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Twelve-single nucleotide polymorphism genetic risk score identifies individuals at increased risk for future atrial fibrillation and stroke.

ABSTRACT: Atrial fibrillation (AF) is prevalent and there is a clinical need for biomarkers to identify individuals at higher risk for AF. Fixed throughout a life course and assayable early in life, genetic biomarkers may meet this need. Here, we investigate whether multiple single nucleotide polymorphisms together as an AF genetic risk score (AF-GRS) can improve prediction of one's risk for AF.In 27 471 participants of the Malmö Diet and Cancer Study, a prospective, community-based cohort, we used Cox models that adjusted for established AF risk factors to assess the association of AF-GRS with incident AF and ischemic stroke. Median follow-up was 14.4 years for incident AF and 14.5 years for ischemic stroke. The AF-GRS comprised 12 single nucleotide polymorphisms that had been previously shown to be associated with AF at genome-wide significance.During follow-up, 2160 participants experienced a first AF event and 1495 had a first ischemic stroke event. Participants in the top AF-GRS quintile were at increased risk for incident AF (hazard ratio, 2.00; 95% confidence interval, 1.73-2.31; P=2.7×10(-21)) and ischemic stroke (hazard ratio, 1.23; 95% confidence interval, 1.04-1.46; P=0.02) when compared with the bottom quintile. Addition of the AF-GRS to established AF risk factors modestly improved both discrimination and reclassification (P<0.0001 for both).An AF-GRS can identify 20% of individuals who are at ?2-fold increased risk for incident AF and at 23% increased risk for ischemic stroke. Targeting diagnostic or therapeutic interventions to this subset may prove clinically useful.

SUBMITTER: Tada H

PROVIDER: S-EPMC4346099 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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Twelve-single nucleotide polymorphism genetic risk score identifies individuals at increased risk for future atrial fibrillation and stroke.

Tada Hayato H Shiffman Dov D Smith J Gustav JG Sjögren Marketa M Lubitz Steven A SA Ellinor Patrick T PT Louie Judy Z JZ Catanese Joseph J JJ Engström Gunnar G Devlin James J JJ Kathiresan Sekar S Melander Olle O

Stroke 20140814 10

<h4>Background and purpose</h4>Atrial fibrillation (AF) is prevalent and there is a clinical need for biomarkers to identify individuals at higher risk for AF. Fixed throughout a life course and assayable early in life, genetic biomarkers may meet this need. Here, we investigate whether multiple single nucleotide polymorphisms together as an AF genetic risk score (AF-GRS) can improve prediction of one's risk for AF.<h4>Methods</h4>In 27 471 participants of the Malmö Diet and Cancer Study, a pros ...[more]

PMID: 25123217

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Project description:BackgroundAtrial fibrillation (AF) is associated with increased risks of stroke and heart failure. Electronic health record (EHR)-based AF risk prediction may facilitate efficient deployment of interventions to diagnose or prevent AF altogether.MethodsWe externally validated an electronic health record AF (EHR-AF) score in IBM Explorys Life Sciences, a multi-institutional dataset containing statistically deidentified EHR data for over 21 million individuals (Explorys Dataset). We included individuals with complete AF risk data, ≥2 office visits within 2 years, and no prevalent AF. We compared EHR-AF to existing scores including CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology Atrial Fibrillation), C2HEST (coronary artery disease or chronic obstructive pulmonary disease, hypertension, elderly, systolic heart failure, thyroid disease), and CHA2DS2-VASc. We assessed association between AF risk scores and 5-year incident AF, stroke, and heart failure using Cox proportional hazards modeling, 5-year AF discrimination using C indices, and calibration of predicted AF risk to observed AF incidence.ResultsOf 21 825 853 individuals in the Explorys Dataset, 4 508 180 comprised the analysis (age 62.5, 56.3% female). AF risk scores were strongly associated with 5-year incident AF (hazard ratio per SD increase 1.85 using CHA2DS2-VASc to 2.88 using EHR-AF), stroke (1.61 using C2HEST to 1.92 using CHARGE-AF), and heart failure (1.91 using CHA2DS2-VASc to 2.58 using EHR-AF). EHR-AF (C index, 0.808 [95% CI, 0.807-0.809]) demonstrated favorable AF discrimination compared to CHARGE-AF (0.806 [95% CI, 0.805-0.807]), C2HEST (0.683 [95% CI, 0.682-0.684]), and CHA2DS2-VASc (0.720 [95% CI, 0.719-0.722]). Of the scores, EHR-AF demonstrated the best calibration to incident AF (calibration slope, 1.002 [95% CI, 0.997-1.007]). In subgroup analyses, AF discrimination using EHR-AF was lower in individuals with stroke (C index, 0.696 [95% CI, 0.692-0.700]) and heart failure (0.621 [95% CI, 0.617-0.625]).ConclusionsEHR-AF demonstrates predictive accuracy for incident AF using readily ascertained EHR data. AF risk is associated with incident stroke and heart failure. Use of such risk scores may facilitate decision support and population health management efforts focused on minimizing AF-related morbidity.

Dataset Information

Twelve-single nucleotide polymorphism genetic risk score identifies individuals at increased risk for future atrial fibrillation and stroke.

Publications

Twelve-single nucleotide polymorphism genetic risk score identifies individuals at increased risk for future atrial fibrillation and stroke.

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