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Research Paper|Volume 15, Issue 22|pp 13434—13451

Predicting the prognosis in patients with sepsis by an endoplasmic reticulum stress gene signature

Jian Liu1, Hao Wang1, Huimin Xiao1, Li Ji1, Yonghui Yao1, Chunshui Cao1, Yong Liu1, Liang Huang1
  • 1Department of Emergency, First Affiliated Hospital of Nanchang University, Nanchang 330006, China
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Received: June 26, 2023Accepted: October 11, 2023Published: November 25, 2023
https://doi.org/10.18632/aging.205252

Copyright: © 2023 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: Prognostic stratification of patients with sepsis is important for the development of individualized treatment strategies. Endoplasmic reticulum stress (ERS) plays a key role in sepsis. This study aimed to identify a set of genes related to ER stress to construct a predictive model for the prognosis of sepsis.

Methods: The transcriptomic and clinical data of 479 sepsis patients were obtained from GSE65682 and divided into a training set (n=288) and a validation set (n=191) at a ratio of 3:2. The external test set was GSE95233 (n=51). LASSO and Cox regression analyses were performed to establish a signature to predict the prognosis of patients with sepsis. Moreover, we developed a nomogram that included the risk signature and clinical features to predict survival probability.

Results: A prognostic signature was constructed with ten endoplasmic reticulum related genes (ADRB2, DHCR7, GABARAPL2, MAOA, MPO, PDZD8, QDPR, SCAP, TFRC, and TLR4) in the training set, which significantly divided patients with sepsis into high- and low-risk groups in terms of survival. This signature was validated using validation and external test sets. A nomogram based on the risk signature was constructed to quantitatively predict the prognosis of patients with sepsis.

Conclusions: We constructed an ERS signature as a novel prognostic marker for predicting survival in sepsis patients, which could be used to develop novel biomarkers for the diagnosis, treatment, and prognosis of sepsis and to provide new ideas and prospects for future clinical research.