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232 results on '"Aragam, Krishna G."'

1. Rare coding variant analysis for human diseases across biobanks and ancestries

Author

Jurgens, Sean J., Wang, Xin, Choi, Seung Hoan, Weng, Lu-Chen, Koyama, Satoshi, Pirruccello, James P., Nguyen, Trang, Smadbeck, Patrick, Jang, Dongkeun, Chaffin, Mark, Walsh, Roddy, Roselli, Carolina, Elliott, Amanda L., Wijdeveld, Leonoor F. J. M., Biddinger, Kiran J., Kany, Shinwan, Rämö, Joel T., Natarajan, Pradeep, Aragam, Krishna G., Flannick, Jason, Burtt, Noël P., Bezzina, Connie R., Lubitz, Steven A., Lunetta, Kathryn L., and Ellinor, Patrick T.

Published
2024
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2. Genome-wide association study of thoracic aortic aneurysm and dissection in the Million Veteran Program

Author

Klarin, Derek, Devineni, Poornima, Sendamarai, Anoop K, Angueira, Anthony R, Graham, Sarah E, Shen, Ying H, Levin, Michael G, Pirruccello, James P, Surakka, Ida, Karnam, Purushotham R, Roychowdhury, Tanmoy, Li, Yanming, Wang, Minxian, Aragam, Krishna G, Paruchuri, Kaavya, Zuber, Verena, Shakt, Gabrielle E, Tsao, Noah L, Judy, Renae L, Vy, Ha My T, Verma, Shefali S, Rader, Daniel J, Do, Ron, Bavaria, Joseph E, Nadkarni, Girish N, Ritchie, Marylyn D, Burgess, Stephen, Guo, Dong-chuan, Ellinor, Patrick T, LeMaire, Scott A, Milewicz, Dianna M, Willer, Cristen J, Natarajan, Pradeep, Tsao, Philip S, Pyarajan, Saiju, and Damrauer, Scott M

Subjects
Cardiovascular, Genetics, Human Genome, Prevention, Aetiology, 2.1 Biological and endogenous factors, Humans, Genome-Wide Association Study, Veterans, Pedigree, Aortic Aneurysm, Thoracic, Aortic Dissection, VA Million Veteran Program, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

The current understanding of the genetic determinants of thoracic aortic aneurysms and dissections (TAAD) has largely been informed through studies of rare, Mendelian forms of disease. Here, we conducted a genome-wide association study (GWAS) of TAAD, testing ~25 million DNA sequence variants in 8,626 participants with and 453,043 participants without TAAD in the Million Veteran Program, with replication in an independent sample of 4,459 individuals with and 512,463 without TAAD from six cohorts. We identified 21 TAAD risk loci, 17 of which have not been previously reported. We leverage multiple downstream analytic methods to identify causal TAAD risk genes and cell types and provide human genetic evidence that TAAD is a non-atherosclerotic aortic disorder distinct from other forms of vascular disease. Our results demonstrate that the genetic architecture of TAAD mirrors that of other complex traits and that it is not solely inherited through protein-altering variants of large effect size.

Published
2023

3. Clinical and genetic associations of deep learning-derived cardiac magnetic resonance-based left ventricular mass

Author

Khurshid, Shaan, Lazarte, Julieta, Pirruccello, James P, Weng, Lu-Chen, Choi, Seung Hoan, Hall, Amelia W, Wang, Xin, Friedman, Samuel F, Nauffal, Victor, Biddinger, Kiran J, Aragam, Krishna G, Batra, Puneet, Ho, Jennifer E, Philippakis, Anthony A, Ellinor, Patrick T, and Lubitz, Steven A

Subjects
Epidemiology, Biomedical and Clinical Sciences, Health Sciences, Genetics, Bioengineering, Rehabilitation, Heart Disease, Cardiovascular, Human Genome, Assistive Technology, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Humans, Genome-Wide Association Study, Deep Learning, Magnetic Resonance Imaging, Cine, Cardiomyopathies, Magnetic Resonance Spectroscopy, Predictive Value of Tests
Abstract

Left ventricular mass is a risk marker for cardiovascular events, and may indicate an underlying cardiomyopathy. Cardiac magnetic resonance is the gold-standard for left ventricular mass estimation, but is challenging to obtain at scale. Here, we use deep learning to enable genome-wide association study of cardiac magnetic resonance-derived left ventricular mass indexed to body surface area within 43,230 UK Biobank participants. We identify 12 genome-wide associations (1 known at TTN and 11 novel for left ventricular mass), implicating genes previously associated with cardiac contractility and cardiomyopathy. Cardiac magnetic resonance-derived indexed left ventricular mass is associated with incident dilated and hypertrophic cardiomyopathies, and implantable cardioverter-defibrillator implant. An indexed left ventricular mass polygenic risk score ≥90th percentile is also associated with incident implantable cardioverter-defibrillator implant in separate UK Biobank (hazard ratio 1.22, 95% CI 1.05-1.44) and Mass General Brigham (hazard ratio 1.75, 95% CI 1.12-2.74) samples. Here, we perform a genome-wide association study of cardiac magnetic resonance-derived indexed left ventricular mass to identify 11 novel variants and demonstrate that cardiac magnetic resonance-derived and genetically predicted indexed left ventricular mass are associated with incident cardiomyopathy.

Published
2023

4. A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease

Author

Patel, Aniruddh P., Wang, Minxian, Ruan, Yunfeng, Koyama, Satoshi, Clarke, Shoa L., Yang, Xiong, Tcheandjieu, Catherine, Agrawal, Saaket, Fahed, Akl C., Ellinor, Patrick T., Tsao, Philip S., Sun, Yan V., Cho, Kelly, Wilson, Peter W. F., Assimes, Themistocles L., van Heel, David A., Butterworth, Adam S., Aragam, Krishna G., Natarajan, Pradeep, and Khera, Amit V.

Published
2023
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5. Genome-wide association meta-analysis of spontaneous coronary artery dissection identifies risk variants and genes related to artery integrity and tissue-mediated coagulation

Author

Adlam, David, Berrandou, Takiy-Eddine, Georges, Adrien, Nelson, Christopher P., Giannoulatou, Eleni, Henry, Joséphine, Ma, Lijiang, Blencowe, Montgomery, Turley, Tamiel N., Yang, Min-Lee, Chopade, Sandesh, Finan, Chris, Braund, Peter S., Sadeg-Sayoud, Ines, Iismaa, Siiri E., Kosel, Matthew L., Zhou, Xiang, Hamby, Stephen E., Cheng, Jenny, Liu, Lu, Tarr, Ingrid, Muller, David W. M., d’Escamard, Valentina, King, Annette, Brunham, Liam R., Baranowska-Clarke, Ania A., Debette, Stéphanie, Amouyel, Philippe, Olin, Jeffrey W., Patil, Snehal, Hesselson, Stephanie E., Junday, Keerat, Kanoni, Stavroula, Aragam, Krishna G., Butterworth, Adam S., Tweet, Marysia S., Gulati, Rajiv, Combaret, Nicolas, Kadian-Dodov, Daniella, Kalman, Jonathan M., Fatkin, Diane, Hingorani, Aroon D., Saw, Jacqueline, Webb, Tom R., Hayes, Sharonne N., Yang, Xia, Ganesh, Santhi K., Olson, Timothy M., Kovacic, Jason C., Graham, Robert M., Samani, Nilesh J., and Bouatia-Naji, Nabila

Published
2023
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6. Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants

Author

Aragam, Krishna G., Jiang, Tao, Goel, Anuj, Kanoni, Stavroula, Wolford, Brooke N., Atri, Deepak S., Weeks, Elle M., Wang, Minxian, Hindy, George, Zhou, Wei, Grace, Christopher, Roselli, Carolina, Marston, Nicholas A., Kamanu, Frederick K., Surakka, Ida, Venegas, Loreto Muñoz, Sherliker, Paul, Koyama, Satoshi, Ishigaki, Kazuyoshi, Åsvold, Bjørn O., Brown, Michael R., Brumpton, Ben, de Vries, Paul S., Giannakopoulou, Olga, Giardoglou, Panagiota, Gudbjartsson, Daniel F., Güldener, Ulrich, Haider, Syed M. Ijlal, Helgadottir, Anna, Ibrahim, Maysson, Kastrati, Adnan, Kessler, Thorsten, Kyriakou, Theodosios, Konopka, Tomasz, Li, Ling, Ma, Lijiang, Meitinger, Thomas, Mucha, Sören, Munz, Matthias, Murgia, Federico, Nielsen, Jonas B., Nöthen, Markus M., Pang, Shichao, Reinberger, Tobias, Schnitzler, Gavin, Smedley, Damian, Thorleifsson, Gudmar, von Scheidt, Moritz, Ulirsch, Jacob C., Arnar, David O., Burtt, Noël P., Costanzo, Maria C., Flannick, Jason, Ito, Kaoru, Jang, Dong-Keun, Kamatani, Yoichiro, Khera, Amit V., Komuro, Issei, Kullo, Iftikhar J., Lotta, Luca A., Nelson, Christopher P., Roberts, Robert, Thorgeirsson, Gudmundur, Thorsteinsdottir, Unnur, Webb, Thomas R., Baras, Aris, Björkegren, Johan L. M., Boerwinkle, Eric, Dedoussis, George, Holm, Hilma, Hveem, Kristian, Melander, Olle, Morrison, Alanna C., Orho-Melander, Marju, Rallidis, Loukianos S., Ruusalepp, Arno, Sabatine, Marc S., Stefansson, Kari, Zalloua, Pierre, Ellinor, Patrick T., Farrall, Martin, Danesh, John, Ruff, Christian T., Finucane, Hilary K., Hopewell, Jemma C., Clarke, Robert, Gupta, Rajat M., Erdmann, Jeanette, Samani, Nilesh J., Schunkert, Heribert, Watkins, Hugh, Willer, Cristen J., Deloukas, Panos, Kathiresan, Sekar, and Butterworth, Adam S.

Published
2022
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7. Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure.

Author

Shah, Sonia, Henry, Albert, Roselli, Carolina, Lin, Honghuang, Sveinbjörnsson, Garðar, Fatemifar, Ghazaleh, Hedman, Åsa K, Wilk, Jemma B, Morley, Michael P, Chaffin, Mark D, Helgadottir, Anna, Verweij, Niek, Dehghan, Abbas, Almgren, Peter, Andersson, Charlotte, Aragam, Krishna G, Ärnlöv, Johan, Backman, Joshua D, Biggs, Mary L, Bloom, Heather L, Brandimarto, Jeffrey, Brown, Michael R, Buckbinder, Leonard, Carey, David J, Chasman, Daniel I, Chen, Xing, Chen, Xu, Chung, Jonathan, Chutkow, William, Cook, James P, Delgado, Graciela E, Denaxas, Spiros, Doney, Alexander S, Dörr, Marcus, Dudley, Samuel C, Dunn, Michael E, Engström, Gunnar, Esko, Tõnu, Felix, Stephan B, Finan, Chris, Ford, Ian, Ghanbari, Mohsen, Ghasemi, Sahar, Giedraitis, Vilmantas, Giulianini, Franco, Gottdiener, John S, Gross, Stefan, Guðbjartsson, Daníel F, Gutmann, Rebecca, Haggerty, Christopher M, van der Harst, Pim, Hyde, Craig L, Ingelsson, Erik, Jukema, J Wouter, Kavousi, Maryam, Khaw, Kay-Tee, Kleber, Marcus E, Køber, Lars, Koekemoer, Andrea, Langenberg, Claudia, Lind, Lars, Lindgren, Cecilia M, London, Barry, Lotta, Luca A, Lovering, Ruth C, Luan, Jian'an, Magnusson, Patrik, Mahajan, Anubha, Margulies, Kenneth B, März, Winfried, Melander, Olle, Mordi, Ify R, Morgan, Thomas, Morris, Andrew D, Morris, Andrew P, Morrison, Alanna C, Nagle, Michael W, Nelson, Christopher P, Niessner, Alexander, Niiranen, Teemu, O'Donoghue, Michelle L, Owens, Anjali T, Palmer, Colin NA, Parry, Helen M, Perola, Markus, Portilla-Fernandez, Eliana, Psaty, Bruce M, Regeneron Genetics Center, Rice, Kenneth M, Ridker, Paul M, Romaine, Simon PR, Rotter, Jerome I, Salo, Perttu, Salomaa, Veikko, van Setten, Jessica, Shalaby, Alaa A, Smelser, Diane T, Smith, Nicholas L, Stender, Steen, and Stott, David J

Subjects
Regeneron Genetics Center, Humans, Atrial Fibrillation, Cardiomyopathies, Microfilament Proteins, Adaptor Proteins, Signal Transducing, Carrier Proteins, Muscle Proteins, Risk Factors, Case-Control Studies, Ventricular Function, Left, Cyclin-Dependent Kinase Inhibitor p21, Apoptosis Regulatory Proteins, Coronary Artery Disease, Heart Failure, Genome-Wide Association Study, Mendelian Randomization Analysis, Adaptor Proteins, Signal Transducing, Ventricular Function, Left
Abstract

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies.

Published
2020

8. Analysis of cardiac magnetic resonance imaging in 36,000 individuals yields genetic insights into dilated cardiomyopathy

Author

Pirruccello, James P, Bick, Alexander, Wang, Minxian, Chaffin, Mark, Friedman, Samuel, Yao, Jie, Guo, Xiuqing, Venkatesh, Bharath Ambale, Taylor, Kent D, Post, Wendy S, Rich, Stephen, Lima, Joao AC, Rotter, Jerome I, Philippakis, Anthony, Lubitz, Steven A, Ellinor, Patrick T, Khera, Amit V, Kathiresan, Sekar, and Aragam, Krishna G

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Genetics, Clinical Research, Rare Diseases, Cardiovascular, Heart Disease, Biomedical Imaging, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Cardiomyopathy, Dilated, Genome-Wide Association Study, Heart, Humans, Magnetic Resonance Imaging, Myocardium, Polymorphism, Single Nucleotide
Abstract

Dilated cardiomyopathy (DCM) is an important cause of heart failure and the leading indication for heart transplantation. Many rare genetic variants have been associated with DCM, but common variant studies of the disease have yielded few associated loci. As structural changes in the heart are a defining feature of DCM, we report a genome-wide association study of cardiac magnetic resonance imaging (MRI)-derived left ventricular measurements in 36,041 UK Biobank participants, with replication in 2184 participants from the Multi-Ethnic Study of Atherosclerosis. We identify 45 previously unreported loci associated with cardiac structure and function, many near well-established genes for Mendelian cardiomyopathies. A polygenic score of MRI-derived left ventricular end systolic volume strongly associates with incident DCM in the general population. Even among carriers of TTN truncating mutations, this polygenic score influences the size and function of the human heart. These results further implicate common genetic polymorphisms in the pathogenesis of DCM.

Published
2020

9. Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK Biobank

Author

Jurgens, Sean J., Choi, Seung Hoan, Morrill, Valerie N., Chaffin, Mark, Pirruccello, James P., Halford, Jennifer L., Weng, Lu-Chen, Nauffal, Victor, Roselli, Carolina, Hall, Amelia W., Oetjens, Matthew T., Lagerman, Braxton, vanMaanen, David P., Aragam, Krishna G., Lunetta, Kathryn L., Haggerty, Christopher M., Lubitz, Steven A., and Ellinor, Patrick T.

Published
2022
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10. Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure

Author

Levin, Michael G., Tsao, Noah L., Singhal, Pankhuri, Liu, Chang, Vy, Ha My T., Paranjpe, Ishan, Backman, Joshua D., Bellomo, Tiffany R., Bone, William P., Biddinger, Kiran J., Hui, Qin, Dikilitas, Ozan, Satterfield, Benjamin A., Yang, Yifan, Morley, Michael P., Bradford, Yuki, Burke, Megan, Reza, Nosheen, Charest, Brian, Judy, Renae L., Puckelwartz, Megan J., Hakonarson, Hakon, Khan, Atlas, Kottyan, Leah C., Kullo, Iftikhar, Luo, Yuan, McNally, Elizabeth M., Rasmussen-Torvik, Laura J., Day, Sharlene M., Do, Ron, Phillips, Lawrence S., Ellinor, Patrick T., Nadkarni, Girish N., Ritchie, Marylyn D., Arany, Zoltan, Cappola, Thomas P., Margulies, Kenneth B., Aragam, Krishna G., Haggerty, Christopher M., Joseph, Jacob, Sun, Yan V., Voight, Benjamin F., and Damrauer, Scott M.

Published
2022
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11. 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 RVR, 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, and Lin, Honghuang

Subjects
Biological Sciences, Genetics, Heart Disease, Cardiovascular, Human Genome, Biotechnology, 2.1 Biological and endogenous factors, Aetiology, Atrial Fibrillation, Case-Control Studies, Ethnicity, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Quantitative Trait Loci, Transcriptome, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

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.

Published
2018

12. Prognosis of patients with secondary mitral regurgitation and reduced ejection fraction

Author

Mowakeaa, Samer, Dwivedi, Aeshita, Grossman, Jason R, Parikh, Gaurav, Curillova, Zelmira, Aragam, Krishna G, Elmariah, Sammy, Kinlay, Scott, and Aragam, Jayashri

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Biomedical Imaging, Clinical Research, Heart Disease, Cardiovascular, death, heart failure hospitalization, secondary mitral regurgitation, Cardiovascular medicine and haematology
Abstract

ObjectiveThe impact of the severity of secondary mitral regurgitation (MR) on the risk of death and heart failure (HF) hospitalisations in patients with reduced left ventricular (LV) systolic function is poorly defined. The study sought to identify the incremental risk of secondary MR in patients with reduced LV systolic function.MethodsWe studied 615 consecutive patients with LV ejection fraction ≤35% by transthoracic echocardiography at a single medical centre. Patients were divided into three groups of no MR, mild, or moderate to severe MR. The median follow-up was 2.9 years. The primary endpoint was a composite of death or HF hospitalisations.ResultsCompared with patients with no MR, the risk of death or HF hospitalisations was higher for mild MR (HR 1.7, P=0.003) and moderate to severe MR (HR 2.7, P

Published
2018

13. Randomized prospective evaluation of genome sequencing versus standard-of-care as a first molecular diagnostic test

Author

Brockman, Deanna G., Austin-Tse, Christina A., Pelletier, Renée C., Harley, Caroline, Patterson, Candace, Head, Holly, Leonard, Courtney Elizabeth, O’Brien, Kimberly, Mahanta, Lisa M., Lebo, Matthew S., Lu, Christine Y., Natarajan, Pradeep, Khera, Amit V., Aragam, Krishna G., Kathiresan, Sekar, Rehm, Heidi L., and Udler, Miriam S.

Published
2021
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16. Polygenic scores in real-world cardiovascular risk prediction: the path forward for assessing worth?

Author

Pillutla, Virimchi and Aragam, Krishna G

Subjects
GENETIC risk score, DISEASE risk factors, ACUTE coronary syndrome, PROPENSITY score matching, BEHAVIORAL assessment
Abstract

The article discusses the use of polygenic risk scores (PRSs) in predicting cardiovascular disease (CVD) risk. PRSs are developed to quantify the risk posed by common DNA variants associated with CVD. While studies have shown that PRSs can improve CVD risk prediction, there is ongoing debate about their clinical relevance. The article highlights a study that implemented a CVD-PRS within the UK's National Health Service Health Check program and found that the PRS increased the proportion of individuals classified as high risk for CVD. However, there are limitations to the study, such as the potential for selection bias and the relatively healthy study population. The article concludes that further research is needed to evaluate the implementation and impact of PRSs in routine clinical practice. [Extracted from the article]

Published
2024
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18. Cardiovascular Disease Knowledge Portal: A Community Resource for Cardiovascular Disease Research

Author

Costanzo, Maria C., primary, Roselli, Carolina, additional, Brandes, MacKenzie, additional, Duby, Marc, additional, Hoang, Quy, additional, Jang, Dongkeun, additional, Koesterer, Ryan, additional, Kudtarkar, Parul, additional, Moriondo, Annie, additional, Nguyen, Trang, additional, Ruebenacker, Oliver, additional, Smadbeck, Patrick, additional, Sun, Ying, additional, Butterworth, Adam S., additional, Aragam, Krishna G., additional, Thomas Lumbers, R., additional, Khera, Amit V., additional, Lubitz, Steven A., additional, Ellinor, Patrick T., additional, Gaulton, Kyle J., additional, Flannick, Jason, additional, and Burtt, Noël P., additional

Published
2023
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23. Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants

Author

Aragam, Krishna G, Jiang, Tao, Goel, Anuj, Kanoni, Stavroula, Wolford, Brooke N, Atri, Deepak S, Weeks, Elle M, Wang, Minxian, Hindy, George, Zhou, Wei, Grace, Christopher, Roselli, Carolina, Marston, Nicholas A, Kamanu, Frederick K, Surakka, Ida, Venegas, Loreto Muñoz, Sherliker, Paul, Koyama, Satoshi, Ishigaki, Kazuyoshi, Åsvold, Bjørn O, Brown, Michael R, Brumpton, Ben, De Vries, Paul S, Giannakopoulou, Olga, Giardoglou, Panagiota, Gudbjartsson, Daniel F, Güldener, Ulrich, Haider, Syed M Ijlal, Helgadottir, Anna, Ibrahim, Maysson, Kastrati, Adnan, Kessler, Thorsten, Kyriakou, Theodosios, Konopka, Tomasz, Li, Ling, Ma, Lijiang, Meitinger, Thomas, Mucha, Sören, Munz, Matthias, Murgia, Federico, Nielsen, Jonas B, Nöthen, Markus M, Pang, Shichao, Reinberger, Tobias, Schnitzler, Gavin, Smedley, Damian, Thorleifsson, Gudmar, Von Scheidt, Moritz, Ulirsch, Jacob C, Danesh, John, Arnar, David O, Burtt, Noël P, Costanzo, Maria C, Flannick, Jason, Ito, Kaoru, Jang, Dong-Keun, Kamatani, Yoichiro, Khera, Amit V, Komuro, Issei, Kullo, Iftikhar J, Lotta, Luca A, Nelson, Christopher P, Roberts, Robert, Thorgeirsson, Gudmundur, Thorsteinsdottir, Unnur, Webb, Thomas R, Baras, Aris, Björkegren, Johan LM, Boerwinkle, Eric, Dedoussis, George, Holm, Hilma, Hveem, Kristian, Melander, Olle, Morrison, Alanna C, Orho-Melander, Marju, Rallidis, Loukianos S, Ruusalepp, Arno, Sabatine, Marc S, Stefansson, Kari, Zalloua, Pierre, Ellinor, Patrick T, Farrall, Martin, Ruff, Christian T, Finucane, Hilary K, Hopewell, Jemma C, Clarke, Robert, Gupta, Rajat M, Erdmann, Jeanette, Samani, Nilesh J, Schunkert, Heribert, Watkins, Hugh, Willer, Cristen J, Deloukas, Panos, Kathiresan, Sekar, Butterworth, Adam S, Aragam, Krishna G [0000-0003-3223-9131], Goel, Anuj [0000-0003-2307-4021], Kanoni, Stavroula [0000-0002-1691-9615], Wolford, Brooke N [0000-0003-3153-1552], Atri, Deepak S [0000-0001-8139-5419], Weeks, Elle M [0000-0002-4317-4444], Wang, Minxian [0000-0002-3753-508X], Zhou, Wei [0000-0001-7719-0859], Roselli, Carolina [0000-0001-5267-6756], Kamanu, Frederick K [0000-0001-7208-1047], Koyama, Satoshi [0000-0002-9286-0360], Ishigaki, Kazuyoshi [0000-0003-2881-0657], Åsvold, Bjørn O [0000-0003-3837-2101], Brumpton, Ben [0000-0002-3058-1059], Gudbjartsson, Daniel F [0000-0002-5222-9857], Güldener, Ulrich [0000-0001-5052-8610], Helgadottir, Anna [0000-0002-1806-2467], Kessler, Thorsten [0000-0003-3326-1621], Li, Ling [0000-0002-3280-9475], Mucha, Sören [0000-0002-1647-2526], Munz, Matthias [0000-0002-4728-3357], Murgia, Federico [0000-0002-3608-845X], Pang, Shichao [0000-0002-4111-2864], Smedley, Damian [0000-0002-5836-9850], Thorleifsson, Gudmar [0000-0003-4623-9087], von Scheidt, Moritz [0000-0001-7159-8271], Ulirsch, Jacob C [0000-0002-7947-0827], Costanzo, Maria C [0000-0001-9043-693X], Flannick, Jason [0000-0002-3618-795X], Ito, Kaoru [0000-0003-1843-773X], Khera, Amit V [0000-0001-6535-5839], Komuro, Issei [0000-0002-0714-7182], Kullo, Iftikhar J [0000-0002-6524-3471], Roberts, Robert [0000-0002-6792-4633], Webb, Thomas R [0000-0001-5998-8226], Baras, Aris [0000-0002-6830-3396], Björkegren, Johan LM [0000-0003-1945-7425], Holm, Hilma [0000-0002-9517-6636], Morrison, Alanna C [0000-0001-6381-4296], Orho-Melander, Marju [0000-0002-3578-2503], Stefansson, Kari [0000-0003-1676-864X], Farrall, Martin [0000-0003-4564-2165], Finucane, Hilary K [0000-0003-3864-9828], Clarke, Robert [0000-0002-9802-8241], Erdmann, Jeanette [0000-0002-4486-6231], Samani, Nilesh J [0000-0002-3286-8133], Schunkert, Heribert [0000-0001-6428-3001], Watkins, Hugh [0000-0002-5287-9016], Willer, Cristen J [0000-0001-5645-4966], Kathiresan, Sekar [0000-0002-3711-7101], Butterworth, Adam S [0000-0002-6915-9015], and Apollo - University of Cambridge Repository

Subjects
692/699/75/2, 631/208/205/2138, article, Humans, Coronary Artery Disease, Genome-Wide Association Study
Abstract

Funder: K.G.A. has received support from the American Heart Association Institute for Precision Cardiovascular Medicine (17IFUNP3384001), a KL2/Catalyst Medical Research Investigator Training (CMeRIT) award from the Harvard Catalyst (KL2 TR002542), and the NIH (1K08HL153937)., Funder: B.N.W is supported by the National Science Foundation Graduate Research Program (DGE 1256260)., Funder: I.S. is supported by a Precision Health Scholars Award from the University of Michigan Medical School., Funder: I.K., S.Ko., and K.It. are funded by the Japan Agency for Medical Research and Development, AMED, under Grant Numbers JP16ek0109070h0003, JP18kk0205008h0003, JP18kk0205001s0703, JP20km0405209, and JP20ek0109487. The BioBank Japan is supported by AMED under Grant Number JP20km0605001., Funder: J.L.M.B. acknowledges research support from NIH R01HL125863, American Heart Association (A14SFRN20840000), the Swedish Research Council (2018-02529) and Heart Lung Foundation (20170265) and the Foundation Leducq (PlaqueOmics: Novel Roles of Smooth Muscle and Other Matrix Producing Cells in Atherosclerotic Plaque Stability and Rupture, 18CVD02., Funder: P.S.dV was supported by American Heart Association grant number 18CDA34110116 and National Heart, Lung, and Blood Institute grant R01HL146860. The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I and HHSN268201700005I), R01HL087641, R01HL059367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research., Funder: O.G. has received funding from the British Heart Foundation (BHF) (FS/14/66/3129)., Funder: T.K. is supported by the Corona-Foundation (Junior Research Group Translational Cardiovascular Genomics) and the German Research Foundation (DFG) as part of the Sonderforschungsbereich SFB 1123 (B02)., Funder: D.S.A. has received support from a training grant from the NIH (T32HL007604)., Funder: N.P.B., M.C.C., J.F., and D.-K.J. have been funded by the National Institute of Diabetes and Digestive and Kidney Diseases (2UM1DK105554)., Funder: A.V.K. has been funded by 1K08HG010155 from the National Human Genome Research Institute., Funder: C.P.N. and T.R.W received funding from the British Heart Foundation (SP/16/4/32697)., Funder: The Trøndelag Health Study (The HUNT Study) is a collaboration between HUNT Research Centre (Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology), Trøndelag County Council, Central Norway Regional Health Authority, and the Norwegian Institute of Public Health. The K.G. Jebsen Center for Genetic Epidemiology is financed by Stiftelsen Kristian Gerhard Jebsen; Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology; and Central Norway Regional Health Authority. Whole genome sequencing for the HUNT study was funded by HL109946., Funder: O.M. was funded by the Swedish Heart- and Lung Foundation, the Swedish Research Council, the European Research Council ERC-AdG-2019-885003 and Lund University Infrastructure grant ”Malmö population-based cohorts” (STYR 2019/2046)., Funder: This work was supported by the European Commission (HEALTH-F2–2013-601456) and the TriPartite Immunometabolism Consortium [TrIC]- NovoNordisk Foundation (NNF15CC0018486), VIAgenomics (SP/19/2/344612), the British Heart Foundation, a Wellcome Trust core award (M.F., H.W., 203141/Z/16/Z) and support from the NIHR Oxford Biomedical Research Centre. M.F. and H.W. are members of the Oxford BHF Centre of Research Excellence (RE/13/1/30181). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health., Funder: J.D. is a British Heart Foundation Professor, European Research Council Senior Investigator, and National Institute for Health Research (NIHR) Senior Investigator., Funder: J.C.H. acknowledges personal funding from the British Heart Foundation (FS/14/55/30806) and is a member of the Oxford BHF Centre of Research Excellence (RE/13/1/30181)., Funder: R.C. has received funding from the British Heart Foundation and British Heart Foundation Centre of Research Excellence., Funder: This research was supported by BHF (SP/13/2/30111) and conducted using the UK Biobank Resource (application number 9922)., Funder: The GerMIFs gratefully acknowledge the support of the Bavarian State Ministry of Health and Care, furthermore founded this work within its framework of DigiMed Bayern (grant No: DMB-1805-0001), the German Federal Ministry of Education and Research (BMBF) within the framework of ERA-NET on Cardiovascular Disease (Druggable-MI-genes: 01KL1802), within the scheme of target validation (BlockCAD: 16GW0198K), within the framework of the e:Med research and funding concept (AbCD-Net: 01ZX1706C), the British Heart Foundation (BHF)/German Centre of Cardiovascular Research (DZHK)-collaboration (VIAgenomics) and the German Research Foundation (DFG) as part of the Sonderforschungsbereich SFB 1123 (B02) and the Sonderforschungsbereich SFB TRR 267 (B05)., Funder: C.J.W. is funded by NIH grant R35-HL135824., Funder: This work was supported by the British Heart Foundation (BHF) grant RG/14/5/30893 (P.D.) and forms part of the research themes contributing to the translational research portfolios of the Barts Biomedical Research Centre funded by the UK National Institute for Health Research (NIHR)., The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR–Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.

Published
2022
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28. Contributors

Author

Achenbach, Stephan, primary, Aragam, Krishna G., additional, Arnold, Suzanne V., additional, Bäck, Magnus, additional, Blaha, Michael J., additional, Blankenberg, Stefan, additional, Blumenthal, Roger S., additional, Camici, Paolo G., additional, Chung, Mina K., additional, Cigarroa, Joaquin E., additional, Crea, Filippo, additional, Davidson, Karina W., additional, De Schutter, Alban, additional, Di Carli, Marcelo F., additional, Douglas, Pamela S., additional, Ducrocq, Gregory, additional, Emdin, Connor A., additional, Emeruwa, Obi, additional, Enriquez, Jonathan R., additional, Fearon, William F., additional, Fordyce, Christopher B., additional, Gaziano, Thomas A., additional, Gersh, Bernard, additional, Gitsioudis, Gitsios, additional, Guo, Yuanlin, additional, Hachamovitch, Rory, additional, Hansson, Göran K., additional, Heinzman, Kristopher, additional, Henry, Timothy D., additional, Hussein, Ayman A., additional, Jensen, Jesper K., additional, Jolicoeur, E. Marc, additional, Kathiresan, Sekar, additional, Khattar, Rajdeep S., additional, Khera, Amit V., additional, Kosiborod, Mikhail, additional, Kwon, Lawrence, additional, Lavie, Carl J., additional, Lawlor, Matthew, additional, Marso, Steven P., additional, Martin, Seth S., additional, Marx, Nikolaus, additional, Mehta, Puja K., additional, Bairey Merz, C. Noel, additional, Michos, Erin D., additional, Milani, Richard V., additional, O’Donnell, Christopher J., additional, Opie, Lionel, additional, Parikh, Shailja V., additional, Prescott, Eva, additional, Reith, Sebastian, additional, Rimoldi, Ornella E., additional, Robinson, Jennifer G., additional, Rodgers, George, additional, Rohatgi, Anand, additional, Rosendorff, Clive, additional, Sahni, Sheila, additional, Sedehi, Daniel, additional, Senior, Roxy, additional, Steg, Philippe Gabriel, additional, Wasson, Lauren, additional, Watson, Karol E., additional, Wei, Janet, additional, Wilson, Peter W.F., additional, and Zeller, Tanja, additional

Published
2018
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29. Predictive Utility of a Coronary Artery Disease Polygenic Risk Score in Primary Prevention

Author

Marston, Nicholas A., primary, Pirruccello, James P., additional, Melloni, Giorgio E. M., additional, Koyama, Satoshi, additional, Kamanu, Frederick K., additional, Weng, Lu-Chen, additional, Roselli, Carolina, additional, Kamatani, Yoichiro, additional, Komuro, Issei, additional, Aragam, Krishna G., additional, Butterworth, Adam S., additional, Ito, Kaoru, additional, Lubitz, Steve A., additional, Ellinor, Patrick T., additional, Sabatine, Marc S., additional, and Ruff, Christian T., additional

Published
2022
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30. Predictive Utility of a Coronary Artery Disease Polygenic Risk Score in Primary Prevention

Author

Marston, Nicholas A, Pirruccello, James P, Melloni, Giorgio EM, Koyama, Satoshi, Kamanu, Frederick K, Weng, Lu-Chen, Roselli, Carolina, Kamatani, Yoichiro, Komuro, Issei, Aragam, Krishna G, Butterworth, Adam S, Ito, Kaoru, Lubitz, Steve A, Ellinor, Patrick T, Sabatine, Marc S, Ruff, Christian T, and Apollo - University of Cambridge Repository

Subjects
Myocardial Infarction, Coronary Artery Disease, Middle Aged, Atherosclerosis, Risk Assessment, Cohort Studies, Primary Prevention, Young Adult, Cardiovascular Diseases, Risk Factors, Humans, Female, Longitudinal Studies, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Cardiology and Cardiovascular Medicine
Abstract

ImportanceThe clinical utility of polygenic risk scores (PRS) for coronary artery disease (CAD) has not yet been established.ObjectiveTo investigate the ability of a CAD PRS to potentially guide statin initiation in primary prevention after accounting for age and clinical risk.Design, Setting, and ParticipantsThis was a longitudinal cohort study with enrollment starting on January 1, 2006, and ending on December 31, 2010, with data updated to mid-2021, using data from the UK Biobank, a long-term population study of UK citizens. A replication analysis was performed in Biobank Japan. The analysis included all patients without a history of CAD and who were not taking lipid-lowering therapy. Data were analyzed from January 1 to June 30, 2022.ExposuresPolygenic risk for CAD was defined as low (bottom 20%), intermediate, and high (top 20%) using a CAD PRS including 241 genome-wide significant single-nucleotide variations (SNVs). The pooled cohort equations were used to estimate 10-year atherosclerotic cardiovascular disease (ASCVD) risk and classify individuals as low (Main Outcomes and MeasuresMyocardial infarction (MI) and ASCVD events (defined as incident clinical CAD [including MI], stroke, or CV death).ResultsA total of 330 201 patients (median [IQR] age, 57 [40-74] years; 189 107 female individuals [57%]) were included from the UK Biobank. Over the 10-year follow-up, 4454 individuals had an MI. The CAD PRS was significantly associated with the risk of MI in all age groups but had significantly stronger risk prediction at younger ages (age 60 years: HR, 1.42; 95% CI, 1.37-1.48; P for interaction Conclusions and RelevanceResults of this cohort study suggest that the predictive ability of a CAD PRS was greater in younger individuals and can be used to better identify patients with borderline and intermediate clinical risk who should initiate statin therapy.

Published
2023

32. Rare and Common Genetic Variation Underlying the Risk of Hypertrophic Cardiomyopathy in a National Biobank

Author

Biddinger, Kiran J., primary, Jurgens, Sean J., additional, Maamari, Dimitri, additional, Gaziano, Liam, additional, Choi, Seung Hoan, additional, Morrill, Valerie N., additional, Halford, Jennifer L., additional, Khera, Amit V., additional, Lubitz, Steven A., additional, Ellinor, Patrick T., additional, and Aragam, Krishna G., additional

Published
2022
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36. Association of the Interaction Between Familial Hypercholesterolemia Variants and Adherence to a Healthy Lifestyle With Risk of Coronary Artery Disease

Author

Fahed, Akl C., primary, Wang, Minxian, additional, Patel, Aniruddh P., additional, Ajufo, Ezimamaka, additional, Maamari, Dimitri J., additional, Aragam, Krishna G., additional, Brockman, Deanna G., additional, Vosburg, Trish, additional, Ellinor, Patrick T., additional, Ng, Kenney, additional, and Khera, Amit V., additional

Published
2022
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39. Clinical and Genetic Associations of Deep Learning-Derived Cardiac Magnetic Resonance-Based Left Ventricular Mass

Author

Khurshid, Shaan, primary, Lazarte, Julieta, additional, Pirruccello, James P., additional, Weng, Lu-Chen, additional, Choi, Seung Hoan, additional, Hall, Amelia W., additional, Wang, Xin, additional, Friedman, Samuel, additional, Nauffal, Victor, additional, Biddinger, Kiran J., additional, Aragam, Krishna G., additional, Batra, Puneet, additional, Ho, Jennifer E., additional, Philippakis, Anthony A., additional, Ellinor, Patrick T., additional, and Lubitz, Steven A., additional

Published
2022
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42. Abstract 13271: Combined Assessments of Monogenic and Polygenic Risk for Dilated Cardiomyopathy

Author

Aragam, Krishna G, primary, Biddinger, Kiran, additional, Jurgens, Sean J, additional, Wang, Minxian, additional, Pirruccello, James, additional, Maamari, Dimitri, additional, Chaffin, Mark, additional, Choi, Seung H, additional, Morrill, Valerie, additional, Newton-cheh, Christopher, additional, Khera, Amit V, additional, Lubitz, Steven A, additional, and Ellinor, Patrick T, additional

Published
2021
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43. Multi-ancestry Multivariate Genome-Wide Analysis Highlights the Role of Common Genetic Variation in Cardiac Structure, Function, and Heart Failure-related Traits

Author

Levin, Michael G., primary, Tsao, Noah L., additional, Bellomo, Tiffany R., additional, Bone, William P., additional, Aragam, Krishna G., additional, Yang, Yifan, additional, Morley, Michael P., additional, Burke, Megan, additional, Judy, Renae L., additional, Arany, Zoltan, additional, Cappola, Thomas P., additional, Day, Sharlene M., additional, Ellinor, Patrick T., additional, Margulies, Kenneth B., additional, Voight, Benjamin F., additional, and Damrauer, Scott M., additional

Published
2021
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44. The genomics of heart failure : design and rationale of the HERMES consortium

Author

Lumbers, R. Thomas, Shah, Sonia, Lin, Honghuang, Czuba, Tomasz, Henry, Albert, Swerdlow, Daniel I., Mälarstig, Anders, Andersson, Charlotte, Verweij, Niek, Holmes, Michael V., Ärnlöv, Johan, Svensson, Per, Hemingway, Harry, Sallah, Neneh, Almgren, Peter, Aragam, Krishna G., Asselin, Geraldine, Backman, Joshua D., Biggs, Mary L., Bloom, Heather L., Boersma, Eric, Brandimarto, Jeffrey, Brown, Michael R., Brunner‐La Rocca, Hans‐Peter, Carey, David J., Chaffin, Mark D., Chasman, Daniel I., Chazara, Olympe, Chen, Xing, Chen, Xu, Chung, Jonathan H., Chutkow, William, Cleland, John G.F., Cook, James P., Denus, Simon, Dehghan, Abbas, Delgado, Graciela E., Denaxas, Spiros, Doney, Alexander S., Dörr, Marcus, Dudley, Samuel C., Engström, Gunnar, Esko, Tõnu, Fatemifar, Ghazaleh, Felix, Stephan B., Finan, Chris, Ford, Ian, Fougerousse, Francoise, Fouodjio, René, Ghanbari, Mohsen, Giedraitis, Vilmantas, Lind, Lars, Smith, J. Gustav, Lumbers, R. Thomas, Shah, Sonia, Lin, Honghuang, Czuba, Tomasz, Henry, Albert, Swerdlow, Daniel I., Mälarstig, Anders, Andersson, Charlotte, Verweij, Niek, Holmes, Michael V., Ärnlöv, Johan, Svensson, Per, Hemingway, Harry, Sallah, Neneh, Almgren, Peter, Aragam, Krishna G., Asselin, Geraldine, Backman, Joshua D., Biggs, Mary L., Bloom, Heather L., Boersma, Eric, Brandimarto, Jeffrey, Brown, Michael R., Brunner‐La Rocca, Hans‐Peter, Carey, David J., Chaffin, Mark D., Chasman, Daniel I., Chazara, Olympe, Chen, Xing, Chen, Xu, Chung, Jonathan H., Chutkow, William, Cleland, John G.F., Cook, James P., Denus, Simon, Dehghan, Abbas, Delgado, Graciela E., Denaxas, Spiros, Doney, Alexander S., Dörr, Marcus, Dudley, Samuel C., Engström, Gunnar, Esko, Tõnu, Fatemifar, Ghazaleh, Felix, Stephan B., Finan, Chris, Ford, Ian, Fougerousse, Francoise, Fouodjio, René, Ghanbari, Mohsen, Giedraitis, Vilmantas, Lind, Lars, and Smith, J. Gustav

Abstract

Aims: The HERMES (HEart failure Molecular Epidemiology for Therapeutic targetS) consortium aims to identify the genomic and molecular basis of heart failure. Methods and results: The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34–90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of ≥1.10 for common variants (allele frequency ≥ 0.05) and ≥1.20 for low-frequency variants (allele frequency 0.01–0.05) at P < 5 × 10−8 under an additive genetic model. Conclusions: HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.

Published
2021
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45. The genomics of heart failure:design and rationale of the HERMES consortium

Author

Lumbers, R. Thomas, Shah, Sonia, Lin, Honghuang, Czuba, Tomasz, Henry, Albert, Swerdlow, Daniel I., Mälarstig, Anders, Andersson, Charlotte, Verweij, Niek, Holmes, Michael V., Ärnlöv, Johan, Svensson, Per, Hemingway, Harry, Sallah, Neneh, Almgren, Peter, Aragam, Krishna G., Asselin, Geraldine, Backman, Joshua D., Biggs, Mary L., Bloom, Heather L., Boersma, Eric, Brandimarto, Jeffrey, Brown, Michael R., Brunner-La Rocca, Hans Peter, Carey, David J., Chaffin, Mark D., Chasman, Daniel I., Chazara, Olympe, Chen, Xing, Chen, Xu, Chung, Jonathan H., Chutkow, William, Cleland, John G.F., Cook, James P., de Denus, Simon, Dehghan, Abbas, Delgado, Graciela E., Denaxas, Spiros, Doney, Alexander S., Dörr, Marcus, Dudley, Samuel C., Engström, Gunnar, Esko, Tõnu, Ghanbari, Mohsen, Kardys, Isabella, Kavousi, Maryam, Portilla-Fernandez, Eliana, Teumer, Alexander, Uitterlinden, Andre G., Yang, Jian, Vasan, RS, Smith, JG, Lumbers, R. Thomas, Shah, Sonia, Lin, Honghuang, Czuba, Tomasz, Henry, Albert, Swerdlow, Daniel I., Mälarstig, Anders, Andersson, Charlotte, Verweij, Niek, Holmes, Michael V., Ärnlöv, Johan, Svensson, Per, Hemingway, Harry, Sallah, Neneh, Almgren, Peter, Aragam, Krishna G., Asselin, Geraldine, Backman, Joshua D., Biggs, Mary L., Bloom, Heather L., Boersma, Eric, Brandimarto, Jeffrey, Brown, Michael R., Brunner-La Rocca, Hans Peter, Carey, David J., Chaffin, Mark D., Chasman, Daniel I., Chazara, Olympe, Chen, Xing, Chen, Xu, Chung, Jonathan H., Chutkow, William, Cleland, John G.F., Cook, James P., de Denus, Simon, Dehghan, Abbas, Delgado, Graciela E., Denaxas, Spiros, Doney, Alexander S., Dörr, Marcus, Dudley, Samuel C., Engström, Gunnar, Esko, Tõnu, Ghanbari, Mohsen, Kardys, Isabella, Kavousi, Maryam, Portilla-Fernandez, Eliana, Teumer, Alexander, Uitterlinden, Andre G., Yang, Jian, Vasan, RS, and Smith, JG

Abstract

Aims: The HERMES (HEart failure Molecular Epidemiology for Therapeutic targetS) consortium aims to identify the genomic and molecular basis of heart failure. Methods and results: The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34–90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of ≥1.10 for common variants (allele frequency ≥ 0.05) and ≥1.20 for low-frequency variants (allele frequency 0.01–0.05) at P < 5 × 10−8 under an additive genetic model. Conclusions: HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.

Published
2021

47. Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood

Author

Massachusetts Institute of Technology. Department of Biology, Khera, Amit V., Chaffin, Mark, Wade, Kaitlin H., Zahid, Sohail, Brancale, Joseph, Xia, Rui, Distefano, Marina, Senol-Cosar, Ozlem, Haas, Mary E., Bick, Alexander, Aragam, Krishna G., Lander, Eric Steven, Smith, George Davey, Mason-Suares, Heather, Fornage, Myriam, Lebo, Matthew, Timpson, Nicholas J., Kaplan, Lee M., Kathiresan, Sekar, Massachusetts Institute of Technology. Department of Biology, Khera, Amit V., Chaffin, Mark, Wade, Kaitlin H., Zahid, Sohail, Brancale, Joseph, Xia, Rui, Distefano, Marina, Senol-Cosar, Ozlem, Haas, Mary E., Bick, Alexander, Aragam, Krishna G., Lander, Eric Steven, Smith, George Davey, Mason-Suares, Heather, Fornage, Myriam, Lebo, Matthew, Timpson, Nicholas J., Kaplan, Lee M., and Kathiresan, Sekar

Abstract

Severe obesity is a rapidly growing global health threat. Although often attributed to unhealthy lifestyle choices or environmental factors, obesity is known to be heritable and highly polygenic; the majority of inherited susceptibility is related to the cumulative effect of many common DNA variants. Here we derive and validate a new polygenic predictor comprised of 2.1 million common variants to quantify this susceptibility and test this predictor in more than 300,000 individuals ranging from middle age to birth. Among middle-aged adults, we observe a 13-kg gradient in weight and a 25-fold gradient in risk of severe obesity across polygenic score deciles. In a longitudinal birth cohort, we note minimal differences in birthweight across score deciles, but a significant gradient emerged in early childhood and reached 12 kg by 18 years of age. This new approach to quantify inherited susceptibility to obesity affords new opportunities for clinical prevention and mechanistic assessment. © 2019 Author(s), National Human Genome Research Institute (1K08HG0101), Wellcome Trust (202802/Z/16/Z), University of Bristol NIHR Biomedical Research Centre (S- BRC-1215-20011), National Human Genome Research Institute (HG008895), National Heart, Lung, and Blood Institute (NHLBI) HHSN268201300025C, National Heart, Lung, and Blood Institute (NHLBI) HHSN268201300026C, National Heart, Lung, and Blood Institute (NHLBI) HHSN268201300027C, National Heart, Lung, and Blood Institute (NHLBI) HHSN268201300028C, National Heart, Lung, and Blood Institute (NHLBI) HHSN268201300029C, National Heart, Lung, and Blood Institute (NHLBI) HHSN268200900041C, National Institute on Aging (AG0005), NHLBI (AG0005), National Human Genome Research Institute (U01-HG004729), National Human Genome Research Institute (U01-HG04424), National Human Genome Research Institute (U01-HG004446), Wellcome (102215/2/13/2)

Published
2020

48. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations

Author

Massachusetts Institute of Technology. Department of Biology, Broad Institute of MIT and Harvard, Khera, Amit V., Chaffin, Mark, Aragam, Krishna G., Haas, Mary E., Roselli, Carolina, Choi, Seung Hoan, Natarajan, Pradeep, Lander, Eric Steven, Lubitz, Steven A., Ellinor, Patrick T., Kathiresan, Sekar, Massachusetts Institute of Technology. Department of Biology, Broad Institute of MIT and Harvard, Khera, Amit V., Chaffin, Mark, Aragam, Krishna G., Haas, Mary E., Roselli, Carolina, Choi, Seung Hoan, Natarajan, Pradeep, Lander, Eric Steven, Lubitz, Steven A., Ellinor, Patrick T., and Kathiresan, Sekar

Abstract

A key public health need is to identify individuals at high risk for a given disease to enable enhanced screening or preventive therapies. Because most common diseases have a genetic component, one important approach is to stratify individuals based on inherited DNA variation 1 . Proposed clinical applications have largely focused on finding carriers of rare monogenic mutations at several-fold increased risk. Although most disease risk is polygenic in nature 2–5 , it has not yet been possible to use polygenic predictors to identify individuals at risk comparable to monogenic mutations. Here, we develop and validate genome-wide polygenic scores for five common diseases. The approach identifies 8.0, 6.1, 3.5, 3.2, and 1.5% of the population at greater than threefold increased risk for coronary artery disease, atrial fibrillation, type 2 diabetes, inflammatory bowel disease, and breast cancer, respectively. For coronary artery disease, this prevalence is 20-fold higher than the carrier frequency of rare monogenic mutations conferring comparable risk 6 . We propose that it is time to contemplate the inclusion of polygenic risk prediction in clinical care, and discuss relevant issues.

Published
2020

49. Transethnic Transferability of a Genome-Wide Polygenic Score for Coronary Artery Disease

Author

Fahed, Akl C., primary, Aragam, Krishna G., additional, Hindy, George, additional, Chen, Yii-Der Ida, additional, Chaudhary, Kumardeep, additional, Dobbyn, Amanda, additional, Krumholz, Harlan M., additional, Sheu, Wayne H.H., additional, Rich, Stephen S., additional, Rotter, Jerome I., additional, Chowdhury, Rajiv, additional, Cho, Judy, additional, Do, Ron, additional, Ellinor, Patrick T., additional, Kathiresan, Sekar, additional, and Khera, Amit V., additional

Published
2021
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50. Genome-wide and phenome-wide analysis of ideal cardiovascular health in the VA Million Veteran Program.

Author

Huang, Rose D. L., Nguyen, Xuan-Mai T., Peloso, Gina M., Trinder, Mark, Posner, Daniel C., Aragam, Krishna G., Ho, Yuk-Lam, Lynch, Julie A., Damrauer, Scott M., Chang, Kyong-Mi, Tsao, Philip S., Natarajan, Pradeep, Assimes, Themistocles, Gaziano, J. Michael, Djousse, Luc, Cho, Kelly, Wilson, Peter W. F., Huffman, Jennifer E., and O'Donnell, Christopher J.

Subjects
DISEASE risk factors, GENOME-wide association studies, GENETIC variation, VETERANS, MONOGENIC & polygenic inheritance (Genetics), SMOKING cessation
Abstract

Background: Genetic studies may help identify causal pathways; therefore, we sought to identify genetic determinants of ideal CVH and their association with CVD outcomes in the multi-population Veteran Administration Million Veteran Program. Methods: An ideal health score (IHS) was calculated from 3 clinical factors (blood pressure, total cholesterol, and blood glucose levels) and 3 behavioral factors (smoking status, physical activity, and BMI), ascertained at baseline. Multi-population genome-wide association study (GWAS) was performed on IHS and binary ideal health using linear and logistic regression, respectively. Using the genome-wide significant SNPs from the IHS GWAS, we created a weighted IHS polygenic risk score (PRSIHS) which was used (i) to conduct a phenome-wide association study (PheWAS) of associations between PRSIHS and ICD-9 phenotypes and (ii) to further test for associations with mortality and selected CVD outcomes using logistic and Cox regression and, as an instrumental variable, in Mendelian Randomization. Results: The discovery and replication cohorts consisted of 142,404 (119,129 European American (EUR); 16,495 African American (AFR)), and 45,766 (37,646 EUR; 5,366 AFR) participants, respectively. The mean age was 65.8 years (SD = 11.2) and 92.7% were male. Overall, 4.2% exhibited ideal CVH based on the clinical and behavioral factors. In the multi-population meta-analysis, variants at 17 loci were associated with IHS and each had known GWAS associations with multiple components of the IHS. PheWAS analysis in 456,026 participants showed that increased PRSIHS was associated with a lower odds ratio for many CVD outcomes and risk factors. Both IHS and PRSIHS measures of ideal CVH were associated with significantly less CVD outcomes and CVD mortality. Conclusion: A set of high interest genetic variants contribute to the presence of ideal CVH in a multi-ethnic cohort of US Veterans. Genetically influenced ideal CVH is associated with lower odds of CVD outcomes and mortality. [ABSTRACT FROM AUTHOR]

Published
2022
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