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1. Transfer Learning Under High-Dimensional Graph Convolutional Regression Model for Node Classification

Author

Chen, Jiachen, Huang, Danyang, Wang, Liyuan, Lunetta, Kathryn L., Mukherjee, Debarghya, and Cheng, Huimin

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Methodology
Abstract

Node classification is a fundamental task, but obtaining node classification labels can be challenging and expensive in many real-world scenarios. Transfer learning has emerged as a promising solution to address this challenge by leveraging knowledge from source domains to enhance learning in a target domain. Existing transfer learning methods for node classification primarily focus on integrating Graph Convolutional Networks (GCNs) with various transfer learning techniques. While these approaches have shown promising results, they often suffer from a lack of theoretical guarantees, restrictive conditions, and high sensitivity to hyperparameter choices. To overcome these limitations, we propose a Graph Convolutional Multinomial Logistic Regression (GCR) model and a transfer learning method based on the GCR model, called Trans-GCR. We provide theoretical guarantees of the estimate obtained under GCR model in high-dimensional settings. Moreover, Trans-GCR demonstrates superior empirical performance, has a low computational cost, and requires fewer hyperparameters than existing methods.

Published
2024

2. Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Author

Kentistou, Katherine A., Kaisinger, Lena R., Stankovic, Stasa, Vaudel, Marc, Mendes de Oliveira, Edson, Messina, Andrea, Walters, Robin G., Liu, Xiaoxi, Busch, Alexander S., Helgason, Hannes, Thompson, Deborah J., Santoni, Federico, Petricek, Konstantin M., Zouaghi, Yassine, Huang-Doran, Isabel, Gudbjartsson, Daniel F., Bratland, Eirik, Lin, Kuang, Gardner, Eugene J., Zhao, Yajie, Jia, Raina Y., Terao, Chikashi, Riggan, Marjorie J., Bolla, Manjeet K., Yazdanpanah, Mojgan, Yazdanpanah, Nahid, Bradfield, Jonathan P., Broer, Linda, Campbell, Archie, Chasman, Daniel I., Cousminer, Diana L., Franceschini, Nora, Franke, Lude H., Girotto, Giorgia, He, Chunyan, Järvelin, Marjo-Riitta, Joshi, Peter K., Kamatani, Yoichiro, Karlsson, Robert, Luan, Jian’an, Lunetta, Kathryn L., Mägi, Reedik, Mangino, Massimo, Medland, Sarah E., Meisinger, Christa, Noordam, Raymond, Nutile, Teresa, Concas, Maria Pina, Polašek, Ozren, Porcu, Eleonora, Ring, Susan M., Sala, Cinzia, Smith, Albert V., Tanaka, Toshiko, van der Most, Peter J., Vitart, Veronique, Wang, Carol A., Willemsen, Gonneke, Zygmunt, Marek, Ahearn, Thomas U., Andrulis, Irene L., Anton-Culver, Hoda, Antoniou, Antonis C., Auer, Paul L., Barnes, Catriona L. K., Beckmann, Matthias W., Berrington de Gonzalez, Amy, Bogdanova, Natalia V., Bojesen, Stig E., Brenner, Hermann, Buring, Julie E., Canzian, Federico, Chang-Claude, Jenny, Couch, Fergus J., Cox, Angela, Crisponi, Laura, Czene, Kamila, Daly, Mary B., Demerath, Ellen W., Dennis, Joe, Devilee, Peter, De Vivo, Immaculata, Dörk, Thilo, Dunning, Alison M., Dwek, Miriam, Eriksson, Johan G., Fasching, Peter A., Fernandez-Rhodes, Lindsay, Ferreli, Liana, Fletcher, Olivia, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A., González-Neira, Anna, Grallert, Harald, Guénel, Pascal, Haiman, Christopher A., Hall, Per, Hamann, Ute, Hakonarson, Hakon, Hart, Roger J., Hickey, Martha, Hooning, Maartje J., Hoppe, Reiner, Hopper, John L., Hottenga, Jouke-Jan, Hu, Frank B., Huebner, Hanna, Hunter, David J., Jernström, Helena, John, Esther M., Karasik, David, Khusnutdinova, Elza K., Kristensen, Vessela N., Lacey, James V., Lambrechts, Diether, Launer, Lenore J., Lind, Penelope A., Lindblom, Annika, Magnusson, Patrik K. E., Mannermaa, Arto, McCarthy, Mark I., Meitinger, Thomas, Menni, Cristina, Michailidou, Kyriaki, Millwood, Iona Y., Milne, Roger L., Montgomery, Grant W., Nevanlinna, Heli, Nolte, Ilja M., Nyholt, Dale R., Obi, Nadia, O’Brien, Katie M., Offit, Kenneth, Oldehinkel, Albertine J., Ostrowski, Sisse R., Palotie, Aarno, Pedersen, Ole B., Peters, Annette, Pianigiani, Giulia, Plaseska-Karanfilska, Dijana, Pouta, Anneli, Pozarickij, Alfred, Radice, Paolo, Rennert, Gad, Rosendaal, Frits R., Ruggiero, Daniela, Saloustros, Emmanouil, Sandler, Dale P., Schipf, Sabine, Schmidt, Carsten O., Schmidt, Marjanka K., Small, Kerrin, Spedicati, Beatrice, Stampfer, Meir, Stone, Jennifer, Tamimi, Rulla M., Teras, Lauren R., Tikkanen, Emmi, Turman, Constance, Vachon, Celine M., Wang, Qin, Winqvist, Robert, Wolk, Alicja, Zemel, Babette S., Zheng, Wei, van Dijk, Ko W., Alizadeh, Behrooz Z., Bandinelli, Stefania, Boerwinkle, Eric, Boomsma, Dorret I., Ciullo, Marina, Chenevix-Trench, Georgia, Cucca, Francesco, Esko, Tõnu, Gieger, Christian, Grant, Struan F. A., Gudnason, Vilmundur, Hayward, Caroline, Kolčić, Ivana, Kraft, Peter, Lawlor, Deborah A., Martin, Nicholas G., Nøhr, Ellen A., Pedersen, Nancy L., Pennell, Craig E., Ridker, Paul M., Robino, Antonietta, Snieder, Harold, Sovio, Ulla, Spector, Tim D., Stöckl, Doris, Sudlow, Cathie, Timpson, Nic J., Toniolo, Daniela, Uitterlinden, André, Ulivi, Sheila, Völzke, Henry, Wareham, Nicholas J., Widen, Elisabeth, Wilson, James F., Pharoah, Paul D. P., Li, Liming, Easton, Douglas F., Njølstad, Pål R., Sulem, Patrick, Murabito, Joanne M., Murray, Anna, Manousaki, Despoina, Juul, Anders, Erikstrup, Christian, Stefansson, Kari, Horikoshi, Momoko, Chen, Zhengming, Farooqi, I. Sadaf, Pitteloud, Nelly, Johansson, Stefan, Day, Felix R., Perry, John R. B., and Ong, Ken K.

Published
2024
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3. Publisher Correction: Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Author

Kentistou, Katherine A., Kaisinger, Lena R., Stankovic, Stasa, Vaudel, Marc, Mendes de Oliveira, Edson, Messina, Andrea, Walters, Robin G., Liu, Xiaoxi, Busch, Alexander S., Helgason, Hannes, Thompson, Deborah J., Santoni, Federico, Petricek, Konstantin M., Zouaghi, Yassine, Huang-Doran, Isabel, Gudbjartsson, Daniel F., Bratland, Eirik, Lin, Kuang, Gardner, Eugene J., Zhao, Yajie, Jia, Raina Y., Terao, Chikashi, Riggan, Marjorie J., Bolla, Manjeet K., Yazdanpanah, Mojgan, Yazdanpanah, Nahid, Bradfield, Jonathan P., Broer, Linda, Campbell, Archie, Chasman, Daniel I., Cousminer, Diana L., Franceschini, Nora, Franke, Lude H., Girotto, Giorgia, He, Chunyan, Järvelin, Marjo-Riitta, Joshi, Peter K., Kamatani, Yoichiro, Karlsson, Robert, Luan, Jian’an, Lunetta, Kathryn L., Mägi, Reedik, Mangino, Massimo, Medland, Sarah E., Meisinger, Christa, Noordam, Raymond, Nutile, Teresa, Concas, Maria Pina, Polašek, Ozren, Porcu, Eleonora, Ring, Susan M., Sala, Cinzia, Smith, Albert V., Tanaka, Toshiko, van der Most, Peter J., Vitart, Veronique, Wang, Carol A., Willemsen, Gonneke, Zygmunt, Marek, Ahearn, Thomas U., Andrulis, Irene L., Anton-Culver, Hoda, Antoniou, Antonis C., Auer, Paul L., Barnes, Catriona L. K., Beckmann, Matthias W., Berrington de Gonzalez, Amy, Bogdanova, Natalia V., Bojesen, Stig E., Brenner, Hermann, Buring, Julie E., Canzian, Federico, Chang-Claude, Jenny, Couch, Fergus J., Cox, Angela, Crisponi, Laura, Czene, Kamila, Daly, Mary B., Demerath, Ellen W., Dennis, Joe, Devilee, Peter, De Vivo, Immaculata, Dörk, Thilo, Dunning, Alison M., Dwek, Miriam, Eriksson, Johan G., Fasching, Peter A., Fernandez-Rhodes, Lindsay, Ferreli, Liana, Fletcher, Olivia, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A., González-Neira, Anna, Grallert, Harald, Guénel, Pascal, Haiman, Christopher A., Hall, Per, Hamann, Ute, Hakonarson, Hakon, Hart, Roger J., Hickey, Martha, Hooning, Maartje J., Hoppe, Reiner, Hopper, John L., Hottenga, Jouke-Jan, Hu, Frank B., Huebner, Hanna, Hunter, David J., Jernström, Helena, John, Esther M., Karasik, David, Khusnutdinova, Elza K., Kristensen, Vessela N., Lacey, James V., Lambrechts, Diether, Launer, Lenore J., Lind, Penelope A., Lindblom, Annika, Magnusson, Patrik K. E., Mannermaa, Arto, McCarthy, Mark I., Meitinger, Thomas, Menni, Cristina, Michailidou, Kyriaki, Millwood, Iona Y., Milne, Roger L., Montgomery, Grant W., Nevanlinna, Heli, Nolte, Ilja M., Nyholt, Dale R., Obi, Nadia, O’Brien, Katie M., Offit, Kenneth, Oldehinkel, Albertine J., Ostrowski, Sisse R., Palotie, Aarno, Pedersen, Ole B., Peters, Annette, Pianigiani, Giulia, Plaseska-Karanfilska, Dijana, Pouta, Anneli, Pozarickij, Alfred, Radice, Paolo, Rennert, Gad, Rosendaal, Frits R., Ruggiero, Daniela, Saloustros, Emmanouil, Sandler, Dale P., Schipf, Sabine, Schmidt, Carsten O., Schmidt, Marjanka K., Small, Kerrin, Spedicati, Beatrice, Stampfer, Meir, Stone, Jennifer, Tamimi, Rulla M., Teras, Lauren R., Tikkanen, Emmi, Turman, Constance, Vachon, Celine M., Wang, Qin, Winqvist, Robert, Wolk, Alicja, Zemel, Babette S., Zheng, Wei, van Dijk, Ko W., Alizadeh, Behrooz Z., Bandinelli, Stefania, Boerwinkle, Eric, Boomsma, Dorret I., Ciullo, Marina, Chenevix-Trench, Georgia, Cucca, Francesco, Esko, Tõnu, Gieger, Christian, Grant, Struan F. A., Gudnason, Vilmundur, Hayward, Caroline, Kolčić, Ivana, Kraft, Peter, Lawlor, Deborah A., Martin, Nicholas G., Nøhr, Ellen A., Pedersen, Nancy L., Pennell, Craig E., Ridker, Paul M., Robino, Antonietta, Snieder, Harold, Sovio, Ulla, Spector, Tim D., Stöckl, Doris, Sudlow, Cathie, Timpson, Nic J., Toniolo, Daniela, Uitterlinden, André, Ulivi, Sheila, Völzke, Henry, Wareham, Nicholas J., Widen, Elisabeth, Wilson, James F., Pharoah, Paul D. P., Li, Liming, Easton, Douglas F., Njølstad, Pål R., Sulem, Patrick, Murabito, Joanne M., Murray, Anna, Manousaki, Despoina, Juul, Anders, Erikstrup, Christian, Stefansson, Kari, Horikoshi, Momoko, Chen, Zhengming, Farooqi, I. Sadaf, Pitteloud, Nelly, Johansson, Stefan, Day, Felix R., Perry, John R. B., and Ong, Ken K.

Published
2024
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8. Different loneliness types, cognitive function, and brain structure in midlife: Findings from the Framingham Heart Study

Author

Tao, Qiushan, Akhter-Khan, Samia C, Ang, Ting Fang Alvin, DeCarli, Charles, Alosco, Michael L, Mez, Jesse, Killiany, Ronald, Devine, Sherral, Rokach, Ami, Itchapurapu, Indira Swetha, Zhang, Xiaoling, Lunetta, Kathryn L, Steffens, David C, Farrer, Lindsay A, Greve, Douglas N, Au, Rhoda, and Qiu, Wei Qiao

Subjects
Health Services and Systems, Public Health, Health Sciences, Alzheimer's Disease, Acquired Cognitive Impairment, Depression, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aging, Biomedical Imaging, Behavioral and Social Science, Brain Disorders, Neurodegenerative, Mental Illness, Clinical Research, Basic Behavioral and Social Science, Mental Health, Dementia, Aetiology, 2.3 Psychological, social and economic factors, Mental health, Neurological, Social isolation, Alzheimer?s disease, Neuroimaging, Cohort study, Brain health, Alzheimer's disease, Clinical sciences, Health services and systems, Public health
Abstract

BackgroundIt remains unclear whether persistent loneliness is related to brain structures that are associated with cognitive decline and development of Alzheimer's disease (AD). This study aimed to investigate the relationships between different loneliness types, cognitive functioning, and regional brain volumes.MethodsLoneliness was measured longitudinally, using the item from the Center for Epidemiologic Studies Depression Scale in the Framingham Heart Study, Generation 3, with participants' average age of 46·3 ± 8·6 years. Robust regression models tested the association between different loneliness types with longitudinal neuropsychological performance (n = 2,609) and regional magnetic resonance imaging brain data (n = 1,829) (2002-2019). Results were stratified for sex, depression, and Apolipoprotein E4 (ApoE4).FindingsPersistent loneliness, but not transient loneliness, was strongly associated with cognitive decline, especially memory and executive function. Persistent loneliness was negatively associated with temporal lobe volume (β = -0.18, 95%CI [-0.32, -0.04], P = 0·01). Among women, persistent loneliness was associated with smaller frontal lobe (β = -0.19, 95%CI [-0.38, -0.01], P = 0·04), temporal lobe (β = -0.20, 95%CI [-0.37, -0.03], P = 0·02), and hippocampus volumes (β = -0.23, 95%CI [-0.40, -0.06], P = 0·007), and larger lateral ventricle volume (β = 0.15, 95%CI [0.02, 0.28], P = 0·03). The higher cumulative loneliness scores across three exams, the smaller parietal, temporal, and hippocampus volumes and larger lateral ventricle were evident, especially in the presence of ApoE4.InterpretationPersistent loneliness in midlife was associated with atrophy in brain regions responsible for memory and executive dysfunction. Interventions to reduce the chronicity of loneliness may mitigate the risk of age-related cognitive decline and AD.FundingUS National Institute on Aging.

Published
2022

10. Monogenic and Polygenic Contributions to QTc Prolongation in the Population.

Author

Nauffal, Victor, Morrill, Valerie N, Jurgens, Sean J, Choi, Seung Hoan, Hall, Amelia W, Weng, Lu-Chen, Halford, Jennifer L, Austin-Tse, Christina, Haggerty, Christopher M, Harris, Stephanie L, Wong, Eugene K, Alonso, Alvaro, Arking, Dan E, Benjamin, Emelia J, Boerwinkle, Eric, Min, Yuan-I, Correa, Adolfo, Fornwalt, Brandon K, Heckbert, Susan R, National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Consortium, Kooperberg, Charles, Lin, Henry J, J F Loos, Ruth, Rice, Kenneth M, Gupta, Namrata, Blackwell, Thomas W, Mitchell, Braxton D, Morrison, Alanna C, Psaty, Bruce M, Post, Wendy S, Redline, Susan, Rehm, Heidi L, Rich, Stephen S, Rotter, Jerome I, Soliman, Elsayed Z, Sotoodehnia, Nona, Lunetta, Kathryn L, Ellinor, Patrick T, Lubitz, Steven A, and TOPMed Investigators

Subjects
National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Investigators, Humans, Long QT Syndrome, Electrocardiography, Heterozygote, Multifactorial Inheritance, Genome-Wide Association Study, Whole Genome Sequencing, QT interval, long QT syndrome, monogenic, polygenic, sudden cardiac death, Human Genome, Heart Disease, Prevention, Cardiovascular, Genetics, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology
Abstract

BackgroundRare sequence variation in genes underlying cardiac repolarization and common polygenic variation influence QT interval duration. However, current clinical genetic testing of individuals with unexplained QT prolongation is restricted to examination of monogenic rare variants. The recent emergence of large-scale biorepositories with sequence data enables examination of the joint contribution of rare and common variations to the QT interval in the population.MethodsWe performed a genome-wide association study of the QTc in 84 630 UK Biobank participants and created a polygenic risk score (PRS). Among 26 976 participants with whole-genome sequencing and ECG data in the TOPMed (Trans-Omics for Precision Medicine) program, we identified 160 carriers of putative pathogenic rare variants in 10 genes known to be associated with the QT interval. We examined QTc associations with the PRS and with rare variants in TOPMed.ResultsFifty-four independent loci were identified by genome-wide association study in the UK Biobank. Twenty-one loci were novel, of which 12 were replicated in TOPMed. The PRS composed of 1 110 494 common variants was significantly associated with the QTc in TOPMed (ΔQTc/decile of PRS=1.4 ms [95% CI, 1.3 to 1.5]; P=1.1×10-196). Carriers of putative pathogenic rare variants had longer QTc than noncarriers (ΔQTc=10.9 ms [95% CI, 7.4 to 14.4]). Of individuals with QTc>480 ms, 23.7% carried either a monogenic rare variant or had a PRS in the top decile (3.4% monogenic, 21% top decile of PRS).ConclusionsQTc duration in the population is influenced by both rare variants in genes underlying cardiac repolarization and polygenic risk, with a sizeable contribution from polygenic risk. Comprehensive assessment of the genetic determinants of QTc prolongation includes incorporation of both polygenic and monogenic risk.

Published
2022

11. A genome-wide search for pleiotropy in more than 100,000 harmonized longitudinal cognitive domain scores

Author

Kang, Moonil, Ang, Ting Fang Alvin, Devine, Sherral A., Sherva, Richard, Mukherjee, Shubhabrata, Trittschuh, Emily H., Gibbons, Laura E., Scollard, Phoebe, Lee, Michael, Choi, Seo-Eun, Klinedinst, Brandon, Nakano, Connie, Dumitrescu, Logan C., Durant, Alaina, Hohman, Timothy J., Cuccaro, Michael L., Saykin, Andrew J., Kukull, Walter A., Bennett, David A., Wang, Li-San, Mayeux, Richard P., Haines, Jonathan L., Pericak-Vance, Margaret A., Schellenberg, Gerard D., Crane, Paul K., Au, Rhoda, Lunetta, Kathryn L., Mez, Jesse B., and Farrer, Lindsay A.

Published
2023
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12. Endophenotype effect sizes support variant pathogenicity in monogenic disease susceptibility genes

Author

Halford, Jennifer L, Morrill, Valerie N, Choi, Seung Hoan, Jurgens, Sean J, Melloni, Giorgio, Marston, Nicholas A, Weng, Lu-Chen, Nauffal, Victor, Hall, Amelia W, Gunn, Sophia, Austin-Tse, Christina A, Pirruccello, James P, Khurshid, Shaan, Rehm, Heidi L, Benjamin, Emelia J, Boerwinkle, Eric, Brody, Jennifer A, Correa, Adolfo, Fornwalt, Brandon K, Gupta, Namrata, Haggerty, Christopher M, Harris, Stephanie, Heckbert, Susan R, Hong, Charles C, Kooperberg, Charles, Lin, Henry J, Loos, Ruth JF, Mitchell, Braxton D, Morrison, Alanna C, Post, Wendy, Psaty, Bruce M, Redline, Susan, Rice, Kenneth M, Rich, Stephen S, Rotter, Jerome I, Schnatz, Peter F, Soliman, Elsayed Z, Sotoodehnia, Nona, Wong, Eugene K, Sabatine, Marc S, Ruff, Christian T, Lunetta, Kathryn L, Ellinor, Patrick T, and Lubitz, Steven A

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Good Health and Well Being, Disease Susceptibility, Endophenotypes, Humans, Long QT Syndrome, Virulence, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
Abstract

Accurate and efficient classification of variant pathogenicity is critical for research and clinical care. Using data from three large studies, we demonstrate that population-based associations between rare variants and quantitative endophenotypes for three monogenic diseases (low-density-lipoprotein cholesterol for familial hypercholesterolemia, electrocardiographic QTc interval for long QT syndrome, and glycosylated hemoglobin for maturity-onset diabetes of the young) provide evidence for variant pathogenicity. Effect sizes are associated with pathogenic ClinVar assertions (P

Published
2022

16. 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

17. Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

Author

McCartney, Daniel L, Min, Josine L, Richmond, Rebecca C, Lu, Ake T, Sobczyk, Maria K, Davies, Gail, Broer, Linda, Guo, Xiuqing, Jeong, Ayoung, Jung, Jeesun, Kasela, Silva, Katrinli, Seyma, Kuo, Pei-Lun, Matias-Garcia, Pamela R, Mishra, Pashupati P, Nygaard, Marianne, Palviainen, Teemu, Patki, Amit, Raffield, Laura M, Ratliff, Scott M, Richardson, Tom G, Robinson, Oliver, Soerensen, Mette, Sun, Dianjianyi, Tsai, Pei-Chien, van der Zee, Matthijs D, Walker, Rosie M, Wang, Xiaochuan, Wang, Yunzhang, Xia, Rui, Xu, Zongli, Yao, Jie, Zhao, Wei, Correa, Adolfo, Boerwinkle, Eric, Dugué, Pierre-Antoine, Durda, Peter, Elliott, Hannah R, Gieger, Christian, de Geus, Eco JC, Harris, Sarah E, Hemani, Gibran, Imboden, Medea, Kähönen, Mika, Kardia, Sharon LR, Kresovich, Jacob K, Li, Shengxu, Lunetta, Kathryn L, Mangino, Massimo, Mason, Dan, McIntosh, Andrew M, Mengel-From, Jonas, Moore, Ann Zenobia, Murabito, Joanne M, Ollikainen, Miina, Pankow, James S, Pedersen, Nancy L, Peters, Annette, Polidoro, Silvia, Porteous, David J, Raitakari, Olli, Rich, Stephen S, Sandler, Dale P, Sillanpää, Elina, Smith, Alicia K, Southey, Melissa C, Strauch, Konstantin, Tiwari, Hemant, Tanaka, Toshiko, Tillin, Therese, Uitterlinden, Andre G, Van Den Berg, David J, van Dongen, Jenny, Wilson, James G, Wright, John, Yet, Idil, Arnett, Donna, Bandinelli, Stefania, Bell, Jordana T, Binder, Alexandra M, Boomsma, Dorret I, Chen, Wei, Christensen, Kaare, Conneely, Karen N, Elliott, Paul, Ferrucci, Luigi, Fornage, Myriam, Hägg, Sara, Hayward, Caroline, Irvin, Marguerite, Kaprio, Jaakko, Lawlor, Deborah A, Lehtimäki, Terho, Lohoff, Falk W, Milani, Lili, Milne, Roger L, Probst-Hensch, Nicole, Reiner, Alex P, Ritz, Beate, and Rotter, Jerome I

Subjects
Prevention, Nutrition, Aging, Human Genome, Genetics, Generic health relevance, Inflammatory and immune system, Good Health and Well Being, Adiposity, Biomarkers, C-Reactive Protein, CpG Islands, DNA Methylation, Educational Status, Epigenesis, Genetic, Genetic Loci, Genetic Markers, Genome, Human, Genome-Wide Association Study, Granulocytes, Humans, Immunity, Innate, Lipid Metabolism, Multifactorial Inheritance, Plasminogen Activator Inhibitor 1, DNA methylation, GWAS, Epigenetic clock, Genetics of DNA Methylation Consortium, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Environmental Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

BackgroundBiological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field.ResultsLeveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels.ConclusionThis study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

Published
2021

18. 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

19. Cross-ancestry GWAS meta-analysis identifies six breast cancer loci in African and European ancestry women.

Author

Adedokun, Babatunde, Du, Zhaohui, Gao, Guimin, Ahearn, Thomas U, Lunetta, Kathryn L, Zirpoli, Gary, Figueroa, Jonine, John, Esther M, Bernstein, Leslie, Zheng, Wei, Hu, Jennifer J, Ziegler, Regina G, Nyante, Sarah, Bandera, Elisa V, Ingles, Sue A, Press, Michael F, Deming-Halverson, Sandra L, Rodriguez-Gil, Jorge L, Yao, Song, Ogundiran, Temidayo O, Ojengbede, Oladosu, Blot, William, Troester, Melissa A, Nathanson, Katherine L, Hennis, Anselm, Nemesure, Barbara, Ambs, Stefan, Fiorica, Peter N, Sucheston-Campbell, Lara E, Bensen, Jeannette T, Kushi, Lawrence H, Torres-Mejia, Gabriela, Hu, Donglei, Fejerman, Laura, Bolla, Manjeet K, Dennis, Joe, Dunning, Alison M, Easton, Douglas F, Michailidou, Kyriaki, Pharoah, Paul DP, Wang, Qin, Sandler, Dale P, Taylor, Jack A, O'Brien, Katie M, Kitahara, Cari M, Falusi, Adeyinka G, Babalola, Chinedum, Yarney, Joel, Awuah, Baffour, Addai-Wiafe, Beatrice, GBHS Study Team, Chanock, Stephen J, Olshan, Andrew F, Ambrosone, Christine B, Conti, David V, Ziv, Elad, Olopade, Olufunmilayo I, Garcia-Closas, Montserrat, Palmer, Julie R, Haiman, Christopher A, and Huo, Dezheng

Subjects
GBHS Study Team, Humans, Breast Neoplasms, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Introns, African Continental Ancestry Group, European Continental Ancestry Group, Female, Genome-Wide Association Study
Abstract

Our study describes breast cancer risk loci using a cross-ancestry GWAS approach. We first identify variants that are associated with breast cancer at P

Published
2021

20. 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

21. Exceptionally low likelihood of Alzheimer's dementia in APOE2 homozygotes from a 5,000-person neuropathological study.

Author

Reiman, Eric M, Arboleda-Velasquez, Joseph F, Quiroz, Yakeel T, Huentelman, Matthew J, Beach, Thomas G, Caselli, Richard J, Chen, Yinghua, Su, Yi, Myers, Amanda J, Hardy, John, Paul Vonsattel, Jean, Younkin, Steven G, Bennett, David A, De Jager, Philip L, Larson, Eric B, Crane, Paul K, Keene, C Dirk, Kamboh, M Ilyas, Kofler, Julia K, Duque, Linda, Gilbert, John R, Gwirtsman, Harry E, Buxbaum, Joseph D, Dickson, Dennis W, Frosch, Matthew P, Ghetti, Bernardino F, Lunetta, Kathryn L, Wang, Li-San, Hyman, Bradley T, Kukull, Walter A, Foroud, Tatiana, Haines, Jonathan L, Mayeux, Richard P, Pericak-Vance, Margaret A, Schneider, Julie A, Trojanowski, John Q, Farrer, Lindsay A, Schellenberg, Gerard D, Beecham, Gary W, Montine, Thomas J, Jun, Gyungah R, and Alzheimer’s Disease Genetics Consortium

Subjects
Alzheimer’s Disease Genetics Consortium, Brain, Humans, Alzheimer Disease, Genetic Predisposition to Disease, Probability, Genotype, Homozygote, Alleles, Aged, Aged, 80 and over, Middle Aged, Female, Male, Apolipoprotein E2, Apolipoprotein E3, Apolipoprotein E4, Genetic Association Studies, Neuropathology, Aging, Brain Disorders, Acquired Cognitive Impairment, Dementia, Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Genetics, Alzheimer's Disease, Prevention, Neurosciences, 2.1 Biological and endogenous factors, Neurological
Abstract

Each additional copy of the apolipoprotein E4 (APOE4) allele is associated with a higher risk of Alzheimer's dementia, while the APOE2 allele is associated with a lower risk of Alzheimer's dementia, it is not yet known whether APOE2 homozygotes have a particularly low risk. We generated Alzheimer's dementia odds ratios and other findings in more than 5,000 clinically characterized and neuropathologically characterized Alzheimer's dementia cases and controls. APOE2/2 was associated with a low Alzheimer's dementia odds ratios compared to APOE2/3 and 3/3, and an exceptionally low odds ratio compared to APOE4/4, and the impact of APOE2 and APOE4 gene dose was significantly greater in the neuropathologically confirmed group than in more than 24,000 neuropathologically unconfirmed cases and controls. Finding and targeting the factors by which APOE and its variants influence Alzheimer's disease could have a major impact on the understanding, treatment and prevention of the disease.

Published
2020

24. The association between circulating CD34+CD133+ endothelial progenitor cells and reduced risk of Alzheimer’s disease in the Framingham Heart Study

Author

Wang, Yixuan, primary, Huang, Jinghan, additional, Ang, Ting Fang Alvin, additional, Zhu, Yibo, additional, Tao, Qiushan, additional, Mez, Jesse, additional, Alosco, Michael, additional, Denis, Gerald V., additional, Belkina, Anna, additional, Gurnani, Ashita, additional, Ross, Mark, additional, Gong, Bin, additional, Han, Jingyan, additional, Lunetta, Kathryn L., additional, Stein, Thor D., additional, Au, Rhoda, additional, Farrer, Lindsay A., additional, Zhang, Xiaoling, additional, and Qiu, Wei Qiao, additional

Published
2024
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25. MitoH3: Mitochondrial Haplogroup and Homoplasmic/Heteroplasmic Variant Calling Pipeline for Alzheimer’s Disease Sequencing Project

Author

Zhu, Congcong, primary, Tong, Tong, additional, Farrell, John J., additional, Martin, Eden R., additional, Bush, William S., additional, Pericak-Vance, Margaret A., additional, Wang, Li-San, additional, Schellenberg, Gerard D., additional, Haines, Jonathan L., additional, Lunetta, Kathryn L., additional, Farrer, Lindsay A., additional, and Zhang, Xiaoling, additional

Published
2024
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26. New insights into the genetic etiology of Alzheimer’s disease and related dementias

Author

Bellenguez, Céline, Küçükali, Fahri, Jansen, Iris E., Kleineidam, Luca, Moreno-Grau, Sonia, Amin, Najaf, Naj, Adam C., Campos-Martin, Rafael, Grenier-Boley, Benjamin, Andrade, Victor, Holmans, Peter A., Boland, Anne, Damotte, Vincent, van der Lee, Sven J., Costa, Marcos R., Kuulasmaa, Teemu, Yang, Qiong, de Rojas, Itziar, Bis, Joshua C., Yaqub, Amber, Prokic, Ivana, Chapuis, Julien, Ahmad, Shahzad, Giedraitis, Vilmantas, Aarsland, Dag, Garcia-Gonzalez, Pablo, Abdelnour, Carla, Alarcón-Martín, Emilio, Alcolea, Daniel, Alegret, Montserrat, Alvarez, Ignacio, Álvarez, Victoria, Armstrong, Nicola J., Tsolaki, Anthoula, Antúnez, Carmen, Appollonio, Ildebrando, Arcaro, Marina, Archetti, Silvana, Pastor, Alfonso Arias, Arosio, Beatrice, Athanasiu, Lavinia, Bailly, Henri, Banaj, Nerisa, Baquero, Miquel, Barral, Sandra, Beiser, Alexa, Pastor, Ana Belén, Below, Jennifer E., Benchek, Penelope, Benussi, Luisa, Berr, Claudine, Besse, Céline, Bessi, Valentina, Binetti, Giuliano, Bizarro, Alessandra, Blesa, Rafael, Boada, Mercè, Boerwinkle, Eric, Borroni, Barbara, Boschi, Silvia, Bossù, Paola, Bråthen, Geir, Bressler, Jan, Bresner, Catherine, Brodaty, Henry, Brookes, Keeley J., Brusco, Luis Ignacio, Buiza-Rueda, Dolores, Bûrger, Katharina, Burholt, Vanessa, Bush, William S., Calero, Miguel, Cantwell, Laura B., Chene, Geneviève, Chung, Jaeyoon, Cuccaro, Michael L., Carracedo, Ángel, Cecchetti, Roberta, Cervera-Carles, Laura, Charbonnier, Camille, Chen, Hung-Hsin, Chillotti, Caterina, Ciccone, Simona, Claassen, Jurgen A. H. R., Clark, Christopher, Conti, Elisa, Corma-Gómez, Anaïs, Costantini, Emanuele, Custodero, Carlo, Daian, Delphine, Dalmasso, Maria Carolina, Daniele, Antonio, Dardiotis, Efthimios, Dartigues, Jean-François, de Deyn, Peter Paul, de Paiva Lopes, Katia, de Witte, Lot D., Debette, Stéphanie, Deckert, Jürgen, del Ser, Teodoro, Denning, Nicola, DeStefano, Anita, Dichgans, Martin, Diehl-Schmid, Janine, Diez-Fairen, Mónica, Rossi, Paolo Dionigi, Djurovic, Srdjan, Duron, Emmanuelle, Düzel, Emrah, Dufouil, Carole, Eiriksdottir, Gudny, Engelborghs, Sebastiaan, Escott-Price, Valentina, Espinosa, Ana, Ewers, Michael, Faber, Kelley M., Fabrizio, Tagliavini, Nielsen, Sune Fallgaard, Fardo, David W., Farotti, Lucia, Fenoglio, Chiara, Fernández-Fuertes, Marta, Ferrari, Raffaele, Ferreira, Catarina B., Ferri, Evelyn, Fin, Bertrand, Fischer, Peter, Fladby, Tormod, Fließbach, Klaus, Fongang, Bernard, Fornage, Myriam, Fortea, Juan, Foroud, Tatiana M., Fostinelli, Silvia, Fox, Nick C., Franco-Macías, Emlio, Bullido, María J., Frank-García, Ana, Froelich, Lutz, Fulton-Howard, Brian, Galimberti, Daniela, García-Alberca, Jose Maria, García-González, Pablo, Garcia-Madrona, Sebastian, Garcia-Ribas, Guillermo, Ghidoni, Roberta, Giegling, Ina, Giorgio, Giaccone, Goate, Alison M., Goldhardt, Oliver, Gomez-Fonseca, Duber, González-Pérez, Antonio, Graff, Caroline, Grande, Giulia, Green, Emma, Grimmer, Timo, Grünblatt, Edna, Grunin, Michelle, Gudnason, Vilmundur, Guetta-Baranes, Tamar, Haapasalo, Annakaisa, Hadjigeorgiou, Georgios, Haines, Jonathan L., Hamilton-Nelson, Kara L., Hampel, Harald, Hanon, Olivier, Hardy, John, Hartmann, Annette M., Hausner, Lucrezia, Harwood, Janet, Heilmann-Heimbach, Stefanie, Helisalmi, Seppo, Heneka, Michael T., Hernández, Isabel, Herrmann, Martin J., Hoffmann, Per, Holmes, Clive, Holstege, Henne, Vilas, Raquel Huerto, Hulsman, Marc, Humphrey, Jack, Biessels, Geert Jan, Jian, Xueqiu, Johansson, Charlotte, Jun, Gyungah R., Kastumata, Yuriko, Kauwe, John, Kehoe, Patrick G., Kilander, Lena, Ståhlbom, Anne Kinhult, Kivipelto, Miia, Koivisto, Anne, Kornhuber, Johannes, Kosmidis, Mary H., Kukull, Walter A., Kuksa, Pavel P., Kunkle, Brian W., Kuzma, Amanda B., Lage, Carmen, Laukka, Erika J., Launer, Lenore, Lauria, Alessandra, Lee, Chien-Yueh, Lehtisalo, Jenni, Lerch, Ondrej, Lleó, Alberto, Longstreth, Jr, William, Lopez, Oscar, de Munain, Adolfo Lopez, Love, Seth, Löwemark, Malin, Luckcuck, Lauren, Lunetta, Kathryn L., Ma, Yiyi, Macías, Juan, MacLeod, Catherine A., Maier, Wolfgang, Mangialasche, Francesca, Spallazzi, Marco, Marquié, Marta, Marshall, Rachel, Martin, Eden R., Montes, Angel Martín, Rodríguez, Carmen Martínez, Masullo, Carlo, Mayeux, Richard, Mead, Simon, Mecocci, Patrizia, Medina, Miguel, Meggy, Alun, Mehrabian, Shima, Mendoza, Silvia, Menéndez-González, Manuel, Mir, Pablo, Moebus, Susanne, Mol, Merel, Molina-Porcel, Laura, Montrreal, Laura, Morelli, Laura, Moreno, Fermin, Morgan, Kevin, Mosley, Thomas, Nöthen, Markus M., Muchnik, Carolina, Mukherjee, Shubhabrata, Nacmias, Benedetta, Ngandu, Tiia, Nicolas, Gael, Nordestgaard, Børge G., Olaso, Robert, Orellana, Adelina, Orsini, Michela, Ortega, Gemma, Padovani, Alessandro, Paolo, Caffarra, Papenberg, Goran, Parnetti, Lucilla, Pasquier, Florence, Pastor, Pau, Peloso, Gina, Pérez-Cordón, Alba, Pérez-Tur, Jordi, Pericard, Pierre, Peters, Oliver, Pijnenburg, Yolande A. L., Pineda, Juan A., Piñol-Ripoll, Gerard, Pisanu, Claudia, Polak, Thomas, Popp, Julius, Posthuma, Danielle, Priller, Josef, Puerta, Raquel, Quenez, Olivier, Quintela, Inés, Thomassen, Jesper Qvist, Rábano, Alberto, Rainero, Innocenzo, Rajabli, Farid, Ramakers, Inez, Real, Luis M., Reinders, Marcel J. T., Reitz, Christiane, Reyes-Dumeyer, Dolly, Ridge, Perry, Riedel-Heller, Steffi, Riederer, Peter, Roberto, Natalia, Rodriguez-Rodriguez, Eloy, Rongve, Arvid, Allende, Irene Rosas, Rosende-Roca, Maitée, Royo, Jose Luis, Rubino, Elisa, Rujescu, Dan, Sáez, María Eugenia, Sakka, Paraskevi, Saltvedt, Ingvild, Sanabria, Ángela, Sánchez-Arjona, María Bernal, Sanchez-Garcia, Florentino, Juan, Pascual Sánchez, Sánchez-Valle, Raquel, Sando, Sigrid B., Sarnowski, Chloé, Satizabal, Claudia L., Scamosci, Michela, Scarmeas, Nikolaos, Scarpini, Elio, Scheltens, Philip, Scherbaum, Norbert, Scherer, Martin, Schmid, Matthias, Schneider, Anja, Schott, Jonathan M., Selbæk, Geir, Seripa, Davide, Serrano, Manuel, Sha, Jin, Shadrin, Alexey A., Skrobot, Olivia, Slifer, Susan, Snijders, Gijsje J. L., Soininen, Hilkka, Solfrizzi, Vincenzo, Solomon, Alina, Song, Yeunjoo, Sorbi, Sandro, Sotolongo-Grau, Oscar, Spalletta, Gianfranco, Spottke, Annika, Squassina, Alessio, Stordal, Eystein, Tartan, Juan Pablo, Tárraga, Lluís, Tesí, Niccolo, Thalamuthu, Anbupalam, Thomas, Tegos, Tosto, Giuseppe, Traykov, Latchezar, Tremolizzo, Lucio, Tybjærg-Hansen, Anne, Uitterlinden, Andre, Ullgren, Abbe, Ulstein, Ingun, Valero, Sergi, Valladares, Otto, Broeckhoven, Christine Van, Vance, Jeffery, Vardarajan, Badri N., van der Lugt, Aad, Dongen, Jasper Van, van Rooij, Jeroen, van Swieten, John, Vandenberghe, Rik, Verhey, Frans, Vidal, Jean-Sébastien, Vogelgsang, Jonathan, Vyhnalek, Martin, Wagner, Michael, Wallon, David, Wang, Li-San, Wang, Ruiqi, Weinhold, Leonie, Wiltfang, Jens, Windle, Gill, Woods, Bob, Yannakoulia, Mary, Zare, Habil, Zhao, Yi, Zhang, Xiaoling, Zhu, Congcong, Zulaica, Miren, Farrer, Lindsay A., Psaty, Bruce M., Ghanbari, Mohsen, Raj, Towfique, Sachdev, Perminder, Mather, Karen, Jessen, Frank, Ikram, M. Arfan, de Mendonça, Alexandre, Hort, Jakub, Tsolaki, Magda, Pericak-Vance, Margaret A., Amouyel, Philippe, Williams, Julie, Frikke-Schmidt, Ruth, Clarimon, Jordi, Deleuze, Jean-François, Rossi, Giacomina, Seshadri, Sudha, Andreassen, Ole A., Ingelsson, Martin, Hiltunen, Mikko, Sleegers, Kristel, Schellenberg, Gerard D., van Duijn, Cornelia M., Sims, Rebecca, van der Flier, Wiesje M., Ruiz, Agustín, Ramirez, Alfredo, and Lambert, Jean-Charles

Published
2022
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27. A meta-analysis of genome-wide association studies identifies multiple longevity genes.

Author

Deelen, Joris, Evans, Daniel S, Arking, Dan E, Tesi, Niccolò, Nygaard, Marianne, Liu, Xiaomin, Wojczynski, Mary K, Biggs, Mary L, van der Spek, Ashley, Atzmon, Gil, Ware, Erin B, Sarnowski, Chloé, Smith, Albert V, Seppälä, Ilkka, Cordell, Heather J, Dose, Janina, Amin, Najaf, Arnold, Alice M, Ayers, Kristin L, Barzilai, Nir, Becker, Elizabeth J, Beekman, Marian, Blanché, Hélène, Christensen, Kaare, Christiansen, Lene, Collerton, Joanna C, Cubaynes, Sarah, Cummings, Steven R, Davies, Karen, Debrabant, Birgit, Deleuze, Jean-François, Duncan, Rachel, Faul, Jessica D, Franceschi, Claudio, Galan, Pilar, Gudnason, Vilmundur, Harris, Tamara B, Huisman, Martijn, Hurme, Mikko A, Jagger, Carol, Jansen, Iris, Jylhä, Marja, Kähönen, Mika, Karasik, David, Kardia, Sharon LR, Kingston, Andrew, Kirkwood, Thomas BL, Launer, Lenore J, Lehtimäki, Terho, Lieb, Wolfgang, Lyytikäinen, Leo-Pekka, Martin-Ruiz, Carmen, Min, Junxia, Nebel, Almut, Newman, Anne B, Nie, Chao, Nohr, Ellen A, Orwoll, Eric S, Perls, Thomas T, Province, Michael A, Psaty, Bruce M, Raitakari, Olli T, Reinders, Marcel JT, Robine, Jean-Marie, Rotter, Jerome I, Sebastiani, Paola, Smith, Jennifer, Sørensen, Thorkild IA, Taylor, Kent D, Uitterlinden, André G, van der Flier, Wiesje, van der Lee, Sven J, van Duijn, Cornelia M, van Heemst, Diana, Vaupel, James W, Weir, David, Ye, Kenny, Zeng, Yi, Zheng, Wanlin, Holstege, Henne, Kiel, Douglas P, Lunetta, Kathryn L, Slagboom, P Eline, and Murabito, Joanne M

Subjects
Humans, Heat-Shock Proteins, Longevity, Apolipoprotein E2, Apolipoprotein E4, Genome-Wide Association Study
Abstract

Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.

Published
2019

28. CpG-related SNPs in the MS4A region have a dose-dependent effect on risk of late-onset Alzheimer disease.

Author

Ma, Yiyi, Jun, Gyungah R, Chung, Jaeyoon, Zhang, Xiaoling, Kunkle, Brian W, Naj, Adam C, White, Charles C, Bennett, David A, De Jager, Philip L, Alzheimer’s Disease Genetics Consortium, Mayeux, Richard, Haines, Jonathan L, Pericak-Vance, Margaret A, Schellenberg, Gerard D, Farrer, Lindsay A, and Lunetta, Kathryn L

Subjects
Alzheimer’s Disease Genetics Consortium, Brain, Humans, Alzheimer Disease, Genetic Predisposition to Disease, Membrane Proteins, Dinucleoside Phosphates, Prognosis, Risk, Cohort Studies, DNA Methylation, CpG Islands, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Aged, Aged, 80 and over, Middle Aged, Female, Male, Genome-Wide Association Study, Alzheimer disease, DNA methylation, eQTL, epigenetics, genetics, mQTL, Dementia, Genetics, Neurodegenerative, Brain Disorders, Aging, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Neurosciences, Alzheimer's Disease, Human Genome, Biotechnology, 2.1 Biological and endogenous factors, Neurological, Developmental Biology, Biological Sciences, Medical and Health Sciences
Abstract

CpG-related single nucleotide polymorphisms (CGS) have the potential to perturb DNA methylation; however, their effects on Alzheimer disease (AD) risk have not been evaluated systematically. We conducted a genome-wide association study using a sliding-window approach to measure the combined effects of CGSes on AD risk in a discovery sample of 24 European ancestry cohorts (12,181 cases, 12,601 controls) from the Alzheimer's Disease Genetics Consortium (ADGC) and replication sample of seven European ancestry cohorts (7,554 cases, 27,382 controls) from the International Genomics of Alzheimer's Project (IGAP). The potential functional relevance of significant associations was evaluated by analysis of methylation and expression levels in brain tissue of the Religious Orders Study and the Rush Memory and Aging Project (ROSMAP), and in whole blood of Framingham Heart Study participants (FHS). Genome-wide significant (p

Published
2019

29. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors

Author

Warrington, Nicole M, Beaumont, Robin N, Horikoshi, Momoko, Day, Felix R, Helgeland, Øyvind, Laurin, Charles, Bacelis, Jonas, Peng, Shouneng, Hao, Ke, Feenstra, Bjarke, Wood, Andrew R, Mahajan, Anubha, Tyrrell, Jessica, Robertson, Neil R, Rayner, N William, Qiao, Zhen, Moen, Gunn-Helen, Vaudel, Marc, Marsit, Carmen J, Chen, Jia, Nodzenski, Michael, Schnurr, Theresia M, Zafarmand, Mohammad H, Bradfield, Jonathan P, Grarup, Niels, Kooijman, Marjolein N, Li-Gao, Ruifang, Geller, Frank, Ahluwalia, Tarunveer S, Paternoster, Lavinia, Rueedi, Rico, Huikari, Ville, Hottenga, Jouke-Jan, Lyytikäinen, Leo-Pekka, Cavadino, Alana, Metrustry, Sarah, Cousminer, Diana L, Wu, Ying, Thiering, Elisabeth, Wang, Carol A, Have, Christian T, Vilor-Tejedor, Natalia, Joshi, Peter K, Painter, Jodie N, Ntalla, Ioanna, Myhre, Ronny, Pitkänen, Niina, van Leeuwen, Elisabeth M, Joro, Raimo, Lagou, Vasiliki, Richmond, Rebecca C, Espinosa, Ana, Barton, Sheila J, Inskip, Hazel M, Holloway, John W, Santa-Marina, Loreto, Estivill, Xavier, Ang, Wei, Marsh, Julie A, Reichetzeder, Christoph, Marullo, Letizia, Hocher, Berthold, Lunetta, Kathryn L, Murabito, Joanne M, Relton, Caroline L, Kogevinas, Manolis, Chatzi, Leda, Allard, Catherine, Bouchard, Luigi, Hivert, Marie-France, Zhang, Ge, Muglia, Louis J, Heikkinen, Jani, Morgen, Camilla S, van Kampen, Antoine HC, van Schaik, Barbera DC, Mentch, Frank D, Langenberg, Claudia, Luan, Jian’an, Scott, Robert A, Zhao, Jing Hua, Hemani, Gibran, Ring, Susan M, Bennett, Amanda J, Gaulton, Kyle J, Fernandez-Tajes, Juan, van Zuydam, Natalie R, Medina-Gomez, Carolina, de Haan, Hugoline G, Rosendaal, Frits R, Kutalik, Zoltán, Marques-Vidal, Pedro, Das, Shikta, Willemsen, Gonneke, Mbarek, Hamdi, Müller-Nurasyid, Martina, Standl, Marie, Appel, Emil VR, Fonvig, Cilius E, and Trier, Caecilie

Subjects
Biological Sciences, Genetics, Cardiovascular, Perinatal Period - Conditions Originating in Perinatal Period, Nutrition, Prevention, Preterm, Low Birth Weight and Health of the Newborn, Pediatric, Obesity, Conditions Affecting the Embryonic and Fetal Periods, Infant Mortality, 2.1 Biological and endogenous factors, Aetiology, Reproductive health and childbirth, Good Health and Well Being, Adult, Birth Weight, Blood Pressure, Body Height, Diabetes Mellitus, Type 2, Female, Fetal Development, Genetic Predisposition to Disease, Genome-Wide Association Study, Heart Diseases, Humans, Infant, Newborn, Male, Maternal Inheritance, Maternal-Fetal Exchange, Metabolic Diseases, Models, Genetic, Polymorphism, Single Nucleotide, Pregnancy, Risk Factors, EGG Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.

Published
2019

30. LMNA Variants and Risk of Adult-Onset Cardiac Disease

Author

Lazarte, Julieta, Jurgens, Sean J., Choi, Seung Hoan, Khurshid, Shaan, Morrill, Valerie N., Weng, Lu-Chen, Nauffal, Victor, Pirruccello, James P., Halford, Jennifer L., Hegele, Robert A., Ellinor, Patrick T., Lunetta, Kathryn L., and Lubitz, Steven A.

Published
2022
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31. 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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32. Publisher Correction: Endophenotype effect sizes support variant pathogenicity in monogenic disease susceptibility genes

Author

Halford, Jennifer L., Morrill, Valerie N., Choi, Seung Hoan, Jurgens, Sean J., Melloni, Giorgio, Marston, Nicholas A., Weng, Lu-Chen, Nauffal, Victor, Hall, Amelia W., Gunn, Sophia, Austin-Tse, Christina A., Pirruccello, James P., Khurshid, Shaan, Rehm, Heidi L., Benjamin, Emelia J., Boerwinkle, Eric, Brody, Jennifer A., Correa, Adolfo, Fornwalt, Brandon K., Gupta, Namrata, Haggerty, Christopher M., Harris, Stephanie, Heckbert, Susan R., Hong, Charles C., Kooperberg, Charles, Lin, Henry J., Loos, Ruth J. F., Mitchell, Braxton D., Morrison, Alanna C., Post, Wendy, Psaty, Bruce M., Redline, Susan, Rice, Kenneth M., Rich, Stephen S., Rotter, Jerome I., Schnatz, Peter F., Soliman, Elsayed Z., Sotoodehnia, Nona, Wong, Eugene K., Sabatine, Marc S., Ruff, Christian T., Lunetta, Kathryn L., Ellinor, Patrick T., and Lubitz, Steven A.

Published
2022
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35. GWAS of epigenetic aging rates in blood reveals a critical role for TERT.

Author

Lu, Ake T, Xue, Luting, Salfati, Elias L, Chen, Brian H, Ferrucci, Luigi, Levy, Daniel, Joehanes, Roby, Murabito, Joanne M, Kiel, Douglas P, Tsai, Pei-Chien, Yet, Idil, Bell, Jordana T, Mangino, Massimo, Tanaka, Toshiko, McRae, Allan F, Marioni, Riccardo E, Visscher, Peter M, Wray, Naomi R, Deary, Ian J, Levine, Morgan E, Quach, Austin, Assimes, Themistocles, Tsao, Philip S, Absher, Devin, Stewart, James D, Li, Yun, Reiner, Alex P, Hou, Lifang, Baccarelli, Andrea A, Whitsel, Eric A, Aviv, Abraham, Cardona, Alexia, Day, Felix R, Wareham, Nicholas J, Perry, John RB, Ong, Ken K, Raj, Kenneth, Lunetta, Kathryn L, and Horvath, Steve

Subjects
Leukocytes, Cells, Cultured, Telomere, Fibroblasts, Humans, Telomerase, DNA Methylation, Epigenesis, Genetic, CpG Islands, Aging, Menopause, Menarche, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Child, Female, Male, Genome-Wide Association Study, Young Adult, Mendelian Randomization Analysis, Cells, Cultured, Epigenesis, Genetic, and over
Abstract

DNA methylation age is an accurate biomarker of chronological age and predicts lifespan, but its underlying molecular mechanisms are unknown. In this genome-wide association study of 9907 individuals, we find gene variants mapping to five loci associated with intrinsic epigenetic age acceleration (IEAA) and gene variants in three loci associated with extrinsic epigenetic age acceleration (EEAA). Mendelian randomization analysis suggests causal influences of menarche and menopause on IEAA and lipoproteins on IEAA and EEAA. Variants associated with longer leukocyte telomere length (LTL) in the telomerase reverse transcriptase gene (TERT) paradoxically confer higher IEAA (P

Published
2018

36. Transethnic genome-wide scan identifies novel Alzheimer's disease loci.

Author

Jun, Gyungah R, Chung, Jaeyoon, Mez, Jesse, Barber, Robert, Beecham, Gary W, Bennett, David A, Buxbaum, Joseph D, Byrd, Goldie S, Carrasquillo, Minerva M, Crane, Paul K, Cruchaga, Carlos, De Jager, Philip, Ertekin-Taner, Nilufer, Evans, Denis, Fallin, M Danielle, Foroud, Tatiana M, Friedland, Robert P, Goate, Alison M, Graff-Radford, Neill R, Hendrie, Hugh, Hall, Kathleen S, Hamilton-Nelson, Kara L, Inzelberg, Rivka, Kamboh, M Ilyas, Kauwe, John SK, Kukull, Walter A, Kunkle, Brian W, Kuwano, Ryozo, Larson, Eric B, Logue, Mark W, Manly, Jennifer J, Martin, Eden R, Montine, Thomas J, Mukherjee, Shubhabrata, Naj, Adam, Reiman, Eric M, Reitz, Christiane, Sherva, Richard, St George-Hyslop, Peter H, Thornton, Timothy, Younkin, Steven G, Vardarajan, Badri N, Wang, Li-San, Wendlund, Jens R, Winslow, Ashley R, Alzheimer's Disease Genetics Consortium, Haines, Jonathan, Mayeux, Richard, Pericak-Vance, Margaret A, Schellenberg, Gerard, Lunetta, Kathryn L, and Farrer, Lindsay A

Subjects
Alzheimer's Disease Genetics Consortium, Humans, Alzheimer Disease, Genetic Predisposition to Disease, Adaptor Proteins, Signal Transducing, GTPase-Activating Proteins, Membrane Glycoproteins, Receptors, GABA, Molecular Chaperones, Polymorphism, Single Nucleotide, NFI Transcription Factors, Apolipoprotein E4, Genome-Wide Association Study, Peroxisomal Bifunctional Enzyme, Heparin-binding EGF-like Growth Factor, APOE interaction, Alzheimer's disease, Genome-wide association, Transethnic, Dementia, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Aging, Human Genome, Neurodegenerative, Prevention, Acquired Cognitive Impairment, Genetics, Alzheimer's Disease, 2.1 Biological and endogenous factors, Geriatrics, Clinical Sciences, Neurosciences
Abstract

IntroductionGenetic loci for Alzheimer's disease (AD) have been identified in whites of European ancestry, but the genetic architecture of AD among other populations is less understood.MethodsWe conducted a transethnic genome-wide association study (GWAS) for late-onset AD in Stage 1 sample including whites of European Ancestry, African-Americans, Japanese, and Israeli-Arabs assembled by the Alzheimer's Disease Genetics Consortium. Suggestive results from Stage 1 from novel loci were followed up using summarized results in the International Genomics Alzheimer's Project GWAS dataset.ResultsGenome-wide significant (GWS) associations in single-nucleotide polymorphism (SNP)-based tests (P

Published
2017

37. Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk.

Author

Day, Felix R, Thompson, Deborah J, Helgason, Hannes, Chasman, Daniel I, Finucane, Hilary, Sulem, Patrick, Ruth, Katherine S, Whalen, Sean, Sarkar, Abhishek K, Albrecht, Eva, Altmaier, Elisabeth, Amini, Marzyeh, Barbieri, Caterina M, Boutin, Thibaud, Campbell, Archie, Demerath, Ellen, Giri, Ayush, He, Chunyan, Hottenga, Jouke J, Karlsson, Robert, Kolcic, Ivana, Loh, Po-Ru, Lunetta, Kathryn L, Mangino, Massimo, Marco, Brumat, McMahon, George, Medland, Sarah E, Nolte, Ilja M, Noordam, Raymond, Nutile, Teresa, Paternoster, Lavinia, Perjakova, Natalia, Porcu, Eleonora, Rose, Lynda M, Schraut, Katharina E, Segrè, Ayellet V, Smith, Albert V, Stolk, Lisette, Teumer, Alexander, Andrulis, Irene L, Bandinelli, Stefania, Beckmann, Matthias W, Benitez, Javier, Bergmann, Sven, Bochud, Murielle, Boerwinkle, Eric, Bojesen, Stig E, Bolla, Manjeet K, Brand, Judith S, Brauch, Hiltrud, Brenner, Hermann, Broer, Linda, Brüning, Thomas, Buring, Julie E, Campbell, Harry, Catamo, Eulalia, Chanock, Stephen, Chenevix-Trench, Georgia, Corre, Tanguy, Couch, Fergus J, Cousminer, Diana L, Cox, Angela, Crisponi, Laura, Czene, Kamila, Davey Smith, George, de Geus, Eco JCN, de Mutsert, Renée, De Vivo, Immaculata, Dennis, Joe, Devilee, Peter, Dos-Santos-Silva, Isabel, Dunning, Alison M, Eriksson, Johan G, Fasching, Peter A, Fernández-Rhodes, Lindsay, Ferrucci, Luigi, Flesch-Janys, Dieter, Franke, Lude, Gabrielson, Marike, Gandin, Ilaria, Giles, Graham G, Grallert, Harald, Gudbjartsson, Daniel F, Guénel, Pascal, Hall, Per, Hallberg, Emily, Hamann, Ute, Harris, Tamara B, Hartman, Catharina A, Heiss, Gerardo, Hooning, Maartje J, Hopper, John L, Hu, Frank, Hunter, David J, Ikram, M Arfan, Im, Hae Kyung, Järvelin, Marjo-Riitta, Joshi, Peter K, Karasik, David, and Kellis, Manolis

Subjects
LifeLines Cohort Study, InterAct Consortium, kConFab/AOCS Investigators, Endometrial Cancer Association Consortium, Ovarian Cancer Association Consortium, PRACTICAL consortium, Humans, Neoplasms, Genetic Predisposition to Disease, Ubiquitin-Protein Ligases, Intercellular Signaling Peptides and Proteins, Calcium-Binding Proteins, Ribonucleoproteins, Membrane Proteins, Body Mass Index, Risk Factors, Age Factors, Genomic Imprinting, Puberty, Menarche, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Databases, Genetic, Adolescent, Female, Male, Genome-Wide Association Study, Aging, Breast Cancer, Biotechnology, Cancer, Human Genome, Genetics, Prostate Cancer, Urologic Diseases, 2.1 Biological and endogenous factors, Aetiology, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10-8) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.

Published
2017

38. 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

39. Genetic Interactions with Age, Sex, Body Mass Index, and Hypertension in Relation to Atrial Fibrillation: The AFGen Consortium

Author

Weng, Lu-Chen, Lunetta, Kathryn L, Müller-Nurasyid, Martina, Smith, Albert Vernon, Thériault, Sébastien, Weeke, Peter E, Barnard, John, Bis, Joshua C, Lyytikäinen, Leo-Pekka, Kleber, Marcus E, Martinsson, Andreas, Lin, Henry J, Rienstra, Michiel, Trompet, Stella, Krijthe, Bouwe P, Dörr, Marcus, Klarin, Derek, Chasman, Daniel I, Sinner, Moritz F, Waldenberger, Melanie, Launer, Lenore J, Harris, Tamara B, Soliman, Elsayed Z, Alonso, Alvaro, Paré, Guillaume, Teixeira, Pedro L, Denny, Joshua C, Shoemaker, M Benjamin, Van Wagoner, David R, Smith, Jonathan D, Psaty, Bruce M, Sotoodehnia, Nona, Taylor, Kent D, Kähönen, Mika, Nikus, Kjell, Delgado, Graciela E, Melander, Olle, Engström, Gunnar, Yao, Jie, Guo, Xiuqing, Christophersen, Ingrid E, Ellinor, Patrick T, Geelhoed, Bastiaan, Verweij, Niek, Macfarlane, Peter, Ford, Ian, Heeringa, Jan, Franco, Oscar H, Uitterlinden, André G, Völker, Uwe, Teumer, Alexander, Rose, Lynda M, Kääb, Stefan, Gudnason, Vilmundur, Arking, Dan E, Conen, David, Roden, Dan M, Chung, Mina K, Heckbert, Susan R, Benjamin, Emelia J, Lehtimäki, Terho, März, Winfried, Smith, J Gustav, Rotter, Jerome I, van der Harst, Pim, Jukema, J Wouter, Stricker, Bruno H, Felix, Stephan B, Albert, Christine M, and Lubitz, Steven A

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Heart Disease, Cardiovascular, Prevention, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Age Factors, Aged, Atrial Fibrillation, Body Mass Index, Chromosomes, Human, Pair 4, Epistasis, Genetic, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Hypertension, Male, Middle Aged, Odds Ratio, Polymorphism, Single Nucleotide, Reproducibility of Results, Risk Factors, Sex Characteristics
Abstract

It is unclear whether genetic markers interact with risk factors to influence atrial fibrillation (AF) risk. We performed genome-wide interaction analyses between genetic variants and age, sex, hypertension, and body mass index in the AFGen Consortium. Study-specific results were combined using meta-analysis (88,383 individuals of European descent, including 7,292 with AF). Variants with nominal interaction associations in the discovery analysis were tested for association in four independent studies (131,441 individuals, including 5,722 with AF). In the discovery analysis, the AF risk associated with the minor rs6817105 allele (at the PITX2 locus) was greater among subjects ≤ 65 years of age than among those > 65 years (interaction p-value = 4.0 × 10-5). The interaction p-value exceeded genome-wide significance in combined discovery and replication analyses (interaction p-value = 1.7 × 10-8). We observed one genome-wide significant interaction with body mass index and several suggestive interactions with age, sex, and body mass index in the discovery analysis. However, none was replicated in the independent sample. Our findings suggest that the pathogenesis of AF may differ according to age in individuals of European descent, but we did not observe evidence of statistically significant genetic interactions with sex, body mass index, or hypertension on AF risk.

Published
2017

40. A novel TCF7L2 type 2 diabetes SNP identified from fine mapping in African American women.

Author

Haddad, Stephen A, Palmer, Julie R, Lunetta, Kathryn L, Ng, Maggie CY, MEDIA Consortium, and Ruiz-Narváez, Edward A

Subjects
MEDIA Consortium, Humans, Diabetes Mellitus, Type 2, Chromosome Mapping, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, African Americans, Female, Young Adult, Transcription Factor 7-Like 2 Protein, Diabetes Mellitus, Type 2, Polymorphism, Single Nucleotide, General Science & Technology
Abstract

SNP rs7903146 in the Wnt pathway's TCF7L2 gene is the variant most significantly associated with type 2 diabetes to date, with associations observed across diverse populations. We sought to determine whether variants in other Wnt pathway genes are also associated with this disease. We evaluated 69 genes involved in the Wnt pathway, including TCF7L2, for associations with type 2 diabetes in 2632 African American cases and 2596 controls from the Black Women's Health Study. Tag SNPs for each gene region were genotyped on a custom Affymetrix Axiom Array, and imputation was performed to 1000 Genomes Phase 3 data. Gene-based analyses were conducted using the adaptive rank truncated product (ARTP) statistic. The PSMD2 gene was significantly associated with type 2 diabetes after correction for multiple testing (corrected p = 0.016), based on the nine most significant single variants in the +/- 20 kb region surrounding the gene, which includes nearby genes EIF4G1, ECE2, and EIF2B5. Association data on four of the nine variants were available from an independent sample of 8284 African American cases and 15,543 controls; associations were in the same direction, but weak and not statistically significant. TCF7L2 was the only other gene associated with type 2 diabetes at nominal p

Published
2017

41. GWAS analysis of handgrip and lower body strength in older adults in the CHARGE consortium.

Author

Matteini, Amy M, Tanaka, Toshiko, Karasik, David, Atzmon, Gil, Chou, Wen-Chi, Eicher, John D, Johnson, Andrew D, Arnold, Alice M, Callisaya, Michele L, Davies, Gail, Evans, Daniel S, Holtfreter, Birte, Lohman, Kurt, Lunetta, Kathryn L, Mangino, Massimo, Smith, Albert V, Smith, Jennifer A, Teumer, Alexander, Yu, Lei, Arking, Dan E, Buchman, Aron S, Chibinik, Lori B, De Jager, Philip L, Evans, Denis A, Faul, Jessica D, Garcia, Melissa E, Gillham-Nasenya, Irina, Gudnason, Vilmundur, Hofman, Albert, Hsu, Yi-Hsiang, Ittermann, Till, Lahousse, Lies, Liewald, David C, Liu, Yongmei, Lopez, Lorna, Rivadeneira, Fernando, Rotter, Jerome I, Siggeirsdottir, Kristin, Starr, John M, Thomson, Russell, Tranah, Gregory J, Uitterlinden, André G, Völker, Uwe, Völzke, Henry, Weir, David R, Yaffe, Kristine, Zhao, Wei, Zhuang, Wei Vivian, Zmuda, Joseph M, Bennett, David A, Cummings, Steven R, Deary, Ian J, Ferrucci, Luigi, Harris, Tamara B, Kardia, Sharon LR, Kocher, Thomas, Kritchevsky, Stephen B, Psaty, Bruce M, Seshadri, Sudha, Spector, Timothy D, Srikanth, Velandai K, Windham, B Gwen, Zillikens, M Carola, Newman, Anne B, Walston, Jeremy D, Kiel, Douglas P, and Murabito, Joanne M

Subjects
Humans, Hand Strength, Cohort Studies, Reproducibility of Results, Chromatin Immunoprecipitation, Epigenesis, Genetic, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Adult, Aged, Muscle Strength, Genome-Wide Association Study, Molecular Sequence Annotation, SNP, aging, genomewide association, meta-analysis, muscle strength, older adults, Epigenesis, Genetic, Polymorphism, Single Nucleotide, Developmental Biology, Medical and Health Sciences, Biological Sciences
Abstract

Decline in muscle strength with aging is an important predictor of health trajectory in the elderly. Several factors, including genetics, are proposed contributors to variability in muscle strength. To identify genetic contributors to muscle strength, a meta-analysis of genomewide association studies of handgrip was conducted. Grip strength was measured using a handheld dynamometer in 27 581 individuals of European descent over 65 years of age from 14 cohort studies. Genomewide association analysis was conducted on ~2.7 million imputed and genotyped variants (SNPs). Replication of the most significant findings was conducted using data from 6393 individuals from three cohorts. GWAS of lower body strength was also characterized in a subset of cohorts. Two genomewide significant (P-value< 5 × 10(-8) ) and 39 suggestive (P-value< 5 × 10(-5) ) associations were observed from meta-analysis of the discovery cohorts. After meta-analysis with replication cohorts, genomewide significant association was observed for rs752045 on chromosome 8 (β = 0.47, SE = 0.08, P-value = 5.20 × 10(-10) ). This SNP is mapped to an intergenic region and is located within an accessible chromatin region (DNase hypersensitivity site) in skeletal muscle myotubes differentiated from the human skeletal muscle myoblasts cell line. This locus alters a binding motif of the CCAAT/enhancer-binding protein-β (CEBPB) that is implicated in muscle repair mechanisms. GWAS of lower body strength did not yield significant results. A common genetic variant in a chromosomal region that regulates myotube differentiation and muscle repair may contribute to variability in grip strength in the elderly. Further studies are needed to uncover the mechanisms that link this genetic variant with muscle strength.

Published
2016

42. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Author

Taliun, Daniel, Harris, Daniel N., Kessler, Michael D., Carlson, Jedidiah, Szpiech, Zachary A., Torres, Raul, Taliun, Sarah A. Gagliano, Corvelo, André, Gogarten, Stephanie M., Kang, Hyun Min, Pitsillides, Achilleas N., LeFaive, Jonathon, Lee, Seung-been, Tian, Xiaowen, Browning, Brian L., Das, Sayantan, Emde, Anne-Katrin, Clarke, Wayne E., Loesch, Douglas P., Shetty, Amol C., Blackwell, Thomas W., Smith, Albert V., Wong, Quenna, Liu, Xiaoming, Conomos, Matthew P., Bobo, Dean M., Aguet, François, Albert, Christine, Alonso, Alvaro, Ardlie, Kristin G., Arking, Dan E., Aslibekyan, Stella, Auer, Paul L., Barnard, John, Barr, R. Graham, Barwick, Lucas, Becker, Lewis C., Beer, Rebecca L., Benjamin, Emelia J., Bielak, Lawrence F., Blangero, John, Boehnke, Michael, Bowden, Donald W., Brody, Jennifer A., Burchard, Esteban G., Cade, Brian E., Casella, James F., Chalazan, Brandon, Chasman, Daniel I., Chen, Yii-Der Ida, Cho, Michael H., Choi, Seung Hoan, Chung, Mina K., Clish, Clary B., Correa, Adolfo, Curran, Joanne E., Custer, Brian, Darbar, Dawood, Daya, Michelle, de Andrade, Mariza, DeMeo, Dawn L., Dutcher, Susan K., Ellinor, Patrick T., Emery, Leslie S., Eng, Celeste, Fatkin, Diane, Fingerlin, Tasha, Forer, Lukas, Fornage, Myriam, Franceschini, Nora, Fuchsberger, Christian, Fullerton, Stephanie M., Germer, Soren, Gladwin, Mark T., Gottlieb, Daniel J., Guo, Xiuqing, Hall, Michael E., He, Jiang, Heard-Costa, Nancy L., Heckbert, Susan R., Irvin, Marguerite R., Johnsen, Jill M., Johnson, Andrew D., Kaplan, Robert, Kardia, Sharon L. R., Kelly, Tanika, Kelly, Shannon, Kenny, Eimear E., Kiel, Douglas P., Klemmer, Robert, Konkle, Barbara A., Kooperberg, Charles, Köttgen, Anna, Lange, Leslie A., Lasky-Su, Jessica, Levy, Daniel, Lin, Xihong, Lin, Keng-Han, Liu, Chunyu, Loos, Ruth J. F., Garman, Lori, Gerszten, Robert, Lubitz, Steven A., Lunetta, Kathryn L., Mak, Angel C. Y., Manichaikul, Ani, Manning, Alisa K., Mathias, Rasika A., McManus, David D., McGarvey, Stephen T., Meigs, James B., Meyers, Deborah A., Mikulla, Julie L., Minear, Mollie A., Mitchell, Braxton D., Mohanty, Sanghamitra, Montasser, May E., Montgomery, Courtney, Morrison, Alanna C., Murabito, Joanne M., Natale, Andrea, Natarajan, Pradeep, Nelson, Sarah C., North, Kari E., O’Connell, Jeffrey R., Palmer, Nicholette D., Pankratz, Nathan, Peloso, Gina M., Peyser, Patricia A., Pleiness, Jacob, Post, Wendy S., Psaty, Bruce M., Rao, D. C., Redline, Susan, Reiner, Alexander P., Roden, Dan, Rotter, Jerome I., Ruczinski, Ingo, Sarnowski, Chloé, Schoenherr, Sebastian, Schwartz, David A., Seo, Jeong-Sun, Seshadri, Sudha, Sheehan, Vivien A., Sheu, Wayne H., Shoemaker, M. Benjamin, Smith, Nicholas L., Smith, Jennifer A., Sotoodehnia, Nona, Stilp, Adrienne M., Tang, Weihong, Taylor, Kent D., Telen, Marilyn, Thornton, Timothy A., Tracy, Russell P., Van Den Berg, David J., Vasan, Ramachandran S., Viaud-Martinez, Karine A., Vrieze, Scott, Weeks, Daniel E., Weir, Bruce S., Weiss, Scott T., Weng, Lu-Chen, Willer, Cristen J., Zhang, Yingze, Zhao, Xutong, Arnett, Donna K., Ashley-Koch, Allison E., Barnes, Kathleen C., Boerwinkle, Eric, Gabriel, Stacey, Gibbs, Richard, Rice, Kenneth M., Rich, Stephen S., Silverman, Edwin K., Qasba, Pankaj, Gan, Weiniu, Papanicolaou, George J., Nickerson, Deborah A., Browning, Sharon R., Zody, Michael C., Zöllner, Sebastian, Wilson, James G., Cupples, L. Adrienne, Laurie, Cathy C., Jaquish, Cashell E., Hernandez, Ryan D., O’Connor, Timothy D., and Abecasis, Gonçalo R.

Published
2021
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46. DNA methylation-based measures of biological age: meta-analysis predicting time to death

Author

Chen, Brian H, Marioni, Riccardo E, Colicino, Elena, Peters, Marjolein J, Ward-Caviness, Cavin K, Tsai, Pei-Chien, Roetker, Nicholas S, Just, Allan C, Demerath, Ellen W, Guan, Weihua, Bressler, Jan, Fornage, Myriam, Studenski, Stephanie, Vandiver, Amy R, Moore, Ann Zenobia, Tanaka, Toshiko, Kiel, Douglas P, Liang, Liming, Vokonas, Pantel, Schwartz, Joel, Lunetta, Kathryn L, Murabito, Joanne M, Bandinelli, Stefania, Hernandez, Dena G, Melzer, David, Nalls, Michael, Pilling, Luke C, Price, Timothy R, Singleton, Andrew B, Gieger, Christian, Holle, Rolf, Kretschmer, Anja, Kronenberg, Florian, Kunze, Sonja, Linseisen, Jakob, Meisinger, Christine, Rathmann, Wolfgang, Waldenberger, Melanie, Visscher, Peter M, Shah, Sonia, Wray, Naomi R, McRae, Allan F, Franco, Oscar H, Hofman, Albert, Uitterlinden, André G, Absher, Devin, Assimes, Themistocles, Levine, Morgan E, Lu, Ake T, Tsao, Philip S, Hou, Lifang, Manson, JoAnn E, Carty, Cara L, LaCroix, Andrea Z, Reiner, Alexander P, Spector, Tim D, Feinberg, Andrew P, Levy, Daniel, Baccarelli, Andrea, van Meurs, Joyce, Bell, Jordana T, Peters, Annette, Deary, Ian J, Pankow, James S, Ferrucci, Luigi, and Horvath, Steve

Subjects
Biological Sciences, Genetics, Clinical Research, Prevention, Good Health and Well Being, Aging, DNA Methylation, Epigenesis, Genetic, Female, Humans, Logistic Models, Male, Mortality, Racial Groups, Risk Factors, Survival Analysis, T-Lymphocyte Subsets, all-cause mortality, lifespan, epigenetics, epigenetic clock, DNA methylation, mortality, Biochemistry and cell biology, Clinical sciences
Abstract

Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2x10-9), independent of chronological age, even after adjusting for additional risk factors (p

Published
2016

47. Gene-gene Interaction Analyses for Atrial Fibrillation

Author

Lin, Honghuang, Mueller-Nurasyid, Martina, Smith, Albert V, Arking, Dan E, Barnard, John, Bartz, Traci M, Lunetta, Kathryn L, Lohman, Kurt, Kleber, Marcus E, Lubitz, Steven A, Geelhoed, Bastiaan, Trompet, Stella, Niemeijer, Maartje N, Kacprowski, Tim, Chasman, Daniel I, Klarin, Derek, Sinner, Moritz F, Waldenberger, Melanie, Meitinger, Thomas, Harris, Tamara B, Launer, Lenore J, Soliman, Elsayed Z, Chen, Lin Y, Smith, Jonathan D, Van Wagoner, David R, Rotter, Jerome I, Psaty, Bruce M, Xie, Zhijun, Hendricks, Audrey E, Ding, Jingzhong, Delgado, Graciela E, Verweij, Niek, van der Harst, Pim, Macfarlane, Peter W, Ford, Ian, Hofman, Albert, Uitterlinden, André, Heeringa, Jan, Franco, Oscar H, Kors, Jan A, Weiss, Stefan, Völzke, Henry, Rose, Lynda M, Natarajan, Pradeep, Kathiresan, Sekar, Kääb, Stefan, Gudnason, Vilmundur, Alonso, Alvaro, Chung, Mina K, Heckbert, Susan R, Benjamin, Emelia J, Liu, Yongmei, März, Winfried, Rienstra, Michiel, Jukema, J Wouter, Stricker, Bruno H, Dörr, Marcus, Albert, Christine M, and Ellinor, Patrick T

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Heart Disease, Human Genome, Cardiovascular, Aetiology, 2.1 Biological and endogenous factors, Aged, Atrial Fibrillation, Cohort Studies, Epistasis, Genetic, Female, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Hyperpolarization-Activated Cyclic Nucleotide-Gated Channels, Male, Membrane Transport Proteins, Middle Aged, Multivariate Analysis, Muscle Proteins, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, Potassium Channels
Abstract

Atrial fibrillation (AF) is a heritable disease that affects more than thirty million individuals worldwide. Extensive efforts have been devoted to the study of genetic determinants of AF. The objective of our study is to examine the effect of gene-gene interaction on AF susceptibility. We performed a large-scale association analysis of gene-gene interactions with AF in 8,173 AF cases, and 65,237 AF-free referents collected from 15 studies for discovery. We examined putative interactions between genome-wide SNPs and 17 known AF-related SNPs. The top interactions were then tested for association in an independent cohort for replication, which included more than 2,363 AF cases and 114,746 AF-free referents. One interaction, between rs7164883 at the HCN4 locus and rs4980345 at the SLC28A1 locus, was found to be significantly associated with AF in the discovery cohorts (interaction OR = 1.44, 95% CI: 1.27-1.65, P = 4.3 × 10-8). Eight additional gene-gene interactions were also marginally significant (P

Published
2016

49. Genome‐wide association study for Alzheimer disease in APOE ɛ4/ɛ4 carriers

Author

Clayton, Samantha, primary, Goldstein, Daniel, additional, Wang, Li‐San, additional, Mayeux, Richard, additional, Haines, Jonathan L., additional, Pericak‐Vance, Margaret A., additional, Schellenberg, Gerald D., additional, Lunetta, Kathryn L., additional, Au, Rhoda, additional, Farrer, Lindsay A., additional, Stein, Thor D., additional, and Jun, Gyungah R, additional

Published
2023
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50. Blood‐derived mitochondrial DNA copy number is associated with Alzheimer’s Disease through the regulation of plasma lipid and amino acid metabolism

Author

Tong, Tong, primary, Zhu, Congcong, additional, Farrell, John, additional, Khurshid, Zainab, additional, Martin, Eden R., additional, Pericak‐Vance, Margaret A., additional, Wang, Li‐San, additional, Schellenberg, Gerald D., additional, Haines, Jonathan L., additional, Lunetta, Kathryn L., additional, Farrer, Lindsay A., additional, and Zhang, Xiaoling, additional

Published
2023
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