TY - JOUR
T1 - Transcription factor activity inference in systemic lupus erythematosus
AU - Lopez-Dominguez, Raul
AU - Toro-Dominguez, Daniel
AU - Martorell-Marugan, Jordi
AU - Garcia-Moreno, Adrian
AU - Holland, Christian H.
AU - Saez-Rodriguez, Julio
AU - Goldman, Daniel
AU - Petri, Michelle A.
AU - Alarcon-Riquelme, Marta E.
AU - Carmona-Saez, Pedro
N1 - Funding Information:
Conflicts of Interest: The authors declare no conflict of interest. J.S.-R. has received funding from GSK and Sanofi and expects consultant fees from Travere Therapeutics
Funding Information:
Funding: This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No. 831434 (3TR). The JU receives support from the European Union’s Horizon 2020 research and innovation program and EFPIA.
Funding Information:
Acknowledgments: This work is part of the Raúl López-Domínguez’s PhD thesis. Raúl López-Domínguez is enrolled in the PhD program in Biomedicine at the University of Granada, Spain. The Hopkins Lupus Cohort is funded by NIH AR69572 and NIH RO-1 grant AR069572.
Publisher Copyright:
© 2021 by the authors.
PY - 2021/4
Y1 - 2021/4
N2 - Background: Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease with diverse clinical manifestations. Although most of the SLE-associated loci are located in regulatory regions, there is a lack of global information about transcription factor (TFs) activities, the mode of regulation of the TFs, or the cell or sample-specific regulatory circuits. The aim of this work is to decipher TFs implicated in SLE. Methods: In order to decipher regulatory mechanisms in SLE, we have inferred TF activities from transcriptomic data for almost all human TFs, defined clusters of SLE patients based on the estimated TF activities and analyzed the differential activity patterns among SLE and healthy samples in two different cohorts. The Transcription Factor activity matrix was used to stratify SLE patients and define sets of TFs with statistically significant differential activity among the disease and control samples. Results: TF activities were able to identify two main subgroups of patients characterized by distinct neutrophil-to-lymphocyte ratio (NLR), with consistent patterns in two independent datasets-one from pediatric patients and other from adults. Furthermore, after contrasting all subgroups of patients and controls, we obtained a significant and robust list of 14 TFs implicated in the dysregulation of SLE by different mechanisms and pathways. Among them, well-known regulators of SLE, such as STAT or IRF, were found, but others suggest new pathways that might have important roles in SLE. Conclusions: These results provide a foundation to comprehend the regulatory mechanism underlying SLE and the established regulatory factors behind SLE heterogeneity that could be potential therapeutic targets.
AB - Background: Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease with diverse clinical manifestations. Although most of the SLE-associated loci are located in regulatory regions, there is a lack of global information about transcription factor (TFs) activities, the mode of regulation of the TFs, or the cell or sample-specific regulatory circuits. The aim of this work is to decipher TFs implicated in SLE. Methods: In order to decipher regulatory mechanisms in SLE, we have inferred TF activities from transcriptomic data for almost all human TFs, defined clusters of SLE patients based on the estimated TF activities and analyzed the differential activity patterns among SLE and healthy samples in two different cohorts. The Transcription Factor activity matrix was used to stratify SLE patients and define sets of TFs with statistically significant differential activity among the disease and control samples. Results: TF activities were able to identify two main subgroups of patients characterized by distinct neutrophil-to-lymphocyte ratio (NLR), with consistent patterns in two independent datasets-one from pediatric patients and other from adults. Furthermore, after contrasting all subgroups of patients and controls, we obtained a significant and robust list of 14 TFs implicated in the dysregulation of SLE by different mechanisms and pathways. Among them, well-known regulators of SLE, such as STAT or IRF, were found, but others suggest new pathways that might have important roles in SLE. Conclusions: These results provide a foundation to comprehend the regulatory mechanism underlying SLE and the established regulatory factors behind SLE heterogeneity that could be potential therapeutic targets.
KW - Clustering analysis
KW - Disease classification
KW - Systemic lupus erythematosus
KW - Transcription factor activity inference
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U2 - 10.3390/life11040299
DO - 10.3390/life11040299
M3 - Article
C2 - 33915751
AN - SCOPUS:85104087130
SN - 0024-3019
VL - 11
JO - Life
JF - Life
IS - 4
M1 - 299
ER -