Dataset Information

Protein Biomarkers and Risk of Atrial Fibrillation: The FHS.

ABSTRACT:

Background

Identification of protein biomarkers associated with incident atrial fibrillation (AF) may improve the understanding of the pathophysiology, risk prediction, and development of new therapeutics for AF. We examined the associations between 85 protein biomarkers and incident AF.

Methods

We included participants ?50 years of age from the FHS (Framingham Heart Study) Offspring and Third Generation cohorts, who had 85 fasting plasma proteins measured using Luminex xMAP platform. Hazard ratios (per 1 SD increment of rank-normalized biomarker [hazard ratio]) and 95% CIs for incident AF were calculated using Cox regression models adjusted for age, sex, height, weight, current smoking, systolic blood pressure, diastolic blood pressure, hypertension treatment, diabetes mellitus, valvular heart disease, prevalent myocardial infarction, and prevalent heart failure. We used the false discovery rate to account for multiple testing.

Results

The study sample comprised 3378 participants (54% women) with mean (SD) age of 61.5 (8.4) years. In total, 401 developed AF over a mean follow-up of 12.3±3.8 years. We observed lower hazard of incident AF associated with higher mean levels of IGF1 (insulin-like growth factor 1; hazard ratio per 1 SD increment in protein level, 0.84 [95% CI, 0.76-0.93]), and higher hazard of incident AF associated with higher mean levels of both IGFBP1 (insulin-like growth factor-binding protein 1; hazard ratio, 1.24 [95% CI, 1.1-1.39]) and NT-proBNP (N-terminal pro-B-type natriuretic peptide; hazard ratio, 1.73 [95% CI, 1.52-1.96]).

Conclusions

Decreased levels of IGF1 and increased levels of IGFBP1 and NT-proBNP were associated with higher risk of incident AF.

SUBMITTER: Staerk L

PROVIDER: S-EPMC7031024 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Protein Biomarkers and Risk of Atrial Fibrillation: The FHS.

Staerk Laila L Preis Sarah R SR Lin Honghuang H Lubitz Steven A SA Ellinor Patrick T PT Levy Daniel D Benjamin Emelia J EJ Trinquart Ludovic L

Circulation. Arrhythmia and electrophysiology 20200115 2

<h4>Background</h4>Identification of protein biomarkers associated with incident atrial fibrillation (AF) may improve the understanding of the pathophysiology, risk prediction, and development of new therapeutics for AF. We examined the associations between 85 protein biomarkers and incident AF.<h4>Methods</h4>We included participants ≥50 years of age from the FHS (Framingham Heart Study) Offspring and Third Generation cohorts, who had 85 fasting plasma proteins measured using Luminex xMAP platf ...[more]

PMID: 31941368

Similar Datasets

Project description:CONTEXT:Although the heritability of atrial fibrillation (AF) is established, the contribution of familial AF to predicting new-onset AF remains unknown. OBJECTIVE:To determine whether familial occurrence of AF is associated with new-onset AF beyond established risk factors. DESIGN, SETTING, AND PARTICIPANTS:The Framingham Heart Study, a prospective community-based cohort study started in 1948. Original and Offspring Cohort participants were aged at least 30 years, were free of AF at the baseline examination, and had at least 1 parent or sibling enrolled in the study. The 4421 participants in this analysis (mean age, 54 [SD, 13] years; 54% women) were followed up through December 31, 2007. MAIN OUTCOME MEASURES:Incremental predictive value of incorporating different features of familial AF (any familial AF, premature familial AF [onset ?65 years old], number of affected relatives, and youngest age of onset in a relative) into a risk model for new-onset AF. RESULTS:Across 11,971 examinations during the period 1968-2007, 440 participants developed AF. Familial AF occurred among 1185 participants (26.8%) and premature familial AF occurred among 351 participants (7.9%). Atrial fibrillation occurred more frequently among participants with familial AF than without familial AF (unadjusted absolute event rates of 5.8% and 3.1%, respectively). The association was not attenuated by adjustment for AF risk factors (multivariable-adjusted hazard ratio, 1.40; 95% confidence interval [CI], 1.13-1.74) or reported AF-related genetic variants. Among the different features of familial AF examined, premature familial AF was associated with improved discrimination beyond traditional risk factors to the greatest extent (traditional risk factors, C statistic, 0.842 [95% CI, 0.826-0.858]; premature familial AF, C statistic, 0.846 [95% CI, 0.831-0.862]; P = .004). Modest changes in integrated discrimination improvement were observed with premature familial AF (2.1%). Net reclassification improvement (assessed using 8-year risk thresholds of <5%, 5%-10%, and >10%) did not change significantly with premature familial AF (index statistic, 0.011; 95% CI, -0.021 to 0.042; P = .51), although categoryless net reclassification was improved (index statistic, 0.127; 95% CI, 0.064-0.189; P = .009). CONCLUSIONS:In this cohort, familial AF was associated with an increased risk of AF that was not attenuated by adjustment for AF risk factors including genetic variants. Assessment of premature familial AF was associated with a very slight increase in predictive accuracy compared with traditional risk factors.

Dataset Information

Protein Biomarkers and Risk of Atrial Fibrillation: The FHS.

Background

Methods

Results

Conclusions

Publications

Protein Biomarkers and Risk of Atrial Fibrillation: The FHS.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets