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

Article, Unknown English OPEN
FRODL, THOMAS ; DONOHOE, GARY ; LOPEZ, LORNA (2014)
  • Publisher: Springer
  • Journal: volume 8, issue 2, pages 153-182 (issn: 1931-7557, eissn: 1931-7565)
  • Related identifiers: pmc: PMC4008818, doi: 10.1007/s11682-013-9269-5, doi: 10.1007/s11682-013-9269-5, doi: 10.1007/s11682-013-9269-5.
  • Subject: TENSOR-BASED MORPHOMETRY | : Genetics & genetic processes [Life sciences] | Genetics; MRI; GWAS; Consortium; Meta-analysis; Multi-site | Consortium | Psychiatry | QUANTITATIVE TRAIT LOCI | Genome-Wide Association Study/methods | Neuroimaging/methods | GWAS | Genes & Society | Genetics | Cooperative Behavior | Clinical Neurology | Neurology | QP | Brain Mapping | Multi-site | RC0321 | CORTICAL SURFACE-AREA | MRI | Neuroscience | Meta-analysis | Meta-Analysis as Topic | Brain Mapping/methods | VOXEL-BASED MORPHOMETRY | Radiology Nuclear Medicine and imaging | HUMAN BRAIN STRUCTURE | WHITE-MATTER MICROSTRUCTURE | BODY-MASS INDEX | Neuroimaging | Psychiatry and Mental health | : Génétique & processus génétiques [Sciences du vivant] | SI: Genetic Neuroimaging in Aging and Age-Related Diseases | Cellular and Molecular Neuroscience | MULTIVARIATE PARALLEL ICA | Genome-Wide Association Study | Behavioral Neuroscience | DISEASE RISK VARIANT | GENOME-WIDE ASSOCIATION | Cognitive Neuroscience | Humans
    mesheuropmc: endocrine system

The 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. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
  • References (197)
    197 references, page 1 of 20

    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). Highdimensional 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.

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