The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

Springer Science and Business Media LLC - Tập 8 Số 2 - Trang 153-182 - 2014
Paul M. Thompson1, Jason L. Stein2, Sarah E. Medland3, Derrek P. Hibar1, Alejandro Arias Vásquez4, Miguel E. Rentería3, Roberto Toro5, Neda Jahanshad1, Günter Schumann6, Barbara Franke4, Margaret J. Wright7, Nicholas G. Martin8, Ingrid Agartz9, Martin Alda10, Saud Alhusaini11, Laura Almasy12, Jorge Almeida13, Kathryn Alpert14, Nancy C. Andreasen15, Ole A. Andreassen16, Liana G. Apostolova17, Katja Appel18, Nicola J. Armstrong19, Benjamin S. Aribisala20, Mark E. Bastin20, Michael Bauer21, Carrie E. Bearden22, Ørjan Bergmann23, Elisabeth B. Binder24, John Blangero12, H. Jeremy Bockholt25, Erlend Bøen26, Catherine Bois27, Dorret I. Boomsma28, Tom Booth20, Ian Bowman1, Janita Bralten29, Rachel M. Brouwer30, Han G. Brunner4, David G. Brohawn31, Randy L. Buckner32, Jan K. Buitelaar29, Kazima Bulayeva33, Juan Bustillo34, Vince D. Calhoun35, Dara M. Cannon36, Rita M. Cantor37, Melanie A. Carless12, Xavier Caseras38, Gianpiero L. Cavalleri11, M. Mallar Chakravarty39, Kiki Chang40, Christopher R. K. Ching1, Andrea Christoforou16, Sven Cichon41, Vincent P. Clark42, Patricia Conrod43, Giovanni Coppola17, Benedicto Crespo‐Facorro44, Joanne E. Curran12, Michael Czisch24, Ian J. Deary20, Eco J. C. de Geus28, Anouk den Braber28, Giuseppe Delvecchio6, Chantal Depondt45, Michael Steffens46, Greig I. de Zubicaray47, Danai Dima6, Ralica Dimitrova27, Srdjan Djurovic16, Hong‐Wei Dong1, Gary Donohoe36, Ravindranath Duggirala12, Thomas D. Dyer12, Stefan Ehrlich48, Carl Johan Ekman9, Torbjørn Elvsåshagen26, Louise Emsell36, Susanne Erk49, Thomas Espeseth16, Jesen Fagerness32, Scott C. Fears37, Iryna O. Fedko28, Guillén Fernández50, Simon E. Fisher29, Tatiana Foroud51, Peter T. Fox52, Clyde Francks29, Sophia Frangou53, Eva Frey54, Thomas Frodl54, Vincent Frouin55, Andreas Heinz56, Sudheer Giddaluru57, David C. Glahn58, Beata R. Godlewska59, Rita Z. Goldstein60, Randy L. Gollub48, Hans J. Grabe18, O. Grimm61, Oliver Gruber62, Tulio Guadalupe63, Raquel E. Gur64, Ruben C. Gur64, Harald H.H. Göring12, Saskia P. Hagenaars27, Tomáš Hájek10, Geoffrey B. Hall65, Jérémy Hall27, John Hardy66, Catharina A. Hartman67, Johanna Haß68, Sean N. Hatton69, Unn K. Haukvik16, Katrin Hegenscheid70, Ian B. Hickie69, Beng‐Choon Ho15, David Hoehn24, Pieter J. Hoekstra67, Marisa O. Hollinshead48, Avram J. Holmes48, Georg Homuth71, Martine Hoogman4, Lijun Hong72, Norbert Hosten70, Jouke‐Jan Hottenga28, Hilleke E. Hulshoff Pol30, Kristy Hwang73, Clifford R. Jack74, Mark Jenkinson75, Caroline Johnston76, Erik G. Jönsson9, René S. Kahn30, Dalia Kasperavičiūtė77, Sinéad Kelly78, Sungeun Kim79, Peter Kochunov72, Laura Koenders46, Bernd Krämer62, John B. Kwok80, Jim Lagopoulos69, Gonzalo Laje81, Mikael Landén82, Bennett A. Landman83, John Lauriello84, Stephen M. Lawrie27, Phil H. Lee85, Stéphanie Le Hellard57, Hervé Lemaître86, Cassandra D. Leonardo1, Chiang-shan Li58, Benny Liberg9, David C. Liewald20, Xinmin Liu87, Lorna M. Lopez88, Eva Loth6, Anbarasu Lourdusamy89, Michelle Luciano20, Fabìo Macciardi90, Marise W. J. Machielsen46, Glenda MacQueen91, Ulrik Fredrik Malt26, René C.W. Mandl30, Dara S. Manoach85, Jean‐Luc Martinot86, Sebastian Guelfi77, Karen A. Mather92, Manuel Mattheisen93, Morten Mattingsdal94, Andreas Meyer‐Lindenberg61, Colm McDonald36, Andrew M. McIntosh27, Francis J. McMahon87, Katie L. McMahon95, Eva Meisenzahl96, Ingrid Melle16, Yuri Milaneschi46, Sebastian Mohnke49, Grant W. Montgomery97, Derek W. Morris78, Eric K. Moses98, Bryon A. Mueller99, Susana Muñoz Maniega100, Thomas W. Mühleisen101, Bertram Müller‐Myhsok24, Benson Mwangi102, Matthias Nauck103, Kwangsik Nho79, Thomas E. Nichols104, Lars Nilsson105, Allison C. Nugent106, Lars Nyberg107, Rene L. Olvera108, Jaap Oosterlaan109, Roel A. Ophoff37, Massimo Pandolfo45, Melina Papalampropoulou-Tsiridou27, Martina Papmeyer27, Tomáš Paus110, Zdenka Pausová111, Godfrey D. Pearlson18, Brenda W.J.H. Penninx112, Charles P. Peterson12, Andrea Pfennig21, Mary L. Phillips13, G. Bruce Pike113, Jean‐Baptiste Poline114, Steven G. Potkin90, Benno Pütz24, Adaikalavan Ramasamy115, Jerod M. Rasmussen90, Marcella Rietschel61, Mark Rijpkema29, Shannon L. Risacher79, Joshua L. Roffman85, Roberto Roiz‐Santiáñez116, Nina Romanczuk‐Seiferth49, Emma J. Rose117, Natalie A. Royle100, Dan Rujescu118, Mina Ryten66, Perminder S. Sachdev92, Alireza Salami107, Theodore D. Satterthwaite64, Jonathan Savitz119, Andrew J. Saykin79, Cathy Scanlon36, Lianne Schmaal112, Hugo G. Schnack30, Andrew J. Schork120, S. Charles Schulz99, Remmelt R. Schür30, Larry J. Seidman121, Li Shen79, Jody M. Shoemaker35, Andrew Simmons122, Sanjay M. Sisodiya77, Colin Smith123, Jordan W. Smoller31, Jair C. Soares102, Scott R. Sponheim99, Emma Sprooten58, John M. Starr124, Arno Villringer57, Stephen M. Strakowski125, Lachlan T. Strike97, Jessika E. Sussmann27, Philipp G. Sämann24, Alexander Teumer71, Arthur W. Toga1, Diana Tordesillas‐Gutiérrez116, Daniah Trabzuni66, Sarah Trost62, Jessica A. Turner126, Martijn P. van den Heuvel30, Nic J. van der Wee127, Kristel van Eijk128, Theo G.M. van Erp90, Neeltje E. M. van Haren30, Dennis van ’t Ent28, Marie‐José van Tol129, Maria C. Valdés Hernández100, Dick J. Veltman112, Amelia Versace13, Henry Völzke130, Robert Walker131, Henrik Walter132, Lei Wang14, Joanna M. Wardlaw100, Michael E. Weale115, Michael W. Weiner133, Wei Wen92, Lars T. Westlye134, Heather C. Whalley27, Christopher D. Whelan11, Tonya White135, Anderson M. Winkler75, Katharina Wittfeld136, Girma Woldehawariat87, Christiane Wolf24, David Zilles62, Marcel P. Zwiers137, Anbupalam Thalamuthu138, Peter R. Schofield139, Nelson B. Freimer140, Natalia Lawrence141, Wayne C. Drevets142
1Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA, 90033, USA
2Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, Netherlands
3QIMR Berghofer Medical Research Institute, Quantitative Genetics, Brisbane, Australia
4Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
5Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
6MRC-SGDP Centre, Institute of Psychiatry, King’s College London, London, UK
7QIMR Berghofer Medical Research Institute, Neuroimaging Genetics, Brisbane, Australia
8QIMR Berghofer Medical Research Institute, Genetic Epidemiology, Brisbane, Australia
9Department of Clinical Neuroscience, Karolinska Institutet and Hospital, Stockholm, Sweden
10Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
11Department of Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland
12Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
13Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
14Departments of Psychiatry and Behavioral Sciences and Radiology, Northwestern University, Chicago, IL, USA
15Department of Psychiatry, University of Iowa, Iowa City, IA, USA
16NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
17Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
18Department of Psychiatry and Psychotherapy, University of Greifswald, Greifswald, Germany
19School of Mathematics and Statistics, University of Sydney, Sydney, Australia
20Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
21Department of Psychiatry and Psychotherapy, Carl Gustav Carus University Hospital, Dresden, Germany
22Department of Psychiatry and Biobehavioral Sciences and the Center for Neurobehavioral Genetics, The Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA
23Institute of Clinical Medicine, University of Oslo, Oslo, Norway
24Max Planck Institute of Psychiatry, Munich, Germany
25Advanced Biomedical Informatics Group, llc., Iowa City, IA, USA
26Department of Psychosomatic Medicine, Oslo University Hospital, Oslo, Norway
27Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
28Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
29Donders Institute for Brain, Cognition, and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
30Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
31Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA
32Massachusetts General Hospital, Boston, MA, USA
33N.I. Vavilov Institute of General Genetics, Russian Academy of Sciences, Gubkin str. 3, Moscow 119991, Russia
34Department of Psychiatry, University of New Mexico, Albuquerque, NM, USA
35The Mind Research Network, Albuquerque, NM, USA
36Clinical Neuroimaging Laboratory, National University of Ireland Galway, University Road, Galway, Ireland
37Center for Neurobehavioral Genetics, University of California, Los Angeles, CA, USA
38MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
39The Kimel Family Translational Imaging Genetics Laboratory, The Centre for Addiction and Mental Health, Toronto, ON, Canada
40Department of Psychiatry, Stanford University School of Medicine, Stanford, CA, USA
41Institute of Human Genetics, University of Bonn, Bonn, Germany
42Department of Psychology, University of New Mexico, Albuquerque, NM, USA
43CHU Sainte Justine University Hospital Research Center, Montreal, QC, Canada
44Department of Psychiatry, Marqués de Valdecilla University Hospital, IFIMAV, School of Medicine, University of Cantabria, Santander, Spain
45Department of Neurology, Hopital Erasme, Universite Libre de Bruxelles, 1070, Brussels, Belgium
46EMGO Institute, VU University Medical Center, Amsterdam, The Netherlands
47School of Psychology, University of Queensland, Brisbane, Qld. 4072, Australia
48MGH/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
49Department of Psychiatry and Psychotherapy, Charité, Universitaetsmedizin Berlin, Charitè Campus Mitte, Berlin, Germany
50Department of Cognitive Neuroscience, Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands
51Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
52Research Imaging Institute, UT Health Science Center at San Antonio, San Antonio, TX, USA
53Psychosis Research Unit, Mount Sinai School of Medicine, New York, NY, USA
54Department of Psychiatry and Psychotherapy, University Regensburg, Regensburg, Germany
55Neurospin, Commissariat à l'Energie Atomique, Paris, France
56Department of Psychiatry, UHC University of Vermont, Bergen, VT, USA
57Dr Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
58Department of Psychiatry; Yale University School of Medicine; New Haven CT USA
59Department of Psychiatry, University of Oxford, Oxford, UK
60Department of Psychiatry and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
61Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
62Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry, Georg August University, Goettingen, Germany
63Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
64Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
65Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
66Department of Molecular Neuroscience, UCL Institute, London, UK
67Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
68University Hospital C.G. Carus, Department of Child and Adolescent Psychiatry, Dresden University of Technology, Dresden, Germany
69The Brain and Mind Research Institute, University of Sydney, Sydney, Australia
70Department of Diagnostic Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany
71Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
72Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD USA
73Oakland University William Beaumont School of Medicine, Rochester Hills, MI, USA
74Mayo Clinic, Rochester, MN USA
75Oxford Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK
76National Institute of Health Research Biomedical Research Centre for Mental Health, South London and Maudsley National Health Service Foundation Trust, London, UK
77Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
78Neuropsychiatric Genetics Research Group, Department of Psychiatry, Institute for Molecular Medicine and Trinity College Institute for Neuroscience, Trinity College, Dublin, Ireland
79Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA
80Neuroscience Research Australia, Sydney, Australia
81Maryland Institute for Neuroscience and Development (MIND), Chevy Chase, MD, USA
82Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
83Electrical Engineering, Vanderbilt University, Nashville, TN, USA
84Department of Psychiatry, University of Missouri, Columbia, MO, USA
85Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
86Research Unit 1000, Neuroimaging and Psychiatry, INSERM-CEA-Faculté de Médecine Paris Sud University-Paris Descartes University, Maison de Solenn Paris, SHFJ Orsay, Paris, France
87Mood and Anxiety Disorders Section, Human Genetics Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Dept of Health and Human Services, Bethesda, MD, USA
88Department of Psychology, The University of Edinburgh, Edinburgh, UK
89School of Medicine, University of Nottingham, Nottingham, UK
90Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
91Mathison Centre for Mental Health Research and Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
92Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Medicine, Sydney, New South Wales, Australia
93Department of Biomedicine, Aarhus University, Aarhus, Denmark
94Research Unit, Sorlandet Hospital HF, Kristiansand, Norway
95Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
96Ludwig-Maximilians-University (LMU), Munich, Germany
97Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Australia
98Centre for Genetic Origins of Health and Disease, The University of Western Australia, Perth, Australia
99Department of Psychiatry, University of Minnesota Medical Center, Minneapolis, MN, USA
100Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
101Institute for Neuroscience and Medicine (INM-1), Centre Jülich, Jülich, Germany
102Department of Psychiatry and Behavioral Sciences, University of Texas Medical School, Houston, TX, USA
103Institute of Clinical Chemistry and Laboratory Medicine, University of Greifswald, Greifswald, Germany
104Department of Statistics & Warwick Manufacturing Group, The University of Warwick, Coventry, UK
105Department of Psychology, Stockholm University, Stockholm, Sweden
106Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD, USA
107Umeå center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
108Department of Psychiatry, UT Health Science Center at San Antonio, San Antonio, TX, USA
109Department of Clinical Neuropsychology, VU University Amsterdam, The Netherlands
110Rotman Research Institute, University of Toronto, Toronto, ON, Canada
111The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
112Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
113Department of Radiology, University of Calgary, Calgary, Alberta, Canada
114Hellen Wills Neuroscience Institute, Brain Imaging Center, University of California at Berkeley, Berkeley, CA, USA
115Department of Medical and Molecular Genetics, King’s College London, London, UK
116Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
117Transdisciplinary and Translational Prevention Program, RTI International, Baltimore, MD, USA
118Department of Psychiatry, University of Halle, Halle, Germany
119Laureate Institute for Brain Research, Tulsa, OK, USA
120Cognitive Science Department, UC San Diego, La Jolla, CA, USA
121Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
122Department of Neuroimaging, Institute of Psychiatry, King’s College London, London, UK
123Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
124Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
125Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
126Department of Psychology and Neuroscience Institute, Georgia State University, Atlanta, GA, USA
127Department of Psychiatry and Leiden Institute for Brain and Cognition, Leiden University Medical Center, Leiden, The Netherlands
128Department of Psychiatry, Rudolf Magnus Institute, University Medical Center Utrecht, Utrecht, The Netherlands
129Behavioural and Cognitive Neuroscience Neuroimaging Center, University Medical Center Groningen, Groningen, the Netherlands
130Institute for Community Medicine, University of Greifswald, Greifswald, Germany
131Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
132Berlin School of Mind and Brain, Humboldt University Berlin, Berlin, Germany
133Departments of Radiology, Medicine, Psychiatry, University of California, San Francisco, CA, USA
134Department of Psychology, University of Oslo, Oslo, Norway
135Department of Child and Adolescent Psychiatry, Erasmus University Medical Centre, Rotterdam, The Netherlands
136German Center for Neurodegenerative Diseases (DZNE), University of Greifswald, Greifswald, Germany
137Radboud University NijmegenDonders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
138Centre for Healthy Brain Ageing, Psychiatry, University of New South Wales (UNSW), Sydney, Australia
139School of Medical Sciences, University of New South Wales, Sydney, Australia
140Department of Psychiatry and Biobehavioral Sciences, UCLA School of Medicine, Los Angeles, CA, USA
141School of Psychology, University of Exeter, Exeter, UK
142Janssen Research & Development, of Johnson & Johnson, Inc., 1125 Trenton-Harbourton Road, Titusville, NJ, 08560, USA

Tóm tắt

Từ khóa


Tài liệu tham khảo

Almasy, L., Gur, R. C., Haack, K., Cole, S. A., Calkins, M. E., Peralta, J. M., et al. (2008). A genome screen for quantitative trait loci influencing schizophrenia and neurocognitive phenotypes. The American Journal of Psychiatry, 165, 1185–1192.

Alzheimer’s Association. (2013). The Worldwide ADNI. URL: http://www.alz.org/research/funding/partnerships/ww-adni_overview.asp . Accessed 2 June 2013.

Amunts, K., Schleicher, A., Burgel, U., Mohlberg, H., Uylings, H. B., & Zilles, K. (1999). Broca’s region revisited: cytoarchitecture and intersubject variability. The Journal of Comparative Neurology, 412, 319–341.

Andreasen, N. C., Wilcox, M. A., Ho, B. C., Epping, E., Ziebell, S., Zeien, E., et al. (2012). Statistical epistasis and progressive brain change in schizophrenia: an approach for examining the relationships between multiple genes. Molecular Psychiatry, 17(11), 1093–1102.

Ashburner, J., Andersson, J. L., & Friston, K. J. (1999). High-dimensional image registration using symmetric priors. NeuroImage, 9, 619–628.

Baaré, W. F., Hulshoff Pol, H. E., Boomsma, D. I., Posthuma, D., de Geus, E. J., Schnack, H. G., et al. (2001). Quantitative genetic modeling of variation in human brain morphology. Cerebral Cortex, 11, 816–824.

Bakken, T. E., Roddey, J. C., Djurovic, S., Akshoomoff, N., Amaral, D. G., Bloss, C. S., et al. (2012). Association of common genetic variants in GPCPD1 with scaling of visual cortical surface area in humans. Proceedings of the National Academy of Sciences of the United States of America, 109, 3985–3990.

Bao, Y., Hudson, Q. J., Perera, E. M., Akan, L., Tobet, S. A., Smith, C. A., et al. (2009). Expression and evolutionary conservation of the tescalcin gene during development. Gene expression patterns : GEP, 9, 273–281.

Batouli, S. A. H., Sachdev, P. S., Wen, W., Wright, M. J., Suo, C., Ames, D., et al. (2012). The heritability of brain metabolites on proton magnetic resonance spectroscopy in older individuals. Neuroimage, 62, 281–289.

Barnes, J., Bartlett, J. W., van de Pol, L. A., Loy, C. T., Scahill, R. I., Frost, C., et al. (2009) A meta-analysis of hippocampal atrophy rates in Alzheimer's disease. Neurobiol Aging, 30(11), 1711–23.

Baumgartner, M., Patel, H., & Barber, D. L. (2004). Na(+)/H(+) exchanger NHE1 as plasma membrane scaffold in the assembly of signaling complexes. American Journal of Physiology - Cell Physiology, 287, C844–C850.

Bertram, L. (2009). Alzheimer’s disease genetics current status and future perspectives. International Review of Neurobiology, 84, 167–184.

Biffi, A., Anderson, C. D., Desikan, R. S., Sabuncu, M., Cortellini, L., Schmansky, N., et al. (2010). Genetic variation and neuroimaging measures in Alzheimer disease. Archives of Neurology, 67, 677–685.

Bis, J. C., DeCarli, C., Smith, A. V., van der Lijn, F., Crivello, F., Fornage, M., et al. (2012). Common variants at 12q14 and 12q24 are associated with hippocampal volume. Nature Genetics, 44, 545–551.

Bishop, D. (2013). Blog posting: http://deevybee.blogspot.co.uk/2013/01/genetic-variation-and-neuroimaging-some.html . Accessed 5 June 2013.

Blangero, J. (2004). Localization and identification of human quantitative trait loci: King Harvest has surely come. Current Opinion in Genetics & Development, 14, 233–240.

Blokland, G. A., de Zubicaray, G. I., McMahon, K. L., & Wright, M. J. (2012). Genetic and environmental influences on neuroimaging phenotypes: a meta-analytical perspective on twin imaging studies. Twin Research and Human Genetics: the Official Journal of the International Society for Twin Studies, 15, 351–371.

Bralten, J., Arias-Vásquez, A., Makkinje, R., Veltman, J. A., Brunner, H. G., Fernández, G., et al. (2011). Association of the Alzheimer’s gene SORL1 with hippocampal volume in young, healthy adults. The American Journal of Psychiatry, 168(10), 1083–1089. doi: 10.1176/appi.ajp.2011.10101509 .

Braskie, M. N., Jahanshad, N., Stein, J. L., Barysheva, M., McMahon, K. L., de Zubicaray, G. I., et al. (2011). Common Alzheimer’s disease risk variant within the CLU gene affects white matter microstructure in young adults. Journal of Neuroscience, 31, 6764–6770.

Braskie, M. N., Jahanshad, N., Stein, J. L., Barysheva, M., Johnson, K., McMahon, K. L., et al. (2012). Relationship of a variant in the NTRK1 gene to white matter microstructure in young adults. Journal of Neuroscience, 32, 5964–5972.

Brouwer, R. M., Mandl, R. C., Peper, J. S., van Baal, G. C., Kahn, R. S., Boomsma, D. I., et al. (2010). Heritability of DTI and MTR in nine-year-old children. Neuroimage, 53(3), 1085–1092.

Bulayeva, K. B., Leal, S. M., Pavlova, T. A., Kurbanov, R. M., Glatt, S. J., Bulayev, O. A., et al. (2005). Mapping genes of complex psychiatric diseases in Daghestan genetic isolates. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 132B(1), 76–84.

Bulayeva, K., Glatt, S., Walsh, C., Gurgenova, F., Berdichevets, I., Bulayev, O., et al. (2013). Significant linkage and structural genomic variants at 12q24.21-q24.32 found in genetic isolate with aggregation of unspecific mental retardation. Open Journal of Genomics, 2, 3.

Button, K. S., Ioannidis, J. P., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S., et al. (2013). Power failure: why small sample size undermines the reliability of neuroscience. Nature Review Neuroscience, 14(5), 365–376. doi: 10.1038/nrn3475 .

Calhoun, V. D., Liu, J., & Adali, T. (2009). A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data. Neuroimage, 45(1 Suppl), S163–S172. doi: 10.1016/j.neuroimage.2008.10.057 .

CARDIoGRAMplusCD4_Consortium, Deloukas, P., Kanoni, S., Willenborg, C., Farrall, M., Assimes, T. L., et al. (2013). Large-scale association analysis identifies new risk loci for coronary artery disease. Nature Genetics, 45, 25–33.

Carrillo, M. C., Bain, L. J., Frisoni, G. B., & Weiner, M. W. (2012). Worldwide Alzheimer’s Disease Neuroimaging Initiative. Alzheimer’s & Dementia : the Journal of the Alzheimer’s Association, 8, 337–342.

Chen, C. H., Panizzon, M. S., Eyler, L. T., Jernigan, T. L., Thompson, W., Fennema-Notestine, C., et al. (2011). Genetic influences on cortical regionalization in the human brain. Neuron, 72, 537–544.

Chen, C. H., Gutierrez, E. D., Thompson, W., Panizzon, M. S., Jernigan, T. L., Eyler, L. T., et al. (2012a). Hierarchical genetic organization of human cortical surface area. Science, 335, 1634–1636.

Chen, J., Calhoun, V. D., Pearlson, G. D., Ehrlich, S., Turner, J., Ho, B. C., et al. (2012b). Multifaceted genomic risk for brain function in schizophrenia. NeuroImage, 61, 866–875.

Chen, J., Calhoun, V.D., Pearlson, G.D., Perrone-Bizzozero, N., Sui, J., Turner, J.A., et al. (2013). Guided exploration of genomic risk for gray matter abnormalities in schizophrenia using parallel independent component analysis with reference. NeuroImage (in press).

Chiang, M. C., McMahon, K. L., de Zubicaray, G. I., Martin, N. G., Hickie, I., Toga, A. W., et al. (2011). Genetics of white matter development: a DTI study of 705 twins and their siblings aged 12 to 29. NeuroImage, 54, 2308–2317.

Chiang, M. C., Barysheva, M., McMahon, K. L., de Zubicaray, G. I., Johnson, K., Montgomery, G. W., et al. (2012). Gene network effects on brain microstructure and intellectual performance identified in 472 twins. Journal of Neuroscience, 32, 8732–8745.

Cichon, S., Mühleisen, T. W., Degenhardt, F. A., Mattheisen, M., Miró, X., Strohmaier, J., et al. (2011). Genome-wide association study identifies genetic variation in neurocan as a susceptibility factor for bipolar disorder. American Journal of Human Genetics, 88(3), 372–381.

Cohen, R. A., Harezlak, J., Schifitto, G., Hana, G., Clark, U., Gongvatana A., et al. (2010). Effects of nadir CD4 count and duration of human immunodeficiency virus infection on brain volumes in the highly active antiretroviral therapy era. Journal of neurovirology, 16(1), 25–32.

Collins, D. L., Neelin, P., Peters, T. M., & Evans, A. C. (1994). Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. Journal of Computer Assisted Tomography, 18, 192–205.

Corder, E. H., Saunders, A. M., Strittmatter, W. J., Schmechel, D. E., Gaskell, P. C., Small, G. W., et al. (1993). Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science, 261, 921–923.

Cross-Disorder_Group_of_the_Psychiatric_Genomics_Consortium, Smoller, J. W., Craddock, N., Kendler, K., Lee, P. H., Neale, B. M., et al. (2013). Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet, 381, 1371–1379.

Davies, G., Tenesa, A., Payton, A., Yang, J., Harris, S. E., Liewald, D., et al. (2011). Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Molecular Psychiatry, 16(10), 996–1005. doi: 10.1038/mp.2011.85 .

Davies, G., Harris, S.E., Reynolds, C.A., Payton, A., Knight, H.M., Liewald, D.C., et al. (2012). A genome-wide association study implicates the APOE locus in nonpathological cognitive ageing. Molecular Psychiatry (in Press).

De Geus, E. J. C. (2010). From genotype to EEG endophenotype: a route for post-genomic understanding of complex psychiatric disease? Genome Medicine, 2, 63. http://genomemedicine.com/content/2/9/63 .

Den Braber, A., Bohlken, M.M., Brouwer, R.M., van ’t Ent, D., Kanai, R., Kahn, R.S., et al. (2013). Heritability of subcortical brain measures: a perspective for future genome-wide association studies. NeuroImage (in press).

Desrivieres, S., et al. (2013). Single nucleotide polymorphism in the neuroplastin locus associates with cortical thickness and verbal intelligence, submitted.

Ecker, C., Ginestet, C., Feng, Y., Johnston, P., Lombardo, M. V., Lai, M. C., et al. (2013). Brain surface anatomy in adults with autism: the relationship between surface area, cortical thickness, and autistic symptoms. JAMA Psychiatry, 70, 59–70.

Elias-Sonnenschein, L. S., Viechtbauer, W., Ramakers, I. H., Verhey, F. R., & Visser, P. J. (2011). Predictive value of APOE-ε4 allele for progression from MCI to AD-type dementia: a meta-analysis. Journal of Neurology, Neurosurgery and Psychiatry, 82(10), 1149–1156. doi: 10.1136/jnnp.2010.231555 .

Erk, S., Meyer-Lindenberg, A., Opitz von Boberfeld, C., Esslinger, C., Schnell, K., Kirsch, P., et al. (2011). Hippocampal function in healthy carriers of the CLU Alzheimer’s disease risk variant. Journal of Neuroscience, 49, 18180–18184.

Erk, S., Meyer-Lindenberg, A., Schmierer, P., Grimm, O., Tost, H., Mühleisen, T., et al. (2013). Functional impact of a recently identified quantitative trait locus for hippocampal volume with genome-wide support. Translational Psychiatry (in press).

Esslinger, C., Walter, H., Kirsch, P., Erk, S., Schnell, K., Arnold, C., et al. (2009) Neural mechanisms of a genome-wide supported psychosis variant. Science, 324(5927), 605.

Estrada, K., Styrkarsdottir, U., Evangelou, E., Hsu, Y. H., Duncan, E. L., Ntzani, E. E., et al. (2012). Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture. Nature Genetics, 44, 491–501.

Evans, A. C. (2006). The NIH MRI study of normal brain development. NeuroImage, 30, 184–202.

Falconer, D. S. (1960). Introduction to quantitative genetics. Edinburgh: Oliver and Boyd.

Fischl, B., van der Kouwe, A., Destrieux, C., Halgren, E., Segonne, F., Salat, D. H., et al. (2004). Automatically parcellating the human cerebral cortex. Cerebral Cortex, 14, 11–22.

Flint, J., & Munafo, M. R. (2013). Candidate and non-candidate genes in behavior genetics. Current Opinion in Neurobiology, 23, 57–61.

Flint, J., Greenspan, R. J., & Kendler, K. S. (2010). How genes influence behavior. Oxford, NY: Oxford University Press.

Fornage, M., Debette, S., Bis, J. C., Schmidt, H., Ikram, M. A., Dufouil, C., et al. (2011). Genome-wide association studies of cerebral white matter lesion burden: the CHARGE consortium. Annals of Neurology, 69, 928–939.

Fornito, A., Zalesky, A., Bassett, D. S., Meunier, D., Ellison-Wright, I., Yücel, M., et al. (2011). Genetic influences on cost-efficient organization of human cortical functional networks. Journal of Neuroscience, 31, 3261–3270. doi: 10.1523/jneurosci.4858-10.2011 .

Frackowiak, R. S. J. (1997). Human brain function. San Diego: Academic.

Friston, K. J., Holmes, A. P., Poline, J. B., Grasby, P. J., Williams, S. C., Frackowiak, R. S., et al. (1995). Analysis of fMRI time-series revisited. NeuroImage, 2, 45–53.

Frodl, T., Meisenzahl, E. M., Zill, P., Baghai, T., Rujescu, D., Leinsinger, G., et al. (2004). Reduced hippocampal volumes associated with the long variant of the serotonin transporter polymorphism in major depression. Archives of General Psychiatry, 61(2), 177–183.

Frodl, T., Koutsouleris, N., Bottlender, R., Jäger, M., Born, C., Mörgenthaler, M., et al. (2008). Reduced gray matter brain volumes are associated with variants of the serotonin transporter gene in major depression. Molecular Psychiatry, 13(12), 1093–1101.

Ge, T., Feng, J., Hibar, D. P., Thompson, P. M., & Nichols, T. E. (2012). Increasing power for voxel-wise genome-wide association studies: the random field theory, least square kernel machines and fast permutation procedures. NeuroImage, 63, 858–873.

Glahn, D. C., Thompson, P. M., & Blangero, J. (2007). Neuroimaging endophenotypes: strategies for finding genes influencing brain structure and function. Human Brain Mapping, 28, 488–501.

Glahn, D. C., Winkler, A. M., Kochunov, P., Almasy, L., Duggirala, R., Carless, M. A., et al. (2010). Genetic control over the resting brain. Proceedings of the National Academy of Sciences of the United States of America, 107, 1223–1228.

Glahn, D. C., Curran, J. E., Winkler, A. M., Carless, M. A., Kent, J. W., Jr., Charlesworth, J. C., et al. (2012). High dimensional endophenotype ranking in the search for major depression risk genes. Biological Psychiatry, 71, 6–14.

Glover, G. H., Mueller, B. A., Turner, J. A., van Erp, T. G., Liu, T. T., Greve, D. N., et al. (2012). Function biomedical informatics research network recommendations for prospective multicenter functional MRI studies. Journal of Magnetic Resonance Imaging, 36(1), 39–54.

Goldman, D. (2012). Our genes, our choices : how genotype and gene interactions affect behavior. London: Elsevier/Academic Press.

Gollub, R., Shoemaker, J.M., King, M., White, T., Ehrlich, S., Sponheim, S., et al. (2013) The MCIC collection: a shared repository of multi-modal, multi-site brain image data from a clinical investigation of schizophrenia. Journal of NeuroInformatics. PMID: 23760817.

Gottesman, I. I., & Gould, T. D. (2003). The endophenotype concept in psychiatry: etymology and strategic intentions. The American Journal of Psychiatry, 160, 636–645.

Hall, J., Whalley, H. C., Job, D. E., Baig, B. J., McIntosh, A. M., Evans, K. L., et al. (2006). A neuregulin 1 variant associated with abnormal cortical function and psychotic symptoms. Nature Neuroscience, 9(12), 1477–1478.

Hariri, A. R., & Weinberger, D. R. (2003). Imaging genomics. British Medical Bulletin, 65, 259–270.

Harold, D., Abraham, R., Hollingworth, P., Sims, R., Gerrish, A., Hamshere, M. L., et al. (2009). Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer’s disease. Nature Genetics, 41, 1088–1093.

Hibar, D. P., Kohannim, O., Stein, J. L., Chiang, M. C., & Thompson, P. M. (2011a). Multilocus genetic analysis of brain images. Frontiers in Genetics, 2, 73.

Hibar, D. P., Stein, J. L., Kohannim, O., Jahanshad, N., Saykin, A. J., Shen, L., et al. (2011b). Voxelwise gene-wide association study (vGeneWAS): multivariate gene-based association testing in 731 elderly subjects. NeuroImage, 56, 1875–1891.

Hibar, D. P., van Erp, T. G. M., Turner, J. A., Haukvik, U. K., Agartz, I., et al. (2013a). Meta-analysis of structural brain differences in bipolar disorder: the ENIGMA-Bipolar Disorder Project. Seattle, WA: OHBM.

Hibar, D. P., Stein, J. L., Ryles, A. B., Kohannim, O., Jahanshad, N., Medland, S. E., et al. (2013b). Genome-wide association identifies genetic variants associated with lentiform nucleus volume in N = 1345 young and elderly subjects. Brain Imaging and Behavior, 7, 102–115.

Hibar, D., Stein, J.L., Jahanshad, N., Toga, A.W., McMahon, K.L., de Zubicaray, G.I., et al. (2013c). Exhaustive search of the SNP-SNP interactome identifies replicated epistatic effects on brain volume. MICCAI 2013, Nagoya, Japan, Sept. 22–26 2013 (in press).

Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., et al. (2009). Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proceedings of the National Academy of Sciences of the United States of America, 106, 9362–9367.

Hollingworth, P., Harold, D., Sims, R., Gerrish, A., Lambert, J. C., Carrasquillo, M. M., et al. (2011). Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer’s disease. Nature Genetics, 43(5), 429–435. doi: 10.1038/ng.803 .

Holmes, A. J., Lee, P. H., Hollinshead, M. O., Bakst, L., Roffman, J. L., Smoller, J. W., et al. (2012). Individual differences in amygdala-medial prefrontal anatomy link negative affect, impaired social function, and polygenic depression risk. Journal of Neuroscience, 32(50), 18087–18100.

Hong, M. G., Reynolds, C. A., Feldman, A. L., Kallin, M., Lambert, J. C., Amouyel, P., et al. (2012). Genome-wide and gene-based association implicates FRMD6 in Alzheimer disease. Human Mutation, 33, 521–529.

Hulshoff Pol, H. E., Schnack, H. G., Mandl, R. C., Brans, R. G., van Haren, N. E., Baare, W. F., et al. (2006). Gray and white matter density changes in monozygotic and same-sex dizygotic twins discordant for schizophrenia using voxel-based morphometry. Neuroimage, 31(2), 482–488.

Ikram, M. A., Fornage, M., Smith, A. V., Seshadri, S., Schmidt, R., Debette, S., et al. (2012). Common variants at 6q22 and 17q21 are associated with intracranial volume. Nature Genetics, 44, 539–544.

Ioannidis, J. P. (2005). Why most published research findings are false. PLoS Medicine, 2, e124.

Jack, C. R., Jr. (2012). Alzheimer disease: new concepts on its neurobiology and the clinical role imaging will play. Radiology, 263, 344–361.

Jahanshad, N., Zhan, L., Bernstein, M.A., Borowski, B.J., Jack, C.R., Toga, A.W., et al. (2010). Diffusion tensor imaging in seven minutes: determining trade-offs between spatial and directional resolution. In: Biomedical Imaging: From Nano to Macro (pp. 1161–1164). 2010 IEEE International Symposium on Biomedical Imaging (ISBI).

Jahanshad, N., Kohannim, O., Hibar, D. P., Stein, J. L., McMahon, K. L., de Zubicaray, G. I., et al. (2012). Brain structure in healthy adults is related to serum transferrin and the H63D polymorphism in the HFE gene. Proceedings National Academy Science USA, 109(14), E851–9. doi: 10.1073/pnas.1105543109 .

Jahanshad, N., Kochunov, P., Sprooten, E., Mandl, R.C., Nichols, T.E., Almasy, L., et al. (2013a). Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: A pilot project of the ENIGMA-DTI working group. Neuroimage, 81, 455–469.

Jahanshad, N., Rajagopalan, P., Hua, X., Hibar, D. P., Nir, T. M., Toga, A. W., et al. (2013b). Genome-wide scan of healthy human connectome discovers SPON1 gene variant influencing dementia severity. Proceedings of the National Academy of Sciences of the United States of America, 110, 4768–4773.

Jahanshad, N., Nir, T. M., Toga, A. W., Jack, C. R., Bernstein, M. A., Weiner, M. W., & Thompson, P. M. (2013c). Seemingly Unrelated Regression empowers detection of network failure in dementia. Neurobiol Aging. In Press (SI: Neuroimaging Biomarkers in Alzheimer's Disease).

Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage, 17(2), 825–841.

Jenkinson, M., Beckmann, C. F., Behrens, T. E., Woolrich, M. W., & Smith, S. M. (2012). FSL. NeuroImage, 62, 782–790.

Jones, E. G., & Mendell, L. M. (1999). Assessing the decade of the brain. Science, 284, 739.

Joyner, A. H., J, C. R., Bloss, C. S., Bakken, T. E., Rimol, L. M., Melle, I., Agartz, I., et al. (2009). A common MECP2 haplotype associates with reduced cortical surface area in humans in two independent populations. Proceedings of the National Academy of Sciences of the United States of America, 106, 15483–15488.

Kam-Thong, T., et al. (2012). GLIDE: GPU-based linear regression for detection of epistasis. Human Heredity, 73(4), 220–236.

Kendler, K. S., & Neale, M. C. (2010). Endophenotype: a conceptual analysis. Molecular Psychiatry, 15, 789–797.

Klei, L., Sanders, S., Murtha, M., Hus, V., Lowe, J., Willsey, A., et al. (2012). Common genetic variants, acting additively, are a major source of risk for autism. Molecular Autism, 3 (1). doi: 10.1186/2040-2392-3-9 . http://www.molecularautism.com/content/3/1/9 .

Kochunov, P., Glahn, D. C., Lancaster, J. L., Winkler, A. M., Smith, S., Thompson, P. M., et al. (2010). Genetics of microstructure of cerebral white matter using diffusion tensor imaging. NeuroImage, 53, 1109–1116.

Kochunov, P., Jahanshad, N., Sprooten, E., Thompson, P., McIntosh, A., Deary, I., et al. (2012) Genome-wide association of full brain white matter integrity—from the ENIGMA DTI working group. In: Organization of Human Brain Mapping, Beijing, China.

Kohannim, O., Jahanshad, N., Braskie, M. N., Stein, J. L., Chiang, M. C., Reese, A. H., et al. (2012). Predicting white matter integrity from multiple common genetic variants. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 37, 2012–2019.

Kohannim, O., Hua, X., Rajagopalan, P., Hibar, D.P., Jahanshad, N., Grill, J., et al. (2013). Multilocus genetic profiling to empower drug trials and predict brain atrophy, Neuroimage-Clinical (in press).

Koten, J. W., Jr., Wood, G., Hagoort, P., Goebel, R., Propping, P., Willmes, K., et al. (2009). Genetic contribution to variation in cognitive function: an FMRI study in twins. Science, 323, 1737–1740. doi: 10.1126/science.1167371 .

Kremen, W. S., Prom-Wormley, E., Panizzon, M. S., Eyler, L. T., Fischl, B., Neale, M. C., et al. (2009). Genetic and environmental influences on the size of specific brain regions in midlife: the VETSA MRI study. NeuroImage, 49(2), 1213–1223. doi: 10.1016/j.neuroimage.2009.09.043 .

Lambert, J. C., Heath, S., Even, G., Campion, D., Sleegers, K., Hiltunen, M., et al. (2009). Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer’s disease. Nature Genetics, 41(10), 1094–1099.

Lango Allen, H., Estrada, K., Lettre, G., Berndt, S. I., Weedon, M. N., Rivadeneira, F., et al. (2010). Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature, 467, 832–838.

Le Floch, Guillemot, V., Frouin, V., Pinel, P., Lalanne, C., Trinchera, L., et al. (2012). Significant correlation between a set of genetic polymorphisms and a functional brain network revealed by feature selection and sparse Partial Least Squares. NeuroImage, 63(1), 11–24.

Lee, S. H., Wray, N. R., Goddard, M. E., & Visscher, P. M. (2011). Estimating missing heritability for disease from genome-wide association studies. Am J Hum Genet, 88, 294–305.

Lee, S. H., Ripke, S., Neale, B. M., Faraone, S. V., Purcell, S. M., Perlis, R. H. et al. (2013). Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nature Genetics, 45, 984–994.

Leow, A. D., Yanovsky, I., Parikshak, N., Hua, X., Lee, S., Toga, A. W., et al. (2009). Alzheimer’s disease neuroimaging initiative: a one-year follow up study using tensor-based morphometry correlating degenerative rates, biomarkers and cognition. NeuroImage, 45, 645–655.

Leung, K. K., Barnes, J., Ridgway, G. R., Bartlett, J. W., Clarkson, M. J., Macdonald, K., et al. (2010). Automated cross-sectional and longitudinal hippocampal volume measurement in mild cognitive impairment and Alzheimer's disease. Neuroimage, 51(4), 1345–59.

Li, M., Luo, X.J., Rietschel, M., Lewis, C.M., Mattheisen, M., Muller-Myhsok, B., et al. (2013) Allelic differences between Europeans and Chinese for CREB1 SNPs and their implications in gene expression regulation, hippocampal structure and function, and bipolar disorder susceptibility. Molecular Psychiatry (in press).

Liu, J., Pearlson, G., Windemuth, A., Ruano, G., Perrone-Bizzozero, N. I., & Calhoun, V. (2009). Combining fMRI and SNP data to investigate connections between brain function and genetics using parallel ICA. Human Brain Mapping, 30(1), 241–255.

Liu, C. C., Kanekiyo, T., Xu, H., & Bu, G. (2013). Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy. Nature Reviews Neurology, 9(2), 106–118. doi: 10.1038/nrneurol.2012.263 .

Logue, M. W., Schu, M., Vardarajan, B. N., Buros, J., Green, R. C., Go, R. C., et al. (2011). A comprehensive genetic association study of Alzheimer disease in African Americans. Archives of Neurology, 68, 1569–1579.

Lopez, L. M., Bastin, M. E., Munoz Maniega, S., Penke, L., Davies, G., Christoforou, A., et al. (2012). A genome-wide search for genetic influences and biological pathways related to the brain’s white matter integrity. Neurobiology of Aging, 33, 1847.e1–14.

Lu, P. H., Thompson, P. M., Leow, A., Lee, G. J., Lee, A., Yanovsky, I., et al. (2011). Apolipoprotein E genotype is associated with temporal and hippocampal atrophy rates in healthy elderly adults: a tensor-based morphometry study. Journal of Alzheimer’s disease : JAD, 23, 433–442.

Mazziotta, J. C., Toga, A. W., Evans, A., Fox, P., & Lancaster, J. (1995). A probabilistic atlas of the human brain: theory and rationale for its development. The International Consortium for Brain Mapping (ICBM). NeuroImage, 2, 89–101.

McCarthy, M. I., & Hirschhorn, J. N. (2008). Genome-wide association studies: potential next steps on a genetic journey. Human Molecular Genetics, 17, R156–R165.

McCarthy, M. I., Abecasis, G. R., Cardon, L. R., Goldstein, D. B., Little, J., Ioannidis, J. P., et al. (2008). Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature Reviews Genetics, 9, 356–369.

McIntosh, A. M., Moorhead, T. W., Job, D., Lymer, G. K., Muñoz Maniega, S., McKirdy, J., et al. (2008). The effects of a neuregulin 1 variant on white matter density and integrity. Molecular Psychiatry, 13(11), 1054–1059.

Meda, S. A., Jagannathan, K., Gelernter, J., Calhoun, V. D., Liu, J., Stevens, M. C., et al. (2010). A pilot multivariate parallel ICA study to investigate differential linkage between neural networks and genetic profiles in schizophrenia. (2010). NeuroImage, 53(3), 1007–1015.

Meda, S. A., Narayanan, B., Liu, J., Perrone-Bizzozero, N. I., Stevens, M. C., Calhoun, V. D., et al. (2012). A large scale multivariate parallel ICA method reveals novel imaging-genetic relationships for Alzheimer’s disease in the ADNI cohort. NeuroImage, 60(3), 1608–1621. doi: 10.1016/j.neuroimage.2011.12.076 .

Mühlau, W., Winkelmann, J., Rujescu, D., Giegling, I., Koutsouleris, N., Gaser, C., et al. (2012). Variation within the Huntington’s disease gene influences normal brain structure. PLoS One, 7(1), e29809.

Mühleisen, T. W., Mattheisen, M., Strohmaier, J., Degenhardt, F., Priebe, L., Schultz, C. C., et al. (2012). Association between schizophrenia and common variation in neurocan (NCAN), a genetic risk factor for bipolar disorder. Schizophrenia Research, 138(1), 69–73.

Naj, A. C., Jun, G., Beecham, G. W., Wang, L. S., Vardarajan, B. N., Buros, J., et al. (2011). Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer’s disease. Nature Genetics, 43, 436–441.

Neel, J. (1992). Minority populations as genetic isolates: the interpretation of inbreeding results. In A. H. Bittles & D. F. Roberts (Eds.), Minority populations: Genetics demography and health. London: The MacMillan Press.

Novak, N. M., Stein, J. L., Medland, S. E., Hibar, D. P., Thompson, P. M., & Toga, A. W. (2012). EnigmaVis: online interactive visualization of genome-wide association studies of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium. Twin Research and Human Genetics, 15, 414–418.

Nugent, A. C., Luckenbaugh, D. A., Wood, S. E., Bogers, W., Zarate, C. A., Jr., & Drevets, W. C. (2012). Automated subcortical segmentation using FIRST: Test-retest reliability, interscanner reliability, and comparison to manual segmentation. Human Brain Mapping. doi: 10.1002/hbm.22068 .

O'Donovan, M. C., Craddock, N., Norton, N., Williams, H., Pierce, T., Moskvina, V., Nikolov, I. et al. (2008). Identification of loci associated with schizophrenia by genome-wide association and follow-up. Nature Genetics, 40(9), 1053–1055.

Pandey, A., Davis, N. A., White, B. C., Pajewski, N. M., Savitz, J., & Drevets, W. C. (2012). Epistasis network centrality analysis yields pathway replication across two GWAS cohorts for bipolar disorder. Translational Psychiatry, 2, e154. doi: 10.1038/tp.2012.80 .

Pasaniuc, B., Rohland, N., McLaren, P. J., Garimella, K., Zaitlen, N., Li, H., et al. (2012). Extremely low-coverage sequencing and imputation increases power for genome-wide association studies. Nature Genetics, 44(6), 631–635.

Patenaude, B., Smith, S. M., Kennedy, D. N., & Jenkinson, M. (2011). A Bayesian model of shape and appearance for subcortical brain segmentation. NeuroImage, 56(3), 907–922.

Paus, T., Bernard, M., Chakravarty, M. M., Davey Smith, G., Gillis, J., Lourdusamy, A., et al. (2012). KCTD8 gene and brain growth in adverse intrauterine environment: a genome-wide association study. Cerebral Cortex, 22(11), 2634–2642. doi: 10.1093/cercor/bhr350 .

Pengas, G., Pereira, J. M., Williams, G. B., & Nestor, P. J. (2009). Comparative reliability of total intracranial volume estimation methods and the influence of atrophy in a longitudinal semantic dementia cohort. Journal of Neuroimaging, 19(1), 37–46. doi: 10.1111/j.1552-6569.2008.00246.x .

Penke, L., Munoz Maniega, S., Murray, C., Gow, A. J., Valdes Hernandez, M. C., Clayden, J. D., et al. (2010). A general factor of brain white matter integrity predicts information processing speed in healthy older people. Journal of Neuroscience, 30(7559), 7674.

Penke, L., Maniega, S. M., Bastin, M. E., Hernandez, M. C. V., Murray, C., Royle, N. A., et al. (2012). Brain white matter integrity as a neural foundation for general intelligence. Molecular Psychiatry, 17, 1026–1030.

Peper, J. S., Brouwer, R. M., Boomsma, D. I., Kahn, R. S., & Hulshoff Pol, H. E. (2007). Genetic influences on human brain structure: a review of brain imaging studies in twins. Human Brain Mapping, 28(6), 464–473. Review.

Pierson, R., Johnson, H., Harris, G., Keefe, H., Paulsen, J. S., Andreasen, N. C., et al. (2011). Fully automated analysis using BRAINS: AutoWorkup. NeuroImage, 54(1), 328–336.

Poline, J. B., Breeze, J. L., Ghosh, S., Gorgolewski, K., Halchenko, Y. O., Hanke, M., et al. (2012). Data sharing in neuroimaging research. Frontiers in Neuroinformatics, 6, 9.

Potkin, S. G., & Ford, J. M. (2009). Widespread cortical dysfunction in schizophrenia: the FBIRN imaging consortium. Schizophrenia Bulletin, 35, 15–18.

Potkin, S. G., Guffanti, G., Lakatos, A., Turner, J. A., Kruggel, F., Fallon, J. H., et al. (2009a). Hippocampal atrophy as a quantitative trait in a genome-wide association study identifying novel susceptibility genes for Alzheimer’s disease. PLoS One, 4, e6501.

Potkin, S. G., Turner, J. A., Guffanti, G., Lakatos, A., Torri, F., Keator, D. B., et al. (2009b). Genome-wide strategies for discovering genetic influences on cognition and cognitive disorders: methodological considerations. Cognitive Neuropsychiatry, 14, 391–418.

Purcell, S. M., Wray, N. R., Stone, J. L., Visscher, P. M., O’Donovan, M. C., Sullivan, P. F., et al. (2009). Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature, 460, 748–752.

Rajagopalan, P., Hibar, D.P., Thompson, P.M. (2013). TREM2 Alzheimer risk gene carriers lose brain tissue faster, Letter to the Editor. New England Journal of Medicine (in press).

Rietschel, M., Mattheisen, M., Degenhardt, F., Kahn, R. S., Linszen, D. H., Os, J. V., et al. (2012). Association between genetic variation in a region on chromosome 11 and schizophrenia in large samples from Europe. Molecular Psychiatry, 17(9), 906–917.

Rietveld, C.A., Medland, S.E., Derringer, J., Yang, J., Esko, T., Martin, N.W., et al. (2013). GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science (in Press).

Rimol, L. M., Agartz, I., Djurovic, S., Brown, A. A., Roddey, J. C., Kahler, A. K., et al. (2010). Sex-dependent association of common variants of microcephaly genes with brain structure. Proceedings of the National Academy of Sciences of the United States of America, 107, 384–388.

Ripke, S., Sanders, A. R., Kendler, K. S., Levinson, D. F., Sklar, P., Holmans, P. A., et al. (2011). Genome-wide association study identifies five new schizophrenia loci. Nature Genetics, 43(10), 969–976. doi: 10.1038/ng.940 .

Roffman, J. L., Gollub, R. L., Calhoun, V. D., Wassink, T. H., Weiss, A. P., Ho, B. C., et al. (2008). MTHFR 677C -> T genotype disrupts prefrontal function in schizophrenia through an interaction with COMT 158Val -> Met. Proceedings of the National Academy of Sciences of the United States of America, 105(45), 17573–17578. doi: 10.1073/pnas.0803727105 .

Rose, E. J., & Donohoe, G. (2013). Brain vs behavior: an effect size comparison of neuroimaging and cognitive studies of genetic risk for schizophrenia. Schizophrenia Bulletin, 39(3), 518–526. doi: 10.1093/schbul/sbs056 .

Rosenblatt, J., Benjamini, Y., Bogomolov, M., Stein, J. L., & Thompson, P. M. (2013). vGWAS revisited: A novel and powerful approach to voxelwise genomewide association studies. Seattle, WA: OHBM.

Ryles, A. B., Kohannim, O., Toga, A. W., Jack, C. R., Jr., Weiner, M. W., McMahon, K. L., et al. (2012). Alzheimer’s disease risk variant in the FRMD6 gene is associated with altered brain structure: Opposite Effects in 740 elderly and 755 young adults. New Orleans, LA: Society for Neuroscience Annual Conference.

Saykin, A. J., Shen, L., Foroud, T. M., Potkin, S. G., Swaminathan, S., Kim, S., et al. (2010). Alzheimer’s Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: genetics core aims, progress, and plans. Alzheimer’s & Dementia : the Journal of the Alzheimer’s Association, 6, 265–273.

Schnack, H. G., van Haren, N. E., Brouwer, R. M., van Baal, G. C., Picchioni, M., Weisbrod, M., et al. (2010). Mapping reliability in multicenter MRI: voxel-based morphometry and cortical thickness. Human Brain Mapping, 31(12), 1967–1982. doi: 10.1002/hbm.20991 .

Schultz, C.C., Mühleisen, T.W., Nenadic, I., Koch, K., Wagner, G., Schachtzabel, C., et al. (2013). Common variation in NCAN, a risk factor for bipolar disorder and schizophrenia, influences local cortical folding in schizophrenia. Psychological Medicine. Manuscript accepted for publication.

Schumann, G., Coin, L. J., Lourdusamy, A., Charoen, P., Berger, K. H., Stacey, D., et al. (2011). Genome-wide association and genetic functional studies identify autism susceptibility candidate 2 gene (AUTS2) in the regulation of alcohol consumption. Proceedings of the National Academy of Sciences of the United States of America, 108(17), 7119–7124. doi: 10.1073/pnas.1017288108 .

Seshadri, S., Fitzpatrick, A. L., Ikram, M. A., DeStefano, A. L., Gudnason, V., Boada, M., et al. (2010). Genome-wide analysis of genetic loci associated with Alzheimer disease. JAMA, the Journal of the American Medical Association, 303, 1832–1840.

Sheffield, V. C., Stone, E. M., & Carmi, R. (1998). Use of isolated inbred human populations for identification of disease genes. Trends in Genetics, 14(10), 391–396.

Shenton, M. E., Dickey, C. C., Frumin, M., & McCarley, R. W. (2001). A review of MRI findings in schizophrenia. Schizophr Res, 49(1–2), 1–52.

Sherva, R., Tripodis, Y., Bennett, D.A., Chibnik, L.B., Crane, P.K., de Jager, P.L., et al (2013). Genome-wide association study of the rate of cognitive decline in Alzheimer’s disease. Alzheimer’s & Dementia : the Journal of the Alzheimer’s Association.

Shokouhi, M., Barnes, A., Suckling, J., Moorhead, T. W., Brennan, D., Job, D., et al. (2011). Assessment of the impact of the scanner-related factors on brain morphometry analysis with Brainvisa. BMC Medical Imaging, 11, 23. doi: 10.1186/1471-2342-11-23 .

Silver, M., Janousova, E., Hua, X., Thompson, P. M., Montana, G., & Alzheimer’s Disease Neuroimaging Initiative. (2012). Identification of gene pathways implicated in Alzheimer’s disease using longitudinal imaging phenotypes with sparse regression. NeuroImage, 63(3), 1681–1694. doi: 10.1016/j.neuroimage.2012.08.002 .

Sklar, P., Ripke, S., Scott, L. J., Andreassen, O. A., Cichon, S., Craddock, N., et al. (2011). Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4. Nature Genetics, 43(10), 977–983. doi: 10.1038/ng.943 .

Smith, S. M., Jenkinson, M., Johansen-Berg, H., Rueckert, D., Nichols, T. E., Mackay, C. E., et al. (2006). Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. NeuroImage, 31(4), 1487–1505.

Speliotes, E. K., Willer, C. J., Berndt, S. I., Monda, K. L., Thorleifsson, G., Jackson, A. U., et al. (2010). Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nature Genetics, 42, 937–948.

Sprooten, E., Fleming, K. M., Thomson, P. A., Bastin, M. E., Whalley, H. C., Hall, J., et al. (2013). White matter integrity as an intermediate phenotype: exploratory genome-wide association analysis in individuals at high risk of bipolar disorder. Psychiatry Research, 206, 223–231.

Stefansson, H., Ophoff, R. A., Steinberg, S., Andreassen, O. A., Cichon, S., Rujescu, D., et al. (2009). Nature, 460, 744–747.

Stein, J. L., Hua, X., Lee, S., Ho, A. J., Leow, A. D., Toga, A. W., et al. (2010). Voxelwise genome-wide association study (vGWAS). NeuroImage, 53, 1160–1174.

Stein, J. L., Hibar, D. P., Madsen, S. K., Khamis, M., McMahon, K. L., de Zubicaray, G. I., et al. (2011). Discovery and replication of dopamine-related gene effects on caudate volume in young and elderly populations (N = 1198) using genome-wide search. Molecular Psychiatry, 16(927–937), 881.

Stein, J. L., Medland, S. E., Vasquez, A. A., Hibar, D. P., Senstad, R. E., Winkler, A. M., et al. (2012). Identification of common variants associated with human hippocampal and intracranial volumes. Nature Genetics, 44, 552–561.

Stranger, B. E., Nica, A. C., Forrest, M. S., Dimas, A., Bird, C. P., Beazley, C., et al. (2007). Population genomics of human gene expression. Nature Genetics, 39, 1217–1224.

Talairach, J., Tournoux, P., & Missir, O. (1993). Referentially oriented cerebral MRI anatomy: an atlas of stereotaxic anatomical correlations for gray and white matter. Stuttgart: G. Thieme Verlag.

Thompson, P. M., & Jahanshad, N. (2012). Ironing out neurodegeneration: is iron intake important during the teenage years? Expert Review of Neurotherapeutics, 12, 629–631.

Thompson, P. M., Cannon, T. D., Narr, K. L., van Erp, T., Poutanen, V. P., Huttunen, M., et al. (2001). Genetic influences on brain structure. Nature Neuroscience, 4, 1253–1258.

Thompson, P.M., Ge, T., Glahn, D.C., Jahanshad, N., Nichols, T.E. (2013). Genetics of the connectome. Neuroimage.

Thorgeirsson, T. E., Geller, F., Sulem, P., Rafnar, T., Wiste, A., Magnusson, K. P., et al. (2008). variant associated with nicotine dependence, lung cancer and peripheral arterial disease. Nature, 452(7187), 638–642. doi: 10.1038/nature06846 .

Turner, J. A., Smyth, P., Macciardi, F., Fallon, J. H., Kennedy, J. L., & Potkin, S. G. (2006). Imaging phenotypes and genotypes in schizophrenia. Neuroinformatics, 4(1), 21–49.

Turner, J. A., Hibar, D. P., Rasmussen, J., Andreassen, O., Haukvik, U. K., Agartz, I., et al. (2013). A prospective meta-analysis of subcortical bain volumes in schizophrenia via the ENIGMA consortium. Seattle, WA: OHBM.

van den Heuvel, M. P., van Soelen, I. L., Stam, C. J., Kahn, R. S., Boomsma, D. I., & Hulshoff Pol, H. E. (2013). Genetic control of functional brain network efficiency in children. European Neuropsychopharmacology, 23, 19–23. doi: 10.1016/j.euroneuro.2012.06.007 .

van Erp, T. G., Saleh, P. A., Huttunen, M., Lonnqvist, J., Kaprio, J., Salonen, O., et al. (2004a). Hippocampal volumes in schizophrenic twins. Archives of General Psychiatry, 61(4), 346–353.

van Erp, T., Cannon, T., Tran, H., Wobbekind, A., Huttunen, M., Lönnqvist, J., et al. (2004) Genetic influences on human brain morphology. IEEE International Symposium on Biomedical Imaging, 583–586.

van Erp, T.G.M., Hibar, D.P., Rasmussen, J., Potkin, S., Ophoff, R., Andreassen, O., et al. (2013). A large-scale meta-analysis of subcortical brain volume abnormalities in schizophrenia via the ENIGMA consortium, Society for Biological Psychiatry (SOBP).

van Soelen, I. L., Brouwer, R. M., Peper, J. S., van Leeuwen, M., Koenis, M. M., van Beijsterveldt, T. C., et al. (2012). Brain SCALE: brain structure and cognition: an adolescent longitudinal twin study into the genetic etiology of individual differences. Twin Research and Human Genetics, 15(3), 453–467. doi: 10.1017/thg.2012.4 .

Vounou, M., Nichols, T. E., & Montana, G. (2010). Discovering genetic associations with high-dimensional neuroimaging phenotypes: a sparse reduced-rank regression approach. NeuroImage, 53, 1147–1159.

Vounou, M., Janousova, E., Wolz, R., Stein, J. L., Thompson, P. M., Rueckert, D., et al. (2012). Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer’s disease. NeuroImage, 60(1), 700–716.

Weiner, M. W., Veitch, D. P., Aisen, P. S., Beckett, L. A., Cairns, N. J., Green, R. C., et al. (2012). The Alzheimer’s disease neuroimaging initiative: a review of papers published since its inception. Alzheimer’s & Dementia : the Journal of the Alzheimer’s Association, 8, S1–S68.

Whalley, H. C., Papmeyer, M., Sprooten, E., Romaniuk, L., Blackwood, D. H., Glahn, D. C., et al. (2013a). The influence of polygenic risk for bipolar disorder on neural activation assessed using fMRI. Translational Psychiatry, 2, e130. doi: 10.1038/tp.2012.60 .

Whalley, H. C., Sprooten, E., Hackett, S., Hall, L., Blackwood, D. H., Glahn, D. C., et al. (2013b). Polygenic risk and white matter integrity in individuals at high risk of mood disorder. Biological Psychiatry. doi: 10.1016/j.biopsych.2013.01.027 .

White, T., & Gottesman, I. I. (2012). Brain connectivity and gyrification as endophenotypes for schizophrenia: weight of the evidence. Current Trends in Medicinal Chemistry, 12, 2393–2403.

White, T., Andreasen, N. C., & Nopoulos, P. (2002). Brain volumes and surface morphology in monozygotic twins. Cerebral Cortex, 12, 486–493.

White, T., El Marroun, H., Nijs, I., Schmidt, M. N., van der Lugt, A., Wielopolski, P., et al. (2013). Pediatric population-based imaging and the Generation R Study: the intersection of developmental neuroscience and epidemiology. European Journal of Epidemiology, 28, 99–111.

Winkler, A. M., Kochunov, P., Blangero, J., Almasy, L., Zilles, K., Fox, P. T., et al. (2010). Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies. NeuroImage, 53(3), 1135–1146. doi: 10.1016/j.neuroimage.2009.12.028 .

Woods, R. P., Mazziotta, J. C., & Cherry, S. R. (1993). MRI-PET registration with automated algorithm. Journal of Computer Assisted Tomography, 17, 536–546.

Wright, I. C., Sham, P., Murray, R. M., Weinberger, D. R., & Bullmore, E. T. (2002). Genetic contributions to regional variability in human brain structure: methods and preliminary results. Neuroimage,17(1), 256–271.

Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011). GCTA: a tool for genome-wide complex trait analysis. American Journal of Human Genetics, 88, 76–82.

Yang, J., Loos, R. J., Powell, J. E., Medland, S. E., Speliotes, E. K., Chasman, D. I., et al. (2012). FTO genotype is associated with phenotypic variability of body mass index. Nature, 490, 267–272.

Zetzsche, T., Preuss, U. W., Bondy, B., Frodl, T., Zill, P., Schmitt, G., et al. (2008). 5-HT1A receptor gene C-1019 G polymorphism and amygdala volume in borderline personality disorder. Genes, Brain and Behavior, 7(3), 306–313.

Zhan, L., Jahanshad, N., Ennis, D.B., Jin, Y., Bernstein, M.A., Borowski, B.J., et al. (2012) Angular versus spatial resolution trade-offs for diffusion imaging under time constraints. Human Brain Mapping.

Thông tin
Thông tin xuất bản

Springer Science and Business Media LLC

Tập 8 Số 2

153-182

Thông tin tác giả