Discovery of new biomarkers for atrial fibrillation using a custom-made proteomics chip. Issue 5 (8th September 2016)

• Record Type: Journal Article
• Authors: Lind, Lars; Sundström, Johan; Stenemo, Markus; Hagström, Emil; Ärnlöv, Johan
• Is Part Of: Heart. Volume 103:Issue 5(2017)
• Page Start: 377
• Page End: 382
• Publication Date: 2016-09-08
• Subjects: Heart -- Diseases -- Treatment -- Periodicals; Cardiology -- Periodicals; 616.12
• DOI: 10.1136/heartjnl-2016-309764
• Languages: English
• ISSNs: 1355-6037

Abstract

Abstract : Background: Apart from several established clinical risk factors for atrial fibrillation (AF), a number of biomarkers have also been identified as potential risk factors for AF. None of these have so far been adopted in clinical practice. Objective: To use a novel custom-made proteomics chip to discover new prognostic biomarkers for AF risk. Methods: In two independent community-based cohorts (Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study (978 participants without AF, mean age 70.1 years, 50% women, median follow-up 10.0 years) and Uppsala Longitudinal Study of Adult Men (ULSAM) (n=725, mean age 77.5 years, median follow-up 7.9 years)), ninety-two plasma proteins were assessed at baseline by a proximity extension assay (PEA) chip. Of those, 85 proteins showed a call rate >70% in both cohorts. Results: Thirteen proteins were related to incident AF in PIVUS (148 events) using a false discovery rate of 5%. Of those, five were replicated in ULSAM at nominal multivariable p value (123 events, N-terminal pro-B-type natriuretic peptide (NT-pro-BNP), fibroblast growth factor 23 (FGF-23), fatty acid-binding protein 4 (FABP4), growth differentiation factor 15 (GDF-15) and interleukin-6 (IL-6)). Of those, NT-pro-BNP and FGF-23 were also associated with AF after adjusting for established AF risk factors. In a prespecified secondary analysis pooling the two data sets, T-cell immunoglobulin and mucin domain 1 (TIM-1) and adrenomedullin (AM) were also significantly related to incident AF in addition to the aforementioned five proteins (Bonferroni-adjustment). The addition of NT-pro-BNP to a model with established risk factors increased the C-statistic from 0.605 to 0.676 (p<0.0001). Conclusions: Using a novel proteomics approach, we confirmed the previously reported association between NT-pro-BNP, FGF-23, GDF-15 and incident AF, and also discovered four proteins (FABP4, IL-6, TIM-1 and AM) that could be of importance in the development of AF.