AUTHOR=Chen Zhen , Chen Rui , Ou Yangpeng , Lu Jianhai , Jiang Qianhua , Liu Genglong , Wang Liping , Liu Yayun , Zhou Zhujiang , Yang Ben , Zuo Liuer 

TITLE=Construction of an HLA Classifier for Early Diagnosis, Prognosis, and Recognition of Immunosuppression in Sepsis by Multiple Transcriptome Datasets

JOURNAL=Frontiers in Physiology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2022.870657

DOI=10.3389/fphys.2022.870657

ISSN=1664-042X

ABSTRACT=Background: 
The effects of HLA genes in sepsis is still not been comprehensively understood.
Methods: 
A systematical search was performed in Gene Expression Omnibus (GEO) and ArrayExpress databases from inception to September 10, 2021. Random forest (RF) and modified Lasso penalized regression were conducted to identify hub genes, thus constructed a prediction model, namely HLA classifier. ArrayExpress databases, as external validation, were utilized to evaluate its diagnostic, prognostic and predictive performance. Next, we systematically correlated the HLA classifier with immunological characteristics from multiple perspectives, such as immune-related cells infiltrating, pivotal molecular pathways, and cytokine expression. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to validate the expression level of HLA genes in clinical samples.
Results: 
A total of 9 datasets comprising 1251 patients were included. Based on RF and modified Lasso penalized regression, 5 HLA genes (B2M, HLA-DQA1, HLA-DPA1, TAP1, and TAP2) were identified as hub genes, which were subject to construct an HLA classifier. In the discovery cohort, HLA classifier exhibited superior diagnostic value (AUC=0.997), performed better in predicting mortality(AUC=0.716) than clinical characteristics or endotypes. Encouragingly, similar results were observed in the ArrayExpress databases. Additionally, immune infiltration analysis reveal that B cells, activated dendritic cell, NK cells, T helper cells, and infiltrating lymphocyte (IL) are significantly richer in HLA low-risk phenotypes, while Tregs and myeloid-derived suppressor cells (MDSC) are more abundant in HLA high-risk phenotypes. Subsequently, molecular pathways analysis uncover that cytokine cytokine receptor interaction (CCR), and antigen-presenting cell (APC) co-stimulation were significantly enriched in HLA low-risk endotypes. Finally, the expression levels of several cytokines (IL-10, IFNG, TNF) were significantly different between the HLA subgroups, and the ratio of IL-10/TNF was significantly positively correlated with HLA score in multi-transcriptome data. Results of qRT-PCR validated that higher expression level of B2M as well as lower expression level of HLA-DQA1, HLA-DPA1, TAP1, and TAP2 in sepsis samples compared to control sample.
Conclusion: 
Based on 5 HLA genes, a diagnostic and prognostic model, namely HLA classifier, was established, which is closely correlated with responses to hydrocortisone and immunosuppression status and might facilitate personalized counseling for specific therapy.