Multi-ethnic genome-wide association study for atrial fibrillation.

Atrial fibrillation (AF) affects more than 33 million individuals worldwide1 and has a complex heritability2. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.

Motion and Noise Artifact-Resilient Atrial Fibrillation Detection using a Smartphone.

We have recently found that our previously-developed atrial fibrillation (AF) detection algorithm for smartphones can give false positives when subjects' fingers or hands move, as we rely on proper finger placement over the smartphone camera to collect the signal of interest. Specifically, smartphone camera pulsatile signals that are obtained from normal sinus rhythm (NSR) subjects but are corrupted by motion and noise artifacts (MNAs) are frequently detected as AF. AF and motion-corrupted episodes have the similar characteristic that pulse-to-pulse intervals (PPIs) are irregular. We have developed an MNA-resilient smartphone-based AF detection algorithm that first discriminates and eliminates MNA-corrupted episodes in smartphone camera recordings, and then detects AF in MNA-free recordings. We found that MNA-corrupted episodes have highly-varying pulse slope, large turning point ratio, or large kurtosis values in smartphone signals compared to MNA-free AF and NSR episodes. We first use these three metrics for MNA discrimination and exclusion. Then, AF is detected in MNA-free signals using our previous algorithm. The capability to discriminate MNAs and AFs separately in smartphone signals increases the specificity of AF detection. To evaluate the performance of the proposed MNA-resilient AF algorithm, 99 subjects, including 88 study participants with AF at baseline and in NSR after electrical cardioversion as well as 11 participants with MNA-corrupted NSR, were recruited. Using iPhone 4S, 5S, and 6S models, we collected 2-minute pulsatile time series from each subject. The clinical results show that the accuracy, sensitivity and specificity of the proposed AF algorithm are 0.97, 0.98, 0.97, respectively, which are higher than those of the previous AF algorithm.

Burden of Psychosocial and Cognitive Impairment in Patients With Atrial Fibrillation.

BACKGROUND: Impairments in psychosocial status and cognition relate to poor clinical outcomes in patients with atrial fibrillation (AF). However, how often these conditions co-occur and associations between burden of psychosocial and cognitive impairment and quality of life (QoL) have not been systematically examined in patients with AF. METHODS: A total of 218 patients with symptomatic AF were enrolled in a prospective study of AF and psychosocial factors between May 2013 and October 2014 at the University of Massachusetts Medical Center. Cognitive function, depression, and anxiety were assessed at baseline and AF-specific QoL was assessed 6 months after enrollment using validated instruments. Demographic and clinical information were obtained from a structured interview and medical record review. RESULTS: The mean age of the study participants was 63.5 ± 10.2 years, 35% were male, and 81% had paroxysmal AF. Prevalences of impairment in 1, 2, and 3 psychosocial/cognitive domains (eg, depression, anxiety, or cognition) were 75 (34.4%), 51 (23.4%), and 16 (7.3%), respectively. Patients with co-occurring psychosocial/cognitive impairments (eg, >1 domain) were older, more likely to smoke, had less education, and were more likely to have heart failure (all P < 0.05). Compared with participants with no psychosocial/cognitive impairments, AF-specific QoL at 6 months was significantly poorer among participants with baseline impairment in 2 (B = -13.6, 95% CI: -21.7 to -5.4) or 3 (B = -15.1, 95% CI: -28.0 to -2.2) psychosocial/cognitive domains. CONCLUSION: Depression, anxiety, and impaired cognition were common in our cohort of patients with symptomatic AF and often co-occurred. Higher burden of psychosocial/cognitive impairment was associated with poorer AF-specific QoL.

Characterization of the platelet transcriptome by RNA sequencing in patients with acute myocardial infarction.

Transcripts in platelets are largely produced in precursor megakaryocytes but remain physiologically active as platelets translate RNAs and regulate protein/RNA levels. Recent studies using transcriptome sequencing (RNA-seq) characterized the platelet transcriptome in limited number of non-diseased individuals. Here, we expand upon these RNA-seq studies by completing RNA-seq in platelets from 32 patients with acute myocardial infarction (MI). Our goals were to characterize the platelet transcriptome using a population of patients with acute MI and relate gene expression to platelet aggregation measures and ST-segment elevation MI (STEMI) (n = 16) vs. non-STEMI (NSTEMI) (n = 16) subtypes. Similar to other studies, we detected 9565 expressed transcripts, including several known platelet-enriched markers (e.g. PPBP, OST4). Our RNA-seq data strongly correlated with independently ascertained platelet expression data and showed enrichment for platelet-related pathways (e.g. wound response, hemostasis, and platelet activation), as well as actin-related and post-transcriptional processes. Several transcripts displayed suggestively higher (FBXL4, ECHDC3, KCNE1, TAOK2, AURKB, ERG, and FKBP5) and lower (MIAT, PVRL3, and PZP) expression in STEMI platelets compared to NSTEMI. We also identified transcripts correlated with platelet aggregation to TRAP (ATP6V1G2, SLC2A3), collagen (CEACAM1, ITGA2), and ADP (PDGFB, PDGFC, ST3GAL6). Our study adds to current platelet gene expression resources by providing transcriptome-wide analyses in platelets isolated from patients with acute MI. In concert with prior studies, we identify various genes for further study in regards to platelet function and acute MI. Future platelet RNA-seq studies examining more diverse sets of healthy and diseased samples will add to our understanding of platelet thrombotic and non-thrombotic functions.

PULSE-SMART: Pulse-Based Arrhythmia Discrimination Using a Novel Smartphone Application.

BACKGROUND: Atrial fibrillation (AF) is a common and dangerous rhythm abnormality. Smartphones are increasingly used for mobile health applications by older patients at risk for AF and may be useful for AF screening. OBJECTIVES: To test whether an enhanced smartphone app for AF detection can discriminate between sinus rhythm (SR), AF, premature atrial contractions (PACs), and premature ventricular contractions (PVCs). METHODS: We analyzed two hundred and nineteen 2-minute pulse recordings from 121 participants with AF (n = 98), PACs (n = 15), or PVCs (n = 15) using an iPhone 4S. We obtained pulsatile time series recordings in 91 participants after successful cardioversion to sinus rhythm from preexisting AF. The PULSE-SMART app conducted pulse analysis using 3 methods (Root Mean Square of Successive RR Differences; Shannon Entropy; Poincare plot). We examined the sensitivity, specificity, and predictive accuracy of the app for AF, PAC, and PVC discrimination from sinus rhythm using the 12-lead EKG or 3-lead telemetry as the gold standard. We also administered a brief usability questionnaire to a subgroup (n = 65) of app users. RESULTS: The smartphone-based app demonstrated excellent sensitivity (0.970), specificity (0.935), and accuracy (0.951) for real-time identification of an irregular pulse during AF. The app also showed good accuracy for PAC (0.955) and PVC discrimination (0.960). The vast majority of surveyed app users (83%) reported that it was "useful" and "not complex" to use. CONCLUSION: A smartphone app can accurately discriminate pulse recordings during AF from sinus rhythm, PACs, and PVCs.

Addition of B-Type Natriuretic Peptide to Existing Clinical Risk Scores Enhances Identification of Patients at Risk for Atrial Fibrillation Recurrence After Pulmonary Vein Isolation.

INTRODUCTION: Predicting which patients will be free from atrial fibrillation (AF) after pulmonary vein isolation (PVI) remains challenging. Clinical risk prediction scores show modest ability to identify patients at risk for AF recurrence after PVI. B-type natriuretic peptide (BNP) is associated with risk for incident and recurrent AF but is not currently included in existing AF risk scores. We sought to evaluate the incremental benefit of adding preoperative BNP to existing risk scores for predicting AF recurrence during the 6 months after PVI. METHODS: One hundred sixty-one patients with paroxysmal or persistent AF underwent an index PVI procedure between 2010 and 2013; 77 patients (48%) had late AF recurrence after PVI (>3 months post-PVI) over the 6-month follow-up period. RESULTS: A BNP greater than or equal to 100 pg/dL (P=0.01) and AF recurrence within 3 months after PVI (P<0.001) were associated with late AF recurrence in multivariate analyses. Addition of BNP to existing clinical risk scores significantly improved the areas under the curve for each score, with an integrated discrimination improvement of 0.08 (P=0.001) and a net reclassification improvement of 60% (P=0.001) for all risk scores. CONCLUSIONS: Circulating BNP levels are independently associated with late AF recurrence after PVI. Inclusion of BNP significantly improves the discriminative ability of CHADS2, CHA2DS2-VASc, R2CHADS2, and the HATCH score in predicting clinically significant, late AF recurrence after PVI and should be incorporated in decision-making algorithms for management of AF. B-R2CHADS2 is the best score model for prediction of late AF recurrence.

Arrhythmia discrimination using a smart phone.

We hypothesize that our smartphone-based arrhythmia discrimination algorithm with data acquisition approach reliably differentiates between normal sinus rhythm (NSR), atrial fibrillation (AF), premature ventricular contractions (PVCs) and premature atrial contraction (PACs) in a diverse group of patients having these common arrhythmias. We combine root mean square of successive RR differences and Shannon entropy with Poincare plot (or turning point ratio method) and pulse rise and fall times to increase the sensitivity of AF discrimination and add new capabilities of PVC and PAC identification. To investigate the capability of the smartphone-based algorithm for arrhythmia discrimination, 99 subjects, including 88 study participants with AF at baseline and in NSR after electrical cardioversion, as well as seven participants with PACs and four with PVCs were recruited. Using a smartphone, we collected 2-min pulsatile time series from each recruited subject. This clinical application results show that the proposed method detects NSR with specificity of 0.9886, and discriminates PVCs and PACs from AF with sensitivities of 0.9684 and 0.9783, respectively.

Plasma microRNAs are associated with atrial fibrillation and change after catheter ablation (the miRhythm study).

BACKGROUND: MicroRNAs (miRNAs) are associated with cardiovascular disease and control gene expression and are detectable in the circulation. OBJECTIVE: The purpose of this study was to test the hypothesis that circulating miRNAs may be associated with atrial fibrillation (AF). METHODS: Using a prospective study design powered to detect subtle differences in miRNAs, we quantified plasma expression of 86 miRNAs by high-throughput quantitative reverse transcriptase-polymerase chain reaction in 112 participants with AF and 99 without AF. To examine parallels between cardiac and plasma miRNA profiles, we quantified atrial tissue and plasma miRNA expression using quantitative reverse transcriptase-polymerase chain reaction in 31 participants undergoing surgery. We also explored the hypothesis that lower AF burden after ablation would be reflected in the circulating blood pool by examining change in plasma miRNAs after AF ablation (n = 47). RESULTS: Mean age of the cohort was 59 years; 58% of participants were men. Plasma miRs-21 and 150 were 2-fold lower in participants with AF than in those without AF after adjustment (P ≤.0006). Plasma levels of miRs-21 and 150 also were lower in participants with paroxysmal AF than in those with persistent AF (P <.05). Expression of miR-21, but not of miR-150, was lower in atrial tissue from patients with AF than in those without AF (P <.05). Plasma levels of miRs-21 and 150 increased 3-fold after AF ablation (P ≤.0006). CONCLUSION: Cardiac miRs-21 and 150 are known to regulate genes implicated in atrial remodeling. Our findings show associations between plasma miRs-21 and 150 and AF, suggesting that circulating miRNAs can provide insights into cardiac gene regulation.

Apurinic/apyrimidinic endonuclease 2 regulates the expansion of germinal centers by protecting against activation-induced cytidine deaminase-independent DNA damage in B cells.

Activation-induced cytidine deaminase (AID) initiates a process generating DNA mutations and breaks in germinal center (GC) B cells that are necessary for somatic hypermutation and class-switch recombination. GC B cells can "tolerate" DNA damage while rapidly proliferating because of partial suppression of the DNA damage response by BCL6. In this study, we develop a model to study the response of mouse GC B cells to endogenous DNA damage. We show that the base excision repair protein apurinic/apyrimidinic endonuclease (APE) 2 protects activated B cells from oxidative damage in vitro. APE2-deficient mice have smaller GCs and reduced Ab responses compared with wild-type mice. DNA double-strand breaks are increased in the rapidly dividing GC centroblasts of APE2-deficient mice, which activate a p53-independent cell cycle checkpoint and a p53-dependent apoptotic response. Proliferative and/or oxidative damage and AID-dependent damage are additive stresses that correlate inversely with GC size in wild-type, AID-, and APE2-deficient mice. Excessive double-strand breaks lead to decreased expression of BCL6, which would enable DNA repair pathways but limit GC cell numbers. These results describe a nonredundant role for APE2 in the protection of GC cells from AID-independent damage, and although GC cells uniquely tolerate DNA damage, we find that the DNA damage response can still regulate GC size through pathways that involve p53 and BCL6.

Recent trends in the incidence, treatment, and prognosis of patients with heart failure and atrial fibrillation (the Worcester Heart Failure Study).

Atrial fibrillation (AF) and heart failure (HF) are common cardiovascular diseases and the co-occurrence of AF and HF has been associated with reduced survival. Data are needed on the potentially changing trends in the characteristics, treatment, and prognosis of patients with acute decompensated HF (ADHF) and AF. The study population consisted of 9,748 patients hospitalized with ADHF at 11 hospitals in the Worcester, Massachusetts, metropolitan area during 4 study years (1995, 2000, 2002, and 2004). Of the 9,748 patients admitted with ADHF, 3,868 (39.7%) had a history of AF and 449 (4.6%) developed new-onset AF during hospitalization. The rates of new-onset AF remained stable (4.9% in 1995; 5.0% in 2004), but the proportion of patients with pre-existing AF (34.5% in 1995; 41.6% in 2004) increased over time. New-onset and pre-existing AF were associated with older age, but pre-existing AF was more closely linked to a greater co-morbid disease burden. The use of HF therapies did not differ greatly by AF status. Despite this, new-onset AF was associated with a longer length of stay (7.5 vs 6.1 days) and greater in-hospital death rates (11.4% vs 6.6%). In contrast, pre-existing AF was associated with lower rates of postdischarge survival compared to patients with no AF (p <0.05 for all). The mortality rates improved significantly over time in patients with AF. In conclusion, AF was common among patients with ADHF, and the proportion of ADHF patients with co-occurring AF increased during the study period. Despite improving trends in survival, patients with ADHF and AF are at increased risk of in-hospital and postdischarge mortality.

A novel application for the detection of an irregular pulse using an iPhone 4S in patients with atrial fibrillation.

BACKGROUND: Atrial fibrillation (AF) is common and associated with adverse health outcomes. Timely detection of AF can be challenging using traditional diagnostic tools. Smartphone use is increasing and may provide an inexpensive and user-friendly means to diagnoseAF. OBJECTIVE: To test the hypothesis that a smartphone-based application could detect an irregular pulse fromAF. METHODS: Seventy-six adults with persistent AF were consented for participation in our study. We obtained pulsatile time series recordings before and after cardioversion using an iPhone 4S camera. A novel smartphone application conducted real-time pulse analysis using 2 statistical methods: root mean square of successive RR difference (RMSSD/mean) and Shannon entropy (ShE). We examined the sensitivity, specificity, and predictive accuracy of both algorithms using the 12-lead electrocardiogram as the gold standard. RESULTS: RMSDD/mean and ShE were higher in participants in AF than in those with sinus rhythm. The 2 methods were inversely related to AF in regression models adjusting for key factors including heart rate and blood pressure (beta coefficients per SD increment in RMSDD/mean and ShE were-0.20 and-0.35; P<.001). An algorithm combining the 2 statistical methods demonstrated excellent sensitivity (0.962), specificity (0.975), and accuracy (0.968) for beat-to-beat discrimination of an irregular pulse during AF from sinus rhythm. CONCLUSIONS: In a prospectively recruited cohort of 76 participants undergoing cardioversion for AF, we found that a novel algorithm analyzing signals recorded using an iPhone 4S accurately distinguished pulse recordings during AF from sinus rhythm. Data are needed to explore the performance and acceptability of smartphone-based applications for AF detection.

Circulating Cell and Plasma microRNA Profiles Differ between Non-ST-Segment and ST-Segment-Elevation Myocardial Infarction.

BACKGROUND: Differences in plasma and whole blood expression microRNAs (miRNAs) in patients with an acute coronary syndrome (ACS) have been determined in both in vitro and in vivo studies. Although most circulating miRNAs are located in the cellular components of whole blood, little is known about the miRNA profiles of whole blood subcomponents, including plasma, platelets and leukocytes in patients with myocardial ischemia. METHODS: Thirteen patients with a ST-segment-elevation (STEMI) or non-ST-segment elevation (NSTEMI) myocardial infarction were identified in the University of Massachusetts Medical Center Emergency Department (ED) or cardiac catheterization laboratory between February and June of 2012. Whole blood was obtained from arterial blood samples at the time of cardiac catheterization and cell-specific miRNA profiling was performed. Expression of 343 miRNAs was quantified from whole blood, plasma, platelets, and peripheral blood mononuclear cells using a high-throughput, quantitative Real-Time polymerase-chain reaction system (qRT-PCR). RESULTS: MiRNAs associated with STEMI as compared to NSTEMI patients included miR-25-3p, miR-221-3p, and miR-374b-5p. MiRNA 30d-5p was associated with plasma, platelets, and leukocytes in both STEMI and NSTEMI patients; miRNAs 221-3p and 483-5p were correlated with plasma and platelets only in NSTEMI patients. CONCLUSIONS: Cell-specific miRNA profiles differed between patients with STEMI and NSTEMI. The miRNA distribution is also unique amongst plasma, platelets, and leukocytes in patients with ischemic heart disease or ACS. Our findings suggest unique miRNA profiles among the circulating subcomponents in patients presenting with myocardial ischemia.