Introduction: Atrial fibrillation (AF) is a common cardiac arrhythmia. Putative genes associated with AF risk have been identified through large genome wide association studies. How expression of these proteins in the left atria differs by AF state (no history of AF, history of paroxysmal AF, history of persistent AF, persistent AF, long-standing persistent AF) has not been examined. Hypothesis: We hypothesized that proteins associated with AF risk differ by AF state. Methods: Left atrial appendage (LAA) tissue was obtained from 222 Cleveland Clinic patients undergoing cardiac surgery. At surgery, 104 were in sinus rhythm (SR) (24 without a history of AF, 50 had a history of paroxysmal AF, 30 had a history of persistent AF) and 118 patients were in AF rhythm (65 with history of persistent AF, 53 long-standing persistent AF). Proteins (n=2539) were identified by mass spectrometry. Protein levels were modeled for associations with AF state using linear regression and adjusted for sex, age, and 23 inferred surrogate variables. Results: Among the quantified proteins we identified 33 encoded from putative AF risk genes. Of these, CASQ2 was increased (p<0.05) and TTN was decreased in patients with a history of AF in SR compared to patients with no history of AF (Table 1A). There were nine proteins that differed between AF rhythm and sinus rhythm, of which five (SYNPO2L, MYPN, NACA, PKP2, and CALU) were increased (Table 1B) and four (TUBA8, MYOZ1, CASQ2, and CAMK2D) were decreased. In patients diagnosed with persistent AF in AF rhythm versus those with a history of persistent AF but in SR at surgery, four were increased (SYNPO2L, MYPN, NACA, and PKP2) and two (CASQ2 and CAMK2D) were decreased (Table 1C). Expression of proteins encoded by putative AF risk genes was not different in long-standing persistent AF rhythm compared to persistent AF rhythm. Conclusions: In one of the largest proteomic datasets in human LAA, we found that key proteins encoded by genes associated with AF risk are altered in patients in AF rhythm. Expression of these proteins also differs by AF state. These studies provide insight into pathways that may be targeted for AF prevention and highlight the importance of early intervention to prevent AF progression.

Introduction: Atrial fibrillation (AF), characterized by episodes of rapid and irregular heart rate, increases left atrial (LA) demand for ATP. While the heart is metabolically flexible, able to use fatty acids, lactate, glucose, ketones, and amino acids to generate ATP, fatty acids are the primary fuel source. AF is associated with altered mitochondrial structure and function, but the role of energetic pathways in early stages of AF progression is not clear. Hypothesis: Decreased expression of mitochondrial proteins contributes to AF progression. Aim: Evaluate expression of proteins that influence mitochondrial structure and energetic capacity in AF onset and progression. Methods: AF burden was assessed weekly by electrocardiography (ECG) in male wild-type (WT) and cAMP responsive element modulator IbΔC-X heterozygous mice (CREM) (n=3). LA (4 - 9 mg) was obtained at 7 weeks and 16 weeks. Global proteomics was conducted, and 139,316 peptides were identified that mapped to 6000 robustly quantified proteins. Results: LA hypertrophy was evident in 7-week and 16-week CREM mice (Figure 1). We detected 2408 proteins differentially expressed in CREM compared to WT. At 7 weeks, Hallmark pathways adipogenesis, fatty acid metabolism, oxidative phosphorylation, and myogenesis were decreased in CREM (Table 1). These changes persisted at 16 weeks. We identified 740 differentially expressed mitochondrial proteins using MitoCarta 3.0 (552 decreased, 188 increased). Mitochondrial pathways associated with energy production, including branched chain amino acid metabolism, fatty acid transport and oxidation, carbohydrate metabolism, and tricarboxylic acid cycle were decreased (Table 1). Mitochondrial cristae organizing system (MICOS) and mitophagy, pathways that influence mitochondrial structure and content, were decreased. Terminal ECGs confirmed AF in 16-week CREM mice only. The coefficient of variation of RR intervals (CVRR), a measure of heart rate variability, was increased in 16-week CREM (Figure 2). These data suggest that decreased expression of mitochondrial proteins accompanies LA hypertrophy but precedes onset of AF. Conclusions: Decreased expression of proteins that regulate mitochondrial structure and energy production prior to AF onset suggests that these proteins play an important role in early LA changes that promote AF onset and progression. Future studies will examine how these changes in protein expression relate to alterations in atrial energy homeostasis.

This study assesses the agreement of Artificial Intelligence-Quantitative Computed Tomography (AI-QCT) with qualitative approaches to atherosclerotic disease burden codified in the multisociety 2022 CAD-RADS 2.0 Expert Consensus. 105 patients who underwent cardiac computed tomography angiography (CCTA) for chest pain were evaluated by a blinded core laboratory through FDA-cleared software (Cleerly, Denver, CO) that performs AI-QCT through artificial intelligence, analyzing factors such as

Introduction: Low physical activity (PA) has been identified as a risk factor for development of atrial fibrillation (AF). However, the effect of changes in PA on directly recorded AF burden has not been well studied. The COVID-19 pandemic offered an opportunity to observe whether changes in activity were correlated with changes in AF burden. To determine if reduced PA is associated with higher AF burden, we assessed daily PA and AF burden data from patients with cardiac implantable electronic devices (CIEDs) enrolled in a prospective clinical trial, Targeting Risk Interventions and Metformin for Atrial Fibrillation (TRIM-AF, NCT03603912). Methods: Daily AF burden and activity were determined from implantable cardiac devices with atrial leads. The pandemic lockdown period was analyzed for up to 1 year. Pre-pandemic periods were matched by month to pandemic periods. To test the potential confounding of aging, pre-pre-pandemic periods were matched by month to pre-pandemic periods. To reduce the confounding of study interventions, matched periods were taken on one side of the study enrollment date. For PA and AF burden, Gaussian linear mixed models and a Bayesian mixed effect model were fitted and adjusted for age, sex, and device manufacturers. A Gaussian model was used to correlate daily activity minutes and AF%. Time splines were added to adjust for non-linear time effects. Outcomes are reported as mean activity minutes and daily AF%. Results: Comparing Pandemic vs. Pre-periods (N=82 periods; 55 male, 27 female), daily activity minutes decreased by a mean of 13.16±1.06 minutes/day, and daily AF burden increased by 16% [5%-26%]. Comparing Pre vs. Pre-Pre-Pandemic periods (N=60 periods; 41 male, 19 female), mean activity decreased by 2.28±1.13 mins/day, and AF burden increased by 57% [50%-64%]. A significant negative correlation between activity and AF burden was demonstrated (coefficient -2.0, 95% CI -2.4, -1.6). A decrease in 2.0 activity minutes was associated with a 10% increase in AF burden. Conclusions: This natural history analysis of PA and AF burden demonstrated decreases in activity and increases in AF burden with time and the pandemic. Activity and AF burden were significantly negatively correlated.

ID 24546 Poster Board 103 G protein-coupled receptor kinase 2 (GRK2) is upregulated in the injured heart, contributes to heart failure (HF) pathogenesis and has emerged as a therapeutic target for cardiac disease. One approach used to target GRK2 activity in murine HF models involves the genetic expression of peptide inhibitors via C- or N- terminal fragments of GRK2. Herein, we subjected transgenic mice with cardiac restricted expression an N-terminal fragment of GRK2 (βARKnt) to pressure overload and found that these mice exhibit sexual dimorphism in HF and atrial susceptibility. This recapitulates the clinical data indicating essential differences between men and women in HF type, epidemiology and pathophysiology. Men are predisposed to the development of HF with reduced ejection fraction due to heart-related conditions. Women, meanwhile, have a higher incidence of HF with preserved ejection fraction due to comorbidities and sex-related factors. The poor inclusion of females in clinical trials and murine studies has contributed to a poor understanding of disease behavior in women. This study carefully dissects both the acute and chronic responses of non-transgenic and βARKnt female mice to trans-aortic constriction (TAC) surgery, and whether they differ from our previous observance in males. Interestingly, while left ventricular (LV) posterior wall thickness during diastole and systole and cardiac ejection fraction were all significantly higher in βARKnt mice prior to surgery, our data demonstrate proportional LV hypertrophic growth in both the βARKnt and non-transgenic mice in response to acute cardiac stress. During chronic stress, in contrast to non-transgenic male mice that transition to heart failure from 10-14 weeks after TAC, ejection fraction was indistinguishable between non-transgenic Sham and TAC females, with elevated yet consistent levels in the βARKnt TAC and more-so Sham females. βARKnt female mice exhibited a robust and continual increase in asymmetric hypertrophy across the 14 week time course. This is in contrast to non-transgenic female mice that have mild, stable and symmetric hypertrophic growth. This is also in contrast to the stable hypertrophy and cardioprotection observed in βARKnt male mice, and opposite to the switch from hypertrophy to wall thinning observed in non-transgenic male mice transitioning into maladaptive remodeling and dilated cardiomyopathy. Additionally, lung weight normalized to tibia length was only elevated in the βARKnt TAC female mice, suggesting pulmonary congestion. Analysis of Masson’s Trichrome and WGA staining demonstrated that unlike in βARKnt male mice, fibrosis and cardiac hypertrophy are evident in βARKnt female mice at baseline and more pronounced following acute and chronic pressure overload stress. Further, these data suggest an increase in immune cell infiltration that is under further investigation. Data in our male mice suggested enhanced metabolic flexibility as part of the mechanism of cardioprotection by βARKnt; however, the opposite was observed in females. Alternatively, RNAseq data suggests dysregulation of phagosome formation and wound healing responses as possible mechanisms for the increased pathological remodeling in our βARKnt female mice that will serve as a focus of ongoing and future studies. Overall, increasing our knowledge about the underlying molecular mechanisms involved in the male versus female failing heart will contribute to more effective sex-specific therapeutic strategies.

BACKGROUND:Genomewide association studies have associated >100 genetic loci with atrial fibrillation (AF), but establishing causal genes contributing to AF remains challenging.OBJECTIVE:The purpose of this study was to determine candidate novel causal genes and mechanistic pathways associated with AF risk loci by incorporating gene expression and coexpression analyses and to provide a resource for functional studies and targeting of AF-associated genes.METHODS:Cis-expression quantitative trait loci were identified for candidate genes near AF risk variants in human left atrial tissues. Coexpression partners were identified for each candidate gene. Weighted gene coexpression network analysis (WGCNA) identified modules and modules with overrepresentation of candidate AF genes. Ingenuity pathway analysis (IPA) was applied to the coexpression partners of each candidate gene. IPA and gene set over representation analysis were applied to each WGCNA module.RESULTS:One hundred sixty-six AF-risk single nucleotide polymorphisms were located in 135 loci. Eighty-one novel genes not previously annotated as putative AF risk genes were identified. IPA identified mitochondrial dysfunction, oxidative stress, epithelial adherens junction signaling, and sirtuin signaling as the most frequent significant pathways. WGCNA characterized 64 modules (candidate AF genes overrepresented in 8), represented by cell injury, death, stress, developmental, metabolic/mitochondrial, transcription/translation, and immune activation/inflammation regulatory pathways.CONCLUSION:Candidate gene coexpression analyses suggest significant roles for cellular stress and remodeling in AF, supporting a dual risk model for AF: Genetic susceptibility to AF may not manifest until later in life, when cellular stressors overwhelm adaptive responses. These analyses also provide a novel resource to guide functional studies on potential causal AF genes.

Introduction: Social media allows for the rapid, global dissemination of new cardiac imaging knowledge. The hashtag #YesCCT originated in 2018 with the goal to promote and educate the field of cardiac computed tomography (CCT) on social media. The long-term impact of this novel hashtag has not been previously assessed.

A doença cardiovascular aterosclerótica (DCVA) é uma doença sistêmica iniciada por um influxo endotelial de partículas lipídicas, incluindo lipoproteínas de baixa densidade (LDL), com subsequente ativação endotelial via recrutamento local de células inflamatórias. Esse processo local– desencadeado pela exposição determinada pela idade a fatores de risco da DCVA genéticos, ambientais e de estilo de vida– é o primeiro passo de um processo que levará a um estado inflamatório sistêmico crônico e de baixo grau. A exposição prolongada do endotélio aos [...]

Introduction: Intermediate-term outcomes of cardiac computed tomography angiography (CCTA) in low to intermediate risk acute coronary syndromes (ACS) is uncertain. There is scarce data on associated plaque findings of atherosclerosis imaging-quantitative computed tomography (AI-QCT) guided by artificial intelligence in these patients

Introduction: Atherosclerosis imaging applied to quantitative computed tomography (AI-QCT) now allows for rapid, accurate assessment of coronary vessel morphology, stenosis and atherosclerosis evaluation through artificial intelligence. AI-QCT may improve identification of patients that would benefit from preventive therapies beyond current guidelines.

Short Editorial related to the article: Epicardial Fat Volume Is Associated with Endothelial Dysfunction, but not with Coronary Calcification: From the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

Atrial fibrillation (AF) risk is heritable. High rate electrical activity in AF requires increased energy. Atrial mitochondrial structure and function are altered in AF patients in an effort to generate adequate ATP through oxidative phosphorylation. Genomic studies have identified putative AF risk genes, but the association of AF risk genes with expression of mitochondrial genes is unclear. We tested the hypothesis that putative AF risk genes are co-expressed with mitochondrial genes that play a role in atrial energy production. RNA-seq was performed on left atrial appendage (LAA) tissues obtained from 251 cardiac surgery patients. RNA coexpression profiles were evaluated for 222 putative AF risk genes. Genes encoding proteins that localize to the mitochondria were identified using MitoCarta 2.0. Changes in metabolic pathways were detected using Ingenuity Pathway Analysis (IPA). Our analysis identified 128 AF risk genes that coexpressed with at least one mitochondrial gene. The highest level of mitochondrial gene coexpression was evident with PCCB, in which 30% (253 of 848) of coexpressed genes were mitochondrial. CASQ2 (24%, 104 of 431) and ASAH1 (20%, 37 of 182) also showed high levels of mitochondrial gene coexpression. The IPA Oxidative Phosphorylation Pathway was significantly altered (p<0.05) for 26 AF risk genes, with CASQ2 (9.42E-79), MYH6 (4.73E-78), YWHAE (4.96E-75), and TTN (4.30E-71) the most strongly associated (Table). Additionally, 12 AF risk genes coexpressed with genes encoded by mitochondrial DNA (mtDNA) (Table). ASAH1, CASQ2, MYH6, NACA, NUCKS1, PLN, TTN, and YWHAE coexpressed with all 13 mtDNA encoded components of the electron transport chain. Many AF risk genes show significant coexpression with mitochondrial genes. We propose that genetic risk scores based on these AF risk genes may identify a subset of AF patients that would benefit from AF therapies that enhance metabolic activity.

Atrial fibrillation (AF) is strongly associated with risk of stroke and heart failure. AF promotes atrial remodeling that increases risk of stroke due to left atrial thrombogenesis, and increases energy demand to support high rate electrical activity and muscle contraction. While many transcriptomic studies have assessed AF-related changes in mRNA abundance, fewer studies have assessed proteomic changes. We performed a proteomic analysis on left atrial appendage (LAA) tissues from 12 patients with a history of AF undergoing elective surgery; atrial rhythm was documented at time of surgery. Proteomic analysis was performed using liquid chromatography with mass spectrometry (LC/MS-MS). Data-dependent analysis identified 3090 unique proteins, with 408 differentially expressed between sinus rhythm and AF. Ingenuity Pathway Analysis of differentially expressed proteins identified mitochondrial dysfunction, oxidative phosphorylation, and sirtuin signaling among the most affected pathways. Increased abundance of electron transport chain (ETC) proteins in AF was accompanied by decreased expression of ETC complex assembly factors, tricarboxylic acid cycle proteins, and other key metabolic modulators. Discordant changes were also evident in the contractile unit with both up and downregulation of key components. Similar pathways were affected in a comparison of patients with a history of persistent vs. paroxysmal AF, presenting for surgery in sinus rhythm. Together, these data suggest that while the LAA attempts to meet the energetic demands of AF, an uncoordinated response may reduce ATP availability, contribute to tissue contractile and electrophysiologic heterogeneity, and promote a progression of AF from paroxysmal episodes to development of a substrate amenable to persistent arrhythmia.

Background: We hypothesized that computerized morphological analysis of the left atrium (LA) and pulmonary veins (PVs) via fractal measurements of shape and texture features of the LA myocardial wall could predict atrial fibrillation (AF) recurrence after ablation. Methods: Preablation contrast computed tomography scans were collected for 203 patients who underwent AF ablation. The LA body, PVs, and myocardial wall were segmented using a semi-automated region growing method. Twenty-eight fractal-based shape and texture-based features were extracted from resulting segments. The top features most associated with postablation recurrence were identified using feature selection and subsequently evaluated with a Random Forest classifier. Feature selection and classifier construction were performed on a discovery cohort (D-1) of 137 patients; classifiers were subsequently validated on an independent set (D-2) of 66 patients. Dedicated classifiers to capture the fractal and morphological properties of LA body (C-LA), PVs (C-PV), and LA myocardial (C-LAM) tissue were constructed, as well as a model (C-All) capturing properties of all segmented compartments. Fractal-based models were also compared against a model employing machine estimation of LA volume. To assess the effect of clinical parameters, such as AF type and catheter technique, a clinical model (C-clin) was also compared against C-All. Results: Statistically significant differences were observed for fractal features of C-LA, C-LAM, and C-All in distinguishing AF recurrence (P<0.001) on D-1. Using the 5 top features, C-All had the best prediction performance (area under the receiver operating characteristic curve [AUROC], 0.81 [95% CI, 0.78-0.85]), followed by C-PV (AUROC, 0.78 [95% CI, 0.74-0.80]), and C-LA (AUROC, 0.70 [95% CI, 0.63-0.78]) on D-2. The clinical parameter model C-clin yielded an AUROC, 0.70 (95% CI, 0.65-0.77), while the atrial volume model yielded an AUROC, 0.59. Combining C-All and C-clin on D-2 improved the AUROC to 0.87 (95% CI, 0.82-0.93). Conclusions: Fractal measurements of the LA, PVs, and atrial myocardium on computed tomography scans were associated with likelihood of postablation AF recurrence.

Introduction: Atrial fibrillation (AF) increases energy demand for contractile and electrical activity. Changes in left atrial (LA) protein expression of AF patients are poorly characterized. Hypothesis: Mitochondrial protein expression in patients with AF is altered in an attempt to meet increased energy demand. Methods: LA appendage tissue was obtained from 198 patients undergoing Maze surgery. At the time of surgery, 80 were in sinus rhythm (SR) (50 paroxysmal AF, 30 persistent AF) and 118 in AF (65 persistent AF, 53 permanent AF). Protein content was assessed by mass spectrometry and 2539 proteins were identified. Results: In AF compared to SR, 257 proteins were differentially expressed (q<0.05); 44 of 62 mitochondrial proteins detected (MitoCarta 3.0) were increased. KEGG pathway analysis revealed Oxidative Phosphorylation was increased (p=1.01E-3) in AF, including 17 subunits of the electron transport chain (A). The Hypertrophic Cardiomyopathy pathway was decreased (p=1.01E-03). Expression of ryanodine receptor, and troponin and tropomyosin subunits decreased, but tropomyosin 4 and myosin heavy chain 9 and 10 increased (B), providing evidence of changes in myofibrillar and calcium regulatory proteins in AF. Among 39 putative AF risk genes detectable at the protein level, 8 were altered in AF (C). The Tricarboxylic Acid Cycle KEGG pathway was decreased (p=2.55E-3) in patients with permanent compared to persistent AF, with no significant changes in other cellular pathways or protein expression of putative AF risk genes. Conclusions: In one of the largest proteomic datasets in human LA to date, we find that expression of proteins in metabolic, myofibrillar, and calcium regulation pathways is altered in patients with AF. Additional metabolic changes were detected with progression to permanent AF. These data identify proteins that are altered in patients with AF providing insight into cellular pathways that may be targeted for AF prevention and therapy.