A proteomic analysis of atrial fibrillation in a prospective longitudinal cohort (AGES-Reykjavik study)

Proteomic Signatures for Risk Prediction of Atrial Fibrillation

BACKGROUND

Proteomic signatures might improve disease prediction and enable targeted disease prevention and management. We explored whether a protein risk score derived from large-scale proteomics data improves risk prediction of atrial fibrillation (AF).

METHODS

A total of 51 680 individuals with 1459 unique plasma protein measurements and without a history of AF were included from the UKB-PPP (UK Biobank Pharma Proteomics Project). A protein risk score was developed with lasso-penalized Cox regression from a random subset of 70% (36 176 individuals, 54.4% women, 2155 events) and was tested on the remaining 30% (15 504 individuals, 54.4% women, 910 events). The protein risk score was externally replicated with the ARIC study (Atherosclerosis Risk in Communities; 11 012 individuals, 54.8% women, 1260 events).

RESULTS

The protein risk score formula developed from the UKB-PPP derivation set was composed of 165 unique plasma proteins, and 15 of them were associated with atrial remodeling. In the UKB-PPP test set, a 1-SD increase in protein risk score was associated with a hazard ratio of 2.20 (95% CI, 2.05-2.41) for incident AF. The C index for a model including CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology Atrial Fibrillation), NT-proBNP (N-terminal B-type natriuretic peptide), polygenic risk score, and protein risk score was 0.816 (95% CI, 0.802-0.829) compared with 0.771 (95% CI, 0.755-0.787) for a model including CHARGE-AF, NT-proBNP, and polygenic risk score (C-index change, 0.044 [95% CI, 0.039-0.055]). Protein risk score added to CHARGE-AF, NT-proBNP, and polygenic risk score resulted in a risk reclassification of 5.4% (95% CI, 2.9%-7.9%) with a 5-year risk threshold of 5%. In the decision curve, the predicted net benefit before and after the addition of protein risk score to a model including CHARGE-AF, NT-proBNP, and polygenic risk score was 3.8 and 5.4 per 1000 people, respectively, at a 5-year risk threshold of 5%. External replication of a protein risk score in the ARIC study showed consistent improvement in risk stratification of AF.

CONCLUSIONS

Protein risk score derived from a single plasma sample improved risk prediction of AF. Further research using proteomic signatures in AF screening and prevention is needed.

X-Chromosome-Linked miRNAs Regulate Sex Differences in Cardiac Physiology

BACKGROUND

Males and females exhibit distinct anatomic and functional characteristics of the heart, predisposing them to specific disease states.

METHODS

We identified microRNAs (miRNAs/miR) with sex-differential expression in mouse hearts.

RESULTS

Four conserved miRNAs are present in a single locus on the X-chromosome and are expressed at higher levels in females than males. We show miRNA, miR-871, is responsible for decreased expression of the protein SRL (sarcalumenin) in females. SRL is involved in calcium signaling, and we show it contributes to differences in electrophysiology between males and females. miR-871 overexpression mimics the effects of the cardiac physiology of conditional cardiomyocyte-specific Srl-null mice. Inhibiting miR-871 with an antagomir in females shortened ventricular repolarization. The human orthologue of miR-871, miR-888, coevolved with the SRL 3' untranslated region and regulates human SRL.

CONCLUSIONS

These data highlight the importance of sex-differential miRNA mechanisms in mediating sex-specific functions and their potential relevance to human cardiac diseases.

Proteomics and Recurrence of Atrial Fibrillation: A Pilot Study Nested in the PREDIMAR Trial

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.

Cardiac arrhythmia in individuals with steroid sulfatase deficiency (X-linked ichthyosis): candidate anatomical and biochemical pathways

Circulating steroids, including sex hormones, can affect cardiac development and function. In mammals, steroid sulfatase (STS) is the enzyme solely responsible for cleaving sulfate groups from various steroid molecules, thereby altering their activity and water solubility. Recent studies have indicated that Xp22.31 genetic deletions encompassing STS (associated with the rare dermatological condition X-linked ichthyosis), and common variants within the STS gene, are associated with a markedly elevated risk of cardiac arrhythmias, notably atrial fibrillation/flutter. Here, we consider emerging basic science and clinical findings which implicate structural heart abnormalities (notably septal defects) as a mediator of this heightened risk, and propose candidate cellular and biochemical mechanisms. Finally, we consider how the biological link between STS activity and heart structure/function might be investigated further and the clinical implications of work in this area.

Precision Medicine for Cardiovascular Prevention and Population Health: A Bridge Too Far?

Precision medicine aims to provide personalized clinical care guided by tools that reflect underlying pathophysiology. The need for such an approach has never been greater in cardiovascular medicine, given the large number of guideline-directed medical therapies available. However, progress has been modest to date with few precision tools available for clinicians. Arguably, cardiovascular prevention and population health are poised for innovation to guide evaluation and management, as these areas are already informed by risk-assessment, but limited by the use of crude assessment tools with marginal performance. Risk assessment in prevention and population health may be improved with the use of genetics, circulating biomarkers, and imaging, leading to outcome-specific risk-prediction and enhanced phenotyping. Personalized management matching therapy to risk profile can be then implemented for either individuals or groups, improving cost-effectiveness and risk-benefit. Here, we explore this precision-like approach, including available tools, potential applications, and future perspectives for cardiovascular prevention and population health management.

Atrial proteomic profiling reveals a switch towards profibrotic gene expression program in CREM-IbΔC-X mice with persistent atrial fibrillation

BACKGROUND

Overexpression of the CREM (cAMP response element-binding modulator) isoform CREM-IbΔC-X in transgenic mice (CREM-Tg) causes the age-dependent development of spontaneous AF.

PURPOSE

To identify key proteome signatures and biological processes accompanying the development of persistent AF through integrated proteomics and bioinformatics analysis.

METHODS

Atrial tissue samples from three CREM-Tg mice and three wild-type littermates were subjected to unbiased mass spectrometry-based quantitative proteomics, differential expression and pathway enrichment analysis, and protein-protein interaction (PPI) network analysis.

RESULTS

A total of 98 differentially expressed proteins were identified. Gene ontology analysis revealed enrichment for biological processes regulating actin cytoskeleton organization and extracellular matrix (ECM) dynamics. Changes in ITGAV, FBLN5, and LCP1 were identified as being relevant to atrial fibrosis and structural based on expression changes, co-expression patterns, and PPI network analysis. Comparative analysis with previously published datasets revealed a shift in protein expression patterns from ion-channel and metabolic regulators in young CREM-Tg mice to profibrotic remodeling factors in older CREM-Tg mice. Furthermore, older CREM-Tg mice exhibited protein expression patterns reminiscent of those seen in humans with persistent AF.

CONCLUSIONS

This study uncovered distinct temporal changes in atrial protein expression patterns with age in CREM-Tg mice consistent with the progressive evolution of AF. Future studies into the role of the key differentially abundant proteins identified in this study in AF progression may open new therapeutic avenues to control atrial fibrosis and substrate development in AF.

Atrial Proteomic Profiling Reveals a Switch Towards Profibrotic Gene Expression Program in CREM-IbΔC-X Mice with Persistent Atrial Fibrillation

Background

Overexpression of the CREM (cAMP response element-binding modulator) isoform CREM-IbΔC-X in transgenic mice (CREM-Tg) causes the age-dependent development of spontaneous AF.

Purpose

To identify key proteome signatures and biological processes accompanying the development of persistent AF through integrated proteomics and bioinformatics analysis.

Methods

Atrial tissue samples from three CREM-Tg mice and three wild-type littermates were subjected to unbiased mass spectrometry-based quantitative proteomics, differential expression and pathway enrichment analysis, and protein-protein interaction (PPI) network analysis.

Results

A total of 98 differentially expressed proteins were identified. Gene ontology analysis revealed enrichment for biological processes regulating actin cytoskeleton organization and extracellular matrix (ECM) dynamics. Changes in ITGAV, FBLN5, and LCP1 were identified as being relevant to atrial fibrosis and remodeling based on expression changes, co-expression patterns, and PPI network analysis. Comparative analysis with previously published datasets revealed a shift in protein expression patterns from ion-channel and metabolic regulators in young CREM-Tg mice to profibrotic remodeling factors in older CREM-Tg mice. Furthermore, older CREM-Tg mice exhibited protein expression patterns that resembled those of humans with persistent AF.

Conclusions

This study uncovered distinct temporal changes in atrial protein expression patterns with age in CREM-Tg mice consistent with the progressive evolution of AF. Future studies into the role of the key differentially abundant proteins identified in this study in AF progression may open new therapeutic avenues to control atrial fibrosis and substrate development in AF.