Integrating bioinformatic resources to identify characteristics of rheumatoid arthritis-related usual interstitial pneumonia.
Integrating bioinformatic resources to identify characteristics of rheumatoid arthritis-related usual interstitial pneumonia.
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DOI：
10.1186/s12864-023-09548-2
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发表时间：
2023-08-10
期刊：
影响因子：
4.4
通讯作者：
中科院分区：
文献类型：
--
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类风湿关节炎(RA)常伴有一种常见的关节外表现，称为类风湿相关性普通性间质性肺炎(RA-UIP)，预后不良。然而，其机制仍不清楚。为了确定可能的机制，我们进行了基于高通量测序的基因表达总括数据库(GEO)的生物信息学分析。加权基因共表达网络分析(WGCNA)分析确定了2个RA阳性相关模块和4个特发性肺纤维化(IPF)阳性相关模块。共获得553个重叠的差异表达基因(DEG)，其中144个在上述模块中被进一步分析。“氧化磷酸化”的生物学过程被发现与RA和IPF最为相关。此外，还筛选出了498个RA-UIP肺组织中上调表达的基因，其中3个与免疫调节密切相关。免疫渗出分析显示RA-UIP与IPF-UIP相比，其外周免疫细胞在肺组织中的分布具有一定的特征性。这些结果描述了RA-UIP的复杂分子和功能格局，有助于阐明RA-UIP的分子病理机制，并为未来寻找新的RA-UIP的生物标志物和治疗靶点奠定基础。网上版载有补充材料，可在10.1186/s12864-023-09548-2查阅。
Rheumatoid arthritis (RA) is often accompanied by a common extra-articular manifestation known as RA-related usual interstitial pneumonia (RA-UIP), which is associated with a poor prognosis. However, the mechanism remains unclear. To identify potential mechanisms, we conducted bioinformatics analysis based on high-throughput sequencing of the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) analysis identified 2 RA-positive related modules and 4 idiopathic pulmonary fibrosis (IPF)-positive related modules. A total of 553 overlapped differentially expressed genes (DEG) were obtained, of which 144 in the above modules were further analyzed. The biological process of “oxidative phosphorylation” was found to be the most relevant with both RA and IPF. Additionally, 498 up-regulated genes in lung tissues of RA-UIP were screened out and enriched by 7 clusters, of which 3 were closely related to immune regulation. The analysis of immune infiltration showed a characteristic distribution of peripheral immune cells in RA-UIP, compared with IPF-UIP in lung tissues. These results describe the complex molecular and functional landscape of RA-UIP, which will help illustrate the molecular pathological mechanism of RA-UIP and identify new biomarkers and therapeutic targets for RA-UIP in the future. The online version contains supplementary material available at 10.1186/s12864-023-09548-2.
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WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
Jvenn：交互式Venn图观看器。
影响因子：
3
作者：
Bardou P;Mariette J;Escudié F;Djemiel C;Klopp C
通讯作者：
Klopp C
DOI：
10.1056/nejmoa1801562
发表时间：
2018-12-06
期刊：
The New England journal of medicine
影响因子：
--
作者：
Juge PA;Lee JS;Ebstein E;Furukawa H;Dobrinskikh E;Gazal S;Kannengiesser C;Ottaviani S;Oka S;Tohma S;Tsuchiya N;Rojas-Serrano J;González-Pérez MI;Mejía M;Buendía-Roldán I;Falfán-Valencia R;Ambrocio-Ortiz E;Manali E;Papiris SA;Karageorgas T;Boumpas D;Antoniou K;van Moorsel CHM;van der Vis J;de Man YA;Grutters JC;Wang Y;Borie R;Wemeau-Stervinou L;Wallaert B;Flipo RM;Nunes H;Valeyre D;Saidenberg-Kermanac'h N;Boissier MC;Marchand-Adam S;Frazier A;Richette P;Allanore Y;Sibilia J;Dromer C;Richez C;Schaeverbeke T;Lioté H;Thabut G;Nathan N;Amselem S;Soubrier M;Cottin V;Clément A;Deane K;Walts AD;Fingerlin T;Fischer A;Ryu JH;Matteson EL;Niewold TB;Assayag D;Gross A;Wolters P;Schwarz MI;Holers M;Solomon JJ;Doyle T;Rosas IO;Blauwendraat C;Nalls MA;Debray MP;Boileau C;Crestani B;Schwartz DA;Dieudé P
通讯作者：
Dieudé P
影响因子：
5.5
作者：
Norton, Sam;Koduri, Gouri;Young, Adam
通讯作者：
Young, Adam
DOI：
10.1093/bioinformatics/btp101
发表时间：
2009-04-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Bindea G;Mlecnik B;Hackl H;Charoentong P;Tosolini M;Kirilovsky A;Fridman WH;Pagès F;Trajanoski Z;Galon J
通讯作者：
Galon J