Browsing by Author "Medland, Sarah"

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    Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning
    (Springer Nature, 2022) Lahti, Jari; Tuominen, Samuli; Yang, Qiong; Pergola, Giulio; Ahmad, Shahzad; Amin, Najaf; Armstrong, Nicola J.; Beiser, Alexa; Bey, Katharina; Bis, Joshua C.; Boerwinkle, Eric; Bressler, Jan; Campbell, Archie; Campbell, Harry; Chen, Qiang; Corley, Janie; Cox, Simon R.; Davies, Gail; De Jager, Philip L.; Derks, Eske M.; Faul, Jessica D.; Fitzpatrick, Annette L.; Fohner, Alison E.; Ford, Ian; Fornage, Myriam; Gerring, Zachary; Grabe, Hans J.; Grodstein, Francine; Gudnason, Vilmundur; Simonsick, Eleanor; Holliday, Elizabeth G.; Joshi, Peter K.; Kajantie, Eero; Kaprio, Jaakko; Karell, Pauliina; Kleineidam, Luca; Knol, Maria J.; Kochan, Nicole A.; Kwok, John B.; Leber, Markus; Lam, Max; Lee, Teresa; Li, Shuo; Loukola, Anu; Luck, Tobias; Marioni, Riccardo E.; Mather, Karen A.; Medland, Sarah; Mirza, Saira S.; Nalls, Mike A.; Nho, Kwangsik; O'Donnell, Adrienne; Oldmeadow, Christopher; Painter, Jodie; Pattie, Alison; Reppermund, Simone; Risacher, Shannon L.; Rose, Richard J.; Sadashivaiah, Vijay; Scholz, Markus; Satizabal, Claudia L.; Schofield, Peter W.; Schraut, Katharina E.; Scott, Rodney J.; Simino, Jeannette; Smith, Albert V.; Smith, Jennifer A.; Stott, David J.; Surakka, Ida; Teumer, Alexander; Thalamuthu, Anbupalam; Trompet, Stella; Turner, Stephen T.; van der Lee, Sven J.; Villringer, Arno; Völker, Uwe; Wilson, Robert S.; Wittfeld, Katharina; Vuoksimaa, Eero; Xia, Rui; Yaffe, Kristine; Yu, Lei; Zare, Habil; Zhao, Wei; Ames, David; Attia, John; Bennett, David A.; Brodaty, Henry; Chasman, Daniel I.; Goldman, Aaron L.; Hayward, Caroline; Ikram, M. Arfan; Jukema, J. Wouter; Kardia, Sharon L.R.; Lencz, Todd; Loeffler, Markus; Mattay, Venkata S.; Palotie, Aarno; Psaty, Bruce M.; Ramirez, Alfredo; Ridker, Paul M.; Riedel-Heller, Steffi G.; Sachdev, Perminder S.; Saykin, Andrew J.; Scherer, Martin; Schofield, Peter R.; Sidney, Stephen; Starr, John M.; Trollor, Julian; Ulrich, William; Wagner, Michael; Weir, David R.; Wilson, James F.; Wright, Margaret J.; Weinberger, Daniel R.; Debette, Stephanie; Eriksson, Johan G.; Mosley, Thomas H., Jr.; Launer, Lenore J.; van Duijn, Cornelia M.; Deary, Ian J.; Seshadri, Sudha; Räikkönen, Katri; Radiology and Imaging Sciences, School of Medicine
    Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.
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    Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization
    (bioRxiv, 2023-12-02) Ge, Ruiyang; Yu, Yuetong; Qi, Yi Xuan; Fan, Yunan Vera; Chen, Shiyu; Gao, Chuntong; Haas, Shalaila S.; Modabbernia, Amirhossein; New, Faye; Agartz, Ingrid; Asherson, Philip; Ayesa-Arriola, Rosa; Banaj, Nerisa; Banaschewski, Tobias; Baumeister, Sarah; Bertolino, Alessandro; Boomsma, Dorret I.; Borgwardt, Stefan; Bourque, Josiane; Brandeis, Daniel; Breier, Alan; Brodaty, Henry; Brouwer, Rachel M.; Buckner, Randy; Buitelaar, Jan K.; Cannon, Dara M.; Caseras, Xavier; Cervenka, Simon; Conrod, Patricia J.; Crespo-Facorro, Benedicto; Crivello, Fabrice; Crone, Eveline A.; de Haan, Liewe; de Zubicaray, Greig I.; Di Giorgio, Annabella; Erk, Susanne; Fisher, Simon E.; Franke, Barbara; Frodl, Thomas; Glahn, David C.; Grotegerd, Dominik; Gruber, Oliver; Gruner, Patricia; Gur, Raquel E.; Gur, Ruben C.; Harrison, Ben J.; Hatton, Sean N.; Hickie, Ian; Howells, Fleur M.; Hulshoff Pol, Hilleke E.; Huyser, Chaim; Jernigan, Terry L.; Jiang, Jiyang; Joska, John A.; Kahn, René S.; Kalnin, Andrew J.; Kochan, Nicole A.; Koops, Sanne; Kuntsi, Jonna; Lagopoulos, Jim; Lazaro, Luisa; Lebedeva, Irina S.; Lochner, Christine; Martin, Nicholas G.; Mazoyer, Bernard; McDonald, Brenna C.; McDonald, Colm; McMahon, Katie L.; Nakao, Tomohiro; Nyberg, Lars; Piras, Fabrizio; Portella, Maria J.; Qiu, Jiang; Roffman, Joshua L.; Sachdev, Perminder S.; Sanford, Nicole; Satterthwaite, Theodore D.; Saykin, Andrew J.; Schumann, Gunter; Sellgren, Carl M.; Sim, Kang; Smoller, Jordan W.; Soares, Jair; Sommer, Iris E.; Spalletta, Gianfranco; Stein, Dan J.; Tamnes, Christian K.; Thomopolous, Sophia I.; Tomyshev, Alexander S.; Tordesillas-Gutiérrez, Diana; Trollor, Julian N.; van 't Ent, Dennis; van den Heuvel, Odile A.; van Erp, Theo Gm.; van Haren, Neeltje Em.; Vecchio, Daniela; Veltman, Dick J.; Walter, Henrik; Wang, Yang; Weber, Bernd; Wei, Dongtao; Wen, Wei; Westlye, Lars T.; Wierenga, Lara M.; Williams, Steven Cr.; Wright, Margaret J.; Medland, Sarah; Wu, Mon-Ju; Yu, Kevin; Jahanshad, Neda; Thompson, Paul M.; Frangou, Sophia; Psychiatry, School of Medicine
    We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/).