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Phage ImmunoPrecipitation sequencing (PhIP-Seq) in autoimmunity research: From high-resolution epitope mapping to multi-omics integration.

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Τίτλος: Phage ImmunoPrecipitation sequencing (PhIP-Seq) in autoimmunity research: From high-resolution epitope mapping to multi-omics integration.
Συγγραφείς: Yu R; Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China; Eight-year Medical Doctor Program, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China., Lu R; Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China; Department of Laboratory Medicine, Shenzhen Baoan Women's and Children's Hospital, Jinan University, Shenzhen, China., Xue C; Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China., Bai Y; Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China., Li M; Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China., Hu C; Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China. Electronic address: huchaojun818@qq.com.
Πηγή: Autoimmunity reviews [Autoimmun Rev] 2026 Aug; Vol. 25 (8), pp. 104094. Date of Electronic Publication: 2026 May 22.
Τύπος έκδοσης: Journal Article; Review
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 101128967 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-0183 (Electronic) Linking ISSN: 15689972 NLM ISO Abbreviation: Autoimmun Rev Subsets: MEDLINE
Imprint Name(s): Original Publication: Amsterdam ; New York : Elsevier, c2002-
Ιατρικοί όροι (MeSH): Epitope Mapping*/methods , Autoimmune Diseases*/immunology , Autoimmune Diseases*/diagnosis , Autoimmunity*/genetics , High-Throughput Nucleotide Sequencing*/methods , Immunoprecipitation*/methods, Autoantibodies/immunology ; Autoantigens/immunology ; Autoantigens/genetics ; Epitopes/immunology ; Humans ; Multiomics ; Animals ; Peptide Library ; Immunoinformatics
Περίληψη: Autoimmune diseases (AIDs) affect 5-10% of the global population, yet effective diagnosis and treatment remain challenging due to their complexity and heterogeneity. Autoantibodies serve as crucial biomarkers for disease classification and prognosis, making comprehensive autoantigen profiling essential for advancing our understanding of autoimmune pathogenesis. Phage ImmunoPrecipitation sequencing (PhIP-Seq) has emerged as a transformative high-throughput technology that combines phage display with next-generation sequencing to comprehensively profile antibody-antigen interactions. This review systematically examines PhIP-Seq's methodology, comparing it with conventional approaches including protein microarrays, immunoprecipitation-mass spectrometry, and traditional serological assays. We detail the experimental workflow encompassing library design, immunoprecipitation protocols, and computational analysis pipelines, while highlighting recent algorithmic advances including generalized Poisson models, Z-score methods, and machine learning approaches for hit determination. PhIP-Seq's applications in autoimmune diseases span autoantibody discovery; clinical model development for disease stratification; high-resolution epitope mapping enabling resolution at tens of amino acids; and longitudinal studies tracking disease progression. The technology's integration with other omics platforms and investigation of viral-autoimmune disease associations further demonstrates its versatility. While PhIP-Seq excels in linear epitope identification and high-throughput screening, limitations include inability to detect conformational epitopes, challenges with low-abundance antigens, and lack of post-translational modifications. This review discusses ongoing advancements in library design, methodological improvements, and data integration to address these issues and unlock PhIP-Seq's full potential in autoimmune research.
(Copyright © 2026 Elsevier B.V. All rights reserved.)
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributed Indexing: Keywords: Antibody repertoire; Autoimmune disease; Epitope spreading; Phage ImmunoPrecipitation sequencing (PhIP-Seq); Proteomics
Substance Nomenclature: 0 (Autoantibodies)
0 (Autoantigens)
0 (Epitopes)
0 (Peptide Library)
Entry Date(s): Date Created: 20260523 Date Completed: 20260708 Latest Revision: 20260708
Update Code: 20260709
DOI: 10.1016/j.autrev.2026.104094
PMID: 42176827
Βάση Δεδομένων: MEDLINE
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  Data: Phage ImmunoPrecipitation sequencing (PhIP-Seq) in autoimmunity research: From high-resolution epitope mapping to multi-omics integration.
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  Data: <searchLink fieldCode="AU" term="%22Yu+R%22">Yu R</searchLink>; Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China; Eight-year Medical Doctor Program, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Lu+R%22">Lu R</searchLink>; Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China; Department of Laboratory Medicine, Shenzhen Baoan Women's and Children's Hospital, Jinan University, Shenzhen, China.<br /><searchLink fieldCode="AU" term="%22Xue+C%22">Xue C</searchLink>; Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China.<br /><searchLink fieldCode="AU" term="%22Bai+Y%22">Bai Y</searchLink>; Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China.<br /><searchLink fieldCode="AU" term="%22Li+M%22">Li M</searchLink>; Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China.<br /><searchLink fieldCode="AU" term="%22Hu+C%22">Hu C</searchLink>; Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China. Electronic address: huchaojun818@qq.com.
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  Data: Autoimmune diseases (AIDs) affect 5-10% of the global population, yet effective diagnosis and treatment remain challenging due to their complexity and heterogeneity. Autoantibodies serve as crucial biomarkers for disease classification and prognosis, making comprehensive autoantigen profiling essential for advancing our understanding of autoimmune pathogenesis. Phage ImmunoPrecipitation sequencing (PhIP-Seq) has emerged as a transformative high-throughput technology that combines phage display with next-generation sequencing to comprehensively profile antibody-antigen interactions. This review systematically examines PhIP-Seq's methodology, comparing it with conventional approaches including protein microarrays, immunoprecipitation-mass spectrometry, and traditional serological assays. We detail the experimental workflow encompassing library design, immunoprecipitation protocols, and computational analysis pipelines, while highlighting recent algorithmic advances including generalized Poisson models, Z-score methods, and machine learning approaches for hit determination. PhIP-Seq's applications in autoimmune diseases span autoantibody discovery; clinical model development for disease stratification; high-resolution epitope mapping enabling resolution at tens of amino acids; and longitudinal studies tracking disease progression. The technology's integration with other omics platforms and investigation of viral-autoimmune disease associations further demonstrates its versatility. While PhIP-Seq excels in linear epitope identification and high-throughput screening, limitations include inability to detect conformational epitopes, challenges with low-abundance antigens, and lack of post-translational modifications. This review discusses ongoing advancements in library design, methodological improvements, and data integration to address these issues and unlock PhIP-Seq's full potential in autoimmune research.<br /> (Copyright © 2026 Elsevier B.V. All rights reserved.)
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  Data: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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