis, DEG analysis and co-expression analysis, to prioritize important genes associated with severe asthma. In the discovery stage, we identified 1129 significant genes associated with moderate-to-severe asthma by using the Sherlock Bayesian analysis. Two hundred twenty-eight genes were prominently replicated by using MAGMA gene-based analysis. These 228 replicated genes were enriched in 17 biological pathways including antigen processing and presentation (Corrected P = 4.30 × 10− 6), type I diabetes mellitus (Corrected P = 7.09 × 10− 5), and asthma (Corrected P = 1.72 × 10− 3). With the use of a series of bioinformatics analyses, we highlighted 11 important genes such as GNGT2, TLR6, and TTC19 as authentic risk genes associated with moderate-to-severe/severe asthma. With respect to GNGT2, there were 3 eSNPs of rs17637472 (PeQTL = 2.98 × 10− 8 and PGWAS = 3.40 × 10− 8), rs11265180 (PeQTL = 6.0 × 10− 6 and PGWAS = 1.99 × 10− 3), and rs1867087 (PeQTL = 1.0 × 10− 4 and PGWAS = 1.84 × 10− 5) identified. In addition, GNGT2 is significantly expressed in severe asthma compared with mild-moderate asthma (P = 0.045), and Gngt2 shows significantly distinct expression patterns between vehicle and various glucocorticoids (Anova P = 1.55 × 10− 6). Our current study provides multiple lines of evidence to support that these 11 identified genes as important candidates implicated in the pathogenesis of severe asthma.
登录
查看更多内容
影响因子：
24.3
作者：
Huang, Shuang;Vasquez, Monica M.;Guerra, Stefano
通讯作者：
Guerra, Stefano
影响因子：
30.8
作者：
Demenais F;Margaritte-Jeannin P;Barnes KC;Cookson WOC;Altmüller J;Ang W;Barr RG;Beaty TH;Becker AB;Beilby J;Bisgaard H;Bjornsdottir US;Bleecker E;Bønnelykke K;Boomsma DI;Bouzigon E;Brightling CE;Brossard M;Brusselle GG;Burchard E;Burkart KM;Bush A;Chan-Yeung M;Chung KF;Couto Alves A;Curtin JA;Custovic A;Daley D;de Jongste JC;Del-Rio-Navarro BE;Donohue KM;Duijts L;Eng C;Eriksson JG;Farrall M;Fedorova Y;Feenstra B;Ferreira MA;Australian Asthma Genetics Consortium (AAGC) collaborators;Freidin MB;Gajdos Z;Gauderman J;Gehring U;Geller F;Genuneit J;Gharib SA;Gilliland F;Granell R;Graves PE;Gudbjartsson DF;Haahtela T;Heckbert SR;Heederik D;Heinrich J;Heliövaara M;Henderson J;Himes BE;Hirose H;Hirschhorn JN;Hofman A;Holt P;Hottenga J;Hudson TJ;Hui J;Imboden M;Ivanov V;Jaddoe VWV;James A;Janson C;Jarvelin MR;Jarvis D;Jones G;Jonsdottir I;Jousilahti P;Kabesch M;Kähönen M;Kantor DB;Karunas AS;Khusnutdinova E;Koppelman GH;Kozyrskyj AL;Kreiner E;Kubo M;Kumar R;Kumar A;Kuokkanen M;Lahousse L;Laitinen T;Laprise C;Lathrop M;Lau S;Lee YA;Lehtimäki T;Letort S;Levin AM;Li G;Liang L;Loehr LR;London SJ;Loth DW;Manichaikul A;Marenholz I;Martinez FJ;Matheson MC;Mathias RA;Matsumoto K;Mbarek H;McArdle WL;Melbye M;Melén E;Meyers D;Michel S;Mohamdi H;Musk AW;Myers RA;Nieuwenhuis MAE;Noguchi E;O'Connor GT;Ogorodova LM;Palmer CD;Palotie A;Park JE;Pennell CE;Pershagen G;Polonikov A;Postma DS;Probst-Hensch N;Puzyrev VP;Raby BA;Raitakari OT;Ramasamy A;Rich SS;Robertson CF;Romieu I;Salam MT;Salomaa V;Schlünssen V;Scott R;Selivanova PA;Sigsgaard T;Simpson A;Siroux V;Smith LJ;Solodilova M;Standl M;Stefansson K;Strachan DP;Stricker BH;Takahashi A;Thompson PJ;Thorleifsson G;Thorsteinsdottir U;Tiesler CMT;Torgerson DG;Tsunoda T;Uitterlinden AG;van der Valk RJP;Vaysse A;Vedantam S;von Berg A;von Mutius E;Vonk JM;Waage J;Wareham NJ;Weiss ST;White WB;Wickman M;Widén E;Willemsen G;Williams LK;Wouters IM;Yang JJ;Zhao JH;Moffatt MF;Ober C;Nicolae DL
通讯作者：
Nicolae DL
DOI：
10.1164/rccm.201107-1317pp
发表时间：
2012-02-15
影响因子：
24.7
作者：
Jarjour, Nizar N.;Erzurum, Serpil C.;Busse, William W.
通讯作者：
Busse, William W.
影响因子：
3.5
作者：
Choi, Yong Jun;Song, Insun;Chung, Yoon-Sok
通讯作者：
Chung, Yoon-Sok
影响因子：
9.8
作者：
Ferreira, Manuel A. R.;Mathur, Riddhima;Almqvist, Catarina
通讯作者：
Almqvist, Catarina