Screening epitope peptides based on a phage-displayed random peptide and peptide microarrays to contribute to improving the diagnostic efficiency of systemic lupus erythematosus.

Antigen epitope polypeptide Biomarker Peptide array Phage display peptide library technology Systemic lupus erythematosus

Journal

Immunology letters
ISSN: 1879-0542
Titre abrégé: Immunol Lett
Pays: Netherlands
ID NLM: 7910006

Informations de publication

Date de publication:
07 2023
Historique:
received: 08 01 2023
revised: 19 05 2023
accepted: 22 05 2023
medline: 13 6 2023
pubmed: 30 5 2023
entrez: 29 5 2023
Statut: ppublish

Résumé

Systemic lupus erythematosus (SLE) is one of the most common autoimmune diseases in China. At present, there are hundreds of autoantibodies in SLE patients; however, only a dozen of the autoantibodies can be routinely detected, and the available diagnostic antibodies are not sufficient for diagnosis or differential diagnosis of SLE patients with atypical clinical manifestations or other autoimmune diseases. Therefore, it is necessary to find new diagnostic markers to improve the diagnostic effect of SLE. The displayed random peptide library and peptide microarray were combined to identify SLE-related epitope peptides. A case-control design was used. The IgG antibodies in the sera from SLE patients, healthy controls, and other autoimmune disease controls underwent a reaction with the phage-display random peptide library, respectively. Selected epitope peptides were used to construct a peptide chip. A total of 644 serum samples (including 296 SLE patients, 168 disease controls, and 180 healthy controls) were used for further screening and verification. Peptides with an area under the curve (AUC) > 0.650 were further verified by ELISA. Finally, 500 serum samples (including 200 SLE patients, 150 disease controls, and 150 healthy controls) were used to verify and evaluate the diagnostic and differential diagnostic efficacy of the selected peptides. After the previous screening, five epitope peptides (SLE_P19, SLE_P20, SLE_P27, SLE_P28, and SLE_P29) may have potential as SLE diagnostic markers. Additionally, SLE_P27 was superior to the other four peptides in the diagnosis and differential diagnosis of SLE and rheumatoid arthritis (RA). The AUC of SLE_P27 was 0.938, the sensitivity was 76.00%, the specificity was 92.70%, the positive likelihood ratio was 10.411, the negative likelihood ratio was 0.259, and the accuracy was 84.40%. The diagnostic efficacy of SLE can be increased by combining the five selected peptides with the anti-double stranded DNA antibody (anti-dsDNA) and anti-Smith antibodies (anti-Sm). In this study, we identified five peptides that may serve as potential biomarkers for SLE diagnosis using the strategy of combining the displayed random peptide library with the peptide microarray. The combination of selected peptides and existing autoantibodies can significantly improve the diagnostic efficiency. These specific peptides are expected to be new diagnostic markers for SLE.

Sections du résumé

BACKGROUND
Systemic lupus erythematosus (SLE) is one of the most common autoimmune diseases in China. At present, there are hundreds of autoantibodies in SLE patients; however, only a dozen of the autoantibodies can be routinely detected, and the available diagnostic antibodies are not sufficient for diagnosis or differential diagnosis of SLE patients with atypical clinical manifestations or other autoimmune diseases. Therefore, it is necessary to find new diagnostic markers to improve the diagnostic effect of SLE.
METHODS
The displayed random peptide library and peptide microarray were combined to identify SLE-related epitope peptides. A case-control design was used. The IgG antibodies in the sera from SLE patients, healthy controls, and other autoimmune disease controls underwent a reaction with the phage-display random peptide library, respectively. Selected epitope peptides were used to construct a peptide chip. A total of 644 serum samples (including 296 SLE patients, 168 disease controls, and 180 healthy controls) were used for further screening and verification. Peptides with an area under the curve (AUC) > 0.650 were further verified by ELISA. Finally, 500 serum samples (including 200 SLE patients, 150 disease controls, and 150 healthy controls) were used to verify and evaluate the diagnostic and differential diagnostic efficacy of the selected peptides.
RESULTS
After the previous screening, five epitope peptides (SLE_P19, SLE_P20, SLE_P27, SLE_P28, and SLE_P29) may have potential as SLE diagnostic markers. Additionally, SLE_P27 was superior to the other four peptides in the diagnosis and differential diagnosis of SLE and rheumatoid arthritis (RA). The AUC of SLE_P27 was 0.938, the sensitivity was 76.00%, the specificity was 92.70%, the positive likelihood ratio was 10.411, the negative likelihood ratio was 0.259, and the accuracy was 84.40%. The diagnostic efficacy of SLE can be increased by combining the five selected peptides with the anti-double stranded DNA antibody (anti-dsDNA) and anti-Smith antibodies (anti-Sm).
CONCLUSIONS
In this study, we identified five peptides that may serve as potential biomarkers for SLE diagnosis using the strategy of combining the displayed random peptide library with the peptide microarray. The combination of selected peptides and existing autoantibodies can significantly improve the diagnostic efficiency. These specific peptides are expected to be new diagnostic markers for SLE.

Identifiants

pubmed: 37247788
pii: S0165-2478(23)00085-8
doi: 10.1016/j.imlet.2023.05.008
pii:
doi:

Substances chimiques

Epitopes 0
Peptide Library 0
Peptides 0
Autoantibodies 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

30-36

Informations de copyright

Copyright © 2023 European Federation of Immunological Societies. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no conflicts of interest.

Auteurs

Xin Li (X)

Laboratory Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.

Hong-Xia Wang (HX)

Laboratory Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.

Xiaofeng Yin (X)

Laboratory Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.

Xueheng Li (X)

Laboratory Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.

Haixia Li (H)

Laboratory Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.

Xiaohe Zhang (X)

Laboratory Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.

Zheng Wang (Z)

Department of Clinical Laboratory, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Yu-Rong Qiu (YR)

Laboratory Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China; Guangzhou Huayin Medical laboratory center. LTD, Guangzhou, China. Electronic address: qyr@smu.edu.cn.

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Classifications MeSH