Combined Salivary Proteome Profiling and Machine Learning Analysis Provides Insight into Molecular Signature for Autoimmune Liver Diseases Classification

Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases that target the liver and have a wide spectrum of presentation. A global overview of quantitative variations on the salivary proteome in presence of these two pathologies is investigated in this study. The...

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Published inInternational journal of molecular sciences Vol. 24; no. 15; p. 12207
Main Authors Guadalupi, Giulia, Contini, Cristina, Iavarone, Federica, Castagnola, Massimo, Messana, Irene, Faa, Gavino, Onali, Simona, Chessa, Luchino, Vitorino, Rui, Amado, Francisco, Diaz, Giacomo, Manconi, Barbara, Cabras, Tiziana, Olianas, Alessandra
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 30.07.2023
MDPI
Subjects
Acids
Antibodies
Antigens
Autoimmune Diseases
Bile ducts
Biopsy
Cholangitis
Comparative analysis
Exocrine glands
Hepatitis, Autoimmune
Humans
Immune system
Ions
Liver cirrhosis
Liver Cirrhosis, Biliary
Liver Diseases
Machine learning
Males
Mass spectrometry
Medical research
Medicine, Experimental
Peptides
Proteins
Proteome
Proteomics
Rheumatoid arthritis
Scientific equipment and supplies industry
Scientific imaging
Smooth muscle
Somatotropin
United States
saliva
Cofilin-1
hornerin
autoimmune hepatitis
autoimmune liver diseases
bottom-up proteomics
mass spectrometry
random forest
primary biliary cholangitis
Online AccessGet full text
ISSN1422-0067
1661-6596
1422-0067
DOI10.3390/ijms241512207

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Abstract Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases that target the liver and have a wide spectrum of presentation. A global overview of quantitative variations on the salivary proteome in presence of these two pathologies is investigated in this study. The acid-insoluble salivary fraction of AIH and PBC patients, and healthy controls (HCs), was analyzed using a gel-based bottom-up proteomic approach combined with a robust machine learning statistical analysis of the dataset. The abundance of Arginase, Junction plakoglobin, Desmoplakin, Hexokinase-3 and Desmocollin-1 decreased, while that of BPI fold-containing family A member 2 increased in AIHp compared to HCs; the abundance of Gelsolin, CD14, Tumor-associated calcium signal transducer 2, Clusterin, Heterogeneous nuclear ribonucleoproteins A2/B1, Cofilin-1 and BPI fold-containing family B member 2 increased in PBCp compared to HCs. The abundance of Hornerin decreased in both AIHp and PBCp with respect to HCs and provided an area under the ROC curve of 0.939. Machine learning analysis confirmed the feasibility of the salivary proteome to discriminate groups of subjects based on AIH or PBC occurrence as previously suggested by our group. The topology-based functional enrichment analysis performed on these potential salivary biomarkers highlights an enrichment of terms mostly related to the immune system, but also with a strong involvement in liver fibrosis process and with antimicrobial activity.
AbstractList Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases that target the liver and have a wide spectrum of presentation. A global overview of quantitative variations on the salivary proteome in presence of these two pathologies is investigated in this study. The acid-insoluble salivary fraction of AIH and PBC patients, and healthy controls (HCs), was analyzed using a gel-based bottom-up proteomic approach combined with a robust machine learning statistical analysis of the dataset. The abundance of Arginase, Junction plakoglobin, Desmoplakin, Hexokinase-3 and Desmocollin-1 decreased, while that of BPI fold-containing family A member 2 increased in AIHp compared to HCs; the abundance of Gelsolin, CD14, Tumor-associated calcium signal transducer 2, Clusterin, Heterogeneous nuclear ribonucleoproteins A2/B1, Cofilin-1 and BPI fold-containing family B member 2 increased in PBCp compared to HCs. The abundance of Hornerin decreased in both AIHp and PBCp with respect to HCs and provided an area under the ROC curve of 0.939. Machine learning analysis confirmed the feasibility of the salivary proteome to discriminate groups of subjects based on AIH or PBC occurrence as previously suggested by our group. The topology-based functional enrichment analysis performed on these potential salivary biomarkers highlights an enrichment of terms mostly related to the immune system, but also with a strong involvement in liver fibrosis process and with antimicrobial activity.Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases that target the liver and have a wide spectrum of presentation. A global overview of quantitative variations on the salivary proteome in presence of these two pathologies is investigated in this study. The acid-insoluble salivary fraction of AIH and PBC patients, and healthy controls (HCs), was analyzed using a gel-based bottom-up proteomic approach combined with a robust machine learning statistical analysis of the dataset. The abundance of Arginase, Junction plakoglobin, Desmoplakin, Hexokinase-3 and Desmocollin-1 decreased, while that of BPI fold-containing family A member 2 increased in AIHp compared to HCs; the abundance of Gelsolin, CD14, Tumor-associated calcium signal transducer 2, Clusterin, Heterogeneous nuclear ribonucleoproteins A2/B1, Cofilin-1 and BPI fold-containing family B member 2 increased in PBCp compared to HCs. The abundance of Hornerin decreased in both AIHp and PBCp with respect to HCs and provided an area under the ROC curve of 0.939. Machine learning analysis confirmed the feasibility of the salivary proteome to discriminate groups of subjects based on AIH or PBC occurrence as previously suggested by our group. The topology-based functional enrichment analysis performed on these potential salivary biomarkers highlights an enrichment of terms mostly related to the immune system, but also with a strong involvement in liver fibrosis process and with antimicrobial activity.
Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases that target the liver and have a wide spectrum of presentation. A global overview of quantitative variations on the salivary proteome in presence of these two pathologies is investigated in this study. The acid-insoluble salivary fraction of AIH and PBC patients, and healthy controls (HCs), was analyzed using a gel-based bottom-up proteomic approach combined with a robust machine learning statistical analysis of the dataset. The abundance of Arginase, Junction plakoglobin, Desmoplakin, Hexokinase-3 and Desmocollin-1 decreased, while that of BPI fold-containing family A member 2 increased in AIHp compared to HCs; the abundance of Gelsolin, CD14, Tumor-associated calcium signal transducer 2, Clusterin, Heterogeneous nuclear ribonucleoproteins A2/B1, Cofilin-1 and BPI fold-containing family B member 2 increased in PBCp compared to HCs. The abundance of Hornerin decreased in both AIHp and PBCp with respect to HCs and provided an area under the ROC curve of 0.939. Machine learning analysis confirmed the feasibility of the salivary proteome to discriminate groups of subjects based on AIH or PBC occurrence as previously suggested by our group. The topology-based functional enrichment analysis performed on these potential salivary biomarkers highlights an enrichment of terms mostly related to the immune system, but also with a strong involvement in liver fibrosis process and with antimicrobial activity.
Audience Academic
Author Chessa, Luchino
Messana, Irene
Olianas, Alessandra
Castagnola, Massimo
Manconi, Barbara
Guadalupi, Giulia
Vitorino, Rui
Onali, Simona
Amado, Francisco
Contini, Cristina
Faa, Gavino
Cabras, Tiziana
Iavarone, Federica
Diaz, Giacomo
AuthorAffiliation 2 Fondazione Policlinico Universitario IRCCS “A. Gemelli”, 00168 Rome, Italy; federica.iavarone@unicatt.it
7 Liver Unit, University Hospital of Cagliari, 09124 Cagliari, Italy; simona.onali@yahoo.it (S.O.); luchinochessa@unica.it (L.C.)
9 UnIC@RISE, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, 4200-319 Porto, Portugal
4 Laboratorio di Proteomica, Centro Europeo di Ricerca sul Cervello, IRCCS Fondazione Santa Lucia, 00168 Rome, Italy; maxcastagnola@outlook.it
10 LAQV/REQUIMTE, Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal; famado@ua.pt
8 iBiMED, Department of Medical Science, University of Aveiro, 3810-193 Aveiro, Portugal; rvitorino@ua.pt
1 Dipartimento di Scienze della Vita e dell’Ambiente, Università di Cagliari, 09124 Cagliari, Italy; giulia.guadalupi@unica.it (G.G.); cristina.contini93@unica.it (C.C.); tcabras@unica.it (T.C.); olianas@unica.it (A.O.)
3 Dipartimento di Scienze Biotecnologiche di Base, Cliniche Intensivolog
AuthorAffiliation_xml – name: 8 iBiMED, Department of Medical Science, University of Aveiro, 3810-193 Aveiro, Portugal; rvitorino@ua.pt
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Keywords saliva
Cofilin-1
hornerin
autoimmune hepatitis
autoimmune liver diseases
bottom-up proteomics
mass spectrometry
random forest
primary biliary cholangitis
Language English
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SSID ssj0023259
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Snippet Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases that target the liver and have a wide spectrum of presentation....
SourceID pubmedcentral
proquest
gale
pubmed
crossref
SourceType Open Access Repository
Aggregation Database
Index Database
Enrichment Source
StartPage 12207
SubjectTerms Acids
Antibodies
Antigens
Autoimmune Diseases
Bile ducts
Biopsy
Cholangitis
Comparative analysis
Exocrine glands
Hepatitis, Autoimmune
Humans
Immune system
Ions
Liver cirrhosis
Liver Cirrhosis, Biliary
Liver Diseases
Machine learning
Males
Mass spectrometry
Medical research
Medicine, Experimental
Peptides
Proteins
Proteome
Proteomics
Rheumatoid arthritis
Scientific equipment and supplies industry
Scientific imaging
Smooth muscle
Somatotropin
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Title Combined Salivary Proteome Profiling and Machine Learning Analysis Provides Insight into Molecular Signature for Autoimmune Liver Diseases Classification
URI https://www.ncbi.nlm.nih.gov/pubmed/37569584
https://www.proquest.com/docview/2849036814
https://www.proquest.com/docview/2850316590
https://pubmed.ncbi.nlm.nih.gov/PMC10418803
Volume 24
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