Person: Holmes, A
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Publication Dopamine Genetic Risk Score Predicts Depressive Symptoms in Healthy Adults and Adults with Depression
(Public Library of Science, 2014) Pearson-Fuhrhop, Kristin M.; Dunn, Erin; Mortero, Sarah; Devan, William J.; Falcone, Guido J.; Lee, Phil; Holmes, A; Hollinshead, Marisa O.; Roffman, Joshua; Smoller, Jordan; Rosand, Jonathan; Cramer, Steven C.Background: Depression is a common source of human disability for which etiologic insights remain limited. Although abnormalities of monoamine neurotransmission, including dopamine, are theorized to contribute to the pathophysiology of depression, evidence linking dopamine-related genes to depression has been mixed. The current study sought to address this knowledge-gap by examining whether the combined effect of dopamine polymorphisms was associated with depressive symptomatology in both healthy individuals and individuals with depression. Methods: Data were drawn from three independent samples: (1) a discovery sample of healthy adult participants (n = 273); (2) a replication sample of adults with depression (n = 1,267); and (3) a replication sample of healthy adult participants (n = 382). A genetic risk score was created by combining functional polymorphisms from five genes involved in synaptic dopamine availability (COMT and DAT) and dopamine receptor binding (DRD1, DRD2, DRD3). Results: In the discovery sample, the genetic risk score was associated with depressive symptomatology (β = −0.80, p = 0.003), with lower dopamine genetic risk scores (indicating lower dopaminergic neurotransmission) predicting higher levels of depression. This result was replicated with a similar genetic risk score based on imputed genetic data from adults with depression (β = −0.51, p = 0.04). Results were of similar magnitude and in the expected direction in a cohort of healthy adult participants (β = −0.86, p = 0.15). Conclusions: Sequence variation in multiple genes regulating dopamine neurotransmission may influence depressive symptoms, in a manner that appears to be additive. Further studies are required to confirm the role of genetic variation in dopamine metabolism and depression.
Publication The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data
(Springer US, 2014) Thompson, Paul M.; Stein, Jason L.; Medland, Sarah E.; Hibar, Derrek P.; Vasquez, Alejandro Arias; Renteria, Miguel E.; Toro, Roberto; Jahanshad, Neda; Schumann, Gunter; Franke, Barbara; Wright, Margaret J.; Martin, Nicholas G.; Agartz, Ingrid; Alda, Martin; Alhusaini, Saud; Almasy, Laura; Almeida, Jorge; Alpert, Kathryn; Andreasen, Nancy C.; Andreassen, Ole A.; Apostolova, Liana G.; Appel, Katja; Armstrong, Nicola J.; Aribisala, Benjamin; Bastin, Mark E.; Bauer, Michael; Bearden, Carrie E.; Bergmann, Ørjan; Binder, Elisabeth B.; Blangero, John; Bockholt, Henry J.; Bøen, Erlend; Bois, Catherine; Boomsma, Dorret I.; Booth, Tom; Bowman, Ian J.; Bralten, Janita; Brouwer, Rachel M.; Brunner, Han G.; Brohawn, David G.; Buckner, Randy; Buitelaar, Jan; Bulayeva, Kazima; Bustillo, Juan R.; Calhoun, Vince D.; Cannon, Dara M.; Cantor, Rita M.; Carless, Melanie A.; Caseras, Xavier; Cavalleri, Gianpiero L.; Chakravarty, M. Mallar; Chang, Kiki D.; Ching, Christopher R. K.; Christoforou, Andrea; Cichon, Sven; Clark, Vincent P.; Conrod, Patricia; Coppola, Giovanni; Crespo-Facorro, Benedicto; Curran, Joanne E.; Czisch, Michael; Deary, Ian J.; de Geus, Eco J. C.; den Braber, Anouk; Delvecchio, Giuseppe; Depondt, Chantal; de Haan, Lieuwe; de Zubicaray, Greig I.; Dima, Danai; Dimitrova, Rali; Djurovic, Srdjan; Dong, Hongwei; Donohoe, Gary; Duggirala, Ravindranath; Dyer, Thomas D.; Ehrlich, Stefan; Ekman, Carl Johan; Elvsåshagen, Torbjørn; Emsell, Louise; Erk, Susanne; Espeseth, Thomas; Fagerness, Jesen; Fears, Scott; Fedko, Iryna; Fernández, Guillén; Fisher, Simon E.; Foroud, Tatiana; Fox, Peter T.; Francks, Clyde; Frangou, Sophia; Frey, Eva Maria; Frodl, Thomas; Frouin, Vincent; Garavan, Hugh; Giddaluru, Sudheer; Glahn, David C.; Godlewska, Beata; Goldstein, Rita Z.; Gollub, Randy; Grabe, Hans J.; Grimm, Oliver; Gruber, Oliver; Guadalupe, Tulio; Gur, Raquel E.; Gur, Ruben C.; Göring, Harald H. H.; Hagenaars, Saskia; Hajek, Tomas; Hall, Geoffrey B.; Hall, Jeremy; Hardy, John; Hartman, Catharina A.; Hass, Johanna; Hatton, Sean N.; Haukvik, Unn K.; Hegenscheid, Katrin; Heinz, Andreas; Hickie, Ian B.; Ho, Beng-Choon; Hoehn, David; Hoekstra, Pieter J.; Hollinshead, Marisa; Holmes, A; Homuth, Georg; Hoogman, Martine; Hong, L. Elliot; Hosten, Norbert; Hottenga, Jouke-Jan; Hulshoff Pol, Hilleke E.; Hwang, Kristy S.; Jack, Clifford R.; Jenkinson, Mark; Johnston, Caroline; Jönsson, Erik G.; Kahn, René S.; Kasperaviciute, Dalia; Kelly, Sinead; Kim, Sungeun; Kochunov, Peter; Koenders, Laura; Krämer, Bernd; Kwok, John B. J.; Lagopoulos, Jim; Laje, Gonzalo; Landen, Mikael; Landman, Bennett A.; Lauriello, John; Lawrie, Stephen M.; Lee, Phil; Le Hellard, Stephanie; Lemaître, Herve; Leonardo, Cassandra D.; Li, Chiang-shan; Liberg, Benny; Liewald, David C.; Liu, Xinmin; Lopez, Lorna M.; Loth, Eva; Lourdusamy, Anbarasu; Luciano, Michelle; Macciardi, Fabio; Machielsen, Marise W. J.; MacQueen, Glenda M.; Malt, Ulrik F.; Mandl, René; Manoach, Dara; Martinot, Jean-Luc; Matarin, Mar; Mather, Karen A.; Mattheisen, Manuel; Mattingsdal, Morten; Meyer-Lindenberg, Andreas; McDonald, Colm; McIntosh, Andrew M.; McMahon, Francis J.; McMahon, Katie L.; Meisenzahl, Eva; Melle, Ingrid; Milaneschi, Yuri; Mohnke, Sebastian; Montgomery, Grant W.; Morris, Derek W.; Moses, Eric K.; Mueller, Bryon A.; Muñoz Maniega, Susana; Mühleisen, Thomas W.; Müller-Myhsok, Bertram; Mwangi, Benson; Nauck, Matthias; Nho, Kwangsik; Nichols, Thomas E.; Nilsson, Lars-Göran; Nugent, Allison C.; Nyberg, Lars; Olvera, Rene L.; Oosterlaan, Jaap; Ophoff, Roel A.; Pandolfo, Massimo; Papalampropoulou-Tsiridou, Melina; Papmeyer, Martina; Paus, Tomas; Pausova, Zdenka; Pearlson, Godfrey D.; Penninx, Brenda W.; Peterson, Charles P.; Pfennig, Andrea; Phillips, Mary; Pike, G. Bruce; Poline, Jean-Baptiste; Potkin, Steven G.; Pütz, Benno; Ramasamy, Adaikalavan; Rasmussen, Jerod; Rietschel, Marcella; Rijpkema, Mark; Risacher, Shannon L.; Roffman, Joshua; Roiz-Santiañez, Roberto; Romanczuk-Seiferth, Nina; Rose, Emma J.; Royle, Natalie A.; Rujescu, Dan; Ryten, Mina; Sachdev, Perminder S.; Salami, Alireza; Satterthwaite, Theodore D.; Savitz, Jonathan; Saykin, Andrew J.; Scanlon, Cathy; Schmaal, Lianne; Schnack, Hugo G.; Schork, Andrew J.; Schulz, S. Charles; Schür, Remmelt; Seidman, Larry Joel; Shen, Li; Shoemaker, Jody M.; Simmons, Andrew; Sisodiya, Sanjay M.; Smith, Colin; Smoller, Jordan; Soares, Jair C.; Sponheim, Scott R.; Sprooten, Emma; Starr, John M.; Steen, Vidar M.; Strakowski, Stephen; Strike, Lachlan; Sussmann, Jessika; Sämann, Philipp G.; Teumer, Alexander; Toga, Arthur W.; Tordesillas-Gutierrez, Diana; Trabzuni, Daniah; Trost, Sarah; Turner, Jessica; Van den Heuvel, Martijn; van der Wee, Nic J.; van Eijk, Kristel; van Erp, Theo G. M.; van Haren, Neeltje E. M.; van ‘t Ent, Dennis; van Tol, Marie-Jose; Valdés Hernández, Maria C.; Veltman, Dick J.; Versace, Amelia; Völzke, Henry; Walker, Robert; Walter, Henrik; Wang, Lei; Wardlaw, Joanna M.; Weale, Michael E.; Weiner, Michael W.; Wen, Wei; Westlye, Lars T.; Whalley, Heather C.; Whelan, Christopher D.; White, Tonya; Winkler, Anderson M.; Wittfeld, Katharina; Woldehawariat, Girma; Wolf, Christiane; Zilles, David; Zwiers, Marcel P.; Thalamuthu, Anbupalam; Schofield, Peter R.; Freimer, Nelson B.; Lawrence, Natalia S.; Drevets, WayneThe Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA’s first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.