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4. Author Correction: Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Author

de Rojas, Itziar, Moreno-Grau, Sonia, Tesi, Niccolo, Grenier-Boley, Benjamin, Andrade, Victor, Jansen, Iris E., Pedersen, Nancy L., Stringa, Najada, Zettergren, Anna, Hernández, Isabel, Montrreal, Laura, Antúnez, Carmen, Antonell, Anna, Tankard, Rick M., Bis, Joshua C., Sims, Rebecca, Bellenguez, Céline, Quintela, Inés, González-Perez, Antonio, Calero, Miguel, Franco-Macías, Emilio, Macías, Juan, Blesa, Rafael, Cervera-Carles, Laura, Menéndez-González, Manuel, Frank-García, Ana, Royo, Jose Luís, Moreno, Fermin, Huerto Vilas, Raquel, Baquero, Miquel, Diez-Fairen, Mónica, Lage, Carmen, García-Madrona, Sebastián, García-González, Pablo, Alarcón-Martín, Emilio, Valero, Sergi, Sotolongo-Grau, Oscar, Ullgren, Abbe, Naj, Adam C., Lemstra, Afina W., Benaque, Alba, Pérez-Cordón, Alba, Benussi, Alberto, Rábano, Alberto, Padovani, Alessandro, Squassina, Alessio, de Mendonça, Alexandre, Arias Pastor, Alfonso, Kok, Almar A. L., Meggy, Alun, Pastor, Ana Belén, Espinosa, Ana, Corma-Gómez, Anaïs, Martín Montes, Angel, Sanabria, Ángela, DeStefano, Anita L., Schneider, Anja, Haapasalo, Annakaisa, Kinhult Ståhlbom, Anne, Tybjærg-Hansen, Anne, Hartmann, Annette M., Spottke, Annika, Corbatón-Anchuelo, Arturo, Rongve, Arvid, Borroni, Barbara, Arosio, Beatrice, Nacmias, Benedetta, Nordestgaard, Børge G., Kunkle, Brian W., Charbonnier, Camille, Abdelnour, Carla, Masullo, Carlo, Martínez Rodríguez, Carmen, Muñoz-Fernandez, Carmen, Dufouil, Carole, Graff, Caroline, Ferreira, Catarina B., Chillotti, Caterina, Reynolds, Chandra A., Fenoglio, Chiara, Van Broeckhoven, Christine, Clark, Christopher, Pisanu, Claudia, Satizabal, Claudia L., Holmes, Clive, Buiza-Rueda, Dolores, Aarsland, Dag, Rujescu, Dan, Alcolea, Daniel, Galimberti, Daniela, Wallon, David, Seripa, Davide, Grünblatt, Edna, Dardiotis, Efthimios, Düzel, Emrah, Scarpini, Elio, Conti, Elisa, Rubino, Elisa, Gelpi, Ellen, Rodriguez-Rodriguez, Eloy, Duron, Emmanuelle, Boerwinkle, Eric, Ferri, Evelyn, Tagliavini, Fabrizio, Küçükali, Fahri, Pasquier, Florence, Sanchez-Garcia, Florentino, Mangialasche, Francesca, Jessen, Frank, Nicolas, Gaël, Selbæk, Geir, Ortega, Gemma, Chêne, Geneviève, Hadjigeorgiou, Georgios, Rossi, Giacomina, Spalletta, Gianfranco, Giaccone, Giorgio, Grande, Giulia, Binetti, Giuliano, Papenberg, Goran, Hampel, Harald, Bailly, Henri, Zetterberg, Henrik, Soininen, Hilkka, Karlsson, Ida K., Alvarez, Ignacio, Appollonio, Ildebrando, Giegling, Ina, Skoog, Ingmar, Saltvedt, Ingvild, Rainero, Innocenzo, Rosas Allende, Irene, Hort, Jakub, Diehl-Schmid, Janine, Van Dongen, Jasper, Vidal, Jean-Sebastien, Lehtisalo, Jenni, Wiltfang, Jens, Thomassen, Jesper Qvist, Kornhuber, Johannes, Haines, Jonathan L., Vogelgsang, Jonathan, Pineda, Juan A., Fortea, Juan, Popp, Julius, Deckert, Jürgen, Buerger, Katharina, Morgan, Kevin, Fließbach, Klaus, Sleegers, Kristel, Molina-Porcel, Laura, Kilander, Lena, Weinhold, Leonie, Farrer, Lindsay A., Wang, Li-San, Kleineidam, Luca, Farotti, Lucia, Parnetti, Lucilla, Tremolizzo, Lucio, Hausner, Lucrezia, Benussi, Luisa, Froelich, Lutz, Ikram, M. Arfan, Deniz-Naranjo, M. Candida, Tsolaki, Magda, Rosende-Roca, Maitée, Löwenmark, Malin, Hulsman, Marc, Spallazzi, Marco, Pericak-Vance, Margaret A., Esiri, Margaret, Bernal Sánchez-Arjona, María, Dalmasso, Maria Carolina, Martínez-Larrad, María Teresa, Arcaro, Marina, Nöthen, Markus M., Fernández-Fuertes, Marta, Dichgans, Martin, Ingelsson, Martin, Herrmann, Martin J., Scherer, Martin, Vyhnalek, Martin, Kosmidis, Mary H., Yannakoulia, Mary, Schmid, Matthias, Ewers, Michael, Heneka, Michael T., Wagner, Michael, Scamosci, Michela, Kivipelto, Miia, Hiltunen, Mikko, Zulaica, Miren, Alegret, Montserrat, Fornage, Myriam, Roberto, Natalia, van Schoor, Natasja M., Seidu, Nazib M., Banaj, Nerisa, Armstrong, Nicola J., Scarmeas, Nikolaos, Scherbaum, Norbert, Goldhardt, Oliver, Hanon, Oliver, Peters, Oliver, Skrobot, Olivia Anna, Quenez, Olivier, Lerch, Ondrej, Bossù, Paola, Caffarra, Paolo, Dionigi Rossi, Paolo, Sakka, Paraskevi, Mecocci, Patrizia, Hoffmann, Per, Holmans, Peter A., Fischer, Peter, Riederer, Peter, Yang, Qiong, Marshall, Rachel, Kalaria, Rajesh N., Mayeux, Richard, Vandenberghe, Rik, Cecchetti, Roberta, Ghidoni, Roberta, Frikke-Schmidt, Ruth, Sorbi, Sandro, Hägg, Sara, Engelborghs, Sebastiaan, Helisalmi, Seppo, Botne Sando, Sigrid, Kern, Silke, Archetti, Silvana, Boschi, Silvia, Fostinelli, Silvia, Gil, Silvia, Mendoza, Silvia, Mead, Simon, Ciccone, Simona, Djurovic, Srdjan, Heilmann-Heimbach, Stefanie, Riedel-Heller, Steffi, Kuulasmaa, Teemu, del Ser, Teodoro, Lebouvier, Thibaud, Polak, Thomas, Ngandu, Tiia, Grimmer, Timo, Bessi, Valentina, Escott-Price, Valentina, Giedraitis, Vilmantas, Deramecourt, Vincent, Maier, Wolfgang, Jian, Xueqiu, Pijnenburg, Yolande A. L., Kehoe, Patrick Gavin, Garcia-Ribas, Guillermo, Sánchez-Juan, Pascual, Pastor, Pau, Pérez-Tur, Jordi, Piñol-Ripoll, Gerard, Lopez de Munain, Adolfo, García-Alberca, Jose María, Bullido, María J., Álvarez, Victoria, Lleó, Alberto, Real, Luis M., Mir, Pablo, Medina, Miguel, Scheltens, Philip, Holstege, Henne, Marquié, Marta, Sáez, María Eugenia, Carracedo, Ángel, Amouyel, Philippe, Schellenberg, Gerard D., Williams, Julie, Seshadri, Sudha, van Duijn, Cornelia M., Mather, Karen A., Sánchez-Valle, Raquel, Serrano-Ríos, Manuel, Orellana, Adelina, Tárraga, Lluís, Blennow, Kaj, Huisman, Martijn, Andreassen, Ole A., Posthuma, Danielle, Clarimón, Jordi, Boada, Mercè, van der Flier, Wiesje M., Ramirez, Alfredo, Lambert, Jean-Charles, van der Lee, Sven J., and Ruiz, Agustín

Published
2023
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5. Polygenic resilience scores capture protective genetic effects for Alzheimer’s disease

Author

Hou, Jiahui, Hess, Jonathan L, Armstrong, Nicola, Bis, Joshua C, Grenier-Boley, Benjamin, Karlsson, Ida K, Leonenko, Ganna, Numbers, Katya, O’Brien, Eleanor K, Shadrin, Alexey, Thalamuthu, Anbupalam, Yang, Qiong, Andreassen, Ole A, Brodaty, Henry, Gatz, Margaret, Kochan, Nicole A, Lambert, Jean-Charles, Laws, Simon M, Masters, Colin L, Mather, Karen A, Pedersen, Nancy L, Posthuma, Danielle, Sachdev, Perminder S, Williams, Julie, Fan, Chun Chieh, Faraone, Stephen V, Fennema-Notestine, Christine, Lin, Shu-Ju, Escott-Price, Valentina, Holmans, Peter, Seshadri, Sudha, Tsuang, Ming T, Kremen, William S, and Glatt, Stephen J

Subjects
Genetics, Alzheimer's Disease, Brain Disorders, Human Genome, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Genetic Testing, Neurodegenerative, Prevention, Dementia, Aging, Acquired Cognitive Impairment, Aetiology, 2.1 Biological and endogenous factors, Alzheimer Disease, Apolipoprotein E4, Apolipoproteins E, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Multifactorial Inheritance, Risk Factors, Alzheimer’s Disease Neuroimaging Initiative, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

Polygenic risk scores (PRSs) can boost risk prediction in late-onset Alzheimer's disease (LOAD) beyond apolipoprotein E (APOE) but have not been leveraged to identify genetic resilience factors. Here, we sought to identify resilience-conferring common genetic variants in (1) unaffected individuals having high PRSs for LOAD, and (2) unaffected APOE-ε4 carriers also having high PRSs for LOAD. We used genome-wide association study (GWAS) to contrast "resilient" unaffected individuals at the highest genetic risk for LOAD with LOAD cases at comparable risk. From GWAS results, we constructed polygenic resilience scores to aggregate the addictive contributions of risk-orthogonal common variants that promote resilience to LOAD. Replication of resilience scores was undertaken in eight independent studies. We successfully replicated two polygenic resilience scores that reduce genetic risk penetrance for LOAD. We also showed that polygenic resilience scores positively correlate with polygenic risk scores in unaffected individuals, perhaps aiding in staving off disease. Our findings align with the hypothesis that a combination of risk-independent common variants mediates resilience to LOAD by moderating genetic disease risk.

Published
2022

11. Associations between Sleep Disorders and Impulsive-Compulsive Behaviors in Parkinson's Disease: A Prospective Cohort Study.

Author

Ye, Meijie, Kang, Xiaoying, Karlsson, Ida K., Wang, Yu, Ji, Qianqian, Liu, Qi, Xu, Xiaowei, Hägg, Sara, Fang, Fang, Wirdefeldt, Karin, and Zhan, Yiqiang

Subjects
RAPID eye movement sleep, SLEEP, PARKINSON'S disease, BEHAVIOR disorders, SLEEP disorders
Abstract

Objective: To examine the associations of excessive daytime sleepiness (EDS) and probable rapid eye movement sleep behavior disorder (pRBD), respectively, with impulsive-compulsive behaviors (ICBs) over a 5-year follow-up in patients with early Parkinson's disease (PD). Methods: The Parkinson's Progression Markers Initiative is a multicenter cohort study based on an ongoing and open-ended registry. Longitudinal associations of sleep disorders with ICB over 5-year follow-up visits were estimated using generalized linear mixed-effects models among PD participants. Results: A total of 825 PD participants were enrolled at baseline. The study sample had a median baseline age of 63.1 (interquartile range: 55.6–69.3) years and comprised 496 (61.5%) men. Among them, 201 (24.9%) had ICB at baseline. In the generalized mixed-effects models, EDS (odds ratio [OR] = 1.09, 95% confidence interval [CI] 1.05, 1.12) and RBD (OR = 1.07, 95% CI 1.03, 1.12) were substantially associated with higher odds of developing ICB over time in PD patients, after multivariate adjustment including age, gender, family history, GDS score, STAI-Y score, MDS-UPDRS part III score, LEDD, and disease duration. Consistent results were observed when stratifying by age at baseline, gender, and PD family history. Conclusions: The study findings suggest a longitudinal association between EDS and pRBD with an increased risk of developing ICB in patients with PD. The findings emphasize the significance of evaluating and addressing sleep disorders in PD patients as a potential approach to managing ICB. [ABSTRACT FROM AUTHOR]

Published
2024
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12. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence

Author

Savage, Jeanne E, Jansen, Philip R, Stringer, Sven, Watanabe, Kyoko, Bryois, Julien, de Leeuw, Christiaan A, Nagel, Mats, Awasthi, Swapnil, Barr, Peter B, Coleman, Jonathan RI, Grasby, Katrina L, Hammerschlag, Anke R, Kaminski, Jakob A, Karlsson, Robert, Krapohl, Eva, Lam, Max, Nygaard, Marianne, Reynolds, Chandra A, Trampush, Joey W, Young, Hannah, Zabaneh, Delilah, Hägg, Sara, Hansell, Narelle K, Karlsson, Ida K, Linnarsson, Sten, Montgomery, Grant W, Muñoz-Manchado, Ana B, Quinlan, Erin B, Schumann, Gunter, Skene, Nathan G, Webb, Bradley T, White, Tonya, Arking, Dan E, Avramopoulos, Dimitrios, Bilder, Robert M, Bitsios, Panos, Burdick, Katherine E, Cannon, Tyrone D, Chiba-Falek, Ornit, Christoforou, Andrea, Cirulli, Elizabeth T, Congdon, Eliza, Corvin, Aiden, Davies, Gail, Deary, Ian J, DeRosse, Pamela, Dickinson, Dwight, Djurovic, Srdjan, Donohoe, Gary, Conley, Emily Drabant, Eriksson, Johan G, Espeseth, Thomas, Freimer, Nelson A, Giakoumaki, Stella, Giegling, Ina, Gill, Michael, Glahn, David C, Hariri, Ahmad R, Hatzimanolis, Alex, Keller, Matthew C, Knowles, Emma, Koltai, Deborah, Konte, Bettina, Lahti, Jari, Le Hellard, Stephanie, Lencz, Todd, Liewald, David C, London, Edythe, Lundervold, Astri J, Malhotra, Anil K, Melle, Ingrid, Morris, Derek, Need, Anna C, Ollier, William, Palotie, Aarno, Payton, Antony, Pendleton, Neil, Poldrack, Russell A, Räikkönen, Katri, Reinvang, Ivar, Roussos, Panos, Rujescu, Dan, Sabb, Fred W, Scult, Matthew A, Smeland, Olav B, Smyrnis, Nikolaos, Starr, John M, Steen, Vidar M, Stefanis, Nikos C, Straub, Richard E, Sundet, Kjetil, Tiemeier, Henning, Voineskos, Aristotle N, Weinberger, Daniel R, Widen, Elisabeth, Yu, Jin, Abecasis, Goncalo, Andreassen, Ole A, Breen, Gerome, and Christiansen, Lene

Subjects
Biological Sciences, Genetics, Brain Disorders, Mental Health, Human Genome, Biotechnology, Neurosciences, Underpinning research, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Aetiology, Mental health, Neurological, Adolescent, Brain, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Intelligence, Male, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Intelligence is highly heritable1 and a major determinant of human health and well-being2. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence3-7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

Published
2018

14. Epigenome‐wide analysis of frailty: Results from two European twin cohorts

Author

Mak, Jonathan K. L., primary, Skovgaard, Asmus Cosmos, additional, Nygaard, Marianne, additional, Kananen, Laura, additional, Reynolds, Chandra A., additional, Wang, Yunzhang, additional, Kuja‐Halkola, Ralf, additional, Karlsson, Ida K., additional, Pedersen, Nancy L., additional, Hägg, Sara, additional, Soerensen, Mette, additional, and Jylhävä, Juulia, additional

Published
2024
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15. A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer’s disease

Author

Wightman, Douglas P., Jansen, Iris E., Savage, Jeanne E., Shadrin, Alexey A., Bahrami, Shahram, Holland, Dominic, Rongve, Arvid, Børte, Sigrid, Winsvold, Bendik S., Drange, Ole Kristian, Martinsen, Amy E., Skogholt, Anne Heidi, Willer, Cristen, Bråthen, Geir, Bosnes, Ingunn, Nielsen, Jonas Bille, Fritsche, Lars G., Thomas, Laurent F., Pedersen, Linda M., Gabrielsen, Maiken E., Johnsen, Marianne Bakke, Meisingset, Tore Wergeland, Zhou, Wei, Proitsi, Petroula, Hodges, Angela, Dobson, Richard, Velayudhan, Latha, Heilbron, Karl, Auton, Adam, Sealock, Julia M., Davis, Lea K., Pedersen, Nancy L., Reynolds, Chandra A., Karlsson, Ida K., Magnusson, Sigurdur, Stefansson, Hreinn, Thordardottir, Steinunn, Jonsson, Palmi V., Snaedal, Jon, Zettergren, Anna, Skoog, Ingmar, Kern, Silke, Waern, Margda, Zetterberg, Henrik, Blennow, Kaj, Stordal, Eystein, Hveem, Kristian, Zwart, John-Anker, Athanasiu, Lavinia, Selnes, Per, Saltvedt, Ingvild, Sando, Sigrid B., Ulstein, Ingun, Djurovic, Srdjan, Fladby, Tormod, Aarsland, Dag, Selbæk, Geir, Ripke, Stephan, Stefansson, Kari, Andreassen, Ole A., and Posthuma, Danielle

Published
2021
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19. Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Author

de Rojas, Itziar, Moreno-Grau, Sonia, Tesi, Niccolo, Grenier-Boley, Benjamin, Andrade, Victor, Jansen, Iris E., Pedersen, Nancy L., Stringa, Najada, Zettergren, Anna, Hernández, Isabel, Montrreal, Laura, Antúnez, Carmen, Antonell, Anna, Tankard, Rick M., Bis, Joshua C., Sims, Rebecca, Bellenguez, Céline, Quintela, Inés, González-Perez, Antonio, Calero, Miguel, Franco-Macías, Emilio, Macías, Juan, Blesa, Rafael, Cervera-Carles, Laura, Menéndez-González, Manuel, Frank-García, Ana, Royo, Jose Luís, Moreno, Fermin, Huerto Vilas, Raquel, Baquero, Miquel, Diez-Fairen, Mónica, Lage, Carmen, García-Madrona, Sebastián, García-González, Pablo, Alarcón-Martín, Emilio, Valero, Sergi, Sotolongo-Grau, Oscar, Ullgren, Abbe, Naj, Adam C., Lemstra, Afina W., Benaque, Alba, Pérez-Cordón, Alba, Benussi, Alberto, Rábano, Alberto, Padovani, Alessandro, Squassina, Alessio, de Mendonça, Alexandre, Arias Pastor, Alfonso, Kok, Almar A. L., Meggy, Alun, Pastor, Ana Belén, Espinosa, Ana, Corma-Gómez, Anaïs, Martín Montes, Angel, Sanabria, Ángela, DeStefano, Anita L., Schneider, Anja, Haapasalo, Annakaisa, Kinhult Ståhlbom, Anne, Tybjærg-Hansen, Anne, Hartmann, Annette M., Spottke, Annika, Corbatón-Anchuelo, Arturo, Rongve, Arvid, Borroni, Barbara, Arosio, Beatrice, Nacmias, Benedetta, Nordestgaard, Børge G., Kunkle, Brian W., Charbonnier, Camille, Abdelnour, Carla, Masullo, Carlo, Martínez Rodríguez, Carmen, Muñoz-Fernandez, Carmen, Dufouil, Carole, Graff, Caroline, Ferreira, Catarina B., Chillotti, Caterina, Reynolds, Chandra A., Fenoglio, Chiara, Van Broeckhoven, Christine, Clark, Christopher, Pisanu, Claudia, Satizabal, Claudia L., Holmes, Clive, Buiza-Rueda, Dolores, Aarsland, Dag, Rujescu, Dan, Alcolea, Daniel, Galimberti, Daniela, Wallon, David, Seripa, Davide, Grünblatt, Edna, Dardiotis, Efthimios, Düzel, Emrah, Scarpini, Elio, Conti, Elisa, Rubino, Elisa, Gelpi, Ellen, Rodriguez-Rodriguez, Eloy, Duron, Emmanuelle, Boerwinkle, Eric, Ferri, Evelyn, Tagliavini, Fabrizio, Küçükali, Fahri, Pasquier, Florence, Sanchez-Garcia, Florentino, Mangialasche, Francesca, Jessen, Frank, Nicolas, Gaël, Selbæk, Geir, Ortega, Gemma, Chêne, Geneviève, Hadjigeorgiou, Georgios, Rossi, Giacomina, Spalletta, Gianfranco, Giaccone, Giorgio, Grande, Giulia, Binetti, Giuliano, Papenberg, Goran, Hampel, Harald, Bailly, Henri, Zetterberg, Henrik, Soininen, Hilkka, Karlsson, Ida K., Alvarez, Ignacio, Appollonio, Ildebrando, Giegling, Ina, Skoog, Ingmar, Saltvedt, Ingvild, Rainero, Innocenzo, Rosas Allende, Irene, Hort, Jakub, Diehl-Schmid, Janine, Van Dongen, Jasper, Vidal, Jean-Sebastien, Lehtisalo, Jenni, Wiltfang, Jens, Thomassen, Jesper Qvist, Kornhuber, Johannes, Haines, Jonathan L., Vogelgsang, Jonathan, Pineda, Juan A., Fortea, Juan, Popp, Julius, Deckert, Jürgen, Buerger, Katharina, Morgan, Kevin, Fließbach, Klaus, Sleegers, Kristel, Molina-Porcel, Laura, Kilander, Lena, Weinhold, Leonie, Farrer, Lindsay A., Wang, Li-San, Kleineidam, Luca, Farotti, Lucia, Parnetti, Lucilla, Tremolizzo, Lucio, Hausner, Lucrezia, Benussi, Luisa, Froelich, Lutz, Ikram, M. Arfan, Deniz-Naranjo, M. Candida, Tsolaki, Magda, Rosende-Roca, Maitée, Löwenmark, Malin, Hulsman, Marc, Spallazzi, Marco, Pericak-Vance, Margaret A., Esiri, Margaret, Bernal Sánchez-Arjona, María, Dalmasso, Maria Carolina, Martínez-Larrad, María Teresa, Arcaro, Marina, Nöthen, Markus M., Fernández-Fuertes, Marta, Dichgans, Martin, Ingelsson, Martin, Herrmann, Martin J., Scherer, Martin, Vyhnalek, Martin, Kosmidis, Mary H., Yannakoulia, Mary, Schmid, Matthias, Ewers, Michael, Heneka, Michael T., Wagner, Michael, Scamosci, Michela, Kivipelto, Miia, Hiltunen, Mikko, Zulaica, Miren, Alegret, Montserrat, Fornage, Myriam, Roberto, Natalia, van Schoor, Natasja M., Seidu, Nazib M., Banaj, Nerisa, Armstrong, Nicola J., Scarmeas, Nikolaos, Scherbaum, Norbert, Goldhardt, Oliver, Hanon, Oliver, Peters, Oliver, Skrobot, Olivia Anna, Quenez, Olivier, Lerch, Ondrej, Bossù, Paola, Caffarra, Paolo, Dionigi Rossi, Paolo, Sakka, Paraskevi, Mecocci, Patrizia, Hoffmann, Per, Holmans, Peter A., Fischer, Peter, Riederer, Peter, Yang, Qiong, Marshall, Rachel, Kalaria, Rajesh N., Mayeux, Richard, Vandenberghe, Rik, Cecchetti, Roberta, Ghidoni, Roberta, Frikke-Schmidt, Ruth, Sorbi, Sandro, Hägg, Sara, Engelborghs, Sebastiaan, Helisalmi, Seppo, Botne Sando, Sigrid, Kern, Silke, Archetti, Silvana, Boschi, Silvia, Fostinelli, Silvia, Gil, Silvia, Mendoza, Silvia, Mead, Simon, Ciccone, Simona, Djurovic, Srdjan, Heilmann-Heimbach, Stefanie, Riedel-Heller, Steffi, Kuulasmaa, Teemu, del Ser, Teodoro, Lebouvier, Thibaud, Polak, Thomas, Ngandu, Tiia, Grimmer, Timo, Bessi, Valentina, Escott-Price, Valentina, Giedraitis, Vilmantas, Deramecourt, Vincent, Maier, Wolfgang, Jian, Xueqiu, Pijnenburg, Yolande A. L., Kehoe, Patrick Gavin, Garcia-Ribas, Guillermo, Sánchez-Juan, Pascual, Pastor, Pau, Pérez-Tur, Jordi, Piñol-Ripoll, Gerard, Lopez de Munain, Adolfo, García-Alberca, Jose María, Bullido, María J., Álvarez, Victoria, Lleó, Alberto, Real, Luis M., Mir, Pablo, Medina, Miguel, Scheltens, Philip, Holstege, Henne, Marquié, Marta, Sáez, María Eugenia, Carracedo, Ángel, Amouyel, Philippe, Schellenberg, Gerard D., Williams, Julie, Seshadri, Sudha, van Duijn, Cornelia M., Mather, Karen A., Sánchez-Valle, Raquel, Serrano-Ríos, Manuel, Orellana, Adelina, Tárraga, Lluís, Blennow, Kaj, Huisman, Martijn, Andreassen, Ole A., Posthuma, Danielle, Clarimón, Jordi, Boada, Mercè, van der Flier, Wiesje M., Ramirez, Alfredo, Lambert, Jean-Charles, van der Lee, Sven J., and Ruiz, Agustín

Published
2021
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25. Author Correction: A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer’s disease

Author

Wightman, Douglas P., Jansen, Iris E., Savage, Jeanne E., Shadrin, Alexey A., Bahrami, Shahram, Holland, Dominic, Rongve, Arvid, Børte, Sigrid, Winsvold, Bendik S., Drange, Ole Kristian, Martinsen, Amy E., Skogholt, Anne Heidi, Willer, Cristen, Bråthen, Geir, Bosnes, Ingunn, Nielsen, Jonas Bille, Fritsche, Lars G., Thomas, Laurent F., Pedersen, Linda M., Gabrielsen, Maiken E., Johnsen, Marianne Bakke, Meisingset, Tore Wergeland, Zhou, Wei, Proitsi, Petroula, Hodges, Angela, Dobson, Richard, Velayudhan, Latha, Heilbron, Karl, Auton, Adam, Sealock, Julia M., Davis, Lea K., Pedersen, Nancy L., Reynolds, Chandra A., Karlsson, Ida K., Magnusson, Sigurdur, Stefansson, Hreinn, Thordardottir, Steinunn, Jonsson, Palmi V., Snaedal, Jon, Zettergren, Anna, Skoog, Ingmar, Kern, Silke, Waern, Margda, Zetterberg, Henrik, Blennow, Kaj, Stordal, Eystein, Hveem, Kristian, Zwart, John-Anker, Athanasiu, Lavinia, Selnes, Per, Saltvedt, Ingvild, Sando, Sigrid B., Ulstein, Ingun, Djurovic, Srdjan, Fladby, Tormod, Aarsland, Dag, Selbæk, Geir, Ripke, Stephan, Stefansson, Kari, Andreassen, Ole A., and Posthuma, Danielle

Published
2022
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27. Dementia and mortality in older adults: A twin study.

Author

Jang, Jung Yun, Beam, Christopher R., Karlsson, Ida K., Pedersen, Nancy L., and Gatz, Margaret

Abstract

INTRODUCTION: Dementia predicts increased mortality. We used case‐control and co‐twin control models to investigate genetic and shared environmental influences on this association. METHODS: Case‐control design, including 987 twins with dementia and 2938 age‐ and sex‐matched controls in the Swedish Twin Registry. Co‐twin control design, including 90 monozygotic (MZ) and 288 dizygotic (DZ) twin pairs discordant for dementia. To test for genetic and environmental confounding, differences were examined in mortality risk between twins with dementia and their matched or co‐twin controls. RESULTS: Twins with dementia showed greater mortality risk than age‐ and sex‐matched controls (HR = 2.02 [1.86, 2.18]). Mortality risk is significantly elevated but attenuated substantially in discordant twin pairs, for example, comparing MZ twins with dementia to their co‐twin controls (HR = 1.48 [1.08, 2.04]). DISCUSSION: Findings suggest that genetic factors partially confound the association between dementia and mortality and provide an alternative hypothesis to increased mortality due to dementia itself. Highlights: We studied dementia and mortality in twin pairs discordant for dementia.People without dementia outlived people with dementia.Identical twins with dementia and their co‐twin controls had similar survival time.Findings suggest genotype may explain the link between dementia and mortality. [ABSTRACT FROM AUTHOR]

Published
2024
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28. Educational Influences on Late-Life Health: Genetic Propensity and Attained Education.

Author

Ericsson, Malin, Finch, Brian, Karlsson, Ida K, Gatz, Margaret, Reynolds, Chandra A, Pedersen, Nancy L, and Mosing, Miriam A

Subjects
GENETICS, HEALTH status indicators, ACQUISITION of data, DIZYGOTIC twins, AGING, QUESTIONNAIRES, RESEARCH funding, EDUCATIONAL attainment, LONGITUDINAL method, COMORBIDITY, OLD age
Abstract

Objectives The educational gradient in late-life health is well established. Despite this, there are still ambiguities concerning the role of underlying confounding by genetic influences and gene-environment (GE) interplay. Here, we investigate the role of educational factors (attained and genetic propensities) on health and mortality in late life using genetic propensity for educational attainment (as measured by a genome-wide polygenic score, PGSEdu) and attained education. Methods By utilizing genetically informative twin data from the Swedish Twin Registry (n = 14,570), we investigated influences of the educational measures, familial confounding as well as the possible presence of passive GE correlation on both objective and subjective indicators of late-life health, that is, the Frailty Index, Multimorbidity, Self-rated health, cardiovascular disease, and all-cause mortality. Results Using between-within models to adjust for shared familial factors, we found that the relationship between educational level and health and mortality later in life persisted despite controlling for familial confounding. PGSEdu and attained education both uniquely predicted late-life health and mortality, even when mutually adjusted. Between-within models of PGSEdu on the health outcomes in dizygotic twins showed weak evidence for passive GE correlation (prGE) in the education-health relationship. Discussion Both genetic propensity to education and attained education are (partly) independently associated with health in late life. These results lend further support for a causal education-health relationship but also raise the importance of genetic contributions and GE interplay. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer’s disease risk

Author

Jansen, Iris E., Savage, Jeanne E., Watanabe, Kyoko, Bryois, Julien, Williams, Dylan M., Steinberg, Stacy, Sealock, Julia, Karlsson, Ida K., Hägg, Sara, Athanasiu, Lavinia, Voyle, Nicola, Proitsi, Petroula, Witoelar, Aree, Stringer, Sven, Aarsland, Dag, Almdahl, Ina S., Andersen, Fred, Bergh, Sverre, Bettella, Francesco, Bjornsson, Sigurbjorn, Brækhus, Anne, Bråthen, Geir, de Leeuw, Christiaan, Desikan, Rahul S., Djurovic, Srdjan, Dumitrescu, Logan, Fladby, Tormod, Hohman, Timothy J., Jonsson, Palmi V., Kiddle, Steven J., Rongve, Arvid, Saltvedt, Ingvild, Sando, Sigrid B., Selbæk, Geir, Shoai, Maryam, Skene, Nathan G., Snaedal, Jon, Stordal, Eystein, Ulstein, Ingun D., Wang, Yunpeng, White, Linda R., Hardy, John, Hjerling-Leffler, Jens, Sullivan, Patrick F., van der Flier, Wiesje M., Dobson, Richard, Davis, Lea K., Stefansson, Hreinn, Stefansson, Kari, Pedersen, Nancy L., Ripke, Stephan, Andreassen, Ole A., and Posthuma, Danielle

Published
2019
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32. Author Correction: A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer’s disease

Author

Wightman, Douglas P., Jansen, Iris E., Savage, Jeanne E., Shadrin, Alexey A., Bahrami, Shahram, Holland, Dominic, Rongve, Arvid, Børte, Sigrid, Winsvold, Bendik S., Drange, Ole Kristian, Martinsen, Amy E., Skogholt, Anne Heidi, Willer, Cristen, Bråthen, Geir, Bosnes, Ingunn, Nielsen, Jonas Bille, Fritsche, Lars G., Thomas, Laurent F., Pedersen, Linda M., Gabrielsen, Maiken E., Johnsen, Marianne Bakke, Meisingset, Tore Wergeland, Zhou, Wei, Proitsi, Petroula, Hodges, Angela, Dobson, Richard, Velayudhan, Latha, Heilbron, Karl, Auton, Adam, Sealock, Julia M., Davis, Lea K., Pedersen, Nancy L., Reynolds, Chandra A., Karlsson, Ida K., Magnusson, Sigurdur, Stefansson, Hreinn, Thordardottir, Steinunn, Jonsson, Palmi V., Snaedal, Jon, Zettergren, Anna, Skoog, Ingmar, Kern, Silke, Waern, Margda, Zetterberg, Henrik, Blennow, Kaj, Stordal, Eystein, Hveem, Kristian, Zwart, John-Anker, Athanasiu, Lavinia, Selnes, Per, Saltvedt, Ingvild, Sando, Sigrid B., Ulstein, Ingun, Djurovic, Srdjan, Fladby, Tormod, Aarsland, Dag, Selbæk, Geir, Ripke, Stephan, Stefansson, Kari, Andreassen, Ole A., and Posthuma, Danielle

Published
2021
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33. Associations between epigenetic aging and diabetes mellitus in a Swedish longitudinal study

Author

Wikström Shemer, Daniel, Mostafaei, Shayan, Tang, Bowen, Pedersen, Nancy L, Karlsson, Ida K, Fall, Tove, and Hägg, Sara

Abstract

Diabetes mellitus type 2 (T2D) is associated with accelerated biological aging and the increased risk of onset of other age-related diseases. Epigenetic changes in DNA methylation levels have been found to serve as reliable biomarkers for biological aging. This study explores the relationship between various epigenetic biomarkers of aging and diabetes risk using longitudinal data. Data from the Swedish Adoption/Twin Study of Aging (SATSA) was collected from 1984 to 2014 and included 536 individuals with at least one epigenetic measurement. The following epigenetic biomarkers of aging were employed: DNAm PAI-1, DNAmTL, DunedinPACE, PCHorvath1, PCHorvath2, PCHannum, PCPhenoAge, and PCGrimAge. Firstly, longitudinal analysis of biomarker trajectories was done. Secondly, linear correlations between the biomarkers and time to diabetes were studied within individuals developing diabetes. Thirdly, Cox proportional hazards (PH) models were used to assess the associations between these biomarkers and time of diabetes diagnosis, with adjustments for chronological age, sex, education, smoking, blood glucose, and BMI. The longitudinal trajectories of the biomarkers revealed differences between individuals with and without diabetes. Smoothened average curves for DunedinPACE and DNAm PAI-1 were higher for individuals with diabetes around the age 60–70, compared to controls. Likewise, DunedinPACE and DNAm PAI-1 were higher closer to diabetes onset. However, no significant associations were found between the epigenetic biomarkers of aging and risk of diabetes in Cox PH models. Our findings suggest the potential value of developing epigenetic biomarkers specifically tailored to T2D, should we wish to model and explore the potential for predicting the disease.

Published
2024
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36. Advanced biological ageing predicts future risk for neurological diagnoses and clinical examination findings.

Author

McMurran, Christopher E, Wang, Yunzhang, Mak, Jonathan K L, Karlsson, Ida K, Tang, Bowen, Ploner, Alexander, Pedersen, Nancy L, and Hägg, Sara

Subjects
AGE, PUPILLARY reflex, ISCHEMIC stroke, PARKINSON'S disease, DISEASE risk factors, VASCULAR dementia
Abstract

Age is a dominant risk factor for some of the most common neurological diseases. Biological ageing encompasses interindividual variation in the rate of ageing and can be calculated from clinical biomarkers or DNA methylation data amongst other approaches. Here, we tested the hypothesis that a biological age greater than one's chronological age affects the risk of future neurological diagnosis and the development of abnormal signs on clinical examination. We analysed data from the Swedish Adoption/Twin Study of Aging (SATSA): a cohort with 3175 assessments of 802 individuals followed-up over several decades. Six measures of biological ageing were generated: two physiological ages (created from bedside clinical measurements and standard blood tests) and four blood methylation age measures. Their effects on future stroke, dementia or Parkinson's disease diagnosis, or development of abnormal clinical signs, were determined using survival analysis, with and without stratification by twin pairs. Older physiological ages were associated with ischaemic stroke risk; for example one standard deviation advancement in baseline PhenoAgePhys or KDMAgePhys residual increased future ischaemic stroke risk by 29.2% [hazard ratio (HR): 1.29, 95% confidence interval (CI) 1.06–1.58, P = 0.012] and 42.9% (HR 1.43, CI 1.18–1.73, P = 3.1 × 10−4), respectively. In contrast, older methylation ages were more predictive of future dementia risk, which was increased by 29.7% (HR 1.30, CI 1.07–1.57, P = 0.007) per standard deviation advancement in HorvathAgeMeth. Older physiological ages were also positively associated with future development of abnormal patellar or pupillary reflexes, and the loss of normal gait. Measures of biological ageing can predict clinically relevant pathology of the nervous system independent of chronological age. This may help to explain variability in disease risk between individuals of the same age and strengthens the case for trials of geroprotective interventions for people with neurological disorders. [ABSTRACT FROM AUTHOR]

Published
2023
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41. Author Correction: Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer’s disease risk

Author

Jansen, Iris E., Savage, Jeanne E., Watanabe, Kyoko, Bryois, Julien, Williams, Dylan M., Steinberg, Stacy, Sealock, Julia, Karlsson, Ida K., Hägg, Sara, Athanasiu, Lavinia, Voyle, Nicola, Proitsi, Petroula, Witoelar, Aree, Stringer, Sven, Aarsland, Dag, Almdahl, Ina S., Andersen, Fred, Bergh, Sverre, Bettella, Francesco, Bjornsson, Sigurbjorn, Brækhus, Anne, Bråthen, Geir, de Leeuw, Christiaan, Desikan, Rahul S., Djurovic, Srdjan, Dumitrescu, Logan, Fladby, Tormod, Hohman, Timothy J., Jonsson, Palmi V., Kiddle, Steven J., Rongve, Arvid, Saltvedt, Ingvild, Sando, Sigrid B., Selbæk, Geir, Shoai, Maryam, Skene, Nathan G., Snaedal, Jon, Stordal, Eystein, Ulstein, Ingun D., Wang, Yunpeng, White, Linda R., Hardy, John, Hjerling-Leffler, Jens, Sullivan, Patrick F., van der Flier, Wiesje M., Dobson, Richard, Davis, Lea K., Stefansson, Hreinn, Stefansson, Kari, Pedersen, Nancy L., Ripke, Stephan, Andreassen, Ole A., and Posthuma, Danielle

Published
2020
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43. Additional file 1 of Independent and joint effects of body mass index and metabolic health in mid- and late-life on all-cause mortality: a cohort study from the Swedish Twin Registry with a mean follow-up of 13 Years

Author

Ler, Peggy, Li, Xia, Hassing, Linda B., Reynolds, Chandra A., Finkel, Deborah, Karlsson, Ida K., and Dahl Aslan, Anna K.

Abstract

Additional file 1: Additional files. Table S1. Effects of bodymass index and metabolic health status interaction on all-cause mortality whenCVD was included as a component for ascertaining metabolic health. Table S2. Effects of bodymass index and metabolic health status interaction on all-cause mortality, whenself-reports were excluded from the ascertainment of metabolic health status. Table S3. Effects of bodymass index and metabolic health status interaction on all-cause mortality, whenmetabolic health is defined as the absence of any metabolic abnormality. Table S4. Effects of body massindex and metabolic health status interaction on all-cause mortality, when waistcircumference was included in the ascertainment of metabolic health status, andmetabolic health is defined as ≤ two metabolic abnormalities. Table S5. Effects of body massindex and metabolic health status interaction on all-cause mortality when waistcircumference is included in the ascertainment of metabolic health status, andmetabolic health is defined as ≤ three metabolic abnormalities. Table S6. Effects of body massindex and metabolic health status interaction on all-cause mortality, when MHS isdefined by new criteria [1], the absence ofhypertension, high waist-hip ratios and diabetes. Table S7a. Effects of mid-life bodymass index and metabolic health status interaction on all-cause mortality, stratifiedby sex. Table S7b. Effects of late-life bodymass index and metabolic health status interaction on all-cause mortality, stratifiedby sex.

Published
2022
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50. Additional file 1 of Epigenome-wide association study of level and change in cognitive abilities from midlife through late life

Author

Karlsson, Ida K., Ericsson, Malin, Yunzhang Wang, Jylhävä, Juulia, Hägg, Sara, Aslan, Anna K. Dahl, Reynolds, Chandra A., and Pedersen, Nancy L.

Abstract

Additional file 1: Table S1-S4. Table S1: Descriptive statistics of the total study sample and stratified by DNA methylation array. Table S2: Null model for intercept level, linear change, and quadratic change in cognitive abilities. Table S3: Comparison of twin-pair correlation between monozygotic and dizygotic twin-pairs. Table S4: Differences in DNA methylation in relation to dementia status.

Published
2021
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