Browsing by Author "Garavan, Hugh"

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    ENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide
    (Elsevier, 2017-01-15) Thompson, Paul M.; Andreassen, Ole A.; Arias-Vasquez, Alejandro; Bearden, Carrie E.; Boedhoe, Premika S.; Brouwer, Rachel M.; Buckner, Randy L.; Buitelaar, Jan K.; Bulayeva, Kazima B.; Cannon, Dara M.; Cohen, Ronald A.; Conrod, Patricia J.; Dale, Anders M.; Deary, Ian J.; Dennis, Emily L.; de Reus, Marcel A.; Desrivieres, Sylvane; Dima, Danai; Donohoe, Gary; Fisher, Simon E.; Fouche, Jean-Paul; Francks, Clyde; Frangou, Sophia; Franke, Barbara; Ganjgahi, Habib; Garavan, Hugh; Glahn, David C.; Grabe, Hans J.; Guadalupe, Tulio; Gutman, Boris A.; Hashimoto, Ryota; Hibar, Derrek P.; Holland, Dominic; Hoogman, Martine; Pol, Hilleke E. Hulshoff; Hosten, Norbert; Jahanshad, Neda; Kelly, Sinead; Kochunov, Peter; Kremen, William S.; Lee, Phil H.; Mackey, Scott; Martin, Nicholas G.; Mazoyer, Bernard; McDonald, Colm; Medland, Sarah E.; Morey, Rajendra A.; Nichols, Thomas E.; Paus, Tomas; Pausova, Zdenka; Schmaal, Lianne; Schumann, Gunter; Shen, Li; Sisodiya, Sanjay M.; Smit, Dirk J.A.; Smoller, Jordan W.; Stein, Dan J.; Stein, Jason L.; Toro, Roberto; Turner, Jessica A.; Heuvel, Martijn P. van den; Heuvel, Odile L. van den; Erp, Theo G.M. van; Rooij, Daan van; Veltman, Dick J.; Walter, Henrik; Wang, Yalin; Wardlaw, Joanna M.; Whelan, Christopher D.; Wright, Margaret J.; Ye, Jieping; ENIGMA Consortium; Radiology and Imaging Sciences, School of Medicine
    In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) – a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date – of schizophrenia and major depression – ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others1, ENIGMA's genomic screens – now numbering over 30,000 MRI scans – have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants – and genetic variants in general – may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures – from tens of thousands of people – that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.
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    Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group
    (Springer Nature, 2021) Jia, Tianye; Chu, Congying; Liu, Yun; Van Dongen, Jenny; Papastergios, Evangelos; Armstrong, Nicola J.; Bastin, Mark E.; Carrillo-Roa, Tania; den Braber, Anouk; Harris, Mathew; Jansen, Rick; Liu, Jingyu; Luciano, Michelle; Ori, Anil P.S.; Santiañez, Roberto Roiz; Ruggeri, Barbara; Sarkisyan, Daniil; Shin, Jean; Sungeun, Kim; Tordesillas Gutiérrez, Diana; van't Ent, Dennis; Ames, David; Artiges, Eric; Bakalkin, Georgy; Banaschewski, Tobias; Bokde, Arun L.W.; Brodaty, Henry; Bromberg, Uli; Brouwer, Rachel; Büchel, Christian; Burke Quinlan, Erin; Cahn, Wiepke; de Zubicaray, Greig I.; Ehrlich, Stefan; Ekström, Tomas J.; Flor, Herta; Fröhner, Juliane H.; Frouin, Vincent; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Hoare, Jacqueline; Ittermann, Bernd; Jahanshad, Neda; Jiang, Jiyang; Kwok, John B.; Martin, Nicholas G.; Martinot, Jean-Luc; Mather, Karen A.; McMahon, Katie L.; McRae, Allan F.; Nees, Frauke; Orfanos, Dimitri Papadopoulos; Paus, Tomáš; Poustka, Luise; Sämann, Philipp G.; Schofield, Peter R.; Smolka, Michael N.; Stein, Dan J.; Strike, Lachlan T.; Teeuw, Jalmar; Thalamuthu, Anbupalam; Trollor, Julian; Walter, Henrik; Wardlaw, Joanna M.; Wen, Wei; Whelan, Robert; Apostolova, Liana G.; Binder, Elisabeth B.; Boomsma, Dorret I.; Calhoun, Vince; Crespo-Facorro, Benedicto; Deary, Ian J.; Hulshoff Pol, Hilleke; Ophoff, Roel A.; Pausova, Zdenka; Sachdev, Perminder S.; Saykin, Andrew; Wright, Margaret J.; Thompson, Paul M.; Schumann, Gunter; Desrivières, Sylvane; Radiology and Imaging Sciences, School of Medicine
    DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)—three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions.