PMID- 35685286
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20220716
IS  - 1664-042X (Print)
IS  - 1664-042X (Electronic)
IS  - 1664-042X (Linking)
VI  - 13
DP  - 2022
TI  - Construction of an HLA Classifier for Early Diagnosis, Prognosis, and Recognition 
      of Immunosuppression in Sepsis by Multiple Transcriptome Datasets.
PG  - 870657
LID - 10.3389/fphys.2022.870657 [doi]
LID - 870657
AB  - Background: Sepsis is a clinical syndrome, due to a dysregulated inflammatory 
      response to infection. Accumulating evidence shows that human leukocyte antigen 
      (HLA) genes play a key role in the immune responses to sepsis. Nevertheless, the 
      effects of HLA genes in sepsis have still not been comprehensively understood. 
      Methods: A systematical search was performed in the Gene Expression Omnibus (GEO) 
      and ArrayExpress databases from inception to 10 September 2021. Random forest 
      (RF) and modified Lasso penalized regression were conducted to identify hub genes 
      in multi-transcriptome data, thus we constructed a prediction model, namely the 
      HLA classifier. ArrayExpress databases, as external validation, were utilized to 
      evaluate its diagnostic, prognostic, and predictive performance. Immune cell 
      infiltration score was calculated via CIBERSORTx tools and single-sample gene set 
      enrichment analysis (ssGSEA). Gene set variation analysis (GSVA) and ssGSEA were 
      conducted to determine the pathways that are significantly enriched in different 
      subgroups. Next, we systematically correlated the HLA classifier with 
      immunological characteristics from multiple perspectives, such as immune-related 
      cell infiltration, 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 nine datasets comprising 1,251 patients were included. Based on RF and 
      modified Lasso penalized regression in multi-transcriptome datasets, five HLA 
      genes (B2M, HLA-DQA1, HLA-DPA1, TAP1, and TAP2) were identified as hub genes, 
      which were used to construct an HLA classifier. In the discovery cohort, the HLA 
      classifier exhibited superior diagnostic value (AUC = 0.997) and performed better 
      in predicting mortality (AUC = 0.716) than clinical characteristics or endotypes. 
      Encouragingly, similar results were observed in the ArrayExpress databases. In 
      the E-MTAB-7581 dataset, the use of hydrocortisone in the HLA high-risk subgroup 
      (OR: 2.84, 95% CI 1.07-7.57, p = 0.037) was associated with increased risk of 
      mortality, but not in the HLA low-risk subgroup. Additionally, immune 
      infiltration analysis by CIBERSORTx and ssGSEA revealed that B cells, activated 
      dendritic cells, NK cells, T helper cells, and infiltrating lymphocytes (ILs) 
      were significantly richer in HLA low-risk phenotypes, while Tregs and 
      myeloid-derived suppressor cells (MDSCs) were more abundant in HLA high-risk 
      phenotypes. The HLA classifier was significantly negatively correlated with B 
      cells, activated dendritic cells, NK cells, T helper cells, and ILs, yet was 
      significantly positively correlated with Tregs and MDSCs. Subsequently, molecular 
      pathways analysis uncovered that cytokine-cytokine receptor (CCR) interaction, 
      human leukocyte antigen (HLA), and antigen-presenting cell (APC) co-stimulation 
      were significantly enriched in HLA low-risk endotypes, which was significantly 
      negatively correlated with the HLA classifier in multi-transcriptome data. 
      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 the 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 five HLA genes, a diagnostic and 
      prognostic model, namely the HLA classifier, was established, which is closely 
      correlated with responses to hydrocortisone and immunosuppression status and 
      might facilitate personalized counseling for specific therapy.
CI  - Copyright (c) 2022 Chen, Chen, Ou, Lu, Jiang, Liu, Wang, Liu, Zhou, Yang and Zuo.
FAU - Chen, Zhen
AU  - Chen Z
AD  - Department of Intensive Care Unit, Shunde Hospital, Southern Medical University 
      (The First People's Hospital of Shunde), Foshan, China.
FAU - Chen, Rui
AU  - Chen R
AD  - Department of Medical Intensive Care Unit, General Hospital of Southern Theater 
      Command, Guangzhou, China.
FAU - Ou, Yangpeng
AU  - Ou Y
AD  - Department of Oncology, Huizhou Third People's Hospital, Guangzhou Medical 
      University, Huizhou, China.
FAU - Lu, Jianhai
AU  - Lu J
AD  - Department of Intensive Care Unit, Shunde Hospital, Southern Medical University 
      (The First People's Hospital of Shunde), Foshan, China.
FAU - Jiang, Qianhua
AU  - Jiang Q
AD  - Department of Intensive Care Unit, Shunde Hospital, Southern Medical University 
      (The First People's Hospital of Shunde), Foshan, China.
FAU - Liu, Genglong
AU  - Liu G
AD  - Department of Pathology, The Third Affiliated Hospital of Guangdong Medical 
      University (Longjiang Hospital of Shunde District), Foshan, China.
FAU - Wang, Liping
AU  - Wang L
AD  - Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated 
      Hospital of Hainan Medical University, Haikou, China.
FAU - Liu, Yayun
AU  - Liu Y
AD  - Department of Endocrinology, GuiYang Huaxi District People's Hospital, Guiyang, 
      China.
FAU - Zhou, Zhujiang
AU  - Zhou Z
AD  - Department of Intensive Care Unit, Shunde Hospital, Southern Medical University 
      (The First People's Hospital of Shunde), Foshan, China.
FAU - Yang, Ben
AU  - Yang B
AD  - Department of Burn Surgery, Huizhou Municipal Central Hospital, Huizhou, China.
FAU - Zuo, Liuer
AU  - Zuo L
AD  - Department of Intensive Care Unit, Shunde Hospital, Southern Medical University 
      (The First People's Hospital of Shunde), Foshan, China.
LA  - eng
PT  - Journal Article
DEP - 20220524
PL  - Switzerland
TA  - Front Physiol
JT  - Frontiers in physiology
JID - 101549006
PMC - PMC9171028
OTO - NOTNLM
OT  - HLA genes
OT  - immune infiltration
OT  - immunosuppression
OT  - model
OT  - sepsis
COIS- The authors declare that the research was conducted in the absence of any 
      commercial or financial relationships that could be construed as a potential 
      conflict of interest.
EDAT- 2022/06/11 06:00
MHDA- 2022/06/11 06:01
PMCR- 2022/05/24
CRDT- 2022/06/10 02:28
PHST- 2022/02/22 00:00 [received]
PHST- 2022/04/18 00:00 [accepted]
PHST- 2022/06/10 02:28 [entrez]
PHST- 2022/06/11 06:00 [pubmed]
PHST- 2022/06/11 06:01 [medline]
PHST- 2022/05/24 00:00 [pmc-release]
AID - 870657 [pii]
AID - 10.3389/fphys.2022.870657 [doi]
PST - epublish
SO  - Front Physiol. 2022 May 24;13:870657. doi: 10.3389/fphys.2022.870657. eCollection 
      2022.