Author: "Arfan Ikram M." - Searchworks@Jio Institute Digital Library Search Results

Your search keyword '"Arfan Ikram M."' showing total 181 results

Start Over Author "Arfan Ikram M."

181 results on '"Arfan Ikram M."'

1. Depressive Symptoms and Plasma Markers of Alzheimer's Disease and Neurodegeneration: A Coordinated Meta-Analysis of 8 Cohort Studies

Author: Twait, Emma L., Kamarioti, Maria, Verberk, Inge M.W., Teunissen, Charlotte E., Nooyens, Astrid C.J., Monique Verschuren, W.M., Visser, Pieter Jelle, Huisman, Martijn, Kok, Almar A.L., Eline Slagboom, P., Beekman, Marian, Vojinovic, Dina, Lakenberg, Nico, Arfan Ikram, M., Schuurmans, Isabel K., Wolters, Frank J., Moonen, Justine E.F., Gerritsen, Lotte, van der Flier, Wiesje M., and Geerlings, Mirjam I.
Published: 2024
Full Text: View/download PDF

2. Obesity Partially Mediates the Diabetogenic Effect of Lowering LDL Cholesterol.

Author: Wu, Peitao, Moon, Jee-Young, Daghlas, Iyas, Franco, Giulianini, Porneala, Bianca, Ahmadizar, Fariba, Richardson, Tom, Isaksen, Jonas, Hindy, Georgy, Yao, Jie, Sitlani, Colleen, Raffield, Laura, Yanek, Lisa, Feitosa, Mary, Cuadrat, Rafael, Qi, Qibin, Arfan Ikram, M, Ellervik, Christina, Ericson, Ulrika, Goodarzi, Mark, Brody, Jennifer, Lange, Leslie, Mercader, Josep, Vaidya, Dhananjay, An, Ping, Schulze, Matthias, Masana, Lluis, Ghanbari, Mohsen, Olesen, Morten, Cai, Jianwen, Guo, Xiuqing, Floyd, James, Jäger, Susanne, Province, Michael, Kalyani, Rita, Psaty, Bruce, Orho-Melander, Marju, Ridker, Paul, Kanters, Jørgen, Uitterlinden, Andre, Davey Smith, George, Gill, Dipender, Kaplan, Robert, Kavousi, Maryam, Raghavan, Sridharan, Chasman, Daniel, Rotter, Jerome, Meigs, James, Florez, Jose, Dupuis, Josée, Liu, Ching-Ti, and Merino, Jordi
Subjects: Cholesterol, LDL, Diabetes Mellitus, Type 2, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Obesity, Risk Factors
Abstract: OBJECTIVE: LDL cholesterol (LDLc)-lowering drugs modestly increase body weight and type 2 diabetes risk, but the extent to which the diabetogenic effect of lowering LDLc is mediated through increased BMI is unknown. RESEARCH DESIGN AND METHODS: We conducted summary-level univariable and multivariable Mendelian randomization (MR) analyses in 921,908 participants to investigate the effect of lowering LDLc on type 2 diabetes risk and the proportion of this effect mediated through BMI. We used data from 92,532 participants from 14 observational studies to replicate findings in individual-level MR analyses. RESULTS: A 1-SD decrease in genetically predicted LDLc was associated with increased type 2 diabetes odds (odds ratio [OR] 1.12 [95% CI 1.01, 1.24]) and BMI (β = 0.07 SD units [95% CI 0.02, 0.12]) in univariable MR analyses. The multivariable MR analysis showed evidence of an indirect effect of lowering LDLc on type 2 diabetes through BMI (OR 1.04 [95% CI 1.01, 1.08]) with a proportion mediated of 38% of the total effect (P = 0.03). Total and indirect effect estimates were similar across a number of sensitivity analyses. Individual-level MR analyses confirmed the indirect effect of lowering LDLc on type 2 diabetes through BMI with an estimated proportion mediated of 8% (P = 0.04). CONCLUSIONS: These findings suggest that the diabetogenic effect attributed to lowering LDLc is partially mediated through increased BMI. Our results could help advance understanding of adipose tissue and lipids in type 2 diabetes pathophysiology and inform strategies to reduce diabetes risk among individuals taking LDLc-lowering medications.
Published: 2022

3. Association of low-frequency and rare coding variants with information processing speed

Author: Bressler, Jan, Davies, Gail, Smith, Albert V, Saba, Yasaman, Bis, Joshua C, Jian, Xueqiu, Hayward, Caroline, Yanek, Lisa, Smith, Jennifer A, Mirza, Saira S, Wang, Ruiqi, Adams, Hieab HH, Becker, Diane, Boerwinkle, Eric, Campbell, Archie, Cox, Simon R, Eiriksdottir, Gudny, Fawns-Ritchie, Chloe, Gottesman, Rebecca F, Grove, Megan L, Guo, Xiuqing, Hofer, Edith, Kardia, Sharon LR, Knol, Maria J, Koini, Marisa, Lopez, Oscar L, Marioni, Riccardo E, Nyquist, Paul, Pattie, Alison, Polasek, Ozren, Porteous, David J, Rudan, Igor, Satizabal, Claudia L, Schmidt, Helena, Schmidt, Reinhold, Sidney, Stephen, Simino, Jeannette, Smith, Blair H, Turner, Stephen T, van der Lee, Sven J, Ware, Erin B, Whitmer, Rachel A, Yaffe, Kristine, Yang, Qiong, Zhao, Wei, Gudnason, Vilmundur, Launer, Lenore J, Fitzpatrick, Annette L, Psaty, Bruce M, Fornage, Myriam, Arfan Ikram, M, van Duijn, Cornelia M, Seshadri, Sudha, Mosley, Thomas H, and Deary, Ian J
Subjects: Genetics, Brain Disorders, Aging, Human Genome, Adult, Cognition, Genome-Wide Association Study, Geroscience, Humans, Polymorphism, Single Nucleotide, Ubiquitin-Protein Ligases, Clinical Sciences, Public Health and Health Services, Psychology
Abstract: Measures of information processing speed vary between individuals and decline with age. Studies of aging twins suggest heritability may be as high as 67%. The Illumina HumanExome Bead Chip genotyping array was used to examine the association of rare coding variants with performance on the Digit-Symbol Substitution Test (DSST) in community-dwelling adults participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. DSST scores were available for 30,576 individuals of European ancestry from nine cohorts and for 5758 individuals of African ancestry from four cohorts who were older than 45 years and free of dementia and clinical stroke. Linear regression models adjusted for age and gender were used for analysis of single genetic variants, and the T5, T1, and T01 burden tests that aggregate the number of rare alleles by gene were also applied. Secondary analyses included further adjustment for education. Meta-analyses to combine cohort-specific results were carried out separately for each ancestry group. Variants in RNF19A reached the threshold for statistical significance (p = 2.01 × 10-6) using the T01 test in individuals of European descent. RNF19A belongs to the class of E3 ubiquitin ligases that confer substrate specificity when proteins are ubiquitinated and targeted for degradation through the 26S proteasome. Variants in SLC22A7 and OR51A7 were suggestively associated with DSST scores after adjustment for education for African-American participants and in the European cohorts, respectively. Further functional characterization of its substrates will be required to confirm the role of RNF19A in cognitive function.
Published: 2021

4. Multi‐phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations

Author: Temprano‐Sagrera, Gerard, Sitlani, Colleen M., Bone, William P., Martin‐Bornez, Miguel, Voight, Benjamin F., Morrison, Alanna C., Damrauer, Scott M., de Vries, Paul S., Smith, Nicholas L., Sabater‐Lleal, Maria, Dehghan, Abbas, Heath, Adam S, Morrison, Alanna C, Reiner, Alex P, Johnson, Andrew, Richmond, Anne, Peters, Annette, van Hylckama Vlieg, Astrid, McKnight, Barbara, Psaty, Bruce M, Hayward, Caroline, Ward‐Caviness, Cavin, O’Donnell, Christopher, Chasman, Daniel, Strachan, David P, Tregouet, David A, Mook‐Kanamori, Dennis, Gill, Dipender, Thibord, Florian, Asselbergs, Folkert W, Leebeek, Frank W.G., Rosendaal, Frits R, Davies, Gail, Homuth, Georg, Temprano, Gerard, Campbell, Harry, Taylor, Herman A, Bressler, Jan, Huffman, Jennifer E, Rotter, Jerome I, Yao, Jie, Wilson, James F, Bis, Joshua C, Hahn, Julie M, Desch, Karl C, Wiggins, Kerri L, Raffield, Laura M, Bielak, Lawrence F, Yanek, Lisa R, Kleber, Marcus E, Mueller, Martina, Kavousi, Maryam, Mangino, Massimo, Liu, Melissa, Brown, Michael R, Conomos, Matthew P, Jhun, Min‐A, Chen, Ming‐Huei, de Maat, Moniek P.M., Pankratz, Nathan, Smith, Nicholas L, Peyser, Patricia A, Elliot, Paul, de Vries, Paul S, Wei, Peng, Wild, Philipp S, Morange, Pierre E, van der Harst, Pim, Yang, Qiong, Le, Ngoc‐Quynh, Marioni, Riccardo, Li, Ruifang, Damrauer, Scott M, Cox, Simon R, Trompet, Stella, Felix, Stephan B, Völker, Uwe, Tang, Weihong, Koenig, Wolfgang, Jukema, J. Wouter, Guo, Xiuqing, Lindstrom, Sara, Wang, Lu, Smith, Erin N, Gordon, William, de Andrade, Mariza, Brody, Jennifer A, Pattee, Jack W, Haessler, Jeffrey, Brumpton, Ben M, Chasman, Daniel I, Suchon, Pierre, Turman, Constance, Germain, Marine, MacDonald, James, Braekkan, Sigrid K, Armasu, Sebastian M, Jackson, Rabecca D, Nielsen, Jonas B, Giulianini, Franco, Puurunen, Marja K, Ibrahim, Manal, Heckbert, Susan R, Bammler, Theo K, Frazer, Kelly A, McCauley, Bryan M, Taylor, Kent, Pankow, James S, Reiner, Alexander P, Gabrielsen, Maiken E, Deleuze, Jean‐François, O’Donnell, Chris J, Kim, Jihye, Kraft, Peter, Hansen, John‐Bjarne, Heit, John A, Kooperberg, Charles, Hveem, Kristian, Ridker, Paul M, Morange, Pierre‐Emmanuel, Johnson, Andrew D, Kabrhel, Christopher, Trégouët, David‐Alexandre, Malik, Rainer, Chauhan, Ganesh, Traylor, Matthew, Sargurupremraj, Muralidharan, Okada, Yukinori, Mishra, Aniket, Rutten‐Jacobs, Loes, Giese, Anne‐Katrin, van der Laan, Sander W, Gretarsdottir, Solveig, Anderson, Christopher D, Chong, Michael, Adams, Hieab HH, Ago, Tetsuro, Almgren, Peter, Amouyel, Philippe, Ay, Hakan, Bartz, Traci M, Benavente, Oscar R, Bevan, Steve, Boncoraglio, Giorgio B, Brown, Robert D, Butterworth, Adam S, Carrera, Caty, Carty, Cara L, Chen, Wei‐Min, Cole, John W, Correa, Adolfo, Cotlarciuc, Ioana, Cruchaga, Carlos, Danesh, John, de Bakker, Paul IW, DeStefano, Anita L, den Hoed, Marcel, Duan, Qing, Engelter, Stefan T, Falcone, Guido J, Gottesman, Rebecca F, Grewal, Raji P, Gudnason, Vilmundur, Gustafsson, Stefan, Harris, Tamara B, Hassan, Ahamad, Havulinna, Aki S, Holliday, Elizabeth G, Howard, George, Hsu, Fang‐Chi, Hyacinth, Hyacinth I, Arfan Ikram, M, Ingelsson, Erik, Irvin, Marguerite R, Jian, Xueqiu, Jiménez‐Conde, Jordi, Johnson, Julie A, Jukema, J Wouter, Kanai, Masahiro, Keene, Keith L, Kissela, Brett M, Kleindorfer, Dawn O, Kubo, Michiaki, Lange, Leslie A, Langefeld, Carl D, Langenberg, Claudia, Launer, Lenore J, Lee, Jin‐Moo, Lemmens, Robin, Leys, Didier, Lewis, Cathryn M, Lin, Wei‐Yu, Lindgren, Arne G, Lorentzen, Erik, Magnusson, Patrik K, Maguire, Jane, Manichaikul, Ani, McArdle, Patrick F, Meschia, James F, Mitchell, Braxton D, Mosley, Thomas H, Nalls, Michael A, Ninomiya, Toshiharu, O’Donnell, Martin J, Pulit, Sara L, Rannikmäe, Kristiina, Rexrode, Kathryn M, Rice, Kenneth, Rich, Stephen S, Rost, Natalia S, Rothwell, Peter M, Rundek, Tatjana, Sacco, Ralph L, Sakaue, Saori, Sale, Michele M, Salomaa, Veikko, Sapkota, Bishwa R, Schmidt, Reinhold, Schmidt, Carsten O, Schminke, Ulf, Sharma, Pankaj, Slowik, Agnieszka, Sudlow, Cathie LM, Tanislav, Christian, Tatlisumak, Turgut, Taylor, Kent D, Thijs, Vincent NS, Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Tiedt, Steffen, Tzourio, Christophe, van Duijn, Cornelia M, Walters, Matthew, Wareham, Nicholas J, Wassertheil‐Smoller, Sylvia, Wilson, James G, Yusuf, Salim, Amin, Najaf, Aparicio, Hugo S, Arnett, Donna K, Attia, John, Beiser, Alexa S, Berr, Claudine, Buring, Julie E, Bustamante, Mariana, Caso, Valeria, Cheng, Yu‐Ching, Hoan Choi, Seung, Chowhan, Ayesha, Cullell, Natalia, Dartigues, Jean‐François, Delavaran, Hossein, Delgado, Pilar, Dörr, Marcus, Engström, Gunnar, Ford, Ian, Gurpreet, Wander S, Hamsten, Anders, Heitsch, Laura, Hozawa, Atsushi, Ibanez, Laura, Ilinca, Andreea, Ingelsson, Martin, Iwasaki, Motoki, Jackson, Rebecca D, Jood, Katarina, Jousilahti, Pekka, Kaffashian, Sara, Kalra, Lalit, Kamouchi, Masahiro, Kitazono, Takanari, Kjartansson, Olafur, Kloss, Manja, Koudstaal, Peter J, Krupinski, Jerzy, Labovitz, Daniel L, Laurie, Cathy C, Levi, Christopher R, Li, Linxin, Lind, Lars, Lindgren, Cecilia M, Lioutas, Vasileios, Mei Liu, Yong, Lopez, Oscar L, Makoto, Hirata, Martinez‐Majander, Nicolas, Matsuda, Koichi, Minegishi, Naoko, Montaner, Joan, Morris, Andrew P, Muiño, Elena, Müller‐Nurasyid, Martina, Norrving, Bo, Ogishima, Soichi, Parati, Eugenio A, Reddy Peddareddygari, Leema, Pedersen, Nancy L, Pera, Joanna, Perola, Markus, Pezzini, Alessandro, Pileggi, Silvana, Rabionet, Raquel, Riba‐Llena, Iolanda, Ribasés, Marta, Romero, Jose R, Roquer, Jaume, Rudd, Anthony G, Sarin, Antti‐Pekka, Sarju, Ralhan, Sarnowski, Chloe, Sasaki, Makoto, Satizabal, Claudia L, Satoh, Mamoru, Sattar, Naveed, Sawada, Norie, Sibolt, Gerli, Sigurdsson, Ásgeir, Smith, Albert, Sobue, Kenji, Soriano‐Tárraga, Carolina, Stanne, Tara, Colin Stine, O, Stott, David J, Strauch, Konstantin, Takai, Takako, Tanaka, Hideo, Tanno, Kozo, Teumer, Alexander, Tomppo, Liisa, Torres‐Aguila, Nuria P, Touze, Emmanuel, Tsugane, Shoichiro, Uitterlinden, Andre G, Valdimarsson, Einar M, van der Lee, Sven J, Völzke, Henry, Wakai, Kenji, Weir, David, Williams, Stephen R, Wolfe, Charles DA, Wong, Quenna, Xu, Huichun, Yamaji, Taiki, Sanghera, Dharambir K, Melander, Olle, Jern, Christina, Strbian, Daniel, Fernandez‐Cadenas, Israel, Longstreth, W T, Rolfs, Arndt, Hata, Jun, Woo, Daniel, Rosand, Jonathan, Pare, Guillaume, Hopewell, Jemma C, Saleheen, Danish, Stefansson, Kari, Worrall, Bradford B, Kittner, Steven J, Seshadri, Sudha, Fornage, Myriam, Markus, Hugh S, Howson, Joanna MM, Kamatani, Yoichiro, Debette, Stephanie, and Dichgans, Martin
Published: 2022
Full Text: View/download PDF

5. Correction: Association of low-frequency and rare coding variants with information processing speed

Author: Bressler, Jan, Davies, Gail, Smith, Albert V., Saba, Yasaman, Bis, Joshua C., Jian, Xueqiu, Hayward, Caroline, Yanek, Lisa, Smith, Jennifer A., Mirza, Saira S., Wang, Ruiqi, Adams, Hieab H. H., Becker, Diane, Boerwinkle, Eric, Campbell, Archie, Cox, Simon R., Eiriksdottir, Gudny, Fawns-Ritchie, Chloe, Gottesman, Rebecca F., Grove, Megan L., Guo, Xiuqing, Hofer, Edith, Kardia, Sharon L. R., Knol, Maria J., Koini, Marisa, Lopez, Oscar L., Marioni, Riccardo E., Nyquist, Paul, Pattie, Alison, Polasek, Ozren, Porteous, David J., Rudan, Igor, Satizabal, Claudia L., Schmidt, Helena, Schmidt, Reinhold, Sidney, Stephen, Simino, Jeannette, Smith, Blair H., Turner, Stephen T., van der Lee, Sven J., Ware, Erin B., Whitmer, Rachel A., Yaffe, Kristine, Yang, Qiong, Zhao, Wei, Gudnason, Vilmundur, Launer, Lenore J., Fitzpatrick, Annette L., Psaty, Bruce M., Fornage, Myriam, Arfan Ikram, M., van Duijn, Cornelia M., Seshadri, Sudha, Mosley, Thomas H., and Deary, Ian J.
Published: 2022
Full Text: View/download PDF

6. Genetic Risk Score for Intracranial Aneurysms: Prediction of Subarachnoid Hemorrhage and Role in Clinical Heterogeneity

Author: Bakker, Mark K., Kanning, Jos P., Abraham, Gad, Martinsen, Amy E., Winsvold, Bendik S., Zwart, John-Anker, Bourcier, Romain, Sawada, Tomonobu, Koido, Masaru, Kamatani, Yoichiro, Morel, Sandrine, Amouyel, Philippe, Debette, Stéphanie, Bijlenga, Philippe, Berrandou, Takiy, Ganesh, Santhi K., Bouatia-Naji, Nabila, Jones, Gregory, Bown, Matthew, Rinkel, Gabriel J.E., Veldink, Jan H., Ruigrok, Ynte M., Hege Aamodt, Anne, Heidi Skogholt, Anne, Brumpton, Ben M, Willer, Cristen J, Sandset, Else C, Kristoffersen, Espen S, Ellekjær, Hanne, Heuch, Ingrid, Nielsen, Jonas B, Hagen, Knut, Hveem, Kristian, Fritsche, Lars G, Thomas, Laurent F, Pedersen, Linda M, Gabrielsen, Maiken E, Holmen, Oddgeir L, Børte, Sigrid, Zhou, Wei, Abboud, Shérine, Pandolfo, Massimo, Thijs, Vincent, Leys, Didier, Bodenant, Marie, Louillet, Fabien, Touzé, Emmanuel, Mas, Jean-Louis, Samson, Yves, Leder, Sara, Léger, Anne, Deltour, Sandrine, Crozier, Sophie, Méresse, Isabelle, Canaple, Sandrine, Godefroy, Olivier, Giroud, Maurice, Béjot, Yannick, Decavel, Pierre, Medeiros, Elizabeth, Montiel, Paola, Moulin, Thierry, Vuillier, Fabrice, Dallongeville, Jean, Metso, Antti J, Metso, Tiina, Tatlisumak, Turgut, Grond-Ginsbach, Caspar, Lichy, Christoph, Kloss, Manja, Werner, Inge, Arnold, Marie-Luise, Dos Santos, Michael, Grau, Armin, Dichgans, Martin, Thomas-Feles, Constanze, Weber, Ralf, Brandt, Tobias, Pezzini, Alessandro, De Giuli, Valeria, Caria, Filomena, Poli, Loris, Padovani, Alessandro, Bersano, Anna, Lanfranconi, Silvia, Beretta, Simone, Ferrarese, Carlo, Giacolone, Giacomo, Paolucci, Stefano, Lyrer, Philippe, Engelter, Stefan, Fluri, Felix, Hatz, Florian, Gisler, Dominique, Bonati, Leo, Gensicke, Henrik, Amort, Margareth, Markus, Hugh, Majersik, Jennifer, Worrall, Bradford, Southerland, Andrew, Cole, John, Kittner, Steven, Evangelou, Evangelos, Warren, Helen R, Gao, He, Ntritsos, Georgios, Dimou, Niki, Esko, Tonu, Mägi, Reedik, Milani, Lili, Almgren, Peter, Boutin, Thibaud, Ding, Jun, Giulianini, Franco, Holliday, Elizabeth G, Jackson, Anne U, Li-Gao, Ruifang, Lin, Wei-Yu, Luan, Jian’an, Mangino, Massimo, Oldmeadow, Christopher, Peter Prins, Bram, Qian, Yong, Sargurupremraj, Muralidharan, Shah, Nabi, Surendran, Praveen, Thériault, Sébastien, Verweij, Niek, Willems, Sara M, Zhao, Jing-Hua, Connell, John, de Mutsert, Renée, Doney, Alex SF, Farrall, Martin, Menni, Cristina, Morris, Andrew D, Noordam, Raymond, Paré, Guillaume, Poulter, Neil R, Shields, Denis C, Stanton, Alice, Thom, Simon, Abecasis, Gonçalo, Amin, Najaf, Arking, Dan E, Ayers, Kristin L, Barbieri, Caterina M, Batini, Chiara, Bis, Joshua C, Blake, Tineka, Bochud, Murielle, Boehnke, Michael, Boerwinkle, Eric, Boomsma, Dorret I, Bottinger, Erwin P, Braund, Peter S, Brumat, Marco, Campbell, Archie, Campbell, Harry, Chakravarti, Aravinda, Chambers, John C, Chauhan, Ganesh, Ciullo, Marina, Cocca, Massimiliano, Collins, Francis, Cordell, Heather J, Davies, Gail, de Borst, Martin H, de Geus, Eco J, Deary, Ian J, Deelen, Joris, Del Greco M, Fabiola, Yusuf Demirkale, Cumhur, Dörr, Marcus, Ehret, Georg B, Elosua, Roberto, Enroth, Stefan, Mesut Erzurumluoglu, A, Ferreira, Teresa, Frånberg, Mattias, Franco, Oscar H, Gandin, Ilaria, Gasparini, Paolo, Giedraitis, Vilmantas, Gieger, Christian, Girotto, Giorgia, Goel, Anuj, Gow, Alan J, Gudnason, Vilmundur, Guo, Xiuqing, Gyllensten, Ulf, Hamsten, Anders, Harris, Tamara B, Harris, Sarah E, Hartman, Catharina A, Havulinna, Aki S, Hicks, Andrew A, Hofer, Edith, Hofman, Albert, Hottenga, Jouke-Jan, Huffman, Jennifer E, Hwang, Shih-Jen, Ingelsson, Erik, James, Alan, Jansen, Rick, Jarvelin, Marjo-Riitta, Joehanes, Roby, Johansson, Åsa, Johnson, Andrew D, Joshi, Peter K, Jousilahti, Pekka, Wouter Jukema, J, Jula, Antti, Kähönen, Mika, Kathiresan, Sekar, Keavney, Bernard D, Khaw, Kay-Tee, Knekt, Paul, Knight, Joanne, Kolcic, Ivana, Kooner, Jaspal S, Koskinen, Seppo, Kristiansson, Kati, Kutalik, Zoltan, Laan, Maris, Larson, Marty, Launer, Lenore J, Lehne, Benjamin, Lehtimäki, Terho, Liewald, David CM, Lin, Li, Lind, Lars, Lindgren, Cecilia M, Liu, YongMei, Loos, Ruth JF, Lopez, Lorna M, Lu, Yingchang, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Mamasoula, Chrysovalanto, Marrugat, Jaume, Marten, Jonathan, Milaneschi, Yuri, Morgan, Anna, Morris, Andrew P, Morrison, Alanna C, Munson, Peter J, Nalls, Mike A, Nandakumar, Priyanka, Nelson, Christopher P, Niiranen, Teemu, Nolte, Ilja M, Nutile, Teresa, Oldehinkel, Albertine J, Oostra, Ben A, O’Reilly, Paul F, Org, Elin, Padmanabhan, Sandosh, Palmas, Walter, Palotie, Aarno, Pattie, Alison, WJH Penninx, Brenda, Perola, Markus, Peters, Annette, Polasek, Ozren, Pramstaller, Peter P, Tri Nguyen, Quang, Raitakari, Olli T, Rettig, Rainer, Rice, Kenneth, Ridker, Paul M, Ried, Janina S, Riese, Harriëtte, Ripatti, Samuli, Robino, Antonietta, Rose, Lynda M, Rotter, Jerome I, Rudan, Igor, Ruggiero, Daniela, Saba, Yasaman, Sala, Cinzia F, Salomaa, Veikko, Samani, Nilesh J, Sarin, Antti-Pekka, Schmidt, Reinhold, Schmidt, Helena, Shrine, Nick, Siscovick, David, Smith, Albert V, Snieder, Harold, Sõber, Siim, Sorice, Rossella, Starr, John M, Stott, David J, Strachan, David P, Strawbridge, Rona J, Sundström, Johan, Swertz, Morris A, Taylor, Kent D, Teumer, Alexander, Tobin, Martin D, Tomaszewski, Maciej, Toniolo, Daniela, Traglia, Michela, Trompet, Stella, Tuomilehto, Jaakko, Tzourio, Christophe, Uitterlinden, André G, Vaez, Ahmad, van der Most, Peter J, van Duijn, Cornelia M, Verwoert, Germaine C, Vitart, Veronique, Völker, Uwe, Vollenweider, Peter, Vuckovic, Dragana, Watkins, Hugh, Wild, Sarah H, Willemsen, Gonneke, Wilson, James F, Wright, Alan F, Yao, Jie, Zemunik, Tatijana, Zhang, Weihua, Attia, John R, Butterworth, Adam S, Chasman, Daniel I, Conen, David, Cucca, Francesco, Danesh, John, Hayward, Caroline, Howson, Joanna MM, Laakso, Markku, Lakatta, Edward G, Langenberg, Claudia, Melander, Olle, Mook-Kanamori, Dennis O, Palmer, Colin NA, Risch, Lorenz, Scott, Robert A, Scott, Rodney J, Sever, Peter, Spector, Tim D, van der Harst, Pim, Wareham, Nicholas J, Zeggini, Eleftheria, Levy, Daniel, Munroe, Patricia B, Newton-Cheh, Christopher, Brown, Morris J, Metspalu, Andres, Psaty, Bruce M., Wain, Louise V, Elliott, Paul, Caulfield, Mark J, Gormley, Padhraig, Anttila, Verneri, Palta, Priit, Esko, Tonu, Pers, Tune H, Farh, Kai-How, Cuenca-Leon, Ester, Muona, Mikko, Furlotte, Nicholas A, Kurth, Tobias, Ingason, Andres, McMahon, George, Ligthart, Lannie, Terwindt, Gisela M, Kallela, Mikko, Freilinger, Tobias M, Ran, Caroline, Gordon, Scott G, Stam, Anine H, Steinberg, Stacy, Borck, Guntram, Koiranen, Markku, Quaye, Lydia, Adams, Hieab H H, Lehtimäki, Terho, Sarin, Antti-Pekka, Wedenoja, Juho, Hinds, David A, Buring, Julie E, Schürks, Markus, Ridker, Paul M, Gudlaug Hrafnsdottir, Maria, Stefansson, Hreinn, Ring, Susan M, Hottenga, Jouke-Jan, Penninx, Brenda W J H, Färkkilä, Markus, Artto, Ville, Kaunisto, Mari, Vepsäläinen, Salli, Malik, Rainer, Heath, Andrew C, Madden, Pamela A F, Martin, Nicholas G, Montgomery, Grant W, Kurki, Mitja I, Kals, Mart, Mägi, Reedik, Pärn, Kalle, Hämäläinen, Eija, Huang, Hailiang, Byrnes, Andrea E, Franke, Lude, Huang, Jie, Stergiakouli, Evie, Lee, Phil H, Sandor, Cynthia, Webber, Caleb, Cader, Zameel, Muller-Myhsok, Bertram, Schreiber, Stefan, Meitinger, Thomas, Eriksson, Johan G, Salomaa, Veikko, Heikkilä, Kauko, Loehrer, Elizabeth, Uitterlinden, Andre G, Hofman, Albert, van Duijn, Cornelia M, Cherkas, Lynn, Pedersen, Linda M, Stubhaug, Audun, Nielsen, Christopher S, Männikkö, Minna, Mihailov, Evelin, Milani, Lili, Göbel, Hartmut, Esserlind, Ann-Louise, Francke Christensen, Anne, Folkmann Hansen, Thomas, Werge, Thomas, Kaprio, Jaakko, Aromaa, Arpo J, Raitakari, Olli, Arfan Ikram, M, Spector, Tim, Järvelin, Marjo-Riitta, Metspalu, Andres, Kubisch, Christian, Strachan, David P, Ferrari, Michel D, Belin, Andrea C, Dichgans, Martin, Wessman, Maija, van den Maagdenberg, Arn M J M, Boomsma, Dorret I, Davey Smith, George, Stefansson, Kari, Eriksson, Nicholas, Daly, Mark J, Neale, Benjamin M, Olesen, Jes, Chasman, Daniel I, Nyholt, Dale R, Palotie, Aarno, Akiyama, Masato, Alg, Varinder S., Børte, Sigrid, Broderick, Joseph P., Brumpton, Ben M., Dauvillier, Jérôme, Desal, Hubert, Dina, Christian, Friedrich, Christoph M., Gaál-Paavola, Emília I., Gentric, Jean-Christophe, Hirsch, Sven, Hostettler, Isabel C., Houlden, Henry, Hveem, Kristian, Jääskeläinen, Juha E., Johnsen, Marianne Bakke, Li, Liming, Lin, Kuang, Lindgren, Antti, Martin, Olivier, Matsuda, Koichi, Millwood, Iona Y., Naggara, Olivier, Niemelä, Mika, Pera, Joanna, Redon, Richard, Rouleau, Guy A., Sandvei, Marie Søfteland, Schilling, Sabine, Shotar, Eimad, Slowik, Agnieszka, Terao, Chikashi, Verschuren, W. M. Monique, Walters, Robin G., Werring, David J., Willer, Cristen J., Woo, Daniel, Worrall, Bradford B., and Zhou, Sirui
Published: 2023
Full Text: View/download PDF

7. Depressive Symptoms and Plasma Markers of Alzheimer's Disease and Neurodegeneration: A Coordinated Meta-Analysis of 8 Cohort Studies

Author: Cardiovasculaire Epi Team 5, Cardiovasculaire Epi Team 7a, Cardiometabolic Health, Circulatory Health, JC onderzoeksprogramma Cardiovascular Health, Brain, Twait, Emma L, Kamarioti, Maria, Verberk, Inge M W, Teunissen, Charlotte E, Nooyens, Astrid C J, Monique Verschuren, W M, Visser, Pieter Jelle, Huisman, Martijn, Kok, Almar A L, Eline Slagboom, P, Beekman, Marian, Vojinovic, Dina, Lakenberg, Nico, Arfan Ikram, M, Schuurmans, Isabel K, Wolters, Frank J, Moonen, Justine E F, Gerritsen, Lotte, van der Flier, Wiesje M, Geerlings, Mirjam I, NCDC Consortium, Cardiovasculaire Epi Team 5, Cardiovasculaire Epi Team 7a, Cardiometabolic Health, Circulatory Health, JC onderzoeksprogramma Cardiovascular Health, Brain, Twait, Emma L, Kamarioti, Maria, Verberk, Inge M W, Teunissen, Charlotte E, Nooyens, Astrid C J, Monique Verschuren, W M, Visser, Pieter Jelle, Huisman, Martijn, Kok, Almar A L, Eline Slagboom, P, Beekman, Marian, Vojinovic, Dina, Lakenberg, Nico, Arfan Ikram, M, Schuurmans, Isabel K, Wolters, Frank J, Moonen, Justine E F, Gerritsen, Lotte, van der Flier, Wiesje M, Geerlings, Mirjam I, and NCDC Consortium
Published: 2024

8. Rare coding variants in genes encoding GABAA receptors in genetic generalised epilepsies: an exome-based case-control study

Author: May, Patrick, Girard, Simon, Harrer, Merle, Bobbili, Dheeraj R, Schubert, Julian, Wolking, Stefan, Becker, Felicitas, Lachance-Touchette, Pamela, Meloche, Caroline, Gravel, Micheline, Niturad, Cristina E, Knaus, Julia, De Kovel, Carolien, Toliat, Mohamad, Polvi, Anne, Iacomino, Michele, Guerrero-López, Rosa, Baulac, Stéphanie, Marini, Carla, Thiele, Holger, Altmüller, Janine, Jabbari, Kamel, Ruppert, Ann-Kathrin, Jurkowski, Wiktor, Lal, Dennis, Rusconi, Raffaella, Cestèle, Sandrine, Terragni, Benedetta, Coombs, Ian D, Reid, Christopher A, Striano, Pasquale, Caglayan, Hande, Siren, Auli, Everett, Kate, Møller, Rikke S, Hjalgrim, Helle, Muhle, Hiltrud, Helbig, Ingo, Kunz, Wolfram S, Weber, Yvonne G, Weckhuysen, Sarah, De Jonghe, Peter, Sisodiya, Sanjay M, Nabbout, Rima, Franceschetti, Silvana, Coppola, Antonietta, Vari, Maria S, Kasteleijn-Nolst Trenité, Dorothée, Baykan, Betul, Ozbek, Ugur, Bebek, Nerses, Klein, Karl M, Rosenow, Felix, Nguyen, Dang K, Dubeau, François, Carmant, Lionel, Lortie, Anne, Desbiens, Richard, Clément, Jean-François, Cieuta-Walti, Cécile, Sills, Graeme J, Auce, Pauls, Francis, Ben, Johnson, Michael R, Marson, Anthony G, Berghuis, Bianca, Sander, Josemir W, Avbersek, Andreja, McCormack, Mark, Cavalleri, Gianpiero L, Delanty, Norman, Depondt, Chantal, Krenn, Martin, Zimprich, Fritz, Peter, Sarah, Nikanorova, Marina, Kraaij, Robert, van Rooij, Jeroen, Balling, Rudi, Arfan Ikram, M, Uitterlinden, André G, Avanzini, Giuliano, Schorge, Stephanie, Petrou, Steven, Mantegazza, Massimo, Sander, Thomas, LeGuern, Eric, Serratosa, Jose M, Koeleman, Bobby P C, Palotie, Aarno, Lehesjoki, Anna-Elina, Nothnagel, Michael, Nürnberg, Peter, Maljevic, Snezana, Zara, Federico, Cossette, Patrick, Krause, Roland, Lerche, Holger, Ferlazzo, Edoardo, di Bonaventura, Carlo, La Neve, Angela, Tinuper, Paolo, Bisulli, Francesca, Vignoli, Aglaia, Capovilla, Giuseppe, Crichiutti, Giovanni, Gambardella, Antonio, Belcastro, Vincenzo, Bianchi, Amedeo, Yalçın, Destina, Dizdarer, Gulsen, Arslan, Kezban, Yapıcı, Zuhal, Kuşcu, Demet, Leu, Costin, Heggeli, Kristin, Willis, Joseph, Langley, Sarah R, Jorgensen, Andrea, Srivastava, Prashant, Rau, Sarah, Hengsbach, Christian, Sonsma, Anja C.M., Jonghe, Peter De, and Ikram, M Arfan
Published: 2018
Full Text: View/download PDF

9. Social Health Is Associated With Tract-Specific Brain White Matter Microstructure in Community-Dwelling Older Adults

Author: Costanzo, A., Velpen, Isabelle F. van der, Arfan Ikram, M., Vernooij-Dassen, M.J.F.J., Niessen, W.J., Vernooij, Meike W., Kas, Martien J., Costanzo, A., Velpen, Isabelle F. van der, Arfan Ikram, M., Vernooij-Dassen, M.J.F.J., Niessen, W.J., Vernooij, Meike W., and Kas, Martien J.
Abstract: Item does not contain fulltext
Published: 2023

10. Genome wide association study identifies variants in NBEA associated with migraine in bipolar disorder

Author: Kelsoe, John R., Greenwood, Tiffany A., Nievergelt, Caroline M., McKinney, Rebecca, Shilling, Paul D., Smith, Erin N., Schork, Nicholas J., Bloss, Cinnamon S., Nurnberger, John I., Jr., Edenberg, Howard J., Foroud, Tatiana, Koller, Daniel L., Gershon, Elliot S., Badner, Judith A., Liu, Chunyu, Scheftner, William A., Lawson, William B., Nwulia, Evaristus A., Hipolito, Maria, Potash, James, Coryell, William, Rice, John, Byerley, William, McMahon, Francis J., Berrettini, Wade H., Zandi, Peter P., Mahon, Pamela B., McInnis, Melvin G., Zöllner, Sebastian, Zhang, Peng, Craig, David W., Szelinger, Szabolics, Barrett, Thomas B., Schulze, Thomas G., Wedenoja, Juho, Kaunisto, Mari A., Heikkilä, Kauko, Kaprio, Jaakko, Wessman, Maija, Kallela, Mikko, Färkkilä, Markus, Artto, Ville, Aromaa, Arpo, Eriksson, Johan G., Winsvold, Bendik S., Zwart, John-Anker, Gormley, Padhraig, Palotie, Aarno, Kurth, Tobias, Rose, Lynda M., Buring, Julie E., Ridker, Paul M., Chasman, Daniel I., Bettella, Francesco, Steinberg, Stacy, Stefansson, Hreinn, Stefansson, Kari, McMahon, George, Davey-Smith, George, Malik, Rainer, Freilinger, Tobias, Erich Wichmann, Heinz, Dichgans, Martin, Muller-Myhsok, Bertram, Meitinger, Thomas, de Vries, Boukje, Terwindt, Gisela, Stam, Anine H., Frants, Rune R., Pelzer, Nadine, Weller, Claudia M., Zielman, Ronald, Ferrari, Michel D., van den Maagdenberg, Arn M.J.M., Medland, Sarah E., Montgomery, Grant W., Martin, Nicholas G., Nyholt, Dale R., Todt, Unda, Borck, Guntram, Kubisch, Christian, Quaye, Lydia, Williams, Frances M.K., Cherkas, Lynn, Koiranen, Markku, Hartikainen, Anna-Liisa, Pouta, Anneli, Jarvelin, Marjo-Riitta, Arfan Ikram, M., van den Ende, Joyce, Uitterlinden, Andre G., Hofman, Albert, Amin, Najaf, van Duijn, Cornelia, Lehtimäki, Terho, Ligthart, Lannie, Hottenga, Jouke-Jan, Vink, Jacqueline M., Penninx, Brenda W., Boomsma, Dorret I., Schürks, Markus, Jakobsson, Finnbogi, Schoenen, Jean, Heath, Andrew C., Madden, Pamela A.F., Göbel, Hartmut, Heinze, Axel, Heinze-Kuhn, Katja, Schreiber, Stefan, Anttila, Verneri, Daly, Mark J., Alexander, Michael, Raitakari, Olli, Strachan, David P., Jacobsen, Kaya K., Zayats, Tetyana, Akiskal, Hagop S., Haavik, Jan, Bernt Fasmer, Ole, Johansson, Stefan, and Oedegaard, Ketil J.
Published: 2015
Full Text: View/download PDF

11. Author reply: Improving the validity of studies on the relationship between social health and immunity of older adults

Author: van der Velpen, Isabelle F., Yaqub, Amber, Vernooij, Meike W., Perry, Marieke, Vernooij-Dassen, Myrra J.F., Ghanbari, Mohsen, Arfan Ikram, M., and Melis, René J.F.
Published: 2024
Full Text: View/download PDF

12. Changes in the Diagnosis of Stroke and Cardiovascular Conditions in Primary Care During the First 2 COVID-19 Waves in the Netherlands

Author: Velek, Premysl, Splinter, Marije J., Kamran Ikram, M., Arfan Ikram, M., Leening, Maarten J. G., Lei, Johan van der, Olde Hartman, T.C., Licher, Silvan, Schepper, Evelien I.T. de, Velek, Premysl, Splinter, Marije J., Kamran Ikram, M., Arfan Ikram, M., Leening, Maarten J. G., Lei, Johan van der, Olde Hartman, T.C., Licher, Silvan, and Schepper, Evelien I.T. de
Abstract: Item does not contain fulltext
Published: 2022

13. Loneliness, Not Social Support, Is Associated with Cognitive Decline and Dementia Across Two Longitudinal Population-Based Cohorts

Author: Freak-Poli, Rosanne, Wagemaker, Nina, Wang, Rui, Lysen, Thom S., Arfan Ikram, M., Vernooij, Meike W., Vernooij-Dassen, M.J.F.J., Melis, R.J.F., Xu, Weili, Tiemeier, Henning, Freak-Poli, Rosanne, Wagemaker, Nina, Wang, Rui, Lysen, Thom S., Arfan Ikram, M., Vernooij, Meike W., Vernooij-Dassen, M.J.F.J., Melis, R.J.F., Xu, Weili, and Tiemeier, Henning
Abstract: Item does not contain fulltext
Published: 2022

14. Recognition of social health: A conceptual framework in the context of dementia research

Author: Vernooij-Dassen, M.J.F.J., Verspoor, E., Samtani, S., Sachdev, P.S., Arfan Ikram, M., Vernooij, Meike W., Melis, R.J.F., Perry, M., Wolf-Ostermann, K., Vernooij-Dassen, M.J.F.J., Verspoor, E., Samtani, S., Sachdev, P.S., Arfan Ikram, M., Vernooij, Meike W., Melis, R.J.F., Perry, M., and Wolf-Ostermann, K.
Abstract: Contains fulltext : 288208.pdf (Publisher’s version ) (Open Access)
Published: 2022

15. Visit-to-visit blood pressure variability and the risk of stroke in the Netherlands:A population-based cohort study

Author: Heshmatollah, Alis, Ma, Yuan, Fani, Lana, Koudstaal, Peter J., Arfan Ikram, M., Kamran Ikram, M., Heshmatollah, Alis, Ma, Yuan, Fani, Lana, Koudstaal, Peter J., Arfan Ikram, M., and Kamran Ikram, M.
Abstract: Background Apart from blood pressure level itself, variation in blood pressure has been implicated in the development of stroke in subgroups at high cardiovascular risk. We determined the associa tion between visit-to-visit blood pressure variability and stroke risk in the general population taking into account the size and direction of variation and several time intervals prior to stroke diagnosis. Methods and findings From 1990 to 2016, we included 9,958 stroke-free participants of the population-based Rot terdam Study in the Netherlands. This is a prospective cohort study including participants aged 45 years and older. Systolic blood pressure (SBP) variability was calculated as absolute SBP difference divided by mean SBP over 2 sequential visits (median 4.6 years apart). Directional SBP variability was defined as SBP difference over 2 visits divided by mean SBP. Using time-varying Cox proportional hazards models adjusted for age, sex, mean SBP, and cardiovascular risk factors, hazard ratios (HRs) for stroke up to January 2016 were estimated per SD increase and in tertiles of variability. We also conducted analyses with 3-, 6-, and 9-year intervals between variability measurement and stroke assessment. These analyses were repeated for diastolic blood pressure (DBP). The mean age of the study population was 67.4 ± 8.2 years and 5,776 (58.0%) were women. During a median fo low-up of 10.1 years, 971 (9.8%) participants had a stroke, including 641 ischemic, 89 hem orrhagic, and 241 unspecified strokes. SBP variability was associated with an increased ris of hemorrhagic stroke (HR per SD 1.27, 95% CI 1.05–1.54, p = 0.02) and unspecified strok (HR per SD 1.21, 95% CI 1.09–1.34, p < 0.001). The associations were stronger for all stroke subtypes with longer time intervals; the HR for any stroke was 1.29 (95% CI 1.21–1.36, p < 0.001) at 3 years, 1.47 (95% CI 1.35–1.59, p < 0.001) at 6 years, and 1.38 (95%C 1.24–1.51, p < 0.001) at 9 years. For DBP variabilit
Published: 2022

16. Sex-specific patterns and lifetime risk of multimorbidity in the general population : a 23-year prospective cohort study

Author: Velek, Premysl, Luik, Annemarie I., Brusselle, Guy G.O., Stricker, Bruno Ch., Bindels, Patrick J.E., Kavousi, Maryam, Kieboom, Brenda C.T., Voortman, Trudy, Ruiter, Rikje, Arfan Ikram, M., Kamran Ikram, M., de Schepper, Evelien I.T., Licher, Silvan, Velek, Premysl, Luik, Annemarie I., Brusselle, Guy G.O., Stricker, Bruno Ch., Bindels, Patrick J.E., Kavousi, Maryam, Kieboom, Brenda C.T., Voortman, Trudy, Ruiter, Rikje, Arfan Ikram, M., Kamran Ikram, M., de Schepper, Evelien I.T., and Licher, Silvan
Abstract: BACKGROUND: Multimorbidity poses a major challenge for care coordination. However, data on what non-communicable diseases lead to multimorbidity, and whether the lifetime risk differs between men and women are lacking. We determined sex-specific differences in multimorbidity patterns and estimated sex-specific lifetime risk of multimorbidity in the general population. METHODS: We followed 6,094 participants from the Rotterdam Study aged 45 years and older for the occurrence of ten diseases (cancer, coronary heart disease, stroke, chronic obstructive pulmonary disease, depression, diabetes, dementia, asthma, heart failure, parkinsonism). We visualised participants' trajectories from a single disease to multimorbidity and the most frequent combinations of diseases. We calculated sex-specific lifetime risk of multimorbidity, considering multimorbidity involving only somatic diseases (1) affecting the same organ system, (2) affecting different organ systems, and (3) multimorbidity involving depression. RESULTS: Over the follow-up period (1993-2016, median years of follow-up 9.2), we observed 6334 disease events. Of the study population, 10.3% had three or more diseases, and 27.9% had two or more diseases. The most frequent pair of co-occurring diseases among men was COPD and cancer (12.5% of participants with multimorbidity), the most frequent pair of diseases among women was depression and dementia (14.9%). The lifetime risk of multimorbidity was similar among men (66.0%, 95% CI: 63.2-68.8%) and women (65.1%, 95% CI: 62.5-67.7%), yet the risk of multimorbidity with depression was higher for women (30.9%, 95% CI: 28.4-33.5%, vs. 17.5%, 95% CI: 15.2-20.1%). The risk of multimorbidity with two diseases affecting the same organ is relatively low for both sexes (4.2% (95% CI: 3.2-5.5%) for men and 4.5% (95% CI: 3.5-5.7%) for women). CONCLUSIONS: Two thirds of people over 45 will develop multimorbidity in their remaining lifetime, with women at nearly double the risk of mult
Published: 2022

17. Liver stiffness not fatty liver disease is associated with atrial fibrillation:The Rotterdam study

Author: van Kleef, Laurens A., Lu, Zuolin, Arfan Ikram, M., de Groot, Natasja M.S., Kavousi, Maryam, de Knegt, Robert J., van Kleef, Laurens A., Lu, Zuolin, Arfan Ikram, M., de Groot, Natasja M.S., Kavousi, Maryam, and de Knegt, Robert J.
Abstract: Background & Aims: Fatty liver disease has become the most prevalent chronic liver disease globally and is linked to cardiovascular disease, including arrhythmias. However, there have been inconsistent reports on the association between fatty liver disease and atrial fibrillation, while the role of liver stiffness in this association remains unclear. Methods: Within the Rotterdam Study, a large prospective ongoing cohort, participants attending the abdominal ultrasound program between 2009-2014 were included. Exclusion criteria were no atrial fibrillation data or >20% missing data across analysis variables. Steatosis was assessed by ultrasound, liver stiffness by transient elastography and atrial fibrillation by 12-lead electrocardiograms. Incident atrial fibrillation was based on medical records and complete until 2014. Logistic and Cox-regression were used to quantify associations between fatty liver disease and atrial fibrillation. Results: We included 5,825 participants (aged 69.5±9.1, 42.9% male), 35.7% had steatosis, liver stiffness measurement was available in 73.3%, and 7.0% had prevalent atrial fibrillation. Steatosis was not associated with prevalent atrial fibrillation in fully adjusted models (odds ratio [OR] 0.80; 95% CI 0.62-1.03), findings were consistent for non-alcoholic or metabolic dysfunction-associated fatty liver disease. Liver stiffness was significantly associated with prevalent atrial fibrillation (OR 1.09 per kPa, 95% CI 1.03-1.16); however, this was only persistent among those without steatosis (OR 1.18 per kPa, 95% CI 1.08-1.29). Lastly, no associations were found between steatosis (hazard ratio 0.88; 95% CI 0.59-1.33; follow-up 2.1 [1.1–3.2] years) and incident atrial fibrillation. Conclusions: Fatty liver disease was not associated with prevalent or incident atrial fibrillation, while liver stiffness was significantly associated with atrial fibrillation, especially among those without steatosis. This association might be drive
Published: 2022

18. Obesity Partially Mediates the Diabetogenic Effect of Lowering LDL Cholesterol

Author: Wu, Peitao, primary, Moon, Jee-Young, additional, Daghlas, Iyas, additional, Franco, Giulianini, additional, Porneala, Bianca C., additional, Ahmadizar, Fariba, additional, Richardson, Tom G., additional, Isaksen, Jonas L., additional, Hindy, Georgy, additional, Yao, Jie, additional, Sitlani, Colleen M., additional, Raffield, Laura M., additional, Yanek, Lisa R., additional, Feitosa, Mary F., additional, Cuadrat, Rafael R.C., additional, Qi, Qibin, additional, Arfan Ikram, M., additional, Ellervik, Christina, additional, Ericson, Ulrika, additional, Goodarzi, Mark O., additional, Brody, Jennifer A., additional, Lange, Leslie, additional, Mercader, Josep M., additional, Vaidya, Dhananjay, additional, An, Ping, additional, Schulze, Matthias B., additional, Masana, Lluis, additional, Ghanbari, Mohsen, additional, Olesen, Morten S., additional, Cai, Jianwen, additional, Guo, Xiuqing, additional, Floyd, James S., additional, Jäger, Susanne, additional, Province, Michael A., additional, Kalyani, Rita R., additional, Psaty, Bruce M., additional, Orho-Melander, Marju, additional, Ridker, Paul M., additional, Kanters, Jørgen K., additional, Uitterlinden, Andre, additional, Davey Smith, George, additional, Gill, Dipender, additional, Kaplan, Robert C., additional, Kavousi, Maryam, additional, Raghavan, Sridharan, additional, Chasman, Daniel I., additional, Rotter, Jerome I., additional, Meigs, James B., additional, Florez, Jose C., additional, Dupuis, Josée, additional, Liu, Ching-Ti, additional, and Merino, Jordi, additional
Published: 2021
Full Text: View/download PDF

19. Amyloid- transmission or unexamined bias&quest;

Author: H. Adams, Hieab H., A. Swanson, Sonja, Hofman, Albert, and Arfan Ikram, M.
Subjects: Glycoproteins -- Health aspects -- Case studies, Somatotropin -- Usage -- Health aspects -- Case studies, Hormone therapy -- Case studies -- Patient outcomes, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract: Author(s): Hieab H. H. Adams [1, 2]; Sonja A. Swanson [1, 3]; Albert Hofman [1, 3]; M. Arfan Ikram (corresponding author) [1, 2, 4] ARISING FROM Z. Jaunmuktane et al [...]
Published: 2016
Full Text: View/download PDF

20. The Rotterdam Study: 2014 objectives and design update

Author: Hofman, Albert, Murad, Sarwa Darwish, van Duijn, Cornelia M., Franco, Oscar H., Goedegebure, André, Arfan Ikram, M., Klaver, Caroline C. W., Nijsten, Tamar E. C., Peeters, Robin P., Stricker, Bruno H. Ch., Tiemeier, Henning W., Uitterlinden, André G., and Vernooij, Meike W.
Published: 2013
Full Text: View/download PDF

21. Plasma Brain-Derived Neurotropic Factor levels are associated with aging and smoking but not with future dementia in the Rotterdam Study

Author: Galle, Sara A., Milders, MM, Deijen, JB, Scherder, E.J.A., Drent, ML, Arfan Ikram, M., van Duijn, C.M., Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, and Internal medicine
Published: 2021

22. Progression along data-driven disease timelines is predictive of Alzheimer's disease in a population-based cohort

Author: Venkatraghavan, Vikram (author), Vinke, Elisabeth J. (author), Bron, Esther E. (author), Niessen, W.J. (author), Arfan Ikram, M. (author), Klein, S. (author), Vernooij, Meike W. (author), Venkatraghavan, Vikram (author), Vinke, Elisabeth J. (author), Bron, Esther E. (author), Niessen, W.J. (author), Arfan Ikram, M. (author), Klein, S. (author), and Vernooij, Meike W. (author)
Abstract: Data-driven disease progression models have provided important insight into the timeline of brain changes in AD phenotypes. However, their utility in predicting the progression of pre-symptomatic AD in a population-based setting has not yet been investigated. In this study, we investigated if the disease timelines constructed in a case-controlled setting, with subjects stratified according to APOE status, are generalizable to a population-based cohort, and if progression along these disease timelines is predictive of AD. Seven volumetric biomarkers derived from structural MRI were considered. We estimated APOE-specific disease timelines of changes in these biomarkers using a recently proposed method called co-initialized discriminative event-based modeling (co-init DEBM). This method can also estimate a disease stage for new subjects by calculating their position along the disease timelines. The model was trained and cross-validated on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, and tested on the population-based Rotterdam Study (RS) cohort. We compared the diagnostic and prognostic value of the disease stage in the two cohorts. Furthermore, we investigated if the rate of change of disease stage in RS participants with longitudinal MRI data was predictive of AD. In ADNI, the estimated disease timeslines for ϵ4 non-carriers and carriers were found to be significantly different from one another (p<0.001). The estimate disease stage along the respective timelines distinguished AD subjects from controls with an AUC of 0.83 in both APOE ϵ4 non-carriers and carriers. In the RS cohort, we obtained an AUC of 0.83 and 0.85 in ϵ4 non-carriers and carriers, respectively. Progression along the disease timelines as estimated by the rate of change of disease stage showed a significant difference (p<0.005) for subjects with pre-symptomatic AD as compared to the general aging population in RS. It distinguished pre-symptomatic AD subjects with an AUC of, ImPhys/Computational Imaging, ImPhys/Medical Imaging, Biomechanical Engineering
Published: 2021
Full Text: View/download PDF

23. GenNet framework: interpretable deep learning for predicting phenotypes from genetic data

Author: van Hilten, Arno (author), Kushner, Steven A. (author), Kayser, Manfred (author), Arfan Ikram, M. (author), Adams, Hieab H.H. (author), Klaver, Caroline C.W. (author), Niessen, W.J. (author), Roshchupkin, Gennady V. (author), van Hilten, Arno (author), Kushner, Steven A. (author), Kayser, Manfred (author), Arfan Ikram, M. (author), Adams, Hieab H.H. (author), Klaver, Caroline C.W. (author), Niessen, W.J. (author), and Roshchupkin, Gennady V. (author)
Abstract: Applying deep learning in population genomics is challenging because of computational issues and lack of interpretable models. Here, we propose GenNet, a novel open-source deep learning framework for predicting phenotypes from genetic variants. In this framework, interpretable and memory-efficient neural network architectures are constructed by embedding biologically knowledge from public databases, resulting in neural networks that contain only biologically plausible connections. We applied the framework to seventeen phenotypes and found well-replicated genes such as HERC2 and OCA2 for hair and eye color, and novel genes such as ZNF773 and PCNT for schizophrenia. Additionally, the framework identified ubiquitin mediated proteolysis, endocrine system and viral infectious diseases as most predictive biological pathways for schizophrenia. GenNet is a freely available, end-to-end deep learning framework that allows researchers to develop and use interpretable neural networks to obtain novel insights into the genetic architecture of complex traits and diseases., ImPhys/Medical Imaging, ImPhys/Computational Imaging, Applied Sciences
Published: 2021
Full Text: View/download PDF

24. Cortical superficial siderosis in the general population: The Framingham Heart and Rotterdam studies.

Author: Shoamanesh, Ashkan, Shoamanesh, Ashkan, Akoudad, Saloua, Himali, Jayandra J, Beiser, Alexa S, DeCarli, Charles, Seshadri, Sudha, Arfan Ikram, M, Romero, Jose R, Vernooij, Meike W, Shoamanesh, Ashkan, Shoamanesh, Ashkan, Akoudad, Saloua, Himali, Jayandra J, Beiser, Alexa S, DeCarli, Charles, Seshadri, Sudha, Arfan Ikram, M, Romero, Jose R, and Vernooij, Meike W
Abstract: ObjectiveWe aimed to characterize cortical superficial siderosis, its determinants and sequel, in community-dwelling older adults.MethodsThe sample consisted of Framingham (n = 1724; 2000-2009) and Rotterdam (n = 4325; 2005-2013) study participants who underwent brain MRI. In pooled individual-level analysis, we compared baseline characteristics in patients with cortical superficial siderosis to two reference groups: (i) persons without hemorrhagic MRI markers of cerebral amyloid angiopathy (no cortical superficial siderosis and no microbleeds) and (ii) those with presumed cerebral amyloid angiopathy based on the presence of strictly lobar microbleeds but without cortical superficial siderosis.ResultsAmong a total of 6049 participants, 4846 did not have any microbleeds or cortical superficial siderosis (80%), 401 had deep/mixed microbleeds (6.6%), 776 had strictly lobar microbleeds without cortical superficial siderosis (12.8%) and 26 had cortical superficial siderosis with/without microbleeds (0.43%). In comparison to participants without microbleeds or cortical superficial siderosis and to those with strictly lobar microbleeds but without cortical superficial siderosis, participants with cortical superficial siderosis were older (OR 1.09 per year, 95% CI 1.05, 1.14; p < 0.001 and 1.04, 95% CI 1.00, 1.09; p = 0.058, respectively), had overrepresentation of the APOE ɛ4 allele (5.19, 2.04, 13.25; p = 0.001 and 3.47, 1.35, 8.92; p = 0.01), and greater prevalence of intracerebral hemorrhage (72.57, 9.12, 577.49; p < 0.001 and 81.49, 3.40, >999.99; p = 0.006). During a mean follow-up of 5.6 years, 42.4% participants with cortical superficial siderosis had a stroke (five intracerebral hemorrhage, two ischemic strokes and four undetermined strokes), 19.2% had transient neurological deficits and 3.8% developed incident dementia.ConclusionOur study adds supporting evidence to the association between cortical superficial siderosis and cerebral amyloid angiopathy wit
Published: 2021

25. Circulatory micrornas in plasma and atrial fibrillation in the general population:The rotterdam study

Author: Geurts, Sven, Mens, Michelle M.J., Bos, Maxime M., Arfan Ikram, M., Ghanbari, Mohsen, Kavousi, Maryam, Geurts, Sven, Mens, Michelle M.J., Bos, Maxime M., Arfan Ikram, M., Ghanbari, Mohsen, and Kavousi, Maryam
Abstract: Background: MicroRNAs (miRNAs), small non-coding RNAs regulating gene expression, have been shown to play an important role in cardiovascular disease. However, limited population-based data regarding the relationship between circulatory miRNAs in plasma and atrial fibrillation (AF) exist. Moreover, it remains unclear if the relationship differs by sex. We therefore aimed to determine the (sex-specific) association between plasma circulatory miRNAs and AF at the population level. Methods: Plasma levels of miRNAs were measured using a targeted next-generation sequencing method in 1999 participants from the population-based Rotterdam Study. Logistic regression and Cox proportional hazards models were used to assess the associations of 591 well-expressed miRNAs with the prevalence and incidence of AF. Models were adjusted for cardiovascular risk factors. We further examined the link between predicted target genes of the identified miRNAs. Results: The mean age was 71.7 years (57.1% women), 98 participants (58 men and 40 women) had prevalent AF at baseline. Moreover, 196 participants (96 men and 100 women) developed AF during a median follow-up of 9.0 years. After adjusting for multiple testing, miR-4798-3p was significantly associated with the odds of prevalent AF among men (odds ratio, 95% confidence interval, 0.39, 0.24–0.66, p-value = 0.000248). No miRNAs were significantly associated with incident AF. MiR-4798-3p could potentially regulate the expression of a number of AF-related genes, including genes involved in calcium and potassium handling in myocytes, protection of cells against oxidative stress, and cardiac fibrosis. Conclusions: Plasma levels of miR-4798-3p were significantly associated with the odds of prevalent AF among men. Several target genes in relation to AF pathophysiology could potentially be regulated by miR-4798-3p that warrant further investigations in future experimental studies.
Published: 2021

26. GenNet framework:interpretable deep learning for predicting phenotypes from genetic data

Author: van Hilten, Arno, Kushner, Steven A., Kayser, Manfred, Arfan Ikram, M., Adams, Hieab H.H., Klaver, Caroline C.W., Niessen, Wiro J., Roshchupkin, Gennady V., van Hilten, Arno, Kushner, Steven A., Kayser, Manfred, Arfan Ikram, M., Adams, Hieab H.H., Klaver, Caroline C.W., Niessen, Wiro J., and Roshchupkin, Gennady V.
Abstract: Applying deep learning in population genomics is challenging because of computational issues and lack of interpretable models. Here, we propose GenNet, a novel open-source deep learning framework for predicting phenotypes from genetic variants. In this framework, interpretable and memory-efficient neural network architectures are constructed by embedding biologically knowledge from public databases, resulting in neural networks that contain only biologically plausible connections. We applied the framework to seventeen phenotypes and found well-replicated genes such as HERC2 and OCA2 for hair and eye color, and novel genes such as ZNF773 and PCNT for schizophrenia. Additionally, the framework identified ubiquitin mediated proteolysis, endocrine system and viral infectious diseases as most predictive biological pathways for schizophrenia. GenNet is a freely available, end-to-end deep learning framework that allows researchers to develop and use interpretable neural networks to obtain novel insights into the genetic architecture of complex traits and diseases.
Published: 2021

27. Genetic susceptibility, obesity and lifetime risk of type 2 diabetes:The ARIC study and Rotterdam Study

Author: Ligthart, Symen, Hasbani, Natalie R., Ahmadizar, Fariba, van Herpt, Thijs T.W., Leening, Maarten J.G., Uitterlinden, André G., Sijbrands, Eric J.G., Morrison, Alanna C., Boerwinkle, Eric, Pankow, James S., Selvin, Elizabeth, Arfan Ikram, M., Kavousi, Maryam, de Vries, Paul S., Dehghan, Abbas, Ligthart, Symen, Hasbani, Natalie R., Ahmadizar, Fariba, van Herpt, Thijs T.W., Leening, Maarten J.G., Uitterlinden, André G., Sijbrands, Eric J.G., Morrison, Alanna C., Boerwinkle, Eric, Pankow, James S., Selvin, Elizabeth, Arfan Ikram, M., Kavousi, Maryam, de Vries, Paul S., and Dehghan, Abbas
Abstract: Aims: Both lifestyle factors and genetic background contribute to the development of type 2 diabetes. Estimation of the lifetime risk of diabetes based on genetic information has not been presented, and the extent to which a normal body weight can offset a high lifetime genetic risk is unknown. Methods: We used data from 15,671 diabetes-free participants of European ancestry aged 45 years and older from the prospective population-based ARIC study and Rotterdam Study (RS). We quantified the remaining lifetime risk of diabetes stratified by genetic risk and quantified the effect of normal weight in terms of relative and lifetime risks in low, intermediate and high genetic risk. Results: At age 45 years, the lifetime risk of type 2 diabetes in ARIC in the low, intermediate and high genetic risk category was 33.2%, 41.3% and 47.2%, and in RS 22.8%, 30.6% and 35.5% respectively. The absolute lifetime risk for individuals with normal weight compared to individuals with obesity was 24% lower in ARIC and 8.6% lower in RS in the low genetic risk group, 36.3% lower in ARIC and 31.3% lower in RS in the intermediate genetic risk group, and 25.0% lower in ARIC and 29.4% lower in RS in the high genetic risk group. Conclusions: Genetic variants for type 2 diabetes have value in estimating the lifetime risk of type 2 diabetes. Normal weight mitigates partly the deleterious effect of high genetic risk.
Published: 2021

28. Transfer Learning by Asymmetric Image Weighting for Segmentation across Scanners

Author: Veronika Cheplygina, Annegreet van Opbroek, Arfan Ikram, M., Vernooij, Meike W., and Marleen de Bruijne
Subjects: FOS: Computer and information sciences, Statistics - Machine Learning, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, Machine Learning (stat.ML), stat.ML, cs.CV
Abstract: Supervised learning has been very successful for automatic segmentation of images from a single scanner. However, several papers report deteriorated performances when using classifiers trained on images from one scanner to segment images from other scanners. We propose a transfer learning classifier that adapts to differences between training and test images. This method uses a weighted ensemble of classifiers trained on individual images. The weight of each classifier is determined by the similarity between its training image and the test image. We examine three unsupervised similarity measures, which can be used in scenarios where no labeled data from a newly introduced scanner or scanning protocol is available. The measures are based on a divergence, a bag distance, and on estimating the labels with a clustering procedure. These measures are asymmetric. We study whether the asymmetry can improve classification. Out of the three similarity measures, the bag similarity measure is the most robust across different studies and achieves excellent results on four brain tissue segmentation datasets and three white matter lesion segmentation datasets, acquired at different centers and with different scanners and scanning protocols. We show that the asymmetry can indeed be informative, and that computing the similarity from the test image to the training images is more appropriate than the opposite direction. Supervised learning has been very successful for automatic segmentation of images from a single scanner. However, several papers report deteriorated performances when using classifiers trained on images from one scanner to segment images from other scanners. We propose a transfer learning classifier that adapts to differences between training and test images. This method uses a weighted ensemble of classifiers trained on individual images. The weight of each classifier is determined by the similarity between its training image and the test image. We examine three unsupervised similarity measures, which can be used in scenarios where no labeled data from a newly introduced scanner or scanning protocol is available. The measures are based on a divergence, a bag distance, and on estimating the labels with a clustering procedure. These measures are asymmetric. We study whether the asymmetry can improve classification. Out of the three similarity measures, the bag similarity measure is the most robust across different studies and achieves excellent results on four brain tissue segmentation datasets and three white matter lesion segmentation datasets, acquired at different centers and with different scanners and scanning protocols. We show that the asymmetry can indeed be informative, and that computing the similarity from the test image to the training images is more appropriate than the opposite direction.
Published: 2020

29. Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults

Author: Hofer, E., Roshchupkin, G.V., Adams, H.H.H., Knol, M.J., Lin, H., Li, S., Zare, H., Ahmad, S., Armstrong, N.J., Satizabal, C.L., Bernard, M., Bis, J.C., Gillespie, N.A., Luciano, M., Mishra, A., Scholz, M., Teumer, A., Xia, R., Jian, X., Mosley, T.H., Saba, Y., Pirpamer, L., Seiler, S., Becker, J.T., Carmichael, O., Rotter, J.I., Psaty, B.M., Lopez, O.L., Amin, N., van der Lee, S.J., Yang, Q., Himali, J.J., Maillard, P., Beiser, A.S., DeCarli, C., Karama, S., Lewis, L., Harris, M., Bastin, M.E., Deary, I.J., Veronica Witte, A., Beyer, F., Loeffler, M., Mather, K.A., Schofield, P.R., Thalamuthu, A., Kwok, J.B., Wright, M.J., Ames, D., Trollor, J., Jiang, J., Brodaty, H., Wen, W., Vernooij, M.W., Hofman, A., Uitterlinden, A.G., Niessen, W.J., Wittfeld, K., Bülow, R., Völker, U., Pausova, Z., Bruce Pike, G., Maingault, S., Crivello, F., Tzourio, C., Amouyel, P., Mazoyer, B., Neale, M.C., Franz, C.E., Lyons, M.J., Panizzon, M.S., Andreassen, O.A., Dale, A.M., Logue, M.A., Grasby, K.L., Jahanshad, N., Painter, J.N., Colodro-Conde, L., Bralten, J., Hibar, D.P., Lind, P.A., Pizzagalli, F., Stein, J.L., Thompson, P.M., Medland, S.E., Sachdev, P.S., Kremen, W.S., Wardlaw, J.M., Villringer, A., van Duijn, C.M., Grabe, H.J., Longstreth, W.T., Fornage, M., Paus, T., Debette, S., Arfan Ikram, M., Schmidt, H., Schmidt, R., Seshadri, S., Hofer, E., Roshchupkin, G.V., Adams, H.H.H., Knol, M.J., Lin, H., Li, S., Zare, H., Ahmad, S., Armstrong, N.J., Satizabal, C.L., Bernard, M., Bis, J.C., Gillespie, N.A., Luciano, M., Mishra, A., Scholz, M., Teumer, A., Xia, R., Jian, X., Mosley, T.H., Saba, Y., Pirpamer, L., Seiler, S., Becker, J.T., Carmichael, O., Rotter, J.I., Psaty, B.M., Lopez, O.L., Amin, N., van der Lee, S.J., Yang, Q., Himali, J.J., Maillard, P., Beiser, A.S., DeCarli, C., Karama, S., Lewis, L., Harris, M., Bastin, M.E., Deary, I.J., Veronica Witte, A., Beyer, F., Loeffler, M., Mather, K.A., Schofield, P.R., Thalamuthu, A., Kwok, J.B., Wright, M.J., Ames, D., Trollor, J., Jiang, J., Brodaty, H., Wen, W., Vernooij, M.W., Hofman, A., Uitterlinden, A.G., Niessen, W.J., Wittfeld, K., Bülow, R., Völker, U., Pausova, Z., Bruce Pike, G., Maingault, S., Crivello, F., Tzourio, C., Amouyel, P., Mazoyer, B., Neale, M.C., Franz, C.E., Lyons, M.J., Panizzon, M.S., Andreassen, O.A., Dale, A.M., Logue, M.A., Grasby, K.L., Jahanshad, N., Painter, J.N., Colodro-Conde, L., Bralten, J., Hibar, D.P., Lind, P.A., Pizzagalli, F., Stein, J.L., Thompson, P.M., Medland, S.E., Sachdev, P.S., Kremen, W.S., Wardlaw, J.M., Villringer, A., van Duijn, C.M., Grabe, H.J., Longstreth, W.T., Fornage, M., Paus, T., Debette, S., Arfan Ikram, M., Schmidt, H., Schmidt, R., and Seshadri, S.
Abstract: Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.
Published: 2020

30. Dietary taste patterns in early childhood : The Generation R Study

Author: Nguyen, Anh N., Langeveld, Astrid W.B., van, Vries, Jeanne H.M., de, Arfan Ikram, M., Graaf, Cees, de, Mars, Monica, Voortman, Trudy, Nguyen, Anh N., Langeveld, Astrid W.B., van, Vries, Jeanne H.M., de, Arfan Ikram, M., Graaf, Cees, de, Mars, Monica, and Voortman, Trudy
Abstract: Background: Taste preference is an important determinant of dietary intake and is influenced by taste exposure in early life. However, data on dietary taste patterns in early childhood are scarce. Objectives: We aimed to evaluate dietary taste patterns in early childhood, to examine their tracking between the ages of 1 and 2 y, and to examine their associations with socioeconomic and lifestyle factors. Methods: Dietary intake of children participating in a population-based cohort was assessed with a 211-item age-specific FFQ at the ages of 1 y (n = 3629) and 2 y (n = 844) (2003–2007). Taste intensity values of FFQ food items were calculated based on a food taste database that had been previously constructed and evaluated using a trained adult sensory panel. Cluster analysis based on taste values identified 5 taste clusters that we named: “neutral,” “sweet and sour,” “sweet and fat,” “fat,” and “salt, umami and fat.” Linear regression models were used to examine associations of percentage energy (E%) intake from these taste clusters with socioeconomic and lifestyle factors. Results: At the age of 1 y, 64% ± 13% (mean ± SD) of energy intake was obtained from the “neutral” cluster, whereas at age 2 y, this was 42% ± 8%. At age 2 y, children had higher energy intakes from the “sweet and fat” (18% ± 7%), “fat” (11% ± 4%), and “salt, umami, and fat” (18% ± 6%) clusters than at age 1 y (7% ± 6%, 6% ± 4%, and 11% ± 6%, respectively). In multivariable models, older maternal age, longer breastfeeding duration, and later introduction of complementary feeding were associated with more energy from the “neutral” cluster (e.g., β: 0.31 E%; 95% CI: 0.19, 0.43 E% per 1 mo longer breastfeeding). Higher child BMI was associated with more energy from the “salt, umami, and fat” cluster (β: 0.22 E%; 95% CI: 0.06, 0.38 E% per BMI standard deviation score). Conclusions: Dietary taste patterns in this Dutch cohort were more varied and intense in taste at age 2 y than at 1 y, reaching a l
Published: 2020

31. Life expectancy of parkinsonism patients in the general population

Author: Dommershuijsen, L.J., Heshmatollah, Alis, Darweesh, S.K.L., Koudstaal, Peter J., Arfan Ikram, M., Kamran Ikram, M., Dommershuijsen, L.J., Heshmatollah, Alis, Darweesh, S.K.L., Koudstaal, Peter J., Arfan Ikram, M., and Kamran Ikram, M.
Abstract: Contains fulltext : 226251.pdf (Publisher’s version ) (Open Access)
Published: 2020

32. Unraveling the Association Between Gait and Mortality-One Step at a Time

Author: Dommershuijsen, L.J., Isik, Berna M., Darweesh, S.K.L., Geest, Jos N. van der, Kamran Ikram, M., Arfan Ikram, M., Dommershuijsen, L.J., Isik, Berna M., Darweesh, S.K.L., Geest, Jos N. van der, Kamran Ikram, M., and Arfan Ikram, M.
Abstract: Contains fulltext : 219823.pdf (publisher's version ) (Closed access)
Published: 2020

33. The genetic architecture of the human cerebral cortex

Author: Grasby, Katrina L., Jahanshad, Neda, Painter, Jodie N., Colodro-Conde, Lucía, Bralten, Janita, Hibar, Derrek P., Lind, Penelope A., Pizzagalli, Fabrizio, Ching, Christopher R.K., McMahon, Mary Agnes B., Shatokhina, Natalia, Zsembik, Leo C.P., Thomopoulos, Sophia I., Zhu, Alyssa H., Strike, Lachlan T., Agartz, Ingrid, Alhusaini, Saud, Almeida, Marcio A.A., Alnæs, Dag, Amlien, Inge K., Andersson, Micael, Ard, Tyler, Armstrong, Nicola J., Ashley-Koch, Allison, Atkins, Joshua R., Bernard, Manon, Brouwer, Rachel M., Buimer, Elizabeth E.L., Bülow, Robin, Bürger, Christian, Cannon, Dara M., Chakravarty, Mallar, Chen, Qiang, Cheung, Joshua W., Couvy-Duchesne, Baptiste, Dale, Anders M., Dalvie, Shareefa, de Araujo, Tânia K., de Zubicaray, Greig I., de Zwarte, Sonja M.C., den Braber, Anouk, Doan, Nhat Trung, Dohm, Katharina, Ehrlich, Stefan, Engelbrecht, Hannah Ruth, Erk, Susanne, Fan, Chun Chieh, Fedko, Iryna O., Foley, Sonya F., Ford, Judith M., Fukunaga, Masaki, Garrett, Melanie E., Ge, Tian, Giddaluru, Sudheer, Goldman, Aaron L., Green, Melissa J., Groenewold, Nynke A., Grotegerd, Dominik, Gurholt, Tiril P., Gutman, Boris A., Hansell, Narelle K., Harris, Mathew A., Harrison, Marc B., Haswell, Courtney C., Hauser, Michael, Herms, Stefan, Heslenfeld, Dirk J., Ho, New Fei, Hoehn, David, Hoffmann, Per, Holleran, Laurena, Hoogman, Martine, Hottenga, Jouke Jan, Ikeda, Masashi, Janowitz, Deborah, Jansen, Iris E., Jia, Tianye, Jockwitz, Christiane, Kanai, Ryota, Karama, Sherif, Kasperaviciute, Dalia, Kaufmann, Tobias, Kelly, Sinead, Kikuchi, Masataka, Klein, Marieke, Knapp, Michael, Knodt, Annchen R., Krämer, Bernd, Lam, Max, Lancaster, Thomas M., Lee, Phil H., Lett, Tristram A., Lewis, Lindsay B., Lopes-Cendes, Iscia, Luciano, Michelle, Macciardi, Fabio, Marquand, Andre F., Mathias, Samuel R., Melzer, Tracy R., Milaneschi, Yuri, Mirza-Schreiber, Nazanin, Moreira, Jose C.V., Mühleisen, Thomas W., Müller-Myhsok, Bertram, Najt, Pablo, Nakahara, Soichiro, Nho, Kwangsik, Olde Loohuis, Loes M., Orfanos, Dimitri Papadopoulos, Pearson, John F., Pitcher, Toni L., Pütz, Benno, Quidé, Yann, Ragothaman, Anjanibhargavi, Rashid, Faisal M., Reay, William R., Redlich, Ronny, Reinbold, Céline S., Repple, Jonathan, Richard, Geneviève, Riedel, Brandalyn C., Risacher, Shannon L., Rocha, Cristiane S., Mota, Nina R., Salminen, Lauren, Saremi, Arvin, Saykin, Andrew J., Schlag, Fenja, Schmaal, Lianne, Schofield, Peter R., Secolin, Rodrigo, Shapland, Chin Yang, Shen, Li, Shin, Jean, Shumskaya, Elena, Sønderby, Ida E., Sprooten, Emma, Tansey, Katherine E., Teumer, Alexander, Thalamuthu, Anbupalam, Tordesillas-Gutiérrez, Diana, Turner, Jessica A., Uhlmann, Anne, Vallerga, Costanza L., van der Meer, Dennis, van Donkelaar, Marjolein M.J., van Eijk, Liza, van Erp, Theo G.M., van Haren, Neeltje E.M., van Rooij, Daan, van Tol, Marie José, Veldink, Jan H., Verhoef, Ellen, Walton, Esther, Wang, Mingyuan, Wang, Yunpeng, Wardlaw, Joanna M., Wen, Wei, Westlye, Lars T., Whelan, Christopher D., Witt, Stephanie H., Wittfeld, Katharina, Wolf, Christiane, Wolfers, Thomas, Wu, Jing Qin, Yasuda, Clarissa L., Zaremba, Dario, Zhang, Zuo, Zwiers, Marcel P., Artiges, Eric, Assareh, Amelia A., Ayesa-Arriola, Rosa, Belger, Aysenil, Brandt, Christine L., Brown, Gregory G., Cichon, Sven, Curran, Joanne E., Davies, Gareth E., Degenhardt, Franziska, Dennis, Michelle F., Dietsche, Bruno, Djurovic, Srdjan, Doherty, Colin P., Espiritu, Ryan, Garijo, Daniel, Gil, Yolanda, Gowland, Penny A., Green, Robert C., Häusler, Alexander N., Heindel, Walter, Ho, Beng Choon, Hoffmann, Wolfgang U., Holsboer, Florian, Homuth, Georg, Hosten, Norbert, Jack, Clifford R., Jang, Mi Hyun, Jansen, Andreas, Kimbrel, Nathan A., Kolskår, Knut, Koops, Sanne, Krug, Axel, Lim, Kelvin O., Luykx, Jurjen J., Mathalon, Daniel H., Mather, Karen A., Mattay, Venkata S., Matthews, Sarah, van Son, Jaqueline Mayoral, McEwen, Sarah C., Melle, Ingrid, Morris, Derek W., Mueller, Bryon A., Nauck, Matthias, Nordvik, Jan E., Nöthen, Markus M., O'Leary, Daniel S., Opel, Nils, Martinot, Marie Laure Paillère, Bruce Pike, G., Preda, Adrian, Quinlan, Erin B., Rasser, Paul E., Ratnakar, Varun, Reppermund, Simone, Steen, Vidar M., Tooney, Paul A., Torres, Fábio R., Veltman, Dick J., Voyvodic, James T., Whelan, Robert, White, Tonya, Yamamori, Hidenaga, Adams, Hieab H.H., Bis, Joshua C., Debette, Stephanie, Decarli, Charles, Fornage, Myriam, Gudnason, Vilmundur, Hofer, Edith, Arfan Ikram, M., Launer, Lenore, Longstreth, W. T., Lopez, Oscar L., Fisher, Simon E., Martin, Nicholas G., McMahon, Katie L., Wright, Margaret J., Thompson, Paul M., Medland, Sarah E., Grasby, Katrina L., Jahanshad, Neda, Painter, Jodie N., Colodro-Conde, Lucía, Bralten, Janita, Hibar, Derrek P., Lind, Penelope A., Pizzagalli, Fabrizio, Ching, Christopher R.K., McMahon, Mary Agnes B., Shatokhina, Natalia, Zsembik, Leo C.P., Thomopoulos, Sophia I., Zhu, Alyssa H., Strike, Lachlan T., Agartz, Ingrid, Alhusaini, Saud, Almeida, Marcio A.A., Alnæs, Dag, Amlien, Inge K., Andersson, Micael, Ard, Tyler, Armstrong, Nicola J., Ashley-Koch, Allison, Atkins, Joshua R., Bernard, Manon, Brouwer, Rachel M., Buimer, Elizabeth E.L., Bülow, Robin, Bürger, Christian, Cannon, Dara M., Chakravarty, Mallar, Chen, Qiang, Cheung, Joshua W., Couvy-Duchesne, Baptiste, Dale, Anders M., Dalvie, Shareefa, de Araujo, Tânia K., de Zubicaray, Greig I., de Zwarte, Sonja M.C., den Braber, Anouk, Doan, Nhat Trung, Dohm, Katharina, Ehrlich, Stefan, Engelbrecht, Hannah Ruth, Erk, Susanne, Fan, Chun Chieh, Fedko, Iryna O., Foley, Sonya F., Ford, Judith M., Fukunaga, Masaki, Garrett, Melanie E., Ge, Tian, Giddaluru, Sudheer, Goldman, Aaron L., Green, Melissa J., Groenewold, Nynke A., Grotegerd, Dominik, Gurholt, Tiril P., Gutman, Boris A., Hansell, Narelle K., Harris, Mathew A., Harrison, Marc B., Haswell, Courtney C., Hauser, Michael, Herms, Stefan, Heslenfeld, Dirk J., Ho, New Fei, Hoehn, David, Hoffmann, Per, Holleran, Laurena, Hoogman, Martine, Hottenga, Jouke Jan, Ikeda, Masashi, Janowitz, Deborah, Jansen, Iris E., Jia, Tianye, Jockwitz, Christiane, Kanai, Ryota, Karama, Sherif, Kasperaviciute, Dalia, Kaufmann, Tobias, Kelly, Sinead, Kikuchi, Masataka, Klein, Marieke, Knapp, Michael, Knodt, Annchen R., Krämer, Bernd, Lam, Max, Lancaster, Thomas M., Lee, Phil H., Lett, Tristram A., Lewis, Lindsay B., Lopes-Cendes, Iscia, Luciano, Michelle, Macciardi, Fabio, Marquand, Andre F., Mathias, Samuel R., Melzer, Tracy R., Milaneschi, Yuri, Mirza-Schreiber, Nazanin, Moreira, Jose C.V., Mühleisen, Thomas W., Müller-Myhsok, Bertram, Najt, Pablo, Nakahara, Soichiro, Nho, Kwangsik, Olde Loohuis, Loes M., Orfanos, Dimitri Papadopoulos, Pearson, John F., Pitcher, Toni L., Pütz, Benno, Quidé, Yann, Ragothaman, Anjanibhargavi, Rashid, Faisal M., Reay, William R., Redlich, Ronny, Reinbold, Céline S., Repple, Jonathan, Richard, Geneviève, Riedel, Brandalyn C., Risacher, Shannon L., Rocha, Cristiane S., Mota, Nina R., Salminen, Lauren, Saremi, Arvin, Saykin, Andrew J., Schlag, Fenja, Schmaal, Lianne, Schofield, Peter R., Secolin, Rodrigo, Shapland, Chin Yang, Shen, Li, Shin, Jean, Shumskaya, Elena, Sønderby, Ida E., Sprooten, Emma, Tansey, Katherine E., Teumer, Alexander, Thalamuthu, Anbupalam, Tordesillas-Gutiérrez, Diana, Turner, Jessica A., Uhlmann, Anne, Vallerga, Costanza L., van der Meer, Dennis, van Donkelaar, Marjolein M.J., van Eijk, Liza, van Erp, Theo G.M., van Haren, Neeltje E.M., van Rooij, Daan, van Tol, Marie José, Veldink, Jan H., Verhoef, Ellen, Walton, Esther, Wang, Mingyuan, Wang, Yunpeng, Wardlaw, Joanna M., Wen, Wei, Westlye, Lars T., Whelan, Christopher D., Witt, Stephanie H., Wittfeld, Katharina, Wolf, Christiane, Wolfers, Thomas, Wu, Jing Qin, Yasuda, Clarissa L., Zaremba, Dario, Zhang, Zuo, Zwiers, Marcel P., Artiges, Eric, Assareh, Amelia A., Ayesa-Arriola, Rosa, Belger, Aysenil, Brandt, Christine L., Brown, Gregory G., Cichon, Sven, Curran, Joanne E., Davies, Gareth E., Degenhardt, Franziska, Dennis, Michelle F., Dietsche, Bruno, Djurovic, Srdjan, Doherty, Colin P., Espiritu, Ryan, Garijo, Daniel, Gil, Yolanda, Gowland, Penny A., Green, Robert C., Häusler, Alexander N., Heindel, Walter, Ho, Beng Choon, Hoffmann, Wolfgang U., Holsboer, Florian, Homuth, Georg, Hosten, Norbert, Jack, Clifford R., Jang, Mi Hyun, Jansen, Andreas, Kimbrel, Nathan A., Kolskår, Knut, Koops, Sanne, Krug, Axel, Lim, Kelvin O., Luykx, Jurjen J., Mathalon, Daniel H., Mather, Karen A., Mattay, Venkata S., Matthews, Sarah, van Son, Jaqueline Mayoral, McEwen, Sarah C., Melle, Ingrid, Morris, Derek W., Mueller, Bryon A., Nauck, Matthias, Nordvik, Jan E., Nöthen, Markus M., O'Leary, Daniel S., Opel, Nils, Martinot, Marie Laure Paillère, Bruce Pike, G., Preda, Adrian, Quinlan, Erin B., Rasser, Paul E., Ratnakar, Varun, Reppermund, Simone, Steen, Vidar M., Tooney, Paul A., Torres, Fábio R., Veltman, Dick J., Voyvodic, James T., Whelan, Robert, White, Tonya, Yamamori, Hidenaga, Adams, Hieab H.H., Bis, Joshua C., Debette, Stephanie, Decarli, Charles, Fornage, Myriam, Gudnason, Vilmundur, Hofer, Edith, Arfan Ikram, M., Launer, Lenore, Longstreth, W. T., Lopez, Oscar L., Fisher, Simon E., Martin, Nicholas G., McMahon, Katie L., Wright, Margaret J., Thompson, Paul M., and Medland, Sarah E.
Abstract: The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
Published: 2020

34. Associations between self-reported sensory impairment and risk of cognitive decline and impairment in the health and retirement study cohort

Author: Maharani, Asri, Dawes, Piers, Nazroo, James, Tampubolon, Gindo, Pendleton, Neil, Bertelsen, Geir, Cosh, Suzanne, Cougnard-Grégoire, Audrey, Delcourt, Cécile, Constantinidou, Fofi, Goedegebure, Andre, Helmer, Catherine, Arfan Ikram, M., Klaver, Caroline C.W., Meester-Smor, Magda, Nael, Virginie, Oosterloo, Neelke, Schirmer, Henrik, Tiemeier, Henning, Maharani, Asri, Dawes, Piers, Nazroo, James, Tampubolon, Gindo, Pendleton, Neil, Bertelsen, Geir, Cosh, Suzanne, Cougnard-Grégoire, Audrey, Delcourt, Cécile, Constantinidou, Fofi, Goedegebure, Andre, Helmer, Catherine, Arfan Ikram, M., Klaver, Caroline C.W., Meester-Smor, Magda, Nael, Virginie, Oosterloo, Neelke, Schirmer, Henrik, and Tiemeier, Henning
Abstract: Objectives: We aimed to determine whether self-assessed single (hearing or visual) and dual sensory (hearing and visual) impairments are associated with cognitive decline and incident possible cognitive impairment, no dementia (CIND) and probable dementia. Method: Data were drawn from the 1996-2014 surveys of the Health and Retirement Study (HRS), involving 19,618 respondents who had no probable dementia and who were aged 50 years or older at the baseline. We used linear mixed models to test the association between self-assessed sensory impairment and cognitive decline followed by a Cox proportional hazard model to estimate the relative risk of incident possible CIND and probable dementia associated with the presence of sensory impairment. Results: Respondents with self-assessed single and dual sensory impairment performed worse in cognitive tests than those without sensory impairment. The fully adjusted incidence of developing possible CIND was 17% higher for respondents with hearing impairment than those without hearing impairment. Respondents with visual impairment had 35% and 25% higher risk for developing possible CIND and probable dementia, respectively, than those without visual impairment. Respondents with dual sensory impairment at baseline were 38% and 26% more likely to develop possible CIND and probable dementia, respectively, than those with no sensory impairment. Discussion: Self-assessed sensory impairment is independently associated with cognitive decline and incident possible CIND and probable dementia. Further studies are needed to identify the mechanism underlying this association and to determine whether treatment of sensory impairment could ameliorate cognitive decline and delay the onset of dementia among older adults.
Published: 2020

35. Trajectories of recall memory as predictive of hearing impairment:A longitudinal cohort study

Author: Maharani, Asri, Dawes, Piers, Nazroo, James, Tampubolon, Gindo, Pendleton, Neil, Bertelsen, Geir, Cosh, Suzanne, Cougnard-Grégoire, Audrey, Delcourt, Cécile, Constantinidou, Fofi, Goedegebure, Andre, Helmer, Catherine, Arfan Ikram, M., Klaver, Caroline C.W., Meester-Smoor, Magda, Nael, Virginie, Oosterloo, Neelke, Schirmer, Henrik, Tiemeier, Henning, Maharani, Asri, Dawes, Piers, Nazroo, James, Tampubolon, Gindo, Pendleton, Neil, Bertelsen, Geir, Cosh, Suzanne, Cougnard-Grégoire, Audrey, Delcourt, Cécile, Constantinidou, Fofi, Goedegebure, Andre, Helmer, Catherine, Arfan Ikram, M., Klaver, Caroline C.W., Meester-Smoor, Magda, Nael, Virginie, Oosterloo, Neelke, Schirmer, Henrik, and Tiemeier, Henning
Abstract: Objectives Accumulating evidence points to a relationship between hearing function and cognitive ability in later life. However, the exact mechanisms of this relationship are still unclear. This study aimed to characterise latent cognitive trajectories in recall memory and identify their association with subsequent risk of hearing impairment. Methods We analysed data from the English Longitudinal Study of Ageing Wave 1 (2002/03) until Wave 7 (2014/15). The study population consisted of 3,615 adults aged 50+ who participated in the first wave of the English Longitudinal Study of Ageing, who had no self-reported hearing impairment in Wave 1, and who underwent a hearing test in Wave 7. Respondents were classified as having hearing impairment if they failed to hear tones quieter than 35 dB HL in the better ear. Results The trajectories of recall memory scores were grouped using latent class growth mixture modelling and were related to the presence of hearing impairment in Wave 7. Models estimating 1-class through 5-class recall memory trajectories were compared and the best-fitting models were 4-class trajectories. The different recall memory trajectories represent different starting points and mean of the memory scores. Compared to respondents with the highest recall memory trajectory, other trajectories were increasingly likely to develop later hearing impairment. Conclusions Long-term changes in cognitive ability predict hearing impairment. Further research is required to identify the mechanisms explaining the association between cognitive trajectories and hearing impairment, as well as to determine whether intervention for maintenance of cognitive function also give benefit on hearing function among older adults.
Published: 2020

36. Cortical superficial siderosis in the general population: The Framingham Heart and Rotterdam studies

Author: Shoamanesh, Ashkan, primary, Akoudad, Saloua, additional, Himali, Jayandra J., additional, Beiser, Alexa S., additional, DeCarli, Charles, additional, Seshadri, Sudha, additional, Arfan Ikram, M, additional, Romero, Jose R, additional, and Vernooij, Meike W, additional
Published: 2021
Full Text: View/download PDF

37. Insulin Resistance and the Risk of Stroke and Stroke Subtypes in the Nondiabetic Elderly

Author: Wieberdink, Renske G., Koudstaal, Peter J., Hofman, Albert, Witteman, Jacqueline C. M., Breteler, Monique M. B., and Arfan Ikram, M.
Published: 2012
Full Text: View/download PDF

38. Association of genetic variation with systolic and diastolic blood pressure among African Americans: the Candidate Gene Association Resource study

Author: Fox, Ervin R., Young, J. Hunter, Li, Yali, Dreisbach, Albert W., Keating, Brendan J., Musani, Solomon K., Liu, Kiang, Morrison, Alanna C., Ganesh, Santhi, Kutlar, Abdullah, Ramachandran, Vasan S., Polak, Josef F., Fabsitz, Richard R., Dries, Daniel L., Farlow, Deborah N., Redline, Susan, Adeyemo, Adebowale, Hirschorn, Joel N., Sun, Yan V., Wyatt, Sharon B., Penman, Alan D., Palmas, Walter, Rotter, Jerome I., Townsend, Raymond R., Doumatey, Ayo P., Tayo, Bamidele O., Mosley, Thomas H., Jr, Lyon, Helen N., Kang, Sun J., Rotimi, Charles N., Cooper, Richard S., Franceschini, Nora, Curb, J. David, Martin, Lisa W., Eaton, Charles B., Kardia, Sharon L.R., Taylor, Herman A., Caulfield, Mark J., Ehret, Georg B., Johnson, Toby, Munroe, Patricia B., Rice, Kenneth M., Bochud, Murielle, Johnson, Andrew D., Chasman, Daniel I., Smith, Albert V., Tobin, Martin D., Verwoert, Germaine C., Hwang, Shih-Jen, Pihur, Vasyl, Vollenweider, Peter, OʼReilly, Paul F., Amin, Najaf, Bragg-Gresham, Jennifer L., Teumer, Alexander, Glazer, Nicole L., Launer, Lenore, Zhao, Jing Hua, Aulchenko, Yurii, Heath, Simon, Sõber, Siim, Parsa, Afshin, Luan, Jianʼan, Arora, Pankaj, Dehghan, Abbas, Zhang, Feng, Lucas, Gavin, Hicks, Andrew A., Jackson, Anne U., Peden, John F., Tanaka, Toshiko, Wild, Sarah H., Rudan, Igor, Igl, Wilmar, Milaneschi, Yuri, Parker, Alex N., Fava, Cristiano, Chambers, John C., Kumari, Meena, JinGo, Min, van der Harst, Pim, Kao, Wen Hong Linda, Sjögren, Marketa, Vinay, D.G., Alexander, Myriam, Tabara, Yasuharu, Shaw-Hawkins, Sue, Whincup, Peter H., Liu, Yongmei, Shi, Gang, Kuusisto, Johanna, Seielstad, Mark, Sim, Xueling, Nguyen, Khanh-Dung Hoang, Lehtimäki, Terho, Matullo, Giuseppe, Wu, Ying, Gaunt, Tom R., Charlotte Onland-Moret, N., Cooper, Matthew N., Platou, Carl G.P., Org, Elin, Hardy, Rebecca, Dahgam, Santosh, Palmen, Jutta, Vitart, Veronique, Braund, Peter S., Kuznetsova, Tatiana, Uiterwaal, Cuno S.P.M., Campbell, Harry, Ludwig, Barbara, Tomaszewski, Maciej, Tzoulaki, Ioanna, Palmer, Nicholette D., Aspelund, Thor, Garcia, Melissa, Chang, Yen-Pei C., OʼConnell, Jeffrey R., Steinle, Nanette I., Grobbee, Diederick E., Arking, Dan E., Hernandez, Dena, Najjar, Samer, McArdle, Wendy L., Hadley, David, Brown, Morris J., Connell, John M., Hingorani, Aroon D., Day, Ian N.M., Lawlor, Debbie A., Beilby, John P., Lawrence, Robert W., Clarke, Robert, Collins, Rory, Hopewell, Jemma C., Ongen, Halit, Bis, Joshua C., Kähönen, Mika, Viikari, Jorma, Adair, Linda S., Lee, Nanette R., Chen, Ming-Huei, Olden, Matthias, Pattaro, Cristian, Hoffman Bolton, Judith A., Köttgen, Anna, Bergmann, Sven, Mooser, Vincent, Chaturvedi, Nish, Frayling, Timothy M., Islam, Muhammad, Jafar, Tazeen H., Erdmann, Jeanette, Kulkarni, Smita R., Bornstein, Stefan R., Grässler, Jürgen, Groop, Leif, Voight, Benjamin F., Kettunen, Johannes, Howard, Philip, Taylor, Andrew, Guarrera, Simonetta, Ricceri, Fulvio, Emilsson, Valur, Plump, Andrew, Barroso, Inês, Khaw, Kay-Tee, Weder, Alan B., Hunt, Steven C., Bergman, Richard N., Collins, Francis S., Bonnycastle, Lori L., Scott, Laura J., Stringham, Heather M., Peltonen, Leena, Perola, Markus, Vartiainen, Erkki, Brand, Stefan-Martin, Staessen, Jan A., Wang, Thomas J., Burton, Paul R., SolerArtigas, Maria, Dong, Yanbin, Snieder, Harold, Wang, Xiaoling, Zhu, Haidong, Lohman, Kurt K., Rudock, Megan E., Heckbert, Susan R., Smith, Nicholas L., Wiggins, Kerri L., Shriner, Daniel, Veldre, Gudrun, Viigimaa, Margus, Kinra, Sanjay, Prabhakaran, Dorairajan, Tripathy, Vikal, Langefeld, Carl D., Rosengren, Annika, Thelle, Dag S., MariaCorsi, Anna, Singleton, Andrew, Forrester, Terrence, Hilton, Gina, McKenzie, Colin A., Salako, Tunde, Iwai, Naoharu, Kita, Yoshikuni, Ogihara, Toshio, Ohkubo, Takayoshi, Okamura, Tomonori, Ueshima, Hirotsugu, Umemura, Satoshi, Eyheramendy, Susana, Meitinger, Thomas, Wichmann, H.-Erich, Cho, Yoon Shin, Kim, Hyung-Lae, Lee, Jong-Young, Scott, James, Sehmi, Joban S., Zhang, Weihua, Hedblad, Bo, Nilsson, Peter, Smith, George Davey, Wong, Andrew, Narisu, Narisu, Stančáková, Alena, Raffel, Leslie J., Yao, Jie, Kathiresan, Sekar, OʼDonnell, Chris, Schwartz, Steven M., Arfan Ikram, M., Longstreth, Will T., Jr, Seshadri, Sudha, Shrine, Nick R.G., Wain, Louise V., Morken, Mario A., Swift, Amy J., Laitinen, Jaana, Prokopenko, Inga, Zitting, Paavo, Cooper, Jackie A., Humphries, Steve E., Danesh, John, Rasheed, Asif, Goel, Anuj, Hamsten, Anders, Watkins, Hugh, Bakker, Stephan J.L., van Gilst, Wiek H., Janipalli, Charles S., Radha Mani, K., Yajnik, Chittaranjan S., Hofman, Albert, Mattace-Raso, Francesco U.S., Oostra, Ben A., Demirkan, Ayse, Isaacs, Aaron, Rivadeneira, Fernando, Lakatta, Edward G., Orru, Marco, Scuteri, Angelo, Ala-Korpela, Mika, Kangas, Antti J., Lyytikäinen, Leo-Pekka, Soininen, Pasi, Tukiainen, Taru, Würz, Peter, Twee-Hee Ong, Rick, Dörr, Marcus, Kroemer, Heyo K., Völker, Uwe, Völzke, Henry, Galan, Pilar, Hercberg, Serge, Lathrop, Mark, Zelenika, Diana, Deloukas, Panos, Mangino, Massimo, Spector, Tim D., Zhai, Guangju, Meschia, James F., Nalls, Michael A., Sharma, Pankaj, Terzic, Janos, Kranthi Kumar, M.J., Denniff, Matthew, Zukowska-Szczechowska, Ewa, Wagenknecht, Lynne E., Fowkes, Gerald R., Charchar, Fadi J., Schwarz, Peter E.H., Hayward, Caroline, Guo, Xiuqing, Bots, Michiel L., Brand, Eva, Samani, Nilesh J., Polasek, Ozren, Talmud, Philippa J., Nyberg, Fredrik, Kuh, Diana, Laan, Maris, Hveem, Kristian, Palmer, Lyle J., van der Schouw, Yvonne T., Casas, Juan P., Mohlke, Karen L., Vineis, Paolo, Raitakari, Olli, Wong, Tien Y., Shyong Tai, E., Laakso, Markku, Rao, Dabeeru C., Harris, Tamara B., Morris, Richard W., Dominiczak, Anna F., Kivimaki, Mika, Marmot, Michael G., Miki, Tetsuro, Saleheen, Danish, Chandak, Giriraj R., Coresh, Josef, Navis, Gerjan, Salomaa, Veikko, Han, Bok-Ghee, Kooner, Jaspal S., Melander, Olle, Ridker, Paul M., Bandinelli, Stefania, Gyllensten, Ulf B., Wright, Alan F., Wilson, James F., Ferrucci, Luigi, Farrall, Martin, Tuomilehto, Jaakko, Pramstaller, Peter P., Elosua, Roberto, Soranzo, Nicole, Sijbrands, Eric J.G., Altshuler, David, Loos, Ruth J.F., Shuldiner, Alan R., Gieger, Christian, Meneton, Pierre, Uitterlinden, Andre G., Wareham, Nicholas J., Gudnason, Vilmundur, Rettig, Rainer, Uda, Manuela, Strachan, David P., Witteman, Jacqueline C.M., Hartikainen, Anna-Liisa, Beckmann, Jacques S., Boerwinkle, Eric, Boehnke, Michael, Larson, Martin G., Järvelin, Marjo-Riitta, Psaty, Bruce M., Abecasis, Gonçalo R., Elliott, Paul, van Duijn, Cornelia M., Newton-Cheh, Christopher, Chakravarti, Aravinda, Zhu, Xiaofeng, and Levy, Daniel
Published: 2011
Full Text: View/download PDF

39. Correction: Predictive value for cardiovascular events of common carotid intima media thickness and its rate of change in individuals at high cardiovascular risk - Results from the PROG-IMT collaboration (PLoS One (2018) 13:4 (e0191172) DOI: 10.1371/journal.pone.0191172)

Author: Lorenz M. W., Gao L., Ziegelbauer K., Norata G. D., Empana J. P., Schmidtmann I., Lin H. -J., McLachlan S., Bokemark L., Ronkainen K., Amato M., Schminke U., Srinivasan S. R., Lind L., Okazaki S., Stehouwer C. D. A., Willeit P., Polak J. F., Steinmetz H., Sander D., Poppert H., Desvarieux M., Arfan Ikram M., Johnsen S. H., Staub D., Sirtori C. R., Iglseder B., Beloqui O., Engstrom G., Friera A., Rozza F., Xie W., Parraga G., Grigore L., Plichart M., Blankenberg S., Su T. -C., Schmidt C., Tuomainen T. -P., Veglia F., Volzke H., Nijpels G., Willeit J., Sacco R. L., Franco O. H., Uthoff H., Hedblad B., Suarez C., Izzo R., Zhao D., Wannarong T., Catapano A., Ducimetiere P., Espinola-Klein C., Chien K. -L., Price J. F., Bergstrom G., Kauhanen J., Tremoli E., Dorr M., Berenson G., Kitagawa K., Dekker J. M., Kiechl S., Sitzer M., Bickel H., Rundek T., Hofman A., Mathiesen E. B., Castelnuovo S., Landecho M. F., Rosvall M., Gabriel R., De Luca N., Liu J., Baldassarre D., Kavousi M., De Groot E., Bots M. L., Yanez D. N., Thompson S. G., Lorenz, M. W., Gao, L., Ziegelbauer, K., Norata, G. D., Empana, J. P., Schmidtmann, I., Lin, H. -J., Mclachlan, S., Bokemark, L., Ronkainen, K., Amato, M., Schminke, U., Srinivasan, S. R., Lind, L., Okazaki, S., Stehouwer, C. D. A., Willeit, P., Polak, J. F., Steinmetz, H., Sander, D., Poppert, H., Desvarieux, M., Arfan Ikram, M., Johnsen, S. H., Staub, D., Sirtori, C. R., Iglseder, B., Beloqui, O., Engstrom, G., Friera, A., Rozza, F., Xie, W., Parraga, G., Grigore, L., Plichart, M., Blankenberg, S., Su, T. -C., Schmidt, C., Tuomainen, T. -P., Veglia, F., Volzke, H., Nijpels, G., Willeit, J., Sacco, R. L., Franco, O. H., Uthoff, H., Hedblad, B., Suarez, C., Izzo, R., Zhao, D., Wannarong, T., Catapano, A., Ducimetiere, P., Espinola-Klein, C., Chien, K. -L., Price, J. F., Bergstrom, G., Kauhanen, J., Tremoli, E., Dorr, M., Berenson, G., Kitagawa, K., Dekker, J. M., Kiechl, S., Sitzer, M., Bickel, H., Rundek, T., Hofman, A., Mathiesen, E. B., Castelnuovo, S., Landecho, M. F., Rosvall, M., Gabriel, R., De Luca, N., Liu, J., Baldassarre, D., Kavousi, M., De Groot, E., Bots, M. L., Yanez, D. N., and Thompson, S. G.
Abstract: An affiliation for Moise Desvarieux is missing. In addition to affiliation #22, Moise Desvarieux is affiliated with: METHODS Core, Centre de Recherche Epidémiologie et Statistique Paris Sorbonne Cité (CRESS), Institut National de la Santé et de la Recherche Médicale (INSERM) UMR 1153, Paris France.
Published: 2018

40. Trajectories of recall memory as predictive of hearing impairment: A longitudinal cohort study

Author: Maharani, Asri, Dawes, Piers, Nazroo, James, Tampubolon, Gindo, Pendleton, Neil, Bertelsen, Geir, Cosh, Suzanne, Cougnard-Grégoire, Audrey, Delcourt, Cécile, Constantinidou, Fofi, Goedegebure, Andre, Helmer, Catherine, Arfan Ikram, M., Klaver, Caroline C.W., Meester-Smoor, Magda, Nael, Virginie, Oosterloo, Neelke, Schirmer, Henrik, Tiemeier, Henning, Otorhinolaryngology and Head and Neck Surgery, Ophthalmology, Epidemiology, and Child and Adolescent Psychiatry / Psychology
Subjects: Male, ResearchInstitutes_Networks_Beacons/global_development_institute, Longitudinal study, Aging, Physiology, Social Sciences, Otology, Audiology, Deafness, Cohort Studies, 0302 clinical medicine, Cognition, Learning and Memory, Hearing, Medicine and Health Sciences, Psychology, Public and Occupational Health, Longitudinal Studies, 030223 otorhinolaryngology, Hearing Disorders, Aged, 80 and over, Cognitive Impairment, Multidisciplinary, VDP::Medisinske Fag: 700::Helsefag: 800::Samfunnsmedisin, sosialmedisin: 801, medicine.diagnostic_test, Cognitive Neurology, Hearing Tests, Middle Aged, England, Neurology, Memory Recall, Medicine, Female, Sensory Perception, Anatomy, Cohort study, Research Article, medicine.medical_specialty, Science, Cognitive Neuroscience, 03 medical and health sciences, Memory, medicine, otorhinolaryngologic diseases, Humans, Cognitive Dysfunction, Association (psychology), Hearing Loss, Aged, Memory Disorders, Recall, Biology and Life Sciences, Physical Activity, Global Development Institute, Otorhinolaryngology, Ageing, Ears, Mental Recall, Hearing test, Cognitive Science, VDP::Medical disciplines: 700::Health sciences: 800::Community medicine, Social medicine: 801, Physiological Processes, Organism Development, Head, 030217 neurology & neurosurgery, Neuroscience, Developmental Biology
Abstract: Objectives - Accumulating evidence points to a relationship between hearing function and cognitive ability in later life. However, the exact mechanisms of this relationship are still unclear. This study aimed to characterise latent cognitive trajectories in recall memory and identify their association with subsequent risk of hearing impairment. Methods - We analysed data from the English Longitudinal Study of Ageing Wave 1 (2002/03) until Wave 7 (2014/15). The study population consisted of 3,615 adults aged 50+ who participated in the first wave of the English Longitudinal Study of Ageing, who had no self-reported hearing impairment in Wave 1, and who underwent a hearing test in Wave 7. Respondents were classified as having hearing impairment if they failed to hear tones quieter than 35 dB HL in the better ear. Results - The trajectories of recall memory scores were grouped using latent class growth mixture modelling and were related to the presence of hearing impairment in Wave 7. Models estimating 1-class through 5-class recall memory trajectories were compared and the best-fitting models were 4-class trajectories. The different recall memory trajectories represent different starting points and mean of the memory scores. Compared to respondents with the highest recall memory trajectory, other trajectories were increasingly likely to develop later hearing impairment. Conclusions - Long-term changes in cognitive ability predict hearing impairment. Further research is required to identify the mechanisms explaining the association between cognitive trajectories and hearing impairment, as well as to determine whether intervention for maintenance of cognitive function also give benefit on hearing function among older adults.
Published: 2019
Full Text: View/download PDF

41. Genetic architecture of subcortical brain structures in 38,851 individuals

Author: Satizabal, Claudia L., Adams, H.H.H., Hibar, Derrek P., White, Charles C., Knol, Maria J., Stein, Jason L., Arias Vasquez, A., Bralten, J.B., Becker, D., Hoogman, M., Klein, M., Marquand, A.F., Shumskaya, E., Rooij, D. van, Wolfers, T., Zwiers, M.P., Bokhoven, H. van, Brunner, H.G., Buitelaar, J.K., Fisher, S.E., Fernandez, G.S.E., Franke, B., Seshadri, Sudha, Arfan Ikram, M., Satizabal, Claudia L., Adams, H.H.H., Hibar, Derrek P., White, Charles C., Knol, Maria J., Stein, Jason L., Arias Vasquez, A., Bralten, J.B., Becker, D., Hoogman, M., Klein, M., Marquand, A.F., Shumskaya, E., Rooij, D. van, Wolfers, T., Zwiers, M.P., Bokhoven, H. van, Brunner, H.G., Buitelaar, J.K., Fisher, S.E., Fernandez, G.S.E., Franke, B., Seshadri, Sudha, and Arfan Ikram, M.
Abstract: Contains fulltext : 209944.pdf (publisher's version ) (Closed access)
Published: 2019

42. A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals

Author: Deelen, J. (Joris), Kettunen, J. (Johannes), Fischer, K. (Krista), van der Spek, A. (Ashley), Trompet, S. (Stella), Kastenmüller, G. (Gabi), Boyd, A. (Andy), Zierer, J. (Jonas), van den Akker, E. B. (Erik B.), Ala-Korpela, M. (Mika), Amin, N. (Najaf), Demirkan, A. (Ayse), Ghanbari, M. (Mohsen), van Heemst, D. (Diana), Arfan Ikram, M. (M.), van Klinken, J. B. (Jan Bert), Mooijaart, S. P. (Simon P.), Peters, A. (Annette), Salomaa, V. (Veikko), Sattar, N. (Naveed), Spector, T. D. (Tim D.), Tiemeier, H. (Henning), Verhoeven, A. (Aswin), Waldenberger, M. (Melanie), Würtz, P. (Peter), Smith, G. D. (George Davey), Metspalu, A. (Andres), Perola, M. (Markus), Menni, C. (Cristina), Geleijnse, J. M. (Johanna M.), Drenos, F. (Fotios), Beekman, M. (Marian), Wouter Jukema, J. (J.), van Duijn, C. M. (Cornelia M.), Slagboom, P. E. (P. Eline), Deelen, J. (Joris), Kettunen, J. (Johannes), Fischer, K. (Krista), van der Spek, A. (Ashley), Trompet, S. (Stella), Kastenmüller, G. (Gabi), Boyd, A. (Andy), Zierer, J. (Jonas), van den Akker, E. B. (Erik B.), Ala-Korpela, M. (Mika), Amin, N. (Najaf), Demirkan, A. (Ayse), Ghanbari, M. (Mohsen), van Heemst, D. (Diana), Arfan Ikram, M. (M.), van Klinken, J. B. (Jan Bert), Mooijaart, S. P. (Simon P.), Peters, A. (Annette), Salomaa, V. (Veikko), Sattar, N. (Naveed), Spector, T. D. (Tim D.), Tiemeier, H. (Henning), Verhoeven, A. (Aswin), Waldenberger, M. (Melanie), Würtz, P. (Peter), Smith, G. D. (George Davey), Metspalu, A. (Andres), Perola, M. (Markus), Menni, C. (Cristina), Geleijnse, J. M. (Johanna M.), Drenos, F. (Fotios), Beekman, M. (Marian), Wouter Jukema, J. (J.), van Duijn, C. M. (Cornelia M.), and Slagboom, P. E. (P. Eline)
Abstract: Predicting longer-term mortality risk requires collection of clinical data, which is often cumbersome. Therefore, we use a well-standardized metabolomics platform to identify metabolic predictors of long-term mortality in the circulation of 44,168 individuals (age at baseline 18–109), of whom 5512 died during follow-up. We apply a stepwise (forward-backward) procedure based on meta-analysis results and identify 14 circulating biomarkers independently associating with all-cause mortality. Overall, these associations are similar in men and women and across different age strata. We subsequently show that the prediction accuracy of 5- and 10-year mortality based on a model containing the identified biomarkers and sex (C-statistic = 0.837 and 0.830, respectively) is better than that of a model containing conventional risk factors for mortality (C-statistic = 0.772 and 0.790, respectively). The use of the identified metabolic profile as a predictor of mortality or surrogate endpoint in clinical studies needs further investigation.
Published: 2019

43. Genetic susceptibility, obesity and lifetime risk of type 2 diabetes: The ARIC study and Rotterdam Study.

Author: Ligthart, Symen, Hasbani, Natalie R., Ahmadizar, Fariba, van Herpt, Thijs T. W., Leening, Maarten J. G., Uitterlinden, André G., Sijbrands, Eric J. G., Morrison, Alanna C., Boerwinkle, Eric, Pankow, James S., Selvin, Elizabeth, Arfan Ikram, M., Kavousi, Maryam, de Vries, Paul S., and Dehghan, Abbas
Subjects: OBESITY complications, LIFESTYLES, GENETICS, BODY weight, TYPE 2 diabetes, RISK assessment, DISEASE susceptibility, DESCRIPTIVE statistics, LONGITUDINAL method, DISEASE risk factors
Abstract: Aims: Both lifestyle factors and genetic background contribute to the development of type 2 diabetes. Estimation of the lifetime risk of diabetes based on genetic information has not been presented, and the extent to which a normal body weight can offset a high lifetime genetic risk is unknown. Methods: We used data from 15,671 diabetes‐free participants of European ancestry aged 45 years and older from the prospective population‐based ARIC study and Rotterdam Study (RS). We quantified the remaining lifetime risk of diabetes stratified by genetic risk and quantified the effect of normal weight in terms of relative and lifetime risks in low, intermediate and high genetic risk. Results: At age 45 years, the lifetime risk of type 2 diabetes in ARIC in the low, intermediate and high genetic risk category was 33.2%, 41.3% and 47.2%, and in RS 22.8%, 30.6% and 35.5% respectively. The absolute lifetime risk for individuals with normal weight compared to individuals with obesity was 24% lower in ARIC and 8.6% lower in RS in the low genetic risk group, 36.3% lower in ARIC and 31.3% lower in RS in the intermediate genetic risk group, and 25.0% lower in ARIC and 29.4% lower in RS in the high genetic risk group. Conclusions: Genetic variants for type 2 diabetes have value in estimating the lifetime risk of type 2 diabetes. Normal weight mitigates partly the deleterious effect of high genetic risk. [ABSTRACT FROM AUTHOR]
Published: 2021
Full Text: View/download PDF

44. GenNet framework: interpretable deep learning for predicting phenotypes from genetic data.

Author: van Hilten, Arno, Kushner, Steven A., Kayser, Manfred, Arfan Ikram, M., Adams, Hieab H. H., Klaver, Caroline C. W., Niessen, Wiro J., and Roshchupkin, Gennady V.
Subjects: DEEP learning, PHENOTYPES, GENETICS of schizophrenia, PROTEOLYSIS, ENDOCRINE system physiology
Abstract: Applying deep learning in population genomics is challenging because of computational issues and lack of interpretable models. Here, we propose GenNet, a novel open-source deep learning framework for predicting phenotypes from genetic variants. In this framework, interpretable and memory-efficient neural network architectures are constructed by embedding biologically knowledge from public databases, resulting in neural networks that contain only biologically plausible connections. We applied the framework to seventeen phenotypes and found well-replicated genes such as HERC2 and OCA2 for hair and eye color, and novel genes such as ZNF773 and PCNT for schizophrenia. Additionally, the framework identified ubiquitin mediated proteolysis, endocrine system and viral infectious diseases as most predictive biological pathways for schizophrenia. GenNet is a freely available, end-to-end deep learning framework that allows researchers to develop and use interpretable neural networks to obtain novel insights into the genetic architecture of complex traits and diseases. van Hilten and colleagues present GenNet, a deep-learning framework for predicting phenotype from genetic data. This framework generates interpretable neural networks that provide insight into the genetic basis of complex traits and diseases. [ABSTRACT FROM AUTHOR]
Published: 2021
Full Text: View/download PDF

45. Tinnitus and Its Central Correlates: A Neuroimaging Study in a Large Aging Population.

Author: Oosterloo, Berthe C., Croll, Pauline H., Goedegebure, André, Roshchupkin, Gennady V., Baatenburg de Jong, Robert J., Arfan Ikram, M., Vernooij, Meike W., and Ikram, M Arfan
Published: 2021
Full Text: View/download PDF

46. Lung Function Impairment and the Risk of Incident Dementia: The Rotterdam Study.

Author: Xiao, Tian, Wijnant, Sara R.A., Licher, Silvan, Terzikhan, Natalie, Lahousse, Lies, Ikram, M. Kamran, Brusselle, Guy G., Ikram, M. Arfan, Kamran Ikram, M, and Arfan Ikram, M
Subjects: OBSTRUCTIVE lung diseases, SYSTOLIC blood pressure, ALZHEIMER'S disease, DEMENTIA, APOLIPOPROTEIN E
Abstract: Background: The etiology of dementia may partly be underpinned by impaired lung function via systemic inflammation and hypoxia.Objective: To prospectively examine the association between chronic obstructive pulmonary disease (COPD) and subclinical impairments in lung function and the risk of dementia.Methods: In the Rotterdam Study, we assessed the risk of incident dementia in participants with Preserved Ratio Impaired Spirometry (PRISm; FEV1/FVC≥0.7, FEV1 < 80% predicted) and in participants with COPD (FEV1/FVC < 0.7) compared to those with normal spirometry (controls; FEV1/FVC≥0.7, FEV1≥80% predicted). Hazard ratios (HRs) with 95% confidence intervals (CI) for dementia were adjusted for age, sex, education attainment, smoking status, systolic blood pressure, body mass index, triglycerides, comorbidities and Apolipoprotein E (APOE) genotype.Results: Of 4,765 participants, 110 (2.3%) developed dementia after 3.3 years. Compared to controls, participants with PRISm, but not COPD, had an increased risk for all-type dementia (adjusted HRPRISm 2.70; 95% CI, 1.53-4.75; adjusted HRCOPD 1.03; 95% CI, 0.61-1.74). These findings were primarily driven by men and smokers. Similarly, participants with FVC% predicted values in the lowest quartile compared to those in the highest quartile were at increased risk of all-type dementia (adjusted HR 2.28; 95% CI, 1.31-3.98), as well as Alzheimer's disease (AD; adjusted HR 2.13; 95% CI, 1.13-4.02).Conclusion: Participants with PRISm or a low FVC% predicted lung function were at increased risk of dementia, compared to those with normal spirometry or a higher FVC% predicted, respectively. Further research is needed to elucidate whether this association is causal and how PRISm might contribute to dementia pathogenesis. [ABSTRACT FROM AUTHOR]
Published: 2021
Full Text: View/download PDF

47. Dietary patterns and changes in frailty status: the Rotterdam study

Author: Haas, S.C.M. de, Jonge, E.A.L. de, Voortman, T., Steenweg-de Graaff, J., Franco, O.H., Arfan Ikram, M., Rivadeneira, F., Kiefte-de Jong, J.C., Schoufour, J.D., de, Haas S.C.M., Graaff, J.S., Ikram, M.A., Kiefte-de, Jong J.C., Epidemiology, and Internal Medicine
Subjects: 0301 basic medicine, Gerontology, Male, Population, Frailty Index, Medicine (miscellaneous), Whole grains, 03 medical and health sciences, Rotterdam Study, 0302 clinical medicine, Elderly, Surveys and Questionnaires, Linear regression, Vegetables, Medicine, Humans, 030212 general & internal medicine, Dietary patterns, education, education.field_of_study, 030109 nutrition & dietetics, Nutrition and Dietetics, Frailty index, Food frequency, Frailty, business.industry, Feeding Behavior, Original Contribution, Middle Aged, Diet, General state, Cross-Sectional Studies, Diet quality, Fruit, Female, business, Demography
Abstract: Purpose To determine the associations between a priori and a posteriori derived dietary patterns and a general state of health, measured as the accumulation of deficits in a frailty index. Methods Cross-sectional and longitudinal analysis embedded in the population-based Rotterdam Study (n = 2632) aged 45 years. Diet was assessed at baseline (year 2006) using food frequency questionnaires. Dietary patterns were defined a priori using an existing index reflecting adherence to national dietary guidelines and a posteriori using principal component analysis. A frailty index was composed of 38 health deficits and measured at baseline and follow-up (4 years later). Linear regression analyses were performed using adherence to each of the dietary patterns as exposure and the frailty index as outcome (all in Z-scores). Results Adherence to the national dietary guidelines was associated with lower frailty at baseline (β −0.05, 95% CI −0.08, −0.02). Additionally, high adherence was associated with lower frailty scores over time (β −0.08, 95% CI −0.12, −0.04). The PCA revealed three dietary patterns that we named a “Traditional” pattern, high in legumes, eggs and savory snacks; a “Carnivore” pattern, high in meat and poultry; and a “Health Conscious” pattern, high in whole grain products, vegetables and fruit. In the cross-sectional analyses adherence to these patterns was not associated with frailty. However, adherence to the “Traditional” pattern was associated with less frailty over time (β −0.09, 95% CI −0.14, −0.05). Conclusion No associations were found for adherence to a “healthy” pattern or “Carnivore” pattern. However, Even in a population that is relatively young and healthy, adherence to dietary guidelines or adherence to the Traditional pattern could help to prevent, delay or reverse frailty levels. Electronic supplementary material The online version of this article (doi:10.1007/s00394-017-1509-9) contains supplementary material, which is available to authorized users.
Published: 2018
Full Text: View/download PDF

48. Molecular genetic overlap between migraine and major depressive disorder

Author: Yang, Y, Zhao, H, Boomsma, DI, Ligthart, L, Belin, AC, Davey Smith, G, Esko, T, Freilinger, TM, Folkmann Hansen, T, Arfan Ikram, M, Kallela, M, Kubisch, C, Paraskevi, C, Strachan, DP, Wessman, M, The International Headache Genetics Consortium, van de Maagdenberg, AMJM, Terwindt, GM, and Nyholt, DR
Abstract: Migraine and major depressive disorder (MDD) are common brain disorders that frequently co-occur. Despite epidemiological evidence that migraine and MDD share a genetic basis, their overlap at the molecular genetic level has not been thoroughly investigated. Using single-nucleotide polymorphism (SNP) and gene-based analysis of genome-wide association study (GWAS) genotype data, we found significant genetic overlap across the two disorders. LD Score regression revealed a significant SNP-based heritability for both migraine (h2 = 12%) and MDD (h2 = 19%), and a significant cross-disorder genetic correlation (rG = 0.25; P = 0.04). Meta-analysis of results for 8,045,569 SNPs from a migraine GWAS (comprising 30,465 migraine cases and 143,147 control samples) and the top 10,000 SNPs from a MDD GWAS (comprising 75,607 MDD cases and 231,747 healthy controls), implicated three SNPs (rs146377178, rs672931, and rs11858956) with novel genome-wide significant association (PSNP ≤ 5 × 10−8) to migraine and MDD. Moreover, gene-based association analyses revealed significant enrichment of genes nominally associated (Pgene-based ≤ 0.05) with both migraine and MDD (Pbinomial-test = 0.001). Combining results across migraine and MDD, two genes, ANKDD1B and KCNK5, produced Fisher’s combined gene-based P values that surpassed the genome-wide significance threshold (PFisher’s-combined ≤ 3.6 × 10−6). Pathway analysis of genes with PFisher’s-combined ≤ 1 × 10−3 suggested several pathways, foremost neural-related pathways of signalling and ion channel regulation, to be involved in migraine and MDD aetiology. In conclusion, our study provides strong molecular genetic support for shared genetically determined biological mechanisms underlying migraine and MDD.
Published: 2018

49. Genome-wide association meta-analysis of individuals of European ancestry identifies new loci explaining a substantial fraction of hair color variation and heritability

Author: Valdes, Ana M., Hysi, Pirro G., Liu, Fan, Furlotte, Nicholas A., Evans, David M., Bataille, Veronique, Visconti, Alessia, Hemani, Gibran, McMahon, George, Ring, Susan M., Smith, George Davey, Duffy, David L., Zhu, Gu, Gordon, Scott D., Medland, Sarah E., Lin, Bochao D., Willemsen, Gonneke, Hottenga, Jouke Jan, Vuckovic, Dragana, Girotto, Giorgia, Gandin, Ilaria, Sala, Cinzia, Pina Concas, Maria, Brumat, Marco, Gasparini, Paolo, Toniolo, Daniela, Cocca, Massimiliano, Robino, Antonietta, Yazar, Seyhan, Hewitt, Alex W., Chen, Yan, Zeng, Changqing, Uitterlinden, Andre G., Arfan Ikram, M., Hamer, Merel A., van Duijn, Cornelia M., Nijsten, Tamar, Mackey, David A., Falchi, Mario, Boomsma, Dorret I., Martin, Nicholas G., Hinds, David A., Kayser, Manfred, Spector, Timothy D., and International Visible Trait Genetics Consortium
Subjects: integumentary system, sense organs
Abstract: © 2018 The Author(s). Hair color is one of the most recognizable visual traits in European populations and is under strong genetic control. Here we report the results of a genome-wide association study meta-analysis of almost 300,000 participants of European descent. We identified 123 autosomal and one X-chromosome loci significantly associated with hair color; all but 13 are novel. Collectively, single-nucleotide polymorphisms associated with hair color within these loci explain 34.6% of red hair, 24.8% of blond hair, and 26.1% of black hair heritability in the study populations. These results confirm the polygenic nature of complex phenotypes and improve our understanding of melanin pigment metabolism in humans.
Published: 2018

50. Predictive value for cardiovascular events of common carotid intima media thickness and its rate of change in individuals at high cardiovascular risk – Results from the PROG-IMT collaboration

Author: Lorenz, Matthias W., Gao, Lu, Ziegelbauer, Kathrin, Norata, Giuseppe Danilo, Empana, Jean Philippe, Schmidtmann, Irene, Lin, Hung Ju, McLachlan, Stela, Bokemark, Lena, Ronkainen, Kimmo, Amato, Mauro, Schminke, Ulf, Srinivasan, Sathanur R., Lind, Lars, Okazaki, Shuhei, Stehouwer, Coen D.A., Willeit, Peter, Polak, Joseph F., Steinmetz, Helmuth, Sander, Dirk, Poppert, Holger, Desvarieux, Moise, Arfan Ikram, M., Johnsen, Stein Harald, Staub, Daniel, Sirtori, Cesare R., Iglseder, Bernhard, Beloqui, Oscar, Engström, Gunnar, Friera, Alfonso, Rozza, Francesco, Xie, Wuxiang, Parraga, Grace, Grigore, Liliana, Plichart, Matthieu, Blankenberg, Stefan, Su, Ta Chen, Schmidt, Caroline, Tuomainen, Tomi Pekka, Veglia, Fabrizio, Völzke, Henry, Nijpels, Giel, Willeit, Johann, Sacco, Ralph L., Franco, Oscar H., Uthoff, Heiko, Hedblad, Bo, Suarez, Carmen, Izzo, Raffaele, Bots, Michiel L., and on behalf of the PROG-IMT study group
Subjects: Agricultural and Biological Sciences(all), Biochemistry, Genetics and Molecular Biology(all)
Abstract: Aims Carotid intima media thickness (CIMT) predicts cardiovascular (CVD) events, but the predictive value of CIMT change is debated. We assessed the relation between CIMT change and events in individuals at high cardiovascular risk. Methods and results From 31 cohorts with two CIMT scans (total n = 89070) on average 3.6 years apart and clinical follow-up, subcohorts were drawn: (A) individuals with at least 3 cardiovascular risk factors without previous CVD events, (B) individuals with carotid plaques without previous CVD events, and (C) individuals with previous CVD events. Cox regression models were fit to estimate the hazard ratio (HR) of the combined endpoint (myocardial infarction, stroke or vascular death) per standard deviation (SD) of CIMT change, adjusted for CVD risk factors. These HRs were pooled across studies. In groups A, B and C we observed 3483, 2845 and 1165 endpoint events, respectively. Average common CIMT was 0.79mm (SD 0.16mm), and annual common CIMT change was 0.01mm (SD 0.07mm), both in group A. The pooled HR per SD of annual common CIMT change (0.02 to 0.43mm) was 0.99 (95% confidence interval: 0.95–1.02) in group A, 0.98 (0.93–1.04) in group B, and 0.95 (0.89–1.04) in group C. The HR per SD of common CIMT (average of the first and the second CIMT scan, 0.09 to 0.75mm) was 1.15 (1.07–1.23) in group A, 1.13 (1.05–1.22) in group B, and 1.12 (1.05–1.20) in group C. Conclusions We confirm that common CIMT is associated with future CVD events in individuals at high risk. CIMT change does not relate to future event risk in high-risk individuals.
Published: 2018

Catalog

Books, media, physical & digital resources

See catalog results

Searchworks

Select search scope, currently: Articles Catalog books, media & more in Jio Institute collections Articles journal articles & other e-resources

Search

Search Constraints

Refine your results

Search Limiters

Topic

Publication Year Range

Language

Publication Type

Journal

Region

Database

Publisher

181 results on '"Arfan Ikram M."'

Search Results

Catalog

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources