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Functional Analysis of Autoantibody Signatures in Rheumatoid Arthritis

For the identification of antigenic protein biomarkers for rheumatoid arthritis (RA), we conducted IgG profiling on high density protein microarrays. Plasma IgG of 96 human samples (healthy controls, osteoarthritis, seropositive and seronegative RA, n = 24 each) and time-series plasma of a pristane-...

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Autores principales: Milchram, Lisa, Fischer, Anita, Huber, Jasmin, Soldo, Regina, Sieghart, Daniela, Vierlinger, Klemens, Blüml, Stephan, Steiner, Günter, Weinhäusel, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8876797/
https://www.ncbi.nlm.nih.gov/pubmed/35209238
http://dx.doi.org/10.3390/molecules27041452
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author Milchram, Lisa
Fischer, Anita
Huber, Jasmin
Soldo, Regina
Sieghart, Daniela
Vierlinger, Klemens
Blüml, Stephan
Steiner, Günter
Weinhäusel, Andreas
author_facet Milchram, Lisa
Fischer, Anita
Huber, Jasmin
Soldo, Regina
Sieghart, Daniela
Vierlinger, Klemens
Blüml, Stephan
Steiner, Günter
Weinhäusel, Andreas
author_sort Milchram, Lisa
collection PubMed
description For the identification of antigenic protein biomarkers for rheumatoid arthritis (RA), we conducted IgG profiling on high density protein microarrays. Plasma IgG of 96 human samples (healthy controls, osteoarthritis, seropositive and seronegative RA, n = 24 each) and time-series plasma of a pristane-induced arthritis (PIA) rat model (n = 24 total) were probed on AIT’s 16k protein microarray. To investigate the analogy of underlying disease pathways, differential reactivity analysis was conducted. A total of n = 602 differentially reactive antigens (DIRAGs) at a significance cutoff of p < 0.05 were identified between seropositive and seronegative RA for the human samples. Correlation with the clinical disease activity index revealed an inverse correlation of antibodies against self-proteins found in pathways relevant for antigen presentation and immune regulation. The PIA model showed n = 1291 significant DIRAGs within acute disease. Significant DIRAGs for (I) seropositive, (II) seronegative and (III) PIA were subjected to the Reactome pathway browser which also revealed pathways relevant for antigen presentation and immune regulation; of these, seven overlapping pathways had high significance. We therefore conclude that the PIA model reflects the biological similarities of the disease pathogenesis. Our data show that protein array analysis can elucidate biological differences and pathways relevant in disease as well be a useful additional layer of omics information.
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spelling pubmed-88767972022-02-26 Functional Analysis of Autoantibody Signatures in Rheumatoid Arthritis Milchram, Lisa Fischer, Anita Huber, Jasmin Soldo, Regina Sieghart, Daniela Vierlinger, Klemens Blüml, Stephan Steiner, Günter Weinhäusel, Andreas Molecules Article For the identification of antigenic protein biomarkers for rheumatoid arthritis (RA), we conducted IgG profiling on high density protein microarrays. Plasma IgG of 96 human samples (healthy controls, osteoarthritis, seropositive and seronegative RA, n = 24 each) and time-series plasma of a pristane-induced arthritis (PIA) rat model (n = 24 total) were probed on AIT’s 16k protein microarray. To investigate the analogy of underlying disease pathways, differential reactivity analysis was conducted. A total of n = 602 differentially reactive antigens (DIRAGs) at a significance cutoff of p < 0.05 were identified between seropositive and seronegative RA for the human samples. Correlation with the clinical disease activity index revealed an inverse correlation of antibodies against self-proteins found in pathways relevant for antigen presentation and immune regulation. The PIA model showed n = 1291 significant DIRAGs within acute disease. Significant DIRAGs for (I) seropositive, (II) seronegative and (III) PIA were subjected to the Reactome pathway browser which also revealed pathways relevant for antigen presentation and immune regulation; of these, seven overlapping pathways had high significance. We therefore conclude that the PIA model reflects the biological similarities of the disease pathogenesis. Our data show that protein array analysis can elucidate biological differences and pathways relevant in disease as well be a useful additional layer of omics information. MDPI 2022-02-21 /pmc/articles/PMC8876797/ /pubmed/35209238 http://dx.doi.org/10.3390/molecules27041452 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Milchram, Lisa
Fischer, Anita
Huber, Jasmin
Soldo, Regina
Sieghart, Daniela
Vierlinger, Klemens
Blüml, Stephan
Steiner, Günter
Weinhäusel, Andreas
Functional Analysis of Autoantibody Signatures in Rheumatoid Arthritis
title Functional Analysis of Autoantibody Signatures in Rheumatoid Arthritis
title_full Functional Analysis of Autoantibody Signatures in Rheumatoid Arthritis
title_fullStr Functional Analysis of Autoantibody Signatures in Rheumatoid Arthritis
title_full_unstemmed Functional Analysis of Autoantibody Signatures in Rheumatoid Arthritis
title_short Functional Analysis of Autoantibody Signatures in Rheumatoid Arthritis
title_sort functional analysis of autoantibody signatures in rheumatoid arthritis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8876797/
https://www.ncbi.nlm.nih.gov/pubmed/35209238
http://dx.doi.org/10.3390/molecules27041452
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