Cristina Razquin, Joaquín Fernandez-Irigoyen, María Teresa Barrio-López, Begoña López, Susana Ravassa, Pablo Ramos, Rosa Macías-Ruíz, Alicia Ibañez Criado, Enrique Santamaría, Leticia Goni, Eduardo Castellanos, Jose Luis Ibañez Criado, Luis Tercedor, Ignacio García-Bolao, Miguel A Martínez-González, Jesús Almendral, Miguel Ruiz-Canela
{"title":"Proteomics and Recurrence of Atrial Fibrillation: A Pilot Study Nested in the PREDIMAR Trial.","authors":"Cristina Razquin, Joaquín Fernandez-Irigoyen, María Teresa Barrio-López, Begoña López, Susana Ravassa, Pablo Ramos, Rosa Macías-Ruíz, Alicia Ibañez Criado, Enrique Santamaría, Leticia Goni, Eduardo Castellanos, Jose Luis Ibañez Criado, Luis Tercedor, Ignacio García-Bolao, Miguel A Martínez-González, Jesús Almendral, Miguel Ruiz-Canela","doi":"10.1159/000543639","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia worldwide. Although catheter ablation is the most efficacious therapy, relapses occur frequently (30%) in the first year after ablation. Novel biomarkers of recurrence are needed for a better prediction of recurrence and management of AF. In this pilot study, we aimed to analyze the baseline proteome of subjects included in a case-control study to find differential proteins associated with AF recurrence.</p><p><strong>Methods: </strong>Baseline serum proteomics (354 proteins) data from 16 cases (recurrent AF) and 17 controls (non-recurrent) were obtained using MS/MS analysis. A false discovery rate was performed using a nonlinear fitting method for the selection of proteins. Logistic regression models were used to further analyze the association between differentially expressed proteins and AF recurrence.</p><p><strong>Results: </strong>Ten proteins were differentially represented in cases vs. controls. Two were upregulated in the cases compared to the controls: keratin type I cytoskeletal 17 (Fold-change [FC] = 2.14; p = 0.017) and endoplasmic bifunctional protein (FC = 1.65; p = 0.032). Eight were downregulated in the cases compared to the controls: C4bpA (FC = 0.64; p = 0.006), coagulation factor XI (FC = 0.83; p = 0.011), CLIC1 (FC = 0.62; p = 0.017), haptoglobin (FC = 0.37; p = 0.021), Ig alpha-2 chain C region (FC = 0.49; p = 0.022), C4bpB (FC = 0.73; p = 0.028), N-acetylglucosamine-1-phosphotransferase subunit gamma (FC = 0.61; p = 0.033), and platelet glycoprotein Ib alpha chain (FC = 0.84; p = 0.038).</p><p><strong>Conclusion: </strong>This pilot study identifies ten differentially expressed serum proteins associated with AF recurrence, offering potential biomarkers for improved prediction and management.</p>","PeriodicalId":18030,"journal":{"name":"Lifestyle Genomics","volume":" ","pages":"52-58"},"PeriodicalIF":2.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Lifestyle Genomics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1159/000543639","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/24 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia worldwide. Although catheter ablation is the most efficacious therapy, relapses occur frequently (30%) in the first year after ablation. Novel biomarkers of recurrence are needed for a better prediction of recurrence and management of AF. In this pilot study, we aimed to analyze the baseline proteome of subjects included in a case-control study to find differential proteins associated with AF recurrence.
Methods: Baseline serum proteomics (354 proteins) data from 16 cases (recurrent AF) and 17 controls (non-recurrent) were obtained using MS/MS analysis. A false discovery rate was performed using a nonlinear fitting method for the selection of proteins. Logistic regression models were used to further analyze the association between differentially expressed proteins and AF recurrence.
Results: Ten proteins were differentially represented in cases vs. controls. Two were upregulated in the cases compared to the controls: keratin type I cytoskeletal 17 (Fold-change [FC] = 2.14; p = 0.017) and endoplasmic bifunctional protein (FC = 1.65; p = 0.032). Eight were downregulated in the cases compared to the controls: C4bpA (FC = 0.64; p = 0.006), coagulation factor XI (FC = 0.83; p = 0.011), CLIC1 (FC = 0.62; p = 0.017), haptoglobin (FC = 0.37; p = 0.021), Ig alpha-2 chain C region (FC = 0.49; p = 0.022), C4bpB (FC = 0.73; p = 0.028), N-acetylglucosamine-1-phosphotransferase subunit gamma (FC = 0.61; p = 0.033), and platelet glycoprotein Ib alpha chain (FC = 0.84; p = 0.038).
Conclusion: This pilot study identifies ten differentially expressed serum proteins associated with AF recurrence, offering potential biomarkers for improved prediction and management.
期刊介绍:
Lifestyle Genomics aims to provide a forum for highlighting new advances in the broad area of lifestyle-gene interactions and their influence on health and disease. The journal welcomes novel contributions that investigate how genetics may influence a person’s response to lifestyle factors, such as diet and nutrition, natural health products, physical activity, and sleep, amongst others. Additionally, contributions examining how lifestyle factors influence the expression/abundance of genes, proteins and metabolites in cell and animal models as well as in humans are also of interest. The journal will publish high-quality original research papers, brief research communications, reviews outlining timely advances in the field, and brief research methods pertaining to lifestyle genomics. It will also include a unique section under the heading “Market Place” presenting articles of companies active in the area of lifestyle genomics. Research articles will undergo rigorous scientific as well as statistical/bioinformatic review to ensure excellence.