A joint transcriptional regulatory network and protein activity inference analysis identifies clinically associated master regulators for biliary atresia.
A joint transcriptional regulatory network and protein activity inference analysis identifies clinically associated master regulators for biliary atresia.
复制标题
联合转录调节网络和蛋白质活性推断分析确定了胆道闭锁的临床相关主调节因子
DOI：
10.3389/fped.2022.1050326
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发表时间：
2022
影响因子：
2.6
通讯作者：
中科院分区：
文献类型：
--
作者：
胆道闭锁（BA）是新生儿的一种严重的胆道疾病.转录因子（Transcription Factors，TFs）是生物过程和疾病的主要调控因子，参与了BA的发病过程。然而，一个全球性的看法，TF及其如何链接到临床表现仍在探索。在这里，我们进行了联合转录调控网络和蛋白质活性推断分析，以调查转录因子在BA的活动。通过整合三个独立的人类BA肝脏转录组数据集，我们确定了22个常见的主调节器，14个激活和8个抑制TF。激活的TF的基因靶点在SMAD、NF-κ B和TGF-β的生物过程中富集，而抑制的TF的基因靶点与脂质代谢相关。挖掘TF的临床相关性，我们确定炎症，纤维化和生存相关的TF。特别地，ZNF 14预测不良存活和晚期肝纤维化。支持这一观察结果，ZNF 14与T辅助细胞，胆管细胞和肝星状细胞呈正相关。总之，我们的分析揭示了BA的关键临床相关主调节因子。
Biliary atresia (BA) is a devastating cholangiopathy in neonate. Transcription factors (TFs), a type of master regulators in biological processes and diseases, have been implicated in pathogenesis of BA. However, a global view of TFs and how they link to clinical presentations remain explored. Here, we perform a joint transcriptional regulatory network and protein activity inference analysis in order to investigate transcription factor activity in BA. By integration of three independent human BA liver transcriptome datasets, we identify 22 common master regulators, with 14 activated- and 8 repressed TFs. Gene targets of activated TFs are enriched in biological processes of SMAD, NF-kappaB and TGF-beta, while those of repressed TFs are related to lipid metabolism. Mining the clinical association of TFs, we identify inflammation-, fibrosis- and survival associated TFs. In particular, ZNF14 is predictive of poor survival and advanced live fibrosis. Supporting this observation, ZNF14 is positively correlated with T helper cells, cholangiocytes and hepatic stellate cells. In sum, our analysis reveals key clinically associated master regulators for BA.
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影响因子：
2.4
作者：
Iordanskaia, Tatiana;Hubal, Monica J.;Koeck, Emily;Rossi, Christopher;Schwarz, Kathleen;Nadler, Evan P.
通讯作者：
Nadler, Evan P.
影响因子：
17.1
作者：
Lorent K;Gong W;Koo KA;Waisbourd-Zinman O;Karjoo S;Zhao X;Sealy I;Kettleborough RN;Stemple DL;Windsor PA;Whittaker SJ;Porter JR;Wells RG;Pack M
通讯作者：
Pack M
影响因子：
30.8
作者：
Finucane HK;Reshef YA;Anttila V;Slowikowski K;Gusev A;Byrnes A;Gazal S;Loh PR;Lareau C;Shoresh N;Genovese G;Saunders A;Macosko E;Pollack S;Brainstorm Consortium;Perry JRB;Buenrostro JD;Bernstein BE;Raychaudhuri S;McCarroll S;Neale BM;Price AL
通讯作者：
Price AL
影响因子：
25
作者：
Brichta, Lars;Shin, William;Greengard, Paul
通讯作者：
Greengard, Paul
影响因子：
5.7
作者：
Iordanskaia, Tatiana;Malesevic, Miroslav;Nadler, Evan P.
通讯作者：
Nadler, Evan P.