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14 results on '"Siland, Joylene E."'

1. Genetic Risk Prediction of Atrial Fibrillation

Author

Lubitz, Steven A, Yin, Xiaoyan, Lin, Henry J, Kolek, Matthew, Smith, J Gustav, Trompet, Stella, Rienstra, Michiel, Rost, Natalia S, Teixeira, Pedro L, Almgren, Peter, Anderson, Christopher D, Chen, Lin Y, Engström, Gunnar, Ford, Ian, Furie, Karen L, Guo, Xiuqing, Larson, Martin G, Lunetta, Kathryn L, Macfarlane, Peter W, Psaty, Bruce M, Soliman, Elsayed Z, Sotoodehnia, Nona, Stott, David J, Taylor, Kent D, Weng, Lu-Chen, Yao, Jie, Geelhoed, Bastiaan, Verweij, Niek, Siland, Joylene E, Kathiresan, Sekar, Roselli, Carolina, Roden, Dan M, van der Harst, Pim, Darbar, Dawood, Jukema, J Wouter, Melander, Olle, Rosand, Jonathan, Rotter, Jerome I, Heckbert, Susan R, Ellinor, Patrick T, Alonso, Alvaro, and Benjamin, Emelia J

Subjects
Epidemiology, Health Sciences, Stroke, Cardiovascular, Prevention, Brain Disorders, Heart Disease, Genetics, Clinical Research, Aged, Atrial Fibrillation, Female, Humans, Incidence, Male, Middle Aged, Risk Factors, atrial fibrillation, atrial flutter, forecasting, genetic association studies, stroke, AFGen Consortium, 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

BackgroundAtrial fibrillation (AF) has a substantial genetic basis. Identification of individuals at greatest AF risk could minimize the incidence of cardioembolic stroke.MethodsTo determine whether genetic data can stratify risk for development of AF, we examined associations between AF genetic risk scores and incident AF in 5 prospective studies comprising 18 919 individuals of European ancestry. We examined associations between AF genetic risk scores and ischemic stroke in a separate study of 509 ischemic stroke cases (202 cardioembolic [40%]) and 3028 referents. Scores were based on 11 to 719 common variants (≥5%) associated with AF at P values ranging from

Published
2017

3. Genetic Susceptibility for Atrial Fibrillation in Patients Undergoing Atrial Fibrillation Ablation

Author

Shoemaker, M. Benjamin, Husser, Daniela, Roselli, Carolina, Al Jazairi, Meelad, Chrispin, Jonathan, Kühne, Michael, Neumann, Benjamin, Knight, Stacey, Sun, Han, Mohanty, Sanghamitra, Shaffer, Christian, Thériault, Sébastien, Rinke, Lauren Lee, Siland, Joylene E., Crawford, Diane M., Ueberham, Laura, Zardkoohi, Omeed, Büttner, Petra, Geelhoed, Bastiaan, Blum, Steffen, Aeschbacher, Stefanie, Smith, Jonathan D., Van Wagoner, David R., Freudling, Rebecca, Müller-Nurasyid, Martina, Montgomery, Jay, Yoneda, Zachary, Wells, Quinn, Issa, Tariq, Weeke, Peter, Jacobs, Victoria, Van Gelder, Isabelle C., Hindricks, Gerhard, Barnard, John, Calkins, Hugh, Darbar, Dawood, Michaud, Greg, Kääb, Stefan, Ellinor, Patrick, Natale, Andrea, Chung, Mina, Nazarian, Saman, Cutler, Michael J., Sinner, Moritz F., Conen, David, Rienstra, Michiel, Bollmann, Andreas, Roden, Dan M., and Lubitz, Steven

Published
2020
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4. Multi-ethnic genome-wide association study for atrial fibrillation

Author

Roselli, Carolina, Chaffin, Mark D., Weng, Lu-Chen, Aeschbacher, Stefanie, Ahlberg, Gustav, Albert, Christine M., Almgren, Peter, Alonso, Alvaro, Anderson, Christopher D., Aragam, Krishna G., Arking, Dan E., Barnard, John, Bartz, Traci M., Benjamin, Emelia J., Bihlmeyer, Nathan A., Bis, Joshua C., Bloom, Heather L., Boerwinkle, Eric, Bottinger, Erwin B., Brody, Jennifer A., Calkins, Hugh, Campbell, Archie, Cappola, Thomas P., Carlquist, John, Chasman, Daniel I., Chen, Lin Y., Chen, Yii-Der Ida, Choi, Eue-Keun, Choi, Seung Hoan, Christophersen, Ingrid E., Chung, Mina K., Cole, John W., Conen, David, Cook, James, Crijns, Harry J., Cutler, Michael J., Damrauer, Scott M., Daniels, Brian R., Darbar, Dawood, Delgado, Graciela, Denny, Joshua C., Dichgans, Martin, Dörr, Marcus, Dudink, Elton A., Dudley, Samuel C., Esa, Nada, Esko, Tonu, Eskola, Markku, Fatkin, Diane, Felix, Stephan B., Ford, Ian, Franco, Oscar H., Geelhoed, Bastiaan, Grewal, Raji P., Gudnason, Vilmundur, Guo, Xiuqing, Gupta, Namrata, Gustafsson, Stefan, Gutmann, Rebecca, Hamsten, Anders, Harris, Tamara B., Hayward, Caroline, Heckbert, Susan R., Hernesniemi, Jussi, Hocking, Lynne J., Hofman, Albert, Horimoto, Andrea R. V. R., Huang, Jie, Huang, Paul L., Huffman, Jennifer, Ingelsson, Erik, Ipek, Esra Gucuk, Ito, Kaoru, Jimenez-Conde, Jordi, Johnson, Renee, Jukema, J. Wouter, Kääb, Stefan, Kähönen, Mika, Kamatani, Yoichiro, Kane, John P., Kastrati, Adnan, Kathiresan, Sekar, Katschnig-Winter, Petra, Kavousi, Maryam, Kessler, Thorsten, Kietselaer, Bas L., Kirchhof, Paulus, Kleber, Marcus E., Knight, Stacey, Krieger, Jose E., Kubo, Michiaki, Launer, Lenore J., Laurikka, Jari, Lehtimäki, Terho, Leineweber, Kirsten, Lemaitre, Rozenn N., Li, Man, Lim, Hong Euy, Lin, Henry J., Lin, Honghuang, Lind, Lars, Lindgren, Cecilia M., Lokki, Marja-Liisa, London, Barry, Loos, Ruth J. F., Low, Siew-Kee, Lu, Yingchang, Lyytikäinen, Leo-Pekka, Macfarlane, Peter W., Magnusson, Patrik K., Mahajan, Anubha, Malik, Rainer, Mansur, Alfredo J., Marcus, Gregory M., Margolin, Lauren, Margulies, Kenneth B., März, Winfried, McManus, David D., Melander, Olle, Mohanty, Sanghamitra, Montgomery, Jay A., Morley, Michael P., Morris, Andrew P., Müller-Nurasyid, Martina, Natale, Andrea, Nazarian, Saman, Neumann, Benjamin, Newton-Cheh, Christopher, Niemeijer, Maartje N., Nikus, Kjell, Nilsson, Peter, Noordam, Raymond, Oellers, Heidi, Olesen, Morten S., Orho-Melander, Marju, Padmanabhan, Sandosh, Pak, Hui-Nam, Paré, Guillaume, Pedersen, Nancy L., Pera, Joanna, Pereira, Alexandre, Porteous, David, Psaty, Bruce M., Pulit, Sara L., Pullinger, Clive R., Rader, Daniel J., Refsgaard, Lena, Ribasés, Marta, Ridker, Paul M., Rienstra, Michiel, Risch, Lorenz, Roden, Dan M., Rosand, Jonathan, Rosenberg, Michael A., Rost, Natalia, Rotter, Jerome I., Saba, Samir, Sandhu, Roopinder K., Schnabel, Renate B., Schramm, Katharina, Schunkert, Heribert, Schurman, Claudia, Scott, Stuart A., Seppälä, Ilkka, Shaffer, Christian, Shah, Svati, Shalaby, Alaa A., Shim, Jaemin, Shoemaker, M. Benjamin, Siland, Joylene E., Sinisalo, Juha, Sinner, Moritz F., Slowik, Agnieszka, Smith, Albert V., Smith, Blair H., Smith, J. Gustav, Smith, Jonathan D., Smith, Nicholas L., Soliman, Elsayed Z., Sotoodehnia, Nona, Stricker, Bruno H., Sun, Albert, Sun, Han, Svendsen, Jesper H., Tanaka, Toshihiro, Tanriverdi, Kahraman, Taylor, Kent D., Teder-Laving, Maris, Teumer, Alexander, Thériault, Sébastien, Trompet, Stella, Tucker, Nathan R., Tveit, Arnljot, Uitterlinden, Andre G., Van Der Harst, Pim, Van Gelder, Isabelle C., Van Wagoner, David R., Verweij, Niek, Vlachopoulou, Efthymia, Völker, Uwe, Wang, Biqi, Weeke, Peter E., Weijs, Bob, Weiss, Raul, Weiss, Stefan, Wells, Quinn S., Wiggins, Kerri L., Wong, Jorge A., Woo, Daniel, Worrall, Bradford B., Yang, Pil-Sung, Yao, Jie, Yoneda, Zachary T., Zeller, Tanja, Zeng, Lingyao, Lubitz, Steven A., Lunetta, Kathryn L., and Ellinor, Patrick T.

Published
2018
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7. Role of genetics in atrial fibrillation management.

Author

Rienstra, Michiel, Siland, Joylene E, and Ellinor, Patrick T

Subjects
ATRIAL fibrillation diagnosis, ATRIAL fibrillation treatment, ATRIAL fibrillation, RESEARCH funding
Abstract

Atrial fibrillation (AF) management has significantly improved during the career of professor Crijns. Research was implemented into guidelines and clinical practice. However, despite advances in AF management, large differences between individual treatment responses still exist and the mechanisms underlying initiation and perpetuation of AF are not completely understood. International collaborations have revealed the genetic contribution to AF and steps towards improving AF management are being made. In this short review, the most important paradigms shifts in the field of AF genetics are recognized and the future role of genetics in personalized management of AF is discussed. [ABSTRACT FROM AUTHOR]

Published
2021
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9. Telomere length and incident atrial fibrillation – data of the PREVEND cohort.

Author

Siland, Joylene E., Geelhoed, Bastiaan, van Gelder, Isabelle C., van der Harst, Pim, and Rienstra, Michiel

Subjects
*TELOMERES, *ATRIAL fibrillation risk factors, *POLYMERASE chain reaction, *BODY mass index, *DATA analysis, *COHORT analysis
Abstract

Background: The incidence of atrial fibrillation (AF) increases with age. Telomere length is considered a marker of biological ageing. We investigated the association between leukocyte telomere length and incident AF in the Dutch Prevention of Renal and Vascular End-stage Disease (PREVEND) study. Methods: We included 7775 individuals without prevalent AF, and with leukocyte telomere length measured. Mean telomere length was determined by a monochrome multiplex quantitative polymerase chain reaction-based assay. Results: Mean age of our cohort was 49±13 years, and 50% were men. During a mean follow-up of 11.4±2.9 years incident AF was detected in 367 (4.7%) individuals. Telomere length was shorter in individuals developing incident AF compared to those without AF (p = 0.013). Incident AF was inversely related to the telomere length. In the quartile with the longest telomere length 68 (3.5%) individuals developed AF, in the shortest telomere length quartile 100 (5.1%) individuals (p = 0.032). Telomere length was associated with incident AF in the second shortest telomere length quartile using the longest telomere length quartile as reference (hazard ratio 1.64; 95% CI 1.02–2.66; p = 0.043). After including age or AF risk factors, the relation between telomere length and incident AF was no longer significant. We found a significant interaction of age, male sex, systolic blood pressure, BMI, heart failure, and myocardial infarction with telomere length for the association with incident AF. Conclusions: We found that shorter leukocyte telomere length is not independently associated with incident AF in a community-based cohort. [ABSTRACT FROM AUTHOR]

Published
2017
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10. Cluster Individuals Based on Phenotype and Determine the Risk for Atrial Fibrillation in the PREVEND and Framingham Heart Study Populations.

Author

Rienstra, Michiel, Geelhoed, Bastiaan, Yin, Xiaoyan, Siland, Joylene E., Vermond, Rob A., Mulder, Bart A., Van Der Harst, Pim, Hillege, Hans L., Benjamin, Emelia J., and Van Gelder, Isabelle C.

Subjects
ATRIAL fibrillation diagnosis, ATRIAL fibrillation treatment, PHENOTYPES, LATENT class analysis (Statistics), LONGITUDINAL method
Abstract

Background: Risk prediction of atrial fibrillation (AF) is of importance to improve the early diagnosis and treatment of AF. Latent class analysis takes into account the possible existence of classes of individuals each with shared risk factors, and maybe a better method of incorporating the phenotypic heterogeneity underlying AF. Methods and findings: Two prospective community-based cohort studies from Netherlands and United States were used. Prevention of Renal and Vascular End-stage Disease (PREVEND) study, started in 1997, and the Framingham Heart Study (FHS) Offspring cohort started in 1971, both with 10-years follow-up. The main objective was to determine the risk of AF using a latent class analysis, and compare the discrimination and reclassification performance with traditional regression analysis. Mean age in PREVEND was 49±13 years, 49.8% were men. During follow-up, 250(3%) individuals developed AF. We built a latent class model based on 18 risk factors. A model with 7 distinct classes (ranging from 341 to 1517 individuals) gave the optimum tradeoff between a high statistical model-likelihood and a low number of model parameters. All classes had a specific profile. The incidence of AF varied; class 1 0.0%, class 2 0.3%, class 3 7.5%, class 4 0.2%, class 5 1.3%, class 6 4.2%, class 7 21.7% (p<0.001). The discrimination (C-statistic 0.830 vs. 0.842, delta-C -0.013, p = 0.22) and reclassification (IDI -0.028, p<0.001, NRI -0.090, p = 0.049, and category-less-NRI -0.049, p = 0.495) performance of both models was comparable. The results were successfully replicated in a sample of the FHS study (n = 3162; mean age 58±9 years, 46.3% men). Conclusions: Latent class analysis to build an AF risk model is feasible. Despite the heterogeneity in number and severity of risk factors between individuals at risk for AF, latent class analysis produces distinguishable groups. [ABSTRACT FROM AUTHOR]

Published
2016
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11. Genome-wide association study reveals novel genetic loci: a new polygenic risk score for mitral valve prolapse.

Author

Roselli C, Yu M, Nauffal V, Georges A, Yang Q, Love K, Weng LC, Delling FN, Maurya SR, Schrölkamp M, Tfelt-Hansen J, Hagège A, Jeunemaitre X, Debette S, Amouyel P, Guan W, Muehlschlegel JD, Body SC, Shah S, Samad Z, Kyryachenko S, Haynes C, Rienstra M, Le Tourneau T, Probst V, Roussel R, Wijdh-Den Hamer IJ, Siland JE, Knowlton KU, Jacques Schott J, Levine RA, Benjamin EJ, Vasan RS, Horne BD, Muhlestein JB, Benfari G, Enriquez-Sarano M, Natale A, Mohanty S, Trivedi C, Shoemaker MB, Yoneda ZT, Wells QS, Baker MT, Farber-Eger E, Michelena HI, Lundby A, Norris RA, Slaugenhaupt SA, Dina C, Lubitz SA, Bouatia-Naji N, Ellinor PT, and Milan DJ

Subjects
Adult, Genetic Loci genetics, Genome-Wide Association Study, Humans, Latent TGF-beta Binding Proteins genetics, Proteomics, Risk Factors, Mitral Valve Prolapse genetics
Abstract

Aims: Mitral valve prolapse (MVP) is a common valvular heart disease with a prevalence of >2% in the general adult population. Despite this high incidence, there is a limited understanding of the molecular mechanism of this disease, and no medical therapy is available for this disease. We aimed to elucidate the genetic basis of MVP in order to better understand this complex disorder., Methods and Results: We performed a meta-analysis of six genome-wide association studies that included 4884 cases and 434 649 controls. We identified 14 loci associated with MVP in our primary analysis and 2 additional loci associated with a subset of the samples that additionally underwent mitral valve surgery. Integration of epigenetic, transcriptional, and proteomic data identified candidate MVP genes including LMCD1, SPTBN1, LTBP2, TGFB2, NMB, and ALPK3. We created a polygenic risk score (PRS) for MVP and showed an improved MVP risk prediction beyond age, sex, and clinical risk factors., Conclusion: We identified 14 genetic loci that are associated with MVP. Multiple analyses identified candidate genes including two transforming growth factor-β signalling molecules and spectrin β. We present the first PRS for MVP that could eventually aid risk stratification of patients for MVP screening in a clinical setting. These findings advance our understanding of this common valvular heart disease and may reveal novel therapeutic targets for intervention., (© The Author(s) 2022. Published by Oxford University Press on behalf of European Society of Cardiology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Published
2022
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12. Role of genetics in atrial fibrillation management.

Author

Rienstra M, Siland JE, and Ellinor PT

Subjects
Humans, Atrial Fibrillation diagnosis, Atrial Fibrillation genetics, Atrial Fibrillation therapy
Abstract

Atrial fibrillation (AF) management has significantly improved during the career of professor Crijns. Research was implemented into guidelines and clinical practice. However, despite advances in AF management, large differences between individual treatment responses still exist and the mechanisms underlying initiation and perpetuation of AF are not completely understood. International collaborations have revealed the genetic contribution to AF and steps towards improving AF management are being made. In this short review, the most important paradigms shifts in the field of AF genetics are recognized and the future role of genetics in personalized management of AF is discussed., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2021. For permissions, please email: journals.permissions@oup.com.)

Published
2021
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13. Erratum: Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation.

Author

Christophersen IE, Rienstra M, Roselli C, Yin X, Geelhoed B, Barnard J, Lin H, Arking DE, Smith AV, Albert CM, Chaffin M, Tucker NR, Li M, Klarin D, Bihlmeyer NA, Low SK, Weeke PE, Müller-Nurasyid M, Smith JG, Brody JA, Niemeijer MN, Dörr M, Trompet S, Huffman J, Gustafsson S, Schurmann C, Kleber ME, Lyytikäinen LP, Seppälä I, Malik R, R V R Horimoto A, Perez M, Sinisalo J, Aeschbacher S, Thériault S, Yao J, Radmanesh F, Weiss S, Teumer A, Choi SH, Weng LC, Clauss S, Deo R, Rader DJ, Shah SH, Sun A, Hopewell JC, Debette S, Chauhan G, Yang Q, Worrall BB, Paré G, Kamatani Y, Hagemeijer YP, Verweij N, Siland JE, Kubo M, Smith JD, Van Wagoner DR, Bis JC, Perz S, Psaty BM, Ridker PM, Magnani JW, Harris TB, Launer LJ, Shoemaker MB, Padmanabhan S, Haessler J, Bartz TM, Waldenberger M, Lichtner P, Arendt M, Krieger JE, Kähönen M, Risch L, Mansur AJ, Peters A, Smith BH, Lind L, Scott SA, Lu Y, Bottinger EB, Hernesniemi J, Lindgren CM, Wong JA, Huang J, Eskola M, Morris AP, Ford I, Reiner AP, Delgado G, Chen LY, Chen YI, Sandhu RK, Li M, Boerwinkle E, Eisele L, Lannfelt L, Rost N, Anderson CD, Taylor KD, Campbell A, Magnusson PK, Porteous D, Hocking LJ, Vlachopoulou E, Pedersen NL, Nikus K, Orho-Melander M, Hamsten A, Heeringa J, Denny JC, Kriebel J, Darbar D, Newton-Cheh C, Shaffer C, Macfarlane PW, Heilmann-Heimbach S, Almgren P, Huang PL, Sotoodehnia N, Soliman EZ, Uitterlinden AG, Hofman A, Franco OH, Völker U, Jöckel KH, Sinner MF, Lin HJ, Guo X, Dichgans M, Ingelsson E, Kooperberg C, Melander O, J F Loos R, Laurikka J, Conen D, Rosand J, van der Harst P, Lokki ML, Kathiresan S, Pereira A, Jukema JW, Hayward C, Rotter JI, März W, Lehtimäki T, Stricker BH, Chung MK, Felix SB, Gudnason V, Alonso A, Roden DM, Kääb S, Chasman DI, Heckbert SR, Benjamin EJ, Tanaka T, Lunetta KL, Lubitz SA, and Ellinor PT

Published
2017
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14. Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation.

Author

Christophersen IE, Rienstra M, Roselli C, Yin X, Geelhoed B, Barnard J, Lin H, Arking DE, Smith AV, Albert CM, Chaffin M, Tucker NR, Li M, Klarin D, Bihlmeyer NA, Low SK, Weeke PE, Müller-Nurasyid M, Smith JG, Brody JA, Niemeijer MN, Dörr M, Trompet S, Huffman J, Gustafsson S, Schurmann C, Kleber ME, Lyytikäinen LP, Seppälä I, Malik R, Horimoto ARVR, Perez M, Sinisalo J, Aeschbacher S, Thériault S, Yao J, Radmanesh F, Weiss S, Teumer A, Choi SH, Weng LC, Clauss S, Deo R, Rader DJ, Shah SH, Sun A, Hopewell JC, Debette S, Chauhan G, Yang Q, Worrall BB, Paré G, Kamatani Y, Hagemeijer YP, Verweij N, Siland JE, Kubo M, Smith JD, Van Wagoner DR, Bis JC, Perz S, Psaty BM, Ridker PM, Magnani JW, Harris TB, Launer LJ, Shoemaker MB, Padmanabhan S, Haessler J, Bartz TM, Waldenberger M, Lichtner P, Arendt M, Krieger JE, Kähönen M, Risch L, Mansur AJ, Peters A, Smith BH, Lind L, Scott SA, Lu Y, Bottinger EB, Hernesniemi J, Lindgren CM, Wong JA, Huang J, Eskola M, Morris AP, Ford I, Reiner AP, Delgado G, Chen LY, Chen YI, Sandhu RK, Li M, Boerwinkle E, Eisele L, Lannfelt L, Rost N, Anderson CD, Taylor KD, Campbell A, Magnusson PK, Porteous D, Hocking LJ, Vlachopoulou E, Pedersen NL, Nikus K, Orho-Melander M, Hamsten A, Heeringa J, Denny JC, Kriebel J, Darbar D, Newton-Cheh C, Shaffer C, Macfarlane PW, Heilmann-Heimbach S, Almgren P, Huang PL, Sotoodehnia N, Soliman EZ, Uitterlinden AG, Hofman A, Franco OH, Völker U, Jöckel KH, Sinner MF, Lin HJ, Guo X, Dichgans M, Ingelsson E, Kooperberg C, Melander O, Loos RJF, Laurikka J, Conen D, Rosand J, van der Harst P, Lokki ML, Kathiresan S, Pereira A, Jukema JW, Hayward C, Rotter JI, März W, Lehtimäki T, Stricker BH, Chung MK, Felix SB, Gudnason V, Alonso A, Roden DM, Kääb S, Chasman DI, Heckbert SR, Benjamin EJ, Tanaka T, Lunetta KL, Lubitz SA, and Ellinor PT

Subjects
Black or African American genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Quantitative Trait Loci, White People genetics, Atrial Fibrillation genetics, Genetic Loci
Abstract

Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death. Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups. To further define the genetic basis of atrial fibrillation, we performed large-scale, trans-ancestry meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 17,931 individuals with atrial fibrillation and 115,142 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,346 cases and 132,086 referents. We identified 12 new genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate the identification of new potential targets for drug discovery.

Published
2017
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