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491 results on '"Kornej, Jelena"'

1. Adherence of Mobile App-Based Surveys and Comparison With Traditional Surveys: eCohort Study

Author

Pathiravasan, Chathurangi H, Zhang, Yuankai, Trinquart, Ludovic, Benjamin, Emelia J, Borrelli, Belinda, McManus, David D, Kheterpal, Vik, Lin, Honghuang, Sardana, Mayank, Hammond, Michael M, Spartano, Nicole L, Dunn, Amy L, Schramm, Eric, Nowak, Christopher, Manders, Emily S, Liu, Hongshan, Kornej, Jelena, Liu, Chunyu, and Murabito, Joanne M

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundeCohort studies offer an efficient approach for data collection. However, eCohort studies are challenged by volunteer bias and low adherence. We designed an eCohort embedded in the Framingham Heart Study (eFHS) to address these challenges and to compare the digital data to traditional data collection. ObjectiveThe aim of this study was to evaluate adherence of the eFHS app-based surveys deployed at baseline (time of enrollment in the eCohort) and every 3 months up to 1 year, and to compare baseline digital surveys with surveys collected at the research center. MethodsWe defined adherence rates as the proportion of participants who completed at least one survey at a given 3-month period and computed adherence rates for each 3-month period. To evaluate agreement, we compared several baseline measures obtained in the eFHS app survey to those obtained at the in-person research center exam using the concordance correlation coefficient (CCC). ResultsAmong the 1948 eFHS participants (mean age 53, SD 9 years; 57% women), we found high adherence to baseline surveys (89%) and a decrease in adherence over time (58% at 3 months, 52% at 6 months, 41% at 9 months, and 40% at 12 months). eFHS participants who returned surveys were more likely to be women (adjusted odds ratio [aOR] 1.58, 95% CI 1.18-2.11) and less likely to be smokers (aOR 0.53, 95% CI 0.32-0.90). Compared to in-person exam data, we observed moderate agreement for baseline app-based surveys of the Physical Activity Index (mean difference 2.27, CCC=0.56), and high agreement for average drinks per week (mean difference 0.54, CCC=0.82) and depressive symptoms scores (mean difference 0.03, CCC=0.77). ConclusionsWe observed that eFHS participants had a high survey return at baseline and each 3-month survey period over the 12 months of follow up. We observed moderate to high agreement between digital and research center measures for several types of surveys, including physical activity, depressive symptoms, and alcohol use. Thus, this digital data collection mechanism is a promising tool to collect data related to cardiovascular disease and its risk factors.

Published
2021
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4. Epigenetic Age and the Risk of Incident Atrial Fibrillation

Author

Roberts, Jason D, Vittinghoff, Eric, Lu, Ake T, Alonso, Alvaro, Wang, Biqi, Sitlani, Colleen M, Mohammadi-Shemirani, Pedrum, Fornage, Myriam, Kornej, Jelena, Brody, Jennifer A, Arking, Dan E, Lin, Honghuang, Heckbert, Susan R, Prokic, Ivana, Ghanbari, Mohsen, Skanes, Allan C, Bartz, Traci M, Perez, Marco V, Taylor, Kent D, Lubitz, Steven A, Ellinor, Patrick T, Lunetta, Kathryn L, Pankow, James S, Paré, Guillaume, Sotoodehnia, Nona, Benjamin, Emelia J, Horvath, Steve, and Marcus, Gregory M

Subjects
Epidemiology, Health Sciences, Genetics, Aging, Heart Disease, Clinical Research, Cardiovascular, Good Health and Well Being, Aged, Atrial Fibrillation, DNA Methylation, Epigenesis, Genetic, Epigenomics, Female, Follow-Up Studies, Humans, Incidence, Male, Mendelian Randomization Analysis, Middle Aged, Models, Cardiovascular, Models, Genetic, atrial fibrillation, aging, genetics, epigenomics, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences, Sports science and exercise
Abstract

BackgroundThe most prominent risk factor for atrial fibrillation (AF) is chronological age; however, underlying mechanisms are unexplained. Algorithms using epigenetic modifications to the human genome effectively predict chronological age. Chronological and epigenetic predicted ages may diverge in a phenomenon referred to as epigenetic age acceleration (EAA), which may reflect accelerated biological aging. We sought to evaluate for associations between epigenetic age measures and incident AF.MethodsMeasures for 4 epigenetic clocks (Horvath, Hannum, DNA methylation [DNAm] PhenoAge, and DNAm GrimAge) and an epigenetic predictor of PAI-1 (plasminogen activator inhibitor-1) levels (ie, DNAm PAI-1) were determined for study participants from 3 population-based cohort studies. Cox models evaluated for associations with incident AF and results were combined via random-effects meta-analyses. Two-sample summary-level Mendelian randomization analyses evaluated for associations between genetic instruments of the EAA measures and AF.ResultsAmong 5600 participants (mean age, 65.5 years; female, 60.1%; Black, 50.7%), there were 905 incident AF cases during a mean follow-up of 12.9 years. Unadjusted analyses revealed all 4 epigenetic clocks and the DNAm PAI-1 predictor were associated with statistically significant higher hazards of incident AF, though the magnitudes of their point estimates were smaller relative to the associations observed for chronological age. The pooled EAA estimates for each epigenetic measure, with the exception of Horvath EAA, were associated with incident AF in models adjusted for chronological age, race, sex, and smoking variables. After multivariable adjustment for additional known AF risk factors that could also potentially function as mediators, pooled EAA measures for 2 clocks remained statistically significant. Five-year increases in EAA measures for DNAm GrimAge and DNAm PhenoAge were associated with 19% (adjusted hazard ratio [HR], 1.19 [95% CI, 1.09-1.31]; P

Published
2021

5. Rare Coding Variants Associated With Electrocardiographic Intervals Identify Monogenic Arrhythmia Susceptibility Genes: A Multi-Ancestry Analysis.

Author

Choi, Seung Hoan, Jurgens, Sean J, Haggerty, Christopher M, Hall, Amelia W, Halford, Jennifer L, Morrill, Valerie N, Weng, Lu-Chen, Lagerman, Braxton, Mirshahi, Tooraj, Pettinger, Mary, Guo, Xiuqing, Lin, Henry J, Alonso, Alvaro, Soliman, Elsayed Z, Kornej, Jelena, Lin, Honghuang, Moscati, Arden, Nadkarni, Girish N, Brody, Jennifer A, Wiggins, Kerri L, Cade, Brian E, Lee, Jiwon, Austin-Tse, Christina, Blackwell, Tom, Chaffin, Mark D, Lee, Christina J-Y, Rehm, Heidi L, Roselli, Carolina, Regeneron Genetics Center, Redline, Susan, Mitchell, Braxton D, Sotoodehnia, Nona, Psaty, Bruce M, Heckbert, Susan R, Loos, Ruth JF, Vasan, Ramachandran S, Benjamin, Emelia J, Correa, Adolfo, Boerwinkle, Eric, Arking, Dan E, Rotter, Jerome I, Rich, Stephen S, Whitsel, Eric A, Perez, Marco, Kooperberg, Charles, Fornwalt, Brandon K, Lunetta, Kathryn L, Ellinor, Patrick T, Lubitz, Steven A, and NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium

Subjects
Regeneron Genetics Center, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Humans, Long QT Syndrome, Death, Sudden, Cardiac, Genetic Predisposition to Disease, Electrocardiography, Heterozygote, Female, Male, Genetic Variation, Exome Sequencing, death, sudden, cardiac, epidemiology, genetics, genome, population, Clinical Research, Cardiovascular, Genetics, Heart Disease, Human Genome, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, death, sudden, cardiac
Abstract

BackgroundAlterations in electrocardiographic (ECG) intervals are well-known markers for arrhythmia and sudden cardiac death (SCD) risk. While the genetics of arrhythmia syndromes have been studied, relations between electrocardiographic intervals and rare genetic variation at a population level are poorly understood.MethodsUsing a discovery sample of 29 000 individuals with whole-genome sequencing from Trans-Omics in Precision Medicine and replication in nearly 100 000 with whole-exome sequencing from the UK Biobank and MyCode, we examined associations between low-frequency and rare coding variants with 5 routinely measured electrocardiographic traits (RR, P-wave, PR, and QRS intervals and corrected QT interval).ResultsWe found that rare variants associated with population-based electrocardiographic intervals identify established monogenic SCD genes (KCNQ1, KCNH2, and SCN5A), a controversial monogenic SCD gene (KCNE1), and novel genes (PAM and MFGE8) involved in cardiac conduction. Loss-of-function and pathogenic SCN5A variants, carried by 0.1% of individuals, were associated with a nearly 6-fold increased odds of the first-degree atrioventricular block (P=8.4×10-5). Similar variants in KCNQ1 and KCNH2 (0.2% of individuals) were associated with a 23-fold increased odds of marked corrected QT interval prolongation (P=4×10-25), a marker of SCD risk. Incomplete penetrance of such deleterious variation was common as over 70% of carriers had normal electrocardiographic intervals.ConclusionsOur findings indicate that large-scale high-depth sequence data and electrocardiographic analysis identifies monogenic arrhythmia susceptibility genes and rare variants with large effects. Known pathogenic variation in conventional arrhythmia and SCD genes exhibited incomplete penetrance and accounted for only a small fraction of marked electrocardiographic interval prolongation.

Published
2021

6. Genetic Determinants of Electrocardiographic P-Wave Duration and Relation to Atrial Fibrillation

Author

Weng, Lu-Chen, Hall, Amelia Weber, Choi, Seung Hoan, Jurgens, Sean J, Haessler, Jeffrey, Bihlmeyer, Nathan A, Grarup, Niels, Lin, Honghuang, Teumer, Alexander, Li-Gao, Ruifang, Yao, Jie, Guo, Xiuqing, Brody, Jennifer A, Müller-Nurasyid, Martina, Schramm, Katharina, Verweij, Niek, van den Berg, Marten E, van Setten, Jessica, Isaacs, Aaron, Ramírez, Julia, Warren, Helen R, Padmanabhan, Sandosh, Kors, Jan A, de Boer, Rudolf A, van der Meer, Peter, Sinner, Moritz F, Waldenberger, Melanie, Psaty, Bruce M, Taylor, Kent D, Völker, Uwe, Kanters, Jørgen K, Li, Man, Alonso, Alvaro, Perez, Marco V, Vaartjes, Ilonca, Bots, Michiel L, Huang, Paul L, Heckbert, Susan R, Lin, Henry J, Kornej, Jelena, Munroe, Patricia B, van Duijn, Cornelia M, Asselbergs, Folkert W, Stricker, Bruno H, van der Harst, Pim, Kääb, Stefan, Peters, Annette, Sotoodehnia, Nona, Rotter, Jerome I, Mook-Kanamori, Dennis O, Dörr, Marcus, Felix, Stephan B, Linneberg, Allan, Hansen, Torben, Arking, Dan E, Kooperberg, Charles, Benjamin, Emelia J, Lunetta, Kathryn L, Ellinor, Patrick T, and Lubitz, Steven A

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Research, Genetics, Heart Disease, Cardiovascular, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Atrial Fibrillation, Cardiac Myosins, Connectin, Electrocardiography, Genetic Variation, Genome-Wide Association Study, Homeodomain Proteins, Humans, Myosin Heavy Chains, NAV1.8 Voltage-Gated Sodium Channel, Quantitative Trait Loci, Transcription Factors, atrial fibrillation, electrophysiology, exome, genetic, genome-wide association studies, population, Medical Biotechnology, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

BackgroundThe P-wave duration (PWD) is an electrocardiographic measurement that represents cardiac conduction in the atria. Shortened or prolonged PWD is associated with atrial fibrillation (AF). We used exome-chip data to examine the associations between common and rare variants with PWD.MethodsFifteen studies comprising 64 440 individuals (56 943 European, 5681 African, 1186 Hispanic, 630 Asian) and ≈230 000 variants were used to examine associations with maximum PWD across the 12-lead ECG. Meta-analyses summarized association results for common variants; gene-based burden and sequence kernel association tests examined low-frequency variant-PWD associations. Additionally, we examined the associations between PWD loci and AF using previous AF genome-wide association studies.ResultsWe identified 21 common and low-frequency genetic loci (14 novel) associated with maximum PWD, including several AF loci (TTN, CAND2, SCN10A, PITX2, CAV1, SYNPO2L, SOX5, TBX5, MYH6, RPL3L). The top variants at known sarcomere genes (TTN, MYH6) were associated with longer PWD and increased AF risk. However, top variants at other loci (eg, PITX2 and SCN10A) were associated with longer PWD but lower AF risk.ConclusionsOur results highlight multiple novel genetic loci associated with PWD, and underscore the shared mechanisms of atrial conduction and AF. Prolonged PWD may be an endophenotype for several different genetic mechanisms of AF.

Published
2020

33. Abstract 14629: Rare Variants for Electrocardiographic Traits Identify Arrhythmia Susceptibility Genes

Author

Jurgens, Sean J, Choi, Seung Hoan, Haggerty, Christopher M, Hall, Amelia W, Halford, Jennifer, Morrill, Valerie, Weng, Lu Chen, Lagerman, Braxton, Mirshahi, Tooraj, Pettinger, Mary, Guo, Xiuqing, Kornej, Jelena, Lin, Honghuang, Moscati, Arden, Nadkarni, Girish, Brody, Jennifer, Wiggins, Kerri, Cade, Brian E, Lee, Jiwon, Austin-Tse, Christina, Blackwell, Tom, Chaffin, Mark, Lee, Christina J, Rehm, Heidi, Redline, Susan, Mitchell, Braxton D, Sotoodehnia, Nona, Psaty, Bruce M, Heckbert, Susan R, Loos, Ruth J, Vasan, Ramachandran S, Benjamin, Emelia J, Correa, Adolfo, Boerwinkle, Eric, Arking, Dan E, Rotter, Jerome I, Rich, Stephen, Whitsel, Eric A, Perez, Marco V, Kooperberg, Charles, Fornwalt, Brandon, Lunetta, Kathryn, Ellinor, Patrick T, and Lubitz, Steven A

Published
2020
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38. Association Between Electrocardiographic Age and Cardiovascular Events in Community Settings : The Framingham Heart Study

Author

Brant, Luisa C. C., Horta Ribeiro, Antônio, Pinto-Filho, Marcelo M., Kornej, Jelena, Preis, Sarah R., Fetterman, Jessica L., Eromosele, Oseiwe B., Magnani, Jared W., Murabito, Joanne M., Larson, Martin G., Benjamin, Emelia J., Ribeiro, Antonio L. P., Lin, Honghuang, Brant, Luisa C. C., Horta Ribeiro, Antônio, Pinto-Filho, Marcelo M., Kornej, Jelena, Preis, Sarah R., Fetterman, Jessica L., Eromosele, Oseiwe B., Magnani, Jared W., Murabito, Joanne M., Larson, Martin G., Benjamin, Emelia J., Ribeiro, Antonio L. P., and Lin, Honghuang

Abstract

BACKGROUND: Deep neural networks have been used to estimate age from ECGs, the electrocardiographic age (ECG-age), which predicts adverse outcomes. However, this prediction ability has been restricted to clinical settings or relatively short periods. We hypothesized that ECG-age is associated with death and cardiovascular outcomes in the long-standing community-based FHS (Framingham Heart Study). METHODS: We tested the association of ECG-age with chronological age in the FHS cohorts in ECGs from 1986 to 2021. We calculated the gap between chronological and ECG-age (& UDelta;age) and classified individuals as having normal, accelerated, or decelerated aging, if & UDelta;age was within, higher, or lower than the mean absolute error of the model, respectively. We assessed the associations of & UDelta;age, accelerated and decelerated aging with death or cardiovascular outcomes (atrial fibrillation, myocardial infarction, and heart failure) using Cox proportional hazards models adjusted for age, sex, and clinical factors. RESULTS:The study population included 9877 FHS participants (mean age, 55 & PLUSMN;13 years; 54.9% women) with 34 948 ECGs. ECG-age was correlated to chronological age (r=0.81; mean absolute error, 9 & PLUSMN;7 years). After 17 & PLUSMN;8 years of follow-up, every 10-year increase of & UDelta;age was associated with 18% increase in all-cause mortality (hazard ratio [HR], 1.18 [95% CI, 1.12-1.23]), 23% increase in atrial fibrillation risk (HR, 1.23 [95% CI, 1.17-1.29]), 14% increase in myocardial infarction risk (HR, 1.14 [95% CI, 1.05-1.23]), and 40% increase in heart failure risk (HR, 1.40 [95% CI, 1.30-1.52]), in multivariable models. In addition, accelerated aging was associated with a 28% increase in all-cause mortality (HR, 1.28 [95% CI, 1.14-1.45]), whereas decelerated aging was associated with a 16% decrease (HR, 0.84 [95% CI, 0.74-0.95]). CONCLUSIONS:ECG-age was highly correlated with chronological age in FHS. The dif

Published
2023
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43. Step Count, Self-reported Physical Activity, and Predicted 5-Year Risk of Atrial Fibrillation: Cross-sectional Analysis

Author

Shapira-Daniels, Ayelet, primary, Kornej, Jelena, additional, Spartano, Nicole L, additional, Wang, Xuzhi, additional, Zhang, Yuankai, additional, Pathiravasan, Chathurangi H, additional, Liu, Chunyu, additional, Trinquart, Ludovic, additional, Borrelli, Belinda, additional, McManus, David D, additional, Murabito, Joanne M, additional, Benjamin, Emelia J, additional, and Lin, Honghuang, additional

Published
2023
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44. Abstract P374: Perception of Short-Term and Lifetime Risk of Atrial Fibrillation: A Survey of American Heart Association Members

Author

Mondesir, Favel L, primary, Thorpe, Alistair, additional, Bradley, GerMya, additional, Hills, Mellanie T, additional, Cozier, Yvette, additional, Ko, Darae, additional, Kornej, Jelena, additional, Lubitz, Steven A, additional, Anderson, Christopher D, additional, Benjamin, Emelia J, additional, Fagerlin, Angela, additional, and Trinquart, Ludovic, additional

Published
2023
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